DeepPCB: a dataset contains 1,500 image pairs, each of which consists of a defect-free template image and an aligned tested image with annotations including positions of 6 most common types of PCB defects: open, short, mousebite, spur, pin hole and spurious copper.

Data Collection

All the images in this dataset are obtained from a linear scan CCD in resolution around 48 pixels per 1 millimetre. The defect-free template images are manually checked and cleaned from sampled images in the above manner. The original size of the template and tested image is around 16k x 16k pixels. Then they are cropped into many sub-images with size of 640 x 640 and aligned through template matching techniques. Next, a threshold is carefully selected to employ binarization to avoid illumination disturbance. Notice that pre-processing algorithms can be various according to the specific PCB defect detection algorithms, however, the image registration and thresholding techniques are common process for high-accuracy PCB defect localization and classification. An example pair in DeepPCB dataset is illustrated in the following figure, where the right one is the defect-free template image and the left one is the defective tested image with the ground truth annotations.