InterDigitalInc/CompressAI

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1627 stars · 277 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

CompressAI is a PyTorch library and evaluation platform for end-to-end learned data compression research. It provides custom layers, entropy models, pre-trained image/video compression models, and benchmarking scripts against classical codecs.

Use cases

• train neural network models for learned image compression
• evaluate learned compression models against JPEG and other codecs
• encode and decode images with pre-trained compression models
• implement custom entropy models and latent codecs in PyTorch
• benchmark rate-distortion performance on datasets like Kodak
• port TensorFlow Compression functionality to PyTorch

When to choose

• you are researching deep learning based image or video compression
• you need pre-trained learned compression models with a model zoo
• you want a PyTorch alternative to TensorFlow Compression
• you need standardized evaluation scripts comparing against classical codecs

When to avoid

• you need general-purpose file or archive compression like zip or zstd
• you require production deployment on Windows or multi-GPU training at scale
• you need a non-PyTorch framework such as TensorFlow or JAX
• you need stable, long-term-supported APIs for production systems

Facets

library · maturity active

machine-learning deep-learning compression image-processing video-processing benchmarking deep-learning machine-learning image-processing python learned-compression pytorch neural-codecs image-compression video-compression entropy-models model-zoo video research linux macos gpu

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markdown · JSON · MCP: product_card(name="InterDigitalInc/CompressAI")