Oblique photograph model processing method, apparatus, device, and readable medium

Abstract

The application discloses a tilt photography model processing method, device and equipment and a readable medium. The method comprises the following steps: acquiring logical features, geometric features and color features of a tilt photography model to be processed; inputting the logical features, the geometric features and the color features into a pre-set scene tree for hierarchical processing; and outputting the processed tilt photography model according to the logical features, the geometric features and the color features after the hierarchical processing. The scheme of the application can automatically complete the processing, input the features of the model into the scene tree by identifying the features of the model, perform hierarchical processing on the identified features through the scene tree containing the features of the model and output the features, so that the tedious steps of processing the tilt photography model manually are omitted, and the efficiency of processing the tilt photography model is improved.

Description

Technical Field

[0001] This invention relates to the field of graphics processing technology, and more particularly to methods, apparatus, devices, and readable media for oblique photogrammetry model processing. Background Technology

[0002] Currently, oblique photogrammetry automatic modeling is gradually becoming the mainstream of scene modeling. However, the data structure of oblique photogrammetry models is relatively complex and can only run in specific software. Therefore, it is necessary to simplify the oblique photogrammetry model.

[0003] Currently, simplifying oblique photogrammetry models requires manual removal of useless details, which consumes a lot of manpower and time, resulting in low simplification efficiency.

[0004] Therefore, a way is needed to improve the efficiency of oblique photogrammetry model processing. Summary of the Invention

[0005] This invention provides a method, apparatus, device, and readable medium for oblique photogrammetry model processing, in order to improve the efficiency of oblique photogrammetry model processing.

[0006] According to one aspect of the present invention, a method for processing oblique photogrammetry models is provided, comprising:

[0007] Obtain the logical, geometric, and color features of the oblique photogrammetry model to be processed;

[0008] The logical features, geometric features, and color features are input into a pre-set scene tree for hierarchical processing;

[0009] The processed oblique photogrammetry model is output based on the hierarchical logical features, geometric features, and color features.

[0010] Optionally, the logical features are obtained in the following manner:

[0011] The pre-trained logical feature recognition model is used to identify the oblique photogrammetry model to be processed, and at least one logical feature is identified.

[0012] Optionally, the logical feature recognition model is trained in the following way:

[0013] Obtain at least one sample oblique photography model;

[0014] The types of at least one logical feature included in each of the sample oblique photography models are labeled to obtain a sample oblique model set;

[0015] The sample tilt model set is input into a preset training model and trained until convergence to obtain the logical feature recognition model.

[0016] Optionally, the geometric features include: planar features and wiring features;

[0017] Accordingly, the geometric features are obtained in the following ways:

[0018] Based on the current logical characteristics, it is divided into polygonal combinations;

[0019] Determine the dihedral angle variation values ​​between the polygons in the polygon combination;

[0020] Based on the dihedral angle change value, at least one planar feature contained in the current logical feature is obtained;

[0021] Based on the planar features, the oblique photogrammetry model to be processed is divided into polygons with islands;

[0022] The island polygon is subdivided into planar features using a surface subdivision algorithm.

[0023] Optionally, the logical features, geometric features, and color features are input into a pre-set scene tree for hierarchical processing, including:

[0024] Select the target feature to be processed from the logical features, the geometric features, and the color features;

[0025] The target features are then simplified.

[0026] Optionally, the simplification process for the target features includes:

[0027] When the target feature is a planar feature, the triangular faces in the target feature are replaced by a bump map to simplify the process.

[0028] When the target feature is the wiring feature, it is simplified using an edge collapse algorithm;

[0029] When the target feature is the color feature, simplification is performed by removing unwanted colors.

[0030] Optionally, after outputting the processed oblique photogrammetry model based on the hierarchically processed logical features, the geometric features, and the color features, the method further includes:

[0031] The processed oblique photography model is then subjected to shadow removal and / or environmental occlusion processing.

[0032] According to another aspect of the present invention, an oblique photography model processing apparatus is provided, comprising:

[0033] The feature acquisition unit is used to acquire the logical features, geometric features, and color features of the oblique photogrammetry model to be processed;

[0034] The feature input unit is used to input the logical features, the geometric features and the color features into a pre-set scene tree for hierarchical processing;

[0035] The model output unit is used to output the processed oblique photogrammetry model based on the hierarchical logical features, the geometric features, and the color features.

[0036] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0037] 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, the computer program being executed by the at least one processor to enable the at least one processor to perform the oblique photogrammetry model processing method according to any embodiment of the present invention.

[0038] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the oblique photogrammetry model processing method according to any embodiment of the present invention.

[0039] The technical solution of this invention involves acquiring the logical features, geometric features, and color features of a photogrammetric model to be processed; inputting the logical features, geometric features, and color features into a pre-set scene tree for hierarchical processing; and outputting the processed photogrammetric model based on the hierarchically processed logical features, geometric features, and color features. This solution can automate the process by identifying the model's features, inputting these features into a scene tree, and then hierarchically processing and outputting the identified features through the scene tree containing the model's features. This eliminates the tedious steps of manual processing of the photogrammetric model and improves the efficiency of photogrammetric model processing.

[0040] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart of an oblique photography model processing method provided in Embodiment 1 of the present invention;

[0043] Figure 2 This is a flowchart of a model feature hierarchical processing method provided in Embodiment 2 of the present invention;

[0044] Figure 3 This is a schematic diagram of the structure of an oblique photography model processing device provided in Embodiment 3 of the present invention;

[0045] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the oblique photography model processing method of the present invention. Detailed Implementation

[0046] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0047] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0048] Example 1

[0049] Figure 1 This is a flowchart of an oblique photogrammetry model processing method provided in Embodiment 1 of the present invention. This embodiment is applicable to the case of simplifying oblique photogrammetry models. The method can be executed by an oblique photogrammetry model processing device, which can be implemented in hardware and / or software and can be configured in a computer.

[0050] like Figure 1 As shown, the method includes:

[0051] S110. Obtain the logical features, geometric features, and color features of the oblique photogrammetry model to be processed.

[0052] Oblique photogrammetry, in particular, comprehensively perceives complex scenes with large scale, high precision, and high definition. The data generated through efficient data acquisition equipment and professional data processing workflows intuitively reflects the appearance, location, height, and other attributes of ground features, ensuring realistic effects and surveying-grade accuracy. Currently, automatic oblique photogrammetry modeling is gradually becoming the mainstream method for scene modeling; however, it suffers from problems such as large generated model sizes, unreasonable linework, numerous useless details, and cumbersome removal processes.

[0053] In this embodiment of the invention, the oblique photogrammetry model to be processed is first read, supporting multiple formats such as Fbx, Obj, Max, Laz, OSGB, and STL. The oblique photogrammetry model to be processed is then extracted based on three categories of features: geometric, logical, and color. Logical features describe the architectural features corresponding to the oblique photogrammetry model, such as facades, roofs, windows, window sills, doors, air conditioner units, eaves, and parapet walls. Geometric features include the planar features and wiring features of the oblique photogrammetry model to be processed. Color features represent the color information of each part of the oblique photogrammetry model to be processed.

[0054] In this embodiment of the invention, the logical feature is obtained in the following manner:

[0055] The pre-trained logical feature recognition model is used to identify the oblique photogrammetry model to be processed, and at least one logical feature is identified.

[0056] The logical feature recognition model is trained in the following way:

[0057] Obtain at least one sample oblique photography model;

[0058] The types of at least one logical feature included in each of the sample oblique photography models are labeled to obtain a sample oblique model set;

[0059] The sample tilt model set is input into a preset training model and trained until convergence to obtain the logical feature recognition model.

[0060] Among them, a recognition convolutional neural network is trained using a large amount of labeled oblique photogrammetry models and texture data. The network can extract the outer boxes and feature IDs of various logical features from the model data.

[0061] In this embodiment of the invention, the geometric features include: planar features and wiring features;

[0062] Accordingly, the geometric features are obtained in the following ways:

[0063] Based on the current logical characteristics, it is divided into polygonal combinations;

[0064] Determine the dihedral angle variation values ​​between the polygons in the polygon combination;

[0065] Based on the dihedral angle change value, at least one planar feature contained in the current logical feature is obtained;

[0066] Based on the planar features, the oblique photogrammetry model to be processed is divided into polygons with islands;

[0067] The island polygon is subdivided into planar features using a surface subdivision algorithm.

[0068] Among these features, planar features are the main features for optimizing the oblique photogrammetry model. Planar features are obtained through polygon expansion and cumulative dihedral angles. That is, a polygon is selected, and the angle between it and its adjacent polygons is detected. If the cumulative dihedral angle changes within the allowable range, they are considered to be on the same plane. Planar features are a stage for further subdividing features after logical features have been identified.

[0069] Wiring features are features extracted based on the vertex distribution of the model. Inappropriate wiring can lead to abnormal lighting later. This program corrects wiring features by first extracting the planar features of the model, converting them into polygons with islands, and then using a surface subdivision algorithm to re-subdivide the planes to obtain good wiring features.

[0070] S120. Input the logical features, geometric features and color features into a pre-set scene tree for hierarchical processing.

[0071] This invention transforms the oblique photogrammetry model to be processed into a topological vertex + index + feature format, called a scene tree. After feature acquisition, it is synchronously stored in the scene tree. These features enable hierarchical output of models with different levels of precision.

[0072] S130. Output the processed oblique photography model based on the hierarchical logical features, the geometric features, and the color features.

[0073] In this process, a classification tree is used to hierarchically process the oblique photogrammetry model to be processed, and the model is optimized from multiple levels such as geometric features, logical features and color features.

[0074] The solution of the present invention can be automated. By identifying the features of the model, the features of the model are input into the scene tree. The scene tree containing the features of the model performs hierarchical processing on the identified features and outputs them, thereby eliminating the tedious steps of manual processing of oblique photogrammetry models and improving the efficiency of oblique photogrammetry model processing.

[0075] Example 2

[0076] Figure 2 This is a flowchart of a model feature hierarchical processing method provided in Embodiment 2 of the present invention.

[0077] like Figure 2 As shown, the method includes:

[0078] S210. Select the target feature to be processed from the logical feature, the geometric feature and the color feature.

[0079] Once the logical, geometric, and color features are acquired, they are simultaneously stored in the scene tree. These features enable tiered output of models with varying levels of precision. For example, for the facade of the same building, the window feature can be output as a model to obtain a more detailed architectural model, or the entire wall can be treated as a planar feature, in which case the window is represented by a diffuse map and a bump map.

[0080] S220. Simplify the target features.

[0081] In this embodiment of the invention, the simplification process for the target feature includes:

[0082] When the target feature is a planar feature, the triangular faces in the target feature are replaced by a bump map to simplify the process.

[0083] When the target feature is the wiring feature, it is simplified by an edge collapse algorithm.

[0084] When the target feature is the color feature, simplification is performed by removing unwanted colors.

[0085] Specifically, after obtaining the planar features, the bump map of the plane can be obtained through a depth algorithm. The plane with the added bump map is then used to replace all the triangular faces that make up the plane, thus completing the feature replacement.

[0086] After obtaining the routing features, the face is simplified by an improved edge collapse algorithm. That is, when collapsing the edge, not only the quadratic error collapse fraction is considered, but also the influence of the uniformity of the planar routing is considered, so as to obtain a model with good routing features.

[0087] Color features are used to remove excessive noise from oblique photogrammetry models. The method involves significantly reducing texture size or increasing texture resolution using repeating textures. First, the program uses planar features to convert the vertex colors of the oblique photogrammetry model into diffuse textures. Then, a recognition network is used to identify image features on the textures, identify repeating units, compare them, remove noise from the image, and replace large areas of the texture with repeating units of a preset proportion.

[0088] In this embodiment of the invention, after outputting the processed oblique photogrammetry model based on the hierarchically processed logical features, the geometric features, and the color features, the method further includes:

[0089] The processed oblique photography model is subjected to shadow removal and / or environmental occlusion processing.

[0090] Due to changes in time, shadows in a scene can be distorted during oblique photography, especially shadows caused by weather changes, which often need to be removed. The program uses projection methods to eliminate shadows. First, it calculates the location of the shadows cast by buildings based on time and the angle of sunlight, finds the shadow boundaries, and then adjusts the brightness of the shadow area by calculating the brightness difference between the shaded and illuminated sides and the brightness difference at the shadow boundaries, thereby eliminating the shadows.

[0091] Before outputting the oblique photogrammetry model, ambient occlusion based on floodlight can be performed. That is, based on a floodlight, a ray tracing algorithm is used to automatically generate an AO map for the model, which increases the realism of the oblique photogrammetry model.

[0092] The solution provided in this invention can automatically complete the optimization of oblique photogrammetry models. Its working method involves identifying model features, merging logically or geometrically related triangles, adjusting unreasonable topology, generating bump maps for the plane under set threshold conditions, automatically removing shadows from the model, regenerating the model's environmental occlusion information, and finally generating a small-volume, high-quality, and detailed 3D model.

[0093] Example 3

[0094] Figure 3 This is a schematic diagram of the structure of an oblique photography model processing device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes:

[0095] The feature acquisition unit 310 is used to acquire the logical features, geometric features and color features of the oblique photogrammetry model to be processed;

[0096] The feature input unit 320 is used to input the logical features, the geometric features and the color features into a pre-set scene tree for hierarchical processing;

[0097] The model output unit 330 is used to output the processed oblique photogrammetry model based on the hierarchical logical features, the geometric features, and the color features.

[0098] Optionally, the feature acquisition unit 310 is used to acquire the logical features in the following manner:

[0099] The pre-trained logical feature recognition model is used to identify the oblique photogrammetry model to be processed, and at least one logical feature is identified.

[0100] Optionally, the logical feature recognition model is trained in the following way:

[0101] Obtain at least one sample oblique photography model;

[0102] The types of at least one logical feature included in each of the sample oblique photography models are labeled to obtain a sample oblique model set;

[0103] The sample tilt model set is input into a preset training model and trained until convergence to obtain the logical feature recognition model.

[0104] Optionally, the geometric features include: planar features and wiring features; correspondingly, the feature acquisition unit 310 is used to acquire the geometric features in the following manner:

[0105] Based on the current logical characteristics, it is divided into polygonal combinations;

[0106] Determine the dihedral angle variation values ​​between the polygons in the polygon combination;

[0107] Based on the dihedral angle change value, at least one planar feature contained in the current logical feature is obtained;

[0108] Based on the planar features, the oblique photogrammetry model to be processed is divided into polygons with islands;

[0109] The island polygon is subdivided into planar features using a surface subdivision algorithm.

[0110] Optionally, the feature input unit 320 is used to perform:

[0111] Select the target feature to be processed from the logical features, the geometric features, and the color features;

[0112] The target features are then simplified.

[0113] Optionally, when performing the simplification process on the target features, the feature input unit 320 specifically performs the following:

[0114] When the target feature is a planar feature, the triangular faces in the target feature are replaced by a bump map to simplify the process.

[0115] When the target feature is the wiring feature, it is simplified by an edge collapse algorithm.

[0116] When the target feature is the color feature, simplification is performed by removing unwanted colors.

[0117] Optionally, the model output unit 330 is also configured to perform shadow removal and / or ambient occlusion processing on the processed oblique photogrammetry model.

[0118] The oblique photogrammetry model processing apparatus provided in the embodiments of the present invention can execute the oblique photogrammetry model processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0119] Example 4

[0120] Figure 4 A schematic diagram of an electronic device 10 that can be used to implement embodiments 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 processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0121] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0122] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0123] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as oblique photogrammetry model processing methods.

[0124] In some embodiments, the oblique photogrammetry model processing method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the oblique photogrammetry model processing method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the oblique photogrammetry model processing method by any other suitable means (e.g., by means of firmware).

[0125] Various embodiments 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-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0126] Computer programs used to implement 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, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0127] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0128] To provide interaction with a user, the systems and techniques described herein can 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 pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0129] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0130] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0131] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0132] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for processing oblique photogrammetry models, characterized in that, include: Obtain the logical, geometric, and color features of the oblique photogrammetry model to be processed; The logical features, geometric features, and color features are input into a pre-set scene tree for hierarchical processing; The processed oblique photogrammetry model is output based on the hierarchical logical features, the geometric features, and the color features. The processed oblique photography model is subjected to shadow removal and environment occlusion processing; The shadow removal process for the processed oblique photography model includes: The projection method is used to eliminate shadows. The shadow boundary is found based on time and sunlight angle. The brightness difference between the backlit side and the lit side and the brightness difference of the shadow boundary are calculated. The shadow is eliminated by adjusting the brightness of the shadow area. The geometric features include: planar features and wiring features; Accordingly, the geometric features are obtained in the following ways: The oblique photogrammetry model to be processed is divided into polygon combinations based on the current logical characteristics; Determine the dihedral angle variation values ​​between the polygons in the polygon combination; Based on the dihedral angle change value, at least one planar feature contained in the current logical feature is obtained; Based on the planar features, the oblique photogrammetry model to be processed is divided into polygons with islands; The island polygon is subdivided into planar features using a surface subdivision algorithm.

2. The method according to claim 1, characterized in that, The logical features are obtained in the following way: The pre-trained logical feature recognition model is used to identify the oblique photogrammetry model to be processed, and at least one logical feature is identified.

3. The method according to claim 2, characterized in that, The logical feature recognition model is trained in the following way: Obtain at least one sample oblique photography model; The types of at least one logical feature included in each of the sample oblique photography models are labeled to obtain a sample oblique model set; The sample tilt model set is input into a preset training model and trained until convergence to obtain the logical feature recognition model.

4. The method according to claim 1, characterized in that, The logical features, geometric features, and color features are input into a pre-set scene tree for hierarchical processing, including: Select the target feature to be processed from the logical features, the geometric features, and the color features; The target features are then simplified.

5. The method according to claim 4, characterized in that, The simplification process for the target features includes: When the target feature is a planar feature, the triangular faces in the target feature are replaced by a bump map to simplify the process. When the target feature is the wiring feature, it is simplified using an edge collapse algorithm; When the target feature is the color feature, simplification is performed by removing unwanted colors.

6. An oblique photography model processing device, characterized in that, include: The feature acquisition unit is used to acquire the logical features, geometric features, and color features of the oblique photogrammetry model to be processed; The feature input unit is used to input the logical features, the geometric features and the color features into a pre-set scene tree for hierarchical processing; The model output unit is used to output the processed oblique photogrammetry model based on the hierarchical logical features, the geometric features, and the color features. The model output unit is further used to perform shadow removal and environmental occlusion processing on the processed oblique photogrammetry model. The shadow removal process for the processed oblique photography model includes: The projection method is used to eliminate shadows. The shadow boundary is found based on time and sunlight angle. The brightness difference between the backlit side and the lit side and the brightness difference of the shadow boundary are calculated. The shadow is eliminated by adjusting the brightness of the shadow area. The geometric features include: planar features and wiring features; The feature acquisition unit is specifically used to acquire the geometric features in the following manner: The oblique photogrammetry model to be processed is divided into polygon combinations based on the current logical characteristics; Determine the dihedral angle variation values ​​between the polygons in the polygon combination; Based on the dihedral angle change value, at least one planar feature contained in the current logical feature is obtained; Based on the planar features, the oblique photogrammetry model to be processed is divided into polygons with islands; The island polygon is subdivided into planar features using a surface subdivision algorithm.

7. An electronic device, characterized in that, The electronic device includes: 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, the computer program being executed by the at least one processor to enable the at least one processor to perform the oblique photogrammetry model processing method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the oblique photogrammetry model processing method according to any one of claims 1-5.

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