Garment pattern generation method and system
By collecting information from primary and secondary users, analyzing preferences and quantifying pattern feature weights, and combining the preset pattern library to generate and optimize clothing patterns, the problem of insufficient personalization and customization in existing technologies is solved, and user satisfaction and design efficiency are improved.
Patent Information
- Application Number
- CN202510824124.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-19
- Publication Date
- 2025-10-17
AI Technical Summary
Existing clothing pattern generation technology is difficult to meet personalization and customization needs, has a low match with user expectations, lacks interactivity and feedback mechanisms, resulting in the generated clothing patterns lacking uniqueness and pertinence, and low user satisfaction.
Collect information about primary users and secondary users with emotional associations, analyze preferences and opinions, quantify the weights of pattern features, filter multi-level features, generate and optimize patterns based on the preset pattern library, and actively collect user comments for adjustments.
It achieves highly personalized and customized clothing pattern design, improves user satisfaction and design and production efficiency, and enhances user participation and interactivity.
Smart Images
Figure CN120804401A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of clothing design, and in particular to a clothing pattern generation method and a system thereof. Background Art
[0002] With the rapid development of the clothing industry and the increasing diversification of consumer demand, traditional clothing design and production methods have become unable to meet the market demand for personalized and customized clothing.
[0003] Existing clothing pattern generation technologies often rely on standardized pattern libraries and fixed design models. While this approach improves production efficiency to a certain extent, it struggles to meet users' demand for personalized clothing patterns. Basic user information and dressing characteristics, particularly the preferences of primary users and their emotionally connected secondary users, are often overlooked or simplified. This results in generated clothing patterns lacking uniqueness and specificity, failing to meet users' growing demand for personalized patterns.
[0004] In existing technologies, the quantification and screening of pattern features is often imprecise and intricate. This results in a significant gap between the generated clothing patterns and user expectations. Users' aesthetic and functional needs for clothing are often not fully met, reducing user satisfaction. Furthermore, existing technologies lack effective user feedback mechanisms, making it impossible to make timely adjustments and optimizations based on user feedback, further exacerbating the mismatch between user expectations and actual patterns.
[0005] In existing technologies, user participation and interactivity are often neglected. Users can only passively accept the generated clothing patterns and cannot participate in the design and production process. This lack of interaction and feedback mechanism leads to reduced user satisfaction and recognition of clothing patterns.
[0006] Therefore, it is necessary to provide a clothing pattern generation method and system thereof to solve the above technical problems. Summary of the Invention
[0007] In order to solve the above technical problems, the present invention provides a clothing pattern generation method and system thereof for solving the problems of limited personalization and customization, low user expectation matching and low production efficiency in existing clothing pattern generation technology.
[0008] The present invention provides a method for generating a garment pattern, comprising the following steps:
[0009] Collect the main user's basic information and clothing characteristics, as well as the secondary users' suggestions on the main user's clothing characteristics, and organize them into an original information database. Among them, the secondary users have an emotional connection with the main user;
[0010] According to the original information base, the clothing style preference opinions of the primary user and the secondary user are analyzed to generate a preference opinion analysis result;
[0011] From the preference opinion analysis result, the style feature weight preferred by the primary user and the style feature weight preferred by the secondary user are quantified respectively;
[0012] Combined with the style feature weight preferred by the primary user and the style feature weight preferred by the secondary user, the multi-level style features are screened and integrated into a plurality of style feature sets;
[0013] According to the style feature set, a corresponding style scheme is matched from a preset clothing style library, and the matched style is displayed to the primary user and the secondary user;
[0014] The comment information of the primary user and the secondary user on the displayed matched style is obtained, the adjustment parameters of the intention of the primary user and the secondary user are identified, and after the style is optimized according to the adjustment parameters, a final clothing style is generated.
[0015] Preferably, the basic information and the wearing characteristic information of the primary user, the wearing characteristic information suggestions of the secondary user to the primary user are collected and formed into an original information base, wherein the secondary user is emotionally associated with the primary user, and the specific steps are as follows:
[0016] A network questionnaire covering the basic information and the wearing characteristics of the primary user is set and sent to the primary user and the secondary user;
[0017] From the network questionnaire, the basic information and the wearing characteristic information of the primary user and the wearing characteristic information suggestions of the secondary user to the primary user are obtained and arranged into an original information base of the primary user and the secondary user.
[0018] Preferably, according to the original information base, the clothing style preference opinions of the primary user and the secondary user are analyzed to generate a preference opinion analysis result, and the specific steps are as follows:
[0019] From the original information base of the primary user and the secondary user, the personal preference opinions of the primary user and the secondary user are analyzed and identified, wherein the preference opinions include style preference, fabric preference and decoration element preference;
[0020] From the preference opinions of the style preference, the fabric preference and the decoration element preference, the commonalities and differences between the personal preference opinions of the primary user and the secondary user are identified and marked;
[0021] The commonalities and differences between the personal preference opinions of the primary user and the secondary user are arranged to generate a preference opinion analysis result containing the personal preference opinions of the primary user, the preference opinions of the secondary user and the consensus of both parties.
[0022] Preferably, the main user's preferred style feature weight and the secondary user's preferred style feature weight are quantified from the analysis result of the preference opinions, and the specific steps are as follows:
[0023] From the analysis result of the preference opinions, the personal preference opinions of the main user and the preference opinions of the secondary user are scored respectively by identifying the keywords, and a scoring result is obtained, wherein different keywords with different preferences are preset with different scores.
[0024] The corresponding style features are extracted from the personal preference opinions of the main user and the preference opinions of the secondary user, and the scores of the personal preference opinions of the main user and the preference opinions of the secondary user are quantified as style feature weight values corresponding to the scores according to the scoring result.
[0025] The style feature weight values of the personal preference opinions of the main user and the preference opinions of the secondary user are integrated into a style feature weight table.
[0026] Preferably, the main user's preferred style feature weight and the secondary user's preferred style feature weight are quantified from the analysis result of the preference opinions, and the specific steps are as follows:
[0027] According to the preset feature weight threshold, the style features exceeding the feature weight threshold are marked as high weight style features from the style feature weight table, and the high weight style features common to the main user and the secondary user are included in the first feature set.
[0028] The high weight style features that differ between the main user and the secondary user are screened, and the high weight style features of the main user are preferentially retained and included in the secondary feature set.
[0029] Preferably, the corresponding style feature set is matched from the preset garment style library according to the style feature set, and the matched style is displayed to the main user and the secondary user, and the specific steps are as follows:
[0030] In the garment style database, the existing garment style is searched according to the keywords of the first feature set, and the garment style with the highest similarity is selected as the basic template;
[0031] The basic template is supplemented with the secondary feature set, and the matched garment style is generated into an effect picture, labeled with the corresponding feature set and synchronously displayed to the main user and the secondary user.
[0032] Preferably, the main user and the secondary user's comment information on the display matched style is obtained, the adjustment parameters of the main user and the secondary user's intention are identified, and the final garment style is generated after the adjustment parameters are optimized, and the specific steps are as follows:
[0033] Collect the parameter suggestion comments of the primary user and the secondary user on the generated effect drawing of the garment pattern, and organize the parameter suggestion comments to generate corresponding parameter adjustment feedback;
[0034] According to the generated parameter adjustment feedback, the matched garment pattern is modified, and the effect drawing is generated again for the primary user to confirm. When the primary user confirms that there is no error, the final garment pattern is generated.
[0035] A garment pattern generation system comprises:
[0036] An information collection module is configured to collect basic information and wearing characteristic information of the primary user, and suggestion of the secondary user on the wearing characteristic information of the primary user, and organize the collected information to form an original information database, wherein the secondary user is emotionally associated with the primary user.
[0037] An information recognition module is configured to analyze the garment pattern preference opinions of the primary user and the secondary user according to the original information database, and generate a preference opinion analysis result.
[0038] A weight quantification module is configured to quantize the garment pattern feature weight preferred by the primary user and the garment pattern feature weight preferred by the secondary user from the preference opinion analysis result.
[0039] A screening and organizing module is configured to screen multi-level garment pattern features and integrate the multi-level garment pattern features into a plurality of garment pattern feature sets by combining the garment pattern feature weight preferred by the primary user and the garment pattern feature weight preferred by the secondary user.
[0040] A pattern matching module is configured to match a corresponding pattern scheme from a preset garment pattern database according to the garment pattern feature set, and show the matched pattern to the primary user and the secondary user.
[0041] A pattern generation module is configured to obtain comment information of the primary user and the secondary user on the shown matched pattern, identify adjustment parameters intended by the primary user and the secondary user, and generate a final garment pattern after optimizing the pattern according to the adjustment parameters.
[0042] Compared with the related art, the garment pattern generation method and system provided by the present application have the following beneficial effects:
[0043] The application realizes high personalization and customization by collecting the basic information and wearing characteristics of the user in detail, including the preferences of the primary user and the secondary users associated with the primary user in emotion, ensures that the generated garment pattern meets the aesthetic and functional needs of the primary user, and also takes into account the opinions of the secondary users; meanwhile, the matching degree with the user's expectation is improved by quantifying the pattern feature weight and screening multi-level pattern features, thereby greatly improving the user's satisfaction; in addition, the matching of the preset garment pattern library optimizes the design and production efficiency, reduces unnecessary waste and cost, actively collects user comment information during the generation process and adjusts according to the user's intention, enhances the user's participation and interactivity, and effectively optimizes the garment pattern design. BRIEF DESCRIPTION OF DRAWINGS
[0044] Figure 1 A flowchart of a garment pattern generation method of the application;
[0045] Figure 2 A system block diagram of a garment pattern generation system of the application. DETAILED DESCRIPTION
[0046] The application will be further described below in combination with the drawings and embodiments.
[0047] Embodiment one
[0048] As shown in Figure 1 A garment pattern generation method, comprising the following steps:
[0049] S1, collecting the basic information and wearing characteristic information of the primary user, the wearing characteristic information suggestion of the secondary user to the primary user, and organizing to form an original information library, wherein the secondary user is emotionally associated with the primary user;
[0050] S2, analyzing the garment pattern preference opinions of the primary user and the secondary user according to the original information library, and generating a preference opinion analysis result;
[0051] S3, quantifying the pattern feature weight preferred by the primary user and the pattern feature weight preferred by the secondary user from the preference opinion analysis result respectively;
[0052] S4, combining the pattern feature weight preferred by the primary user and the pattern feature weight preferred by the secondary user, screening multi-level pattern features, and integrating into a plurality of pattern feature sets;
[0053] S5, according to the pattern feature set, matching the corresponding pattern scheme from the preset garment pattern library, and showing the matching pattern to the primary user and the secondary user;
[0054] S6, obtaining the comment information of the primary user and the secondary user on the display matching version, identifying the adjustment parameters of the primary user and the secondary user, and generating a final garment version after optimizing the version according to the adjustment parameters.
[0055] In the implementation process, the specific steps of step S1 are:
[0056] S101, set up a network questionnaire covering the basic information and wearing characteristics of the primary user and distribute it to the primary user and the secondary user.
[0057] Specifically, according to the demand of generating a garment version, a network questionnaire is designed. The questionnaire should cover the basic information of the primary user (such as height, weight, body shape, age, gender, etc.) and wearing characteristics (such as favorite clothing type, color preference, fabric preference, version preference, decoration element preference, etc.). At the same time, the questionnaire should also include the part for the secondary user, asking for their suggestions or opinions on the wearing characteristics of the primary user, and clearly stating the distribution object of the questionnaire, i.e. the primary user and the secondary user who has emotional connection with the primary user; finally, through the channels of email, social media and online survey platform, the designed network questionnaire is distributed to the primary user and the secondary user.
[0058] S102, obtaining the basic information and wearing characteristics of the primary user and the suggestions of the secondary user on the wearing characteristics of the primary user from the network questionnaire, and arranging them into the original information base of the primary user and the secondary user.
[0059] Specifically, within a certain period of time, the questionnaire data filled in by the primary user and the secondary user is collected, and the collected questionnaire data is arranged. The basic information and wearing characteristics of the primary user and the suggestions of the secondary user are classified, summarized and arranged. The arranged data is input into the database to establish the original information base of the primary user and the secondary user. The information base should include the basic information, wearing characteristics of the primary user and the suggestions of the secondary user.
[0060] In the implementation process, the specific steps of step S2 are:
[0061] S201, from the original information base of the primary user and the secondary user, analyze and identify the personal preference opinions of the primary user and the secondary user, wherein the preference opinions include version preference, fabric preference and decoration element preference.
[0062] Specifically, the information base contains the basic information of the primary user (such as height, weight, body shape, etc.), wearing characteristics (such as version preference, color preference, fabric preference, etc.), and the suggestions of the secondary users on the wearing characteristics of the primary user. These information is classified according to the primary user and the secondary users, and the respective preference opinions are extracted. For the primary user, the direct preference opinions of the individual on the garment version are extracted, such as the version characteristics of slim, loose, straight tube, and the preferences on the fabric and decorative elements. For the secondary users, the suggestions of the secondary users on the wearing characteristics of the primary user are extracted, wherein the preference opinions of the secondary users include version preference, fabric preference, and decorative element preference.
[0063] S202, from the version preference, fabric preference, and decorative element preference, the commonalities and differences between the personal preference opinions of the primary user and the preference opinions of the secondary users are identified and labeled.
[0064] Specifically, it is necessary to identify which preference opinions are common to the primary user and the secondary user, and which are different, and to clearly label these commonalities and differences. It should be noted that for the commonalities, these preference opinions are recognized by both the primary user and the secondary user, so they should be given priority consideration in the subsequent version generation process. For the differences, the commonalities and differences between the personal preference opinions of the primary user and the preference opinions of the secondary users are identified and labeled.
[0065] For example, the primary user and the secondary user have no explicit objection to the version preference, which can be considered as a commonality in this respect. In terms of fabric preference, the primary user prefers silk or cotton fabric, while the secondary user has not specified a specific fabric preference, so it can also be considered as a commonality in this respect. However, in terms of decorative element preference, the primary user prefers a simple style.
[0066] S203, the identified commonalities and differences between the personal preference opinions of the primary user and the preference opinions of the secondary users are sorted to generate a preference opinion analysis result containing the personal preference opinions of the primary user, the preference opinions of the secondary users, and the consensus of both parties.
[0067] In the specific implementation process, the specific steps of step S3 are:
[0068] S301, from the preference opinion analysis result, the personal preference opinions of the primary user and the preference opinions of the secondary users are scored respectively by identifying keywords, and a scoring result is obtained, wherein different keywords of different preferences are pre-set as different scores.
[0069] Specifically, from the preference opinion analysis results, the keywords in the preferences of the primary user and the secondary users are identified, which usually represent the specific preferences of the users for the garment style, fabric, decorative elements, etc., and each keyword is pre-assigned a corresponding score, with the score representing the importance of the preference of the user for the keyword.
[0070] In this embodiment, the pre-set keywords for each garment style, fabric, and decorative element are dislike, general, like, and very like, which correspond to 1 point, 2 points, 3 points, and 4 points, respectively.
[0071] S302, extract the style features from the personal preference opinions of the primary user and the preference opinions of the secondary users, and quantize the scores of the personal preference opinions of the primary user and the preference opinions of the secondary users into style feature weight values corresponding to the scores according to the score results.
[0072] Specifically, from the personal preference opinions of the primary user and the preference opinions of the secondary users, by searching for the keywords of their opinions on each garment style, fabric, and decorative element, the keywords are sorted and assigned corresponding scores, and then the score of each keyword is converted into a corresponding style feature weight value. This weight value represents the importance of the style feature in the final garment style design.
[0073] For example, in the personal preference opinions of the primary user, the keyword for the slim fit style feature is identified as like, and the score for the slim fit style feature is 3, and the score is converted into a corresponding style feature weight value of 3.
[0074] S303, integrate the style feature weight values of the personal preference opinions of the primary user and the preference opinions of the secondary users into a style feature weight table.
[0075] Specifically, all the extracted style features and their corresponding weight values are integrated into a table to form a style feature weight table. This table clearly shows the importance of each style feature in the final garment style design and the preference degree of the primary user and the secondary user for these features.
[0076] In the specific implementation process, the specific steps of step S4 are:
[0077] S401, according to the pre-set feature weight threshold, mark the style features exceeding the feature weight threshold in the style feature weight table as high-weight style features, and include the high-weight style features common to the primary user and the secondary user in the primary feature set.
[0078] Specifically, first, a feature weight threshold is preset, and the feature weight threshold preset in this embodiment is 3, which is used to distinguish which pattern features are important (high weight) and which are relatively secondary (low weight), then, all pattern features exceeding the preset feature weight threshold are screened out from the pattern feature weight table, these features are considered to be very important pattern features for both the primary user and the secondary user, finally, the high weight pattern features common to the primary user and the secondary user are included in the first feature set, and the first feature set is the key basis for subsequent search for matching existing garment patterns.
[0079] For example, assuming that the primary user prefers a loose pattern, and the secondary user also suggests that the primary user choose a loose pattern, in the pattern feature weight table, the weight of the "loose pattern" is very high, exceeding the preset feature weight threshold, therefore, the "loose pattern" will be included in the first feature set as the key feature for subsequent search for matching garment patterns.
[0080] S402, screen the high weight pattern features of the primary user and the secondary user difference, and prefer to retain the high weight pattern features of the primary user into the secondary feature set.
[0081] Specifically, after screening out the common high weight pattern features, the high weight pattern features of the primary user and the secondary user difference are further screened, wherein the high weight pattern features of the primary user are preferentially retained. This is because the primary user is the final wearer of the garment, and his preferences should be given priority.
[0082] For example, assuming that the primary user not only prefers a loose pattern, but also particularly likes a design with pockets, and the secondary user has no explicit requirement for the pocket design. In the pattern feature weight table, the weight of the "design with pockets" is very high for the primary user, but the secondary user does not show obvious preference. Therefore, the "design with pockets" will be included in the secondary feature set as the individualized demand for feature supplement to the basic template.
[0083] In the specific implementation process, the specific steps of step S5 are:
[0084] S501, in the garment pattern database, search for matching existing garment patterns according to the keywords of the first feature set, and select the garment pattern with the highest similarity as the basic template.
[0085] Specifically, the pattern-related keywords in the first feature set are analyzed, and the garment patterns matching these keywords are searched in the preset garment pattern database. The implementation is carried out in the way of content-based image retrieval (CBIR), to analyze the similarity between each garment pattern and the first feature set, and finally, the garment pattern with the highest similarity is selected as the basic template.
[0086] S502, supplement the basic template with the secondary feature set, generate a garment pattern effect map matched with the basic template, and label the corresponding feature set and synchronize the display to the primary user and the secondary user.
[0087] Specifically, after determining the basic template, the basic template is supplemented with the secondary feature set. The secondary feature set contains high-weight pattern features that are different between the primary user and the secondary user, wherein the high-weight pattern features of the primary user are preferentially retained, and the basic template is adjusted to meet the requirements in the secondary feature set. The adjustment includes modifying the pattern lines, adding or deleting decorative elements, and changing the fabric.
[0088] In the specific implementation process, the specific steps of step S6 are:
[0089] S601, collect parameter suggestion comments of the primary user and the secondary user on the garment pattern generation effect map, and organize the parameter suggestion comments to generate a corresponding parameter adjustment feedback.
[0090] Specifically, after the primary user and the secondary user view the garment pattern effect map generated in step S502, a convenient feedback channel, such as an online form, a comment box or a special feedback application, is provided for them to input parameter suggestion comments on the garment pattern. Then, the comment information is collected and organized, including identifying specific modification suggestions, improvement suggestions or confirmation of no change, etc. According to the organized comment information, a parameter adjustment feedback report is generated.
[0091] S602, modify the matched garment pattern according to the generated parameter adjustment feedback, and generate a second effect map for user confirmation. After the user confirms that there is no error, the final garment pattern is generated.
[0092] Specifically, according to the parameter adjustment feedback report generated in step S601, the original garment pattern is modified, which can be implemented through existing drawing software. The modified garment pattern will be re-rendered into an effect map so that the primary user and the secondary user can intuitively see the modified effect. The modified effect map will be displayed to the primary user and the secondary user. If the primary user and the secondary user confirm that there is no error or have no further modification suggestions, the modified garment pattern will be considered as the final garment pattern.
[0093] Embodiment Two
[0094] As shown in Figure 2 A garment pattern generation system, specifically comprising:
[0095] An information collection module for collecting basic information and wearing characteristic information of a primary user, and suggestions of a secondary user on the wearing characteristic information of the primary user, and organizing the information to form an original information library, wherein the secondary user is emotionally associated with the primary user.
[0096] An information recognition module is configured to analyze the clothing style preference opinions of the primary user and the secondary user according to the original information base, and generate a preference opinion analysis result;
[0097] A weight quantification module is configured to quantize the style feature weight preferred by the primary user and the style feature weight preferred by the secondary user from the preference opinion analysis result, respectively;
[0098] A screening and sorting module is configured to screen multiple level style features and integrate them into multiple style feature sets in combination with the style feature weight preferred by the primary user and the style feature weight preferred by the secondary user;
[0099] A style matching module is configured to match a corresponding style scheme from a preset clothing style base according to the style feature set, and show the matched style to the primary user and the secondary user;
[0100] A style generation module is configured to obtain the comment information of the primary user and the secondary user on the matched style, identify the adjustment parameters intended by the primary user and the secondary user, and generate a final clothing style after optimizing the style according to the adjustment parameters.
[0101] The present application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 An apparatus for implementing each flow or multiple flows and / or blocks Figure 1 An apparatus for implementing the functions specified in each block or multiple blocks.
[0102] Those skilled in the art can understand that all or part of the steps in the above-mentioned embodiments can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer readable storage medium, including Read-Only Memory (ROM), Random Access Memory (RAM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), One-time Programmable Read-Only Memory (OTPROM), Electrically-Erasable Programmable Read-Only Memory (EEPROM), Compact Disc Read-Only Memory (CD-ROM) or other optical disk storage, magnetic disk storage, magnetic tape storage, or any other medium that can be used to carry or store data which can be read by a computer.
[0103] It should also be noted that the terms "comprising", "containing", or any other variant thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements in the list, but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the statement "comprising a" does not exclude the existence of additional identical elements in the process, method, article, or apparatus that includes the element.
Claims
1. A method for generating a clothing pattern, characterized in that: The generation method comprises the following steps: Collect the main user's basic information and clothing characteristics, as well as the secondary users' suggestions on the main user's clothing characteristics, and organize them into an original information database. Among them, the secondary users have an emotional connection with the main user; Analyze the clothing style preferences of primary users and secondary users based on the original information database and generate preference analysis results; Quantify the weights of the layout features preferred by the primary user and the layout features preferred by the secondary user based on the preference opinion analysis results; Combine the weights of the pattern features preferred by the primary user and the weights of the pattern features preferred by the secondary user to filter the multi-level pattern features and integrate them into multiple pattern feature sets; According to the pattern feature set, the corresponding pattern solution is matched from the preset clothing pattern library, and the matching pattern is displayed to the primary user and secondary users; Obtain the comments of the primary user and the secondary user on the displayed matching pattern, identify the adjustment parameters intended by the primary user and the secondary user, optimize the pattern according to the adjustment parameters, and generate the final clothing pattern.
2. A method for generating a clothing pattern according to claim 1, characterized in that: The basic information and clothing characteristics of the primary user, the clothing characteristics suggestions of the secondary users to the primary user, and the collection of the original information database, wherein the secondary users and the primary user are emotionally associated, are collected in the following specific steps: Set up an online questionnaire covering the primary user's basic information and clothing characteristics and distribute it to the primary user and secondary users; From the online questionnaire, we obtain the main user's basic information and clothing characteristics information as well as the secondary users' suggestions on the main user's clothing characteristics information, and organize them into an original information database of the main user and the secondary users.
3. A method for generating a clothing pattern according to claim 2, characterized in that: The specific steps of analyzing the clothing pattern preferences of the primary user and the secondary user based on the original information database to generate the preference analysis results are as follows: From the original information database of primary users and secondary users, analyze and identify the primary user's personal preferences and secondary users' preferences, where preferences include pattern preferences, fabric preferences, and decorative element preferences; From the preference opinions on pattern preference, fabric preference, and decorative element preference, identify the similarities and differences between the primary user's personal preference opinions and the secondary user's preference opinions and mark them; The similarities and differences between the identified primary user's personal preference opinions and the secondary user's preference opinions are sorted out to generate a preference opinion analysis result including the primary user's personal preference opinions, the secondary user's preference opinions and the consensus of both parties.
4. A method for generating a garment pattern according to claim 3, characterized in that: The specific steps of quantifying the weight of the layout feature preferred by the primary user and the weight of the layout feature preferred by the secondary user from the preference opinion analysis results are as follows: From the preference opinion analysis results, the personal preference opinions of the primary user and the preference opinions of the secondary users are scored by identifying the keywords, and the scoring results are obtained. Among them, different preference keywords are preset to have different scores; Extract the corresponding layout features from the primary user's personal preference opinions and the secondary user's preference opinions, and quantify the scores of the primary user's personal preference opinions and the secondary user's preference opinions into layout feature weight values corresponding to the scores based on the scoring results; The weight values of the main user's personal preference opinions and the secondary user's preference opinions are integrated into a version feature weight table.
5. A method for generating a garment pattern according to claim 4, characterized in that: The specific steps of combining the weight of the pattern feature preferred by the primary user and the weight of the pattern feature preferred by the secondary user to screen the multi-level pattern features and integrate them into multiple pattern feature sets are as follows: According to the preset feature weight threshold, the pattern features that exceed the feature weight threshold are marked as high-weight pattern features from the pattern feature weight table, and the high-weight pattern features shared by the primary user and the secondary user are included in the primary feature set; The high-weighted version features that differ between the primary user and the secondary user are screened, and the high-weighted version features of the primary user are preferentially retained and included in the secondary feature set.
6. A method for generating a garment pattern according to claim 5, characterized in that: The specific steps of matching the corresponding pattern solution from the preset clothing pattern library according to the pattern feature set and displaying the matching pattern to the primary user and the secondary user are as follows: In the clothing pattern database, search for existing clothing patterns according to the keywords of the first-level feature set, and select the clothing pattern with the highest similarity as the basic template; The basic template is supplemented with features using the secondary feature set, and a rendering of the matching clothing pattern is generated, marked with its corresponding feature set and displayed simultaneously to the primary user and the secondary user.
7. A method for generating a garment pattern according to claim 6, characterized in that: The steps of obtaining the comments of the primary user and the secondary user on the displayed matching pattern, identifying the adjustment parameters intended by the primary user and the secondary user, optimizing the pattern according to the adjustment parameters, and generating the final clothing pattern are as follows: Collect the parameter suggestions and comments of primary and secondary users on the clothing pattern generation renderings, organize the parameter suggestions and comments, and generate corresponding parameter adjustment feedback; Adjust the feedback based on the generated parameters, modify the matching clothing pattern, and generate the renderings for the main user to confirm. After the main user confirms that they are correct, the final clothing pattern is generated.
8. A clothing pattern generation system, applied to a clothing pattern generation method according to any one of claims 1 to 7, characterized in that: The generation system comprises: The information collection module is used to collect the basic information and clothing characteristics of the primary user, as well as the clothing characteristics suggestions of the secondary users to the primary user, and organize them into an original information database. Among them, the secondary users have an emotional connection with the primary user; An information recognition module is used to analyze the clothing pattern preferences of primary users and secondary users based on the original information database and generate preference analysis results; The weight quantification module is used to quantify the weight of the version features preferred by the primary user and the weight of the version features preferred by the secondary user based on the preference opinion analysis results; The screening and sorting module is used to combine the pattern feature weights of the primary user's preferences and the pattern feature weights of the secondary user's preferences, screen the multi-level pattern features, and integrate them into multiple pattern feature sets; The pattern matching module is used to match the corresponding pattern scheme from the preset clothing pattern library according to the pattern feature set, and display the matching pattern to the primary user and secondary users; The pattern generation module is used to obtain the comments of the primary user and the secondary user on the displayed matching pattern, identify the adjustment parameters intended by the primary user and the secondary user, optimize the pattern according to the adjustment parameters, and generate the final clothing pattern.