Defect Detection Dataset: Porosities in Machined Aluminum Holes

Each image has a resolution of 400x400 pixels in RGB color space, providing detailed views of potential defects. The dataset is intended for developing and evaluating algorithms for automated defect detection in industrial manufacturing, specifically targeting porosity defects in aluminum casting processes.

It does not include annotations or labels. Researchers can use these images to: *Train and test machine learning models for defect detection.