A data analysis-based garment design simulation model evaluation system and method

Abstract

The application discloses a kind of clothing design simulation model evaluation system and method based on data analysis, belong to data analysis and computer simulation technical field.The application includes: obtaining the size data of user, generates user curve data set;According to the clothing information selected by user, the design data of the clothing selected by user is extracted, and the clothing design data is processed according to the clothing label, to generate simulation data set;Based on user curve data set, the clothing selected by user is processed by simulation model, simulates and generates the upper body diagram of clothing, and calculates the adaptation of each size of user and clothing;According to the adaptation calculation result, the clothing selection information of user is evaluated, and the selection behavior of user is tracked, and the tracking data is fed back.By simulation technology, the performance of clothing design when wearing by user is analyzed, the adaptability of clothing and user is evaluated, so that user can select appropriate clothing according to own demand, reduce the probability of return and exchange.

Description

Technical Field

[0001] This invention relates to the fields of data analysis and computer simulation technology, specifically to a data analysis-based evaluation system and method for clothing design simulation models. Background Technology

[0002] As consumer demand for high-quality apparel products grows, fashion designers need to respond more accurately to market changes, and advancements in information technology have driven the digital transformation of the apparel industry. The maturity of 3D design and simulation technologies has provided new tools and methods for apparel design.

[0003] When purchasing clothing online, e-commerce users typically rely on product displays and buyer reviews to understand how the clothing will look on them, and then select garments based on the sizes provided by the seller. However, when users choose clothing based on size and their imagined fit, the actual garment often doesn't match their expectations. Returns and exchanges waste significant human and material resources and negatively impact environmental sustainability.

[0004] In existing technologies, 3D modeling can be used to simulate the wearing effect of clothing in a virtual environment, helping e-commerce users preview how clothing will look on the human body. However, detailed 3D simulation requires a large amount of computing resources, and real-time rendering requires a long waiting time, affecting the user's simulation experience. When users use virtual models to simulate the effect of clothing, it is difficult to adjust the parameters of the virtual model according to personal data in order to protect privacy and security, resulting in insufficient personalization of the simulation.

[0005] Therefore, this invention provides a data analysis-based clothing design simulation model evaluation system and method, which uses simulation technology to analyze the performance of different sizes of clothing designs when worn by users, and evaluates the suitability of clothing to users. Summary of the Invention

[0006] The purpose of this invention is to provide a data analysis-based simulation model evaluation system and method for clothing design to solve the problems mentioned in the background art.

[0007] To address the aforementioned technical problems, this invention provides the following technical solution: a data analysis-based method for evaluating clothing design simulation models, the method comprising:

[0008] Step 1: Obtain the user's size data, process the user's size data, and generate the user's curve dataset;

[0009] Step 2: Based on the clothing information selected by the user, extract the design data of the selected clothing, process the clothing design data according to the clothing tags, and generate a simulation dataset.

[0010] Step 3: Based on the user curve dataset, process the clothing selected by the user through a simulation model, simulate and generate an upper body illustration of the clothing, and calculate the fit between the user and the clothing size.

[0011] Step 4: Track user selection behavior based on the fit calculation results and user evaluation feedback.

[0012] Furthermore, step one includes:

[0013] Step 1-1: Obtain the user's dimensional data and convert it into a three-dimensional model using computer-aided design software to generate a user body model; the user body model can represent the user's body shape and dimensional information;

[0014] Based on the user's body model, body curves are depicted. The depiction process is as follows:

[0015] Using the user's side profile as the front view, a frontal projection is performed on the user's body model to generate a two-dimensional plane of the user's body model. The midline of the user's body model is used as the horizontal axis to establish a two-dimensional coordinate system in the two-dimensional plane. n height nodes are marked on the midline in order from head to toe. The height nodes are used as the horizontal axis of the two-dimensional coordinate system to depict the edge curve of the two-dimensional plane, which is then used as the body curve.

[0016] Steps 1-2: Mark the peak points and valley points on the body curve. Use the valley points as curve segmentation points. Form curve segments between any two adjacent valley points, and each curve segment contains exactly one peak point. Number the valley points uniformly, and denote the curve segment formed between the a-th valley point and the (a+1)-th valley point as S. a Collect and generate a user curve dataset, denoted as S={S a |a∈[1,b]}, where b represents the total number of curve segments;

[0017] S a S represents the a-th curve segment of the user curve. a ={h a ,Q(h a )]|h a ∈[I a E a ]}; where h a Q(h) represents the height node number in the a-th curve segment. a ) represents the h-th user in the a-th curve segment. a The dimensional feature values ​​corresponding to each height node; I a E represents the starting height node corresponding to the a-th curve segment. aThis represents the termination height node corresponding to the a-th curve segment;

[0018] By identifying curve data in a user's body model, we can obtain information on how the user's dimensional features change with height.

[0019] Based on the above method, mapping virtual try-on onto a two-dimensional plane for analysis can greatly reduce the computational workload of computers, improve the response speed and efficiency of simulation, and more conveniently respond to users' clothing selection behavior, thereby enhancing the user's online clothing shopping experience.

[0020] Furthermore, step two includes:

[0021] Step 2-1: The clothing information includes clothing codes and clothing tags; based on the clothing information selected by the user, the clothing design data corresponding to the clothing codes stored in the database is extracted to the data processing center; the clothing tags are used to distinguish clothing types;

[0022] Step 2-2: Based on the clothing tag, obtain the clothing 3D model from the database. The clothing 3D model has a virtual try-on on a standard body model. Measure the area of ​​the clothing covering the standard body model in the virtual try-on state, and record the coordinates of the boundary position of the clothing coverage, which is recorded as the standard coverage area.

[0023] The standard body model is a standard reference model for computer-created virtual characters.

[0024] Steps 2-3: The data processing center uses computer software to convert the clothing design data into a simulation dataset, denoted as AD={f c |c∈[1,z]};where, f c The c-th size represents the clothing simulation range, and z represents the number of clothing sizes. The clothing simulation range represents the deformable range of the clothing length and width parameters during simulation, and the deformable range reflects the degree to which the length and width parameters of the clothing can be changed during simulation.

[0025] Furthermore, step three includes:

[0026] Step 3-1: Calculate the fit between the user and the clothing size using the following formula:

[0027] Step 3-1: Calculate the fit between the user and the clothing size using the following formula:

[0028] ;

[0029] Where SP(c) represents the fit between the user and the c-th size of the clothing; Cover(f c() indicates the standard coverage range of the c-th size of clothing; This represents the number of height nodes that overlap between the user's curve mapping range and the standard coverage range of the c-th size of clothing.

[0030] This represents a conditional function, where the h-th user in the a-th curve segment... a When the dimensional feature value corresponding to each height node belongs to the clothing simulation range corresponding to the c-th size =1; when the user's h-th segment in the a-th curve segment... a When the dimensional feature value corresponding to a height node does not belong to the clothing simulation range corresponding to the c-th size =0;

[0031] When SP(c)≥1, it means that the c-th size of the clothing meets the user's dimensional requirements; when SP(c)<1, it means that the c-th size of the clothing does not meet the user's dimensional requirements.

[0032] The evaluation results will be fed back to the user.

[0033] Based on the above methods, it is possible to fit the user's body curves to the clothing design. By analyzing the correspondence between the standard coverage of different clothing sizes and the user's dimensional characteristic values, the user's clothing size selection can be evaluated, helping the user to judge whether the clothing design can meet their own wearing needs based on their own dimensional characteristics.

[0034] Step 3-2: When the c-th size of the clothing meets the user's dimensional requirements, deform the 3D model of the clothing based on the user's curve dataset; map the 3D model of the clothing onto the user's body model, and set the point corresponding to the maximum value of the height node in the mapped area as the reference point;

[0035] The following formula is used to calculate the new coordinates of the reference point in the two-dimensional plane of the user's body model after the clothing model has been deformed, and their mapping value to the horizontal axis of the two-dimensional coordinate system:

[0036] ;

[0037] ;

[0038] Where △P(y) represents the degree of deformation of the garment; P new (y) represents the new coordinates of the reference point mapped to the horizontal axis in the two-dimensional coordinate system; L(f c ) represents the average length of the lower boundary of the standard coverage area corresponding to the c-th size; h I Indicates the starting height node of the curve within the clothing coverage area; h k This represents the height node corresponding to the highest point of the body curve within the area covered by the clothing.

[0039] Based on the new coordinates of the reference point after deformation and their mapping value on the horizontal axis of the two-dimensional coordinate system, the lower boundary of the garment after deformation can be determined. The upper body illustration of the garment is then generated through simulation engine simulation. Users can evaluate and provide feedback on the garment design based on the upper body illustration.

[0040] Based on the above methods, users can simulate the effect of clothing on their body by combining their body curves. Compared with the standard body model, the simulation model allows users to intuitively understand the visual length of the clothing design when they wear it, helping them to identify the length characteristics of the clothing design. This enables users to choose suitable clothing according to their own preferences and needs, reducing the probability of returns and exchanges.

[0041] Furthermore, step four includes:

[0042] Based on the user's clothing size fit calculation results and user evaluation feedback in step three, the user's clothing selection behavior is tracked. Steps two and three are repeated based on the clothing selected by the user and the corresponding size. The fit calculation results and user evaluation feedback corresponding to the tracked user clothing selection behavior are recorded.

[0043] A data analysis-based clothing design simulation model evaluation system, the system comprising: a user interaction data acquisition module, a clothing data analysis module, an intelligent simulation module, and an evaluation feedback module;

[0044] The user interaction data acquisition module is used to acquire the user's size data, process the user's size data, and generate a user curve dataset.

[0045] The clothing data analysis module is used to extract the design data of the clothing selected by the user based on the clothing information selected by the user, process the clothing design data according to the clothing tags, and generate a simulation dataset.

[0046] The intelligent simulation module is based on the user curve dataset. It processes the clothing selected by the user through a simulation model, simulates and generates an upper body illustration of the clothing, and calculates the fit between the user and each size of the clothing.

[0047] The evaluation feedback module is used to track the user's selection behavior based on the user's fit with clothing size calculation results and the user's evaluation feedback, and to record the tracking data.

[0048] Furthermore, the user interaction data acquisition module includes a user authorization unit, a data acquisition unit, and a user data processing unit;

[0049] The user authorization unit is used to control data access according to user permissions;

[0050] The data acquisition unit is used to acquire the user's size data and convert the user's size data into a three-dimensional model using computer-aided design software to generate a user body model.

[0051] The user data processing unit delineates body curves based on the user's body model and marks peak points and valley points in the body curves. Valley points are used as curve segmentation points, and curve segments are formed between any two adjacent valley points. Each curve segment contains one and only one peak point.

[0052] Furthermore, the clothing data analysis module includes a clothing design data extraction unit, a data processing center, and a clothing design data processing unit;

[0053] The clothing design data extraction unit is used to extract the clothing design data corresponding to the clothing codes stored in the database to the data processing center based on the clothing information selected by the user; the clothing tags are used to distinguish clothing types.

[0054] The data processing center uses computer software to transform clothing design data into simulation datasets.

[0055] The clothing design data processing unit measures the area of ​​the standard body model covered by the clothing under virtual try-on conditions based on the clothing label, and records the coordinates of the boundary position of the clothing coverage, which is denoted as the standard coverage area.

[0056] Furthermore, the intelligent simulation module includes a simulation model processing unit and an adaptation analysis unit;

[0057] The simulation model processing unit deforms the 3D clothing model based on the user curve dataset; maps the 3D clothing model onto the user's body model, and sets the point corresponding to the maximum value of the height node in the mapping area as the reference point; according to the new coordinates of the reference point after deformation and the horizontal axis mapping value in the two-dimensional coordinate system, the lower boundary of the clothing after deformation can be determined, and the upper body illustration of the clothing can be generated through simulation engine.

[0058] The fit analysis unit is used to analyze the fit between users and clothing sizes based on the user curve dataset and the output data of the clothing data analysis module.

[0059] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0060] This invention provides a more efficient, personalized, and user-friendly simulation and evaluation system and method for clothing design, which helps improve user satisfaction and brings a competitive advantage to clothing designers and brands.

[0061] This invention acquires and processes user size data to generate user-specific curve datasets, which can more accurately reflect the user's body characteristics and help the user choose the most suitable clothing size. Based on the clothing information selected by the user, design data is extracted and processed to generate simulation datasets, which can more vividly simulate the effect of clothing on the user and improve the realism of clothing design.

[0062] This invention uses a simulation model to generate the effect of clothing on a user's body model and calculates the fit between the user and the clothing size. Based on the evaluation data of the fit calculation results, suggestions are made to the user. Since users can preview the effect of the clothing before purchasing and choose the clothing that best suits their size, returns and exchanges caused by online size ambiguity can be significantly reduced, the situation of clothing not fitting after purchase can be reduced, and resource consumption can be avoided.

[0063] The user interaction design of this invention allows users to provide feedback on clothing and tracks user selection behavior, enhancing the user experience of selecting clothing online. At the same time, it provides merchants with intuitive feedback information, which can help them improve clothing design and simulation processes. Attached Figure Description

[0064] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0065] Figure 1 This is a schematic diagram of the structure of a data analysis-based clothing design simulation model evaluation system according to the present invention;

[0066] Figure 2 This is a flowchart illustrating a data analysis-based method for evaluating clothing design simulation models according to the present invention. Detailed Implementation

[0067] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0068] Please see Figure 1 In this first embodiment: a data analysis-based clothing design simulation model evaluation system is provided, the system including: a user interaction data acquisition module, a clothing data analysis module, an intelligent simulation module and an evaluation feedback module;

[0069] The user interaction data acquisition module is used to acquire user size data, process the user size data, and generate user curve datasets; it includes a user authorization unit, a data acquisition unit, and a user data processing unit.

[0070] The user authorization unit is used to control data access based on user permissions;

[0071] The data acquisition unit is used to acquire the user's dimensional data and convert the user's dimensional data into a three-dimensional model through computer-aided design software to generate the user's body model.

[0072] The user data processing unit, based on the user's body model, depicts body curves and marks peak points and valley points in the body curves. The valley points are used as curve segmentation points, and curve segments are formed between any two adjacent valley points. Each curve segment contains one and only one peak point.

[0073] The clothing data analysis module is used to extract the design data of the clothing selected by the user based on the clothing information selected by the user, process the clothing design data according to the clothing tags, and generate a simulation dataset; it includes a clothing design data extraction unit, a data processing center, and a clothing design data processing unit.

[0074] The clothing design data extraction unit is used to extract the clothing design data corresponding to the clothing codes stored in the database to the data processing center based on the clothing information selected by the user; clothing tags are used to distinguish clothing types.

[0075] The data processing center uses computer software to transform clothing design data into simulation datasets;

[0076] The clothing design data processing unit measures the area of ​​the standard body model covered by the clothing under virtual try-on conditions based on clothing tags, and records the coordinates of the boundary position of the clothing coverage, which is recorded as the standard coverage area.

[0077] The intelligent simulation module is based on the user curve dataset. It processes the clothing selected by the user through a simulation model, simulates and generates an upper body illustration of the clothing, and calculates the fit between the user and each size of the clothing. It includes a simulation model processing unit and a fit analysis unit.

[0078] The simulation model processing unit deforms the 3D model of clothing based on the user curve dataset; it maps the 3D model of clothing onto the user's body model, and sets the point corresponding to the maximum value of the height node in the mapping area as the reference point; based on the new coordinates of the reference point after deformation and the horizontal axis mapping value in the two-dimensional coordinate system, the lower boundary of the clothing after deformation can be determined, and the upper body illustration of the clothing can be generated through simulation engine.

[0079] The fit analysis unit is used to analyze the fit between users and clothing sizes based on the user curve dataset and the output data of the clothing data analysis module.

[0080] The evaluation and feedback module is used to track user selection behavior based on the user's fit with clothing size calculation results and user evaluation feedback, and to record the tracking data.

[0081] Please see Figure 2 Example 2 provides a data analysis-based method for evaluating clothing design simulation models, including:

[0082] Step 1: Apply for user permission, obtain the user's size data, process the user's size data, and generate the user's curve dataset;

[0083] Step 1-1: After obtaining user authorization, acquire the user's size data through user input or scanning using a terminal, and convert the user's size data into a three-dimensional model using computer-aided design software to generate a user body model; the user body model can represent the user's body shape and size information;

[0084] In one implementation, the user selects a body model provided by the merchant and uses the body model data that best matches their own characteristics as the size data.

[0085] Based on the user's body model, body curves are depicted. The depiction process is as follows:

[0086] Using the user's side profile as the front view, project the user's body model onto the front view to generate a two-dimensional plane of the user's body model. Use the midline of the user's body model as the horizontal axis to establish a two-dimensional coordinate system in the two-dimensional plane. Mark n height nodes on the midline in order from head to toe. Use the height nodes as the horizontal axis of the two-dimensional coordinate system to depict the edge curve of the two-dimensional plane and use it as the body curve.

[0087] Steps 1-2: Mark the peak and trough points on the body curve. Use the trough points as curve segmentation points. Form curve segments between any two adjacent trough points, and each curve segment contains exactly one peak point. Number the trough points uniformly, and denote the curve segment formed between the a-th trough point and the (a+1)-th trough point as S. a Collect and generate a user curve dataset, denoted as S={S a |a∈[1,b]}, where b represents the total number of curve segments;

[0088] S a S represents the a-th curve segment of the user curve. a ={h a ,Q(h a )]|ha ∈[I a E a ]}; where h a Q(h) represents the height node number in the a-th curve segment. a ) represents the h-th user in the a-th curve segment. a The dimensional feature values ​​corresponding to each height node; I a E represents the starting height node corresponding to the a-th curve segment. a This represents the termination height node corresponding to the a-th curve segment;

[0089] It should be noted that this invention mainly analyzes the torso features of the user's body. The design complexity of the user body model is relatively low, and precise details are not required for model control and rendering. Therefore, when identifying the surface curves of the user body model in the above steps, it is only necessary to identify the curves of key parts that can reflect the user's body features. This reduces the workload of the computer software and improves the response rate of the user body model.

[0090] By identifying curve data in a user's body model, we can obtain information on how the user's dimensional features change with height.

[0091] Step 2: Based on the clothing information selected by the user, extract the design data of the selected clothing, process the clothing design data according to the clothing tags, and generate a simulation dataset.

[0092] Step 2-1: Clothing information includes clothing codes and clothing tags; based on the clothing information selected by the user, the clothing design data corresponding to the clothing codes stored in the database is extracted to the data processing center; clothing tags are used to distinguish clothing types; for example, clothing types can be tops, bottoms, jumpsuits, and suits;

[0093] Step 2-2: Based on the clothing tag, obtain the clothing 3D model from the database. The clothing 3D model has a virtual try-on on the standard body model. Measure the area of ​​the clothing covering the standard body model in the virtual try-on state, record the coordinates of the boundary position of the clothing coverage, and record it as the standard coverage area.

[0094] The standard body model is a standard reference model for computer-created virtual characters;

[0095] Steps 2-3: The data processing center uses computer software to convert the clothing design data into a simulation dataset, denoted as AD={f c |c∈[1,z]};where, f cThis represents the simulation range of the garment corresponding to the c-th size, and z represents the number of garment sizes. Garment sizes include S, M, L, XL, etc. The garment simulation range represents the deformable range of the garment's length and width parameters during simulation. The deformable range reflects the degree to which the length and width parameters of the garment can be changed during simulation.

[0096] Optionally, physical properties of the clothing, such as fabric elasticity, can be defined in the 3D model of the clothing.

[0097] Step 3: Based on the user curve dataset, process the clothing selected by the user through a simulation model, simulate and generate an upper body illustration of the clothing, and calculate the fit between the user and the clothing size.

[0098] Step 3-1: Calculate the fit between the user and the clothing size using the following formula:

[0099] ;

[0100] Where SP(c) represents the fit between the user and the c-th size of the clothing; Cover(fc) represents the standard coverage range of the c-th size of the clothing. This represents the number of height nodes that overlap between the user's curve mapping range and the standard coverage range of the c-th size of clothing.

[0101] This represents a conditional function, which states that when the dimensional feature value corresponding to the user's height node in the a-th curve segment falls within the simulation range of the clothing size corresponding to the c-th size... =1; when the dimensional feature value corresponding to the user's ha-th height node in the a-th curve segment does not belong to the clothing simulation range corresponding to the c-th size. =0;

[0102] When SP(c)≥1, it means that the c-th size of the clothing meets the user's dimensional requirements; when SP(c)<1, it means that the c-th size of the clothing does not meet the user's dimensional requirements.

[0103] The evaluation results will be fed back to the user.

[0104] Based on the above methods, it is possible to fit the user's body curves to the clothing design. By analyzing the correspondence between the standard coverage of different clothing sizes and the user's dimensional characteristic values, the user's clothing size selection can be evaluated, helping the user to judge whether the clothing design can meet their own wearing needs based on their own dimensional characteristics.

[0105] Step 3-2: When the c-th size of the clothing meets the user's dimensional requirements, deform the 3D model of the clothing based on the user's curve dataset; map the 3D model of the clothing onto the user's body model, and set the point corresponding to the maximum value of the height node in the mapped area as the reference point;

[0106] The following formula is used to calculate the new coordinates of the reference point in the two-dimensional plane of the user's body model after the clothing model has been deformed, and their mapping value to the horizontal axis of the two-dimensional coordinate system:

[0107] ;

[0108] ;

[0109] Where △P(y) represents the degree of deformation of the garment; P new (y) represents the new coordinates of the reference point mapped to the horizontal axis in the two-dimensional coordinate system; L(f c ) represents the average length of the lower boundary of the standard coverage area corresponding to the c-th size; h I Indicates the starting height node of the curve within the clothing coverage area; h k This represents the height node corresponding to the highest point of the body curve within the area covered by the clothing.

[0110] Based on the new coordinates of the reference point after deformation and their mapping value on the horizontal axis of the two-dimensional coordinate system, the lower boundary of the garment after deformation can be determined. The upper body illustration of the garment is then generated through simulation engine simulation. Users can evaluate and provide feedback on the garment design based on the upper body illustration.

[0111] Based on the above methods, users can simulate the effect of clothing on their body by combining their body curves. Compared with the standard body model, the simulation model allows users to intuitively understand the visual length of the clothing design when they wear it, helping them to identify the length characteristics of the clothing design. This enables users to choose suitable clothing according to their own preferences and needs, reducing the probability of returns and exchanges.

[0112] Step 4: Based on the user's clothing size fit calculation results and user evaluation feedback in Step 3, track the user's clothing selection behavior. Repeat Step 2 and Step 3 according to the clothing selected by the user and the corresponding size, and record the fit calculation results and user evaluation feedback corresponding to the tracked user clothing selection behavior.

[0113] Optionally, based on the fit calculation results, for cases that do not meet the user's needs, the evaluation reasons for the non-compliance are fed back to the user, prompting the user to select reference data when choosing clothing designs;

[0114] Optionally, track users' clothing purchase and return / exchange behavior, and use the user's final purchase results to reverse-engineer the relevant data of the user's body model to update the user's body model in step one.

[0115] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0116] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A data analysis-based method for evaluating clothing design simulation models, characterized in that, The method includes: Step 1: Obtain the user's size data, process the user's size data, and generate the user's curve dataset; Step 2: Based on the clothing information selected by the user, extract the design data of the selected clothing, process the clothing design data according to the clothing tags, and generate a simulation dataset. Step 3: Based on the user curve dataset, process the clothing selected by the user through a simulation model, simulate and generate an upper body illustration of the clothing, and calculate the fit between the user and the clothing size. Step 4: Track user selection behavior based on the fit calculation results and user evaluation feedback; Step three includes: Step 3-1: Calculate the fit between the user and the clothing size using the following formula: Where SP(c) represents the fit between the user and the c-th size of the clothing; Cover(f c () indicates the standard coverage range of the c-th size of clothing; This represents the number of height nodes that overlap between the user's curve mapping range and the standard coverage range of the c-th size of clothing. This represents a conditional function, where the h-th user in the a-th curve segment... a When the dimensional feature value corresponding to each height node belongs to the clothing simulation range corresponding to the c-th size =1; when the user's h-th segment in the a-th curve segment... a When the dimensional feature value corresponding to a height node does not belong to the clothing simulation range corresponding to the c-th size When SP(c)≥1, it means that the c-th size of the clothing meets the user's dimensional requirements; when SP(c)<1, it means that the c-th size of the clothing does not meet the user's dimensional requirements. Step 3-2: When the c-th size of the clothing meets the user's dimensional requirements, deform the 3D model of the clothing based on the user's curve dataset; map the 3D model of the clothing onto the user's body model, and set the point corresponding to the maximum value of the height node in the mapped area as the reference point; The following formula is used to calculate the new coordinates of the reference point in the two-dimensional plane of the user's body model after the clothing model has been deformed, and their mapping value to the horizontal axis of the two-dimensional coordinate system: ; Where △P(y) represents the degree of deformation of the garment; P new (y) represents the new coordinates of the reference point mapped to the horizontal axis in the two-dimensional coordinate system; L(f c ) represents the average length of the lower boundary of the standard coverage area corresponding to the c-th size; h I Indicates the starting height node of the curve within the clothing coverage area; h k This represents the height node corresponding to the highest point of the body curve within the area covered by the clothing. Based on the new coordinates of the reference point after deformation and their horizontal axis mapping values ​​in the two-dimensional coordinate system, a simulation engine generates an upper body illustration of the garment; users then evaluate and provide feedback on the garment design based on this upper body illustration.

2. The method for evaluating a clothing design simulation model based on data analysis according to claim 1, characterized in that, Step one includes: Step 1-1: Obtain the user's size data and use computer-aided design software to convert the user's size data into a three-dimensional model to generate the user's body model; Based on the user's body model, body curves are depicted. The depiction process is as follows: Using the user's side profile as the front view, a frontal projection is performed on the user's body model to generate a two-dimensional plane of the user's body model. The midline of the user's body model is used as the horizontal axis to establish a two-dimensional coordinate system in the two-dimensional plane. n height nodes are marked on the midline in order from head to toe. The height nodes are used as the horizontal axis of the two-dimensional coordinate system to depict the edge curve of the two-dimensional plane, which is then used as the body curve. Steps 1-2: Mark the peak points and valley points on the body curve. Use the valley points as curve segmentation points. Form curve segments between any two adjacent valley points, and each curve segment contains exactly one peak point. Number the valley points uniformly, and denote the curve segment formed between the a-th valley point and the (a+1)-th valley point as S. a Collect and generate a user curve dataset, denoted as S={S a |a∈[1,b]}, where b represents the total number of curve segments; S a S represents the a-th curve segment of the user curve. a ={h a ,Q(h a )]|h a ∈[I a E a ]}; where h a Q(h) represents the height node number in the a-th curve segment. a ) represents the h-th user in the a-th curve segment. a The dimensional feature values ​​corresponding to each height node; I a E represents the starting height node corresponding to the a-th curve segment. a This represents the termination height node corresponding to the a-th curve segment.

3. The method for evaluating a clothing design simulation model based on data analysis according to claim 1, characterized in that, Step two includes: Step 2-1: The clothing information includes clothing codes and clothing tags; based on the clothing information selected by the user, the clothing design data corresponding to the clothing codes stored in the database is extracted to the data processing center; the clothing tags are used to distinguish clothing types; Step 2-2: Based on the clothing tag, obtain the clothing 3D model from the database. The clothing 3D model has a virtual try-on on a standard body model. Measure the area of ​​the clothing covering the standard body model in the virtual try-on state, and record the coordinates of the boundary position of the clothing coverage, which is recorded as the standard coverage area. Steps 2-3: The data processing center uses computer software to convert the clothing design data into a simulation dataset, denoted as AD={f c |c∈[1,z]};where, f c This represents the simulated range of clothing corresponding to the c-th size, and z represents the number of clothing sizes.

4. The method for evaluating a clothing design simulation model based on data analysis according to claim 1, characterized in that, Step four includes: Based on the user's clothing size fit calculation results and user evaluation feedback in step three, the user's clothing selection behavior is tracked. Steps two and three are repeated based on the clothing selected by the user and the corresponding size. The fit calculation results and user evaluation feedback corresponding to the tracked user clothing selection behavior are recorded.

5. A data analysis-based clothing design simulation model evaluation system, executing the data analysis-based clothing design simulation model evaluation method as described in any one of claims 1-4, characterized in that, The system includes: a user interaction data acquisition module, a clothing data analysis module, an intelligent simulation module, and an evaluation feedback module; The user interaction data acquisition module is used to acquire the user's size data, process the user's size data, and generate a user curve dataset. The clothing data analysis module is used to extract the design data of the clothing selected by the user based on the clothing information selected by the user, process the clothing design data according to the clothing tags, and generate a simulation dataset. The intelligent simulation module is based on the user curve dataset. It processes the clothing selected by the user through a simulation model, simulates and generates an upper body illustration of the clothing, and calculates the fit between the user and each size of the clothing. The evaluation feedback module is used to track the user's selection behavior based on the user's fit with clothing size calculation results and the user's evaluation feedback, and to record the tracking data.

6. The data analysis-based clothing design simulation model evaluation system according to claim 5, characterized in that: The user interaction data acquisition module includes a user authorization unit, a data acquisition unit, and a user data processing unit; The user authorization unit is used to control data access according to user permissions; The data acquisition unit is used to acquire the user's size data and convert the user's size data into a three-dimensional model using computer-aided design software to generate a user body model. The user data processing unit delineates body curves based on the user's body model and marks peak points and valley points in the body curves. Valley points are used as curve segmentation points, and curve segments are formed between any two adjacent valley points. Each curve segment contains one and only one peak point.

7. The data analysis-based clothing design simulation model evaluation system according to claim 5, characterized in that: The apparel data analysis module includes an apparel design data extraction unit, a data processing center, and an apparel design data processing unit. The clothing design data extraction unit is used to extract the clothing design data corresponding to the clothing codes stored in the database to the data processing center based on the clothing information selected by the user. The clothing label is used to distinguish clothing types; The data processing center uses computer software to transform clothing design data into simulation datasets. The clothing design data processing unit measures the area of ​​the standard body model covered by the clothing under virtual try-on conditions based on the clothing label, and records the coordinates of the boundary position of the clothing coverage, which is denoted as the standard coverage area.

8. The data analysis-based clothing design simulation model evaluation system according to claim 5, characterized in that: The intelligent simulation module includes a simulation model processing unit and an adaptation analysis unit; The simulation model processing unit deforms the clothing 3D model based on the user curve dataset; it maps the clothing 3D model onto the user body model, and sets the point corresponding to the maximum value of the height node in the mapping area as the reference point. Based on the horizontal axis mapping value of the new coordinates of the reference point after deformation in the two-dimensional coordinate system, the upper body illustration of the clothing is generated by simulation engine. The fit analysis unit is used to analyze the fit between users and clothing sizes based on the user curve dataset and the output data of the clothing data analysis module.

Images