fix: cross-platform setup and missing dependencies

.gitattributes

@@ -1 +1,4 @@
 large_files/ filter=lfs diff=lfs merge=lfs -text
+
+# Keep shell scripts with Unix line endings on all platforms
+*.sh text eol=lf

.gitignore

@@ -50,3 +50,7 @@ sam3_src/
 # Local processing & debug
 arrow_processing/
 debug_output/
+
+# Local planning notes & AI tool session data
+.amir-zone/
+.claude/

README.md

@@ -36,6 +36,13 @@ Powered by SAM 3 and multimodal large models, it enables high-fidelity reconstru
 
 > [!WARNING]
 > **Please note**: Our GitHub repository currently trails behind our web-based service. For the most up-to-date features and performance, we recommend using our web platform.
+
+> [!NOTE]
+> **Known limitation — multi-panel / schematic figures.** Recent updates (v2 prompts: 19 → 78; new hierarchical layer assignment; [Stage 8 vector export to SVG/PDF](https://github.com/Sdamirsa/Edit-Banana/commit/d6c445a)) significantly improved single-element extraction, but the pipeline still under-understands complex **multi-panel scientific schematics**. Detection is per-element; the global semantics — which arrow connects which box across panel boundaries, which legend swatch labels which plot — is not yet modeled.
+>
+> **Roadmap directions on this challenge:**
+> 1. **Two-pass extraction with panel splitting.** First detect sub-figure panels (Stage 8's `section_detector` already produces panel candidates), split the source image into per-panel crops, then recursively run the full pipeline on each crop. The orchestration loop is the missing piece.
+> 2. **Smart per-element-type margin padding** around cropped rasters. Tight bboxes clip strokes; loose ones bleed neighbors. A per-type heuristic (icon vs. photo vs. schematic illustration) would help, but the logic is hard to pin down cleanly.
 ---
 ## 💬 Join WeChat Group
 

main.py

@@ -12,6 +12,8 @@
     python main.py -i input/test.png -o output/custom/
     python main.py -i input/test.png --refine
     python main.py -i input/test.png --no-text
+    python main.py -i input/test.png --vector-level=all
+    python main.py -i input/test.png --no-vectors
 """
 
 import os
@@ -39,7 +41,10 @@
     XMLMerger,
     MetricEvaluator,
     RefinementProcessor,
-
+
+    # Stage 8: Vector export
+    VectorExporter,
+
     # Text (modules/text/)
     TextRestorer,
 
@@ -89,6 +94,7 @@ def __init__(self, config: dict = None):
         self._xml_merger = None
         self._metric_evaluator = None
         self._refinement_processor = None
+        self._vector_exporter = None
 
     @property
     def text_restorer(self):
@@ -138,13 +144,21 @@ def refinement_processor(self) -> RefinementProcessor:
         if self._refinement_processor is None:
             self._refinement_processor = RefinementProcessor()
         return self._refinement_processor
+
+    @property
+    def vector_exporter(self) -> VectorExporter:
+        if self._vector_exporter is None:
+            self._vector_exporter = VectorExporter()
+        return self._vector_exporter
 
     def process_image(self,
                       image_path: str,
                       output_dir: str = None,
                       with_refinement: bool = False,
                       with_text: bool = True,
-                      groups: List[PromptGroup] = None) -> Optional[str]:
+                      groups: List[PromptGroup] = None,
+                      vector_level: str = "granular",
+                      no_vectors: bool = False) -> Optional[str]:
         """Run pipeline on one image. Returns output XML path or None."""
         print(f"\n{'='*60}")
         print(f"Processing: {image_path}")
@@ -264,8 +278,28 @@ def process_image(self,
 
             output_path = merge_result.metadata.get('output_path')
             print(f"   Output: {output_path}")
+
+            # ============ Stage 8: Vector Export ============
+            if not no_vectors:
+                print(f"\n[8] Vector export (level={vector_level})...")
+                context.intermediate_results['vector_level'] = vector_level
+                try:
+                    vec_result = self.vector_exporter.process(context)
+                    if vec_result.success:
+                        vec_count = vec_result.metadata.get('exported_count', 0)
+                        vec_dir = vec_result.metadata.get('vector_dir', '')
+                        print(f"   Exported {vec_count} elements -> {vec_dir}")
+                    else:
+                        print(f"   Vector export failed: {vec_result.error_message}")
+                except Exception as e:
+                    print(f"   Vector export failed: {e}")
+                    import traceback
+                    traceback.print_exc()
+            else:
+                print("\n[8] Vector export (skipped)")
+
             print(f"\n{'='*60}\nDone.\n{'='*60}")
-            
+
             return output_path
 
         except Exception as e:
@@ -332,6 +366,8 @@ def main():
   python main.py
   python main.py -i test.png --refine
   python main.py -i test.png --groups image arrow
+  python main.py -i test.png --vector-level=all
+  python main.py -i test.png --no-vectors
         """
     )
 
@@ -348,6 +384,13 @@ def main():
                         help="Prompt groups to process (default: all)")
     parser.add_argument("--show-prompts", action="store_true",
                         help="Show prompt config")
+
+    # Stage 8: Vector export options
+    parser.add_argument("--vector-level", type=str, default="granular",
+                        choices=['granular', 'section', 'component', 'all'],
+                        help="Vector export granularity (default: granular)")
+    parser.add_argument("--no-vectors", action="store_true",
+                        help="Skip vector export (Stage 8)")
 
     args = parser.parse_args()
 
@@ -417,7 +460,9 @@ def main():
             output_dir=output_dir,
             with_refinement=args.refine,
             with_text=not args.no_text,
-            groups=groups
+            groups=groups,
+            vector_level=args.vector_level,
+            no_vectors=args.no_vectors,
         )
         if result:
             success_count += 1

modules/__init__.py

@@ -21,6 +21,12 @@
 from .metric_evaluator import MetricEvaluator
 from .refinement_processor import RefinementProcessor
 
+# Stage 8: Vector export
+from .vector_exporter import VectorExporter
+from .svg_generator import SVGGenerator
+from .pdf_combiner import PDFCombiner
+from .section_detector import SectionDetector
+
 # Text (modules/text/); optional if ocr/coord_processor missing
 try:
     from .text.restorer import TextRestorer
@@ -53,4 +59,9 @@
     'BasicShapeProcessor',
     'MetricEvaluator',
     'RefinementProcessor',
+    # Stage 8: Vector export
+    'VectorExporter',
+    'SVGGenerator',
+    'PDFCombiner',
+    'SectionDetector',
 ]

modules/data_types.py

@@ -255,37 +255,81 @@ def from_yaml(cls, yaml_path: str) -> 'ProcessingConfig':
 
 
 # ======================== 辅助函数 ========================
+
+def _expand_forms(prompts):
+    """Return set containing both lowercase-with-spaces and lowercase-with-underscores forms."""
+    out = set()
+    for p in prompts:
+        low = p.lower()
+        out.add(low)
+        out.add(low.replace(" ", "_"))
+    return out
+
+
+# Lazy-built prompt-derived type sets. Built on first call of get_layer_level
+# to avoid import-time cycles (prompts has no deps, but be safe).
+_TYPE_SETS_CACHE = {}
+
+
+def _get_type_sets():
+    """Build and cache prompt-derived type sets."""
+    if _TYPE_SETS_CACHE:
+        return _TYPE_SETS_CACHE
+    try:
+        from prompts.image import IMAGE_PROMPT
+        from prompts.shape import SHAPE_PROMPT
+        from prompts.arrow import ARROW_PROMPT
+        from prompts.background import BACKGROUND_PROMPT
+    except ImportError:
+        # Fallback: empty sets; legacy hardcoded lists below still apply.
+        IMAGE_PROMPT = SHAPE_PROMPT = ARROW_PROMPT = BACKGROUND_PROMPT = []
+
+    _TYPE_SETS_CACHE["image"] = _expand_forms(IMAGE_PROMPT)
+    _TYPE_SETS_CACHE["shape"] = _expand_forms(SHAPE_PROMPT)
+    _TYPE_SETS_CACHE["arrow"] = _expand_forms(ARROW_PROMPT)
+    _TYPE_SETS_CACHE["background"] = _expand_forms(BACKGROUND_PROMPT)
+    return _TYPE_SETS_CACHE
+
+
 def get_layer_level(element_type: str) -> int:
     """
     根据元素类型获取默认层级
-
-    供各子模块使用，确保层级分配一致
+
+    供各子模块使用，确保层级分配一致。
+
+    v2 fix: derive image/shape/arrow/background sets from prompt files so
+    specific prompts like "3D heart model" or "MRI image" (which were
+    silently falling through to LayerLevel.OTHER and breaking stacking)
+    now get the correct IMAGE layer.
     """
     element_type = element_type.lower()
-
-    # 背景/容器类（最底层）
-    if element_type in {'section_panel', 'title_bar'}:
+    sets = _get_type_sets()
+
+    # 背景/容器类（最底层）— legacy names + prompt-derived
+    if element_type in {'section_panel', 'title_bar'} or element_type in sets["background"]:
         return LayerLevel.BACKGROUND.value
-    
-    # 箭头/连接线
-    if element_type in {'arrow', 'line', 'connector'}:
+
+    # 箭头/连接线 — legacy names + prompt-derived
+    if element_type in {'arrow', 'line', 'connector'} or element_type in sets["arrow"]:
         return LayerLevel.ARROW.value
-    
+
     # 文字
     if element_type == 'text':
         return LayerLevel.TEXT.value
-
-    # 图片类
-    if element_type in {'icon', 'picture', 'image', 'logo', 'chart', 'function_graph'}:
+
+    # 图片类 — legacy names + prompt-derived (this is the fix path for the heart bug)
+    if element_type in {
+        'icon', 'picture', 'image', 'logo', 'chart', 'function_graph'
+    } or element_type in sets["image"]:
         return LayerLevel.IMAGE.value
-    
-    # 基本图形
+
+    # 基本图形 — legacy names + prompt-derived
     if element_type in {
         'rectangle', 'rounded_rectangle', 'rounded rectangle',
         'diamond', 'ellipse', 'circle', 'cylinder', 'cloud',
         'hexagon', 'triangle', 'parallelogram', 'actor'
-    }:
+    } or element_type in sets["shape"]:
         return LayerLevel.BASIC_SHAPE.value
-    
+
     # 其他
     return LayerLevel.OTHER.value

modules/icon_picture_processor.py

@@ -315,8 +315,15 @@ def process(self, context: ProcessingContext) -> ProcessingResult:
         )
 
     def _get_elements_to_process(self, elements: List[ElementInfo]) -> List[ElementInfo]:
-        """Filter elements to process (icons, arrows, etc.; arrows treated as icon crop)."""
-        all_types = set(IMAGE_PROMPT) | {"arrow", "line", "connector"}
+        """Filter elements to process (icons, arrows, etc.; arrows treated as icon crop).
+
+        NOTE: IMAGE_PROMPT contains mixed-case strings (e.g. "3D heart model",
+        "MRI image", "CT scan image"). Comparing `.lower()` against the raw
+        set caused those detections to be silently skipped — no base64 was
+        generated and downstream SVG rendering fell back to a plain polygon
+        outline. Always normalize both sides.
+        """
+        all_types = {t.lower() for t in IMAGE_PROMPT} | {"arrow", "line", "connector"}
         return [
             e for e in elements
             if e.element_type.lower() in all_types and e.base64 is None