YOLOv8 Object Detection Setup 🤖 📷

This repository facilitates the implementation of object detection using the YOLOv8 algorithm. Users can effortlessly run their models, and the program will automatically generate output videos in the results folder. Sample models are included for quick and easy usage.

Overview

The YOLOv8 Object Detection Setup allows users to perform real-time object detection using the YOLOv8 algorithm. The project is designed for simplicity and convenience, enabling users to run their models seamlessly and obtain output videos with detected objects.

Prerequisites

Ensure the following dependencies are installed:

• Python 3.x
• YOLOv8 (refer to YOLOv8 documentation for installation instructions)
• Nvidia CUDA Framework (optional)

Installation (windows)

1. Clone the repository and navigate to the project directory:

git clone https://github.com/aabduvak/object-detection-setup.git setup ;
cd setup

2. Install required packages

pip install -r requirements.txt

If there is conflict on version of packages

pip install ultralytics supervision PyQt5 opencv-contrib-python

Usage

Run model with GUI (PyQt5), choose model and source

python main.py

Run model in command-line

python stream.py --source=path-to-source --weights=path-to-model --target=output.mp4

Example

python stream.py --weights=models/person.pt --target=result.mp4 --source=0 #webcam

Customization

You can easily customize the object detection system by modifying configurations, integrating your own YOLOv8 models, or adjusting other parameters as needed.

For more info:
https://docs.ultralytics.com/modes/train/#introduction

Contributing

Contributions are welcome! 🙃

Contact

For support, feedback, or questions, please contact [email protected] or open an issue on the GitHub repository.