The invention provides a
humanoid robot data set quality evaluation method and a
humanoid robot data set quality
evaluation system based on multi-dimensional evaluation, and provides a systematized and standardized evaluation process aiming at the quality problems of the existing
robot multi-
modal data set in the aspects of normalization, integrity, accuracy, consistency, timeliness,
accessibility, availability and the like. According to the method, an automatic tool is combined with manual auditing, the structure,
metadata,
annotation content, data formats, multi-
modal alignment and the like of a data set are comprehensively detected, a
deep learning algorithm is introduced to achieve detection of pornographic pictures and sensitive words of visual content, and content safety and compliance are effectively improved. The
system can flexibly adjust the weight of each evaluation dimension according to different application scenes, automatically generates a quality evaluation report, and supports
continuous monitoring and optimization and improvement. Practical application shows that the method can significantly improve the overall quality of the
robot data set, and provides reliable data basis and
technical support for intelligent training and application of the
robot.