Simple Python package for colorized terminal output

Grayscale image colorization using a U-Net CNN (with VGG-19) and perceptual loss.

Colorization using ab channel averaging during training.

PyTorch implementation of a modified cascaded refinement network for the colorization of grayscale images

Simple, yet powerful tool to colorize terminal output

Multimedia&Lab lecture Hint based Image Colorization Challenge from Prof. Yong Ju Jung in Gachon Univ

Colorizing grayscale images with python and deep learning.

Image Colorization is a service to colorize the gray scale images using Generative AI.

Image colorizer built with machine learning

Comprehensive AI-powered solution for manga and comic translation and colorization. Utilizes PaddleOCR, DeepL API, LAMA-based text removal, and ResNeXt-based colorization for high accuracy and quality.

Sistema de cores.

A DL-based super-resolution and colorization tool built with PyTorch.

This project implements automatic black-and-white image colorization using deep learning models. The models used are: ECCV16: "Colorful Image Colorization" SIGGRAPH17: "Real-Time User-Guided Image Colorization"

Unofficial implementation of "The Surprising Effectiveness of Linear Unsupervised Image-to-Image Translation"

Colorful Bias is a longitudinal benchmarking of algorithmic colorization of images containing human skin tones.

🏞 Colorizing grayscale photographs.

Rest API를 활용한 딥러닝 모델(Reference-Based-Colorization) 서빙

U-Net Model conditioned with MobileNet features for Grayscale -> Color mapping

🎨 Automatic Image Colorization using TensorFlow based on Residual Encoder Network

This is the implementation of the "Comicolorization: Semi-automatic Manga Colorization"