Update app.py

app.py

@@ -59,15 +59,37 @@ def predict_on_video(video_in_filepath, video_out_filepath, detection_model, cat
         fps,
         (frame_w, frame_h)
     )
-    while True:
-        ret, frame = video_reader.read()
-        if not ret:
-            break  # Break the loop if the video is finished
-        
-        processed_frame = predict(frame)
-        processed_frame_np = np.array(processed_frame)
-        video_writer.write(processed_frame_np)
+    # while True:
+    #     ret, frame = video_reader.read()
+    #     if not ret:
+    #         break  # Break the loop if the video is finished
         
+    #     processed_frame = predict(frame)
+    #     processed_frame_np = np.array(processed_frame)
+    #     video_writer.write(processed_frame_np)
+    for i in tqdm(range(nb_frames)):
+        ret, image_np = video_reader.read()
+        input_tensor = tf.convert_to_tensor(np.expand_dims(image_np, 0), dtype=tf.uint8)
+        results = detection_model(input_tensor)
+        viz_utils.visualize_boxes_and_labels_on_image_array(
+                  image_np,
+                  results['detection_boxes'][0].numpy(),
+                  (results['detection_classes'][0].numpy()+ label_id_offset).astype(int),
+                  results['detection_scores'][0].numpy(),
+                  category_index,
+                  use_normalized_coordinates=True,
+                  max_boxes_to_draw=200,
+                  min_score_thresh=.50,
+                  agnostic_mode=False,
+                  line_thickness=2)
+
+        video_writer.write(np.uint8(image_np))
+                
+    # Release camera and close windows
+    video_reader.release()
+    video_writer.release() 
+    cv2.destroyAllWindows() 
+    cv2.waitKey(1)        
     video_reader.release()
     video_writer.release()
     cv2.destroyAllWindows()