RGB Mask Preprocessing for Semantic Segmentation

This project describes how to streamline the preparation of RGB masks for training computer vision models in semantic segmentation tasks. It converts color-coded masks—where each class is represented by a specific RGB value—into a single-channel format (replicated across three channels) suitable for model training.