Metadata-Version: 2.1
Name: vae-anomaly-detection
Version: 1.0.0
Summary: Pytorch/TF1 implementation of Variational AutoEncoder for anomaly detection following the paper "Variational Autoencoder based Anomaly Detection using Reconstruction Probability by Jinwon An, Sungzoon Cho"
Home-page: https://github.com/Michedev/VAE_anomaly_detection
License: MIT
Keywords: vae,anomaly detection,deep learning,pytorch
Author: Michele De Vita
Author-email: mik3dev@gmail.com
Requires-Python: >=3.6.2
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: PyYAML (>=5.0)
Requires-Dist: numpy (>=1.18)
Requires-Dist: path (>=15.0)
Requires-Dist: pytorch-ignite (>=0.4)
Requires-Dist: tensorboard (>=0.20)
Requires-Dist: torch (>=1.8.0)
Requires-Dist: tqdm (>=4.0)
Project-URL: Repository, https://github.com/Michedev/VAE_anomaly_detection
