mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-10-15 20:07:23 +02:00
41 lines
1.5 KiB
Python
41 lines
1.5 KiB
Python
import time
|
|
import datetime
|
|
import cv2
|
|
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)
|
|
|
|
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()
|
|
|
|
video.release() |