This project utilizes Generative Adversarial Networks to colorize grayscale images.
The training and GPU resources were utilized primarily from Kaggle Notebooks and Google Colab environments.
The COCO Dataset is the one used for training and testing purposes.
The final model selected utilized a UNet as the Generator, and a Patch Discriminator model as the Discriminator.
The following is a sample output of the model after training. The top row shows input grayscale images, the middle row shows images colorized using the model, and the bottom row show the real colored version of the image.