README.md

---
license: mit
metrics:
- precision
- recall
base_model:
- Ultralytics/YOLOv8
pipeline_tag: object-detection
tags:
- defect-detection
- industrial, quality-control, yolov8
---
# Industrial Surface Defect Detection Model (NEU-DET)

A YOLOv8-based deep learning model for real-time detection of 6 types of surface defects in industrial materials.

## 📋 Model Overview

**Architecture:** YOLOv8  
**Dataset:** NEU-DET (1,800 grayscale images)  
**Task:** Object Detection (Defect Classification)  
**Framework:** Ultralytics  
**Input:** Images (JPEG/PNG)  
**Output:** Bounding boxes + Confidence scores

## 🔍 Supported Defect Classes

| Defect Type | Description |
|------------|-------------|
| **Crazing** | Fine surface cracks forming network patterns |
| **Inclusion** | Foreign material embedded in surface |
| **Patches** | Surface irregularities and discoloration |
| **Pitted Surface** | Pitting and corrosion damage |
| **Rolled-in Scale** | Scale/oxide layers rolled into material |
| **Scratches** | Surface abrasions and scratch marks |