3D model picture automatic generation method and device, electronic equipment and storage medium
By using automated 3D model rendering and image uploading technology, the problem of cumbersome and error-prone image acquisition in the parts resource library has been solved, improving the quality of the resource library and user experience, and reducing the company's operating costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- 粤港澳大湾区(广东)国创中心
- Filing Date
- 2024-10-14
- Publication Date
- 2026-05-29
AI Technical Summary
The existing parts resource library has problems with uploading product images, which is cumbersome and error-prone. Especially when real product images are hard to obtain, unrendered 3D model images lack realism, and rendering with 3D modeling software is costly, resulting in poor user experience and low efficiency.
Through automated 3D model rendering technology, the system uses a pre-set library of materials and surface treatment resources to render the 3D model to be processed, generating realistic rendered images. The system also simplifies the image acquisition process by automatically capturing and uploading the images.
It improves the display quality and user experience of 3D models in the resource library, reduces the company's operating costs and human resource investment, and ensures the accuracy and efficiency of image uploading.
Smart Images
Figure CN119444950B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of 3D model technology, and in particular to a method, apparatus, device and storage medium for automatically generating 3D model images. Background Technology
[0002] Currently, with the rapid development of industrial software and data, 3D component resource libraries have become an important tool for enterprises to showcase their products. However, existing resource libraries have significant shortcomings in terms of uploading product images. Enterprises need to manually find, download, or screenshot real product images of components and manually upload them to the resource library. This process is cumbersome, error-prone, and degrades the user experience. Furthermore, when real product images are difficult to obtain, uploading unrendered 3D model images fails to provide a sufficient sensory experience, while rendering with 3D modeling software further increases labor and time costs. Therefore, existing technologies still need improvement in the construction of component resource libraries. Summary of the Invention
[0003] The main objective of this application is to propose a method, apparatus, electronic device, and storage medium for automatically generating 3D model images. The aim is to quickly and accurately add realistic materials, colors, and surface treatment effects to complex 3D models through automatic rendering technology of 3D models of parts. The operation is simple and the rendering effect is realistic.
[0004] To achieve the above objectives, a first aspect of this application proposes a method for automatically generating 3D model images, the method comprising:
[0005] The platform's 3D model images are detected. If a 3D model image is missing at a specified location on the platform, the corresponding 3D model to be processed at the specified location is obtained.
[0006] Using a preset material resource library and surface treatment resource library, the 3D model to be processed is rendered to obtain a rendered 3D model;
[0007] Extract an image of the rendered 3D model to obtain a rendered image of the 3D model;
[0008] The rendered image is uploaded to the designated location on the platform.
[0009] In some embodiments, the step of uploading the rendered image to a designated location on the platform specifically includes:
[0010] The rendered image is named according to the name of the 3D model to obtain a named rendered image;
[0011] Obtain the storage path corresponding to the specified location on the platform;
[0012] The named rendered image is uploaded to the designated location on the platform according to the storage path.
[0013] In some embodiments, the step of rendering the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model specifically includes:
[0014] The 3D model to be processed is opened using 3D modeling software to obtain the component categories and component attributes of the 3D model to be processed.
[0015] Based on the component category and the component attributes, obtain the rendering parameters of the 3D model to be processed;
[0016] Based on the rendering parameters, the 3D model to be processed is rendered using a preset material resource library and surface treatment resource library to obtain a rendered 3D model.
[0017] In some embodiments, the step of capturing an image of the rendered 3D model to obtain a rendered image of the 3D model specifically includes:
[0018] Obtain the component categories and component attributes of the 3D model to be processed;
[0019] Obtain the screenshot angle of the 3D model to be processed based on the component category;
[0020] The screenshot scale and screenshot size of the 3D model to be processed are obtained based on the attributes of the components.
[0021] Based on the screenshot angle, screenshot ratio, and screenshot size, an image of the rendered 3D model is captured to obtain the rendered image of the 3D model.
[0022] In some embodiments, the step of rendering the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model specifically includes:
[0023] Obtain the custom rendering parameters of the 3D model;
[0024] Based on the custom rendering parameters, the 3D model to be processed is rendered using a preset material resource library and surface treatment resource library to obtain a rendered 3D model.
[0025] In some embodiments, the step of rendering the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model specifically includes:
[0026] Obtain several 3D models to be processed, and distribute the 3D models to be processed to several sub-servers;
[0027] Obtain several rendered 3D models uploaded by the sub-server;
[0028] The sub-server is used to render the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model.
[0029] In some embodiments, after the step of detecting the 3D model image of the platform and obtaining the corresponding 3D model to be processed if a 3D model image is missing at a specified location on the platform, the method further includes:
[0030] The 3D model to be processed is converted into STP format.
[0031] To achieve the above objectives, a second aspect of this application provides an automatic 3D model image generation device, the device comprising:
[0032] The image detection module is used to detect 3D model images on the platform. If a 3D model image is missing at a specified location on the platform, the corresponding 3D model to be processed at the specified location is obtained.
[0033] The model rendering module is used to render the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model.
[0034] The image capture module is used to capture images of the rendered 3D model to obtain the rendered image of the 3D model.
[0035] The image upload module is used to upload the rendered image to a designated location on the platform.
[0036] To achieve the above objectives, a third aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method for automatically generating 3D model images.
[0037] To achieve the above objectives, a fourth aspect of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for automatically generating 3D model images.
[0038] This application proposes a method, apparatus, device, and storage medium for automatically generating 3D model images. The method renders a 3D model lacking a 3D model image, captures an image of the rendered 3D model, and uploads the image to a designated location of the missing image. By automatically rendering and capturing 3D models, the operation steps for obtaining product images are greatly simplified, saving enterprises significant time and labor costs. Attached Figure Description
[0039] Figure 1 This is a flowchart of the automatic generation method for 3D model images provided in the embodiments of this application;
[0040] Figure 2 yes Figure 1 The flowchart of step S104 in the process;
[0041] Figure 3 yes Figure 1 The flowchart of step S102 in the document;
[0042] Figure 4 yes Figure 1 The flowchart of step S103 in the process;
[0043] Figure 5 This is a schematic diagram of the structure of the 3D model image automatic generation device provided in the embodiments of this application;
[0044] Figure 6 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation
[0045] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0046] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.
[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.
[0048] First, let's analyze some of the terms used in this application:
[0049] 3D models, also known as three-dimensional models, are models with three-dimensional data constructed using 3D software in a virtual three-dimensional space. They are commonly used in fields such as 3D printing, computer graphics, film, television, video games, and virtual reality. These models define the shape, size, position, and surface properties of objects in a three-dimensional coordinate system through a series of geometric elements such as points, lines, and surfaces. 3D models can represent real-world objects or scenes in great detail, including their shape, texture, color, lighting effects, etc. They can be created using various 3D modeling software, such as Blender, 3ds Max, Maya, Cinema 4D, and SketchUp. The process of creating a 3D model typically involves steps such as design, modeling, texture mapping, lighting, and rendering.
[0050] Rendering: Rendering 3D models is a crucial part of computer graphics, involving the transformation of 3D models into realistic 2D images. The basic principle of rendering is to simulate the propagation and reflection of light in 3D space. Based on the surface properties of the 3D model (such as material, color, and texture) and light source factors (position, direction, and intensity), the color and brightness values of each pixel at different locations are calculated, thereby generating a 2D image. This process involves complex physical and mathematical calculations to ensure that the generated image has a high degree of realism and fidelity.
[0051] The importance of industrial software and industrial data is increasingly prominent. As the cornerstone of intelligent manufacturing, they are driving the manufacturing industry towards greater efficiency and intelligence. Against this backdrop, the construction of 3D component resource libraries has become a key measure for enterprises to improve the efficiency of product design, manufacturing, and supply chain management. These libraries not only provide internal design teams with a convenient platform for searching and selecting components, but also promote resource sharing and collaborative design across enterprises, accelerating product innovation and market response speed. However, although current component resource libraries have made significant progress in displaying basic 3D models, they still have many shortcomings in providing real product images of components. Some resource libraries are limited to displaying simple 3D models, lacking intuitiveness and realism, and failing to meet users' needs for in-depth understanding of component appearance, materials, and actual application scenarios. While some more advanced resource libraries have attempted to introduce real product images, the processes of image acquisition, filtering, and uploading still rely heavily on manual operations. This is not only inefficient but also prone to human error, affecting user experience and the accuracy of the resource library.
[0052] When building a parts resource library, companies need to invest significant human and material resources in collecting, screening, and uploading real product images of the parts. This process involves tedious and complex steps such as manually searching, downloading, screenshotting, verifying, and uploading, which is not only time-consuming and labor-intensive but also prone to human error leading to incorrect image uploads, misleading users, and reducing the library's credibility and user experience. When companies cannot obtain suitable real product images, they often choose to directly screenshot or render 3D models as a substitute. However, this approach has significant limitations. Unrendered 3D model images often lack realism and detail, making it difficult to accurately reflect the actual appearance and materials of the parts. While rendering using 3D modeling software can improve image quality, this process also requires substantial manual time and effort and demands advanced rendering technology, increasing the company's operating costs.
[0053] Based on this, embodiments of this application provide a method, apparatus, device, and storage medium for automatically generating 3D model images, aiming to improve the efficiency of 3D model display and reduce enterprise operating costs through automatic rendering of 3D models. The method, apparatus, device, and storage medium for automatically generating 3D model images provided in this application are specifically described through the following embodiments. First, the method for automatically generating 3D model images in this application embodiment is described.
[0054] The automatic 3D model image generation method provided in this application relates to the field of 3D model technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as 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, CDN, and big data and artificial intelligence platforms; the software can implement the application of the automatic 3D model image generation method, but is not limited to the above forms.
[0055] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.
[0056] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent will be obtained first. Furthermore, the collection, use, and processing of this data will comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user will be obtained through pop-ups or redirects to confirmation pages. Only after obtaining the user's separate permission or consent will the necessary user-related data for the normal operation of the embodiments of this application be obtained.
[0057] Figure 1 This is an optional flowchart of the 3D model image automatic generation method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S104.
[0058] Step S101: Detect the 3D model image of the platform. If the 3D model image is missing at a specified location of the platform, obtain the 3D model to be processed corresponding to the specified location.
[0059] Step S102: Using a preset material resource library and surface treatment resource library, the 3D model to be processed is rendered to obtain a rendered 3D model.
[0060] Step S103: Capture the image of the rendered 3D model to obtain the rendered image of the rendered 3D model;
[0061] Step S104: Upload the rendered image to the designated location on the platform.
[0062] Steps S101 to S104 shown in this embodiment of the application realize the automatic detection, rendering, cropping and uploading of 3D model images in the resource library through automation and intelligence, effectively solving the problem of current parts resource libraries in displaying real product images, and improving the quality of the resource library and user experience.
[0063] Specifically, the system first iterates through a designated location in the resource library to check for missing 3D model images. This is done by comparing the model information recorded in the database with the actual stored image files. Next, based on the attributes and requirements of the 3D model to be processed, the system selects appropriate materials and surface treatment effects from a pre-set material and surface treatment resource library. These resources are then applied to render the model. The rendering process involves advanced graphics processing techniques such as lighting simulation, shadow processing, and texture mapping. After rendering is complete, the system automatically captures an image of the rendered 3D model. Finally, the system uploads the captured rendered image to a designated location in the resource library and updates the relevant records in the database to reflect this change.
[0064] In step S104 of some embodiments, referring to Figure 2 Specifically, it includes:
[0065] S1041. Name the rendered image according to the name of the 3D model to obtain a named rendered image;
[0066] S1042. Obtain the storage path corresponding to the specified location on the platform;
[0067] S1043. Upload the named rendered image to the designated location on the platform according to the storage path.
[0068] In the embodiments of this application, steps S1041 to S1043, during the process of uploading the rendered image to the designated location on the platform, ensure the accuracy and efficiency of image uploading through standardized naming, automatic acquisition of storage paths, and automated uploading, thereby improving the quality of the resource library and the user experience.
[0069] Specifically, the system automatically generates a corresponding rendered image name based on the name of the 3D model to be processed. This name can include key information such as the model's ID, type, and size to ensure uniqueness and recognizability. Next, the system automatically calculates the storage path corresponding to the specified location based on the resource library's directory structure and storage rules, and uploads the image to the specified location in the resource library according to the named rendered image and storage path obtained in the previous steps.
[0070] In step S102 of some embodiments, referring to Figure 3 Specifically, it includes:
[0071] S1021. Open the 3D model to be processed using 3D modeling software, and obtain the component categories and component attributes of the 3D model to be processed;
[0072] S1022. Obtain the rendering parameters of the 3D model to be processed according to the component category and the component attributes;
[0073] S1023. According to the rendering parameters, the 3D model to be processed is rendered using a preset material resource library and surface treatment resource library to obtain a rendered 3D model.
[0074] Steps S1021 to S1023, as shown in the embodiments of this application, ensure the accuracy and quality of the rendering results by analyzing the component categories and attributes of the model, accurately matching rendering parameters, and applying high-quality materials and surface treatment effects during the rendering process of the 3D model to be processed. This not only improves the display effect of the 3D models in the resource library, but also provides users with a more intuitive and realistic visual experience.
[0075] Specifically, the system first opens the 3D model file to be processed using professional 3D modeling software (such as SolidWorks, AutoCAD, etc.). After opening the model, the system traverses each component, identifying and extracting the category (such as mechanical parts, electronic components, etc.) and attributes (such as size, shape, material, etc.) of each component. Through detailed analysis of the component categories and attributes, the system can more accurately understand the model's structure and characteristics, providing a reliable foundation for determining subsequent rendering parameters. After obtaining the component categories and attributes, the system selects appropriate rendering parameters for each component based on a preset rendering parameter library. These rendering parameters include light intensity, shadow effects, texture resolution, and material reflectivity. After determining the rendering parameters, the system selects suitable materials and surface treatment effects from a preset material resource library and surface treatment resource library, and applies these resources to render the model. By applying high-quality materials and surface treatment effects, as well as precise rendering parameters, the system can generate realistic and detailed rendered 3D models, providing users with a more intuitive and lifelike visual experience.
[0076] In step S103 of some embodiments, referring to Figure 4 Specifically, it includes:
[0077] S1031. Obtain the component categories and component attributes of the 3D model to be processed;
[0078] S1032. Obtain the screenshot angle of the 3D model to be processed according to the component category;
[0079] S1033. Obtain the screenshot ratio and screenshot size of the 3D model to be processed based on the attributes of the components;
[0080] S1034. Based on the screenshot angle, screenshot ratio, and screenshot size, capture an image of the rendered 3D model to obtain a rendered image of the rendered 3D model.
[0081] In the embodiments of this application, steps S1031 to S1034, during the process of capturing and rendering 3D model images, comprehensively consider the component categories and attributes of the 3D model to be processed, ensuring the rationality and accuracy of the screenshot parameters, thereby improving the quality and display effect of the rendered images.
[0082] Specifically, the system first obtains the component categories and attributes of the 3D model to be processed. Then, based on the component category, and combined with a preset screenshot angle library or intelligent recommendation based on machine learning algorithms, it determines the optimal screenshot angle. For example, for mechanical parts, it may be necessary to show their assembly interfaces and internal structures; for electronic components, it may be necessary to highlight their pin layout and appearance features. Simultaneously, the system determines the appropriate screenshot ratio and size based on the component attributes and preset screenshot ratio and size rules. After determining the screenshot-related parameters, the system performs screenshot operations on the rendered 3D model according to parameters such as screenshot angle, screenshot ratio, and screenshot size to ensure that the final generated rendered image meets the preset requirements. Reasonable screenshot parameter settings ensure that the rendered image is clear, complete, and easy to understand, thereby improving the user's visual experience and satisfaction.
[0083] In some embodiments, the step of rendering the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model specifically includes:
[0084] Obtain the custom rendering parameters of the 3D model;
[0085] Based on the custom rendering parameters, the 3D model to be processed is rendered using a preset material resource library and surface treatment resource library to obtain a rendered 3D model.
[0086] Specifically, the system first checks whether the 3D model to be processed contains custom rendering parameters. These parameters may be pre-set by the user or model designer to control effects such as lighting, shadows, color, texture, and reflectivity during the rendering process. Custom rendering parameters may exist in various forms, such as metadata embedded in the 3D model file, external configuration files, or parameters entered by the user through the interface. The system parses these parameters and prepares to apply them in subsequent rendering processes. After the rendering step begins, the system uses the previously obtained custom rendering parameters, combined with a preset material resource library and surface treatment resource library, to render the 3D model to be processed. The preset material resource library contains information on various materials, such as metal, plastic, wood, and glass, each with corresponding texture, color, and reflectivity attributes. The surface treatment resource library contains various surface treatment effects, such as polishing, sandblasting, and electroplating, which can further enhance the realism and detail of the model. The system selects appropriate materials from the material resource library according to the requirements in the custom rendering parameters and applies the corresponding surface treatment effects, ultimately generating the rendered 3D model. By allowing users or model designers to set custom rendering parameters, the system can flexibly handle various rendering needs and meet different display and application scenarios.
[0087] In some embodiments, the step of rendering the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model specifically includes:
[0088] Obtain several 3D models to be processed, and distribute the 3D models to be processed to several sub-servers;
[0089] Obtain several rendered 3D models uploaded by the sub-server;
[0090] The sub-server is used to render the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model.
[0091] Specifically, the system first collects and acquires multiple 3D models to be processed, which may come from user uploads, database imports, or other sources. The system then distributes these 3D models to multiple sub-servers based on the number of available sub-servers and their load conditions. The distribution strategy is optimized based on factors such as load balancing, model size, and rendering complexity to ensure that each sub-server can efficiently handle its assigned rendering tasks. Upon receiving the 3D model, each sub-server renders it using a pre-defined material and surface treatment resource library. These resource libraries may be stored locally or accessed via a network, depending on the system's design and configuration. After completing the rendering task, each sub-server uploads the generated rendered 3D model back to the main server or a designated storage location. The system collects these rendering results and performs necessary integration and verification to ensure that all rendering tasks have been successfully completed. Through distributed rendering, the system can handle multiple rendering tasks simultaneously, significantly reducing overall rendering time. Furthermore, the system can dynamically adjust task allocation based on the sub-server load and the complexity of the rendering tasks to optimize resource utilization. By increasing the number of sub-servers, the system can easily expand its rendering capacity to accommodate larger-scale rendering needs.
[0092] In some embodiments, after the step of detecting the 3D model image of the platform and obtaining the corresponding 3D model to be processed if a 3D model image is missing at a specified location on the platform, the method further includes:
[0093] The 3D model to be processed is converted into STP format.
[0094] Specifically, the system reads and parses the acquired 3D model to be processed, and then converts it into STP format. The converted STP file will contain complete 3D model information and be represented in a standardized way, which allows it to be opened, edited and exchanged in different CAD (Computer-Aided Design) systems, CAE (Computer-Aided Engineering) systems, CAM (Computer-Aided Manufacturing) systems and other software that supports the STP format.
[0095] Please see Figure 5 This application also provides a 3D model image automatic generation device, the device comprising:
[0096] Image detection module 101 is used to detect 3D model images of the platform. If a 3D model image is missing at a specified location of the platform, the corresponding 3D model to be processed at the specified location is obtained.
[0097] The model rendering module 102 is used to render the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model.
[0098] Image capture module 103 is used to capture images of the rendered 3D model to obtain rendered images of the rendered 3D model;
[0099] Image upload module 104 is used to upload the rendered image to a designated location on the platform.
[0100] The specific implementation of the 3D model image automatic generation device is basically the same as the specific implementation of the 3D model image automatic generation method described above, and will not be repeated here.
[0101] Please see Figure 6 , Figure 6 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes:
[0102] The processor 601 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.
[0103] The memory 602 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 602 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 602 and is called and executed by the processor 601 using the automatic 3D model image generation method of the embodiments of this application.
[0104] The input / output interface 603 is used to implement information input and output;
[0105] The communication interface 604 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).
[0106] Bus 605 transmits information between various components of the device (e.g., processor 601, memory 602, input / output interface 603, and communication interface 604);
[0107] The processor 601, memory 602, input / output interface 603, and communication interface 604 are connected to each other within the device via bus 605.
[0108] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for automatically generating 3D model images.
[0109] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
[0110] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. Those skilled in the art will know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.
[0111] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.
[0112] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.
[0113] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0114] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.
[0115] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.
[0116] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0117] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0118] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.
Claims
1. A method for automatically generating 3D model images, characterized in that, The method includes: The platform's 3D model images are detected. If a 3D model image is missing at a specified location on the platform, the corresponding 3D model to be processed at the specified location is obtained. Using a preset material resource library and surface treatment resource library, the 3D model to be processed is rendered to obtain a rendered 3D model, including: The 3D model to be processed is opened using 3D modeling software to obtain the component categories and component attributes of the 3D model to be processed. Based on the component category and the component attributes, obtain the rendering parameters of the 3D model to be processed; Based on the rendering parameters, the 3D model to be processed is rendered using a preset material resource library and surface treatment resource library to obtain a rendered 3D model. Extracting an image of the rendered 3D model to obtain a rendered image of the 3D model includes: Obtain the component categories and component attributes of the 3D model to be processed; Obtain the screenshot angle of the 3D model to be processed based on the component category; The screenshot scale and screenshot size of the 3D model to be processed are obtained based on the attributes of the components. Based on the screenshot angle, screenshot ratio, and screenshot size, an image of the rendered 3D model is captured to obtain a rendered image of the rendered 3D model; The rendered image is uploaded to the designated location on the platform.
2. The method for automatically generating 3D model images according to claim 1, characterized in that, The step of uploading the rendered image to the designated location on the platform specifically includes: The rendered image is named according to the name of the 3D model to obtain a named rendered image; Obtain the storage path corresponding to the specified location on the platform; The named rendered image is uploaded to the designated location on the platform according to the storage path.
3. The method for automatically generating 3D model images according to claim 1, characterized in that, The step of rendering the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model specifically includes: Obtain the custom rendering parameters of the 3D model; Based on the custom rendering parameters, the 3D model to be processed is rendered using a preset material resource library and surface treatment resource library to obtain a rendered 3D model.
4. The method for automatically generating 3D model images according to claim 1, characterized in that, The step of rendering the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model specifically includes: Obtain several 3D models to be processed, and distribute the 3D models to be processed to several sub-servers; Obtain several rendered 3D models uploaded by the sub-server; The sub-server is used to render the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model.
5. The method for automatically generating 3D model images according to claim 1, characterized in that, After the step of detecting 3D model images on the platform and obtaining the corresponding 3D model to be processed if a 3D model image is missing at a specified location on the platform, the method further includes: The 3D model to be processed is converted into STP format.
6. A device for automatically generating 3D model images, characterized in that, The device includes: The image detection module is used to detect 3D model images on the platform. If a 3D model image is missing at a specified location on the platform, the corresponding 3D model to be processed at the specified location is obtained. The model rendering module is used to render the 3D model to be processed using a preset material resource library and surface treatment resource library to obtain a rendered 3D model, including: The 3D model to be processed is opened using 3D modeling software to obtain the component categories and component attributes of the 3D model to be processed. Based on the component category and the component attributes, obtain the rendering parameters of the 3D model to be processed; Based on the rendering parameters, the 3D model to be processed is rendered using a preset material resource library and surface treatment resource library to obtain a rendered 3D model. The image cropping module is used to crop an image of the rendered 3D model to obtain a rendered image of the 3D model, including: Obtain the component categories and component attributes of the 3D model to be processed; Obtain the screenshot angle of the 3D model to be processed based on the component category; The screenshot scale and screenshot size of the 3D model to be processed are obtained based on the attributes of the components. Based on the screenshot angle, screenshot ratio, and screenshot size, an image of the rendered 3D model is captured to obtain a rendered image of the rendered 3D model; The image upload module is used to upload the rendered image to a designated location on the platform.
7. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the automatic generation method for 3D model images according to any one of claims 1 to 5.
8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the automatic generation method of 3D model images as described in any one of claims 1 to 5.