jantic/DeOldifyArchived
DeOldify
DeOldify is a deep learning system and a set of pre-trained computer vision models designed to apply realistic colors to grayscale photographs and video footage. It functions as a neural media restoration tool that uses trained networks to estimate original hues for black-and-white media and remove glitches and artifacts from aged images and film.
The project employs a NoGAN colorization technique that removes the GAN discriminator during training to prevent artifacts and avoid over-saturation of pixels. For cinematic sequences, it applies temporal frame consistency to maintain color stability and prevent flickering between consecutive frames.
The framework covers broad capability areas including deep learning image processing and media restoration. It utilizes generative adversarial networks, convolutional neural architectures, and automatic color labeling to synthesize realistic color values based on learned patterns from large datasets.