This repository provides a customizable implementation of the U-Net architecture in PyTorch, originally designed for biomedical image segmentation and adapted here for Kaggle’s Carvana Image Masking Challenge. It includes training pipelines with mixed precision support, integration with TensorBoard and Weights & Biases for experiment tracking, Docker deployment options, and pretrained model weights.