CPU-only and Colab-ready tests

.vscode/c_cpp_properties.json

@@ -0,0 +1,21 @@
+{
+    "configurations": [
+        {
+            "name": "Win32",
+            "includePath": [
+                "${workspaceFolder}/**"
+            ],
+            "defines": [
+                "_DEBUG",
+                "UNICODE",
+                "_UNICODE"
+            ],
+            "windowsSdkVersion": "10.0.26100.0",
+            "compilerPath": "cl.exe",
+            "cStandard": "c17",
+            "cppStandard": "c++17",
+            "intelliSenseMode": "windows-msvc-x64"
+        }
+    ],
+    "version": 4
+}

.vscode/settings.json

@@ -0,0 +1,9 @@
+{
+    "python-envs.pythonProjects": [
+        {
+            "path": "",
+            "envManager": "ms-python.python:conda",
+            "packageManager": "ms-python.python:conda"
+        }
+    ]
+}

LQVG_test.ipynb

@@ -0,0 +1,300 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "gpuType": "T4"
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "accelerator": "GPU"
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## **The modified source code compatible with colab (gdown does not work for downloading):**"
+      ],
+      "metadata": {
+        "id": "kTnynktRAMnJ"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from google.colab import drive\n",
+        "drive.mount('/content/drive')"
+      ],
+      "metadata": {
+        "id": "WixriWROqUUx"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## **LQVG weights trained on DIOR-RSVG and RSVG-HR**"
+      ],
+      "metadata": {
+        "id": "JVkx_5-QFK4o"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!gdown --folder https://drive.google.com/drive/folders/1uC9TAPOwiIbHcee6hSO_3b2Mwr-zDGtg?usp=drive_link -O drive/MyDrive/weights"
+      ],
+      "metadata": {
+        "id": "dlUmSOwieC9o"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cd /content/drive/.shortcut-targets-by-id/18OjYDfO70rO2e-oLMPmNbu2Z1WH7nppd/LQVG\n"
+      ],
+      "metadata": {
+        "id": "KddNyUyDwvP6"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install torch torchvision torchaudio\n"
+      ],
+      "metadata": {
+        "id": "gmmmP7yqvVf7"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install -r requirements.txt\n"
+      ],
+      "metadata": {
+        "id": "NVWRfbjfwUYx"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install 'git+https://github.com/facebookresearch/fvcore'\n"
+      ],
+      "metadata": {
+        "id": "3MbdnvA9sKI_"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install -U 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'\n"
+      ],
+      "metadata": {
+        "id": "nvEpgsttsY3L"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cd /content/drive/.shortcut-targets-by-id/18OjYDfO70rO2e-oLMPmNbu2Z1WH7nppd/LQVG/models/ops"
+      ],
+      "metadata": {
+        "id": "tUCBNrYGshhy"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!python setup.py build install"
+      ],
+      "metadata": {
+        "id": "ENyTettCskxg"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cd ../.."
+      ],
+      "metadata": {
+        "id": "bU-A2IBKsmo5"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Inference:"
+      ],
+      "metadata": {
+        "id": "7g2sVjoVFQiJ"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!python3 inference_rsvg.py --dataset_file rsvg_mm --num_queries 10 --with_box_refine --binary --freeze_text_encoder \\\n",
+        "--resume /content/drive/MyDrive/weights/RSVG-HR/checkpoint.pth --backbone resnet50"
+      ],
+      "metadata": {
+        "id": "x3dfhLHB9nET"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## **Visualize some results:**"
+      ],
+      "metadata": {
+        "id": "TQpWSEAMIQwF"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import os\n",
+        "from pathlib import Path\n",
+        "import math\n",
+        "from PIL import Image\n",
+        "import matplotlib.pyplot as plt\n",
+        "\n",
+        "# --- Config ---\n",
+        "IDS = [120, 159, 316, 328, 377, 502, 507, 510]\n",
+        "folder = \"/content/drive/MyDrive/LQVG/test_output/test\"  # Input folder\n",
+        "save_path = \"/content/drive/MyDrive/grid/grid.png\"       # Output file\n",
+        "cols = 4                                                 # Grid columns\n",
+        "\n",
+        "# --- Ensure save directory exists ---\n",
+        "os.makedirs(os.path.dirname(save_path), exist_ok=True)\n",
+        "\n",
+        "# --- Functions ---\n",
+        "def load_images(root, ids):\n",
+        "    \"\"\"Load images by IDs from a folder.\"\"\"\n",
+        "    imgs = []\n",
+        "    for i in ids:\n",
+        "        name = f\"UASs_{i}.jpg\"\n",
+        "        path = Path(root) / name\n",
+        "        if not path.is_file():\n",
+        "            print(f\"❌ Missing: {path}\")\n",
+        "            continue\n",
+        "        imgs.append(Image.open(path).convert(\"RGB\"))\n",
+        "        print(f\"✅ Loaded: {path}\")\n",
+        "    return imgs\n",
+        "\n",
+        "def show_grid(images, cols=4, save=None):\n",
+        "    \"\"\"Display images in a grid and optionally save.\"\"\"\n",
+        "    if not images:\n",
+        "        print(\"⚠ No images to display.\")\n",
+        "        return\n",
+        "\n",
+        "    rows = math.ceil(len(images) / cols)\n",
+        "\n",
+        "    # Scale figure size based on image dimensions\n",
+        "    img_width, img_height = images[0].size\n",
+        "    fig_width = cols * img_width / 100\n",
+        "    fig_height = rows * img_height / 100\n",
+        "\n",
+        "    plt.figure(figsize=(fig_width, fig_height))\n",
+        "    for idx, img in enumerate(images, 1):\n",
+        "        ax = plt.subplot(rows, cols, idx)\n",
+        "        ax.imshow(img)\n",
+        "        ax.axis(\"off\")\n",
+        "\n",
+        "    if save:\n",
+        "        plt.savefig(save, dpi=150, bbox_inches='tight', pad_inches=0)\n",
+        "        print(f\"💾 Saved grid to: {save}\")\n",
+        "\n",
+        "    plt.show()\n",
+        "\n",
+        "# --- Main ---\n",
+        "imgs = load_images(folder, IDS)\n",
+        "show_grid(imgs, cols=cols, save=save_path)\n"
+      ],
+      "metadata": {
+        "id": "jprFeczaICMm"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Training:"
+      ],
+      "metadata": {
+        "id": "bcyW0BLPFWCE"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!wget -O datasets/coco_eval.py https://raw.githubusercontent.com/facebookresearch/detr/main/datasets/coco_eval.py"
+      ],
+      "metadata": {
+        "id": "Ug4WCa_WW42F"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!python main.py \\\n",
+        "    --dataset_file rsvg_mm \\\n",
+        "    --rsvg_mm_path \"/content/drive/MyDrive/data\" \\\n",
+        "    --binary \\\n",
+        "    --with_box_refine \\\n",
+        "    --batch_size 1 \\\n",
+        "    --num_frames 1 \\\n",
+        "    --epochs 70 \\\n",
+        "    --lr_drop 40 \\\n",
+        "    --num_queries 10 \\\n",
+        "    --output_dir \"/content/drive/MyDrive/rsvg_dirs/r50_bidrection_fusion_10query_70epo_multiscale\" \\\n",
+        "    --backbone resnet50 \\\n",
+        "    --device cuda"
+      ],
+      "metadata": {
+        "id": "dcooaiTTVGF4"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "jupyter nbconvert --to pdf LQVG-test.ipynb\n"
+      ],
+      "metadata": {
+        "id": "XQfZsqqFWAVd"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}

RSVG-HR/Annotations/rsvg_hr_test_10.txt

@@ -0,0 +1,28 @@
+UASs_120.jpg,2671.0,1921.0,2814.0,2104.0,Compact square-like cluster with roughly symmetrical slightly irregular outline, weed: erigeron canadensis, middle-center of lentil crop field
+UASs_121.jpg,2195.0,2413.0,2568.0,2784.0,Moderately sized square-like cluster with irregular sprawling outline, weed: bassia scoparia, bottom-center of lentil crop field
+UASs_123.jpg,1656.0,683.0,2047.0,1052.0,Moderately sized square-like cluster with irregular sprawling outline, weed: bassia scoparia, top-left of lentil crop field
+UASs_124.jpg,2269.0,1248.0,2616.0,1695.0,Medium-sized square-like cluster with broadly irregular potentially sprawling outline, weed: ambrosia artemisiifolia, middle-center of lentil crop field
+UASs_137.jpg,663.0,3508.0,985.0,3643.0,Medium-sized square-like cluster with broadly irregular potentially sprawling outline, weed: ambrosia artemisiifolia, bottom-left of lentil crop field
+UASs_157.jpg,2665.0,13.0,2985.0,481.0,Medium-sized square-like cluster with broadly irregular potentially sprawling outline, weed: ambrosia artemisiifolia, top-center of lentil crop field
+UASs_159.jpg,2442.0,3.0,2545.0,132.0,Moderately sized square-like cluster with irregular sprawling outline, weed: bassia scoparia, top-center of lentil crop field
+UASs_180.jpg,498.0,3132.0,877.0,3366.0,Medium-sized square-like cluster with irregular somewhat elongated outline, weed: amaranthus tuberculatus, bottom-left of lentil crop field
+UASs_181.jpg,153.0,3197.0,413.0,3479.0,Moderately sized square-like cluster with irregular sprawling outline, weed: bassia scoparia, bottom-left of lentil crop field
+UASs_224.jpg,4683.0,528.0,4937.0,856.0,Medium-sized square-like cluster with broadly irregular potentially sprawling outline, weed: ambrosia artemisiifolia, top-right of lentil crop field
+UASs_236.jpg,1347.0,2371.0,1571.0,2615.0,Moderately sized square-like cluster with irregular sprawling outline, weed: bassia scoparia, bottom-left of lentil crop field
+UASs_237.jpg,396.0,2163.0,755.0,2512.0,Medium-sized square-like cluster with irregular somewhat elongated outline, weed: amaranthus tuberculatus, middle-left of lentil crop field
+UASs_288.jpg,576.0,2168.0,669.0,2284.0,Compact square-like cluster with roughly symmetrical slightly irregular outline, weed: erigeron canadensis, middle-left of lentil crop field
+UASs_316.jpg,539.0,3.0,740.0,279.0,Moderately sized square-like cluster with irregular sprawling outline, weed: bassia scoparia, top-left of lentil crop field
+UASs_328.jpg,1772.0,3136.0,2140.0,3537.0,Medium-sized square-like cluster with broadly irregular potentially sprawling outline, weed: ambrosia artemisiifolia, bottom-left of lentil crop field
+UASs_377.jpg,1438.0,1725.0,1641.0,1936.0,Medium-sized square-like cluster with irregular somewhat elongated outline, weed: amaranthus tuberculatus, middle-left of lentil crop field
+UASs_496.jpg,17.0,64.0,223.0,282.0,Moderately sized square-like cluster with irregular sprawling outline, weed: bassia scoparia, top-left of lentil crop field
+UASs_502.jpg,2349.0,1193.0,2516.0,1384.0,Compact square-like cluster with roughly symmetrical slightly irregular outline, weed: erigeron canadensis, middle-center of lentil crop field
+UASs_503.jpg,2767.0,524.0,3121.0,916.0,Medium-sized square-like cluster with broadly irregular potentially sprawling outline, weed: ambrosia artemisiifolia, top-center of lentil crop field
+UASs_504.jpg,2858.0,728.0,3325.0,1225.0,Medium-sized square-like cluster with irregular somewhat elongated outline, weed: amaranthus tuberculatus, top-center of lentil crop field
+UASs_505.jpg,2813.0,1574.0,3069.0,1894.0,Medium-sized square-like cluster with irregular somewhat elongated outline, weed: amaranthus tuberculatus, middle-center of lentil crop field
+UASs_506.jpg,1917.0,9.0,2100.0,162.0,Moderately sized square-like cluster with irregular sprawling outline, weed: bassia scoparia, top-center of lentil crop field
+UASs_507.jpg,2219.0,360.0,2389.0,570.0,Medium-sized square-like cluster with irregular somewhat elongated outline, weed: amaranthus tuberculatus, top-center of lentil crop field
+UASs_509.jpg,2428.0,7.0,2790.0,320.0,Moderately sized square-like cluster with irregular sprawling outline, weed: bassia scoparia, top-center of lentil crop field
+UASs_510.jpg,2221.0,1071.0,2372.0,1229.0,Compact square-like cluster with roughly symmetrical slightly irregular outline, weed: erigeron canadensis, top-center of lentil crop field
+UASs_660.jpg,1679.0,668.0,2066.0,1052.0,Moderately sized square-like cluster with irregular sprawling outline, weed: bassia scoparia, top-left of lentil crop field
+UASs_661.jpg,1927.0,2768.0,2368.0,3189.0,Medium-sized square-like cluster with irregular somewhat elongated outline, weed: amaranthus tuberculatus, bottom-center of lentil crop field
+UASs_93.jpg,166.0,2184.0,417.0,2396.0,Medium-sized square-like cluster with broadly irregular potentially sprawling outline, weed: ambrosia artemisiifolia, middle-left of lentil crop field