Update app.py

app.py

@@ -10,6 +10,7 @@ import re
 import numpy as np
 import spaces
 from PIL import Image, ImageDraw
+import re
 
 model_id = "mattraj/curacel-autodamage-1"
 COLORS = ['#4285f4', '#db4437', '#f4b400', '#0f9d58', '#e48ef1']
@@ -50,12 +51,25 @@ def infer(
 def extract_bounding_boxes(result):
     """
     Extract bounding boxes and labels from the model result.
-    Placeholder logic - replace this with actual parsing logic from model output.
+    Each bounding box is represented by two locXXXX tags and a label.
     
     Example return: [((x1, y1, x2, y2), "Label")]
     """
-    # Example static bounding box and label
-    return [((50, 50, 200, 200), "Damage"), ((300, 300, 400, 400), "Dent")]
+    bounding_boxes = []
+    
+    # Regular expression to find <locXXXX> tags and labels
+    pattern = re.compile(r'<loc(\d{4})><loc(\d{4})>\s*(\S.+?)\s*(?=<loc|\Z)')
+    
+    matches = pattern.findall(result)
+    
+    for match in matches:
+        x1, y1 = int(match[0][:2]), int(match[0][2:])
+        x2, y2 = int(match[1][:2]), int(match[1][2:])
+        label = match[2].strip()
+        
+        bounding_boxes.append(((x1, y1, x2, y2), label))
+    
+    return bounding_boxes
 
 ######## Demo