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| # Docker image with pytorch-CycleGAN-and-pix2pix | |
| We provide both Dockerfile and pre-built Docker container that can run this code repo. | |
| ## Prerequisite | |
| - Install [docker-ce](https://docs.docker.com/install/linux/docker-ce/ubuntu/) | |
| - Install [nvidia-docker](https://github.com/NVIDIA/nvidia-docker#quickstart) | |
| ## Running pre-built Dockerfile | |
| - Pull the pre-built docker file | |
| ```bash | |
| docker pull taesungp/pytorch-cyclegan-and-pix2pix | |
| ``` | |
| - Start an interactive docker session. `-p 8097:8097` option is needed if you want to run `visdom` server on the Docker container. | |
| ```bash | |
| nvidia-docker run -it -p 8097:8097 taesungp/pytorch-cyclegan-and-pix2pix | |
| ``` | |
| - Now you are in the Docker environment. Go to our code repo and start running things. | |
| ```bash | |
| cd /workspace/pytorch-CycleGAN-and-pix2pix | |
| bash datasets/download_pix2pix_dataset.sh facades | |
| python -m visdom.server & | |
| bash scripts/train_pix2pix.sh | |
| ``` | |
| ## Running with Dockerfile | |
| We also posted the [Dockerfile](Dockerfile). To generate the pre-built file, download the Dockerfile in this directory and run | |
| ```bash | |
| docker build -t [target_tag] . | |
| ``` | |
| in the directory that contains the Dockerfile. | |