Metadata-Version: 2.1
Name: farabio
Version: 0.0.2
Summary: farabio - Deep learning for biomedical imaging
Home-page: https://github.com/tuttelikz/farabio
Author: San Askaruly
Author-email: s.askaruly@gmail.com
License: Apache license
Project-URL: Bug Tracker, https://github.com/tuttelikz/farabio/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

![logo](logo/logo.png)

[![GitHub](https://img.shields.io/github/license/tuttelikz/farabio)](https://opensource.org/licenses/Apache-2.0) [![Documentation Status](https://readthedocs.org/projects/farabio/badge/?version=latest)](https://farabio.readthedocs.io/en/latest)
[![PyPI version](https://img.shields.io/pypi/v/farabio)](https://badge.fury.io/py/farabio)

# farabio
- [What's New](#whats-new)
- [Introduction](#introduction)
- [Features](#features)
- [Biodatasets](#biodatasets)
- [Models](#models)
- [Getting Started (Installation)](#getting-started-installation)
- [Credits](#credits)
- [Licenses](#licenses)
- [Links](#links)

## What's New

### August 18, 2021
Release of [`farabio==0.0.2`](https://pypi.org/project/farabio/)

### April 21, 2021
This work is presented at PyTorch Ecosystem day. Poster is [here](https://pytorch.org/ecosystem/pted/2021).

### April 2, 2021
Release of [`farabio==0.0.1`](https://pypi.org/project/farabio/)  

### March 3, 2021
This work is selected for PyTorch Ecosystem Day.

## Introduction

**farabio** is a minimal PyTorch toolkit for out-of-the-box deep learning support in biomedical imaging. For further information, see [*Wikis*](https://github.com/tuttelikz/farabio/wiki) and [*Docs*](https://farabio.readthedocs.io).

## Features
- Biomedical datasets
- Common DL models
- Flexible trainers (**in progress*)

## Biodatasets
* Chest X-Ray Images (Pneumonia):  
https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia
* 2018 Data Science Bowl:  
https://www.kaggle.com/c/data-science-bowl-2018/overview
* Histopathologic Cancer Detection:  
https://www.kaggle.com/c/histopathologic-cancer-detection/overview
* RANZCR CLiP - Catheter and Line Position Challenge:  
https://www.kaggle.com/c/ranzcr-clip-catheter-line-classification/overview
* APTOS 2019 Blindness Detection:  
https://www.kaggle.com/c/aptos2019-blindness-detection/overview

## Models
* AlexNet - https://papers.nips.cc/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf
* GoogLeNet - https://arxiv.org/pdf/1409.4842.pdf
* MobileNetV2 - https://arxiv.org/pdf/1801.04381.pdf
* MobileNetV3 - https://arxiv.org/pdf/1905.02244.pdf
* ResNet - https://arxiv.org/pdf/1512.03385.pdf
* ShuffleNetV2 - https://arxiv.org/pdf/1807.11164.pdf
* SqueezeNet - https://arxiv.org/pdf/1602.07360.pdf
* VGG - https://arxiv.org/pdf/1409.1556.pdf

## Getting started (Installation)

### 1. Activate conda environment:
```bash
$ conda create -n myenv python=3.8
$ conda activate myenv
```

### 2. Install **farabio**:
**A. With pip**:
```bash
$ pip install farabio -f https://download.pytorch.org/whl/torch_stable.html
```

**B. Setup from source**:
```bash
$ git clone https://github.com/tuttelikz/farabio.git && cd farabio
$ pip install . -f https://download.pytorch.org/whl/torch_stable.html
```

## Credits
If you like this repository, please click on Star.

## Licenses
This work is licensed [Apache 2.0](https://github.com/tuttelikz/farabio/blob/main/LICENSE).

## Links
- API documentations: https://farabio.readthedocs.io
- Code: https://github.com/tuttelikz/farabio
- Issue tracker: https://github.com/tuttelikz/farabio/issues
- PyPI package: https://pypi.org/project/farabio/
- Wiki: https://github.com/tuttelikz/farabio/wiki


