How to read mp4 video to be processed by scikit-im

Question

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.

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.

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.

Answer 1

An easy way to read video in python is using skviode. A single line code can help to read entire video.

import skvideo.io  
videodata = skvideo.io.vread("video_file_name")  
print(videodata.shape)

http://mllearners.blogspot.in/2018/01/scikit-video-skvideo-tutorial-for.html

Answer 2

You could use scikit-video, like this:

from skvideo.io import VideoCapture

cap = VideoCapture(filename)
cap.open()

while True:
    retval, image = cap.read()
    # image is a numpy array containing the next frame
    # do something with image here
    if not retval:
        break

This uses avconv or ffmpeg under the hood. The performance is quite good, with a small overhead to move the data into python compared to just decoding the video in avconv.

The advantage of scikit-video is that the API is exactly the same as the video reading/writing API of OpenCV; just replace cv2.VideoCapture with skvideo.io.VideoCapture.

Answer 3

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()

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()))

To install imageio you can use pip:

pip install imageio

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.

---

response to first comment

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

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')