Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/simoninithomas/catdcgan
A DCGAN that generate Cat pictures 🐱💻
https://github.com/simoninithomas/catdcgan
cats dcgan dcgan-tensorflow deep-learning gan tensorflow
Last synced: 1 day ago
JSON representation
A DCGAN that generate Cat pictures 🐱💻
- Host: GitHub
- URL: https://github.com/simoninithomas/catdcgan
- Owner: simoninithomas
- Created: 2018-03-05T15:19:06.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2021-04-05T14:34:53.000Z (over 3 years ago)
- Last Synced: 2023-10-20T23:08:24.638Z (about 1 year ago)
- Topics: cats, dcgan, dcgan-tensorflow, deep-learning, gan, tensorflow
- Language: Jupyter Notebook
- Homepage: https://simoninithomas.github.io/CatDCGAN/
- Size: 34.4 MB
- Stars: 199
- Watchers: 7
- Forks: 69
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# CatDCGAN 🐱💻
A DGAN that generate Cat pictures
Cat DCGAN is a Deep Convolutional Generative Adversarial Network (DCGAN) that generates pictures of cats
This is an open source project
## The tutorial 📃
If you want to implement it by yourself and understand how it works, please read my article on FreeCodeCamp https://medium.freecodecamp.org/how-ai-can-learn-to-generate-pictures-of-cats-ba692cb6eae4
## Links 🔗
🌐 : https://simoninithomas.github.io/CatDCGAN/
If you have any questions, feel free to ask me:
Github: https://github.com/simoninithomas/CatDCGAN
🌐 : https://www.simoninithomas.com
Twitter: @ThomasSimonini
In this part we're going to implement the DCGAN.
Our Architecture:
## Getting Started 📝
- Download the dataset here: https://www.kaggle.com/crawford/cat-dataset
- Download the model checkpoint : https://drive.google.com/drive/folders/1zdZZ91fjOUiOsIdAQKZkUTATXzqy7hiz?usp=sharing
- Type `sh start.sh` it will handle extract, remove outliers, normalization and face centering
- Launch Jupyter Notebook `jupyter notebook --no-browser`
- Launch CatDCGAN
- Change `do_preprocess = True` ⚠️⚠️⚠️ important!
- If you want to train from scratch : change `from_checkpoint = False`
- If you want to train from last model saved (you save 20 hours of training 🎉) : change `from_checkpoint = True`## Important note 🤔
You can't run this on your computer (except if you have GPUs or wait 10 years 😅), personally I train this DCGAN for 20 hours with Microsoft Azure and their Deep Learning Virtual Machine (they offer 170$)
https://azuremarketplace.microsoft.com/en-us/marketplace/apps/microsoft-ads.dsvm-deep-learning
⚠️ I don't have any business relations with them. I just loved their excellent customer service.If you have some troubles to use follow the explainations of this excellent article here (without last the part fast.ai): https://medium.com/@manikantayadunanda/setting-up-deeplearning-machine-and-fast-ai-on-azure-a22eb6bd6429
## Contributing 🙌
If you want to contribute to the project, your help is very welcome. This is an open source project.![](https://media.giphy.com/media/14cAg6Rn5jndIc/giphy.gif)
We currently working on improving our Generative adversarial network architecture. If you're motivated come join us and submit your pull requests.
## Acknowledgements 👏
This project was made possible thanks to:
- Udacity Face Generator Project
- The start.sh and preprocess part (modified) made by Alexia Jolicoeur-Martineau https://ajolicoeur.wordpress.com/cats/
- Siraj's Raval PokeGan https://github.com/llSourcell/Pokemon_GAN
- The choice of learning rate by Alexia Jolicoeur-Martineau https://ajolicoeur.wordpress.com/cats/