🎨 Colorize black and white images using OpenCV and deep learning, transforming grayscale photos into vibrant artworks instantly.

UNet model to colorize black & white images

A deep learning project that automatically colorizes anime sketches using a custom U-Net architecture. The model takes grayscale sketches and color scribbles as input to generate fully colorized anime characters.

Hierarchical image colorization model combining a Swin Transformer encoder with an EMA-based VQ-VAE bottleneck and a residual decoder. Learns discrete color representations and produces realistic, perceptually consistent colorizations

A Deep Learning based Vapoursynth filter for colorizing and restoring old images and video, based on DeOldify, DDColor, ColorMNet and DeepRemaster.

A PyTorch implementation of a Variational Autoencoder (VAE) with a U-Net architecture, self-attention, and perceptual loss to colorize grayscale images of birds.

📚 A collection of Deep Learning based Image Colorization and Video Colorization papers.

A mobile application that colorizes black and white images using AI, consisting of a Flask backend server and a React Native mobile app.

An Image Colorization automatically colorize grayscale pictures by learning from colored examples.

Automatic image colorization using Conditional GANs (ResNet-UNet + PatchGAN) trained on Tiny ImageNet.

An image/video colorization web application with authentication, user history and image editing posibilities

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

The Flask-Python web app utilizes a pre-trained image colorization model based on Caffe. It allows users to upload black and white images and applies the colorization model to automatically generate colored versions. The app leverages the power of deep learning to provide an intuitive and interactive way to add color to grayscale images with ease.

This is a Gray-Scale Image Colorizer that is based on a modified Pix2Pix structure

CS550 - Machine Learning : SAR Image Colorization

A Collection of Low Level Vision Research Groups

Developed for the "Neural Networks and Deep Learning" course, this project utilizes PyTorch for GAN implementation.

The smAIrtColorizer project is an advanced image and video colorization tool that leverages deep learning to transform historical grayscale media into vibrant, colorized outputs.

This is code to change the color of an image through Python, where you can specify the range of RGB pixels and indicate how much you want to increase or replace a particular value, ranging from 0 to 255.

Colorize black-and-white (grayscale) photos using a pre-trained deep learning model in OpenCV's DNN module.