Structural information acquisition method and device, storage medium and electronic equipment

Abstract

The invention discloses a structure information acquisition method and device, a storage medium and electronic equipment. The method comprises the steps that a plurality of pixels are obtained, the pixels are basic composition elements of an object structure diagram, and the object structure diagram is an example diagram of an object structure; according to the structural features of the pixels, at least two pixels belonging to the same structural component are determined from the multiple pixels, the structural component formed by combining the at least two pixels is recognized, and the structural component is a constituent part of the object structure; and obtaining structural information corresponding to the structural member formed by combining the at least two pixels. The technical problem that the acquisition efficiency of the structure information is low is solved.

Description

Technical Field

[0001] The present application relates to the field of computers, and in particular to a method, device, storage medium, and electronic device for acquiring structural information. Background Art

[0002] In the acquisition of structural information, engineers usually read the drawings and then manually enter the information. However, manual drawing acquisition is slow and it is difficult to find content in the drawings, which leads to low efficiency in acquiring structural information.

[0003] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0004] The embodiments of the present application provide a method, device, storage medium, and electronic device for obtaining structural information, so as to at least solve the technical problem of low efficiency in obtaining structural information.

[0005] According to one aspect of an embodiment of the present application, a method for obtaining structural information is provided, including: obtaining a plurality of pixels, wherein the pixels are basic components of an object structure diagram, and the object structure diagram is an example diagram of the object structure; determining, based on the structural characteristics of the pixels, at least two pixels belonging to the same structural component from the plurality of pixels, and identifying a structural component formed by combining the at least two pixels, wherein the structural component is a component of the object structure; and obtaining structural information corresponding to the structural component formed by combining the at least two pixels.

[0006] According to another aspect of an embodiment of the present application, a device for acquiring structural information is also provided, including: a first acquisition unit, used to acquire multiple pixels, wherein the above-mentioned pixels are basic components of an object structure diagram, and the above-mentioned object structure diagram is an example diagram of the object structure; an identification unit, used to determine at least two pixels belonging to the same structural component from the above-mentioned multiple pixels based on the structural characteristics of the above-mentioned pixels, and identify the structural component composed of the above-mentioned at least two pixels, wherein the above-mentioned structural component is a component of the above-mentioned object structure; a second acquisition unit, used to acquire structural information corresponding to the structural component composed of the above-mentioned at least two pixels.

[0007] As an optional solution, the above-mentioned recognition unit includes: a grouping module, which is used to group the above-mentioned multiple pixels once according to the type characteristics of the above-mentioned pixels to obtain a candidate pixel set, wherein the above-mentioned structural characteristics include the above-mentioned type characteristics; an identification module, which is used to determine the above-mentioned at least two pixels from the above-mentioned candidate pixel set according to the graphic characteristics of the above-mentioned pixels, and identify the structural component composed of the above-mentioned at least two pixels, wherein the above-mentioned structural characteristics include the above-mentioned graphic characteristics.

[0008] As an optional solution, the above-mentioned grouping module includes: an acquisition sub-module, used to obtain the minimum candidate pixel belonging to the target type from the above-mentioned multiple pixels based on the above-mentioned type characteristics, wherein the above-mentioned target type is the structural type to which the structural component composed of the above-mentioned at least two pixels belongs; a first determination sub-module, used to determine the candidate pixel range from the above-mentioned object structure diagram along the above-mentioned minimum candidate pixel; and a second determination sub-module, used to determine the pixels within the above-mentioned candidate pixel range as pixels in the above-mentioned candidate pixel set.

[0009] As an optional solution, the above-mentioned recognition module includes: a recognition sub-module, which is used to determine the above-mentioned at least two pixels from the above-mentioned candidate pixel set based on the above-mentioned graphic features, and identify the structural component composed of the above-mentioned at least two pixels, wherein the closed figure in which the above-mentioned at least two pixels are located matches the outer contour corresponding to the above-mentioned target type.

[0010] As an optional solution, the above-mentioned second acquisition unit includes: an acquisition module, which is used to obtain the above-mentioned structural information based on the reference information about the structural component composed of the above-mentioned at least two pixels in the above-mentioned object structure diagram, and the shape characteristics of the structural component composed of the above-mentioned at least two pixels.

[0011] As an optional solution, the above-mentioned device also includes: a determination module for determining the numerical setting range associated with the structural component composed of the at least two pixels in the above-mentioned object structure diagram before obtaining the above-mentioned structural information about the reference information of the structural component composed of the at least two pixels and the shape characteristics of the structural component composed of the at least two pixels in the above-mentioned object structure diagram; a reading module for reading the above-mentioned reference information from the above-mentioned numerical setting range before obtaining the above-mentioned structural information about the reference information of the structural component composed of the at least two pixels and the shape characteristics of the structural component composed of the at least two pixels in the above-mentioned object structure diagram.

[0012] As an optional solution, the above-mentioned device also includes: an input module for inputting the structural image into a pre-trained neural network model to obtain the above-mentioned structural information before obtaining the above-mentioned structural information based on the above-mentioned object structure diagram, reference information about the structural component composed of the above-mentioned at least two pixels, and shape characteristics of the structural component composed of the above-mentioned at least two pixels, wherein the above-mentioned structural image is an image containing the structural component composed of the above-mentioned at least two pixels.

[0013] As an optional solution, the above-mentioned device also includes: a search unit, which is used to obtain the above-mentioned at least two pixels in response to a search operation performed on the structural component composed of the above-mentioned at least two pixels, or the above-mentioned structural information, after obtaining the structural information corresponding to the structural component composed of the above-mentioned at least two pixels.

[0014] According to another aspect of the embodiments of the present application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform the above-described method for obtaining structural information.

[0015] According to another aspect of an embodiment of the present application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the method for acquiring structural information through the computer program.

[0016] In an embodiment of the present application, a plurality of pixels are obtained, wherein the above-mentioned pixels are basic components of an object structure diagram, and the above-mentioned object structure diagram is an example diagram of the object structure; based on the structural characteristics of the above-mentioned pixels, at least two pixels belonging to the same structural component are determined from the above-mentioned plurality of pixels, and a structural component composed of the above-mentioned at least two pixels is identified, wherein the above-mentioned structural component is a component of the above-mentioned object structure; and structural information corresponding to the structural component composed of the above-mentioned at least two pixels is obtained.

[0017] Specifically, multiple pixels are first acquired. These pixels are the basic elements that constitute the object structure diagram. As a graphical representation of the structure, the object structure diagram provides an intuitive display of the structural components. Next, the pixels are intelligently classified and identified based on their structural characteristics, accurately determining at least two pixels belonging to the same structural component from the pixel set. This process replaces the tedious steps of manual search and confirmation, greatly improving the speed and accuracy of recognition. Subsequently, the identified pixels are combined into complete structural components. These components are the basic components of the object structure and can quickly form a comprehensive understanding of the structural components, avoiding the complexity and potential errors of manual combination. Finally, the corresponding structural information is automatically obtained based on the combined structural components. Through automated information acquisition, the workload of manual data entry is reduced and the accuracy and consistency of data are improved, thereby achieving the technical effect of improving the efficiency of structural information acquisition and solving the technical problem of low efficiency in structural information acquisition. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 is a schematic diagram of an application environment of an optional method for obtaining structure information according to an embodiment of the present application;

[0020] Figure 2 is a schematic diagram of a process of an optional method for obtaining structural information according to an embodiment of the present application;

[0021] Figure 3 is a schematic diagram of an optional method for obtaining structural information according to an embodiment of the present application;

[0022] Figure 4 is a schematic diagram of another optional method for obtaining structural information according to an embodiment of the present application;

[0023] Figure 5 is a schematic diagram of another optional method for obtaining structural information according to an embodiment of the present application;

[0024] Figure 6 is a schematic diagram of another optional method for obtaining structural information according to an embodiment of the present application;

[0025] Figure 7 is a schematic diagram of another optional method for obtaining structural information according to an embodiment of the present application;

[0026] Figure 8 is a schematic diagram of an optional device for acquiring structural information according to an embodiment of the present application;

[0027] Figure 9 It is a schematic structural diagram of an optional electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] According to one aspect of the embodiment of the present application, a method for obtaining structural information is provided. Optionally, as an optional implementation, the above method for obtaining structural information can be applied to, but is not limited to, Figure 1 In the environment shown, the environment may include, but is not limited to, a user device 102 and a server 112 . The user device 102 may include, but is not limited to, a display 104 , a processor 106 , and a memory 108 . The server 112 includes a database 114 and a processing engine 116 .

[0031] The specific process can be as follows:

[0032] Step S102, the user device 102 obtains a plurality of pixels;

[0033] Step S104 , sending the plurality of pixels to the server 112 via the network 110 ;

[0034] In steps S106-S108, the server 112 uses the processing engine 116 to determine, based on the structural features of the pixels, at least two pixels belonging to the same structural component from the plurality of pixels, identify the structural component formed by the at least two pixels, and further obtain structural information corresponding to the structural component formed by the at least two pixels.

[0035] In step S110 , the structure information is sent to the user device 102 via the network 110 . The user device 102 displays the structure information on the display 104 via the processor 106 and stores the structure information in the memory 108 .

[0036] remove Figure 1In addition to the examples shown, the above-mentioned terminal device can be a terminal device configured with a target client, which can include but is not limited to at least one of the following: a mobile phone (such as an Android phone, an iOS phone, etc.), a laptop computer, a tablet computer, a PDA, an MID (Mobile Internet Devices), a PAD, a desktop computer, a smart TV, etc. The target client can be a video client, an instant messaging client, a browser client, an education client, etc. The above-mentioned network can include but is not limited to: a wired network, a wireless network, wherein the wired network includes: a local area network, a metropolitan area network and a wide area network, and the wireless network includes: Bluetooth, WIFI and other networks that realize wireless communication. The above-mentioned server can be a single server, or it can be a server cluster composed of multiple servers, or a cloud server. The above is only an example, and no limitation is made to this in this embodiment.

[0037] Alternatively, as an optional implementation, Figure 2 As shown, the method for obtaining structure information can be executed by an electronic device, which can be, for example, Figure 1 The user device or server shown in the figure includes the following steps:

[0038] S202, obtaining a plurality of pixels, wherein a pixel is a basic component of an object structure graph, and the object structure graph is an example graph of an object structure;

[0039] S204, determining at least two pixels belonging to the same structural component from the plurality of pixels based on the structural characteristics of the pixels, and identifying the structural component formed by the at least two pixels, wherein the structural component is a component of the object structure;

[0040] S206: Obtain structural information corresponding to a structural component composed of at least two pixels.

[0041] Optionally, in this embodiment, pixel: in the object structure diagram, a pixel is a basic graphic element constituting a drawing, such as a line segment, an arc, a polygon, etc.

[0042] Optionally, in this embodiment, the object structure diagram is a graphical representation showing the structure of an object (such as a building, a mechanical component, etc.), and is usually composed of a plurality of pixels.

[0043] Optionally, in this embodiment, a structural component is an independent part of an object structure, such as a beam, a column, a wall, etc. in a building, and is represented by a combination of at least two pixels.

[0044] To illustrate, for example, in a building plan, each wall, door, window, staircase, and so on is represented by different pixels (such as line segments and rectangles). The system first identifies these pixels and then, based on their position, length, shape, and other characteristics, determines which pixels together constitute a structural component, such as a wall or a door. Finally, the system extracts structural information such as size, material, and location from these identified structural components.

[0045] Specifically, this embodiment can be applied to various fields that require interpretation of structural drawings, such as architectural design, mechanical design, civil engineering, etc. By automatically identifying and extracting structural information, work efficiency can be greatly improved, human errors can be reduced, and accurate data support can be provided for subsequent design, construction, or maintenance work.

[0046] Through the embodiments provided by the present application, a plurality of pixels are obtained, wherein pixels are basic components of an object structure diagram, and the object structure diagram is an example diagram of an object structure; based on the structural characteristics of the pixels, at least two pixels belonging to the same structural component are determined from the plurality of pixels, and a structural component composed of at least two pixels is identified, wherein the structural component is a component of the object structure; and structural information corresponding to the structural component composed of at least two pixels is obtained.

[0047] Specifically, a plurality of pixels are first acquired, which are the basic elements that constitute the object structure diagram. As a graphical representation of the structure, the object structure diagram provides an intuitive display of the structural components. Then, based on the structural characteristics of the pixels, the pixels are intelligently classified and identified, and at least two pixels belonging to the same structural component can be accurately determined from the pixel set. This process replaces the tedious steps of manual search and confirmation, greatly improving the speed and accuracy of recognition. Subsequently, the identified pixels are combined into complete structural components. These components are the basic components of the object structure and can quickly form a comprehensive understanding of the structural components, avoiding the complexity and potential errors of manual combination. Finally, the corresponding structural information is automatically obtained based on the combined structural components. Through automated information acquisition, the purpose of reducing the workload of manual data entry and improving the accuracy and consistency of data is achieved, thereby achieving the technical effect of improving the efficiency of obtaining structural information.

[0048] As an optional solution, based on the structural characteristics of the pixels, at least two pixels belonging to the same structural component are determined from a plurality of pixels, and the structural component formed by the combination of the at least two pixels is identified, including:

[0049] S1-1, grouping multiple pixels according to their type features to obtain a set of candidate pixels, wherein the structural features include type features;

[0050] S1-2, determining at least two pixels from a candidate pixel set according to graphic features of the pixels, and identifying a structural component composed of the at least two pixels, wherein the structural features include graphic features.

[0051] Optionally, in this embodiment, type features refer to basic classifications of pixels, such as line segments, arcs, polygons, etc. These features are used to preliminarily distinguish and group pixels.

[0052] Optionally, in this embodiment, graphic features refer to detailed features of pixels such as specific shape, size, direction, position, etc. These features are used to accurately identify and combine structural components in a candidate pixel set.

[0053] It should be noted that this embodiment describes the process of identifying and combining structural components from multiple pixels. First, the pixels are preliminarily grouped according to their type characteristics (such as line segments, circles, polygons, etc.) to form multiple candidate pixel sets. Then, within these candidate sets, the pixels' graphical characteristics (such as length, angle, relative position, etc.) are used to further determine which pixels belong to the same structural component, and ultimately, the complete structural component formed by combining these pixels is identified.

[0054] To further illustrate, when parsing an architectural drawing, the system can first group pixels based on their type characteristics (e.g., line segments, rectangles, etc.). For example, all line segment pixels are grouped together, and all rectangle pixels are grouped together in another group, forming candidate pixel sets. Then, within each set, the system determines which pixels together form a complete structural component, such as a wall or a window, based on graphical features (e.g., line segment length and angle, rectangle size and position, etc.).

[0055] By first grouping pixels based on their type characteristics and then accurately identifying and combining them based on their graphic features, this method effectively extracts useful structural information from complex graphics. This not only reduces processing complexity but also improves recognition accuracy. Furthermore, because this method operates based on the intrinsic characteristics of pixels, it is highly adaptable to graphics of varying sizes, orientations, and positions, significantly improving the efficiency and reliability of structural information acquisition.

[0056] As an optional solution, multiple pixels are grouped according to their type characteristics to obtain a candidate pixel set, including:

[0057] S2-1, obtaining a minimum candidate pixel belonging to a target type from a plurality of pixels according to the type feature, wherein the target type is a structural type to which a structural component composed of at least two pixels belongs;

[0058] S2-2, along the minimum candidate pixel, determine the candidate pixel range from the object structure graph;

[0059] S2-3, determining pixels within the candidate pixel range as pixels in the candidate pixel set.

[0060] Optionally, in this embodiment, the target type refers to the structural type to which the structural component to be identified from the object structure diagram in this embodiment belongs, such as a wall, a beam, a column, and the like.

[0061] Optionally, in this embodiment, the minimum candidate pixel is a pixel of the target type and having the smallest size or range among multiple pixels, which serves as the starting point for determining the range of candidate pixels.

[0062] Optionally, in this embodiment, the candidate pixel range is an area defined in the object structure diagram based on the minimum candidate pixel, and all pixels in the area are likely to belong to the target type of structural components.

[0063] It should be noted that this embodiment describes how to group multiple pixels according to the type characteristics of the pixels to obtain a set of candidate pixels. First, it determines the target type, that is, the structural type (such as wall, beam, column, etc.) to which the structural component to be identified belongs. Next, the minimum candidate pixel belonging to this target type is found from multiple pixels. Then, based on this minimum candidate pixel, a range of candidate pixels is determined in the object structure diagram. Finally, all pixels within this range are determined as members of the candidate pixel set.

[0064] To further illustrate, let's assume that the target type in this embodiment is a "wall" in an architectural drawing. The system will first find the smallest candidate pixel of the "wall" type from among the numerous pixels. This could be a short line segment representing a portion of a wall. The system will then define a range within the architectural drawing along this short line segment. This range may include other line segments connected to or close to this short line segment. Finally, the system will identify all line segments within this range as pixels in the candidate pixel set, as they all potentially constitute a complete wall.

[0065] By first determining the target type and finding the minimum candidate pixel, then defining the candidate pixel range based on this, and finally determining the pixels in the candidate pixel set, this method can effectively extract candidate pixels belonging to specific structural components from complex object structure graphs. This not only simplifies the recognition process but also improves its specificity and accuracy. Furthermore, because this method operates based on the type characteristics of the pixels, it is highly adaptable to structural components of varying sizes, shapes, and locations.

[0066] As an optional solution, at least two pixels are determined from a set of candidate pixels based on the graphic features of the pixels, and a structural component composed of the at least two pixels is identified, including:

[0067] At least two pixels are determined from the candidate pixel set according to the graphic features, and a structural component composed of the at least two pixels is identified, wherein the closed graphic in which the at least two pixels are located matches the outer contour corresponding to the target type.

[0068] Optionally, in this embodiment, the closed graphic is composed of at least two pixels, forming a continuous and closed graphic area.

[0069] Optionally, in this embodiment, the outer contours are matched: the outer boundary shape of the closed figure is similar to or consistent with the standard outer contour shape of the target type.

[0070] It should be noted that this embodiment describes how to determine at least two pixels from a candidate pixel set based on graphic features and identify the structural component formed by these pixels. The key is that the at least two pixels determined must form a closed shape, and the outer contour of this closed shape must match the outer contour of the target type (i.e., the type of structural component to be identified).

[0071] To illustrate this further, for example, when identifying door and window structures in architectural drawings, the system searches for pixels in the candidate pixel set that can be combined to form a closed rectangle (doors and windows are usually rectangular). The outer contour of these pixels, when combined, should match the standard door and window rectangle. Once such a pixel combination is found, the system identifies it as a door and window structural component.

[0072] By identifying at least two pixels from a candidate pixel set based on graphical features and then recognizing the structural components formed by these pixels, this embodiment can accurately extract structural information matching the target type from complex drawings. This method improves recognition accuracy and efficiency, particularly when processing large numbers of drawings or complex structures, significantly reducing manual intervention and errors and improving overall work efficiency.

[0073] As an optional solution, obtaining structural information corresponding to a structural component composed of at least two pixels includes:

[0074] Structural information is acquired according to reference information about a structural component composed of at least two pixels and shape features of the structural component composed of at least two pixels in the object structure diagram.

[0075] Optionally, in this embodiment, reference information refers to additional data or descriptions associated with a structural component composed of at least two pixels in an object structure diagram, such as annotations, dimensions, materials, etc.

[0076] Optionally, in this embodiment, shape feature refers to a specific shape or morphological feature exhibited by a structural component after being combined with at least two pixels.

[0077] It should be noted that this embodiment describes how to obtain the structural information corresponding to a structural component composed of at least two pixels. Specifically, it is obtained by combining the reference information about the structural component in the object structure diagram and the shape characteristics of the structural component.

[0078] To further illustrate, let's assume that this embodiment has identified a rectangular wall composed of multiple line segment pixels in an architectural drawing. To obtain the structural information of this wall, this embodiment will review the annotations of the wall in the drawing (such as reference information such as thickness and material), and combine them with the rectangular shape characteristics of the wall (such as length and width). By combining this information, this embodiment can fully understand the structural details of the wall.

[0079] By combining reference information from the object's structural diagram with the shape characteristics of the structural components to obtain structural information, this embodiment can obtain more comprehensive and accurate data about the structural components. This method not only improves the accuracy of information acquisition but also facilitates subsequent design, analysis, or construction work. It reduces the possibility of information omissions or misunderstandings, thereby improving the efficiency and accuracy of the entire workflow.

[0080] As an optional solution, before obtaining the structural information based on the reference information about the structural component composed of at least two pixels and the shape characteristics of the structural component composed of at least two pixels in the object structure diagram, the method further includes:

[0081] S3-1, determining a structural component composed of at least two pixels and a value setting range associated with the structural component in the object structure diagram;

[0082] S3-2, read reference information from the value setting range.

[0083] Optionally, in this embodiment, the value setting range is: a predefined area or data set associated with a specific structural component in the object structure diagram, used to store and retrieve relevant reference information of the structural component.

[0084] Optionally, in this embodiment, reference information is read: reference data related to the structural component, such as size, material properties, design parameters, etc., is retrieved and extracted from a value setting range.

[0085] It should be noted that this embodiment describes two key steps required before obtaining structural information for a structural component composed of at least two pixels. First, the numerical setting range associated with the structural component in the object structure diagram must be determined. This range is typically a predefined area or dataset containing various reference information related to the structural component. Second, specific reference information within this numerical setting range is read. This information will be used in the subsequent structural information acquisition process.

[0086] To illustrate, consider an architectural drawing depicting a beam structure composed of multiple elements. This may have an associated annotation area or data table, representing the beam's numerical range. Within this range, the designer may have specified key information such as the beam's dimensions, material type, and load-bearing capacity. Before retrieving the beam's structural information, the system must first locate this numerical range and retrieve this critical reference information.

[0087] By first determining the numerical setting range associated with the structural components in the object structure diagram and then retrieving reference information from this range, the subsequent structural information obtained can be guaranteed to be accurate and comprehensive. This approach improves the targetedness and efficiency of information acquisition and reduces the time cost of blindly searching through massive amounts of data. Furthermore, because the reference information is directly associated with the structural components, its accuracy and reliability are also guaranteed, which is crucial for subsequent design analysis, production, and manufacturing.

[0088] As an optional solution, before obtaining the structural information based on the reference information about the structural component composed of at least two pixels and the shape characteristics of the structural component composed of at least two pixels in the object structure diagram, the method further includes:

[0089] The structural image is input into a pre-trained neural network model to obtain structural information, wherein the structural image is an image of a structural component composed of at least two pixels.

[0090] Optionally, in this embodiment, the neural network model is an algorithm model that simulates the working mode of the human brain neural network, which learns and recognizes complex patterns such as images and voices through large amounts of data training.

[0091] Optionally, in this embodiment, the structural image: an image of a structural component composed of at least two pixels, is input data of the neural network model.

[0092] It should be noted that this embodiment describes a method for obtaining structural information using a pre-trained neural network model. Before obtaining structural information based on reference information and shape features in the object structure diagram, an image of a structural component composed of at least two pixels (i.e., a structural image) can be input into the pre-trained neural network model. Through automatic processing and analysis by the model, the structural information can be directly obtained.

[0093] For example, in the field of architecture, this embodiment can input architectural blueprint images containing structural components such as walls, doors, and windows into a pre-trained neural network model. This model can automatically identify and analyze the structural components in the blueprint and output their structural information, such as the size, location, and material of the wall.

[0094] By inputting structural images into a pre-trained neural network model to acquire structural information, rapid, accurate, and automated structural component identification and information extraction can be achieved. This approach not only improves the efficiency and accuracy of information acquisition, but also reduces reliance on manual operations, saving time and costs. Furthermore, the neural network model's powerful learning ability enables it to adapt to a variety of complex and variable structural component shapes and characteristics, further enhancing the flexibility and reliability of information acquisition.

[0095] As an optional solution, after obtaining structural information corresponding to a structural component composed of at least two pixels, the method further includes:

[0096] In response to a lookup operation performed on a structural member composed of at least two pixels, or structural information, at least two pixels are obtained.

[0097] Optionally, in this embodiment, the search operation refers to an operation performed by a user to locate or retrieve a specific structural component or its structural information.

[0098] It should be noted that this embodiment describes how, after obtaining the structural information corresponding to a structural component composed of at least two pixels, the system can also respond to a user's search operation on this structural component or its structural information to further obtain and display the at least two pixels. This provides a reverse search mechanism for users, allowing them to quickly locate the pixels that constitute this component based on a known structural component or its information.

[0099] Optionally, in this embodiment, the reverse search mechanism is a function of locating and acquiring pixels constituting a known structural component or its information.

[0100] To illustrate this further, let's assume that in an architectural drawing management system, a user already knows the dimensions and material information for a specific wall and wants to quickly locate the elements that make up that wall for further editing or analysis. The system provides a search function. After the user enters the relevant information about the wall, the system can quickly locate and highlight all the elements that make up the wall.

[0101] By providing a reverse search function, the system significantly enhances users' ability to manage and analyze drawings or designs. Users no longer need to manually search for specific elements within complex drawings or designs. Instead, they can quickly locate the target object through a simple search operation. This not only improves work efficiency but also reduces the possibility of errors and omissions. This feature also enhances the system's interactivity and user-friendliness, improving the user experience.

[0102] As an optional solution, for ease of understanding, the above-mentioned method for obtaining structural information is applied to a two-dimensional structural construction drawing (object structure drawing) scenario of Computer Aided Design (CAD).

[0103] Alternatively, in a two-dimensional structural construction drawing, primitives such as lines, points, and lines with CAD features (e.g., polylines) are the basic elements of the drawing. A single primitive typically does not directly represent the physical properties of a structural component; instead, a combination of multiple primitives is required to fully depict the characteristics of the component.

[0104] In terms of computer storage, pixel information, rather than direct structural information, is generally stored during the design process. To improve engineers' efficiency in utilizing drawings, this embodiment proposes a solution that uses artificial intelligence technology to directly extract component information from pixels. This includes component information extraction technology, as well as information expansion and search.

[0105] Optionally, in this embodiment, the component information extraction technology is based on the characteristics of the structural component construction drawing (including structural characteristics) as a restriction condition; performs logical self-consistent analysis on the pixels (including their characteristics); and extracts component information in a step-by-step and grouping manner.

[0106] Optionally, in this embodiment, information expansion use and search are based on the component information extracted in the first step; information expansion application is performed to realize the search function for specific component pixel information; this search function is mainly used to optimize the design by modifying the pixels.

[0107] It should be noted that in this embodiment, electronic signatures are introduced to optimize the process during the review (including the conversion of two-dimensional drawings to three-dimensional drawings). The information contained in the electronic signature is divided into two parts: graphic data and ancillary information. Among them, the graphic data can be displayed graphically in CAD and allow users to edit it. This signature mechanism is intended to solve the problem of insufficient parameter reflection and the need to repeatedly enter parameters.

[0108] This function mainly covers the following aspects:

[0109] 1. Function activation: Users can easily enable the electronic signature function.

[0110] 2. Data storage: The system provides data storage function to ensure the integrity and security of signature information and related data.

[0111] 3. Quick data viewing: Users can quickly view embedded data through the system to improve work efficiency.

[0112] 4. Stamp graphic editing: allows users to edit the graphic data of the stamp to meet different needs and scenarios.

[0113] By integrating these functions, this embodiment aims to provide an efficient and flexible electronic signature system to support information management and operation optimization during the review and design process.

[0114] To further illustrate, the optional Figure 3 As shown, the command pops up the smart search column (interface), and the conditions are set in the smart search column (interface). Click OK to select the range to be searched and complete the search.

[0115] Optionally, the technical implementation process of this embodiment is as follows: Figure 4 The specific steps are as follows:

[0116] S402, using artificial intelligence to analyze design elements, extract component information, and record the corresponding relationship between elements and components;

[0117] S404, selecting components based on the structural information and the information selection conditions;

[0118] S406, finding the pixel corresponding to the specific screening component in S402.

[0119] Specifically, in this embodiment, the logic of artificial intelligence obtaining component information is as follows:

[0120] Structural construction drawings primarily reflect the detailed characteristics of a structure through outline graphics, text, and graphic symbols. To extract useful component information from these complex drawings, this embodiment employs artificial intelligence (AI) technology for image recognition. The core principle of this technology is to deeply analyze the characteristics and relative positions of elements based on the cognitive laws of design drawings. Through logical self-consistency verification and big data analysis methods, it grouped, classified, and assembled elements along specific paths, thereby accurately extracting key component information.

[0121] To further illustrate, optionally Figure 5 As shown in the figure, the component information extraction process is as follows, taking the conventional column construction drawing details as an example:

[0122] 1. Pixel grouping: This embodiment first implements preliminary pixel grouping by identifying specific characters (such as "KZ") in professional logos. The specific steps include locating the characters containing "KZ", finding the smallest grid where the characters are located, and using this grid as a reference, searching three grids downward and one grid upward to define the range of a component data unit. This method effectively reduces the amount of single-group data, reduces the possibility of pixel combinations, and makes information extraction more accurate. Figure 6 shown.

[0123] 2. Contour recognition: Within the defined data unit, this embodiment traverses the pixels in the largest sub-box to find the largest closed box of the same color. The one with the largest area is considered as the column contour. In this way, this embodiment can obtain the outer contour information of a specific component (such as a column), and this information will be used for subsequent image recognition and positioning, such as Figure 7 shown.

[0124] 3. Rebar information extraction: Set a reasonable search range above and on the left side of the drawing, and extract detailed information about the reinforcement by looking for identification text with reinforcement symbols, such as "B side reinforcement 3 20" and "H side reinforcement 3 20".

[0125] 4. Stirrup Information Acquisition: Acquisition of stirrup information relies on the identification of steel meshes. This embodiment uses machine learning to analyze the shape characteristics of steel meshes in a large number of drawings (such as the number of points and length of polylines) to summarize recognition patterns, thereby accurately determining information such as the number of stirrup limbs. For example, "4x4" indicates the number of stirrup limbs.

[0126] By deeply analyzing the pixel features and orientation of components in graphic design drawings, combined with logical self-consistency verification and big data processing technologies, this embodiment achieves precise grouping, classification, and assembly of pixels along specific paths, thereby fully extracting component information. This method not only improves the intelligent level of image recognition but also provides strong support for subsequent engineering design, construction, and management.

[0127] In addition, this embodiment can further optimize the algorithm and expand the range of factors for pixel analysis, including but not limited to pixel characteristics provided by properties in CAD and auxiliary characteristics of xdata search, so as to improve the accuracy and efficiency of information extraction.

[0128] Through the examples provided in this application, a logically self-consistent and in-depth analysis of elements and their characteristics is performed using the construction drawing features (including structural properties) of structural components as constraints. This example implements a step-by-step, grouped intelligent component information extraction technology. This technology can accurately identify and extract key information from construction drawings, providing a solid foundation for subsequent design modifications and optimization.

[0129] Secondly, by using the extracted component information, this embodiment can efficiently search and locate two-dimensional pixels. This not only speeds up the design modification process, but also ensures the accuracy and pertinence of the modifications, thereby greatly improving the overall efficiency of the design work.

[0130] Furthermore, the introduction of artificial intelligence (AI) technology has significantly improved the efficiency of obtaining construction drawing information. Traditional information extraction methods are often time-consuming and error-prone, while AI technology can automatically complete the identification and extraction of large amounts of information in a short period of time, significantly saving manpower and time costs.

[0131] Finally, due to the efficient extraction of construction drawing information, this embodiment can now carry out more plane-based Figure 2 Searching and editing 2D component attributes and features is now possible. This means designers can quickly find and edit specific component elements in 2D drawings, enabling fine-tuning and optimization of designs. This improvement not only increases design flexibility and innovation, but also further shortens design cycles, giving companies a greater competitive advantage.

[0132] It is understandable that in the specific implementation of this application, related data such as user information is involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0133] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0134] According to another aspect of the embodiment of the present application, a device for obtaining structural information for implementing the above structural information obtaining method is also provided. Figure 8 As shown, the device includes:

[0135] A first acquiring unit 802 is configured to acquire a plurality of pixels, wherein a pixel is a basic component of an object structure graph, and the object structure graph is an example graph of an object structure;

[0136] The identification unit 804 is configured to determine, from a plurality of pixels, at least two pixels belonging to the same structural component based on the structural characteristics of the pixels, and identify the structural component formed by the at least two pixels, wherein the structural component is a component of the object structure;

[0137] The second acquiring unit 806 is configured to acquire structural information corresponding to a structural component composed of at least two pixels.

[0138] For a specific embodiment, reference may be made to the example shown in the above method for obtaining structural information, which will not be described in detail in this example.

[0139] As an optional solution, the identification unit 804 includes:

[0140] A grouping module, configured to group multiple pixels according to type features of the pixels to obtain a set of candidate pixels, wherein the structural features include type features;

[0141] The recognition module is used to determine at least two pixels from the candidate pixel set according to the graphic features of the pixels, and recognize the structural component composed of the at least two pixels, wherein the structural features include graphic features.

[0142] For a specific embodiment, reference may be made to the example shown in the above method for obtaining structural information, which will not be described in detail in this example.

[0143] As an optional solution, group modules include:

[0144] an acquisition submodule, configured to acquire, from a plurality of pixels, a minimum candidate pixel belonging to a target type according to the type feature, wherein the target type is a structural type to which a structural component composed of at least two pixels belongs;

[0145] A first determining submodule is configured to determine a candidate pixel range from the object structure graph along the minimum candidate pixel;

[0146] The second determining submodule is configured to determine pixels within the candidate pixel range as pixels in the candidate pixel set.

[0147] For a specific embodiment, reference may be made to the example shown in the above method for obtaining structural information, which will not be described in detail in this example.

[0148] As an optional solution, the identification module includes:

[0149] The recognition submodule is used to determine at least two pixels from the candidate pixel set based on the graphic features, and identify the structural component composed of the at least two pixels, wherein the closed figure in which the at least two pixels are located matches the outer contour corresponding to the target type.

[0150] For a specific embodiment, reference may be made to the example shown in the above method for obtaining structural information, which will not be described in detail in this example.

[0151] As an optional solution, the second obtaining unit 806 includes:

[0152] The acquisition module is used to acquire structural information based on reference information about a structural component composed of at least two pixels and shape features of the structural component composed of at least two pixels in the object structure diagram.

[0153] For a specific embodiment, reference may be made to the example shown in the above method for obtaining structural information, which will not be described in detail in this example.

[0154] As an optional solution, the device further includes:

[0155] a determination module configured to determine, before obtaining structural information based on reference information about a structural component composed of at least two pixels and shape features of the structural component composed of at least two pixels in the object structure diagram, a value setting range associated with the structural component composed of at least two pixels in the object structure diagram;

[0156] The reading module is used to read reference information from a value setting range before obtaining structural information based on reference information about a structural component composed of at least two pixels and shape characteristics of a structural component composed of at least two pixels in an object structure diagram.

[0157] For a specific embodiment, reference may be made to the example shown in the above method for obtaining structural information, which will not be described in detail in this example.

[0158] As an optional solution, the device further includes:

[0159] The input module is used to input a structural image into a pre-trained neural network model to obtain structural information before obtaining structural information based on reference information about a structural component composed of at least two pixels and shape characteristics of the structural component composed of at least two pixels in the object structure diagram, wherein the structural image is an image containing a structural component composed of at least two pixels.

[0160] For a specific embodiment, reference may be made to the example shown in the above method for obtaining structural information, which will not be described in detail in this example.

[0161] As an optional solution, the device further includes:

[0162] The search unit is configured to obtain at least two pixels in response to a search operation performed on the structural component composed of at least two pixels or the structural information after obtaining structural information corresponding to the structural component composed of at least two pixels.

[0163] For a specific embodiment, reference may be made to the example shown in the above method for obtaining structural information, which will not be described in detail in this example.

[0164] According to another aspect of the embodiment of the present application, an electronic device for implementing the above-mentioned method for obtaining structural information is also provided. The electronic device can be, but is not limited to, Figure 1 The user device 102 or server 112 shown in FIG. 1 is used as an example to illustrate the embodiment. Figure 9 As shown, the electronic device includes a memory 902 and a processor 904. The memory 902 stores a computer program, and the processor 904 is configured to execute the steps in any of the above method embodiments through the computer program.

[0165] Optionally, in this embodiment, the electronic device may be located in at least one network device among a plurality of network devices of a computer network.

[0166] Optionally, in this embodiment, the processor may be configured to execute the following steps through a computer program:

[0167] S1, obtaining a plurality of pixels, wherein a pixel is a basic component element of an object structure graph, and the object structure graph is an example graph of an object structure;

[0168] S2, determining at least two pixels belonging to the same structural component from the plurality of pixels based on the structural characteristics of the pixels, and identifying the structural component formed by the at least two pixels, wherein the structural component is a component of the object structure;

[0169] S3, obtaining structural information corresponding to a structural component composed of at least two pixels.

[0170] Alternatively, those skilled in the art will appreciate that Figure 9 The structure shown is for illustration only. Figure 9 It does not limit the structure of the above electronic device. For example, the electronic device may also include Figure 9 More or fewer components (such as network interfaces, etc.) as shown in, or with Figure 9 Different configurations shown.

[0171] Among them, the memory 902 can be used to store software programs and modules, such as the program instructions / modules corresponding to the method and device for obtaining structural information in the embodiments of the present application. The processor 904 executes various functional applications and data processing by running the software programs and modules stored in the memory 902, that is, realizing the above-mentioned method for obtaining structural information. The memory 902 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 902 may further include a memory remotely located relative to the processor 904, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. Among them, the memory 902 can be used to store information such as pixels, structural features, and structural information, but is not limited to it. As an example, if Figure 9 As shown, the memory 902 may include, but is not limited to, the first acquisition unit 802, the identification unit 804, and the second acquisition unit 806 in the above-mentioned structure information acquisition device. In addition, it may also include, but is not limited to, other module units in the above-mentioned structure information acquisition device, which will not be repeated in this example.

[0172] Optionally, the transmission device 906 is used to receive or send data via a network. Specific examples of the network may include wired networks and wireless networks. In one embodiment, the transmission device 906 includes a network interface controller (NIC), which can be connected to other network devices and a router via a network cable to communicate with the Internet or a local area network. In one embodiment, the transmission device 906 is a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0173] In addition, the electronic device further includes: a display 908 for displaying the above-mentioned pixels, structural features, structural information and other information; and a connection bus 910 for connecting various module components in the electronic device.

[0174] In other embodiments, the user device or server may be a node in a distributed system, wherein the distributed system may be a blockchain system, and the blockchain system may be a distributed system formed by connecting multiple nodes via network communication. The nodes may form a peer-to-peer network, and any computing device, such as a server, user device, or other electronic device, may become a node in the blockchain system by joining the peer-to-peer network.

[0175] According to one aspect of the present application, a computer program product is provided, comprising a computer program / instructions containing program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication component and / or installed from a removable medium. When the computer program is executed by a central processing unit, the various functions provided in the embodiments of the present application are performed.

[0176] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0177] It should be noted that the computer system of the electronic device is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0178] A computer system includes a central processing unit (CPU), which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) or programs loaded from the storage unit into random access memory (RAM). The RAM also stores various programs and data required for system operation. The CPU, the read-only memory, and the RAM are connected to each other via a bus. Input / output interfaces (I / O interfaces) are also connected to the bus.

[0179] The following components are connected to the input / output interface: an input section including a keyboard, mouse, etc.; an output section including a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section including a hard disk; and a communication section including a network interface card such as a local area network card and a modem. The communication section performs communication processing via a network such as the Internet. A drive is also connected to the input / output interface as needed. Removable media such as magnetic disks, optical disks, magneto-optical disks, semiconductor memories, etc. are installed in the drive as needed so that computer programs read from them can be installed into the storage section as needed.

[0180] In particular, according to an embodiment of the present application, the processes described in the various method flow charts can be implemented as computer software programs. For example, an embodiment of the present application includes a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for executing the methods shown in the flow charts. In such an embodiment, the computer program can be downloaded and installed from a network via a communication portion, and / or installed from a removable medium. When the computer program is executed by a central processing unit, the various functions defined in the system of the present application are performed.

[0181] According to one aspect of the present application, a computer-readable storage medium is provided, and a processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the various optional implementations described above.

[0182] Optionally, in this embodiment, the computer-readable storage medium may be configured to store a computer program for performing the following steps:

[0183] S1, obtaining a plurality of pixels, wherein a pixel is a basic component element of an object structure graph, and the object structure graph is an example graph of an object structure;

[0184] S2, determining at least two pixels belonging to the same structural component from the plurality of pixels based on the structural characteristics of the pixels, and identifying the structural component formed by the at least two pixels, wherein the structural component is a component of the object structure;

[0185] S3, obtaining structural information corresponding to a structural component composed of at least two pixels.

[0186] Alternatively, in the embodiments of the present application, the term "module" or "unit" refers to a computer program or a part of a computer program that has a predetermined function and works together with other related parts to achieve a predetermined goal, and can be implemented in whole or in part by using software, hardware (such as processing circuits or memories), or a combination thereof. Similarly, a processor (or multiple processors or memories) can be used to implement one or more modules or units. In addition, each module or unit can be part of an overall module or unit that includes the function of the module or unit.

[0187] Optionally, in this embodiment, a person of ordinary skill in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing hardware related to the electronic device through a program, and the program may be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0188] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0189] If the integrated units in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in the above-mentioned computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling one or more computer devices (which can be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods of each embodiment of the present application.

[0190] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0191] In the several embodiments provided in this application, it should be understood that the disclosed user equipment can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, and can be electrical or other forms.

[0192] Units described as separate components may or may not be physically separate, and 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 these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0193] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0194] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for acquiring structural information, characterized in that: include: Acquire a plurality of pixels, wherein the pixels are basic constituent elements of an object structure graph, and the object structure graph is an example graph of an object structure; According to the structural features of the pixels, at least two pixels belonging to the same structural component are determined from the plurality of pixels, and a structural component composed of the at least two pixels is identified, wherein the structural component is a component of the object structure; Structural information corresponding to the structural component formed by combining the at least two pixels is obtained.

2. The method according to claim 1, characterized in that The step of determining at least two pixels belonging to the same structural component from the plurality of pixels according to the structural features of the pixels, and identifying the structural component formed by the combination of the at least two pixels, comprises: According to the type feature of the pixel, the plurality of pixels are grouped once to obtain a candidate pixel set, wherein the structural feature includes the type feature; According to the graphic features of the pixels, the at least two pixels are determined from the candidate pixel set, and a structural component formed by the at least two pixels is identified, wherein the structural feature includes the graphic feature.

3. The method according to claim 2, characterized in that The step of grouping the plurality of pixels once according to the type characteristics of the pixels to obtain a candidate pixel set includes: According to the type feature, obtaining a minimum candidate pixel belonging to a target type from the plurality of pixels, wherein the target type is a structural type to which a structural component formed by combining the at least two pixels belongs; Determine a candidate pixel range from the object structure graph along the minimum candidate pixel; The pixels within the candidate pixel range are determined as pixels in the candidate pixel set.

4. The method according to claim 3, characterized in that The step of determining the at least two pixels from the candidate pixel set according to the graphic features of the pixels, and identifying the structural component formed by the combination of the at least two pixels, comprises: According to the graphic features, the at least two pixels are determined from the candidate pixel set, and a structural component composed of the at least two pixels is identified, wherein the closed figure in which the at least two pixels are located matches the outer contour corresponding to the target type.

5. The method according to claim 1, characterized in that The obtaining of structural information corresponding to the structural component formed by the at least two pixels comprises: The structural information is acquired according to reference information about the structural component composed of the at least two pixels and shape features of the structural component composed of the at least two pixels in the object structure diagram.

6. The method according to claim 5, characterized in that Before obtaining the structural information based on the object structure diagram, the reference information about the structural component composed of the at least two pixels and the shape characteristics of the structural component composed of the at least two pixels, the method further includes: Determine a numerical setting range associated with the structural component composed of the at least two pixels in the object structure diagram; The reference information is read from the value setting range.

7. The method according to claim 5, characterized in that Before obtaining the structural information based on the object structure diagram, the reference information about the structural component composed of the at least two pixels and the shape characteristics of the structural component composed of the at least two pixels, the method further includes: The structural image is input into a pre-trained neural network model to obtain the structural information, wherein the structural image is an image containing a structural component composed of at least two pixels.

8. The method according to any one of claims 1 to 7, characterized in that After obtaining the structural information corresponding to the structural component formed by combining the at least two pixels, the method further includes: In response to a search operation performed on a structural component composed of the at least two pixels or the structural information, the at least two pixels are acquired.

9. A device for acquiring structural information, characterized in that: include: A first acquisition unit is used to acquire a plurality of pixels, wherein the pixels are basic components of an object structure graph, and the object structure graph is an example graph of an object structure; an identification unit, configured to determine at least two pixels belonging to the same structural component from the plurality of pixels according to the structural features of the pixels, and to identify the structural component formed by the combination of the at least two pixels, wherein the structural component is a component of the object structure; The second acquisition unit is used to acquire the structural information corresponding to the structural component composed of the at least two pixels.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 8 when executed by an electronic device.

11. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method described in any one of claims 1 to 8 are implemented.

12. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 8 through the computer program.

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