monemati / YOLOv8-Sheep-Detection-Counting

YOLOv8 Aerial Sheep Detection and Counting. Simulated on Gazebo.

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YOLOv8 Aerial Sheep Detection and Counting

YOLOv8 Aerial Sheep Detection and Counting. Simulated on Gazebo.

Introduction

This repository contains a Sheep Detector and Counter trained by YOLOv8 algorithm with Sheep Dataset from Roboflow.

Train Results

Train results on YOLOv8n. Weights are provided in resources/weights direcotry.

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Installation

Create a virtual environment

# create
python -m venv yolov8-sheep

# activate
source yolov8-sheep/bin/activate

Clone repository

git clone https://github.com/monemati/YOLOv8-Sheep-Detection-Counting.git
cd YOLOv8-Sheep-Detection-Counting

Install packages

pip install -e '.[dev]'

Run

# On image
python count.py

# On Video
python track.py
  • Change file_path to your desired files. Sample files are provided in resources/images and resources/videos direcotries.

Simulate in Gazebo

  • You need to follow this tutorial to setup test environment.
  • You can use Models and Worlds provided in resources/models and resources/worlds direcotries.
  • Open a terminal and use the command below to launch your world (this will launch gazebo):
roslaunch gazebo_ros agriculture.launch
  • Open a new terminal and run a UAV:
cd ~/ardupilot/Tools/autotest && ./sim_vehicle.py -v ArduCopter -f gazebo-iris -I0
  • After seeing "APM: EKF2 IMU0 is using GPS" message in console, you can use the commands below to takeoff:
mode guided
arm throttle
takeoff 40
  • Now in a new terminal use the command below:
python sheep.py

Results

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Acknowledgement

About

YOLOv8 Aerial Sheep Detection and Counting. Simulated on Gazebo.

License:GNU Affero General Public License v3.0


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