tkwoo / Anogan Keras
Unsupervised anomaly detection with generative model, keras implementation
Stars: ✭ 157
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query image | generated similar image | differece |
---|---|---|
AnoGAN keras implementation
Unsupervised anomaly detection with DCGAN
Requirements
- Python 3.6
- OpenCV 3.4.0 (option: build from src with highgui)
- h5py
- scikit-learn
- PyQt5
- tqdm
- Keras 2.1.4
- TensorFlow 1.5.0
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
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