🏎️ 🔥 Cool-chic 3.2: Go fast boiii 🔥 🏎️

Cool-chic (pronounced /kul ʃik/ as in French 🥖🧀🍷) is is a low-complexity neural image codec based on overfitting. Image coding performance are on par with VVC for 2000 multiplications per decoded pixels.

Check out the Cool-chic documentation page!

Notable improvements

• Fast CPU-only decoder as proposed in Overfitted image coding at reduced complexity, Blard et al.
  • Decode a 512x768 image in 100 ms
  • C API for binary arithmetic coding
• Encoding time reduced by 35%
• Rate reduction of 5% compared to Cool-chic 3.1

Check-out the release history to see previous versions of Cool-chic.

Setup

More details are available on the Cool-chic page

# We need to get these packages to compile the C API and bind it to python.
sudo add-apt-repository -y ppa:deadsnakes/ppa && sudo apt update
sudo apt install -y build-essential python3.10-dev pip
git clone https://github.com/Orange-OpenSource/Cool-Chic.git && cd Cool-Chic

# Install create and activate virtual env
python3.10 -m pip install virtualenv
python3.10 -m virtualenv venv && source venv/bin/activate

# Install Cool-chic
pip install -e .

# Sanity check
python -m test.sanity_check

You're good to go!

Performance

The Cool-chic page provides comprehensive rate-distortion results and compressed bitstreams allowing to reproduce the results inside the results/ directory.

Kodak

More results to come in the following days!

Thanks

Special thanks go to Hyunjik Kim, Matthias Bauer, Lucas Theis, Jonathan Richard Schwarz and Emilien Dupont for their great work enhancing Cool-chic: C3: High-performance and low-complexity neural compression from a single image or video, Kim et al.