initial commit

debug_pipeline.py

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+#!/usr/bin/env python3
+import os
+import random
+import subprocess
+from pathlib import Path
+import shutil
+
+def run_command(cmd):
+    print(f"Running: {' '.join(cmd)}")
+    subprocess.run(cmd, check=True)
+
+def main():
+    # Setup paths
+    base_dir = Path(__file__).parent
+    img_dir = base_dir / "ICCAD2019" / "img"
+    out_dir = base_dir / "out" / "debug1"
+    
+    if out_dir.exists():
+        shutil.rmtree(out_dir)
+    out_dir.mkdir(parents=True, exist_ok=True)
+
+    # Get images
+    all_images = list(img_dir.glob("*.png"))
+    if not all_images:
+        print("No images found in ICCAD2019/img")
+        return
+
+    selected_images = random.sample(all_images, min(5, len(all_images)))
+    
+    print(f"Selected {len(selected_images)} images for debugging.")
+
+    for img_path in selected_images:
+        print(f"\nProcessing {img_path.name}...")
+        case_dir = out_dir / img_path.stem
+        case_dir.mkdir(exist_ok=True)
+        
+        # 1. Skeleton Extraction
+        # Note: The user mentioned "black background, white subject" or vice versa.
+        # The script has --invert. I'll try without invert first, assuming standard layout (often drawn dark on light or light on dark).
+        # Let's check one image first? No, I'll just run it.
+        # Actually, usually layouts are drawn objects. If background is black, objects are white.
+        # My script assumes objects are white (value 1) for skeletonization.
+        # If the image is white background, I need to invert.
+        # I'll try both or just assume one. Let's assume we might need --invert if it's white background.
+        # I'll run with --invert if the mean pixel value is high (white background).
+        
+        # But wait, I can't easily check mean here without loading. 
+        # I'll just run the extraction script.
+        
+        extract_cmd = [
+            "python3", "scripts/skeleton_extract.py",
+            str(img_path),
+            str(case_dir),
+            "--denoise", "3"
+        ]
+        # Heuristic: if filename contains 'nonhotspot', it might be a clip.
+        # Let's just try running it.
+        run_command(extract_cmd)
+        
+        sk_png = case_dir / (img_path.stem + "_sk.png")
+        if not sk_png.exists():
+            print(f"Failed to generate skeleton for {img_path.name}")
+            continue
+
+        # 2. Vectorization
+        vec_json = case_dir / (img_path.stem + "_vec.json")
+        vec_cmd = [
+            "python3", "scripts/vectorize_skeleton.py",
+            str(sk_png),
+            str(vec_json)
+        ]
+        run_command(vec_cmd)
+
+        # 3. Expansion (Reconstruction)
+        recon_png = case_dir / (img_path.stem + "_recon.png")
+        expand_cmd = [
+            "python3", "scripts/expand_skeleton.py",
+            str(vec_json),
+            str(recon_png),
+            "--line-width", "3" # Adjust as needed
+        ]
+        run_command(expand_cmd)
+
+    print(f"\nDebug run complete. Check results in {out_dir}")
+
+if __name__ == "__main__":
+    main()