如何从Windows ffmpeg获取实时video帧和时间戳

search替代作为OpenCV不会提供实时相机stream(在Windows上) ,这是我的计算机视觉algorithm所需的时间戳,我发现ffmpeg和这个优秀的文章https://zulko.github.io/blog/2013/09 / 27 / read-and-write-video-frames-in-python-using-ffmpeg /解决scheme使用ffmpeg,访问其标准输出(stdout)stream。 我扩展它来读取标准错误(stderr)stream。

在windows上处理python代码,而我从ffmpeg stdout接收video帧,但stderr在为第一帧传送showinfo videofilter细节(时间戳)之后冻结。

我回忆起在ffmpeg论坛上看到,像showinfo这样的videofilter在redirect时被绕过。 这就是为什么下面的代码不能按预期工作?

预期:它应该写video帧到磁盘以及打印时间戳详细信息。
实际:它写入video文件,但没有得到时间戳(showinfo)的细节。

这是我尝试的代码:

import subprocess as sp import numpy import cv2 command = [ 'ffmpeg', '-i', 'e:\sample.wmv', '-pix_fmt', 'rgb24', '-vcodec', 'rawvideo', '-vf', 'showinfo', # video filter - showinfo will provide frame timestamps '-an','-sn', #-an, -sn disables audio and sub-title processing respectively '-f', 'image2pipe', '-'] # we need to output to a pipe pipe = sp.Popen(command, stdout = sp.PIPE, stderr = sp.PIPE) # TODO someone on ffmpeg forum said video filters (eg showinfo) are bypassed when stdout is redirected to pipes??? for i in range(10): raw_image = pipe.stdout.read(1280*720*3) img_info = pipe.stderr.read(244) # 244 characters is the current output of showinfo video filter print "showinfo output", img_info image1 = numpy.fromstring(raw_image, dtype='uint8') image2 = image1.reshape((720,1280,3)) # write video frame to file just to verify videoFrameName = 'Video_Frame{0}.png'.format(i) cv2.imwrite(videoFrameName,image2) # throw away the data in the pipe's buffer. pipe.stdout.flush() pipe.stderr.flush() 

那么如何仍然从ffmpeg帧时间戳到Python代码,以便它可以在我的计算机视觉algorithm中使用…

Solutions Collecting From Web of "如何从Windows ffmpeg获取实时video帧和时间戳"

您可以使用MoviePy :

 import moviepy.editor as mpy vid = mpy.VideoFileClip('e:\\sample.wmv') for timestamp, raw_img in vid.iter_frames(with_times=True): # do stuff 

重定向stderr在Python中工作。
所以不是这个pipe = sp.Popen(command, stdout = sp.PIPE, stderr = sp.PIPE)
做这个pipe = sp.Popen(command, stdout = sp.PIPE, stderr = sp.STDOUT)

我们可以通过添加异步调用来读取ffmpeg的标准流(stdout和stderr)来避免重定向。 这将避免视频帧和时间戳的混合,从而避免错误的分离。 所以修改原来的代码来使用threading模块看起来像这样:

 # Python script to read video frames and timestamps using ffmpeg import subprocess as sp import threading import matplotlib.pyplot as plt import numpy import cv2 ffmpeg_command = [ 'ffmpeg', '-nostats', # do not print extra statistics #'-debug_ts', # -debug_ts could provide timestamps avoiding showinfo filter (-vcodec copy). Need to check by providing expected fps TODO '-r', '30', # output 30 frames per second '-i', 'e:\sample.wmv', '-an','-sn', #-an, -sn disables audio and sub-title processing respectively '-pix_fmt', 'rgb24', '-vcodec', 'rawvideo', #'-vcodec', 'copy', # very fast!, direct copy - Note: No Filters, No Decode/Encode, no quality loss #'-vframes', '20', # process n video frames only. For Debugging '-vf', 'showinfo', # showinfo videofilter provides frame timestamps as pts_time '-f', 'image2pipe', 'pipe:1' ] # outputs to stdout pipe. can also use '-' which is redirected to pipe # seperate method to read images on stdout asynchronousously def AppendProcStdout(proc, nbytes, AppendList): while proc.poll() is None: # continue while the process is alive AppendList.append(proc.stdout.read(nbytes)) # read image bytes at a time # seperate method to read image info. on stderr asynchronousously def AppendProcStderr(proc, AppendList): while proc.poll() is None: # continue while the process is alive try: AppendList.append(proc.stderr.next()) # read stderr until empty except StopIteration: continue # ignore stderr empty exception and continue if __name__ == '__main__': # run ffmpeg command pipe = sp.Popen(ffmpeg_command, stdout=sp.PIPE, stderr=sp.PIPE) # 2 threads to talk with ffmpeg stdout and stderr pipes framesList = []; frameDetailsList = [] appendFramesThread = threading.Thread(group=None, target=AppendProcStdout, name='FramesThread', args=(pipe, 1280*720*3, framesList), kwargs=None, verbose=None) # assuming rgb video frame with size 1280*720 appendInfoThread = threading.Thread(group=None, target=AppendProcStderr, name='InfoThread', args=(pipe, frameDetailsList), kwargs=None, verbose=None) # start threads to capture ffmpeg frames and info. appendFramesThread.start() appendInfoThread.start() # wait for few seconds and close - simulating cancel import time; time.sleep(2) pipe.terminate() # check if threads finished and close appendFramesThread.join() appendInfoThread.join() # save an image per 30 frames to disk savedList = [] for cnt,raw_image in enumerate(framesList): if (cnt%30 != 0): continue image1 = numpy.fromstring(raw_image, dtype='uint8') image2 = image1.reshape((720,1280,3)) # assuming rgb image with size 1280 X 720 # write video frame to file just to verify videoFrameName = 'video_frame{0}.png'.format(cnt) cv2.imwrite(videoFrameName,image2) savedList.append('{} {}'.format(videoFrameName, image2.shape)) print '### Results ###' print 'Images captured: ({}) \nImages saved to disk:{}\n'.format(len(framesList), savedList) # framesList contains all the video frames got from the ffmpeg print 'Images info captured: \n', ''.join(frameDetailsList) # this contains all the timestamp details got from the ffmpeg showinfo videofilter and some initial noise text which can be easily removed while parsing