Update sam2_mask.py

sam2_mask.py

@@ -111,8 +111,8 @@ def show_masks(image, masks, scores, point_coords=None, box_coords=None, input_l
 @spaces.GPU()
 def sam_process(original_image, points, labels):
     
-    print(f"Points: {points}")
-    print(f"Labels: {labels}")
+    print(f"Points: {points.value}")
+    print(f"Labels: {labels.value}")
     image = Image.open(original_image)
     image = np.array(image.convert("RGB"))
     
@@ -120,7 +120,7 @@ def sam_process(original_image, points, labels):
         print("No points or labels provided, returning None")
         return None
     # Convert image to numpy array for SAM2 processing
-    image = np.array(original_image)
+    # image = np.array(original_image)
     predictor = SAM2ImagePredictor.from_pretrained("facebook/sam2.1-hiera-large")
     predictor.set_image(image)
     input_point = np.array(points.value)
@@ -166,38 +166,34 @@ def create_sam2_tab():
             with gr.Column():
                 output_image = gr.Image("Segmented Output")
                 output_result_mask = gr.Image()
-        
 
-        
-
-        
-        # Event handlers
-        points_map.upload(
-            fn = preprocess_image,
-            inputs = [points_map], 
-            outputs=[sam_input_image, first_frame, tracking_points, trackings_input_label],
-            # outputs = [first_frame_path, tracking_points, trackings_input_label, input_image]
-            queue=False
-        )
-        
-        clear_button.click(
-            lambda img: ([], [], img),
-            inputs=first_frame,
-            outputs=[tracking_points, trackings_input_label, points_map],
-            queue=False
-        )
-        
-        points_map.select(
-            get_point,
-            inputs=[point_type, tracking_points, trackings_input_label, first_frame],
-            outputs=[tracking_points, trackings_input_label, points_map],
-            queue = False
-        )
-        
-        submit_button.click(
-            sam_process,
-            inputs=[sam_input_image, tracking_points, trackings_input_label],
-            outputs = [output_image, output_result_mask]
-        )
+    # Event handlers
+    points_map.upload(
+        fn = preprocess_image,
+        inputs = [points_map], 
+        outputs=[sam_input_image, first_frame, tracking_points, trackings_input_label],
+        # outputs = [first_frame_path, tracking_points, trackings_input_label, input_image]
+        queue=False
+    )
+    
+    clear_button.click(
+        lambda img: ([], [], img),
+        inputs=first_frame,
+        outputs=[tracking_points, trackings_input_label, points_map],
+        queue=False
+    )
+    
+    points_map.select(
+        get_point,
+        inputs=[point_type, tracking_points, trackings_input_label, first_frame],
+        outputs=[tracking_points, trackings_input_label, points_map],
+        queue = False
+    )
+    
+    submit_button.click(
+        sam_process,
+        inputs=[sam_input_image, tracking_points, trackings_input_label],
+        outputs = [output_image, output_result_mask]
+    )
     
     return sam_input_image, points_map, output_image