Awesome
Cool-chic (pronounced <span class="ipa">/kul สik/</span> as in French ๐ฅ๐ง๐ท) 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
- โ On par with VVC for image coding
- โ Upcoming improved Cool-chic video
- I/O format
- โ PPM for 8-bit RGB images, yuv420 8-bit and 10-bit
- โ yuv444
- โ Additional output precisions (12, 14 and 16-bit)
- โ Output PNG instead of PPM for the decoded images
- Decoder
- โ Fast C implementation
- โ Integer computation for the ARM
- โ Complete integerization
- โ Decrease memory footprint & faster decoding
Latest release: ๐ Cool-chic 3.3: An even faster decoder! ๐
- 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 | <span style="color:green" > - 1.9 % </span> | <span style="color:green"> - 3.4 % </span> | <span style="color:green" > - 16.4 % </span> | <span style="color:#f50" > + 4.5 % </span> | 1880 | 96 |
| clic20-pro-valid | <span style="color:green" > - 4.2 % </span> | <span style="color:green"> - 1.0 % </span> | <span style="color:green" > - 24.8 % </span> | <span style="color:green"> - 1.9 % </span> | 1907 | 364 |
| jvet class B | <span style="color:green" > - 7.2 % </span> | <span style="color:gray"> / </span> | <span style="color:green" > - 10.8 % </span> | <span style="color:#f50"> + 19.5 % </span> | 1803 | 260 |
Kodak
<div style="text-align: center;"> <!-- <img src="./results/image/kodak/rd.png" alt="Kodak rd results" width="800" style="centered"/> --> <img src="./docs/source/assets/kodak/rd.png" alt="Kodak rd results" width="750" style="centered"/> <img src="./docs/source/assets/kodak/perf_complexity.png" alt="Kodak performance complexity" width="750" style="centered"/> <!-- <img src="./results/image/jvet/rd.png" alt="CLIC rd results" width="800" style="centered"/> --> </div> <br/>CLIC20 Pro Valid
<div style="text-align: center;"> <!-- <img src="./results/image/kodak/rd.png" alt="Kodak rd results" width="800" style="centered"/> --> <img src="./docs/source/assets/clic20-pro-valid/rd.png" alt="CLIC20 rd results" width="750" style="centered"/> <img src="./docs/source/assets/clic20-pro-valid/perf_complexity.png" alt="CLIC20 performance complexity" width="750" style="centered"/> <!-- <img src="./results/image/jvet/rd.png" alt="CLIC rd results" width="800" style="centered"/> --> </div> <br/>JVET Class B
<div style="text-align: center;"> <!-- <img src="./results/image/kodak/rd.png" alt="Kodak rd results" width="800" style="centered"/> --> <img src="./docs/source/assets/jvet/rd_classB.png" alt="JVET class B rd results" width="750" style="centered"/> <img src="./docs/source/assets/jvet/perf_complexity_classB.png" alt="JVET class B performance complexity" width="750" style="centered"/> <!-- <img src="./results/image/jvet/rd.png" alt="CLIC rd results" width="800" style="centered"/> --> </div> <br/>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.
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