1,386 images of Printed Circuit Boards (PCBs) categorized into 6 distinct defect classes. The dataset provides visual examples for identifying manufacturing flaws in electronic components.
Use Cases
- Train a computer vision model to identify 6 types of manufacturing defects in PCB images
- Evaluate the performance of anomaly detection algorithms on 1,386 industrial circuit board samples
- Build a classification system to sort PCB images based on the specific defect category present
Strengths
- 1,386 images of printed circuit boards
- 6 distinct defect categories
- Visual samples for defect classification