CAD2X - A Complete, End-to-End Solution for Training Deep Learning Networks for Industrial Applications

Abstract

With the growing demand for automation in the manufacturing industry, computer vision-based systems have become a popular tool for tasks such as object detection, object picking, and quality control. One of the main challenges in developing such systems is obtaining enough high-quality training data. In this paper, we present a suite of tools that create artificial training data and applies it to solve industrial problems. CAD2Render is a tool for generating synthetic images, starting from a 3D CAD model, which can be used to create large datasets with a large spectrum of controlled variations. CAD2Detect uses these synthetic images to train object detection models. CAD2Pose focuses on estimating the 6 degree of freedom pose of objects in images. Finally, CAD2Defect uses anomaly detection to identify defects in manufactured parts. Overall, the CAD2X suite provides a comprehensive set of tools for training computer vision models for manufacturing applications, while minimizing the need for large amounts of real training data. We demonstrate the effectiveness of our approach on a range of industrial use cases.