This is a repository of multi-dimensional evaluation frameworks for computer vision deep learning models.
This open-source project aims to develop a multi-dimensional evaluation framework for computer vision deep learning models, including accuracy, fairness, transferability, and robustness. The framework provides a set of evaluation methods and indicators for each dimension to help users gain a comprehensive understanding and compare the performance of different models. These evaluation methods and indicators have been rigorously researched and validated to improve the objectivity and accuracy of model evaluation. In addition, the framework provides visualization and report generation tools to help users gain a more intuitive understanding of the evaluation results. Overall, this framework helps improve the reliability, stability, and usability of computer vision deep learning models.