Abstract: Described herein is a system and computer implemented method for finding similars for a selected clothing image amongst a set of clothing images in an electronic catalog in an online store serving online customers. An object detection model is applied to extract the clothing section within the clothing images to create a preprocessed image. A first machine learning model is applied on the preprocessed image(s) to convert the colors and textures of said preprocessed image into a first set of vector representations. A second machine learning model is applied on the preprocessed image(s) to convert the shapes of said preprocessed image into a second set of vector representations. Operations of mapping nearest vectors, matching attributes, sorting and ranking are performed, and thereafter similar images are displayed to the online customer.

Abstract: Described herein is a system and computer implemented method of grouping clothing products by brands within a set of clothing images in an electronic catalog of an internet store serving online customers. Apply an object detection model to extract the dress section within the clothing image(s) to create preprocessed image(s). A machine learning model model is applied to the preprocessed image(s) to convert the image into a vector representation through an unsupervised technique. The vector contains the design features of the clothing image. The design features are representative of the brands. A clustering model is applied on the vector representations to arrive at the grouping of similar images of the clothing products. The grouped clothing products are displayed via a user interface, ordered by brands, to the online customers.