https://github.com/aabduvak/object-detection-setup
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.
https://github.com/aabduvak/object-detection-setup
computer-vision deep-neural-networks object-detection opencv yolov8
Last synced: 3 months ago
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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.
- Host: GitHub
- URL: https://github.com/aabduvak/object-detection-setup
- Owner: aabduvak
- License: gpl-3.0
- Created: 2024-01-22T22:44:43.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-05-23T23:39:14.000Z (about 1 year ago)
- Last Synced: 2025-01-22T22:11:18.870Z (4 months ago)
- Topics: computer-vision, deep-neural-networks, object-detection, opencv, yolov8
- Language: Python
- Homepage:
- Size: 23 MB
- Stars: 2
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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:
```bash
git clone https://github.com/aabduvak/object-detection-setup.git setup ;
cd setup
```
2. Install required packages
```bash
pip install -r requirements.txt
```
If there is conflict on version of packages
```bash
pip install ultralytics supervision PyQt5 opencv-contrib-python
```
## Usage
Run model with GUI (PyQt5), choose model and source
```bash
python main.py
```
Run model in command-line
```bash
python stream.py --source=path-to-source --weights=path-to-model --target=output.mp4
```
Example
```bash
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.