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title: Defect detection for Printed Circuit Boards
emoji: 🔌
colorFrom: green
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sdk: gradio
app_file: app.py
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Defect detection for Printed Circuit Boards
AI to detect and recognize six types of defects on printed circuit boards: missing hole, mouse bite, open circuit, short, spur, and spurious copper.
Table of contents
Live demo
General information
This is an AI that was trained on images of defect printed circuit boards to carry out defect detection and recognition. It can recognize six types of defects on printed circuit boards: missing hole, mouse bite, open circuit, short, spur, and spurious copper.
Dataset
The Open Lab on Human Robot Interaction of Peking University released the PCB defect dataset.
R. Ding, L. Dai, G. Li and H. Liu, "TDD-net: a tiny defect detection network for printed circuit boards," in CAAI Transactions on Intelligence Technology, vol. 4, no. 2, pp. 110-116, 6 2019, doi: 10.1049/trit.2019.0019.
How does it work
Technologies used:
- RT-DETR: Object detection model to detect and recognize defects.