Model weights for PCBInspect-AI, a deep learning platform for automated PCB (Printed Circuit Board) feature detection in Automated Optical Inspection (AOI) pipelines.
Open http://localhost:7860, select a model in the Model tab, and run inference in the Inference tab.
Training
YOLOv12 Two-Stage Regime
Stage 1 (100 epochs): 640x640 resolution, heavy augmentation for fast convergence
Stage 2 (60 epochs): 896x896 resolution, lighter augmentation for fine-tuning
RF-DETR
100 epochs with DINOv2 backbone
Bounding box annotations in COCO format
Citation
If you use these weights, please reference the associated project:
PCBInspect-AI - Automated Generation of PCB Inspection Recipes Using Deep Learning-Based Feature Detection
National University of Singapore (NUS)
https://github.com/JC-prog/pcb-inspect-ai
