BIM loading optimization method and device, electronic equipment and medium

Abstract

The invention discloses a BIM loading optimization method and device, electronic equipment and a medium, and the method comprises the steps: screening an alternative optimization building model meeting a target loading optimization condition in to-be-loaded building model data, and calculating OBB information; adopting at least one detail level rule to screen out an alternative hiding model and a target hiding model step by step; screening out a target hiding model according to a shielding relationship of each alternative hiding model calculated by adopting a painter algorithm, and constructing each corresponding target OBB model; and loading each target OBB model into the rendering scene for synchronous display while loading and displaying other model data except the target hidden model in the building model data in the rendering scene. Through a detail level rule and a painter algorithm, the rendering state of the model in the scene is dynamically updated, the number of ineffectively rendered models is reduced, the rendering load is reduced, the loading efficiency of the BIM is improved, and the loading performance of the BIM is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of building information modeling, and in particular to an optimization method, device, electronic equipment and medium for BIM loading. Background Art

[0002] With the increasing popularity of Building Information Modeling (BIM) technology, the field of architectural design often faces problems such as high model complexity and large number, which often become bottlenecks restricting model loading performance.

[0003] In the prior art, the performance burden is generally reduced by reducing the model accuracy through the Level of Detail (LOD) rule. However, the LOD rule is mainly applicable to high-precision triangular models, and for scenes with a large number of small-sized models inside building floors, LOD technology is difficult to meet performance requirements. In addition, existing occlusion query algorithms, such as hard query methods, cannot flexibly handle occlusion problems. Although the ray detection method has high accuracy, it consumes performance and is not suitable for occlusion of small objects inside multi-story building models, resulting in more models being rendered in the scene, reducing the loading efficiency and performance of BIM. Summary of the invention

[0004] The present invention provides a BIM loading optimization method to solve the problems of low loading efficiency and poor loading performance of building information model.

[0005] According to one aspect of an embodiment of the present invention, a method for optimizing BIM loading is provided, comprising:

[0006] In the building model data to be loaded, selecting candidate optimized building models that meet the target loading optimization conditions;

[0007] Calculate the oriented bounding box OBB information of each candidate optimized building model respectively;

[0008] According to the OBB information of each candidate optimized building model, at least one level of detail rule is used to screen out candidate hidden models and target hidden models from each candidate optimized building model step by step;

[0009] According to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, a target hidden model is screened out from each candidate hidden model, and a target OBB model corresponding to each target hidden model is constructed;

[0010] While other model data in the building model data except the target hidden model are loaded and displayed in the rendering scene, each target OBB model is loaded into the rendering scene for synchronous display.

[0011] According to another aspect of an embodiment of the present invention, there is also provided a BIM loading optimization device, comprising:

[0012] A building model screening module is used to screen candidate optimized building models that meet target loading optimization conditions from the building model data to be loaded;

[0013] An information calculation module is used to calculate the OBB information of each candidate optimized building model respectively;

[0014] A hidden model screening module is used to screen out candidate hidden models and target hidden models from each candidate optimized building model step by step according to the OBB information of each candidate optimized building model and using at least one level of detail rule;

[0015] A model construction module, used to select a target hidden model from each candidate hidden model according to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, and to construct a target OBB model corresponding to each target hidden model;

[0016] The model display module is used to load and display other model data in the building model data except the target hidden model in the rendering scene, and load each target OBB model into the rendering scene for synchronous display.

[0017] According to another aspect of an embodiment of the present invention, an electronic device is provided, the electronic device comprising:

[0018] at least one processor; and

[0019] a memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the BIM loading optimization method described in any embodiment of the present invention.

[0021] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is further provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the BIM loading optimization method described in any embodiment of the present invention when executed.

[0022] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program / instruction, wherein when the computer program / instruction is executed by a processor, the steps of the method described in any embodiment of the present invention are implemented.

[0023] The technical solution of the embodiment of the present invention is to select the candidate optimized building models that meet the target loading optimization conditions in the building model data to be loaded; calculate the OBB information of each candidate optimized building model respectively; according to the OBB information of each candidate optimized building model, use at least one detail level rule to select the candidate hidden model and the target hidden model in each candidate optimized building model step by step; according to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, select the target hidden model in each candidate hidden model, and construct the target OBB model corresponding to each target hidden model; while loading and displaying other model data in the building model data except the target hidden model in the rendering scene, each target OBB model is loaded into the rendering scene for synchronous display. Through the detail level rule and the painter algorithm, the rendering status of the model in the scene is dynamically updated, the number of invalidly rendered models is reduced, the rendering load is reduced, the loading efficiency of BIM is improved, and the loading performance of BIM is optimized.

[0024] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 is a flow chart of a BIM loading optimization method provided according to Embodiment 1 of the present invention;

[0027] Figure 2 is a flow chart of another BIM loading optimization method provided according to the second embodiment of the present invention;

[0028] Figure 3 It is a model initialization and classification flow chart applicable to the embodiment of the present invention;

[0029] Figure 4 It is a model display and hide query result calculation flow chart applicable to the embodiment of the present invention;

[0030] Figure 5 is a model loading flow chart applicable to the embodiment of the present invention;

[0031] Figure 6 is a structural schematic diagram of a BIM loading optimization device provided according to Embodiment 3 of the present invention;

[0032] Figure 7 It is a structural schematic diagram of an electronic device for implementing the optimization method for BIM loading according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] Embodiment 1

[0036] Figure 1 This is a flowchart of a BIM loading optimization method provided in the first embodiment of the present invention. This embodiment can be applied to the case where a building model is loaded into a rendering scene, and the building model that is blocked in the building information model is filtered and hidden. The method can be executed by a BIM loading optimization device, which can be implemented in the form of hardware and / or software and can generally be configured in an electronic device. Figure 1 As shown, the method includes:

[0037] S110 , selecting candidate optimized building models that meet target loading optimization conditions from among the building model data to be loaded.

[0038] In the embodiment of the present invention, the target loading optimization condition can be specifically understood as: the building parts that are mainly concerned with the large volume and may constitute an occlusion relationship in the building model data to be loaded, such as pipes, walls and elbows (a pipe fitting that changes the direction of the pipeline) and other building parts. Because these parts may affect the line of sight when rendering, it is necessary to consider their occlusion relationship with other building parts before loading and rendering. On the contrary, for parts that are large in volume but have no occlusion relationship, such as floors, they usually do not affect the line of sight, so they can be ignored in the optimization process. The alternative optimized building model can be specifically understood as: the building parts with large volume and occlusion relationship that are screened out from the building model to be loaded according to the target loading optimization condition, and the building parts near these building parts that may constitute an occlusion relationship are large in number and relatively small in size.

[0039] Specifically, in the building model data to be loaded, the candidate optimized building models that meet the target loading optimization conditions are screened, such as building parts such as pipes, walls, elbows, and their vicinity that may constitute an occlusion relationship and have a large number of relatively small building parts.

[0040] S120, respectively calculating the OBB information of each candidate optimized building model.

[0041] In the embodiment of the present invention, OBB (Oriented Bounding Box) refers to a minimum bounding box used to enclose an object in a three-dimensional space, which can be rotated to more closely fit the shape of the object to better adapt to the direction of the object.

[0042] Specifically, the convex hull of the vertices of each alternative optimized building model is determined by calculating the minimum convex polygon of all vertices; principal component analysis is performed on the convex hull vertices to identify the principal axis of the building model (the principal axis determines the direction of the OBB), and the boundary of the OBB is determined based on the analysis results; the vertices of the OBB are reconstructed by projecting the points onto the principal axis and calculating the minimum and maximum values ​​of the projection; finally, the OBB vertices are converted from the principal component analysis space back to the original space to obtain the OBB information of each alternative optimized building model.

[0043] S130 , according to the OBB information of each candidate optimized building model, at least one level of detail rule is adopted to screen out candidate hidden models and target hidden models from each candidate optimized building model step by step.

[0044] In the embodiment of the present invention, the Level of Detail (LOD) rule refers to dynamically adjusting the rendering details of the object according to the distance between the 3D object and the observation point (such as a camera). When the object is far away from the observation point, a model with fewer polygons or lower details is used for rendering, thereby reducing the rendering load and improving the rendering efficiency; when the object is close to the observation point, a more detailed and larger number of models are used to maintain the visual quality, and a smooth transition is made between different LOD models, visually maintaining the continuity of the scene and the resolution of the model. The target hidden model can be specifically understood as: a building model that needs to be hidden, which in S130 refers to an alternative optimized building model that meets the LOD filtering rule and is screened out from each alternative optimized building model step by step using at least one level of detail rule, that is, an alternative optimized building model that needs to be hidden. The alternative hidden model can be specifically understood as: a building model other than the target hidden model in the alternative optimized building model, that is, an alternative optimized building model that does not meet the LOD filtering rule. The LOD rule can specifically include: an LOD angle culling rule and an LOD scene management rule. Among them, LOD angle culling refers to culling objects that are not in the camera's field of view according to the camera's angle and the object's orientation to reduce the rendering burden. LOD scene management refers to dividing the scene into different areas, each area using a different LOD strategy to optimize resource allocation.

[0045] Specifically, according to the OBB information of each candidate optimized building model, at least one LOD filtering rule is adopted, such as the LOD angle culling rule and the LOD scene management rule, and the candidate optimized building models that meet the LOD filtering rule are screened out from each candidate optimized building model step by step as the target hidden model, and the remaining candidate optimized building models are used as candidate hidden models.

[0046] S140 , according to the occlusion relationship of each candidate hidden model calculated by using the painter algorithm, select a target hidden model from each candidate hidden model, and construct a target OBB model corresponding to each target hidden model.

[0047] In the embodiment of the present invention, the painter algorithm refers to sorting the building models in the scene according to their distance from the observation point, and then drawing the building models one by one in order from far to near. Since the building model close to the observation point is drawn last, it covers the building model far away, and finally generates the occlusion relationship of the corresponding building models on the screen, thereby determining the mutual occlusion relationship of the building models, and the occlusion relationship can specifically include: complete occlusion, partial occlusion and no occlusion.

[0048] Specifically, the painter's algorithm is used to calculate and determine the mutual occlusion relationship of each candidate hidden model, and the occluded building model that needs to be hidden is screened out, that is, the target hidden model, and the target OBB model is constructed according to the corresponding OBB information to replace the occluded building model that is not rendered.

[0049] S150. While loading and displaying other model data in the building model data except the target hidden model in the rendering scene, load each target OBB model into the rendering scene for synchronous display.

[0050] Specifically, the other model data in the building model data except the target hidden model, that is, the building model that needs to be displayed, is loaded and displayed in the rendering scene. At the same time, each target OBB model (that is, the building model in the building model data that is not rendered due to occlusion) is loaded into the rendering scene for synchronous display.

[0051] The technical solution of the embodiment of the present invention is to select the candidate optimized building models that meet the target loading optimization conditions in the building model data to be loaded; calculate the OBB information of each candidate optimized building model respectively; according to the OBB information of each candidate optimized building model, use at least one detail level rule to select the candidate hidden model and the target hidden model in each candidate optimized building model step by step; according to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, select the target hidden model in each candidate hidden model, and construct the target OBB model corresponding to each target hidden model; while loading and displaying other model data in the building model data except the target hidden model in the rendering scene, each target OBB model is loaded into the rendering scene for synchronous display. Through the detail level rule and the painter algorithm, the rendering status of the model in the scene is dynamically updated, the number of invalidly rendered models is reduced, the rendering load is reduced, the loading efficiency of BIM is improved, and the loading performance of BIM is optimized.

[0052] Optionally, on the basis of the above embodiments, according to the OBB information corresponding to each candidate optimized building model, at least one level of detail rule is adopted to screen out candidate hidden models and target hidden models from each candidate optimized building model step by step, including:

[0053] According to the OBB information corresponding to each candidate optimized building model, the candidate optimized building model located outside the viewing frustum is screened out through the viewing frustum query as the target hidden model, and the remaining candidate optimized building models are used as candidate hidden models.

[0054] In the embodiment of the present invention, the viewing frustum query refers to determining which building models in the scene are located within the viewing frustum of the observation point (such as a camera). Only the building models within the viewing frustum will be rendered, while the building models outside the viewing frustum will be ignored, thereby reducing the rendering burden.

[0055] Specifically, according to the OBB information corresponding to each candidate optimized building model, the distance between each point of the OBB corresponding to each candidate optimized building model and the observation point (such as a camera) is calculated, and the point with the closest distance is taken as the minimum point, and the point with the farthest distance is taken as the maximum point. By judging whether the minimum point, maximum point and center point of the OBB corresponding to each candidate optimized building model are within the viewing cone of the observation point (such as a camera), it is determined whether the building model needs to be hidden. For example, when all three points are within the viewing cone, they do not need to be hidden. When two points or one point are within the viewing cone, they are across the viewing cone. When no point is within the viewing cone, they are outside the viewing cone. The building models that are across the viewing cone and outside the viewing cone need to be hidden, that is, the candidate optimized building models located outside the viewing cone are screened out and need to be used as the target hidden model, and the remaining candidate optimized building models are used as candidate hidden models to reduce unnecessary rendering and calculation, and improve the performance of BIM loading and rendering.

[0056] Further, based on the above embodiments, while selecting the candidate optimized building models outside the viewing frustum as the target hidden models, the method further includes:

[0057] Obtain the OBB information of the pipeline building model from the remaining OBB information of each candidate optimized building model;

[0058] According to the OBB information of the pipeline building model, a first ratio of the camera distance of each pipeline building model divided by the pipe diameter is calculated, and the candidate optimized building model whose first ratio is greater than or equal to the first preset threshold is screened out as the target hidden model.

[0059] In the embodiment of the present invention, the first ratio can be specifically understood as: the ratio of the distance from the camera (observation point) to the center of the pipeline (camera distance) to the diameter of the pipeline, which is used to determine the relative size of the pipeline and the relative distance of the camera. The first preset threshold value can be specifically understood as: the LOD threshold value set according to project requirements and performance considerations, so as to determine whether to hide the building model during rendering according to the calculated first ratio.

[0060] Specifically, after selecting the candidate optimized building model outside the viewing frustum as the target hidden model, the OBB information of the pipeline building model is obtained from the OBB information of the remaining candidate optimized building models, including obtaining the distance from the camera (observation point) to the center of the pipeline (camera distance) and the diameter of the pipeline, dividing the camera distance by the pipeline diameter to obtain a first ratio, and comparing the first ratio with a first preset threshold value. When the first ratio is greater than or equal to the first preset threshold value, it means that the pipeline is relatively far from the camera and the diameter of the pipeline is relatively small and needs to be hidden. That is, the candidate optimized building model is used as the target hidden model, and the remaining candidate optimized building models are used as candidate hidden models, so as to achieve preliminary filtering of the candidate optimized building models in the viewing frustum according to the relationship between the camera distance and the pipeline diameter.

[0061] Further, based on the above embodiments, after selecting the candidate optimized building models whose first ratio is greater than or equal to the first preset threshold as the target hidden model, the method further includes:

[0062] According to the remaining OBB information of each candidate optimized building model, a second ratio of the camera distance of each candidate optimized building model divided by the size of the bounding box to which it belongs is calculated, and the candidate optimized building models whose second ratio is greater than or equal to the second preset threshold are screened out as the target hidden models.

[0063] In the embodiment of the present invention, the second ratio can be specifically understood as: the ratio of the distance from the camera (observation point) to the center point of the OBB bounding box or the reference point set according to the requirements (camera distance) to the size of the OBB bounding box, which is used to dynamically adjust the rendering details according to the relative distance between the camera and the building model OBB bounding box and the size of the building model OBB bounding box. The second preset threshold value can be specifically understood as: the LOD threshold value set according to project requirements and performance considerations, so as to decide whether to hide the building model during rendering according to the calculated second ratio.

[0064] Specifically, after screening out the alternative optimized building models with a first ratio greater than or equal to the first preset threshold as the target hidden model, the camera distance from the camera (observation point) to the center point of the OBB bounding box or the reference point set as required is calculated and divided by the size of the bounding box to obtain a second ratio, wherein the size of the OBB bounding box can be: the difference between the maximum and minimum coordinate values ​​of the bounding box along the X, Y, Z axes and the diagonal, and the second ratio is compared with the second preset threshold. When the second ratio is greater than or equal to the second preset threshold, it means that the OBB bounding box is relatively far from the camera and the size of the OBB bounding box is relatively small and needs to be hidden. That is, the alternative optimized building model is used as the target hidden model, and the remaining alternative optimized building models are used as alternative hidden models, so as to achieve further filtering of the alternative optimized building models according to the relationship between the camera distance and the size of the packaging box.

[0065] Further, based on the above embodiments, after selecting the candidate optimized building models whose second ratio is greater than or equal to the second preset threshold as the target hidden model, the method further includes:

[0066] Each candidate optimized building model is projected onto the screen plane, and according to the remaining OBB information of each candidate optimized building model, a third ratio of the camera distance of each candidate optimized building model divided by the minimum circumscribed rectangle area to which the projection belongs is calculated, and the candidate optimized building models whose third ratio is greater than or equal to the third preset threshold are screened out as the target hidden models.

[0067] In the embodiment of the present invention, the third ratio can be specifically understood as: the ratio of the distance from the camera (observation point) to the center point of the OBB bounding box or the reference point set according to the requirements (camera distance) to the area of ​​the minimum circumscribed rectangle formed by projecting the OBB bounding box to the screen plane, which is used to dynamically adjust the rendering details according to the relative distance between the camera and the building model OBB bounding box and the size of the projection area of ​​the building model OBB bounding box on the screen. The third preset threshold value can be specifically understood as: the LOD threshold value set according to project requirements and performance considerations, so as to decide whether to hide the building model during rendering according to the calculated third ratio.

[0068] Specifically, after selecting the candidate optimized building models whose second ratio is greater than or equal to the second preset threshold value as the target hidden model, each candidate optimized building model is projected onto the screen plane, and according to the remaining OBB information of each candidate optimized building model, the camera distance from the camera (observation point) to the center point of the OBB bounding box or the reference point set as required is calculated, divided by the area of ​​the minimum circumscribed rectangle formed by projecting the OBB bounding box onto the screen plane to a third ratio, wherein the area of ​​the minimum circumscribed rectangle formed by projecting the OBB bounding box onto the screen plane can be: in the screen coordinate system, the minimum circumscribed rectangle is calculated using the projected OBB vertices, and the minimum and maximum x and y coordinates of the projected vertices on the screen plane are determined, thereby determining the boundary of the circumscribed rectangle, and then calculating the area.

[0069] Then, the third ratio is compared with the third preset threshold value. When the third ratio is greater than or equal to the third preset threshold value, it means that the OBB bounding box is relatively far from the camera and the projection area of ​​the OBB bounding box on the screen is relatively small and needs to be hidden. That is, the alternative optimized building model is used as the target hidden model, and the remaining alternative optimized building models are used as alternative hidden models, so as to further filter the alternative optimized building models according to the relationship between the camera distance and the projection area of ​​the OBB bounding box on the screen.

[0070] Further, based on the above embodiments, after selecting the candidate optimized building models whose third ratio is greater than or equal to the third preset threshold as the target hidden model, the method further includes:

[0071] Each candidate optimized building model is projected onto the screen plane, and a fourth ratio obtained by dividing the camera distance of each candidate optimized building model by the number of screen squares occupied by the projection is calculated according to the remaining OBB information of each candidate optimized building model, and the alternative optimized building models whose fourth ratio is greater than or equal to a fourth preset threshold are screened out as target hidden models.

[0072] In the embodiment of the present invention, the fourth ratio can be specifically understood as: the ratio of the distance (camera distance) from the camera (observation point) to the center point of the OBB bounding box or the reference point set as required to the number of screen squares occupied by projecting the OBB bounding box to the screen plane, which is used to dynamically adjust the rendering details according to the relative distance between the camera and the building model OBB bounding box and the number of screen squares occupied by the projection of the building model OBB bounding box on the screen. The fourth preset threshold value can be specifically understood as: the LOD threshold value set according to project requirements and performance considerations, so as to decide whether to hide the building model during rendering according to the calculated fourth ratio.

[0073] Specifically, after screening out the alternative optimized building models whose third ratio is greater than or equal to the third preset threshold value as the target hidden model, each alternative optimized building model is projected to the screen plane, and according to the remaining OBB information of each alternative optimized building model, the camera distance from the camera (observation point) to the center point of the OBB bounding box or the reference point set as required is calculated divided by the fourth ratio of the number of screen squares occupied by the OBB bounding box projected to the screen plane, where the number of screen squares occupied by the OBB bounding box projected to the screen plane can be: in the screen coordinate system, determine the minimum and maximum x and y coordinates of the OBB vertices, thereby determining the boundary of the OBB on the screen, that is, determining the minimum circumscribed rectangle of the OBB projection.

[0074] Then, the size of the screen space occupied by the OBB can be calculated by dividing the size of the screen grid by the size of the screen grid, and the number of screen grids occupied by the OBB can be calculated, and the fourth ratio can be compared with the fourth preset threshold value. When the fourth ratio is greater than or equal to the fourth preset threshold value, it means that the OBB bounding box is relatively far from the camera and the number of screen grids occupied by the projection of the OBB bounding box on the screen is relatively small and needs to be hidden, that is, the candidate optimized building model is used as the target hidden model, and the remaining candidate optimized building models are used as candidate hidden models, so as to further filter the candidate optimized building models according to the relationship between the camera distance and the projection area of ​​the OBB bounding box on the screen. By adopting LOD rules such as the view cone query, the relationship between the pipe diameter and the camera distance, the relationship between the bounding box size and the camera distance, the relationship between the projection area and the camera distance, and the relationship between the number of screen occupied grids and the camera distance, the candidate hidden models and the target hidden models are screened out in each candidate optimized building model step by step, so as to achieve refined model filtering, reduce the number of invalidly rendered models, reduce the rendering load, improve the loading efficiency of BIM, and optimize the loading performance of BIM.

[0075] Embodiment 2

[0076] Figure 2 A flowchart of another BIM loading optimization method provided in Example 2 of the present invention. This embodiment is a refinement of the operation of screening out a target hidden model from each candidate hidden model according to the occlusion relationship of each candidate hidden model calculated by the painter's algorithm in the above embodiment, and constructing a target OBB model corresponding to each target hidden model, specifically including: screening out a completely occluded candidate hidden model as the target hidden model according to the occlusion relationship of each candidate hidden model calculated by the painter's algorithm; calculating the fifth ratio of the occlusion ratio of each remaining candidate hidden model, and screening out an alternative optimized building model with a fifth ratio greater than or equal to a fifth preset threshold as the target hidden model.

[0077] Correspondingly, such as Figure 2As shown, the method includes:

[0078] S210 , selecting candidate optimized building models that meet target loading optimization conditions from among the building model data to be loaded.

[0079] S220: Calculate the OBB information of each candidate optimized building model respectively.

[0080] S230 , according to the OBB information of each candidate optimized building model, at least one level of detail rule is adopted to screen out candidate hidden models and target hidden models from each candidate optimized building model step by step.

[0081] S240 , according to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, select the candidate hidden model that is completely occluded as the target hidden model.

[0082] Specifically, in the building model data to be loaded, the candidate optimized building models that meet the target loading optimization conditions are screened, and the OBB information of each candidate optimized building model is calculated respectively. According to the OBB information of each candidate optimized building model, one or more detail level rules are used to screen out the candidate hidden models and the target hidden models in each candidate optimized building model step by step, and the painter algorithm is used to calculate the occlusion relationship of each candidate hidden model, such as complete occlusion, partial occlusion and unocclusion. The completely occluded candidate hidden model is screened out as the target hidden model. Among them, it can be checked whether the OBB projection of the building model has an occlusion relationship with the projection of other building models OBB by comparing the overlap of the screen grid of the OBB projection with the screen grid of other OBB projections.

[0083] S250, calculating a fifth ratio of the occlusion ratio of each remaining candidate hidden model, and selecting candidate hidden models whose fifth ratio is greater than or equal to a fifth preset threshold as target hidden models.

[0084] In the embodiment of the present invention, the fifth ratio can be specifically understood as: when the OBB is projected onto the screen plane, the number of screen squares of the OBB projection overlaps with other OBB projections, divided by the total number of screen squares of the OBB. The fifth preset threshold value can be specifically understood as: the allowed occlusion ratio threshold value set according to project requirements and performance considerations, so as to decide whether to hide the building model during rendering according to the calculated fifth ratio.

[0085] Specifically, the OBB is projected onto the screen plane, and in the screen coordinate system, the minimum circumscribed rectangle of the OBB projection is determined, and the number of screen squares covered by the rectangle and overlapped with other OBB projections is calculated, and then divided by the total number of screen squares of the rectangle, that is, the fifth ratio of the occlusion ratio of each remaining candidate hidden model is calculated. The fifth ratio is compared with the fifth preset threshold value, and when the fifth ratio is greater than or equal to the fifth preset threshold value, for example, when the fifth preset threshold value is 80%, when the fifth ratio is 90%, it means that 90% of the candidate hidden model corresponding to the OBB is blocked, and the candidate hidden model corresponding to the OBB needs to be hidden, that is, the candidate hidden model with a fifth ratio greater than or equal to the fifth preset threshold value is selected as the target hidden model.

[0086] S260: while loading and displaying other model data in the building model data except the target hidden model in the rendering scene, load each target OBB model into the rendering scene for synchronous display.

[0087] Specifically, the other model data in the building model data except the target hidden model, that is, the building model that needs to be displayed, is loaded and displayed in the rendering scene. At the same time, each target OBB model (that is, the building model in the building model data that is not rendered due to occlusion) is loaded into the rendering scene for synchronous display.

[0088] The technical solution of the embodiment of the present invention is to select the candidate optimized building models that meet the target loading optimization conditions in the building model data to be loaded; calculate the OBB information of each candidate optimized building model respectively; according to the OBB information of each candidate optimized building model, use at least one detail level rule to select the candidate hidden model and the target hidden model in each candidate optimized building model step by step; according to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, select the completely occluded candidate hidden model as the target hidden model; calculate the fifth ratio obtained by the occlusion ratio of each remaining candidate hidden model, and select the candidate hidden model whose fifth ratio is greater than or equal to the fifth preset threshold value as the target hidden model; while loading and displaying other model data in the building model data except the target hidden model in the rendering scene, each target OBB model is loaded into the rendering scene for synchronous display. By using the painter algorithm to determine the building models that are occluded or mostly occluded, the calculation amount of rendering these building models is reduced, and the overall rendering performance is improved. Especially in complex scenes with a large number of small models, there are situations where multiple OBBs may occlude each other. The painter algorithm dynamically adjusts the rendering strategy to optimize performance and visual effects, and uses OBB bounding boxes to replace these hidden models to reduce the number of actual rendered models, improve the BIM loading efficiency, and optimize the BIM loading performance.

[0089] Optionally, based on the above embodiments, screening the candidate optimized building models that meet the target loading optimization conditions in the building model data to be loaded may include:

[0090] In the database, obtain the building model data to be loaded;

[0091] In the building model data to be loaded, select candidate optimized building models that meet the target loading optimization conditions, and determine the basic geometric shapes corresponding to each candidate optimized building model;

[0092] The basic geometric shapes include: pipes, walls and elbows.

[0093] In the embodiment of the present invention, the basic geometric shape can be specifically understood as: the geometric shape of the building model that may cause an occlusion relationship between building components during the loading and rendering process of the building model, and may specifically include: pipes, which are usually cylindrical or rectangular. Inside the building, especially in a dense pipe network, the pipes may block the line of sight or light; walls, which are usually rectangular or cubic in shape and are used to separate spaces and provide support. The thickness and height of the walls may block the line of sight and light; elbows, which are pipe fittings used to change the direction of the pipes, are usually circular or elliptical, and may block the line of sight in a dense pipe network; beams and columns may also be included, which are usually rectangular or cylindrical and are used to support the weight of the building, and may form an occlusion relationship with other small building components inside the building.

[0094] By determining the basic geometric shapes including pipes, walls and elbows corresponding to each candidate optimized building model, when subsequently screening the target hidden model for the pipeline building model, the pipeline model that needs to be processed separately can be quickly located, thereby improving processing efficiency and reducing the time to search for specific parts in a large number of candidate optimized building models. In addition, before performing BIM loading optimization, the candidate optimized building models including pipes, walls and elbows can also be maintained and managed to ensure that the building models of these key parts are correct.

[0095] Specific application scenarios

[0096] With the widespread application of BIM technology, architectural design often encounters problems such as complex models and a large number of models, which leads to performance bottlenecks in model loading. In order to solve the problems of low loading efficiency and poor loading performance of building information models, an embodiment of the present invention proposes an optimization method for BIM loading, which can specifically include three steps: model initialization and classification, model display and hide query result calculation, and model loading.

[0097] Figure 3is a model initialization and classification flow chart applicable to the embodiment of the present invention, such as Figure 3 As shown, the model initialization and classification steps may specifically include:

[0098] First, the building model data is obtained from the database, and the models are classified according to the query conditions such as geometric shape category and volume and possible occlusion relationship (equivalent to the target loading optimization condition), and the basic geometric shapes such as pipes, walls and elbows and their nearby building parts with large number and relatively small size that may form occlusion relationships are screened out for subsequent processing. The remaining building models that do not meet the query conditions are used as display loading models.

[0099] Then, basic information calculation is performed for each model, and its OBB information is calculated, including its size, position and direction, for subsequent LOD rules and occlusion calculations; the screen segmentation projection data source is calculated based on the OBB information, that is, the data set of the OBB projection in the screen space is calculated, including the projection area and the number of screen occupied grids; the model OBB placeholder model and the model display and hide query result status are generated to record the OBB model generated in the model display and hide query result calculation link and the calculated model display and hide query results.

[0100] Figure 4 A model display and hide query result calculation flow chart applicable to the embodiment of the present invention is shown as follows: Figure 4 As shown in the figure, the model display and hide query result calculation link is to gradually screen and filter the model through five LOD rules, including the view cone query, the relationship between the pipe diameter and the camera distance, the relationship between the bounding box size and the camera distance, the relationship between the projection area and the camera distance, and the relationship between the number of screen grids occupied after projection and the camera distance. The model is then dynamically displayed and hidden by combining the painter algorithm for occlusion calculation. Specifically, it can include:

[0101] 1. Vertebral Query

[0102] According to whether each OBB is within the camera's viewing frustum, the models that cross the viewing frustum and are outside the viewing frustum are screened out and hidden, the corresponding OBB model status is updated, and its hiding information is recorded in the model display and hide query result status.

[0103] 2. Relationship between pipe diameter and camera distance

[0104] A preliminary filtering is performed based on the relationship between the camera distance and the pipe diameter. Pipes that are farther away from the camera and have smaller diameters will be hidden (for example, the ratio of the camera distance to the pipe diameter is greater than the preset ratio threshold). The corresponding OBB model status is updated, and its hiding information is recorded in the model display and hide query result status.

[0105] 3. Relationship between bounding box size and camera distance

[0106] Filter out models with small bounding box size and far away from the camera (for example, the ratio of camera distance to bounding box size is greater than a preset ratio threshold), update the corresponding OBB model status, and record its hidden information in the model display and hide query result status.

[0107] 4. Relationship between projection area and camera distance

[0108] The OBB bounding box is projected onto the screen plane, and filtered according to the relationship between the minimum enclosing rectangle area formed after projection and the distance from the camera. Models with small minimum enclosing rectangle area and far away from the camera are filtered out (for example, the ratio of the camera distance to the minimum enclosing rectangle area is greater than the preset ratio threshold), and the corresponding OBB model state is updated, and its hidden information is recorded in the model display and hide query result state, and the calculated OBB projection information after projection is updated and recorded in the screen segmentation projection data source.

[0109] 5. Relationship between the number of screen grids occupied after projection and the camera distance

[0110] According to the number of screen squares occupied by the OBB bounding box after projection and the camera distance, further filtering is performed to filter out models whose OBB bounding box occupies a small number of screen squares after projection and are far away from the camera (for example, the ratio of the camera distance to the number of occupied screen squares is greater than a preset ratio threshold), update the corresponding OBB model state, and record its hidden information in the model display and hide query result state, and update the calculated OBB projection information after projection and record it in the screen segmentation projection data source.

[0111] 6. Occlusion calculation and model dynamic display and hiding

[0112] Based on the filtered model, the painter algorithm is applied to calculate the occlusion relationship of the model, and the calculation results are recorded in the screen segmentation projection data source. The occlusion relationship is determined by comparing whether the grids occupied by the projections of each OBB model on the screen overlap. First, the completely occluded OBB model is filtered out, and its hidden information is recorded in the model display and hide query result status. Then the number of screen grids covered by the OBB and the overlapped grids of other OBB projections is calculated and divided by the total number of screen grids of the OBB to obtain the occlusion ratio, and the models with a large occlusion ratio (for example, the occlusion ratio is greater than the preset ratio threshold) are filtered out, and the OBB bounding box is used to replace these hidden models to reduce the number of actual rendered models, and their hidden information is recorded in the model display and hide query result status, and the display information of the remaining models is recorded in the model display and hide query result status.

[0113] Figure 5 is a model loading flow chart applicable to the embodiment of the present invention, such as Figure 5 As shown, the model loading process may specifically include: obtaining the display and hiding status of the model through the above LOD rules and occlusion calculations, and dynamically updating the rendering status of the model in the scene. The other model data except the hidden model in the building model data, that is, the real BIM model to be displayed, is loaded and displayed in the rendering scene, and at the same time, the hidden real model is displayed by the corresponding OBB bounding box.

[0114] The embodiment of the present invention proposes an optimization method for loading a building information model (BIM), which reduces the number of models actually rendered by combining multiple LOD rules and occlusion algorithms and uses OBB bounding boxes to replace hidden models, thereby improving the response speed and rendering efficiency of the BIM system when processing BIM models. In particular, in scenes where there are many models with small sizes inside building floors, the number of invalidly rendered models inside complex models of multi-story buildings is effectively reduced, and the rendering status of the models in the scene is dynamically updated, thereby reducing the rendering load, improving the loading efficiency and response speed of BIM, and optimizing the loading performance of BIM.

[0115] Embodiment 3

[0116] Figure 6 This is a schematic diagram of the structure of a BIM loading optimization device provided in the third embodiment of the present invention. Figure 6 As shown, the device includes: a building model screening module 610, an information calculation module 620, a hidden model screening module 630, a model construction module 640 and a model display module 650.

[0117] The building model screening module 610 is used to screen the candidate optimized building models that meet the target loading optimization conditions from the building model data to be loaded;

[0118] The information calculation module 620 is used to calculate the OBB information of each candidate optimized building model respectively;

[0119] The hidden model screening module 630 is used to screen out candidate hidden models and target hidden models from each candidate optimized building model step by step according to the OBB information of each candidate optimized building model and using at least one level of detail rule;

[0120] A model construction module 640 is used to select a target hidden model from each candidate hidden model according to the occlusion relationship of each candidate hidden model calculated by the painter's algorithm, and to construct a target OBB model corresponding to each target hidden model;

[0121] The model display module 650 is used to load each target OBB model into the rendering scene for synchronous display while loading and displaying other model data in the building model data except the target hidden model in the rendering scene.

[0122] The technical solution of the embodiment of the present invention is to select the candidate optimized building models that meet the target loading optimization conditions in the building model data to be loaded; calculate the OBB information of each candidate optimized building model respectively; according to the OBB information of each candidate optimized building model, use at least one detail level rule to select the candidate hidden model and the target hidden model in each candidate optimized building model step by step; according to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, select the target hidden model in each candidate hidden model, and construct the target OBB model corresponding to each target hidden model; while loading and displaying other model data in the building model data except the target hidden model in the rendering scene, each target OBB model is loaded into the rendering scene for synchronous display. Through the detail level rule and the painter algorithm, the rendering status of the model in the scene is dynamically updated, the number of invalidly rendered models is reduced, the rendering load is reduced, the loading efficiency of BIM is improved, and the loading performance of BIM is optimized.

[0123] Based on the above embodiments, the hidden model screening module 630 is specifically used for:

[0124] According to the OBB information corresponding to each candidate optimized building model, the candidate optimized building model located outside the viewing frustum is screened out through the viewing frustum query as the target hidden model, and the remaining candidate optimized building models are used as candidate hidden models.

[0125] Optionally, based on the above embodiments, the hidden model screening module 630 may include: an OBB information acquisition unit and a first ratio calculation unit.

[0126] An OBB information acquisition unit is used to select the candidate optimized building models outside the visual frustum as the target hidden model, and at the same time, acquire the OBB information of the pipeline building model from the OBB information of the remaining candidate optimized building models;

[0127] The first ratio calculation unit is used to calculate a first ratio of the camera distance of each pipeline-type building model divided by the pipe diameter according to the OBB information of the pipeline-type building model, and screen out the alternative optimized building model whose first ratio is less than a first preset threshold value as the target hidden model.

[0128] Further, based on the above embodiments, the hidden model screening module 630 may further include: a second ratio calculation unit.

[0129] The second ratio calculation unit is used to calculate a second ratio obtained by dividing the camera distance of each candidate optimized building model by the size of its bounding box according to the OBB information of the remaining candidate optimized building models after screening out the candidate optimized building models whose first ratio is greater than or equal to the first preset threshold as the target hidden model, and screen out the candidate optimized building models whose second ratio is greater than or equal to the second preset threshold as the target hidden model.

[0130] Further, based on the above embodiments, the hidden model screening module 630 may further include: a third ratio calculation unit.

[0131] The third ratio calculation unit is used to, after screening out the alternative optimized building models whose second ratio is greater than or equal to the second preset threshold value as the target hidden model, project each alternative optimized building model onto the screen plane, calculate, according to the remaining OBB information of each alternative optimized building model, a third ratio obtained by dividing the camera distance of each alternative optimized building model by the area of ​​the minimum circumscribed rectangle to which the projection belongs, and screen out the alternative optimized building models whose third ratio is greater than or equal to the third preset threshold value as the target hidden model.

[0132] Further, based on the above embodiments, the hidden model screening module 630 may further include: a fourth ratio calculation unit.

[0133] The fourth ratio calculation unit is used to, after screening out the alternative optimized building models whose third ratio is greater than or equal to the third preset threshold value as the target hidden model, project each alternative optimized building model onto the screen plane, calculate, according to the remaining OBB information of each alternative optimized building model, a fourth ratio obtained by dividing the camera distance of each alternative optimized building model by the number of screen squares occupied by the projection, and screen out the alternative optimized building models whose fourth ratio is greater than or equal to the fourth preset threshold value as the target hidden model.

[0134] Based on the above embodiments, the model building module 640 is specifically used for:

[0135] According to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, the candidate hidden model that is completely occluded is selected as the target hidden model;

[0136] A fifth ratio is obtained by calculating the occlusion ratio of each remaining candidate hidden model, and the candidate optimized building models whose fifth ratio is greater than or equal to the fifth preset threshold are screened out as target hidden models.

[0137] Based on the above embodiments, the building model screening module 610 is specifically used for:

[0138] In the database, obtain the building model data to be loaded;

[0139] In the building model data to be loaded, select candidate optimized building models that meet the target loading optimization conditions, and determine the basic geometric shapes corresponding to each candidate optimized building model;

[0140] The basic geometric shapes include: pipes, walls and elbows.

[0141] The BIM loading optimization device provided in the embodiment of the present invention can execute the BIM loading optimization method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0142] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0143] Embodiment 4

[0144] Figure 7 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0145] like Figure 7 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0146] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0147] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as the optimization method for BIM loading, that is:

[0148] In the building model data to be loaded, selecting candidate optimized building models that meet the target loading optimization conditions;

[0149] Calculate the OBB information of each candidate optimized building model respectively;

[0150] According to the OBB information of each candidate optimized building model, at least one level of detail rule is used to screen out candidate hidden models and target hidden models from each candidate optimized building model step by step;

[0151] According to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, a target hidden model is screened out from each candidate hidden model, and a target OBB model corresponding to each target hidden model is constructed;

[0152] While other model data in the building model data except the target hidden model are loaded and displayed in the rendering scene, each target OBB model is loaded into the rendering scene for synchronous display.

[0153] In some embodiments, the optimization method for BIM loading may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the optimization method for BIM loading described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the optimization method for BIM loading in any other appropriate manner (e.g., by means of firmware).

[0154] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0155] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0156] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0157] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0158] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0159] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0160] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0161] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing building information model (BIM) loading, characterized in that: include: In the building model data to be loaded, selecting candidate optimized building models that meet the target loading optimization conditions; Calculate the oriented bounding box OBB information of each candidate optimized building model respectively; According to the OBB information of each candidate optimized building model, at least one level of detail rule is used to screen out candidate hidden models and target hidden models from each candidate optimized building model step by step; According to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, a target hidden model is screened out from each candidate hidden model, and a target OBB model corresponding to each target hidden model is constructed; While other model data in the building model data except the target hidden model are loaded and displayed in the rendering scene, each target OBB model is loaded into the rendering scene for synchronous display.

2. The method according to claim 1, characterized in that According to the OBB information corresponding to each candidate optimized building model, at least one level of detail rule is adopted to gradually select candidate hidden models and target hidden models from each candidate optimized building model, including: According to the OBB information corresponding to each candidate optimized building model, the candidate optimized building model located outside the viewing frustum is screened out through the viewing frustum query as the target hidden model, and the remaining candidate optimized building models are used as candidate hidden models.

3. The method according to claim 2, characterized in that While screening out the candidate optimized building models outside the viewing frustum as the target hidden model, it also includes: Obtain the OBB information of the pipeline building model from the remaining OBB information of each candidate optimized building model; According to the OBB information of the pipeline building model, a first ratio of the camera distance of each pipeline building model divided by the pipe diameter is calculated, and the candidate optimized building model whose first ratio is greater than or equal to the first preset threshold is screened out as the target hidden model.

4. The method according to claim 3, characterized in that After selecting the candidate optimized building models whose first ratio is greater than or equal to the first preset threshold as the target hidden model, the method further includes: According to the remaining OBB information of each candidate optimized building model, a second ratio of the camera distance of each candidate optimized building model divided by the size of the bounding box to which it belongs is calculated, and the candidate optimized building models whose second ratio is greater than or equal to the second preset threshold are screened out as the target hidden models.

5. The method according to claim 4, characterized in that After selecting the candidate optimized building model whose second ratio is greater than or equal to the second preset threshold as the target hidden model, the method further includes: Each candidate optimized building model is projected onto the screen plane, and according to the remaining OBB information of each candidate optimized building model, a third ratio of the camera distance of each candidate optimized building model divided by the minimum circumscribed rectangle area to which the projection belongs is calculated, and the candidate optimized building models whose third ratio is greater than or equal to the third preset threshold are screened out as the target hidden models.

6. The method according to claim 5, characterized in that After selecting the candidate optimized building model whose third ratio is greater than or equal to the third preset threshold as the target hidden model, the method further includes: Each candidate optimized building model is projected onto the screen plane, and a fourth ratio obtained by dividing the camera distance of each candidate optimized building model by the number of screen squares occupied by the projection is calculated according to the remaining OBB information of each candidate optimized building model, and the alternative optimized building models whose fourth ratio is greater than or equal to a fourth preset threshold are screened out as target hidden models.

7. The method according to any one of claim 1, characterized in that: According to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, the target hidden model is screened out from each candidate hidden model, and a target OBB model corresponding to each target hidden model is constructed, including: According to the occlusion relationship of each candidate hidden model calculated by the painter algorithm, the candidate hidden model that is completely occluded is selected as the target hidden model; A fifth ratio is obtained by calculating the occlusion ratio of each remaining candidate hidden model, and the candidate hidden models whose fifth ratio is greater than or equal to the fifth preset threshold are screened out as target hidden models.

8. The method according to any one of claims 1 to 7, characterized in that: In the building model data to be loaded, select the candidate optimized building models that meet the target loading optimization conditions, including: In the database, obtain the building model data to be loaded; In the building model data to be loaded, select candidate optimized building models that meet the target loading optimization conditions, and determine the basic geometric shapes corresponding to each candidate optimized building model; The basic geometric shapes include: pipes, walls and elbows.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the BIM loading optimization method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the BIM loading optimization method according to any one of claims 1 to 7 when executed.

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