/anogan-keras

Unsupervised anomaly detection with generative model, keras implementation

Primary LanguagePython






query image generated similar image differece



AnoGAN keras implementation

Unsupervised anomaly detection with DCGAN

Requirements

Usage

First, check directory structure

├── main.py
├── anogan.py 
├── weights
    ├── discriminator.h5
    └── generator.h5
└── result
    └── save the generated images when training

To test this project

$ python main.py

To train a model

$ python main.py --mode train

Then, the training steps(image) will be saved 'result' directory


usage: main.py [-h] [--img_idx IMG_IDX] 
                    [--label_idx LABEL_IDX] 
                    [--mode MODE]

Reference

paper : https://arxiv.org/abs/1703.05921
AnoGAN(code, keras) : https://github.com/yjucho1/anoGAN
AnoGAN(code, tf) : https://github.com/LeeDoYup/AnoGAN