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.
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')