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--- |
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license: mit |
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metrics: |
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- precision |
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- recall |
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base_model: |
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- Ultralytics/YOLOv8 |
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pipeline_tag: object-detection |
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tags: |
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- defect-detection |
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- industrial, quality-control, yolov8 |
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--- |
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# Industrial Surface Defect Detection Model (NEU-DET) |
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A YOLOv8-based deep learning model for real-time detection of 6 types of surface defects in industrial materials. |
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## 📋 Model Overview |
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**Architecture:** YOLOv8 |
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**Dataset:** NEU-DET (1,800 grayscale images) |
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**Task:** Object Detection (Defect Classification) |
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**Framework:** Ultralytics |
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**Input:** Images (JPEG/PNG) |
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**Output:** Bounding boxes + Confidence scores |
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## 🔍 Supported Defect Classes |
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| Defect Type | Description | |
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|------------|-------------| |
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| **Crazing** | Fine surface cracks forming network patterns | |
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| **Inclusion** | Foreign material embedded in surface | |
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| **Patches** | Surface irregularities and discoloration | |
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| **Pitted Surface** | Pitting and corrosion damage | |
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| **Rolled-in Scale** | Scale/oxide layers rolled into material | |
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| **Scratches** | Surface abrasions and scratch marks | |
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