Update app.py

app.py

@@ -136,6 +136,58 @@ def process_live_frame(frame):
         return processed, status_txt, None
 
 
+# Constants for the video experiment
+VIDEO_FPS = 30.0
+CHUNK_SIZE_SECONDS = 2
+CHUNK_FRAME_COUNT = int(VIDEO_FPS * CHUNK_SIZE_SECONDS)
+TEMP_VIDEO_FILE = "temp_video_chunk.mp4"
+
+def process_video_chunk(frame, frame_buffer):
+    """
+    Processes a single frame, adds it to a buffer, and encodes a video chunk
+    when the buffer is full. The alert system remains real-time.
+    """
+    if frame is None:
+        return None, "Status: Inactive", None, [] # Return empty buffer
+
+    # --- Real-time detection and alerting (This is not delayed) ---
+    try:
+        processed_frame, indic = detector.process_frame(frame)
+    except Exception as e:
+        logging.error(f"Error processing frame: {e}")
+        processed_frame = np.zeros_like(frame)
+        indic = {"drowsiness_level": "Error", "lighting": "Unknown", "details": {"Score": 0.0}}
+
+    level = indic.get("drowsiness_level", "Awake")
+    lighting = indic.get("lighting", "Good")
+    score = indic.get("details", {}).get("Score", 0.0)
+    status_txt = f"Lighting: {lighting}\nStatus: {level}\nScore: {score:.2f}"
+    
+    audio_payload = alert_manager.trigger_alert(level, lighting)
+    audio_out = gr.Audio(value=audio_payload, autoplay=True) if audio_payload else None
+
+    # --- Video Buffering Logic ---
+    frame_buffer.append(processed_frame)
+
+    video_out = None # No video output until the chunk is ready
+    if len(frame_buffer) >= CHUNK_FRAME_COUNT:
+        logging.info(f"Buffer full. Encoding {len(frame_buffer)} frames to video chunk...")
+        # Encode the buffer to a video file
+        h, w, _ = frame_buffer[0].shape
+        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        writer = cv2.VideoWriter(TEMP_VIDEO_FILE, fourcc, VIDEO_FPS, (w, h))
+        for f in frame_buffer:
+            writer.write(f)
+        writer.release()
+        
+        video_out = TEMP_VIDEO_FILE # Set the output to the new video file path
+        frame_buffer = [] # Clear the buffer for the next chunk
+        logging.info("Encoding complete. Sending video to frontend.")
+
+    # Note: Status and Audio are returned on every frame for real-time feedback
+    return video_out, status_txt, audio_out, frame_buffer
+
+
 # ───────────────────────────── UI Definition
 def create_readme_tab():
     """Creates the content for the 'About' tab."""
@@ -215,11 +267,36 @@ def create_detection_tab():
             outputs=[out_img, out_text, out_audio] # The output now targets the placeholder
         )
 
+def create_video_experiment_tab():
+    """Creates the content for the Video Chunk experiment tab."""
+    with gr.Blocks() as video_tab:
+        gr.Markdown("## 🧪 Video Output Experiment")
+        gr.Markdown(f"This feed buffers processed frames and outputs them as **{CHUNK_SIZE_SECONDS}-second video chunks**. Notice the trade-off between smoothness and latency. Alerts remain real-time.")
+        with gr.Row():
+            with gr.Column(scale=2):
+                cam_video = gr.Image(sources=["webcam"], streaming=True, label="Live Camera Feed")
+            with gr.Column(scale=1):
+                out_video = gr.Video(label="Processed Video Chunk")
+                out_text_video = gr.Textbox(label="Live Status", lines=3, interactive=False)
+                out_audio_video = gr.Audio(label="Alert", autoplay=True, visible=False)
+
+        # State to hold the buffer of frames between updates
+        frame_buffer_state = gr.State([])
+        
+        cam_video.stream(
+            fn=process_video_chunk,
+            inputs=[cam_video, frame_buffer_state],
+            outputs=[out_video, out_text_video, out_audio_video, frame_buffer_state]
+        )
+    return video_tab
+    
 with gr.Blocks(title="🚗 Drive Paddy – Drowsiness Detection", theme=gr.themes.Soft()) as app:
     gr.Markdown("# 🚗 **Drive Paddy**")
     with gr.Tabs():
         with gr.TabItem("Live Detection"):
             create_detection_tab()
+        with gr.TabItem("Video Output Experiment"):
+            create_video_experiment_tab()
         with gr.TabItem("About this App"):
             create_readme_tab()