https://github.com/ethanhe42/gan-mnist
Generative Adversarial Network for MNIST with tensorflow
https://github.com/ethanhe42/gan-mnist
dcgan-model deep-learning face gan generative-adversarial-network mnist tensorflow
Last synced: about 1 month ago
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Generative Adversarial Network for MNIST with tensorflow
- Host: GitHub
- URL: https://github.com/ethanhe42/gan-mnist
- Owner: ethanhe42
- License: mit
- Created: 2016-08-02T09:38:12.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2024-05-02T06:46:13.000Z (about 1 year ago)
- Last Synced: 2024-11-03T20:27:21.707Z (7 months ago)
- Topics: dcgan-model, deep-learning, face, gan, generative-adversarial-network, mnist, tensorflow
- Language: Python
- Homepage: https://yihui-he.github.io/blog/gan-on-mnist-with-tensorflow
- Size: 10.5 MB
- Stars: 185
- Watchers: 16
- Forks: 70
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
README
# GAN on MNIST with TensorFlow
[GitHub - yihui-he/GAN-MNIST: Generative Adversarial Network for MNIST with tensorflow](https://github.com/yihui-he/GAN-MNIST)
### Tensorflow implementation
- All the codes in this project are mere replication of [Theano version](https://github.com/Newmu/dcgan_code)
### Code
- Under `face/` and `mnist/`
- model.py
- Definition of DCGAN model
- train.py
- Training the DCGAN model (and Generating samples time to time)
- util.py
- Image related utils
### Dataset
- MNIST
- http://yann.lecun.com/exdb/mnist/
- CelebA Face dataset
- http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
- Download “img_align_celeba” images
- Set “face_image_path” in train.py according to the path of downloaded dataset
### references
https://github.com/carpedm20/DCGAN-tensorflow
### Citation
If you find the code useful in your research, please consider citing:
```
@InProceedings{He_2017_ICCV,
author = {He, Yihui and Zhang, Xiangyu and Sun, Jian},
title = {Channel Pruning for Accelerating Very Deep Neural Networks},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {Oct},
year = {2017}
}
```