mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-12-23 19:11:14 +01:00
95 lines
3.6 KiB
Python
95 lines
3.6 KiB
Python
import time
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import datetime
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import cv2
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import threading
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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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# detection_process has consumed the current frame
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def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_shape, rtsp_url):
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# convert shared memory array into numpy and shape into image array
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arr = tonumpyarray(shared_arr).reshape(frame_shape)
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# start the video capture
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video = cv2.VideoCapture()
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video.open(rtsp_url)
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# keep the buffer small so we minimize old data
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video.set(cv2.CAP_PROP_BUFFERSIZE,1)
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bad_frame_counter = 0
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while True:
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# check if the video stream is still open, and reopen if needed
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if not video.isOpened():
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success = video.open(rtsp_url)
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if not success:
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time.sleep(1)
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continue
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# grab the frame, but dont decode it yet
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ret = video.grab()
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# snapshot the time the frame was grabbed
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frame_time = datetime.datetime.now()
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if ret:
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# go ahead and decode the current frame
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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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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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bad_frame_counter = 0
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else:
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print("Unable to decode frame")
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bad_frame_counter += 1
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else:
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print("Unable to grab a frame")
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bad_frame_counter += 1
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if bad_frame_counter > 100:
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video.release()
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video.release()
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# Stores 2 seconds worth of frames when motion is detected so they can be used for other threads
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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()
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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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# wait for the global motion flag to change
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with self.motion_changed:
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self.motion_changed.wait() |