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Decode provided bitstreams · Compression performance

Cool-chic (pronounced /kul ʃik/ as in French 🥖🧀🍷) is is a low-complexity neural image codec based on overfitting. It offers image coding performance competitive with H.266/VVC for 2000 multiplications per decoded pixel.

Current & future features

Coding performance
- ✅ On par with VVC for image coding
- ❌ Upcoming improved Cool-chic video
I/O format
- ✅ PPM for 8-bit RGB images, yuv420 8-bit and 10-bit
- ❌ yuv444
- ❌ Additional output precisions (12, 14 and 16-bit)
- ❌ Output PNG instead of PPM for the decoded images
Decoder
- ✅ Fast C implementation
- ✅ Integer computation for the ARM
- ✅ Complete integerization
- ✅ Decrease memory footprint & faster decoding

Latest release: 🚀 Cool-chic 3.3: An even faster decoder! 🚀

Make the CPU-only decoder even faster.
- Decode a 720p image in 100 ms, 2x faster than Cool-chic 3.2
- Full integerization of the decoder for replicability
- Reduce decoder memory footprint
- Optimized implementation of 3x3 convolutions & fusion of successive 1x1 convolutions

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.

Dataset	Vs. Cool-chic 3.1	Vs. C3, Kim et al.	Vs. HEVC (HM 16.20)	Vs. VVC (VTM 19.1)	Avg decoder MAC / pixel	Avg decoding time [ms]
kodak	- 1.9 %	- 3.4 %	- 16.4 %	+ 4.5 %	1880	96
clic20-pro-valid	- 4.2 %	- 1.0 %	- 24.8 %	- 1.9 %	1907	364
jvet class B	- 7.2 %	/	- 10.8 %	+ 19.5 %	1803	260

Kodak

CLIC20 Pro Valid

JVET Class B

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.