Glass Inspection with Computer Vision

James Gallagher's guide, "Glass Inspection with Computer Vision," outlines the process of using computer vision models to identify defects in glass with high accuracy, such as scratches, blemishes, and chips. The guide details how to build a vision system by first creating a Roboflow project to store data and models, then collecting and annotating images of glass defects, training a model with this data, and finally deploying the model using Roboflow Inference. The process emphasizes using representative data from the specific environment where the model will be implemented to optimize performance. Gallagher provides step-by-step instructions, including setting up and labeling images with Roboflow, generating a dataset version, training the model from a Microsoft COCO checkpoint, and deploying it for practical use, while also offering guidance on improving model accuracy through preprocessing and data augmentation. This system can be applied to various types of glass, from solar panels to bottles, and the Roboflow sales team is available for assistance in developing custom computer vision solutions for different industries.