8results about How to "Generate flexible" patented technology

The present disclosure relates to systems, methods, and non-transitory computer-readable media for performing interactive digital image editing operations with machine learning models and feature backpropagation refinement layers. For example, the disclosed systems perform interactive digital image editing operations by incorporating a feature backpropagation refinement layer into a non-interactive machine learning model that utilizes a consistency loss to adjust the feature backpropagation refinement layer according to one or more user interactions. In some embodiments, the disclosed systems utilize a feature backpropagation refinement layer that includes a bias sublayer for localizing changes to a digital image and a convolution sublayer for per-channel scaling and feature combination across channels. In some cases, the disclosed systems utilize a consistency loss that facilitates localized modifications to a digital image based on a distance of various pixels or features from a user interaction.

The embodiment of the invention provides a method and a device for dynamically generating an upper computer interface of a battery management system. The method for dynamically generating the upper computer interface of the battery management system comprises the following steps: acquiring parameter information of a plurality of battery parameters corresponding to a battery module in the battery management system; reading a configuration file generated by a user through user-defined configuration, analyzing the configuration file to obtain a template view corresponding to the parameter information, and obtaining a binding relationship between different battery parameters and different template controls; determining target template controls bound with the plurality of battery parameters according to the binding relationship, and combining the target template controls according to the template view to generate an initial upper computer interface; and based on the binding relationship, dynamically filling the target template control in the initial upper computer interface with the parameter information, and generating a target upper computer interface for visual display.

The invention discloses a Chinese character font generation method and a terminal, and the method comprises the steps: obtaining a font file, and extracting a Chinese character image set from the font file, the Chinese character image set comprising a first source font image set and a first target font image set; training a font generation model according to the first source font image set and the first target font image set, and inputting a second source font image set into the trained font generation model to obtain a second target font image set; and converting the second target font image set into a vector image set, and creating a new font file according to the vector image set. Through the trained font generation model, the second target font image set is generated according to the second source font image set, automatic image generation and image visual style conversion are realized, the generated bitmap image is converted into the vector image, the font is created according to the vector image, the font design efficiency is improved, and the font design efficiency is improved. And diversified design requirements and application scenes are met.

The invention provides a component editing method which comprises the steps that a game editing scene is displayed in a graphical user interface, and the game editing scene comprises a plurality of virtual components; and in response to a selection operation for a first virtual component and a second virtual component in the plurality of virtual components, displaying an associated display effect of the second virtual component in a target surface area of the first virtual component, the associated display effect being determined based on visual features of the second virtual component. Therefore, the user can directly use the existing component in the scene to generate the sticker effect and preview the sticker effect in real time without the tedious process of screenshot, export and reimport.

The application discloses a model training method, an address positioning method, an electronic device, a storage medium and a computer program product, relates to the technical field of large models and image positioning, and the method comprises the following steps: acquiring a training data set, wherein the training data set comprises a training scene image and a visual question and answer data set of corresponding address information of the training scene image; performing cross-view alignment training on an initial multi-modal address positioning model by using the training data set, to generate an intermediate multi-modal address positioning model; and performing address positioning training on the intermediate multi-modal address positioning model by using the training data set, to generate a target multi-modal address positioning model, wherein the target multi-modal address positioning model is used for performing address positioning analysis on a target scene image to be processed and an address question, to obtain an address answer. The application solves the technical problems of the image address positioning scheme provided in the related art, such as coarse positioning granularity, poor positioning accuracy and poor flexibility of question and answer interaction.

The application provides a digital human generation method and device based on a multi-modal large model, relates to the technical field of digital human generation, breaks through the generation limitation of traditional key points or three-dimensional representation based on posture, and can generate a digital human image that is natural and delicate in target parts. The method comprises the following steps: acquiring multi-modal data input by a user and performing intention recognition and emotion analysis based on a multi-modal large model to determine audio sequence data corresponding to response text data; acquiring visual feature vector representation of reference image data; determining mask feature vector representation corresponding to the target part according to the position of the target part of the character in the reference image data; performing denoising processing on at least one noise vector representation based on a diffusion model according to the audio sequence data, the visual feature vector representation and the mask feature vector representation to generate at least one frame of image data of a digital human; and generating a digital human animation with voice according to the at least one frame of image data of the digital human and the audio sequence data.

This invention discloses a laser array pointing error control system based on a programmable intensity gradient potential well, relating to the field of laser technology. This invention uses a programmable intensity gradient potential well as optical hardware to replace the traditional camera imaging method, eliminating the need for complex backend software calculations and reducing the complexity and development cost of the application system. Simultaneously, it can flexibly generate various dynamic intensity gradient potential wells, meeting the needs of cutting-edge research in light field manipulation technologies such as controllable scanning of synthetic light spots on extended targets and generation of special light fields. It overcomes the challenge of not being able to achieve array beam pointing error correction and dynamic scanning for extended targets using only fixed intensity gradient information. By placing the programmable intensity gradient potential well in front of the photosensitive surface of the photodetector, the two together construct a dynamic intensity gradient potential well based on transmittance, establishing a mapping relationship between the light intensity information of the photodetector and the light spot position information.

The embodiment of the disclosure provides a data dashboard generation method, device, equipment, storage medium and product, through responding to receiving a dashboard generation instruction, performing semantic recognition on a natural language in the instruction to obtain a dashboard parameter; based on the dashboard parameter, generating a layer generation instruction, the layer generation instruction containing a layer parameter of a to-be-generated layer; based on the layer generation instruction, generating a layer generation code corresponding to the to-be-generated layer; based on the layer generation code, rendering and generating a dashboard vector diagram, which realizes automatic and efficient generation of a dashboard vector diagram based on a natural language in a dashboard generation instruction, and further helps to improve the efficiency and flexibility of data visualization.