pix2pixHD

Why we included this project

Pix2PixHD is the reference PyTorch implementation of the CVPR 2018 method for high-resolution image-to-image translation, turning semantic label maps or face parsing masks into photorealistic output at up to 2048x1024 pixels. That resolution is exactly where naive GANs start to blur or collapse, so teams working on synthetic data generation or visual effects get a real training and inference pipeline rather than a toy. The codebase is compact and well documented, with scripts for single and multi GPU training and mixed precision support, and it adapts to your own datasets instead of only the bundled Cityscapes examples. It does expect a serious NVIDIA GPU with at least 11 GB of memory, so budget for hardware before planning high-resolution experiments.