The Object Detection App is a web-based application that identifies and labels over 50 fruits and vegetables in real-time using a custom YOLOv8 model. This project was developed to provide an intuitive tool for visual recognition tasks and demonstrates the practical application of computer vision and machine learning.
Built with Python, YOLOv8, and web technologies (HTML, JSON), this app combines object detection with an easy-to-use interface for users to quickly identify items from images.
- Real-time object detection for fruits and vegetables
- Labels detected objects and provides their names
- Supports integration with mechanical systems (e.g., vegetable cutter) for automation
- User-friendly web interface
- Uses a custom-trained YOLOv8 model for high accuracy
- Lightweight and efficient, suitable for web deployment
- Programming Languages: Python, HTML, JavaScript
- Frameworks/Libraries: YOLOv8, OpenCV, Flask (or FastAPI if used)
- Data Handling: JSON for object information
- Python 3.x installed
- Required Python libraries:
pip install ultralytics opencv-python flask numpy