pix2pixHD

Overview

Project | YouTube | Paper

Pix2PixHD is a Pytorch implementation of a deep learning-based method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translation. It can be used for turning semantic label maps into photo-realistic images or synthesizing portraits from face label maps.

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs in CVPR 2018.

The pix2pixHD model is available for commercial use via a Berkeley Software Distribution (BSD) License.

Datasets

• We use the Cityscapes dataset. To train a model on the full dataset, please download it from the official website (registration required). After downloading, please put it under the datasets folder in the same way the example images are provided.

Metadata

• Linux or macOS
• Python 2 or 3
• NVIDIA GPU (11G memory or larger) + CUDA cuDNN
• Install PyTorch and dependencies from the NGC Container Registry
• Install python libraries dominate