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CONDITIONAL GAN: pix2pixHD

Project

Pytorch implementation of our 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.

Image-to-image translation at 2k/1k resolution

  • Our src images and preprocess image

- Image-to-image translation results

Prerequisites

  • Linux or macOS
  • Python 2 or 3
  • NVIDIA GPU (11G memory or larger) + CUDA cuDNN

Getting Started

Installation

pip install dominate

## pip install ...
pip install dominate -i http://pypi.douban.com/simple --trusted-host pypi.douban.com --user
  • Clone this repo:
git clone https://github.com/NVIDIA/pix2pixHD
cd pix2pixHD

Dataset

  • We use the BONC dataset.

Training

  • Train a model
  • python train.py --label_nc 0 --no_instance --resize_or_crop 1088 --gpu_ids 0,1 --no_flip --tf_log
  • python test.py --label_nc 0 --no_instance --resize_or_crop none --name bp_ab --resize_or_crop none --gpu_ids 0,1 --no_flip