parallel-video-io 0.1.9

Tools for reading and writing videos, and loading them efficiently with PyTorch.

Parallel Video IO

The Parallel Video IO (PVIO) package is motivated by the following problems that I kept having:

1. I could never remember the ffmpeg and ffprob commands for simple tasks, so I have to Google them every time.
2. Precise random seek in videos (for scientific use) is not so trivial.
3. I just want some simple dataloader that works for ML training and inference.

After finding myself writing the same thing over and over again for different projects, I wrote this package with the following features:

1. Read frames from videos (random access or sequential) using imageio/FFmpeg.
2. Write sequences of NumPy frames to H.264 MP4 files with sensible defaults.
3. PyTorch-compatible VideoCollectionDataset and VideoCollectionDataLoader that stream frames from many videos in parallel across worker processes.
   • SimpleVideoCollectionLoader provides a convenience API that combines dataset and dataloader creation in one call.
4. A small pvio command-line tool (an ffmpeg-lite helper): pvio encode combines a directory or list of image files into an H.264 MP4 (with --mode, --quality, and --preset flags), and pvio info prints a video's frame count, frame size, and FPS.

GPU acceleration is automatic. On a machine with a CUDA GPU, decoding uses the GPU (TorchCodec/NVDEC, with frame-accurate seeking preserved) and writing uses the GPU encoder (FFmpeg/NVENC at a visually-lossless setting); both fall back to the CPU when no GPU is available. SimpleVideoCollectionLoader runs in the main process when decoding on the GPU (CUDA cannot be used in forked workers). Pass device="cpu" (loader/EncodedVideo) or mode="cpu" (write_frames_to_video) to opt out.

Linux only. macOS and Windows are not currently supported.

Installation, code examples, and documentation

See the documentation site.

Development

Clone and install with the dev dependencies:

git clone [e-mail]:sibocw/parallel-video-io.git
cd parallel-video-io
uv sync --extra dev

Run the test suite:

pytest tests

Build and preview the documentation site locally:

uv run mkdocs serve