Data visualization method and system based on digital model

Abstract

The invention provides a data visualization method and system based on a digital model. According to the method, in response to a selection instruction acting on a selectable object on a digital model, a model object having an association relationship with the selectable object is determined as a target object, and then target model data corresponding to the target object is loaded to a preferential loading stack in a memory space. According to the method and the device, the model rendering resources are preferentially called for data visualization by using the preferential loading stack as the target model data, so that the target object associated with the current selectable object can be quickly accessed and processed, and the problem of rendering lagging or interruption caused by data loading delay is avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and particularly relates to a data visualization method and system based on a digital model. BACKGROUND

[0002] In the field of data processing and computer graphics, data visualization technology plays a crucial role in presenting complex data in an intuitive and easily understandable manner to users, thereby improving the efficiency and accuracy of data analysis. In particular, in applications involving digital models, such as mechanical design, architectural planning, medical image analysis, etc., data visualization technology can help users better understand and manipulate three-dimensional models, enabling efficient interaction and design optimization.

[0003] However, traditional data visualization methods often encounter rendering lag, delay or even interruption when dealing with high-precision and high-complexity digital models. This is mainly due to the fact that when a user interacts with a digital model (such as selecting, hiding, separating, etc.), the system needs to load and render model data related to the current operation in real time.

[0004] In existing technologies, this process is usually a passive response, i.e., only after receiving explicit operation instructions from the user, the system will start loading and rendering the corresponding model data. This passive loading method leads to a lag in data loading and rendering resource allocation, which cannot meet the real-time and smooth interaction requirements. The delay of lagging data loading and rendering not only affects the user's interaction experience, but also may cause system performance degradation due to improper rendering resource allocation, even causing lag or crash. SUMMARY

[0005] The present application provides a data visualization method and system based on a digital model to ensure that digital model visualization data can be quickly processed and accessed, thereby avoiding rendering lag or interruption problems caused by data loading delay.

[0006] In a first aspect, the present application provides a data visualization method based on a digital model, comprising: In response to a selection instruction acting on a selectable object of a digital model, determining a target object corresponding to the selectable object, wherein the target object is a model object in the digital model that has an association relationship with the selectable object; Loading target model data corresponding to the target object into a priority loading stack in a memory space, wherein the priority loading stack is a storage space in the memory space for preferentially calling model rendering resources for data visualization.

[0007] Optionally, the optional object is an optional surface object, and the target object is a region required to be displayed by the digital model after the optional surface object is hidden.

[0008] Optionally, the target object includes a target surface sequence composed of a plurality of target surfaces. Correspondingly, the loading of the target model data corresponding to the target object into the priority loading stack in the memory space includes: determining the target model data according to the target surface sequence, the target model data including a target model sequence corresponding to the target surface sequence; loading the target model sequence into the priority loading stack in the memory space.

[0009] Optionally, the optional object is an optional component, and the target object is at least one target component in the digital model having an assembly relationship with the optional component.

[0010] Optionally, the target object includes a target component sequence composed of a plurality of target components. Correspondingly, the loading of the target model data corresponding to the target object into the priority loading stack in the memory space includes: determining the target model data according to the target component sequence, the target model data including a target model sequence corresponding to the target component sequence; loading the target model sequence into the priority loading stack in the memory space.

[0011] Optionally, after the loading of the target model data corresponding to the target object into the priority loading stack in the memory space, the method further includes: directly rendering the target model data by the graphics card to form to-be-displayed model data; loading the to-be-displayed model data into the memory space for storage.

[0012] Optionally, after the loading of the target model data corresponding to the target object into the priority loading stack in the memory space, the method further includes: in response to a target instruction acting on the optional object, rendering the target model data by the graphics card to form to-be-displayed model data, wherein the target instruction includes a hiding instruction and a separation instruction; loading the to-be-displayed model data into the current data visualization interface for display.

[0013] In a second aspect, the application provides a data visualization system based on a digital model, including: An acquisition module is configured to acquire a selection instruction for a selectable object acting on a digital model; A processing module is configured to determine a target object corresponding to the selectable object, wherein the target object is a model object in the digital model having an association relationship with the selectable object; A storage module is configured to load target model data corresponding to the target object to a priority loading stack in a memory space, wherein the priority loading stack is a storage space in the memory space for preferentially invoking a model rendering resource for data visualization.

[0014] In a third aspect, the present application provides an electronic device, comprising: a processor; and a memory configured to store executable instructions of the processor; The processor is configured to execute any one of the possible methods of the first aspect by executing the executable instructions.

[0015] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by a processor to implement any one of the possible methods of the first aspect.

[0016] The data visualization method and system based on a digital model provided by the present application can determine a model object having an association relationship with a selectable object as a target object in response to a selection instruction for the selectable object acting on a digital model, load target model data corresponding to the target object to a priority loading stack in a memory space, and implement preferential invocation of a model rendering resource for data visualization for the target model data through the priority loading stack, thereby ensuring that the target object associated with the current selectable object can be quickly accessed and processed, and thereby avoiding rendering lag or interruption caused by data loading delay. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and serve to explain the principles of the present application together with the specification.

[0018] Figure 1 is a flowchart of a data visualization method based on a digital model according to an example embodiment of the present application; Figure 2 is a flowchart of a data visualization method based on a digital model according to another example embodiment of the present application; Figure 3 is a flowchart of a data visualization method based on a digital model according to another example embodiment of the present application; Figure 4 is a structural schematic diagram of a data visualization system based on a digital model according to an example embodiment of the present application; Figure 5 is a structural schematic diagram of an electronic device according to an example embodiment of the present application.

[0019] Through the above figures, the specific embodiments of the present application have been shown, and will be described in more detail hereinafter. These figures and textual descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0020] The example embodiments will be described in detail herein with reference to the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following example embodiments are not meant to represent all implementations consistent with the present application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present application as detailed in the appended claims.

[0021] In the existing digital model data visualization technology, the interaction between the user and the digital model usually adopts a passive response mechanism. Specifically, when the user selects a selectable object (such as a face or a component) on the digital model, the system needs to first receive and analyze the selection instruction, then query other model objects (i.e. target objects) associated with the selectable object in the model database, and finally load and render the data of these target objects. This process has obvious delay, especially when dealing with high-precision and high-complexity digital models, the burden of data loading and rendering increases significantly, leading to frequent problems of rendering lag, delay and even system crash.

[0022] Among them, the limitations of the above-mentioned prior art mainly manifest in the following aspects: Passive response mechanism: data loading and rendering resource allocation lags behind user interaction, which cannot meet the real-time requirement.

[0023] Improper resource allocation: in complex model scenarios, resource competition is intense, which easily leads to performance decline.

[0024] Limited user experience: rendering delay and lag seriously affect the user's interactive experience and operation efficiency.

[0025] In order to solve the above problems in the prior art, the present application proposes a data visualization method and system based on a digital model. The method realizes the optimization of data loading and rendering resource allocation by actively predicting and loading the target model data associated with the user interaction operation in advance.

[0026] Specifically, the technical solution of the present application includes the following two core steps: In response to the selection instruction, the target object is determined: the system captures the user's selection instruction for the selectable object on the digital model on the user interface, and quickly determines the target object associated with the selectable object according to the internally maintained association relationship database.

[0027] The priority loading stack design loads the target model data in advance: a priority loading stack is set in the memory space, and the target model data corresponding to the target object is loaded into the stack in advance, so that the model rendering resources can be quickly called for data visualization when needed.

[0028] The method proposed in the present application is compared with the prior art, and the improvements are embodied in the following aspects: Comparison between active prediction and passive response: the prior art adopts a passive response mechanism, that is, the system starts to load and render related data only after the user issues an operation instruction. This approach causes a delay in data loading and rendering, which cannot meet the real-time requirements. The method proposed in the present application actively predicts the objects that the user is likely to interact with, and loads related data into the priority loading stack in advance. When the user actually issues an operation instruction, the system can directly call the loaded data from the priority loading stack for rendering, thereby significantly reducing the rendering delay. The method provided in the present application changes the data loading process from "passive response" to "active prediction", and prepares data in advance through the preloading mechanism, ensuring real-time performance and smoothness.

[0029] Comparison of resource allocation optimization: in the prior art, resource competition is fierce in complex model scenarios, and the system needs to dynamically allocate rendering resources according to user operations, which easily leads to performance degradation and lag. The method provided in the present application uses the design of the priority loading stack, and the system can preallocate and reserve sufficient rendering resources for the data in the priority loading stack. When rendering is needed, the system can directly call the data from the priority loading stack, avoiding resource competition and performance degradation. The introduction of the priority loading stack in the method provided in the present application realizes the pre-allocation and priority calling of rendering resources, effectively solves the resource competition problem, and improves the system performance.

[0030] Comparison of user experience improvement: due to rendering delay and stuttering, users often encounter unsmooth operation and slow response during interaction, which seriously affects the user experience. The method provided by the application can provide smooth and stutter-free interaction experience by preloading and preferentially calling target model data. Users can immediately see the rendering result when performing operations such as selection, hiding, and separation, greatly improving operation efficiency and satisfaction. The method provided by the application optimizes the data loading and rendering process, significantly improves the user experience, and enables users to interact with digital models more efficiently and enjoyably.

[0031] In order to realize the technical scheme of the application, the application mainly relates to the following key technical points: Construction of association relationship database: an association relationship database is maintained inside the system to record the association relationship between each element in the digital model. The database can be implemented by adjacency table, graph structure or relational database, etc., to ensure fast query and efficient management.

[0032] Management of priority loading stack: the priority loading stack is implemented by using stack data structure, supporting fast push and pop operations of data. The system determines the priority order of data according to the distance between the target object and the camera view, the intersection area size, the assembly order, etc., and loads the high-priority data into the stack first.

[0033] Dynamic adjustment mechanism: during user interaction, the system can dynamically adjust the data order in the priority loading stack to ensure that the most important target surface or component of the current view and the user is always loaded and rendered first.

[0034] Figure 1 is a flowchart of the data visualization method based on digital model according to an example embodiment. As shown in Figure 1 The data visualization method based on digital model provided by the embodiment includes: S101, in response to the selection instruction of the selectable object acting on the digital model, determining the target object corresponding to the selectable object.

[0035] In this step, the target object corresponding to the selectable object can be determined in response to the selection instruction of the selectable object acting on the digital model, wherein the target object is a model object in the digital model that has an association relationship with the selectable object.

[0036] Specifically, a user can be allowed to select a selectable object on the digital model by mouse click, touch screen touch or other input devices on the user interface of the data visualization system. The selectable object can be a face, a component or other predefined model element in the digital model. When a user selects a selectable object, the system captures the selection operation and generates a corresponding selection instruction. The instruction contains the unique identifier or position information of the selected selectable object.

[0037] Then, the system internally maintains an association database or data structure to record the association relationship between various elements in the digital model. For example, an adjacency list, a graph structure or a relational database can be used to store this information. Upon receiving the selection instruction, the system queries the model objects associated with the selected selectable object in the association database according to the ID or position information of the selected selectable object. These model objects are the target objects. For example, if the selectable object is a face, the target objects can be other faces adjacent to the face, or components containing the face, or other faces hidden or deleted by the face (i.e. faces that become visible from the current camera perspective after the face is hidden or deleted). According to the query result, the system determines one or more target objects. These target objects will be the basis for subsequent data loading and rendering. If the target objects include multiple elements (such as multiple faces or components), the system also needs to determine the ordering relationship between these elements in order to perform ordered loading and rendering in subsequent steps.

[0038] S102, loading the target model data corresponding to the target object into a priority loading stack in the memory space.

[0039] In this step, the target model data corresponding to the target object is loaded into the priority loading stack in the memory space, wherein the priority loading stack is a storage space in the memory space for preferentially calling model rendering resources for data visualization.

[0040] Specifically, a priority loading stack can be set up in the memory space to store target model data that needs to be preferentially called for model rendering resources for data visualization. The priority loading stack can be implemented using a stack data structure to support fast push and pop operations of data. It is worth noting that the stack data has the characteristic of first-in, last-out. In order to improve rendering efficiency, the data in the priority loading stack should be stored in a certain priority order. The priority can be determined according to the distance of the target object from the camera perspective, the intersection area size, the assembly order and other factors.

[0041] If the target object includes multiple elements (such as multiple faces or components), the system needs to load the target model data corresponding to these elements into the priority loading stack in the order determined by the sorting relationship. For example, if the faces in the target face sequence are sorted from far to near according to the distance from the camera view, the system also needs to load the data in this order. It is worth noting that the priority loading stack described above can have the highest priority when called in memory. Secondly, the priority loading stack described above can be activated only after the selection instruction described above is detected.

[0042] During the loading process, the system needs to monitor the use of memory space to ensure that there is enough memory for storing target model data. If the memory is insufficient, the system can also take data compression, paging loading and other strategies to optimize memory usage. At the same time, the system also needs to consider the release of data. When the data in the priority loading stack is no longer needed (such as when the user switches the view or selects other selectable objects), the system should release the memory space occupied by these data in time.

[0043] In this embodiment, by responding to the selection instruction of the selectable object on the digital model, the model object associated with the selectable object is determined as the target object, and then the target model data corresponding to the target object is loaded into the priority loading stack in the memory space, so as to realize the priority calling of the model rendering resource for the target model data through the priority loading stack to realize data visualization, thereby ensuring that the target object associated with the current selectable object can be quickly accessed and processed, thereby avoiding the problem of rendering lag or interruption caused by data loading delay.

[0044] It is worth noting that, compared with the prior art in which the model object that needs to be further displayed is loaded only after the operation instruction (for example, the hiding instruction) of the selectable object on the digital model is performed, the target model data in the above embodiment is loaded in advance when the related selectable object is selected, and is loaded into the priority loading stack in the memory which has the highest priority to call the model rendering resource. Compared with the prior art, the above embodiment realizes the three technical effects of reducing rendering delay, improving resource utilization and enhancing interaction adaptability through the cooperation of the selection stage preloading and the priority loading stack scheduling. The core advantage is to change the data loading and rendering resource allocation from "passive response" to "active prediction", which is especially suitable for high-precision and strong-interactive digital model visualization scenarios (such as mechanical design, building planning, medical imaging), and provides underlying technical support for real-time and smooth model operation.

[0045] Figure 2 is a flowchart of a data visualization method based on a digital model according to another example embodiment of the present application. As shown in Figure 2 the data visualization method based on a digital model provided by the present embodiment comprises: S201, in response to a selection instruction of the selectable object acting on the digital model, determine the target object corresponding to the selectable object.

[0046] In this step, the target object corresponding to the selectable object can be determined in response to a selection instruction of the selectable object acting on the digital model, wherein the target object is a model object in the digital model having an association relationship with the selectable object.

[0047] S202, load the target model data corresponding to the target object to a priority loading stack in the memory space.

[0048] In this step, the target model data corresponding to the target object is loaded to a priority loading stack in the memory space, wherein the priority loading stack is a storage space in the memory space for preferentially calling model rendering resources for data visualization.

[0049] In a specific application scenario, the selectable object is a selectable face object, and the target object is a region of the digital model to be displayed after the selectable face object is hidden.

[0050] In the visualization interface of the digital model, the user can directly click or box-select any face in the model as a selectable face object through interactive methods such as a mouse, a touch screen, or gesture recognition. The interface needs to provide a highlight display or contour marking function, and when the user hovers over or selects a face, the face is highlighted with a different color or transparency to clearly feedback the current selectable object. In addition, multiple selection is also supported, and the user can select multiple face objects at the same time, and subsequent perspective processing will be performed uniformly on all selected faces. Furthermore, in the underlying data structure of the digital model, each face object is defined by a list of vertex indices (such as three vertex indices of a triangular face) to define its geometry. Additional attributes include face normal vectors (for lighting calculation and perspective direction judgment), material IDs (associated with texture or color information), and associated model component IDs (for hierarchical model management). When the user selects a face object, the system quickly locates the corresponding face in the model data through the vertex index and extracts its geometry and attribute information.

[0051] The target region can be strictly limited to the part to be displayed after hiding through adjacent face expansion and visibility optimization, avoiding the loading of irrelevant data (such as model external space or completely occluded regions). Furthermore, the target region can also be dynamically adjusted with the camera position and hidden face selection, supporting real-time interactive scenarios (such as 360-degree rotation to observe the hidden model interior).

[0052] In some practical scenarios of possible applications, for example, in the field of mechanical design, the user hides the device shell surface, and the target area automatically contains key components such as internal circuit boards and gear sets, supporting high-precision troubleshooting; in the field of architectural design, the target area is expanded to indoor layout (such as furniture and partitions) after hiding the building outer wall, and the rear irrelevant floors are removed through occlusion culling, improving rendering efficiency; in the field of medical image analysis, the target area dynamically displays subcutaneous tissue (such as muscles and blood vessels) after hiding the skin surface in a three-dimensional human model, and simplifies the details of distant organs through LOD technology to ensure real-time interaction fluency.

[0053] In a possible implementation, the target object includes a target face sequence composed of a plurality of target faces, and the order of the target faces in the target face sequence is inversely related to the distance order between the target faces and the current camera reference point under the current camera view, and the distance order is from far to near. Then, the target model data is determined according to the target face sequence, and the target model data includes a target model sequence corresponding to the target face sequence. The target model sequence is loaded into a priority loading stack in the memory space, so that the storage order of the target models in the priority loading stack is inversely related to the distance order between the target faces and the current camera reference point under the current camera view.

[0054] By sorting the target faces according to the inverse distance relationship with the camera reference point and loading the corresponding target model data into the priority loading stack, the system can ensure that the target face data far from the camera is loaded into the stack first. Due to the last-in-first-out feature of the priority loading stack, the target face data loaded later and closer to the camera is at the top of the stack, which facilitates fast access and rendering. This strategy effectively manages the memory space, so that the distant target face data is loaded first but does not immediately occupy the rendering resources, while the nearby target face data is ready for rendering at any time, thereby optimizing the memory usage.

[0055] In combination with the FILO feature of the priority loading stack, when the camera view changes or the user issues a rendering instruction, the system can quickly obtain the target face data closer to the camera and about to become the visual focus from the top of the stack for rendering. Since this data has been pre-loaded into the stack and is in an immediately accessible state, the rendering response speed is significantly improved. At the same time, the distant target face data is at the bottom of the stack but does not interfere with the current rendering process, ensuring the efficiency and fluency of the rendering process.

[0056] Further, by pre-loading and managing the target face data into the priority loading stack, the rendering delay and lag caused by loading the distant target face data in real time are effectively avoided. During user interaction, such as rotating and scaling the model, the system can quickly adjust the order of the data in the stack (by recalculating the distance and sorting) or directly obtain the required data from the stack for rendering, ensuring real-time interaction and no lag.

[0057] In another possible implementation, the target object includes a target face sequence composed of multiple target faces, wherein the order of the target faces in the target face sequence is the same as the order of the intersection areas between the target faces and the current camera view in the current camera view, and the order of the intersection areas is from large to small. The target model data is determined according to the target face sequence, and the target model data includes a target model sequence corresponding to the target face sequence. The target model sequence is loaded into a priority loading stack in the memory space, so that the storage order of the target models in the priority loading stack is the same as the order of the distances between the target faces and the current camera reference point in the current camera view.

[0058] Firstly, by arranging the target faces in the order of the intersection areas with the current camera view from large to small, the system can accurately identify and prioritize the target faces that have the greatest visual impact in the current view. This ordering strategy ensures that rendering resources are first allocated to the model parts that the user is most likely to focus on, thereby improving the relevance and effectiveness of visual presentation.

[0059] Secondly, according to the ordered target face sequence, the system loads the corresponding target model data into a priority loading stack in the memory space. Then, by using the last-in-first-out feature of the priority loading stack, the most recently loaded (and usually larger intersection area) target model data can be quickly called by the rendering engine, thereby optimizing the overall rendering process. Further, by sorting the target faces in advance and loading them into the priority loading stack, the performance overhead caused by indiscriminate calculation and rendering of all target faces in the rendering stage is effectively avoided. The system can concentrate resources on processing the target faces that contribute most to the current visual presentation, while temporarily ignoring or delaying the processing of target faces with small intersection areas and insignificant visual impact, thereby reducing the burden on GPU and CPU and improving overall rendering efficiency.

[0060] Further, in the application scenario of dynamic view changes, such as user rotation, scaling or translation of the model, the above steps can quickly respond to view changes and recalculate the intersection areas of the target faces with the current camera view. Based on the new ordering results, the system can dynamically adjust the order of the target model data in the priority loading stack to ensure that the most important target faces in the current view are always loaded and rendered first. This dynamic adjustment capability significantly enhances the stability and continuity of the rendering process, avoiding rendering lag or flicker problems caused by view changes.

[0061] S203, directly rendering the target model data by the graphics card to form the to-be-displayed model data.

[0062] By directly utilizing the parallel computing capability of the graphics card to render the target model data in the priority loading stack, the efficiency of data processing is significantly improved.

[0063] S204, load the to-be-displayed model data into the memory space for storage.

[0064] The rendered to-be-displayed model data is loaded into the memory space for storage, which realizes effective management and reuse of the rendering result. By storing the to-be-displayed model data in the memory, the system can quickly read these data when needed, avoiding the performance overhead caused by repeated rendering.

[0065] Moreover, since the to-be-displayed model data has been pre-rendered and stored in the memory, the system can directly read these data from the memory when receiving the display instruction, without the need for rendering calculation again. This process significantly reduces the rendering delay, making the display of model data more rapid and smooth. Especially when dealing with complex models or real-time interaction, the pre-rendering and memory storage strategy can effectively avoid frame freezing or interruption caused by rendering calculation, improving the user experience.

[0066] The above steps, through the pre-rendering and memory storage strategy, enhance the stability and reliability of the system. During the rendering process, the parallel computing capability of the graphics card and the high-speed access characteristics of the memory work together to reduce the risk of system crash or data loss caused by rendering calculation. The storage and quick access of these data in the memory enable the system to guarantee the rendering quality while meeting the user's demand for high-precision and complex scene visualization.

[0067] Figure 3 is a flowchart of a data visualization method based on a digital model according to still another example embodiment. As shown in Figure 3 The data visualization method based on a digital model provided by the embodiment includes: S301, in response to a selection instruction of a selectable object acting on a digital model, determining a target object corresponding to the selectable object.

[0068] In this step, in response to a selection instruction of a selectable object acting on a digital model, the target object corresponding to the selectable object can be determined, wherein the target object is a model object in the digital model that has an association relationship with the selectable object.

[0069] S302, loading target model data corresponding to the target object into a priority loading stack in the memory space.

[0070] In this step, the target model data corresponding to the target object is loaded into a priority loading stack in the memory space, wherein the priority loading stack is a storage space in the memory space for preferentially calling model rendering resources for data visualization.

[0071] Optionally, the optional object is an optional component, and the target object is at least one target component in the digital model that has an assembly relationship with the optional component, i.e., the digital model is an assembly model.

[0072] Further, the target object can include a target component sequence composed of multiple target components, wherein the order of the target components in the target component sequence is in reverse order of the assembly order of the target components in the digital model. Then, the target model data is determined according to the target component sequence, and the target model data includes a target model sequence corresponding to the target component sequence. The target model sequence is loaded into a priority loading stack in the memory space, so that the storage order of the target models in the priority loading stack is in reverse order of the assembly order of the target components in the target component sequence in the digital model.

[0073] Firstly, by setting the order of the target component sequence to be in reverse order of the assembly order of the digital model, the system can automatically establish a rendering priority that is opposite to the actual assembly process. In the assembly process, the components assembled later are usually located at the upper layer or more prominent position of the model, and the reverse order arrangement makes these components enter the priority loading stack first when the data is loaded. This logical matching ensures that the components that are visually more prominent are processed first in the rendering stage, thereby improving the intuitiveness and accuracy of the rendering result.

[0074] Secondly, the last-in-first-out feature of the priority loading stack cooperates with the reverse order arrangement of the target components. When the target model sequence is loaded into the stack, the components assembled later (i.e., the components at the front of the sequence) are pushed to the top of the stack first, while the components assembled earlier are at the bottom of the stack. In the rendering process, the system reads the data from the top of the stack in sequence, which exactly meets the requirement of "rendering the components assembled later first", reducing the randomness of memory access and improving the cache hit rate, thereby optimizing the memory access efficiency.

[0075] Further, since the order of the target models stored in the priority loading stack corresponds to the reverse order of the assembly order, the system does not need to dynamically adjust the data order or perform additional sorting calculations during rendering. When a rendering request is triggered by user interaction (such as hiding or removing), the system can directly obtain data from the top of the stack and render it, avoiding the delay caused by data reorganization. This pre-sorting mechanism significantly improves the response speed of interaction, especially when dealing with complex models, the effect is more obvious.

[0076] In a dynamic assembly scenario, such as simulating the process of installing components one by one, the above steps can be used to dynamically synchronize the rendering order by adjusting the order of the target component sequence (i.e., updating the assembly order in reverse order) and reloading it into the priority loading stack. For example, when a new component is added, the system inserts it at the head of the sequence (i.e., at the end of the assembly order) and reloads it at the top of the stack, ensuring that the new component is displayed first in the rendering.

[0077] Finally, by combining reverse arrangement and priority loading stack, the system avoids unnecessary repeated calculation and data copying. In the traditional method, all parts may need to be globally sorted or depth tested before rendering, while the above steps disperse the calculation amount to the loading stage through pre-sorting and stack management, and only one sorting can support multiple renderings. In addition, the locality principle of the stack (i.e. frequently accessing the top data of the stack) further reduces the data transmission amount between the CPU and the GPU, thereby reducing the overall resource consumption of the system.

[0078] S303, in response to the target instruction acting on the selectable object, rendering the target model data through the graphics card to form the to-be-displayed model data.

[0079] In this step, in response to the target instruction acting on the selectable object, the target model data is rendered through the graphics card to form the to-be-displayed model data, wherein the target instruction includes a hiding instruction and a separation instruction.

[0080] By taking the target instruction (the hiding instruction and the separation instruction) as the rendering trigger condition, the system realizes fine control of the model data rendering process. The hiding instruction can dynamically hide specific parts or model regions, and the separation instruction supports decoupling related parts from the overall model and displaying them independently.

[0081] The target model data stored in the priority loading stack has been sorted according to the preset priority (such as the reverse assembly order in step S302), and when the target instruction is received, the system can quickly locate the model fragment to be processed. For example, when executing the separation instruction, only the data block corresponding to the target part needs to be extracted from the stack for rendering, without the need to traverse the entire model, reducing the data retrieval time. The collaborative design of this stack structure and the rendering queue decouples the instruction processing efficiency from the model complexity, ensuring stability in high-load scenarios.

[0082] S304, loading the to-be-displayed model data into the current data visualization interface for display.

[0083] Directly loading the to-be-displayed model data generated by rendering into the visualization interface realizes seamless updating of the interface content. After the execution of the hiding instruction, only the non-hidden parts are displayed in the interface, and the model space coordinate system remains unchanged; after the execution of the separation instruction, the separated parts are displayed in an independent coordinate system, while the association with the original model is preserved. This dynamic updating mechanism supports users to achieve multi-level model analysis through instruction combination (such as first hiding non-key parts, and then separating target parts for detailed observation), significantly improving the information carrying capacity of the visualization interface. For example, in mechanical assembly simulation, users can observe the assembly process by hiding installed parts and separating to-be-installed parts, and this interactive mode directly depends on the instruction processing and dynamic rendering capabilities provided by the present technical solution.

[0084] It is worth mentioning that S303-S304 in the embodiment can also be selectively used with S203-S204 in the previous embodiment, that is, when the graphics card rendering resources are sufficient (for example, the occupied resources are less than the preset occupation ratio), the way of S203-S204 in the previous embodiment can be adopted, that is, after the target model data is loaded into the memory space, the target model data is directly rendered by the graphics card before the target instruction is received; when the graphics card rendering resources are insufficient (for example, the occupied resources are greater than the preset occupation ratio), the way of S303-S304 in the embodiment can be adopted, that is, after the target model data is loaded into the memory space, the rendering resources are not directly called for rendering, but rendering is performed after the target instruction is received.

[0085] When the graphics card rendering resources are sufficient, that is, the occupied resources of the current graphics card are less than the preset occupation ratio, after the target model data is loaded into the memory space, the system can directly render the target model data by the graphics card without waiting for the user to issue a target instruction, form the to-be-displayed model data, and load it into the memory space for storage. Since rendering can be performed without waiting for the user instruction, the system can immediately convert the target model data into a visualized model, reducing the user waiting time and improving the immediacy and fluency of interaction. In the case of sufficient graphics card resources, the parallel computing capability of the graphics card is fully utilized for immediate rendering, avoiding the idling and waste of rendering resources and improving the overall utilization of system resources. The pre-rendered to-be-displayed model data is stored in the memory, and when it needs to be displayed, the system can directly read the data from the memory, avoiding the computational overhead of repeated rendering and further improving the display speed. This strategy realizes the immediate update of the data visualization interface by reducing the rendering delay, and is suitable for the smooth interaction demand in a low-load scenario.

[0086] When the graphics card rendering resource is tight, i.e., the current graphics card occupies more resources than the preset occupancy ratio, after the target model data is loaded into the memory space, the system does not directly call the rendering resource for rendering, but waits to receive the target instruction (such as a hiding instruction, a separation instruction) issued by the user, and then performs rendering and displays the to-be-displayed model data in the current data visualization interface. In the case of tight graphics card resources, the system protects the resource requirements of the key rendering task through the delayed rendering strategy, avoiding the decline in rendering quality or system lag caused by resource competition. At the same time, the target instruction triggers the rendering, ensuring the priority management of the rendering task and prioritizing the processing of the model part that the user is most concerned about. The delayed rendering strategy reduces unnecessary calculations when the graphics card resource is tight, avoiding performance degradation caused by rendering all target model data immediately. The system only renders when necessary (i.e., after receiving the target instruction), thereby saving computing resources. This strategy avoids lag caused by resource competition by delaying the rendering task, and is suitable for stability protection in high-load scenarios.

[0087] The above dynamic switching strategy avoids system instability or crash problems caused by graphics card resource competition, improving the overall stability and reliability of the system. Moreover, the system can dynamically allocate rendering resources according to actual conditions, ensuring efficient use of resources and avoiding waste of resources.

[0088] Figure 4 is a structural schematic diagram of a data visualization system based on a digital model according to an example embodiment. As shown in Figure 4 The data visualization system based on a digital model 400 provided by the embodiment includes: The acquisition module 410 is configured to acquire a selection instruction of a selectable object acting on a digital model. The processing module 420 is configured to determine a target object corresponding to the selectable object, wherein the target object is a model object in the digital model that has an association relationship with the selectable object. The storage module 430 is configured to load target model data corresponding to the target object into a priority loading stack in a memory space, wherein the priority loading stack is a storage space in the memory space for preferentially calling model rendering resources for data visualization.

[0089] Optionally, the selectable object is a selectable face object, and the target object is a region of the digital model that needs to be displayed after the selectable face object is hidden.

[0090] Optionally, the target object includes a target face sequence composed of multiple target faces. Correspondingly, the storage module 430 is specifically configured to: The target model data is determined according to the target face sequence, and the target model data includes a target model sequence corresponding to the target face sequence. The target model sequence is loaded into the priority loading stack in the memory space.

[0091] Optionally, the optional object is an optional component, and the target object is at least one target component in the digital model that has an assembly relationship with the optional component.

[0092] Optionally, the target object includes a target component sequence composed of a plurality of target components. Correspondingly, the storage module 430 is specifically configured to: The target model data is determined according to the target component sequence, and the target model data includes a target model sequence corresponding to the target component sequence. The target model sequence is loaded into the priority loading stack in the memory space.

[0093] Optionally, the processing module 420 is further configured to directly render the target model data through a graphics card to form to-be-displayed model data. The storage module 430 is further configured to load the to-be-displayed model data into the memory space for storage.

[0094] Optionally, the processing module 420 is configured to, in response to a target instruction acting on the optional object, render the target model data through a graphics card to form to-be-displayed model data, wherein the target instruction includes a hiding instruction and a separating instruction. The display module 440 is configured to load the to-be-displayed model data into a current data visualization interface for display.

[0095] Figure 5 is a structural schematic diagram of an electronic device according to an example embodiment. As shown in the figure, Figure 5 The electronic device 500 provided in the embodiment includes a processor 501 and a memory 502. The memory 502 is configured to store a computer program, and the memory can also be a flash memory.

[0096] The processor 501 is configured to execute an execution instruction stored in the memory to implement each step in the above method. For details, refer to the related description in the method embodiment.

[0097] Optionally, the memory 502 can be independent or integrated with the processor 501.

[0098] When the memory 502 is a device independent of the processor 501, the electronic device 500 can further include: a bus 503 for connecting the memory 502 and the processor 501.

[0099] The embodiments also provide a readable storage medium, and the readable storage medium stores a computer program. When at least one processor of an electronic device executes the computer program, the electronic device executes the method provided by the various embodiments.

[0100] The embodiments also provide a program product, and the program product includes a computer program stored in a readable storage medium. At least one processor of an electronic device can read the computer program from the readable storage medium, and the at least one processor executes the computer program to make the electronic device implement the method provided by the various embodiments.

[0101] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0102] It should be understood that the application is not limited to the precise construction that has been described above and shown in the accompanying drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application is to be defined by the claims appended hereto.

Claims

1. A data visualization method based on a digital model, characterized in that: include: In response to a selection instruction of a selectable object on a digital model, determining a target object corresponding to the selectable object, wherein the target object is a model object in the digital model that has an associated relationship with the selectable object; The target model data corresponding to the target object is loaded into a priority loading stack in the memory space, wherein the priority loading stack is a storage space in the memory space used to preferentially call model rendering resources for data visualization.

2. The data visualization method based on digital model according to claim 1, characterized in that: The optional object is an optional surface object, and the target object is an area of ​​the digital model that needs to be displayed after the optional surface object is hidden.

3. The data visualization method based on digital model according to claim 2, characterized in that: The target object includes a target surface sequence composed of multiple target surfaces; Correspondingly, the step of loading the target model data corresponding to the target object into the priority loading stack in the memory space includes: Determine the target model data according to the target surface sequence, wherein the target model data includes a target model sequence corresponding to the target surface sequence; The target model sequence is loaded into the priority loading stack in the memory space.

4. The data visualization method based on digital model according to claim 1, characterized in that: The optional object is an optional component, and the target object is at least one target component in the digital model that has an assembly relationship with the optional component.

5. The data visualization method based on digital model according to claim 4, characterized in that: The target object includes a target component sequence consisting of a plurality of target components; Correspondingly, the step of loading the target model data corresponding to the target object into the priority loading stack in the memory space includes: Determine the target model data according to the target component sequence, wherein the target model data includes a target model sequence corresponding to the target component sequence; The target model sequence is loaded into the priority loading stack in the memory space.

6. The data visualization method based on digital model according to any one of claims 1 to 5, characterized in that: After the target model data corresponding to the target object is loaded into the priority loading stack in the memory space, the method further includes: Directly rendering the target model data through a graphics card to form model data to be displayed; The model data to be displayed is loaded into the memory space for storage.

7. The data visualization method based on digital model according to any one of claims 1 to 5, characterized in that: After the target model data corresponding to the target object is loaded into the priority loading stack in the memory space, the method further includes: In response to a target instruction acting on the selectable object, rendering the target model data through a graphics card to form model data to be displayed, wherein the target instruction includes a hiding instruction and a separating instruction; The model data to be displayed is loaded into the current data visualization interface for display.

8. A data visualization system based on a digital model, characterized in that: include: An acquisition module, used for acquiring a selection instruction acting on a selectable object on a digital model; a processing module, configured to determine a target object corresponding to the selectable object, wherein the target object is a model object in the digital model that has an association relationship with the selectable object; A storage module is used to load the target model data corresponding to the target object into a priority loading stack in the memory space, wherein the priority loading stack is a storage space in the memory space used to preferentially call model rendering resources for data visualization.

9. An electronic device, characterized in that: include: processor; as well as, a memory for storing executable instructions of the processor; The processor is configured to perform the method according to any one of claims 1 to 7 by executing the executable instructions.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

Images