Foxy-Roxy/Wheel_Defect_Detection

1---2title: Wheel_Defect_Detection3emoji: 🛞4colorFrom: red5colorTo: red6sdk: streamlit7app_port: 85018tags:9  - streamlit10app_file: app.py11pinned: false12short_description: Streamlit template space13license: mit14sdk_version: 1.45.115---16 17# Welcome to Streamlit!18 19Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:20 21If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community22forums](https://discuss.streamlit.io).23 24🛞 Tire Defect Detection using YOLOv825A real-time deep learning project to detect and classify tire defects such as bulges, cracks, and flat spots using the YOLOv8 object detection model.26 27🔍 Objective28The goal of this project is to overcome the limitations of traditional sensor-based tire defect detection systems (like in the research paper) by using a camera-based, AI-powered solution that:29 30Works in real-time31Requires no specialized hardware32Supports multiple defect types33🚀 Features34Detects 4 classes: Bulge, Cracks, Flat Spots, Non-defective35Trained using YOLOv8n (Ultralytics)36Works with static images and can be extended to video/webcam37Real-time feedback with bounding boxes38Easy deployment and portable39📂 Dataset40Labeled dataset from Roboflow in YOLO format41Classes: ['Bulge', 'Cracks', 'Flat spots', 'Non-defective']42