colorization and interactive-deep-colorization
These are complementary tools where the second builds upon the first's neural network architecture—junyanz/interactive-deep-colorization extends richzhang/colorization's automatic approach by adding interactive user guidance, allowing users to refine colorization results with manual color hints rather than relying solely on the model's predictions.
About colorization
richzhang/colorization
Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.
This tool brings old black-and-white photos to life by automatically adding realistic colors. You provide a grayscale image, and it outputs a colorized version, making it useful for historians, archivists, or anyone looking to revitalize vintage imagery. It can also be used by digital artists or photographers seeking to quickly add color to line art or sketches.
About interactive-deep-colorization
junyanz/interactive-deep-colorization
Deep learning software for colorizing black and white images with a few clicks.
This software helps photographers, artists, and anyone with old black and white photos bring them to life with realistic color. You provide a grayscale image and, with a few clicks, add color hints to guide the AI, resulting in a beautifully colorized picture. It's designed for anyone looking to restore or creatively enhance monochrome images without extensive graphic design skills.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work