🖼️ Object Detection System with YOLOv8 & OpenCV
An object detection system built using YOLOv8 and OpenCV, capable of detecting and tracking multiple objects in images and videos with high accuracy and real-time performance.
🚀 Features
🧠 YOLOv8 Model for state-of-the-art object detection
🎥 Real-time Video Processing using OpenCV
⚡ Lightweight & Fast inference
🛠️ Installation
Clone the repository:
git clone https://github.com/your-username/Object-Detection-YOLOv8.git cd Object-Detection-YOLOv8
Create a virtual environment (optional but recommended):
python -m venv venv source venv/bin/activate # Linux / Mac venv\Scripts\activate # Windows
Install dependencies:
pip install -r requirements.txt
📦 Dependencies
Python 3.8+
OpenCV
Ultralytics YOLOv8
NumPy
Install them manually if needed:
pip install opencv-python ultralytics numpy
🔹 Run on a video python detect.py --video videos/sample.mp4
🔹 Run on webcam python detect.py --webcam
🎯 Example Results 📸 Image Detection
🎥 Video Detection
Bounding boxes with labels are displayed in real time.
📊 Model Performance Model Variant Speed (ms) mAP@50 Parameters YOLOv8n 1.2 37.3 3.2M YOLOv8s 1.9 44.9 11.2M YOLOv8m 2.8 50.2 25.9M 🏗️ Future Improvements
✅ Object tracking (DeepSORT/ByteTrack integration)
✅ Custom dataset training
✅ Deploy as a web app (Flask/Streamlit)
🤝 Contributing
Contributions, issues, and feature requests are welcome! Feel free to fork the repo and submit a pull request.
📜 License
This project is licensed under the MIT License.