Tensorflow implementation of OCGAN
# Tensorflow Implementation of OCGAN This repository provides a [Tensorflow](https://www.tensorflow.org/) implementation of the OCGAN presented in CVPR 2019 paper “[OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations](http://openaccess.thecvf.com/content_CVPR_2019/papers/Perera_OCGAN_One-Class_Novelty_Detection_Using_GANs_With_Constrained_Latent_Representations_CVPR_2019_paper.pdf)”.
The author’s implementation of OCGAN in MXNet is at [here](https://github.com/PramuPerera/OCGAN).
## Installation This code is written in Python 3.5 and tested with Tensorflow 1.13.
Install using pip or clone this repository.
1. Installation using pip: `bash pip install ocgan `
`python from ocgan import OCGAN `
- Clone this repository:
`bash git clone https://github.com/nuclearboy95/Deep-SVDD-Tensorflow.git `
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size ocgan-1.0-py3-none-any.whl (6.7 kB)||File type Wheel||Python version py3||Upload date||Hashes View hashes|