Compressors#
Compressors is a library of containing flexible implementations of state-of-the-art compression systems.
Compressors is early in development, but aims to include:
Lossless compression systems, which can be used standalone or as part of a lossy compression system.
Energy compacting transforms like the DCT, MCDCT, Wavelet transforms, and Wavelet packet transform.
Differentiable soft quantizers for learned compression
DNN autoencoder building blocks for standard modalities such as stereo audio, and RGB image/video
DNN autoencoder building blocks for arbitrary signal shapes and dimensions, allowing users to easily create codecs for non-standard inputs (spatial audio arrays, hyperspectral images, 3d volumes, etc)
End-to-end codec pipelines that combine the above techniques
Conventional distortion metrics (e.g. PSNR, SSIM) for training and evaluation
DNN-based distortion metrics (e.g. LPIPS, DISTS) for training and evaluation
Tools for creating machine-oriented codecs, which can be optimized for downstream applications in addition to one or more distortion metrics
Package#
Python package:
pip install compressors