Metadata-Version: 2.1
Name: DeepCell-RetinaMask
Version: 0.1.0
Summary: RetinaNet and RetinaMask models for object detection using TensorFlow and DeepCell-tf.
Home-page: https://github.com/vanvalenlab/deepcell-retinamask
Author: The Van Valen Lab
Author-email: vanvalen@caltech.edu
License: LICENSE
Download-URL: https://github.com/vanvalenlab/deepcell-retinamask/tarball/0.1.0
Description: # DeepCell-RetinaMask
        
        [![Build Status](https://github.com/vanvalenlab/deepcell-retinamask/workflows/build/badge.svg)](https://github.com/vanvalenlab/deepcell-retinamask/actions)
        [![Coverage Status](https://coveralls.io/repos/github/vanvalenlab/deepcell-retinamask/badge.svg?branch=master)](https://coveralls.io/github/vanvalenlab/deepcell-retinamask?branch=master)
        [![Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/vanvalenlab/deepcell-retinamask/blob/master/LICENSE)
        [![PyPI version](https://badge.fury.io/py/DeepCell-RetinaMask.svg)](https://badge.fury.io/py/deepcell-retinamask)
        [![Python Versions](https://img.shields.io/pypi/pyversions/deepcell-retinamask.svg)](https://pypi.org/project/deepcell-retinamask/)
        
        `deepcell-retinamask` is a deep learning library for building RetinaNet and RetinaMask based object detection models with `tensorflow` and `deepcell-tf`.
        
        This project was heavily influenced by [keras-retinanet](https://github.com/fizyr/keras-retinanet) and [keras-maskrcnn](https://github.com/fizyr/keras-maskrcnn).
        
        ## Install
        
        `deepcell-retinamask` can be easily installed with pip:
        
        ```bash
        $ pip install deepcell-retinamask
        ```
        
        ## Examples
        
        For examples of how to train models with the `deepcell-retinamask` library, check out the following notebooks:
        
        - [Training a RetinaNet Model](https://github.com/vanvalenlab/deepcell-retinamask/blob/master/notebooks/RetinaNet.ipynb)
        - [Training a RetinaMask Model](https://github.com/vanvalenlab/deepcell-retinamask/blob/master/notebooks/RetinaMask.ipynb)
        - [Training a PanOpticFPN Model](https://github.com/vanvalenlab/deepcell-retinamask/blob/master/notebooks/PanOpticFPN.ipynb)
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Image Processing
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.6, <3.9
Description-Content-Type: text/markdown
Provides-Extra: tests
