UI Picture-to-DSL Data Page Rendering With Automated Correction
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Solution Overview
Problem
Existing data page generation methods using domain-specific languages (DSL) are inefficient, prone to errors, and require significant manual intervention and communication, leading to high costs and low efficiency.
Innovation Solution
A data page generation method utilizing a multimodal large model to automatically recognize components and layout in a user interface picture, convert natural language descriptions to DSL codes, and perform rendering, with preprocessing and correction rules to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual methods are used to construct data pages by clicking and dragging components, then the process allows direct visual control and component placement, but the generation efficiency is low and requires significant manual intervention
Solution Approach 1:
The system automatically recognizes components and their layouts from UI pictures using a multimodal large model, and generates DSL codes without requiring manual clicking and dragging operations. The system serves itself by converting visual information directly into executable code, eliminating the need for manual component placement while maintaining accuracy through automated image recognition and code generation capabilities.
2Productivity
If automated methods are used to generate data pages, then generation efficiency improves, but accuracy and precision may deteriorate due to automation errors
Solution Approach 1:
The system incorporates a correction module that uses pre-established correction rules to review and refine the generated DSL codes. This feedback mechanism identifies and corrects potential errors in component recognition and code generation, ensuring high accuracy while maintaining automated efficiency. The correction rules act as a quality control layer that validates the output against expected patterns and standards.
3Reliability
If manual construction methods are used, then error rates are lower due to human verification, but communication costs and manual effort increase significantly
Solution Approach 1:
The multimodal large model acts as an intermediary between the UI picture and the DSL code generation process. It automatically performs the verification and translation functions that would otherwise require manual human intervention and communication. The model bridges the gap between visual design and executable code, eliminating the need for back-and-forth communication between stakeholders while maintaining reliability through its built-in recognition and validation capabilities.
4Manufacturing precision
If complex preprocessing and correction procedures are added to enhance accuracy, then manufacturing precision improves, but device complexity increases
Solution Approach 1:
The system performs preprocessing of the UI picture before main recognition, including tasks such as image enhancement and normalization. Correction rules are pre-established and applied systematically to the generated codes. These preliminary actions prepare the data and establish validation frameworks in advance, improving accuracy while managing complexity through structured, pre-planned processing steps rather than ad-hoc complexity.
Data Source
AI summary
The present disclosure provides a data page generation method and a related device. The data page generation method includes: recognizing components and a layout of the components in a user interface picture based on a multimodal large model to obtain a natural language page description corresponding to the user interface picture; converting the natural language page description into domain-specific language codes corresponding to the user interface picture; and performing data page rendering based on the domain-specific language codes to generate a data page corresponding to the user interface picture.