# brambox

**Repository Path**: twang9/brambox

## Basic Information

- **Project Name**: brambox
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-08-14
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<img src="docs/.static/logo-wide.png" alt="Logo" width="1000" />

_Basic Requisites for Algorithms on iMages toolBOX_

[![Version][version-badge]][release-url]
[![Wheel][wheel-badge]][wheel-url]
[![Pipeline][pipeline-badge]][pipeline-badge]
[![Coverage][coverage-badge]][coverage-url]

Brambox is a python toolbox that provides the necessary tools to convert image annotations, compute statitics and more.
It's main use is for object detection algorithms and datasets.


## Installing
```bash
# From wheel
pip install brambox

# From source
pip install numpy
pip install git+https://gitlab.com/eavise/brambox
```
> This project is python 3.6 and higher so on some systems you might want to use 'pip3.6' instead of 'pip'


## Using
Once you installed brambox, you can import it in your own python program with:
```python
import brambox as bb
```
For tutorials and the API documentation [click here][doc-url].


## Contributing
See [the contribution guidelines](CONTRIBUTING.md)


[version-badge]: https://img.shields.io/pypi/v/brambox.svg?label=version
[wheel-badge]: https://img.shields.io/pypi/wheel/brambox.svg
[pipeline-badge]: https://gitlab.com/EAVISE/brambox/badges/master/pipeline.svg
[coverage-badge]: https://codecov.io/gl/EAVISE/brambox/branch/master/graph/badge.svg
[release-url]: https://gitlab.com/EAVISE/brambox/tags
[wheel-url]: https://pypi.org/project/brambox
[coverage-url]: https://codecov.io/gl/EAVISE/brambox
[doc-url]: https://eavise.gitlab.io/brambox