Clothing customization design system and method based on AI body shape data analysis

Abstract

The application discloses a clothing customization design system and method based on AI body shape data analysis, relates to the technical field of data processing, carries out user customized girth basic evaluation based on user girth body shape data, generates clothing design schemes of each part of the user in each scene according to the user customized girth basic evaluation result, carries out clothing design scheme adjustment evaluation based on muscle change data and activity data of each part, judges whether the clothing design scheme needs to be adjusted based on the clothing design scheme adjustment evaluation result, outputs each part needing adjustment in each scene of the user according to the clothing design scheme adjustment evaluation judgment result, carries out clothing customization design according to different conditions of each part of the user in each scene, adapts to different scenes and demands, ensures that clothing does not limit movement while showing personal style, and improves user wearing comfort and long-term use experience.

Description

Technical Field

[0001] This application belongs to the field of data processing, specifically a clothing customization design system and method based on AI body shape data analysis. Background Art

[0002] Customized clothing design is a way of designing clothing that is tailored to the user's personal needs and preferences. Compared with traditional standardized clothing design, customized design has the advantages of uniqueness, individuality, perfect fit and comfort. It is an important way for many people to pursue a high quality of life.

[0003] The current customized clothing design is designed by designers based on the user's body shape and style. It not only makes the user more comfortable to wear, but also incorporates some fashion elements to ensure that the user has a unique wearing experience, improves the overall image, shows personal style, and provides more personalized choices.

[0004] However, the following problems still exist in the current clothing customization design:

[0005] Single data dimension: Traditional methods only use simple indices such as weight divided by height to assess user body shape. This method lacks quantitative analysis of the user's muscle dynamics and joint mobility, resulting in poor clothing adaptability in different scenarios.

[0006] Fragmented evaluation standards: Existing technologies rely on establishing a correlation model between circumference data and functional requirements, resulting in customized clothing designs failing to meet both aesthetic and freedom of movement requirements.

[0007] In order to solve the problems raised by this background technology, this application designs a clothing customization design system and method based on AI body shape data analysis. Summary of the Invention

[0008] In response to the above-mentioned technical deficiencies, this application proposes a clothing customization design system and method based on AI body shape data analysis.

[0009] To solve the above technical problems, the present invention adopts the following technical solution: This application provides a clothing customization design method based on AI body shape data analysis, which includes the following specific steps:

[0010] S1. Obtaining the user's body circumference data, muscle changes in various parts of the body, and activity data of various parts of the body;

[0011] S2. Performing a user-customized girth basic assessment based on the user's girth body data, and generating a clothing design plan for each part of the user in each scenario based on the user's customized girth basic assessment results;

[0012] S3. Based on the muscle change data and activity data of each part, adjust and evaluate the clothing design scheme of each part in each scenario of the user;

[0013] S4. Based on the evaluation results of the clothing design scheme adjustment for each part of the user in each scene, determine whether the clothing design scheme for each part of the user in each scene needs to be adjusted, and output the parts of the user that need to be adjusted in each scene according to the evaluation judgment results of the clothing design scheme adjustment for each part of the user in each scene.

[0014] It should be noted that, as a preferred technical solution for the clothing customization design method based on AI body shape data analysis, the specific steps of S1 are:

[0015] S11. Acquire the user's body circumference data through three-dimensional scanning, wherein the user's body circumference data includes the user's chest circumference data, waist circumference data, and hip circumference data;

[0016] S12. Obtaining muscle change data of various parts of the user through ultrasonic testing and three-dimensional motion capture, wherein the muscle change data of various parts of the user includes strain rate data and size change data of various muscle groups of the user in various scenarios;

[0017] S13. Acquire activity data of various parts of the user through a surface electromyography system and an inertial sensor system, wherein the activity data of various parts of the user include activity degree data of various muscle groups in various scenes of the user and joint activity angle data corresponding to various muscle groups in various scenes of the user;

[0018] S14. Storing the collected data in a storage component for use in the analysis process.

[0019] It should be noted that, as a preferred technical solution for the clothing customization design method based on AI body shape data analysis, S2 includes the following specific steps:

[0020] S21. Perform a user-customized girth basic assessment based on the user's girth body data, wherein the user-customized girth basic assessment value calculation formula is: , where X is the user's chest circumference, Y is the user's waist circumference, H is the user's hip circumference, and W is the standard latitude value. is the waist circumference weight, is the weight of hip circumference. It should be noted that in this formula Part of the evaluation is done by quantifying the user's three measurements to assess the user's customized girth basic evaluation value. Partially evaluate the adaptability of the user's clothing design plan to the user's actual circumference by the degree of deviation between the user's three measurements and the standard body circumference;

[0021] S22. Obtain the calculated user-customized basic girth evaluation value, and generate a clothing design plan for each part of the user in each scenario according to the user-customized basic girth evaluation value.

[0022] It should be noted that, as a preferred technical solution for the clothing customization design method based on AI body shape data analysis, the specific steps of S3 are:

[0023] S31, obtaining an impact assessment value of muscle changes at each part of the user in each scenario based on the strain rate data and size change data of each part of the user's muscle group in each scenario;

[0024] S32, obtaining an activity comfort evaluation value for each part of the user in each scenario based on the activity degree data of each muscle group in each part of the user and the joint activity angle data corresponding to each muscle group in each scenario;

[0025] S33. Weightedly add the muscle change impact assessment values ​​and activity comfort assessment values ​​of each part of the user in each scenario to obtain the clothing design adjustment assessment values ​​of each part of the user in each scenario.

[0026] It should be noted that, as a preferred technical solution for the clothing customization design method based on AI body shape data analysis, the specific steps of S31 are:

[0027] S311. Based on the strain rate data and size change data of each muscle group in each scene of the user, the change amount of each part of the human body muscle in each scene of the user is evaluated. The calculation formula of the change amount of the evaluation value of the j-th part of the human body muscle in the i-th scene of the user is: , where i is the number corresponding to each scene, i is any item from 1 to N, j is the number corresponding to each part of the user, j is any item from 1 to M, is the strain rate corresponding to the j-th muscle group of the user, As a reference to the human body strain rate, is the weight of the jth muscle group in the user's i-th scene, is the actual size change data of the jth muscle group of the human body in the i-th scenario of the user, is the ideal size change of the jth muscle group of the human body in the i-th scenario. It should be noted that in this formula, The purpose of setting is to evaluate the elasticity of the user's muscle groups by the rate of change of deformation of the user's muscle groups in unit time. The purpose of setting is to evaluate the elasticity of the user's muscle group by comparing the actual elasticity of the user's muscle group with the reference elasticity. The purpose of setting is to evaluate the relative importance of the elasticity and size change of each muscle group in a specific scenario. The purpose of some settings is to measure the gap between the actual change state and the ideal change state of muscle groups in various parts of the human body in various scenarios of the user through the ratio between the actual change data of muscle groups in various parts of the human body in various scenarios of the user and the ideal change data of muscle groups in various parts of the human body in various scenarios of the user. This formula comprehensively evaluates the impact of the change of muscle groups in various parts of the user in various scenarios on the customized design of clothing through the elasticity of muscle groups in various parts of the user and the change state of muscle groups in various scenarios of the user. When the evaluation value of the change amount of muscle groups in various parts of the human body in various scenarios of the user is larger, that is, the closer the degree of muscle change of the user is to the ideal value, the customized design of clothing for that part of the user in that scenario does not need to be adjusted;

[0028] S312: Obtain the evaluation results of the amount of muscle changes in each part of the user's body in each scenario, and evaluate the impact of the muscle changes in each part of the user in each scenario based on the evaluation results of the amount of muscle changes in each part of the user in each scenario. The evaluation formula for the impact of the muscle change in the jth part of the user in the i-th scenario is: ,in, is the distance between the jth part of the user and its adjacent parts, is the change in the evaluation value of the muscle change of the jth part of the user in the i-th scenario, is the reference value of the muscle change of the user's jth part. It should be noted that in this formula The influence of the muscle change evaluation value of each part of the user's body on its adjacent parts in each scene is evaluated by integrating the changes in the distance between the user's body muscle change evaluation value and its adjacent parts in each scene and then calculating the average value. The influence of the muscle changes of each part of the user on other adjacent parts in each scene is obtained by summing up the influence of the muscle changes of each part of the user on its adjacent parts in each scene. By comparing the impact value of the human muscle changes in each part of the user in each scenario on other adjacent parts with the evaluation value of the reference human muscle changes in each part of the user, the importance of the impact of the human muscle changes in each part of the user in each scenario on its adjacent parts is evaluated.

[0029] It should be noted that, as a preferred technical solution for the clothing customization design method based on AI body shape data analysis, the specific steps of S32 are: based on the activity degree data of each muscle group of each part of the user in each scene and the joint activity angle data corresponding to each muscle group of each part of the user in each scene, the user's activity comfort evaluation of each part in each scene is performed, wherein the calculation formula for the activity comfort evaluation value of the jth part of the user in the i-th scene is: ,in, is the joint motion angle corresponding to the j-th muscle group in the user's i-th scene, The joint movement angle allowed by the clothing corresponding to the j-th muscle group in the user's i-th scene, is the maximum value of the human joint motion angle corresponding to the j-th muscle group of the user, is the muscle activity intensity corresponding to the j-th muscle group in the user's i-th scenario, is the clothing pressure corresponding to the jth muscle group in the user's i-th scene, is the muscle tolerance threshold corresponding to the j-th muscle group of the user, is the weight of the joint activity of the jth muscle group in the user's i-th scene. It should be noted that in this formula, The limitation of the joint movement angles of the muscle groups in each scene and the joint movement angles allowed by the clothing are expressed in part by the joint movement angles of the muscle groups in each scene and the joint movement angles allowed by the clothing. It is the limit value of joint movement angle corresponding to muscle groups in various parts of the human body. Part of it is to directly reflect the activity restriction rate of each joint of the user in each scenario by calculating the ratio of the restricted angle of the user's joint to the total activity potential of the user's joint. The activity restriction rate of each part of the user in each scene is converted into the freedom of movement of each part of the user in each scene. The meaning is to make the value positively correlated with the activity comfort evaluation value. That is, the larger the freedom of movement value, the smaller the impact of the clothing on joint movement, and the larger the activity comfort evaluation value. In this formula, Reflects the degree of muscle fiber activation when the user's muscle groups exercise in various scenarios. Reflects the vertical pressure exerted on the muscles by the clothing corresponding to each muscle group in each scene. Reflects the physiological stress limit of each muscle group. The actual mechanical load of each muscle group in each scene of the user is represented by the product of the muscle activity intensity corresponding to each muscle group in each scene of the user and the pressure of the clothing. The risk value of the activity intensity of each muscle group in each scenario of the user is reflected in part by the ratio of the actual mechanical load corresponding to each muscle group in each scenario of the user and the physiological stress limit of each muscle group. The purpose of is to negatively correlate the activity intensity risk value of each muscle group in each scene with the activity comfort evaluation value result of the user, that is, The smaller the portion, The larger the portion, the greater the activity comfort assessment value.

[0030] It should be noted that, as the preferred technical solution of the clothing customization design method based on AI body data analysis, the specific steps of S4 are: obtaining the clothing design scheme adjustment evaluation value of each part of the user in each scenario, and comparing the clothing design scheme adjustment evaluation value of each part of the user in each scenario with the set clothing design scheme adjustment evaluation value threshold. If the clothing design scheme adjustment evaluation value of a certain part of the user in a certain scenario is greater than or equal to the set clothing design scheme adjustment evaluation value threshold, it is judged that the clothing design scheme of the part in the scenario does not need to be adjusted; if the clothing design scheme adjustment evaluation value of a certain part of the user in a certain scenario is less than the set clothing design scheme adjustment evaluation value threshold, it is judged that the clothing design scheme of the part in the scenario needs to be adjusted.

[0031] A clothing customization design system based on AI body shape data analysis is implemented based on the above-mentioned clothing customization design method based on AI body shape data analysis. It specifically includes a user body shape data acquisition module, a basic plan generation module, a plan adjustment analysis module, and a customized design execution module. The user body shape data acquisition module is used to obtain the user's circumference body shape data, muscle change data of each part, and activity data of each part;

[0032] The basic scheme generation module is used to perform a user-customized girth basic assessment based on the user's girth body data, and generate a clothing design scheme for each part of the user in each scenario according to the user's customized girth basic assessment result;

[0033] The scheme adjustment analysis module is used to evaluate the adjustment of clothing design schemes for each part of the user in each scenario based on the muscle change data and the activity data of each part;

[0034] The customized design execution module is used to judge whether the clothing design schemes of each part of the user in each scenario need to be adjusted based on the evaluation results of the clothing design schemes of each part of the user in each scenario, and output the parts of the user that need to be adjusted in each scenario according to the evaluation judgment results of the clothing design schemes of each part of the user in each scenario.

[0035] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0036] The processor executes the above-mentioned clothing customization design method based on AI body shape data analysis by calling the computer program stored in the memory.

[0037] A computer-readable storage medium stores instructions. When the instructions are executed on a computer, the computer executes the above-mentioned clothing customization design method based on AI body shape data analysis.

[0038] Compared with the prior art, the beneficial effects of the present invention are: the present invention obtains the user's circumference body shape data, muscle change data of various parts and activity data of various parts; performs a user-customized circumference basic assessment based on the user's circumference body shape data, and generates a clothing design scheme for each part of the user in each scenario according to the user's customized circumference basic assessment result; performs an adjustment assessment of the clothing design scheme for each part of the user in each scenario based on the muscle change data of each part and the activity data of each part; judges whether the clothing design scheme for each part of the user in each scenario needs to be adjusted based on the adjustment assessment result of the clothing design scheme for each part of the user in each scenario, outputs the parts that need to be adjusted in each scenario of the user according to the judgment result of the adjustment assessment of the clothing design scheme for each part of the user in each scenario, performs customized clothing design according to the different conditions of each part of the user in each scenario, adapts to different scenarios and needs, allows users to show their personal style while ensuring that the clothing will not restrict exercise, and improves user comfort and long-term use experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a schematic diagram of the overall process of the clothing customization design method based on AI body shape data analysis in this application.

[0040] Figure 2 This is a flowchart of step S3 of the clothing customization design method based on AI body shape data analysis in this application.

[0041] Figure 3 This is a schematic diagram of the overall framework of the clothing customization design system based on AI body shape data analysis in this application.

[0042] Figure 4 Schematic diagram of the process for obtaining the evaluation value of the clothing design scheme adjustment in the clothing customization design method based on AI body shape data analysis in this application. DETAILED DESCRIPTION

[0043] In order to better understand the present application, various aspects of the present application will be described in more detail with reference to the accompanying drawings.

[0044] In order to solve the technical problems raised in the background technology, this application provides a preferred embodiment:

[0045] The specific contents of this embodiment are:

[0046] like Figure 1 As shown in FIG, the clothing customization design method based on AI body shape data analysis includes the following specific steps:

[0047] S1. Obtaining the user's body circumference data, muscle changes in various parts of the body, and activity data of various parts of the body;

[0048] In this embodiment, the specific steps of S1 are:

[0049] S11. Acquire the user's body circumference data through three-dimensional scanning, wherein the user's body circumference data includes the user's chest circumference data, waist circumference data, and hip circumference data;

[0050] S12. Obtaining muscle change data of various parts of the user through ultrasonic testing and three-dimensional motion capture, wherein the muscle change data of various parts of the user includes strain rate data and size change data of various muscle groups of the user in various scenarios;

[0051] S13. Acquire activity data of various parts of the user through a surface electromyography system and an inertial sensor system, wherein the activity data of various parts of the user include activity degree data of various muscle groups in various scenes of the user and joint activity angle data corresponding to various muscle groups in various scenes of the user;

[0052] S14. Storing the collected data in a storage component for use in the analysis process.

[0053] In one implementation of the present invention, the user's circumference body shape data is obtained through three-dimensional scanning, and the adaptability of the user's basic clothing design plan to the user's actual circumference is analyzed. The data on muscle changes in various parts of the user are obtained through ultrasonic detection and three-dimensional motion capture, and the impact of changes in muscle groups in various parts of the user in various scenarios on customized clothing design is analyzed. The activity data of various parts of the user are obtained through a surface electromyography system and an inertial sensor system, and the activity restriction rate of each joint of the user in various scenarios and the activity intensity risk value of each muscle group of the user in various scenarios are analyzed.

[0054] S2. Performing a user-customized girth basic assessment based on the user's girth body data, and generating a clothing design plan for each part of the user in each scenario based on the user's customized girth basic assessment results;

[0055] In this embodiment, S2 includes the following specific steps:

[0056] S21. Perform a user-customized girth basic assessment based on the user's girth body data, wherein the user-customized girth basic assessment value calculation formula is: , where X is the user's chest circumference, Y is the user's waist circumference, H is the user's hip circumference, and W is the standard latitude value. is the waist circumference weight, is the weight of hip circumference. It should be noted that in this formula Part of the evaluation is done by quantifying the user's three measurements to assess the user's customized girth basic evaluation value. Part of the evaluation is based on the degree of deviation between the user's three measurements and the standard body measurements to assess the adaptability of the user's clothing design basic solution. For example, 、 If the custom clothing is a top, then The value can be 0.3, The value can be 0.2. If the custom clothing is bottoms, then The value can be 0.4, The possible value is 0.5;

[0057] S22. Obtain the calculated user-customized basic girth evaluation value, and generate a clothing design plan for each part of the user in each scenario according to the user-customized basic girth evaluation value.

[0058] S3. Based on the muscle change data and activity data of each part, adjust and evaluate the clothing design scheme of each part in each scenario of the user;

[0059] like Figure 2 As shown, in this embodiment, the specific steps of S3 are:

[0060] S31, obtaining an impact assessment value of muscle changes at each part of the user in each scenario based on the strain rate data and size change data of each part of the user's muscle group in each scenario;

[0061] In this embodiment, the specific steps of S31 are:

[0062] S311. Based on the strain rate data and size change data of each muscle group in each scene of the user, the change amount of each part of the human body muscle in each scene of the user is evaluated. The calculation formula of the change amount of the evaluation value of the j-th part of the human body muscle in the i-th scene of the user is: , where i is the number corresponding to each scene, i is any item from 1 to N, j is the number corresponding to each part of the user, j is any item from 1 to M, is the strain rate corresponding to the j-th muscle group of the user, As a reference to the human body strain rate, is the weight of the jth muscle group in the user's i-th scene, is the actual size change data of the jth muscle group of the human body in the i-th scenario of the user, is the ideal size change of the jth muscle group of the human body in the i-th scenario. It should be noted that in this formula, The purpose of setting is to evaluate the elasticity of the user's muscle groups by the rate of change of deformation of the user's muscle groups in unit time. The purpose of setting is to evaluate the elasticity of the user's muscle group by comparing the actual elasticity of the user's muscle group with the reference elasticity. The purpose of setting is to evaluate the relative importance of the elasticity and size change of each muscle group in a specific scenario. The purpose of some settings is to measure the gap between the actual change state and the ideal change state of muscle groups in various parts of the human body in various scenarios of the user through the ratio between the actual change data of muscle groups in various parts of the human body in various scenarios of the user and the ideal change data of muscle groups in various parts of the human body in various scenarios of the user. This formula comprehensively evaluates the impact of the changes in muscle groups in various parts of the user in various scenarios on the customized design of clothing through the elasticity of muscle groups in various parts of the user and the change state of muscle groups in various parts of the user in various scenarios. When the evaluation value of the change amount of muscle groups in various parts of the human body in various scenarios of the user is greater, that is, the closer the degree of change of the user's muscles is to the ideal value, the customized design of clothing for this part of the user in this scenario does not need to be adjusted. For example, for example For example, in a sports scene, the change in the thigh muscle group is more important than the change in the arm muscle group, so the thigh muscle group should have a higher weight;

[0063] S312: Obtain the evaluation results of the amount of muscle changes in each part of the user's body in each scenario, and evaluate the impact of the muscle changes in each part of the user in each scenario based on the evaluation results of the amount of muscle changes in each part of the user in each scenario. The evaluation formula for the impact of the muscle change in the jth part of the user in the i-th scenario is: ,in, is the distance between the jth part of the user and its adjacent parts, is the change in the evaluation value of the muscle change of the jth part of the user in the i-th scenario, is the reference value of the muscle change of the user's jth part. It should be noted that in this formula The influence of the muscle change evaluation value of each part of the user's body on its adjacent parts in each scene is evaluated by integrating the changes in the distance between the user's body muscle change evaluation value and its adjacent parts in each scene and then calculating the average value. The influence of the muscle changes of each part of the user on other adjacent parts in each scene is obtained by summing up the influence of the muscle changes of each part of the user on its adjacent parts in each scene. By comparing the impact value of the human muscle changes in each part of the user in each scenario on other adjacent parts with the evaluation value of the reference human muscle changes in each part of the user, the importance of the impact of the human muscle changes in each part of the user in each scenario on its adjacent parts is evaluated.

[0064] S32, obtaining an activity comfort evaluation value for each part of the user in each scenario based on the activity degree data of each muscle group in each part of the user and the joint activity angle data corresponding to each muscle group in each scenario;

[0065] In this embodiment, the specific steps of S32 are: based on the activity degree data of each muscle group of each part of the user in each scene and the joint activity angle data corresponding to each muscle group of each part of the user in each scene, the user's activity comfort level in each scene is evaluated, wherein the calculation formula for the activity comfort level evaluation value of the jth part of the user in the i-th scene is: ,in, is the joint motion angle corresponding to the j-th muscle group in the user's i-th scene, The joint movement angle allowed by the clothing corresponding to the j-th muscle group in the user's i-th scene, is the maximum value of the human joint motion angle corresponding to the j-th muscle group of the user, is the muscle activity intensity corresponding to the j-th muscle group in the user's i-th scenario, is the clothing pressure corresponding to the jth muscle group in the user's i-th scene, is the muscle tolerance threshold corresponding to the j-th muscle group of the user, is the weight of the joint activity of the jth muscle group in the user's i-th scene. It should be noted that in this formula, The limitation of the joint movement angles of the muscle groups in each scene and the joint movement angles allowed by the clothing are expressed in part by the joint movement angles of the muscle groups in each scene and the joint movement angles allowed by the clothing. It is the limit value of joint movement angle corresponding to muscle groups in various parts of the human body. Part of it is to directly reflect the activity restriction rate of each joint of the user in each scenario by calculating the ratio of the restricted angle of the user's joint to the total activity potential of the user's joint. The activity restriction rate of each part of the user in each scene is converted into the freedom of movement of each part of the user in each scene. The meaning is to make the value positively correlated with the activity comfort evaluation value. That is, the larger the freedom of movement value, the smaller the impact of the clothing on joint movement, and the larger the activity comfort evaluation value. In this formula, Reflects the degree of muscle fiber activation when the user's muscle groups exercise in various scenarios. Reflects the vertical pressure exerted on the muscles by the clothing corresponding to each muscle group in each scene. Reflects the physiological stress limit of each muscle group. The actual mechanical load of each muscle group in each scene of the user is represented by the product of the muscle activity intensity corresponding to each muscle group in each scene of the user and the pressure of the clothing. The risk value of the activity intensity of each muscle group in each scenario of the user is reflected in part by the ratio of the actual mechanical load corresponding to each muscle group in each scenario of the user and the physiological stress limit of each muscle group. The purpose of is to negatively correlate the activity intensity risk value of each muscle group in each scene with the activity comfort evaluation value result of the user, that is, The smaller the portion, The larger the part, the greater the activity comfort evaluation value. For example, the formula The role of this formula Part of it represents the actual mechanical load on the user's muscle groups in various scenarios. The muscle groups in higher active parts require greater blood flow and oxygen supply, and the clothing load will aggravate capillary compression.

[0066] S33, such as Figure 4 As shown in FIG, the evaluation value of the muscle change influence of each part of the user in each scene and the evaluation value of the activity comfort are weighted and added together to obtain the evaluation value of the clothing design adjustment scheme of each part of the user in each scene.

[0067] S4. Based on the evaluation results of the clothing design scheme adjustment for each part of the user in each scene, determine whether the clothing design scheme for each part of the user in each scene needs to be adjusted, and output the parts of the user that need to be adjusted in each scene according to the evaluation judgment results of the clothing design scheme adjustment for each part of the user in each scene.

[0068] In this embodiment, the specific steps of S4 are: obtaining the clothing design scheme adjustment evaluation value of each part of the user in each scenario, and comparing the clothing design scheme adjustment evaluation value of each part of the user in each scenario with the set clothing design scheme adjustment evaluation value threshold. If the clothing design scheme adjustment evaluation value of a certain part of the user in a certain scenario is greater than or equal to the set clothing design scheme adjustment evaluation value threshold, it is judged that the clothing design scheme of the part in the scenario does not need to be adjusted; if the clothing design scheme adjustment evaluation value of a certain part of the user in a certain scenario is less than the set clothing design scheme adjustment evaluation value threshold, it is judged that the clothing design scheme of the part in the scenario needs to be adjusted.

[0069] It should be noted here that the setting parameters (such as weights and thresholds, etc.) in this embodiment need to be set by technical personnel in this field based on relevant experiments. The specific experimental method is: obtain the user's circumference body shape data, muscle change data of each part, and activity data of each part, and bring them into the various steps in this embodiment to calculate the clothing design adjustment evaluation value of each part of the user in each scenario, obtain the judgment result of the clothing design adjustment evaluation value of each part of the user in each scenario, import the judgment result of the clothing design adjustment evaluation value of each part of the user in each scenario and the output of each part that needs to be adjusted in each scenario of the user into the fitting software for continuous fitting, and output the clothing design adjustment evaluation value that meets the output setting parameters (such as weights and thresholds, etc.) of each part that needs to be adjusted in each scenario of the user.

[0070] According to the above implementation content, this embodiment has the following advantages over the existing technology: this embodiment obtains the user's circumference body shape data, muscle change data of each part and activity data of each part; performs a user-customized circumference basic assessment based on the user's circumference body shape data, and generates a clothing design plan for each part of the user in each scenario based on the user's customized circumference basic assessment result; performs an adjustment assessment of the clothing design plan for each part of the user in each scenario based on the muscle change data of each part and the activity data of each part; judges whether the clothing design plan for each part of the user in each scenario needs to be adjusted based on the adjustment assessment result of the clothing design plan for each part of the user in each scenario, and outputs the parts of the user that need to be adjusted in each scenario based on the judgment result of the adjustment assessment of the clothing design plan for each part of the user in each scenario, and performs customized clothing design according to the different conditions of each part of the user in each scenario to adapt to different scenarios and needs, so that users can show their personal style while ensuring that the clothing will not restrict exercise, thereby improving user comfort and long-term use experience.

[0071] like Figure 3 As shown, the present embodiment also provides a clothing customization design system based on AI body shape data analysis, which is implemented based on the above-mentioned clothing customization design method based on AI body shape data analysis, and specifically includes a user body shape data acquisition module, a basic scheme generation module, a scheme adjustment analysis module and a customized design execution module. The user body shape data acquisition module is used to obtain the user's circumference body shape data, muscle change data of each part and activity data of each part; the basic scheme generation module is used to perform a user customized circumference basic evaluation based on the user's circumference body shape data, and generate a clothing design scheme for each part of the user in each scenario according to the user customized circumference basic evaluation result; the scheme adjustment analysis module is used to perform an adjustment evaluation of the clothing design scheme for each part of the user in each scenario based on the muscle change data of each part and the activity data of each part; the customized design execution module is used to judge whether the clothing design scheme for each part of the user in each scenario needs to be adjusted based on the evaluation result of the clothing design scheme adjustment for each part of the user, and output the parts that need to be adjusted in each scenario of the user according to the judgment result of the clothing design scheme adjustment for each part of the user.

[0072] For the specific steps for each unit module in the above-mentioned clothing customization design system based on AI body data analysis of this application to realize the corresponding functions, please refer to the steps in the embodiment of the clothing customization design method based on AI body data analysis above, and will not be repeated here.

[0073] This embodiment further provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0074] The processor executes the above-mentioned clothing customization design method based on AI body shape data analysis by calling the computer program stored in the memory.

[0075] The memory can be used to store instructions, programs, codes, code sets, or instruction sets. The memory 310 can include a program storage area and a data storage area. The program storage area can store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the clothing customization design method based on AI body shape data analysis provided in the above embodiment, etc. The data storage area can store data involved in the clothing customization design method based on AI body shape data analysis provided in the above embodiment, etc.

[0076] The processor may include one or more processing cores. The processor executes instructions, programs, code sets, or instruction sets stored in memory, calls data stored in memory, and performs the various functions and processes data of the present application. The processor may be at least one of an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field-programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller, and a microprocessor. It is understood that for different devices, the electronic components used to implement the above-mentioned processor functions may also be other, and the embodiments of the present application are not specifically limited thereto.

[0077] A communication bus may also be included. This communication bus may include a path for transmitting information between the aforementioned components. Examples of communication buses include the PCI (Peripheral Component Interconnect) bus and the EISA (Extended Industry Standard Architecture) bus. Communication buses can be categorized as address buses, data buses, and control buses.

[0078] This embodiment also proposes a computer-readable storage medium storing instructions. When the instructions are executed on a computer, the computer executes the above-mentioned clothing customization design method based on AI body shape data analysis.

[0079] For example, the computer readable storage medium can be a read-only memory, a random access memory, a read-only CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0080] The above embodiments can be implemented in whole or in part via software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. A computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions according to the embodiments of the present application are fully or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. A computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0081] The terms "comprises," "comprising," 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 inherent to such process, method, article, or apparatus.

[0082] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of application of this application is not limited to technical solutions formed by a specific combination of the aforementioned technical features. It also encompasses other technical solutions formed by any combination of the aforementioned technical features or their equivalents, without departing from the aforementioned application concepts. For example, a technical solution formed by replacing the aforementioned features with (but not limited to) technical features with similar functions claimed in this application.

Claims

1. A clothing customization design method based on AI body shape data analysis, characterized by: include: S1. Obtaining the user's body circumference data, muscle changes in various parts of the body, and activity data of various parts of the body; S2. Performing a user-customized girth basic assessment based on the user's girth body data, and generating a clothing design plan for each part of the user in each scenario based on the user's customized girth basic assessment results; S3, based on the muscle change data and activity data of each part, conduct an evaluation of the clothing design adjustments for each part of the user in each scenario. The specific steps of S3 are: S31, obtaining the impact assessment value of muscle changes in each part of the user in each scene by using the strain rate data and size change data of each part of the user in each scene, wherein the specific steps of S31 are: S311. Obtain an estimated value of the amount of change in the muscles of each part of the user in each scenario based on the strain rate data and size change data of the muscle groups of each part of the user in each scenario. The calculation formula for the estimated value of the amount of change in the muscles of the jth part of the user in the i-th scenario is: , where i is the number corresponding to each scene, i is any item from 1 to N, j is the number corresponding to each part of the user, j is any item from 1 to M, is the strain rate corresponding to the j-th muscle group of the user, As a reference to the human body strain rate, is the weight of the jth muscle group in the user's i-th scene, is the actual size change data of the jth muscle group of the human body in the i-th scenario of the user, is the ideal size change of the jth muscle group in the user's i-th scenario; S312: Obtain the evaluation results of the amount of muscle changes in each part of the user's body in each scenario, and evaluate the impact of the muscle changes in each part of the user in each scenario based on the evaluation results of the amount of muscle changes in each part of the user in each scenario. The evaluation formula for the impact of the muscle change in the jth part of the user in the i-th scenario is: ,in, is the distance between the jth part of the user and its adjacent parts, is the change in the evaluation value of the muscle change of the jth part of the user in the i-th scenario, The reference human muscle change evaluation value for the jth part of the user; S32, obtaining an activity comfort evaluation value for each part of the user in each scenario based on the activity degree data of each muscle group in each part of the user and the joint activity angle data corresponding to each muscle group in each scenario; S33, weighting the muscle change impact assessment value and activity comfort assessment value of each part of the user in each scenario and adding them together to obtain the clothing design adjustment assessment value of each part of the user in each scenario; S4. Based on the evaluation results of the clothing design scheme adjustment for each part of the user in each scene, determine whether the clothing design scheme for each part of the user in each scene needs to be adjusted, and output the parts of the user that need to be adjusted in each scene according to the evaluation judgment results of the clothing design scheme adjustment for each part of the user in each scene.

2. The method for customized clothing design based on AI body shape data analysis according to claim 1, characterized in that: The S2 includes the following specific steps: S21, obtaining a user-customized girth basic assessment value based on the user's girth body data; S22. Obtain the calculated user-customized basic girth evaluation value, and generate a clothing design plan for each part of the user in each scenario according to the user-customized basic girth evaluation value.

3. The method for customized clothing design based on AI body shape data analysis according to claim 2, characterized in that: The specific steps of S32 are: based on the activity degree data of each muscle group of each part of the user in each scene and the joint activity angle data corresponding to each muscle group of each part of the user in each scene, the user's activity comfort level in each scene is evaluated, wherein the calculation formula for the activity comfort level evaluation value of the j-th part of the user in the i-th scene is: ,in, is the joint motion angle corresponding to the j-th muscle group in the user's i-th scene, The joint movement angle allowed by the clothing corresponding to the j-th muscle group in the user's i-th scene, is the maximum value of the human joint motion angle corresponding to the j-th muscle group of the user, is the muscle activity intensity corresponding to the j-th muscle group in the user's i-th scenario, is the clothing pressure corresponding to the jth muscle group in the user's i-th scene, is the muscle tolerance threshold corresponding to the j-th muscle group of the user, is the weight corresponding to the degree of joint activity of the j-th muscle group in the user's i-th scenario.

4. The method for customized clothing design based on AI body shape data analysis according to claim 3, characterized in that: The specific steps of S4 are: obtaining the clothing design scheme adjustment evaluation value of each part of the user in each scenario, and comparing the clothing design scheme adjustment evaluation value of each part of the user in each scenario with the set clothing design scheme adjustment evaluation value threshold. If the clothing design scheme adjustment evaluation value of a certain part of the user in a certain scenario is greater than or equal to the set clothing design scheme adjustment evaluation value threshold, it is judged that the clothing design scheme of the part in the scenario does not need to be adjusted; if the clothing design scheme adjustment evaluation value of a certain part of the user in a certain scenario is less than the set clothing design scheme adjustment evaluation value threshold, it is judged that the clothing design scheme of the part in the scenario needs to be adjusted.

5. A clothing customization design system based on AI body shape data analysis, which is implemented based on the clothing customization design method based on AI body shape data analysis according to any one of claims 1 to 4, characterized in that: It specifically includes a user body shape data acquisition module, a basic plan generation module, a plan adjustment analysis module and a customized design execution module. The user body shape data acquisition module is used to obtain the user's body shape data, muscle change data of each part and activity data of each part; The basic scheme generation module is used to perform a user-customized girth basic assessment based on the user's girth body data, and generate a clothing design scheme for each part of the user in each scenario according to the user's customized girth basic assessment result; The scheme adjustment analysis module is used to evaluate the adjustment of clothing design schemes for each part of the user in each scenario based on the muscle change data and the activity data of each part; The customized design execution module is used to judge whether the clothing design schemes of each part of the user in each scenario need to be adjusted based on the evaluation results of the clothing design schemes of each part of the user in each scenario, and output the parts of the user that need to be adjusted in each scenario according to the evaluation judgment results of the clothing design schemes of each part of the user in each scenario.

6. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the clothing customization design method based on AI body shape data analysis as described in any one of claims 1 to 4 by calling the computer program stored in the memory.

7. A computer-readable storage medium, characterized in that Instructions are stored, and when the instructions are run on a computer, the computer is caused to execute the clothing customization design method based on AI body shape data analysis as described in any one of claims 1 to 4.

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