Garment design three-dimensional model visual display method based on AI model

Abstract

The invention provides a garment design three-dimensional model visual display method based on an AI model, and belongs to the technical field of image processing, and the method specifically comprises the steps: determining design deviation feedback data of different reference design objects under different sizes according to after-sales data and comment data corresponding to the different reference design objects, based on the design deviation feedback data, deviation design sizes under different reference design objects are determined, and when it is determined that no target size exists according to distribution data of the deviation design sizes of different sizes under different reference design objects, display processing sequences under different sizes are determined by means of the distribution data, and determining future design processing schemes under different sizes by utilizing the displayed design deviation data under the different sizes and combining the planned production data under the sizes, and performing visual display processing by utilizing an AI model on the basis of the design processing schemes, so as to obtain a visual display result. And a foundation is laid for further reducing the return rate caused by size deviation.

Description

Technical Field

[0001] The present invention belongs to the technical field of image processing, and in particular relates to a method for visualizing and displaying a three-dimensional model of clothing design based on an AI model. Background Art

[0002] In order to improve the accuracy and efficiency of clothing design processing, the construction of virtual three-dimensional models can quickly and conveniently reflect the real clothing effects. Specifically, in the invention patent application CN202411348044.3 "Clothing Design Three-Dimensional Modeling Visualization Display System", according to multiple independent model grid accuracy rates and multiple fusion model grid accuracy rates, multiple regional modeling accuracy parameters and model modeling accuracy parameters are classified, and multiple historical modeling accuracies are updated, and visual identification and display are performed. However, there are the following technical problems: When simulating clothing design, the existing technical solutions often use fixed height and weight under the same size for simulation processing. However, since there may be overlaps in height or weight under certain sizes during the size division process, for example, the height is the same but the weight is different, some customers with overlapping situations often return the goods because of choosing the wrong size. Therefore, how to generate design processing solutions under different sizes in a targeted manner, so that clothing designers can visualize the deviation of the version and size when the size is selected incorrectly, and then carry out targeted design optimization processing to further reduce the after-sales rate has become a technical problem that needs to be solved urgently.

[0003] In order to solve the above technical problems, the present application provides a method for visualizing and displaying a three-dimensional model of clothing design based on an AI model. Summary of the invention

[0004] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: Specifically, in the first aspect, the present application provides a method for visualizing a clothing design three-dimensional model based on an AI model, which specifically includes: S1: acquiring the planned listing data of the target design object on different e-commerce platforms, and combining the planned production data of the target design object, and determining that the size deviation data of the target design object needs to be considered during the design process, and then proceeding to the next step; S2 determines the reference design object of the target design object based on the material data and cutting type of the target design object at different clothing parts, determines the design deviation feedback data of the different reference design objects at different sizes according to the after-sales data and comment data corresponding to the different reference design objects, and determines the deviation design sizes under the different reference design objects based on the design deviation feedback data; S3 determines that when there is no target size based on the distribution data of the deviation design size of different sizes under different reference design objects, the display processing order under different sizes is determined by using the distribution data, and the design deviation data of different sizes that have been displayed and processed are used in combination with the planned production data under the sizes to determine the design processing schemes under different sizes in the future, and the AI ​​model is used for visual display processing based on the design processing schemes.

[0005] The beneficial effects of the present invention are: The distribution data of deviation design sizes under different reference design objects is used to determine the display processing order under different sizes, thereby realizing the determination of the display processing order of different sizes from the perspective of deviation risk. It can quickly and effectively realize the identification and processing of pattern abnormalities caused by size purchase errors, and then on the basis of a high degree of abnormality, in order to ensure the clothing design effect, the efficiency of determining the first design processing solution for different sizes is laid.

[0006] Based on the design processing plan, AI models are used for visual display processing, which enables visual display processing under different sizes and multiple heights and weights. This can ensure the visual analysis processing of clothing designers, and then make targeted modifications to the pattern, reducing the return rate due to buying the wrong size.

[0007] A further technical solution is that the planned listing data includes the number of e-commerce platforms on which the products are planned to be listed.

[0008] A further technical solution is that the planned production data includes the planned production quantity of the target design object in different sizes.

[0009] A further technical solution is to determine that the target design object needs to consider the size deviation data during the design process, specifically including: Based on the planned listing data of the target design object on different e-commerce platforms, determine the e-commerce platform where the target design object is planned to be listed, and use it as the planned listing platform; Determining the planned production quantity of the target design object according to the planned production data of the target design object; Based on the planned number of shelves and the planned production quantity, it is determined whether the target design object needs to consider the dimension deviation data during the design process.

[0010] A further technical solution is that when the number of the planned platforms to be put on the shelves is greater than a preset platform number threshold and the planned production quantity is greater than a preset production quantity threshold, it is determined that the target design object needs to consider size deviation data during design processing.

[0011] A further technical solution lies in that the method for determining the design processing solution under the said size is as follows: Take the size that has been displayed and processed as the displayed processing size, determine the number of types of design deviations matching different displayed processing sizes based on the design deviation data of different displayed processing sizes, and take it as the number of deviation types; Based on the production plan data under the said size, determine the proportion of the planned production quantity of the said size in the target design object, and take it as the production quantity proportion; Determine the design processing solution under the said size according to the number of deviation types of different displayed processing sizes and the production quantity proportion under the said size.

[0012] A further technical solution lies in that determining the design processing solution under the said size according to the number of deviation types of different displayed processing sizes and the production quantity proportion under the said size specifically includes: When there is a displayed processing size with the number of deviation types greater than the preset deviation type number threshold, use the first design processing solution to determine the design processing solutions for all subsequent sizes; When there is no displayed processing size with the number of deviation types greater than the preset deviation type number threshold, judge whether the production quantity proportion under the said size is greater than the preset quantity proportion threshold. If so, use the first design processing solution to determine the design processing solution under the said size. If not, use the second design processing solution to determine the design processing solution under the said size.

[0013] Specifically, the second design processing solution is to generate a design solution only based on the median of the corresponding weight and height under the said size.

[0014] A further technical solution lies in that performing visual display processing, which specifically includes: Based on the design processing solutions under different sizes, generate design targets under different sizes; Taking the weight and height corresponding to the design target, the material data of the target design object under the said size, and the cutting type as input quantities, use a convolutional neural network to automatically identify the detailed features of the clothing structure and folds, and generate a 3D model.

[0015] Other features and advantages will be described in the subsequent specification. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification and the drawings.

[0016] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, makes a detailed description as follows. Description of the Drawings

[0017] The above and other features and advantages of the present invention will become more apparent by describing its exemplary embodiments in detail with reference to the accompanying drawings.

[0018] Figure 1 is a flowchart of a method for visualizing a three-dimensional model of clothing design based on an AI model; Figure 2 is a flowchart for determining the dimensional deviation data that needs to be considered when processing the target design object; Figure 3 is a flowchart of a method for determining the deviation design dimensions; Figure 4 is a flowchart of a method for determining the design processing plan under the dimensions. Detailed Embodiments

[0019] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this specification without creative efforts shall fall within the scope of protection of this specification.

[0020] In this application, during the process of generating design solutions for different sizes, by comprehensively considering the planned production data and the abnormal probability of the pattern when there is a purchase deviation in size under different sizes, different design processing solutions are generated under different sizes. On the basis of reducing the difficulty of design processing, designers can timely and effectively discover pattern abnormality problems, thereby reducing the return rate.

[0021] When the number of e-commerce platforms planned to be launched is more than 3 and the planned production quantity is more than 5000 pieces, it is necessary to consider the abnormal situation of the pattern when there is a deviation in the size purchased by users.

[0022] The reference design object is a historical designed garment with the same material data and cutting type as the target design object in different clothing parts.

[0023] The deviation design dimension is the dimension in which the proportion of the number of purchasing users with size design defects, structural imbalance, deviation in three-dimensional fit, and asymmetry and disproportion in the feedback keywords is more than 0.25.

[0024] The target dimension is the dimension in which the number of reference design objects belonging to the deviation design dimension is more than 8.

[0025] Determine the display processing order for different sizes in descending order according to the number of reference design objects belonging to the deviation design size.

[0026] Use the design deviation data for different sizes that have been displayed and processed, and combine the planned production data for the corresponding sizes to determine the future design processing solutions for different sizes. When the number of sizes with design deviations that have been displayed and processed is more than 3, the first design processing solution is used to determine the design processing solution. When the number of sizes with design deviations that have been displayed and processed is not more than 3, and when the proportion of the planned production volume for a size is 0.2 or more, the first design processing solution is used to determine the design processing solution. When the proportion of the planned production volume for a size is less than 0.2, the second design processing solution is used to determine the design processing solution.

[0027] Example 1 As Figure 1 shown, the present application provides a method for visual display of a three-dimensional model of clothing design based on an AI model, specifically including: S1 Obtain the planned listing data of the target design object on different e-commerce platforms, and combine the planned production data of the target design object. When it is determined that size deviation data needs to be considered during the design processing of the target design object, proceed to the next step; Furthermore, the planned listing data includes the number of e-commerce platforms on which the listing is planned.

[0028] It can be understood that the planned production data includes the planned production quantity of the target design object in different sizes.

[0029] Specifically, as Figure 2 shown, determining that size deviation data needs to be considered during the design processing of the target design object specifically includes: Based on the planned listing data of the target design object on different e-commerce platforms, determine the e-commerce platforms on which the target design object is planned to be listed, and use them as the planned listing platforms; According to the planned production data of the target design object, determine the planned production quantity of the target design object; Based on the number of planned listing platforms and the planned production quantity, determine whether size deviation data needs to be considered during the design processing of the target design object.

[0030] Furthermore, when the number of planned listing platforms is greater than the preset platform quantity threshold and the planned production quantity is greater than the preset production quantity threshold, it is determined that size deviation data needs to be considered during the design processing of the target design object.

[0031] In another possible embodiment, determining that the target design object needs to consider dimensional deviation data during the design process specifically includes: Based on the planned listing data of the target design object on different e-commerce platforms, determine the e-commerce platform on which the target design object is planned to be listed, and use it as the planned listing platform; According to the planned production data of the target design object, determine the planned production quantity of the target design object; Based on the product of the quantity on the planned listing platform and the planned production quantity, determine the construction requirement value of the target design object, and determine whether the target design object needs to consider dimensional deviation data during the design process according to the construction requirement value.

[0032] Further, when the construction requirement value is greater than the preset construction requirement threshold, it is determined that the target design object needs to consider dimensional deviation data during the design process.

[0033] S2 Determine the reference design object of the target design object based on the material data and cutting types of the target design object in different clothing parts. According to the after-sales data and comment data corresponding to different reference design objects, determine the design deviation feedback data of different reference design objects under different sizes, and determine the deviation design sizes under different reference design objects based on the design deviation feedback data; It can be understood that the material data includes cotton, linen, silk, wool, artificial fibers, synthetic fibers, blended and functional fabrics, modal, and chiffon.

[0034] Specifically, the cutting types include cutting sizes and cutting patterns.

[0035] It should be noted that the reference design object is a historical design object that is consistent with the target design in terms of material data in different clothing parts and the deviation amounts of cutting sizes and cutting patterns are within the preset deviation amount range.

[0036] Further, the types of design deviations include dimensional design defects, structural imbalance, three-dimensional fit deviation, symmetry and proportion imbalance.

[0037] In addition, it should be noted that the design deviation feedback data includes the number of feedback users under different types of design deviations.

[0038] Specifically, as Figure 3 shown, the method for determining the deviation design size is: Based on the design deviation feedback data of the reference design object, determine the feedback users under different types of design deviations; For the feedback users corresponding to the purchase sizes under different types of design deviations, determine the number of feedback users of the feedback data with design deviations under different sizes; Based on the number of feedback users of the feedback data with design deviations under different sizes, determine whether the size is a deviation design size.

[0039] Further, when the number of feedback users of the feedback data with design deviations under the size is greater than the preset feedback user number threshold, then determine the size as a deviation design size under the reference design object.

[0040] In another possible embodiment, the method for determining the deviation design size is as follows: Based on the design deviation feedback data of the reference design object, determine the feedback users under different types of design deviations; For the feedback users corresponding to the purchase sizes under different types of design deviations, determine the number of feedback users of the feedback data with design deviations under different sizes; Based on the proportion of the number of feedback users of the feedback data with design deviations under the size in the number of feedback users of the feedback data with design deviations of the reference design object, determine the feedback deviation quantity proportion, and based on the feedback deviation quantity proportion, determine whether the size is a deviation design size.

[0041] Further, when the feedback deviation quantity proportion is greater than the preset deviation quantity proportion threshold, then determine the size as a deviation design size.

[0042] S3 When it is determined that there is no target size according to the distribution data of the deviation design sizes of different sizes under different reference design objects, use the distribution data to determine the display processing order of different sizes, use the design deviation data of different sizes that have been displayed and processed, and combine the planned production data of the size to determine the future design processing plans of different sizes. Based on the design processing plans, perform visual display processing using an AI model.

[0043] Specifically, determining that there is no target size specifically includes: Based on the distribution data of the deviation design sizes of different sizes under different reference design objects, determine the reference design objects to which the size belongs to the deviation design size, and use them as deviation design objects; Based on the number of the deviation design objects, determine whether the size belongs to the target size.

[0044] Further, based on the number of the deviation design objects, determining whether the size belongs to the target size specifically includes: When there is a dimension where the number of deviation design objects is greater than the preset threshold of the number of deviation design objects, the dimension with the largest number of deviation design objects is taken as the target dimension; When there is no dimension where the number of deviation design objects is greater than the preset threshold of the number of deviation design objects, it is determined that there is no target dimension.

[0045] It can be understood that when there is a target dimension, the design processing solution under the target dimension is determined by adopting the first design processing solution. And when the number of types of matching design deviations under the target dimension is greater than the preset deviation number threshold, the first design processing solution is adopted for all dimensions to determine the design processing solutions for different dimensions. Otherwise, the second design processing solution is adopted for all dimensions to determine the design processing solutions for different dimensions.

[0046] In another possible embodiment, determining that there is no target dimension specifically includes: S21 Based on the distribution data of the deviation design dimensions of different dimensions under different reference design objects, determine the reference design objects to which the dimension belongs as deviation design objects; It should be noted that before proceeding to step S22, it is also necessary to determine whether there are deviation design objects for the dimension and whether the number of deviation design objects meets the requirements. Specifically, a threshold method is used to determine whether the number of deviation design objects meets the requirements.

[0047] It can be understood that when there are no deviation design objects for the dimension, it is directly determined that the dimension does not belong to the target dimension.

[0048] Specifically, even if there are no deviation design objects, if the number of deviation design objects corresponding to the dimension is too small, when it is less than a certain threshold, it is directly determined that the number of its deviation design objects does not meet the requirements, so it can be directly determined that it does not belong to the target dimension.

[0049] It should be noted that through the screening of the above steps, the screening of dimensions with a large number of deviation design objects can be achieved, thereby improving the efficiency of the screening process of the target dimension.

[0050] S22 Determine the feedback anomaly coefficient of different deviation design objects at the dimension based on the number of users with feedback data for different deviation design objects at the dimension and in combination with the number of feedback users with design deviation feedback data for different deviation design objects at the dimension; Exemplarily, before entering step S23, it is also necessary to determine whether the sum of the number of feedback users of the feedback data with design deviations of the dimension in different deviation design objects at the dimension meets the requirements, and whether the feedback abnormal coefficients of different deviation design objects are all less than the preset abnormal coefficient threshold.

[0051] It should be noted that when the sum of the number of feedback users of the feedback data with design deviations of the dimension in different deviation design objects at the dimension is too small, that is, less than the preset quantity threshold, at this time, it can be directly determined that the sum of the number of feedback users of the feedback data with design deviations of the dimension in different deviation design objects at the dimension meets the requirements. Since the number of its feedback users is small, it can be directly determined that it does not belong to the target dimension.

[0052] In addition, it should be noted that even if the number of its feedback users meets the requirements, if the feedback abnormal coefficients of different deviation design objects are all less than the preset abnormal coefficient threshold, and at the same time the number of deviation design objects is within the preset quantity range, at this time, since the credibility of different deviation design objects is not high and the number of deviation design objects is not large, it can be directly determined that it does not belong to the target dimension.

[0053] S23 determines the comprehensive abnormal value of the dimension according to the number of the deviation design objects and the feedback abnormal coefficients of different deviation design objects at the dimension, and determines whether the dimension belongs to the target dimension based on the comprehensive abnormal value.

[0054] It can be understood that when there is a dimension with a comprehensive abnormal value greater than the preset abnormal threshold, the dimension with the largest comprehensive abnormal value is used as the target dimension. When there is no dimension with a comprehensive abnormal value greater than the preset abnormal threshold, it is determined that there is no target dimension.

[0055] It can be understood that the comprehensive abnormal value of the dimension can be determined by means of expert scoring. Specifically, the number of deviation design objects and the feedback abnormal coefficients of different deviation design objects at the dimension are used as input quantities, and the comprehensive abnormal value of the dimension is determined according to the output result of the expert scoring mathematical model.

[0056] Furthermore, the display processing order is determined from large to small according to the number of reference design objects of different dimensions belonging to the deviation design dimensions.

[0057] Specifically, as Figure 4 shown, the method for determining the design processing scheme under the dimension is: Taking the dimension that has been displayed and processed as the displayed and processed dimension, determining the number of types of design deviations matched by different displayed and processed dimensions based on the design deviation data of different displayed and processed dimensions, and using it as the number of deviation types; Determine the proportion of the planned production quantity of the dimension in the target design object based on the production plan data at the dimension, and use it as the production quantity proportion. Determine the design processing scheme at the dimension according to the number of deviation types of different display processing dimensions and the production quantity proportion at the dimension.

[0058] Furthermore, determining the design processing scheme at the dimension according to the number of deviation types of different display processing dimensions and the production quantity proportion at the dimension specifically includes: When there is a display processing dimension with the number of deviation types greater than the preset deviation type number threshold, use the first design processing scheme to determine the design processing schemes for all subsequent dimensions. When there is no display processing dimension with the number of deviation types greater than the preset deviation type number threshold, judge whether the production quantity proportion at the dimension is greater than the preset quantity proportion threshold. If so, use the first design processing scheme to determine the design processing scheme at the dimension. If not, use the second design processing scheme to determine the design processing scheme at the dimension.

[0059] Optionally, the method for determining the design processing scheme at the dimension is: S41 Determine the proportion of the planned production quantity of the dimension in the target design object based on the production plan data at the dimension, and use it as the production quantity proportion, and combine the number of reference design objects of the dimension belonging to the deviation design dimension to determine the deviation influence coefficient at the dimension. Optionally, before entering step S42, it is also necessary to sequentially judge whether the production quantity proportion at the dimension meets the requirements, whether the number of reference design objects of the dimension belonging to the deviation design dimension meets the requirements, and whether the deviation influence coefficient at the dimension meets the requirements. Specifically, it can be determined whether it meets the requirements in the way of a fixed threshold.

[0060] Specifically, when the production quantity proportion at the dimension is greater than the preset quantity proportion threshold, use the first design processing scheme to determine the design processing scheme at the dimension. And even when the production quantity proportion at the dimension is not greater than the preset quantity proportion threshold, it is still necessary to judge whether the number of reference design objects of the dimension belonging to the deviation design dimension meets the requirements. When the number of reference design objects of the dimension belonging to the deviation design dimension does not meet the requirements, directly determine to use the first design processing scheme to determine the design processing scheme at the dimension.

[0061] It can be understood that when the number of reference design objects whose dimensions belong to the deviation design dimensions meets the requirements, it is necessary to further determine whether the deviation influence coefficient under the dimension is greater than a fixed threshold. If so, directly determine the design processing scheme under the dimension by adopting the first design processing scheme. If not, when the deviation influence coefficient is within the preset influence coefficient range, it indicates that the deviation influence coefficient is small. At this time, the second design processing scheme is adopted to determine the design processing scheme under the dimension.

[0062] Specifically, when and only when the deviation influence coefficient is within the preset influence coefficient range, step S42 is entered.

[0063] S42 takes the dimensions that have been displayed and processed as the displayed and processed dimensions, determines the number of types of design deviations matching different displayed and processed dimensions based on the design deviation data of different displayed and processed dimensions, and takes it as the number of deviation types. According to the number of deviation types under different displayed and processed dimensions, the design deviation probability of the target design object is determined; It should be further noted that before entering step S43, it is also necessary to determine whether there are displayed and processed dimensions whose number of deviation types does not meet the requirements. In addition, it is also necessary to further determine whether the design deviation probability of the target design object meets the requirements. When there are displayed and processed dimensions whose number of deviation types does not meet the requirements or the design deviation probability of the target design object does not meet the requirements, directly determine the design processing scheme under the dimension by adopting the second design processing scheme.

[0064] Specifically, to determine whether it meets the requirements, a preset threshold method can be used.

[0065] When and only when all the above conditions are met, step S43 is entered.

[0066] S43 determines the abnormal influence coefficient under the dimension based on the deviation influence coefficient and the design deviation probability under the dimension, and determines the design processing scheme under the dimension based on the abnormal influence coefficient.

[0067] It should be further noted that when the abnormal influence coefficient under the dimension is greater than the preset influence coefficient threshold, the first design processing scheme is adopted to determine the design processing scheme under the dimension. If not, the second design processing scheme is adopted to determine the design processing scheme under the dimension.

[0068] It can be understood that the first design processing scheme is based on the clothing of the dimension, takes the median of the weight and height corresponding to the previous and next dimensions of the dimension as the endpoints of the design scheme, and equally divides within the range of the endpoints according to the preset number of schemes to obtain the divided endpoints, and takes the height and weight corresponding to the divided endpoints as the design scheme of the clothing of the dimension.

[0069] Specifically, for example, taking the median of the weight and height of the previous size and the median of the weight and height of the next size as endpoints, endpoint A and endpoint B are formed. Each endpoint has corresponding height and weight. The two endpoints are equally spaced according to the number of design schemes 2 to obtain endpoints C and D inside the endpoints after division. Based on the height and weight corresponding to endpoint A, point B, endpoint C, and endpoint D, the design scheme is determined.

[0070] Specifically, the second design processing scheme is to generate a design scheme only based on the median of the weight and height corresponding to the size under the size.

[0071] Specifically, for visual display processing, it specifically includes: Based on the design processing schemes under different sizes, design goals under different sizes are generated; Taking the weight and height corresponding to the design goal, the material data of the target design object under the size, and the cutting type as input quantities, using a convolutional neural network to automatically identify the detailed features of the clothing structure and folds, and generate a 3D model.

[0072] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for the embodiments of the device, equipment, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0073] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired results. Additionally, the processes depicted in the figures do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0074] The above is only one or more embodiments of this specification and is not used to limit this specification. For those skilled in the art, one or more embodiments of this specification can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A three-dimensional model visualization display method for clothing design based on an AI model, characterized in that, Specifically include: When obtaining the planned listing data of the target design object on different e-commerce platforms and combining the planned production data of the target design object, and determining that the target design object needs to consider size deviation data during design processing, proceed to the next step; Determine the reference design object of the target design object based on the material data and cutting types of the target design object in different clothing parts. According to the after-sales data and comment data corresponding to different reference design objects, determine the design deviation feedback data of different reference design objects at different sizes. Based on the design deviation feedback data, determine the deviation design sizes under different reference design objects; When determining that there is no target size according to the distribution data of the deviation design sizes of different sizes under different reference design objects, use the distribution data to determine the display processing order of different sizes. Utilize the design deviation data of different sizes that have been displayed and processed, and combine the planned production data of the sizes to determine the design processing solutions for future different sizes. Based on the design processing solutions, perform visual display processing using an AI model.

2. The three-dimensional model visualization display method of clothing design based on the AI model according to claim 1, wherein, The planned listing data includes the number of e-commerce platforms planned to be listed.

3. The three-dimensional model visualization display method for clothing design based on the AI model according to claim 1, characterized in that, The planned production data includes the planned production quantity of the target design object at different sizes.

4. The three-dimensional model visualization display method for clothing design based on an AI model according to claim 1, characterized in that, Determining that the target design object needs to consider size deviation data during design processing specifically includes: Based on the planned listing data of the target design object on different e-commerce platforms, determine the e-commerce platforms planned to be listed for the target design object and use it as the planned listing platform; According to the planned production data of the target design object, determine the planned production quantity of the target design object; Based on the number of the planned listing platforms and the planned production quantity, determine whether the target design object needs to consider size deviation data during design processing.

5. The three-dimensional model visualization display method for clothing design based on the AI model according to claim 1, characterized in that, The material data includes cotton, linen, silk, wool, man-made fiber, synthetic fiber, blended and functional fabrics, modal, and chiffon.

6. The three-dimensional model visualization display method of clothing design based on the AI model according to claim 1, characterized in that The reference design object is a historical design object that is consistent with the target design in terms of material data in different clothing parts and the deviation amounts of cutting sizes and cutting patterns are within the preset deviation amount range.

7. The three-dimensional model visualization display method of clothing design based on the AI model according to claim 1, characterized in that The types of design deviations include size design defects, structural imbalance, three-dimensional fitting deviation, symmetry and proportion imbalance.

8. The three-dimensional model visualization display method of clothing design based on the AI model according to claim 7, characterized in that, The design deviation feedback data includes the number of feedback users under different types of design deviations.

9. The three-dimensional model visualization display method of clothing design based on the AI model according to claim 1, characterized in that The method for determining the design processing solution for the size is: Take the sizes that have been displayed and processed as the displayed processing sizes. Based on the design deviation data of different displayed processing sizes, determine the number of types of design deviations matched by different displayed processing sizes and use it as the number of deviation types; Based on the production plan data of the size, determine the proportion of the planned production quantity of the size in the target design object and use it as the production quantity proportion; According to the number of deviation types of different displayed processing sizes and the production quantity proportion of the size, determine the design processing solution for the size.

10. The three-dimensional model visualization display method of clothing design based on the AI model according to claim 1, characterized in that, Performing visual display processing specifically includes: Based on the design processing solutions for different sizes, generate design targets for different sizes; Using the weight and height corresponding to the design target, the material data of the target design object at the said size, and the cutting type as input quantities, automatically identify the detailed features of the clothing structure and folds by means of a convolutional neural network to generate a 3D model.

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