blakeblackshear.frigate/frigate/video.py

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import time
import datetime
import cv2
import threading
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from . util import tonumpyarray
# fetch the frames as fast a possible, only decoding the frames when the
# detection_process has consumed the current frame
def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_shape, rtsp_url):
# convert shared memory array into numpy and shape into image array
arr = tonumpyarray(shared_arr).reshape(frame_shape)
# start the video capture
video = cv2.VideoCapture()
video.open(rtsp_url)
# keep the buffer small so we minimize old data
video.set(cv2.CAP_PROP_BUFFERSIZE,1)
bad_frame_counter = 0
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while True:
# check if the video stream is still open, and reopen if needed
if not video.isOpened():
success = video.open(rtsp_url)
if not success:
time.sleep(1)
continue
# grab the frame, but dont decode it yet
ret = video.grab()
# snapshot the time the frame was grabbed
frame_time = datetime.datetime.now()
if ret:
# go ahead and decode the current frame
ret, frame = video.retrieve()
if ret:
# Lock access and update frame
with frame_lock:
arr[:] = frame
shared_frame_time.value = frame_time.timestamp()
# Notify with the condition that a new frame is ready
with frame_ready:
frame_ready.notify_all()
bad_frame_counter = 0
else:
print("Unable to decode frame")
bad_frame_counter += 1
else:
print("Unable to grab a frame")
bad_frame_counter += 1
if bad_frame_counter > 100:
video.release()
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video.release()
# Stores 2 seconds worth of frames when motion is detected so they can be used for other threads
class FrameTracker(threading.Thread):
def __init__(self, shared_frame, frame_time, frame_ready, frame_lock, recent_frames, motion_changed, motion_regions):
threading.Thread.__init__(self)
self.shared_frame = shared_frame
self.frame_time = frame_time
self.frame_ready = frame_ready
self.frame_lock = frame_lock
self.recent_frames = recent_frames
self.motion_changed = motion_changed
self.motion_regions = motion_regions
def run(self):
frame_time = 0.0
while True:
# while there is motion
while len([r for r in self.motion_regions if r.is_set()]) > 0:
now = datetime.datetime.now().timestamp()
# wait for a frame
with self.frame_ready:
# if there isnt a frame ready for processing or it is old, wait for a signal
if self.frame_time.value == frame_time or (now - self.frame_time.value) > 0.5:
self.frame_ready.wait()
# lock and make a copy of the frame
with self.frame_lock:
frame = self.shared_frame.copy().astype('uint8')
frame_time = self.frame_time.value
# add the frame to recent frames
self.recent_frames[frame_time] = frame
# delete any old frames
stored_frame_times = list(self.recent_frames.keys())
for k in stored_frame_times:
if (now - k) > 2:
del self.recent_frames[k]
# wait for the global motion flag to change
with self.motion_changed:
self.motion_changed.wait()