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Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 9 |
1 files changed, 5 insertions, 4 deletions
@@ -44,7 +44,7 @@ In CVPR 2017. ## Getting Started ### Installation - Install PyTorch and dependencies from http://pytorch.org/ -- Install python libraries [dominate](https://github.com/Knio/dominate). +- Install python libraries [dominate](https://github.com/Knio/dominate) and [visdom](https://github.com/facebookresearch/visdom) (optional). - Clone this repo: ```bash git clone https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix @@ -74,12 +74,12 @@ bash ./datasets/download_pix2pix_dataset.sh facades ``` - Train a model: ```bash -python train.py --dataroot ./datasets/facades --name facades_pix2pix --gpu_ids 0 --model pix2pix --align_data --which_direction BtoA +python train.py --dataroot ./datasets/facades --name facades_pix2pix --model pix2pix --which_model_netG unet_256 --align_data --which_direction BtoA ``` To view results as the model trains, check out the html file `./checkpoints/facades_pix2pix/web/index.html` - Test the model: ```bash -python test.py --dataroot ./datasets/facades --name facades_pix2pix --model pix2pix --phase val --align_data --which_direction BtoA +python test.py --dataroot ./datasets/facades --name facades_pix2pix --model pix2pix --which_model_netG unet_256 --align_data --which_direction BtoA ``` The test results will be saved to a html file here: `./results/facades_pix2pix/latest_val/index.html`. @@ -87,9 +87,10 @@ More example scripts can be found at `scripts` directory. ## Training/test Details - See `options/train_options.py` and `options/base_options.py` for training flags; see `optoins/test_options.py` and `options/base_options.py` for test flags. -- CPU/GPU: Set `--gpu_ids -1` to use CPU mode; set `--gpu_ids 0,1,2` for multi-GPU mode. +- CPU/GPU (default `--gpu_ids 0`): Set `--gpu_ids -1` to use CPU mode; set `--gpu_ids 0,1,2` for multi-GPU mode. - During training, you can visualize the result of current training. If you set `--display_id 0`, we will periodically save the training results to `[opt.checkpoints_dir]/[opt.name]/web/`. If you set `--display_id` > 0, the results will be shown on a local graphics web server launched by [visdom](https://github.com/facebookresearch/visdom). To do this, you should visdom installed. You need to invoke `python -m visdom.server` to start the server. The default server URL is `http://localhost:8097`. `display_id` corresponds to the window ID that is displayed on the `visdom` server. + ### CycleGAN Datasets Download the CycleGAN datasets using the following script: ```bash |