diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
new file mode 100644
index 0000000..667744e
--- /dev/null
+++ b/.github/workflows/build.yml
@@ -0,0 +1,86 @@
+name: Build EXE on PR
+
+# Run only on pull requests targeting develop or main
+on:
+  pull_request:
+    branches: [develop, main]
+
+# Concurrency: one run per commit in a PR
+concurrency:
+  group: pr-exe-${{ github.event.pull_request.head.sha }}
+  cancel-in-progress: true
+
+# Least-privilege permissions
+permissions:
+  contents: read
+
+# Global environment variables
+env:
+  PYTHON_VERSION: "3.12"
+  APP_NAME: "uq_desktop_processor"
+  SPEC_PATH: "UrbanQualityAI.spec"
+
+# Job: build Windows EXE with PyInstaller
+jobs:
+  build-windows-exe:
+    name: Build Windows EXE (PyInstaller)
+    runs-on: windows-latest
+    timeout-minutes: 30
+    env:
+      PIP_DISABLE_PIP_VERSION_CHECK: "1"
+      PYTHONDONTWRITEBYTECODE: "1"
+
+    steps:
+      # Get repository code
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      # Install chosen Python version + cache pip
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ env.PYTHON_VERSION }}
+          cache: pip
+          cache-dependency-path: |
+            pyproject.toml
+            poetry.lock
+
+      # Install all dependencies except CLIP, which needs a legacy-style build path.
+      - name: Install base deps (without CLIP)
+        shell: pwsh
+        run: |
+          python -m pip install --upgrade pip "setuptools<81" wheel
+          Get-Content requirements.txt | Where-Object { $_ -notmatch '^clip @ ' } | Set-Content requirements-ci.txt
+          Get-Content requirements-dev.txt | Where-Object { $_ -notmatch '^clip @ ' } | Set-Content requirements-dev-ci.txt
+          pip install -r requirements-ci.txt -r requirements-dev-ci.txt
+
+      # Install CLIP separately without isolated PEP 517 build and without overriding pinned deps.
+      - name: Install CLIP separately
+        run: pip install --no-deps --no-build-isolation "clip @ git+https://github.com/openai/CLIP.git@dcba3cb2e2827b402d2701e7e1c7d9fed8a20ef1"
+
+      # Ensure PyInstaller exists (exe builder).
+      - name: Install PyInstaller
+        run: python -m pip install pyinstaller
+
+      # Verify .spec file exists, otherwise fail with error
+      - name: Verify .spec exists
+        run: |
+          if (-not (Test-Path "${{ env.SPEC_PATH }}")) {
+            Write-Error "Missing PyInstaller spec file '${{ env.SPEC_PATH }}'"
+          }
+
+      # Build EXE using PyInstaller with the .spec file
+      # Then list the contents of dist/ for debugging/logging
+      - name: Build exe with PyInstaller (.spec only)
+        run: |
+          python -m PyInstaller --noconfirm --clean "${{ env.SPEC_PATH }}"
+          if (Test-Path dist) { Get-ChildItem -Recurse dist | Format-Table -AutoSize }
+
+      # Upload the dist/ folder as artifact for download
+      - name: Upload artifact (dist)
+        uses: actions/upload-artifact@v4
+        with:
+          name: ${{ env.APP_NAME }}-dist
+          path: dist/**
+          if-no-files-found: error
+          retention-days: 7
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
new file mode 100644
index 0000000..7cad9b4
--- /dev/null
+++ b/.github/workflows/ci.yml
@@ -0,0 +1,98 @@
+name: CI
+
+# Triggers: on any push (all branches), ignore tags, also on PRs
+on:
+  push:
+    branches: ["**"]
+    tags-ignore: ["*"]
+  pull_request:
+
+# Concurrency: one run per branch/PR, cancel old if new starts
+concurrency:
+  group: ci-${{ github.ref }}
+  cancel-in-progress: true
+
+# Least-privilege permissions for this workflow
+permissions:
+  contents: read
+
+# Global environment
+env:
+  PYTHON_VERSION: "3.12"
+
+# Job: linting, type checks, and tests
+jobs:
+  checks:
+    name: Lint, types & tests
+    runs-on: windows-latest
+    timeout-minutes: 15
+    env:
+      PIP_DISABLE_PIP_VERSION_CHECK: "1"
+      PYTHONDONTWRITEBYTECODE: "1"
+
+    steps:
+      # Get repository code
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      # Install chosen Python version + enable pip cache
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ env.PYTHON_VERSION }}
+          cache: pip
+          cache-dependency-path: |
+            pyproject.toml
+            poetry.lock
+
+      # Install Poetry itself (via pip)
+      - name: Install Poetry
+        run: python -m pip install --upgrade pip poetry
+
+      # Keep virtualenv inside repo for easier caching
+      - name: Enable in-project venv for Poetry
+        run: poetry config virtualenvs.in-project true
+
+      # Cache the .venv folder based on lockfile + Python version
+      - name: Cache Poetry venv
+        uses: actions/cache@v4
+        with:
+          path: .venv
+          key: venv-${{ runner.os }}-${{ env.PYTHON_VERSION }}-${{ hashFiles('poetry.lock') }}
+          restore-keys: |
+            venv-${{ runner.os }}-${{ env.PYTHON_VERSION }}-
+
+      # Install all dependencies except CLIP, which needs a legacy-style build path.
+      - name: Install base deps (without CLIP)
+        shell: pwsh
+        run: |
+          python -m pip install --upgrade pip "setuptools<81" wheel
+          Get-Content requirements.txt | Where-Object { $_ -notmatch '^clip @ ' } | Set-Content requirements-ci.txt
+          Get-Content requirements-dev.txt | Where-Object { $_ -notmatch '^clip @ ' } | Set-Content requirements-dev-ci.txt
+          pip install -r requirements-ci.txt -r requirements-dev-ci.txt
+
+      # Install CLIP separately without isolated PEP 517 build and without overriding pinned deps.
+      - name: Install CLIP separately
+        run: pip install --no-deps --no-build-isolation "clip @ git+https://github.com/openai/CLIP.git@dcba3cb2e2827b402d2701e7e1c7d9fed8a20ef1"
+
+      # Run linter (Ruff) with GitHub-friendly output
+      - name: Ruff (lint)
+        run: poetry run ruff check --output-format=github .
+
+      # Run formatter (Black) in check-only mode, with diff if fails
+      - name: Black (format check)
+        run: poetry run black --check --diff .
+
+      # Cache mypy cache folder to speed up type checking
+      - name: Cache mypy
+        uses: actions/cache@v4
+        with:
+          path: .mypy_cache
+          key: mypy-${{ runner.os }}-${{ env.PYTHON_VERSION }}-${{ hashFiles('pyproject.toml') }}
+          restore-keys: |
+            mypy-${{ runner.os }}-${{ env.PYTHON_VERSION }}-
+
+      # Run static type checker (Mypy) with auto-install types
+      - name: Mypy (type check)
+        continue-on-error: true
+        run: poetry run mypy --install-types --non-interactive --pretty .
\ No newline at end of file
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
new file mode 100644
index 0000000..142e6e9
--- /dev/null
+++ b/.github/workflows/release.yml
@@ -0,0 +1,152 @@
+name: Build & Publish EXE (Release or Tag)
+
+# Run workflow when:
+# - a release is published in GitHub UI
+# - any tag is pushed (tags: ["*"])
+on:
+  release:
+    types: [published]
+  push:
+    tags: ["*"]
+
+# Permissions: allow writing release assets to the repository
+permissions:
+  contents: write
+
+# Concurrency: group runs per tag/release, don't cancel older runs
+concurrency:
+  group: rel-${{ github.event_name == 'release' && github.event.release.tag_name || github.ref_name }}
+  cancel-in-progress: false
+
+# Global environment variables
+env:
+  PYTHON_VERSION: "3.12"
+  APP_NAME: "uq_desktop_processor"
+  SPEC_PATH: "UrbanQualityAI.spec"
+  TAG_NAME: ${{ github.event_name == 'release' && github.event.release.tag_name || github.ref_name }}
+
+jobs:
+  build-and-publish:
+    name: Build & Publish Windows EXE
+    runs-on: windows-latest
+    timeout-minutes: 30
+    env:
+      PIP_DISABLE_PIP_VERSION_CHECK: "1"
+      PYTHONDONTWRITEBYTECODE: "1"
+
+    steps:
+      # Get repository code
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0 # fetch full history (needed for branch ancestry check)
+          ref: ${{ env.TAG_NAME }}
+
+      # Verify that the tag commit is part of the main branch history (PowerShell)
+      - name: Verify tag points to commit on main
+        if: startsWith(github.ref, 'refs/tags/') || github.event_name == 'release'
+        run: |
+          git fetch origin +refs/heads/main:refs/remotes/origin/main
+          $TagSha = (git rev-parse HEAD).Trim()
+          git merge-base --is-ancestor $TagSha origin/main
+          if ($LASTEXITCODE -ne 0) {
+            Write-Error "Tag '${{ env.TAG_NAME }}' does not point to a commit on the 'main' branch. Publishing blocked."
+          }
+
+      # Install a chosen Python version + enable pip cache (helps to install Poetry)
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ env.PYTHON_VERSION }}
+          cache: pip
+          cache-dependency-path: |
+            pyproject.toml
+            poetry.lock
+
+      # Install Poetry itself (via pip)
+      - name: Install Poetry
+        run: python -m pip install --upgrade pip poetry
+
+      # Keep virtualenv inside repo for easier caching
+      - name: Enable in-project venv for Poetry
+        run: poetry config virtualenvs.in-project true
+
+      # Cache the .venv folder based on lockfile + Python version
+      - name: Cache Poetry venv
+        uses: actions/cache@v4
+        with:
+          path: .venv
+          key: venv-${{ runner.os }}-${{ env.PYTHON_VERSION }}-${{ hashFiles('poetry.lock') }}
+          restore-keys: |
+            venv-${{ runner.os }}-${{ env.PYTHON_VERSION }}-
+
+      # Install all dependencies (main + dev) from pyproject.toml
+      - name: Install deps (poetry)
+        run: poetry install --no-interaction --with dev
+
+      # Verify .spec file exists, otherwise fail with error
+      - name: Verify .spec exists
+        run: |
+          if (-not (Test-Path "${{ env.SPEC_PATH }}")) {
+            Write-Error "Missing PyInstaller spec file '${{ env.SPEC_PATH }}'"
+          }
+
+      # Build EXE using PyInstaller with the .spec file
+      # Then list the contents of dist/ for debugging/logging
+      - name: Build exe with PyInstaller (.spec only)
+        run: |
+          poetry run pyinstaller --noconfirm --clean "${{ env.SPEC_PATH }}"
+          if (Test-Path dist) { Get-ChildItem -Recurse dist | Format-Table -AutoSize }
+
+      # Sanity check: ensure at least one .exe exists before publishing
+      - name: Ensure at least one EXE exists
+        run: |
+          $files = Get-ChildItem -Path dist -Filter *.exe -Recurse -ErrorAction SilentlyContinue
+          if (-not $files) { Write-Error "No .exe files found in dist/**" }
+
+      # Package all built EXE files into a single ZIP archive
+      - name: Package EXE(s) into ZIP
+        run: |
+          $zipName = "dist/${{ env.APP_NAME }}-${{ env.TAG_NAME }}.zip"
+          if (Test-Path $zipName) { Remove-Item $zipName -Force }
+          $exeFiles = Get-ChildItem -Path dist -Filter *.exe -Recurse | Select-Object -ExpandProperty FullName
+          if (-not $exeFiles) { Write-Error "No .exe files to zip"; exit 1 }
+          Compress-Archive -Path $exeFiles -DestinationPath $zipName -Force
+          Get-ChildItem -Path dist -Filter *.zip -Recurse | ForEach-Object { Write-Host $_.FullName }
+
+      # Generate a SHA256 checksum file for the created ZIP
+      - name: Create sha256
+        run: |
+          $zipPath = "dist/${{ env.APP_NAME }}-${{ env.TAG_NAME }}.zip"
+          $hash = Get-FileHash $zipPath -Algorithm SHA256 | Select-Object -ExpandProperty Hash
+          $hash | Out-File -FilePath "dist/${{ env.APP_NAME }}-${{ env.TAG_NAME }}.sha256" -Encoding ascii
+          Get-ChildItem -Path dist -Filter *.sha256 -Recurse | ForEach-Object { Write-Host $_.FullName }
+
+      # Publish release metadata on GitHub (create or update release without assets)
+      - name: Create/Update GitHub Release (no files)
+        uses: softprops/action-gh-release@v2
+        with:
+          tag_name: ${{ env.TAG_NAME }}
+          name: ${{ env.TAG_NAME }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+      # Upload the generated ZIP file as a release asset
+      - name: Upload ZIP asset
+        uses: svenstaro/upload-release-action@v2
+        with:
+          repo_token: ${{ secrets.GITHUB_TOKEN }}
+          tag: ${{ env.TAG_NAME }}
+          file: dist/${{ env.APP_NAME }}-${{ env.TAG_NAME }}.zip
+          overwrite: true
+          file_glob: false
+
+      # Upload the SHA256 checksum file as a release asset
+      - name: Upload SHA256 asset
+        uses: svenstaro/upload-release-action@v2
+        with:
+          repo_token: ${{ secrets.GITHUB_TOKEN }}
+          tag: ${{ env.TAG_NAME }}
+          file: dist/${{ env.APP_NAME }}-${{ env.TAG_NAME }}.sha256
+          overwrite: true
+          file_glob: false
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..894231d
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,74 @@
+# Ignore PyCharm project files
+.idea/
+*.iml
+
+# Ignore virtual environment directories
+venv/
+env/
+ENV/
+.venv/
+.ENV/
+.venv.bak/
+venv.bak/
+
+# Ignore Python bytecode files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# Ignore temporary and log files
+*.log
+*.tmp
+*.swp
+*.swo
+cache
+
+# Ignore system files (macOS / Windows / Linux)
+.DS_Store
+Thumbs.db
+ehthumbs.db
+Icon?
+desktop.ini
+
+# Ignore test-related files
+.coverage
+.coverage.*
+.hypothesis/
+coverage.xml
+htmlcov/
+.tox/
+.nox/
+.cache/
+.pytest_cache/
+
+# Ignore pip logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Ignore Jupyter Notebook checkpoints
+.ipynb_checkpoints/
+
+# Ignore editor-specific configuration files
+.vscode/
+
+# Secrets and local environment variables
+.env
+.env.local
+.env.*
+
+# Ignore build artifacts
+build/
+dist/
+*.egg-info/
+.eggs/
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# ruff
+.ruff_cache/
+
+# pyright / pylance
+.pyright/
\ No newline at end of file
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..2224e9d
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,36 @@
+# Minimum version of pre-commit required
+minimum_pre_commit_version: "3.6.0"
+
+# Set the default Python version to be used by hooks
+default_language_version:
+  python: python3.12
+
+repos:
+  # Basic pre-commit hooks for common issues (whitespace, newlines, merge conflicts, YAML validity)
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v5.0.0
+    hooks:
+      - id: trailing-whitespace     # Removes trailing whitespace
+      - id: end-of-file-fixer       # Ensures files end with a newline
+      - id: check-merge-conflict    # Detects merge conflict markers
+      - id: check-yaml              # Validates YAML syntax
+
+  # Black formatter for Python code
+  - repo: https://github.com/psf/black
+    rev: "25.1.0"
+    hooks:
+      - id: black                   # Automatically formats Python code
+
+  # Ruff linter and code analyzer
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: "v0.12.12"
+    hooks:
+      - id: ruff                    # Lints Python code using Ruff
+
+  # Mypy static type checker
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: "v1.17.1"
+    hooks:
+      - id: mypy                    # Performs type checking with mypy
+        pass_filenames: false       # Keep behavior aligned with CI (check full project)
+        args: ["--install-types", "--non-interactive", "--pretty", "."]
diff --git a/UrbanQualityAI.spec b/UrbanQualityAI.spec
new file mode 100644
index 0000000..323abaf
--- /dev/null
+++ b/UrbanQualityAI.spec
@@ -0,0 +1,75 @@
+# -*- mode: python ; coding: utf-8 -*-
+
+import os
+
+from PyInstaller.utils.hooks import collect_data_files, collect_dynamic_libs, collect_submodules
+
+
+hiddenimports = []
+
+assets_src = os.path.join("src", "uq_desktop_processor", "assets")
+assets_icon = os.path.join(assets_src, "img", "icon.ico")
+assets_datas = []
+if os.path.exists(assets_src):
+    assets_datas.append((assets_src, os.path.join("uq_desktop_processor", "assets")))
+
+# Qt WebEngine and friends are notorious for dynamic imports; help PyInstaller a bit.
+hiddenimports += collect_submodules("PySide6.QtWebEngineCore")
+hiddenimports += collect_submodules("PySide6.QtWebEngineWidgets")
+# pyogrio uses compiled extension modules loaded dynamically.
+hiddenimports += collect_submodules("pyogrio")
+
+
+a = Analysis(
+    ["src\\uq_desktop_processor\\__main__.py"],
+    pathex=["src"],
+    binaries=[
+        # Bundle GDAL-related native libs shipped with the pyogrio wheel.
+        *collect_dynamic_libs("pyogrio"),
+    ],
+    datas=[
+        *assets_datas,
+        # openai/CLIP tokenizer vocab (and other clip assets) must be bundled as data files,
+        # otherwise the packaged app will crash trying to open `bpe_simple_vocab_16e6.txt.gz`.
+        *collect_data_files("clip"),
+        # Include pyogrio package data files required by GDAL/OGR runtime.
+        *collect_data_files("pyogrio"),
+    ],
+    hiddenimports=hiddenimports,
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=[
+        # hook-torch tries to import tensorboard via torch.utils.tensorboard;
+        # exclude it unless you explicitly depend on TensorBoard.
+        "tensorboard",
+        "torch.utils.tensorboard",
+    ],
+    noarchive=False,
+    optimize=0,
+)
+
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    a.binaries,
+    a.datas,
+    [],
+    name="uq_desktop_processor",
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=False,
+    upx_exclude=[],
+    runtime_tmpdir=None,
+    console=False,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None,
+    icon=assets_icon if os.path.exists(assets_icon) else None,
+)
+
diff --git a/docs/css/mkdocstrings.css b/docs/css/mkdocstrings.css
new file mode 100644
index 0000000..3b16ced
--- /dev/null
+++ b/docs/css/mkdocstrings.css
@@ -0,0 +1,23 @@
+/*
+  Documentation layout styles for MkDocs Material.
+  Defines spacing, typography, and table formatting
+  to improve readability and consistency across docs.
+*/
+
+/* Add vertical spacing between documentation objects */
+.md-typeset .doc .doc-object { margin: 1.1rem 0; }
+
+/* Allow function/method signatures to wrap across lines */
+.md-typeset .doc .sig { white-space: normal; word-break: break-word; }
+
+/* Adjust table cell padding and align text to the top */
+.md-typeset .doc .table th,
+.md-typeset .doc .table td {
+  padding: .5rem .75rem;
+  vertical-align: top;
+}
+
+/* Apply alternating background color to table rows for readability */
+.md-typeset .doc .table tr:nth-child(odd) td {
+  background: var(--md-code-bg-color);
+}
diff --git a/docs/css/theme-variants.css b/docs/css/theme-variants.css
new file mode 100644
index 0000000..b4707d4
--- /dev/null
+++ b/docs/css/theme-variants.css
@@ -0,0 +1,146 @@
+/*
+  Documentation theme styles for MkDocs Material.
+  Defines heading sizes, documentation object layout,
+  code signature blocks, and table formatting.
+  Includes multiple color/spacing schemes (brand, compact, comfy)
+  for different presentation preferences.
+*/
+
+/* Style level-1 headings */
+.md-typeset h1 {
+  font-size: 1.4rem;
+  color: var(--md-default-fg-color--light);
+  font-weight: 800;
+  letter-spacing: .01em;
+  margin-top: 1.2rem;
+  margin-bottom: .6rem;
+}
+
+/* Style level-2 headings */
+.md-typeset h2 {
+  font-size: 1rem;
+  color: var(--md-default-fg-color--light);
+  font-weight: 700;
+  letter-spacing: .02em;
+  margin-top: .8rem;
+  margin-bottom: .4rem;
+}
+
+/* Style level-3 headings */
+.md-typeset h3 {
+  font-size: 0.9rem;
+  color: var(--md-default-fg-color--light);
+  font-weight: 600;
+  letter-spacing: .01em;
+  margin-top: .6rem;
+  margin-bottom: .3rem;
+}
+
+/* Card-like container for documentation objects */
+.md-typeset .doc .doc-object {
+  margin: 1rem 0 1.25rem;
+  padding: 1rem 1.25rem;
+  border: 1px solid var(--md-default-fg-color--lighter);
+  border-radius: .75rem;
+  background: var(--md-default-bg-color);
+  box-shadow: 0 1px 0 var(--md-default-fg-color--lighter);
+}
+
+/* Heading inside a documentation object */
+.md-typeset .doc .doc-object > .doc-heading {
+  font-weight: 700;
+  margin-bottom: .5rem;
+}
+
+/* Code signature block inside documentation */
+.md-typeset .doc .sig {
+  display: block;
+  white-space: pre-wrap;
+  word-break: break-word;
+  background: var(--md-code-bg-color);
+  padding: .5rem .75rem;
+  border-radius: .5rem;
+  line-height: 1.45;
+}
+
+/* Section titles inside documentation */
+.md-typeset .doc .doc-section-title {
+  font-weight: 800;
+  text-transform: uppercase;
+  font-size: .78rem;
+  letter-spacing: .04em;
+  color: var(--md-default-fg-color--light);
+  margin-top: .9rem;
+  border-top: 1px solid var(--md-default-fg-color--lighter);
+  padding-top: .5rem;
+}
+
+/* Table base styles */
+.md-typeset .doc .table table {
+  width: 100%;
+  border-collapse: collapse;
+}
+.md-typeset .doc .table thead th {
+  font-weight: 700;
+  border-bottom: 1px solid var(--md-default-fg-color--lighter);
+}
+.md-typeset .doc .table th,
+.md-typeset .doc .table td {
+  padding: .45rem .6rem;
+  vertical-align: top;
+}
+/* Alternating row background */
+.md-typeset .doc .table tr:nth-child(odd) td {
+  background: var(--md-code-bg-color);
+}
+
+/* ============================= */
+/* BRAND color scheme            */
+/* ============================= */
+[data-md-color-scheme="brand"] {
+  --md-primary-fg-color: #6e56cf;
+  --md-accent-fg-color: #00c2a8;
+  --md-code-bg-color: rgba(110, 86, 207, .08);
+}
+[data-md-color-scheme="brand"] .md-typeset .doc .doc-object {
+  border-color: rgba(110, 86, 207, .35);
+  box-shadow: 0 1px 0 rgba(110, 86, 207, .25);
+}
+
+/* ============================= */
+/* COMPACT color scheme          */
+/* ============================= */
+[data-md-color-scheme="compact"] .md-typeset {
+  font-size: 0.94rem;
+  line-height: 1.55;
+}
+[data-md-color-scheme="compact"] .md-typeset .doc .doc-object {
+  margin: .75rem 0 1rem;
+  padding: .75rem .9rem;
+}
+[data-md-color-scheme="compact"] .md-typeset .doc .table th,
+[data-md-color-scheme="compact"] .md-typeset .doc .table td {
+  padding: .35rem .5rem;
+}
+[data-md-color-scheme="compact"] .md-typeset .sig {
+  line-height: 1.35;
+}
+
+/* ============================= */
+/* COMFY color scheme            */
+/* ============================= */
+[data-md-color-scheme="comfy"] .md-typeset {
+  font-size: 1.05rem;
+  line-height: 1.7;
+}
+[data-md-color-scheme="comfy"] .md-typeset .doc .doc-object {
+  margin: 1.2rem 0 1.5rem;
+  padding: 1.1rem 1.35rem;
+}
+[data-md-color-scheme="comfy"] .md-typeset .doc .table th,
+[data-md-color-scheme="comfy"] .md-typeset .doc .table td {
+  padding: .55rem .75rem;
+}
+[data-md-color-scheme="comfy"] .md-typeset .sig {
+  line-height: 1.55;
+}
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diff --git a/docs/gen_ref_pages/config.py b/docs/gen_ref_pages/config.py
new file mode 100644
index 0000000..bb20e78
--- /dev/null
+++ b/docs/gen_ref_pages/config.py
@@ -0,0 +1,60 @@
+from pathlib import Path
+
+# Global configuration flags and constants
+INCLUDE_PRIVATE = True  # Whether to include private packages (names starting with "_")
+SOURCE_DIR = Path("src")  # Root source directory to search for packages
+
+# Mapping from source subdirectories > human-readable section titles
+SECTION_TITLE_MAP = {
+    "services": "Services",
+    "threads": "Threads",
+    "ui": "UI",
+    "utils": "Utils",
+}
+
+# Explicit ordering for sections when displaying documentation or indexes
+SECTION_ORDER = {"Ui": 1, "Services": 2, "Threads": 3, "Utils": 4}
+
+# File extensions that should be recognized as linkable images
+LINKABLE_IMAGE_EXTENSIONS = {".png", ".jpg", ".jpeg", ".ico", ".gif"}
+
+
+def _is_pkg_dir(path: Path) -> bool:
+    """
+    Check whether a given path points to a valid Python package directory.
+
+    A valid package directory must:
+      1. Be a directory.
+      2. Contain an __init__.py file.
+
+    :param path: Filesystem path to check.
+    :return: True if the path is a Python package directory, False otherwise.
+    """
+    return path.is_dir() and (path / "__init__.py").exists()
+
+
+def find_package_dir(include_private: bool = INCLUDE_PRIVATE) -> tuple[Path, str]:
+    """
+    Locate the first valid Python package directory under SOURCE_DIR.
+
+    - Private packages (names starting with "_") can be excluded unless explicitly allowed.
+    - If multiple candidates exist, the package with the lexicographically smallest name is chosen.
+
+    :param include_private: Whether to allow private packages (default: global INCLUDE_PRIVATE).
+    :return: Tuple (package_path, package_name).
+    :raises SystemExit: If no valid package directory is found.
+    """
+    # Gather all package directories under SOURCE_DIR
+    candidates = [
+        package_path
+        for package_path in SOURCE_DIR.iterdir()
+        if _is_pkg_dir(package_path) and (include_private or not package_path.name.startswith("_"))
+    ]
+
+    # No valid package found > stop execution with an error message
+    if not candidates:
+        raise SystemExit("No package found in src/. Make sure you have something like " "src/yourpkg/__init__.py")
+
+    # Pick the lexicographically smallest directory (deterministic choice)
+    package_dir = min(candidates, key=lambda package_path: package_path.name)
+    return package_dir, package_dir.name
diff --git a/docs/gen_ref_pages/context.py b/docs/gen_ref_pages/context.py
new file mode 100644
index 0000000..3a841b1
--- /dev/null
+++ b/docs/gen_ref_pages/context.py
@@ -0,0 +1,50 @@
+from dataclasses import dataclass, field
+
+# Record structure:
+# - tuple: arbitrary metadata (e.g., file info)
+# - tuple[str, ...]: path parts (e.g., ("pkg", "subpkg"))
+# - str: identifier/name
+# - bool: status flag
+Record = tuple[tuple, tuple[str, ...], str, bool]
+
+
+@dataclass
+class Context:
+    """
+    Holds the in-memory representation of a package hierarchy. (tree structure)
+
+    Tracks:
+      - Created folder paths.
+      - Relationships between parent folders → child directories/modules.
+      - Records associated with discovered entities.
+    """
+
+    # Set of folder paths already created (each as a tuple of path parts).
+    created_folders: set[tuple[str, ...]] = field(default_factory=set)
+
+    # Map: parent folder > set of child directories.
+    children_directories: dict[tuple[str, ...], set[tuple[str, ...]]] = field(default_factory=dict)
+
+    # Map: parent folder > list of child modules.
+    children_modules: dict[tuple[str, ...], list[tuple[str, ...]]] = field(default_factory=dict)
+
+    # Collected records for all discovered items (see Record type alias).
+    records: list[Record] = field(default_factory=list)
+
+    def ensure_folder(self, parts: list[str]) -> None:
+        """
+        Ensure that a folder path is registered in the context.
+
+        If the folder path is not yet known:
+          - Add it to created_folders.
+          - Initialize its entry in children_directories and children_modules.
+
+        :param parts: Path components for the folder (e.g., ["pkg", "subpkg"]).
+        :return: None
+        """
+        key = tuple(parts)
+
+        if key not in self.created_folders:
+            self.created_folders.add(key)
+            self.children_directories.setdefault(key, set())
+            self.children_modules.setdefault(key, [])
diff --git a/docs/gen_ref_pages/gen_ref_pages.py b/docs/gen_ref_pages/gen_ref_pages.py
new file mode 100644
index 0000000..71a0da6
--- /dev/null
+++ b/docs/gen_ref_pages/gen_ref_pages.py
@@ -0,0 +1,150 @@
+"""
+Automatic API Documentation Generator for MkDocs.
+
+This script integrates with the `mkdocs-gen-files` plugin to dynamically
+generate API reference documentation from a Python package located in
+the source directory (by default `src/`, but this can be changed in `config.py`
+via the `SOURCE_DIR` setting).
+
+Workflow:
+1. Detects the main package directory under `SOURCE_DIR` (logic in `config.py`).
+2. Traverses the package structure (using `traverse.py`) to discover
+   modules, subpackages, and static files.
+3. Generates Markdown pages for:
+   - Each Python module (using `::: module.path` blocks for mkdocstrings).
+   - Each package/directory (with backlinks, subdirectory lists,
+     module lists, and static file sections).
+4. Stores navigation metadata in a `Context` object (`context.py`).
+5. Builds navigation files:
+   - `reference/index.md` → top-level reference index page,
+   - `reference/SUMMARY.md` → literate navigation for MkDocs.
+
+Usage (short form):
+- Run this script as part of the MkDocs build process (`mkdocs build` or `mkdocs serve`).
+- The script will automatically:
+  - detect the target package,
+  - create a documentation tree in the `reference/` directory,
+  - prepare navigation for integration with MkDocs.
+
+Usage (with MkDocs):
+1) Install required packages:
+   pip install mkdocs mkdocs-gen-files "mkdocstrings[python]"
+
+2) Ensure your project layout looks for example like this:
+   .
+   ├─ mkdocs.yml
+   ├─ docs/
+   │  └─ gen_ref_pages/
+   │     ├─ gen_ref_pages.py        # this script
+   │     ├─ config.py
+   │     ├─ context.py
+   │     ├─ generate.py
+   │     ├─ helpers.py
+   │     └─ traverse.py
+   ├─ src/                          # or another source dir set in config.SOURCE_DIR
+   │  └─ <your_package>/...
+
+3) Configure `mkdocs.yml` with plugins and navigation, e.g.:
+   site_name: Your Documentation
+   plugins:
+     - search
+     - gen-files:
+         scripts:
+           - docs/gen_ref_pages/gen_ref_pages.py   # path to this script
+     - mkdocstrings:
+         handlers:
+           python:
+             options:
+               show_source: true
+               docstring_style: google   # or "sphinx"/"numpy", depending on your style
+   nav:
+     - Reference: reference/              # generated reference section
+
+4) Run:
+   - Live preview: mkdocs serve
+   - Build static site: mkdocs build
+
+Customization:
+- Configuration is located in `config.py`:
+  - `SOURCE_DIR`: source directory where the package is located (default: `Path("src")`).
+    You can change this to any other directory (e.g. `Path("packages")`).
+  - `INCLUDE_PRIVATE`: whether to include private modules/packages (path parts starting with `_`).
+  - `SECTION_TITLE_MAP` and `SECTION_ORDER`: control naming and ordering of sections in navigation.
+  - `LINKABLE_IMAGE_EXTENSIONS`: which static files (in source directories) should be linked as clickable images.
+
+This script is intended to be run automatically as part of the MkDocs build process.
+You can place it anywhere in your repository and reference its path under `gen-files.scripts`.
+"""
+
+import sys
+from pathlib import Path
+
+# Ensure the current directory is on sys.path so local imports work correctly
+THIS_DIR = Path(__file__).resolve().parent
+THIS_DIR_STR = str(THIS_DIR)
+if THIS_DIR_STR not in sys.path:
+    sys.path.insert(0, THIS_DIR_STR)
+
+import mkdocs_gen_files  # noqa E402
+from config import INCLUDE_PRIVATE, find_package_dir  # noqa E402
+from context import Context  # noqa E402
+from generate import generate_directory_pages, generate_module_pages  # noqa E402
+from traverse import traverse_directories  # noqa E402
+
+
+def _build_nav(package_name: str, ctx: Context) -> None:
+    """
+    Build MkDocs navigation files from collected documentation records.
+
+    - Creates `reference/index.md` with a title and introduction.
+    - Creates `reference/SUMMARY.md` containing a literate navigation structure.
+
+    :param package_name: Name of the discovered package.
+    :param ctx: Context holding collected records from traversal.
+    :return: None
+    """
+    nav = mkdocs_gen_files.Nav()
+
+    # Sort collected records and populate the navigation
+    for _, display, doc_rel_path, _ in sorted(ctx.records, key=lambda record: record[0]):
+        nav[display] = doc_rel_path
+
+    # Generate top-level index page
+    with mkdocs_gen_files.open("reference/index.md", "w") as file_handle:
+        file_handle.write(f"# Reference – `{package_name}`\n\n")
+        file_handle.write("This section contains API documentation automatically " "generated from code.\n\n")
+
+    # Generate SUMMARY.md for MkDocs navigation
+    with mkdocs_gen_files.open("reference/SUMMARY.md", "w") as nav_file:
+        nav_file.writelines(nav.build_literate_nav())
+
+
+def main() -> None:
+    """
+    Entry point for documentation generation.
+
+    - Finds the main package under `src/`.
+    - Traverses directories to collect modules/folders.
+    - Generates module and directory pages.
+    - Builds MkDocs navigation files.
+
+    :return: None
+    """
+    package_dir, package_name = find_package_dir(INCLUDE_PRIVATE)
+
+    # Initialize a context object to hold traversal state and records
+    ctx = Context()
+
+    # Walk through directories and collect module/folder information
+    traverse_directories(package_dir, package_name, INCLUDE_PRIVATE, ctx)
+
+    # Generate documentation pages for modules and directories
+    generate_module_pages(package_dir, ctx)
+    generate_directory_pages(ctx)
+
+    # Build navigation index files
+    _build_nav(package_name, ctx)
+
+
+# Run the main process when the script is executed
+main()
diff --git a/docs/gen_ref_pages/generate.py b/docs/gen_ref_pages/generate.py
new file mode 100644
index 0000000..2fa6e0b
--- /dev/null
+++ b/docs/gen_ref_pages/generate.py
@@ -0,0 +1,289 @@
+import ast
+from pathlib import Path
+from typing import TextIO
+
+import mkdocs_gen_files
+from config import INCLUDE_PRIVATE, LINKABLE_IMAGE_EXTENSIONS, SOURCE_DIR
+from context import Context
+from helpers import display_parts_for, is_private, sort_key_for
+
+
+def _defined_public_members(source_file: Path, include_private: bool) -> list[str]:
+    try:
+        tree = ast.parse(source_file.read_text(encoding="utf-8"), filename=str(source_file))
+    except SyntaxError:
+        return []
+    names: list[str] = []
+    for node in tree.body:
+        if isinstance(node, ast.FunctionDef | ast.AsyncFunctionDef | ast.ClassDef):
+            if include_private or not node.name.startswith("_"):
+                names.append(node.name)
+    return names
+
+
+def _iter_public_python_files(package_dir: Path) -> list[Path]:
+    """
+    Recursively collect all public Python files within a package directory.
+
+    - Excludes __init__.py files.
+    - Excludes private files (names starting with "_").
+
+    :param package_dir: Base package directory.
+    :return: Sorted list of Python file paths.
+    """
+    files: list[Path] = []
+    for python_file in package_dir.rglob("*.py"):
+        if python_file.name == "__init__.py":
+            continue
+        if is_private(python_file):
+            continue
+        files.append(python_file)
+    return sorted(files)
+
+
+def _parts_from_source(python_file: Path) -> tuple[str, ...]:
+    """
+    Convert a Python file path under SOURCE_DIR into module parts.
+
+    Example:
+      src/pkg/module.py > ("pkg", "module")
+
+    :param python_file: Path to a Python file under SOURCE_DIR.
+    :return: Tuple of path components without an extension.
+    """
+    return tuple(python_file.relative_to(SOURCE_DIR).with_suffix("").parts)
+
+
+def _write_backlink_if_needed(fh: TextIO, parts: list[str]) -> None:
+    """
+    Write a backlink to the parent index if the page is not top-level.
+
+    :param fh: File handle to write to.
+    :param parts: Current parts representing this page.
+    :return: None
+    """
+    if len(parts) > 1:
+        parent_label = display_parts_for(parts[:-1])[-1]
+        fh.write(f"[⬅ Back to {parent_label}](../index.md)\n\n")
+
+
+def _record_page(ctx: Context, display_parts: list[str], doc_path: Path, is_directory: bool) -> None:
+    """
+    Add a record of a generated page to the context.
+
+    :param ctx: Shared Context object.
+    :param display_parts: Human-readable parts for display.
+    :param doc_path: Path to the generated documentation file.
+    :param is_directory: Whether the record refers to a directory index.
+    :return: None
+    """
+    display_tuple = tuple(display_parts)
+    doc_rel_path = doc_path.relative_to("reference").as_posix()
+    ctx.records.append((sort_key_for(display_parts), display_tuple, doc_rel_path, is_directory))
+
+
+def _display_sort_key(parts_like: tuple[str, ...]) -> tuple:
+    """
+    Compute a sort key for display purposes.
+
+    :param parts_like: Tuple of path parts.
+    :return: Sort key tuple.
+    """
+    return sort_key_for(display_parts_for(list(parts_like)))
+
+
+def _write_module_page(doc_path: Path, module_path: str, parent_parts: tuple[str, ...], source_file: Path) -> None:
+    """
+    Generate a documentation page for a single module.
+
+    :param doc_path: Target documentation path (index.md).
+    :param module_path: Dotted module path (e.g., "pkg.module").
+    :param parent_parts: Path parts for the parent package.
+    :param source_file: Path to the source Python file.
+    :return: None
+    """
+    mkdocs_gen_files.set_edit_path(doc_path, source_file)
+
+    members = _defined_public_members(source_file, INCLUDE_PRIVATE)
+
+    with mkdocs_gen_files.open(doc_path, "w") as fh:
+        if parent_parts:
+            _write_backlink_if_needed(fh, list(parent_parts) + ["_placeholder_"])
+        fh.write(f"::: {module_path}\n")
+        if members:
+            fh.write("    options:\n")
+            fh.write("      members:\n")
+            for name in members:
+                fh.write(f"      - {name}\n")
+
+
+def _collect_static_files(source_folder_fs: Path) -> list[Path]:
+    """
+    Collect non-Python static files in a source folder.
+
+    - Skips private files (names starting with "_").
+    - Includes only non-.py files.
+
+    :param source_folder_fs: Filesystem path to the source folder.
+    :return: List of static file paths.
+    """
+    static_files: list[Path] = []
+    if source_folder_fs.exists():
+        for source_file in sorted(source_folder_fs.iterdir()):
+            if source_file.name.startswith("_"):
+                continue
+            if source_file.is_file() and source_file.suffix != ".py":
+                static_files.append(source_file)
+    return static_files
+
+
+def _emit_static_files_list(
+    parts: list[str],
+    static_files: list[Path],
+    file_handle: TextIO,
+) -> None:
+    """
+    Emit a section listing static files for a given folder.
+
+    - Copies static files into `reference/.../_files/`.
+    - Links images if the extension is in LINKABLE_IMAGE_EXTENSIONS.
+
+    :param parts: Path parts of the folder.
+    :param static_files: List of static file paths.
+    :param file_handle: File handle to write documentation into.
+    :return: None
+    """
+    if not static_files:
+        return
+
+    file_handle.write("## 🗃️ Static Files\n\n")
+
+    for file_path in static_files:
+        destination = Path("reference", *parts, "_files", file_path.name)
+
+        # Copy file content into the documentation tree
+        with mkdocs_gen_files.open(destination, "wb") as out_file:
+            out_file.write(file_path.read_bytes())
+
+        # Build relative link
+        relative_link = f"_files/{file_path.name}"
+        ext = file_path.suffix.lower()
+
+        # Display images as clickable links
+        if ext in LINKABLE_IMAGE_EXTENSIONS:
+            file_handle.write(f"- [{file_path.name}]({relative_link})\n")
+        else:
+            file_handle.write(f"- {file_path.name}\n")
+
+    file_handle.write("\n")
+
+
+def _write_directory_page(
+    ctx: Context,
+    parts: list[str],
+    subdirectories: list[tuple[str, ...]],
+    modules: list[tuple[str, ...]],
+    static_files: list[Path],
+) -> Path:
+    """
+    Generate a documentation index page for a directory.
+
+    Includes:
+      - Backlink to parent if applicable.
+      - Subdirectory links.
+      - Module links.
+      - Static file listings.
+
+    :param ctx: Context to update with record.
+    :param parts: Path parts of the directory.
+    :param subdirectories: List of subdirectory paths.
+    :param modules: List of module paths.
+    :param static_files: List of static file paths in this directory.
+    :return: Path to generated index.md file.
+    """
+    doc_path = Path("reference", *parts, "index.md")
+
+    mkdocs_gen_files.set_edit_path(doc_path, SOURCE_DIR.joinpath(*parts, "__init__.py"))
+
+    with mkdocs_gen_files.open(doc_path, "w") as file_handle:
+        _write_backlink_if_needed(file_handle, parts)
+
+        file_handle.write(f"# `{'.'.join(parts)}`\n\n")
+
+        if subdirectories:
+            file_handle.write("## 📁 Subdirectories\n\n")
+            for child in subdirectories:
+                label = display_parts_for(list(child))[-1]
+                file_handle.write(f"- [{label}]({child[-1]}/index.md)\n")
+            file_handle.write("\n")
+
+        if modules:
+            file_handle.write("## 📄 Modules\n\n")
+            for child in modules:
+                label = display_parts_for(list(child))[-1]
+                file_handle.write(f"- [{label}]({child[-1]}/index.md)\n")
+            file_handle.write("\n")
+
+        _emit_static_files_list(parts, static_files, file_handle)
+
+        # Fallback if directory is empty
+        if not subdirectories and not modules and not static_files:
+            file_handle.write("_This section has no subdirectories, modules, or static files yet._\n")
+
+    _record_page(ctx, display_parts_for(parts), doc_path, is_directory=True)
+    return doc_path
+
+
+def generate_module_pages(package_dir: Path, ctx: Context) -> None:
+    """
+    Generate documentation pages for all public modules under a package.
+
+    :param package_dir: Root package directory.
+    :param ctx: Context object to update.
+    :return: None
+    """
+    for python_file in _iter_public_python_files(package_dir):
+        parts = _parts_from_source(python_file)
+        parent_parts = parts[:-1]
+
+        # Ensure parent folder exists in context
+        ctx.ensure_folder(list(parent_parts))
+
+        # Add this module under its parent
+        ctx.children_modules.setdefault(parent_parts, []).append(parts)
+
+        module_path = ".".join(parts)
+        doc_path = Path("reference", *parts, "index.md")
+
+        # Write module page and record it
+        _write_module_page(doc_path, module_path, parent_parts, python_file)
+        _record_page(ctx, display_parts_for(list(parts)), doc_path, is_directory=False)
+
+
+def generate_directory_pages(ctx: Context) -> None:
+    """
+    Generate documentation index pages for all discovered directories.
+
+    :param ctx: Context object holding traversal state.
+    :return: None
+    """
+    for key in sorted(ctx.created_folders):
+        parts = list(key)
+        parts_tuple = tuple(parts)
+
+        source_folder_fs = SOURCE_DIR.joinpath(*parts)
+        source_folder_fs = SOURCE_DIR.joinpath(*parts)
+        static_files = _collect_static_files(source_folder_fs)
+
+        # Gather subdirectories and modules for this folder
+        subdirectories = sorted(
+            ctx.children_directories.get(parts_tuple, set()),
+            key=_display_sort_key,
+        )
+        modules = sorted(
+            ctx.children_modules.get(parts_tuple, []),
+            key=_display_sort_key,
+        )
+
+        # Write directory index page
+        _write_directory_page(ctx, parts, subdirectories, modules, static_files)
diff --git a/docs/gen_ref_pages/helpers.py b/docs/gen_ref_pages/helpers.py
new file mode 100644
index 0000000..7710695
--- /dev/null
+++ b/docs/gen_ref_pages/helpers.py
@@ -0,0 +1,83 @@
+from collections.abc import Iterable
+from pathlib import Path
+
+from config import INCLUDE_PRIVATE, SECTION_ORDER, SECTION_TITLE_MAP
+
+
+def is_private(path: Path) -> bool:
+    """
+    Determine whether a given path should be considered private.
+
+    Rules:
+      - If INCLUDE_PRIVATE is True > nothing is private.
+      - Otherwise, any path component starting with "_" marks it as private.
+
+    :param path: Filesystem path.
+    :return: True if the path is private, False otherwise.
+    """
+    return False if INCLUDE_PRIVATE else any(package_path.startswith("_") for package_path in path.parts)
+
+
+def prettify(label: str) -> str:
+    """
+    Convert an identifier string into a user-friendly label.
+
+    - Underscores are replaced with spaces.
+    - Each word is capitalized.
+
+    Example:
+      "my_module" > "My Module"
+
+    :param label: Original string.
+    :return: Prettified version.
+    """
+    return label.replace("_", " ").title()
+
+
+def display_parts_for(parts: list[str]) -> list[str]:
+    """
+    Build display-friendly parts for navigation from raw path parts.
+
+    - Second element may be replaced by a mapped section title (SECTION_TITLE_MAP).
+    - Remaining elements are prettified.
+
+    Example:
+      ["mypkg", "ui", "main_window"]
+      > ["mypkg", "UI", "Main Window"]
+
+    :param parts: Raw path components.
+    :return: List of human-readable display parts.
+    """
+    display = list(parts)
+
+    # Replace known section keys (e.g., "ui" > "UI")
+    if len(display) >= 2 and display[1] in SECTION_TITLE_MAP:
+        display[1] = SECTION_TITLE_MAP[display[1]]
+
+    # Prettify remaining elements
+    for i in range(1, len(display)):
+        display[i] = prettify(display[i])
+
+    return display
+
+
+def sort_key_for(display_parts: Iterable[str]) -> tuple:
+    """
+    Build a sort key for consistent ordering of navigation items.
+
+    Criteria:
+      1. Section order (from SECTION_ORDER, default 999).
+      2. Path length (shorter first).
+      3. Alphabetical (case-insensitive).
+
+    :param display_parts: Human-readable path parts.
+    :return: Tuple usable as the sort key.
+    """
+    path_parts = list(display_parts)
+    section = path_parts[1] if len(path_parts) >= 2 else ""
+
+    return (
+        SECTION_ORDER.get(section, 999),
+        len(path_parts),
+        tuple(part.lower() for part in path_parts),
+    )
diff --git a/docs/gen_ref_pages/traverse.py b/docs/gen_ref_pages/traverse.py
new file mode 100644
index 0000000..1c13896
--- /dev/null
+++ b/docs/gen_ref_pages/traverse.py
@@ -0,0 +1,127 @@
+import os
+from collections.abc import Iterable
+from pathlib import Path
+
+from context import Context
+from helpers import is_private
+
+
+def _walk_dirs(package_dir: Path, include_private: bool) -> Iterable[tuple[Path, list[str]]]:
+    """
+    Walk the filesystem tree starting at package_dir and yield
+    (relative_dir, subdirs) pairs.
+
+    Rules:
+      - Private subdirectories (names starting with "_") are removed in-place
+        unless include_private=True.
+      - Entire directories marked private are skipped completely.
+
+    :param package_dir: Path to the root package (e.g., src/mypkg).
+    :param include_private: Whether to include private directories.
+    :return: Iterator of (relative_dir, subdirs).
+
+    Example:
+        "src/mypkg" > [(Path("mypkg"), ["subdir1", "subdir2"])]
+    """
+    source_dir = package_dir.parent
+
+    # Walk filesystem tree starting at package_dir
+    for current_dirpath, subdirs, _ in os.walk(package_dir):
+        relative_dir = Path(current_dirpath).relative_to(source_dir)
+
+        # Remove unnecessary catalogues (pycache, build, dist)
+        subdirs[:] = [dirname for dirname in subdirs if dirname != "__pycache__" and dirname not in {"build", "dist"}]
+
+        # Remove private subdirectories in-place if not including them
+        if not include_private:
+            subdirs[:] = [dirname for dirname in subdirs if not dirname.startswith("_")]
+
+        # Skip the current directory if it's marked private
+        if is_private(relative_dir):
+            continue
+
+        yield relative_dir, subdirs
+
+
+def _parts_for(relative_dir: Path, package_name: str) -> list[str]:
+    """
+    Convert a relative path into parts; fallback to package_name for the root.
+
+    :param relative_dir: Path relative to the source directory.
+    :param package_name: Top-level package name.
+    :return: List of path components.
+
+    Examples:
+        "mypkg/subdir" > ["mypkg", "subdir"]
+        "." (root) > ["mypkg"]
+    """
+    return list(relative_dir.parts) or [package_name]
+
+
+def _register_folder(ctx: Context, folder_parts: list[str]) -> tuple[str, ...]:
+    """
+    Ensure the given folder exists in Context and return it as a tuple key.
+
+    :param ctx: Shared Context object.
+    :param folder_parts: List of folder path components.
+    :return: Tuple representation of the folder path.
+
+    Example:
+        ["mypkg", "subdir"] > ("mypkg", "subdir")
+    """
+    ctx.ensure_folder(folder_parts)
+    return tuple(folder_parts)
+
+
+def _register_children(ctx: Context, parent_parts: list[str], child_names: Iterable[str]) -> None:
+    """
+    Register each child subdirectory of a given parent folder in Context.
+
+    :param ctx: Shared Context object.
+    :param parent_parts: Parent folder path components.
+    :param child_names: Iterable of subdirectory names.
+    :return: None
+
+    Example:
+        ["mypkg"], ["a", "b"] > {("mypkg", "a"), ("mypkg", "b")}
+    """
+    parent_t = tuple(parent_parts)
+    # Register each child subdirectory
+    for dirname in sorted(child_names):
+        child_parts = parent_parts + [dirname]
+        ctx.ensure_folder(child_parts)
+        ctx.children_directories[parent_t].add(tuple(child_parts))
+
+
+def traverse_directories(
+    package_dir: Path,
+    package_name: str,
+    include_private: bool,
+    ctx: Context,
+) -> None:
+    """
+    Walk through the package directory tree and populate the Context
+    with discovered folders and their relationships.
+
+    Rules:
+      - Private directories (names starting with "_") are skipped unless
+        include_private=True.
+      - Each valid folder is registered in ctx.created_folders.
+      - Parent > child directory relationships are stored in ctx.children_directories.
+
+    :param package_dir: Path to the root package (e.g., src/mypkg).
+    :param package_name: Top-level package name.
+    :param include_private: Whether to include private directories.
+    :param ctx: Shared Context object to update.
+    :return: None
+
+    Example:
+        "src/mypkg" > {("mypkg",)}
+    """
+    for relative_dir, subdirs in _walk_dirs(package_dir, include_private=include_private):
+        # Convert the path into parts; fallback to package_name for root
+        folder_parts = _parts_for(relative_dir, package_name)
+        _register_folder(ctx, folder_parts)
+
+        # Register each child subdirectory
+        _register_children(ctx, folder_parts, subdirs)
diff --git a/docs/index.md b/docs/index.md
new file mode 100644
index 0000000..754b4ea
--- /dev/null
+++ b/docs/index.md
@@ -0,0 +1,105 @@
+# UQ Desktop Processor
+
+`uq-desktop-processor` is a desktop app and Python package for visual urban assessment from street-level imagery.  
+It combines road-network sampling, optional Mapillary downloads (or your own images), CLIP-based prefiltering and scoring, optional ViT workflows, and GIS-friendly export formats.
+
+> Package name: `uq_desktop_processor`  
+> Python: `3.12-3.14`
+
+---
+
+## Key Features
+
+- Chinese postman / drive routes with GPX export for efficient field coverage.
+- Road-based sampling points with configurable spacing and minimum separation.
+- Mapillary image download near points, or processing of local image folders.
+- CLIP prefilter that moves low-relevance images to `rejected`.
+- CLIP prompt scoring on urban-quality axes (for example: beauty, safety, wealth).
+- Optional ViT / finetuned evaluation path.
+- Export to GeoJSON, GPKG, SHP, and Parquet via GeoPandas.
+
+---
+
+## Quick Start
+
+### Run with Poetry (recommended)
+
+```bash
+poetry install
+poetry run uq_desktop_processor
+```
+
+### Run with pip
+
+```bash
+python -m venv .venv
+.venv\Scripts\activate
+pip install --upgrade pip
+pip install -e .
+python -m uq_desktop_processor
+```
+
+---
+
+## Mapillary Token
+
+For Mapillary downloads, set `MAPILLARY_ACCESS_TOKEN` (or provide the token directly in the GUI).
+
+PowerShell:
+
+```powershell
+$env:MAPILLARY_ACCESS_TOKEN = "YOUR_TOKEN_HERE"
+```
+
+Bash:
+
+```bash
+export MAPILLARY_ACCESS_TOKEN="YOUR_TOKEN_HERE"
+```
+
+---
+
+## Typical Data Layout
+
+```text
+data/
+|- images/
+|  |- raw/
+|  `- rejected/
+`- results/
+   |- sampling_points.geojson
+   `- urban_quality_ai_output.geojson
+```
+
+---
+
+## Documentation and Development
+
+- Build docs locally:
+
+```bash
+mkdocs serve
+mkdocs build
+```
+
+- Common checks:
+
+```bash
+poetry run pytest
+poetry run mypy src/
+poetry run ruff check .
+poetry run black --check .
+pre-commit run --all-files
+```
+
+---
+
+## Project Source
+
+Main package: `src/uq_desktop_processor/`
+
+- `gui/` - PySide6 application shell and pages
+- `pipeline/` - pipeline orchestration and defaults
+- `evaluation/` - CLIP prefilter/evaluator and finetuned evaluator
+- `street_view_analysis/` - sampling, road graph, Mapillary, drive routes
+- `layer_creation/` - vector outputs for GIS workflows
diff --git a/docs/readme_images/gui-drive-routes.png b/docs/readme_images/gui-drive-routes.png
new file mode 100644
index 0000000..9b63dfa
Binary files /dev/null and b/docs/readme_images/gui-drive-routes.png differ
diff --git a/docs/readme_images/gui-sampling-points.png b/docs/readme_images/gui-sampling-points.png
new file mode 100644
index 0000000..d320d9c
Binary files /dev/null and b/docs/readme_images/gui-sampling-points.png differ
diff --git a/docs/readme_images/gui-vit-evaluation.png b/docs/readme_images/gui-vit-evaluation.png
new file mode 100644
index 0000000..7339abd
Binary files /dev/null and b/docs/readme_images/gui-vit-evaluation.png differ
diff --git a/mkdocs.yml b/mkdocs.yml
new file mode 100644
index 0000000..e067bd0
--- /dev/null
+++ b/mkdocs.yml
@@ -0,0 +1,109 @@
+# Project information
+site_name: "UrbanQuality-AI: desktop_processor"               # The title of the documentation site
+site_description: Docs for UrbanQuality-AI desktop_processor  # Short description of the site (used in metadata)
+repo_url: https://github.com/UrbanQuality-AI/uq-desktop-processor  # Link to the GitHub repository
+repo_name: UrbanQuality-AI/uq-desktop-processor       # Name of the repository displayed in the UI
+
+# Theme configuration
+theme:
+  name: material                    # Use the "Material for MkDocs" theme
+  language: en                      # Interface language
+  font:
+    text: Inter                     # Font used for body text
+    code: JetBrains Mono            # Font used for code blocks
+  features:                         # Enable additional theme features
+    - navigation.tabs               # Show navigation tabs at the top
+    - navigation.tabs.sticky        # Keep tabs visible while scrolling
+    - navigation.top                # Back-to-top button
+    - navigation.sections           # Group navigation items into sections
+    - navigation.indexes            # Allow section index pages
+    - toc.integrate                 # Integrate table of contents into the navigation
+    - toc.follow                    # Highlight current section in the table of contents
+    - content.code.copy             # Add a "copy" button to code blocks
+    - search.suggest                # Enable search suggestions
+    - search.highlight              # Highlight search matches in content
+  palette:                          # Define color palettes and UI themes
+    - media: "(prefers-color-scheme: light)"  # Default light mode
+      scheme: default
+      primary: indigo
+      accent: indigo
+      toggle:
+        icon: material/weather-night # Icon for switching to dark mode
+        name: Dark mode
+    - media: "(prefers-color-scheme: dark)"   # Default dark mode
+      scheme: slate
+      primary: indigo
+      accent: indigo
+      toggle:
+        icon: material/weather-sunny # Icon for switching back to light mode
+        name: Light mode
+    - scheme: brand                 # Custom "brand" color scheme
+      primary: deep purple
+      accent: cyan
+      toggle:
+        icon: material/palette
+        name: Brand look
+    - scheme: compact               # Compact layout variant
+      primary: indigo
+      accent: indigo
+      toggle:
+        icon: material/format-line-spacing
+        name: Compact spacing
+    - scheme: comfy                 # Comfortable spacing variant
+      primary: indigo
+      accent: indigo
+      toggle:
+        icon: material/format-size
+        name: Comfortable size
+
+# Plugins extend MkDocs functionality
+plugins:
+  - search                                        # Built-in search engine
+  - autorefs                                      # Automatic cross-references between documents
+  - gen-files:                                    # Generate files dynamically
+      scripts:
+        - docs/gen_ref_pages/gen_ref_pages.py     # Script for generating reference pages
+  - literate-nav                                  # Define navigation structure from Markdown files
+  - mkdocstrings:                                 # Auto-generate API documentation from docstrings
+      handlers:
+        python:                                   # Handler for Python code
+          paths: [src]                            # Source code directory
+          options:                                # Rendering options
+            docstring_style: sphinx
+            docstring_section_style: table
+            separate_signature: true
+            show_signature_annotations: true
+            line_length: 88
+            group_by_category: true
+            show_category_heading: true
+            merge_init_into_class: true
+            members_order: source
+            inherited_members: true
+            show_if_no_docstring: true
+            show_root_heading: true
+            show_root_toc_entry: true
+            show_source: false      # Do not show source code links
+
+
+# Markdown extensions
+markdown_extensions:
+  - admonition                      # Support for callout/admonition blocks
+  - footnotes                       # Support for footnotes
+  - attr_list                       # Allow attributes inside Markdown elements
+  - pymdownx.details                # Collapsible details blocks
+  - pymdownx.superfences            # Enhanced fenced code blocks
+  - pymdownx.tabbed:                # Tabbed content
+      alternate_style: true
+  - pymdownx.highlight              # Syntax highlighting for code blocks
+  - toc:                            # Table of contents
+      permalink: true               # Add anchor links to TOC headings
+
+# Extra custom CSS
+extra_css:
+  - css/mkdocstrings.css            # Custom styles for mkdocstrings
+  - css/theme-variants.css          # Custom styles for theme variants
+
+# Navigation (menu structure)
+nav:
+  - Home: index.md
+  - Reference: reference/SUMMARY.md
\ No newline at end of file
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..a3c62c7
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,3488 @@
+# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand.
+
+[[package]]
+name = "anyio"
+version = "4.11.0"
+description = "High-level concurrency and networking framework on top of asyncio or Trio"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "anyio-4.11.0-py3-none-any.whl", hash = "sha256:0287e96f4d26d4149305414d4e3bc32f0dcd0862365a4bddea19d7a1ec38c4fc"},
+    {file = "anyio-4.11.0.tar.gz", hash = "sha256:82a8d0b81e318cc5ce71a5f1f8b5c4e63619620b63141ef8c995fa0db95a57c4"},
+]
+
+[package.dependencies]
+idna = ">=2.8"
+sniffio = ">=1.1"
+typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""}
+
+[package.extras]
+trio = ["trio (>=0.31.0)"]
+
+[[package]]
+name = "attrs"
+version = "25.4.0"
+description = "Classes Without Boilerplate"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "attrs-25.4.0-py3-none-any.whl", hash = "sha256:adcf7e2a1fb3b36ac48d97835bb6d8ade15b8dcce26aba8bf1d14847b57a3373"},
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+
+[[package]]
+name = "babel"
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+groups = ["dev"]
+files = [
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+
+[package.extras]
+dev = ["backports.zoneinfo ; python_version < \"3.9\"", "freezegun (>=1.0,<2.0)", "jinja2 (>=3.0)", "pytest (>=6.0)", "pytest-cov", "pytz", "setuptools", "tzdata ; sys_platform == \"win32\""]
+
+[[package]]
+name = "backrefs"
+version = "6.1"
+description = "A wrapper around re and regex that adds additional back references."
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+python-versions = ">=3.9"
+groups = ["dev"]
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+
+[[package]]
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+
+[package.dependencies]
+distlib = ">=0.3.7,<1"
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+platformdirs = ">=3.9.1,<5"
+
+[package.extras]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
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+
+[[package]]
+name = "watchdog"
+version = "6.0.0"
+description = "Filesystem events monitoring"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
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+    {file = "watchdog-6.0.0-py3-none-manylinux2014_armv7l.whl", hash = "sha256:9041567ee8953024c83343288ccc458fd0a2d811d6a0fd68c4c22609e3490379"},
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+    {file = "watchdog-6.0.0-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:e3df4cbb9a450c6d49318f6d14f4bbc80d763fa587ba46ec86f99f9e6876bb26"},
+    {file = "watchdog-6.0.0-py3-none-manylinux2014_s390x.whl", hash = "sha256:2cce7cfc2008eb51feb6aab51251fd79b85d9894e98ba847408f662b3395ca3c"},
+    {file = "watchdog-6.0.0-py3-none-manylinux2014_x86_64.whl", hash = "sha256:20ffe5b202af80ab4266dcd3e91aae72bf2da48c0d33bdb15c66658e685e94e2"},
+    {file = "watchdog-6.0.0-py3-none-win32.whl", hash = "sha256:07df1fdd701c5d4c8e55ef6cf55b8f0120fe1aef7ef39a1c6fc6bc2e606d517a"},
+    {file = "watchdog-6.0.0-py3-none-win_amd64.whl", hash = "sha256:cbafb470cf848d93b5d013e2ecb245d4aa1c8fd0504e863ccefa32445359d680"},
+    {file = "watchdog-6.0.0-py3-none-win_ia64.whl", hash = "sha256:a1914259fa9e1454315171103c6a30961236f508b9b623eae470268bbcc6a22f"},
+    {file = "watchdog-6.0.0.tar.gz", hash = "sha256:9ddf7c82fda3ae8e24decda1338ede66e1c99883db93711d8fb941eaa2d8c282"},
+]
+
+[package.extras]
+watchmedo = ["PyYAML (>=3.10)"]
+
+[[package]]
+name = "wcwidth"
+version = "0.2.14"
+description = "Measures the displayed width of unicode strings in a terminal"
+optional = false
+python-versions = ">=3.6"
+groups = ["main"]
+files = [
+    {file = "wcwidth-0.2.14-py2.py3-none-any.whl", hash = "sha256:a7bb560c8aee30f9957e5f9895805edd20602f2d7f720186dfd906e82b4982e1"},
+    {file = "wcwidth-0.2.14.tar.gz", hash = "sha256:4d478375d31bc5395a3c55c40ccdf3354688364cd61c4f6adacaa9215d0b3605"},
+]
+
+[[package]]
+name = "yaspin"
+version = "3.3.0"
+description = "Yet Another Terminal Spinner"
+optional = false
+python-versions = "<4.0,>=3.9"
+groups = ["main"]
+files = [
+    {file = "yaspin-3.3.0-py3-none-any.whl", hash = "sha256:ab5113be4b34ef33f7d4d97be9b6867101ad020c2fb02bc92e3137c75b06d712"},
+    {file = "yaspin-3.3.0.tar.gz", hash = "sha256:505c9a44c6e3723a1bee8f7a17a055b17475176b74dd93e468fa8db48c172a41"},
+]
+
+[package.dependencies]
+termcolor = ">=3.1,<4.0"
+
+[metadata]
+lock-version = "2.1"
+python-versions = ">=3.12,<3.15"
+content-hash = "7ffbc7895146e77cf680414205531433181a8ae70b594d696e7dbba4a28e42cb"
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..095118d
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,89 @@
+[tool.poetry]
+package-mode = true
+packages = [{ include = "uq_desktop_processor", from = "src" }]
+
+[project]
+name = "uq_desktop_processor"
+version = "1.0.0"
+description = "AI-assisted visual urban assessment from street-level imagery: road-network sampling, Mapillary downloads, CLIP/ViT scoring, and GIS-ready exports (GeoJSON/GPKG)."
+readme = "README.md"
+requires-python = ">=3.12,<3.15"
+license = "LicenseRef-UNLICENSED"
+license-files = ["LICENSE"]
+authors = [{ name = "Antek-N", email = "antek.nikolajdu@gmail.com" }]
+dynamic = ["dependencies", "optional-dependencies"]
+
+[project.scripts]
+uq_desktop_processor = "uq_desktop_processor.__main__:main"
+uq-desktop-processor = "uq_desktop_processor.__main__:main"
+
+[tool.poetry.dependencies]
+python = ">=3.12,<3.15"
+torch = "^2.4.0"
+torchvision = "^0.19.0"
+timm = "^1.0.0"
+numpy = "<2.0"
+pillow = "^10.0.0"
+tqdm = "^4.66.0"
+tabulate = "^0.9.0"
+joblib = "^1.4.0"
+clip = { git = "https://github.com/openai/CLIP.git" }
+ftfy = "^6.3.1"
+regex = "^2025.9.1"
+geopandas = "^1.0.0"
+shapely = "^2.0.0"
+pyproj = "^3.6.0"
+fiona = "^1.9.0"
+pyogrio = "^0.9.0"
+osmnx = "^1.9.0"
+yaspin = "^3.0.0"
+matplotlib = "^3.8.0"
+requests = "^2.32.0"
+opencv-python-headless = "^4.9.0"
+piexif = "^1.1.3"
+py360convert  = "^0.1.0"
+pyside6 = "^6.11.0"
+gpxpy = "^1.6.2"
+pydeck = "^0.9.1"
+
+[tool.poetry.group.dev.dependencies]
+black = "^25.1.0"
+ruff = "^0.12.12"
+mypy = "^1.17.1"
+pytest = "^8.3.0"
+pytest-cov = "^5.0.0"
+pre-commit = "^3.6.0"
+mkdocs = "^1.6"
+mkdocs-material = "^9.5"
+mkdocs-autorefs = "^1.2"
+mkdocs-gen-files = "^0.5"
+mkdocs-literate-nav = "^0.6"
+mkdocstrings = "^0.25"
+mkdocstrings-python = "^1.10"
+pymdown-extensions = "^10.8"
+types-requests = "^2.32.4.20250913"
+
+[build-system]
+requires = ["poetry-core>=2.0.0,<3.0.0"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.black]
+line-length = 120
+target-version = ["py312"]
+
+[tool.ruff]
+line-length = 120
+target-version = "py312"
+fix = false
+
+[tool.ruff.lint]
+select = ["E", "F", "I", "B", "UP"]
+ignore = ["E501"]
+
+[tool.mypy]
+python_version = "3.12"
+strict = false
+warn_unused_configs = true
+disallow_untyped_defs = true
+ignore_missing_imports = true
+exclude = "^(tests/|site/|\\.venv/|out/)"
\ No newline at end of file
diff --git a/requirements-dev.txt b/requirements-dev.txt
new file mode 100644
index 0000000..b9e5403
--- /dev/null
+++ b/requirements-dev.txt
@@ -0,0 +1,124 @@
+anyio==4.11.0 ; python_version >= "3.12" and python_version < "3.15"
+attrs==25.4.0 ; python_version >= "3.12" and python_version < "3.15"
+babel==2.17.0 ; python_version >= "3.12" and python_version < "3.15"
+backrefs==6.1 ; python_version >= "3.12" and python_version < "3.15"
+black==25.11.0 ; python_version >= "3.12" and python_version < "3.15"
+certifi==2025.11.12 ; python_version >= "3.12" and python_version < "3.15"
+cfgv==3.5.0 ; python_version >= "3.12" and python_version < "3.15"
+charset-normalizer==3.4.4 ; python_version >= "3.12" and python_version < "3.15"
+click-plugins==1.1.1.2 ; python_version >= "3.12" and python_version < "3.15"
+click==8.3.1 ; python_version >= "3.12" and python_version < "3.15"
+cligj==0.7.2 ; python_version >= "3.12" and python_version < "3.15"
+clip @ git+https://github.com/openai/CLIP.git@dcba3cb2e2827b402d2701e7e1c7d9fed8a20ef1 ; python_version >= "3.12" and python_version < "3.15"
+colorama==0.4.6 ; python_version >= "3.12" and python_version < "3.15"
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+coverage==7.12.0 ; python_version >= "3.12" and python_version < "3.15"
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+distlib==0.4.0 ; python_version >= "3.12" and python_version < "3.15"
+filelock==3.20.0 ; python_version >= "3.12" and python_version < "3.15"
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+fonttools==4.60.1 ; python_version >= "3.12" and python_version < "3.15"
+fsspec==2025.10.0 ; python_version >= "3.12" and python_version < "3.15"
+ftfy==6.3.1 ; python_version >= "3.12" and python_version < "3.15"
+geopandas==1.1.1 ; python_version >= "3.12" and python_version < "3.15"
+ghp-import==2.1.0 ; python_version >= "3.12" and python_version < "3.15"
+gpxpy==1.6.2 ; python_version >= "3.12" and python_version < "3.15"
+griffe==1.15.0 ; python_version >= "3.12" and python_version < "3.15"
+h11==0.16.0 ; python_version >= "3.12" and python_version < "3.15"
+hf-xet==1.2.0 ; python_version >= "3.12" and python_version < "3.15" and (platform_machine == "x86_64" or platform_machine == "amd64" or platform_machine == "AMD64" or platform_machine == "arm64" or platform_machine == "aarch64")
+httpcore==1.0.9 ; python_version >= "3.12" and python_version < "3.15"
+httpx==0.28.1 ; python_version >= "3.12" and python_version < "3.15"
+huggingface-hub==1.1.5 ; python_version >= "3.12" and python_version < "3.15"
+identify==2.6.15 ; python_version >= "3.12" and python_version < "3.15"
+idna==3.11 ; python_version >= "3.12" and python_version < "3.15"
+iniconfig==2.3.0 ; python_version >= "3.12" and python_version < "3.15"
+jinja2==3.1.6 ; python_version >= "3.12" and python_version < "3.15"
+joblib==1.5.2 ; python_version >= "3.12" and python_version < "3.15"
+kiwisolver==1.4.9 ; python_version >= "3.12" and python_version < "3.15"
+markdown==3.10 ; python_version >= "3.12" and python_version < "3.15"
+markupsafe==3.0.3 ; python_version >= "3.12" and python_version < "3.15"
+matplotlib==3.10.7 ; python_version >= "3.12" and python_version < "3.15"
+mergedeep==1.3.4 ; python_version >= "3.12" and python_version < "3.15"
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+mkdocs-gen-files==0.5.0 ; python_version >= "3.12" and python_version < "3.15"
+mkdocs-get-deps==0.2.0 ; python_version >= "3.12" and python_version < "3.15"
+mkdocs-literate-nav==0.6.2 ; python_version >= "3.12" and python_version < "3.15"
+mkdocs-material-extensions==1.3.1 ; python_version >= "3.12" and python_version < "3.15"
+mkdocs-material==9.7.0 ; python_version >= "3.12" and python_version < "3.15"
+mkdocs==1.6.1 ; python_version >= "3.12" and python_version < "3.15"
+mkdocstrings-python==1.10.9 ; python_version >= "3.12" and python_version < "3.15"
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+mpmath==1.3.0 ; python_version >= "3.12" and python_version < "3.15"
+mypy-extensions==1.1.0 ; python_version >= "3.12" and python_version < "3.15"
+mypy==1.18.2 ; python_version >= "3.12" and python_version < "3.15"
+networkx==3.5 ; python_version >= "3.12" and python_version < "3.15"
+nodeenv==1.9.1 ; python_version >= "3.12" and python_version < "3.15"
+numpy==1.26.4 ; python_version >= "3.12" and python_version < "3.15"
+nvidia-cublas-cu12==12.1.3.1 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cuda-cupti-cu12==12.1.105 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cuda-nvrtc-cu12==12.1.105 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cuda-runtime-cu12==12.1.105 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cudnn-cu12==9.1.0.70 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cufft-cu12==11.0.2.54 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-curand-cu12==10.3.2.106 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cusolver-cu12==11.4.5.107 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cusparse-cu12==12.1.0.106 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-nccl-cu12==2.20.5 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-nvjitlink-cu12==12.8.93 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-nvtx-cu12==12.1.105 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+opencv-python-headless==4.11.0.86 ; python_version >= "3.12" and python_version < "3.15"
+osmnx==1.9.3 ; python_version >= "3.12" and python_version < "3.15"
+packaging==25.0 ; python_version >= "3.12" and python_version < "3.15"
+paginate==0.5.7 ; python_version >= "3.12" and python_version < "3.15"
+pandas==2.3.3 ; python_version >= "3.12" and python_version < "3.15"
+pathspec==0.12.1 ; python_version >= "3.12" and python_version < "3.15"
+piexif==1.1.3 ; python_version >= "3.12" and python_version < "3.15"
+pillow==10.4.0 ; python_version >= "3.12" and python_version < "3.15"
+platformdirs==4.5.0 ; python_version >= "3.12" and python_version < "3.15"
+pluggy==1.6.0 ; python_version >= "3.12" and python_version < "3.15"
+pre-commit==3.8.0 ; python_version >= "3.12" and python_version < "3.15"
+py360convert==0.1.0 ; python_version >= "3.12" and python_version < "3.15"
+pydeck==0.9.1 ; python_version >= "3.12" and python_version < "3.15"
+pygments==2.19.2 ; python_version >= "3.12" and python_version < "3.15"
+pymdown-extensions==10.17.1 ; python_version >= "3.12" and python_version < "3.15"
+pyogrio==0.9.0 ; python_version >= "3.12" and python_version < "3.15"
+pyparsing==3.2.5 ; python_version >= "3.12" and python_version < "3.15"
+pyproj==3.7.2 ; python_version >= "3.12" and python_version < "3.15"
+pyside6-addons==6.11.0 ; python_version >= "3.12" and python_version < "3.15"
+pyside6-essentials==6.11.0 ; python_version >= "3.12" and python_version < "3.15"
+pyside6==6.11.0 ; python_version >= "3.12" and python_version < "3.15"
+pytest-cov==5.0.0 ; python_version >= "3.12" and python_version < "3.15"
+pytest==8.4.2 ; python_version >= "3.12" and python_version < "3.15"
+python-dateutil==2.9.0.post0 ; python_version >= "3.12" and python_version < "3.15"
+pytokens==0.3.0 ; python_version >= "3.12" and python_version < "3.15"
+pytz==2025.2 ; python_version >= "3.12" and python_version < "3.15"
+pyyaml-env-tag==1.1 ; python_version >= "3.12" and python_version < "3.15"
+pyyaml==6.0.3 ; python_version >= "3.12" and python_version < "3.15"
+regex==2025.11.3 ; python_version >= "3.12" and python_version < "3.15"
+requests==2.32.5 ; python_version >= "3.12" and python_version < "3.15"
+ruff==0.12.12 ; python_version >= "3.12" and python_version < "3.15"
+safetensors==0.7.0 ; python_version >= "3.12" and python_version < "3.15"
+scipy==1.16.3 ; python_version >= "3.12" and python_version < "3.15"
+setuptools==80.9.0 ; python_version >= "3.12" and python_version < "3.15"
+shapely==2.1.2 ; python_version >= "3.12" and python_version < "3.15"
+shellingham==1.5.4 ; python_version >= "3.12" and python_version < "3.15"
+shiboken6==6.11.0 ; python_version >= "3.12" and python_version < "3.15"
+six==1.17.0 ; python_version >= "3.12" and python_version < "3.15"
+sniffio==1.3.1 ; python_version >= "3.12" and python_version < "3.15"
+sympy==1.14.0 ; python_version >= "3.12" and python_version < "3.15"
+tabulate==0.9.0 ; python_version >= "3.12" and python_version < "3.15"
+termcolor==3.2.0 ; python_version >= "3.12" and python_version < "3.15"
+timm==1.0.22 ; python_version >= "3.12" and python_version < "3.15"
+torch==2.4.1 ; python_version >= "3.12" and python_version < "3.15"
+torchvision==0.19.1 ; python_version >= "3.12" and python_version < "3.15"
+tqdm==4.67.1 ; python_version >= "3.12" and python_version < "3.15"
+triton==3.0.0 ; python_version == "3.12" and platform_system == "Linux" and platform_machine == "x86_64"
+typer-slim==0.20.0 ; python_version >= "3.12" and python_version < "3.15"
+types-requests==2.32.4.20250913 ; python_version >= "3.12" and python_version < "3.15"
+typing-extensions==4.15.0 ; python_version >= "3.12" and python_version < "3.15"
+tzdata==2025.2 ; python_version >= "3.12" and python_version < "3.15"
+urllib3==2.5.0 ; python_version >= "3.12" and python_version < "3.15"
+virtualenv==20.35.4 ; python_version >= "3.12" and python_version < "3.15"
+watchdog==6.0.0 ; python_version >= "3.12" and python_version < "3.15"
+wcwidth==0.2.14 ; python_version >= "3.12" and python_version < "3.15"
+yaspin==3.3.0 ; python_version >= "3.12" and python_version < "3.15"
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..75722c7
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,85 @@
+anyio==4.11.0 ; python_version >= "3.12" and python_version < "3.15"
+attrs==25.4.0 ; python_version >= "3.12" and python_version < "3.15"
+certifi==2025.11.12 ; python_version >= "3.12" and python_version < "3.15"
+charset-normalizer==3.4.4 ; python_version >= "3.12" and python_version < "3.15"
+click-plugins==1.1.1.2 ; python_version >= "3.12" and python_version < "3.15"
+click==8.3.1 ; python_version >= "3.12" and python_version < "3.15"
+cligj==0.7.2 ; python_version >= "3.12" and python_version < "3.15"
+clip @ git+https://github.com/openai/CLIP.git@dcba3cb2e2827b402d2701e7e1c7d9fed8a20ef1 ; python_version >= "3.12" and python_version < "3.15"
+colorama==0.4.6 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Windows"
+contourpy==1.3.3 ; python_version >= "3.12" and python_version < "3.15"
+cycler==0.12.1 ; python_version >= "3.12" and python_version < "3.15"
+filelock==3.20.0 ; python_version >= "3.12" and python_version < "3.15"
+fiona==1.10.1 ; python_version >= "3.12" and python_version < "3.15"
+fonttools==4.60.1 ; python_version >= "3.12" and python_version < "3.15"
+fsspec==2025.10.0 ; python_version >= "3.12" and python_version < "3.15"
+ftfy==6.3.1 ; python_version >= "3.12" and python_version < "3.15"
+geopandas==1.1.1 ; python_version >= "3.12" and python_version < "3.15"
+gpxpy==1.6.2 ; python_version >= "3.12" and python_version < "3.15"
+h11==0.16.0 ; python_version >= "3.12" and python_version < "3.15"
+hf-xet==1.2.0 ; python_version >= "3.12" and python_version < "3.15" and (platform_machine == "x86_64" or platform_machine == "amd64" or platform_machine == "AMD64" or platform_machine == "arm64" or platform_machine == "aarch64")
+httpcore==1.0.9 ; python_version >= "3.12" and python_version < "3.15"
+httpx==0.28.1 ; python_version >= "3.12" and python_version < "3.15"
+huggingface-hub==1.1.5 ; python_version >= "3.12" and python_version < "3.15"
+idna==3.11 ; python_version >= "3.12" and python_version < "3.15"
+jinja2==3.1.6 ; python_version >= "3.12" and python_version < "3.15"
+joblib==1.5.2 ; python_version >= "3.12" and python_version < "3.15"
+kiwisolver==1.4.9 ; python_version >= "3.12" and python_version < "3.15"
+markupsafe==3.0.3 ; python_version >= "3.12" and python_version < "3.15"
+matplotlib==3.10.7 ; python_version >= "3.12" and python_version < "3.15"
+mpmath==1.3.0 ; python_version >= "3.12" and python_version < "3.15"
+networkx==3.5 ; python_version >= "3.12" and python_version < "3.15"
+numpy==1.26.4 ; python_version >= "3.12" and python_version < "3.15"
+nvidia-cublas-cu12==12.1.3.1 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cuda-cupti-cu12==12.1.105 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cuda-nvrtc-cu12==12.1.105 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cuda-runtime-cu12==12.1.105 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cudnn-cu12==9.1.0.70 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cufft-cu12==11.0.2.54 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-curand-cu12==10.3.2.106 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cusolver-cu12==11.4.5.107 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-cusparse-cu12==12.1.0.106 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-nccl-cu12==2.20.5 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-nvjitlink-cu12==12.8.93 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+nvidia-nvtx-cu12==12.1.105 ; python_version >= "3.12" and python_version < "3.15" and platform_system == "Linux" and platform_machine == "x86_64"
+opencv-python-headless==4.11.0.86 ; python_version >= "3.12" and python_version < "3.15"
+osmnx==1.9.3 ; python_version >= "3.12" and python_version < "3.15"
+packaging==25.0 ; python_version >= "3.12" and python_version < "3.15"
+pandas==2.3.3 ; python_version >= "3.12" and python_version < "3.15"
+piexif==1.1.3 ; python_version >= "3.12" and python_version < "3.15"
+pillow==10.4.0 ; python_version >= "3.12" and python_version < "3.15"
+py360convert==0.1.0 ; python_version >= "3.12" and python_version < "3.15"
+pydeck==0.9.1 ; python_version >= "3.12" and python_version < "3.15"
+pyogrio==0.9.0 ; python_version >= "3.12" and python_version < "3.15"
+pyparsing==3.2.5 ; python_version >= "3.12" and python_version < "3.15"
+pyproj==3.7.2 ; python_version >= "3.12" and python_version < "3.15"
+pyside6-addons==6.11.0 ; python_version >= "3.12" and python_version < "3.15"
+pyside6-essentials==6.11.0 ; python_version >= "3.12" and python_version < "3.15"
+pyside6==6.11.0 ; python_version >= "3.12" and python_version < "3.15"
+python-dateutil==2.9.0.post0 ; python_version >= "3.12" and python_version < "3.15"
+pytz==2025.2 ; python_version >= "3.12" and python_version < "3.15"
+pyyaml==6.0.3 ; python_version >= "3.12" and python_version < "3.15"
+regex==2025.11.3 ; python_version >= "3.12" and python_version < "3.15"
+requests==2.32.5 ; python_version >= "3.12" and python_version < "3.15"
+safetensors==0.7.0 ; python_version >= "3.12" and python_version < "3.15"
+scipy==1.16.3 ; python_version >= "3.12" and python_version < "3.15"
+setuptools==80.9.0 ; python_version >= "3.12" and python_version < "3.15"
+shapely==2.1.2 ; python_version >= "3.12" and python_version < "3.15"
+shellingham==1.5.4 ; python_version >= "3.12" and python_version < "3.15"
+shiboken6==6.11.0 ; python_version >= "3.12" and python_version < "3.15"
+six==1.17.0 ; python_version >= "3.12" and python_version < "3.15"
+sniffio==1.3.1 ; python_version >= "3.12" and python_version < "3.15"
+sympy==1.14.0 ; python_version >= "3.12" and python_version < "3.15"
+tabulate==0.9.0 ; python_version >= "3.12" and python_version < "3.15"
+termcolor==3.2.0 ; python_version >= "3.12" and python_version < "3.15"
+timm==1.0.22 ; python_version >= "3.12" and python_version < "3.15"
+torch==2.4.1 ; python_version >= "3.12" and python_version < "3.15"
+torchvision==0.19.1 ; python_version >= "3.12" and python_version < "3.15"
+tqdm==4.67.1 ; python_version >= "3.12" and python_version < "3.15"
+triton==3.0.0 ; python_version == "3.12" and platform_system == "Linux" and platform_machine == "x86_64"
+typer-slim==0.20.0 ; python_version >= "3.12" and python_version < "3.15"
+typing-extensions==4.15.0 ; python_version >= "3.12" and python_version < "3.15"
+tzdata==2025.2 ; python_version >= "3.12" and python_version < "3.15"
+urllib3==2.5.0 ; python_version >= "3.12" and python_version < "3.15"
+wcwidth==0.2.14 ; python_version >= "3.12" and python_version < "3.15"
+yaspin==3.3.0 ; python_version >= "3.12" and python_version < "3.15"
diff --git a/src/uq_desktop_processor/__init__.py b/src/uq_desktop_processor/__init__.py
new file mode 100644
index 0000000..0d488c5
--- /dev/null
+++ b/src/uq_desktop_processor/__init__.py
@@ -0,0 +1,8 @@
+from importlib.metadata import PackageNotFoundError, version
+
+try:
+    __version__ = version("UrbanQuality-AI")
+except PackageNotFoundError:  # pragma: no cover
+    __version__ = "0.0.0"
+
+__all__ = ["__version__"]
diff --git a/src/uq_desktop_processor/__main__.py b/src/uq_desktop_processor/__main__.py
new file mode 100644
index 0000000..8508bff
--- /dev/null
+++ b/src/uq_desktop_processor/__main__.py
@@ -0,0 +1,47 @@
+"""
+Application entry point for `python -m uq_desktop_processor` (logging setup and GUI launch).
+"""
+
+import logging
+import sys
+
+from uq_desktop_processor.gui import main as start_gui
+from uq_desktop_processor.logging_config import configure_logging
+
+
+def main() -> int:
+    """
+    Main entry point for the City-Lens pipeline.
+
+    Configures logging, starts the application, and returns the exit code.
+    """
+    # 1. Configure logging system
+    configure_logging(level=logging.DEBUG)
+
+    # 2. Get the main logger
+    log = logging.getLogger(__name__)
+    log.debug("Logging configured.")
+
+    # 3. Log application launch
+    log.info("Launching UrbanQuality-AI application pipeline...")
+
+    # 4. Run the main pipeline function and get its exit code
+    try:
+        exit_code = start_gui()
+
+        if exit_code == 0:
+            log.info("Application pipeline finished successfully (Exit Code 0).")
+        else:
+            log.warning("Application pipeline finished with errors (Exit Code %d).", exit_code)
+
+        return exit_code
+
+    except Exception as e:
+        # Catch any critical, unhandled exceptions
+        log.critical("An unhandled exception occurred: %s", e, exc_info=True)
+        return 1
+
+
+if __name__ == "__main__":
+    # Call main() and exit with its proper return code
+    sys.exit(main())
diff --git a/src/uq_desktop_processor/assets/img/icon.ico b/src/uq_desktop_processor/assets/img/icon.ico
new file mode 100644
index 0000000..693aea5
Binary files /dev/null and b/src/uq_desktop_processor/assets/img/icon.ico differ
diff --git a/src/uq_desktop_processor/assets/img/icon.png b/src/uq_desktop_processor/assets/img/icon.png
new file mode 100644
index 0000000..610137d
Binary files /dev/null and b/src/uq_desktop_processor/assets/img/icon.png differ
diff --git a/src/uq_desktop_processor/evaluation/__init__.py b/src/uq_desktop_processor/evaluation/__init__.py
new file mode 100644
index 0000000..4ee0c1f
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/__init__.py
@@ -0,0 +1,15 @@
+"""
+Evaluation module:   init  .
+"""
+
+from .clip_common import print_results
+from .clip_evaluator import evaluate_images_with_clip
+from .clip_prefilter import prefilter_folder
+from .finetuned_evaluator import evaluate_images_with_finetuned
+
+__all__ = [
+    "evaluate_images_with_clip",
+    "evaluate_images_with_finetuned",
+    "prefilter_folder",
+    "print_results",
+]
diff --git a/src/uq_desktop_processor/evaluation/clip_common/__init__.py b/src/uq_desktop_processor/evaluation/clip_common/__init__.py
new file mode 100644
index 0000000..6320109
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_common/__init__.py
@@ -0,0 +1,50 @@
+"""
+Evaluation module:   init  .
+"""
+
+from .directions import encode_image, prepare_directions
+from .model import encode_texts, load_model, sigmoid_probability
+from .printer import print_results
+from .validate import (
+    # Classes and main functions
+    ValidationError,
+    all_nonempty_strings,
+    as_string_set,
+    check_beta_sigmoid,
+    check_device,
+    check_image_folder,
+    check_keyset_consistency,
+    check_model_names,
+    check_order,
+    check_prompts,
+    check_weights,
+    # Low-level validation functions (for flexibility)
+    is_nonempty_string,
+    is_percentage,
+    list_or_empty,
+    validate_config,
+)
+
+__all__ = [
+    "ValidationError",
+    "all_nonempty_strings",
+    "as_string_set",
+    "check_beta_sigmoid",
+    "check_device",
+    "check_image_folder",
+    "check_keyset_consistency",
+    "check_model_names",
+    "check_order",
+    "check_prompts",
+    "check_weights",
+    "encode_image",
+    "encode_texts",
+    "is_nonempty_string",
+    "is_percentage",
+    "list_or_empty",
+    "load_model",
+    "prepare_directions",
+    "print_results",
+    "sigmoid_probability",
+    "validate_config",
+]
diff --git a/src/uq_desktop_processor/evaluation/clip_common/directions.py b/src/uq_desktop_processor/evaluation/clip_common/directions.py
new file mode 100644
index 0000000..a3865ce
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_common/directions.py
@@ -0,0 +1,101 @@
+"""
+Builds CLIP embedding direction vectors from positive/negative prompt pairs per category.
+"""
+
+import logging
+from collections.abc import Callable, Iterable, Mapping
+from typing import Any, cast
+
+import torch
+from PIL import Image
+from torch import Tensor, nn
+
+from .model import encode_texts
+
+log = logging.getLogger(__name__)
+
+
+def _normalize(vector: Tensor) -> Tensor:
+    """
+    Normalize a vector to unit length (L2 norm).
+    Returns the original vector if its norm is zero.
+
+    Example::
+        In: _normalize(vector)
+        Out: function result returned for provided inputs
+    """
+    vector_norm = vector.norm(p=2)
+    return vector / vector_norm if vector_norm > 0 else vector
+
+
+def prepare_directions(
+    prompts: Mapping[str, Mapping[str, Iterable[str]]],
+    model: nn.Module,
+    device: torch.device | str,
+) -> dict[str, Tensor]:
+    """
+    Compute semantic direction vectors for each category based on
+    positive and negative prompt examples.
+
+    :param prompts: Dictionary containing categories with "pos" and "neg" prompt lists.
+    :param model: Text encoding model.
+    :param device: Torch device for computations.
+    :return: Dictionary mapping category names to normalized direction vectors.
+
+    Example::
+        In: prepare_directions(prompts, model, device)
+        Out: function result returned for provided inputs
+    """
+    directions: dict[str, Tensor] = {}
+
+    for category, prompt_sides in prompts.items():
+        log.debug("Encoding prompts for category: '%s'", category)
+
+        try:
+            # Encode positive prompts and compute their average embedding
+            positive_prompt_embedding = encode_texts(prompt_sides["pos"], model, device).mean(dim=0)
+            # Encode negative prompts and compute their average embedding
+            negative_prompt_embedding = encode_texts(prompt_sides["neg"], model, device).mean(dim=0)
+
+            # Compute difference and normalize to get a direction vector
+            direction = _normalize(positive_prompt_embedding - negative_prompt_embedding)
+            directions[category] = direction
+        except Exception as error:
+            log.error("Failed to compute direction for category '%s': %s", category, error)
+            raise
+
+    log.debug("All direction vectors computed successfully.")
+
+    return directions
+
+
+@torch.no_grad()
+def encode_image(
+    img: Image.Image,
+    preprocess: Callable[[Image.Image], Tensor],
+    model: nn.Module,
+    device: torch.device | str,
+) -> Tensor:
+    """
+    Encode an image into a normalized feature vector using the model.
+
+    :param img: Input PIL image.
+    :param preprocess: Preprocessing function for the model.
+    :param model: Vision encoder model.
+    :param device: Torch device for computations.
+    :return: Normalized image embedding tensor.
+
+    Example::
+        In: encode_image(img, preprocess, model, device)
+        Out: function result returned for provided inputs
+    """
+    if log.isEnabledFor(logging.DEBUG):
+        log.debug("Encoding image tensor (size: %s)...", img.size)
+
+    # Convert image to RGB, preprocess, and move to device
+    tensor = preprocess(img.convert("RGB")).unsqueeze(0).to(device)
+    # Extract image features
+    model_any = cast(Any, model)
+    features = model_any.encode_image(tensor)
+    # Normalize the feature vector
+    return (features / features.norm(dim=-1, keepdim=True)).squeeze()
diff --git a/src/uq_desktop_processor/evaluation/clip_common/model.py b/src/uq_desktop_processor/evaluation/clip_common/model.py
new file mode 100644
index 0000000..b21a80d
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_common/model.py
@@ -0,0 +1,108 @@
+"""
+Loads OpenAI CLIP models and provides text/image encoding for evaluation pipelines.
+"""
+
+import logging
+import math
+from collections.abc import Callable, Iterable
+from typing import Any, cast
+
+import clip
+import torch
+from PIL import Image
+
+log = logging.getLogger(__name__)
+
+
+def load_model(
+    model_names: Iterable[str],
+    device: str | torch.device = "cpu",
+) -> tuple[torch.nn.Module, Callable[[Image.Image], torch.Tensor], str]:
+    """
+    Try loading a CLIP model from a list of model names.
+    Returns the first successfully loaded model along with its preprocess function
+    and the model name that was used.
+
+    :param model_names: Iterable of CLIP model names to try loading.
+    :param device: Device to load the model onto.
+    :return: (model, preprocess_function, loaded_model_name)
+
+    Example::
+        In: load_model(model_names, device)
+        Out: function result returned for provided inputs
+    """
+    log.info("Attempting to load CLIP model on device: %s", device)
+
+    last_error = None
+    for name in model_names:
+        try:
+            # Attempt to load a model using the CLIP API
+            model, preprocess = clip.load(name, device=device, jit=False)
+            return model.eval(), preprocess, name
+        except RuntimeError as runtime_error:
+            # Store the last error in case all models fail
+            last_error = runtime_error
+    # Raise an error if none of the models could be loaded
+    raise RuntimeError("No model could be loaded into memory.") from last_error
+
+
+@torch.no_grad()
+def encode_texts(
+    texts: str | Iterable[str],
+    model: torch.nn.Module,
+    device: str | torch.device,
+) -> torch.Tensor:
+    """
+    Tokenize and encode one or multiple text inputs using a CLIP model.
+    Returns L2-normalized text embeddings.
+
+    :param texts: A single string or a sequence of text strings.
+    :param model: The CLIP model used for encoding.
+    :param device: Device to run the encoding on.
+    :return: Normalized text embedding tensor of shape (N, D).
+
+    Example::
+        In: encode_texts(texts, model, device)
+        Out: function result returned for provided inputs
+    """
+    # Ensure texts is a materialized sequence.
+    text_list = [texts] if isinstance(texts, str) else list(texts)
+
+    if log.isEnabledFor(logging.DEBUG):
+        log.debug("Encoding %s text prompt(s)...", len(text_list))
+
+    # Tokenize text and move to device
+    tokens = clip.tokenize(text_list, truncate=True).to(device)
+
+    # Encode text using CLIP
+    model_any = cast(Any, model)
+    features = model_any.encode_text(tokens)
+
+    # Return normalized embeddings
+    return features / features.norm(dim=-1, keepdim=True)
+
+
+def sigmoid_probability(
+    delta: float | torch.Tensor,
+    beta: float | torch.Tensor,
+) -> float | torch.Tensor:
+    """
+    Compute a sigmoid-based probability scaled to 0–100 range.
+    Accepts both scalars and torch tensors.
+
+    :param delta: Input value (difference or score).
+    :param beta: Scaling factor controlling steepness.
+    :return: Probability between 0 and 100.
+
+    Example::
+        In: sigmoid_probability(delta, beta)
+        Out: function result returned for provided inputs
+    """
+    # Tensor-based implementation if either input is a tensor
+    if isinstance(delta, torch.Tensor) or isinstance(beta, torch.Tensor):
+        delta_t = delta if isinstance(delta, torch.Tensor) else torch.tensor(delta)
+        beta_t = beta if isinstance(beta, torch.Tensor) else torch.tensor(beta)
+        return 100.0 / (1.0 + torch.exp(-beta_t * delta_t))
+
+    # Fallback to pure Python math for scalar values
+    return 100.0 / (1.0 + math.exp(-beta * delta))
diff --git a/src/uq_desktop_processor/evaluation/clip_common/printer.py b/src/uq_desktop_processor/evaluation/clip_common/printer.py
new file mode 100644
index 0000000..0c1029e
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_common/printer.py
@@ -0,0 +1,157 @@
+"""
+Prints CLIP evaluation summaries and validation output to the console (e.g. tabulated).
+"""
+
+import logging
+
+from tabulate import tabulate  # type: ignore[import-untyped]
+
+log = logging.getLogger(__name__)
+
+
+def _handle_errors(result: dict) -> bool:
+    """
+    Check whether the result dictionary contains validation errors.
+    If errors exist, print them along with any warnings.
+
+    :param result: Result dictionary potentially containing "errors" and "warnings".
+    :return: True if errors were found (and processing should stop), otherwise False.
+
+    Example::
+        In: _handle_errors(result)
+        Out: function result returned for provided inputs
+    """
+    errors = result.get("errors")
+    if not errors:
+        return False
+
+    # Log validation errors
+    log.error("Configuration validation failed:")
+    for error_message in errors:
+        log.error(" - %s", error_message)
+
+    # Log warnings if present
+    warnings = result.get("warnings") or []
+    if warnings:
+        log.warning("Warnings:")
+        for warning_message in warnings:
+            log.warning(" - %s", warning_message)
+
+    return True
+
+
+def _build_rows(images: list, order: list[str]) -> list[list[str]]:
+    """
+    Build table rows for output based on image results and category order.
+
+    :param images: List of image result dictionaries.
+    :param order: List of category names in display order.
+    :return: List of formatted table rows.
+
+    Example::
+        In: _build_rows(images, order)
+        Out: function result returned for provided inputs
+    """
+    if log.isEnabledFor(logging.DEBUG):
+        log.debug("Formatting results table for %s images...", len(images))
+
+    rows = []
+    for image_result in images:
+        # Start each row with the filename
+        row = [image_result["filename"]]
+
+        # Add delta and probability for each category
+        for category_name in order:
+            category_data = image_result["categories"][category_name]
+            delta = category_data.get("delta")
+            delta_cell = f"{delta:+.3f}" if isinstance(delta, int | float) else "   n/a"
+            row += [
+                delta_cell,  # Signed delta value (or n/a for non-CLIP pipelines)
+                f"{category_data['probability_pct']:6.1f}%",  # Probability percentage
+            ]
+
+        # Add overall score
+        row.append(f"{image_result['overall_pct']:6.1f}%")
+        rows.append(row)
+
+    # Sort rows by overall score in descending order
+    rows.sort(key=lambda row_values: float(row_values[-1].rstrip("%")), reverse=True)
+    return rows
+
+
+def _build_headers(order: list[str]) -> list[str]:
+    """
+    Build column headers for the results table based on category order.
+
+    :param order: List of category names.
+    :return: List of formatted column headers.
+
+    Example::
+        In: _build_headers(order)
+        Out: function result returned for provided inputs
+    """
+    return (
+        ["filename"]
+        + [
+            # Even index > value column, odd index > percentage column
+            f"{category_name} value" if index % 2 == 0 else f"{category_name} %"
+            for index, category_name in enumerate(order * 2)
+        ]
+        + ["overall %"]
+    )
+
+
+def _log_warnings(warnings: list[str] | None) -> None:
+    """
+    Log warnings if any exist.
+
+    :param warnings: List of warning messages or None.
+
+    Example::
+        In: _log_warnings(warnings)
+        Out: function result returned for provided inputs
+    """
+    if not warnings:
+        return
+
+    log.warning("[WARNINGS]")
+    for warning_message in warnings:
+        log.warning(" - %s", warning_message)
+
+
+def print_results(result: dict) -> None:
+    """
+    Print formatted results using 'tabulate', including scores per image,
+    model name, overall average, and warnings.
+
+    :param result: Dictionary containing processed evaluation results.
+
+    Example::
+        In: print_results(result)
+        Out: function result returned for provided inputs
+    """
+    # Stop if validation errors were detected
+    if _handle_errors(result):
+        return
+
+    images = result.get("images", [])
+    order = result.get("order", [])
+    model_name = result.get("model_name", "unknown")
+
+    if not images:
+        print("No results to display.")
+        return
+
+    rows = _build_rows(images, order)
+    headers = _build_headers(order)
+
+    print(f"\nResults using model: {model_name}")
+    print(tabulate(rows, headers=headers, tablefmt="github"))
+
+    # Print average overall score if available
+    average_overall_pct = result.get("average_overall_pct")
+    if average_overall_pct is not None:
+        print(f"\nAverage overall score: {average_overall_pct:.1f}%")
+
+    # Print any warnings
+    _log_warnings(result.get("warnings"))
diff --git a/src/uq_desktop_processor/evaluation/clip_common/validate.py b/src/uq_desktop_processor/evaluation/clip_common/validate.py
new file mode 100644
index 0000000..eca7377
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_common/validate.py
@@ -0,0 +1,526 @@
+"""
+Validates CLIP evaluation configuration and prepares per-category direction tensors.
+"""
+
+import logging
+import os
+from collections.abc import Iterable, Mapping
+from typing import Any
+
+import torch
+
+try:
+    import clip
+except ImportError:
+    clip = None
+    _HAS_CLIP = False
+else:
+    _HAS_CLIP = True
+
+log = logging.getLogger(__name__)
+
+
+class ValidationError(Exception):
+    """Custom exception storing validation errors and warnings.
+
+    Example::
+        In: raise ValidationError(["missing token"], ["beta is high"])
+        Out: exception with .errors and .warnings attributes populated
+    """
+
+    def __init__(self, errors: list[str], warnings: list[str] | None = None):
+        """
+        Initialize validation error with collected errors and optional warnings.
+
+        :param errors: Validation error messages.
+        :param warnings: Validation warnings gathered during checks.
+
+        Example::
+            In: ValidationError(["missing token"], ["beta is high"])
+            Out: exception with .errors and .warnings attributes populated
+        """
+        super().__init__("\n".join(errors))
+        self.errors = errors
+        self.warnings = warnings or []
+
+
+# Expected keys for prompt categories
+SIDES: tuple[str, str] = ("pos", "neg")
+
+
+def is_nonempty_string(value: Any) -> bool:
+    """
+    Check whether a value is a non-empty string.
+
+    :param value: Any value to test.
+    :return: True if value is a non-empty string, else False.
+
+    Example::
+        In: is_nonempty_string(value)
+        Out: function result returned for provided inputs
+    """
+    return isinstance(value, str) and value.strip() != ""
+
+
+def all_nonempty_strings(values: Iterable[Any]) -> bool:
+    """
+    Check whether all values in an iterable are non-empty strings.
+
+    :param values: Iterable of values.
+    :return: True if all are non-empty strings.
+
+    Example::
+        In: all_nonempty_strings(values)
+        Out: function result returned for provided inputs
+    """
+    return all(is_nonempty_string(value) for value in values)
+
+
+def as_string_set(values: Iterable[str]) -> set[str]:
+    """
+    Convert an iterable of strings into a cleaned set (trimmed, non-empty).
+
+    :param values: Iterable of strings.
+    :return: A set of stripped, valid strings.
+
+    Example::
+        In: as_string_set(values)
+        Out: function result returned for provided inputs
+    """
+    return {value.strip() for value in values if is_nonempty_string(value)}
+
+
+def list_or_empty(values: Iterable[Any] | None) -> list[Any]:
+    """
+    Convert an iterable to a list, or return an empty list if None.
+
+    :param values: Iterable or None.
+    :return: List of items or empty list.
+
+    Example::
+        In: list_or_empty(values)
+        Out: function result returned for provided inputs
+    """
+    return list(values) if values is not None else []
+
+
+def is_percentage(value: Any) -> bool:
+    """
+    Check whether a value is a numeric percentage between 0 and 100.
+
+    :param value: Any value.
+    :return: True if within a valid percentage range.
+
+    Example::
+        In: is_percentage(value)
+        Out: function result returned for provided inputs
+    """
+    return isinstance(value, int | float) and 0.0 <= float(value) <= 100.0
+
+
+def check_image_folder(image_folder_path: str) -> tuple[list[str], list[str]]:
+    """
+    Validate a folder containing images.
+
+    :param image_folder_path: Path to folder.
+    :return: (errors, warnings)
+
+    Example::
+        In: check_image_folder(image_folder_path)
+        Out: function result returned for provided inputs
+    """
+    errors_list: list[str] = []
+    warnings_list: list[str] = []
+
+    log.debug("Validating image folder path: %s", image_folder_path)
+
+    # Validate path input
+    if not is_nonempty_string(image_folder_path):
+        error_message = "image_folder: empty path."
+        log.error(error_message)
+        errors_list.append(error_message)
+        return errors_list, warnings_list
+
+    # Check folder existence
+    if not os.path.isdir(image_folder_path):
+        error_message = f"image_folder: folder does not exist: {image_folder_path!r}."
+        log.error(error_message)
+        errors_list.append(error_message)
+        return errors_list, warnings_list
+
+    # Check folder readability and image files
+    try:
+        file_names = [
+            file_name
+            for file_name in os.listdir(image_folder_path)
+            if file_name.lower().endswith((".png", ".jpg", ".jpeg"))
+        ]
+        log.debug("Found %s valid image files in folder.", len(file_names))
+    except PermissionError:
+        error_message = f"image_folder: no read permission: {image_folder_path!r}."
+        log.error(error_message)
+        errors_list.append(error_message)
+        return errors_list, warnings_list
+
+    if not file_names:
+        error_message = f"image_folder: no .png/.jpg/.jpeg files found in {image_folder_path!r}."
+        log.error(error_message)
+        errors_list.append(error_message)
+
+    return errors_list, warnings_list
+
+
+def check_device(device_name: str) -> tuple[list[str], list[str]]:
+    """
+    Validate a PyTorch device string (CPU or CUDA).
+
+    :param device_name: Device identifier string.
+    :return: (errors, warnings)
+
+    Example::
+        In: check_device(device_name)
+        Out: function result returned for provided inputs
+    """
+    errors_list: list[str] = []
+    warnings_list: list[str] = []
+    log.debug("Validating device configuration: %s", device_name)
+
+    if not is_nonempty_string(device_name):
+        errors_list.append("device: empty string.")
+        return errors_list, warnings_list
+
+    # CPU always valid
+    if device_name == "cpu":
+        return errors_list, warnings_list
+
+    # CUDA validation
+    if device_name.startswith("cuda"):
+        if not torch.cuda.is_available():
+            error_message = "device: 'cuda' specified but CUDA is not available."
+            log.error(error_message)
+            errors_list.append(error_message)
+            return errors_list, warnings_list
+
+        # Check GPU index if provided (e.g., 'cuda:1')
+        if ":" in device_name:
+            _, _, index_str = device_name.partition(":")
+            try:
+                index_int = int(index_str)
+                gpu_count = torch.cuda.device_count()
+                if not (0 <= index_int < gpu_count):
+                    error_message = f"device: GPU index out of range (0..{gpu_count - 1})."
+                    log.error(error_message)
+                    errors_list.append(error_message)
+            except ValueError:
+                errors_list.append("device: invalid format after 'cuda:'.")
+        return errors_list, warnings_list
+
+    # Unknown device > warning only
+    warning_message = f"device: unknown identifier '{device_name}', PyTorch will attempt to use it automatically."
+    log.warning(warning_message)
+    warnings_list.append(warning_message)
+    return errors_list, warnings_list
+
+
+def check_model_names(model_name_iterable: Iterable[str]) -> tuple[list[str], list[str]]:
+    """
+    Validate model name list for CLIP models.
+
+    :param model_name_iterable: Iterable of model names.
+    :return: (errors, warnings)
+
+    Example::
+        In: check_model_names(model_name_iterable)
+        Out: function result returned for provided inputs
+    """
+    errors_list: list[str] = []
+    warnings_list: list[str] = []
+
+    names_list = list(model_name_iterable) if model_name_iterable is not None else []
+    log.debug("Validating model names: %s", names_list)
+
+    if not names_list:
+        errors_list.append("model_names: empty list or tuple.")
+        return errors_list, warnings_list
+
+    if not all_nonempty_strings(names_list):
+        errors_list.append("model_names: all elements must be non-empty strings.")
+
+    # Check availability if CLIP is installed
+    if _HAS_CLIP:
+        try:
+            available_models_set = set(clip.available_models())
+            unknown_names = [name for name in names_list if name not in available_models_set]
+            if unknown_names:
+                warning_message = f"model_names: unsupported by clip: {', '.join(unknown_names)}."
+                log.warning(warning_message)
+                warnings_list.append(warning_message)
+        except (OSError, RuntimeError, AttributeError):
+            log.warning("Failed to retrieve available CLIP models list.")
+            warnings_list.append("model_names: failed to read clip.available_models().")
+    else:
+        log.debug("CLIP module not loaded, skipping model name availability check.")
+        warnings_list.append("model_names: 'clip' module not loaded — skipping availability check.")
+
+    return errors_list, warnings_list
+
+
+def check_beta_sigmoid(beta_value: float) -> tuple[list[str], list[str]]:
+    """
+    Validate the beta parameter used in the sigmoid probability function.
+
+    :param beta_value: Numeric beta parameter.
+    :return: (errors, warnings)
+
+    Example::
+        In: check_beta_sigmoid(beta_value)
+        Out: function result returned for provided inputs
+    """
+    errors_list: list[str] = []
+    warnings_list: list[str] = []
+
+    if not isinstance(beta_value, int | float):
+        errors_list.append("beta_sigmoid: must be a number.")
+        return errors_list, warnings_list
+
+    if beta_value <= 0:
+        errors_list.append("beta_sigmoid: must be > 0.")
+    elif beta_value > 100:
+        warning_message = f"beta_sigmoid: {beta_value} > 100 — the curve will be extremely steep."
+        log.warning(warning_message)
+        warnings_list.append(warning_message)
+
+    return errors_list, warnings_list
+
+
+def check_order(category_order: Iterable[str]) -> tuple[list[str], list[str]]:
+    """
+    Validate the order of categories used in scoring.
+
+    :param category_order: Iterable of category names.
+    :return: (errors, warnings)
+
+    Example::
+        In: check_order(category_order)
+        Out: function result returned for provided inputs
+    """
+    errors_list: list[str] = []
+    warnings_list: list[str] = []
+    order_list = list_or_empty(category_order)
+
+    if not order_list:
+        errors_list.append("order: cannot be empty.")
+        return errors_list, warnings_list
+
+    if not all_nonempty_strings(order_list):
+        errors_list.append("order: all category names must be non-empty strings.")
+
+    if len(set(order_list)) != len(order_list):
+        errors_list.append("order: duplicate categories are not allowed.")
+
+    return errors_list, warnings_list
+
+
+def check_weights(weight_mapping: Mapping[str, float]) -> tuple[list[str], list[str]]:
+    """
+    Validate category weight configuration.
+
+    :param weight_mapping: Mapping category → weight value.
+    :return: (errors, warnings)
+
+    Example::
+        In: check_weights(weight_mapping)
+        Out: function result returned for provided inputs
+    """
+    errors_list: list[str] = []
+    warnings_list: list[str] = []
+
+    if not isinstance(weight_mapping, Mapping):
+        errors_list.append("weights: must be Mapping[str, float].")
+        return errors_list, warnings_list
+
+    if not weight_mapping:
+        errors_list.append("weights: cannot be empty.")
+        return errors_list, warnings_list
+
+    # Validate each weight
+    for category_key, weight_value in weight_mapping.items():
+        if not is_nonempty_string(category_key):
+            errors_list.append("weights: category key cannot be empty.")
+        if not isinstance(weight_value, int | float):
+            errors_list.append(f"weights[{category_key!r}]: must be a number.")
+        elif weight_value <= 0:
+            errors_list.append(f"weights[{category_key!r}]: must be > 0 (geometric mean).")
+        elif not (float(weight_value) < float("inf")):
+            errors_list.append(f"weights[{category_key!r}]: Inf/NaN values are not allowed.")
+
+    # Aggregate checks
+    try:
+        total_weight = sum(float(value) for value in weight_mapping.values())
+        if total_weight <= 0:
+            errors_list.append("weights: the sum of weights must be > 0.")
+
+        # Warn if one weight dominates the rest
+        if weight_mapping and max(weight_mapping.values()) >= 10 * (total_weight / len(weight_mapping)):
+            warning_message = "weights: one weight dominates (>= 10× the average)."
+            log.warning(warning_message)
+            warnings_list.append(warning_message)
+    except (ValueError, TypeError):
+        pass
+
+    return errors_list, warnings_list
+
+
+def check_prompts(prompt_mapping: Mapping[str, dict[str, Iterable[str]]]) -> tuple[list[str], list[str]]:
+    """
+    Validate the prompt structure (categories with 'pos'/'neg' lists).
+
+    :param prompt_mapping: Mapping category → {'pos': [...], 'neg': [...]}
+    :return: (errors, warnings)
+
+    Example::
+        In: check_prompts(prompt_mapping)
+        Out: function result returned for provided inputs
+    """
+    errors_list: list[str] = []
+    warnings_list: list[str] = []
+
+    if not isinstance(prompt_mapping, Mapping) or not prompt_mapping:
+        errors_list.append("prompts: must be a non-empty Mapping.")
+        return errors_list, warnings_list
+
+    for category_name, side_mapping in prompt_mapping.items():
+        if not isinstance(side_mapping, Mapping):
+            errors_list.append(f"prompts[{category_name!r}]: value must be a dict.")
+            continue
+
+        # Validate 'pos' and 'neg'
+        for side_name in SIDES:
+            if side_name not in side_mapping:
+                errors_list.append(f"prompts[{category_name!r}]: missing key '{side_name}'.")
+                continue
+
+            values_list = list_or_empty(side_mapping[side_name])
+
+            if len(values_list) == 0:
+                errors_list.append(f"prompts[{category_name!r}]['{side_name}']: list cannot be empty.")
+            elif not all_nonempty_strings(values_list):
+                errors_list.append(
+                    f"prompts[{category_name!r}]['{side_name}']: all elements must be non-empty strings."
+                )
+
+            # Warn about extremely long prompts (CLIP has token limits)
+            very_long_prompts = [prompt for prompt in values_list if isinstance(prompt, str) and len(prompt) > 512]
+            if very_long_prompts:
+                warning_message = f"prompts[{category_name!r}]['{side_name}']: {len(very_long_prompts)} very long prompts (>512 characters)."
+                log.warning(warning_message)
+                warnings_list.append(warning_message)
+
+    return errors_list, warnings_list
+
+
+def check_keyset_consistency(
+    category_order: Iterable[str],
+    weight_mapping: Mapping[str, float],
+    prompt_mapping: Mapping[str, dict[str, Iterable[str]]],
+) -> tuple[list[str], list[str]]:
+    """
+    Ensure that the category names across 'order', 'weights', and 'prompts' match.
+
+    :param category_order: Iterable of category names.
+    :param weight_mapping: Mapping category → weight.
+    :param prompt_mapping: Mapping category → prompt pairs.
+    :return: (errors, warnings)
+
+    Example::
+        In: check_keyset_consistency(category_order, weight_mapping, prompt_mapping)
+        Out: function result returned for provided inputs
+    """
+    errors_list: list[str] = []
+    warnings_list: list[str] = []
+
+    order_set = as_string_set(category_order)
+    weights_set = as_string_set(weight_mapping.keys())
+    prompts_set = as_string_set(prompt_mapping.keys())
+
+    # All three sets must match exactly
+    if not (order_set == weights_set == prompts_set):
+        error_message = f"inconsistent keys: order={sorted(order_set)}, weights={sorted(weights_set)}, prompts={sorted(prompts_set)} — sets should match."
+        log.error(error_message)
+        errors_list.append(error_message)
+
+    return errors_list, warnings_list
+
+
+def validate_config(
+    *,
+    image_folder: str,
+    device: str,
+    model_names: Iterable[str],
+    beta_sigmoid: float,
+    order: Iterable[str],
+    weights: Mapping[str, float],
+    prompts: Mapping[str, dict[str, Iterable[str]]],
+    raise_on_error: bool = True,
+) -> tuple[list[str], list[str]]:
+    """
+    Validate all configuration components and optionally raise an error.
+
+    :param image_folder: Path to folder with images.
+    :param device: PyTorch device string.
+    :param model_names: List of CLIP model names.
+    :param beta_sigmoid: Sigmoid scaling factor.
+    :param order: Category order.
+    :param weights: Category weights.
+    :param prompts: Category → prompt structure.
+    :param raise_on_error: Raise exception if errors found.
+    :return: (errors, warnings)
+
+    Example::
+        In: validate_config()
+        Out: function result returned for provided inputs
+    """
+    log.info("Starting configuration validation...")
+    errors_accumulated: list[str] = []
+    warnings_accumulated: list[str] = []
+
+    # List of validator functions to run
+    check_functions = [
+        lambda: check_image_folder(image_folder),
+        lambda: check_device(device),
+        lambda: check_model_names(model_names),
+        lambda: check_beta_sigmoid(beta_sigmoid),
+        lambda: check_order(order),
+        lambda: check_weights(weights),
+        lambda: check_prompts(prompts),
+        lambda: check_keyset_consistency(order, weights, prompts),
+    ]
+
+    # Aggregate errors and warnings from all checks
+    for check_function in check_functions:
+        check_errors, check_warnings = check_function()
+        errors_accumulated.extend(check_errors)
+        warnings_accumulated.extend(check_warnings)
+
+    # Remove duplicates while preserving order
+    errors_accumulated = list(dict.fromkeys(errors_accumulated))
+    warnings_accumulated = list(dict.fromkeys(warnings_accumulated))
+
+    if warnings_accumulated:
+        log.info(
+            "Configuration validation produced %s warning(s).",
+            len(warnings_accumulated),
+        )
+
+    # Raise exception if configured to do so
+    if errors_accumulated:
+        log.error(
+            "Configuration validation failed with %s error(s).",
+            len(errors_accumulated),
+        )
+        if raise_on_error:
+            raise ValidationError(errors_accumulated, warnings_accumulated)
+    else:
+        log.info("Configuration validation passed.")
+
+    return errors_accumulated, warnings_accumulated
diff --git a/src/uq_desktop_processor/evaluation/clip_evaluator/__init__.py b/src/uq_desktop_processor/evaluation/clip_evaluator/__init__.py
new file mode 100644
index 0000000..cea62ea
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_evaluator/__init__.py
@@ -0,0 +1,7 @@
+"""
+Evaluation module:   init  .
+"""
+
+from .run import evaluate_images_with_clip
+
+__all__ = ["evaluate_images_with_clip"]
diff --git a/src/uq_desktop_processor/evaluation/clip_evaluator/defaults.py b/src/uq_desktop_processor/evaluation/clip_evaluator/defaults.py
new file mode 100644
index 0000000..7f9d2d3
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_evaluator/defaults.py
@@ -0,0 +1,72 @@
+"""
+Default paths, model names, and hyperparameters for the CLIP image evaluator.
+"""
+
+from types import MappingProxyType
+
+DEFAULT_IMAGE_FOLDER = "images/to_evaluate"
+DEFAULT_DEVICE = "cuda"
+DEFAULT_MODEL_NAMES = ("ViT-L/14@336px",)
+DEFAULT_BETA_SIGMOID = 30.0
+
+DEFAULT_ORDER = ("wealth", "safety", "beauty")
+DEFAULT_WEIGHTS = MappingProxyType(
+    {
+        "wealth": 0.01,
+        "safety": 1.5,
+        "beauty": 0.01,
+    }
+)
+
+DEFAULT_PROMPTS = MappingProxyType(
+    {
+        "wealth": {
+            "pos": (
+                "modern upscale neighborhood with well-maintained houses and clean sidewalks",
+                "affluent residential street with manicured lawns and luxury cars parked neatly",
+                "elegant suburban area with detached villas and landscaped gardens",
+                "wealthy quiet street with new facades, large windows, and decorative lighting",
+                "high-income residential zone with stone fences and premium architecture",
+            ),
+            "neg": (
+                "run-down street with peeling paint and old damaged houses",
+                "poor urban area with graffiti and broken sidewalks",
+                "low-income neighborhood with abandoned or boarded-up buildings",
+                "crowded residential block with cluttered yards and visible decay",
+                "street showing signs of poverty, trash, and disrepair",
+            ),
+        },
+        "safety": {
+            "pos": (
+                "peaceful residential street with clear visibility and no signs of danger",
+                "calm, well-lit suburban neighborhood with families walking and children playing",
+                "clean area with maintained houses and no graffiti or broken glass",
+                "quiet street with orderly parked cars and good street lighting",
+                "safe environment with tidy gardens, fences, and visible community care",
+            ),
+            "neg": (
+                "dark alley with broken lights, graffiti, and litter on the ground",
+                "street showing vandalism, smashed windows, or police tape",
+                "abandoned neighborhood with derelict buildings and no people",
+                "unsafe area with heavy shadows and visible neglect",
+                "crime-ridden urban zone with damaged cars and boarded houses",
+            ),
+        },
+        "beauty": {
+            "pos": (
+                "beautiful tree-lined residential street under warm sunlight",
+                "charming neighborhood with colorful facades and blooming gardens",
+                "scenic avenue with tidy sidewalks, greenery, and balanced composition",
+                "aesthetically pleasing street with clean architecture and natural light",
+                "picturesque suburban scene with flowers, cafés, and cozy atmosphere",
+            ),
+            "neg": (
+                "dreary street under grey overcast sky with bare trees",
+                "dirty industrial-looking road with trash and potholes",
+                "unappealing neighborhood with dull colors and visual clutter",
+                "ugly or neglected street lacking greenery and harmony",
+                "bleak winter street with mud, slush, and poor lighting",
+            ),
+        },
+    }
+)
diff --git a/src/uq_desktop_processor/evaluation/clip_evaluator/run.py b/src/uq_desktop_processor/evaluation/clip_evaluator/run.py
new file mode 100644
index 0000000..bebbb77
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_evaluator/run.py
@@ -0,0 +1,216 @@
+"""
+Batch-scores images with CLIP against configured semantic directions and writes JSON results.
+"""
+
+import logging
+import os
+from collections.abc import Mapping
+from typing import Any
+
+from uq_desktop_processor.evaluation.clip_common import ValidationError, load_model, prepare_directions, validate_config
+from uq_desktop_processor.evaluation.evaluation_utils import make_evaluation_result
+
+from . import defaults
+from .scoring import score_image
+
+log = logging.getLogger(__name__)
+
+
+def _get_image_files(folder: str) -> list[str]:
+    """
+    Return a sorted list of image filenames in the specified folder.
+    Only .png, .jpg, and .jpeg extensions are included.
+
+    :param folder: Path to image folder.
+    :return: Sorted list of filenames.
+
+    Example::
+        In: _get_image_files(folder)
+        Out: function result returned for provided inputs
+    """
+    files = sorted(filename for filename in os.listdir(folder) if filename.lower().endswith((".png", ".jpg", ".jpeg")))
+    log.debug("Scanned folder '%s': found %s valid image files.", folder, len(files))
+    return files
+
+
+def _format_single_result(
+    filename: str, image_path: str, raw_result: dict[str, Any], order: tuple[str, ...]
+) -> dict[str, Any]:
+    """
+    Format raw scoring output for a single image into a clean result structure.
+
+    :param filename: Image filename.
+    :param raw_result: Raw scoring dictionary from score_image().
+    :param order: Category order tuple.
+    :return: Formatted result dictionary.
+
+    Example::
+        In: _format_single_result(filename, raw_result, order)
+        Out: function result returned for provided inputs
+    """
+    return {
+        "filename": filename,
+        "image_path": image_path,
+        "categories": {
+            category_name: {
+                "delta": float(f"{raw_result[category_name]['delta']:.6f}"),
+                "probability_pct": float(f"{raw_result[category_name]['probability']:.1f}"),
+            }
+            for category_name in order
+        },
+        "overall_pct": float(f"{raw_result['overall']:.1f}"),
+    }
+
+
+def _create_error_response(
+    validation_exception: ValidationError, order: tuple, weights: Mapping, beta_sigmoid_value: float
+) -> dict[str, Any]:
+    """
+    Build a consistent response dictionary when validation fails.
+
+    :param validation_exception: ValidationError instance.
+    :param order: Category order.
+    :param weights: Weight mapping.
+    :param beta_sigmoid_value: Sigmoid beta value.
+    :return: Error response structure.
+
+    Example::
+        In: _create_error_response(validation_exception, order, weights, beta_sigmoid_value)
+        Out: function result returned for provided inputs
+    """
+    return {
+        "model_name": None,
+        "order": order,
+        "weights": dict(weights),
+        "beta_sigmoid": beta_sigmoid_value,
+        "warnings": list(validation_exception.warnings),
+        "images": [],
+        "average_overall_pct": None,
+        "errors": list(validation_exception.errors),
+    }
+
+
+def evaluate_images_with_clip(
+    image_folder: str = defaults.DEFAULT_IMAGE_FOLDER,
+    device: str = defaults.DEFAULT_DEVICE,
+    model_names: tuple[str, ...] = defaults.DEFAULT_MODEL_NAMES,
+    beta_sigmoid: float = defaults.DEFAULT_BETA_SIGMOID,
+    order: tuple[str, ...] = defaults.DEFAULT_ORDER,
+    weights: Mapping[str, float] = defaults.DEFAULT_WEIGHTS,
+    prompts: Mapping[str, dict] = defaults.DEFAULT_PROMPTS,
+    *,
+    raise_on_validation_error: bool = True,
+) -> dict[str, Any]:
+    """
+    Evaluate all images in a folder using CLIP-based scoring.
+    Performs validation, loads the model, prepares direction vectors,
+    scores each image, and produces a final aggregated result.
+
+    :param image_folder: Folder containing image files.
+    :param device: PyTorch device string ("cpu" or "cuda").
+    :param model_names: Models to attempt loading.
+    :param beta_sigmoid: Sigmoid scaling factor.
+    :param order: Category order tuple.
+    :param weights: Weight mapping for categories.
+    :param prompts: Prompt mapping for positive/negative directions.
+    :param raise_on_validation_error: Whether to raise or return structured error output.
+    :return: Full evaluation result dictionary.
+
+    Example::
+        In: evaluate_images_with_clip(image_folder, device, model_names, beta_sigmoid, order, weights, prompts)
+        Out: function result returned for provided inputs
+    """
+    log.info("Starting CLIP evaluation pipeline.")
+
+    try:
+        # Validate configuration before processing
+        error_messages, warning_messages = validate_config(
+            image_folder=image_folder,
+            device=device,
+            model_names=model_names,
+            beta_sigmoid=beta_sigmoid,
+            order=order,
+            weights=weights,
+            prompts=prompts,
+            raise_on_error=raise_on_validation_error,
+        )
+    except ValidationError as validation_exception:
+        log.error("Validation failed with %s errors.", len(validation_exception.errors))
+        # Return structured error result instead of raising
+        if raise_on_validation_error:
+            raise
+        log.warning("Returning structured error response (raise_on_validation_error=False).")
+        return make_evaluation_result(
+            model_name=None,
+            order=order,
+            weights=dict(weights),
+            beta_sigmoid=beta_sigmoid,
+            images=[],
+            average_overall_pct=None,
+            warnings=list(validation_exception.warnings),
+            errors=list(validation_exception.errors),
+            skipped_images=[],
+        )
+
+    # Load input images
+    image_filenames = _get_image_files(image_folder)
+
+    if not image_filenames:
+        log.warning("No images found in '%s'. Aborting evaluation.", image_folder)
+    else:
+        log.info("Found %s images to evaluate in '%s'.", len(image_filenames), image_folder)
+
+    # Load CLIP model
+    model, preprocess, loaded_model_name = load_model(model_names, device)
+
+    # Compute semantic direction vectors for categories
+    direction_vectors = prepare_directions(prompts, model, device)
+
+    # Build shared configuration for scoring function
+    configuration_for_scoring = {
+        "device": device,
+        "beta_sigmoid": beta_sigmoid,
+        "order": order,
+        "weights": weights,
+    }
+
+    formatted_image_results = []
+    overall_scores = []
+
+    # Evaluate each image
+    for filename in image_filenames:
+        if log.isEnabledFor(logging.DEBUG):
+            log.debug("Scoring image: %s", filename)
+
+        image_path = os.path.join(image_folder, filename)
+
+        # Compute raw score
+        raw_score_result = score_image(image_path, model, preprocess, direction_vectors, configuration_for_scoring)
+
+        # Format final clean result for this image
+        formatted_result = _format_single_result(filename, image_path, raw_score_result, order)
+        formatted_image_results.append(formatted_result)
+
+        # Collect overall score for averaging
+        overall_scores.append(raw_score_result["overall"])
+
+    # Compute mean overall score
+    average_overall_score = sum(overall_scores) / len(overall_scores) if overall_scores else None
+
+    log.info(
+        "Evaluation finished. Average overall score: %s (for %s images).",
+        average_overall_score,
+        len(overall_scores),
+    )
+
+    return make_evaluation_result(
+        model_name=loaded_model_name,
+        order=order,
+        weights=dict(weights),
+        beta_sigmoid=beta_sigmoid,
+        images=formatted_image_results,
+        average_overall_pct=(round(average_overall_score, 1) if average_overall_score is not None else None),
+        warnings=warning_messages,
+        errors=None,
+        skipped_images=[],
+    )
diff --git a/src/uq_desktop_processor/evaluation/clip_evaluator/scoring.py b/src/uq_desktop_processor/evaluation/clip_evaluator/scoring.py
new file mode 100644
index 0000000..130e7d5
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_evaluator/scoring.py
@@ -0,0 +1,155 @@
+"""
+Per-image CLIP scoring: sigmoid probabilities, categories, and optional weighting.
+"""
+
+import logging
+import math
+from collections.abc import Callable
+from typing import Any, cast
+
+import torch
+from PIL import Image
+from torch import Tensor, nn
+
+from uq_desktop_processor.evaluation.clip_common.model import sigmoid_probability
+
+log = logging.getLogger(__name__)
+
+
+def _load_and_encode_image(
+    path: str, preprocess: Callable[[Image.Image], Tensor], model: nn.Module, device: torch.device
+) -> Tensor:
+    """
+    Load an image from disk, preprocess it, and return its normalized
+    CLIP feature embedding.
+
+    :param path: Path to the image file.
+    :param preprocess: Preprocessing function associated with the CLIP model.
+    :param model: CLIP model used for encoding images.
+    :param device: Torch device on which computation is performed.
+    :return: L2-normalized image embedding tensor (1D).
+
+    Example::
+        In: _load_and_encode_image(path, preprocess, model, device)
+        Out: function result returned for provided inputs
+    """
+    log.debug("Loading and encoding image from: %s", path)
+
+    try:
+        # Load the image and convert to RGB
+        image = Image.open(path).convert("RGB")
+
+        # Apply CLIP preprocessing and move to device
+        tensor = preprocess(image).unsqueeze(0).to(device)
+
+        # Extract feature embedding
+        model_any = cast(Any, model)
+        features = model_any.encode_image(tensor)
+
+        # Normalize the feature vector
+        features = features / features.norm(dim=-1, keepdim=True)
+
+        return features.squeeze()
+
+    except Exception as error:
+        log.error("Failed to process image '%s': %s", path, error)
+        raise
+
+
+def _compute_weighted_score(
+    results: dict[str, dict[str, float]], categories: list[str], weights: dict[str, float]
+) -> float:
+    """
+    Compute the overall score using a weighted geometric mean of probabilities.
+
+    :param results: Dict of per-category scores, each containing:
+                    { "delta": float, "probability": float }
+    :param categories: List of category names in scoring order.
+    :param weights: Mapping category → weight.
+    :return: Weighted overall score as a percentage.
+
+    Example::
+        In: _compute_weighted_score(results, categories, weights)
+        Out: function result returned for provided inputs
+    """
+    min_prob: float = 1e-6  # Avoid log(0) by clamping very small values
+    weighted_log_sum: float = 0.0
+    total_weight: float = 0.0
+
+    for category in categories:
+        # Probability is stored as percentage; convert to [0, 1] range
+        prob_percent: float = results[category]["probability"]
+        prob: float = max(prob_percent / 100.0, min_prob)
+
+        weight: float = weights[category]
+
+        # Use weighted geometric mean = exp(weighted average of log-probabilities)
+        weighted_log_sum += weight * math.log(prob)
+        total_weight += weight
+
+    # Convert weighted log-mean back to percentage probability space.
+    score: float = math.exp(weighted_log_sum / total_weight) * 100.0
+    return score
+
+
+@torch.no_grad()
+def score_image(
+    path: str,
+    model: nn.Module,
+    preprocess: Callable[[Image.Image], Tensor],
+    directions: dict[str, Tensor],
+    config: dict[str, Any],
+) -> dict[str, Any]:
+    """
+    Score a single image using CLIP by comparing it with category direction vectors.
+
+    :param path: Path to the image file.
+    :param model: CLIP model for encoding.
+    :param preprocess: CLIP-specific preprocessing function.
+    :param directions: Precomputed direction vectors per category.
+    :param config: Scoring configuration dictionary containing:
+                   - "device": torch.device
+                   - "beta_sigmoid": float
+                   - "order": list/tuple of categories
+                   - "weights": weight mapping
+    :return: Structured scoring result:
+             {
+                "category": { "delta": float, "probability": float },
+                ...
+                "overall": float
+             }
+
+    Example::
+        In: score_image(path, model, preprocess, directions, config)
+        Out: function result returned for provided inputs
+    """
+    device: torch.device = config["device"]
+    beta: float = config["beta_sigmoid"]
+
+    try:
+        # Load and encode the image into CLIP's embedding space
+        features: Tensor = _load_and_encode_image(path, preprocess, model, device)
+
+        results: dict[str, Any] = {}
+
+        # Compute per-category delta and probability
+        for category in config["order"]:
+            # Dot product measures similarity to direction vector
+            delta: float = torch.dot(features, directions[category]).item()
+            # Convert similarity into a probability using a sigmoid curve
+            probability: float = sigmoid_probability(delta, beta)
+            results[category] = {"delta": delta, "probability": probability}
+
+        # Compute final overall score via weighted geometric mean
+        overall: float = _compute_weighted_score(results, config["order"], config["weights"])
+
+        results["overall"] = overall
+
+        if log.isEnabledFor(logging.DEBUG):
+            log.debug("Scored '%s' -> Overall: %.2f", path, overall)
+
+        return results
+
+    except Exception as error:
+        log.error("Error while scoring image '%s': %s", path, error)
+        raise
diff --git a/src/uq_desktop_processor/evaluation/clip_evaluator/utils.py b/src/uq_desktop_processor/evaluation/clip_evaluator/utils.py
new file mode 100644
index 0000000..218c112
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_evaluator/utils.py
@@ -0,0 +1,25 @@
+"""
+Filesystem and formatting helpers used by the CLIP evaluator CLI run.
+"""
+
+from typing import Any
+
+from uq_desktop_processor.evaluation.clip_common import print_results as _print_common_results
+
+
+def print_results(result: dict[str, Any]) -> None:
+    """
+    Wrapper around the shared print_results function.
+
+    This exists to provide a local entry point for printing evaluation
+    results, while delegating the actual formatting and output logic
+    to the shared printer utility.
+
+    :param result: Result dictionary produced by the evaluation pipeline.
+    :return: Whatever the underlying printer function returns.
+
+    Example::
+        In: print_results(result)
+        Out: function result returned for provided inputs
+    """
+    return _print_common_results(result)
diff --git a/src/uq_desktop_processor/evaluation/clip_prefilter/__init__.py b/src/uq_desktop_processor/evaluation/clip_prefilter/__init__.py
new file mode 100644
index 0000000..4919cc6
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_prefilter/__init__.py
@@ -0,0 +1,7 @@
+"""
+Evaluation module:   init  .
+"""
+
+from .run import prefilter_folder
+
+__all__ = ["prefilter_folder"]
diff --git a/src/uq_desktop_processor/evaluation/clip_prefilter/defaults.py b/src/uq_desktop_processor/evaluation/clip_prefilter/defaults.py
new file mode 100644
index 0000000..b46d86e
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_prefilter/defaults.py
@@ -0,0 +1,41 @@
+"""
+Default prompts, thresholds, and folder names for CLIP-based image prefiltering.
+"""
+
+from types import MappingProxyType
+
+DEFAULT_IMAGE_FOLDER = "images/to_filter"
+DEFAULT_DEVICE = "cuda"
+DEFAULT_MODEL_NAMES = ("ViT-L/14@336px",)
+
+DEFAULT_BETA_SIGMOID = 30.0
+DEFAULT_FILTER_THRESHOLD = 40.0
+
+DEFAULT_REJECTED_FOLDER = "rejected"
+
+FILTER_PROMPTS = MappingProxyType(
+    {
+        "pos": (
+            "sunny day",
+            "clear sky",
+            "blue sky",
+            "bright daylight",
+            "good weather",
+            "sunlit street",
+            "dry road surface",
+            "high visibility",
+        ),
+        "neg": (
+            "rain",
+            "rainy weather",
+            "heavy rain",
+            "drizzle",
+            "wet road surface",
+            "puddles on the road",
+            "overcast sky",
+            "dark cloudy sky",
+            "fog",
+            "snow",
+        ),
+    }
+)
diff --git a/src/uq_desktop_processor/evaluation/clip_prefilter/run.py b/src/uq_desktop_processor/evaluation/clip_prefilter/run.py
new file mode 100644
index 0000000..1b378d5
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_prefilter/run.py
@@ -0,0 +1,179 @@
+"""
+Moves images into kept or rejected folders using a CLIP semantic accept/reject filter.
+"""
+
+import logging
+import os
+from collections.abc import Iterable, Mapping
+from typing import Any
+
+import torch
+from PIL import Image
+from torch import nn
+
+from uq_desktop_processor.evaluation.clip_common import encode_image, encode_texts, load_model, sigmoid_probability
+
+from . import defaults
+from .utils import _list_images, _move, _validate_dirs, resolve_rejected_folder_path
+from .validators import _validate_prefilter_config
+
+log = logging.getLogger(__name__)
+
+
+@torch.no_grad()
+def _build_filter_direction(model: nn.Module, device: str, filter_prompts: Mapping[str, Iterable[str]]) -> torch.Tensor:
+    """
+    Build a direction vector representing the semantic difference
+    between positive and negative filtering prompts.
+
+    :param model: CLIP model.
+    :param device: Torch device.
+    :param filter_prompts: Mapping with 'pos' and 'neg' prompt lists.
+    :return: Normalized direction vector in embedding space.
+
+    Example::
+        In: _build_filter_direction(model, device, filter_prompts)
+        Out: function result returned for provided inputs
+    """
+    log.debug("Building semantic filter direction vector from prompts...")
+    positive_embeddings = encode_texts(filter_prompts["pos"], model, device).mean(0)
+    negative_embeddings = encode_texts(filter_prompts["neg"], model, device).mean(0)
+
+    direction_vector = positive_embeddings - negative_embeddings
+    direction_norm = direction_vector.norm(p=2)
+
+    return direction_vector / direction_norm if direction_norm > 0 else direction_vector
+
+
+@torch.no_grad()
+def prefilter_folder(
+    image_folder: str = defaults.DEFAULT_IMAGE_FOLDER,
+    device: str = defaults.DEFAULT_DEVICE,
+    model_names: tuple[str, ...] = defaults.DEFAULT_MODEL_NAMES,
+    beta_sigmoid: float = defaults.DEFAULT_BETA_SIGMOID,
+    filter_threshold: float = defaults.DEFAULT_FILTER_THRESHOLD,
+    filter_prompts: Mapping[str, Iterable[str]] = defaults.FILTER_PROMPTS,
+    rejected_folder: str = defaults.DEFAULT_REJECTED_FOLDER,
+    dry_run: bool = False,
+) -> dict[str, Any]:
+    """
+    Filter images in a folder based on similarity to prompt directions.
+    Images below a threshold are moved to a rejected folder (unless dry_run=True).
+
+    :param image_folder: Folder containing image files.
+    :param device: PyTorch device string ("cpu" or "cuda").
+    :param model_names: Models to attempt loading.
+    :param beta_sigmoid: Sigmoid scaling factor.
+    :param filter_threshold: The cutoff percentage [0, 100] for the filter.
+    :param filter_prompts: A mapping containing 'pos' (positive) and 'neg' (negative) prompt lists.
+    :param rejected_folder: Sub-folder name for rejected images.
+    :param dry_run: If True, no files are moved.
+    :return: Summary dictionary of kept/rejected images.
+
+    Example::
+        In: prefilter_folder(image_folder, device, model_names, beta_sigmoid, filter_threshold, filter_prompts, rejected_folder, dry_run)
+        Out: function result returned for provided inputs
+    """
+    log.info(
+        "Starting pre-filter in '%s' (Threshold: %s%%).",
+        image_folder,
+        filter_threshold,
+    )
+
+    if dry_run:
+        log.warning("Dry run enabled: No files will actually be moved.")
+
+    # 1. Validate inputs
+    error_messages, warning_messages = _validate_prefilter_config(
+        image_folder=image_folder,
+        device=device,
+        model_names=model_names,
+        beta_sigmoid=beta_sigmoid,
+        filter_threshold=filter_threshold,
+        filter_prompts=filter_prompts,
+        raise_on_error=True,
+    )
+
+    # 2. Prepare directories
+    image_filenames = _list_images(image_folder)
+
+    if not image_filenames:
+        log.warning("No images found in '%s'. Aborting pre-filter.", image_folder)
+    else:
+        log.info("Found %s images to process.", len(image_filenames))
+
+    absolute_rejected_folder = resolve_rejected_folder_path(image_folder, rejected_folder)
+    _validate_dirs(image_folder, absolute_rejected_folder)
+
+    # 3. Load Model and Build Filter Direction
+    model, preprocess_function, loaded_model_name = load_model(model_names, device)
+    filter_direction_vector = _build_filter_direction(model, device, filter_prompts)
+
+    kept_images: list[dict[str, Any]] = []
+    rejected_images: list[dict[str, Any]] = []
+
+    # 4. Process Images
+    for filename in image_filenames:
+        image_path = os.path.join(image_folder, filename)
+        try:
+            with Image.open(image_path) as opened_image:
+                image_features = encode_image(opened_image, preprocess_function, model, device)
+        except Exception as open_exception:
+            log.error("Failed to open/process image '%s': %s", filename, open_exception)
+            rejected_images.append({"filename": filename, "reason": f"open_error: {open_exception}"})
+            continue
+
+        # Project image features onto direction vector
+        delta_value = torch.dot(image_features, filter_direction_vector).item()
+
+        # Convert to probability using sigmoid
+        probability_value = float(sigmoid_probability(delta_value, beta_sigmoid))
+
+        # Apply threshold filtering
+        if probability_value < filter_threshold:
+            if log.isEnabledFor(logging.DEBUG):
+                log.debug(
+                    "REJECT: '%s' (%.1f%% < %s%%)",
+                    filename,
+                    probability_value,
+                    filter_threshold,
+                )
+
+            rejected_images.append({"filename": filename, "filter_pct": round(probability_value, 1)})
+            if not dry_run:
+                # Keep file move side effect explicit and easy to spot.
+                _move(image_path, absolute_rejected_folder)
+        else:
+            if log.isEnabledFor(logging.DEBUG):
+                log.debug(
+                    "KEEP: '%s' (%.1f%% >= %s%%)",
+                    filename,
+                    probability_value,
+                    filter_threshold,
+                )
+
+            kept_images.append({"filename": filename, "filter_pct": round(probability_value, 1)})
+
+    log.info(
+        "Pre-filtering complete. Kept: %s, Rejected: %s.",
+        len(kept_images),
+        len(rejected_images),
+    )
+
+    # 5. Return Summary
+    return {
+        "model_name": loaded_model_name,
+        "image_folder": image_folder,
+        "rejected_folder": absolute_rejected_folder,
+        "beta_sigmoid": beta_sigmoid,
+        "filter_threshold": filter_threshold,
+        "kept": kept_images,
+        "rejected": rejected_images,
+        "summary": {
+            "total": len(image_filenames),
+            "kept": len(kept_images),
+            "rejected": len(rejected_images),
+        },
+        "warnings": warning_messages,
+        "dry_run": dry_run,
+    }
diff --git a/src/uq_desktop_processor/evaluation/clip_prefilter/utils.py b/src/uq_desktop_processor/evaluation/clip_prefilter/utils.py
new file mode 100644
index 0000000..63b5894
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_prefilter/utils.py
@@ -0,0 +1,138 @@
+"""
+Image discovery, directory checks, and file moves for the prefilter workflow.
+"""
+
+import logging
+import os
+import shutil
+import time
+
+log = logging.getLogger(__name__)
+
+
+def _list_images(folder: str) -> list[str]:
+    """
+    Return list of image filenames (png/jpg/jpeg) from a folder.
+
+    :param folder: Path to folder.
+    :return: Sorted list of image filenames.
+
+    Example::
+        In: _list_images(folder)
+        Out: function result returned for provided inputs
+    """
+    log.debug("Scanning folder for images: %s", folder)
+
+    return sorted(filename for filename in os.listdir(folder) if filename.lower().endswith((".png", ".jpg", ".jpeg")))
+
+
+def _unique_path(destination_directory: str, filename: str) -> str:
+    """
+    Generate a unique destination path to avoid overwriting existing files.
+    Appends timestamp and a counter until a free filename is found.
+
+    :param destination_directory: Target folder.
+    :param filename: Original filename.
+    :return: Unique full file path.
+
+    Example::
+        In: _unique_path(destination_directory, filename)
+        Out: function result returned for provided inputs
+    """
+    file_base, file_extension = os.path.splitext(filename)
+    candidate_path = os.path.join(destination_directory, filename)
+    counter = 1
+
+    while os.path.exists(candidate_path):
+        candidate_path = os.path.join(
+            destination_directory, f"{file_base}__{int(time.time())}_{counter}{file_extension}"
+        )
+        counter += 1
+
+    if counter > 1:
+        log.debug(
+            "File collision detected. Renamed to: %s",
+            os.path.basename(candidate_path),
+        )
+
+    return candidate_path
+
+
+def _ensure_dir(directory_path: str) -> None:
+    """
+    Ensure that a directory exists, creating it if needed.
+
+    :param directory_path: Directory path to ensure.
+
+    Example::
+        In: _ensure_dir(directory_path)
+        Out: function result returned for provided inputs
+    """
+    if not os.path.exists(directory_path):
+        log.debug("Creating directory: %s", directory_path)
+    os.makedirs(directory_path, exist_ok=True)
+
+
+def _move(source_path: str, destination_directory: str) -> None:
+    """
+    Move a file to another directory using a unique destination filename.
+
+    :param source_path: Source file path.
+    :param destination_directory: Target folder.
+
+    Example::
+        In: _move(source_path, destination_directory)
+        Out: function result returned for provided inputs
+    """
+    _ensure_dir(destination_directory)
+    unique_destination = _unique_path(destination_directory, os.path.basename(source_path))
+
+    if log.isEnabledFor(logging.DEBUG):
+        log.debug("Moving file '%s' to '%s'", source_path, unique_destination)
+
+    shutil.move(source_path, unique_destination)
+
+
+def resolve_rejected_folder_path(image_folder: str, rejected_folder: str) -> str:
+    """
+    Resolve where rejected images are stored.
+
+    If ``rejected_folder`` is an absolute path, it is used as-is (expanded).
+    Otherwise it is resolved relative to the parent directory of ``image_folder``
+    (same behaviour as a sibling folder name such as ``rejected``).
+
+    :param image_folder: Folder being filtered (absolute or relative).
+    :param rejected_folder: Absolute path, or relative name/path under the image folder's parent.
+    :return: Absolute path to the rejected-images directory.
+
+    Example::
+        In: resolve_rejected_folder_path(image_folder, rejected_folder)
+        Out: function result returned for provided inputs
+    """
+    image_abs = os.path.abspath(os.path.expanduser(image_folder))
+    rejected_folder_input = (rejected_folder or "").strip() or "rejected"
+    rejected_folder_expanded = os.path.expanduser(rejected_folder_input)
+    if os.path.isabs(rejected_folder_expanded):
+        return os.path.abspath(rejected_folder_expanded)
+    return os.path.abspath(os.path.join(os.path.dirname(image_abs), rejected_folder_expanded))
+
+
+def _validate_dirs(image_folder: str, rejected_absolute_path: str) -> None:
+    """
+    Ensure the source image folder and the destination rejected folder are distinct.
+
+    This prevents operations where files might be moved into the same directory
+    they currently reside in.
+
+    :param image_folder: Path to the source directory containing images.
+    :param rejected_absolute_path: Absolute path to the directory for rejected items.
+    :raises ValueError: If both paths resolve to the same directory.
+
+    Example::
+        In: _validate_dirs(image_folder, rejected_absolute_path)
+        Out: function result returned for provided inputs
+    """
+    if os.path.abspath(image_folder) == os.path.abspath(rejected_absolute_path):
+        error_message = "rejected_folder must be different from image_folder."
+        log.error(error_message)
+        raise ValueError(error_message)
diff --git a/src/uq_desktop_processor/evaluation/clip_prefilter/validators.py b/src/uq_desktop_processor/evaluation/clip_prefilter/validators.py
new file mode 100644
index 0000000..bbe3d7f
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/clip_prefilter/validators.py
@@ -0,0 +1,167 @@
+"""
+Validates prefilter configuration dicts before loading models or scanning images.
+"""
+
+import logging
+from collections.abc import Iterable, Mapping
+from typing import Any
+
+from uq_desktop_processor.evaluation.clip_common import (
+    ValidationError,
+    check_beta_sigmoid,
+    check_device,
+    check_image_folder,
+    check_model_names,
+)
+
+log = logging.getLogger(__name__)
+
+
+def _is_percentage(value: Any) -> bool:
+    """
+    Check whether a given value represents a valid percentage (0–100).
+
+    :param value: Value to test.
+    :return: True if value is numeric and in range [0, 100].
+
+    Example::
+        In: _is_percentage(value)
+        Out: function result returned for provided inputs
+    """
+    try:
+        numeric_value = float(value)
+    except (ValueError, TypeError):
+        return False
+    return 0.0 <= numeric_value <= 100.0
+
+
+def _check_filter_threshold(threshold_value: float) -> tuple[list[str], list[str]]:
+    """
+    Validate the numeric threshold used for filtering.
+    Ensures the value is a number and within [0, 100].
+
+    :param threshold_value: Threshold percentage.
+    :return: (errors, warnings)
+
+    Example::
+        In: _check_filter_threshold(threshold_value)
+        Out: function result returned for provided inputs
+    """
+    error_messages: list[str] = []
+    warning_messages: list[str] = []
+
+    if not isinstance(threshold_value, int | float):
+        error_message = "filter_threshold: must be a number."
+        log.error(error_message)
+        error_messages.append(error_message)
+        return error_messages, warning_messages
+
+    if not _is_percentage(threshold_value):
+        error_message = "filter_threshold: allowed range is [0, 100]."
+        log.error(error_message)
+        error_messages.append(error_message)
+
+    return error_messages, warning_messages
+
+
+def _check_filter_prompts(filter_prompt_mapping: Mapping[str, Iterable[str]]) -> tuple[list[str], list[str]]:
+    """
+    Validate the structure and content of filter prompts.
+    Ensures presence of 'pos' and 'neg' keys and that all prompts are non-empty strings.
+
+    :param filter_prompt_mapping: Mapping with keys 'pos' and 'neg' pointing to lists of prompts.
+    :return: (errors, warnings)
+
+    Example::
+        In: _check_filter_prompts(filter_prompt_mapping)
+        Out: function result returned for provided inputs
+    """
+    error_messages: list[str] = []
+    warning_messages: list[str] = []
+
+    if not isinstance(filter_prompt_mapping, Mapping):
+        error_message = "filter_prompts: must be a Mapping."
+        log.error(error_message)
+        error_messages.append(error_message)
+        return error_messages, warning_messages
+
+    for prompt_side_name in ("pos", "neg"):
+        if prompt_side_name not in filter_prompt_mapping:
+            error_message = f"filter_prompts: missing key '{prompt_side_name}'."
+            log.error(error_message)
+            error_messages.append(error_message)
+            continue
+
+        prompt_values = list(filter_prompt_mapping[prompt_side_name] or [])
+        if not prompt_values:
+            error_message = f"filter_prompts['{prompt_side_name}']: list cannot be empty."
+            log.error(error_message)
+            error_messages.append(error_message)
+        elif not all(isinstance(prompt_text, str) and prompt_text.strip() for prompt_text in prompt_values):
+            error_message = f"filter_prompts['{prompt_side_name}']: all elements must be non-empty strings."
+            log.error(error_message)
+            error_messages.append(error_message)
+
+    return error_messages, warning_messages
+
+
+def _validate_prefilter_config(
+    *,
+    image_folder: str,
+    device: str,
+    model_names: Iterable[str],
+    beta_sigmoid: float,
+    filter_threshold: float,
+    filter_prompts: Mapping[str, Iterable[str]],
+    raise_on_error: bool = True,
+) -> tuple[list[str], list[str]]:
+    """
+    Validate the configuration parameters for the pre-filtering process.
+
+    This function aggregates various validation checks for image sources, compute devices,
+    CLIP model specifications, and filtering parameters (thresholds and prompts).
+
+    :param image_folder: Path to the directory containing images to be processed.
+    :param device: The compute device identifier (e.g., 'cpu', 'cuda').
+    :param model_names: An iterable of CLIP model names to be utilized.
+    :param beta_sigmoid: The beta coefficient used in the sigmoid scaling function.
+    :param filter_threshold: The cutoff percentage [0, 100] for the filter.
+    :param filter_prompts: A mapping containing 'pos' (positive) and 'neg' (negative) prompt lists.
+    :param raise_on_error: If True, raises a ValidationError when errors occur. Defaults to True.
+    :return: A tuple containing a list of error messages and a list of warning messages.
+    :raises ValidationError: If errors are found and raise_on_error is True.
+
+    Example::
+        In: _validate_prefilter_config()
+        Out: function result returned for provided inputs
+    """
+    log.debug("Validating pre-filter configuration...")
+    error_messages: list[str] = []
+    warning_messages: list[str] = []
+
+    validation_checks = [
+        lambda: check_image_folder(image_folder),
+        lambda: check_device(device),
+        lambda: check_model_names(model_names),
+        lambda: check_beta_sigmoid(beta_sigmoid),
+        lambda: _check_filter_threshold(filter_threshold),
+        lambda: _check_filter_prompts(filter_prompts),
+    ]
+
+    for validation_function in validation_checks:
+        function_errors, function_warnings = validation_function()
+        error_messages += function_errors
+        warning_messages += function_warnings
+
+    # Remove duplicates while preserving order
+    error_messages = list(dict.fromkeys(error_messages))
+    warning_messages = list(dict.fromkeys(warning_messages))
+
+    if error_messages:
+        log.error("Pre-filter validation failed with %s errors.", len(error_messages))
+        if raise_on_error:
+            raise ValidationError(error_messages, warning_messages)
+    else:
+        log.debug("Pre-filter configuration valid.")
+
+    return error_messages, warning_messages
diff --git a/src/uq_desktop_processor/evaluation/evaluation_utils/__init__.py b/src/uq_desktop_processor/evaluation/evaluation_utils/__init__.py
new file mode 100644
index 0000000..d018ee2
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/evaluation_utils/__init__.py
@@ -0,0 +1,21 @@
+"""
+Evaluation module:   init  .
+"""
+
+from .schema import (
+    CategoryScore,
+    EvaluationResult,
+    ImageResult,
+    make_category_score,
+    make_evaluation_result,
+    make_image_result,
+)
+
+__all__ = [
+    "CategoryScore",
+    "ImageResult",
+    "EvaluationResult",
+    "make_category_score",
+    "make_image_result",
+    "make_evaluation_result",
+]
diff --git a/src/uq_desktop_processor/evaluation/evaluation_utils/schema.py b/src/uq_desktop_processor/evaluation/evaluation_utils/schema.py
new file mode 100644
index 0000000..c9033bd
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/evaluation_utils/schema.py
@@ -0,0 +1,147 @@
+"""
+TypedDict schemas and helpers for structured CLIP (and related) evaluation JSON output.
+"""
+
+from collections.abc import Mapping, Sequence
+from typing import Any, NotRequired, TypedDict
+
+
+class CategoryScore(TypedDict):
+    """
+    CategoryScore evaluation helper class.
+
+    Example::
+        In: CategoryScore(...)
+        Out: initialized instance ready for use
+    """
+
+    probability_pct: float
+    delta: float | None
+
+
+class ImageResult(TypedDict):
+    """
+    ImageResult evaluation helper class.
+
+    Example::
+        In: ImageResult(...)
+        Out: initialized instance ready for use
+    """
+
+    filename: str
+    image_path: NotRequired[str]
+    overall_pct: float
+    categories: Mapping[str, CategoryScore]
+
+
+class EvaluationResult(TypedDict):
+    """
+    EvaluationResult evaluation helper class.
+
+    Example::
+        In: EvaluationResult(...)
+        Out: initialized instance ready for use
+    """
+
+    model_name: str | None
+    order: Sequence[str]
+    weights: NotRequired[Mapping[str, float] | None]
+    beta_sigmoid: float | None
+    images: list[ImageResult]
+    average_overall_pct: float | None
+    skipped_images: NotRequired[list[str]]
+    warnings: list[str]
+    errors: list[str] | None
+    # Optional extension point for future pipelines
+    extra: NotRequired[Mapping[str, Any]]
+
+
+def make_category_score(*, probability_pct: float, delta: float | None) -> CategoryScore:
+    """
+    Build one category score entry.
+
+    :param probability_pct: Category probability in percent.
+    :param delta: Raw directional score, if available.
+    :return: Typed category score dictionary.
+
+    Example::
+        In: make_category_score(probability_pct=62.5, delta=0.12)
+        Out: {"probability_pct": 62.5, "delta": 0.12}
+    """
+    return {"probability_pct": float(probability_pct), "delta": None if delta is None else float(delta)}
+
+
+def make_image_result(
+    *,
+    filename: str,
+    image_path: str | None = None,
+    overall_pct: float,
+    categories: Mapping[str, CategoryScore],
+) -> ImageResult:
+    """
+    Build one image-level result record.
+
+    :param filename: Source image path or name.
+    :param image_path: Optional absolute/relative path to source image.
+    :param overall_pct: Overall score in percent.
+    :param categories: Per-category score mapping.
+    :return: Typed image result dictionary.
+
+    Example::
+        In: make_image_result(filename="img.jpg", overall_pct=57.0, categories={"wealthier": {"probability_pct": 60.0, "delta": 0.2}})
+        Out: {"filename": "img.jpg", "overall_pct": 57.0, "categories": {...}}
+    """
+    out: ImageResult = {"filename": str(filename), "overall_pct": float(overall_pct), "categories": categories}
+    if image_path is not None:
+        out["image_path"] = str(image_path)
+    return out
+
+
+def make_evaluation_result(
+    *,
+    model_name: str | None,
+    order: Sequence[str],
+    beta_sigmoid: float | None,
+    images: list[ImageResult],
+    average_overall_pct: float | None,
+    warnings: list[str] | None = None,
+    errors: list[str] | None = None,
+    weights: Mapping[str, float] | None = None,
+    skipped_images: list[str] | None = None,
+    extra: Mapping[str, Any] | None = None,
+) -> EvaluationResult:
+    """
+    Assemble full evaluation payload in a consistent schema.
+
+    :param model_name: Model identifier.
+    :param order: Category output order.
+    :param beta_sigmoid: Beta value used by sigmoid scoring (if applicable).
+    :param images: Per-image results.
+    :param average_overall_pct: Dataset average score.
+    :param warnings: Non-fatal warnings.
+    :param errors: Fatal or aggregated errors.
+    :param weights: Optional category weights.
+    :param skipped_images: Optional skipped-image messages.
+    :param extra: Optional extension block.
+    :return: Typed evaluation result dictionary.
+
+    Example::
+        In: make_evaluation_result(model_name="ViT-L/14", order=("wealthier",), beta_sigmoid=30.0, images=[], average_overall_pct=None)
+        Out: {"model_name": "ViT-L/14", "order": ("wealthier",), "images": [], ...}
+    """
+    out: EvaluationResult = {
+        "model_name": model_name,
+        "order": tuple(order),
+        "beta_sigmoid": beta_sigmoid,
+        "images": images,
+        "average_overall_pct": average_overall_pct,
+        "warnings": list(warnings or []),
+        "errors": errors,
+    }
+    if weights is not None:
+        out["weights"] = dict(weights)
+    if skipped_images is not None:
+        out["skipped_images"] = list(skipped_images)
+    if extra is not None:
+        out["extra"] = dict(extra)
+    return out
diff --git a/src/uq_desktop_processor/evaluation/finetuned_evaluator/__init__.py b/src/uq_desktop_processor/evaluation/finetuned_evaluator/__init__.py
new file mode 100644
index 0000000..4f870d7
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/finetuned_evaluator/__init__.py
@@ -0,0 +1,7 @@
+"""
+Evaluation module:   init  .
+"""
+
+from .run import evaluate_images_with_finetuned
+
+__all__ = ["evaluate_images_with_finetuned"]
diff --git a/src/uq_desktop_processor/evaluation/finetuned_evaluator/defaults.py b/src/uq_desktop_processor/evaluation/finetuned_evaluator/defaults.py
new file mode 100644
index 0000000..2e6aa80
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/finetuned_evaluator/defaults.py
@@ -0,0 +1,14 @@
+"""
+Default checkpoint paths and inference settings for fine-tuned ViT scoring.
+"""
+
+from collections.abc import Sequence
+
+DEFAULT_CATEGORY_ORDER: Sequence[str] = (
+    "safer",
+    "wealthier",
+    "more beautiful",
+    "livelier",
+    "less depressing",
+    "less boring",
+)
diff --git a/src/uq_desktop_processor/evaluation/finetuned_evaluator/model.py b/src/uq_desktop_processor/evaluation/finetuned_evaluator/model.py
new file mode 100644
index 0000000..f74e0a7
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/finetuned_evaluator/model.py
@@ -0,0 +1,82 @@
+"""
+Fine-tuned vision model construction and forward pass utilities for image scoring.
+"""
+
+import logging
+from typing import Any, cast
+
+import torch
+import torch.nn as nn
+
+log = logging.getLogger(__name__)
+
+try:
+    import timm
+except Exception as import_error:
+    raise RuntimeError("Install timm: pip install timm") from import_error
+
+
+class ViTMultiHead(nn.Module):
+    """
+    ViT backbone with a multi-output prediction head.
+
+    Example::
+        In: ViTMultiHead(...)
+        Out: initialized instance ready for use
+    """
+
+    def __init__(self, model_name: str, num_outputs: int = 6, image_size: int = 224) -> None:
+        """
+        Create model backbone and MLP head for fine-tuned scoring.
+
+        :param model_name: timm model name for the backbone.
+        :param num_outputs: Number of output targets.
+        :param image_size: Input image size used by the backbone.
+
+        Example::
+            In: ViTMultiHead("vit_base_patch14_dinov2.lvd142m", num_outputs=6, image_size=224)
+            Out: initialized module ready for forward passes
+        """
+        super().__init__()
+        log.info("Initializing ViTMultiHead. Backbone: '%s'", model_name)
+
+        self.backbone = timm.create_model(
+            model_name, pretrained=True, num_classes=0, dynamic_img_size=True, img_size=image_size
+        )
+        backbone_any = cast(Any, self.backbone)
+
+        if hasattr(backbone_any, "num_features"):
+            feat_dim = int(backbone_any.num_features)
+        else:
+            feat_dim = int(backbone_any.embed_dim)
+
+        self.head = nn.Sequential(
+            nn.LayerNorm(feat_dim * 2),
+            nn.Linear(feat_dim * 2, 512),
+            nn.GELU(),
+            nn.Dropout(0.2),
+            nn.Linear(512, 256),
+            nn.GELU(),
+            nn.Linear(256, num_outputs),
+        )
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        """
+        Run one forward pass.
+
+        :param x: Input batch tensor ``(N, C, H, W)``.
+        :return: Predicted outputs ``(N, num_outputs)``.
+
+        Example::
+            In: model.forward(torch.randn(2, 3, 224, 224))
+            Out: tensor with shape (2, num_outputs)
+        """
+        # Combine global CLS token with pooled patch context before the MLP head.
+        backbone_any = cast(Any, self.backbone)
+        features = backbone_any.forward_features(x)
+        cls_token = features[:, 0]
+        patch_tokens = features[:, 1:]
+        pooled_patches = torch.mean(patch_tokens, dim=1)
+
+        combined = torch.cat([cls_token, pooled_patches], dim=1)
+        return self.head(combined)
diff --git a/src/uq_desktop_processor/evaluation/finetuned_evaluator/run.py b/src/uq_desktop_processor/evaluation/finetuned_evaluator/run.py
new file mode 100644
index 0000000..8000378
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/finetuned_evaluator/run.py
@@ -0,0 +1,342 @@
+"""
+Runs fine-tuned ViT scoring over a folder of images and aggregates JSON results.
+"""
+
+import logging
+from collections.abc import Sequence
+from pathlib import Path
+
+import numpy as np
+import torch
+from PIL import Image
+from tqdm.auto import tqdm
+
+from uq_desktop_processor.evaluation.evaluation_utils import make_evaluation_result
+
+from . import defaults
+from .utils import (
+    _apply_calibration,
+    _build_transform,
+    _iter_image_paths,
+    _load_calibrators,
+    _load_checkpoint_and_model,
+)
+
+log = logging.getLogger(__name__)
+
+
+def _resolve_paths(
+    images_dir: str | Path,
+    model_path: str | Path,
+    calibrators_dir: str | Path | None,
+) -> tuple[Path, Path, Path | None]:
+    """
+    Resolve and validate input paths.
+    Raises FileNotFoundError or NotADirectoryError if paths are invalid.
+
+    Example::
+        In: _resolve_paths(images_dir, model_path, calibrators_dir)
+        Out: function result returned for provided inputs
+    """
+    images_dir = Path(images_dir)
+    model_path = Path(model_path)
+    calibrators_dir_path = Path(calibrators_dir) if calibrators_dir else None
+
+    log.debug(
+        "Resolving paths: images='%s', model='%s', calibrators='%s'",
+        images_dir,
+        model_path,
+        calibrators_dir_path,
+    )
+
+    # Validate images directory
+    if not images_dir.exists():
+        error_message = f"Images directory not found: {images_dir}"
+        log.error(error_message)
+        raise FileNotFoundError(error_message)
+    if not images_dir.is_dir():
+        error_message = f"Images path is not a directory: {images_dir}"
+        log.error(error_message)
+        raise NotADirectoryError(error_message)
+
+    # Validate model file
+    if not model_path.exists():
+        error_message = f"Model file not found: {model_path}"
+        log.error(error_message)
+        raise FileNotFoundError(error_message)
+    if not model_path.is_file():
+        error_message = f"Model path must be a file: {model_path}"
+        log.error(error_message)
+        raise IsADirectoryError(error_message)
+
+    # Validate calibrators directory
+    if calibrators_dir_path is not None:
+        if not calibrators_dir_path.exists():
+            error_message = f"Calibrators directory not found: {calibrators_dir_path}"
+            log.error(error_message)
+            raise FileNotFoundError(error_message)
+        if not calibrators_dir_path.is_dir():
+            error_message = f"Calibrators path is not a directory: {calibrators_dir_path}"
+            log.error(error_message)
+            raise NotADirectoryError(error_message)
+
+    return images_dir, model_path, calibrators_dir_path
+
+
+def _get_calibrators(calibrators_dir: Path | None, category_order: Sequence[str]) -> dict:
+    """
+    Load per-category calibration metadata if provided; otherwise fall back.
+
+    If ``calibrators_dir`` is None, calibration is effectively OFF.
+
+    Example::
+        In: _get_calibrators(calibrators_dir, category_order)
+        Out: function result returned for provided inputs
+    """
+    if calibrators_dir is None:
+        log.info("No calibrators directory provided. Calibration is OFF (fallback scaling).")
+        return {category_name: {"type": "fallback"} for category_name in category_order}
+
+    log.info("Loading calibrators from: %s", calibrators_dir)
+    calibrators = _load_calibrators(calibrators_dir, category_order)
+    loaded_calibrator_types = {category_name: spec["type"] for category_name, spec in calibrators.items()}
+    log.info("Loaded calibrator types: %s", loaded_calibrator_types)
+    return calibrators
+
+
+def _predict_batch(model: torch.nn.Module, batch_tensors: list[torch.Tensor], device: torch.device) -> np.ndarray:
+    """
+    Run a batch of images through the fine-tuned model and return raw predictions.
+
+    :param model: Fine-tuned model used for inference.
+    :param batch_tensors: List of transformed image tensors.
+    :param device: Device used for evaluation.
+    :return: Numpy array of model outputs with shape (batch_size, num_outputs).
+
+    Example::
+        In: _predict_batch(model, batch_tensors, device)
+        Out: function result returned for provided inputs
+    """
+    if log.isEnabledFor(logging.DEBUG):
+        log.debug(
+            "Predicting batch of size %s on device %s",
+            len(batch_tensors),
+            device,
+        )
+
+    batch_tensor = torch.stack(batch_tensors, dim=0).to(device)
+    use_mixed_precision = torch.cuda.is_available()
+
+    with torch.amp.autocast("cuda", enabled=use_mixed_precision):
+        return model(batch_tensor).detach().cpu().numpy().astype(np.float32)
+
+
+def _format_single_result(
+    image_path: Path,
+    raw_probs: np.ndarray,
+    calibrators: dict,
+    category_order: Sequence[str],
+) -> dict:
+    """
+    Format one model output entry into a standardized result dictionary.
+
+    :param image_path: Path to the evaluated image.
+    :param raw_probs: Raw model output (one vector per image).
+    :param calibrators: Calibration metadata.
+    :return: Dictionary formatted for downstream tooling (similar to CLIP pipeline outputs).
+
+    Example::
+        In: _format_single_result(image_path, raw_probs, calibrators, category_order)
+        Out: function result returned for provided inputs
+    """
+    calibrated_probs = _apply_calibration(raw_probs, calibrators, category_order)
+
+    # Overall score = mean of calibrated per-category probabilities
+    overall_score = float(np.mean([calibrated_probs[cat] for cat in category_order]))
+
+    # CLIP pipeline expects "delta" values, but fine-tuned models do not provide them
+    category_block = {
+        category_name: {"probability_pct": float(calibrated_probs[category_name]), "delta": None}
+        for category_name in category_order
+    }
+
+    return {
+        "filename": image_path.name,
+        "image_path": str(image_path),
+        "overall_pct": overall_score,
+        "categories": category_block,
+    }
+
+
+def _process_batch(
+    model: torch.nn.Module,
+    batch_tensors: list[torch.Tensor],
+    batch_paths: list[Path],
+    calibrators: dict,
+    device: torch.device,
+    category_order: Sequence[str],
+) -> list[dict]:
+    """
+    Evaluate one batch and convert its outputs into result dictionaries.
+
+    :param model: Fine-tuned model.
+    :param batch_tensors: List of tensors in the current batch.
+    :param batch_paths: Corresponding list of image paths.
+    :param calibrators: Calibration metadata.
+    :param device: Torch device.
+    :return: List of results for each image in the batch.
+
+    Example::
+        In: _process_batch(model, batch_tensors, batch_paths, calibrators, device, category_order)
+        Out: function result returned for provided inputs
+    """
+    raw_output = _predict_batch(model, batch_tensors, device)
+    results = []
+
+    for index in range(raw_output.shape[0]):
+        # Keep path and prediction aligned by shared batch index.
+        result = _format_single_result(batch_paths[index], raw_output[index], calibrators, category_order)
+        results.append(result)
+
+    return results
+
+
+def _calculate_final_stats(results_images: list[dict]) -> float | None:
+    """
+    Compute the mean overall score across all evaluated images.
+
+    :param results_images: List of result dictionaries.
+    :return: Average score or None if no images were processed.
+
+    Example::
+        In: _calculate_final_stats(results_images)
+        Out: function result returned for provided inputs
+    """
+    if not results_images:
+        return None
+
+    return float(np.mean([res["overall_pct"] for res in results_images]))
+
+
+@torch.no_grad()
+def evaluate_images_with_finetuned(
+    images_dir: str | Path,
+    model_path: str | Path,
+    calibrators_dir: str | Path | None = None,
+    model_name: str = "vit_base_patch14_dinov2.lvd142m",
+    image_size: int = 224,
+    batch_size: int = 32,
+    torch_device: str = "auto",
+    category_order: Sequence[str] = defaults.DEFAULT_CATEGORY_ORDER,
+) -> dict:
+    """
+    Evaluate a set of images using a fine-tuned ViT-like model (loaded from checkpoint).
+
+    This pipeline:
+      - resolves paths and loads the model
+      - builds transforms
+      - optionally loads calibrators
+      - iterates through images in batches
+      - computes calibrated probabilities
+      - formats results into a CLIP-compatible schema
+
+    :return: Structured result dictionary similar to CLIP scoring outputs.
+
+    Example::
+        In: evaluate_images_with_finetuned(images_dir, model_path, calibrators_dir, model_name, image_size, batch_size, torch_device, category_order)
+        Out: function result returned for provided inputs
+    """
+    log.info("Starting fine-tuned model evaluation pipeline.")
+
+    # Resolve filesystem paths
+    images_dir, model_path, calibrators_dir_path = _resolve_paths(
+        images_dir=images_dir,
+        model_path=model_path,
+        calibrators_dir=calibrators_dir,
+    )
+
+    num_outputs = len(category_order)
+
+    # Load model and preprocessing
+    torch_device_name = (torch_device or "auto").lower().strip()
+    if torch_device_name not in ("auto", "cpu", "cuda"):
+        raise ValueError("torch_device must be one of: auto, cpu, cuda")
+    if torch_device_name == "cuda" and not torch.cuda.is_available():
+        raise RuntimeError("CUDA requested but not available in this environment.")
+    if torch_device_name == "cuda":
+        device = torch.device("cuda")
+    elif torch_device_name == "cpu":
+        device = torch.device("cpu")
+    else:
+        device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    log.info("Loading model weights from: %s (Model: %s)", model_path, model_name)
+    log.info("Using device: %s", device)
+
+    model = _load_checkpoint_and_model(model_path, model_name, image_size, device, num_outputs)
+    transform_function = _build_transform(model_name, image_size)
+    calibrators = _get_calibrators(calibrators_dir_path, category_order)
+
+    # Gather image paths
+    image_paths = _iter_image_paths(images_dir)
+    if not image_paths:
+        error_message = f"No images found in: {images_dir}"
+        log.error(error_message)
+        raise FileNotFoundError(error_message)
+
+    log.info("Found %s images to evaluate.", len(image_paths))
+
+    results_images: list[dict] = []
+    skipped: list[str] = []
+    warnings: list[str] = []
+
+    batch_tensors: list[torch.Tensor] = []
+    batch_paths: list[Path] = []
+
+    iterator = tqdm(image_paths, desc="Scoring images", dynamic_ncols=True)
+
+    # Process images batch-by-batch
+    for image_path in iterator:
+        try:
+            image = Image.open(image_path).convert("RGB")
+        except Exception as open_error:
+            warning_message = f"Failed to open image '{image_path.name}': {open_error}"
+            log.warning(warning_message)
+            skipped.append(f"{image_path.name}: {open_error}")
+            continue
+
+        batch_tensors.append(transform_function(image))
+        batch_paths.append(image_path)
+
+        # Full batch > process it
+        if len(batch_tensors) >= batch_size:
+            batch_results = _process_batch(model, batch_tensors, batch_paths, calibrators, device, category_order)
+            results_images.extend(batch_results)
+            batch_tensors, batch_paths = [], []
+
+    # Process leftovers
+    if batch_tensors:
+        batch_results = _process_batch(model, batch_tensors, batch_paths, calibrators, device, category_order)
+        results_images.extend(batch_results)
+
+    # Compute overall stats
+    average_overall_score = _calculate_final_stats(results_images)
+
+    log.info(
+        "Evaluation complete. Average score: %s (Processed: %s, Skipped: %s)",
+        average_overall_score,
+        len(results_images),
+        len(skipped),
+    )
+
+    return make_evaluation_result(
+        model_name=f"{model_name} (fine-tuned)",
+        order=category_order,
+        weights=None,
+        beta_sigmoid=None,
+        images=results_images,
+        average_overall_pct=average_overall_score,
+        warnings=warnings,
+        errors=None,
+        skipped_images=skipped,
+        extra={"calibration": "on" if calibrators_dir_path is not None else "off"},
+    )
diff --git a/src/uq_desktop_processor/evaluation/finetuned_evaluator/utils.py b/src/uq_desktop_processor/evaluation/finetuned_evaluator/utils.py
new file mode 100644
index 0000000..662e4a3
--- /dev/null
+++ b/src/uq_desktop_processor/evaluation/finetuned_evaluator/utils.py
@@ -0,0 +1,354 @@
+"""
+Loads checkpoints, image transforms, and calibration for fine-tuned evaluation.
+"""
+
+import json
+import logging
+import math
+from collections.abc import Callable, Sequence
+from pathlib import Path
+from typing import Any, cast
+
+import joblib
+import numpy as np
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+from .model import ViTMultiHead
+
+log = logging.getLogger(__name__)
+
+try:
+    import timm
+    from timm.data import resolve_data_config
+    from timm.data.transforms_factory import create_transform
+except Exception as import_error:
+    # Provide a clear installation message if timm is missing
+    raise RuntimeError("Install timm: pip install timm") from import_error
+
+
+def _build_transform(model_name: str, image_size: int) -> Callable[[Any], torch.Tensor]:
+    """
+    Build the preprocessing transform used for the fine-tuned model.
+
+    Uses TIMM utilities to resolve the correct mean/std and transform pipeline
+    based on the model's pretrained configuration.
+
+    :param model_name: Name of the backbone model.
+    :param image_size: Input image size expected by the model.
+    :return: A torchvision-compatible transform function.
+
+    Example::
+        In: _build_transform(model_name, image_size)
+        Out: function result returned for provided inputs
+    """
+    log.debug("Building transform for model '%s' (size: %s)", model_name, image_size)
+    pretrained_config = timm.get_pretrained_cfg(model_name)
+    pretrained_cfg_dict: dict[str, Any] = pretrained_config.to_dict() if pretrained_config is not None else {}
+    base_config = resolve_data_config(pretrained_cfg=pretrained_cfg_dict)
+
+    transform = create_transform(
+        input_size=(3, image_size, image_size),
+        is_training=False,
+        mean=base_config.get("mean"),
+        std=base_config.get("std"),
+    )
+    return transform
+
+
+def _load_checkpoint_and_model(
+    checkpoint_path: Path,
+    model_name: str,
+    image_size: int,
+    device: torch.device,
+    num_outputs: int,
+) -> nn.Module:
+    """
+    Load a fine-tuned ViTMultiHead model and restore weights from checkpoint.
+
+    :param checkpoint_path: Path to a .pt checkpoint containing the saved state_dict.
+    :param model_name: Name of the TIMM backbone.
+    :param image_size: Input resolution.
+    :param device: Torch device for model instantiation.
+    :return: Loaded and ready-to-evaluate model instance.
+
+    Example::
+        In: _load_checkpoint_and_model(checkpoint_path, model_name, image_size, device, num_outputs)
+        Out: function result returned for provided inputs
+    """
+    log.debug("Loading checkpoint from: %s", checkpoint_path)
+
+    try:
+        checkpoint = torch.load(checkpoint_path, map_location=device)
+    except Exception as error:
+        log.error("Failed to load checkpoint file: %s", error)
+        raise
+
+    # Create the classifier head with the correct shape
+    model = ViTMultiHead(model_name, num_outputs=num_outputs, image_size=image_size).to(device)
+
+    def _resize_backbone_pos_embed_if_needed(state_dict_in: dict[str, Any], model_in: nn.Module) -> dict[str, Any]:
+        """
+        Resize checkpoint positional embeddings to the current model's image size if needed.
+
+        This function handles the spatial interpolation of ViT positional embeddings
+        when the inference resolution differs from the training resolution.
+
+        :param state_dict_in: The source state dictionary from the loaded checkpoint.
+        :param model_in: The target model instance to match the shapes against.
+        :return: A state dictionary with adjusted (resized) positional embeddings.
+
+        Example::
+            In: _resize_backbone_pos_embed_if_needed(state_dict_in, model_in)
+            Out: function result returned for provided inputs
+        """
+        pos_key = "backbone.pos_embed"
+
+        # Check if the positional embedding key exists in both the checkpoint and the model
+        if pos_key not in state_dict_in:
+            return state_dict_in
+
+        model_state = model_in.state_dict()
+        if pos_key not in model_state:
+            return state_dict_in
+
+        checkpoint_pos_embed = state_dict_in[pos_key]
+        target_pos_embed = model_state[pos_key]
+
+        # Ensure we are dealing with tensors
+        if not isinstance(checkpoint_pos_embed, torch.Tensor) or not isinstance(target_pos_embed, torch.Tensor):
+            return state_dict_in
+
+        # If shapes already match, no interpolation is required
+        if checkpoint_pos_embed.shape == target_pos_embed.shape:
+            return state_dict_in
+
+        # Validate dimensions before proceeding
+        if checkpoint_pos_embed.ndim != 3 or target_pos_embed.ndim != 3:
+            log.warning("Unexpected pos_embed shape. Falling back to model defaults for pos_embed.")
+            state_dict_copy = dict(state_dict_in)
+            state_dict_copy.pop(pos_key, None)
+            return state_dict_copy
+
+        checkpoint_tokens = checkpoint_pos_embed.shape[1]
+        target_tokens = target_pos_embed.shape[1]
+        embed_dim = checkpoint_pos_embed.shape[2]
+
+        # Check if the embedding vector size (last dimension) matches
+        if embed_dim != target_pos_embed.shape[2]:
+            log.warning("pos_embed embedding dim mismatch. Falling back to model defaults.")
+            state_dict_copy = dict(state_dict_in)
+            state_dict_copy.pop(pos_key, None)
+            return state_dict_copy
+
+        # Determine the number of special tokens (e.g., [CLS]) to separate them from grid tokens
+        backbone_any = cast(Any, model_in.backbone)
+        num_prefix_tokens = int(getattr(backbone_any, "num_prefix_tokens", 1))
+
+        source_grid_tokens = checkpoint_tokens - num_prefix_tokens
+        target_grid_tokens = target_tokens - num_prefix_tokens
+        source_size = int(math.sqrt(source_grid_tokens))
+        target_size = int(math.sqrt(target_grid_tokens))
+
+        # Ensure the spatial tokens form a perfect square
+        if (
+            source_size * source_size != source_grid_tokens
+            or target_size * target_size != target_grid_tokens
+            or source_grid_tokens <= 0
+            or target_grid_tokens <= 0
+        ):
+            log.warning("Cannot infer square token grid. Falling back to model defaults.")
+            state_dict_copy = dict(state_dict_in)
+            state_dict_copy.pop(pos_key, None)
+            return state_dict_copy
+
+        # Separate prefix tokens from patch tokens
+        cls_tokens = checkpoint_pos_embed[:, :num_prefix_tokens, :]
+        patch_tokens = checkpoint_pos_embed[:, num_prefix_tokens:, :]
+
+        # Reshape patch tokens to a spatial grid for bicubic interpolation
+        patch_tokens = patch_tokens.reshape(1, source_size, source_size, embed_dim).permute(0, 3, 1, 2)
+        patch_tokens = F.interpolate(patch_tokens, size=(target_size, target_size), mode="bicubic", align_corners=False)
+
+        # Flatten back to the sequence format
+        patch_tokens = patch_tokens.permute(0, 2, 3, 1).reshape(1, target_size * target_size, embed_dim)
+
+        # Combine prefix tokens with the newly resized patch tokens
+        resized_pos_embed = torch.cat([cls_tokens, patch_tokens], dim=1).to(dtype=target_pos_embed.dtype)
+
+        state_dict_copy = dict(state_dict_in)
+        state_dict_copy[pos_key] = resized_pos_embed
+
+        log.info(
+            "Resized checkpoint pos_embed from %s to %s to match GUI image size.",
+            tuple(checkpoint_pos_embed.shape),
+            tuple(target_pos_embed.shape),
+        )
+        return state_dict_copy
+
+    # Load weights and configure for inference
+    try:
+        if isinstance(checkpoint, dict) and "model" in checkpoint:
+            state_dict = checkpoint["model"]
+            log.info("Detected dictionary checkpoint format (key 'model' found).")
+        else:
+            state_dict = checkpoint
+            log.info("Detected direct state_dict checkpoint format.")
+
+        typed_state_dict = cast(dict[str, Any], state_dict)
+        adjusted_state_dict = _resize_backbone_pos_embed_if_needed(typed_state_dict, model)
+        missing_keys, unexpected_keys = model.load_state_dict(adjusted_state_dict, strict=False)
+
+        filtered_missing_keys = [key for key in missing_keys if key != "backbone.pos_embed"]
+        if filtered_missing_keys or unexpected_keys:
+            log.warning(
+                "Checkpoint loaded with missing/unexpected keys. missing=%s unexpected=%s",
+                filtered_missing_keys,
+                unexpected_keys,
+            )
+
+    except Exception as error:
+        log.error("Error loading state_dict: %s", error)
+        raise
+
+    model.eval()
+    torch.set_grad_enabled(False)
+
+    log.info("Model loaded and ready for inference.")
+    return model
+
+
+def _load_calibrators(calibrators_dir: Path, category_order: Sequence[str]) -> dict[str, dict[str, Any]]:
+    """
+    Load isotonic calibrators and their metadata from the specified directory.
+
+    This function attempts to load specific joblib models for each category
+    based on the mapping found in 'calibrators_meta.json'.
+
+    :param calibrators_dir: Path to the directory containing .joblib files and metadata.
+    :param category_order: Sequence of category names expected by the model.
+    :return: A dictionary mapping each category to its calibrator model or a fallback.
+
+    Example::
+        In: _load_calibrators(calibrators_dir, category_order)
+        Out: function result returned for provided inputs
+    """
+    meta_path = calibrators_dir / "calibrators_meta.json"
+    meta: dict[str, dict] = {}
+
+    # Attempt to load metadata that maps categories to specific files
+    if meta_path.exists():
+        try:
+            with open(meta_path, encoding="utf-8") as meta_file:
+                meta = json.load(meta_file)
+        except Exception as error:
+            log.warning("Failed to load calibration metadata: %s", error)
+
+    calibrators: dict[str, dict[str, Any]] = {}
+
+    for category_name in category_order:
+        entry = meta.get(category_name)
+
+        # Retrieve filename from metadata or construct a default based on the category name
+        file_name_any = entry.get("file") if entry else None
+        file_name = (
+            str(file_name_any)
+            if isinstance(file_name_any, str) and file_name_any.strip()
+            else f'calibrator_{category_name.replace(" ", "_")}.joblib'
+        )
+        calibrator_path = calibrators_dir / file_name
+
+        if calibrator_path.exists():
+            try:
+                # Load the isotonic regression model using joblib
+                calibrators[category_name] = {
+                    "type": "isotonic",
+                    "model": cast(Any, joblib.load(calibrator_path)),
+                }
+                log.debug("Loaded isotonic calibrator for %s", category_name)
+                continue
+            except Exception as error:
+                log.warning("Could not load calibrator file %s: %s", file_name, error)
+
+        # Set fallback if the file is missing or corrupted
+        calibrators[category_name] = {"type": "fallback"}
+
+    return calibrators
+
+
+def _apply_calibration(
+    raw_score_vector: np.ndarray,
+    calibrators: dict[str, dict[str, Any]],
+    category_order: Sequence[str],
+) -> dict[str, float]:
+    """
+    Apply category-specific calibration to raw model outputs.
+
+    Supported calibration types:
+      • pchip – monotonic cubic Hermite spline
+      • isotonic – isotonic regression model
+      • minmax – simple linear normalization
+      • fallback – heuristic scaling
+
+    :param raw_score_vector: Raw predictions for all categories (vector of length 6).
+    :param calibrators: Per-category calibrator configuration.
+    :return: Mapping category → calibrated probability in [0, 100].
+
+    Example::
+        In: _apply_calibration(raw_score_vector, calibrators, category_order)
+        Out: function result returned for provided inputs
+    """
+    calibrated_probabilities: dict[str, float] = {}
+
+    for index, category_name in enumerate(category_order):
+        calibrator_spec = calibrators.get(category_name, {"type": "fallback"})
+        raw_value = float(raw_score_vector[index])
+
+        # PCHIP interpolation
+        if calibrator_spec.get("type") == "pchip" and "model" in calibrator_spec:
+            pchip_model = calibrator_spec["model"]
+            calibrated_value = float(pchip_model(raw_value))
+            calibrated_probabilities[category_name] = float(np.clip(calibrated_value, 0.0, 100.0))
+
+        # Isotonic regression
+        elif calibrator_spec.get("type") == "isotonic" and "model" in calibrator_spec:
+            calibrated_probabilities[category_name] = float(calibrator_spec["model"].predict([raw_value])[0])
+
+        # Min–max normalization
+        elif calibrator_spec.get("type") == "minmax":
+            lower_bound = float(calibrator_spec["x_lo"])
+            upper_bound = float(calibrator_spec["x_hi"])
+
+            if upper_bound <= lower_bound:
+                # Invalid calibrator — fall back to neutral midpoint
+                calibrated_probabilities[category_name] = 50.0
+            else:
+                normalized_value = (raw_value - lower_bound) / (upper_bound - lower_bound)
+                calibrated_probabilities[category_name] = float(np.clip(100.0 * normalized_value, 0.0, 100.0))
+
+        # Fallback heuristic: crude linear scaling
+        else:
+            calibrated_probabilities[category_name] = float(np.clip(50.0 + 25.0 * raw_value, 0.0, 100.0))
+
+    return calibrated_probabilities
+
+
+def _iter_image_paths(images_dir: Path) -> list[Path]:
+    """
+    Gather all valid image paths from a directory.
+
+    Recognizes .jpg, .jpeg, .png in any capitalization.
+
+    :param images_dir: Directory containing images.
+    :return: Sorted list of path objects.
+
+    Example::
+        In: _iter_image_paths(images_dir)
+        Out: function result returned for provided inputs
+    """
+    valid_extensions = (".jpg", ".jpeg", ".png", ".JPG", ".JPEG", ".PNG")
+
+    log.debug("Scanning for images in: %s", images_dir)
+
+    return sorted([image_path for image_path in Path(images_dir).glob("*") if image_path.suffix in valid_extensions])
diff --git a/src/uq_desktop_processor/gui/__init__.py b/src/uq_desktop_processor/gui/__init__.py
new file mode 100644
index 0000000..f8eeecf
--- /dev/null
+++ b/src/uq_desktop_processor/gui/__init__.py
@@ -0,0 +1,41 @@
+"""
+GUI module:   init  .
+"""
+
+import ctypes
+import sys
+
+from PySide6.QtCore import Qt
+from PySide6.QtGui import QIcon
+from PySide6.QtWidgets import QApplication
+
+from .paths import APP_ICON_PATH
+from .platform.webengine import configure_webengine_for_deck_gl
+from .shell.explorer import UrbanQualityAIExplorer
+
+
+def main() -> int:
+    """
+    Run main.
+
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: main()
+        Out: UI/application state updated as intended.
+    """
+    configure_webengine_for_deck_gl()
+    if sys.platform == "win32":
+        ctypes.windll.shell32.SetCurrentProcessExplicitAppUserModelID("uq_desktop_processor.app")
+    QApplication.setAttribute(Qt.ApplicationAttribute.AA_ShareOpenGLContexts, True)
+    app = QApplication(sys.argv)
+    app.setStyle("Fusion")
+    app_icon = QIcon(str(APP_ICON_PATH))
+    app.setWindowIcon(app_icon)
+    gui = UrbanQualityAIExplorer()
+    gui.setWindowIcon(app_icon)
+    gui.show()
+    return app.exec()
+
+
+__all__ = ["main", "UrbanQualityAIExplorer"]
diff --git a/src/uq_desktop_processor/gui/map_view/__init__.py b/src/uq_desktop_processor/gui/map_view/__init__.py
new file mode 100644
index 0000000..b83e8ec
--- /dev/null
+++ b/src/uq_desktop_processor/gui/map_view/__init__.py
@@ -0,0 +1,5 @@
+"""
+GUI module:   init  .
+"""
+
+__all__: list[str] = []
diff --git a/src/uq_desktop_processor/gui/map_view/constants.py b/src/uq_desktop_processor/gui/map_view/constants.py
new file mode 100644
index 0000000..3d569cf
--- /dev/null
+++ b/src/uq_desktop_processor/gui/map_view/constants.py
@@ -0,0 +1,89 @@
+"""
+Map layer IDs, color palettes, and display limits for PyDeck-based map views.
+"""
+
+EULER_LINE_COLORS: list[list[int]] = [
+    [0, 242, 255],
+    [255, 0, 170],
+    [0, 255, 136],
+    [255, 214, 0],
+    [136, 86, 255],
+    [255, 128, 0],
+    [120, 220, 255],
+    [255, 80, 80],
+    [180, 255, 120],
+    [200, 120, 255],
+]
+
+# QListWidget: first row = drawn on top of the map (deck.gl last in stack).
+MAP_LAYER_IDS_TOP_FIRST: tuple[str, ...] = ("clip", "points", "euler", "roads")
+MAP_LAYER_LABELS: dict[str, str] = {
+    "roads": "Road network",
+    "points": "Sampling points",
+    "euler": "Euler routes (GPX)",
+    "clip": "Estimation results (avg)",
+}
+
+MAP_REDRAW_DEBOUNCE_MS = 48
+ROADS_MAP_SIMPLIFY_METERS_BASE = 12.0
+ROADS_MAP_MAX_FEATURES_BASE = 25000
+POINTS_MAP_MAX_BASE = 120_000
+EULER_VERTEX_BUDGET_BASE = 250_000
+
+# Read live camera before setHtml so toggling layers does not reset pan/zoom.
+DECK_VIEW_STATE_JS = r"""
+(function() {
+  try {
+    function normalizeVs(vs) {
+      if (!vs) return null;
+      if (vs.latitude != null && vs.longitude != null && vs.zoom != null) return vs;
+      return null;
+    }
+    function deepPickVs(obj, depth) {
+      if (!obj || depth > 6) return null;
+      var n = normalizeVs(obj);
+      if (n) return n;
+      if (typeof obj !== "object") return null;
+      var keys = Object.keys(obj);
+      for (var i = 0; i < keys.length; i++) {
+        var inner = obj[keys[i]];
+        var p = deepPickVs(inner, depth + 1);
+        if (p) return p;
+      }
+      return null;
+    }
+    var di = (typeof window.cityLensDeck !== "undefined") ? window.cityLensDeck : null;
+    if (!di) return null;
+    var root = di.deck || di;
+    var vs = normalizeVs(root.viewState);
+    if (!vs) vs = deepPickVs(root.viewState, 0);
+    if (!vs && root.viewManager) {
+      var m = root.viewManager;
+      vs = normalizeVs(m.viewState) || deepPickVs(m.viewState, 0);
+      if (!vs && m.viewStates) vs = deepPickVs(m.viewStates, 0);
+      if (!vs && m._viewports && m._viewports.length) {
+        var vp = m._viewports[0];
+        vs = normalizeVs(vp.viewState) || deepPickVs(vp.viewState, 0);
+        if (!vs && vp.viewport) vs = normalizeVs(vp.viewport) || deepPickVs(vp.viewport, 0);
+      }
+    }
+    if (!vs && typeof root.getViewports === "function") {
+      try {
+        var vps = root.getViewports(root.width && root.height ? [0, 0, root.width, root.height] : undefined);
+        if (vps && vps.length) {
+          var vp0 = vps[0];
+          vs = normalizeVs(vp0) || deepPickVs(vp0, 0);
+        }
+      } catch (e2) {}
+    }
+    if (!vs || vs.latitude == null || vs.longitude == null || vs.zoom == null) return null;
+    return JSON.stringify({
+      latitude: vs.latitude,
+      longitude: vs.longitude,
+      zoom: vs.zoom,
+      pitch: vs.pitch != null ? vs.pitch : 0,
+      bearing: vs.bearing != null ? vs.bearing : 0
+    });
+  } catch (e) { return null; }
+})()
+"""
diff --git a/src/uq_desktop_processor/gui/map_view/data.py b/src/uq_desktop_processor/gui/map_view/data.py
new file mode 100644
index 0000000..9a45a30
--- /dev/null
+++ b/src/uq_desktop_processor/gui/map_view/data.py
@@ -0,0 +1,176 @@
+"""
+Builds numpy/PyDeck-friendly data from GeoJSON, sampling points, and evaluation results.
+"""
+
+import math
+from typing import Any
+
+import geopandas as gpd
+import numpy as np
+import pydeck as pdk
+
+from uq_desktop_processor.gui.map_view.constants import (
+    EULER_VERTEX_BUDGET_BASE,
+    POINTS_MAP_MAX_BASE,
+    ROADS_MAP_MAX_FEATURES_BASE,
+    ROADS_MAP_SIMPLIFY_METERS_BASE,
+)
+from uq_desktop_processor.layer_creation.vector_layers.point_layer.utils import parse_lat_lon
+
+
+def evaluation_scatter_data(results: dict[str, Any]) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+    """
+    Run evaluation scatter data.
+
+    :param results: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: evaluation_scatter_data(results)
+        Out: UI/application state updated as intended.
+    """
+    xs: list[float] = []
+    ys: list[float] = []
+    scores: list[float] = []
+    for image_result in results.get("images") or []:
+        image_path = image_result.get("image_path") or ""
+        try:
+            if not image_path:
+                raise ValueError("Missing image_path in evaluation record.")
+            lat, lon = parse_lat_lon(image_path)
+        except (ValueError, IndexError):
+            continue
+        xs.append(lon)
+        ys.append(lat)
+        scores.append(float(image_result.get("overall_pct") or 0.0))
+    if not xs:
+        return np.array([]), np.array([]), np.array([])
+    return np.array(xs), np.array(ys), np.array(scores)
+
+
+def fit_view_state(lons: list[float], lats: list[float]) -> pdk.ViewState:
+    """
+    Run fit view state.
+
+    :param lons: See caller/context.
+    :param lats: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: fit_view_state(lons, lats)
+        Out: UI/application state updated as intended.
+    """
+    if not lons or not lats:
+        return pdk.ViewState(latitude=50.0, longitude=19.0, zoom=4, pitch=0, bearing=0)
+    lo, hi = min(lons), max(lons)
+    la_lo, la_hi = min(lats), max(lats)
+    span = max(hi - lo, la_hi - la_lo, 1e-6)
+    pad = 0.08 * span
+    lo, hi = lo - pad, hi + pad
+    la_lo, la_hi = la_lo - pad, la_hi + pad
+    center_lon = (lo + hi) / 2
+    center_lat = (la_lo + la_hi) / 2
+    lon_span = max(hi - lo, 1e-6)
+    zoom = math.log2(360 / lon_span) - 0.75
+    zoom = max(2.0, min(17.0, zoom))
+    return pdk.ViewState(
+        latitude=float(center_lat),
+        longitude=float(center_lon),
+        zoom=float(zoom),
+        pitch=0,
+        bearing=0,
+    )
+
+
+def red_yellow_green_rgba(scores: np.ndarray) -> list[list[int]]:
+    """
+    Run red yellow green rgba.
+
+    :param scores: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: red_yellow_green_rgba(scores)
+        Out: UI/application state updated as intended.
+    """
+    if scores.size == 0:
+        return []
+    vmin, vmax = float(np.min(scores)), float(np.max(scores))
+    if vmax <= vmin:
+        vmin -= 1.0
+        vmax += 1.0
+    colors_rgba: list[list[int]] = []
+    for score_value in scores:
+        normalized_score = (float(score_value) - vmin) / (vmax - vmin)
+        normalized_score = max(0.0, min(1.0, normalized_score))
+        if normalized_score <= 0.5:
+            blend_factor = normalized_score / 0.5
+            red_channel, green_channel, blue_channel = 255, int(255 * blend_factor), 0
+        else:
+            blend_factor = (normalized_score - 0.5) / 0.5
+            red_channel, green_channel, blue_channel = int(255 * (1.0 - blend_factor)), 255, 0
+        colors_rgba.append([int(red_channel), int(green_channel), int(blue_channel), 220])
+    return colors_rgba
+
+
+def simplify_roads_gdf_for_map_display(
+    roads_gdf: gpd.GeoDataFrame,
+    *,
+    simplify_meters: float,
+    max_features: int,
+) -> gpd.GeoDataFrame:
+    """Reduce vertex / feature count for GeoJsonLayer (display only; pipeline keeps full geometry)."""
+    if roads_gdf.empty:
+        return roads_gdf
+    projected_roads_gdf = roads_gdf.to_crs(3857)
+    simplified_geometry = projected_roads_gdf.geometry.simplify(simplify_meters, preserve_topology=True)
+    display_roads_gdf = gpd.GeoDataFrame(geometry=simplified_geometry, crs=projected_roads_gdf.crs)
+    display_roads_gdf = display_roads_gdf[~display_roads_gdf.geometry.is_empty & display_roads_gdf.geometry.notna()]
+    display_roads_gdf = display_roads_gdf.to_crs(4326)
+    feature_count = len(display_roads_gdf)
+    cap = max(500, int(max_features))
+    if feature_count > cap:
+        step = max(1, math.ceil(feature_count / cap))
+        display_roads_gdf = display_roads_gdf.iloc[::step].copy()
+    return display_roads_gdf
+
+
+def map_display_budgets(n_visible_layers: int) -> dict[str, float | int]:
+    """
+    When several deck.gl layers are visible, total attribute + index data grows quickly.
+    Qt WebEngine (often SwiftShader) can hit GPU memory or inline-JSON practical limits; scale caps with n.
+    """
+    visible_layer_count = max(1, n_visible_layers)
+    scale_divisor = math.sqrt(float(visible_layer_count))
+    road_max = max(4000, int(ROADS_MAP_MAX_FEATURES_BASE / scale_divisor))
+    road_simplify = ROADS_MAP_SIMPLIFY_METERS_BASE * (1.0 + 0.35 * (visible_layer_count - 1))
+    points_max = max(8000, int(POINTS_MAP_MAX_BASE / scale_divisor))
+    euler_vertices = max(40_000, int(EULER_VERTEX_BUDGET_BASE / scale_divisor))
+    return {
+        "road_max_features": road_max,
+        "road_simplify_meters": road_simplify,
+        "points_max": points_max,
+        "euler_vertex_budget": euler_vertices,
+    }
+
+
+def euler_polylines_for_display(
+    polylines: list[list[tuple[float, float]]],
+    vertex_budget: int,
+) -> list[list[tuple[float, float]]]:
+    """Same length as input so sector index / colors stay aligned with the original route list."""
+    total_vertex_count = sum(len(polyline) for polyline in polylines if len(polyline) >= 2)
+    if total_vertex_count <= vertex_budget:
+        return [list(polyline) for polyline in polylines]
+    display_polylines: list[list[tuple[float, float]]] = []
+    for polyline in polylines:
+        if len(polyline) < 2:
+            display_polylines.append(list(polyline))
+            continue
+        vertex_share = max(2, int(vertex_budget * len(polyline) / total_vertex_count))
+        if len(polyline) <= vertex_share:
+            display_polylines.append(list(polyline))
+        else:
+            sampled_indices = np.linspace(0, len(polyline) - 1, vertex_share).astype(int)
+            display_polylines.append([polyline[int(vertex_index)] for vertex_index in sampled_indices])
+    return display_polylines
diff --git a/src/uq_desktop_processor/gui/map_view/geo.py b/src/uq_desktop_processor/gui/map_view/geo.py
new file mode 100644
index 0000000..9bf67a8
--- /dev/null
+++ b/src/uq_desktop_processor/gui/map_view/geo.py
@@ -0,0 +1,20 @@
+"""
+Geographic helpers: bounds fitting, coordinate transforms, and map viewport math.
+"""
+
+from pyproj import Geod
+
+_GEO_WGS84 = Geod(ellps="WGS84")
+
+
+def polyline_geodesic_length_m(poly: tuple[tuple[float, float], ...]) -> float:
+    """Sum of geodesic segment lengths for a (lon, lat) polyline in WGS84."""
+    if len(poly) < 2:
+        return 0.0
+    total = 0.0
+    for i in range(len(poly) - 1):
+        lon1, lat1 = poly[i]
+        lon2, lat2 = poly[i + 1]
+        _, _, dist_m = _GEO_WGS84.inv(lon1, lat1, lon2, lat2)
+        total += abs(dist_m)
+    return total
diff --git a/src/uq_desktop_processor/gui/map_view/html.py b/src/uq_desktop_processor/gui/map_view/html.py
new file mode 100644
index 0000000..61c2b03
--- /dev/null
+++ b/src/uq_desktop_processor/gui/map_view/html.py
@@ -0,0 +1,84 @@
+"""
+HTML templates and embedding glue for standalone or Qt-embedded map pages.
+"""
+
+import json
+import logging
+import re
+
+from PySide6.QtCore import QJsonValue
+
+
+def sanitize_pydeck_inline_json_html(deck_html: str) -> str:
+    """
+    Escape ``</script>`` sequences inside the deck JSON block so Chromium does not
+    terminate the script tag early (e.g. OSM tags in string data).
+    """
+    marker = "const jsonInput = "
+    if marker not in deck_html:
+        return deck_html
+
+    parts = deck_html.split(marker)
+    if len(parts) < 2:
+        return deck_html
+
+    json_and_rest = parts[1].split("</script>", 1)
+    if len(json_and_rest) < 2:
+        return deck_html
+
+    json_content = json_and_rest[0]
+    rest_of_page = json_and_rest[1]
+
+    safe_json = re.sub(r"</script", r"<\\/script", json_content, flags=re.IGNORECASE)
+
+    return parts[0] + marker + safe_json + "</script>" + rest_of_page
+
+
+def expose_deck_instance_on_window(deck_html: str) -> str:
+    """Make the deck wrapper reachable from ``runJavaScript`` (``const`` is not a window property)."""
+    needle = "const deckInstance = createDeck("
+    if needle in deck_html:
+        return deck_html.replace(needle, "window.cityLensDeck = createDeck(", 1)
+    logging.getLogger(__name__).warning(
+        "pydeck HTML has no expected deckInstance line; map view may not preserve pan/zoom on layer toggles."
+    )
+    return deck_html
+
+
+def inject_mapbox_gl_css(deck_html: str) -> str:
+    """Pydeck template loads mapbox-gl.js but not mapbox-gl.css; add it to silence warnings / layout glitches."""
+    if "mapbox-gl.css" in deck_html:
+        return deck_html
+    marker = "mapbox-gl-js/v1.13.0/mapbox-gl.js"
+    script_marker_index = deck_html.find(marker)
+    if script_marker_index < 0:
+        return deck_html
+    script_close_index = deck_html.find("</script>", script_marker_index)
+    if script_close_index < 0:
+        return deck_html
+    script_close_index += len("</script>")
+    link = '\n    <link rel="stylesheet" ' 'href="https://api.tiles.mapbox.com/mapbox-gl-js/v1.13.0/mapbox-gl.css" />'
+    return deck_html[:script_close_index] + link + deck_html[script_close_index:]
+
+
+def coerce_webengine_js_json(result: object) -> object:
+    """QWebEnginePage.runJavaScript often delivers a QJsonValue; normalize to Python types."""
+    if isinstance(result, QJsonValue):
+        if result.isNull() or result.isUndefined():
+            return None
+        return result.toVariant()
+    return result
+
+
+def parse_view_state_json(result: object) -> dict[str, object] | None:
+    """Parse JS-returned view state string/dict into a plain dict."""
+    result = coerce_webengine_js_json(result)
+    if isinstance(result, str) and result.strip() not in ("", "null", "undefined"):
+        try:
+            parsed = json.loads(result)
+            return parsed if isinstance(parsed, dict) else None
+        except json.JSONDecodeError:
+            return None
+    if isinstance(result, dict):
+        return result
+    return None
diff --git a/src/uq_desktop_processor/gui/paths.py b/src/uq_desktop_processor/gui/paths.py
new file mode 100644
index 0000000..b9fce87
--- /dev/null
+++ b/src/uq_desktop_processor/gui/paths.py
@@ -0,0 +1,11 @@
+"""
+Shared GUI filesystem paths.
+"""
+
+from pathlib import Path
+
+PROJECT_ROOT = Path(__file__).resolve().parents[3]
+PACKAGE_ROOT = Path(__file__).resolve().parents[1]
+APP_ICON_PATH = PACKAGE_ROOT / "assets" / "img" / "icon.ico"
+
+__all__ = ["PROJECT_ROOT", "PACKAGE_ROOT", "APP_ICON_PATH"]
diff --git a/src/uq_desktop_processor/gui/platform/__init__.py b/src/uq_desktop_processor/gui/platform/__init__.py
new file mode 100644
index 0000000..55e0255
--- /dev/null
+++ b/src/uq_desktop_processor/gui/platform/__init__.py
@@ -0,0 +1,7 @@
+"""
+GUI module:   init  .
+"""
+
+from .webengine import configure_webengine_for_deck_gl
+
+__all__ = ["configure_webengine_for_deck_gl"]
diff --git a/src/uq_desktop_processor/gui/platform/webengine.py b/src/uq_desktop_processor/gui/platform/webengine.py
new file mode 100644
index 0000000..f3d8550
--- /dev/null
+++ b/src/uq_desktop_processor/gui/platform/webengine.py
@@ -0,0 +1,37 @@
+"""
+Qt WebEngine profile and view helpers for embedding maps and web content.
+"""
+
+import logging
+import os
+import sys
+
+
+def configure_webengine_for_deck_gl() -> None:
+    """
+    deck.gl needs a working **WebGL** context. ``--disable-gpu`` turns WebGL off entirely
+    (GL_RENDERER = Disabled), so the map cannot start.
+
+    On Windows, native ANGLE/D3D11 can hit DXGI_ERROR_DEVICE_REMOVED; the stable default is
+    **SwiftShader** (CPU WebGL via ``--use-angle=swiftshader``).
+
+    If ``QTWEBENGINE_CHROMIUM_FLAGS`` is already set, it is left unchanged.
+
+    ``CITYLENS_WEBENGINE_USE_GPU=1``: try native GPU with light sandbox mitigations only.
+    """
+    if os.environ.get("QTWEBENGINE_CHROMIUM_FLAGS", "").strip():
+        return
+    if sys.platform != "win32":
+        return
+    log = logging.getLogger(__name__)
+    if os.environ.get("CITYLENS_WEBENGINE_USE_GPU", "").lower() in ("1", "true", "yes"):
+        os.environ["QTWEBENGINE_CHROMIUM_FLAGS"] = "--disable-gpu-sandbox --ignore-gpu-blocklist"
+        log.info(
+            "Qt WebEngine: native GPU (no SwiftShader). If the map crashes, unset "
+            "CITYLENS_WEBENGINE_USE_GPU or set flags manually via QTWEBENGINE_CHROMIUM_FLAGS."
+        )
+        return
+    os.environ["QTWEBENGINE_CHROMIUM_FLAGS"] = (
+        "--use-angle=swiftshader " "--enable-unsafe-swiftshader " "--disable-gpu-sandbox " "--ignore-gpu-blocklist"
+    )
+    log.info("Qt WebEngine: SwiftShader (CPU WebGL) for deck.gl. For native GPU: " "set CITYLENS_WEBENGINE_USE_GPU=1")
diff --git a/src/uq_desktop_processor/gui/shell/__init__.py b/src/uq_desktop_processor/gui/shell/__init__.py
new file mode 100644
index 0000000..261d6ad
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/__init__.py
@@ -0,0 +1,7 @@
+"""
+GUI module:   init  .
+"""
+
+from .explorer import UrbanQualityAIExplorer
+
+__all__ = ["UrbanQualityAIExplorer"]
diff --git a/src/uq_desktop_processor/gui/shell/constants.py b/src/uq_desktop_processor/gui/shell/constants.py
new file mode 100644
index 0000000..1f2c28c
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/constants.py
@@ -0,0 +1,24 @@
+"""
+Shell-wide UI constants: titles, spacing keys, and shared resource identifiers.
+"""
+
+CLIP_MODEL_CHOICES: list[tuple[str, tuple[str, ...]]] = [
+    ("ViT-L/14 @336px", ("ViT-L/14@336px",)),
+    ("ViT-L/14", ("ViT-L/14",)),
+    ("ViT-B/32", ("ViT-B/32",)),
+    ("ViT-B/16", ("ViT-B/16",)),
+]
+
+# Combo userData order must match stacked pages in route/planner input stacks.
+SOURCE_INPUT_STACK_PAGE_ORDER: tuple[str, ...] = ("place", "region", "roads")
+
+EULER_SOURCE_FIELD_LABELS: dict[str, str] = {
+    "place": "City / place",
+    "region": "Region file",
+    "roads": "Roads file",
+}
+PLANNER_SOURCE_FIELD_LABELS: dict[str, str] = {
+    "place": "Target city / place",
+    "region": "Region file",
+    "roads": "Roads file",
+}
diff --git a/src/uq_desktop_processor/gui/shell/explorer/__init__.py b/src/uq_desktop_processor/gui/shell/explorer/__init__.py
new file mode 100644
index 0000000..d41c744
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/explorer/__init__.py
@@ -0,0 +1,7 @@
+"""
+GUI module:   init  .
+"""
+
+from .window import UrbanQualityAIExplorer
+
+__all__ = ["UrbanQualityAIExplorer"]
diff --git a/src/uq_desktop_processor/gui/shell/explorer/console.py b/src/uq_desktop_processor/gui/shell/explorer/console.py
new file mode 100644
index 0000000..236bfbd
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/explorer/console.py
@@ -0,0 +1,54 @@
+"""
+Embedded console widget for the explorer window (command/output surface).
+"""
+
+from typing import Protocol
+
+from PySide6.QtGui import QTextCursor
+from PySide6.QtWidgets import QTextEdit
+
+
+class ConsoleSupported(Protocol):
+    """
+    ConsoleSupported UI helper class.
+    """
+
+    console: QTextEdit
+    metrics_text: QTextEdit
+
+
+class ConsoleMixin:
+    """
+    ConsoleMixin UI helper class.
+    """
+
+    def _append_console(self: ConsoleSupported, line: str) -> None:
+        """
+        Run  append console.
+
+        :param line: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _append_console(line)
+            Out: UI/application state updated as intended.
+        """
+        self.console.append(line.rstrip())
+
+    def _append_data_science_section(self: ConsoleSupported, title: str, lines: list[str]) -> None:
+        """
+        Run  append data science section.
+
+        :param title: See caller/context.
+        :param lines: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _append_data_science_section(title, lines)
+            Out: UI/application state updated as intended.
+        """
+        current = self.metrics_text.toPlainText().rstrip()
+        sep = "\n\n" + "─" * 44 + "\n\n" if current else ""
+        body = "\n".join(lines)
+        self.metrics_text.setPlainText(f"{current}{sep}{title}\n{body}")
+        self.metrics_text.moveCursor(QTextCursor.MoveOperation.End)
diff --git a/src/uq_desktop_processor/gui/shell/explorer/dialogs.py b/src/uq_desktop_processor/gui/shell/explorer/dialogs.py
new file mode 100644
index 0000000..1f25c83
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/explorer/dialogs.py
@@ -0,0 +1,86 @@
+"""
+Modal dialogs for the explorer: paths, confirmations, and configuration prompts.
+"""
+
+from PySide6.QtWidgets import QFileDialog, QLineEdit, QWidget
+
+
+class DialogsMixin:
+    """
+    DialogsMixin UI helper class.
+    """
+
+    def pick_file(self, target: QLineEdit, filt: str) -> None:
+        """
+        Run pick file.
+
+        :param target: See caller/context.
+        :param filt: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: pick_file(target, filt)
+            Out: UI/application state updated as intended.
+        """
+        parent_widget: QWidget | None = self if isinstance(self, QWidget) else None
+        path, _ = QFileDialog.getOpenFileName(parent_widget, "Select file", "", filt)
+        if path:
+            target.setText(path)
+
+    def pick_folder(self, target: QLineEdit) -> None:
+        """
+        Run pick folder.
+
+        :param target: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: pick_folder(target)
+            Out: UI/application state updated as intended.
+        """
+        parent_widget: QWidget | None = self if isinstance(self, QWidget) else None
+        path = QFileDialog.getExistingDirectory(parent_widget, "Select folder")
+        if path:
+            target.setText(path)
+
+    def pick_save_points_layer(self, target: QLineEdit) -> None:
+        """
+        Run pick save points layer.
+
+        :param target: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: pick_save_points_layer(target)
+            Out: UI/application state updated as intended.
+        """
+        parent_widget: QWidget | None = self if isinstance(self, QWidget) else None
+        path, _ = QFileDialog.getSaveFileName(
+            parent_widget,
+            "Save point layer",
+            target.text() or "sampling_points.geojson",
+            "GeoJSON (*.geojson);;GeoPackage (*.gpkg)",
+        )
+        if path:
+            target.setText(path)
+
+    def pick_save_gpkg(self, target: QLineEdit) -> None:
+        """
+        Run pick save gpkg.
+
+        :param target: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: pick_save_gpkg(target)
+            Out: UI/application state updated as intended.
+        """
+        parent_widget: QWidget | None = self if isinstance(self, QWidget) else None
+        path, _ = QFileDialog.getSaveFileName(
+            parent_widget,
+            "Save GeoPackage layer",
+            target.text() or "vit_finetuned_scores.gpkg",
+            "GeoPackage (*.gpkg)",
+        )
+        if path:
+            target.setText(path)
diff --git a/src/uq_desktop_processor/gui/shell/explorer/modules.py b/src/uq_desktop_processor/gui/shell/explorer/modules.py
new file mode 100644
index 0000000..f73eac4
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/explorer/modules.py
@@ -0,0 +1,46 @@
+"""
+Registers explorer tool modules and exposes metadata for the sidebar.
+"""
+
+from PySide6.QtWidgets import QButtonGroup, QSplitter, QStackedWidget, QWidget
+
+
+class ModulesMixin:
+    """
+    ModulesMixin UI helper class.
+    """
+
+    tool_container: QWidget
+    button_group: QButtonGroup
+    stacked_tools: QStackedWidget
+    main_splitter: QSplitter
+    current_active_module: int
+
+    def toggle_module_panel(self, index: int) -> None:
+        """
+        Run toggle module panel.
+
+        :param index: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: toggle_module_panel(index)
+            Out: UI/application state updated as intended.
+        """
+        is_visible = self.tool_container.isVisible()
+
+        if is_visible and self.current_active_module == index:
+            self.tool_container.setVisible(False)
+            self.button_group.setExclusive(False)
+            self.button_group.button(index).setChecked(False)
+            self.button_group.setExclusive(True)
+            self.current_active_module = -1
+        else:
+            self.stacked_tools.setCurrentIndex(index)
+            self.tool_container.setVisible(True)
+
+            sizes = self.main_splitter.sizes()
+            if sizes and sizes[0] < 50:
+                self.main_splitter.setSizes([320, 800, 320])
+
+            self.current_active_module = index
diff --git a/src/uq_desktop_processor/gui/shell/explorer/pipeline.py b/src/uq_desktop_processor/gui/shell/explorer/pipeline.py
new file mode 100644
index 0000000..c190748
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/explorer/pipeline.py
@@ -0,0 +1,478 @@
+"""
+Connects pipeline execution and progress signals to the explorer UI.
+"""
+
+import logging
+import os
+from collections.abc import Callable, Iterable
+from pathlib import Path
+from typing import TYPE_CHECKING, Any
+
+from PySide6.QtCore import QTimer
+from PySide6.QtWidgets import (
+    QCheckBox,
+    QComboBox,
+    QDoubleSpinBox,
+    QLineEdit,
+    QPlainTextEdit,
+    QProgressBar,
+    QPushButton,
+    QSlider,
+    QSpinBox,
+    QWidget,
+)
+
+from uq_desktop_processor.evaluation.clip_prefilter.defaults import FILTER_PROMPTS as CLIP_PREFILTER_DEFAULT_PROMPTS
+from uq_desktop_processor.gui.shell.formatters import (
+    format_download_summary,
+    format_euler_routes_summary,
+    format_prefilter_summary,
+    format_vit_summary,
+)
+from uq_desktop_processor.gui.shell.worker import StepThread
+from uq_desktop_processor.street_view_analysis import EulerRoutesResult, generate_clean_routes
+
+if TYPE_CHECKING:
+    Base = QWidget
+else:
+    Base = object
+
+
+class PipelineMixin(Base):
+    """
+    PipelineMixin UI helper class.
+    """
+
+    prefilter_pos_edit: QPlainTextEdit
+    prefilter_neg_edit: QPlainTextEdit
+    model_combo: QComboBox
+    planner_source_combo: QComboBox
+    place_name_edit: QLineEdit
+    region_path_edit: QLineEdit
+    road_path_edit: QLineEdit
+    spacing_edit: QLineEdit
+    min_dist_edit: QLineEdit
+    planner_points_out_edit: QLineEdit
+    token_edit: QLineEdit
+    mapillary_points_edit: QLineEdit
+    mapillary_out_edit: QLineEdit
+    radius_edit: QLineEdit
+    workers_spin: QSpinBox
+    device_combo: QComboBox
+    prefilter_image_folder_edit: QLineEdit
+    prefilter_rejected_edit: QLineEdit
+    threshold_slider: QSlider
+    beta_spin: QDoubleSpinBox
+    vit_images_dir_edit: QLineEdit
+    vit_model_path_edit: QLineEdit
+    vit_calibrators_edit: QLineEdit
+    vit_output_path_edit: QLineEdit
+    vit_output_layer_name_edit: QLineEdit
+    vit_model_name_edit: QLineEdit
+    vit_image_size_spin: QSpinBox
+    vit_batch_size_spin: QSpinBox
+    vit_device_combo: QComboBox
+    progress_bar: QProgressBar
+    run_buttons: Iterable[QPushButton]
+    route_source_combo: QComboBox
+    route_grid_cols: QSpinBox
+    route_grid_rows: QSpinBox
+    route_out_edit: QLineEdit
+    route_consolidate_tol: QDoubleSpinBox
+    route_cache_check: QCheckBox
+    route_city_edit: QLineEdit
+    route_region_path_edit: QLineEdit
+    route_roads_path_edit: QLineEdit
+
+    pipeline: Any
+    map_canvas: Any
+    _worker: StepThread | None
+    _last_euler_result: EulerRoutesResult | None
+
+    def _append_data_science_section(self, title: str, lines: list[str]) -> None:
+        """
+        Run  append data science section.
+
+        :param title: See caller/context.
+        :param lines: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _append_data_science_section(title, lines)
+            Out: UI/application state updated as intended.
+        """
+        pass
+
+    def reset_clip_prefilter_prompts(self) -> None:
+        """
+        Run reset clip prefilter prompts.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: reset_clip_prefilter_prompts()
+            Out: UI/application state updated as intended.
+        """
+        self.prefilter_pos_edit.setPlainText("\n".join(CLIP_PREFILTER_DEFAULT_PROMPTS["pos"]))
+        self.prefilter_neg_edit.setPlainText("\n".join(CLIP_PREFILTER_DEFAULT_PROMPTS["neg"]))
+
+    def _apply_config_from_ui(self) -> None:
+        """
+        Run  apply config from ui.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _apply_config_from_ui()
+            Out: UI/application state updated as intended.
+        """
+        model_tuple = self.model_combo.currentData()
+        if not isinstance(model_tuple, tuple):
+            # Keep a valid fallback if combo-box payload is malformed.
+            model_tuple = ("ViT-L/14@336px",)
+
+        # Snapshot all controls into pipeline config before launching any step.
+        self.pipeline.update_config(
+            {
+                "planner_source": self.planner_source_combo.currentData(),
+                "place_name": self.place_name_edit.text().strip(),
+                "region_geojson_path": self.region_path_edit.text().strip(),
+                "road_geojson_path": self.road_path_edit.text().strip(),
+                "spacing": float(self.spacing_edit.text() or "100"),
+                "min_distance": float(self.min_dist_edit.text() or "50"),
+                "points_layer_path": self.planner_points_out_edit.text().strip(),
+                "mapillary_token": self.token_edit.text().strip() or os.environ.get("MAPILLARY_ACCESS_TOKEN", ""),
+                "mapillary_points_path": self.mapillary_points_edit.text().strip(),
+                "mapillary_images_output_dir": self.mapillary_out_edit.text().strip(),
+                "search_radius": float(self.radius_edit.text() or "150"),
+                "mapillary_max_workers": int(self.workers_spin.value()),
+                "clip_model_names": model_tuple,
+                "torch_device": self.device_combo.currentData(),
+                "prefilter_image_folder": self.prefilter_image_folder_edit.text().strip(),
+                "prefilter_rejected_folder": self.prefilter_rejected_edit.text().strip(),
+                "prefilter_pos_prompts": self.prefilter_pos_edit.toPlainText(),
+                "prefilter_neg_prompts": self.prefilter_neg_edit.toPlainText(),
+                "filter_threshold": float(self.threshold_slider.value()),
+                "beta_sigmoid": float(self.beta_spin.value()),
+                "vit_images_dir": self.vit_images_dir_edit.text().strip(),
+                "vit_model_path": self.vit_model_path_edit.text().strip(),
+                "vit_calibrators_dir": self.vit_calibrators_edit.text().strip(),
+                "vit_output_layer_path": self.vit_output_path_edit.text().strip(),
+                "vit_output_layer_name": self.vit_output_layer_name_edit.text().strip(),
+                "vit_model_name": self.vit_model_name_edit.text().strip(),
+                "vit_image_size": int(self.vit_image_size_spin.value()),
+                "vit_batch_size": int(self.vit_batch_size_spin.value()),
+                "vit_torch_device": self.vit_device_combo.currentData(),
+            }
+        )
+        self.pipeline.base_dir = Path(self.pipeline.config["base_dir"])
+        image_output_dir = (self.pipeline.config.get("mapillary_images_output_dir") or "").strip()
+        if image_output_dir:
+            self.pipeline.raw_dir = Path(image_output_dir).expanduser().resolve()
+        else:
+            # Planner default output lives under base_dir/images/raw.
+            self.pipeline.raw_dir = self.pipeline.base_dir / "images" / "raw"
+        self.pipeline.rejected_dir = self.pipeline.base_dir / "images" / "rejected"
+        self.pipeline.results_dir = self.pipeline.base_dir / "results"
+        self.pipeline.ensure_directories()
+
+    def _set_busy(self, busy: bool) -> None:
+        """
+        Run  set busy.
+
+        :param busy: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _set_busy(busy)
+            Out: UI/application state updated as intended.
+        """
+        self.progress_bar.setRange(0, 0 if busy else 100)
+        if not busy:
+            self.progress_bar.setValue(0)
+        for run_button in self.run_buttons:
+            run_button.setDisabled(busy)
+
+    def _run_async(self, task_fn: Callable[[], Any], on_ok: Callable[[Any], None] | None = None) -> None:
+        """
+        Run  run async.
+
+        :param task_fn: See caller/context.
+        :param on_ok: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _run_async(task_fn, on_ok)
+            Out: UI/application state updated as intended.
+        """
+        if self._worker is not None and self._worker.isRunning():
+            logging.getLogger(__name__).warning("An operation is already running.")
+            return
+        self._apply_config_from_ui()
+        self._set_busy(True)
+
+        self._worker = StepThread(task_fn, self)
+
+        def _done(result: Any, error_message: str) -> None:
+            """
+            Run  done.
+
+            :param result: See caller/context.
+            :param error_message: See caller/context.
+            :return: Result of this step or updated UI/application state.
+
+            Example::
+                In: _done(result, error_message)
+                Out: UI/application state updated as intended.
+            """
+            self._set_busy(False)
+            if error_message:
+                logging.getLogger(__name__).error("Worker thread: %s", error_message)
+            elif on_ok is not None:
+                # Marshal callbacks back onto the GUI event loop.
+                QTimer.singleShot(0, lambda: on_ok(result))
+            self._worker = None
+
+        self._worker.finished.connect(_done)
+        self._worker.start()
+
+    def _refresh_map_after_points(self) -> None:
+        """
+        Run  refresh map after points.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _refresh_map_after_points()
+            Out: UI/application state updated as intended.
+        """
+        self.map_canvas.update_planner_layers(self.pipeline.roads_gdf, self.pipeline.points)
+
+    def _refresh_map_after_eval(self) -> None:
+        """
+        Run  refresh map after eval.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _refresh_map_after_eval()
+            Out: UI/application state updated as intended.
+        """
+        self.map_canvas.update_eval_layer(self.pipeline.roads_gdf, self.pipeline.evaluation_results)
+        evaluation_results = self.pipeline.evaluation_results
+        if evaluation_results:
+            self._append_data_science_section(
+                "ViT scoring (fine-tuned)",
+                format_vit_summary(
+                    evaluation_results,
+                    pipeline_config=self.pipeline.config,
+                    default_results_dir=self.pipeline.results_dir,
+                ),
+            )
+
+    def _on_sampling_points_done(self, count: Any) -> None:
+        """
+        Run  on sampling points done.
+
+        :param count: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _on_sampling_points_done(count)
+            Out: UI/application state updated as intended.
+        """
+        self._refresh_map_after_points()
+        out = (self.pipeline.config.get("points_layer_path") or "").strip()
+        path_disp = str(Path(out).resolve()) if out else "(unknown)"
+        generated_count = int(count) if count is not None else 0
+        self._append_data_science_section(
+            "Sampling points",
+            [
+                f"Generated points: {generated_count}",
+                f"Output path: {path_disp}",
+            ],
+        )
+
+    def on_run_planner(self) -> None:
+        """
+        Run on run planner.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: on_run_planner()
+            Out: UI/application state updated as intended.
+        """
+        self._run_async(
+            self.pipeline.step_1_generate_points,
+            on_ok=self._on_sampling_points_done,
+        )
+
+    def _on_download_done(self, stats: Any) -> None:
+        """
+        Run  on download done.
+
+        :param stats: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _on_download_done(stats)
+            Out: UI/application state updated as intended.
+        """
+        self._refresh_map_after_points()
+        if isinstance(stats, dict):
+            self._append_data_science_section("Mapillary download", format_download_summary(stats))
+
+    def on_run_download(self) -> None:
+        """
+        Run on run download.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: on_run_download()
+            Out: UI/application state updated as intended.
+        """
+        self._run_async(
+            self.pipeline.step_2_download_images,
+            on_ok=self._on_download_done,
+        )
+
+    def _on_prefilter_done(self, stats: Any) -> None:
+        """
+        Run  on prefilter done.
+
+        :param stats: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _on_prefilter_done(stats)
+            Out: UI/application state updated as intended.
+        """
+        self._refresh_map_after_points()
+        if isinstance(stats, dict):
+            self._append_data_science_section("CLIP prefilter", format_prefilter_summary(stats))
+
+    def on_run_prefilter(self) -> None:
+        """
+        Run on run prefilter.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: on_run_prefilter()
+            Out: UI/application state updated as intended.
+        """
+        self._run_async(
+            self.pipeline.step_3_prefilter,
+            on_ok=self._on_prefilter_done,
+        )
+
+    def on_run_vit_evaluate(self) -> None:
+        """
+        Run on run vit evaluate.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: on_run_vit_evaluate()
+            Out: UI/application state updated as intended.
+        """
+        self._run_async(
+            self.pipeline.step_6_evaluate_vit,
+            on_ok=lambda _result: self._refresh_map_after_eval(),
+        )
+
+    @staticmethod
+    def on_run_export(_checked: bool = False) -> None:
+        """
+        Run on run export.
+
+        :param _checked: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: on_run_export(_checked)
+            Out: UI/application state updated as intended.
+        """
+        logging.getLogger(__name__).warning("Export UI is not enabled yet. This tab is intentionally empty for now.")
+
+    def on_run_euler_routes(self) -> None:
+        """
+        Run on run euler routes.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: on_run_euler_routes()
+            Out: UI/application state updated as intended.
+        """
+        route_source = self.route_source_combo.currentData()
+        kwargs: dict[str, Any] = {
+            "grid_size": (int(self.route_grid_cols.value()), int(self.route_grid_rows.value())),
+            "output_dir": self.route_out_edit.text().strip() or "routes_chinese_postman_gpx",
+            "consolidate_tolerance_m": float(self.route_consolidate_tol.value()),
+            "use_cache": self.route_cache_check.isChecked(),
+        }
+        if route_source == "place":
+            city = self.route_city_edit.text().strip()
+            if not city:
+                logging.getLogger(__name__).warning("Enter a city / place name.")
+                return
+            kwargs["city_name"] = city
+            kwargs["region_geojson_path"] = None
+            kwargs["road_geojson_path"] = None
+        elif route_source == "region":
+            region_path = self.route_region_path_edit.text().strip()
+            if not region_path:
+                logging.getLogger(__name__).warning("Select a region polygon GeoJSON file.")
+                return
+            kwargs["region_geojson_path"] = region_path
+            kwargs["city_name"] = None
+            kwargs["road_geojson_path"] = None
+        elif route_source == "roads":
+            roads_path = self.route_roads_path_edit.text().strip()
+            if not roads_path:
+                logging.getLogger(__name__).warning("Select a road network GeoJSON file.")
+                return
+            kwargs["road_geojson_path"] = roads_path
+            kwargs["city_name"] = None
+            kwargs["region_geojson_path"] = None
+        else:
+            logging.getLogger(__name__).error("Unknown route source: %s", route_source)
+            return
+
+        def task() -> EulerRoutesResult:
+            """
+            Run task.
+
+            :return: Result of this step or updated UI/application state.
+
+            Example::
+                In: task()
+                Out: UI/application state updated as intended.
+            """
+            return generate_clean_routes(**kwargs)
+
+        self._run_async(task, on_ok=self._on_euler_routes_done)
+
+    def _on_euler_routes_done(self, result: Any) -> None:
+        """
+        Run  on euler routes done.
+
+        :param result: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _on_euler_routes_done(result)
+            Out: UI/application state updated as intended.
+        """
+        if not isinstance(result, EulerRoutesResult):
+            return
+        self._last_euler_result = result
+        polylines = [list(polyline) for polyline in result.polylines_wgs84]
+        self.map_canvas.update_euler_layer(polylines)
+        self._append_data_science_section(
+            "Chinese postman / GPX drive routes",
+            format_euler_routes_summary(result),
+        )
diff --git a/src/uq_desktop_processor/gui/shell/explorer/sources.py b/src/uq_desktop_processor/gui/shell/explorer/sources.py
new file mode 100644
index 0000000..26ade4a
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/explorer/sources.py
@@ -0,0 +1,44 @@
+"""
+Defines map layer sources and GeoJSON loading for the explorer map.
+"""
+
+from PySide6.QtWidgets import QComboBox, QLabel
+
+from uq_desktop_processor.gui.shell.constants import SOURCE_INPUT_STACK_PAGE_ORDER
+from uq_desktop_processor.gui.widgets import CompactStackedWidget
+
+
+class SourceInputsMixin:
+    """
+    SourceInputsMixin UI helper class.
+    """
+
+    @staticmethod
+    def _apply_source_input_page(
+        combo: QComboBox,
+        stack: CompactStackedWidget,
+        field_label: QLabel,
+        labels: dict[str, str],
+    ) -> None:
+        """
+        Run  apply source input page.
+
+        :param combo: See caller/context.
+        :param stack: See caller/context.
+        :param field_label: See caller/context.
+        :param labels: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _apply_source_input_page(combo, stack, field_label, labels)
+            Out: UI/application state updated as intended.
+        """
+        selected_source = combo.currentData()
+        source_key = str(selected_source) if selected_source is not None else "place"
+        try:
+            page_index = SOURCE_INPUT_STACK_PAGE_ORDER.index(source_key)
+        except ValueError:
+            page_index = 0
+            source_key = "place"
+        stack.setCurrentIndex(page_index)
+        field_label.setText(labels[source_key])
diff --git a/src/uq_desktop_processor/gui/shell/explorer/window.py b/src/uq_desktop_processor/gui/shell/explorer/window.py
new file mode 100644
index 0000000..8e14025
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/explorer/window.py
@@ -0,0 +1,176 @@
+"""
+Main explorer window: layout, menus, and coordination of map and tools.
+"""
+
+import logging
+
+from PySide6.QtGui import QIcon
+from PySide6.QtWidgets import (
+    QButtonGroup,
+    QCheckBox,
+    QComboBox,
+    QDoubleSpinBox,
+    QFrame,
+    QLabel,
+    QLineEdit,
+    QMainWindow,
+    QPlainTextEdit,
+    QProgressBar,
+    QPushButton,
+    QSlider,
+    QSpinBox,
+    QSplitter,
+    QStackedWidget,
+    QTextEdit,
+    QVBoxLayout,
+)
+
+from uq_desktop_processor.gui.paths import APP_ICON_PATH
+from uq_desktop_processor.gui.shell.constants import EULER_SOURCE_FIELD_LABELS, PLANNER_SOURCE_FIELD_LABELS
+from uq_desktop_processor.gui.shell.explorer.console import ConsoleMixin
+from uq_desktop_processor.gui.shell.explorer.dialogs import DialogsMixin
+from uq_desktop_processor.gui.shell.explorer.modules import ModulesMixin
+from uq_desktop_processor.gui.shell.explorer.pipeline import PipelineMixin
+from uq_desktop_processor.gui.shell.explorer.sources import SourceInputsMixin
+from uq_desktop_processor.gui.shell.logging_bridge import LogBridge, QtLogHandler
+from uq_desktop_processor.gui.shell.ui.main_frame import build_main_frame
+from uq_desktop_processor.gui.shell.worker import StepThread
+from uq_desktop_processor.gui.styles.theme import NEON_STYLE
+from uq_desktop_processor.gui.widgets import CompactStackedWidget, DeckMapWidget, NeonPanel
+from uq_desktop_processor.pipeline import UrbanQualityAIPipeline
+from uq_desktop_processor.street_view_analysis import EulerRoutesResult
+
+
+class UrbanQualityAIExplorer(
+    QMainWindow,
+    ConsoleMixin,
+    DialogsMixin,
+    SourceInputsMixin,
+    PipelineMixin,
+    ModulesMixin,
+):
+    """Main window; shell UI is built by ``urban_quality_ai.gui.shell.ui``."""
+
+    sidebar: QFrame
+    button_group: QButtonGroup
+    main_splitter: QSplitter
+    tool_container: QFrame
+    tool_layout: QVBoxLayout
+    stacked_tools: QStackedWidget
+    map_container: QFrame
+    map_canvas: DeckMapWidget
+    right_panel: QFrame
+    ai_vision_box: NeonPanel
+    metrics_text: QTextEdit
+    logs_box: NeonPanel
+    console: QTextEdit
+    progress_bar: QProgressBar
+    route_source_combo: QComboBox
+    _route_input_stack: CompactStackedWidget
+    route_city_edit: QLineEdit
+    route_region_path_edit: QLineEdit
+    route_roads_path_edit: QLineEdit
+    _route_input_field_label: QLabel
+    route_grid_cols: QSpinBox
+    route_grid_rows: QSpinBox
+    route_out_edit: QLineEdit
+    route_consolidate_tol: QDoubleSpinBox
+    route_cache_check: QCheckBox
+    planner_source_combo: QComboBox
+    _planner_input_stack: CompactStackedWidget
+    place_name_edit: QLineEdit
+    region_path_edit: QLineEdit
+    road_path_edit: QLineEdit
+    _planner_input_field_label: QLabel
+    spacing_edit: QLineEdit
+    min_dist_edit: QLineEdit
+    planner_points_out_edit: QLineEdit
+    token_edit: QLineEdit
+    mapillary_points_edit: QLineEdit
+    mapillary_out_edit: QLineEdit
+    radius_edit: QLineEdit
+    workers_spin: QSpinBox
+    prefilter_image_folder_edit: QLineEdit
+    prefilter_rejected_edit: QLineEdit
+    model_combo: QComboBox
+    device_combo: QComboBox
+    threshold_slider: QSlider
+    threshold_label: QLabel
+    beta_spin: QDoubleSpinBox
+    prefilter_pos_edit: QPlainTextEdit
+    prefilter_neg_edit: QPlainTextEdit
+    vit_images_dir_edit: QLineEdit
+    vit_model_path_edit: QLineEdit
+    vit_calibrators_edit: QLineEdit
+    vit_output_path_edit: QLineEdit
+    vit_output_layer_name_edit: QLineEdit
+    vit_model_name_edit: QLineEdit
+    vit_image_size_spin: QSpinBox
+    vit_batch_size_spin: QSpinBox
+    vit_device_combo: QComboBox
+    run_buttons: list[QPushButton]
+
+    def __init__(self) -> None:
+        """
+        Run   init  .
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: __init__()
+            Out: UI/application state updated as intended.
+        """
+        super().__init__()
+        self.setWindowTitle("UrbanQuality-AI 2026")
+        self.setWindowIcon(QIcon(str(APP_ICON_PATH)))
+        self.resize(1400, 850)
+        self.setStyleSheet(NEON_STYLE)
+
+        self.pipeline = UrbanQualityAIPipeline()
+        self.current_active_module = -1
+        self._worker: StepThread | None = None
+        self.run_buttons = []
+        self._last_euler_result: EulerRoutesResult | None = None
+
+        self._log_bridge = LogBridge()
+        self._log_bridge.append_text.connect(self._append_console)
+        self._qt_log_handler = QtLogHandler(self._log_bridge)
+        self._qt_log_handler.setLevel(logging.INFO)
+        self._qt_log_handler.setFormatter(logging.Formatter("%(levelname)s %(name)s: %(message)s"))
+        logging.getLogger().addHandler(self._qt_log_handler)
+
+        build_main_frame(self)
+
+    def on_route_source_changed(self) -> None:
+        """
+        Run on route source changed.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: on_route_source_changed()
+            Out: UI/application state updated as intended.
+        """
+        self._apply_source_input_page(
+            self.route_source_combo,
+            self._route_input_stack,
+            self._route_input_field_label,
+            EULER_SOURCE_FIELD_LABELS,
+        )
+
+    def on_planner_source_changed(self) -> None:
+        """
+        Run on planner source changed.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: on_planner_source_changed()
+            Out: UI/application state updated as intended.
+        """
+        self._apply_source_input_page(
+            self.planner_source_combo,
+            self._planner_input_stack,
+            self._planner_input_field_label,
+            PLANNER_SOURCE_FIELD_LABELS,
+        )
diff --git a/src/uq_desktop_processor/gui/shell/formatters.py b/src/uq_desktop_processor/gui/shell/formatters.py
new file mode 100644
index 0000000..322f5d1
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/formatters.py
@@ -0,0 +1,164 @@
+"""
+Small string formatting helpers for pipeline status and shell UI labels.
+"""
+
+from pathlib import Path
+from typing import Any
+
+import numpy as np
+
+from uq_desktop_processor.gui.map_view.geo import polyline_geodesic_length_m
+from uq_desktop_processor.street_view_analysis import EulerRoutesResult
+
+
+def format_euler_routes_summary(result: EulerRoutesResult) -> list[str]:
+    """
+    Run format euler routes summary.
+
+    :param result: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: format_euler_routes_summary(result)
+        Out: UI/application state updated as intended.
+    """
+    file_count = len(result.gpx_paths)
+    polylines = result.polylines_wgs84
+    segment_lengths_m = [polyline_geodesic_length_m(polyline) for polyline in polylines]
+    total_length_m = sum(segment_lengths_m)
+    lines: list[str] = [
+        f"Output directory: {result.output_dir}",
+        f"GPX files written: {file_count}",
+        f"Route segments (polylines): {len(polylines)}",
+    ]
+    for segment_index, segment_length_m in enumerate(segment_lengths_m, start=1):
+        lines.append(f"  Segment {segment_index}: {segment_length_m / 1000.0:.3f} km")
+    lines.append(f"Total length (all segments): {total_length_m / 1000.0:.3f} km")
+    return lines
+
+
+def format_download_summary(stats: dict[str, Any]) -> list[str]:
+    """
+    Run format download summary.
+
+    :param stats: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: format_download_summary(stats)
+        Out: UI/application state updated as intended.
+    """
+    point_count = int(stats.get("point_count") or 0)
+    downloaded_count = int(stats.get("downloaded") or 0)
+    elapsed = float(stats.get("elapsed_s") or 0.0)
+    output_folder = str(stats.get("output_folder") or "")
+    images_per_second = float(stats.get("images_per_second") or 0.0)
+    failed_messages: list[str] = list(stats.get("failed_messages") or [])
+    lines = [
+        f"Points processed: {point_count}",
+        f"Images saved: {downloaded_count}",
+        f"Output path: {output_folder}",
+        f"Elapsed: {elapsed:.1f} s",
+        f"Mean throughput (saved images / s): {images_per_second:.2f}",
+    ]
+    if failed_messages:
+        max_show = 12
+        lines.append(f"Not downloaded / failed ({len(failed_messages)}):")
+        for failed_message in failed_messages[:max_show]:
+            lines.append(f"  • {failed_message}")
+        if len(failed_messages) > max_show:
+            lines.append(f"  … and {len(failed_messages) - max_show} more")
+    else:
+        lines.append("Failures: none")
+    return lines
+
+
+def format_prefilter_summary(stats: dict[str, Any]) -> list[str]:
+    """
+    Run format prefilter summary.
+
+    :param stats: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: format_prefilter_summary(stats)
+        Out: UI/application state updated as intended.
+    """
+    summary = stats.get("summary") or {}
+    rejected_folder = stats.get("rejected_folder") or ""
+    rejected_count = int(summary.get("rejected") or 0)
+    kept_count = int(summary.get("kept") or 0)
+    model_name = stats.get("model_name") or ""
+    return [
+        f"CLIP model: {model_name}",
+        f"Rejected (moved): {rejected_count}",
+        f"Kept: {kept_count}",
+        f"Rejected folder: {rejected_folder}",
+    ]
+
+
+def format_vit_summary(
+    results: dict[str, Any],
+    *,
+    pipeline_config: dict[str, Any],
+    default_results_dir: Path,
+) -> list[str]:
+    """
+    Run format vit summary.
+
+    :param results: See caller/context.
+    :param pipeline_config: See caller/context.
+    :param default_results_dir: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: format_vit_summary(results)
+        Out: UI/application state updated as intended.
+    """
+    out_spec = (pipeline_config.get("vit_output_layer_path") or "").strip()
+    if out_spec:
+        out_path = str(Path(out_spec).expanduser().resolve())
+    else:
+        out_path = str((default_results_dir / "vit_finetuned_scores.gpkg").resolve())
+    model = str(results.get("model_name") or "")
+    images = results.get("images") or []
+    order = list(results.get("order") or [])
+    checkpoint_path = (pipeline_config.get("vit_model_path") or "").strip()
+    checkpoint_line = str(Path(checkpoint_path).expanduser().resolve()) if checkpoint_path else "(not set)"
+    calibrators_spec = (pipeline_config.get("vit_calibrators_dir") or "").strip()
+    calibrators_line = str(Path(calibrators_spec).expanduser().resolve()) if calibrators_spec else "(calibration off)"
+    arch = (pipeline_config.get("vit_model_name") or "").strip()
+    image_size = int(pipeline_config.get("vit_image_size") or 224)
+    batch_size = int(pipeline_config.get("vit_batch_size") or 32)
+    torch_device = str(pipeline_config.get("vit_torch_device") or "auto")
+    lines: list[str] = [
+        f"Output path: {out_path}",
+        f"Model (architecture): {arch}",
+        f"Weights file: {checkpoint_line}",
+        f"Calibrators: {calibrators_line}",
+        f"Inference: image_size={image_size}, batch_size={batch_size}, device={torch_device}",
+        f"Readout model label: {model}",
+        f"Images scored: {len(images)}",
+    ]
+    for cat in order:
+        vals: list[float] = []
+        for im in images:
+            block = (im.get("categories") or {}).get(cat) or {}
+            if "probability_pct" in block:
+                vals.append(float(block["probability_pct"]))
+        if not vals:
+            continue
+        arr = np.array(vals, dtype=np.float64)
+        lo = float(arr.min())
+        hi = float(arr.max())
+        lines.append(f"  {cat}: avg={float(arr.mean()):.2f}%, min={lo:.2f}%, max={hi:.2f}%, range={hi - lo:.2f}%")
+    average_overall_pct = results.get("average_overall_pct")
+    if average_overall_pct is not None:
+        lines.append(f"Overall (mean of per-image means): {float(average_overall_pct):.2f}%")
+    skipped_images = results.get("skipped_images") or []
+    if skipped_images:
+        lines.append(f"Skipped images: {len(skipped_images)}")
+    warnings = results.get("warnings") or []
+    if warnings:
+        lines.append("Warnings: " + "; ".join(str(warning_message) for warning_message in warnings))
+    return lines
diff --git a/src/uq_desktop_processor/gui/shell/logging_bridge.py b/src/uq_desktop_processor/gui/shell/logging_bridge.py
new file mode 100644
index 0000000..ceb48ca
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/logging_bridge.py
@@ -0,0 +1,54 @@
+"""
+Forwards Python logging records into Qt text widgets for in-app log panes.
+"""
+
+import logging
+
+from PySide6.QtCore import QObject, Signal
+
+
+class LogBridge(QObject):
+    """
+    LogBridge UI helper class.
+    """
+
+    append_text = Signal(str)
+
+
+class QtLogHandler(logging.Handler):
+    """
+    QtLogHandler UI helper class.
+    """
+
+    def __init__(self, bridge: LogBridge) -> None:
+        """
+        Run   init  .
+
+        :param bridge: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: __init__(bridge)
+            Out: UI/application state updated as intended.
+        """
+        super().__init__()
+        self._bridge = bridge
+
+    def emit(self, record: logging.LogRecord) -> None:
+        """
+        Run emit.
+
+        :param record: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: emit(record)
+            Out: UI/application state updated as intended.
+        """
+        try:
+            formatted_message = self.format(record)
+            self._bridge.append_text.emit(formatted_message)
+        except (KeyboardInterrupt, SystemExit):
+            raise
+        except (RuntimeError, ValueError, TypeError, AttributeError):
+            self.handleError(record)
diff --git a/src/uq_desktop_processor/gui/shell/ui/__init__.py b/src/uq_desktop_processor/gui/shell/ui/__init__.py
new file mode 100644
index 0000000..46a4359
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/__init__.py
@@ -0,0 +1,7 @@
+"""
+GUI module:   init  .
+"""
+
+from .main_frame import build_main_frame
+
+__all__ = ["build_main_frame"]
diff --git a/src/uq_desktop_processor/gui/shell/ui/main_frame.py b/src/uq_desktop_processor/gui/shell/ui/main_frame.py
new file mode 100644
index 0000000..f1c8595
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/main_frame.py
@@ -0,0 +1,142 @@
+"""
+Primary application frame hosting the stacked tool pages and central splitter.
+"""
+
+from typing import TYPE_CHECKING
+
+from PySide6.QtCore import Qt
+from PySide6.QtWidgets import (
+    QButtonGroup,
+    QFrame,
+    QHBoxLayout,
+    QLabel,
+    QProgressBar,
+    QPushButton,
+    QSplitter,
+    QStackedWidget,
+    QTextEdit,
+    QVBoxLayout,
+    QWidget,
+)
+
+from uq_desktop_processor.gui.shell.ui.module_pages import setup_module_pages
+from uq_desktop_processor.gui.widgets import DeckMapWidget, NeonPanel
+
+if TYPE_CHECKING:
+    from uq_desktop_processor.gui.shell.explorer import UrbanQualityAIExplorer
+
+
+def build_main_frame(explorer: "UrbanQualityAIExplorer") -> None:
+    """
+    Run build main frame.
+
+    :param explorer: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: build_main_frame(explorer)
+        Out: UI/application state updated as intended.
+    """
+    central_widget = QWidget()
+    explorer.setCentralWidget(central_widget)
+    main_layout = QVBoxLayout(central_widget)
+    main_layout.setContentsMargins(0, 0, 0, 0)
+    main_layout.setSpacing(0)
+
+    top_layout = QHBoxLayout()
+    top_layout.setSpacing(0)
+    top_layout.setContentsMargins(0, 0, 0, 0)
+
+    explorer.sidebar = QFrame()
+    explorer.sidebar.setObjectName("Sidebar")
+    explorer.sidebar.setFixedWidth(70)
+    sidebar_layout = QVBoxLayout(explorer.sidebar)
+    sidebar_layout.setAlignment(Qt.AlignmentFlag.AlignTop)
+
+    explorer.button_group = QButtonGroup(explorer)
+    explorer.button_group.setExclusive(True)
+
+    for panel_index, (icon, name) in enumerate(
+        [
+            ("1", "Drive route"),
+            ("2", "Sampling points"),
+            ("3", "Mapillary download"),
+            ("4", "Panoramas → views"),
+            ("5", "CLIP prefilter"),
+            ("6", "ViT scoring"),
+            ("7", "Export results"),
+            ("8", "Validation"),
+        ]
+    ):
+        sidebar_button = QPushButton(icon)
+        sidebar_button.setObjectName("SidebarBtn")
+        sidebar_button.setCheckable(True)
+        sidebar_button.setToolTip(name)
+        sidebar_button.setFixedSize(70, 70)
+        sidebar_button.clicked.connect(
+            lambda _checked=False, panel_idx=panel_index: explorer.toggle_module_panel(panel_idx)
+        )
+        explorer.button_group.addButton(sidebar_button, panel_index)
+        sidebar_layout.addWidget(sidebar_button)
+
+    top_layout.addWidget(explorer.sidebar)
+
+    explorer.main_splitter = QSplitter(Qt.Orientation.Horizontal)
+    explorer.main_splitter.setHandleWidth(6)
+
+    explorer.tool_container = QFrame()
+    explorer.tool_container.setObjectName("ToolPanelContainer")
+    explorer.tool_container.setMinimumWidth(320)
+    explorer.tool_layout = QVBoxLayout(explorer.tool_container)
+
+    explorer.stacked_tools = QStackedWidget()
+    explorer.tool_layout.addWidget(explorer.stacked_tools)
+
+    setup_module_pages(explorer)
+    explorer.tool_container.setVisible(False)
+
+    explorer.map_container = QFrame()
+    explorer.map_container.setObjectName("PanelBackground")
+    map_layout = QVBoxLayout(explorer.map_container)
+    map_header = QLabel("Live Map View")
+    map_layout.addWidget(map_header)
+
+    explorer.map_canvas = DeckMapWidget()
+    map_layout.addWidget(explorer.map_canvas, 1)
+
+    explorer.right_panel = QFrame()
+    explorer.right_panel.setMinimumWidth(300)
+    right_layout = QVBoxLayout(explorer.right_panel)
+
+    explorer.ai_vision_box = NeonPanel("Data Science Console")
+    explorer.metrics_text = QTextEdit()
+    explorer.metrics_text.setReadOnly(True)
+    explorer.metrics_text.setObjectName("Console")
+    explorer.metrics_text.setMaximumHeight(160)
+    explorer.metrics_text.setPlaceholderText(
+        "Pipeline summaries will appear here. Use the tools on the left to run a step; each "
+        "completed run appends metrics and output paths below."
+    )
+    explorer.ai_vision_box.main_layout.addWidget(explorer.metrics_text)
+    explorer.ai_vision_box.main_layout.addStretch()
+    right_layout.addWidget(explorer.ai_vision_box, 1)
+
+    explorer.logs_box = NeonPanel("System Logs")
+    explorer.console = QTextEdit()
+    explorer.console.setObjectName("Console")
+    explorer.console.setReadOnly(True)
+    explorer.console.append("[INFO] System Ready...")
+    explorer.logs_box.main_layout.addWidget(explorer.console)
+    right_layout.addWidget(explorer.logs_box, 2)
+
+    explorer.main_splitter.addWidget(explorer.tool_container)
+    explorer.main_splitter.addWidget(explorer.map_container)
+    explorer.main_splitter.addWidget(explorer.right_panel)
+
+    explorer.main_splitter.setStretchFactor(1, 1)
+
+    top_layout.addWidget(explorer.main_splitter)
+    main_layout.addLayout(top_layout, 1)
+
+    explorer.progress_bar = QProgressBar()
+    main_layout.addWidget(explorer.progress_bar)
diff --git a/src/uq_desktop_processor/gui/shell/ui/module_pages.py b/src/uq_desktop_processor/gui/shell/ui/module_pages.py
new file mode 100644
index 0000000..ea506df
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/module_pages.py
@@ -0,0 +1,47 @@
+"""
+Builds or wires stacked module pages into the shell navigation model.
+"""
+
+from typing import TYPE_CHECKING
+
+from uq_desktop_processor.gui.shell.ui.pages import clip_prefilter, drive_route, mapillary, sampling_points, vit_scoring
+from uq_desktop_processor.gui.shell.ui.placeholders import add_placeholder_tool_page
+
+if TYPE_CHECKING:
+    from uq_desktop_processor.gui.shell.explorer import UrbanQualityAIExplorer
+
+
+def setup_module_pages(explorer: "UrbanQualityAIExplorer") -> None:
+    """
+    Run setup module pages.
+
+    :param explorer: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: setup_module_pages(explorer)
+        Out: UI/application state updated as intended.
+    """
+    drive_route.add_drive_route_page(explorer)
+    sampling_points.add_sampling_points_page(explorer)
+    mapillary.add_mapillary_page(explorer)
+    add_placeholder_tool_page(
+        explorer.stacked_tools,
+        explorer.run_buttons,
+        title="Panoramas → views",
+        description="This module is a placeholder and will be implemented later.",
+    )
+    clip_prefilter.add_clip_prefilter_page(explorer)
+    vit_scoring.add_vit_scoring_page(explorer)
+    add_placeholder_tool_page(
+        explorer.stacked_tools,
+        explorer.run_buttons,
+        title="Export results",
+        description="This module is a placeholder and will be implemented later.",
+    )
+    add_placeholder_tool_page(
+        explorer.stacked_tools,
+        explorer.run_buttons,
+        title="Validation",
+        description="This module is a placeholder and will be implemented later.",
+    )
diff --git a/src/uq_desktop_processor/gui/shell/ui/osm_source_block.py b/src/uq_desktop_processor/gui/shell/ui/osm_source_block.py
new file mode 100644
index 0000000..78060d9
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/osm_source_block.py
@@ -0,0 +1,90 @@
+"""
+UI block for selecting and validating OSM / road-graph input sources.
+"""
+
+from collections.abc import Callable
+from dataclasses import dataclass
+
+from PySide6.QtWidgets import QComboBox, QHBoxLayout, QLabel, QLineEdit, QPushButton, QWidget
+
+from uq_desktop_processor.gui.widgets import CompactStackedWidget
+
+GEOJSON_FILTER = "GeoJSON (*.geojson *.json)"
+
+
+@dataclass(frozen=True)
+class OsmTripleSourceWidgets:
+    """
+    OsmTripleSourceWidgets UI helper class.
+    """
+
+    combo: QComboBox
+    stack: CompactStackedWidget
+    field_label: QLabel
+    place_edit: QLineEdit
+    region_edit: QLineEdit
+    roads_edit: QLineEdit
+
+
+def build_osm_triple_source_block(
+    pick_file: Callable[[QLineEdit, str], None],
+    field_labels: dict[str, str],
+    on_changed: Callable[[], None],
+    initial_place: str,
+    *,
+    roads_item_label: str,
+) -> OsmTripleSourceWidgets:
+    """
+    Run build osm triple source block.
+
+    :param pick_file: See caller/context.
+    :param field_labels: See caller/context.
+    :param on_changed: See caller/context.
+    :param initial_place: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: build_osm_triple_source_block(pick_file, field_labels, on_changed, initial_place)
+        Out: UI/application state updated as intended.
+    """
+    combo = QComboBox()
+    combo.addItem("Place name (OSM)", "place")
+    combo.addItem("Region polygon (GeoJSON)", "region")
+    combo.addItem(roads_item_label, "roads")
+    combo.currentIndexChanged.connect(on_changed)
+
+    stack = CompactStackedWidget()
+
+    page_place = QWidget()
+    lay_place = QHBoxLayout(page_place)
+    lay_place.setContentsMargins(0, 0, 0, 0)
+    place_edit = QLineEdit(initial_place)
+    lay_place.addWidget(place_edit)
+    stack.addWidget(page_place)
+
+    page_region = QWidget()
+    lay_region = QHBoxLayout(page_region)
+    lay_region.setContentsMargins(0, 0, 0, 0)
+    region_edit = QLineEdit()
+    region_edit.setPlaceholderText("polygon.geojson …")
+    btn_region = QPushButton("…")
+    btn_region.setFixedWidth(36)
+    btn_region.clicked.connect(lambda: pick_file(region_edit, GEOJSON_FILTER))
+    lay_region.addWidget(region_edit)
+    lay_region.addWidget(btn_region)
+    stack.addWidget(page_region)
+
+    page_roads = QWidget()
+    lay_roads = QHBoxLayout(page_roads)
+    lay_roads.setContentsMargins(0, 0, 0, 0)
+    roads_edit = QLineEdit()
+    roads_edit.setPlaceholderText("roads.geojson …")
+    btn_roads = QPushButton("…")
+    btn_roads.setFixedWidth(36)
+    btn_roads.clicked.connect(lambda: pick_file(roads_edit, GEOJSON_FILTER))
+    lay_roads.addWidget(roads_edit)
+    lay_roads.addWidget(btn_roads)
+    stack.addWidget(page_roads)
+
+    field_label = QLabel(field_labels["place"])
+    return OsmTripleSourceWidgets(combo, stack, field_label, place_edit, region_edit, roads_edit)
diff --git a/src/uq_desktop_processor/gui/shell/ui/pages/__init__.py b/src/uq_desktop_processor/gui/shell/ui/pages/__init__.py
new file mode 100644
index 0000000..f434173
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/pages/__init__.py
@@ -0,0 +1 @@
+"""Individual stacked tool pages."""
diff --git a/src/uq_desktop_processor/gui/shell/ui/pages/clip_prefilter.py b/src/uq_desktop_processor/gui/shell/ui/pages/clip_prefilter.py
new file mode 100644
index 0000000..6b1469a
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/pages/clip_prefilter.py
@@ -0,0 +1,131 @@
+"""
+Stacked tool page: CLIP prefilter (configure and run image filtering).
+"""
+
+from pathlib import Path
+from typing import TYPE_CHECKING
+
+from PySide6.QtCore import Qt
+from PySide6.QtWidgets import (
+    QComboBox,
+    QDoubleSpinBox,
+    QFormLayout,
+    QHBoxLayout,
+    QLabel,
+    QLineEdit,
+    QPlainTextEdit,
+    QPushButton,
+    QSlider,
+    QVBoxLayout,
+    QWidget,
+)
+
+from uq_desktop_processor.evaluation.clip_prefilter.defaults import FILTER_PROMPTS as CLIP_PREFILTER_DEFAULT_PROMPTS
+from uq_desktop_processor.gui.shell.constants import CLIP_MODEL_CHOICES
+from uq_desktop_processor.gui.widgets import NeonPanel
+
+if TYPE_CHECKING:
+    from uq_desktop_processor.gui.shell.explorer import UrbanQualityAIExplorer
+
+
+def add_clip_prefilter_page(explorer: "UrbanQualityAIExplorer") -> None:
+    """
+    Run add clip prefilter page.
+
+    :param explorer: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: add_clip_prefilter_page(explorer)
+        Out: UI/application state updated as intended.
+    """
+    prefilter_page = QWidget()
+    page_layout = QVBoxLayout(prefilter_page)
+    prefilter_panel = NeonPanel(
+        "CLIP prefilter",
+        "Compare images to two phrase lists and move low-score matches to the rejected folder.",
+    )
+    form_layout = QFormLayout()
+
+    pre_in_row = QHBoxLayout()
+    explorer.prefilter_image_folder_edit = QLineEdit(str(Path("data") / "images" / "raw"))
+    explorer.prefilter_image_folder_edit.setPlaceholderText("Folder with .jpg / .png to filter")
+    btn_pf_in = QPushButton("…")
+    btn_pf_in.setFixedWidth(36)
+    btn_pf_in.clicked.connect(lambda: explorer.pick_folder(explorer.prefilter_image_folder_edit))
+    pre_in_row.addWidget(explorer.prefilter_image_folder_edit)
+    pre_in_row.addWidget(btn_pf_in)
+    form_layout.addRow("Input: images folder", pre_in_row)
+
+    pre_rej_row = QHBoxLayout()
+    explorer.prefilter_rejected_edit = QLineEdit("rejected")
+    explorer.prefilter_rejected_edit.setPlaceholderText("Sibling name (e.g. rejected) or full folder path")
+    btn_pf_rej = QPushButton("…")
+    btn_pf_rej.setFixedWidth(36)
+    btn_pf_rej.clicked.connect(lambda: explorer.pick_folder(explorer.prefilter_rejected_edit))
+    pre_rej_row.addWidget(explorer.prefilter_rejected_edit)
+    pre_rej_row.addWidget(btn_pf_rej)
+    form_layout.addRow("Output: rejected folder", pre_rej_row)
+
+    explorer.model_combo = QComboBox()
+    for label, names in CLIP_MODEL_CHOICES:
+        explorer.model_combo.addItem(label, names)
+    form_layout.addRow("CLIP model", explorer.model_combo)
+
+    explorer.device_combo = QComboBox()
+    explorer.device_combo.addItem("Auto (CUDA if FORCE_CUDA=1)", "auto")
+    explorer.device_combo.addItem("CPU", "cpu")
+    explorer.device_combo.addItem("CUDA", "cuda")
+    form_layout.addRow("Torch device", explorer.device_combo)
+
+    explorer.threshold_slider = QSlider(Qt.Orientation.Horizontal)
+    explorer.threshold_slider.setRange(0, 100)
+    explorer.threshold_slider.setValue(40)
+    explorer.threshold_label = QLabel("40 %")
+    explorer.threshold_slider.valueChanged.connect(
+        lambda slider_value: explorer.threshold_label.setText(f"{slider_value} %")
+    )
+    th_row = QHBoxLayout()
+    th_row.addWidget(explorer.threshold_slider)
+    th_row.addWidget(explorer.threshold_label)
+    form_layout.addRow("Threshold", th_row)
+
+    explorer.beta_spin = QDoubleSpinBox()
+    explorer.beta_spin.setRange(1.0, 100.0)
+    explorer.beta_spin.setValue(30.0)
+    explorer.beta_spin.setDecimals(1)
+    form_layout.addRow("Sigmoid β", explorer.beta_spin)
+
+    pos_lbl = QLabel("Phrases: direction to KEEP (higher match)")
+    pos_lbl.setStyleSheet("font-weight: normal; text-transform: none; color: #afa;")
+    form_layout.addRow(pos_lbl)
+    explorer.prefilter_pos_edit = QPlainTextEdit()
+    explorer.prefilter_pos_edit.setPlaceholderText("One phrase per line…")
+    explorer.prefilter_pos_edit.setMinimumHeight(88)
+    explorer.prefilter_pos_edit.setPlainText("\n".join(CLIP_PREFILTER_DEFAULT_PROMPTS["pos"]))
+    form_layout.addRow(explorer.prefilter_pos_edit)
+
+    neg_lbl = QLabel("Phrases: contrast / away from (lower → reject)")
+    neg_lbl.setStyleSheet("font-weight: normal; text-transform: none; color: #faa;")
+    form_layout.addRow(neg_lbl)
+    explorer.prefilter_neg_edit = QPlainTextEdit()
+    explorer.prefilter_neg_edit.setPlaceholderText("One phrase per line…")
+    explorer.prefilter_neg_edit.setMinimumHeight(88)
+    explorer.prefilter_neg_edit.setPlainText("\n".join(CLIP_PREFILTER_DEFAULT_PROMPTS["neg"]))
+    form_layout.addRow(explorer.prefilter_neg_edit)
+
+    prefilter_panel.main_layout.addLayout(form_layout)
+    reset_prompts_row = QHBoxLayout()
+    btn_reset_pf_prompts = QPushButton("Reset phrases to defaults")
+    btn_reset_pf_prompts.clicked.connect(explorer.reset_clip_prefilter_prompts)
+    reset_prompts_row.addWidget(btn_reset_pf_prompts)
+    reset_prompts_row.addStretch()
+    prefilter_panel.main_layout.addLayout(reset_prompts_row)
+    prefilter_panel.main_layout.addStretch()
+    btn4 = QPushButton("PREFILTER (CLIP) ◆")
+    btn4.setObjectName("RunBtn")
+    btn4.clicked.connect(explorer.on_run_prefilter)
+    prefilter_panel.main_layout.addWidget(btn4)
+    page_layout.addWidget(prefilter_panel)
+    explorer.stacked_tools.addWidget(prefilter_page)
+    explorer.run_buttons.append(btn4)
diff --git a/src/uq_desktop_processor/gui/shell/ui/pages/drive_route.py b/src/uq_desktop_processor/gui/shell/ui/pages/drive_route.py
new file mode 100644
index 0000000..38665b0
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/pages/drive_route.py
@@ -0,0 +1,99 @@
+"""
+Stacked tool page: Chinese postman routes and GPX export for drive coverage.
+"""
+
+from typing import TYPE_CHECKING
+
+from PySide6.QtWidgets import (
+    QCheckBox,
+    QDoubleSpinBox,
+    QFormLayout,
+    QHBoxLayout,
+    QLineEdit,
+    QPushButton,
+    QSpinBox,
+    QVBoxLayout,
+    QWidget,
+)
+
+from uq_desktop_processor.gui.shell.constants import EULER_SOURCE_FIELD_LABELS
+from uq_desktop_processor.gui.shell.ui.osm_source_block import build_osm_triple_source_block
+from uq_desktop_processor.gui.widgets import NeonPanel
+
+if TYPE_CHECKING:
+    from uq_desktop_processor.gui.shell.explorer import UrbanQualityAIExplorer
+
+
+def add_drive_route_page(explorer: "UrbanQualityAIExplorer") -> None:
+    """
+    Run add drive route page.
+
+    :param explorer: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: add_drive_route_page(explorer)
+        Out: UI/application state updated as intended.
+    """
+    p0 = QWidget()
+    l0 = QVBoxLayout(p0)
+    pan0 = NeonPanel(
+        "Drive route (Chinese postman/GPX)",
+        "Generate a drivable GPX route over the road network.",
+    )
+    f0 = QFormLayout()
+
+    euler = build_osm_triple_source_block(
+        explorer.pick_file,
+        EULER_SOURCE_FIELD_LABELS,
+        explorer.on_route_source_changed,
+        "Katowice, Poland",
+        roads_item_label="Road network (GeoJSON)",
+    )
+    explorer.route_source_combo = euler.combo
+    explorer._route_input_stack = euler.stack
+    explorer.route_city_edit = euler.place_edit
+    explorer.route_region_path_edit = euler.region_edit
+    explorer.route_roads_path_edit = euler.roads_edit
+    explorer._route_input_field_label = euler.field_label
+    f0.addRow("Data source", explorer.route_source_combo)
+    f0.addRow(explorer._route_input_field_label, explorer._route_input_stack)
+
+    explorer.route_grid_cols = QSpinBox()
+    explorer.route_grid_cols.setRange(1, 30)
+    explorer.route_grid_cols.setValue(3)
+    f0.addRow("Grid columns", explorer.route_grid_cols)
+    explorer.route_grid_rows = QSpinBox()
+    explorer.route_grid_rows.setRange(1, 30)
+    explorer.route_grid_rows.setValue(3)
+    f0.addRow("Grid rows", explorer.route_grid_rows)
+
+    out_row = QHBoxLayout()
+    explorer.route_out_edit = QLineEdit("routes_chinese_postman_gpx")
+    explorer.route_out_edit.setPlaceholderText("Output folder for .gpx files")
+    btn_out = QPushButton("…")
+    btn_out.setFixedWidth(36)
+    btn_out.clicked.connect(lambda: explorer.pick_folder(explorer.route_out_edit))
+    out_row.addWidget(explorer.route_out_edit)
+    out_row.addWidget(btn_out)
+    f0.addRow("Output folder", out_row)
+
+    explorer.route_consolidate_tol = QDoubleSpinBox()
+    explorer.route_consolidate_tol.setRange(5.0, 80.0)
+    explorer.route_consolidate_tol.setValue(15.0)
+    explorer.route_consolidate_tol.setSuffix(" m")
+    f0.addRow("Consolidate tolerance", explorer.route_consolidate_tol)
+    explorer.route_cache_check = QCheckBox("Use OSMnx cache")
+    explorer.route_cache_check.setChecked(True)
+    f0.addRow("", explorer.route_cache_check)
+
+    pan0.main_layout.addLayout(f0)
+    pan0.main_layout.addStretch()
+    btn0 = QPushButton("GENERATE ROUTE ▶")
+    btn0.setObjectName("RunBtn")
+    btn0.clicked.connect(explorer.on_run_euler_routes)
+    pan0.main_layout.addWidget(btn0)
+    l0.addWidget(pan0)
+    explorer.stacked_tools.addWidget(p0)
+    explorer.run_buttons.append(btn0)
+    explorer.on_route_source_changed()
diff --git a/src/uq_desktop_processor/gui/shell/ui/pages/mapillary.py b/src/uq_desktop_processor/gui/shell/ui/pages/mapillary.py
new file mode 100644
index 0000000..5ddefd1
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/pages/mapillary.py
@@ -0,0 +1,77 @@
+"""
+Stacked tool page: Mapillary image search and download around sampling points.
+"""
+
+from pathlib import Path
+from typing import TYPE_CHECKING
+
+from PySide6.QtWidgets import QFormLayout, QHBoxLayout, QLineEdit, QPushButton, QSpinBox, QVBoxLayout, QWidget
+
+from uq_desktop_processor.gui.widgets import NeonPanel
+
+if TYPE_CHECKING:
+    from uq_desktop_processor.gui.shell.explorer import UrbanQualityAIExplorer
+
+
+def add_mapillary_page(explorer: "UrbanQualityAIExplorer") -> None:
+    """
+    Run add mapillary page.
+
+    :param explorer: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: add_mapillary_page(explorer)
+        Out: UI/application state updated as intended.
+    """
+    p2 = QWidget()
+    l2 = QVBoxLayout(p2)
+    pan2 = NeonPanel(
+        "Mapillary download",
+        "Download street-level images for the generated sampling points.",
+    )
+    f2 = QFormLayout()
+    explorer.token_edit = QLineEdit()
+    explorer.token_edit.setPlaceholderText("Paste token or set MAPILLARY_ACCESS_TOKEN")
+    f2.addRow("Mapillary token", explorer.token_edit)
+
+    pts_in_row = QHBoxLayout()
+    explorer.mapillary_points_edit = QLineEdit(str(Path("data") / "results" / "sampling_points.geojson"))
+    explorer.mapillary_points_edit.setPlaceholderText(".geojson / .gpkg from point generation step")
+    btn_mapillary_pts = QPushButton("…")
+    btn_mapillary_pts.setFixedWidth(36)
+    btn_mapillary_pts.clicked.connect(
+        lambda: explorer.pick_file(
+            explorer.mapillary_points_edit,
+            "GeoJSON (*.geojson);;GeoPackage (*.gpkg)",
+        )
+    )
+    pts_in_row.addWidget(explorer.mapillary_points_edit)
+    pts_in_row.addWidget(btn_mapillary_pts)
+    f2.addRow("Input: point layer", pts_in_row)
+
+    img_out_row = QHBoxLayout()
+    explorer.mapillary_out_edit = QLineEdit(str(Path("data") / "images" / "raw"))
+    explorer.mapillary_out_edit.setPlaceholderText("Folder for downloaded JPEGs (used by later CLIP steps)")
+    btn_mapillary_out = QPushButton("…")
+    btn_mapillary_out.setFixedWidth(36)
+    btn_mapillary_out.clicked.connect(lambda: explorer.pick_folder(explorer.mapillary_out_edit))
+    img_out_row.addWidget(explorer.mapillary_out_edit)
+    img_out_row.addWidget(btn_mapillary_out)
+    f2.addRow("Output: image folder", img_out_row)
+
+    explorer.radius_edit = QLineEdit("150")
+    f2.addRow("Search radius (m)", explorer.radius_edit)
+    explorer.workers_spin = QSpinBox()
+    explorer.workers_spin.setRange(1, 64)
+    explorer.workers_spin.setValue(20)
+    f2.addRow("Parallel workers", explorer.workers_spin)
+    pan2.main_layout.addLayout(f2)
+    pan2.main_layout.addStretch()
+    btn2 = QPushButton("DOWNLOAD IMAGES ⬇")
+    btn2.setObjectName("RunBtn")
+    btn2.clicked.connect(explorer.on_run_download)
+    pan2.main_layout.addWidget(btn2)
+    l2.addWidget(pan2)
+    explorer.stacked_tools.addWidget(p2)
+    explorer.run_buttons.append(btn2)
diff --git a/src/uq_desktop_processor/gui/shell/ui/pages/sampling_points.py b/src/uq_desktop_processor/gui/shell/ui/pages/sampling_points.py
new file mode 100644
index 0000000..d4065e7
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/pages/sampling_points.py
@@ -0,0 +1,75 @@
+"""
+Stacked tool page: generate and visualize road sampling points (GeoJSON output).
+"""
+
+from typing import TYPE_CHECKING
+
+from PySide6.QtWidgets import QFormLayout, QHBoxLayout, QLineEdit, QPushButton, QVBoxLayout, QWidget
+
+from uq_desktop_processor.gui.shell.constants import PLANNER_SOURCE_FIELD_LABELS
+from uq_desktop_processor.gui.shell.ui.osm_source_block import build_osm_triple_source_block
+from uq_desktop_processor.gui.widgets import NeonPanel
+
+if TYPE_CHECKING:
+    from uq_desktop_processor.gui.shell.explorer import UrbanQualityAIExplorer
+
+
+def add_sampling_points_page(explorer: "UrbanQualityAIExplorer") -> None:
+    """
+    Run add sampling points page.
+
+    :param explorer: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: add_sampling_points_page(explorer)
+        Out: UI/application state updated as intended.
+    """
+    p1 = QWidget()
+    l1 = QVBoxLayout(p1)
+    pan1 = NeonPanel(
+        "Sampling points",
+        "Generate a point layer along roads for image sampling.",
+    )
+    f1 = QFormLayout()
+
+    planner = build_osm_triple_source_block(
+        explorer.pick_file,
+        PLANNER_SOURCE_FIELD_LABELS,
+        explorer.on_planner_source_changed,
+        "Katowice, Poland",
+        roads_item_label="Road network file (GeoJSON)",
+    )
+    explorer.planner_source_combo = planner.combo
+    explorer._planner_input_stack = planner.stack
+    explorer.place_name_edit = planner.place_edit
+    explorer.region_path_edit = planner.region_edit
+    explorer.road_path_edit = planner.roads_edit
+    explorer._planner_input_field_label = planner.field_label
+    f1.addRow("Data source", explorer.planner_source_combo)
+    f1.addRow(explorer._planner_input_field_label, explorer._planner_input_stack)
+
+    explorer.spacing_edit = QLineEdit("100")
+    f1.addRow("Distance between points (m)", explorer.spacing_edit)
+    explorer.min_dist_edit = QLineEdit("50")
+    f1.addRow("Min distance (m)", explorer.min_dist_edit)
+    points_out_row = QHBoxLayout()
+    explorer.planner_points_out_edit = QLineEdit("data/results/sampling_points.geojson")
+    explorer.planner_points_out_edit.setPlaceholderText("path and filename (.geojson / .gpkg)")
+    btn_points_out = QPushButton("…")
+    btn_points_out.setFixedWidth(36)
+    btn_points_out.clicked.connect(lambda: explorer.pick_save_points_layer(explorer.planner_points_out_edit))
+    points_out_row.addWidget(explorer.planner_points_out_edit)
+    points_out_row.addWidget(btn_points_out)
+    f1.addRow("Output: point layer", points_out_row)
+
+    pan1.main_layout.addLayout(f1)
+    pan1.main_layout.addStretch()
+    btn1 = QPushButton("GENERATE POINTS ▶")
+    btn1.setObjectName("RunBtn")
+    btn1.clicked.connect(explorer.on_run_planner)
+    pan1.main_layout.addWidget(btn1)
+    l1.addWidget(pan1)
+    explorer.stacked_tools.addWidget(p1)
+    explorer.run_buttons.append(btn1)
+    explorer.on_planner_source_changed()
diff --git a/src/uq_desktop_processor/gui/shell/ui/pages/vit_scoring.py b/src/uq_desktop_processor/gui/shell/ui/pages/vit_scoring.py
new file mode 100644
index 0000000..0c66d3f
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/pages/vit_scoring.py
@@ -0,0 +1,113 @@
+"""
+Stacked tool page: fine-tuned ViT scoring configuration and batch runs.
+"""
+
+from typing import TYPE_CHECKING
+
+from PySide6.QtWidgets import (
+    QComboBox,
+    QFormLayout,
+    QHBoxLayout,
+    QLineEdit,
+    QPushButton,
+    QSpinBox,
+    QVBoxLayout,
+    QWidget,
+)
+
+from uq_desktop_processor.gui.widgets import NeonPanel
+
+if TYPE_CHECKING:
+    from uq_desktop_processor.gui.shell.explorer import UrbanQualityAIExplorer
+
+
+def add_vit_scoring_page(explorer: "UrbanQualityAIExplorer") -> None:
+    """
+    Run add vit scoring page.
+
+    :param explorer: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: add_vit_scoring_page(explorer)
+        Out: UI/application state updated as intended.
+    """
+    p5 = QWidget()
+    l5 = QVBoxLayout(p5)
+    pan5 = NeonPanel(
+        "ViT scoring (fine-tuned)",
+        "Score images with a fine-tuned ViT model and write a GeoPackage layer.",
+    )
+    f5 = QFormLayout()
+
+    imgs_row = QHBoxLayout()
+    explorer.vit_images_dir_edit = QLineEdit("")
+    explorer.vit_images_dir_edit.setPlaceholderText("folder with images (required)")
+    btn_imgs = QPushButton("…")
+    btn_imgs.setFixedWidth(36)
+    btn_imgs.clicked.connect(lambda: explorer.pick_folder(explorer.vit_images_dir_edit))
+    imgs_row.addWidget(explorer.vit_images_dir_edit)
+    imgs_row.addWidget(btn_imgs)
+    f5.addRow("Images folder", imgs_row)
+
+    model_row = QHBoxLayout()
+    explorer.vit_model_path_edit = QLineEdit("")
+    explorer.vit_model_path_edit.setPlaceholderText("model weights file (.pt/.pth) (required)")
+    btn_model = QPushButton("…")
+    btn_model.setFixedWidth(36)
+    btn_model.clicked.connect(lambda: explorer.pick_file(explorer.vit_model_path_edit, "Model (*.pt *.pth)"))
+    model_row.addWidget(explorer.vit_model_path_edit)
+    model_row.addWidget(btn_model)
+    f5.addRow("Model path", model_row)
+
+    cal_row = QHBoxLayout()
+    explorer.vit_calibrators_edit = QLineEdit("")
+    explorer.vit_calibrators_edit.setPlaceholderText("(optional) folder with calibrators; empty = calibration OFF")
+    btn_cal = QPushButton("…")
+    btn_cal.setFixedWidth(36)
+    btn_cal.clicked.connect(lambda: explorer.pick_folder(explorer.vit_calibrators_edit))
+    cal_row.addWidget(explorer.vit_calibrators_edit)
+    cal_row.addWidget(btn_cal)
+    f5.addRow("Calibrators dir", cal_row)
+
+    vit_out_row = QHBoxLayout()
+    explorer.vit_output_path_edit = QLineEdit("")
+    explorer.vit_output_path_edit.setPlaceholderText("e.g. results/vit_scores.gpkg (include .gpkg)")
+    btn_vit_out = QPushButton("…")
+    btn_vit_out.setFixedWidth(36)
+    btn_vit_out.clicked.connect(lambda: explorer.pick_save_gpkg(explorer.vit_output_path_edit))
+    vit_out_row.addWidget(explorer.vit_output_path_edit)
+    vit_out_row.addWidget(btn_vit_out)
+    f5.addRow("Output layer (.gpkg)", vit_out_row)
+
+    explorer.vit_output_layer_name_edit = QLineEdit("vit_finetuned_scores")
+    f5.addRow("Layer name", explorer.vit_output_layer_name_edit)
+
+    explorer.vit_model_name_edit = QLineEdit("vit_base_patch14_dinov2.lvd142m")
+    f5.addRow("Model name", explorer.vit_model_name_edit)
+
+    explorer.vit_image_size_spin = QSpinBox()
+    explorer.vit_image_size_spin.setRange(128, 1024)
+    explorer.vit_image_size_spin.setValue(224)
+    f5.addRow("Image size", explorer.vit_image_size_spin)
+
+    explorer.vit_batch_size_spin = QSpinBox()
+    explorer.vit_batch_size_spin.setRange(1, 256)
+    explorer.vit_batch_size_spin.setValue(32)
+    f5.addRow("Batch size", explorer.vit_batch_size_spin)
+
+    explorer.vit_device_combo = QComboBox()
+    explorer.vit_device_combo.addItem("Auto (CUDA if FORCE_CUDA=1)", "auto")
+    explorer.vit_device_combo.addItem("CPU", "cpu")
+    explorer.vit_device_combo.addItem("CUDA", "cuda")
+    f5.addRow("Torch device", explorer.vit_device_combo)
+
+    pan5.main_layout.addLayout(f5)
+    pan5.main_layout.addStretch()
+    btn5 = QPushButton("EVALUATE (ViT) ⚙")
+    btn5.setObjectName("RunBtn")
+    btn5.clicked.connect(explorer.on_run_vit_evaluate)
+    pan5.main_layout.addWidget(btn5)
+    l5.addWidget(pan5)
+    explorer.stacked_tools.addWidget(p5)
+    explorer.run_buttons.append(btn5)
diff --git a/src/uq_desktop_processor/gui/shell/ui/placeholders.py b/src/uq_desktop_processor/gui/shell/ui/placeholders.py
new file mode 100644
index 0000000..b42004b
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/ui/placeholders.py
@@ -0,0 +1,38 @@
+"""
+Placeholder pages and stub widgets for shell sections not yet implemented.
+"""
+
+from PySide6.QtWidgets import QPushButton, QStackedWidget, QVBoxLayout, QWidget
+
+from uq_desktop_processor.gui.widgets import NeonPanel
+
+
+def add_placeholder_tool_page(
+    stacked_tools: QStackedWidget,
+    run_buttons: list[QPushButton],
+    *,
+    title: str,
+    description: str,
+) -> None:
+    """
+    Run add placeholder tool page.
+
+    :param stacked_tools: See caller/context.
+    :param run_buttons: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: add_placeholder_tool_page(stacked_tools, run_buttons)
+        Out: UI/application state updated as intended.
+    """
+    page = QWidget()
+    layout = QVBoxLayout(page)
+    panel = NeonPanel(title, description)
+    panel.main_layout.addStretch()
+    btn = QPushButton("COMING SOON")
+    btn.setObjectName("RunBtn")
+    btn.setEnabled(False)
+    panel.main_layout.addWidget(btn)
+    layout.addWidget(panel)
+    stacked_tools.addWidget(page)
+    run_buttons.append(btn)
diff --git a/src/uq_desktop_processor/gui/shell/worker.py b/src/uq_desktop_processor/gui/shell/worker.py
new file mode 100644
index 0000000..79ee920
--- /dev/null
+++ b/src/uq_desktop_processor/gui/shell/worker.py
@@ -0,0 +1,47 @@
+"""
+QThread-based workers for running pipeline steps without blocking the GUI.
+"""
+
+from collections.abc import Callable
+from typing import Any
+
+from PySide6.QtCore import QObject, QThread, Signal
+
+
+class StepThread(QThread):
+    """
+    StepThread UI helper class.
+    """
+
+    finished = Signal(object, str)
+
+    def __init__(self, func: Callable[[], Any], parent: QObject | None = None) -> None:
+        """
+        Run   init  .
+
+        :param func: See caller/context.
+        :param parent: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: __init__(func, parent)
+            Out: UI/application state updated as intended.
+        """
+        super().__init__(parent)
+        self._func = func
+
+    def run(self) -> None:
+        """
+        Run run.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: run()
+            Out: UI/application state updated as intended.
+        """
+        try:
+            result = self._func()
+            self.finished.emit(result, "")
+        except Exception as error:
+            self.finished.emit(None, str(error))
diff --git a/src/uq_desktop_processor/gui/styles/__init__.py b/src/uq_desktop_processor/gui/styles/__init__.py
new file mode 100644
index 0000000..133aeb7
--- /dev/null
+++ b/src/uq_desktop_processor/gui/styles/__init__.py
@@ -0,0 +1,7 @@
+"""
+GUI module:   init  .
+"""
+
+from .theme import NEON_STYLE
+
+__all__ = ["NEON_STYLE"]
diff --git a/src/uq_desktop_processor/gui/styles/theme.py b/src/uq_desktop_processor/gui/styles/theme.py
new file mode 100644
index 0000000..3b0172b
--- /dev/null
+++ b/src/uq_desktop_processor/gui/styles/theme.py
@@ -0,0 +1,225 @@
+"""
+Neon-style Qt stylesheet (QSS) strings and palette for the UrbanQuality-AI GUI.
+"""
+
+NEON_STYLE = """
+QMainWindow {
+    background-color: #050505;
+}
+
+QFrame#Sidebar {
+    background-color: #0a0a0a;
+    border-right: 1px solid #00f2ff;
+}
+
+QFrame#PanelBackground {
+    background-color: #0d0d0d;
+    border: 1px solid #1a1a1a;
+    border-radius: 10px;
+}
+
+QSplitter::handle {
+    background-color: #1a1a1a;
+}
+
+QSplitter::handle:horizontal {
+    width: 4px;
+}
+
+QSplitter::handle:hover {
+    background-color: #00f2ff;
+}
+
+QLabel {
+    color: #00f2ff;
+    font-family: 'Segoe UI', sans-serif;
+    text-transform: uppercase;
+    font-weight: bold;
+    font-size: 10px;
+}
+
+QLabel#PanelTitle {
+    font-size: 14px;
+    letter-spacing: 2px;
+    margin-bottom: 8px;
+    color: #fff;
+    border-bottom: 1px solid #00f2ff;
+    padding-bottom: 5px;
+}
+
+QLabel#PanelSubtitle {
+    font-size: 11px;
+    font-weight: normal;
+    text-transform: none;
+    letter-spacing: 0px;
+    color: #9cf;
+    margin-top: 0px;
+    margin-bottom: 12px;
+}
+
+QLineEdit, QComboBox, QSpinBox, QDoubleSpinBox, QPlainTextEdit {
+    background-color: #111;
+    border: 1px solid #333;
+    color: #fff;
+    padding: 8px;
+    border-radius: 2px;
+}
+
+QAbstractSpinBox {
+    /* Reserve space for the right-side buttons so clicks don't land on the editor area. */
+    padding-right: 24px;
+}
+
+QAbstractSpinBox::up-button, QAbstractSpinBox::down-button {
+    subcontrol-origin: padding;
+    width: 18px;
+    border-left: 1px solid #333;
+}
+
+QSpinBox::up-arrow, QDoubleSpinBox::up-arrow {
+    image: none;
+    width: 10px;
+    height: 10px;
+    border-left: 5px solid transparent;
+    border-right: 5px solid transparent;
+    border-bottom: 7px solid #0b7a2a;
+}
+
+QSpinBox::down-arrow, QDoubleSpinBox::down-arrow {
+    image: none;
+    width: 10px;
+    height: 10px;
+    border-left: 5px solid transparent;
+    border-right: 5px solid transparent;
+    border-top: 7px solid #8a1f1f;
+}
+
+QAbstractSpinBox::up-button {
+    subcontrol-position: top right;
+    height: 14px;
+    background-color: #151515;
+    border-bottom: 1px solid #262626;
+}
+
+QAbstractSpinBox::down-button {
+    subcontrol-position: bottom right;
+    height: 14px;
+    background-color: #151515;
+    border-top: 1px solid #262626;
+}
+
+QAbstractSpinBox::up-button:hover, QAbstractSpinBox::down-button:hover {
+    border-left: 1px solid #00f2ff;
+    background-color: #1f1f1f;
+}
+
+QLineEdit:focus, QPlainTextEdit:focus {
+    border: 1px solid #00f2ff;
+}
+
+QPushButton#SidebarBtn {
+    background-color: transparent;
+    border: none;
+    color: #444;
+    padding: 15px;
+    font-size: 20px;
+}
+
+QPushButton#SidebarBtn:hover {
+    color: #00f2ff;
+}
+
+QPushButton#SidebarBtn:checked {
+    color: #00f2ff;
+    background-color: #001a1a;
+    border-left: 3px solid #00f2ff;
+}
+
+QPushButton#RunBtn {
+    background-color: #00f2ff;
+    color: #000;
+    font-weight: bold;
+    font-size: 11px;
+    padding: 12px;
+    border-radius: 5px;
+    margin-top: 10px;
+}
+
+QPushButton#RunBtn:hover {
+    background-color: #55faff;
+}
+
+QPushButton#RunBtn:disabled {
+    background-color: #333;
+    color: #666;
+}
+
+QTextEdit#Console {
+    background-color: #050505;
+    border: 1px solid #1a1a1a;
+    color: #00ff41;
+    font-family: 'Consolas', monospace;
+    font-size: 11px;
+}
+
+QProgressBar {
+    border: 1px solid #1a1a1a;
+    background-color: #0a0a0a;
+    text-align: center;
+    color: #fff;
+    height: 10px;
+}
+
+QProgressBar::chunk {
+    background-color: #00f2ff;
+}
+
+QFrame#MapLayerPanel {
+    background-color: rgba(10, 10, 10, 220);
+    border: 1px solid rgba(0, 242, 255, 0.28);
+    border-radius: 8px;
+    min-width: 168px;
+}
+
+QLabel#MapLayerTitle {
+    color: #fff;
+    font-size: 11px;
+    letter-spacing: 1px;
+    padding: 6px 8px 2px 8px;
+}
+
+QListWidget#MapLayerList {
+    background-color: #050505;
+    border: none;
+    color: #ccc;
+    font-size: 11px;
+    outline: none;
+}
+
+QListWidget#MapLayerList::item {
+    padding: 6px 4px;
+    border-radius: 4px;
+}
+
+QListWidget#MapLayerList::item:selected {
+    background-color: #001a1a;
+    color: #00f2ff;
+}
+
+QListWidget#MapLayerList::item:hover:!active {
+    background-color: #111;
+}
+
+QPushButton#LayerOrderUp, QPushButton#LayerOrderDown {
+    background-color: #111;
+    border: 1px solid #333;
+    color: #00f2ff;
+    font-size: 10px;
+    padding: 4px 6px;
+    border-radius: 3px;
+}
+
+QPushButton#LayerOrderUp:hover, QPushButton#LayerOrderDown:hover {
+    border: 1px solid #00f2ff;
+}
+"""
diff --git a/src/uq_desktop_processor/gui/widgets/__init__.py b/src/uq_desktop_processor/gui/widgets/__init__.py
new file mode 100644
index 0000000..a3b3e76
--- /dev/null
+++ b/src/uq_desktop_processor/gui/widgets/__init__.py
@@ -0,0 +1,16 @@
+"""
+GUI module:   init  .
+"""
+
+from .deck_map import DeckMapWidget
+from .map_layer_list import MapLayerListWidget
+from .map_web_stack import MapWebStack
+from .stacked import CompactStackedWidget, NeonPanel
+
+__all__ = [
+    "CompactStackedWidget",
+    "DeckMapWidget",
+    "MapLayerListWidget",
+    "MapWebStack",
+    "NeonPanel",
+]
diff --git a/src/uq_desktop_processor/gui/widgets/deck_map/__init__.py b/src/uq_desktop_processor/gui/widgets/deck_map/__init__.py
new file mode 100644
index 0000000..98e2669
--- /dev/null
+++ b/src/uq_desktop_processor/gui/widgets/deck_map/__init__.py
@@ -0,0 +1,7 @@
+"""
+GUI module:   init  .
+"""
+
+from .widget import DeckMapWidget
+
+__all__ = ["DeckMapWidget"]
diff --git a/src/uq_desktop_processor/gui/widgets/deck_map/layer_panel.py b/src/uq_desktop_processor/gui/widgets/deck_map/layer_panel.py
new file mode 100644
index 0000000..1784353
--- /dev/null
+++ b/src/uq_desktop_processor/gui/widgets/deck_map/layer_panel.py
@@ -0,0 +1,186 @@
+"""
+Side panel UI for toggling and ordering PyDeck map layers.
+"""
+
+from collections.abc import Callable
+from typing import Any
+
+from PySide6.QtCore import Qt
+from PySide6.QtWidgets import (
+    QAbstractItemView,
+    QFrame,
+    QHBoxLayout,
+    QLabel,
+    QListWidgetItem,
+    QPushButton,
+    QVBoxLayout,
+    QWidget,
+)
+
+from uq_desktop_processor.gui.widgets.map_layer_list import MapLayerListWidget
+
+
+class LayerPanel:
+    """
+    LayerPanel UI helper class.
+    """
+
+    _LAYER_ID_ROLE: int = int(Qt.ItemDataRole.UserRole)
+
+    def __init__(
+        self,
+        parent: QWidget,
+        *,
+        layer_ids_top_first: list[str],
+        layer_labels: dict[str, str],
+        on_changed: Callable[[], None],
+        on_reordered: Callable[[], None],
+        on_move_up: Callable[[], None],
+        on_move_down: Callable[[], None],
+    ) -> None:
+        """
+        Run   init  .
+
+        :param parent: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: __init__(parent)
+            Out: UI/application state updated as intended.
+        """
+        self.layer_ids_top_first = layer_ids_top_first
+        self._layer_labels = layer_labels
+        self._on_changed = on_changed
+        self._on_reordered = on_reordered
+
+        panel = QFrame(parent)
+        panel.setObjectName("MapLayerPanel")
+        panel_layout = QVBoxLayout(panel)
+        panel_layout.setContentsMargins(6, 4, 6, 6)
+        panel_layout.setSpacing(4)
+
+        title = QLabel("Layers")
+        title.setObjectName("MapLayerTitle")
+        panel_layout.addWidget(title)
+
+        self.list = MapLayerListWidget(panel)
+        self.list.setObjectName("MapLayerList")
+        self.list.setMaximumHeight(200)
+        self.list.setHorizontalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOff)
+        self.list.setVerticalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAsNeeded)
+        self.list.setDragDropMode(QAbstractItemView.DragDropMode.InternalMove)
+        self.list.setDefaultDropAction(Qt.DropAction.MoveAction)
+        self.list.setDragDropOverwriteMode(False)
+        self.list.setSelectionMode(QAbstractItemView.SelectionMode.SingleSelection)
+        self.list.setSpacing(2)
+
+        for lid in layer_ids_top_first:
+            item = QListWidgetItem(layer_labels[lid])
+            item.setData(self._LAYER_ID_ROLE, lid)
+            item.setFlags(Qt.ItemFlag.NoItemFlags)
+            self.list.addItem(item)
+
+        self.list.itemChanged.connect(lambda _it: self._on_changed())
+        self.list.model().rowsMoved.connect(lambda *_a: self._on_reordered())
+        self.list.reordered.connect(lambda *_a: self._on_reordered())
+        panel_layout.addWidget(self.list, 1)
+
+        order_row = QHBoxLayout()
+        order_row.setSpacing(6)
+        btn_up = QPushButton("▲ Up")
+        btn_up.setObjectName("LayerOrderUp")
+        btn_up.setToolTip("Higher in the list = drawn above lower layers")
+        btn_up.clicked.connect(on_move_up)
+        btn_down = QPushButton("▼ Down")
+        btn_down.setObjectName("LayerOrderDown")
+        btn_down.clicked.connect(on_move_down)
+        order_row.addWidget(btn_up)
+        order_row.addWidget(btn_down)
+        panel_layout.addLayout(order_row)
+
+        self.widget = panel
+
+    def item_for_layer(self, lid: str) -> QListWidgetItem | None:
+        """
+        Run item for layer.
+
+        :param lid: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: item_for_layer(lid)
+            Out: UI/application state updated as intended.
+        """
+        for row in range(self.list.count()):
+            it = self.list.item(row)
+            if it is not None and it.data(self._LAYER_ID_ROLE) == lid:
+                return it
+        return None
+
+    def layer_order_top_to_bottom(self) -> list[str]:
+        """
+        Run layer order top to bottom.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: layer_order_top_to_bottom()
+            Out: UI/application state updated as intended.
+        """
+        out: list[str] = []
+        for row in range(self.list.count()):
+            it = self.list.item(row)
+            if it is None:
+                continue
+            lid = it.data(self._LAYER_ID_ROLE)
+            if isinstance(lid, str):
+                out.append(lid)
+        return out
+
+    def layer_checked(self, lid: str) -> bool:
+        """
+        Run layer checked.
+
+        :param lid: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: layer_checked(lid)
+            Out: UI/application state updated as intended.
+        """
+        item = self.item_for_layer(lid)
+        if item is None:
+            return False
+        return item.checkState() == Qt.CheckState.Checked
+
+    @staticmethod
+    def active_item_flags() -> Any:
+        """
+        Run active item flags.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: active_item_flags()
+            Out: UI/application state updated as intended.
+        """
+        return (
+            Qt.ItemFlag.ItemIsEnabled
+            | Qt.ItemFlag.ItemIsSelectable
+            | Qt.ItemFlag.ItemIsUserCheckable
+            | Qt.ItemFlag.ItemIsDragEnabled
+            | Qt.ItemFlag.ItemIsDropEnabled
+        )
+
+    @staticmethod
+    def inactive_item_flags() -> Any:
+        """
+        Run inactive item flags.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: inactive_item_flags()
+            Out: UI/application state updated as intended.
+        """
+        return Qt.ItemFlag.ItemIsEnabled | Qt.ItemFlag.ItemIsSelectable | Qt.ItemFlag.ItemIsDragEnabled
diff --git a/src/uq_desktop_processor/gui/widgets/deck_map/layers.py b/src/uq_desktop_processor/gui/widgets/deck_map/layers.py
new file mode 100644
index 0000000..0fcffa8
--- /dev/null
+++ b/src/uq_desktop_processor/gui/widgets/deck_map/layers.py
@@ -0,0 +1,273 @@
+"""
+Constructs PyDeck layers from geodata and evaluation overlays with tooltips.
+"""
+
+import json
+import math
+from typing import Any
+
+import geopandas as gpd
+import pydeck as pdk
+
+from uq_desktop_processor.gui.map_view.constants import EULER_LINE_COLORS
+from uq_desktop_processor.gui.map_view.data import (
+    euler_polylines_for_display,
+    evaluation_scatter_data,
+    map_display_budgets,
+    red_yellow_green_rgba,
+    simplify_roads_gdf_for_map_display,
+)
+
+
+def roads_geojson_layer(
+    roads_gdf: gpd.GeoDataFrame | None,
+    *,
+    simplify_meters: float,
+    max_features: int,
+    line_rgba: tuple[int, int, int, int] = (68, 68, 68, 235),
+) -> Any:
+    """
+    Run roads geojson layer.
+
+    :param roads_gdf: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: roads_geojson_layer(roads_gdf)
+        Out: UI/application state updated as intended.
+    """
+    if roads_gdf is None or roads_gdf.empty:
+        return None
+    display_roads_gdf = simplify_roads_gdf_for_map_display(
+        roads_gdf.to_crs(4326),
+        simplify_meters=simplify_meters,
+        max_features=max_features,
+    )
+    if display_roads_gdf.empty:
+        return None
+    data = json.loads(display_roads_gdf.to_json())
+    return pdk.Layer(
+        "GeoJsonLayer",
+        id="roads-layer",
+        data=data,
+        stroked=True,
+        filled=False,
+        line_width_min_pixels=1,
+        get_line_color=list(line_rgba),
+        pickable=False,
+        opacity=0.8,
+        parameters={"depthTest": False},
+    )
+
+
+def append_bounds_roads(roads_gdf: gpd.GeoDataFrame | None, lons: list[float], lats: list[float]) -> None:
+    """
+    Run append bounds roads.
+
+    :param roads_gdf: See caller/context.
+    :param lons: See caller/context.
+    :param lats: See caller/context.
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: append_bounds_roads(roads_gdf, lons, lats)
+        Out: UI/application state updated as intended.
+    """
+    if roads_gdf is None or roads_gdf.empty:
+        return
+    bounds = roads_gdf.to_crs(4326).total_bounds
+    lons.extend([float(bounds[0]), float(bounds[2])])
+    lats.extend([float(bounds[1]), float(bounds[3])])
+
+
+def bounds_for_all_data(
+    *,
+    planner_roads: gpd.GeoDataFrame | None,
+    planner_points: list[tuple[float, float]],
+    euler_polylines: list[list[tuple[float, float]]],
+    eval_results: dict[str, Any] | None,
+) -> tuple[list[float], list[float]]:
+    """
+    Run bounds for all data.
+
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: bounds_for_all_data()
+        Out: UI/application state updated as intended.
+    """
+    lons: list[float] = []
+    lats: list[float] = []
+    append_bounds_roads(planner_roads, lons, lats)
+    for lat, lon in planner_points:
+        lons.append(float(lon))
+        lats.append(float(lat))
+    for poly in euler_polylines:
+        for lon, la in poly:
+            lons.append(float(lon))
+            lats.append(float(la))
+    if eval_results:
+        lon, la, _s = evaluation_scatter_data(eval_results)
+        for i in range(len(lon)):
+            lons.append(float(lon[i]))
+            lats.append(float(la[i]))
+    return lons, lats
+
+
+def build_deck_layers(
+    *,
+    layer_order_top_to_bottom: list[str],
+    layer_checked: dict[str, bool],
+    layer_has_data: dict[str, bool],
+    planner_roads: gpd.GeoDataFrame | None,
+    planner_points: list[tuple[float, float]],
+    euler_polylines: list[list[tuple[float, float]]],
+    eval_results: dict[str, Any] | None,
+) -> list[Any]:
+    """
+    Run build deck layers.
+
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: build_deck_layers()
+        Out: UI/application state updated as intended.
+    """
+    order_bottom_first = list(reversed(layer_order_top_to_bottom))
+    layers: list[Any] = []
+    visible = sum(1 for lid, on in layer_checked.items() if on and layer_has_data.get(lid, False))
+    budgets = map_display_budgets(visible)
+    common_params = {"depthTest": False}
+
+    for lid in order_bottom_first:
+        if not layer_checked.get(lid, False) or not layer_has_data.get(lid, False):
+            continue
+        if lid == "roads":
+            layer = roads_geojson_layer(
+                planner_roads,
+                simplify_meters=float(budgets["road_simplify_meters"]),
+                max_features=int(budgets["road_max_features"]),
+            )
+            if layer is not None:
+                layers.append(layer)
+        elif lid == "points":
+            rows = [{"lon": float(lon), "lat": float(lat)} for lat, lon in planner_points]
+            cap = int(budgets["points_max"])
+            if len(rows) > cap:
+                step = max(1, math.ceil(len(rows) / cap))
+                rows = rows[::step]
+            layers.append(
+                pdk.Layer(
+                    "ScatterplotLayer",
+                    id="points-layer",
+                    data=rows,
+                    get_position="[lon, lat]",
+                    get_fill_color=[0, 242, 255, 195],
+                    get_line_color=[0, 242, 255, 255],
+                    stroked=True,
+                    line_width_min_pixels=1,
+                    get_radius=22,
+                    radius_min_pixels=4,
+                    radius_max_pixels=28,
+                    pickable=True,
+                    parameters=common_params,
+                )
+            )
+        elif lid == "euler":
+            paths: list[dict[str, Any]] = []
+            euler_polys = euler_polylines_for_display(
+                euler_polylines,
+                int(budgets["euler_vertex_budget"]),
+            )
+            for polyline_index, polyline in enumerate(euler_polys):
+                if len(polyline) < 2:
+                    continue
+                rgb = EULER_LINE_COLORS[polyline_index % len(EULER_LINE_COLORS)]
+                path = [[float(lon), float(lat)] for lon, lat in polyline]
+                paths.append({"path": path, "name": f"Sector {polyline_index + 1}", "color": [*rgb, 235]})
+            if paths:
+                layers.append(
+                    pdk.Layer(
+                        "PathLayer",
+                        id="euler-layer",
+                        data=paths,
+                        get_path="path",
+                        get_color="color",
+                        width_min_pixels=3,
+                        cap_rounded=True,
+                        joint_rounded=True,
+                        pickable=True,
+                        parameters=common_params,
+                    )
+                )
+        elif lid == "clip" and eval_results is not None:
+            lon_values, lat_values, scores = evaluation_scatter_data(eval_results)
+            if lon_values.size == 0:
+                continue
+            colors = red_yellow_green_rgba(scores)
+            rows = [
+                {
+                    "lon": float(lon_values[row_index]),
+                    "lat": float(lat_values[row_index]),
+                    "overall": round(float(scores[row_index]), 1),
+                    "color": colors[row_index],
+                }
+                for row_index in range(len(lon_values))
+            ]
+            cap = int(budgets["points_max"])
+            if len(rows) > cap:
+                step = max(1, math.ceil(len(rows) / cap))
+                rows = rows[::step]
+            layers.append(
+                pdk.Layer(
+                    "ScatterplotLayer",
+                    id="clip-layer",
+                    data=rows,
+                    get_position="[lon, lat]",
+                    get_fill_color="color",
+                    get_line_color=[0, 242, 255, 200],
+                    stroked=True,
+                    line_width_min_pixels=1,
+                    get_radius=26,
+                    radius_min_pixels=5,
+                    radius_max_pixels=32,
+                    pickable=True,
+                    parameters=common_params,
+                )
+            )
+    return layers
+
+
+def pick_tooltip(*, layer_checked: dict[str, bool], layer_has_data: dict[str, bool]) -> dict[str, Any]:
+    """
+    Run pick tooltip.
+
+    :return: Result of this step or updated UI/application state.
+
+    Example::
+        In: pick_tooltip()
+        Out: UI/application state updated as intended.
+    """
+    pickable_on = sum(
+        1
+        for layer_id in ("clip", "euler", "points")
+        if layer_checked.get(layer_id, False) and layer_has_data.get(layer_id, False)
+    )
+    if pickable_on > 1:
+        return {
+            "html": "<b>Layer:</b> {layer}<br/>Configure the view in the panel",
+            "style": {"backgroundColor": "#111", "color": "#fff", "fontSize": "10px"},
+        }
+    if layer_checked.get("clip", False) and layer_has_data.get("clip", False):
+        return {
+            "html": "<b>Avg estimation</b><br/>{overall}%",
+            "style": {"backgroundColor": "#111", "color": "#00ff41", "fontSize": "12px"},
+        }
+    if layer_checked.get("euler", False) and layer_has_data.get("euler", False):
+        return {
+            "html": "<b>{name}</b><br/>Euler / GPX",
+            "style": {"backgroundColor": "#111", "color": "#00f2ff"},
+        }
+    if layer_checked.get("points", False) and layer_has_data.get("points", False):
+        return {"html": "<b>Point</b><br/>{lat}, {lon}", "style": {"color": "#00f2ff"}}
+    return {}
diff --git a/src/uq_desktop_processor/gui/widgets/deck_map/web.py b/src/uq_desktop_processor/gui/widgets/deck_map/web.py
new file mode 100644
index 0000000..05f896f
--- /dev/null
+++ b/src/uq_desktop_processor/gui/widgets/deck_map/web.py
@@ -0,0 +1,167 @@
+"""
+Bridges PyDeck HTML output to Qt WebEngine (inject data, reload, callbacks).
+"""
+
+import logging
+from collections import deque
+from collections.abc import Callable
+from pathlib import Path
+from typing import Any, cast
+
+import pydeck as pdk
+from PySide6.QtCore import QTemporaryDir, QUrl
+from PySide6.QtWebEngineWidgets import QWebEngineView
+
+from uq_desktop_processor.gui.map_view.constants import DECK_VIEW_STATE_JS
+from uq_desktop_processor.gui.map_view.html import (
+    expose_deck_instance_on_window,
+    inject_mapbox_gl_css,
+    parse_view_state_json,
+    sanitize_pydeck_inline_json_html,
+)
+
+
+class DeckWebController:
+    """
+    DeckWebController UI helper class.
+    """
+
+    def __init__(self, web: QWebEngineView) -> None:
+        """
+        Run   init  .
+
+        :param web: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: __init__(web)
+            Out: UI/application state updated as intended.
+        """
+        self._web = web
+        self._deck_html_dir = QTemporaryDir()
+        if not self._deck_html_dir.isValid():
+            logging.getLogger(__name__).warning("QTemporaryDir for map HTML is invalid; using setHtml.")
+
+        self.map_commit_generation = 0
+        self.deck_surface_ready = False
+        self._deck_expecting_html_load = False
+        self._deck_html_gen = 0
+        self._deck_finish_queue: deque[int] = deque()
+
+        self._web.loadFinished.connect(self._on_deck_html_load_finished)
+
+    def _on_deck_html_load_finished(self, ok: bool) -> None:
+        """
+        Run  on deck html load finished.
+
+        :param ok: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _on_deck_html_load_finished(ok)
+            Out: UI/application state updated as intended.
+        """
+        if not self._deck_expecting_html_load or not self._deck_finish_queue:
+            return
+        finished_gen = self._deck_finish_queue.popleft()
+        if finished_gen != self._deck_html_gen:
+            return
+        self._deck_expecting_html_load = False
+        self.deck_surface_ready = bool(ok)
+        if not ok:
+            logging.getLogger(__name__).warning("WebEngine load failed.")
+
+    def set_deck_page_html(self, deck: pdk.Deck) -> None:
+        """
+        Run set deck page html.
+
+        :param deck: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: set_deck_page_html(deck)
+            Out: UI/application state updated as intended.
+        """
+        self._deck_html_gen += 1
+        self._deck_finish_queue.append(self._deck_html_gen)
+        self._deck_expecting_html_load = True
+        self.deck_surface_ready = False
+
+        raw = deck.to_html(as_string=True, css_background_color="#0d0d0d")
+        raw = sanitize_pydeck_inline_json_html(raw)
+        html = expose_deck_instance_on_window(inject_mapbox_gl_css(raw))
+        if self._deck_html_dir.isValid():
+            path = Path(self._deck_html_dir.path()) / "deck.html"
+            path.write_text(html, encoding="utf-8")
+            self._web.load(QUrl.fromLocalFile(str(path.resolve())))
+        else:
+            self._web.setHtml(html, QUrl("https://cdn.jsdelivr.net/"))
+
+    def clear_pending(self) -> None:
+        """
+        Run clear pending.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: clear_pending()
+            Out: UI/application state updated as intended.
+        """
+        self.deck_surface_ready = False
+        self._deck_expecting_html_load = False
+        self._deck_finish_queue.clear()
+
+    def schedule_reload_preserving_view(
+        self,
+        *,
+        on_view: Callable[[pdk.ViewState | None, int], None],
+    ) -> None:
+        """
+        Run schedule reload preserving view.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: schedule_reload_preserving_view()
+            Out: UI/application state updated as intended.
+        """
+        self.map_commit_generation += 1
+        gen = self.map_commit_generation
+        self._web.page().runJavaScript(
+            DECK_VIEW_STATE_JS,
+            lambda res, g=gen: self._on_deck_view_captured(res, g, on_view),
+        )
+
+    @staticmethod
+    def _on_deck_view_captured(
+        result: Any,
+        scheduled_gen: int,
+        on_view: Callable[[pdk.ViewState | None, int], None],
+    ) -> None:
+        """
+        Run  on deck view captured.
+
+        :param result: See caller/context.
+        :param scheduled_gen: See caller/context.
+        :param on_view: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _on_deck_view_captured(result, scheduled_gen, on_view)
+            Out: UI/application state updated as intended.
+        """
+        view: pdk.ViewState | None = None
+        if isinstance(result, dict):
+            parsed = parse_view_state_json(result)
+            if parsed is not None:
+                try:
+                    view = pdk.ViewState(
+                        latitude=float(cast(Any, parsed["latitude"])),
+                        longitude=float(cast(Any, parsed["longitude"])),
+                        zoom=float(cast(Any, parsed["zoom"])),
+                        pitch=float(cast(Any, parsed.get("pitch", 0))),
+                        bearing=float(cast(Any, parsed.get("bearing", 0))),
+                    )
+                except (KeyError, TypeError, ValueError):
+                    view = None
+        on_view(view, scheduled_gen)
diff --git a/src/uq_desktop_processor/gui/widgets/deck_map/widget.py b/src/uq_desktop_processor/gui/widgets/deck_map/widget.py
new file mode 100644
index 0000000..1410902
--- /dev/null
+++ b/src/uq_desktop_processor/gui/widgets/deck_map/widget.py
@@ -0,0 +1,468 @@
+"""
+Composite PyDeck map widget: web view, layer panel, and redraw orchestration.
+"""
+
+from typing import Any
+
+import geopandas as gpd
+import pydeck as pdk
+from PySide6.QtCore import Qt, QTimer, QUrl
+from PySide6.QtGui import QColor
+from PySide6.QtWebEngineCore import QWebEngineSettings
+from PySide6.QtWebEngineWidgets import QWebEngineView
+from PySide6.QtWidgets import QFrame, QLabel, QSizePolicy, QVBoxLayout, QWidget
+
+from uq_desktop_processor.gui.map_view.constants import (
+    MAP_LAYER_IDS_TOP_FIRST,
+    MAP_LAYER_LABELS,
+    MAP_REDRAW_DEBOUNCE_MS,
+)
+from uq_desktop_processor.gui.map_view.data import evaluation_scatter_data, fit_view_state
+from uq_desktop_processor.gui.widgets.deck_map.layer_panel import LayerPanel
+from uq_desktop_processor.gui.widgets.deck_map.layers import bounds_for_all_data, build_deck_layers, pick_tooltip
+from uq_desktop_processor.gui.widgets.deck_map.web import DeckWebController
+from uq_desktop_processor.gui.widgets.map_web_stack import MapWebStack
+
+
+class DeckMapWidget(QWidget):
+    """
+    DeckMapWidget UI helper class.
+    """
+
+    def __init__(self) -> None:
+        """
+        Run   init  .
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: __init__()
+            Out: UI/application state updated as intended.
+        """
+        super().__init__()
+        self._planner_roads: gpd.GeoDataFrame | None = None
+        self._planner_points: list[tuple[float, float]] = []
+        self._euler_polylines: list[list[tuple[float, float]]] = []
+        self._eval_results: dict[str, Any] | None = None
+
+        self._stored_view: Any = None
+        self._layers_first_auto_check: set[str] = set()
+
+        self._map_redraw_timer = QTimer(self)
+        self._map_redraw_timer.setSingleShot(True)
+        self._map_redraw_timer.setInterval(MAP_REDRAW_DEBOUNCE_MS)
+        self._map_redraw_timer.timeout.connect(self._flush_map_redraw)
+        self._map_redraw_wants_refit = False
+
+        root = QVBoxLayout(self)
+        root.setContentsMargins(0, 0, 0, 0)
+        root.setSpacing(0)
+
+        self._web = QWebEngineView(self)
+        self._web.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding)
+        wes = self._web.settings()
+        wes.setAttribute(QWebEngineSettings.WebAttribute.LocalContentCanAccessRemoteUrls, True)
+        wes.setAttribute(QWebEngineSettings.WebAttribute.LocalContentCanAccessFileUrls, True)
+        self._web.setStyleSheet("background-color: #0d0d0d;")
+        self._web.page().setBackgroundColor(QColor(0x0D, 0x0D, 0x0D))
+
+        self._deck_web = DeckWebController(self._web)
+
+        self._map_idle_overlay = QFrame(self)
+        self._map_idle_overlay.setObjectName("MapIdleOverlay")
+        self._map_idle_overlay.setStyleSheet(
+            "QFrame#MapIdleOverlay { background-color: rgba(13, 13, 13, 0.96); border: 1px solid #2a2a2a; }"
+        )
+        idle_layout = QVBoxLayout(self._map_idle_overlay)
+        idle_layout.addStretch(1)
+        idle_msg = QLabel(
+            "The map becomes active after generating the first preview layer\n"
+            "(roads, sampling points, Euler/GPX routes, or CLIP results)."
+        )
+        idle_msg.setWordWrap(True)
+        idle_msg.setAlignment(Qt.AlignmentFlag.AlignCenter)
+        idle_msg.setStyleSheet("color: #777; font-size: 12px; padding: 28px;")
+        idle_layout.addWidget(idle_msg)
+        idle_layout.addStretch(1)
+
+        self._layer_panel = LayerPanel(
+            self,
+            layer_ids_top_first=list(MAP_LAYER_IDS_TOP_FIRST),
+            layer_labels=MAP_LAYER_LABELS,
+            on_changed=lambda: self._request_map_redraw(refit=False),
+            on_reordered=lambda: self._request_map_redraw(refit=False),
+            on_move_up=self._move_layer_up,
+            on_move_down=self._move_layer_down,
+        )
+
+        self._map_web_host = MapWebStack(self._web, self._map_idle_overlay, self._layer_panel.widget)
+        self._map_web_host.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding)
+        root.addWidget(self._map_web_host, 1)
+
+        self.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding)
+        self._sync_layer_list_items()
+        self._apply_map_redraw(refit=True)
+
+    def _has_roads_data(self) -> bool:
+        """
+        Run  has roads data.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _has_roads_data()
+            Out: UI/application state updated as intended.
+        """
+        return self._planner_roads is not None and not self._planner_roads.empty
+
+    def _has_points_data(self) -> bool:
+        """
+        Run  has points data.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _has_points_data()
+            Out: UI/application state updated as intended.
+        """
+        return bool(self._planner_points)
+
+    def _has_euler_data(self) -> bool:
+        """
+        Run  has euler data.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _has_euler_data()
+            Out: UI/application state updated as intended.
+        """
+        return any(len(polyline) >= 2 for polyline in self._euler_polylines)
+
+    def _has_clip_data(self) -> bool:
+        """
+        Run  has clip data.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _has_clip_data()
+            Out: UI/application state updated as intended.
+        """
+        if not self._eval_results:
+            return False
+        lon_values, _lat_values, _score_values = evaluation_scatter_data(self._eval_results)
+        return lon_values.size > 0
+
+    def _layer_has_data(self, layer_id: str) -> bool:
+        """
+        Run  layer has data.
+
+        :param layer_id: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _layer_has_data(layer_id)
+            Out: UI/application state updated as intended.
+        """
+        return {
+            "roads": self._has_roads_data(),
+            "points": self._has_points_data(),
+            "euler": self._has_euler_data(),
+            "clip": self._has_clip_data(),
+        }[layer_id]
+
+    def _has_any_map_data(self) -> bool:
+        """
+        Run  has any map data.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _has_any_map_data()
+            Out: UI/application state updated as intended.
+        """
+        return any(self._layer_has_data(lid) for lid in MAP_LAYER_IDS_TOP_FIRST)
+
+    def _sync_layer_list_items(self) -> None:
+        """
+        Run  sync layer list items.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _sync_layer_list_items()
+            Out: UI/application state updated as intended.
+        """
+        self._layer_panel.list.blockSignals(True)
+        try:
+            for layer_id in MAP_LAYER_IDS_TOP_FIRST:
+                item = self._layer_panel.item_for_layer(layer_id)
+                if item is None:
+                    continue
+                has_data = self._layer_has_data(layer_id)
+                if has_data:
+                    item.setFlags(self._layer_panel.active_item_flags())
+                    if layer_id not in self._layers_first_auto_check:
+                        # Auto-enable a layer once when its data appears for the first time.
+                        item.setCheckState(Qt.CheckState.Checked)
+                        self._layers_first_auto_check.add(layer_id)
+                else:
+                    # Data disappeared (or was reset), so disable the item again.
+                    self._layers_first_auto_check.discard(layer_id)
+                    item.setCheckState(Qt.CheckState.Unchecked)
+                    item.setFlags(self._layer_panel.inactive_item_flags())
+        finally:
+            self._layer_panel.list.blockSignals(False)
+
+    def _move_layer_up(self) -> None:
+        """
+        Run  move layer up.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _move_layer_up()
+            Out: UI/application state updated as intended.
+        """
+        row = self._layer_panel.list.currentRow()
+        if row <= 0:
+            return
+        self._layer_panel.list.blockSignals(True)
+        try:
+            item = self._layer_panel.list.takeItem(row)
+            if item:
+                self._layer_panel.list.insertItem(row - 1, item)
+                self._layer_panel.list.setCurrentRow(row - 1)
+        finally:
+            self._layer_panel.list.blockSignals(False)
+        self._request_map_redraw(refit=False)
+
+    def _move_layer_down(self) -> None:
+        """
+        Run  move layer down.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _move_layer_down()
+            Out: UI/application state updated as intended.
+        """
+        row = self._layer_panel.list.currentRow()
+        # Nothing to move when no selection or already at the last row.
+        if row < 0 or row >= self._layer_panel.list.count() - 1:
+            return
+        self._layer_panel.list.blockSignals(True)
+        try:
+            item = self._layer_panel.list.takeItem(row)
+            if item:
+                self._layer_panel.list.insertItem(row + 1, item)
+                self._layer_panel.list.setCurrentRow(row + 1)
+        finally:
+            self._layer_panel.list.blockSignals(False)
+        self._request_map_redraw(refit=False)
+
+    def _bounds_for_all_data(self) -> tuple[list[float], list[float]]:
+        """
+        Run  bounds for all data.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _bounds_for_all_data()
+            Out: UI/application state updated as intended.
+        """
+        return bounds_for_all_data(
+            planner_roads=self._planner_roads,
+            planner_points=self._planner_points,
+            euler_polylines=self._euler_polylines,
+            eval_results=self._eval_results,
+        )
+
+    def _build_deck_layers(self) -> list[Any]:
+        """
+        Run  build deck layers.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _build_deck_layers()
+            Out: UI/application state updated as intended.
+        """
+        order_top_first = self._layer_panel.layer_order_top_to_bottom()
+        checked = {layer_id: self._layer_panel.layer_checked(layer_id) for layer_id in MAP_LAYER_IDS_TOP_FIRST}
+        has_data = {layer_id: self._layer_has_data(layer_id) for layer_id in MAP_LAYER_IDS_TOP_FIRST}
+        return build_deck_layers(
+            layer_order_top_to_bottom=order_top_first,
+            layer_checked=checked,
+            layer_has_data=has_data,
+            planner_roads=self._planner_roads,
+            planner_points=self._planner_points,
+            euler_polylines=self._euler_polylines,
+            eval_results=self._eval_results,
+        )
+
+    def _pick_tooltip(self) -> dict[str, Any]:
+        """
+        Run  pick tooltip.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _pick_tooltip()
+            Out: UI/application state updated as intended.
+        """
+        checked = {layer_id: self._layer_panel.layer_checked(layer_id) for layer_id in MAP_LAYER_IDS_TOP_FIRST}
+        has_data = {layer_id: self._layer_has_data(layer_id) for layer_id in MAP_LAYER_IDS_TOP_FIRST}
+        return pick_tooltip(layer_checked=checked, layer_has_data=has_data)
+
+    def _request_map_redraw(self, refit: bool) -> None:
+        """
+        Run  request map redraw.
+
+        :param refit: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _request_map_redraw(refit)
+            Out: UI/application state updated as intended.
+        """
+        self._map_redraw_wants_refit = self._map_redraw_wants_refit or refit
+        self._map_redraw_timer.start()
+
+    def _flush_map_redraw(self) -> None:
+        """
+        Run  flush map redraw.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _flush_map_redraw()
+            Out: UI/application state updated as intended.
+        """
+        refit = self._map_redraw_wants_refit
+        self._map_redraw_wants_refit = False
+        self._apply_map_redraw(refit=refit)
+
+    def _apply_map_redraw(self, *, refit: bool) -> None:
+        """
+        Run  apply map redraw.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _apply_map_redraw()
+            Out: UI/application state updated as intended.
+        """
+        if not self._has_any_map_data():
+            self._deck_web.clear_pending()
+            self._stored_view = None
+            self._map_idle_overlay.setVisible(True)
+            self._web.setEnabled(False)
+            self._web.setHtml(
+                '<!DOCTYPE html><html><head><meta charset="utf-8"/>'
+                "<style>html,body{margin:0;height:100%;background:#0d0d0d;}</style></head><body></body></html>",
+                QUrl("about:blank"),
+            )
+            return
+
+        self._map_idle_overlay.setVisible(False)
+        self._web.setEnabled(True)
+
+        longitudes, latitudes = self._bounds_for_all_data()
+
+        if refit or self._stored_view is None or not self._deck_web.deck_surface_ready:
+            self._deck_web.map_commit_generation += 1
+            self._stored_view = fit_view_state(longitudes, latitudes)
+            deck = pdk.Deck(
+                layers=self._build_deck_layers(),
+                initial_view_state=self._stored_view,
+                map_style=pdk.map_styles.CARTO_DARK,
+                tooltip=self._pick_tooltip(),
+            )
+            self._deck_web.set_deck_page_html(deck)
+            return
+
+        def _on_view(view: pdk.ViewState | None, generation: int) -> None:
+            """
+            Run  on view.
+
+            :param view: See caller/context.
+            :param generation: See caller/context.
+            :return: Result of this step or updated UI/application state.
+
+            Example::
+                In: _on_view(view, generation)
+                Out: UI/application state updated as intended.
+            """
+            if generation != self._deck_web.map_commit_generation:
+                return
+            if view is not None:
+                self._stored_view = view
+            elif self._stored_view is None:
+                self._stored_view = fit_view_state(longitudes, latitudes)
+            deck = pdk.Deck(
+                layers=self._build_deck_layers(),
+                initial_view_state=self._stored_view,
+                map_style=pdk.map_styles.CARTO_DARK,
+                tooltip=self._pick_tooltip(),
+            )
+            self._deck_web.set_deck_page_html(deck)
+
+        self._deck_web.schedule_reload_preserving_view(on_view=_on_view)
+
+    def update_planner_layers(
+        self,
+        roads_gdf: gpd.GeoDataFrame | None,
+        points: list[tuple[float, float]] | None,
+    ) -> None:
+        """
+        Run update planner layers.
+
+        :param roads_gdf: See caller/context.
+        :param points: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: update_planner_layers(roads_gdf, points)
+            Out: UI/application state updated as intended.
+        """
+        self._planner_roads = roads_gdf
+        self._planner_points = list(points) if points else []
+        self._sync_layer_list_items()
+        self._request_map_redraw(refit=True)
+
+    def update_euler_layer(self, polylines: list[list[tuple[float, float]]]) -> None:
+        """
+        Run update euler layer.
+
+        :param polylines: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: update_euler_layer(polylines)
+            Out: UI/application state updated as intended.
+        """
+        self._euler_polylines = [list(polyline) for polyline in polylines]
+        self._sync_layer_list_items()
+        self._request_map_redraw(refit=True)
+
+    def update_eval_layer(self, _roads_gdf: gpd.GeoDataFrame | None, results: dict[str, Any] | None) -> None:
+        """
+        Run update eval layer.
+
+        :param _roads_gdf: See caller/context.
+        :param results: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: update_eval_layer(_roads_gdf, results)
+            Out: UI/application state updated as intended.
+        """
+        if results:
+            lon_values, _lat_values, _score_values = evaluation_scatter_data(results)
+            self._eval_results = results if lon_values.size != 0 else None
+        else:
+            self._eval_results = None
+        self._sync_layer_list_items()
+        self._request_map_redraw(refit=True)
diff --git a/src/uq_desktop_processor/gui/widgets/map_layer_list.py b/src/uq_desktop_processor/gui/widgets/map_layer_list.py
new file mode 100644
index 0000000..ca36f23
--- /dev/null
+++ b/src/uq_desktop_processor/gui/widgets/map_layer_list.py
@@ -0,0 +1,100 @@
+"""
+QListWidget-based layer list with reordering and visibility for map stacks.
+"""
+
+import logging
+
+from PySide6.QtCore import Qt, Signal
+from PySide6.QtGui import QDropEvent
+from PySide6.QtWidgets import QListWidget, QWidget
+
+log = logging.getLogger(__name__)
+
+
+class MapLayerListWidget(QListWidget):
+    """
+    MapLayerListWidget UI helper class.
+    """
+
+    reordered = Signal()
+
+    def __init__(self, parent: QWidget | None = None) -> None:
+        """
+        Run   init  .
+
+        :param parent: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: __init__(parent)
+            Out: UI/application state updated as intended.
+        """
+        super().__init__(parent)
+        self._drag_src_row: int = -1
+
+    def startDrag(self, supported_actions: Qt.DropAction) -> None:
+        """
+        Run startDrag.
+
+        :param supported_actions: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: startDrag(supported_actions)
+            Out: UI/application state updated as intended.
+        """
+        self._drag_src_row = self.currentRow()
+        super().startDrag(supported_actions)
+
+    def dropEvent(self, event: QDropEvent) -> None:
+        """
+        Run dropEvent.
+
+        :param event: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: dropEvent(event)
+            Out: UI/application state updated as intended.
+        """
+        try:
+            src_row = self._drag_src_row if self._drag_src_row >= 0 else self.currentRow()
+            if src_row < 0:
+                super().dropEvent(event)
+                return
+
+            drop_position = event.position().toPoint()
+            drop_item = self.itemAt(drop_position)
+
+            if drop_item is None:
+                dst_row = self.count()
+            else:
+                drop_item_rect = self.visualItemRect(drop_item)
+                y_mid = drop_item_rect.y() + drop_item_rect.height() / 2.0
+                dst_row = self.row(drop_item)
+                if drop_position.y() >= y_mid:
+                    dst_row += 1
+
+            if dst_row > src_row:
+                dst_row -= 1
+
+            if dst_row == src_row:
+                event.acceptProposedAction()
+                return
+
+            moved_item = self.takeItem(src_row)
+            if moved_item is None:
+                return
+
+            self.insertItem(dst_row, moved_item)
+            self.setCurrentRow(dst_row)
+            self.reordered.emit()
+
+            event.setDropAction(Qt.DropAction.MoveAction)
+            event.accept()
+
+        except (AttributeError, TypeError, RuntimeError) as error:
+            log.error("Drop error: %s", error)
+            super().dropEvent(event)
+        finally:
+            self._drag_src_row = -1
diff --git a/src/uq_desktop_processor/gui/widgets/map_web_stack.py b/src/uq_desktop_processor/gui/widgets/map_web_stack.py
new file mode 100644
index 0000000..97b27aa
--- /dev/null
+++ b/src/uq_desktop_processor/gui/widgets/map_web_stack.py
@@ -0,0 +1,73 @@
+"""
+Stacked Qt web views for switching between multiple embedded map instances.
+"""
+
+from PySide6.QtGui import QResizeEvent
+from PySide6.QtWidgets import QVBoxLayout, QWidget
+
+
+class MapWebStack(QWidget):
+    """
+    MapWebStack UI helper class.
+    """
+
+    _LAYER_CORNER_MARGIN = 10
+    _LAYER_PANEL_MAX_WIDTH = 210
+
+    def __init__(
+        self,
+        web: QWidget,
+        overlay: QWidget,
+        layer_panel: QWidget | None = None,
+    ) -> None:
+        """
+        Run   init  .
+
+        :param web: See caller/context.
+        :param overlay: See caller/context.
+        :param layer_panel: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: __init__(web, overlay, layer_panel)
+            Out: UI/application state updated as intended.
+        """
+        super().__init__()
+        self._web = web
+        self._overlay = overlay
+        self._layer_panel = layer_panel
+        lay = QVBoxLayout(self)
+        lay.setContentsMargins(0, 0, 0, 0)
+        lay.setSpacing(0)
+        lay.addWidget(web)
+        overlay.setParent(self)
+        if layer_panel is not None:
+            layer_panel.setParent(self)
+
+    def resizeEvent(self, event: QResizeEvent) -> None:
+        """
+        Run resizeEvent.
+
+        :param event: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: resizeEvent(event)
+            Out: UI/application state updated as intended.
+        """
+        super().resizeEvent(event)
+        r = self.rect()
+        self._overlay.setGeometry(r)
+        if self._layer_panel is not None:
+            lp = self._layer_panel
+            m = self._LAYER_CORNER_MARGIN
+            lp.adjustSize()
+            hint = lp.sizeHint()
+            w = max(lp.minimumWidth(), min(hint.width(), self._LAYER_PANEL_MAX_WIDTH))
+            max_h = max(100, r.height() - 2 * m)
+            h = min(hint.height(), max_h)
+            x = r.x() + r.width() - w - m
+            y = r.y() + m
+            lp.setGeometry(x, y, w, h)
+            lp.raise_()
+        self._overlay.raise_()
diff --git a/src/uq_desktop_processor/gui/widgets/stacked.py b/src/uq_desktop_processor/gui/widgets/stacked.py
new file mode 100644
index 0000000..7c18dfe
--- /dev/null
+++ b/src/uq_desktop_processor/gui/widgets/stacked.py
@@ -0,0 +1,107 @@
+"""
+Generic stacked page container with a sidebar list and content widget swapper.
+"""
+
+from PySide6.QtCore import QSize
+from PySide6.QtWidgets import QFrame, QLabel, QSizePolicy, QStackedWidget, QVBoxLayout, QWidget
+
+
+class CompactStackedWidget(QStackedWidget):
+    """
+    ``QStackedWidget`` that sizes vertically to the *current* page only.
+
+    The default stacked widget reserves the height of the *tallest* page, which
+    leaves a large empty gap when a shorter page (e.g. single line edit) is shown.
+    """
+
+    def __init__(self, parent: QWidget | None = None) -> None:
+        """
+        Run   init  .
+
+        :param parent: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: __init__(parent)
+            Out: UI/application state updated as intended.
+        """
+        super().__init__(parent)
+        self.currentChanged.connect(self._on_page_changed)
+        self.setSizePolicy(QSizePolicy.Policy.Preferred, QSizePolicy.Policy.Maximum)
+
+    def _on_page_changed(self, _index: int) -> None:
+        """
+        Run  on page changed.
+
+        :param _index: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: _on_page_changed(_index)
+            Out: UI/application state updated as intended.
+        """
+        self.updateGeometry()
+        parent_widget = self.parentWidget()
+        if parent_widget is not None:
+            parent_widget.updateGeometry()
+
+    def sizeHint(self) -> QSize:  # noqa: N802  (Qt naming)
+        """
+        Run sizeHint.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: sizeHint()
+            Out: UI/application state updated as intended.
+        """
+        w = self.currentWidget()
+        if w is not None:
+            cw = w.sizeHint()
+            base_w = super().sizeHint().width()
+            return QSize(max(base_w, cw.width()), cw.height())
+        return super().sizeHint()
+
+    def minimumSizeHint(self) -> QSize:  # noqa: N802
+        """
+        Run minimumSizeHint.
+
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: minimumSizeHint()
+            Out: UI/application state updated as intended.
+        """
+        w = self.currentWidget()
+        if w is not None:
+            cm = w.minimumSizeHint()
+            base_w = super().minimumSizeHint().width()
+            return QSize(max(base_w, cm.width()), cm.height())
+        return super().minimumSizeHint()
+
+
+class NeonPanel(QFrame):
+    """Titled panel with a vertical layout."""
+
+    def __init__(self, title: str, subtitle: str | None = None) -> None:
+        """
+        Run   init  .
+
+        :param title: See caller/context.
+        :param subtitle: See caller/context.
+        :return: Result of this step or updated UI/application state.
+
+        Example::
+            In: __init__(title, subtitle)
+            Out: UI/application state updated as intended.
+        """
+        super().__init__()
+        self.main_layout = QVBoxLayout(self)
+        self.title_label = QLabel(title)
+        self.title_label.setObjectName("PanelTitle")
+        self.main_layout.addWidget(self.title_label)
+        if subtitle:
+            self.subtitle_label = QLabel(subtitle)
+            self.subtitle_label.setObjectName("PanelSubtitle")
+            self.subtitle_label.setWordWrap(True)
+            self.main_layout.addWidget(self.subtitle_label)
diff --git a/src/uq_desktop_processor/layer_creation/__init__.py b/src/uq_desktop_processor/layer_creation/__init__.py
new file mode 100644
index 0000000..72779bf
--- /dev/null
+++ b/src/uq_desktop_processor/layer_creation/__init__.py
@@ -0,0 +1,7 @@
+"""
+Layer-creation public API for exporting scored points to vector formats.
+"""
+
+from .vector_layers import export_point_layer
+
+__all__ = ["export_point_layer"]
diff --git a/src/uq_desktop_processor/layer_creation/vector_layers/__init__.py b/src/uq_desktop_processor/layer_creation/vector_layers/__init__.py
new file mode 100644
index 0000000..a78ec13
--- /dev/null
+++ b/src/uq_desktop_processor/layer_creation/vector_layers/__init__.py
@@ -0,0 +1,7 @@
+"""
+Vector-layer export API.
+"""
+
+from .point_layer import export_point_layer
+
+__all__ = ["export_point_layer"]
diff --git a/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/__init__.py b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/__init__.py
new file mode 100644
index 0000000..fa3b3c7
--- /dev/null
+++ b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/__init__.py
@@ -0,0 +1,7 @@
+"""
+Point-layer exporter entrypoint.
+"""
+
+from .exporter import export_point_layer
+
+__all__ = ["export_point_layer"]
diff --git a/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/converters.py b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/converters.py
new file mode 100644
index 0000000..b00ba48
--- /dev/null
+++ b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/converters.py
@@ -0,0 +1,195 @@
+"""
+Converts evaluation result dicts into GeoJSON-like feature collections for export.
+"""
+
+import logging
+from typing import Any
+
+from . import defaults
+from .utils import parse_lat_lon
+
+log = logging.getLogger(__name__)
+
+DEFAULT_CATEGORIES = defaults.DEFAULT_CATEGORIES
+
+
+def _get_value_from_categories(categories_data: dict[str, Any], key: str) -> dict[str, Any]:
+    """
+    Safely retrieve a category sub-dictionary from the categories mapping.
+
+    :param categories_data: Mapping of model category keys to dictionaries.
+    :param key: Key to retrieve from the mapping.
+    :return: The corresponding dict if present and of correct type, otherwise {}.
+
+    Example::
+        In: _get_value_from_categories({"wealthier": {"delta": 0.3}}, "wealthier")
+        Out: {"delta": 0.3}
+    """
+    value = categories_data.get(key)
+    if isinstance(value, dict):
+        return value
+    return {}
+
+
+def _resolve_weight(global_weights: dict[str, Any], key: str, alias: str) -> float | None:
+    """
+    Resolve a category weight using either the canonical category name or its alias.
+
+    :param global_weights: Mapping of category names or aliases to weight values.
+    :param key: Canonical category name (e.g. "greenery").
+    :param alias: Alternate key used in the model output, if different.
+    :return: The resolved weight, or None if no matching key was found.
+
+    Example::
+        In: _resolve_weight({"wealthier": 0.4}, "wealthier", "wealth")
+        Out: 0.4
+    """
+    if not global_weights:
+        return None
+    canonical_weight = global_weights.get(key)
+    if canonical_weight is not None:
+        return canonical_weight
+    return global_weights.get(alias)
+
+
+def _build_feature(
+    image_data: dict[str, Any],
+    global_metadata: dict[str, Any],
+    categories: list[str],
+    aliases: dict[str, str],
+) -> dict[str, Any]:
+    """
+    Convert a single scoring result into a GeoJSON Feature.
+
+    This function:
+      - extracts lat/lon coordinates from the filename,
+      - merges global metadata (model name, beta, weights),
+      - attaches per-category probability and delta values,
+      - builds a valid GeoJSON Point feature.
+
+    :param image_data: Single entry from results["images"] with per-image metrics.
+    :param global_metadata: Metadata shared across all images
+                            (model_name, beta_sigmoid, weights, etc.).
+    :param categories: List of logical category names to export.
+    :param aliases: Mapping from logical category names to model keys.
+    :return: A GeoJSON Feature dictionary.
+
+    Example::
+        In: _build_feature(image_data, global_metadata, ["wealthier"], {"wealthier": "wealthier"})
+        Out: {"type": "Feature", "geometry": {"type": "Point", ...}, "properties": {...}}
+    """
+    # Location comes strictly from image metadata (EXIF GPS).
+    filename = image_data.get("filename", "")
+    image_path = image_data.get("image_path")
+    if not image_path:
+        raise ValueError("Missing image_path; cannot read EXIF GPS metadata.")
+    lat, lon = parse_lat_lon(image_path)
+
+    # Per-category data provided by the scoring pipeline
+    categories_data = image_data.get("categories", {}) or {}
+
+    # Base properties (apply to the entire image/result)
+    properties = {
+        "filename": filename,
+        "image_path": image_path,
+        "overall_pct": image_data.get("overall_pct"),
+        "model_name": global_metadata.get("model_name"),
+        "beta_sigmoid": global_metadata.get("beta_sigmoid"),
+    }
+
+    global_weights = global_metadata.get("weights") or {}
+
+    # Add per-category values.
+    for category_key in categories:
+        category_values = _get_value_from_categories(categories_data, category_key)
+
+        # Property names should not contain spaces
+        clean_key = category_key.replace(" ", "_")
+
+        # Probability and delta per category
+        properties[f"{clean_key}_prob_pct"] = category_values.get("probability_pct")
+        properties[f"{clean_key}_delta"] = category_values.get("delta")
+
+        # Optional weight information for this category.
+        category_alias = aliases.get(category_key, category_key)
+        weight = _resolve_weight(global_weights, category_key, category_alias)
+        if weight is not None:
+            properties[f"weights_{clean_key}"] = weight
+
+    feature = {
+        "type": "Feature",
+        "geometry": {"type": "Point", "coordinates": [lon, lat]},
+        "properties": properties,
+    }
+    return feature
+
+
+def _results_to_feature_collection(
+    results: dict[str, Any],
+    categories: list[str] | None = None,
+    aliases: dict[str, str] | None = None,
+) -> dict[str, Any]:
+    """
+    Convert the full evaluation output into a GeoJSON FeatureCollection.
+
+    :param results: Dictionary returned by the scoring pipeline.
+    :param categories: Optional list of categories to export. If None, uses
+                        defaults.DEFAULT_CATEGORIES.
+    :param aliases: Optional mapping from category names to model keys.
+                    If None, uses defaults.DEFAULT_ALIASES.
+    :return: A GeoJSON FeatureCollection dictionary including extra metadata
+             under the "x_meta" key.
+
+    Example::
+        In: _results_to_feature_collection({"images": [], "model_name": "clip"})
+        Out: {"type": "FeatureCollection", "features": [], "x_meta": {...}}
+    """
+    target_categories = categories if categories is not None else DEFAULT_CATEGORIES
+    target_aliases = aliases if aliases is not None else getattr(defaults, "DEFAULT_ALIASES", {})
+
+    images_list = results.get("images", []) or []
+
+    log.debug("Converting %s results to GeoJSON features.", len(images_list))
+
+    # Data shared between all features; also emitted in x_meta.
+    global_metadata = {
+        "model_name": results.get("model_name"),
+        "beta_sigmoid": results.get("beta_sigmoid"),
+        "weights": results.get("weights"),
+        "order": results.get("order"),
+        "average_overall_pct": results.get("average_overall_pct"),
+    }
+
+    features_list: list[dict[str, Any]] = []
+
+    for image_entry in images_list:
+        try:
+            feature = _build_feature(
+                image_entry,
+                global_metadata,
+                target_categories,
+                target_aliases,
+            )
+            features_list.append(feature)
+        except Exception as exception:
+            # Do not fail the entire export on a single bad filename or record.
+            filename = image_entry.get("filename", "unknown")
+            log.warning("Skipping '%s': %s", filename, exception)
+
+    if not features_list:
+        log.warning("No features were generated during conversion (all input images failed or list was empty).")
+
+    feature_collection = {
+        "type": "FeatureCollection",
+        "name": results.get("model_name") or "model_points",
+        "crs": {"type": "name", "properties": {"name": "EPSG:4326"}},
+        "features": features_list,
+        "x_meta": {
+            **global_metadata,
+            "exported_categories": target_categories,
+            "skipped_images": results.get("skipped_images", []),
+            "warnings": results.get("warnings", []),
+            "errors": results.get("errors"),
+        },
+    }
+    return feature_collection
diff --git a/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/defaults.py b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/defaults.py
new file mode 100644
index 0000000..ca7e5a1
--- /dev/null
+++ b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/defaults.py
@@ -0,0 +1,6 @@
+"""
+Default filenames and options for point-layer GeoJSON/GPKG export.
+"""
+
+# Display order used when writing per-category attributes.
+DEFAULT_CATEGORIES = ["wealthier", "safer", "more beautiful", "livelier", "less depressing", "less boring"]
diff --git a/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/exporter.py b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/exporter.py
new file mode 100644
index 0000000..68bd6d0
--- /dev/null
+++ b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/exporter.py
@@ -0,0 +1,71 @@
+"""
+Exports scoring results to GeoJSON or GeoPandas-backed spatial files.
+"""
+
+import logging
+import os
+from typing import Any
+
+from .converters import _results_to_feature_collection
+from .utils import _is_geopandas_available
+from .writers import _write_geojson, _write_with_geopandas
+
+log = logging.getLogger(__name__)
+
+
+def export_point_layer(
+    results: dict[str, Any], output_path: str, layer: str | None = None, categories: list[str] | None = None
+) -> str:
+    """
+    Export scoring results to a geospatial file.
+
+    The output format is inferred from the file extension:
+
+      - .geojson / .json  -> plain GeoJSON, written with the standard json module
+      - .gpkg / .shp / .parquet / others supported by GeoPandas -> written using GeoPandas
+
+    :param results: Dictionary returned by the evaluation pipeline.
+    :param output_path: Destination file path (extension determines format).
+    :param layer: Optional layer name (for formats that support multiple layers).
+    :param categories: Optional subset of categories to include (default uses
+                        defaults.DEFAULT_CATEGORIES).
+    :return: Absolute path to the saved file.
+
+    Example::
+        In: export_point_layer(results, "data/results/urban_quality_ai_output.geojson")
+        Out: "C:/.../data/results/urban_quality_ai_output.geojson"
+    """
+    log.info("Preparing to export data to: %s", output_path)
+
+    try:
+        # Convert raw results into a structured FeatureCollection.
+        feature_collection = _results_to_feature_collection(results, categories=categories)
+
+        feature_count = len(feature_collection.get("features", []))
+        log.debug("Converted results to FeatureCollection with %s features.", feature_count)
+
+        absolute_output_path = os.path.abspath(output_path)
+        file_extension = os.path.splitext(output_path.lower())[1]
+
+        # JSON-based formats do not require GeoPandas.
+        if file_extension in (".geojson", ".json"):
+            _write_geojson(feature_collection, absolute_output_path)
+        else:
+            # Other formats require GeoPandas.
+            if not _is_geopandas_available():
+                msg = (
+                    "GeoPandas is required to save to binary formats (GPKG, SHP, Parquet).\n"
+                    "Install: pip install geopandas pyproj fiona shapely\n"
+                    "Or use the .geojson extension."
+                )
+                log.error(msg)
+                raise RuntimeError(msg)
+
+            _write_with_geopandas(feature_collection, absolute_output_path, layer=layer)
+
+        log.info("Export successful. File saved at: %s", absolute_output_path)
+        return absolute_output_path
+
+    except Exception as error:
+        log.error("Failed to export layer to '%s': %s", output_path, error)
+        raise
diff --git a/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/utils.py b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/utils.py
new file mode 100644
index 0000000..46a952c
--- /dev/null
+++ b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/utils.py
@@ -0,0 +1,129 @@
+"""
+Parses lat/lon from image metadata and misc helpers for point layer creation.
+"""
+
+import logging
+from pathlib import Path
+from typing import Any
+
+log = logging.getLogger(__name__)
+
+
+def _exif_gps_to_decimal(exif_gps: dict[int, Any]) -> tuple[float, float] | None:
+    """
+    Convert EXIF GPSInfo dict to (lat, lon) in decimal degrees.
+
+    Works with EXIF dicts returned by PIL.Image.getexif() where GPSInfo is a mapping
+    of numeric keys to values (rationals, tuples).
+
+    :param exif_gps: GPSInfo mapping from EXIF.
+    :return: ``(lat, lon)`` if GPS fields are complete and valid, otherwise None.
+
+    Example::
+        In: _exif_gps_to_decimal({1: "N", 2: ((50,1),(3,1),(0,1)), 3: "E", 4: ((19,1),(56,1),(0,1))})
+        Out: (50.05, 19.933333333333334)
+    """
+
+    def _ratio_to_float(ratio_value: Any) -> float:
+        # PIL can return IFDRational or tuple(num, den)
+        try:
+            return float(ratio_value)
+        except (TypeError, ValueError):
+            pass
+        if isinstance(ratio_value, tuple | list) and len(ratio_value) == 2:
+            numerator, denominator = ratio_value
+            return float(numerator) / float(denominator)
+        raise ValueError(f"Unsupported rational type: {type(ratio_value)}")
+
+    def _dms_to_deg(dms_value: Any, reference: str) -> float:
+        if not isinstance(dms_value, tuple | list) or len(dms_value) != 3:
+            raise ValueError("GPS DMS must be a 3-tuple")
+        degrees = _ratio_to_float(dms_value[0])
+        minutes = _ratio_to_float(dms_value[1])
+        seconds = _ratio_to_float(dms_value[2])
+        decimal_degrees = degrees + minutes / 60.0 + seconds / 3600.0
+        normalized_reference = (reference or "").upper()
+        if normalized_reference in ("S", "W"):
+            decimal_degrees = -decimal_degrees
+        return float(decimal_degrees)
+
+    try:
+        # EXIF GPS tag ids: 1/2 latitude ref+value, 3/4 longitude ref+value.
+        lat_ref = exif_gps.get(1)  # GPSLatitudeRef
+        lat_dms = exif_gps.get(2)  # GPSLatitude
+        lon_ref = exif_gps.get(3)  # GPSLongitudeRef
+        lon_dms = exif_gps.get(4)  # GPSLongitude
+        if not lat_ref or not lon_ref or not lat_dms or not lon_dms:
+            return None
+        lat = _dms_to_deg(lat_dms, str(lat_ref))
+        lon = _dms_to_deg(lon_dms, str(lon_ref))
+        return lat, lon
+    except (ValueError, TypeError, ZeroDivisionError):
+        return None
+
+
+def parse_lat_lon_from_image_metadata(image_path: str | Path) -> tuple[float, float]:
+    """
+    Extract (lat, lon) from image EXIF GPS metadata.
+
+    :param image_path: Path to an image file.
+    :return: ``(latitude, longitude)`` from EXIF GPS tags.
+    :raises ValueError: if GPS metadata is missing or invalid.
+
+    Example::
+        In: parse_lat_lon_from_image_metadata("data/images/raw/123.jpg")
+        Out: (50.0612, 19.9377)
+    """
+    from PIL import Image
+
+    image_path_obj = Path(image_path)
+    try:
+        with Image.open(image_path_obj) as im:
+            exif = im.getexif()
+            if not exif:
+                raise ValueError("missing EXIF")
+            gps_info = exif.get_ifd(0x8825)  # GPSInfo IFD
+            if not isinstance(gps_info, dict):
+                raise ValueError("missing GPSInfo")
+            latlon_coordinates = _exif_gps_to_decimal(gps_info)
+            if latlon_coordinates is None:
+                raise ValueError("missing GPS lat/lon")
+            return latlon_coordinates
+    except ValueError:
+        raise
+    except Exception as error:
+        raise ValueError(f"cannot read EXIF GPS from image: {image_path_obj}") from error
+
+
+def parse_lat_lon(image_path: str | Path) -> tuple[float, float]:
+    """
+    Parse coordinates strictly from EXIF GPS metadata.
+
+    :param image_path: Path to an image file.
+    :return: ``(latitude, longitude)``.
+
+    Example::
+        In: parse_lat_lon("data/images/raw/img_0001.jpg")
+        Out: (50.0612, 19.9377)
+    """
+    return parse_lat_lon_from_image_metadata(image_path)
+
+
+def _is_geopandas_available() -> bool:
+    """
+    Check whether GeoPandas and Shapely are available in the environment.
+
+    :return: True if both packages can be imported, False otherwise.
+
+    Example::
+        In: _is_geopandas_available()
+        Out: True
+    """
+    try:
+        import geopandas  # noqa: F401
+        import shapely  # noqa: F401
+
+        return True
+    except ImportError as error:
+        log.debug("GeoPandas availability check failed: %s", error)
+        return False
diff --git a/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/writers.py b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/writers.py
new file mode 100644
index 0000000..9360502
--- /dev/null
+++ b/src/uq_desktop_processor/layer_creation/vector_layers/point_layer/writers.py
@@ -0,0 +1,94 @@
+"""
+Low-level writers for GeoJSON and GeoPandas outputs used by the exporter.
+"""
+
+import json
+import logging
+import os
+from typing import Any
+
+log = logging.getLogger(__name__)
+
+
+def _write_geojson(feature_collection: dict[str, Any], output_path: str) -> None:
+    """
+    Save a GeoJSON FeatureCollection to a .geojson or .json file.
+
+    :param feature_collection: GeoJSON FeatureCollection dictionary.
+    :param output_path: Destination path for the JSON/GeoJSON file.
+
+    Example::
+        In: _write_geojson(feature_collection, "out.geojson")
+        Out: "out.geojson" created on disk
+    """
+    with open(output_path, "w", encoding="utf-8") as file_handle:
+        json.dump(feature_collection, file_handle, ensure_ascii=False, indent=2)
+
+    feature_count = len(feature_collection.get("features", []))
+    log.info("Saved GeoJSON: %s (object count: %s)", output_path, feature_count)
+
+
+def _write_with_geopandas(feature_collection: dict[str, Any], output_path: str, layer: str | None = None) -> None:
+    """
+    Save a FeatureCollection to a binary geospatial format using GeoPandas.
+
+    Supported formats (inferred from file extension):
+      - .gpkg  (GeoPackage)
+      - .shp   (ESRI Shapefile)
+      - .parquet
+      - other formats supported by GeoPandas drivers
+
+    :param feature_collection: GeoJSON-like structure to be converted.
+    :param output_path: Output file path.
+    :param layer: Optional layer name for multi-layer formats (e.g. GeoPackage).
+
+    Example::
+        In: _write_with_geopandas(feature_collection, "out.gpkg", layer="scores")
+        Out: "out.gpkg" created on disk with layer "scores"
+    """
+    import geopandas as gpd
+    from shapely.geometry import Point
+
+    if not feature_collection["features"]:
+        log.warning("No objects to save; feature collection is empty.")
+        return
+
+    rows: list[dict[str, Any]] = []
+
+    # Convert each GeoJSON feature into a GeoPandas row.
+    for feature_item in feature_collection["features"]:
+        lon, lat = feature_item["geometry"]["coordinates"]
+        properties = feature_item["properties"].copy()
+        rows.append({**properties, "geometry": Point(lon, lat)})
+
+    log.debug("Converted %s features to GeoDataFrame rows.", len(rows))
+
+    geo_data_frame = gpd.GeoDataFrame(rows, geometry="geometry", crs="EPSG:4326")
+
+    file_extension = os.path.splitext(output_path.lower())[1]
+
+    try:
+        if file_extension == ".gpkg":
+            # Use provided layer name or fall back to collection name.
+            layer_name = layer or (feature_collection.get("name") or "data").replace("/", "_")
+            geo_data_frame.to_file(output_path, layer=layer_name, driver="GPKG")  # type: ignore[assignment]
+
+        elif file_extension == ".shp":
+            geo_data_frame.to_file(output_path, driver="ESRI Shapefile")  # type: ignore[assignment]
+
+        elif file_extension == ".parquet":
+            geo_data_frame.to_parquet(output_path, index=False)  # type: ignore[assignment]
+
+        else:
+            # Default driver chosen by GeoPandas based on extension.
+            geo_data_frame.to_file(output_path)  # type: ignore[assignment]
+
+        log.info(
+            "Saved %s: %s (object count: %s)",
+            file_extension.upper(),
+            output_path,
+            len(geo_data_frame),
+        )
+
+    except Exception as error:
+        log.error("GeoPandas save error: %s", error)
diff --git a/src/uq_desktop_processor/logging_config.py b/src/uq_desktop_processor/logging_config.py
new file mode 100644
index 0000000..272bdb6
--- /dev/null
+++ b/src/uq_desktop_processor/logging_config.py
@@ -0,0 +1,445 @@
+"""
+Central logging setup: UTC timestamps, optional colors, and file handlers.
+Call `configure_logging` once at startup; use `getLogger(__name__)` afterward.
+"""
+
+import logging
+import os
+import sys
+import time
+from dataclasses import dataclass
+from typing import IO
+
+__all__ = ["configure_logging", "add_file_logging"]
+
+
+COLORS = {
+    "DEBUG": "\033[90m",
+    "INFO": "\033[32m",
+    "WARNING": "\033[93m",
+    "ERROR": "\033[91m",
+    "CRITICAL": "\033[97;41m",
+    "RESET": "\033[0m",
+}
+
+
+@dataclass(frozen=True)
+class ColorSupport:
+    """
+    Represents whether ANSI color output is supported in the current environment.
+
+    Attributes:
+        supported (bool): True if ANSI colors are supported, False otherwise.
+        reason (Optional[str]): Explanation why colors are not supported (if applicable).
+        env_hint (Optional[str]): Environment hint to provide user-specific tips (e.g. 'vscode', 'pycharm').
+    """
+
+    supported: bool
+    reason: str | None = None
+    env_hint: str | None = None
+
+
+class ColorEnv:
+    """
+    Detects environment characteristics related to color/ANSI support
+    and provides methods to enable or disable ANSI colors in different terminals.
+    """
+
+    _WINDOWS_ANSI_ENABLED = False
+    _COLOR_HINT_SHOWN = False
+
+    @staticmethod
+    def is_ci() -> bool:
+        """
+        Detects if the current process is running inside a CI environment.
+
+        :return: True if running in a known CI system, False otherwise.
+        """
+        return os.environ.get("CI") == "1" or any(
+            os.environ.get(env_var)
+            for env_var in (
+                "GITHUB_ACTIONS",
+                "GITLAB_CI",
+                "TF_BUILD",
+                "TEAMCITY_VERSION",
+                "BUILDKITE",
+                "TRAVIS",
+                "CIRCLECI",
+                "APPVEYOR",
+                "DRONE",
+                "JENKINS_URL",
+            )
+        )
+
+    @staticmethod
+    def is_vscode() -> bool:
+        """
+        Detects if the process is running inside VS Code's Integrated Terminal or Debug Console.
+
+        :return: True if running in VS Code, False otherwise.
+        """
+        return bool(os.environ.get("TERM_PROGRAM") == "vscode" or os.environ.get("VSCODE_PID"))
+
+    @staticmethod
+    def is_pycharm() -> bool:
+        """
+        Detects if the process is running inside the PyCharm IDE.
+
+        :return: True if running in PyCharm, False otherwise.
+        """
+        return bool(os.environ.get("PYCHARM_HOSTED"))
+
+    @staticmethod
+    def is_windows_terminal() -> bool:
+        """
+        Detects if the process is running in Windows Terminal or ConEmu.
+
+        :return: True if running in Windows Terminal or ConEmu, False otherwise.
+        """
+        return bool(os.environ.get("WT_SESSION") or os.environ.get("ConEmuPID"))
+
+    @staticmethod
+    def is_jupyter() -> bool:
+        """
+        Detects if the process is running inside a Jupyter or Spyder kernel.
+
+        :return: True if in Jupyter, False otherwise.
+        """
+        try:
+            import ipykernel  # noqa: F401
+
+            return True
+        except ImportError:
+            return False
+
+    @classmethod
+    def ensure_windows_ansi(cls) -> None:
+        """
+        Ensures that ANSI escape sequences are enabled in Windows consoles.
+        Requires the `colorama` package.
+
+        :return: None
+        """
+        if cls._WINDOWS_ANSI_ENABLED or os.name != "nt":
+            return
+
+        try:
+            import colorama  # noqa E402
+        except ImportError:
+            return
+
+        colorama.just_fix_windows_console()
+        cls._WINDOWS_ANSI_ENABLED = True
+
+    @staticmethod
+    def stream_isatty(stream: IO[str]) -> bool:
+        """
+        Checks whether a given stream is connected to a TTY (interactive terminal).
+
+        :param stream: The stream to check.
+        :return: True if the stream is a TTY, False otherwise.
+        """
+        try:
+            return hasattr(stream, "isatty") and callable(stream.isatty) and stream.isatty()
+        except (OSError, ValueError):
+            return False
+
+    @classmethod
+    def color_support_with_reason(cls, stream: IO[str]) -> ColorSupport:
+        """
+        Determines whether colors are supported in the current environment,
+        including reasons and environment hints if disabled.
+
+        :param stream: The output stream (e.g. sys.stderr).
+        :return: A ColorSupport instance with the decision and explanation.
+        """
+        if os.environ.get("FORCE_COLOR"):
+            cls.ensure_windows_ansi()
+            return ColorSupport(True)
+
+        if os.environ.get("NO_COLOR"):
+            return ColorSupport(False, "NO_COLOR is set.", None)
+
+        if cls.is_pycharm():
+            cls.ensure_windows_ansi()
+            return ColorSupport(True, env_hint="pycharm")
+
+        if cls.is_vscode():
+            cls.ensure_windows_ansi()
+            return ColorSupport(True, env_hint="vscode")
+
+        if cls.is_windows_terminal():
+            cls.ensure_windows_ansi()
+
+        if cls.is_jupyter():
+            return ColorSupport(True, env_hint="jupyter")
+
+        if not cls.stream_isatty(stream):
+            return ColorSupport(False, "Output is not a TTY (file/pipe/IDE wo/ emulation).", None)
+
+        if os.name == "nt":
+            cls.ensure_windows_ansi()
+            return (
+                ColorSupport(True)
+                if cls._WINDOWS_ANSI_ENABLED
+                else ColorSupport(False, "Windows without 'colorama'.", "windows")
+            )
+
+        terminal_type = os.environ.get("TERM", "")
+        if terminal_type in ("", "dumb"):
+            return ColorSupport(False, f"TERM={terminal_type!r} does not support ANSI.", "unix")
+
+        return ColorSupport(True)
+
+    @classmethod
+    def maybe_show_color_hint(cls, reason: str | None, env_hint: str | None) -> None:
+        """
+        Optionally prints a hint to stderr explaining why colors are disabled
+        and how to enable them, depending on the environment.
+
+        :param reason: Reason why colors are disabled.
+        :param env_hint: Environment hint (if available).
+        :return: None
+        """
+        if cls._COLOR_HINT_SHOWN or cls.is_ci() or os.environ.get("LOG_COLOR_HINT") != "1":
+            return
+
+        if not reason:
+            return
+
+        cls._COLOR_HINT_SHOWN = True
+
+        base_tips = [
+            "- If redirecting to a file/pipeline: colors are intentionally disabled.",
+            "- Remove the `NO_COLOR` variable if it's set.",
+            "- You can force colors: `FORCE_COLOR=1`.",
+        ]
+
+        env_tips = {
+            "pycharm": ["- PyCharm: enable **Run → Emulate terminal in output console**."],
+            "vscode": [
+                "- VS Code: use the **Integrated Terminal** (View → Terminal),",
+                "  or set `FORCE_COLOR=1` in your Debug Configuration.",
+            ],
+            "windows": ["- Windows: `pip install colorama` or run in Windows Terminal."],
+            "unix": [
+                "- Linux/macOS: ensure `TERM` is something like `xterm-256color`.",
+                "- In Docker, run with a TTY: `docker run -it ...`.",
+            ],
+            "jupyter": ["- Jupyter: colors usually work; to disable set `NO_COLOR=1`."],
+            None: [
+                "- Windows: consider **Windows Terminal** or `pip install colorama`.",
+                "- VS Code/PyCharm: run via the **Integrated/Emulated Terminal**.",
+                "- Docker: add `-t` (pseudo-TTY).",
+            ],
+        }
+
+        tips = env_tips.get(env_hint, env_tips[None])
+
+        message = (
+            "[log-color] Colors are disabled: "
+            f"{reason}  How to enable them:\n  "
+            + "\n  ".join(tips + base_tips)
+            + "\n  (Silence tips: LOG_COLOR_HINT=0 / off by default)"
+        )
+
+        try:
+            print(message, file=sys.stderr)
+        except (OSError, ValueError):
+            pass
+
+
+class UtcFormatter(logging.Formatter):
+    """
+    Formatter that enforces UTC timestamps for log records.
+    """
+
+    @staticmethod
+    def _converter(secs: float | None) -> time.struct_time:
+        return time.gmtime(0 if secs is None else secs)
+
+    converter = _converter
+
+
+class ColoredFormatter(UtcFormatter):
+    """
+    A log formatter that applies ANSI color codes to messages based on log level.
+
+    Extends UtcFormatter to add colorization when enabled.
+    """
+
+    def __init__(self, format_string: str, date_format: str | None, use_color: bool) -> None:
+        super().__init__(fmt=format_string, datefmt=date_format)
+        self.use_color = use_color
+
+    def format(self, record: logging.LogRecord) -> str:
+        message = super().format(record)
+
+        if not self.use_color:
+            return message
+
+        color = COLORS.get(record.levelname, COLORS["RESET"])
+        return f"{color}{message}{COLORS['RESET']}"
+
+
+class HandlerFactory:
+    """
+    Factory for creating logging handlers with appropriate formatters
+    (stream handlers with optional colors, or file handlers without colors).
+    """
+
+    @staticmethod
+    def stream_handler(stream: IO[str], fmt: str, date_format: str) -> logging.Handler:
+        handler = logging.StreamHandler(stream)
+        handler.setLevel(logging.NOTSET)
+
+        support = ColorEnv.color_support_with_reason(stream)
+        if not support.supported:
+            ColorEnv.maybe_show_color_hint(support.reason, support.env_hint)
+
+        handler.setFormatter(ColoredFormatter(format_string=fmt, date_format=date_format, use_color=support.supported))
+        return handler
+
+    @staticmethod
+    def file_handler(path: str, fmt: str, date_format: str, encoding: str = "utf-8") -> logging.Handler:
+        absolute_path = os.path.abspath(path)
+        handler = logging.FileHandler(absolute_path, encoding=encoding)
+        handler.setLevel(logging.NOTSET)
+        handler.setFormatter(UtcFormatter(fmt=fmt, datefmt=date_format))
+        return handler
+
+
+class LoggingConfigurator:
+    """
+    Provides high-level configuration methods for setting up logging
+    with optional color support for console and file handlers.
+    """
+
+    @staticmethod
+    def configure(
+        level: int = logging.DEBUG,
+        stream: IO[str] = sys.stderr,
+        format_string: str = "%(asctime)s.%(msecs)03dZ [%(levelname)s] %(name)s: %(message)s",
+        date_format: str = "%Y-%m-%dT%H:%M:%S",
+        *,
+        replace_handlers: bool = False,
+        capture_warnings: bool = True,
+    ) -> None:
+        """
+        Configures global logging with colorized console output.
+
+        :param level: Minimum logging level (default DEBUG).
+        :param stream: Stream to log to (default sys.stderr).
+        :param format_string: Log message format string.
+        :param date_format: Date/time format string.
+        :param replace_handlers: If True, removes existing handlers first.
+        :param capture_warnings: If True, redirects warnings to logging.
+        :return: None
+        """
+        root = logging.getLogger()
+
+        if replace_handlers:
+            for handler in root.handlers[:]:
+                root.removeHandler(handler)
+            if hasattr(root, "_colored_logging_configured"):
+                delattr(root, "_colored_logging_configured")
+
+        if getattr(root, "_colored_logging_configured", False) and not replace_handlers:
+            if capture_warnings:
+                logging.captureWarnings(True)
+            return
+
+        root.setLevel(level)
+        root.addHandler(HandlerFactory.stream_handler(stream, format_string, date_format))
+        root._colored_logging_configured = True  # type: ignore[attr-defined]
+
+        if capture_warnings:
+            logging.captureWarnings(True)
+
+    @staticmethod
+    def add_file_logging(
+        path: str,
+        level: int = logging.DEBUG,
+        format_string: str = "%(asctime)s.%(msecs)03dZ [%(levelname)s] %(name)s: %(message)s",
+        date_format: str = "%Y-%m-%dT%H:%M:%S",
+        encoding: str = "utf-8",
+    ) -> None:
+        """
+        Adds a file handler to the global logger, writing logs in UTC.
+
+        :param path: Path to the log file.
+        :param level: Minimum logging level (default DEBUG).
+        :param format_string: Log message format string.
+        :param date_format: Date/time format string.
+        :param encoding: File encoding (default UTF-8).
+        :return: None
+        """
+        root = logging.getLogger()
+        absolute_path = os.path.abspath(path)
+
+        for handler in root.handlers:
+            if isinstance(handler, logging.FileHandler) and getattr(handler, "baseFilename", None) == absolute_path:
+                if root.level > level:
+                    root.setLevel(level)
+                return
+
+        root.addHandler(HandlerFactory.file_handler(absolute_path, format_string, date_format, encoding))
+
+        if root.level > level:
+            root.setLevel(level)
+
+
+def configure_logging(
+    level: int = logging.DEBUG,
+    stream: IO[str] = sys.stderr,
+    format_string: str = "%(asctime)s.%(msecs)03dZ [%(levelname)s] %(name)s: %(message)s",
+    date_format: str = "%Y-%m-%dT%H:%M:%S",
+    *,
+    replace_handlers: bool = False,
+    capture_warnings: bool = True,
+) -> None:
+    """
+    Public API to configure global logging with colorized console output.
+
+    :param level: Minimum logging level (default DEBUG).
+    :param stream: Stream to log to (default sys.stderr).
+    :param format_string: Log message format string.
+    :param date_format: Date/time format string.
+    :param replace_handlers: If True, removes existing handlers first.
+    :param capture_warnings: If True, redirects warnings to logging.
+    :return: None
+    """
+    LoggingConfigurator.configure(
+        level=level,
+        stream=stream,
+        format_string=format_string,
+        date_format=date_format,
+        replace_handlers=replace_handlers,
+        capture_warnings=capture_warnings,
+    )
+
+
+def add_file_logging(
+    path: str,
+    level: int = logging.DEBUG,
+    format_string: str = "%(asctime)s.%(msecs)03dZ [%(levelname)s] %(name)s: %(message)s",  # Default - ISO-8601
+    date_format: str = "%Y-%m-%dT%H:%M:%S",
+    encoding: str = "utf-8",
+) -> None:
+    """
+    Public API to add file logging to the global logger.
+
+    :param path: Path to the log file.
+    :param level: Minimum logging level (default DEBUG).
+    :param format_string: Log message format string.
+    :param date_format: Date/time format string.
+    :param encoding: File encoding (default UTF-8).
+    :return: None
+    """
+    LoggingConfigurator.add_file_logging(
+        path=path,
+        level=level,
+        format_string=format_string,
+        date_format=date_format,
+        encoding=encoding,
+    )
diff --git a/src/uq_desktop_processor/pipeline/__init__.py b/src/uq_desktop_processor/pipeline/__init__.py
new file mode 100644
index 0000000..863a8f0
--- /dev/null
+++ b/src/uq_desktop_processor/pipeline/__init__.py
@@ -0,0 +1,17 @@
+"""
+Public pipeline API: defaults, orchestrator, CLI entrypoint, and point/prefilter helpers.
+"""
+
+from uq_desktop_processor.pipeline.cli import run_pipeline
+from uq_desktop_processor.pipeline.defaults import DEFAULT_CONFIG
+from uq_desktop_processor.pipeline.pipeline import UrbanQualityAIPipeline
+from uq_desktop_processor.pipeline.points_io import load_sampling_points_latlon
+from uq_desktop_processor.pipeline.prefilter_config import prefilter_prompts_from_config
+
+__all__ = [
+    "DEFAULT_CONFIG",
+    "UrbanQualityAIPipeline",
+    "load_sampling_points_latlon",
+    "prefilter_prompts_from_config",
+    "run_pipeline",
+]
diff --git a/src/uq_desktop_processor/pipeline/cli.py b/src/uq_desktop_processor/pipeline/cli.py
new file mode 100644
index 0000000..7e34a51
--- /dev/null
+++ b/src/uq_desktop_processor/pipeline/cli.py
@@ -0,0 +1,39 @@
+"""
+CLI entry: runs the full UrbanQuality-AI pipeline (points, download, prefilter, evaluate, export).
+"""
+
+import logging
+
+from uq_desktop_processor.pipeline.pipeline import UrbanQualityAIPipeline
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+
+def run_pipeline() -> int:
+    """
+    Run the default end-to-end pipeline from the command line.
+
+    :return: Process-like exit code (0 success, 1 operational error, 130 interrupted).
+
+    Example::
+        In: run_pipeline()
+        Out: 0
+    """
+    pipeline = UrbanQualityAIPipeline()
+    try:
+        pipeline.step_1_generate_points()
+        pipeline.step_2_download_images()
+
+        prefilter_stats = pipeline.step_3_prefilter()
+
+        # Skip scoring/export when prefilter removed all images.
+        if prefilter_stats.get("summary", {}).get("kept", 0) > 0:
+            pipeline.step_4_evaluate()
+            pipeline.step_5_export()
+        return 0
+    except KeyboardInterrupt:
+        return 130
+    except (RuntimeError, OSError, ValueError) as error:
+        logger.error("Pipeline failed due to operational error: %s", error)
+        return 1
diff --git a/src/uq_desktop_processor/pipeline/defaults.py b/src/uq_desktop_processor/pipeline/defaults.py
new file mode 100644
index 0000000..29a9f00
--- /dev/null
+++ b/src/uq_desktop_processor/pipeline/defaults.py
@@ -0,0 +1,44 @@
+"""
+Default directories and parameters for each pipeline step.
+"""
+
+import os
+from pathlib import Path
+from typing import Any
+
+DEFAULT_CONFIG: dict[str, Any] = {
+    "place_name": "Katowice, Poland",
+    # Source for sampling-point planning: "place" | "region" | "roads".
+    "planner_source": "place",
+    "region_geojson_path": "",
+    "road_geojson_path": "",
+    # Distances are interpreted in meters.
+    "spacing": 100,
+    "min_distance": 50,
+    "search_radius": 100,
+    "mapillary_max_workers": 20,
+    "mapillary_fov_deg": 90,
+    "mapillary_points_path": "",
+    "mapillary_images_output_dir": "",
+    "base_dir": "data",
+    "points_layer_path": str(Path("data") / "results" / "sampling_points.geojson"),
+    "mapillary_token": os.environ.get("MAPILLARY_ACCESS_TOKEN", ""),
+    "clip_model_names": ("ViT-L/14@336px",),
+    "prefilter_image_folder": "",
+    "prefilter_rejected_folder": "",
+    "prefilter_pos_prompts": "",
+    "prefilter_neg_prompts": "",
+    "filter_threshold": 40.0,
+    "beta_sigmoid": 30.0,
+    "export_path": "",
+    "torch_device": "auto",
+    "vit_images_dir": "",
+    "vit_model_path": "",
+    "vit_calibrators_dir": "",
+    "vit_model_name": "vit_base_patch14_dinov2.lvd142m",
+    "vit_image_size": 224,
+    "vit_batch_size": 32,
+    "vit_torch_device": "auto",
+    "vit_output_layer_path": "",
+    "vit_output_layer_name": "vit_finetuned_scores",
+}
diff --git a/src/uq_desktop_processor/pipeline/pipeline.py b/src/uq_desktop_processor/pipeline/pipeline.py
new file mode 100644
index 0000000..632fb64
--- /dev/null
+++ b/src/uq_desktop_processor/pipeline/pipeline.py
@@ -0,0 +1,368 @@
+"""
+Orchestrates end-to-end processing: points, images, prefilter, CLIP eval, vector export.
+"""
+
+import logging
+import os
+from pathlib import Path
+from typing import Any
+
+from uq_desktop_processor.evaluation import (
+    evaluate_images_with_clip,
+    prefilter_folder,
+)
+from uq_desktop_processor.evaluation.finetuned_evaluator.run import evaluate_images_with_finetuned
+from uq_desktop_processor.layer_creation import export_point_layer
+from uq_desktop_processor.pipeline.defaults import DEFAULT_CONFIG
+from uq_desktop_processor.pipeline.points_io import load_sampling_points_latlon
+from uq_desktop_processor.pipeline.prefilter_config import prefilter_prompts_from_config
+from uq_desktop_processor.street_view_analysis import build_points_pipeline, download_mapillary_images
+
+
+class UrbanQualityAIPipeline:
+    """
+    Application pipeline controller.
+
+    Holds in-memory state (roads, points, evaluation) and exposes steps to run sequentially.
+    """
+
+    def __init__(self, config: dict[str, Any] | None = None):
+        """
+        Initialize pipeline state and merge runtime overrides with defaults.
+
+        :param config: Optional dictionary with config overrides.
+
+        Example::
+            In: UrbanQualityAIPipeline({"base_dir": "data_dev"})
+            Out: pipeline object with directories initialized under "data_dev"
+        """
+        self.log = logging.getLogger("UrbanQualityAI")
+        self.log.setLevel(logging.DEBUG)
+
+        self.config = {**DEFAULT_CONFIG, **(config or {})}
+
+        self.base_dir = Path(self.config["base_dir"])
+        self.raw_dir = self.base_dir / "images" / "raw"
+        self.rejected_dir = self.base_dir / "images" / "rejected"
+        self.results_dir = self.base_dir / "results"
+
+        self.roads_gdf = None
+        self.points: list[tuple[float, float]] = []
+        self.evaluation_results = None
+
+        self._ensure_directories()
+
+    def _resolve_torch_device(self) -> str:
+        """
+        Resolve torch device from config and environment fallback rules.
+
+        :return: ``"cpu"`` or ``"cuda"``.
+
+        Example::
+            In: pipeline._resolve_torch_device()
+            Out: "cpu"
+        """
+        configured_device = self.config.get("torch_device", "auto")
+        if configured_device == "cpu":
+            return "cpu"
+        if configured_device == "cuda":
+            return "cuda"
+        return "cuda" if os.environ.get("FORCE_CUDA") == "1" else "cpu"
+
+    def update_config(self, new_config: dict[str, Any]) -> None:
+        """
+        Merge new settings into active runtime config.
+
+        :param new_config: Partial config dictionary to apply.
+
+        Example::
+            In: pipeline.update_config({"spacing": 80})
+            Out: pipeline.config["spacing"] == 80
+        """
+        self.config.update(new_config)
+        self.log.info("Configuration updated: %s", new_config)
+
+    def _ensure_directories(self) -> None:
+        """Create raw/rejected/results directories if they are missing."""
+        for directory_path in [self.raw_dir, self.rejected_dir, self.results_dir]:
+            directory_path.mkdir(parents=True, exist_ok=True)
+
+    def ensure_directories(self) -> None:
+        """
+        Public wrapper for directory bootstrap.
+
+        Example::
+            In: pipeline.ensure_directories()
+            Out: required directories exist on disk
+        """
+        self._ensure_directories()
+
+    def step_1_generate_points(self) -> int:
+        """
+        Step 1: generate sampling points and save them to the configured layer path.
+
+        :return: Number of generated points.
+
+        Example::
+            In: pipeline.step_1_generate_points()
+            Out: 1248
+        """
+        planner_source = self.config.get("planner_source", "place")
+        spacing = float(self.config["spacing"])
+        min_distance = float(self.config["min_distance"])
+        points_output_path = (self.config.get("points_layer_path") or "").strip()
+        if not points_output_path:
+            raise ValueError("Set ``points_layer_path`` to a .geojson / .gpkg output path.")
+
+        self.log.info("=== STEP 1: Point generation (source=%s, spacing=%sm) ===", planner_source, spacing)
+
+        try:
+            # Choose exactly one planner source mode.
+            if planner_source == "place":
+                place = self.config["place_name"]
+                self.roads_gdf, self.points = build_points_pipeline(
+                    output_points_path=points_output_path,
+                    place_name=place,
+                    spacing=spacing,
+                    min_distance_m=min_distance,
+                )
+            elif planner_source == "region":
+                region_path = (self.config.get("region_geojson_path") or "").strip()
+                if not region_path:
+                    raise ValueError("Region GeoJSON path is empty.")
+                self.roads_gdf, self.points = build_points_pipeline(
+                    output_points_path=points_output_path,
+                    region_geojson_path=region_path,
+                    spacing=spacing,
+                    min_distance_m=min_distance,
+                )
+            elif planner_source == "roads":
+                roads_path = (self.config.get("road_geojson_path") or "").strip()
+                if not roads_path:
+                    raise ValueError("Road network GeoJSON path is empty.")
+                self.roads_gdf, self.points = build_points_pipeline(
+                    output_points_path=points_output_path,
+                    road_geojson_path=roads_path,
+                    spacing=spacing,
+                    min_distance_m=min_distance,
+                )
+            else:
+                raise ValueError(f"Unknown planner source: {planner_source}")
+
+            count = len(self.points)
+            self.log.info("Success. Generated %s points; saved to %s", count, Path(points_output_path).resolve())
+            return count
+        except Exception as error:
+            self.log.error("Step 1 failed: %s", error)
+            raise
+
+    def step_2_download_images(self) -> dict[str, Any]:
+        """
+        Step 2: download Mapillary images for loaded sampling points.
+
+        :return: Download summary dictionary.
+
+        Example::
+            In: pipeline.step_2_download_images()["downloaded"]
+            Out: 915
+        """
+        self.log.info("=== STEP 2: Mapillary download ===")
+
+        points_path = (self.config.get("mapillary_points_path") or "").strip()
+        if not points_path:
+            points_path = (self.config.get("points_layer_path") or "").strip()
+        if not points_path:
+            raise ValueError("Set a point layer path (Mapillary tab or planner output path).")
+        try:
+            # Reload points from disk to keep GUI/CLI behavior consistent.
+            self.points = load_sampling_points_latlon(points_path)
+        except FileNotFoundError as error:
+            self.log.error("%s", error)
+            raise RuntimeError("Sampling points file missing. Run step 1 (generate points) first.") from error
+        if not self.points:
+            raise RuntimeError(f"Point layer is empty: {points_path}")
+
+        token = self.config["mapillary_token"]
+        if not token:
+            self.log.error("Mapillary token is missing.")
+            raise ValueError("A Mapillary access token is required.")
+
+        image_output_dir = (self.config.get("mapillary_images_output_dir") or "").strip()
+        if image_output_dir:
+            self.raw_dir = Path(image_output_dir).expanduser().resolve()
+        else:
+            self.raw_dir = self.base_dir / "images" / "raw"
+        self._ensure_directories()
+
+        # Downloader returns per-point outcomes plus aggregate timing/count metrics.
+        stats = download_mapillary_images(
+            points=self.points,
+            output_folder=str(self.raw_dir),
+            mapillary_token=token,
+            search_radius_m=float(self.config["search_radius"]),
+            fov_deg=float(self.config.get("mapillary_fov_deg", 90)),
+            max_workers=int(self.config.get("mapillary_max_workers", 20)),
+        )
+        self.log.info("Download finished.")
+        return stats
+
+    def step_3_prefilter(self) -> dict[str, Any]:
+        """
+        Step 3: run CLIP prefilter and split images into kept/rejected groups.
+
+        :return: Prefilter statistics dictionary.
+
+        Example::
+            ``pipeline.step_3_prefilter()["summary"]["kept"] -> 640``
+        """
+        self.log.info("=== STEP 3: CLIP prefilter ===")
+
+        device = self._resolve_torch_device()
+
+        configured_image_folder = (self.config.get("prefilter_image_folder") or "").strip()
+        if not configured_image_folder:
+            image_folder = str(self.raw_dir.resolve())
+        else:
+            image_folder = str(Path(configured_image_folder).expanduser().resolve())
+
+        rejected_spec = (self.config.get("prefilter_rejected_folder") or "").strip()
+        if not rejected_spec:
+            # Relative name means "inside image_folder".
+            rejected_spec = "rejected"
+
+        model_names = tuple(self.config.get("clip_model_names") or ("ViT-L/14@336px",))
+        stats = prefilter_folder(
+            image_folder=image_folder,
+            rejected_folder=rejected_spec,
+            device=device,
+            model_names=model_names,
+            beta_sigmoid=float(self.config.get("beta_sigmoid", 30.0)),
+            filter_threshold=float(self.config.get("filter_threshold", 40.0)),
+            filter_prompts=prefilter_prompts_from_config(self.config),
+        )
+
+        kept_count = stats["summary"]["kept"]
+        rejected_count = stats["summary"]["rejected"]
+        self.log.info("Prefilter done. Kept: %s, rejected: %s", kept_count, rejected_count)
+        return stats
+
+    def step_4_evaluate(self) -> dict[str, Any]:
+        """
+        Step 4: run CLIP scoring for configured dimensions.
+
+        :return: Evaluation results dictionary.
+
+        Example::
+            In: pipeline.step_4_evaluate()
+            Out: {"results": [...], "summary": {...}, ...}
+        """
+        self.log.info("=== STEP 4: CLIP image scoring ===")
+
+        device = self._resolve_torch_device()
+
+        model_names = tuple(self.config.get("clip_model_names") or ("ViT-L/14@336px",))
+        evaluation_results = evaluate_images_with_clip(
+            image_folder=str(self.raw_dir),
+            device=device,
+            model_names=model_names,
+            beta_sigmoid=float(self.config.get("beta_sigmoid", 30.0)),
+            raise_on_validation_error=True,
+        )
+        self.evaluation_results = evaluation_results
+
+        self.log.info("Scoring finished successfully.")
+        return evaluation_results
+
+    def step_5_export(self) -> str:
+        """
+        Step 5: export scored points to a vector file.
+
+        :return: Path to saved output file.
+
+        Example::
+            In: pipeline.step_5_export()
+            Out: "data/results/urban_quality_ai_output.geojson"
+        """
+        self.log.info("=== STEP 5: Export results ===")
+
+        if not self.evaluation_results:
+            self.log.warning("No evaluation results. Run step 4 first.")
+            raise RuntimeError("Nothing to export.")
+
+        custom = (self.config.get("export_path") or "").strip()
+        if custom:
+            output_path = Path(custom)
+            if not output_path.is_absolute():
+                # Keep relative paths anchored to current working directory.
+                output_path = Path.cwd() / output_path
+        else:
+            output_path = self.results_dir / "urban_quality_ai_output.geojson"
+        output_path.parent.mkdir(parents=True, exist_ok=True)
+        saved_path = export_point_layer(
+            results=self.evaluation_results,
+            output_path=str(output_path),
+        )
+        self.log.info("Written to %s", saved_path)
+        return str(saved_path)
+
+    def step_6_evaluate_vit(self) -> dict[str, Any]:
+        """
+        Step 6: run fine-tuned ViT scoring and export result layer.
+
+        :return: Evaluation results dictionary.
+
+        Example::
+            In: pipeline.step_6_evaluate_vit()
+            Out: {"results": [...], "summary": {...}, ...}
+        """
+        self.log.info("=== STEP 6: Fine-tuned ViT scoring ===")
+
+        images_dir_spec = (self.config.get("vit_images_dir") or "").strip()
+        if not images_dir_spec:
+            raise ValueError("Set 'vit_images_dir' (folder with images).")
+        images_dir = str(Path(images_dir_spec).expanduser().resolve())
+
+        model_path_spec = (self.config.get("vit_model_path") or "").strip()
+        if not model_path_spec:
+            # Backward-compatible alias used by some configs.
+            model_path_spec = (self.config.get("vit_checkpoint_path") or "").strip()
+        if not model_path_spec:
+            raise ValueError("Set 'vit_model_path' (model weights file).")
+        model_path = Path(model_path_spec)
+
+        calibrators_dir_spec = (self.config.get("vit_calibrators_dir") or "").strip()
+        calibrators_dir = Path(calibrators_dir_spec) if calibrators_dir_spec else None
+
+        output_layer_spec = (self.config.get("vit_output_layer_path") or "").strip()
+        output_layer_path = (
+            Path(output_layer_spec) if output_layer_spec else (self.results_dir / "vit_finetuned_scores.gpkg")
+        )
+        output_layer_name = (self.config.get("vit_output_layer_name") or "").strip() or None
+
+        model_name = str(self.config.get("vit_model_name") or "vit_base_patch14_dinov2.lvd142m")
+        image_size = int(self.config.get("vit_image_size") or 224)
+        batch_size = int(self.config.get("vit_batch_size") or 32)
+        vit_torch_device = str(self.config.get("vit_torch_device") or "auto")
+
+        evaluation_results = evaluate_images_with_finetuned(
+            images_dir=images_dir,
+            model_path=model_path,
+            calibrators_dir=calibrators_dir,
+            model_name=model_name,
+            image_size=image_size,
+            batch_size=batch_size,
+            torch_device=vit_torch_device,
+        )
+        self.evaluation_results = evaluation_results
+
+        # Export is intentionally done at the pipeline layer (avoid evaluation -> layer_creation coupling).
+        output_layer_path.parent.mkdir(parents=True, exist_ok=True)
+        export_point_layer(
+            results=evaluation_results,
+            output_path=str(output_layer_path),
+            layer=output_layer_name,
+        )
+        self.log.info("Exported fine-tuned results to: %s", output_layer_path)
+
+        self.log.info("ViT scoring finished successfully.")
+        return evaluation_results
diff --git a/src/uq_desktop_processor/pipeline/points_io.py b/src/uq_desktop_processor/pipeline/points_io.py
new file mode 100644
index 0000000..f572cdb
--- /dev/null
+++ b/src/uq_desktop_processor/pipeline/points_io.py
@@ -0,0 +1,45 @@
+"""
+Loads and saves sampling-point GeoJSON used between pipeline stages.
+"""
+
+from pathlib import Path
+
+import geopandas as gpd
+
+
+def load_sampling_points_latlon(path: str | Path) -> list[tuple[float, float]]:
+    """
+    Load a point layer (Point geometries, WGS84) into ``(latitude, longitude)`` tuples
+    for Mapillary download and map display.
+
+    Non-point geometries are converted to centroids.
+
+    :param path: Path to a vector layer containing sampling geometries.
+    :return: Sampling points as ``(latitude, longitude)`` pairs.
+    :raises FileNotFoundError: If the point layer file does not exist.
+
+    Example::
+        In: load_sampling_points_latlon("data/results/sampling_points.geojson")
+        Out: [(50.0612, 19.9377), (50.0620, 19.9402), ...]
+    """
+    point_layer_path = Path(path)
+    if not point_layer_path.is_file():
+        raise FileNotFoundError(f"Point layer file not found: {point_layer_path}")
+    gdf = gpd.read_file(point_layer_path)
+    if gdf.empty:
+        return []
+    if gdf.crs is None:
+        gdf = gdf.set_crs("EPSG:4326")
+    else:
+        gdf = gdf.to_crs("EPSG:4326")
+    latlon_points: list[tuple[float, float]] = []
+    for geom in gdf.geometry:
+        if geom is None or geom.is_empty:
+            continue
+        if geom.geom_type == "Point":
+            latlon_points.append((float(geom.y), float(geom.x)))
+        else:
+            # Keep a single representative coordinate for non-point input.
+            centroid = geom.centroid
+            latlon_points.append((float(centroid.y), float(centroid.x)))
+    return latlon_points
diff --git a/src/uq_desktop_processor/pipeline/prefilter_config.py b/src/uq_desktop_processor/pipeline/prefilter_config.py
new file mode 100644
index 0000000..472a86c
--- /dev/null
+++ b/src/uq_desktop_processor/pipeline/prefilter_config.py
@@ -0,0 +1,36 @@
+"""
+Loads YAML/JSON prefilter settings and merges them with pipeline defaults.
+"""
+
+from typing import Any
+
+from uq_desktop_processor.evaluation.clip_prefilter import defaults as clip_prefilter_defaults
+
+
+def prefilter_prompts_from_config(config: dict[str, Any]) -> dict[str, tuple[str, ...]]:
+    """
+    Parse multiline ``prefilter_*_prompts`` strings into positive/negative prompt tuples.
+
+    Falls back to bundled defaults when any side is missing.
+
+    :param config: Pipeline config dictionary with optional ``prefilter_pos_prompts`` / ``prefilter_neg_prompts``.
+    :return: Dict with ``"pos"`` and ``"neg"`` tuple values.
+
+    Example::
+        In: prefilter_prompts_from_config({"prefilter_pos_prompts": "green\\npark", "prefilter_neg_prompts": ""})
+        Out: {"pos": ("green", "park"), "neg": (...defaults...)}
+    """
+
+    def lines(text: Any) -> tuple[str, ...]:
+        # Accept only non-empty strings; ignore blank lines.
+        if not text or not isinstance(text, str):
+            return ()
+        return tuple(line.strip() for line in text.splitlines() if line.strip())
+
+    positive_prompts = lines(config.get("prefilter_pos_prompts"))
+    negative_prompts = lines(config.get("prefilter_neg_prompts"))
+    if not positive_prompts:
+        positive_prompts = tuple(clip_prefilter_defaults.FILTER_PROMPTS["pos"])
+    if not negative_prompts:
+        negative_prompts = tuple(clip_prefilter_defaults.FILTER_PROMPTS["neg"])
+    return {"pos": positive_prompts, "neg": negative_prompts}
diff --git a/src/uq_desktop_processor/street_view_analysis/__init__.py b/src/uq_desktop_processor/street_view_analysis/__init__.py
new file mode 100644
index 0000000..08db078
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/__init__.py
@@ -0,0 +1,14 @@
+"""
+Street-view analysis: road sampling, Mapillary download, and Euler route generation.
+"""
+
+from .chinese_postman_routes import EulerRoutesResult, generate_clean_routes
+from .images_downloader import download_mapillary_images
+from .road_points_generator import build_points_pipeline
+
+__all__ = [
+    "EulerRoutesResult",
+    "build_points_pipeline",
+    "download_mapillary_images",
+    "generate_clean_routes",
+]
diff --git a/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/__init__.py b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/__init__.py
new file mode 100644
index 0000000..a306e6a
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/__init__.py
@@ -0,0 +1,9 @@
+"""
+Road-network coverage routes (Chinese postman / Eulerian circuits) split on a grid;
+export to GPX in WGS84.
+"""
+
+from .generate import generate_clean_routes
+from .result import EulerRoutesResult
+
+__all__ = ["EulerRoutesResult", "generate_clean_routes"]
diff --git a/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/generate.py b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/generate.py
new file mode 100644
index 0000000..83b0788
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/generate.py
@@ -0,0 +1,166 @@
+"""
+Grid-sector Euler routes: truncate graph per tile, Chinese postman per component, write GPX.
+"""
+
+import logging
+from pathlib import Path
+from typing import cast
+
+import networkx as nx
+import numpy as np
+import osmnx as ox
+from osmnx.truncate import truncate_graph_bbox
+
+from uq_desktop_processor.street_view_analysis.road_graph_prepare import load_route_aligned_graph_wgs84
+
+from .gpx_export import build_gpx, write_gpx
+from .postman import chinese_postman_polyline
+from .result import EulerRoutesResult
+
+log = logging.getLogger(__name__)
+
+
+def generate_clean_routes(
+    city_name: str = "Katowice, Poland",
+    grid_size: tuple[int, int] = (3, 3),
+    output_dir: str | Path = "routes_chinese_postman_gpx",
+    *,
+    consolidate_tolerance_m: float = 15.0,
+    use_cache: bool = True,
+    region_geojson_path: str | Path | None = None,
+    road_geojson_path: str | Path | None = None,
+) -> EulerRoutesResult:
+    """
+    Split the study area into a lat/lon grid, run Chinese postman on each sector, emit GPX files.
+
+    :param city_name: Default place when no region or road file is passed.
+    :param grid_size: ``(columns, rows)`` of bounding-box sectors.
+    :param output_dir: Directory for ``trasa_*.gpx`` outputs.
+    :param consolidate_tolerance_m: Same as :func:`load_route_aligned_graph_wgs84`.
+    :param use_cache: OSMnx HTTP cache.
+    :param region_geojson_path: Optional polygon AOI instead of ``city_name``.
+    :param road_geojson_path: Optional local roads instead of downloading.
+    :return: Resolved paths and polylines for all successful sectors.
+
+    Example::
+        In: generate_clean_routes(city_name="Katowice, Poland", grid_size=(2, 2)).gpx_paths
+        Out: tuple of saved GPX paths, e.g. (Path(".../trasa_1.gpx"), Path(".../trasa_2.gpx"), ...)
+    """
+    output_directory = Path(output_dir)
+    output_directory.mkdir(parents=True, exist_ok=True)
+
+    geographic_graph, city_gdf = load_route_aligned_graph_wgs84(
+        city_name=city_name,
+        region_geojson_path=region_geojson_path,
+        road_geojson_path=road_geojson_path,
+        consolidate_tolerance_m=consolidate_tolerance_m,
+        use_cache=use_cache,
+    )
+
+    # OSMnx truncate_* expects a MultiDiGraph (successors/predecessors); load_route_aligned_graph_wgs84 returns MultiGraph.
+    directed_geographic_graph = nx.MultiDiGraph(geographic_graph)
+    directed_geographic_graph.graph.update(geographic_graph.graph)
+
+    w_bound, s_bound, e_bound, n_bound = city_gdf.total_bounds
+    column_count, row_count = grid_size[0], grid_size[1]
+    # Grid lines in WGS84; each cell becomes one sector
+    lon_grid_boundaries = np.linspace(w_bound, e_bound, column_count + 1)
+    lat_grid_boundaries = np.linspace(s_bound, n_bound, row_count + 1)
+
+    sectors: list[dict[str, float]] = []
+    for lat_index in range(len(lat_grid_boundaries) - 1):
+        for lon_index in range(len(lon_grid_boundaries) - 1):
+            sectors.append(
+                {
+                    "s": float(lat_grid_boundaries[lat_index]),
+                    "n": float(lat_grid_boundaries[lat_index + 1]),
+                    "w": float(lon_grid_boundaries[lon_index]),
+                    "e": float(lon_grid_boundaries[lon_index + 1]),
+                }
+            )
+
+    gpx_paths: list[Path] = []
+    polylines: list[tuple[tuple[float, float], ...]] = []
+
+    for sector_index, sector_bounds in enumerate(sectors):
+        tile_number = sector_index + 1
+        log.info("Sector %s / %s", tile_number, len(sectors))
+
+        try:
+            # OSMnx bbox order: north, south, east, west
+            bounding_box = (sector_bounds["n"], sector_bounds["s"], sector_bounds["e"], sector_bounds["w"])
+            sector_graph = truncate_graph_bbox(directed_geographic_graph, bbox=bounding_box, truncate_by_edge=True)
+
+            if sector_graph is None or len(sector_graph.nodes) < 2:
+                log.warning("Sector %s: empty graph, skipping.", tile_number)
+                continue
+
+            undirected_sector_graph = ox.get_undirected(cast(nx.MultiDiGraph, sector_graph))
+            connected_components = list(nx.connected_components(undirected_sector_graph))
+            connected_components.sort(key=len, reverse=True)  # Larger components first (typical main roads)
+
+            sector_polylines: list[list[tuple[float, float]]] = []
+
+            for component_index, component_nodes in enumerate(connected_components, start=1):
+                component_subgraph = undirected_sector_graph.subgraph(component_nodes).copy()
+                if component_subgraph.number_of_edges() < 1:
+                    continue
+                try:
+                    route_polyline = chinese_postman_polyline(cast(nx.MultiGraph, component_subgraph))
+                except Exception as component_error:
+                    log.exception(
+                        "Sector %s subgraph %s / %s: Chinese postman failed: %s",
+                        tile_number,
+                        component_index,
+                        len(connected_components),
+                        component_error,
+                    )
+                    continue
+                if len(route_polyline) < 2:
+                    continue
+                sector_polylines.append(route_polyline)
+
+            if not sector_polylines:
+                log.warning("Sector %s: no routable subgraphs, skipping file.", tile_number)
+                continue
+
+            # Inform when one tile produced multiple disjoint walks
+            # Count only components that actually contain edges (ignore isolated-node components).
+            component_count_with_edges = sum(
+                1
+                for component_nodes in connected_components
+                if undirected_sector_graph.subgraph(component_nodes).number_of_edges() >= 1
+            )
+            if component_count_with_edges > 1:
+                log.info(
+                    "Sector %s: %s route(s) covering %s disconnected subgraph(s) with edges.",
+                    tile_number,
+                    len(sector_polylines),
+                    component_count_with_edges,
+                )
+
+            gpx_document = build_gpx(sector_polylines, sector_name=f"Sector {tile_number}")
+            gpx_file_path = output_directory / f"route_{tile_number}.gpx"
+            write_gpx(gpx_file_path, gpx_document)
+            log.info("Wrote %s", gpx_file_path)
+
+            gpx_paths.append(gpx_file_path)
+            polylines.extend(tuple(polyline) for polyline in sector_polylines)
+
+        except ValueError as error:
+            # Empty bbox / polygon (e.g. sector outside drivable network after simplify)
+            if "no graph nodes" in str(error).lower():
+                log.warning("Sector %s: no graph nodes in sector bounds, skipping.", tile_number)
+                continue
+            raise
+        except Exception as error:
+            log.exception("Error in sector %s: %s", tile_number, error)
+
+    return EulerRoutesResult(
+        output_dir=output_directory.resolve(),
+        gpx_paths=tuple(gpx_paths),
+        polylines_wgs84=tuple(polylines),
+    )
+
+
+__all__ = ["generate_clean_routes"]
diff --git a/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/gpx_export.py b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/gpx_export.py
new file mode 100644
index 0000000..4212043
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/gpx_export.py
@@ -0,0 +1,52 @@
+"""
+Build GPX documents from WGS84 polylines and write them to disk.
+"""
+
+from pathlib import Path
+
+import gpxpy.gpx
+
+
+def build_gpx(polylines_wgs84: list[list[tuple[float, float]]], *, sector_name: str) -> gpxpy.gpx.GPX:
+    """
+    Create one GPX with one track per polyline; split tracks are named with a part suffix.
+
+    :param polylines_wgs84: Each inner list is ``(longitude, latitude)`` vertices.
+    :param sector_name: Base name for track metadata.
+    :return: In-memory GPX object.
+
+    Example::
+        In: build_gpx([[(19.94, 50.06), (19.95, 50.06)]], sector_name="Sector 1")
+        Out: GPX with 1 track, 1 segment, 2 points, track name "Sector 1"
+    """
+    gpx = gpxpy.gpx.GPX()
+    for polyline_coordinates in polylines_wgs84:
+        # One track + one segment per closed/open walk
+        track = gpxpy.gpx.GPXTrack()
+        gpx.tracks.append(track)
+        track_segment = gpxpy.gpx.GPXTrackSegment()
+        track.segments.append(track_segment)
+        for longitude, latitude in polyline_coordinates:
+            track_segment.points.append(gpxpy.gpx.GPXTrackPoint(latitude=latitude, longitude=longitude))
+
+    # Multiple subgraphs -> numbered track names
+    for track_index, track in enumerate(gpx.tracks):
+        if len(gpx.tracks) == 1:
+            track.name = sector_name
+        else:
+            track.name = f"{sector_name} part {track_index + 1}"
+    return gpx
+
+
+def write_gpx(output_path: Path, gpx_document: gpxpy.gpx.GPX) -> None:
+    """
+    Serialize a GPX object to UTF-8 text.
+
+    :param output_path: Destination ``.gpx`` path.
+    :param gpx_document: Object from :func:`build_gpx`.
+
+    Example::
+        In: write_gpx(Path("routes/trasa_1.gpx"), gpx)
+        Out: "routes/trasa_1.gpx" created on disk (UTF-8 GPX XML)
+    """
+    output_path.write_text(gpx_document.to_xml(), encoding="utf-8")
diff --git a/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/polyline.py b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/polyline.py
new file mode 100644
index 0000000..dbf6b04
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/polyline.py
@@ -0,0 +1,57 @@
+"""
+Order edge geometries along an Eulerian circuit into a single WGS84 polyline.
+"""
+
+from typing import Any
+
+import networkx as nx
+
+
+def polyline_from_eulerian_circuit(
+    eulerian_graph: nx.MultiGraph,
+    circuit: list[tuple[Any, Any, Any]],
+) -> list[tuple[float, float]]:
+    """
+    Walk the circuit and concatenate edge ``geometry`` coords (or node x/y) in order.
+
+    Coordinates are ``(longitude, latitude)``. Duplicate consecutive vertices are skipped.
+
+    :param eulerian_graph: Graph whose edges may carry Shapely line geometries (OSMnx-style).
+    :param circuit: Eulerian circuit from ``nx.eulerian_circuit(..., keys=True)``.
+    :return: Ordered vertex list along the closed walk.
+
+    Example::
+        In: polyline_from_eulerian_circuit(eulerian_graph, circuit)
+        Out: [(19.94, 50.06), (19.95, 50.06), ...]
+    """
+    ordered_polyline: list[tuple[float, float]] = []
+    for start_node, end_node, edge_key in circuit:
+        edge_data = eulerian_graph.get_edge_data(start_node, end_node, edge_key)
+        start_node_data = eulerian_graph.nodes[start_node]
+
+        if edge_data is not None and "geometry" in edge_data:
+            coords = list(edge_data["geometry"].coords)
+            # Orient LineString to start near circuit start_node
+            start_distance_squared = (coords[0][0] - start_node_data["x"]) ** 2 + (
+                coords[0][1] - start_node_data["y"]
+            ) ** 2
+            end_distance_squared = (coords[-1][0] - start_node_data["x"]) ** 2 + (
+                coords[-1][1] - start_node_data["y"]
+            ) ** 2
+            if end_distance_squared < start_distance_squared:
+                coords = coords[::-1]
+            for lon, lat in coords:
+                # Append only when this vertex differs from the previous one.
+                # This avoids duplicate consecutive points at segment joins.
+                if not ordered_polyline or (ordered_polyline[-1][1] != lat or ordered_polyline[-1][0] != lon):
+                    ordered_polyline.append((float(lon), float(lat)))
+        else:
+            # Straight edge: use node coordinates only
+            for node_id in (start_node, end_node):
+                node_data = eulerian_graph.nodes[node_id]
+                node_lon = float(node_data["x"])
+                node_lat = float(node_data["y"])
+                # Same dedup rule for fallback node-based coordinates.
+                if not ordered_polyline or (ordered_polyline[-1][1] != node_lat or ordered_polyline[-1][0] != node_lon):
+                    ordered_polyline.append((node_lon, node_lat))
+    return ordered_polyline
diff --git a/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/postman.py b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/postman.py
new file mode 100644
index 0000000..59ec343
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/postman.py
@@ -0,0 +1,53 @@
+"""
+Chinese postman: duplicate edges to balance odd degrees, then extract an Euler tour polyline.
+"""
+
+from typing import Any
+
+import networkx as nx
+
+from .polyline import polyline_from_eulerian_circuit
+
+
+def chinese_postman_polyline(undirected_graph: nx.MultiGraph) -> list[tuple[float, float]]:
+    """
+    Minimum-length closed walk covering every edge at least once (undirected, connected, with edges).
+
+    Odd-degree nodes are paired by min-weight matching on shortest-path distances; duplicated
+    edges are added, then an Euler circuit is converted to a ``(lon, lat)`` polyline.
+
+    :param undirected_graph: Road subgraph; edge attribute ``length`` weights paths and matching.
+    :return: Closed polyline in WGS84 node order.
+
+    Example::
+        In: chinese_postman_polyline(undirected_graph)
+        Out: [(19.94, 50.06), (19.95, 50.06), ...]
+    """
+    odd_degree_nodes = [node_id for node_id, degree in undirected_graph.degree() if degree % 2 == 1]
+    odd_node_matching: Any = []
+    if odd_degree_nodes:
+        # Pair odd vertices by shortest-path length; min matching yields min duplicate mileage
+        odd_complete_graph = nx.Graph()
+        for odd_node_index, source_node in enumerate(odd_degree_nodes):
+            distance_by_node = nx.single_source_dijkstra_path_length(undirected_graph, source_node, weight="length")
+            for target_node in odd_degree_nodes[odd_node_index + 1 :]:
+                if target_node in distance_by_node:
+                    odd_complete_graph.add_edge(source_node, target_node, weight=distance_by_node[target_node])
+        odd_node_matching = nx.algorithms.matching.min_weight_matching(odd_complete_graph, weight="weight")
+
+    # Start from original edges; duplicate along shortest paths to make all degrees even
+    eulerian_graph = nx.MultiGraph(undirected_graph)
+    for source_node, target_node in odd_node_matching:
+        shortest_path_nodes = nx.shortest_path(undirected_graph, source_node, target_node, weight="length")
+        for path_index in range(len(shortest_path_nodes) - 1):
+            path_start_node, path_end_node = shortest_path_nodes[path_index], shortest_path_nodes[path_index + 1]
+            edge_data = undirected_graph.get_edge_data(path_start_node, path_end_node)
+            # MultiGraph: pick first parallel edge's attrs when duplicating
+            edge_attributes = edge_data[0] if isinstance(edge_data, dict) and 0 in edge_data else edge_data
+            if isinstance(edge_attributes, dict):
+                eulerian_graph.add_edge(path_start_node, path_end_node, **edge_attributes)
+            else:
+                eulerian_graph.add_edge(path_start_node, path_end_node)
+
+    eulerian_circuit_edges = list(nx.eulerian_circuit(eulerian_graph, keys=True))
+    return polyline_from_eulerian_circuit(eulerian_graph, eulerian_circuit_edges)
diff --git a/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/result.py b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/result.py
new file mode 100644
index 0000000..6173367
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/chinese_postman_routes/result.py
@@ -0,0 +1,19 @@
+"""
+Container for GPX paths and polylines returned by grid-sector route generation.
+"""
+
+from dataclasses import dataclass, field
+from pathlib import Path
+
+
+@dataclass(frozen=True)
+class EulerRoutesResult:
+    """
+    Output directory, list of GPX paths, and WGS84 polylines (one sequence per route).
+
+    ``polylines_wgs84`` has multiple entries when a sector contained several disconnected subgraphs.
+    """
+
+    output_dir: Path
+    gpx_paths: tuple[Path, ...] = field(default_factory=tuple)
+    polylines_wgs84: tuple[tuple[tuple[float, float], ...], ...] = field(default_factory=tuple)
diff --git a/src/uq_desktop_processor/street_view_analysis/images_downloader/__init__.py b/src/uq_desktop_processor/street_view_analysis/images_downloader/__init__.py
new file mode 100644
index 0000000..c580e3a
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/images_downloader/__init__.py
@@ -0,0 +1,19 @@
+"""
+Mapillary image download, API helpers, and panorama processing.
+"""
+
+from .api import query_mapillary_image
+from .downloader import download_mapillary_images
+from .helpers import lat_lon_from_geometry, lat_lon_from_mapillary_record, mapillary_image_filename
+from .image_processing import download_image, process_panorama, save_jpeg_with_exif
+
+__all__ = [
+    "download_image",
+    "download_mapillary_images",
+    "lat_lon_from_geometry",
+    "lat_lon_from_mapillary_record",
+    "mapillary_image_filename",
+    "process_panorama",
+    "query_mapillary_image",
+    "save_jpeg_with_exif",
+]
diff --git a/src/uq_desktop_processor/street_view_analysis/images_downloader/api.py b/src/uq_desktop_processor/street_view_analysis/images_downloader/api.py
new file mode 100644
index 0000000..4ba6122
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/images_downloader/api.py
@@ -0,0 +1,185 @@
+"""
+Mapillary Graph API client: image search by bbox and metadata retrieval.
+"""
+
+import logging
+
+import numpy as np
+import requests
+from requests.exceptions import ConnectionError, HTTPError, Timeout
+
+log = logging.getLogger(__name__)
+
+MAPILLARY_API_URL = "https://graph.mapillary.com/images"
+
+
+def _calculate_bounding_box(lat: float, lon: float, radius_m: float) -> tuple[float, float, float, float]:
+    """
+    Build a geographic bounding box from a center point and radius in meters.
+
+    :param lat: Latitude of the center.
+    :param lon: Longitude of the center.
+    :param radius_m: Half-edge size in meters (approximate).
+    :return: ``(min_lon, min_lat, max_lon, max_lat)``.
+
+    Example::
+        In: _calculate_bounding_box(50.05, 19.94, 100)
+        Out: tuple (min_lon, min_lat, max_lon, max_lat) around the input point
+    """
+    # ~111.32 km per degree latitude; longitude spacing scales with cos(lat)
+    delta_lat = radius_m / 111320
+    delta_lon = delta_lat / np.cos(np.radians(lat))
+    return lon - delta_lon, lat - delta_lat, lon + delta_lon, lat + delta_lat
+
+
+def _build_mapillary_query_params(min_lon: float, min_lat: float, max_lon: float, max_lat: float) -> dict:
+    """
+    Build query parameters for a single-image Mapillary ``/images`` request.
+
+    :param min_lon: Bounding box minimum longitude.
+    :param min_lat: Bounding box minimum latitude.
+    :param max_lon: Bounding box maximum longitude.
+    :param max_lat: Bounding box maximum latitude.
+    :return: Query parameter mapping for ``requests.get``.
+
+    Example::
+        In: _build_mapillary_query_params(19.9, 50.0, 20.0, 50.1)["limit"]
+        Out: 1
+    """
+    return {
+        "fields": "id,thumb_1024_url,is_pano,captured_at,geometry,computed_geometry",
+        "bbox": f"{min_lon},{min_lat},{max_lon},{max_lat}",
+        "limit": 1,
+    }
+
+
+def _is_radius_timeout_error(response: requests.Response) -> bool:
+    """
+    Detect Mapillary error 3404014 (bbox / radius too large for the request).
+
+    :param response: HTTP response with error JSON body.
+    :return: True if the error subcode indicates radius timeout.
+    """
+    try:
+        error_info = response.json().get("error")
+        # Mapillary: bbox too large / request timed out
+        return error_info and error_info.get("error_subcode") == 3404014
+
+    except ValueError:
+        return False
+
+
+def _fetch_mapillary_data(params: dict, headers: dict, timeout: float) -> dict:
+    """
+    GET the Mapillary images endpoint and return parsed JSON.
+
+    :param params: Query string parameters.
+    :param headers: Request headers (e.g. OAuth).
+    :param timeout: Socket read timeout in seconds.
+    :return: Parsed JSON body.
+    :raises HTTPError: If the status code indicates failure.
+    """
+    log.debug("Requesting Mapillary API with params: %s", params)
+    response = requests.get(MAPILLARY_API_URL, params=params, headers=headers, timeout=timeout)
+    response.raise_for_status()
+    return response.json()
+
+
+def _get_single_image_from_response(data: dict) -> dict | None:
+    """
+    Return the first image record from a Mapillary list response.
+
+    :param data: Parsed JSON from ``/images``.
+    :return: One image dict, or None if the list is empty.
+
+    Example::
+        In: _get_single_image_from_response({"data": [{"id": "abc"}]})
+        Out: {"id": "abc"}
+    """
+    images = data.get("data", [])
+    if not images:
+        log.debug("No images found in API response.")
+    return images[0] if images else None
+
+
+def query_mapillary_image(
+    lat: float, lon: float, token: str, radius: float, timeout: float, retries: int = 2
+) -> dict | None:
+    """
+    Find one image near ``(lat, lon)``, shrinking the radius or retrying on certain errors.
+
+    :param lat: Search latitude.
+    :param lon: Search longitude.
+    :param token: OAuth access token.
+    :param radius: Initial search radius in meters.
+    :param timeout: HTTP timeout in seconds.
+    :param retries: Extra attempts after the first request (radius shrink and HTTP retries).
+    :return: Image metadata dict, or None if no image or unrecoverable error.
+
+    Example::
+        In: query_mapillary_image(50.06, 19.94, token="...", radius=150, timeout=10.0)
+        Out: {"id": "...", ...} | None
+    """
+    headers = {"Authorization": f"OAuth {token}"}
+
+    # First attempt + retries (radius shrink, 5xx, or network)
+    for attempt_index in range(retries + 1):
+        min_lon, min_lat, max_lon, max_lat = _calculate_bounding_box(lat, lon, radius)
+        params = _build_mapillary_query_params(min_lon, min_lat, max_lon, max_lat)
+
+        try:
+            data = _fetch_mapillary_data(params, headers, timeout)
+            result = _get_single_image_from_response(data)
+            if result:
+                log.debug(
+                    "Found image for (%s, %s) at attempt %s.",
+                    lat,
+                    lon,
+                    attempt_index + 1,
+                )
+            return result
+
+        except HTTPError as http_error:
+            # Shrink search area and retry
+            if http_error.response.status_code == 400 and _is_radius_timeout_error(http_error.response):
+                old_radius = radius
+                radius = max(50, radius // 2)
+                log.warning(
+                    "Radius %sm too large for (%s, %s). Reducing to %sm and retrying.",
+                    old_radius,
+                    lat,
+                    lon,
+                    radius,
+                )
+                continue
+
+            # Transient server errors: retry same bbox
+            if 500 <= http_error.response.status_code < 600:
+                log.warning(
+                    "Mapillary server error %s for (%s, %s). Retrying...",
+                    http_error.response.status_code,
+                    lat,
+                    lon,
+                )
+                continue
+
+            # Auth, bad request, etc.: do not loop forever
+            log.error("HTTP error querying Mapillary for (%s, %s): %s", lat, lon, http_error)
+            break
+
+        except (Timeout, ConnectionError) as network_error:
+            log.warning(
+                "Network error querying Mapillary for (%s, %s): %s. Retrying...",
+                lat,
+                lon,
+                network_error,
+            )
+            continue
+
+    log.info(
+        "Failed to retrieve image for (%s, %s) after %s attempts.",
+        lat,
+        lon,
+        retries + 1,
+    )
+    return None
diff --git a/src/uq_desktop_processor/street_view_analysis/images_downloader/downloader.py b/src/uq_desktop_processor/street_view_analysis/images_downloader/downloader.py
new file mode 100644
index 0000000..1b7a7b9
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/images_downloader/downloader.py
@@ -0,0 +1,218 @@
+"""
+Downloads street-view images for sampling points with concurrency and retries.
+"""
+
+import logging
+import os
+import time
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+from typing import Any
+
+from .api import query_mapillary_image
+from .helpers import lat_lon_from_mapillary_record, mapillary_image_filename
+from .image_processing import download_image, process_panorama, save_jpeg_with_exif
+
+log = logging.getLogger(__name__)
+
+
+def _handle_single_point(
+    lat_lon: tuple[float, float],
+    output_folder: str,
+    mapillary_token: str,
+    search_radius_m: float,
+    fov_deg: float,
+    output_hw: tuple[int, int],
+    api_timeout_s: float,
+    retries: int = 3,
+) -> str:
+    """
+    Fetch and save a Mapillary image for one point, with retries on failure.
+
+    :param lat_lon: ``(latitude, longitude)`` of the target location.
+    :param output_folder: Directory for the saved JPEG.
+    :param mapillary_token: OAuth token for the Mapillary API.
+    :param search_radius_m: Search radius in meters around the point.
+    :param fov_deg: Horizontal field of view in degrees for panorama cropping.
+    :param output_hw: Output size as ``(height, width)``.
+    :param api_timeout_s: Timeout for API and HTTP download requests.
+    :param retries: Attempt count including the first try.
+    :return: Status message (success or failure reason).
+
+    Example::
+        In: _handle_single_point((50.06, 19.94), "data/images", token, 150, 90, (512, 512), 10.0)
+        Out: status string, e.g. "Success (50.06000, 19.94000): <id>.jpg" or "(50.06000, 19.94000) - no image found"
+    """
+    latitude, longitude = lat_lon
+    for attempt_index in range(retries):
+        try:
+            # One full fetch+save path; outer loop handles retries
+            return _try_fetch_and_save_image(
+                latitude, longitude, output_folder, mapillary_token, search_radius_m, fov_deg, output_hw, api_timeout_s
+            )
+        except Exception as error:
+            if attempt_index < retries - 1:
+                log.warning(
+                    "(%.5f, %.5f) Attempt %s failed: %s. Retrying...",
+                    latitude,
+                    longitude,
+                    attempt_index + 1,
+                    error,
+                )
+                time.sleep(1)
+            else:
+                return f"({latitude:.5f}, {longitude:.5f}) Critical error: {error}"
+
+    # e.g. retries == 0
+    return f"({latitude:.5f}, {longitude:.5f}) - failed after {retries} attempts"
+
+
+def _try_fetch_and_save_image(
+    lat: float,
+    lon: float,
+    output_folder: str,
+    mapillary_token: str,
+    search_radius_m: float,
+    fov_deg: float,
+    output_hw: tuple[int, int],
+    api_timeout_s: float,
+) -> str:
+    """
+    Query Mapillary, download the image, optionally unwrap panorama, write JPEG with EXIF.
+
+    :param lat: Latitude of the target point.
+    :param lon: Longitude of the target point.
+    :param output_folder: Directory for the output file.
+    :param mapillary_token: OAuth token for the Mapillary API.
+    :param search_radius_m: Search radius in meters.
+    :param fov_deg: Field of view in degrees for panorama cropping.
+    :param output_hw: Output resolution ``(height, width)``.
+    :param api_timeout_s: Timeout for API and download.
+    :return: Status message indicating success or failure.
+
+    Example::
+        In: _try_fetch_and_save_image(50.06, 19.94, "data/images", token, 150, 90, (512, 512), 10.0)
+        Out: status string, e.g. "Success (...)" or "(...) - missing image URL in API response"
+    """
+    # Nearest image metadata in bbox (or None)
+    data = query_mapillary_image(lat, lon, mapillary_token, search_radius_m, api_timeout_s)
+    if not data:
+        return f"({lat:.5f}, {lon:.5f}) - no image found"
+
+    image_url = data.get("thumb_1024_url")
+    if not image_url:
+        return f"({lat:.5f}, {lon:.5f}) - missing image URL in API response"
+
+    image_array = download_image(image_url, api_timeout_s)
+    if image_array is None:
+        return f"({lat:.5f}, {lon:.5f}) - download failed"
+
+    # Panoramas: equirectangular -> perspective crop
+    if data.get("is_pano", False):
+        image_array = process_panorama(image_array, fov_deg, output_hw)
+
+    image_id = data.get("id")
+    if not image_id:
+        return f"({lat:.5f}, {lon:.5f}) - missing image id in API response"
+
+    image_coordinates = lat_lon_from_mapillary_record(data)
+    # Fall back to query point if the record has no usable geometry
+    image_latitude, image_longitude = image_coordinates if image_coordinates is not None else (lat, lon)
+
+    filename = mapillary_image_filename(str(image_id))
+    path = os.path.join(output_folder, filename)
+    captured_at = data.get("captured_at")
+    save_jpeg_with_exif(
+        image_array,
+        path,
+        lat=image_latitude,
+        lon=image_longitude,
+        captured_at_ms=captured_at,
+    )
+
+    return f"Success ({lat:.5f}, {lon:.5f}): {filename}"
+
+
+def download_mapillary_images(
+    points: list[tuple[float, float]],
+    output_folder: str,
+    mapillary_token: str,
+    *,
+    search_radius_m: float = 150,
+    fov_deg: float = 90,
+    output_hw: tuple[int, int] = (512, 512),
+    max_workers: int = 20,
+    api_timeout_s: float = 10.0,
+) -> dict[str, Any]:
+    """
+    Download Mapillary images for many points using a thread pool.
+
+    :param points: ``(latitude, longitude)`` tuples to query.
+    :param output_folder: Folder for saved JPEGs (created if missing).
+    :param mapillary_token: OAuth token for the Mapillary API.
+    :param search_radius_m: Maximum search radius in meters.
+    :param fov_deg: Field of view for panoramic crops.
+    :param output_hw: Output image ``(height, width)``.
+    :param max_workers: Parallel worker threads.
+    :param api_timeout_s: Per-request timeout in seconds.
+    :return: Summary with counts, timing, failure messages, and resolved output path.
+
+    Example::
+        In: download_mapillary_images([(50.06, 19.94)], "data/images", token)["downloaded"]
+        Out: summary dict, e.g. {"point_count": 1, "downloaded": 1, "failed_messages": [], ...}
+    """
+    os.makedirs(output_folder, exist_ok=True)
+    out_resolved = str(Path(output_folder).resolve())
+
+    total_point_count = len(points)
+    log.info(
+        "Start downloading images for %s points using %s threads...",
+        total_point_count,
+        max_workers,
+    )
+
+    start_time = time.time()
+    status_messages: list[str] = []
+
+    # I/O-bound: threads overlap API + download latency
+    with ThreadPoolExecutor(max_workers=max_workers) as pool:
+        for status_message in pool.map(
+            lambda point_coordinates: _handle_single_point(
+                point_coordinates, output_folder, mapillary_token, search_radius_m, fov_deg, output_hw, api_timeout_s
+            ),
+            points,
+        ):
+            status_messages.append(status_message)
+            # Quiet expected outcomes; surface real failures
+            if status_message.startswith("Success") or "no image found" in status_message:
+                log.debug(status_message)
+            else:
+                log.warning(status_message)
+
+    elapsed_seconds = time.time() - start_time
+    # Success is encoded in the message prefix from _handle_single_point.
+    downloaded_image_count = sum(1 for status_message in status_messages if status_message.startswith("Success"))
+    # Keep all non-success messages for caller inspection/reporting.
+    failure_messages = [
+        status_message for status_message in status_messages if not status_message.startswith("Success")
+    ]
+    if total_point_count > 0:
+        log.info(
+            "Download complete in %.1f s (avg %.2f s/point); saved %s / %s images.",
+            elapsed_seconds,
+            elapsed_seconds / total_point_count,
+            downloaded_image_count,
+            total_point_count,
+        )
+    else:
+        log.info("Download complete: no points to process.")
+
+    images_per_second = (downloaded_image_count / elapsed_seconds) if elapsed_seconds > 0 else 0.0
+    return {
+        "point_count": total_point_count,
+        "downloaded": downloaded_image_count,
+        "failed_messages": failure_messages,
+        "elapsed_s": elapsed_seconds,
+        "output_folder": out_resolved,
+        "images_per_second": images_per_second,
+    }
diff --git a/src/uq_desktop_processor/street_view_analysis/images_downloader/helpers.py b/src/uq_desktop_processor/street_view_analysis/images_downloader/helpers.py
new file mode 100644
index 0000000..6497efc
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/images_downloader/helpers.py
@@ -0,0 +1,69 @@
+"""
+Shared helpers for paths, HTTP sessions, and image naming in the downloader.
+"""
+
+import re
+
+
+def mapillary_image_filename(image_id: str) -> str:
+    """
+    Build a filesystem-safe JPEG filename from a Mapillary image id.
+
+    :param image_id: Mapillary image identifier (as returned by the Graph API).
+    :return: Filename such as ``{id}.jpg``.
+
+    Example::
+        In: mapillary_image_filename("123/abc")
+        Out: "123_abc.jpg"
+    """
+    # Strip unsafe path characters for cross-platform filenames
+    sanitized_image_id = re.sub(r"[^\w.\-]", "_", str(image_id).strip())
+    if not sanitized_image_id:
+        raise ValueError("image_id must be non-empty after sanitization")
+    return f"{sanitized_image_id}.jpg"
+
+
+def lat_lon_from_mapillary_record(data: dict) -> tuple[float, float] | None:
+    """
+    Read image coordinates from a Mapillary image record.
+
+    Prefers ``computed_geometry`` over raw ``geometry``.
+
+    :param data: Image object from the Mapillary API.
+    :return: ``(latitude, longitude)`` or None if no valid Point geometry.
+
+    Example::
+        In: lat_lon_from_mapillary_record({"geometry": {"type": "Point", "coordinates": [19.94, 50.06]}})
+        Out: (50.06, 19.94)
+    """
+    for key in ("computed_geometry", "geometry"):
+        latitude_longitude = lat_lon_from_geometry(data.get(key))
+        if latitude_longitude is not None:
+            return latitude_longitude
+    return None
+
+
+def lat_lon_from_geometry(geometry: dict | None) -> tuple[float, float] | None:
+    """
+    Parse GeoJSON Point coordinates from a Mapillary ``geometry`` field.
+
+    Coordinates are ``[longitude, latitude]`` per GeoJSON.
+
+    :param geometry: The ``geometry`` object from a Mapillary image record, or None.
+    :return: ``(latitude, longitude)`` or None if missing or invalid.
+
+    Example::
+        In: lat_lon_from_geometry({"type": "Point", "coordinates": [19.94, 50.06]})
+        Out: (50.06, 19.94)
+    """
+    if not geometry or geometry.get("type") != "Point":
+        return None
+    coords = geometry.get("coordinates")
+    if not isinstance(coords, list | tuple) or len(coords) < 2:
+        return None
+    try:
+        lon, lat = float(coords[0]), float(coords[1])
+    except (TypeError, ValueError):
+        return None
+    # API is GeoJSON order; callers use (lat, lon)
+    return lat, lon
diff --git a/src/uq_desktop_processor/street_view_analysis/images_downloader/image_processing.py b/src/uq_desktop_processor/street_view_analysis/images_downloader/image_processing.py
new file mode 100644
index 0000000..efed2d9
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/images_downloader/image_processing.py
@@ -0,0 +1,164 @@
+"""
+Resize, EXIF, and panorama-to-perspective conversion for downloaded images.
+"""
+
+import logging
+from datetime import UTC, datetime
+
+import cv2
+import numpy as np
+import piexif
+import py360convert
+import requests
+from PIL import Image
+
+log = logging.getLogger(__name__)
+
+
+def _decimal_deg_to_exif_rationals(decimal_deg: float) -> tuple[tuple[int, int], tuple[int, int], tuple[int, int]]:
+    """
+    Convert signed decimal degrees to EXIF GPS DMS rationals (absolute value; Ref gives hemisphere).
+
+    :param decimal_deg: Latitude or longitude in degrees.
+    :return: Three rationals ``(degrees, minutes, seconds)`` for piexif.
+
+    Example::
+        In: _decimal_deg_to_exif_rationals(50.5)
+        Out: ((50, 1), (30, 1), (0, 1000000))
+    """
+    absolute = abs(decimal_deg)
+    deg = int(absolute)
+    minutes_float = (absolute - deg) * 60.0
+    minutes = int(minutes_float)
+    seconds = (minutes_float - minutes) * 60.0
+    sec_num = int(round(seconds * 1_000_000))
+    # Keep sub-second rational within one minute
+    if sec_num >= 60 * 1_000_000:
+        sec_num = 59_999_999
+    return (deg, 1), (minutes, 1), (sec_num, 1_000_000)
+
+
+def save_jpeg_with_exif(
+    bgr: np.ndarray,
+    path: str,
+    *,
+    lat: float,
+    lon: float,
+    captured_at_ms: int | float | None = None,
+    jpeg_quality: int = 95,
+) -> None:
+    """
+    Save a BGR image as JPEG with GPS and optional capture time in EXIF.
+
+    :param bgr: Image in OpenCV BGR layout.
+    :param path: Output ``.jpg`` path.
+    :param lat: Latitude in WGS84 (degrees).
+    :param lon: Longitude in WGS84 (degrees).
+    :param captured_at_ms: Unix time in milliseconds (e.g. Mapillary ``captured_at``), or None.
+    :param jpeg_quality: JPEG quality 1-100.
+
+    Example::
+        In: save_jpeg_with_exif(img, "out.jpg", lat=50.06, lon=19.94, captured_at_ms=1710000000000)
+        Out: "out.jpg" saved with GPS EXIF and capture timestamp metadata
+    """
+    rgb = cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB)
+    pil_image = Image.fromarray(rgb)
+
+    # piexif expects these IFD buckets even when mostly empty
+    exif_dict: dict = {"0th": {}, "Exif": {}, "GPS": {}, "1st": {}, "thumbnail": None}
+
+    if captured_at_ms is not None:
+        try:
+            ts = float(captured_at_ms) / 1000.0
+            dt = datetime.fromtimestamp(ts, tz=UTC)
+            dt_str = dt.strftime("%Y:%m:%d %H:%M:%S")
+        except (OSError, OverflowError, TypeError, ValueError):
+            dt_str = None
+        if dt_str:
+            exif_dict["0th"][piexif.ImageIFD.DateTime] = dt_str
+            exif_dict["Exif"][piexif.ExifIFD.DateTimeOriginal] = dt_str
+            exif_dict["Exif"][piexif.ExifIFD.DateTimeDigitized] = dt_str
+
+    # GPS refs encode hemisphere; rationals use absolute values
+    lat_ref = b"N" if lat >= 0 else b"S"
+    lon_ref = b"E" if lon >= 0 else b"W"
+    exif_dict["GPS"][piexif.GPSIFD.GPSVersionID] = (2, 0, 0, 0)
+    exif_dict["GPS"][piexif.GPSIFD.GPSLatitudeRef] = lat_ref
+    exif_dict["GPS"][piexif.GPSIFD.GPSLatitude] = _decimal_deg_to_exif_rationals(lat)
+    exif_dict["GPS"][piexif.GPSIFD.GPSLongitudeRef] = lon_ref
+    exif_dict["GPS"][piexif.GPSIFD.GPSLongitude] = _decimal_deg_to_exif_rationals(lon)
+
+    exif_bytes = piexif.dump(exif_dict)
+    pil_image.save(path, format="JPEG", quality=jpeg_quality, exif=exif_bytes)
+
+
+def download_image(url: str, timeout: float) -> np.ndarray | None:
+    """
+    Download an image URL and decode it to a BGR ``ndarray``.
+
+    :param url: Image URL.
+    :param timeout: HTTP timeout in seconds.
+    :return: BGR image, or None on network/decode failure.
+
+    Example::
+        In: download_image("https://example.com/photo.jpg", timeout=10.0)
+        Out: decoded BGR image array (H, W, 3) or None if download/decode fails
+    """
+    try:
+        if log.isEnabledFor(logging.DEBUG):
+            log.debug("Downloading image from: %s", url)
+
+        response = requests.get(url, stream=True, timeout=timeout)
+        response.raise_for_status()
+
+        # OpenCV expects a 1-D uint8 buffer for imdecode
+        image_data = np.asarray(bytearray(response.content), dtype=np.uint8)
+        image = cv2.imdecode(image_data, cv2.IMREAD_COLOR)
+
+        if image is None:
+            log.warning("OpenCV failed to decode image from: %s", url)
+            return None
+
+        return image
+
+    except (requests.RequestException, ValueError) as download_error:
+        log.warning("Download/decode error for %s: %s", url, download_error)
+        return None
+
+
+def process_panorama(img: np.ndarray, fov_deg: float, out_hw: tuple[int, int]) -> np.ndarray:
+    """
+    Convert a 360° equirectangular image to a perspective crop.
+
+    Scalar ``fov_deg`` is expanded to ``(h_fov, v_fov)`` so py360convert uses a stable code path.
+
+    :param img: Equirectangular panorama (BGR).
+    :param fov_deg: Field of view in degrees, or ``(h, v)`` if a pair is needed.
+    :param out_hw: Output ``(height, width)``.
+    :return: Perspective image as BGR ``ndarray``.
+
+    Example::
+        In: process_panorama(pano_bgr, fov_deg=90, out_hw=(512, 512))
+        Out: perspective BGR image array with shape (512, 512, 3)
+    """
+    if log.isEnabledFor(logging.DEBUG):
+        log.debug(
+            "Converting panorama (Input shape: %s, FOV: %s)",
+            img.shape,
+            fov_deg,
+        )
+
+    # Tuple FOV avoids a buggy scalar branch in some py360convert versions
+    fov_hv = (
+        (float(fov_deg[0]), float(fov_deg[1]))
+        if isinstance(fov_deg, tuple | list) and len(fov_deg) >= 2
+        else (float(fov_deg), float(fov_deg))
+    )
+
+    return py360convert.e2p(
+        img,
+        fov_hv,
+        0,
+        0,
+        out_hw,
+    )
diff --git a/src/uq_desktop_processor/street_view_analysis/road_graph_prepare/__init__.py b/src/uq_desktop_processor/street_view_analysis/road_graph_prepare/__init__.py
new file mode 100644
index 0000000..645a73e
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/road_graph_prepare/__init__.py
@@ -0,0 +1,11 @@
+"""
+OSMnx road graph loading with highway filtering and metric edge extraction.
+"""
+
+from .prepare_graph import (
+    EXCLUDED_HIGHWAY_TYPES,
+    load_route_aligned_graph_wgs84,
+    route_aligned_edges_web_mercator,
+)
+
+__all__ = ["EXCLUDED_HIGHWAY_TYPES", "load_route_aligned_graph_wgs84", "route_aligned_edges_web_mercator"]
diff --git a/src/uq_desktop_processor/street_view_analysis/road_graph_prepare/prepare_graph.py b/src/uq_desktop_processor/street_view_analysis/road_graph_prepare/prepare_graph.py
new file mode 100644
index 0000000..1958bd2
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/road_graph_prepare/prepare_graph.py
@@ -0,0 +1,162 @@
+"""
+Load a drive network from OSM or files, filter highways, consolidate intersections, project to WGS84.
+"""
+
+import logging
+from pathlib import Path
+from typing import Any, cast
+
+import geopandas as gpd
+import networkx as nx
+import osmnx as ox
+
+log = logging.getLogger(__name__)
+
+EXCLUDED_HIGHWAY_TYPES = frozenset(
+    {
+        "motorway",
+        "motorway_link",
+        "trunk",
+        "trunk_link",
+    }
+)
+
+
+def _edge_has_excluded_highway(edge_data: dict[str, Any]) -> bool:
+    """
+    Return True if an edge's ``highway`` tag is in :data:`EXCLUDED_HIGHWAY_TYPES`.
+
+    :param edge_data: OSMnx edge attribute dict.
+    :return: Whether the edge should be dropped before routing.
+
+    Example::
+        In: _edge_has_excluded_highway({"highway": "motorway"})
+        Out: True
+    """
+    highway_value = edge_data.get("highway")
+    if highway_value is None:
+        return False
+    if isinstance(highway_value, str):
+        return highway_value in EXCLUDED_HIGHWAY_TYPES
+    if isinstance(highway_value, list | tuple):
+        return any(
+            isinstance(highway_entry, str) and highway_entry in EXCLUDED_HIGHWAY_TYPES
+            for highway_entry in highway_value
+        )
+    return False
+
+
+def load_route_aligned_graph_wgs84(
+    *,
+    city_name: str | None = None,
+    region_geojson_path: str | Path | None = None,
+    road_geojson_path: str | Path | None = None,
+    consolidate_tolerance_m: float = 15.0,
+    use_cache: bool = True,
+) -> tuple[nx.MultiGraph, gpd.GeoDataFrame]:
+    """
+    Build an undirected multigraph in EPSG:4326 for routing and point sampling.
+
+    Exactly one of ``city_name``, ``region_geojson_path``, or ``road_geojson_path`` must be set.
+    Freeway/trunk edges are removed, intersections are merged, then the graph is reprojected to WGS84.
+
+    :param city_name: OSM place query.
+    :param region_geojson_path: Polygon file to download a network inside.
+    :param road_geojson_path: Existing road lines to turn into a graph.
+    :param consolidate_tolerance_m: Meters for ``ox.consolidate_intersections``.
+    :param use_cache: OSMnx HTTP cache toggle.
+    :return: ``(graph_wgs84, area_or_edges_gdf)`` for bounds or bookkeeping.
+    :raises ValueError: If not exactly one source is provided.
+
+    Example::
+        In: load_route_aligned_graph_wgs84(city_name="Katowice, Poland")
+        Out: (nx.MultiGraph with WGS84 node coords, GeoDataFrame describing area/edges bounds)
+    """
+    ox.settings.use_cache = use_cache  # type: ignore
+
+    sources = [
+        city_name is not None,
+        region_geojson_path is not None,
+        road_geojson_path is not None,
+    ]
+    if sum(sources) != 1:
+        msg = "Provide exactly one of: city_name, region_geojson_path, road_geojson_path."
+        raise ValueError(msg)
+
+    # Branch 1: user-supplied line geometries -> graph
+    if road_geojson_path is not None:
+        road_file_path = Path(road_geojson_path)
+        log.info("Loading road network from file: %s", road_file_path)
+        road_edges_gdf = gpd.read_file(road_file_path)
+        if road_edges_gdf.crs is None:
+            road_edges_gdf = road_edges_gdf.set_crs("EPSG:4326")
+
+        raw_graph = ox.graph_from_gdfs(gdf_nodes=cast(Any, None), gdf_edges=road_edges_gdf)
+        city_gdf = road_edges_gdf.to_crs("EPSG:4326")
+    # Branch 2: polygon AOI -> download inside
+    elif region_geojson_path is not None:
+        region_file_path = Path(region_geojson_path)
+        log.info("Loading region polygon from file: %s", region_file_path)
+        region_gdf = gpd.read_file(region_file_path)
+        region_polygon_union = region_gdf.unary_union
+        raw_graph = ox.graph_from_polygon(region_polygon_union, network_type="drive", simplify=True)
+        city_gdf = region_gdf.to_crs("EPSG:4326")
+    # Branch 3: named place -> download
+    else:
+        assert city_name is not None
+        log.info("Downloading and building graph for %s", city_name)
+        raw_graph = ox.graph_from_place(city_name, network_type="drive", simplify=True)
+        city_gdf = ox.geocode_to_gdf(city_name)
+
+    # Drop motorways/trunk and any nodes left isolated
+    edges_to_remove = [
+        (start_node, end_node, edge_key)
+        for start_node, end_node, edge_key, edge_attributes in raw_graph.edges(data=True, keys=True)  # type: ignore
+        if _edge_has_excluded_highway(edge_attributes)
+    ]
+    raw_graph.remove_edges_from(edges_to_remove)
+    isolated_nodes = list(nx.isolates(raw_graph))
+    raw_graph.remove_nodes_from(isolated_nodes)
+    log.info("Removed %s edges and %s isolated nodes.", len(edges_to_remove), len(isolated_nodes))
+
+    # Consolidation runs in projected (metric) CRS
+    projected_graph = ox.project_graph(raw_graph)
+    log.info("Consolidating intersections (tolerance=%s m)", consolidate_tolerance_m)
+    consolidated_graph = ox.consolidate_intersections(
+        projected_graph,
+        rebuild_graph=True,
+        tolerance=consolidate_tolerance_m,
+        dead_ends=False,
+    )
+
+    geographic_directed_graph = ox.project_graph(consolidated_graph, to_crs="EPSG:4326")
+
+    # Undirected multigraph for downstream algorithms
+    geographic_undirected_graph = nx.MultiGraph(geographic_directed_graph)
+    geographic_undirected_graph.graph.update(geographic_directed_graph.graph)  # type: ignore
+
+    return geographic_undirected_graph, city_gdf
+
+
+def route_aligned_edges_web_mercator(geographic_graph: nx.MultiGraph) -> gpd.GeoDataFrame:
+    """
+    Export non-duplicate road edges as a Web Mercator GeoDataFrame for metric sampling.
+
+    :param geographic_graph: Output of :func:`load_route_aligned_graph_wgs84`.
+    :return: Edge table with unique geometries in EPSG:3857.
+
+    Example::
+        In: route_aligned_edges_web_mercator(geographic_graph).crs.to_string()
+        Out: "EPSG:3857"
+    """
+    edges = ox.graph_to_gdfs(cast(nx.MultiDiGraph, geographic_graph), nodes=False, edges=True)
+    edges = edges.to_crs(epsg=3857)
+    # Same physical street can appear as two directed rows
+    return edges.drop_duplicates(subset="geometry")
+
+
+__all__ = [
+    "EXCLUDED_HIGHWAY_TYPES",
+    "load_route_aligned_graph_wgs84",
+    "route_aligned_edges_web_mercator",
+]
diff --git a/src/uq_desktop_processor/street_view_analysis/road_points_generator/__init__.py b/src/uq_desktop_processor/street_view_analysis/road_points_generator/__init__.py
new file mode 100644
index 0000000..244ad8b
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/road_points_generator/__init__.py
@@ -0,0 +1,16 @@
+"""
+Road-network sampling points: load graph, generate points, optional filtering.
+"""
+
+from .filtering import filter_close_points
+from .generator import generate_points_along_roads
+from .io import download_road_network, read_road_geojson
+from .run import build_points_pipeline
+
+__all__ = [
+    "build_points_pipeline",
+    "download_road_network",
+    "filter_close_points",
+    "generate_points_along_roads",
+    "read_road_geojson",
+]
diff --git a/src/uq_desktop_processor/street_view_analysis/road_points_generator/filtering.py b/src/uq_desktop_processor/street_view_analysis/road_points_generator/filtering.py
new file mode 100644
index 0000000..6d729f6
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/road_points_generator/filtering.py
@@ -0,0 +1,133 @@
+"""
+Filters and deduplicates candidate road sampling coordinates.
+"""
+
+import logging
+
+import geopandas as gpd
+import numpy as np
+import numpy.typing as npt
+
+log = logging.getLogger(__name__)
+
+
+def _compute_projected_coords(
+    points: list[tuple[float, float]], crs_from: str = "EPSG:4326", crs_to: str = "EPSG:3857"
+) -> npt.NDArray[np.float64]:
+    """
+    Project geographic ``(lat, lon)`` points to metric coordinates for distance checks.
+
+    :param points: Non-empty list of ``(latitude, longitude)`` tuples.
+    :param crs_from: Source CRS (default WGS84).
+    :param crs_to: Target CRS in meters (default Web Mercator).
+    :return: Array of shape ``(n, 2)`` with ``(x, y)`` in meters.
+    :raises ValueError: If ``points`` is empty or invalid.
+    :raises RuntimeError: If GeoPandas projection fails.
+
+    Example::
+        In: _compute_projected_coords([(50.06, 19.94)]).shape
+        Out: (1, 2)
+    """
+    if log.isEnabledFor(logging.DEBUG):
+        log.debug(
+            "Projecting %s points from %s to %s.",
+            len(points),
+            crs_from,
+            crs_to,
+        )
+
+    try:
+        latitudes, longitudes = zip(*points, strict=False)
+    except ValueError as error:
+        log.error("Input `points` list is invalid or empty.")
+        raise ValueError("Expected `points` to be a non-empty list of (lat, lon) tuples.") from error
+
+    try:
+        # points_from_xy expects (x=lon, y=lat) in geographic CRS
+        projected_gdf = gpd.GeoDataFrame(geometry=gpd.points_from_xy(longitudes, latitudes), crs=crs_from).to_crs(
+            crs_to
+        )
+    except Exception as projection_error:
+        log.error("Coordinate projection failed: %s", projection_error)
+        raise RuntimeError("Coordinate projection failed.") from projection_error
+
+    x_coords = projected_gdf.geometry.x
+    y_coords = projected_gdf.geometry.y
+    return np.column_stack((x_coords, y_coords))
+
+
+def _find_sparse_indices(points: npt.NDArray[np.float64], min_distance_m: float) -> list[int]:
+    """
+    Greedy index selection so kept points are at least ``min_distance_m`` apart (planar).
+
+    Uses a grid hash to limit neighbor checks.
+
+    :param points: Projected ``(x, y)`` coordinates in meters.
+    :param min_distance_m: Minimum separation between any two kept points.
+    :return: Indices into ``points`` of the kept samples (in traversal order).
+
+    Example::
+        In: _find_sparse_indices(np.array([[0.0, 0.0], [1.0, 1.0], [50.0, 50.0]]), 20)
+        Out: [0, 2]
+    """
+    # Cell side ~ min_distance_m -> only compare within a 3x3 neighborhood
+    grid_coords = np.floor(points / min_distance_m).astype(int)
+
+    occupied_cells: dict[tuple[int, int], int] = {}
+    kept_indices: list[int] = []
+
+    # Self + 8 neighbors in grid space
+    neighbor_offsets = [(-1, -1), (-1, 0), (-1, 1), (0, -1), (0, 0), (0, 1), (1, -1), (1, 0), (1, 1)]
+
+    for point_index, (grid_x, grid_y) in enumerate(grid_coords):
+        too_close = False
+        for delta_x, delta_y in neighbor_offsets:
+            neighbor_cell = (grid_x + delta_x, grid_y + delta_y)
+            if neighbor_cell in occupied_cells:
+                neighbor_idx = occupied_cells[neighbor_cell]
+                distance = np.linalg.norm(points[point_index] - points[neighbor_idx])
+                if distance < min_distance_m:
+                    too_close = True
+                    break
+
+        if not too_close:
+            kept_indices.append(point_index)
+            occupied_cells[(grid_x, grid_y)] = point_index
+
+    return kept_indices
+
+
+def filter_close_points(points: list[tuple[float, float]], min_distance_m: float = 20) -> list[tuple[float, float]]:
+    """
+    Drop points that lie closer than ``min_distance_m`` to an already kept point.
+
+    :param points: ``(latitude, longitude)`` candidates.
+    :param min_distance_m: Minimum spacing in meters (Web Mercator plane).
+    :return: Subset of ``points`` in original order, thinned by the rule above.
+
+    Example::
+        In: filter_close_points([(50.06, 19.94), (50.06001, 19.94001)], min_distance_m=20)
+        Out: [(50.06, 19.94)]
+    """
+    if not points:
+        log.debug("No points provided for filtering.")
+        return []
+
+    if min_distance_m <= 0:
+        msg = "`min_distance_m` must be a positive number."
+        log.error(msg)
+        raise ValueError(msg)
+
+    # Planar distances in meters (Web Mercator)
+    coords = _compute_projected_coords(points)
+    kept_indices = _find_sparse_indices(coords, min_distance_m)
+    filtered_points = [points[kept_point_index] for kept_point_index in kept_indices]
+
+    log.info(
+        "Point filtering complete: %s -> %s points kept (min_dist=%sm).",
+        len(points),
+        len(filtered_points),
+        min_distance_m,
+    )
+
+    return filtered_points
diff --git a/src/uq_desktop_processor/street_view_analysis/road_points_generator/generator.py b/src/uq_desktop_processor/street_view_analysis/road_points_generator/generator.py
new file mode 100644
index 0000000..ba603a8
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/road_points_generator/generator.py
@@ -0,0 +1,102 @@
+"""
+Generates evenly spaced sampling points along road network edges.
+"""
+
+import logging
+
+import geopandas as gpd
+from shapely.geometry import LineString, MultiLineString, Point
+from shapely.geometry.base import BaseGeometry
+from tqdm import tqdm
+
+from .filtering import filter_close_points
+
+log = logging.getLogger(__name__)
+
+
+def _get_lines_from_geometry(geometry: BaseGeometry) -> list[LineString]:
+    """
+    Normalize geometry to a list of ``LineString`` parts.
+
+    :param geometry: ``LineString`` or ``MultiLineString``.
+    :return: Non-empty list of lines, or empty if the type is unsupported.
+
+    Example::
+        In: _get_lines_from_geometry(LineString([(0, 0), (1, 1)]))
+        Out: [LineString(...)]
+    """
+    if isinstance(geometry, LineString):
+        return [geometry]
+    elif isinstance(geometry, MultiLineString):
+        return list(geometry.geoms)
+    return []
+
+
+def _generate_points_from_lines(lines: list[LineString], spacing: float) -> list[Point]:
+    """
+    Place points every ``spacing`` meters along each line (including endpoints where applicable).
+
+    :param lines: Road segments in a metric CRS.
+    :param spacing: Step length in meters.
+    :return: Shapely ``Point`` geometries along the lines.
+
+    Example::
+        In: _generate_points_from_lines([LineString([(0, 0), (100, 0)])], spacing=50)
+        Out: [Point(...), Point(...), Point(...)]
+    """
+    if spacing <= 0:
+        msg = "Spacing must be a positive number greater than zero."
+        log.error(msg)
+        raise ValueError(msg)
+
+    points = []
+    for line in lines:
+        length = line.length
+        num_points = int(length // spacing)
+        # Include start and regular steps along the segment (metric CRS)
+        points.extend([line.interpolate(step_index * spacing) for step_index in range(num_points + 1)])
+    return points
+
+
+def generate_points_along_roads(
+    roads_gdf: gpd.GeoDataFrame, spacing: float = 100, min_distance_m: float = 20
+) -> list[tuple[float, float]]:
+    """
+    Sample ``(latitude, longitude)`` along road line geometries, then thin by minimum distance.
+
+    :param roads_gdf: Roads as ``LineString`` / ``MultiLineString``; reprojected to metric CRS if geographic.
+    :param spacing: Along-line spacing in meters.
+    :param min_distance_m: Post-process minimum separation between returned points.
+    :return: List of ``(lat, lon)`` in WGS84 after :func:`filter_close_points`.
+
+    Example::
+        In: generate_points_along_roads(roads_gdf, spacing=100, min_distance_m=20)
+        Out: [(50.06, 19.94), ...]
+    """
+    log.info(
+        "Generating road points for %s geometry objects (spacing=%sm).",
+        len(roads_gdf),
+        spacing,
+    )
+
+    if roads_gdf.crs is None or roads_gdf.crs.is_geographic:
+        log.debug("Reprojecting input GeoDataFrame to EPSG:3857.")
+        roads_gdf = roads_gdf.to_crs(epsg=3857)
+
+    generated_points = []  # Shapely Points in roads_gdf.crs (meters)
+
+    for _, row in tqdm(roads_gdf.iterrows(), total=len(roads_gdf), desc="Generating points"):
+        lines = _get_lines_from_geometry(row.geometry)
+        points = _generate_points_from_lines(lines, spacing)
+        generated_points.extend(points)
+
+    log.debug(
+        "Generated %s raw points. Converting to WGS84...",
+        len(generated_points),
+    )
+
+    geo_series = gpd.GeoSeries(generated_points, crs=roads_gdf.crs).to_crs(epsg=4326)
+    # Pipeline convention: (lat, lon)
+    latlon_points = [(point.y, point.x) for point in geo_series]
+
+    return filter_close_points(latlon_points, min_distance_m)
diff --git a/src/uq_desktop_processor/street_view_analysis/road_points_generator/io.py b/src/uq_desktop_processor/street_view_analysis/road_points_generator/io.py
new file mode 100644
index 0000000..8fb5fa5
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/road_points_generator/io.py
@@ -0,0 +1,192 @@
+"""
+Reads/writes sampling-point layers and loads route-aligned road networks.
+"""
+
+import logging
+
+import geopandas as gpd
+import requests
+from fiona.errors import DriverError, FionaValueError
+from pyogrio.errors import DataSourceError
+from yaspin import yaspin
+
+from uq_desktop_processor.street_view_analysis.road_graph_prepare import (
+    load_route_aligned_graph_wgs84,
+    route_aligned_edges_web_mercator,
+)
+
+log = logging.getLogger(__name__)
+
+
+def load_roads_route_aligned(
+    *,
+    place_name: str | None = None,
+    region_geojson_path: str | None = None,
+    road_geojson_path: str | None = None,
+    consolidate_tolerance_m: float = 15.0,
+    use_cache: bool = True,
+) -> gpd.GeoDataFrame:
+    """
+    Road edges in EPSG:3857 from the same graph pipeline as Euler routes (drive, no trunk/motorway).
+
+    :param place_name: OSM place query, if used alone.
+    :param region_geojson_path: Region polygon file, if used alone.
+    :param road_geojson_path: Local road lines file, if used alone.
+    :param consolidate_tolerance_m: ``ox.consolidate_intersections`` tolerance in meters.
+    :param use_cache: Whether OSMnx may use its HTTP cache.
+    :return: Edge GeoDataFrame in Web Mercator.
+
+    Example::
+        In: load_roads_route_aligned(place_name="Katowice, Poland").crs.to_string()
+        Out: "EPSG:3857"
+    """
+    # Shared graph build with Euler / sampling; then edge geometries only
+    geographic_graph, _ = load_route_aligned_graph_wgs84(
+        city_name=place_name,
+        region_geojson_path=region_geojson_path,
+        road_geojson_path=road_geojson_path,
+        consolidate_tolerance_m=consolidate_tolerance_m,
+        use_cache=use_cache,
+    )
+    return route_aligned_edges_web_mercator(geographic_graph)
+
+
+def download_road_network(
+    place_name: str,
+    *,
+    consolidate_tolerance_m: float = 15.0,
+    use_cache: bool = True,
+) -> gpd.GeoDataFrame:
+    """
+    Load route-aligned roads for a named place (same settings as GPX route generation).
+
+    :param place_name: OSM geocodable place string.
+    :param consolidate_tolerance_m: Intersection merge tolerance in meters.
+    :param use_cache: OSMnx cache flag.
+    :return: Metric road edges.
+    :raises ValueError: If no roads are found for the place.
+    :raises ConnectionError: On Overpass/network failure.
+    :raises RuntimeError: On other load failures.
+
+    Example::
+        In: download_road_network("Katowice, Poland")
+        Out: GeoDataFrame with LineString/MultiLineString road edges in EPSG:3857
+    """
+    log.info("Initiating route-aligned road network download for: '%s'", place_name)
+
+    with yaspin(text=f"Downloading road network for: {place_name}..."):
+        try:
+            edges = load_roads_route_aligned(
+                place_name=place_name,
+                consolidate_tolerance_m=consolidate_tolerance_m,
+                use_cache=use_cache,
+            )
+            log.info(
+                "Successfully loaded %s road segments for '%s' (route-aligned).",
+                len(edges),
+                place_name,
+            )
+            return edges
+
+        except ValueError as error:
+            log.error("No road data or invalid location: %s: %s", place_name, error)
+            raise ValueError(f"No roads found for: {place_name}") from error
+
+        except requests.exceptions.RequestException as error:
+            log.error("Network error when downloading data for '%s': %s", place_name, error)
+            raise ConnectionError("Connection problem with Overpass API") from error
+
+        except Exception as error:
+            log.error("Unexpected error when downloading road network for '%s': %s", place_name, error)
+            raise RuntimeError(f"Error while downloading road network for: {place_name}") from error
+
+
+def read_road_geojson(input_path: str) -> gpd.GeoDataFrame:
+    """
+    Load line geometries from a local GeoJSON (no route-aligned graph build).
+
+    For Euler-aligned sampling, prefer :func:`load_roads_route_aligned` with ``road_geojson_path``.
+
+    :param input_path: Path to a vector file readable by GeoPandas.
+    :return: Subset of features that are ``LineString`` or ``MultiLineString``.
+    :raises ValueError: If the file is invalid.
+    :raises FileNotFoundError: If the path does not exist.
+    :raises RuntimeError: On unexpected read errors.
+
+    Example::
+        In: read_road_geojson("roads.geojson").geometry.type.isin(["LineString", "MultiLineString"]).all()
+        Out: True
+    """
+    log.info("Reading local road network from: %s", input_path)
+
+    try:
+        roads_geodataframe = gpd.read_file(input_path)
+        # Ignore points/polygons if the file is mixed
+        line_geometries = roads_geodataframe[roads_geodataframe.geometry.type.isin(["LineString", "MultiLineString"])]
+
+        log.debug("Loaded %s valid road geometries from file.", len(line_geometries))
+        return line_geometries
+
+    except (FionaValueError, DriverError, OSError) as error:
+        log.error("Error reading GeoJSON: %s", error)
+        raise ValueError(f"Invalid GeoJSON file: {input_path}") from error
+
+    except DataSourceError as error:
+        if "No such file or directory" in str(error):
+            log.error("File does not exist: %s", input_path)
+            raise FileNotFoundError(f"File not found: {input_path}") from error
+        log.error("Error reading GeoJSON: %s", error)
+        raise ValueError(f"Invalid GeoJSON file: {input_path}") from error
+
+    except Exception as error:
+        log.error("Unexpected error while loading file: %s", error)
+        raise RuntimeError(f"Error while loading GeoJSON file: {input_path}") from error
+
+
+def download_roads_from_region(
+    region_path: str,
+    *,
+    consolidate_tolerance_m: float = 15.0,
+    use_cache: bool = True,
+) -> gpd.GeoDataFrame:
+    """
+    Load route-aligned roads clipped to the first polygon in a region file.
+
+    :param region_path: GeoJSON (or similar) with a polygon geometry.
+    :param consolidate_tolerance_m: Intersection merge tolerance in meters.
+    :param use_cache: OSMnx cache flag.
+    :return: Metric road edges for the region.
+    :raises RuntimeError: If the region file cannot be processed.
+
+    Example::
+        In: download_roads_from_region("region.geojson")
+        Out: GeoDataFrame with route-aligned road edges for the region (EPSG:3857)
+    """
+    log.info("Downloading route-aligned road network for region: %s", region_path)
+
+    try:
+        region_geodataframe = gpd.read_file(region_path)
+
+        if region_geodataframe.empty or region_geodataframe.geometry.iloc[0] is None:
+            raise ValueError(f"The provided region file is empty or invalid: {region_path}")
+
+        # First feature defines the AOI (WGS84 for OSMnx)
+        polygon = region_geodataframe.to_crs(epsg=4326).geometry.iloc[0]
+
+        if polygon.geom_type not in ("Polygon", "MultiPolygon"):
+            raise ValueError(f"Expected a Polygon geometry in {region_path}, but found {polygon.geom_type}.")
+
+        with yaspin(text=f"Downloading road network for region: {region_path}..."):
+            road_edges = load_roads_route_aligned(
+                region_geojson_path=region_path,
+                consolidate_tolerance_m=consolidate_tolerance_m,
+                use_cache=use_cache,
+            )
+            log.info("Successfully loaded %s road segments for custom region.", len(road_edges))
+            return road_edges
+
+    except ValueError:
+        raise
+    except Exception as error:
+        log.error("Error processing region file '%s': %s", region_path, error)
+        raise RuntimeError(f"Failed to download roads for region: {region_path}") from error
diff --git a/src/uq_desktop_processor/street_view_analysis/road_points_generator/run.py b/src/uq_desktop_processor/street_view_analysis/road_points_generator/run.py
new file mode 100644
index 0000000..7c69e4d
--- /dev/null
+++ b/src/uq_desktop_processor/street_view_analysis/road_points_generator/run.py
@@ -0,0 +1,121 @@
+"""
+CLI-oriented pipeline: load route-aligned roads, sample points, write a layer file.
+"""
+
+import logging
+from pathlib import Path
+
+import geopandas as gpd
+
+from .generator import generate_points_along_roads
+from .io import load_roads_route_aligned
+
+log = logging.getLogger(__name__)
+
+
+def _save_sampling_points_layer(
+    points: list[tuple[float, float]],
+    output_path: str | Path,
+) -> Path:
+    """
+    Write sampling points to a vector file in EPSG:4326.
+
+    Coordinates follow :func:`generate_points_along_roads`: each tuple is ``(latitude, longitude)``.
+
+    :param points: Sample locations.
+    :param output_path: GeoPackage, GeoJSON, or other OGR path.
+    :return: Resolved path that was written.
+
+    Example::
+        In: _save_sampling_points_layer([(50.06, 19.94)], "data/results/points.geojson")
+        Out: Path(".../points.geojson")
+    """
+    output_path_obj = Path(output_path)
+    output_path_obj.parent.mkdir(parents=True, exist_ok=True)
+    if not points:
+        points_gdf = gpd.GeoDataFrame({"id": []}, geometry=gpd.GeoSeries([], crs="EPSG:4326"))
+    else:
+        latitudes, longitudes = zip(*points, strict=False)
+        # points_from_xy: x=lon, y=lat (EPSG:4326)
+        points_gdf = gpd.GeoDataFrame(
+            {"id": range(len(points))},
+            geometry=gpd.points_from_xy(longitudes, latitudes),
+            crs="EPSG:4326",
+        )
+    points_gdf.to_file(output_path_obj)
+    return output_path_obj.resolve()
+
+
+def build_points_pipeline(
+    *,
+    output_points_path: str | Path,
+    place_name: str | None = None,
+    region_geojson_path: str | None = None,
+    road_geojson_path: str | None = None,
+    spacing: float = 100,
+    min_distance_m: float = 20,
+    consolidate_tolerance_m: float = 15.0,
+    use_cache: bool = True,
+) -> tuple[gpd.GeoDataFrame, list[tuple[float, float]]]:
+    """
+    End-to-end sampling: exactly one of place, region file, or road file; then generate and save points.
+
+    :param output_points_path: Output vector path for point features.
+    :param place_name: OSM place name (mutually exclusive with region/road paths).
+    :param region_geojson_path: Polygon file for a custom AOI.
+    :param road_geojson_path: Predefined road lines file.
+    :param spacing: Along-road spacing in meters.
+    :param min_distance_m: Minimum spacing after global thinning.
+    :param consolidate_tolerance_m: Same as Euler route graph preparation.
+    :param use_cache: OSMnx HTTP cache.
+    :return: ``(roads_gdf, list of (lat, lon))``.
+    :raises ValueError: If zero or more than one source argument is given.
+
+    Example::
+        In: build_points_pipeline(place_name="Katowice, Poland", output_points_path="out/points.geojson")
+        Out: (road_edges_gdf, [(50.06, 19.94), (50.0612, 19.9415), ...])
+    """
+    log.info(
+        "Starting points generation pipeline (spacing=%sm, min_dist=%sm, consolidate=%sm).",
+        spacing,
+        min_distance_m,
+        consolidate_tolerance_m,
+    )
+
+    # Exactly one OSM / file source for load_route_aligned_graph_wgs84
+    sources_provided = sum(
+        source_value is not None for source_value in [place_name, region_geojson_path, road_geojson_path]
+    )
+
+    if sources_provided != 1:
+        msg = (
+            "You must provide exactly one data source: " "`place_name`, `region_geojson_path`, OR `road_geojson_path`."
+        )
+        log.error(msg)
+        raise ValueError(msg)
+
+    if place_name is not None:
+        log.info("Source selected: place name '%s'", place_name)
+    elif region_geojson_path is not None:
+        log.info("Source selected: region polygon '%s'", region_geojson_path)
+    else:
+        log.info("Source selected: road GeoJSON '%s'", road_geojson_path)
+
+    roads = load_roads_route_aligned(
+        place_name=place_name,
+        region_geojson_path=region_geojson_path,
+        road_geojson_path=road_geojson_path,
+        consolidate_tolerance_m=consolidate_tolerance_m,
+        use_cache=use_cache,
+    )
+
+    points = generate_points_along_roads(
+        roads,
+        spacing=spacing,
+        min_distance_m=min_distance_m,
+    )
+
+    saved_output_path = _save_sampling_points_layer(points, output_points_path)
+    log.info("Pipeline finished. Total points generated: %s. Saved to %s", len(points), saved_output_path)
+
+    return roads, points