Research and Development of Machine Vision Algorithm Performance Evaluation System in Complex Scenes

Abstract

In recent years, deep learning technology has gained widespread attention and has been successfully applied in various applications, including machine vision for automatic driving. However, one of the major challenges in this field is the ability of AI models to perform well in complex scenes with varying weather conditions and lighting conditions. The proposed scheme uses VR technology to simulate different weather conditions and lighting conditions and to evaluate the performance of AI products in such complex scenes. To further enhance the generalization capabilities of AI models, the Software Development Kit has been updated with complex scene data with configurable parameters, and training data with typical characteristics according to machine vision tasks. This approach has the potential to significantly improve the accuracy and reliability of machine vision systems for automatic driving, ultimately enhancing their safety and effectiveness.