尝试使用网络摄像头python opencv捕获视频时gstreamer严重错误 [英] gstreamer critical error when trying to capture video using webcam python opencv

问题描述

我正在尝试使用带有简单代码的opencv和python使用网络摄像头拍摄视频

i'm trying to take a video with webcam using opencv and python with a simple code

import numpy as np
import cv2

cap = cv2.VideoCapture(0)
print('cap.isOpened')
if cap.isOpened():
    print ('cap is opened')
    while(True):
        re,img=cap.read()
        cv2.imshow("video output", img)
        k = cv2.waitKey(10)&0xFF
        if k==27:
            break
cap.release()
cv2.destroyAllWindows()

如果我尝试播放现有视频(例如.mp4文件)，效果很好.但是当我尝试使用网络摄像头时出现错误

it's working fine if i try to play an existing video such as .mp4 file. but when i try using a webcam i got an error

GStreamer-CRITICAL **:gst_element_get_state:断言"GST_IS_ELEMENT(元素)"失败 cap.isOpened

GStreamer-CRITICAL **: gst_element_get_state: assertion 'GST_IS_ELEMENT (element)' failed cap.isOpened

有关更多信息，我将odroid xu4与ubuntu 16.04一起使用，网络摄像头我使用logitech c170(它在webcamtest和guvcview中正常工作)以为在奶酪和camorama上不起作用.

for more information i'm using odroid xu4 with ubuntu 16.04, webcam i use logitech c170 ( it work properly in webcamtest and using guvcview) thought it doesn't workon cheese and camorama.

需要对此的帮助..

推荐答案

以下解决方法具有合理的工作机会:

The following workaround has a reasonable chance of working:

cap = cv2.VideoCapture(0, cv2.CAP_V4L)

OpenCV 3中增加了选择后端的功能，请参见VideoCapture() 文档.

The ability to select backends was added in OpenCV 3, see the VideoCapture() docs.

该解决方法将OpenCV 3.4.4构建的后端切换到 V4L (来自默认GStreamer)，并在16.04机器上支持GStreamer.这是问题代码的输出以及export OPENCV_VIDEOIO_DEBUG=TRUE之后的解决方法:

The workaround switches the backend to V4L (from default GStreamer) for my OpenCV 3.4.4 build with GStreamer support on a 16.04 box. Here the output of the question's code with workaround after export OPENCV_VIDEOIO_DEBUG=TRUE:

[ WARN:0] VIDEOIO(cvCreateCameraCapture_V4L(index)): trying ...

[ WARN:0] VIDEOIO(cvCreateCameraCapture_V4L(index)): result=0x20b1470 ...

cap.isOpened
cap is opened

如果解决方法不适合您，则可以使用print(cv2.getBuildInformation())检查您的OpenCV版本是否支持V4L.这里是我构建的相关部分:

If the workaround does not work for you, you can check whether your OpenCV build supports V4L using print(cv2.getBuildInformation()). Here the relevant section for my build:

Video I/O:
  DC1394:                      YES (ver 2.2.4)
  FFMPEG:                      YES
    avcodec:                   YES (ver 56.60.100)
    avformat:                  YES (ver 56.40.101)
    avutil:                    YES (ver 54.31.100)
    swscale:                   YES (ver 3.1.101)
    avresample:                NO
  GStreamer:                  
    base:                      YES (ver 1.8.3)
    video:                     YES (ver 1.8.3)
    app:                       YES (ver 1.8.3)
    riff:                      YES (ver 1.8.3)
    pbutils:                   YES (ver 1.8.3)
  libv4l/libv4l2:              NO
  v4l/v4l2:                    linux/videodev2.h

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