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Update app.py
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app.py
CHANGED
@@ -93,7 +93,6 @@ class AlertManager:
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alert_manager = AlertManager(CFG["alerting"])
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# βββββββββββββββββββββββββββββ frame processing <--- MAJOR CHANGE
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# Simplified by the AlertManager. No longer needs to pass 'last_alert_ts' back and forth.
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def process_live_frame(frame):
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if frame is None:
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return (
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@@ -105,7 +104,6 @@ def process_live_frame(frame):
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t0 = time.perf_counter()
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try:
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# Assuming your detector returns (processed_image, indicators_dict)
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processed, indic = detector.process_frame(frame)
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except Exception as e:
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logging.error(f"Error processing frame: {e}")
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@@ -125,30 +123,36 @@ def process_live_frame(frame):
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else f"Status: {level}\nScore: {score:.2f}")
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)
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# Check for an alert and get the audio payload if ready
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audio_payload = alert_manager.trigger_alert(level, lighting)
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# This is the key: return a new gr.Audio component when an alert fires.
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# Otherwise, return None to clear the component on the frontend.
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if audio_payload:
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return processed, status_txt, gr.Audio(value=audio_payload, autoplay=True)
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else:
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return processed, status_txt, None
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# Constants for the video experiment
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VIDEO_FPS = 30.0
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CHUNK_SIZE_SECONDS = 2
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CHUNK_FRAME_COUNT = int(VIDEO_FPS * CHUNK_SIZE_SECONDS)
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TEMP_VIDEO_FILE = "temp_video_chunk.mp4"
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def process_video_chunk(frame,
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"""
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Processes a single frame, adds it to a buffer, and encodes a video chunk
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when the buffer is full.
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"""
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if frame is None:
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return None, "Status: Inactive", None,
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# --- Real-time detection and alerting (This is not delayed) ---
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try:
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@@ -161,6 +165,7 @@ def process_video_chunk(frame, frame_buffer):
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level = indic.get("drowsiness_level", "Awake")
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lighting = indic.get("lighting", "Good")
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score = indic.get("details", {}).get("Score", 0.0)
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status_txt = f"Lighting: {lighting}\nStatus: {level}\nScore: {score:.2f}"
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audio_payload = alert_manager.trigger_alert(level, lighting)
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@@ -171,7 +176,13 @@ def process_video_chunk(frame, frame_buffer):
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video_out = None # No video output until the chunk is ready
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if len(frame_buffer) >= CHUNK_FRAME_COUNT:
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-
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# Encode the buffer to a video file
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h, w, _ = frame_buffer[0].shape
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fourcc = cv2.VideoWriter_fourcc(*'mp4v')
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@@ -180,13 +191,18 @@ def process_video_chunk(frame, frame_buffer):
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writer.write(f)
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writer.release()
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video_out = TEMP_VIDEO_FILE # Set the output to the new video file path
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frame_buffer = [] # Clear the buffer for the next chunk
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# Note: Status and Audio are returned on every frame for real-time feedback
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return video_out, status_txt, audio_out,
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-
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# βββββββββββββββββββββββββββββ UI Definition
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def create_readme_tab():
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@@ -280,8 +296,8 @@ def create_video_experiment_tab():
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out_text_video = gr.Textbox(label="Live Status", lines=3, interactive=False)
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out_audio_video = gr.Audio(label="Alert", autoplay=True, visible=False)
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# State to hold the buffer
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frame_buffer_state = gr.State([])
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cam_video.stream(
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fn=process_video_chunk,
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alert_manager = AlertManager(CFG["alerting"])
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# βββββββββββββββββββββββββββββ frame processing <--- MAJOR CHANGE
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def process_live_frame(frame):
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if frame is None:
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return (
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t0 = time.perf_counter()
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try:
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processed, indic = detector.process_frame(frame)
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except Exception as e:
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logging.error(f"Error processing frame: {e}")
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else f"Status: {level}\nScore: {score:.2f}")
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)
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audio_payload = alert_manager.trigger_alert(level, lighting)
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if audio_payload:
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return processed, status_txt, gr.Audio(value=audio_payload, autoplay=True)
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else:
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return processed, status_txt, None
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+
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# Constants for the video experiment
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VIDEO_FPS = 30.0
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CHUNK_SIZE_SECONDS = 2
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CHUNK_FRAME_COUNT = int(VIDEO_FPS * CHUNK_SIZE_SECONDS)
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TEMP_VIDEO_FILE = "temp_video_chunk.mp4"
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def process_video_chunk(frame, state_dict):
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"""
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Processes a single frame, adds it to a buffer, and encodes a video chunk
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when the buffer is full. Now includes detailed timing logs.
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"""
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if frame is None:
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return None, "Status: Inactive", None, state_dict
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# Unpack the state
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frame_buffer = state_dict['buffer']
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start_time = state_dict['start_time']
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# If the buffer is empty, this is the first frame of a new chunk. Record start time.
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if not frame_buffer:
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start_time = time.perf_counter()
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# --- Real-time detection and alerting (This is not delayed) ---
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try:
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level = indic.get("drowsiness_level", "Awake")
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lighting = indic.get("lighting", "Good")
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score = indic.get("details", {}).get("Score", 0.0)
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# The status text is updated on every single frame.
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status_txt = f"Lighting: {lighting}\nStatus: {level}\nScore: {score:.2f}"
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audio_payload = alert_manager.trigger_alert(level, lighting)
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video_out = None # No video output until the chunk is ready
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if len(frame_buffer) >= CHUNK_FRAME_COUNT:
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# --- NEW: Logging buffer fill time ---
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buffer_fill_time = time.perf_counter() - start_time
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logging.info(f"BUFFER: Filled {len(frame_buffer)} frames in {buffer_fill_time:.2f} seconds.")
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# --- NEW: Logging encoding time ---
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encoding_start_time = time.perf_counter()
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# Encode the buffer to a video file
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h, w, _ = frame_buffer[0].shape
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fourcc = cv2.VideoWriter_fourcc(*'mp4v')
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writer.write(f)
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writer.release()
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encoding_time = time.perf_counter() - encoding_start_time
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logging.info(f"ENCODING: Video chunk encoded in {encoding_time:.2f} seconds.")
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video_out = TEMP_VIDEO_FILE # Set the output to the new video file path
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frame_buffer = [] # Clear the buffer for the next chunk
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start_time = None # Reset start time
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# Pack state back up to return
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new_state = {'buffer': frame_buffer, 'start_time': start_time}
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# Note: Status and Audio are returned on every frame for real-time feedback
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return video_out, status_txt, audio_out, new_state
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# βββββββββββββββββββββββββββββ UI Definition
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def create_readme_tab():
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out_text_video = gr.Textbox(label="Live Status", lines=3, interactive=False)
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out_audio_video = gr.Audio(label="Alert", autoplay=True, visible=False)
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# NEW: State is now a dictionary to hold the buffer and start time
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frame_buffer_state = gr.State({'buffer': [], 'start_time': None})
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cam_video.stream(
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fn=process_video_chunk,
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