Continuous Conditional GAN (CcGAN)
If you use this code, please cite
@inproceedings{
ding2021ccgan,
title={Cc{\{}GAN{\}}: Continuous Conditional Generative Adversarial Networks for Image Generation},
author={Xin Ding and Yongwei Wang and Zuheng Xu and William J Welch and Z. Jane Wang},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=PrzjugOsDeE}
}
@misc{ding2020continuous,
title={Continuous Conditional Generative Adversarial Networks for Image Generation: Novel Losses and Label Input Mechanisms},
author={Xin Ding and Yongwei Wang and Zuheng Xu and William J. Welch and Z. Jane Wang},
year={2020},
eprint={2011.07466},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
1. Datasets
The RC-49 Dataset (h5 file)
https://1drv.ms/u/s!Arj2pETbYnWQr7MY2Pr5qipSUpZKEQ?e=aRym3k
Download 'RC-49_64x64.h5' and put it in './improved_CcGAN/dataset/RC-49'
The preprocessed UTKFace Dataset (h5 file)
https://1drv.ms/u/s!Arj2pETbYnWQr7MW_sGY9tJC4G3eMw?e=ohhRTe
Download 'UTKFace_64x64.h5' and put it in './improved_CcGAN/dataset/UTKFace'
The Cell-200 dataset (h5 file)
https://1drv.ms/u/s!Arj2pETbYnWQr8tDP9Etf16nWddoTQ
Download 'Cell200_64x64.h5' and put it in './improved_CcGAN/dataset/Cell200'
The Steering Angle dataset (h5 file)
For CcGAN, AE, and Regression CNN training:
https://1drv.ms/u/s!Arj2pETbYnWQr7Mdwe6H-IS0YwXh3A?e=U0BiIq
For Clssification CNN training:
https://1drv.ms/u/s!Arj2pETbYnWQr8xEgY3ZHSe2b1CHlQ?e=SE7pv6
Download 'SteeringAngle_64x64.h5' and 'SteeringAngle_5_scenes_64x64' and put them in './improved_CcGAN/dataset/SteeringAngle'
2. Sample Usage
If a folder has 'improved' in its name, this folder corresponds to a ILI-based CcGAN; otherwise, a NLI-based CcGAN.
2.1 Simulation ('./improved_CcGAN/Simulation')
First, set the ROOT_PATH and DATA_PATH in the './scripts/run_train.sh' to yours.
Then, run 'run_train.sh'.
2.2 RC-49 ('./improved_CcGAN/RC-49' and './improved_CcGAN/RC-49-improved'')
First, set the ROOT_PATH and DATA_PATH in the './scripts/run_train.sh' to yours.
Then, run 'run_train.sh'.
2.3 UTKFace ('./improved_CcGAN/UTKFace' and './improved_CcGAN/UTKFace-improved')
First, set the ROOT_PATH and DATA_PATH in './scripts/run_train.sh' to yours.
Then, run 'run_train.sh'.
2.4 Cell-200 ('./improved_CcGAN/Cell200' and './improved_CcGAN/Cell200-improved')
First, set the ROOT_PATH and DATA_PATH in './scripts/run_train.sh' to yours.
Then, run 'run_train.sh'.
2.5 Steering Angle ('./improved_CcGAN/SteeringAngle' and './improved_CcGAN/SteeringAngle-improved')
First, set the ROOT_PATH and DATA_PATH in './scripts/run_train.sh' to yours.
Then, run 'run_train.sh'.
3. NIQE
The code for computing NIQE is in './improved_CcGAN/NIQE'. Corresponding tutorial will be provided soon.