https://github.com/thevarunsharma/facegan
Generating images of human faces using GANs
https://github.com/thevarunsharma/facegan
deep-learning generative-adversarial-network machine-learning tensorflow unsupervised-learning
Last synced: about 2 months ago
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Generating images of human faces using GANs
- Host: GitHub
- URL: https://github.com/thevarunsharma/facegan
- Owner: thevarunsharma
- Created: 2018-12-25T11:23:32.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2019-01-04T14:55:17.000Z (over 7 years ago)
- Last Synced: 2025-10-09T22:42:43.347Z (9 months ago)
- Topics: deep-learning, generative-adversarial-network, machine-learning, tensorflow, unsupervised-learning
- Language: Jupyter Notebook
- Size: 6.74 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# FaceGAN
Generating images of human faces using GANs
Generative Adversarial Networks(GANs) are a class of artificial intelligence algorithms used in unsupervised machine learning, implemented by a system of two neural networks contesting with each other in a zero-sum game framework.
A GAN has two parts:
- a Generator which generates data, and
- a Discrimintor which differntiates between real and generated data.
Generator's goal is to fool the discriminator and Discriminator's goal is to not get fooled by the generator.
Sample Run
Run main.py and enter number of images to generate. One sample run yields the following
