shenqiti / GANs

This is a repository about Generative Adversarial Networks. Mainly for generate gaussian curve.

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An introduction to Generative Adversarial Networks

This is the code that we used to generate our GAN 1D Gaussian approximation.

Installing dependencies

Written for Python 3.x (tested on 3.6.1).

For the Python dependencies, first install the requirements file:

$ pip install -r requirements.txt

If you want to also generate the animations, you need to also make sure that ffmpeg is installed and on your path.

Training

For a full list of parameters, run:

$ python gan.py --help

To run without minibatch discrimination (and plot the resulting distributions):

$ python gan.py

To run with minibatch discrimination (and plot the resulting distributions):

$ python gan.py --minibatch

Notes:

my_cgan_tensorfolw.py is a conditional generative adversarial networks test about MNIST database.

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This is a repository about Generative Adversarial Networks. Mainly for generate gaussian curve.


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