pavelgonchar/colornet

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

3552 stars · 316 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Colornet is a Python/TensorFlow neural network implementation that colorizes grayscale images, based on VGG16 features and YUV color-channel prediction from automatic colorization research. It provides the model code and training examples, and has been demonstrated on tasks such as anime colorization.

Use cases

• colorize black and white photos with a neural network
• automatically add color to grayscale images
• restore color to old photographs using deep learning
• colorize anime frames
• train an automatic image colorization model
• study a VGG16-based colorization reference implementation

When to choose

• You want a compact, well-known reference implementation of automatic image colorization to study or adapt
• You want to reproduce or build on research like Automatic Colorization / VGG16 hypercolumn colorization
• You need a simple codebase to tweak for grayscale-to-color inference on images or anime frames

When to avoid

• You need actively maintained, production-grade colorization with modern pretrained models
• You need a clear license for commercial use - the repository has no license
• You want a one-click GUI tool rather than Python scripts and model weights

Facets

library · maturity abandoned

image-processing deep-learning machine-learning computer-vision image-processing deep-learning machine-learning artificial-intelligence python image-colorization grayscale-to-color neural-networks tensorflow vgg16 cnn yuv-color-space research-code anime-colorization gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="pavelgonchar/colornet")