Metadata-Version: 2.1
Name: CitologyAnomalyDetector
Version: 0.0.4
Summary: Deep Learning model for anomaly detection of citology images
Home-page: https://github.com/joheras/CitologyAnomalyDetector
Author: Jónathan Heras Vicente
Author-email: joheras@gmail.com
Maintainer: Jónathan Heras Vicente
Maintainer-email: joheras@gmail.com
License: GNU General Public License v3 (GPLv3)
Keywords: anomaly detection fastai
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
License-File: LICENSE.txt

# Citology Anomaly Detector

Install with `pip install CitologyAnomalyDetector`.

Use it with:
```bash
anomaly-detection <path>
```

where <path> is the path to a folder with two subfolders train and valid. The train folder should contain at least one imagen, and the valid folder contain the images to analyse. 


