Machine learning method distinguishing foreground and background of image

Abstract

A method used in application of training a model of machine learning is described. Foregrounds and backgrounds of a first image are distinguished to generate a first mask image. The first image is cropped to generate second and third images. The first mask image is cropped to generate second and third mask images. Positions of the second and the third mask image correspond to positions of the second and the third image, respectively. First and second feature vector groups of the second image and the third image are generated by a model. A first matrix is generated according to the first and second feature vector groups. A second matrix is generated according to the second and third mask images. A function is generated according to the first and second matrices. The model is adjusted according to the function.