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This repository is an implementation of our IGARSS2018 paper "Image Translation Between Sar and Optical Imagery with Generative Adversarial Nets".
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configs
datasets
dis_models
evaluations
gen_models
source
supp_info
updaters
.gitignore
README.md
__init__.py
requirements.txt
train_mn_pix2pix.py
train_pix2pix.py

README.md

Image Translation Between Sar and Optical Imagery with Generative Adversarial Nets

This repository is an implementation of "Image Translation Between Sar and Optical Imagery with Generative Adversarial Nets".

Setup

Install required python libraries

pip install -r requirements.txt

Download Palsar-Aster dataset (WIP)

Training examples

You need set each parameters in a config file.

CUDA_VISIBLE_DEVICES=0 python train_pix2pix.py --config_path configs/config_pix2pix.yml --results_dir results/pix2pix

If you want to resume the training from snapshot, use --snapshot option.

  • pretrained model (WIP)

Evaluation examples

CUDA_VISIBLE_DEVICES=0 python evaluations/test.py --results_dir results/test_pix2pix --config_path results/pix2pix/config_pix2pix.yml --gen_model results/pix2pix/Generator_<iterations>.npz

License

Academic use only.

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