https://github.com/anyantudre/generative-adversarial-networks-gans

A very basic and simple example of how to use GANs to generate fake handwritten numbers.
https://github.com/anyantudre/generative-adversarial-networks-gans

cnn-pytorch deep-learning gan gans generative-adversarial-network pytorch

Last synced: 1 day ago
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A very basic and simple example of how to use GANs to generate fake handwritten numbers.

• Host: GitHub
• URL: https://github.com/anyantudre/generative-adversarial-networks-gans
• Owner: ANYANTUDRE
• License: mit
• Created: 2024-12-07T12:57:43.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-12-07T14:35:12.000Z (about 2 months ago)
• Last Synced: 2024-12-07T15:25:38.494Z (about 2 months ago)
• Topics: cnn-pytorch, deep-learning, gan, gans, generative-adversarial-network, pytorch
• Language: Jupyter Notebook
• Homepage:
• Size: 72.3 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Generative-Adversarial-Networks-GANs

This is a simple implementation of **Deep Convolutional Generative Adversarial Network using PyTorch** to generate handwritten digits with a generator that learns to generate images that look real and a discriminator that learns to tell real images apart from fakes from the famous MNIST dataset.

![GAN](https://github.com/ANYANTUDRE/Generative-Adversarial-Networks-GANs/blob/main/img/GANs.png?raw=true)