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TorchCodec is a Python package with a goal to provide useful and fast APIs to decode video frames to PyTorch Tensors.
Note
Here's a condensed summary of what you can do with TorchCodec. For a more detailed example, check out our documentation!
from torchcodec.decoders import SimpleVideoDecoder
decoder = SimpleVideoDecoder("path/to/video.mp4")
decoder.metadata
# VideoStreamMetadata:
# num_frames: 250
# duration_seconds: 10.0
# bit_rate: 31315.0
# codec: h264
# average_fps: 25.0
# ... (truncated output)
len(decoder) # == decoder.metadata.num_frames!
# 250
decoder.metadata.average_fps # Note: instantaneous fps can be higher or lower
# 25.0
# Simple Indexing API
decoder[0] # uint8 tensor of shape [C, H, W]
decoder[0 : -1 : 20] # uint8 stacked tensor of shape [N, C, H, W]
# Iterate over frames:
for frame in decoder:
pass
# Indexing, with PTS and duration info
decoder.get_frame_at(len(decoder) - 1)
# Frame:
# data (shape): torch.Size([3, 400, 640])
# pts_seconds: 9.960000038146973
# duration_seconds: 0.03999999910593033
decoder.get_frames_at(start=10, stop=30, step=5)
# FrameBatch:
# data (shape): torch.Size([4, 3, 400, 640])
# pts_seconds: tensor([0.4000, 0.6000, 0.8000, 1.0000])
# duration_seconds: tensor([0.0400, 0.0400, 0.0400, 0.0400])
# Time-based indexing with PTS and duration info
decoder.get_frame_displayed_at(pts_seconds=2)
# Frame:
# data (shape): torch.Size([3, 400, 640])
# pts_seconds: 2.0
# duration_seconds: 0.03999999910593033
You can use the following snippet to generate a video with FFmpeg and tryout TorchCodec:
fontfile=/usr/share/fonts/dejavu-sans-mono-fonts/DejaVuSansMono-Bold.ttf
output_video_file=/tmp/output_video.mp4
ffmpeg -f lavfi -i \
color=size=640x400:duration=10:rate=25:color=blue \
-vf "drawtext=fontfile=${fontfile}:fontsize=30:fontcolor=white:x=(w-text_w)/2:y=(h-text_h)/2:text='Frame %{frame_num}'" \
${output_video_file}
Note: if you're on MacOS, you'll need to build from source. Instructions below assume you're on Linux.
First install the latest stable version of PyTorch following the official instructions.
Then:
pip install torchcodec
You will also need FFmpeg installed on your system, and TorchCodec decoding capabilities are determined by your underlying FFmpeg installation. There are different options to install FFmpeg e.g.:
conda install ffmpeg
# or
conda install ffmpeg -c conda-forge
Your Linux distribution probably comes with FFmpeg pre-installed as well. TorchCodec supports all major FFmpeg version in [4, 7].
We are actively working on the following features:
- Ship wheels for MacOS, so
that MacOS users can
pip install torchcodec
. For now this is only supported on Linux, but MacOS users can build from source. - GPU decoding
- Audio decoding
Let us know if you have any feature requests by opening an issue!
We welcome contributions to TorchCodec! Please see our contributing guide for more details.
TorchCodec is released under the BSD 3 license.