Application of image processing and resnet 50-model in diagnosing defects in mechanical product details

Machine learning and computer vision play pivotal roles in detecting product defects across various industries, enhancing effectiveness, precision, and minimizing labor expenditures. This journalutilizes image manipulation through the OpenCV, coupled with machine learning employing the ResNet-50 model, to specifically identify surface defects and dimensions in bearings.