Python ffmpegio package aims to bring the full capability of FFmpeg to read, write, probe, and manipulate multimedia data to Python. FFmpeg is an open-source cross-platform multimedia framework, which can handle most of the multimedia formats available today.
Note
Since v0.3.0, ffmpegio Python distribution package has been split into ffmpegio-core and ffmpegio to allow Numpy-independent installation.
Install the full ffmpegio package via pip:
pip install ffmpegioIf numpy.ndarray data I/O is not needed, instead use
pip install ffmpegio-core- Pure-Python light-weight package interacting with FFmpeg executable found in the system
- Transcode a media file to another in Python
- Read, write, filter, and create functions for audio, image, and video data
- Context-managing ffmpegio.open to perform stream read/write operations of video and audio
- Automatically detect and convert audio & video formats to and from numpy.ndarray properties
- Probe media file information
- Accepts all FFmpeg options including filter graphs
- Supports a user callback whenever FFmpeg updates its progress information file (see -progress FFmpeg option)
- ffconcat scripter to make the use of -f concat demuxer easier
- I/O device enumeration to eliminate the need to look up device names. (currently supports only: Windows DirectShow)
- More features to follow
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To import ffmpegio
>>> import ffmpegio- Transcoding
- Read Audio Files
- Read Image Files / Capture Video Frames
- Read Video Files
- Read Multiple Files or Streams
- Write Audio, Image, & Video Files
- Filter Audio, Image, & Video Data
- Stream I/O
- Device I/O Enumeration
- Progress Callback
- Filtergraph Builder
- Run FFmpeg and FFprobe Directly
>>> # transcode, overwrite output file if exists, showing the FFmpeg log
>>> ffmpegio.transcode('input.avi', 'output.mp4', overwrite=True, show_log=True)
>>> # 1-pass H.264 transcoding
>>> ffmpegio.transcode('input.avi', 'output.mkv', vcodec='libx264', show_log=True,
>>> preset='slow', crf=22, acodec='copy')
>>> # 2-pass H.264 transcoding
>>> ffmpegio.transcode('input.avi', 'output.mkv', two_pass=True, show_log=True,
>>> **{'c:v':'libx264', 'b:v':'2600k', 'c:a':'aac', 'b:a':'128k'})
>>> # concatenate videos using concat demuxer
>>> files = ['/video/video1.mkv','/video/video2.mkv']
>>> ffconcat = ffmpegio.FFConcat()
>>> ffconcat.add_files(files)
>>> with ffconcat: # generates temporary ffconcat file
>>> ffmpegio.transcode(ffconcat, 'output.mkv', f_in='concat', codec='copy', safe_in=0)>>> # read audio samples in its native sample format and return all channels
>>> fs, x = ffmpegio.audio.read('myaudio.wav')
>>> # fs: sampling rate in samples/second, x: [nsamples x nchannels] numpy array
>>> # read audio samples from 24.15 seconds to 63.2 seconds, pre-convert to mono in float data type
>>> fs, x = ffmpegio.audio.read('myaudio.flac', ss=24.15, to=63.2, sample_fmt='dbl', ac=1)
>>> # read filtered audio samples first 10 seconds
>>> # filter: equalizer which attenuate 10 dB at 1 kHz with a bandwidth of 200 Hz
>>> fs, x = ffmpegio.audio.read('myaudio.mp3', t=10.0, af='equalizer=f=1000:t=h:width=200:g=-10')>>> # list supported image extensions
>>> ffmpegio.caps.muxer_info('image2')['extensions']
['bmp', 'dpx', 'exr', 'jls', 'jpeg', 'jpg', 'ljpg', 'pam', 'pbm', 'pcx', 'pfm', 'pgm', 'pgmyuv',
'png', 'ppm', 'sgi', 'tga', 'tif', 'tiff', 'jp2', 'j2c', 'j2k', 'xwd', 'sun', 'ras', 'rs', 'im1',
'im8', 'im24', 'sunras', 'xbm', 'xface', 'pix', 'y']
>>> # read BMP image with auto-detected pixel format (rgb24, gray, rgba, or ya8)
>>> I = ffmpegio.image.read('myimage.bmp') # I: [height x width x ncomp] numpy array
>>> # read JPEG image, then convert to grayscale and proportionally scale so the width is 480 pixels
>>> I = ffmpegio.image.read('myimage.jpg', pix_fmt='grayscale', s='480x-1')
>>> # read PNG image with transparency, convert it to plain RGB by filling transparent pixels orange
>>> I = ffmpegio.image.read('myimage.png', pix_fmt='rgb24', fill_color='orange')
>>> # capture video frame at timestamp=4:25.3 and convert non-square pixels to square
>>> I = ffmpegio.image.read('myvideo.mpg', ss='4:25.3', square_pixels='upscale')
>>> # capture 5 video frames and tile them on 3x2 grid with 7px between them, and 2px of initial margin
>>> I = ffmpegio.image.read('myvideo.mp4', vf='tile=3x2:nb_frames=5:padding=7:margin=2')
>>> # create spectrogram of the audio input (must specify pix_fmt if input is audio)
>>> I = ffmpegio.image.read('myaudio.mp3', filter_complex='showspectrumpic=s=960x540', pix_fmt='rgb24')>>> # read 50 video frames at t=00:32:40 then convert to grayscale
>>> fs, F = ffmpegio.video.read('myvideo.mp4', ss='00:32:40', vframes=50, pix_fmt='gray')
>>> # fs: frame rate in frames/second, F: [nframes x height x width x ncomp] numpy array
>>> # get running spectrogram of audio input (must specify pix_fmt if input is audio)
>>> fs, F = ffmpegio.video.read('myvideo.mp4', pix_fmt='rgb24', filter_complex='showspectrum=s=1280x480')>>> # read both video and audio streams (1 ea)
>>> rates, data = ffmpegio.media.read('mymedia.mp4')
>>> # rates: dict of frame rate and sampling rate: keys="v:0" and "a:0"
>>> # data: dict of video frame array and audio sample array: keys="v:0" and "a:0"
>>> # combine video and audio files
>>> rates, data = ffmpegio.media.read('myvideo.mp4','myaudio.mp3')
>>> # get output of complex filtergraph (can take multiple inputs)
>>> expr = "[v:0]split=2[out0][l1];[l1]edgedetect[out1]"
>>> rates, data = ffmpegio.media.read('myvideo.mp4',filter_complex=expr,map=['[out0]','[out1]'])
>>> # rates: dict of frame rates: keys="v:0" and "v:1"
>>> # data: dict of video frame arrays: keys="v:0" and "v:1">>> # create a video file from a numpy array
>>> ffmpegio.video.write('myvideo.mp4', rate, F)
>>> # create an image file from a numpy array
>>> ffmpegio.image.write('myimage.png', F)
>>> # create an audio file from a numpy array
>>> ffmpegio.audio.write('myaudio.mp3', rate, x)>>> # Add fade-in and fade-out effects to audio data
>>> fs_out, y = ffmpegio.audio.filter('afade=t=in:ss=0:d=15,afade=t=out:st=875:d=25', fs_in, x)
>>> # Apply mirror effect to an image
>>> I_out = ffmpegio.image.filter('crop=iw/2:ih:0:0,split[left][tmp];[tmp]hflip[right];[left][right] hstack', I_in)
>>> # Add text at the center of the video frame
>>> filter = "drawtext=fontsize=30:fontfile=FreeSerif.ttf:text='hello world':x=(w-text_w)/2:y=(h-text_h)/2"
>>> fs_out, F_out = ffmpegio.video.filter(filter, fs_in, F_in)>>> # process video 100 frames at a time and save output as a new video
>>> # with the same frame rate
>>> with ffmpegio.open('myvideo.mp4', 'rv', blocksize=100) as fin,
>>> ffmpegio.open('myoutput.mp4', 'wv', rate=fin.rate) as fout:
>>> for frames in fin:
>>> fout.write(myprocess(frames))>>> # build complex filtergraph
>>> from ffmpegio import filtergraph as fgb
>>>
>>> v0 = "[0]" >> fgb.trim(start_frame=10, end_frame=20)
>>> v1 = "[0]" >> fgb.trim(start_frame=30, end_frame=40)
>>> v3 = "[1]" >> fgb.hflip()
>>> v2 = (v0 | v1) + fgb.concat(2)
>>> v5 = (v2|v3) + fgb.overlay(eof_action='repeat') + fgb.drawbox(50, 50, 120, 120, 'red', t=5)
>>> v5
<ffmpegio.filtergraph.Graph.Graph object at 0x2a4ef084bd0>
FFmpeg expression: "[0]trim=start_frame=10:end_frame=20[L0];[0]trim=start_frame=30:end_frame=40[L1];[L0][L1]concat=2[L2];[1]hflip[L3];[L2][L3]overlay=eof_action=repeat,drawbox=50:50:120:120:red:t=5"
Number of chains: 5
chain[0]: [0]trim=start_frame=10:end_frame=20[L0];
chain[1]: [0]trim=start_frame=30:end_frame=40[L1];
chain[2]: [L0][L1]concat=2[L2];
chain[3]: [1]hflip[L3];
chain[4]: [L2][L3]overlay=eof_action=repeat,drawbox=50:50:120:120:red:t=5[UNC0]
Available input pads (0):
Available output pads: (1): (4, 1, 0)>>> # record 5 minutes of audio from Windows microphone
>>> fs, x = ffmpegio.audio.read('a:0', f_in='dshow', sample_fmt='dbl', t=300)
>>> # capture Windows' webcam frame
>>> with ffmpegio.open('v:0', 'rv', f_in='dshow') as webcam,
>>> for frame in webcam:
>>> process_frame(frame)>>> import pprint
>>> # progress callback
>>> def progress(info, done):
>>> pprint(info) # bunch of stats
>>> if done:
>>> print('video decoding completed')
>>> else:
>>> return check_cancel_command(): # return True to kill immediately
>>> # can be used in any butch processing
>>> rate, F = ffmpegio.video.read('myvideo.mp4', progress=progress)
>>> # as well as for stream processing
>>> with ffmpegio.open('myvideo.mp4', 'rv', blocksize=100, progress=progress) as fin:
>>> for frames in fin:
>>> myprocess(frames)>>> from ffmpegio import ffmpeg, FFprobe, ffmpegprocess
>>> from subprocess import PIPE
>>> # call with options as a long string
>>> ffmpeg('-i input.avi -b:v 64k -bufsize 64k output.avi')
>>> # or call with list of options
>>> ffmpeg(['-i', 'input.avi' ,'-r', '24', 'output.avi'])
>>> # the same for ffprobe
>>> ffprobe('ffprobe -show_streams -select_streams a INPUT')
>>> # specify subprocess arguments to capture stdout
>>> out = ffprobe('ffprobe -of json -show_frames INPUT',
stdout=PIPE, universal_newlines=True).stdout
>>> # use ffmpegprocess to take advantage of ffmpegio's default behaviors
>>> out = ffmpegprocess.run({"inputs": [("input.avi", None)],
"outputs": [("out1.mp4", None),
("-", {"f": "rawvideo", "vframes": 1, "pix_fmt": "gray", "an": None})
}, capture_log=True)
>>> print(out.stderr) # print the captured FFmpeg logs (banner text omitted)
>>> b = out.stdout # width*height bytes of the first frame