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https://github.com/blakeblackshear/frigate.git
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manage 2 seconds worth of motion frames for processing
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@ -18,7 +18,7 @@ from frigate.util import tonumpyarray
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from frigate.mqtt import MqttMotionPublisher, MqttObjectPublisher
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from frigate.mqtt import MqttMotionPublisher, MqttObjectPublisher
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from frigate.objects import ObjectParser, ObjectCleaner
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from frigate.objects import ObjectParser, ObjectCleaner
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from frigate.motion import detect_motion
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from frigate.motion import detect_motion
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from frigate.video import fetch_frames
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from frigate.video import fetch_frames, FrameTracker
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from frigate.object_detection import detect_objects
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from frigate.object_detection import detect_objects
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RTSP_URL = os.getenv('RTSP_URL')
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RTSP_URL = os.getenv('RTSP_URL')
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@ -35,6 +35,7 @@ DEBUG = (os.getenv('DEBUG') == '1')
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def main():
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def main():
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DETECTED_OBJECTS = []
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DETECTED_OBJECTS = []
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recent_motion_frames = {}
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# Parse selected regions
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# Parse selected regions
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regions = []
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regions = []
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for region_string in REGIONS.split(':'):
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for region_string in REGIONS.split(':'):
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@ -120,6 +121,11 @@ def main():
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motion_process.daemon = True
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motion_process.daemon = True
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motion_processes.append(motion_process)
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motion_processes.append(motion_process)
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# start a thread to store recent motion frames for processing
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frame_tracker = FrameTracker(frame_arr, shared_frame_time, frame_ready, frame_lock,
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recent_motion_frames, motion_changed, [region['motion_detected'] for region in regions])
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frame_tracker.start()
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# start a thread to parse objects from the queue
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# start a thread to parse objects from the queue
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object_parser = ObjectParser(object_queue, objects_parsed, DETECTED_OBJECTS)
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object_parser = ObjectParser(object_queue, objects_parsed, DETECTED_OBJECTS)
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object_parser.start()
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object_parser.start()
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@ -212,6 +218,7 @@ def main():
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detection_process.join()
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detection_process.join()
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for motion_process in motion_processes:
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for motion_process in motion_processes:
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motion_process.join()
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motion_process.join()
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frame_tracker.join()
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object_parser.join()
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object_parser.join()
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object_cleaner.join()
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object_cleaner.join()
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mqtt_publisher.join()
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mqtt_publisher.join()
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@ -1,6 +1,7 @@
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import time
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import time
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import datetime
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import datetime
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import cv2
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import cv2
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import threading
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from . util import tonumpyarray
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from . util import tonumpyarray
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# fetch the frames as fast a possible, only decoding the frames when the
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# fetch the frames as fast a possible, only decoding the frames when the
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@ -38,4 +39,47 @@ def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_s
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with frame_ready:
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with frame_ready:
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frame_ready.notify_all()
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frame_ready.notify_all()
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video.release()
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video.release()
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class FrameTracker(threading.Thread):
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def __init__(self, shared_frame, frame_time, frame_ready, frame_lock, recent_frames, motion_changed, motion_regions):
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threading.Thread.__init__(self)
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self.shared_frame = shared_frame
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self.frame_time = frame_time
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self.frame_ready = frame_ready
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self.frame_lock = frame_lock
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self.recent_frames = recent_frames
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self.motion_changed = motion_changed
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self.motion_regions = motion_regions
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def run(self):
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frame_time = 0.0
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while True:
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# while there is motion
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while len([r for r in self.motion_regions if r.is_set()]) > 0:
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now = datetime.datetime.now().timestamp()
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# wait for a frame
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with self.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 self.frame_time.value == frame_time or (now - self.frame_time.value) > 0.5:
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self.frame_ready.wait()
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# lock and make a copy of the frame
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with self.frame_lock:
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frame = self.shared_frame.copy().astype('uint8')
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frame_time = self.frame_time.value
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# add the frame to recent frames
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self.recent_frames[frame_time] = frame
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# delete any old frames
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stored_frame_times = list(self.recent_frames.keys())
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for k in stored_frame_times:
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if (now - k) > 2:
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del self.recent_frames[k]
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print(stored_frame_times)
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# wait for the global motion flag to change
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with self.motion_changed:
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self.motion_changed.wait()
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