Skip to main content

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

Project description

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.

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 git@github.com: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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

parallel_video_io-0.1.6.tar.gz (117.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

parallel_video_io-0.1.6-py3-none-any.whl (17.0 kB view details)

Uploaded Python 3

File details

Details for the file parallel_video_io-0.1.6.tar.gz.

File metadata

  • Download URL: parallel_video_io-0.1.6.tar.gz
  • Upload date:
  • Size: 117.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for parallel_video_io-0.1.6.tar.gz
Algorithm Hash digest
SHA256 57fff507df70a0dbcf96bdc852dda8bf2e2c46825527a37f918fb76c98fbe47f
MD5 afc553dcf08811eaefd47bb18a3b12c2
BLAKE2b-256 e926deb52c4cc7081b795cae97e47e0eeb2aef5ec905ba99fc02c414e312dd3a

See more details on using hashes here.

Provenance

The following attestation bundles were made for parallel_video_io-0.1.6.tar.gz:

Publisher: publish.yml on sibocw/parallel-video-io

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file parallel_video_io-0.1.6-py3-none-any.whl.

File metadata

File hashes

Hashes for parallel_video_io-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 d4c3d3760cd9bed18dea9d7cd1abbaba622971d698c05efd05e4ad36bf893f04
MD5 5eb911f8a637c16875c267d17b67db83
BLAKE2b-256 be3670f3cf02b7f4fbb69a9e3a8aad7f52d734b3566ce0ff0e3afaddc273bdd2

See more details on using hashes here.

Provenance

The following attestation bundles were made for parallel_video_io-0.1.6-py3-none-any.whl:

Publisher: publish.yml on sibocw/parallel-video-io

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page