https://github.com/edezhic/fashion-generator
In-browser GPU-accelerated Generative Adversarial Network trained on Fashion-MNIST dataset (tensorflow + deeplearn.js)
https://github.com/edezhic/fashion-generator
browser-game deep-learning generative-adversarial-network
Last synced: about 1 year ago
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In-browser GPU-accelerated Generative Adversarial Network trained on Fashion-MNIST dataset (tensorflow + deeplearn.js)
- Host: GitHub
- URL: https://github.com/edezhic/fashion-generator
- Owner: edezhic
- Archived: true
- Created: 2017-09-19T07:52:18.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2018-08-28T07:11:56.000Z (almost 8 years ago)
- Last Synced: 2023-05-03T20:31:05.483Z (about 3 years ago)
- Topics: browser-game, deep-learning, generative-adversarial-network
- Language: Python
- Homepage: https://towardsdatascience.com/generating-your-own-fashion-line-in-1-click-a8155c0c207
- Size: 19.5 KB
- Stars: 9
- Watchers: 5
- Forks: 5
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Fashion Generator
GAN model trained in Tensorflow and then ported to browsers using GPU-accelarated framework [deeplearn.js](https://github.com/PAIR-code/deeplearnjs) which is now the core of tensorflow.js
You can repeat the whole experiment in 3 steps:
- Run train.py to get ./weights folder
- Build generator.ts
- Run node server and open index.html
- You are awesome!
##### ./model contents:
- train.py - creates and trains the model, saves generator weights
- GAN.py - model definition (originated from [this repo](https://github.com/hwalsuklee/tensorflow-generative-model-collections))
- yellowfin.py - powerful custom TF optimizer, [original repo](https://github.com/JianGoForIt/YellowFin). Not really required, just a nice thing.
- ops.py and utils.py - simplified TF operations and other utility functions
##### ./browser contents:
- generator.ts - downloads weights and defines generator model
- index.html - simple wrapper
- other configs