Motorcycle GAN

Based on CycleGAN codebase by Jun-Yan Zhu and Taesung Park (Link to original repo).

More project information soon.

You may find useful information in training/test tips and frequently asked questions.

Prerequisites

• Linux or macOS
• Python 2 or 3
• CPU or NVIDIA GPU + CUDA CuDNN

Getting Started

Installation

• Clone this repo:

git clone https://github.com/GauthamN/MotorcycleGAN.git

• Install PyTorch 0.4+ and torchvision from http://pytorch.org and other dependencies (e.g., visdom and dominate). You can install all the dependencies by

pip install -r requirements.txt

• For Conda users, we include a script ./scripts/conda_deps.sh to install PyTorch and other libraries.

CycleGAN train/test

• Download a CycleGAN dataset (e.g. maps):

bash ./datasets/download_cyclegan_dataset.sh maps

• Train a model:

#!./scripts/train_cyclegan.sh
python train.py --dataroot ./datasets/maps --name maps_cyclegan --model cycle_gan

• To view training results and loss plots, run python -m visdom.server and click the URL http://localhost:8097. To see more intermediate results, check out ./checkpoints/maps_cyclegan/web/index.html.

• Test the model:

#!./scripts/test_cyclegan.sh
python test.py --dataroot ./datasets/maps --name maps_cyclegan --model cycle_gan

• The test results will be saved to a html file here: ./results/maps_cyclegan/latest_test/index.html.