Abstract: A training method for a handwritten text image generation model includes: obtaining training data including a sample content image, a first sample handwritten text image and a second sample handwritten text image, constructing an initial training model; obtaining a first predicted handwritten text image by inputting the sample content image and the second sample handwritten text image into an initial handwritten text image generation model of the initial training model; obtaining a second predicted handwritten text image by inputting the sample content image and the first sample handwritten text image into an initial handwritten text image reconstruction model of the initial training model; training the initial training model according to the first and second predicted handwritten text images and the first sample handwritten text image; and determining a handwritten text image generation model of the training model after training as a target handwritten text image generation model.

Abstract: According to embodiments of the present disclosure, a map constructing method, a positioning method, and a wireless communication terminal are provided. The map constructing method includes: a series of environment images of a current; first image feature information of the environment image is obtained, where the first image feature information includes feature point information and descriptor information and based on the first image feature information, a feature point matching is performed on the environment images to select keyframe images; depth information of matched feature points in the keyframe image are acquired, based on the feature point information; and map data of the current environment are generated based on the keyframe images, where the map data includes the image feature information and the depth information of the keyframe image.