Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

A PyTorch implementation of Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

Table of Contents

• Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks
  • Table of Contents
  • Prerequisites
  • Installation
  • Training
  • Logging In Tensorboard
  • Contribute

Prerequisites

• Python 3 (tested with Python 3.7)
• PyTorch (tested with torch v1.3 and torchvision v0.4)
• Python packages as specified in requirements.txt

Installation

$ git clone https://github.com/RashedDoha/Unsupervised-Pixel-Level-Domain-Adaptation.git
$ cd Unsupervised-Pixel-Level-Domain-Adaptation/
$ sudo pip3 install -r requirements.txt

Training

Training on CPU

python train.py

To train on a CUDA enabled GPU, use the --cuda flag: python train.py --cuda

Logging In Tensorboard

To launch tensorboard make sure to set the --logdir flag with the same directory as in the command line flag for train.py --tensorboard_logs. (default: logs)

Contribute

To contribute to the project, please refer to the contribution guidelines