43 results about "Design intent" patented technology

In various embodiments, a computer-implemented method for generating a design object comprises combining at least two of a design intent text or one or more non-textual inputs to generate a multimodal prompt, executing a trained machine learning (ML) model on the multimodal prompt to generate a design object, and displaying the design object in a design space.

The invention relates to the technical field of gift packaging three-dimensional modeling, and discloses a construction method of a gift box packaging design three-dimensional model. The method comprises the following steps: collecting natural language description, a freehand sketch image and a physical material attribute parameter; analyzing a natural language to construct a design intention map, and analyzing a sketch to generate a geometric feature code; performing knowledge alignment fusion on the two to form enhanced design semantic representation; generating an initial three-dimensional design framework by using a generative design algorithm; material parameters are integrated, compatibility simulation test is carried out, parameter self-adaptive adjustment circulation is started according to a feasibility evaluation report, and component parameters are dynamically optimized; and rendering and outputting a final model. Through deep fusion of multi-modal design information and preposed dynamic optimization of physical attributes, the accuracy of design intention expression and the producibility of a three-dimensional model are improved, and automation and intelligentization of a design process are realized.

The invention relates to the technical field of layout design, and particularly provides a PCB layout design verification method, system and device and a medium, and the method comprises the steps: extracting a design intention from a design demand text through a natural language processing technology; querying design constraint parameters from a pre-constructed knowledge graph based on the design intention; generating a dynamic verification rule according to the design constraint parameter; and verifying the design parameters in the PCB layout by using a rule engine and applying the dynamic verification rule, and outputting a verification result. According to the invention, the verification efficiency is improved, and the rework rate caused by constraint deficiency is reduced.

The invention relates to the technical field of integrated circuit design automation, and discloses an integrated circuit design whole-process collaborative verification and consistency guarantee method, which comprises the following steps of: constructing a unified design data model, and representing design data from function specifications to physical layout by using a multi-level attribute graph structure; establishing a design intention keeping mechanism, and tracking the transmission of the design intention in the hierarchical refinement process through intention semantic annotation, cross-level entity mapping and intention keeping degree evaluation; executing a hybrid verification strategy, combining formalized verification with dynamic simulation, and guiding verification resource allocation through a coverage rate feedback mechanism; performing constraint consistency check, performing constraint comparison at key nodes of the design process, and automatically identifying and positioning constraint conflicts; according to the method, the capture time of design errors can be brought forward by 80%, the number of design iterations is reduced by 40%, and the design quality and efficiency are remarkably improved.

The embodiment of the invention discloses a design code generation method based on cloud service. The method is applied to a cloud management platform. According to the method, the dominant design intention input by the user can be obtained from the configuration interface, and the target design knowledge associated with the current dominant design intention of the user can be inquired from the knowledge graph so as to capture the implicit design intention implicit to the target design object. Thus, the dominant design intention and the target design knowledge from the knowledge graph can be combined to guide the large language model to efficiently and accurately generate the target design code meeting the design requirement of the user, intelligent generation of the target design code is achieved, the design task is accurately and efficiently achieved according to the target design code, and the user experience is improved. And obtaining a target design object.

Disclosed in the embodiments of the present application is a cloud service-based design code generation method, the method being applied to a cloud management platform. The method can not only acquire from a configuration interface an explicit design intention input by a user, but also query a knowledge graph for target design knowledge associated with the current explicit design intention of the user so as to capture an implicit design intention of a target design object. Thus, the explicit design intention and the target design knowledge from the knowledge graph can be combined to guide a large language model in efficiently and accurately generating target design code that meets a design requirement of the user, thereby intelligently generating the target design code so as to accurately and efficiently implement a design task on the basis of the target design code to obtain the target design object.

The invention provides a method and system for generating cultural and creative contents based on large model fine tuning, and the method comprises the steps: processing cultural symbols in text description data through employing a text analysis technology according to an initial feature vector, and building a correlation mapping relation between visual features and cultural semantics; obtaining similar design element clusters according to different culture backgrounds through the structured design resource library, and judging design logic consistency in the clusters; according to the design logic consistency judgment result, processing the similar design element cluster by adopting an iterative optimization technology to obtain an optimal design element combination scheme; if semantic conflicts exist in the optimization design element combination scheme, combination parameters are adjusted, and a final adaptive design intention expression form is determined; and through the final adaptive design intention expression form, generating a creative and cultural design content fusing traditional and modern styles, and obtaining an output result with uniqueness.

The embodiment of the invention discloses an industrial model generation method. The method comprises the steps that a design intention input by a user is acquired, and the design intention comprises related information for generating a target industrial model; a first industrial model matched with the design intention is retrieved from an industrial model database, the first industrial model serves as a reference model, and according to the design intention, basic appearance fitting, independent appearance subcomponent fitting and surface concave-convex detail fitting are conducted on the first industrial model, so that a second industrial model serving as a target industrial model is obtained. According to the method, the multi-modal intention input by the user is understood, the industrial model meeting the multi-modal intention is matched in the model database to serve as the reference model, meanwhile, the basic model is continuously optimized based on deep understanding of the multi-modal intention input by the user, and the industrial model meeting the design intention of the user can be rapidly and accurately generated.

In various embodiments, a computer-implemented method for generating a design object comprises generating a prompt within a design space generated by a design exploration application, wherein the prompt has a prompt definition that includes at least design intent text, and a prompt volume that occupies a portion of the design space and exerts a sphere of influence within the prompt volume, executing a trained machine learning (ML) model on the prompt to generate the design object, and displaying the design object within the prompt volume.

The invention discloses an agent security execution control method and system, and relates to the technical field of artificial intelligence, and the method comprises the following steps: receiving a natural language input of a user, analyzing a spoken language demand into a structured design intention expression through an intention analysis agent, and obtaining a structured design intention expression; the design intention representation at least comprises a target entity, an operation constraint and an acceptance condition; on the basis of the design intention representation, relevant context information is retrieved from design data and a rule base through a retrieval enhancement agent until the retrieval coverage degree and the key anchor point positioning confidence degree reach preset threshold values; by introducing multi-agent cooperation and a natural language driven normal form, a DFT design process is upgraded from tedious and error-prone manual script writing to an intention-driven automatic closed loop. The system can automatically analyze the spoken requirements of the user, intelligently retrieve the design context and generate an interpretable and rollback execution plan, so that engineers are liberated from underlying commands and primitive operations, and the design efficiency is remarkably improved.

The present application relates to the technical field of gift packaging three-dimensional modeling, and discloses a kind of construction methods of gift box packaging design three-dimensional model.The method includes collecting natural language description, hand-drawing sketch image and physical material attribute parameter;Analysis natural language construction design intent graph, analyze sketch to generate geometry feature code;The knowledge alignment fusion of the two forms enhanced design semantic representation;Initial three-dimensional design framework is generated using generative design algorithm;Integrate material parameters and carry out compatibility simulation test, start parameter self-adaptive adjustment cycle according to feasibility evaluation report, dynamically optimize component parameters;Render output final model.Through the deep fusion of multi-modal design information and the preposition of physical attributes dynamic optimization, the accuracy of design intent expression and the producibility of three-dimensional model are improved, and the automation and intelligentization of design process are realized.

The invention provides an automatic programming method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a design demand of a project through an editor, sending a project-containing design request to a predictor, executing prediction through the predictor according to the design demand, returning a plurality of project design intentions to the editor, determining a target design intention from the plurality of project design intentions through the editor, and sending a project programming request to the predictor, executing programming design by the predictor based on the target design intention, and returning programming data to the editor, so that the editor generates an application program of the project. Therefore, through cooperation of the predictor and the editor, intelligent processing from project design requirements to project program generation is achieved, programming efficiency is improved, and design requirements of different application scenes can be accurately met.

This invention discloses a rapid interactive and verification method for mold structures based on wireframe preview, applied to a computer-aided design system. The method includes: receiving and loading a parametric 3D structural model of the target mold; parsing the 3D structural model, extracting and registering the driving design parameters, and generating a parameter registry; constructing and displaying a lightweight wireframe preview model representing the structural outline based on the parameter values ​​in the parameter registry; adjusting the design parameters, updating the parameter values ​​in the parameter registry in real time, and driving the wireframe preview model to update synchronously; after confirming that the updated wireframe preview model meets the design intent, driving the computer-aided design system to generate the final 3D solid structure based on the final parameter registry. This invention significantly improves the efficiency of mold structure design by providing real-time preview and rapid adjustment interaction during the design process.

This invention relates to the field of PCB layout design technology, specifically providing a PCB layout design verification method, system, device, and medium, comprising: extracting design intent from design requirement text using natural language processing technology; querying design constraint parameters from a pre-constructed knowledge graph based on the design intent; generating dynamic verification rules according to the design constraint parameters; applying the dynamic verification rules using a rule engine to verify the design parameters in the PCB layout, and outputting the verification results. This invention improves verification efficiency and reduces the rework rate caused by missing constraints.

The invention relates to the technical field of building information processing, and discloses a building interior design and construction integrated platform based on a BIM technology, and the platform can analyze a semantic design intention label preset in a building information model, and converts the semantic design intention label into a formalized engineering constraint condition; based on the engineering constraint condition and the construction process knowledge graph, generating a final-version construction instruction packet through multi-dimensional simulation rehearsal; in the construction process, the platform collects on-site actual execution data, and compares and analyzes the actual execution data with the plan data in the instruction packet to identify systematic deviation; and finally, according to the identified systematic deviation, the platform updates the construction technology knowledge graph under a man-machine collaborative auditing mechanism. According to the method, a data closed loop from the design intention to the construction practice and then to the core knowledge base is constructed, the technical problems that design and construction are disjointed and the plan performability is low are solved, and self-evolution and continuous optimization of a construction knowledge system are achieved.

This invention provides a controllable intelligent regeneration method for architectural contexts based on the Flux large-scale model ecosystem. The method involves inputting a design model drawing into the ComfyUI interface and reading its dimensions; determining the modeling accuracy of the design model drawing and matching it with the corresponding basic shape control algorithm; inputting an architectural context reference image and generating architectural context prompts; setting a style transfer model sequence and connecting it to a Flux large-scale model-based image generation module to obtain an architectural context rendering image; determining whether the architectural context rendering image conforms to the design intent; if it does, it is directly output; otherwise, precise modification and regeneration of the rendering image are completed through text control; finally, the architectural context rendering image is enlarged and restored to generate a high-resolution architectural context rendering image, which is then output. This invention solves problems such as insufficient intelligence in the image generation process, the need for manually written prompts, reliance on manual selection for modification results, and deficiencies in the quality and content matching of architectural context rendering images.

The application relates to the technical field of front-end development, and in particular to a code generation method and device based on semantic marking, equipment and a medium. The method system performs semantic recognition on a design draft, determines component requirement information, extracts the design intention in the design draft, then matches the component requirement information with meta information, associates the design intention with code semantics, after the matching is completed, extracts the code structure of the component element, extracts the text content of the corresponding to-be-converted component, and injects the text content into the code structure, realizes the restoration of the static structure, injects the variable declaration into the code after the text injection, realizes the support for dynamic data binding, and generates the final code. The application can be applied to business scenarios such as digital finance and intelligent medical treatment, thereby automatically matching the component intention in the design draft with the code library component semantic understanding, so as to accurately generate code according to the design draft.

The embodiment of the invention provides a software processing method and device which are used for quickly determining the design intention of software, so that a user can clearly know the design architecture of the software. The scheme relates to the technical field of software engineering. Through the scheme, the computing device can perform design mode analysis on the code of the target software to obtain the design information of at least one design mode contained in the software. Thus, a user or a computing device can quickly determine the design intent of the software through the design information of the design mode in the software, so that the user can clearly know the design architecture of the software.

In various embodiments, a computer-implemented method for generating a design object includes generating a cue within a design space generated by a design exploration application, where the cue has a cue definition including at least a design intent text, and a cue volume, the cue volume occupies a part of the design space and an influence range is applied in the cue volume; executing a trained machine learning (ML) model on the cue to generate the design object; and displaying the design object within the cue volume.

The present invention discloses a method for extracting design intent of large-scale engineering equipment based on multimodal data fusion, which belongs to the technical field of engineering design intent extraction, and comprises the following steps: classifying historical project design resources to form multimodal resources, extracting multimodal feature vectors through a multi-branch unimodal feature extraction network based on a convolutional neural network and an encoder, fusing component model feature vectors in the multimodal vector through a unimodal feature fusion network based on a self-attention mechanism to obtain a component fusion feature vector, and fusing the multimodal feature vectors through a multimodal feature fusion network to obtain a design intent feature vector. The present invention combines the characteristics of multimodal design resources, retains the association information between components, improves the accuracy of extraction, can assist design tasks in the design process of large-scale engineering machinery equipment, reduces design overhead in the design process of large-scale engineering machinery equipment, and reduces design change losses caused by design errors.

The invention relates to the technical field of constructional engineering digital design, and particularly discloses a constructional engineering geometric constraint solving method and system based on a design intention. And the high-dimensional nonlinear equation set is converted into cascade solution of a plurality of low-dimensional subsystems. A single geometric constraint system is sequentially calculated in order, and the degree of freedom corresponding to each calculation is solved, so that the calculation complexity is remarkably reduced; on one hand, for an unfixed geometric constraint system, a fixed geometric constraint condition conforming to a building design intention is added; and on the other hand, when the geometric constraint is solved, only the constrained degree of freedom of the component primitive is calculated, so that the solving result is more in line with the design intention.

The invention relates to the technical field of power equipment model design, and provides a design intention-based design control automatic configuration system, which comprises a control self-defining module, a grouping ID (Identity) generation module, a design intention-based design control automatic configuration module and a design intention-based design control automatic configuration module, the intention recognition module is used for receiving a user instruction, determining user intention information corresponding to the user instruction and generating a legend style based on the user intention; and the operation control module is used for executing automatic marshalling according to the marshalling ID when the user determines the legend style, and generating a control configuration scheme.

The invention relates to the technical field of computer-aided design, and discloses a computer-aided design method for automatically generating and reflecting a design intention, and the method comprises the steps: carrying out the cooperative work of a design intention understanding module, a design knowledge base module, a design scheme generation module and a design scheme optimization module; the intelligent analysis of the design intention of the user and the generation of the automatic design scheme are realized. The design intention understanding module adopts natural language processing and machine learning technologies to accurately extract user requirements; the design knowledge base module stores a large number of design rules and parameters and provides reference for design; the design scheme generation module automatically creates a preliminary design scheme according to user requirements and knowledge base information; and the design scheme optimization module performs performance improvement on the design scheme through an optimization algorithm. The method improves the design efficiency, reduces the number of design iterations, reduces the manpower and time cost, is suitable for various engineering design fields, and has a wide application prospect.

An embodiment of the present application discloses a design code generation method based on cloud services, and this method is applied to a cloud management platform. In this method, not only can explicit design intentions input by users be obtained from the configuration interface, but also target design knowledge associated with the current explicit design intentions of users can be queried from the knowledge graph to capture implicit design intentions for target design objects. In this way, the explicit design intentions and the target design knowledge from the knowledge graph can be combined to guide the large language model to efficiently and accurately generate target design codes that meet the design requirements of users, realizing the intelligent generation of target design codes, and accurately and efficiently implementing design tasks according to the target design codes to obtain target design objects.

In various embodiments, a computer-implemented method for generating a design object comprises generating a prompt within a design space generated by a design exploration application, wherein the prompt has a prompt definition that includes at least design intent text, and a prompt volume that occupies a portion of the design space and exerts a sphere of influence within the prompt volume, executing a trained machine learning (ML) model on the prompt to generate the design object, and displaying the design object within the prompt volume.

The invention discloses a man-machine mutual cognition concept design method and device based on deep learning and knowledge management, and the method comprises the steps: collecting operation data in a concept design process of a designer, and obtaining a design image and a design description; marking a design image and a design description, and mapping the design image and the design description to a design intention to obtain a private design multi-modal data set of a designer; dividing the private design multi-modal data set into a training data set and a test data set; training the deep learning network by using the training data set to obtain a model pre-training weight of the recognition model; calling a model pre-training weight, and performing design intention recognition on the test set through the recognition model to obtain a to-be-fed-back design intention; using a design knowledge matching framework to match design knowledge concerned by a designer from a design knowledge base based on the to-be-fed-back design intention; and according to a design knowledge matching result, recommending to a designer in sequence by utilizing a knowledge recommendation algorithm. According to the method, the man-machine cooperation efficiency of the conceptual design is effectively improved.

The invention discloses a folk art product aided design system and method, and relates to the technical field of computer aided design, the folk art product aided design system comprises a behavior data acquisition unit for acquiring operation records in a user design process; the design state recognition unit recognizes a design intention state corresponding to the operation; the creative stage division unit divides design stages according to intention state transition; the style venation extraction unit is used for extracting a similar mode of a multi-user graphic element adoption sequence in the creative stable stage to form a style evolution venation diagram; the creative contribution evaluation unit is used for comprehensively designing the intention state, the style evolution venation diagram and the color scheme to adjust the path intersection and calculating the creative contribution degree of the user; and the auxiliary strategy matching unit generates an auxiliary strategy according to the contribution degree and the intention state combination. According to the method, dynamic analysis and accurate assistance of the multi-user collaborative design process are realized.

The application discloses a kind of high fidelity style reference relationship cognitive enhancement methods for collaborative intelligent agent and related devices, wherein the method comprises: generating design context vector according to fine-grained interactive behavior flow and the structure metadata of current design document;According to the design context vector, a dynamically evolving design cognitive ontology is constructed, and an initial design cognitive graph is constructed according to the design cognitive ontology and cross-document reference link;The initial design cognitive graph is input into the comparative graph neural network and causal reasoning network model to identify implicit style reference and design intent, and output high-order reference relationship graph with intent label and confidence;According to the high-order reference relationship graph, the origin node and evolution tree of the design element, the use context and team consensus intensity score are dynamically presented.The application realizes the systematic representation and organization of design style knowledge, improves the accuracy of design style reference relationship identification, dynamically analyzes and predicts the evolution trend of design style, and provides support for design decision.

The application provides a jig scheme generation method, system, device and storage medium, relates to the technical field of artificial intelligence, and fundamentally changes the condition that traditional design seriously depends on manual experience, a process is discrete, and consistency is poor. Through standardization semantic modeling of clamping requirements, the bottleneck that a design intention is not machine-readable is solved. Through deep integration of structure constraint rules and a large model, it is ensured that the generated scheme meets functional requirements and engineering feasibility, so that automation, intelligentization and standardization of the design process are realized, and design efficiency, scheme reliability and knowledge reuse level are significantly improved.

For lithography mask layout verification, training data is collected for each design intent in a set of design intents by identifying a set of failures expected to occur during the fabrication of the design intent and recording the failure mode and location of each failure in the set of failures. Next, the training data is used to train a machine learning model, such as an artificial neural network, to predict the failure mode and location of failures. Then, the trained machine learning model is used to predict a set of failures for a given design intent. Next, for each predicted failure, a mask enhancement technology (RET) scheme can be selected based on the failure mode of the failure, and the selected RET scheme can be applied to the area around the location of the failure.