项目中涉及读取视频流部分,但是读取视频流有时不是很顺利,总会导致软件的卡顿,现把解决此问题的心得分享给大家~
目录
- import cv2
- import time
-
-
- url = 'rtsp://admin:aiat12345@192.168.1.10:554/Streaming/Channels/10'
- start_time = time.time()
- capture = cv2.VideoCapture(url)
- ok, frame = capture.read()
- print('是否读取到视频流:', ok)
- print('耗时{}s'.format(time.time() - start_time))
>>> 运行结果(无效视频流):
是否读取到视频流: False
耗时91.21544742584229s
warning: Error opening file (/build/opencv/modules/videoio/src/cap_ffmpeg_impl.hpp:856)
warning: rtsp://admin:aiat12345@192.168.1.10:554/Streaming/Channels/10 (/build/opencv/modules/videoio/src/cap_ffmpeg_impl.hpp:857)Process finished with exit code 0
注意:虽然没有成功读取视频流,但是程序没有报错,只是警告。
>>> 运行结果(有效视频流):
是否读取到视频流: True
耗时1.4005577564239502sProcess finished with exit code 0
由运行结果可知,如果没有成功读取视频流,会耗时90s左右;反之,需要1.4s左右。
尝试了很多办法都无功而返,亲历了柳暗花明又一村,无意间发现一篇博客:
python timeout(设置函数超时退出)_嘿,不许笑的博客-CSDN博客_python timeout
https://blog.csdn.net/qq_43994782/article/details/119033086?utm_source=app&app_version=5.3.0&code=app_1562916241&uLinkId=usr1mkqgl919blen虽然之前尝试了利用装饰符@,可能是没有选对库导致失败告终,但是最后还是很简单的利用装饰器解决了此问题,具体实现见如下代码:
- import cv2
- import time
- from func_timeout import func_set_timeout
-
-
- url = 'rtsp://admin:aiat12345@192.168.1.10:554/Streaming/Channels/10'
-
- # 设定超时时间
- @func_set_timeout(5)
- def read_url(url):
- capture = cv2.VideoCapture(url)
- return capture
-
- start_time = time.time()
- try:
- # 调用读取URL的函数
- capture = read_url(url)
- ok, frame = capture.read()
- except:
- print('耗时{}s'.format(time.time() - start_time))
>>> 运行结果:
耗时5.110106706619263s
Process finished with exit code 0
@func_set_timeout() 装饰器的作用:如果修饰的函数在规定时间内没有运行成功,便会直接报错,如下面的代码的报错截图所示。
- import cv2
- import time
- from func_timeout import func_set_timeout
-
-
- url = 'rtsp://admin:aiat12345@192.168.1.10:554/Streaming/Channels/10'
-
- # 设定超时时间
- @func_set_timeout(5)
- def read_url(url):
- capture = cv2.VideoCapture(url)
- return capture
-
- start_time = time.time()
-
- # 调用读取URL的函数
- capture = read_url(url)
- ok, frame = capture.read()
-
- print('耗时{}s'.format(time.time() - start_time))

故融入到项目中,需要加入容错步骤(try),即如果 try 中的代码报错,Pycharm会直接跳过这部分代码,继续执行剩余部分的代码。
注意:
>>>如有问题,欢迎评论区一起探讨。