CN116579829A - Personalized customization virtual simulation verification method and system for service-oriented manufacturing - Google Patents
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Abstract
The application discloses a personalized customized virtual verification method and a system for service-oriented manufacturing, wherein the method comprises the following steps: providing a web page to a customer; acquiring a data format required for displaying on the reality presentation device according to the model of the reality presentation device; obtaining production data of customized products in an order associated with the customer, and constructing a virtual sample image capable of being displayed on the real presentation device according to the production data and the data format; and storing the corresponding relation between the virtual sample image and the customized product in a database, and providing the download link of the virtual sample image for the client through the webpage. The application solves the problem of increasing capital and time cost caused by the mode of first producing samples and then carrying out mass production in the customized production, thereby improving the verification efficiency of the customized product and reducing the cost.
Description
Technical Field
The application relates to the field of intelligent manufacturing, in particular to a personalized customized virtual verification method and system for service-oriented manufacturing.
Background
In the conventional manufacturing industry, there are generally manufacturers that produce products and then put the produced products on the market. The production method of the product can set a standard production flow for the product to be produced, and the product is produced in large batch by using the same raw materials and production process. The production mode can reduce the cost of the product to the greatest extent.
However, this production method has its own weakness, that is, the produced product may not meet the needs of some users. The user cannot achieve customized production. To solve this problem, a concept of direct user manufacturing, i.e., C2M is an abbreviation of english Customer-to-Manufacturer, is proposed in the related art, and is a new commercial model of industrial internet e-commerce, which is also called "short-circuit economy".
In the C2M mode, the concept of consumer direct to the factory is introduced, emphasizing the engagement of manufacturing with consumers. In fact, it is a "smart" mode: in the C2M mode, consumers directly place orders through a platform, and factories receive personalized demand orders of the consumers and then design, purchase, production and shipment according to demands. Mainly comprises pure flexible production and small-batch and multi-batch rapid supply chain reaction.
In the customization mode, production data are obtained according to the order demands of customers, in order to ensure that products produced according to the production data meet the demands of customers, samples are generally produced according to the production data, the samples are mailed to the customers, and after confirmation of the customers is obtained, large-scale production is performed. This way of first producing the sample creates additional costs and wastes some time, increasing the time costs of production.
Disclosure of Invention
The embodiment of the application provides a personalized customized virtual verification method and a personalized customized virtual verification system for service-oriented manufacturing, which at least solve the problems of increased funds and time cost caused by a mode of first producing samples and then carrying out mass production in customized production.
According to one aspect of the present application, there is provided a personalized customized virtual verification method for service-oriented manufacturing, comprising: providing a webpage for a client, wherein the webpage comprises an input control, and the input control is used for inputting the model of the real presentation device; acquiring a data format required for displaying on the reality presentation device according to the model of the reality presentation device; obtaining production data of customized products in an order associated with the customer, and constructing a virtual sample image capable of being displayed on the real presentation device according to the production data and the data format; and storing the corresponding relation between the virtual sample image and the customized product in a database, and providing the download link of the virtual sample image for the client through the webpage.
Further, constructing a virtual sample image displayable on the real-world presentation device from the production data and the data format includes: constructing a 3D image of a sample corresponding to the production data according to the production data; and converting the 3D image into a virtual sample image displayed on the reality presentation device according to the data format.
Further, constructing a 3D image of a sample corresponding to the production data from the production data includes: inputting the production data into a first machine learning model, wherein the first machine learning model is a supervised neural network model trained using a plurality of sets of first training data, each set of first training data comprising: input data and output data, wherein the input data is production data, and the output data is a 3D image; and acquiring a 3D image output by the first machine learning model from the first machine learning model, wherein the 3D image is a 3D image of a sample corresponding to the production data.
Further, converting the 3D image into a virtual sample presentation displayed on the real-world presentation device according to the data format comprises: inputting the data format and the 3D image into a second machine learning model, wherein the second machine learning model is a supervised neural network model trained using a plurality of sets of second training data, wherein each set of second training data in the plurality of sets of second training data comprises: input data and output data, wherein the input data is in a data format and a 3D image, and the output data is a virtual sample image; and obtaining a virtual sample image output by the second machine learning model from the second machine learning model, wherein the output virtual sample image is a virtual sample image displayed on the reality presentation device.
According to another aspect of the present application, there is also provided a personalized customized virtual verification system for service-oriented manufacturing, including: the first providing module is used for providing a webpage for a client, wherein the webpage comprises an input control, and the input control is used for inputting the model of the real presentation device; the acquisition module is used for acquiring a data format required by display on the reality presentation equipment according to the model of the reality presentation equipment; a construction module for obtaining production data of a customized product in an order associated with the customer, constructing a virtual sample image displayable on the real-world presentation device according to the production data and the data format; and the second providing module is used for storing the corresponding relation between the virtual sample image and the customized product in a database, and providing the download link of the virtual sample image for the client through the webpage.
Further, the construction module is configured to: constructing a 3D image of a sample corresponding to the production data according to the production data; and converting the 3D image into a virtual sample image displayed on the reality presentation device according to the data format.
Further, the construction module is configured to: inputting the production data into a first machine learning model, wherein the first machine learning model is a supervised neural network model trained using a plurality of sets of first training data, each set of first training data comprising: input data and output data, wherein the input data is production data, and the output data is a 3D image; and acquiring a 3D image output by the first machine learning model from the first machine learning model, wherein the 3D image is a 3D image of a sample corresponding to the production data.
Further, the construction module is configured to: inputting the data format and the 3D image into a second machine learning model, wherein the second machine learning model is a supervised neural network model trained using a plurality of sets of second training data, wherein each set of second training data in the plurality of sets of second training data comprises: input data and output data, wherein the input data is in a data format and a 3D image, and the output data is a virtual sample image; and obtaining a virtual sample image output by the second machine learning model from the second machine learning model, wherein the output virtual sample image is a virtual sample image displayed on the reality presentation device.
According to another aspect of the present application, there is also provided an electronic device including a memory and a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to perform the method steps described above.
According to another aspect of the present application there is also provided a readable storage medium having stored thereon computer instructions which when executed by a processor perform the above-mentioned method steps.
In the embodiment of the application, a webpage is provided for a client, wherein the webpage comprises an input control, and the input control is used for inputting the model of the real presentation equipment; acquiring a data format required for displaying on the reality presentation device according to the model of the reality presentation device; obtaining production data of customized products in an order associated with the customer, and constructing a virtual sample image capable of being displayed on the real presentation device according to the production data and the data format; and storing the corresponding relation between the virtual sample image and the customized product in a database, and providing the download link of the virtual sample image for the client through the webpage. The application solves the problem of increasing capital and time cost caused by the mode of first producing samples and then carrying out mass production in the customized production, thereby improving the verification efficiency of the customized product and reducing the cost.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:
FIG. 1 is a flow chart of a personalized customized virtual verification method for service oriented manufacturing according to an embodiment of the application.
Detailed Description
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
In the following embodiments, reference is made to an AR device, a VR device, an MR device and an XR device, and it should be noted that these devices are collectively referred to as a reality presentation device in the following embodiments, and AR, VR, MR and XR technologies are first described below.
AR augmented reality (Augmented Reality)
AR is an abbreviation for english phrase Augmented Reality, chinese translation is "augmented reality". In short, virtual information is superimposed into the real world, and a real scene and a virtual scene are combined to be experienced through electronic devices such as a smart phone, a tablet personal computer and the like.
VR Virtual Reality (Virtual Reality)
VR is an abbreviation for Virtual Reality of english phrases, chinese is translated into "Virtual Reality", and a completely Virtual world is generated by device simulation, and is entered into the Virtual world through wearing VR devices, so as to achieve an immersive experience.
MR Mixed Reality (Mixed Reality)
VR and AR have not each gone to the extreme, however there has been evidence of fusion, which is Mixed Reality (MR), i.e., mr=vr AR, or mixing the real world and virtual world together to create a new visual environment that contains both physical and virtual information and must be "real-time". The relative position of the virtual object of the AR device is such that it will move with the movement of the device and the MR will not. In an ideal situation, the virtual object created by the AR device is clearly visible as virtual, whereas the virtual object seen by the MR device user is almost indistinguishable from the real object.
XR augmented Reality (Extended Reality)
XR augmented reality is a new concept that refers to a real and virtual combined, man-machine interactive environment created by computer technology and wearable devices. Augmented reality includes various forms of Augmented Reality (AR), virtual Reality (VR), mixed Reality (MR), and the like. In other words, XR is actually a generic term, including AR, VR, MR, in order to avoid confusion of concepts. XR is divided into multiple layers, from a virtual world input through limited sensors to a fully immersive virtual world.
Various configurations of the real-world presentation device may be used in the following embodiments, and the configuration of the real-world presentation device is described below in connection with several examples.
AR device
The AR device includes: a frame; an AR display module mounted on the frame; the lens with adjustable degrees comprises a first lens and a second lens which are arranged on the lens frame at left and right intervals; the first lens and the second lens are positioned behind the AR display module; the inside of each of the first lens and the second lens is provided with a liquid storage cavity, and one side wall of the liquid storage cavity is a flexible transparent film; the container is used for containing transparent liquid, is arranged on the glasses frame, is respectively connected with the liquid storage cavity of the first lens and the liquid storage cavity of the second lens, and is provided with a liquid pump on the connecting pipeline; and the main board module is used for controlling the operation of the liquid pump.
Optionally, a side wall of the liquid storage cavity of the first lens, which is close to the AR display module, is made of a rigid transparent material, and a side wall of the liquid storage cavity of the first lens, which is far away from the AR display module, is a flexible transparent film; the side wall, close to the AR display module, of the liquid storage cavity of the second lens is made of a rigid transparent material, and the side wall, far away from the AR display module, is a flexible transparent film. The container is a flexible container, and the container is connected with the liquid storage cavity of the first lens and the liquid storage cavity of the second lens through hoses respectively. The container is arranged at the middle position of the back surface of the mirror frame. The top end of the liquid storage cavity of the first lens is provided with a first opening, and the first opening is connected with the container through a hose; the top end of the liquid storage cavity of the second lens is provided with a second opening, and the second opening is connected with the container through a hose. A first valve is further arranged on a connecting pipeline between the container and the liquid storage cavity of the first lens, and the main board module controls the on-off of the first valve; and a second valve is further arranged on a connecting pipeline between the container and the liquid storage cavity of the second lens, and the main board module controls the on-off of the second valve. A first flowmeter is further arranged on a connecting pipeline between the container and the liquid storage cavity of the first lens, and the first flowmeter sends a detected flow signal to the main board module; and a second flowmeter is further arranged on a connecting pipeline between the container and the liquid storage cavity of the second lens, and the second flowmeter sends the detected flow signal to the main board module. The glasses frame is provided with a first adjusting key and a second adjusting key, and the first adjusting key and the second adjusting key are respectively and electrically connected with the main board module. The glasses frame is provided with an alarm module, and the main board module controls the operation of the alarm module. The glasses frame is provided with a wireless communication module, and the main board module is communicated with the upper computer or/and the mobile terminal through the wireless communication module.
VR device
The MR device comprises an MR calculation module, an MR light path module and an MR posture module; the MR computing module includes a display component; the MR gesture module comprises a shooting component and an IMU component; the shooting component is used for collecting images in the preset angle direction of the display component; the IMU component is used for acquiring attitude data of the MR equipment; the MR computing module is connected with the MR gesture module and adjusts the display content of the display component according to the image data and gesture data acquired by the MR gesture module. The MR light path module comprises a virtual image light path and a mixed light path; the virtual image light path is connected with the display component; the input end of the mixed light path is connected with the virtual image light path, and the output end is an observation end; a semi-transparent semi-reflecting mirror is arranged at the mixed light path; one surface of the semi-transparent semi-reflecting mirror is a real image introducing surface, and the other surface of the semi-transparent semi-reflecting mirror is a virtual image introducing surface; the real image introducing surface faces to a real environment; the virtual image introducing surface faces the virtual image light path; the display content of the display component is processed and transmitted through a virtual image light path to form a virtual image, and virtual image light rays are reflected to an observation end through a virtual image introducing surface; the light rays of the real environment are transmitted to the observation end through the real image introducing surface and are mixed with the virtual image to form a mixed reality image.
The MR computing module is a main smart phone; the display component is a display module of the main smart phone; the IMU component comprises a magnetometer, a gyroscope and an accelerometer; the IMU component comprises a main IMU component and an auxiliary IMU component; the main IMU component collects gesture data of the display component; the main IMU component is arranged at the main smart phone; the auxiliary IMU component is arranged at more than one control device which is connected with the main smart phone in a wireless mode; the auxiliary IMU component collects attitude data or position data of the control equipment; the attitude data comprises attitude angle, angular rate or acceleration data; the shooting assembly comprises a main shooting assembly and an auxiliary shooting assembly, wherein the main shooting assembly is a rear camera of the main smart phone, and the auxiliary shooting assembly is a camera at a control device. The MR light path module is a passive MR head-mounted mechanism; the main smart phone is fixed at the MR head-mounted mechanism; the main shooting component is a rear camera of the main smart phone; the control device is a game handle, or is wearable on hands or feet, or is a sensor and a control device fixed on the MR head-mounted mechanism, or is an auxiliary mobile phone held by a user or tied on limbs. The virtual image light path of the MR head-mounted mechanism comprises a rest plate, a total reflection mirror and a view field lens; the view field lens is formed by splicing two Fresnel lenses; the main smart phone is transversely placed on the placing plate; when the MR headset works, the main smart phone plays an image of a VR split screen mode in a transverse double split screen mode, image light rays of two split screens are reflected to two Fresnel lenses by the total reflection mirror, the two Fresnel lenses refract the image light rays of the two split screens, so that the image light rays form two virtual image light rays with a preset field angle, and the virtual image light rays are reflected to an observation end through the virtual image introducing surface; the light rays of the real environment are transmitted to the observation end through the real image introduction surface, and the light rays of the real environment and the virtual image are mixed to enable the observation end to form a mixed reality image. The direction of the rear camera of the main smart phone is the direction of the MR headset; the gesture data of the display component is the gesture data of the main smart phone; the IMU component at the main smart phone collects gesture data of the main smart phone, when the MR headset works, the rear camera of the main smart phone collects characteristic points of a real scene at the initial orientation position of the MR headset, and continuously collects images as gesture images when the MR headset works; the MR calculation module adjusts the image on the double split screen according to the change of the characteristic points at the gesture image and the change of gesture data of the main smart phone. The image played in the transverse double-split screen mode comprises a virtual character and a control identifier, the MR computing module generates the control identifier according to the gesture data and the position data of the control equipment uploaded by the auxiliary IMU component, and the control identifier moves along with the movement of the control equipment; the avatar may interact with the control tag. The main intelligent mobile phone is connected with external equipment through a network, a virtual character and a control identifier which are included in the image played in a transverse double-split-screen mode are part of a mixed reality image, the virtual character corresponds to the external equipment, and when the virtual character can interact with the control identifier, the external equipment performs corresponding operation according to the interaction content.
Other MR and XR devices may be used with existing devices and are not described in this embodiment.
In the following embodiments, the following method may be employed to obtain parameters used by a production apparatus in producing a product, and to produce a customized product using the obtained parameters.
The personalized customization method for service-oriented manufacturing comprises the following steps: acquiring an order from a customer, and extracting identification information of a product to be processed from the order; the identification information is used for uniquely identifying the product to be processed; acquiring identification information of the product to be processed from the order, and searching for component parts of the product to be processed according to the identification information; acquiring the characteristics of the product to be processed from the order, and adjusting and/or replacing the component parts according to the characteristics of the product to be processed to obtain the part characteristics of the product to be processed; searching a part model conforming to the part characteristics of the product to be processed from design software according to the part characteristics of the product to be processed, and assembling the part model into a product model; and generating production data for manufacturing a product corresponding to the product model according to the product model, and sending the production data to production equipment. The method for acquiring the production data is only an optional acquisition method, other methods are adopted to acquire the production data and send the production data to production equipment for production, and the same technical effects are obtained, so that the other acquisition methods of the production data are not described in detail herein.
It should be noted that, after the production data is sent to the production device, the product is produced, that is, the verification of the customer is not passed before the product is produced. To solve this problem, some manufacturers produce small amounts of samples, send the samples to customers, and then mass produce the samples after the customers confirm the samples, but this process increases the cost, and the samples involve mailing processes, delays the time, and is inefficient.
In order to solve the above-mentioned problems, in the following embodiments, a personalized virtual verification method for service-oriented manufacturing is provided, fig. 1 is a flowchart of a personalized virtual verification method for service-oriented manufacturing according to an embodiment of the present application, and steps involved in the method in fig. 1 are described below.
Step S102, a webpage is provided for a client, wherein the webpage comprises an input control, and the input control is used for inputting the model of the real presentation device.
Step S104, the data format required for displaying on the reality presenting device is obtained according to the model of the reality presenting device.
Step S106, obtaining production data of customized products in orders associated with the clients, and constructing virtual sample images capable of being displayed on the reality presentation device according to the production data and the data format.
In an alternative embodiment, after generating 3D data corresponding to a sample according to production data, the 3D data is 3D data conforming to predetermined design software, and the 3D data may generate a 3D model that the design software can support; and generating a 3D model which can be supported by the design software according to the 3D data, configuring the 3D model in the design software for verification, and generating a 3D image corresponding to the sample according to the 3D data after the verification is passed.
Step S108, storing the corresponding relation between the virtual sample image and the customized product in a database, and providing the download link of the virtual sample image for the client through the webpage.
As another optional implementation manner, a prompt language is added to the virtual sample image, and the prompt language is made according to a time axis of displaying the virtual sample image, wherein when the virtual sample image is displayed on a different component, the prompt language prompts whether the component needs to be modified. After the virtual sample image is downloaded, displaying the virtual sample image in the reality presentation device, playing the prompt voice in the displaying process, recording the displaying process of the whole virtual sample image, and uploading the recorded displaying process through a webpage.
And acquiring the recorded display process, extracting the voice of the client, converting the extracted voice into characters, acquiring modification of production data (or called product parameters) of the sample according to the characters, regenerating a virtual sample image according to the modified production data, and uploading the virtual sample image to a webpage.
For the modified production data, a saving mode is also provided in the present embodiment. The method comprises the following steps: obtaining an order submitted by a customer through a web page, and storing various product parameters in the order in a database, wherein in the database, product information is stored in a piece of original data, the piece of original data comprises a plurality of fields, each field is used for storing one product parameter, the piece of data also comprises an order identifier and a data identifier, the order identifier is used for uniquely identifying the order, the data identifier comprises a timestamp, a customer identifier and an order state, the timestamp is used for indicating the time when the customer submitted the order, the customer identifier is used for uniquely identifying the customer, and the order state comprises: initial, modified and determined, wherein the initial is used for indicating that the piece of data is generated when the customer originally submits the order, the modified is used for indicating that the piece of data is generated when the customer modifies the order, and the determined is used for indicating that the piece of data is generated when the customer finally determines the order; determining that the client submits the modification to the order through a webpage, and acquiring the changed product parameters in the modified order; generating a piece of modification data in the database in response to modification of the order, wherein unchanged product parameters in a field for storing product parameters in the modification data are copied from the original data, and the acquired changed product parameters are stored in the modification data; the modification data further comprises the order identification and the data identification, the time stamp of the data identification of the modification data is used for indicating the time of the client modifying the order, and the order state of the data identification of the modification data is modification; each time a modification to the order is made, new modification data is generated.
In the above steps, the virtual sample image which can be supported by the corresponding reality presentation device can be generated according to the model of the reality presentation device owned by the customer, so that the problems of increasing capital and time cost caused by the mode that the samples are produced first and then are produced in a large scale in the customized production are solved by the steps, the verification efficiency of the customized product is improved, and the cost is reduced.
In step S106, there are various ways of generating a virtual sample image, for example, constructing a virtual sample image capable of being displayed on the real presentation device according to the production data and the data format may include the steps of: constructing a 3D image of a sample corresponding to the production data according to the production data; and converting the 3D image into a virtual sample image displayed on the reality presentation device according to the data format.
In one embodiment, artificial intelligence may be used to generate 3D images and virtual sample imagery.
For example, constructing a 3D image of a sample corresponding to the production data from the production data may comprise the steps of: inputting the production data into a first machine learning model, wherein the first machine learning model is a supervised neural network model trained using a plurality of sets of first training data, each set of first training data comprising: input data and output data, wherein the input data is production data, and the output data is a 3D image; and acquiring a 3D image output by the first machine learning model from the first machine learning model, wherein the 3D image is a 3D image of a sample corresponding to the production data.
For example, converting the 3D image into a virtual sample presentation displayed on the real-world presentation device according to the data format may comprise the steps of: inputting the data format and the 3D image into a second machine learning model, wherein the second machine learning model is a supervised neural network model trained using a plurality of sets of second training data, wherein each set of second training data in the plurality of sets of second training data comprises: input data and output data, wherein the input data is in a data format and a 3D image, and the output data is a virtual sample image; and obtaining a virtual sample image output by the second machine learning model from the second machine learning model, wherein the output virtual sample image is a virtual sample image displayed on the reality presentation device.
Through the optional implementation manner, virtual verification of various design data of product personalized customization can be realized by various industrial software, and besides, display and customer interaction of test products can be realized by using related virtual simulation technologies (VR, AR, MR and the like), so that customer experience is improved, and cost is reduced.
In this embodiment, there is provided an electronic device including a memory in which a computer program is stored, and a processor configured to run the computer program to perform the method in the above embodiment.
The above-described programs may be run on a processor or may also be stored in memory (or referred to as computer-readable media), including both permanent and non-permanent, removable and non-removable media, and information storage may be implemented by any method or technique. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device.
These computer programs may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks and/or block diagram block or blocks, and corresponding steps may be implemented in different modules.
Such an apparatus or system is provided in this embodiment. This system is called a personalized customized virtual verification system for service-oriented manufacturing, and comprises: the first providing module is used for providing a webpage for a client, wherein the webpage comprises an input control, and the input control is used for inputting the model of the real presentation device; the acquisition module is used for acquiring a data format required by display on the reality presentation equipment according to the model of the reality presentation equipment; a construction module for obtaining production data of a customized product in an order associated with the customer, constructing a virtual sample image displayable on the real-world presentation device according to the production data and the data format; and the second providing module is used for storing the corresponding relation between the virtual sample image and the customized product in a database, and providing the download link of the virtual sample image for the client through the webpage.
The system or the device is used for realizing the functions of the method in the above embodiment, and each module in the system or the device corresponds to each step in the method, which has been described in the method, and will not be described herein.
Optionally, the construction module is configured to: constructing a 3D image of a sample corresponding to the production data according to the production data; and converting the 3D image into a virtual sample image displayed on the reality presentation device according to the data format.
Optionally, the construction module is configured to: inputting the production data into a first machine learning model, wherein the first machine learning model is a supervised neural network model trained using a plurality of sets of first training data, each set of first training data comprising: input data and output data, wherein the input data is production data, and the output data is a 3D image; and acquiring a 3D image output by the first machine learning model from the first machine learning model, wherein the 3D image is a 3D image of a sample corresponding to the production data.
Optionally, the construction module is configured to: inputting the data format and the 3D image into a second machine learning model, wherein the second machine learning model is a supervised neural network model trained using a plurality of sets of second training data, wherein each set of second training data in the plurality of sets of second training data comprises: input data and output data, wherein the input data is in a data format and a 3D image, and the output data is a virtual sample image; and obtaining a virtual sample image output by the second machine learning model from the second machine learning model, wherein the output virtual sample image is a virtual sample image displayed on the reality presentation device.
The method solves the problem of increasing capital and time cost caused by the mode that samples are produced first and then mass production is carried out in the customized production, thereby improving the verification efficiency of the customized product and reducing the cost.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (10)
1. A personalized customized virtual verification method for service-oriented manufacturing, comprising:
providing a webpage for a client, wherein the webpage comprises an input control, and the input control is used for inputting the model of the real presentation device;
acquiring a data format required for displaying on the reality presentation device according to the model of the reality presentation device;
obtaining production data of customized products in an order associated with the customer, and constructing a virtual sample image capable of being displayed on the real presentation device according to the production data and the data format;
and storing the corresponding relation between the virtual sample image and the customized product in a database, and providing the download link of the virtual sample image for the client through the webpage.
2. The method of claim 1, wherein constructing a virtual sample image displayable on the real world presentation device from the production data and the data format comprises:
constructing a 3D image of a sample corresponding to the production data according to the production data;
and converting the 3D image into a virtual sample image displayed on the reality presentation device according to the data format.
3. The method of claim 2, wherein constructing a 3D image of a sample corresponding to the production data from the production data comprises:
inputting the production data into a first machine learning model, wherein the first machine learning model is a supervised neural network model trained using a plurality of sets of first training data, each set of first training data comprising: input data and output data, wherein the input data is production data, and the output data is a 3D image;
and acquiring a 3D image output by the first machine learning model from the first machine learning model, wherein the 3D image is a 3D image of a sample corresponding to the production data.
4. The method of claim 2, wherein converting the 3D image into a virtual sample image displayed on the real-world presentation device according to the data format comprises:
inputting the data format and the 3D image into a second machine learning model, wherein the second machine learning model is a supervised neural network model trained using a plurality of sets of second training data, wherein each set of second training data in the plurality of sets of second training data comprises: input data and output data, wherein the input data is in a data format and a 3D image, and the output data is a virtual sample image;
and obtaining a virtual sample image output by the second machine learning model from the second machine learning model, wherein the output virtual sample image is a virtual sample image displayed on the reality presentation device.
5. A personalized customized virtual verification system for service-oriented manufacturing, comprising:
the first providing module is used for providing a webpage for a client, wherein the webpage comprises an input control, and the input control is used for inputting the model of the real presentation device;
the acquisition module is used for acquiring a data format required by display on the reality presentation equipment according to the model of the reality presentation equipment;
a construction module for obtaining production data of a customized product in an order associated with the customer, constructing a virtual sample image displayable on the real-world presentation device according to the production data and the data format;
and the second providing module is used for storing the corresponding relation between the virtual sample image and the customized product in a database, and providing the download link of the virtual sample image for the client through the webpage.
6. The system of claim 5, wherein the construction module is configured to:
constructing a 3D image of a sample corresponding to the production data according to the production data;
and converting the 3D image into a virtual sample image displayed on the reality presentation device according to the data format.
7. The system of claim 6, wherein the construction module is configured to:
inputting the production data into a first machine learning model, wherein the first machine learning model is a supervised neural network model trained using a plurality of sets of first training data, each set of first training data comprising: input data and output data, wherein the input data is production data, and the output data is a 3D image;
and acquiring a 3D image output by the first machine learning model from the first machine learning model, wherein the 3D image is a 3D image of a sample corresponding to the production data.
8. The system of claim 6, wherein the construction module is configured to:
inputting the data format and the 3D image into a second machine learning model, wherein the second machine learning model is a supervised neural network model trained using a plurality of sets of second training data, wherein each set of second training data in the plurality of sets of second training data comprises: input data and output data, wherein the input data is in a data format and a 3D image, and the output data is a virtual sample image;
and obtaining a virtual sample image output by the second machine learning model from the second machine learning model, wherein the output virtual sample image is a virtual sample image displayed on the reality presentation device.
9. An electronic device includes a memory and a processor; wherein the memory is for storing one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps of any of claims 1 to 4.
10. A readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the method steps of any of claims 1 to 4.
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