TensorFlow implementation of GANomaly with MNIST dataset.
PyTorch Version is also implemented.
Loss graph in the training procedure.
Each graph shows encoding loss, reconstruction loss, adversarial loss, and total (target) loss respectively.
Normal samples classified as normal.
Abnormal samples classified as normal.
Normal samples classified as abnormal.
Abnormal samples classified as abnormal.
- Python 3.7.4
- Tensorflow 1.14.0
- Numpy 1.17.1
- Matplotlib 3.1.1
- Scikit Learn (sklearn) 0.21.3
[1] S Akcay, et al. (2018). Ganomaly: Semi-supervised anomaly detection via adversarial training.. arXiv preprint arXiv:1805.06725.