Update app.py

app.py

@@ -31,7 +31,14 @@ def convert_seg_to_bbox(api_key: str, dataset_url: str):
     ws, proj, ver = parse_roboflow_url(dataset_url)
     version_obj = rf.workspace(ws).project(proj).version(ver)
     dataset = version_obj.download("coco-segmentation")
-    root = dataset.location  # e.g. "/home/user/app/YourProject"
+    root = dataset.location  # e.g. "/home/user/app/ds-2"
+
+    # --- DEBUG: print out the downloaded directory tree ---
+    print(f"Dataset downloaded to: {root}")
+    for dirpath, dirnames, filenames in os.walk(root):
+        print(f"\nDirectory: {dirpath}")
+        print(f"  Subdirs: {dirnames}")
+        print(f"  Files: {filenames}")
 
     # 2) search for any JSON file with "train" in its name
     ann_file = None
@@ -39,6 +46,7 @@ def convert_seg_to_bbox(api_key: str, dataset_url: str):
         for fname in filenames:
             if 'train' in fname.lower() and fname.lower().endswith('.json'):
                 ann_file = os.path.join(dirpath, fname)
+                print(f"Found annotation file: {ann_file}")
                 break
         if ann_file:
             break
@@ -60,6 +68,7 @@ def convert_seg_to_bbox(api_key: str, dataset_url: str):
     lbl_out = os.path.join(out_root, "labels")
     os.makedirs(img_out, exist_ok=True)
     os.makedirs(lbl_out, exist_ok=True)
+    print(f"Preparing YOLOv8 output in: {out_root}")
 
     # 6) convert each segmentation annotation to a YOLO bbox line
     annos = {}
@@ -85,6 +94,7 @@ def convert_seg_to_bbox(api_key: str, dataset_url: str):
     for dirpath, _, files in os.walk(root):
         if any(f.lower().endswith(('.jpg', '.png', '.jpeg')) for f in files):
             train_img_dir = dirpath
+            print(f"Found image directory: {train_img_dir}")
             break
     if train_img_dir is None:
         raise FileNotFoundError(f"No image files found under {root}")