Method and device for constructing building model, electronic equipment and storage medium

Abstract

The application provides a method and device for constructing a building model, electronic equipment and a storage medium. The method comprises: generating a three-dimensional building model of a target building according to building parameters of the target building; dividing walls of the target building into N wall categories according to wall widths of the target building; dividing floors of the target building into M floor groups according to the number of floors of the target building, each floor group comprising at least one floor, and N and M being integers greater than or equal to 2; for each floor group, determining a corresponding map image of each of the N wall categories, and the map image corresponding to at least one of the N wall categories comprising a window object; and performing map processing on the three-dimensional building model according to the map images corresponding to the M floor groups to generate a building model. The application can perform map processing on each end surface of a three-dimensional building model for an irregularly shaped building, thereby solving the problem of a large area of blank space without windows on the outer surface of the model.

Description

Technical Field

[0001] This application relates to the field of model building technology, and in particular to a method, apparatus, electronic device and storage medium for building a building model. Background Technology

[0002] Currently, in order to simulate the sunlight received by a building, a building model can be automatically generated based on data such as the building outline, total floor height, and number of floors. The model can then be used to set windows on at least some of the four end faces (the front and rear end faces and two side faces determined by the outer rectangle of the building outline) and realize sunlight simulation based on the building model.

[0003] However, when automatically generating building models based on existing rules, buildings with irregular shapes often have a large number of blank wall areas without windows, resulting in poor lighting effects and affecting the simulation of sunlight.

[0004] Therefore, it can be seen that in the existing technology, when generating building models to simulate the lighting conditions of buildings with irregular shapes, there is a problem that the lighting effect of the building models is not good, which affects the effect of sunlight simulation. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, and storage medium for constructing building models to solve the problem in the prior art where the building models generated for irregularly shaped buildings have poor lighting effects, affecting the simulation of sunlight.

[0006] In a first aspect, embodiments of this application provide a method for constructing a building model, including:

[0007] Generate a 3D building model of the target building based on its architectural parameters;

[0008] Based on the wall width of the target building, the walls of the target building are divided into N wall categories, where N is an integer greater than or equal to 2;

[0009] Based on the number of floors corresponding to the target building, the floors corresponding to the target building are divided into M floor groups, each floor group including at least one floor, where M is an integer greater than or equal to 2;

[0010] For each floor group, determine the texture images corresponding to N wall categories respectively, and the texture image corresponding to at least one of the N wall categories includes a window object;

[0011] Based on the texture images corresponding to the M floor groups, the 3D building model is processed to generate the building model of the target building.

[0012] Secondly, embodiments of this application provide an apparatus for constructing a building model, comprising:

[0013] The generation module is used to generate a three-dimensional building model of the target building based on the building parameters of the target building;

[0014] The first division module is used to divide the walls of the target building into N wall categories based on the wall width of the target building, where N is an integer greater than or equal to 2;

[0015] The second partitioning module is used to divide the floors corresponding to the target building into M floor groups according to the number of floors corresponding to the target building. Each floor group includes at least one floor, and M is an integer greater than or equal to 2.

[0016] The first determining module is used to determine the texture images corresponding to N wall categories for each floor group, wherein the texture image corresponding to at least one of the N wall categories includes a window object;

[0017] The processing and generation module is used to perform texture processing on the 3D building model according to the texture images corresponding to the M floor groups, and generate the building model of the target building.

[0018] Thirdly, embodiments of this application provide an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps in the method for constructing a building model as described in the first aspect above.

[0019] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method for constructing a building model as described in the first aspect above.

[0020] The technical solution of this application divides the walls of the target building into N wall categories based on the wall width and divides the floors of the target building into M floor groups based on the number of floors. For each floor group, a texture image corresponding to each of the N wall categories is determined. This allows for determining texture images by wall category and by floor group. By determining texture images by wall category, texture processing can be applied to the end faces of the 3D building model for buildings with irregular shapes. By setting window objects in the texture images corresponding to at least one of the N wall categories, texture processing can solve the problem of large areas of blank or windowless areas on the outer surface of the model, adapting to the automatic generation of models of buildings with different shapes and ensuring the effect of sunlight simulation. By determining the texture images corresponding to the floors by floor group, the texture images corresponding to different floors can be differentiated. Attached Figure Description

[0021] Figure 1 A schematic diagram illustrating the method for constructing a building model provided in an embodiment of this application;

[0022] Figures 2a to 2c A schematic diagram showing the building model corresponding to the irregularly shaped, unusual building provided in the embodiments of this application;

[0023] Figure 3a One of the schematic diagrams showing the image set corresponding to the floor grouping provided in the embodiments of this application;

[0024] Figure 3b A second schematic diagram illustrating the image set corresponding to the floor grouping provided in the embodiments of this application;

[0025] Figure 3c The third schematic diagram illustrating the image set corresponding to the floor grouping provided in the embodiments of this application;

[0026] Figure 4 A schematic diagram showing the texture image corresponding to the wall provided in the embodiments of this application;

[0027] Figures 5a to 5d This is a schematic diagram illustrating the combination and splicing of texture images provided in the embodiments of this application;

[0028] Figure 6a This is a schematic diagram illustrating the setting of a base model at the bottom of a three-dimensional building model and the texturing of a wainscoting image, as provided in the embodiments of this application.

[0029] Figure 6b This illustration shows how the waistline texture image is attached to the corresponding position in the 3D building model according to the embodiments of this application. Figure 1 ;

[0030] Figure 6c This is a schematic diagram showing how the waistline texture image is attached to the corresponding position of a three-dimensional building model according to an embodiment of this application.

[0031] Figure 7a This is a schematic diagram illustrating the texturing process applied to the rooftop area of ​​a 3D building model according to an embodiment of this application.

[0032] Figure 7b This is a schematic diagram illustrating the processing of a three-dimensional building model based on the outer edge shape of the roof of the target building, as provided in an embodiment of this application.

[0033] Figure 7c This is a schematic diagram illustrating the processing of a three-dimensional building model based on the inner side shape of the roof of the target building, as provided in an embodiment of this application.

[0034] Figure 8 A schematic diagram illustrating the apparatus for constructing a building model provided in an embodiment of this application;

[0035] Figure 9 This is a schematic diagram of the electronic device structure provided in the embodiments of this application. Detailed Implementation

[0036] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0037] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0038] In the various embodiments of this application, it should be understood that the sequence number of each process described below does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0039] This application provides a method for constructing a building model. See [link to relevant documentation]. Figure 1 As shown, the method includes:

[0040] Step 101: Generate a three-dimensional building model of the target building based on its architectural parameters.

[0041] The method for constructing a building model provided in this application first obtains the building parameters of a target building, and then generates a three-dimensional building model corresponding to the target building based on the building parameters. The target building can be any building within a selected residential area, a commercial building, or other types of buildings. Furthermore, the target building can be an irregularly shaped building, such as [see...]. Figures 2a to 2c The image shows a specific illustration of a building model corresponding to an irregularly shaped building. The architectural parameters of the target building can include data such as its total height, building outline, floor height, and the length of each outline line. Generating a 3D architectural model of the target building based on these parameters is the process of 3D modeling.

[0042] Step 102: Based on the wall width of the target building, divide the walls of the target building into N wall categories, where N is an integer greater than or equal to 2.

[0043] The target building corresponds to multiple walls. Based on the width of each wall in the target building, the walls are divided into N wall categories, where N is an integer greater than or equal to 2. That is, the walls of the target building are divided into at least two wall categories based on their width. The number of walls corresponding to different wall categories can vary. By classifying the walls, they can be distinguished based on their width information.

[0044] Step 103: Based on the number of floors corresponding to the target building, divide the floors corresponding to the target building into M floor groups, each floor group including at least one floor, where M is an integer greater than or equal to 2.

[0045] The target building corresponds to multiple floors. These floors can be divided into M floor groups based on the number of floors in the target building. Each floor group can include at least one floor, and M can be less than or equal to the number of floors. For each of the M floor groups, the number of floors in each group can be the same or different. If they are different, some floor groups may have the same number of floors, or all M floor groups may have different numbers of floors. For any floor group, if it includes at least two floors, these at least two floors can be consecutive or spaced out. The number of floor groups is related to the number of floors in the target building and the number of floors included in each floor group.

[0046] Step 104: For each floor group, determine the texture images corresponding to N wall categories respectively. The texture image corresponding to at least one of the N wall categories includes a window object.

[0047] After determining M floor groups and N wall categories, each of the M floor groups corresponds to one of the N wall categories. For each floor group, the texture images corresponding to the N wall categories of the current floor group can be determined, thus determining the texture images corresponding to the M floor groups.

[0048] For N wall categories, each wall category can correspond to a set of texture images, and at least one of the N wall categories has a texture image that includes a window object. By obtaining a texture image that includes a window object, we can avoid situations where a large area of ​​the model's outer surface is blank and without windows. Furthermore, the texture images corresponding to the same wall object can be different for different floor groups.

[0049] By classifying the multiple walls of the target building based on their width, the corresponding texture image can be determined based on the wall category, allowing texture images to be determined on a per-wall-category basis, thus enabling differences in texture images corresponding to walls belonging to different wall categories. Similarly, by dividing the floors of the target building into M floor groups, the texture image corresponding to each floor can be determined on a per-floor-group basis, allowing differences in texture images corresponding to different floors.

[0050] Step 105: Based on the texture images corresponding to the M floor groups, perform texture processing on the 3D building model to generate the building model of the target building.

[0051] After determining the corresponding texture image for each floor group to obtain the texture images corresponding to M floor groups, the 3D building model can be textured based on the texture images corresponding to the M floor groups. The building model corresponding to the target building can be generated through texture processing. This achieves texture processing of the 3D building model based on the texture images corresponding to the walls. It can generate corresponding building models for buildings with irregular shapes, ensuring the effect of sunlight simulation of the building model.

[0052] The above-described implementation process of this application divides the walls of the target building into N wall categories based on the wall width and divides the corresponding floors of the target building into M floor groups based on the number of floors. For each floor group, a texture image corresponding to each of the N wall categories is determined. This allows for determining texture images by wall category and by floor group. By determining texture images by wall category, texture processing can be applied to the end faces of the 3D building model for buildings with irregular shapes. By setting window objects in the texture images corresponding to at least one of the N wall categories, texture processing can solve the problem of large areas of blank or windowless areas on the outer surface of the model, adapting to the automatic generation of models of buildings with different shapes and ensuring the effect of sunlight simulation. By determining the texture images corresponding to the floors by floor group, the texture images corresponding to different floors can be differentiated.

[0053] The process of determining N wall categories is described below. When dividing the walls of the target building into N wall categories based on the wall width of the target building, the process includes: obtaining the width information corresponding to each of the multiple walls of the target building; determining N interval ranges based on the width information corresponding to each of the multiple walls, with each interval range corresponding to a wall category.

[0054] When determining the N wall categories corresponding to a target building, we can first obtain the width information of each of the multiple walls in the target building. Based on the width information of each wall, we can determine N interval ranges, which are continuous in width information. The width information of each wall belongs to one of these interval ranges, and each interval range corresponds to a wall category, thus realizing the classification of walls based on wall width information.

[0055] For example, based on the width information of the multiple walls of the target building, three ranges are determined: a range less than or equal to 1.5 meters, a range greater than 1.5 meters but less than or equal to 22 meters, and a range greater than 22 meters. In this case, the target building can correspond to three wall categories: the range less than or equal to 1.5 meters corresponds to wall category 1, the range greater than 1.5 meters but less than or equal to 22 meters corresponds to wall category 2, and the range greater than 22 meters corresponds to wall category 3. In this scenario, a single wall in the target building with a width of 10 meters corresponds to wall category 2, and a single wall in the target building with a width of 1 meter corresponds to wall category 1.

[0056] The above implementation process of this application classifies the multiple walls of the target building based on the wall width, and determines N wall categories. This facilitates the subsequent determination of the texture image corresponding to the wall category on a unit basis, thereby realizing the distinction between texture images corresponding to different wall categories.

[0057] The process of determining the M floor groups is described below. When dividing the floors of the target building into M floor groups based on the number of floors in the target building, the process includes:

[0058] Based on the number of floors, and with the principle that the number of floors corresponding to each floor group is equal and at least two floors in the same floor group are consecutive, the floors corresponding to the target building are divided into M floor groups; wherein, the number of floors corresponding to each of the M floor groups is a first value, or, the number of floors corresponding to (M-1) floor groups is the first value and the number of floors corresponding to another floor group is the second value.

[0059] When dividing the floors of a target building into groups based on the number of floors in that building, the principle for dividing the floors is that each group has the same number of floors and at least two floors within the same group are consecutive. This results in M ​​floor groups. Since the division is based on the principle of equal floors in each group, if the ratio of the number of floors in the target building to the number of floors in the corresponding group is an integer, then the number of floors in each of the M groups is the first value, which is equal to the ratio of the number of floors in the target building to M. If the ratio is not an integer, then the number of floors in (M-1) groups is the first value, and the number of floors in the third group is the second value, with the first and second values ​​being distinct.

[0060] Specifically, by dividing the floors according to the principle that the number of floors corresponding to each floor group is equal, it is possible to make the number of floors corresponding to M floor groups equal or to make the number of floors corresponding to (M-1) floor groups equal; by dividing the floors according to the principle that at least two floors in the same floor group are consecutive, consecutive floors can correspond to the same floor group, so that consecutive floors can correspond to the same texture image or correspond to the same texture image.

[0061] The following example illustrates the process of grouping floors. When each floor group corresponds to 2 floors, and the target building has 23 floors, the value of M is 12. Eleven floor groups correspond to 2 floors each, and one floor group corresponds to 1 floor. The floor number can be assigned as follows: floor 1 corresponds to floor group 1, floors 2-3 to floor group 2, floors 4-5 to floor group 3, floors 6-7 to floor group 4, and so on. Alternatively, floors 1-2 can correspond to floor group 1, floor 3 to floor group 2, floors 4-5 to floor group 3, floors 6-7 to floor group 4, and so on. Of course, the floors corresponding to the M floor groups can also take other forms.

[0062] If each floor group corresponds to 2 floors and the target building corresponds to 22 floors, then the value of M is 11, and the number of floors corresponding to each of the 11 floor groups is 2.

[0063] The above implementation process of this application divides the floors of the target building into M floor groups based on the number of floors in the target building, with the principle that the number of floors corresponding to each floor group is equal and at least two floors in the same floor group are consecutive. This can achieve that the number of floors corresponding to M floor groups or (M-1) floor groups is equal, and can make consecutive floors correspond to the same floor group, so that consecutive floors can correspond to the same texture image or correspond to the same texture image.

[0064] The following describes the process of determining the texture images corresponding to each floor group. When determining the texture images corresponding to N wall categories for each floor group, the process includes: for each floor group, determining the texture images corresponding to the N wall categories corresponding to each floor group based on the position of the floors included in the target building.

[0065] When determining the texture images corresponding to floor groups, for each floor group, based on the position of the floors included in the current floor group within the target building, the texture images corresponding to the N wall categories of the current floor group can be determined, thus obtaining the texture images corresponding to the current floor group. In this embodiment, the texture images corresponding to different positions in the target building can be different. By determining the corresponding texture images based on the position of the floors included in the floor group within the target building, texture image determination based on floor position is achieved.

[0066] Specifically, when determining the texture images corresponding to the N wall categories corresponding to the floor grouping in the target building based on the positions of the floors included in the floor grouping, the process includes:

[0067] When the height of the floors included in the floor group in the target building is greater than or equal to a preset height, a first image set corresponding to the floor group is determined. The first image set includes the texture images corresponding to the N wall categories respectively.

[0068] When the height of the floors included in the floor group in the target building is less than a preset height, a second image set corresponding to the floor group is determined. The second image set includes the texture images corresponding to the N wall categories respectively.

[0069] For floor grouping, since at least two floors in a floor group are consecutive, the image set corresponding to the floor group can be determined based on the height information of the floors in the floor group. When the height of the floors included in the floor group in the target building is greater than or equal to a preset height, a first image set corresponding to the floor group is determined; when the height of the floors included in the floor group in the target building is less than the preset height, a second image set corresponding to the floor group is determined. That is, different floor groups are distinguished based on floor height information, and then the corresponding image set is determined.

[0070] The first image set corresponding to the floor group includes the texture images corresponding to the N wall categories of the floor group, and the second image set corresponding to the floor group includes the texture images corresponding to the N wall categories of the floor group.

[0071] In this embodiment, the floor groups corresponding to floors below a preset height all correspond to the second image set, and the floor groups corresponding to floors above the preset height all correspond to the first image set. This allows for the determination of the corresponding texture image based on the floor height. This texture image determination method, when the second image set and the first image set are distinct, ensures that different floor groups in the building model above the preset height have the same texture style, and that different floor groups in the building model below the preset height have the same texture style. This allows for a more reasonable simulation of sunlight conditions and achieves a good sunlight simulation effect.

[0072] Among the N wall categories, each wall category corresponds to a type of texture image, and the texture image category corresponding to the wall category matches the wall width corresponding to the wall category.

[0073] For the multiple walls of the target building, there are N wall categories. Each wall category corresponds to a type of texture image, and the width of the texture image associated with each wall category matches the width of the wall category. Since each wall category corresponds to a range, and each range corresponds to a type of texture image, each wall category corresponds to a type of texture image. The matching relationship between the texture image category and the wall width corresponding to the wall category can be such that the larger the width of the wall category, the more complex the texture image style and the more window objects the texture image corresponds to.

[0074] For a given wall category, this wall category corresponds to a type of texture image. Since the current wall category corresponds to M floor groups, different floor groups within these M floor groups have texture images belonging to the same category for the current wall category. However, the texture images can be the same or different. By determining the texture image category based on the wall category, the texture image categories corresponding to walls of different widths can be distinguished, thus making it easier for users to understand the approximate range of wall widths based on the texture image categories.

[0075] The following example illustrates the process of determining the image set corresponding to each floor group. When the target building has 13 floors, based on the principle that each floor group includes two floors and the two floors within the same floor group are consecutive, the target building can be divided into 7 floor groups. Six of these groups consist of two floors each, and one group consists of one floor. Specifically, this can be in the following form: floors 1 and 2 correspond to floor group 1; floors 3 correspond to floor group 2; floors 4 and 5 correspond to floor group 3; floors 6 and 7 correspond to floor group 4; floors 8 and 9 correspond to floor group 5; floors 10 and 11 correspond to floor group 6; and floors 12 and 13 correspond to floor group 7. Other forms are also possible.

[0076] The target building corresponds to 13 wall categories, each wall category corresponding to a type of texture image. This example first explains the case where the wall width is greater than 1.5 meters and less than or equal to 22 meters. Specifically, the range greater than 1.5 meters and less than or equal to 2 meters corresponds to wall category 1; greater than 2 meters and less than or equal to 4 meters corresponds to wall category 2; greater than 4 meters and less than or equal to 6 meters corresponds to wall category 3; greater than 6 meters and less than or equal to 8 meters corresponds to wall category 4; greater than 8 meters and less than or equal to 10 meters corresponds to wall category 5; greater than 10 meters and less than or equal to 12 meters corresponds to wall category 6; greater than 12 meters and less than or equal to 14 meters corresponds to wall category 7; and greater than 14 meters and less than... The wall height range of 16 meters or less corresponds to wall category 8; the range greater than 16 meters and less than or equal to 18 meters corresponds to wall category 9; the range greater than 18 meters and less than or equal to 20 meters corresponds to wall category 10; and the range greater than 20 meters and less than or equal to 22 meters corresponds to wall category 11. These 11 wall categories correspond to 11 types of texture images. If the height of a building is greater than or equal to a preset height (3 floors or more), or less than a preset height (3 floors or less), then a first image set is determined for buildings with more than 3 floors, and a second image set is determined for buildings with 3 floors or less. See also... Figure 3a The image shown is the second set of images corresponding to floor group 1 (including floors 1 and 2); see also Figure 3b The image shown is the second set of images corresponding to floor group 2 (including floor 3); see also Figure 3c The image shown represents the first image set corresponding to floor groups 3 through 7. At this point, (M-2) floor groups correspond to the first image set, and 2 floor groups correspond to the second image set, with the texture images in the second image sets corresponding to the 2 floor groups being different. Floor group 1 and floor group 3 have the same texture image category but different texture image styles. For the case where the total number of floors in the target building is even (e.g., 12 floors), based on the principle that each floor group includes two floors and the two floors in the same floor group are consecutive, the target building can be divided into 6 floor groups, each containing two floors. The remaining process is similar to the above process and will not be repeated here.

[0077] For walls with a width of 1.5 meters or less (corresponding to wall category 12), the corresponding texture image may not include the window object, as shown in [reference needed]. Figure 4 As shown. Furthermore, for walls with a width of 1.5 meters or less, the texture colors corresponding to different floor groups can be different, so as to distinguish different floor groups based on texture colors.

[0078] For walls wider than 22 meters (corresponding to wall category 13), you can select the largest texture image and then tile the largest possible combination of textures at both ends. See, for example... Figures 5a to 5d As shown, in Figure 5a In the example, if the wall width is 24 meters, then for the middle 21-meter section, select texture images corresponding to a range greater than 20 meters and less than or equal to 22 meters; for the two ends, select texture images corresponding to a range less than or equal to 1.5 meters. Figure 5b In the example, if the wall width is 25 meters, then for the middle 21-meter section, select texture images corresponding to a range greater than 20 meters and less than or equal to 22 meters; for the two ends, select texture images corresponding to a range greater than 1.5 meters and less than or equal to 2 meters. Figure 5c In the example, if the wall width is 27 meters, then for the middle 21-meter section, select texture images corresponding to a range greater than 20 meters and less than or equal to 22 meters; for the two ends, select texture images corresponding to a range greater than 2 meters and less than or equal to 4 meters. Figure 5d If the wall width is 35 meters, then for the middle 21-meter section, select the texture image corresponding to the range of 20 meters or less than or equal to 22 meters, and for the two ends, select the texture image corresponding to the range of 6 meters or less than or equal to 8 meters.

[0079] The above example illustrates the process of determining floor groups, classifying wall types, and determining the image set corresponding to each floor group. Of course, there may be other implementation methods depending on different classification principles.

[0080] The following describes the texture processing process. When processing the texture of the 3D building model according to the texture images corresponding to the M floors, the process includes:

[0081] For each of the M floor groups, a first matching position is determined on the three-dimensional building model based on the position of the floor group in the target building.

[0082] The texture image corresponding to the floor group is pasted onto the first position to perform texture processing on the three-dimensional building model based on the texture image corresponding to the floor group.

[0083] After obtaining the corresponding texture image for each floor group, for each of the M floor groups, based on the current floor group's position in the target building, a first matching position can be determined on the 3D building model. Then, the texture image corresponding to the current floor group is pasted onto the determined first position. After completing the pasting of texture images at the corresponding positions in the 3D building model for the M floor groups, the texturing processing of the 3D building model is achieved.

[0084] Before or after applying textures to the 3D building model based on the texture images corresponding to the M floor groups, the process further includes: determining a second position on the 3D building model that matches the wainscoting of the target building, and determining a third position that matches the waistline of the target building; applying the wainscoting texture image corresponding to the wainscoting of the target building to the second position, and applying the waistline texture image corresponding to the waistline of the target building to the third position.

[0085] Based on the location of the wainscoting within the target building, a second matching position is determined on the 3D building model; based on the location of the waistline within the target building, a third matching position is determined on the 3D building model. At this point, the 3D building model can be either the model before or after texturing the texture images corresponding to the M floor groups.

[0086] After determining the second and third positions, the wainscoting texture image corresponding to the target building's wainscoting is applied to the second position, and the waistline texture image corresponding to the target building's waistline is applied to the third position. See, for example. Figure 6a As shown, the wainscoting of the target building is 0.6 meters high, and the wainscoting texture image is attached to the bottom of the 3D building model. Specifically, when constructing the 3D building model, a corresponding base model can be created on the 3D building model based on the building's base (formed by extending proportionally outwards from the building's outer contour). Figure 6a The diagram illustrates the formation of a base model at the bottom of the original model. See also... Figure 6b The image shows a schematic diagram of texturing the two waistlines on the target building at their corresponding positions in the 3D architectural model; see also... Figure 6c The image shows a schematic diagram of texturing the top waistline of the target building at the corresponding position in the 3D building model.

[0087] See Figure 7a As shown, the highest point from the waistline upwards to a height of 1 meter represents the rooftop, where textures can be applied to the rooftop area of ​​the 3D architectural model; see [link / reference]. Figure 7b As shown, the 3D building model can be processed accordingly based on the shape of the outer edge of the target building's roof; see also Figure 7c As shown, the 3D building model can be processed accordingly based on the shape of the inner side of the roof of the target building.

[0088] The above implementation process, by attaching wainscoting texture images to the 3D building model, makes it easier for users to distinguish between buildings and the ground based on the wainscoting texture images; by attaching waistline texture images to the 3D building model, it makes it easier for users to quickly identify the floor number in the building model based on the waistline texture images.

[0089] The above describes the overall implementation process of the method for constructing a building model provided in this application embodiment. By dividing the walls of the target building into N wall categories according to the wall width and dividing the floors of the target building into M floor groups according to the number of floors, and determining the texture images corresponding to the N wall categories for each floor group, it is possible to determine the texture images by wall category and by floor group. By determining the texture images by wall category, texture processing can be performed on each end face of the 3D building model for buildings with irregular shapes. By setting a window object in the texture image corresponding to at least one of the N wall categories, texture processing can solve the problem of a large area of ​​blank and windowless areas on the outer surface of the model, adapting to the automatic generation of models of buildings with different shapes, and ensuring the effect of sunlight simulation. By determining the texture images corresponding to the floors by floor group, the texture images corresponding to different floors can be differentiated.

[0090] Furthermore, by dividing the floors of the target building into M floor groups based on the number of floors in each floor group and the principle that the number of floors in each floor group is equal and at least two floors in the same floor group are consecutive, it is possible to achieve that the number of floors in the M floor groups or (M-1) floor groups is equal, and that consecutive floors correspond to the same floor group, so that consecutive floors can correspond to the same texture image or the same texture image.

[0091] By distinguishing image sets by height information, the texture styles of different floor groups in the building model above the preset height can be the same, and the texture styles of different floor groups in the building model below the preset height can be the same. This can reasonably simulate sunlight conditions and achieve good sunlight simulation effects. By determining the texture image category based on the wall category, the texture image categories corresponding to walls of different widths can be different, which makes it easier for users to understand the approximate range of wall width based on the texture image category.

[0092] By attaching wainscoting textures to 3D building models, users can easily distinguish buildings from the ground based on the wainscoting textures; by attaching waistline textures to 3D building models, users can easily quickly identify the number of floors in the building model based on the waistline textures.

[0093] This application provides an apparatus for constructing a building model, see [link to relevant documentation]. Figure 8 As shown, the apparatus for constructing the building model includes:

[0094] The generation module 801 is used to generate a three-dimensional building model of the target building based on the building parameters of the target building;

[0095] The first division module 802 is used to divide the walls of the target building into N wall categories based on the wall width of the target building, where N is an integer greater than or equal to 2;

[0096] The second division module 803 is used to divide the floors corresponding to the target building into M floor groups according to the number of floors corresponding to the target building, and each floor group includes at least one floor, where M is an integer greater than or equal to 2;

[0097] The first determining module 804 is used to determine the texture images corresponding to N wall categories for each floor group, wherein the texture image corresponding to at least one of the N wall categories includes a window object;

[0098] The processing and generation module 805 is used to perform texture processing on the three-dimensional building model according to the texture images corresponding to the M floor groups, and generate the building model of the target building.

[0099] Optionally, the first partitioning module includes:

[0100] The acquisition submodule is used to acquire the width information corresponding to the multiple walls of the target building;

[0101] The first determining submodule is used to determine N interval ranges based on the width information corresponding to the multiple walls, and each interval range corresponds to a wall category.

[0102] Optionally, the second partitioning module is further configured to:

[0103] Based on the number of floors, and with the principle that the number of floors corresponding to each floor group is equal and at least two floors in the same floor group are consecutive, the floors corresponding to the target building are divided into M floor groups;

[0104] Wherein, the number of floors corresponding to each of the M floor groups is the first value, or, the number of floors corresponding to (M-1) floor groups is the first value and the number of floors corresponding to another floor group is the second value.

[0105] Optionally, the first determining module is further configured to:

[0106] For each floor group, based on the position of the floors included in the floor group within the target building, determine the texture images corresponding to the N wall categories of the floor group.

[0107] Optionally, the first determining module includes:

[0108] The second determining submodule is used to determine a first image set corresponding to the floor group when the height of the floors included in the floor group in the target building is greater than or equal to a preset height. The first image set includes texture images corresponding to the N wall categories respectively.

[0109] The third determining submodule is used to determine the second image set corresponding to the floor group when the height of the floors included in the floor group in the target building is less than a preset height. The second image set includes the texture images corresponding to the N wall categories respectively.

[0110] Optionally, among the N wall categories, each wall category corresponds to a type of texture image, and the texture image category corresponding to the wall category matches the wall width corresponding to the wall category.

[0111] Optionally, the processing generation module includes:

[0112] The fourth determination submodule is used to determine a first matching position on the three-dimensional building model for each of the M floor groups, based on the position of the floor group in the target building.

[0113] The bonding submodule is used to bond the texture image corresponding to the floor group to the first position, so as to perform texture processing on the three-dimensional building model based on the texture image corresponding to the floor group.

[0114] Optionally, the device further includes:

[0115] The second determining module is used to determine, before or after the processing and generating module performs texture processing on the 3D building model according to the texture images corresponding to the M floor groups, a second position matching the skirting of the target building and a third position matching the waistline of the target building on the 3D building model.

[0116] The bonding module is used to bond the wall skirt texture image corresponding to the wall skirt of the target building to the second position and the waistline texture image corresponding to the waistline of the target building to the third position.

[0117] As the apparatus embodiments of this application are basically similar to the method embodiments for constructing building models, the description is relatively simple. For relevant details, please refer to the description of the method embodiments. They will not be repeated here.

[0118] This application also provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the various processes of the above-described method embodiment for constructing a building model and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0119] For example, Figure 9 A schematic diagram of the physical structure of an electronic device is shown. (For example...) Figure 9 As shown, the electronic device may include: a processor 910, a communication interface 920, a memory 930, and a communication bus 940, wherein the processor 910, the communication interface 920, and the memory 930 communicate with each other through the communication bus 940. The processor 910 can call logical instructions in the memory 930, and the processor 910 is used to perform the following steps: generating a three-dimensional building model of the target building based on the building parameters of the target building; dividing the walls of the target building into N wall categories based on the wall width of the target building, where N is an integer greater than or equal to 2; dividing the floors of the target building into M floor groups based on the number of floors corresponding to the target building, where each floor group includes at least one floor; determining the texture images corresponding to the N wall categories for each floor group, where the texture image corresponding to at least one of the N wall categories includes a window object; and performing texture processing on the three-dimensional building model based on the texture images corresponding to the M floor groups to generate the building model of the target building. The processor 910 can also execute other schemes in the embodiments of this application, which will not be further described here.

[0120] Furthermore, the logical instructions in the aforementioned memory 930 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0121] This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described method embodiment for constructing a building model and achieves the same technical effect. To avoid repetition, it will not be described again here. The computer-readable storage medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0122] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0123] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0124] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0125] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0126] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0127] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0128] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0129] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0130] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0131] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for constructing a building model, characterized in that, include: Generate a 3D building model of the target building based on its architectural parameters; Based on the wall width of the target building, the walls of the target building are divided into N wall categories, where N is an integer greater than or equal to 2; Based on the number of floors corresponding to the target building, the floors corresponding to the target building are divided into M floor groups, each floor group including at least one floor, where M is an integer greater than or equal to 2; For each floor group, determine the texture images corresponding to N wall categories respectively, and the texture image corresponding to at least one of the N wall categories includes a window object; Based on the texture images corresponding to the M floor groups, the 3D building model is processed to generate the building model of the target building; The wall of the target building is divided into N wall categories based on the wall width, including: Obtain the width information of each of the multiple walls of the target building; Based on the width information corresponding to each of the multiple walls, N interval ranges are determined, and each interval range corresponds to a wall category.

2. The method according to claim 1, characterized in that, The step of dividing the floors of the target building into M floor groups based on the floor number of the target building includes: Based on the number of floors, the floors corresponding to the target building are divided into M floor groups according to the principle that the number of floors corresponding to each floor group is equal and at least two floors in the same floor group are consecutive. Wherein, the number of floors corresponding to each of the M floor groups is the first value, or, the number of floors corresponding to (M-1) floor groups is the first value and the number of floors corresponding to another floor group is the second value.

3. The method according to claim 2, characterized in that, The process of determining the corresponding texture images for each of the N wall categories for each floor group includes: For each floor group, based on the position of the floors included in the floor group within the target building, determine the texture images corresponding to the N wall categories of the floor group.

4. The method according to claim 3, characterized in that, The step of determining the texture images corresponding to the N wall categories corresponding to the floor grouping in the target building based on the position of the floors included in the floor grouping includes: When the height of the floors included in the floor group in the target building is greater than or equal to a preset height, a first image set corresponding to the floor group is determined. The first image set includes the texture images corresponding to the N wall categories respectively. When the height of the floors included in the floor group in the target building is less than a preset height, a second image set corresponding to the floor group is determined. The second image set includes the texture images corresponding to the N wall categories respectively.

5. The method according to any one of claims 1 to 4, characterized in that, Among the N wall categories, each wall category corresponds to a type of texture image, and the texture image category corresponding to the wall category matches the wall width corresponding to the wall category.

6. The method according to claim 1, characterized in that, The step of applying textures to the 3D building model based on the texture images corresponding to the M floor groups includes: For each of the M floor groups, a first matching position is determined on the three-dimensional building model based on the position of the floor group in the target building. The texture image corresponding to the floor group is pasted onto the first position to perform texture processing on the three-dimensional building model based on the texture image corresponding to the floor group.

7. The method according to claim 1, characterized in that, Before or after applying textures to the 3D building model based on the texture images corresponding to the M floor groups, the process further includes: On the three-dimensional building model, determine a second position that matches the wainscoting of the target building and a third position that matches the waistline of the target building; The wainscoting texture image corresponding to the wainscoting of the target building is attached to the second position, and the waistline texture image corresponding to the waistline of the target building is attached to the third position.

8. An apparatus for constructing a building model, characterized in that, include: The generation module is used to generate a three-dimensional building model of the target building based on the building parameters of the target building; The first division module is used to divide the walls of the target building into N wall categories based on the wall width of the target building, where N is an integer greater than or equal to 2; The second partitioning module is used to divide the floors corresponding to the target building into M floor groups according to the number of floors corresponding to the target building. Each floor group includes at least one floor, and M is an integer greater than or equal to 2. The first determining module is used to determine the texture images corresponding to N wall categories for each floor group, wherein the texture image corresponding to at least one of the N wall categories includes a window object; The processing and generation module is used to perform texture processing on the three-dimensional building model according to the texture images corresponding to the M floor groups, and generate the building model of the target building; The first partitioning module includes: The acquisition submodule is used to acquire the width information corresponding to the multiple walls of the target building; The first determining submodule is used to determine N interval ranges based on the width information corresponding to the multiple walls, and each interval range corresponds to a wall category.

9. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method for constructing a building model as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the steps of the method for constructing a building model as described in any one of claims 1 to 7.

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