Update app.py

app.py

@@ -5,12 +5,14 @@ import tensorflow as tf
 from object_detection.utils import label_map_util
 from object_detection.utils import visualization_utils as viz_utils
 from object_detection.utils import ops as utils_op
-import tarfile
-import wget 
+# import tarfile
+# import wget 
 import gradio as gr
-from huggingface_hub import snapshot_download
+# from huggingface_hub import snapshot_download
 import os
 import cv2
+import time
+
 
 PATH_TO_LABELS = 'data/label_map.pbtxt'   
 category_index = label_map_util.create_category_index_from_labelmap(PATH_TO_LABELS, use_display_name=True)
@@ -57,18 +59,25 @@ def predict_on_video(video_in_filepath, video_out_filepath, detection_model, cat
         fps,
         (frame_w, frame_h)
     )
-    label_id_offset = 0
     while True:
         ret, frame = video_reader.read()
         if not ret:
             break  # Break the loop if the video is finished
+        
+        start_time = time.time()
         processed_frame = predict(frame)
+        end_time = time.time()
+        processing_time = end_time - start_time
         processed_frame_np = np.array(processed_frame)
         video_writer.write(processed_frame_np)
+        
+        # Adjust the delay based on processing time
+        delay_time = max(1, int((1 / fps - processing_time) * 1000))
+        cv2.waitKey(delay_time)
     video_reader.release()
     video_writer.release()
     cv2.destroyAllWindows()
-    cv2.waitKey(1)
+    cv2.waitKey(5)
 
 # Function to process a video
 def process_video(video_path):