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: 5 days 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 (over 8 years ago)
• Default Branch: master
• Last Pushed: 2024-05-02T06:46:13.000Z (9 months ago)
• Last Synced: 2024-11-03T20:27:21.707Z (3 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)

![Untitled](https://github.com/ethanhe42/GAN-MNIST/assets/10027339/8f39f2b6-b2dd-4f0b-9fbf-f33247b0b70e)

![Untitled 1](https://github.com/ethanhe42/GAN-MNIST/assets/10027339/de4f99c4-f615-4954-9db1-e9883396dc3a)

### 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}

}

```