Update app.py

app.py

@@ -170,7 +170,7 @@ def draw_angled_line(image, line_params, color=(0, 255, 0), thickness=2):
     _, _, start_point, end_point = line_params
     cv2.line(image, start_point, end_point, color, thickness)
 
-def process_video(confidence_threshold=0.5, selected_classes=None, stream_url=None):
+def process_video(confidence_threshold=0.5, selected_classes=None, stream_url=None, target_fps=30):
     """
     Processes the IP camera stream to count objects of the selected classes crossing the line.
     """
@@ -202,6 +202,7 @@ def process_video(confidence_threshold=0.5, selected_classes=None, stream_url=No
     frame_queue = deque(maxlen=10)
 
     logger.info("Starting to process the stream...")
+    last_time = time.time()
     while cap.isOpened():
         ret, frame = cap.read()
         if not ret:
@@ -258,6 +259,15 @@ def process_video(confidence_threshold=0.5, selected_classes=None, stream_url=No
             # Yield the annotated frame to Gradio
             yield annotated_frame, ""
 
+        # Calculate the time taken to process the frame
+        current_time = time.time()
+        elapsed_time = current_time - last_time
+        last_time = current_time
+
+        # Calculate the time to sleep to maintain the target FPS
+        sleep_time = max(0, (1.0 / target_fps) - elapsed_time)
+        time.sleep(sleep_time)
+
     cap.release()
     logger.info("Stream processing completed.")
 
@@ -291,6 +301,10 @@ with gr.Blocks() as demo:
         gr.Markdown("### Step 3: Adjust Confidence Threshold (Optional)")
         confidence_threshold = gr.Slider(minimum=0.0, maximum=1.0, value=0.2, label="Confidence Threshold")
 
+        # Step 4: Set target FPS
+        gr.Markdown("### Step 4: Set Target FPS (Optional)")
+        target_fps = gr.Slider(minimum=1, maximum=60, value=30, label="Target FPS")
+
         # Process the stream
         process_button = gr.Button("Process Stream")
 
@@ -301,7 +315,7 @@ with gr.Blocks() as demo:
         error_box = gr.Textbox(label="Errors/Warnings", interactive=False)
 
         # Event listener for processing the video
-        process_button.click(process_video, inputs=[confidence_threshold, selected_classes, stream_url], outputs=[output_image, error_box])
+        process_button.click(process_video, inputs=[confidence_threshold, selected_classes, stream_url, target_fps], outputs=[output_image, error_box])
 
 # Launch the interface
 demo.launch(debug=True)