Update app.py

app.py

@@ -74,17 +74,17 @@ def clipseg_prediction(image):
 
     # Vehicle checking
     if bbox_area(vehicle_bbox) > bbox_area(damage_bbox):
-        return True, [bbox_normalization(damage_bbox, img_w, img_h)]
+        return True, bbox_normalization(damage_bbox, img_w, img_h)
     else:
         return False, [[]]
      
 
 @torch.no_grad()
-def foward_pass(image_input: np.ndarray, points: List[List[int]]) -> np.ndarray:
+def foward_pass(image_input: np.ndarray, points: List[int]) -> np.ndarray:
     print('SAM-Segmentation-started------->')
     global cache_data
     image_input = Image.fromarray(image_input)
-    inputs = processor(image_input, input_points=points, return_tensors="pt").to(device)
+    inputs = processor(image_input, input_boxes=points, return_tensors="pt").to(device)
     if not cache_data or not torch.equal(inputs['pixel_values'],cache_data[0]):
         embedding = model.get_image_embeddings(inputs["pixel_values"])
         pixels = inputs["pixel_values"]