Virtual plant modeling method and device, electronic equipment, medium and product

Abstract

The invention discloses a virtual plant modeling method and device, electronic equipment, a medium and a product, and is applied to the technical field of digital modeling. The method comprises the steps of obtaining a plant name of a to-be-generated virtual plant in response to a first input operation; determining matched vegetation morphological parameters of the plant name in a preset botanical knowledge base, wherein the vegetation morphological parameters are used for representing three-dimensional morphological characteristics of the virtual plant; determining the value of each vegetation morphological parameter, and performing parameter mapping on each vegetation morphological parameter to generate an initial model file, the initial model file comprising initial model parameters for generating a three-dimensional model of a virtual plant; and generating a three-dimensional model of the virtual plant based on the initial model file. Therefore, the modeling threshold can be reduced, the modeling efficiency of the virtual plant is greatly improved while the modeling reasonability is guaranteed, and the project development progress is effectively improved.

Description

Technical Field

[0001] This application belongs to the field of digital modeling technology, specifically relating to a modeling method for virtual plants, a modeling device for virtual plants, electronic equipment, computer-readable storage media, and computer program products. Background Technology

[0002] Virtual plants are an important component in building realistic virtual worlds, and the accuracy of their forms directly determines the visual effects and immersive experience of virtual scenes. Open worlds in virtual games, natural landscapes in film and television special effects, and ecological simulations in virtual reality all rely on high-quality virtual plant modeling.

[0003] However, existing manual modeling methods in 3ds Max, which rely on manual topology and sculpting of details to achieve high-precision customization of virtual plants, suffer from extremely low modeling efficiency, difficulty in batch generation, high labor costs, and poor standardization. The existing procedural method using SpeedTree simulates plant growth logic through parametric algorithms, rapidly generating virtual plants that conform to ecological characteristics in batches. However, it suffers from over-reliance on algorithm templates, requiring developers to have extensive experience in vegetation creation and long-term use of SpeedTree software, resulting in a high development threshold and making it difficult for users without prior experience to quickly get started. These existing methods severely restrict the development progress of large-scale virtual scenes and fail to meet the industry's urgent need for efficient, batch generation of virtual plants. Summary of the Invention

[0004] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a virtual plant modeling method, a virtual plant modeling device, an electronic device, a computer-readable storage medium, and a computer program product, which can lower the modeling threshold, significantly improve the modeling efficiency of virtual plants while ensuring the rationality of the modeling, and effectively accelerate the project development progress.

[0005] Firstly, this application provides a method for modeling virtual plants, comprising: In response to the first input operation, obtain the plant name of the virtual plant to be generated; Determine the vegetation morphology parameters that match the plant name in a preset botanical knowledge base. The vegetation morphology parameters are used to characterize the three-dimensional morphological features of the virtual plant. The preset botanical knowledge base includes at least one set of vegetation morphology parameters, including the vegetation morphology parameters that match the plant name. The values ​​of each of the vegetation morphology parameters are determined, and parameter mapping is performed on each of the vegetation morphology parameters to generate an initial model file, which contains the initial model parameters for generating the three-dimensional model of the virtual plant. A three-dimensional model of the virtual plant is generated based on the initial model file.

[0006] Secondly, this application provides a virtual plant modeling device, comprising: The acquisition module is used to acquire the plant name of the virtual plant to be generated in response to the first input operation; The determination module is used to determine the vegetation morphology parameters that match the plant name in a preset botanical knowledge base. The vegetation morphology parameters are used to characterize the three-dimensional morphological features of the virtual plant. The preset botanical knowledge base includes at least one set of vegetation morphology parameters, including the vegetation morphology parameters that match the plant name. The mapping module is used to determine the values ​​of each of the vegetation morphology parameters and perform parameter mapping on each of the vegetation morphology parameters to generate an initial model file, wherein the initial model file contains the initial model parameters for generating the three-dimensional model of the virtual plant. The generation module is used to generate a three-dimensional model of the virtual plant based on the initial model file.

[0007] Thirdly, this application provides an electronic device including a memory and a processor; the memory stores a computer program, and the processor executes the above-mentioned virtual plant modeling method by calling the computer program stored in the memory.

[0008] Fourthly, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned virtual plant modeling method.

[0009] Fifthly, this application provides a computer program product including computer instructions, which, when executed by a processor, implement the aforementioned virtual plant modeling method.

[0010] The virtual plant modeling method, virtual plant modeling device, electronic device, computer-readable storage medium, and computer program product provided in this application embodiment obtain the plant name of the virtual plant to be modeled by responding to a first input operation. Then, it queries and obtains vegetation morphology parameters that match the plant name from a preset botanical knowledge base. Since the vegetation morphology parameters in the botanical knowledge base can be determined based on the morphology parameters of actual plants, the accuracy of the three-dimensional morphological features of the virtual plant can be guaranteed. Then, the values ​​of each vegetation morphology parameter are determined to determine the basic structure of the virtual plant, which facilitates subsequent modeling. By mapping the various vegetation morphology parameters of the virtual plant, an initial model file containing the initial model parameters required for modeling is obtained. Finally, the modeling of the virtual plant is completed based on the initial model file.

[0011] Thus, compared to manually adjusting modeling details such as wiring and shape, this application only requires inputting the plant name, which lowers the modeling threshold. While ensuring the rationality of the modeling through a botanical knowledge base, it significantly improves the modeling efficiency of virtual plants, effectively speeds up the project's development progress, and meets the needs of large-scale virtual scenes.

[0012] Additional aspects and advantages of embodiments of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of embodiments of this application. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Among them: Figure 1 This is an application scenario diagram of the virtual plant modeling method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the first process of the virtual plant modeling method provided in the embodiments of this application; Figure 3 This is a schematic diagram of the second process of the virtual plant modeling method provided in the embodiments of this application; Figure 4 This is a schematic diagram of the third process of the virtual plant modeling method provided in the embodiments of this application; Figure 5 This is a schematic diagram showing the configuration interface of the virtual plant modeling method provided in the embodiments of this application; Figure 6 This is a schematic diagram of the modules of the virtual plant modeling device provided in the embodiments of this application; Figure 7 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application; Figure 8 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0014] The embodiments of this application are described in detail below. Examples of the embodiments of this application are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0015] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0016] In view of the problems existing in the background art, the present application provides a method for modeling virtual plants, a device for modeling virtual plants, an electronic device, a computer-readable storage medium, and a computer program product.

[0017] Specifically, the virtual plant modeling method of this application embodiment can be executed by an electronic device, which can be a terminal or a server. The terminal can be a smartphone, tablet, laptop, smart TV, wearable smart device, smart vehicle terminal, etc. The terminal can also include a client, which can be a modeling client, browser client, instant messaging client, or mini-program, etc. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0018] For example, when the virtual plant modeling method runs on a terminal device, the terminal device may include a display screen and a processor. The display screen is used to present the modeling screen and receive instructions generated by the user interacting with it. The processor is used to store the modeling application, run the modeling application, generate the modeling screen, respond to instructions, and control the display of the modeling screen on the display screen. When the user operates the modeling screen through the display screen, the modeling screen can control the local content of the terminal device in response to the received operation instructions. The terminal device can provide the graphical user interface to the user in various ways, such as rendering it on the terminal device's display screen or presenting the graphical user interface through holographic projection.

[0019] For example, when the virtual plant modeling method runs on a server, it can be implemented and executed based on a cloud modeling system. A cloud modeling system refers to a modeling approach based on cloud computing. A cloud modeling system includes a server and client devices. The main body running the modeling application and the main body presenting the modeling screen are separate. The storage and execution of the virtual plant modeling method are completed on the server. The presentation of the modeling screen is completed on the client. The client is mainly used for receiving and sending modeling data and presenting the modeling screen. For example, the client can be a display device with data transmission capabilities located close to the user, such as a mobile terminal, television, computer, PDA, personal digital assistant, head-mounted display device, etc. However, the terminal device for processing modeling data is the server in the cloud. During modeling, the user operates the client to send instructions to the server. The server controls the operation of the modeling application according to the instructions, encodes and compresses the modeling screen and other data, returns it to the client via the network, and finally, the client decodes and outputs the modeling screen.

[0020] It should be noted that, in this embodiment, the executing entity of the virtual plant modeling method can be a terminal device or a server. The terminal device can be a local terminal device or a client device in the aforementioned cloud modeling system. This embodiment does not limit the type of executing entity.

[0021] It is understood that in the specific implementation of this application, user object data, context data and other related data are involved. When the embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0022] For example, in conjunction with the above description, Figure 1 This application illustrates a modeling system 100 for implementing a virtual plant modeling method. The modeling system 100 may include at least one terminal 10, at least one server 20, at least one database 30, and a network. The user-held terminal 10 can connect to different servers 20 via the network. The terminal 10 can be any device with computing hardware capable of supporting and executing software application tools corresponding to the modeling process.

[0023] In the aforementioned modeling system 100, terminal 10 is used to install and run the modeling application. In some cases, the modeling application may not need to be pre-installed on terminal 10; users can directly access the modeling application through a browser or other client. Users can log in to the modeling application using their registered account to participate in modeling. When a user logs in, terminal 10 sends a login request to server 20. Server 20 verifies the user's account and determines the corresponding modeling mechanism based on the login request. If verification is successful, a login success notification is returned to terminal 10. During the user's participation in modeling through the modeling application, terminal 10 and server 20 interact. Terminal 10 sends various information to server 20, and server 20 determines the display data for terminal 10 based on the stored modeling mechanism and the received information, then sends the display data back to terminal 10 so that terminal 10 can display the data sent by server 20 to the user.

[0024] In possible application scenarios, different terminals 10 may be served by different servers 20. Therefore, in order to distinguish the servers 20 corresponding to different terminals 10, the embodiments of this application will use the terms "first" and "second" to describe them. In fact, the servers 20 corresponding to different terminals 10 can be the same server 20. Therefore, without distinguishing between "first" and "second", it can be understood that terminals 10 located in the same modeling scene are served by the same server 20.

[0025] Furthermore, when the modeling system 100 includes multiple terminals, multiple servers, and multiple networks, different terminals can connect to each other through different networks and servers. The network can be a wireless network or a wired network; for example, wireless networks include wireless local area networks (WLAN), local area networks (LAN), cellular networks, 4G networks, 5G networks, etc. Additionally, different terminals can also connect to other terminals or to servers using their own Bluetooth networks or hotspot networks. Moreover, the system 100 can include multiple databases coupled to different servers, and can continuously store modeling-related information in the databases as different users perform multi-user modeling online.

[0026] It should be noted that in this embodiment, multiple terminal devices run the same virtual modeling application. Therefore, data interaction between multiple terminal devices can be achieved through the server of the virtual modeling application. Thus, sending data from terminal device 1 to terminal device 2 can be understood as: terminal device 1 sends data to the server corresponding to the virtual modeling application, and the server sends the data to terminal device 2. Receiving data from terminal device 2 can be understood as: terminal device 1 receives data sent by the server of the virtual modeling application, which is the data sent by terminal device 2 to the server. Alternatively, there may be no server corresponding to the virtual modeling application, and terminal device 1 directly sends modeling data to terminal device 2.

[0027] It should be noted that, Figure 1 The schematic diagram of the modeling system shown is merely an example. The modeling system described in this application embodiment is intended to more clearly illustrate the technical solutions of this application embodiment and does not constitute a limitation on the technical solutions provided in this application embodiment. As those skilled in the art will know, with the evolution of modeling systems and the emergence of new business scenarios, the technical solutions provided in this application embodiment are also applicable to similar technical problems.

[0028] It should be noted that the input operations mentioned in the subsequent detailed description of the virtual plant modeling method provided in this application embodiment can all be regarded as trigger operations performed by the user through a finger or by controlling a medium such as a mouse, keyboard, or stylus. The specific medium used can be determined based on the type of electronic device. For example, when the electronic device is a touchscreen device such as a mobile phone or tablet, the user can operate on the touchscreen using any suitable object or accessory such as a finger or stylus. When the terminal device is a non-touchscreen terminal device such as a desktop computer or laptop, the user can operate using external devices such as a mouse or keyboard. In this application embodiment, a graphical user interface is provided through the terminal device.

[0029] The technical solution of this application will be described in detail below through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0030] Based on the above-described scenarios, this application provides a method for modeling virtual plants. The method for modeling virtual plants will be described in detail below: Please see Figure 2 The virtual plant modeling method provided in this application embodiment is implemented by steps 011, 012, 013 and 014, which are described in detail below.

[0031] Step 011: In response to the first input operation, obtain the plant name of the virtual plant to be generated; The first input operation refers to the operation of inputting information through an input device. For example, the input information is the name of a plant.

[0032] Optionally, the first input operation can be that the user manually enters the plant name in the graphical user interface, or manually selects the plant name, or the user enters the plant name by voice, or the user uploads a file containing the plant names of the virtual plants to be modeled in batches, and the plant names are obtained after the file is read, etc., which are not limited here.

[0033] Optionally, the plant name should include at least the plant type, and may also include at least one of the following: plant growing region, plant growing season, and plant age. Thus, by adding attributes such as plant growing region, plant growing season, and / or plant age to the plant type, the plant name to be modeled can be determined more precisely, reducing the bias in subsequent query matching, significantly improving modeling efficiency and diversity, and helping to obtain diverse virtual plant assets to meet the needs of complex virtual scenes.

[0034] Step 012: Determine the vegetation morphology parameters that match the plant name in the preset botanical knowledge base. The vegetation morphology parameters are used to characterize the three-dimensional morphological features of the virtual plant. The preset botanical knowledge base is a structured database that integrates the morphological characteristics and quantitative parameters of various plants. The preset botanical knowledge base stores accurate vegetation morphological parameters of various plants, and includes at least one set of vegetation morphological parameters, including the vegetation morphological parameters matching the plant name (of the virtual plant to be generated).

[0035] Among them, vegetation morphology parameters are a set of quantitative indicators that describe the external morphology and structural characteristics of plants. Optionally, vegetation morphology parameters include tree shape parameters, branch parameters, and leaf parameters; tree shape parameters are used to describe the overall outline and spatial morphology of plants, branch parameters are used to describe the structural characteristics of the trunk and branches, and leaf parameters are used to describe the morphology and arrangement of leaves.

[0036] Optionally, vegetation morphology parameters also include flower and fruit parameters and root parameters. Flower and fruit parameters are used to describe the appearance and distribution of flowers and fruits, while root parameters are used to describe the root structure and distribution of plants.

[0037] Among them, three-dimensional morphological features are the three-dimensional attributes that determine the spatial geometry and structural arrangement of virtual plants.

[0038] Specifically, by identifying the plant name of the virtual plant, the core attributes (such as type, growth region, etc.) in the plant name are extracted; for example, the core attributes of a mature North American cedar include North America, mature, and cedar; based on the extracted core attributes, the corresponding matching entries are retrieved in the preset botanical knowledge base, and the vegetation morphology parameters corresponding to the entries are obtained as the vegetation morphology parameters of the virtual plant to be modeled, providing accurate data support for the subsequent modeling process.

[0039] In this way, by matching plant names based on a pre-set botanical knowledge base, there is no need for manual consultation of botanical data, which can significantly reduce the modeling threshold of virtual plants, while ensuring the standardization and accuracy of vegetation morphology parameters, avoiding subjective biases set by humans, and effectively improving modeling efficiency.

[0040] Optionally, if there are multiple sets of vegetation morphology parameters that match the plant name, for example, if the plant name is North American cedar and there are 3 sets of corresponding entries in the preset botanical knowledge base (corresponding to juvenile, adult, and old age respectively), the set of vegetation morphology parameters that is ranked first in the preset order will be automatically selected as the required vegetation morphology parameters, or the set of vegetation morphology parameters selected by the user will be determined as the required vegetation morphology parameters in response to the user's operation.

[0041] Optionally, please refer to Figure 3 Step 012 includes either step 0121 or step 0122, as detailed below.

[0042] Step 0121: Search the plant knowledge base for vegetation morphology parameters that match the plant name; or, Step 0122: In response to the third input operation, obtain the vegetation morphology information of the virtual plant to be generated, and query the vegetation morphology parameters that match the vegetation morphology information in the botany knowledge base.

[0043] Among them, vegetation morphology information refers to the desired appearance and structural features of the virtual plant to be generated. The third input operation is the user interaction behavior that obtains the vegetation morphology information of the virtual plant to be generated.

[0044] Specifically, using plant names as search criteria, matching vegetation morphology parameters are directly filtered from a pre-set botanical knowledge base. The basic principle is similar to step 012, and will not be repeated here. Alternatively, through a third input operation, the desired vegetation morphology information of the virtual plant to be generated (such as umbrella-shaped crown, needle-shaped leaves) can be directly input or selected. Using the desired vegetation morphology information as search criteria, matching vegetation morphology parameters are filtered from a pre-set botanical knowledge base, providing data support for the personalized virtual plant modeling process.

[0045] Optionally, a morphology selection interface is displayed on the graphical user interface. The morphology selection interface includes at least one selection box, and each selection box corresponds to different types of vegetation morphology information (such as tree morphology features, branch structure features, leaf morphology features, etc.). Through a third input operation, at least one selection box can be triggered to select the desired vegetation morphology information in at least one selection box. Then, all vegetation morphology information is combined to form the vegetation morphology information of the virtual plant to be generated, and the vegetation morphology parameters that match the vegetation morphology information are queried in the botanical knowledge base.

[0046] In this way, by matching plant names, the production threshold can be lowered and the modeling efficiency can be improved; by matching custom vegetation morphology information, the limitations of plant name matching can be overcome, the modeling needs of non-standard and personalized virtual plants can be met, the flexibility and accuracy of virtual plant modeling can be improved, and the construction of diverse virtual scenes can be supported.

[0047] Step 013: Determine the values ​​of each vegetation morphology parameter and perform parameter mapping on each vegetation morphology parameter to generate an initial model file. The initial model file contains the initial model parameters for generating a 3D model of virtual plants. Parameter mapping is the process of establishing a correspondence between vegetation morphology parameters and the parameter interfaces of relevant modules in modeling software (such as SpeedTreee); initial model parameters are the basic quantitative configuration data that supports the generation of three-dimensional models of virtual plants.

[0048] Specifically, the process begins by combining the correctly standardized and / or ranged parameters from a pre-defined botanical knowledge base to determine the specific values ​​for each vegetation morphology parameter (e.g., the height parameter of an adult cedar tree is within the range of 25-35 meters, and can be randomly selected, determined by pre-defined rules, or user-defined). Then, these vegetation morphology parameter values ​​are precisely mapped to the corresponding parameter interfaces of the modeling software (e.g., height corresponds to the tree shape), resulting in the initial model parameters. Finally, these parameters are integrated to generate an initial model file containing all the initial model data.

[0049] Thus, by clearly defining the values ​​of vegetation morphology parameters and accurately mapping them, it is possible to ensure that the initial model parameters conform to botanical characteristics and modeling specifications, avoiding morphological distortion caused by chaotic vegetation morphology parameters. Simultaneously, the automated conversion of vegetation morphology parameters to the initial model file significantly reduces the workload of manual parameter adjustments, effectively improving modeling efficiency.

[0050] In one alternative embodiment, please refer to Figure 3 Step 013 includes: Step 0131: Randomly determine any value within the preset range corresponding to each vegetation morphology parameter, which will be the value of each vegetation morphology parameter.

[0051] The preset value range is obtained from a preset botanical knowledge base and is a numerical range that conforms to botanical laws.

[0052] Specifically, while determining the vegetation morphology parameters that match the plant name in a preset botanical knowledge base, the preset value range for each vegetation morphology parameter is obtained. A value is then randomly selected from the preset value range for each vegetation morphology parameter as its value.

[0053] In this way, while ensuring that the values ​​of vegetation morphology parameters are reasonable, the problem of homogenization of model morphology caused by single parameter values ​​can be avoided, giving virtual plants natural individual differences and enhancing the realism of virtual scenes.

[0054] In one alternative embodiment, please refer to Figure 4 Step 013 includes: Step 0132: Display the configuration interface, which includes various vegetation morphology parameters matching the plant name; Step 0133: In response to the second input operation, update the values ​​of each vegetation morphology parameter.

[0055] The configuration interface displays vegetation morphology parameters matching plant names, allowing users to view and adjust parameter values. The second input operation is the user's interactive behavior of modifying the values ​​of vegetation morphology parameters within the configuration interface.

[0056] Specifically, after determining the vegetation morphology parameters that match the plant name in the preset botanical knowledge base, a configuration interface can be displayed on the graphical user interface, showing all vegetation morphology parameters that match the plant name and their current values. The values ​​of the vegetation morphology parameters are adjusted in response to the user's second input operation, and the values ​​of each vegetation morphology parameter are updated in a timely manner, replacing the original purely random assignment.

[0057] For example, please see Figure 5 The vegetation morphology parameters include tree shape parameters, branch parameters, and leaf parameters. The configuration interface consists of four parts: tree shape parameter area, branch parameter area, leaf parameter area, and preview view area. The tree shape parameter area displays and adjusts the values ​​of the parameters belonging to the tree shape; the branch parameter area displays and adjusts the values ​​of the parameters belonging to the branch; the leaf parameter area displays and adjusts the values ​​of the parameters belonging to the leaf; and the preview view area displays the corresponding 3D model that can be generated for these vegetation morphology parameters in real time, allowing users to observe and adjust the values ​​of each vegetation morphology parameter accordingly.

[0058] Thus, by providing a configuration interface, users can customize the values ​​of various vegetation morphology parameters, which can balance the need for randomness and human intervention, improve the controllability of virtual plant modeling morphology, and meet personalized modeling needs.

[0059] In one alternative embodiment, please refer to Figure 3 Step 013 includes: Step 0134: Perform parameter mapping on the tree parameters to determine the first model parameters, which are used to define the contour curves and volume distribution of the 3D model; Step 0135: Perform parameter mapping on the branch parameters to determine the second model parameters. The second model parameters are used to define the branch generation rules of the 3D model. Step 0136: Perform parameter mapping on the blade parameters to determine the third model parameters. The third model parameters are used to define the blade attachment rules of the three-dimensional model.

[0060] Among them, vegetation morphology parameters include tree shape parameters, branch and trunk parameters, and leaf parameters, and initial model parameters include first model parameters, second model parameters, and third model parameters.

[0061] Specifically, the visual appearance of virtual plants generally includes tree shape, branches, and leaves, corresponding to three types of vegetation morphology parameters: tree shape parameters, branch parameters, and leaf parameters. Tree shape parameters describe the overall outline and spatial form of the plant, corresponding to the contour curves and volume distribution of the virtual plant's 3D model. Therefore, tree shape parameters are mapped to the first model parameters. Branch parameters describe the structural features of the trunk and branches, corresponding to the branch generation rules of the virtual plant's 3D model. Therefore, branch parameters are mapped to the second model parameters. Leaf parameters describe the leaf morphology and arrangement, corresponding to the leaf attachment rules of the virtual plant's 3D model. Therefore, leaf parameters are mapped to the third model parameters.

[0062] For example, tree shape parameters, branch parameters, and leaf parameters are mapped separately to a pre-defined modular component library to achieve parameter mapping. The pre-defined modular component library includes a tree shape module, a branch generation module, and a leaf attachment module. The tree shape module defines the overall outline curve and volume distribution of the plant. Importing the tree shape parameters into the tree shape module in the modular component library yields accurate outline curves and volume distributions, thus obtaining precise first model parameters. The branch generation module pre-defines the plant's whorled rhythm, branch radial extension curves, and secondary branch generation rules. Importing the branch generation parameters into the branch generation module yields accurate branch generation rules, thus obtaining precise second model parameters. The leaf attachment module defines how plant leaves grow in clusters at short branch points and controls the size and direction of the clusters. Importing the leaf parameters into the leaf attachment module yields accurate leaf attachment rules, thus obtaining precise third model parameters.

[0063] In this way, by mapping the three types of vegetation morphology parameters—tree shape parameters, branch parameters, and leaf parameters—we can achieve a precise correspondence between vegetation morphology parameters and model parameters, avoid confusion between vegetation morphology parameters of different dimensions, and thus ensure that the model parameters of each dimension conform to botanical laws, thereby improving the modeling accuracy of virtual plants.

[0064] In one alternative embodiment, please refer to Figure 4 Step 0134 includes step 01341, step 0135 includes step 01351, and step 0136 includes step 01361. The details are explained below.

[0065] Step 01341: Use shape, height, and crown width as constraint parameters for generating a 3D model to determine the first model parameters; The tree-like parameters include shape, height, and crown width. Constraint parameters are quantitative feature parameters used to limit the range of values ​​for model parameters and ensure the reasonable modeling morphology of the virtual plant.

[0066] Specifically, for the tree dimension, the core constraint parameters are shape, height, and crown width among the tree parameters. Shape (such as oval, conical, umbrella, etc.) directly constrains the type of contour curve, while height and crown width are quantitative indicators that constrain volume distribution. The ratio of height to crown width (i.e., crown-to-height ratio) constrains the steepness or gentleness of the contour curve, thereby determining the first model parameters and avoiding tree shape distortion.

[0067] Step 01351: Use branching method, number of branches, trunk-to-branch angle and bark texture as constraint parameters to generate a 3D model, and determine the parameters of the second model; Among them, the branch parameters include branching pattern, number of branches, trunk-to-branch angle, and bark texture.

[0068] Specifically, for the branch dimension, core constraint parameters include branching pattern, number of branches, trunk-to-branch angle, and bark texture. These parameters work together to constrain the branch generation rules. For example, branching pattern (such as opposite, alternate, and whorled) directly constrains the arrangement logic of branches; the number of branches limits the total number of branches at each level; the trunk-to-branch angle constrains the angle of branch extension; and bark texture (such as shallow fissures, deep longitudinal fissures, and smooth flaking) limits the detailed attributes of the branch surface, thereby determining the second model parameters. In this way, the growth position, morphology, and surface features of branches in the 3D model can be accurately determined, improving the accuracy of modeling.

[0069] Step 01361: Use leaf-shaped mesh, leaf length, leaf color, and cluster density as constraint parameters to generate the 3D model, and determine the parameters of the third model.

[0070] The leaf parameters include leaf shape grid, leaf length, leaf color, and cluster density.

[0071] Specifically, for the leaf dimension, constraint parameters centered on leaf shape mesh, length, color, and cluster density work together to constrain leaf attachment rules. For example, leaf shape mesh (such as ovate, palmate, and needle-shaped) limits the geometric template of the leaf; leaf length constrains the size range of the leaf; leaf color (such as green, yellow, and red) constrains the visual attributes of the leaf; and cluster density constrains the number and spacing of leaf clusters on short branches, thus determining the third model parameters. In this way, the final output third model parameters can accurately guide the generation and attachment of leaves in the 3D model, improving the accuracy of virtual plant modeling.

[0072] In this way, by setting specific constraint parameters in different dimensions, the core features of tree shape, branches, and leaves can be precisely defined, avoiding subjective biases in parameter mapping, ensuring that the model parameters in each dimension conform to botanical laws, and improving the accuracy and standardization of virtual plant modeling.

[0073] Optionally, tree shape parameters may also include trunk straightness (i.e., whether the trunk is bent and the degree of bending), branch parameters may also include bark color, branch thickness ratio (i.e., the ratio of the diameter of the main branch to the secondary branch), and leaf parameters may also include leaf margin (e.g., entire, serrated, wavy, etc.), leaf thickness, etc., and the constraint parameters of the three-dimensional model are regenerated respectively to redetermine the first model parameters, second model parameters, and third model parameters. This embodiment of the application does not limit the scope of the application.

[0074] Step 014: Generate a 3D model of the virtual plant based on the initial model file.

[0075] Specifically, the initial model file containing the first model parameters, the second model parameters, and the third model parameters is read. These model parameters are then substituted into the corresponding modules of the corresponding generation software (such as the generation modules corresponding to tree shape, branches, and leaves). According to the contour curves, volume distribution, branch generation rules, and leaf attachment rules defined by these model parameters, a three-dimensional model of a visualized virtual plant is rendered.

[0076] In this way, the automatic generation of plant names, vegetation morphology parameters, and 3D models can be achieved, replacing manual modeling and greatly improving the modeling efficiency of virtual plants. Moreover, while ensuring that the virtual plant morphology conforms to botanical characteristics, it can take into account both diversity and consistency.

[0077] In one alternative embodiment, please refer to Figure 3 Step 014 includes: Step 0141: Perform parameter transformation on each initial model parameter of the initial model file to generate the target model file, which includes the target model parameters for generating the 3D model of the virtual plant; Step 0142: Input the target model file into the preset plant generation program to generate a 3D model. The parameters of the target model are matched with those of the plant generation program.

[0078] Parameter conversion refers to transforming parameters from one format to another that is compatible with the plant generation program. The target model parameters are standardized parameters compatible with the plant generation program and can directly drive the generation of 3D models. The plant generation program is a computer program with virtual plant modeling capabilities that can read parameters to generate 3D models; for example, the SpeedTree software.

[0079] Specifically, the initial model parameters are converted in format and value range to match the parameter interface of the plant generation program, and corresponding control instructions matching the plant generation program are generated and integrated into a target model file, such as a Python script (.py) or a modified SpeedTree project file (.spm). The target model file is then input into the preset plant generation program. The plant generation program reads the compatible target model parameters and, based on the contour curves, volume distribution, branch generation rules, and leaf attachment rules defined by the target model parameters, automatically generates a visualized 3D model of a virtual plant.

[0080] In this way, by converting parameters to adapt the model parameters to the plant generation program, the problem of parameter incompatibility when crossing software is avoided. The generated target model file is input into the plant generation program to directly complete the modeling, which can improve the universality and stability of the modeling process, reduce the modeling threshold, and improve modeling efficiency.

[0081] In one alternative embodiment, please continue to refer to Figure 3 Before generating the initial model file by mapping parameters for each vegetation morphology parameter, the virtual plant modeling method also includes steps 015 and 016, which are explained in detail below.

[0082] Step 015: Perform morphological conflict detection based on each vegetation morphological parameter to identify the target morphological parameter with morphological conflict among the various vegetation morphological parameters. Step 016: Adjust the values ​​of the target shape parameters to eliminate shape conflicts.

[0083] Among them, morphological conflict detection is the process of verifying the logical relationship between various vegetation morphological parameters and identifying contradictions in parameter values ​​that violate the laws of plant growth.

[0084] Specifically, based on botanical growth patterns, the matching between parameters such as tree shape, branches, and leaves is examined to identify conflicting target morphological parameters. For the detected target morphological parameters, their values ​​are adjusted manually or automatically to eliminate logical contradictions between various vegetation morphological parameters and ensure conformity with plant growth characteristics.

[0085] For example, if the tree shape parameters include the parameter described as "weeping willow" and the branch parameters include the parameter described as "growing upwards obliquely", since the tree shape is "weeping willow", the corresponding branches should be slender and naturally drooping. This creates a shape conflict with the parameters in the branch parameters. Therefore, the target shape parameters are the parameters described as "weeping willow" in the tree shape parameters and the parameter described as "growing upwards obliquely" in the branch parameters. At least one of them needs to be adjusted to eliminate the shape conflict.

[0086] Thus, by detecting morphological conflicts, the cost of manual investigation can be reduced, and the generation of 3D models that violate botanical laws can be avoided due to contradictions in the values ​​of vegetation morphological parameters, thereby improving the morphological rationality and realism of the model.

[0087] In one alternative embodiment, please refer to Figure 4 Before mapping the parameters of each vegetation morphology to generate the initial model file, the virtual plant modeling method also includes steps 017 and 018, which are explained in detail below.

[0088] Step 017: Based on the preset value range corresponding to each vegetation morphology parameter, perform numerical verification on each vegetation morphology parameter to determine abnormal morphology parameters. Step 018: Adjust the values ​​of the abnormal morphology parameters so that the values ​​of the abnormal morphology parameters are within the corresponding preset value range.

[0089] Numerical verification is a process of checking whether the values ​​of vegetation morphology parameters are reasonable. Abnormal morphological parameters are those that exceed the corresponding preset value range and do not conform to the conventional standards for vegetation morphology.

[0090] Specifically, the values ​​of the corresponding vegetation morphology parameters are checked one by one according to the preset value range. If there are abnormal morphology parameters, the abnormal morphology parameters that are out of range are found and marked. Then, the values ​​of the abnormal morphology parameters are adjusted to correct the values ​​to the corresponding preset value range, thereby ensuring that each vegetation morphology parameter conforms to the correct vegetation morphology specifications.

[0091] In this way, by performing numerical verification before parameter mapping, abnormal morphological parameters can be detected and eliminated in advance, avoiding morphological distortion in virtual plant modeling, reducing modeling rework caused by parameter problems, and improving modeling efficiency.

[0092] All of the above technical solutions can be combined in any way to form optional embodiments of this application, and will not be described in detail here.

[0093] Based on the method described in the above embodiments, this application also provides a virtual plant modeling apparatus for performing the steps in the above virtual plant modeling method. Please refer to... Figure 6 , Figure 6 This is a schematic diagram of the modules of the virtual plant modeling device 200 provided in this application embodiment. The virtual plant modeling device 200 includes: The acquisition module 201 is used to acquire the plant name of the virtual plant to be generated in response to the first input operation; The determination module 202 is used to determine the vegetation morphology parameters that match the plant name in the preset botanical knowledge base. The vegetation morphology parameters are used to characterize the three-dimensional morphological features of the virtual plant. The mapping module 203 is used to determine the values ​​of each vegetation morphology parameter and perform parameter mapping on each vegetation morphology parameter to generate an initial model file. The initial model file contains the initial model parameters for generating a three-dimensional model of virtual plants. The generation module 204 is used to generate a three-dimensional model of the virtual plant based on the initial model file.

[0094] It should be noted that the specific details of each module unit in the above-mentioned virtual plant modeling device have been described in detail in the embodiments of the above-mentioned virtual plant modeling method, and will not be repeated here.

[0095] In the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0096] In one optional embodiment, the virtual plant modeling device in this application embodiment can be implemented in hardware, such as an electronic device or a component in an electronic device, such as an integrated circuit or a chip; the virtual plant modeling device can also be implemented in software, such as as an application installed in an electronic device.

[0097] This application also provides an electronic device, including a processor and a memory; the memory stores a computer program, and the processor executes various processes of the above-described virtual plant modeling method by calling the computer program stored in the memory, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0098] Optionally, the electronic device includes a display screen. The display screen can be used to display a graphical user interface (GUI) and receive operation commands generated by the user interacting with the GUI. The display screen may include a display panel and a touch panel. The display panel can be used to display information input by the user or information provided to the user, as well as various GUIs of the electronic device, which can be composed of graphics, text, icons, video, and any combination thereof. The touch panel can be used to collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel), generate corresponding operation commands, and execute the corresponding program according to the operation commands.

[0099] Optionally, the touch panel may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch location and the signal generated by the touch operation, transmitting the signal to the touch controller. The touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to the processor, and can receive and execute commands from the processor. The touch panel may cover the display panel. When the touch panel detects a touch operation on or near it, it transmits the information to the processor to determine the type of touch event. Subsequently, the processor provides corresponding visual output on the display panel based on the type of touch event. In this embodiment, the touch panel and display panel can be integrated into the display screen to achieve input and output functions. However, in some embodiments, the touch panel and display panel can be implemented as two independent components to achieve input and output functions.

[0100] In one alternative embodiment, please refer to Figure 7 , Figure 7 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. The electronic device 300 includes a processor 301 and a memory 302. The memory 302 stores a computer program 303 that can run on the processor 301. When the computer program 303 is executed by the processor 301, it implements the various processes of the embodiments of the above-described virtual plant modeling method and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0101] Please see Figure 8 , Figure 8 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. The electronic device can be a terminal or a server. Exemplarily, the electronic device 400 includes a central processing unit (CPU) 401, a system memory 404 including random access memory (RAM) 402 and read-only memory (ROM) 403, and a system bus 405 connecting the system memory 404 and the central processing unit 401.

[0102] In some embodiments, the electronic device 400 may also include a basic input / output system 406 that helps transmit information between various devices within the computer, and a mass storage device 407 for storing the operating system 413, the client 414, and other program modules 415.

[0103] In some embodiments, the basic input / output system 406 includes a display 408 for displaying information and an input device 409 for user input, such as a touch panel and other input devices. A touch panel is also called a touchscreen. A touch panel may include both a touch device and a touch controller. Other input devices may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, and joysticks, which will not be described further here.

[0104] Both the display 408 and the input device 409 are connected to the central processing unit 401 via an input / output controller 410 connected to the system bus 405. The basic input / output system 406 may also include the input / output controller 410 for receiving and processing input from touch panels, other input devices, etc. Optionally, the input / output system 406 may also include output devices, such as displays, printers, or other types of output devices.

[0105] Mass storage device 407 is connected to central processing unit 401 via a mass storage controller (not shown) connected to system bus 405. Mass storage device 407 and its associated computer-readable media provide non-volatile storage for electronic device 400. That is, mass storage device 407 may include computer-readable media (not shown) such as hard disk or compact disc read-only memory (CD-ROM) drive.

[0106] According to various embodiments of this application, the electronic device 400 can also be connected to a remote computer on a network, such as the Internet. That is, the electronic device 400 can be connected to a network 417 via a network interface unit 416 connected to a system bus 405, or the network interface unit 416 can be used to connect to other types of networks or remote computer systems (not shown).

[0107] This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described virtual plant modeling method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here.

[0108] The processor can be the processor in the electronic device described in the above embodiments. The computer-readable storage medium can be a computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, etc.

[0109] Computer-readable media can include computer storage media and communication media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented by any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include RAM, ROM, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other solid-state storage technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape cassettes, magnetic tape, disk storage, or other magnetic storage devices. Of course, those skilled in the art will recognize that computer storage media are not limited to the above-mentioned types.

[0110] This application also provides a computer program product, including computer instructions that, when executed by a processor, implement the aforementioned virtual plant modeling method. The processor may be a processor in the electronic device described in the above embodiments. When executed by the processor, the computer instructions implement various processes of the embodiments of the aforementioned virtual plant modeling method and achieve the same technical effects; therefore, to avoid repetition, they will not be described again here.

[0111] It is understood that in the specific implementation of this application, data related to user identity or characteristics 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 related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0112] In the description of this specification, the references to terms such as "certain embodiments," "an alternative embodiment," and "exemplarily" indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0113] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order according to the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0114] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for modeling virtual plants, characterized in that, include: In response to the first input operation, obtain the plant name of the virtual plant to be generated; Determine the vegetation morphology parameters that match the plant name in a preset botanical knowledge base, wherein the vegetation morphology parameters are used to characterize the three-dimensional morphological features of the virtual plant, and the preset botanical knowledge base includes at least one set of vegetation morphology parameters, including the vegetation morphology parameters that match the plant name. The values ​​of each of the vegetation morphology parameters are determined, and parameter mapping is performed on each of the vegetation morphology parameters to generate an initial model file, which contains the initial model parameters for generating the three-dimensional model of the virtual plant. A three-dimensional model of the virtual plant is generated based on the initial model file.

2. The virtual plant modeling method according to claim 1, characterized in that, Determining the values ​​of each of the vegetation morphology parameters includes: Randomly determine any value within a preset range corresponding to each of the vegetation morphology parameters, which will be the values ​​of each of the vegetation morphology parameters.

3. The virtual plant modeling method according to claim 1, characterized in that, Determining the values ​​of each of the vegetation morphology parameters includes: The configuration interface is displayed, which includes various vegetation morphology parameters that match the plant name; In response to the second input operation, the values ​​of each of the vegetation morphology parameters are updated.

4. The method for modeling virtual plants according to any one of claims 1, characterized in that, The step of determining the vegetation morphology parameters that match the plant name in a preset botanical knowledge base includes: Search the plant knowledge base for vegetation morphology parameters that match the plant name; or, In response to the third input operation, the vegetation morphology information of the virtual plant to be generated is obtained, and the vegetation morphology parameters matching the vegetation morphology information are queried in the botanical knowledge base.

5. The virtual plant modeling method according to claim 1, characterized in that, The vegetation morphology parameters include tree shape parameters, branch parameters, and leaf parameters. The initial model parameters include first model parameters, second model parameters, and third model parameters. The step of mapping each of the vegetation morphology parameters to generate an initial model file includes: The tree parameters are mapped to determine the first model parameters, which are used to define the contour curves and volume distribution of the three-dimensional model. The branch parameters are mapped to determine the second model parameters, which are used to define the branch generation rules of the three-dimensional model. The blade parameters are mapped to determine the third model parameters, which are used to define the blade attachment rules of the three-dimensional model.

6. The virtual plant modeling method according to claim 5, characterized in that, The tree parameters include shape, height, and crown width. The step of mapping the tree parameters to determine the first model parameters includes: The shape, height, and crown width are used as constraint parameters for generating the three-dimensional model to determine the parameters of the first model; The branch parameters include branching pattern, number of branches, trunk-to-branch angle, and bark texture. The step of mapping the branch parameters to determine the second model parameters includes: The branching pattern, number of branches, trunk-to-branch angle, and bark texture are used as constraint parameters for generating the three-dimensional model to determine the parameters of the second model. The leaf parameters include leaf shape grid, leaf length, leaf color, and cluster density. The parameter mapping of these leaf parameters to determine the third model parameters includes: The leaf-shaped mesh, length, color, and cluster density are used as constraint parameters for generating the three-dimensional model to determine the parameters of the third model.

7. The method for modeling virtual plants according to any one of claims 1-6, characterized in that, Before performing parameter mapping on each of the vegetation morphology parameters to generate an initial model file, the method further includes: Based on the various vegetation morphology parameters, morphological conflict detection is performed to identify the target morphological parameter with morphological conflict among the various vegetation morphology parameters. Adjust the values ​​of the target morphological parameters to eliminate the morphological conflict.

8. The method for modeling virtual plants according to any one of claims 1-6, characterized in that, Before performing parameter mapping on each of the vegetation morphology parameters to generate an initial model file, the method further includes: Based on the preset value range corresponding to each of the vegetation morphology parameters, numerical verification is performed on each of the vegetation morphology parameters to determine abnormal morphology parameters. Adjust the value of the abnormal morphology parameter so that the value of the abnormal morphology parameter is within the corresponding preset value range.

9. The virtual plant modeling method according to claim 1, characterized in that, The process of generating a three-dimensional model of the virtual plant based on the initial model file includes: The parameters of each initial model in the initial model file are transformed to generate a target model file, which includes the target model parameters for generating the three-dimensional model of the virtual plant. The target model file is input into a preset plant generation program to generate the three-dimensional model, wherein the parameters of the target model are matched with the plant generation program.

10. The virtual plant modeling method according to claim 1, characterized in that, The plant name includes at least the plant type, and also includes at least one of the following: plant growing region, plant growing season, and plant age.

11. A virtual plant modeling device, characterized in that, include: The acquisition module is used to acquire the plant name of the virtual plant to be generated in response to the first input operation; The determination module is used to determine the vegetation morphology parameters that match the plant name in a preset botanical knowledge base. The vegetation morphology parameters are used to characterize the three-dimensional morphological features of the virtual plant. The preset botanical knowledge base includes at least one set of vegetation morphology parameters, including the vegetation morphology parameters that match the plant name. The mapping module is used to determine the values ​​of each of the vegetation morphology parameters and perform parameter mapping on each of the vegetation morphology parameters to generate an initial model file, wherein the initial model file contains the initial model parameters for generating the three-dimensional model of the virtual plant. The generation module is used to generate a three-dimensional model of the virtual plant based on the initial model file.

12. An electronic device, characterized in that, It includes a processor and a memory; the memory stores a computer program, and the processor executes the virtual plant modeling method as described in any one of claims 1-10 by calling the computer program stored in the memory.

13. A computer-readable storage medium, characterized in that, The device contains a computer program that, when executed by a processor, implements the modeling method for virtual plants as described in any one of claims 1-10.

14. A computer program product, characterized in that, It includes computer instructions that, when executed by a processor, implement the modeling method for virtual plants as described in any one of claims 1-10.

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