Image Video Colorization

This project was conceived as part of the "Sujets Spéciaux" course at UQAC under the supervision of Kevin Bouchard

Objective

The aim was to deploy a video image colorization application. To this end, I have taken up the GitHub project of Richard Zhang and his co-authors with models and papers presented at ECCV16 and SIGGRAPH17. Their solutions are based on convolutional neural networks.

The interface for the models was designed on Streamlit and deployed in a Space on Hugging Face.

The tutorial with all the design steps is available on my Medium blog.

The following features are available:

• Colorization of a batch of images.
• Colorization of MP4, MKV and AVI video files.
• Colorization of Youtube videos.

Interface

Running Locally

If you want to process longer videos and you're limited by the Hugging Face space memory's limits, you can run this app locally.

ffmpeg.exe is needed to run this app, you can install it using brew install ffmpeg and update the IMAGEIO_FFMPEG_EXE environment variable accordingly.

git clone https://github.com/Wazzabeee/image-video-colorization
cd image-video-colorization
pip install -r requirements.txt
streamlit run 01_📼_Upload_Video_File.py

Todos

Other models based on GANs will probably be implemented in the future if my application for a community grant to gain access to a GPU on Hugging Face is successful.

References

1. Richard Zhang, Phillip Isola et Alexei A Efros. « Colorful Image Colorization ». In : ECCV. 2016.
2. Richard Zhang et al. « Real-Time User-Guided Image Colorization with Learned Deep Priors ». In : ACM Transactions on Graphics (TOG) 9.4 (2017).