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Karl Kroening
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README
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README
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# ffmpeg-python: Python bindings for FFmpeg with complex filtering support
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## Overview
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There are tons of Python FFmpeg wrappers out there but they seem to lack complex filter support. `ffmpeg-python` works well for simple as well as complex signal graphs.
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## Quickstart
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```
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import ffmpeg
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ffmpeg \
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.file_input('input.mp4') \
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.file_output('output.mp4') \
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.run()
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```
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Or if you prefer a non-fluent interface:
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```
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import ffmpeg
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in = ffmpeg.file_input('input.mp4')
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out = ffmpeg.file_output(in)
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ffmpeg.run(out)
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```
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## Complex filter graphs
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FFmpeg is extremely powerful, but it's command-line interface gets really complicated really quickly - especially when working with signal graphs and doing anything more than trivial.
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Take for example a signal graph that looks like this:
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<img src="https://raw.githubusercontent.com/kkroening/ffmpeg-python/master/doc/graph1.png" alt="Signal graph" align="middle" width="50%" />
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The corresponding command-line arguments are pretty gnarly:
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```
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ffmpeg -i input.mp4 \
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-filter_complex "\
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[0]trim=start_frame=10:end_frame=20,setpts=PTS-STARTPTS[v0];\
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[0]trim=start_frame=30:end_frame=40,setpts=PTS-STARTPTS[v1];\
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[v0][v1]concat=n=2[v2];\
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[1]hflip[v3];\
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[v2][v3]overlay=eof_action=repeat[v4];\
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[v4]drawbox=50:50:120:120:red:t=5[v5]"\
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-map [v5] output.mp4
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```
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Maybe this looks great to you, but if you haven't worked with FFmpeg before, it probably looks pretty alien.
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If you're like me and find Python to be powerful and readable, it's easy with `ffmpeg-python`:
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```
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import ffmpeg
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in_file = ffmpeg.file_input(TEST_INPUT_FILE)
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overlay_file = ffmpeg.file_input(TEST_OVERLAY_FILE)
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ffmpeg \
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.concat(
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in_file.trim(10, 20),
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in_file.trim(30, 40),
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) \
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.overlay(overlay_file.hflip()) \
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.drawbox(50, 50, 120, 120, color='red', thickness=5) \
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.file_output(TEST_OUTPUT_FILE) \
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.run()
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```
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`ffmpeg-python` takes care of running `ffmpeg` with the command-line arguments that correspond to the above filter diagram, and it's easy to what's going on and make changes as needed.
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Real-world signal graphs can get a heck of a lot more complex, but `ffmpeg-python` handles them with ease.
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69
README.md
Normal file
69
README.md
Normal file
@ -0,0 +1,69 @@
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# ffmpeg-python: Python bindings for FFmpeg with complex filtering support
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## Overview
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There are tons of Python FFmpeg wrappers out there but they seem to lack complex filter support. `ffmpeg-python` works well for simple as well as complex signal graphs.
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## Quickstart
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Flip a video horizontally:
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```
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import ffmpeg
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ffmpeg \
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.file_input('input.mp4') \
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.hflip() \
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.file_output('output.mp4') \
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.run()
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```
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Or if you prefer a non-fluent interface:
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```
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import ffmpeg
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in = ffmpeg.file_input('input.mp4')
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flipped = ffmpeg.hflip(in)
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out = ffmpeg.file_output(flipped)
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ffmpeg.run(out)
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```
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## Complex filter graphs
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FFmpeg is extremely powerful, but it's command-line interface gets really complicated really quickly - especially when working with signal graphs and doing anything more than trivial.
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|
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Take for example a signal graph that looks like this:
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<img src="https://raw.githubusercontent.com/kkroening/ffmpeg-python/master/doc/graph1.png" alt="Signal graph" align="middle" width="50%" />
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The corresponding command-line arguments are pretty gnarly:
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```
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ffmpeg -i input.mp4 \
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-filter_complex "\
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[0]trim=start_frame=10:end_frame=20,setpts=PTS-STARTPTS[v0];\
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[0]trim=start_frame=30:end_frame=40,setpts=PTS-STARTPTS[v1];\
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[v0][v1]concat=n=2[v2];\
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[1]hflip[v3];\
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[v2][v3]overlay=eof_action=repeat[v4];\
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[v4]drawbox=50:50:120:120:red:t=5[v5]"\
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-map [v5] output.mp4
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```
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Maybe this looks great to you, but if you haven't worked with FFmpeg before, it probably looks pretty alien.
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If you're like me and find Python to be powerful and readable, it's easy with `ffmpeg-python`:
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```
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import ffmpeg
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in_file = ffmpeg.file_input(TEST_INPUT_FILE)
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overlay_file = ffmpeg.file_input(TEST_OVERLAY_FILE)
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ffmpeg \
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.concat(
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in_file.trim(10, 20),
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in_file.trim(30, 40),
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) \
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.overlay(overlay_file.hflip()) \
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.drawbox(50, 50, 120, 120, color='red', thickness=5) \
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.file_output(TEST_OUTPUT_FILE) \
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.run()
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```
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`ffmpeg-python` takes care of running `ffmpeg` with the command-line arguments that correspond to the above filter diagram, and it's easy to what's going on and make changes as needed.
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Real-world signal graphs can get a heck of a lot more complex, but `ffmpeg-python` handles them with ease.
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