Update app.py

app.py

@@ -47,22 +47,22 @@ def detect_person(image):
     if bboxes.shape[0] == 0:  # Aucun visage détecté
         return []
 
+    height, width, _ = img.shape  # Get image dimensions
+
     bboxes = np.round(bboxes[:, :4]).astype(int)
-    kpss = np.round(kpss).astype(int)
-    kpss[:, :, 0] = np.clip(kpss[:, :, 0], 0, img.shape[1])
-    kpss[:, :, 1] = np.clip(kpss[:, :, 1], 0, img.shape[0])
-    vbboxes = bboxes.copy()
-    vbboxes[:, 0] = kpss[:, 0, 0]
-    vbboxes[:, 1] = kpss[:, 0, 1]
-    vbboxes[:, 2] = kpss[:, 4, 0]
-    vbboxes[:, 3] = kpss[:, 4, 1]
+    
+    # Clamp bounding boxes within image boundaries
+    bboxes[:, 0] = np.clip(bboxes[:, 0], 0, width)   # x1
+    bboxes[:, 1] = np.clip(bboxes[:, 1], 0, height)  # y1
+    bboxes[:, 2] = np.clip(bboxes[:, 2], 0, width)   # x2
+    bboxes[:, 3] = np.clip(bboxes[:, 3], 0, height)  # y2
 
     person_images = []
     for i in range(bboxes.shape[0]):
         bbox = bboxes[i]
         x1, y1, x2, y2 = bbox
         person_img = img[y1:y2, x1:x2]
-        
+
         # Convert numpy array to PIL Image and encode to base64
         pil_img = Image.fromarray(person_img[:, :, ::-1])  # BGR -> RGB
         base64_img = encode_image_to_base64(pil_img)
@@ -83,7 +83,6 @@ def detect():
     except Exception as e:
         return jsonify({'error': str(e)}), 500
 
-
 def segment_image(img, clothes):
     img = decode_image_from_base64(img)
     return segment_clothing(img, clothes)