Trained a simple CNN model to colorize grayscale images. The model is trained on the Lab color space, where it learns to predict the color channels (a and b) given only the grayscale (L) channel.
- Data Preprocessing: Converts images from RGB to Lab color space and normalizes input channels for training.
- Model Architecture: Uses an encoder-decoder CNN architecture to learn colorization.