An image processing method, comprising: in response to detecting that a number of images in an image set to be processed exceeds a preset threshold, acquiring a first cluster dimension applied to obtain the image set to be processed based on a cluster tag of the image set, wherein the cluster tag is generated by clustering images to obtain the image set to be processed and the cluster tag comprises the first cluster dimension; selecting a second cluster dimension from a plurality of pre-stored dimensions, the second cluster dimension being different from the first cluster dimension; and clustering the images in the image set according to the second cluster dimension to acquire a plurality of first image subsets of the image set, the first cluster dimension and the second cluster dimension each being a criterion for performing clustering of images; wherein, detecting that the number of images in the image set to be processed exceeds the preset threshold further comprises: acquiring a cluster level of the image set, wherein a child image set of an image set having an N th level has an (N+1) th level, where N is an integer greater than 1; acquiring a threshold corresponding to the cluster level as the preset threshold; and detecting whether the number of images in the image set exceeds the preset threshold; wherein, cluster dimensions are different for different cluster levels and different preset thresholds are set for different cluster levels, and the preset threshold for the N th level is higher than the preset threshold for the (N+1) th level. in response to detecting that a number of images in an image set to be processed exceeds a preset threshold, acquiring a first cluster dimension applied to obtain the image set to be processed based on a cluster tag of the image set, wherein the cluster tag is generated by clustering images to obtain the image set to be processed and the cluster tag comprises the first cluster dimension; selecting a second cluster dimension from a plurality of pre-stored dimensions, the second cluster dimension being different from the first cluster dimension; and clustering the images in the image set according to the second cluster dimension to acquire a plurality of first image subsets of the image set, the first cluster dimension and the second cluster dimension each being a criterion for performing clustering of images; wherein, detecting that the number of images in the image set to be processed exceeds the preset threshold further comprises: acquiring a cluster level of the image set, wherein a child image set of an image set having an N th level has an (N+1) th level, where N is an integer greater than 1; acquiring a threshold corresponding to the cluster level as the preset threshold; and detecting whether the number of images in the image set exceeds the preset threshold; wherein, cluster dimensions are different for different cluster levels and different preset thresholds are set for different cluster levels, and the preset threshold for the N th level is higher than the preset threshold for the (N+1) th level. acquiring a cluster level of the image set, wherein a child image set of an image set having an N th level has an (N+1) th level, where N is an integer greater than 1; acquiring a threshold corresponding to the cluster level as the preset threshold; and detecting whether the number of images in the image set exceeds the preset threshold; wherein, cluster dimensions are different for different cluster levels and different preset thresholds are set for different cluster levels, and the preset threshold for the N th level is higher than the preset threshold for the (N+1) th level. <EOS>