Update app.py

app.py

@@ -49,13 +49,24 @@ 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}")
+                print(f"Found TRAIN annotation file: {ann_file}")
                 break
         if ann_file:
             break
 
+    # 2b) fallback: first .json anywhere
     if ann_file is None:
-        raise FileNotFoundError(f"No JSON file containing 'train' found under {root}")
+        for dirpath, _, filenames in os.walk(root):
+            for fname in filenames:
+                if fname.lower().endswith('.json'):
+                    ann_file = os.path.join(dirpath, fname)
+                    print(f"No TRAIN file—falling back to first JSON: {ann_file}")
+                    break
+            if ann_file:
+                break
+
+    if ann_file is None:
+        raise FileNotFoundError(f"No JSON annotations found under {root}")
 
     # 3) load COCO annotations
     with open(ann_file, 'r') as f:
@@ -93,7 +104,7 @@ def convert_seg_to_bbox(api_key: str, dataset_url: str):
         )
         annos.setdefault(img_id, []).append(line)
 
-    # 7) locate your train-images folder (first folder under root with any image files)
+    # 7) locate your image folder (first with any .jpg/.png)
     train_img_dir = None
     for dirpath, _, files in os.walk(root):
         if any(f.lower().endswith(('.jpg', '.png', '.jpeg')) for f in files):
@@ -122,16 +133,13 @@ def convert_seg_to_bbox(api_key: str, dataset_url: str):
         src = os.path.join(train_img_dir, fname)
         img = cv2.cvtColor(cv2.imread(src), cv2.COLOR_BGR2RGB)
 
-        # draw segmentation polygons
         seg_vis = img.copy()
         img_id = name_to_id[fname]
         for anno in coco['annotations']:
-            if anno['image_id'] != img_id:
-                continue
+            if anno['image_id'] != img_id: continue
             pts = np.array(anno['segmentation'][0], dtype=np.int32).reshape(-1, 2)
             cv2.polylines(seg_vis, [pts], True, (255, 0, 0), 2)
 
-        # draw bounding boxes
         box_vis = img.copy()
         for line in annos.get(img_id, []):
             _, cxn, cyn, wnorm, hnorm = map(float, line.split())