GitHub repository: umd-fire-coml/2021-Image-Colorization
Primary language: Jupyter Notebook
Description: This image colorization model takes an input image, convert it to greyscale, then creates a realistic colorization of the image based off of the trained model. The model architecture utilizes the YCbCr colorspace in order to colorize the image, because Y is equivalent to grayscale, so the model has to predict only the Cb and Cr channels. The model uses a series of convolutional layers to transform the 256x256 input into the 256x256x2 output. The model was trained using the places365 dataset as ground truth images for the colorization, and a greyscale version of the places365 dataset as training images.