facebookresearch/pytorchvideo

Health v2 · maintenance only

Adoption not part of the score

3566 stars · 425 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

PyTorchVideo is a deep learning library from Facebook Research focused on video understanding research, built on PyTorch. It provides reusable, modular components including pretrained video models (model zoo), video datasets, data loaders, and video-specific transforms, with support for accelerated inference on hardware including mobile devices.

Use cases

• classify actions in videos with pretrained models
• train a video classification model in PyTorch
• run video action detection with SlowFast
• load Kinetics-400 pretrained video models via Torch Hub
• decode and preprocess video clips for deep learning
• deploy video models for accelerated mobile inference
• research video understanding architectures

When to choose

• you need state-of-the-art pretrained video models like SlowFast or X3D
• you want PyTorch-ecosystem components for video research
• you need efficient video-specific data loading and transforms
• you want reproducible benchmarks for video understanding

When to avoid

• you need general-purpose video editing or encoding rather than ML
• you work with images only instead of video
• you need a non-PyTorch framework like TensorFlow or JAX
• you need actively developed features - the project sees infrequent releases

Facets

library · maturity maintenance

machine-learning deep-learning video-processing data-science deep-learning computer-vision machine-learning python cross-platform pytorch video-understanding model-zoo action-recognition video-classification pretrained-models torch-hub video research gpu mobile

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