Scene image labeling method based on coarse-fine granularity multi-image multi-label learning

The invention provides a scene image labeling method based on coarse-fine granularity multi-image multi-label learning, and relates to the technical field of image classification. The method comprisesthe following steps: firstly, obtaining an original scene image data set and a corresponding label set, and carrying out data preprocessing on the original scene image data set to obtain a multi-image data structure, namely an image packet; defining a graph-kernel-based graph-level score function and a packet-level score function of each label; constructing an objective function based on sortingloss; and optimizing a target function based on sorting loss through a sub-gradient descent algorithm to obtain an optimal weight value of each label, and then constructing a graph-level classifier and a packet-level classifier to realize prediction of a label set of an unknown multi-graph data packet and a label set of graphs in the packet and complete labeling of a scene image. Label predictionis allowed to be carried ou