Metadata-Version: 2.1
Name: openweedlocator-tools
Version: 0.0.1
Summary: A toolkit for green-on-brown and green-on-green weed detection
Home-page: https://github.com/geezacoleman/openweedlocator-tools
Author: Guy Coleman
Author-email: hoot@openweedlocator.com
Maintainer-email: guy.coleman@sydney.edu.au
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: imutils<1.0,>=0.5
Requires-Dist: numpy<2.0,>=1.10
Requires-Dist: opencv-contrib-python<5.0,>=4.0
Requires-Dist: opencv-python<5.0,>=4.0
Requires-Dist: pandas>2.0
Requires-Dist: python-dateutil<3.0,>=2.8
Provides-Extra: desktop
Requires-Dist: ultralytics; extra == "desktop"
Provides-Extra: rpi

# Official OpenWeedLocator Toolkit
Simplifying the integration of weed detection into your platform.

[![OWL-tools](https://github.com/geezacoleman/openweedlocator-tools/actions/workflows/owl-testing.yml/badge.svg)](https://github.com/geezacoleman/openweedlocator-tools/actions/workflows/owl-testing.yml)

## Overview
The OpenWeedLocator (OWL) is an open-source weed detection device for low-cost, 
DIY site-specific weed management. Here, we're making the software that supports 
the OWL more accesible with an easy-to-use API, so you can integrate weed detection 
into your own devices and services more easily by simply calling 
`GreenonBrown.find()`.

Currently, it supports green-on-brown detection on all platforms, and green-on-green
on desktops through the Ultralytics package.

In the future, we will support plant counting, GPS integration and green-on-green 
on edge devices (Jetson Nano, Raspberry Pi)

## Installation
To install the latest version of `openweedlocator-tools` simply run:
### Desktop
```
pip install openweedlocator-tools[desktop]
```

## Quick Start
```
from owl.viz import webcam, images_and_video
# Run using your webcam
webcam(algorithm='gog') # press escape to exit
# or 
images_and_video(media_path='path/to/your/media_files
```

## Streamlit App
Try it for yourself now with the online, Streamlit app!
