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https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
use events to signal when motion is detected
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blakeblackshear
parent
8525f05f29
commit
957bd2adeb
@ -153,7 +153,7 @@ class MqttPublisher(threading.Thread):
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# send message for motion
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motion_status = 'OFF'
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if any(obj.value == 1 for obj in self.motion_flags):
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if any(obj.is_set() for obj in self.motion_flags):
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motion_status = 'ON'
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if motion_status != last_motion:
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@ -172,11 +172,8 @@ def main():
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'x_offset': int(region_parts[1]),
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'y_offset': int(region_parts[2]),
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'min_object_size': int(region_parts[3]),
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# shared value for signaling to the capture process that we are ready for the next frame
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# (1 for ready 0 for not ready)
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'ready_for_frame': mp.Value('i', 1),
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# shared value for motion detection signal (1 for motion 0 for no motion)
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'motion_detected': mp.Value('i', 0),
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# Event for motion detection signaling
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'motion_detected': mp.Event(),
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# create shared array for storing 10 detected objects
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# note: this must be a double even though the value you are storing
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# is a float. otherwise it stops updating the value in shared
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@ -212,18 +209,18 @@ def main():
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capture_process.daemon = True
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detection_processes = []
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for index, region in enumerate(regions):
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motion_processes = []
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for region in regions:
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detection_process = mp.Process(target=process_frames, args=(shared_arr,
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region['output_array'],
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shared_frame_time,
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frame_lock, frame_ready,
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region['motion_detected'],
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frame_shape,
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region['size'], region['x_offset'], region['y_offset']))
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detection_process.daemon = True
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detection_processes.append(detection_process)
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motion_processes = []
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for index, region in enumerate(regions):
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motion_process = mp.Process(target=detect_motion, args=(shared_arr,
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shared_frame_time,
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frame_lock, frame_ready,
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@ -267,9 +264,8 @@ def main():
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# make a copy of the current detected objects
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detected_objects = DETECTED_OBJECTS.copy()
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# lock and make a copy of the current frame
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frame_lock.aquire()
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frame = frame_arr.copy()
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frame_lock.release()
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with frame_lock:
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frame = frame_arr.copy()
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# convert to RGB for drawing
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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# draw the bounding boxes on the screen
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@ -286,7 +282,7 @@ def main():
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for region in regions:
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color = (255,255,255)
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if region['motion_detected'].value == 1:
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if region['motion_detected'].is_set():
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color = (0,255,0)
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cv2.rectangle(frame, (region['x_offset'], region['y_offset']),
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(region['x_offset']+region['size'], region['y_offset']+region['size']),
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@ -336,10 +332,9 @@ def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_s
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ret, frame = video.retrieve()
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if ret:
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# Lock access and update frame
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frame_lock.acquire()
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arr[:] = frame
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shared_frame_time.value = frame_time.timestamp()
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frame_lock.release()
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with frame_lock:
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arr[:] = frame
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shared_frame_time.value = frame_time.timestamp()
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# Notify with the condition that a new frame is ready
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with frame_ready:
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frame_ready.notify_all()
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@ -347,7 +342,7 @@ def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_s
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video.release()
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# do the actual object detection
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def process_frames(shared_arr, shared_output_arr, shared_frame_time, shared_motion, frame_shape, region_size, region_x_offset, region_y_offset):
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def process_frames(shared_arr, shared_output_arr, shared_frame_time, frame_lock, frame_ready, motion_detected, frame_shape, region_size, region_x_offset, region_y_offset):
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debug = True
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# shape shared input array into frame for processing
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arr = tonumpyarray(shared_arr).reshape(frame_shape)
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@ -362,42 +357,22 @@ def process_frames(shared_arr, shared_output_arr, shared_frame_time, shared_moti
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tf.import_graph_def(od_graph_def, name='')
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sess = tf.Session(graph=detection_graph)
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no_frames_available = -1
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frame_time = 0.0
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while True:
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now = datetime.datetime.now().timestamp()
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# if there is no motion detected
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if shared_motion.value == 0:
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time.sleep(0.1)
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continue
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# if there isnt a new frame ready for processing
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if shared_frame_time.value == frame_time:
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# save the first time there were no frames available
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if no_frames_available == -1:
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no_frames_available = now
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# if there havent been any frames available in 30 seconds,
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# sleep to avoid using so much cpu if the camera feed is down
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if no_frames_available > 0 and (now - no_frames_available) > 30:
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time.sleep(1)
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print("sleeping because no frames have been available in a while")
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else:
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# rest a little bit to avoid maxing out the CPU
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time.sleep(0.1)
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continue
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# we got a valid frame, so reset the timer
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no_frames_available = -1
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# wait until motion is detected
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motion_detected.wait()
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# if the frame is more than 0.5 second old, ignore it
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if (now - shared_frame_time.value) > 0.5:
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# rest a little bit to avoid maxing out the CPU
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time.sleep(0.1)
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continue
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with frame_ready:
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# if there isnt a frame ready for processing or it is old, wait for a signal
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if shared_frame_time.value == frame_time or (now - shared_frame_time.value) > 0.5:
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frame_ready.wait()
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# make a copy of the cropped frame
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cropped_frame = arr[region_y_offset:region_y_offset+region_size, region_x_offset:region_x_offset+region_size].copy()
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frame_time = shared_frame_time.value
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with frame_lock:
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cropped_frame = arr[region_y_offset:region_y_offset+region_size, region_x_offset:region_x_offset+region_size].copy()
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frame_time = shared_frame_time.value
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# convert to RGB
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cropped_frame_rgb = cv2.cvtColor(cropped_frame, cv2.COLOR_BGR2RGB)
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@ -407,11 +382,10 @@ def process_frames(shared_arr, shared_output_arr, shared_frame_time, shared_moti
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shared_output_arr[:] = objects + [0.0] * (60-len(objects))
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# do the actual motion detection
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def detect_motion(shared_arr, shared_frame_time, frame_lock, frame_ready, shared_motion, frame_shape, region_size, region_x_offset, region_y_offset, min_motion_area, debug):
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def detect_motion(shared_arr, shared_frame_time, frame_lock, frame_ready, motion_detected, frame_shape, region_size, region_x_offset, region_y_offset, min_motion_area, debug):
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# shape shared input array into frame for processing
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arr = tonumpyarray(shared_arr).reshape(frame_shape)
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no_frames_available = -1
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avg_frame = None
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last_motion = -1
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frame_time = 0.0
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@ -421,7 +395,7 @@ def detect_motion(shared_arr, shared_frame_time, frame_lock, frame_ready, shared
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# if it has been long enough since the last motion, clear the flag
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if last_motion > 0 and (now - last_motion) > 2:
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last_motion = -1
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shared_motion.value = 0
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motion_detected.clear()
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with frame_ready:
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# if there isnt a frame ready for processing or it is old, wait for a signal
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@ -429,10 +403,9 @@ def detect_motion(shared_arr, shared_frame_time, frame_lock, frame_ready, shared
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frame_ready.wait()
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# lock and make a copy of the cropped frame
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frame_lock.acquire()
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cropped_frame = arr[region_y_offset:region_y_offset+region_size, region_x_offset:region_x_offset+region_size].copy().astype('uint8')
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frame_time = shared_frame_time.value
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frame_lock.release()
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with frame_lock:
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cropped_frame = arr[region_y_offset:region_y_offset+region_size, region_x_offset:region_x_offset+region_size].copy().astype('uint8')
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frame_time = shared_frame_time.value
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# convert to grayscale
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gray = cv2.cvtColor(cropped_frame, cv2.COLOR_BGR2GRAY)
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@ -480,7 +453,7 @@ def detect_motion(shared_arr, shared_frame_time, frame_lock, frame_ready, shared
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motion_frames += 1
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# if there have been enough consecutive motion frames, report motion
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if motion_frames >= 3:
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shared_motion.value = 1
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motion_detected.set()
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last_motion = now
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else:
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motion_frames = 0
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