如何阅读scikit-image要处理的mp4视频? [英] How to read mp4 video to be processed by scikit-image?

问题描述

我想对mp4视频，h264编码的帧应用scikit-image函数(特别是模板匹配函数match_template).对我的应用程序来说，跟踪每个帧的时间很重要，但是我知道帧速率，因此可以轻松地从帧号进行计算.

I would like to apply a scikit-image function (specifically the template matching function match_template) to the frames of a mp4 video, h264 encoding. It's important for my application to track the time of each frame, but I know the framerate so I can easily calculate from the frame number.

请注意，我使用的资源较少，并且我希望保持依赖性尽可能的小:无论如何都需要numpy，并且由于我打算使用scikit-image，因此我避免导入(并进行编译)openCV只是为了阅读视频.

Please note that I'm running on low resources, and I would like to keep dependencies as slim as possible: numpy is needed anyway, and since I'm planning to use scikit-image, I would avoid importing (and compiling) openCV just to read the video.

我在此页面的底部看到，scikit-image可以无缝处理存储的视频作为numpy数组，因此获得该数组将是理想的.

I see at the bottom of this page that scikit-image can seamleassly process video stored as a numpy array, obtaining that would thus be ideal.

推荐答案

Imageio python包应该可以完成您的操作想.这是使用此软件包的python代码段:

Imageio python package should do what you want. Here is a python snippet using this package:

import pylab
import imageio
filename = '/tmp/file.mp4'
vid = imageio.get_reader(filename,  'ffmpeg')
nums = [10, 287]
for num in nums:
    image = vid.get_data(num)
    fig = pylab.figure()
    fig.suptitle('image #{}'.format(num), fontsize=20)
    pylab.imshow(image)
pylab.show()

您还可以直接遍历文件中的图像(请参阅文档):

You can also directly iterate over the images in the file (see the documentation ):

for i, im in enumerate(vid):
    print('Mean of frame %i is %1.1f' % (i, im.mean()))

要安装imageio，可以使用pip:

To install imageio you can use pip:

pip install imageio

另一种解决方案是使用 moviepy (使用类似的代码来读取视频)，但我认为imageio更轻巧，可以完成工作.

An other solution would be to use moviepy (which use a similar code to read video), but I think imageio is lighter and does the job.

回复第一条评论

为了检查整个文件的标称帧频是否相同，您可以计算迭代器中的帧数:

In order to check if the nominal frame rate is the same over the whole file, you can count the number of frame in the iterator:

count = 0
try:
    for _ in vid:
        count += 1
except RuntimeError:
    print('something went wront in iterating, maybee wrong fps number')
finally:
    print('number of frames counted {}, number of frames in metada {}'.format(count, vid.get_meta_data()['nframes']))


In [10]: something went wront in iterating, maybee wrong fps number
         number of frames counted 454, number of frames in metada 461

为了显示每帧的时间戳:

In order to display the timestamp of each frame:

try:
    for num, image in enumerate(vid.iter_data()):
        if num % int(vid._meta['fps']):
            continue
        else:
            fig = pylab.figure()
            pylab.imshow(image)
            timestamp = float(num)/ vid.get_meta_data()['fps']
            print(timestamp)
            fig.suptitle('image #{}, timestamp={}'.format(num, timestamp), fontsize=20)
            pylab.show()
except RuntimeError:
    print('something went wrong')

这篇关于如何阅读scikit-image要处理的mp4视频?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！