An intelligent clothing rental and retail management system

Abstract

The present invention provides an intelligent clothing rental and retail management system, including a clothing information input module, a clothing rental and sales service module and an order management module; the clothing information input module is used to input the basic information and picture information of each rental and sales clothing; the clothing rental and sales service module is used to obtain the user's clothing demand information, and screen matching clothing according to the clothing demand information for display to the user; and according to the user's try-on instruction, provide the user with an online try-on service for the specified clothing, so that the user can complete the rental and sale order of the clothing according to the try-on result; the order management module is used to manage the user's clothing rental and sales order, and complete the delivery of the specified clothing according to the order information. The present invention helps to improve the accurate selection of clothing products in the clothing rental and retail process, improves the user experience, and also indirectly saves manpower and material resources, and increases the merchant's income.

Description

Technical Field

[0001] The present invention relates to the technical field of clothing rental and sale management, and in particular to an intelligent clothing rental and retail management system. Background Art

[0002] With the development of online e-commerce, the scale of online clothing sales is getting bigger and bigger. After users select their favorite clothing online, they can quickly complete the purchase or rental of clothing online, which is very convenient.

[0003] At present, when users select clothing online, they can easily understand and select clothing styles through pictures, videos, etc. However, when selecting sizes or dimensions, the existing technology usually publishes clothing size parameters for users to choose. However, when faced with various digital dimensions, users usually cannot accurately perceive the differences between various dimensions, resulting in deviations when users select dimensions. For example, users need to buy clothing of multiple sizes at the same time and try them on at home before they can choose the most suitable size and return the rest of the clothing of inappropriate sizes. This method makes it very inconvenient for users to choose clothing, and also causes unnecessary transportation capacity consumption, affecting user experience. Summary of the invention

[0004] In view of the above problems, the present invention aims to provide an intelligent clothing rental and retail management system.

[0005] The purpose of the present invention is achieved by adopting the following technical solutions:

[0006] The present invention shows an intelligent clothing rental and retail management system, including a clothing information input module, a clothing rental and sales service module and an order management module;

[0007] The clothing information input module is used to input the basic information and picture information of each rental and sale clothing, wherein the basic information includes the name of the clothing, rental and sale information, size information, dimension information, sheet material information and inventory information;

[0008] The clothing rental and sales service module is used to obtain the user's clothing demand information, and screen matching clothing according to the clothing demand information and display it to the user; and provide the user with online try-on services for designated clothing according to the try-on instructions initiated by the user, so that the user can complete the rental and sale order of clothing according to the try-on results;

[0009] The order management module is used to manage the user's clothing rental and sales orders, and complete the delivery of designated clothing according to the order information.

[0010] Preferably, the clothing information input module includes a basic information input unit, a picture input unit and a status management unit; wherein,

[0011] The basic information input unit is used to input the basic information of clothing. The basic information of clothing is input into the system according to the clothing actually rented and sold, and a corresponding clothing file is established for each clothing.

[0012] The picture input unit is used to obtain actual picture information of clothing, and to benchmark the collected picture information with the size information and dimension information corresponding to the clothing, and to add the clothing picture information to the clothing file of the corresponding clothing;

[0013] The status management unit is used to update and manage the status of clothing according to the basic information of clothing, wherein the clothing status includes rentable, sellable, remaining stock, out of stock, etc.

[0014] Preferably, the clothing rental and sales service module includes a demand acquisition unit, a demand matching unit and a clothing fitting unit; wherein,

[0015] The demand acquisition unit is used to acquire the user's clothing demand information, wherein the clothing demand information includes clothing category, clothing size, rental and sale category and other demand information;

[0016] The demand matching unit is used to extract the corresponding demand tag according to the acquired clothing demand unit, match the corresponding clothing archive from the clothing archive according to the obtained demand tag, and classify and display the matched clothing archive;

[0017] The clothing fitting unit is used to obtain user basic information and target fitting clothing information according to the user's fitting instructions, wherein the user basic information includes the user's body parameters, and the target fitting clothing information includes the target clothing and corresponding size information; generate a user basic model according to the obtained user body parameters; generate a corresponding clothing map according to the target fitting clothing information, integrate the clothing map into the user basic model, obtain a user fitting model, and display the user fitting model.

[0018] Preferably, the clothing fitting unit includes a target user unit, a target clothing unit, a user model generation unit, a clothing map generation unit, an integration unit and a display unit; wherein,

[0019] The target user unit is used to obtain the user's basic information according to the user's fitting instruction, wherein the basic information includes the user's face image and the user's body parameters; wherein the user's body parameters include gender, height, weight, shoulder width, waist circumference, chest circumference, leg length, hip circumference, etc.;

[0020] The target clothing unit is used to obtain target try-on clothing information according to the user's try-on instruction, wherein the target try-on clothing includes clothing name and corresponding size information;

[0021] The user model generation unit is used to apply the user face image to the specified position of the standard model according to the obtained user basic information, and adjust the size parameters of the corresponding position of the standard model according to the obtained body shape parameters, so that the pixel size ratio of the adjusted standard model corresponds to the user body shape parameters, thereby generating a user basic model;

[0022] The clothing map generation unit is used to call the corresponding clothing picture according to the target clothing information, and adjust the pixel size of the clothing picture according to the size parameter to generate the corresponding clothing map;

[0023] The integration unit is used to integrate the obtained clothing map into the user basic model to obtain the user try-on model;

[0024] The display unit is used to display the obtained user try-on model.

[0025] Preferably, the acquired basic information of the user also includes a full-body image of the user;

[0026] The user model generation unit also includes: extracting a user full body model according to the obtained user full body image, adjusting the user full body model to a corresponding pixel size according to the obtained user full body model and user body shape parameters, and obtaining a user basic model.

[0027] Preferably, the user model production unit includes:

[0028] According to the preset conversion standard, the length dimension parameters in the user's body shape parameters are converted into pixel dimension parameters, and the corresponding feature parameters in the standard model are adjusted to the corresponding pixel dimension to obtain the user basic model.

[0029] Preferably, the order management module includes an order management unit and a logistics management unit; wherein,

[0030] The order management unit is used to manage the user's clothing rental and sales order after the user places an order for the specified clothing;

[0031] The logistics management unit is used to initiate logistics distribution based on clothing rental and sales orders.

[0032] The beneficial effects of the present invention are as follows: the present invention proposes an intelligent clothing rental and retail management system, which enables clothing suppliers to uniformly manage clothing product information and enter clothing products into the system for unified information management. At the same time, online fitting services are provided for clothing products selected by users, which helps users to conduct personalized fittings based on their own conditions for the selected clothing products, helps users to select suitable clothing and corresponding sizes, helps to improve the accurate selection of clothing products in the clothing rental and retail process, improves user experience, and indirectly saves manpower and material resources, and increases the profits of merchants.

[0033] When entering clothing information, the corresponding clothing model can be generated based on the clothing image information and the corresponding size information, and the clothing model can be integrated into the character model to complete the try-on, providing users with accurate clothing display when trying on online, improving the effect of online try-on, and assisting users to complete clothing rental and sale orders based on the try-on results, thereby improving users' experience in online clothing purchase and rental. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0035] Figure 1 It is a framework structure diagram of the present invention;

[0036] Figure 2 It is a framework structure diagram of each functional module of the present invention;

[0037] Figure 3 It is a frame structure diagram of the clothing fitting unit of the present invention. DETAILED DESCRIPTION

[0038] The present invention is further described in conjunction with the following application scenarios.

[0039] See also Figure 1 An intelligent clothing rental and retail management system shown in the embodiment includes a clothing information entry module, a clothing rental and sales service module, and an order management module;

[0040] The clothing information input module is used to input the basic information and picture information of each rental and sale clothing, where the basic information includes the name of the clothing, rental and sale information, size information, dimension information, sheet material information and inventory information;

[0041] The clothing rental and sales service module is used to obtain the user's clothing demand information, and screen matching clothing according to the clothing demand information and display it to the user; and provide the user with online try-on services for designated clothing according to the try-on instructions initiated by the user, so that the user can complete the rental and sale order of clothing according to the try-on results;

[0042] The order management module is used to manage the user's clothing rental and sales orders, and complete the delivery of designated clothing according to the order information.

[0043] The present invention proposes an intelligent clothing rental and retail management system, which can enable clothing suppliers to uniformly manage clothing product information and enter clothing products into the system for unified information management. At the same time, it provides online fitting services for clothing products selected by users, which helps users to perform personalized fittings based on their own conditions for the selected clothing products, and helps users to select suitable clothing and corresponding sizes, which helps to improve the accurate selection of clothing products in the clothing rental and retail process, improves user experience, and indirectly saves manpower and material resources, and increases the profits of merchants.

[0044] When entering clothing information, the corresponding clothing model can be generated based on the clothing image information and the corresponding size information, and the clothing model can be integrated into the character model to complete the try-on, providing users with accurate clothing display when trying on online, improving the effect of online try-on, and assisting users to complete clothing rental and sale orders based on the try-on results, thereby improving users' experience in online clothing purchase and rental.

[0045] Among them, the clothing referred to in the above implementation includes tops, pants, gloves, shoes, hats, socks, scarves, ties, accessories, handbags, etc. In particular, the same clothing has a variety of sizes, lengths and other dimensions.

[0046] In one embodiment, see Figure 2 The clothing information input module includes a basic information input unit, a picture input unit and a status management unit; wherein,

[0047] The basic information input unit is used to input the basic information of clothing. The basic information of clothing is input into the system according to the clothing actually rented and sold, and a corresponding clothing file is established for each clothing.

[0048] The picture input unit is used to obtain actual picture information of clothing, and to benchmark the collected picture information with the size information and dimension information corresponding to the clothing, and to add the clothing picture information to the clothing file of the corresponding clothing;

[0049] The status management unit is used to update and manage the status of clothing according to the basic information of clothing, wherein the clothing status includes rentable, sellable, remaining stock, out of stock, etc.

[0050] In one implementation, the picture input unit includes:

[0051] Clothing is extracted based on the actual clothing pictures obtained to obtain clothing pictures, and the clothing pictures are associated with size information or length size information corresponding to the actual clothing, and the clothing picture information to be size-marked is added to the corresponding clothing file.

[0052] When merchants enter information, they first enter the basic information of clothing products through the basic information entry unit to create a clothing file for the clothing products; at the same time, they obtain clothing pictures through the picture entry unit, and associate the clothing pictures with the corresponding size information to facilitate subsequent online try-on calls. After completing the establishment of the clothing file, merchants can update and manage the status of each clothing through the status management unit, such as the operation of clothing on and off the shelves, and complete the establishment of online clothing rental and sales information.

[0053] In one scenario, after a merchant enters the basic information of a pair of pants, he also enters the corresponding picture information of the pants. The picture entry unit extracts the pants picture according to the entered picture, and associates and marks the pants picture with the actual size parameter information of the pants (such as waist circumference, hip circumference, thigh circumference, front crotch, trouser leg width, trouser length, etc.), and stores them together in the file of the pants to complete the file establishment of the pants; at the same time, the merchant completes the merchant of the pants through the status management unit, changes the status of the pants to saleable, updates the inventory information of each size, and completes the product listing of the pants. That is, users can browse the product information of the pants through the online platform and wear and purchase them online.

[0054] In one implementation, when the image input unit extracts clothing based on the acquired actual clothing image, it can be performed through an OTSU algorithm, an edge detection segmentation algorithm, etc., which is not specifically limited in the present invention.

[0055] In one embodiment, the clothing rental and sales service module includes a demand acquisition unit, a demand matching unit and a clothing fitting unit; wherein:

[0056] The demand acquisition unit is used to acquire the user's clothing demand information, wherein the clothing demand information includes clothing category, clothing size, rental and sale category and other demand information;

[0057] The demand matching unit is used to extract the corresponding demand tag according to the acquired clothing demand unit, match the corresponding clothing archive from the clothing archive according to the obtained demand tag, and classify and display the matched clothing archive;

[0058] The clothing fitting unit is used to obtain user basic information and target fitting clothing information according to the user's fitting instructions, wherein the user basic information includes the user's body parameters, and the target fitting clothing information includes the target clothing and corresponding size information; generate a user basic model according to the obtained user body parameters; generate a corresponding clothing map according to the target fitting clothing information, integrate the clothing map into the user basic model, obtain a user fitting model, and display the user fitting model.

[0059] When providing clothing rental and sales services, it is able to match the corresponding clothing results according to the demand information provided by the user and continue to display them to the user so that the user can choose the favorite clothing to purchase or rent, which is convenient for users. Specifically, when matching clothing needs, it is able to classify according to clothing classification, material, color, keywords and other parameters, and match the corresponding clothing files from the database for display based on the obtained demand labels.

[0060] When a user has chosen a favorite clothing style but wants to confirm the size, he or she can initiate a clothing try-on request. The clothing try-on unit generates and displays a corresponding try-on model based on the user's basic information and the clothing style to be tried in the clothing try-on instruction, which is used as a reference for the user to make a selection. This helps to improve the accuracy of the user's size selection for clothing and improve the user experience of clothing rental and sales.

[0061] In one scenario, when a user needs to try on specified clothing, he or she can enter the user's body shape parameters and select the target clothing and the size parameters corresponding to the target clothing, generate a try-on instruction and send it to the clothing try-on unit to initiate a try-on request for the target clothing and send the corresponding try-on instruction to the system.

[0062] In one embodiment, see Figure 3 In the embodiment, the clothing fitting unit includes a target user unit, a target clothing unit, a user model generating unit, a clothing map generating unit, an integrating unit and a display unit; wherein,

[0063] The target user unit is used to obtain the user's basic information according to the user's fitting instruction, wherein the basic information includes the user's face image and the user's body parameters; wherein the user's body parameters include gender, height, weight, shoulder width, waist circumference, chest circumference, leg length, hip circumference, etc.;

[0064] The target clothing unit is used to obtain target try-on clothing information according to the user's try-on instruction, wherein the target try-on clothing includes clothing name and corresponding size information;

[0065] The user model generation unit is used to apply the user face image to the specified position of the standard model according to the obtained user basic information, and adjust the size parameters of the corresponding position of the standard model according to the obtained body shape parameters, so that the pixel size ratio of the adjusted standard model corresponds to the user body shape parameters, thereby generating a user basic model;

[0066] The clothing map generation unit is used to call the corresponding clothing picture according to the target clothing information, and adjust the pixel size of the clothing picture according to the size parameter to generate the corresponding clothing map;

[0067] The integration unit is used to integrate the obtained clothing map into the user basic model to obtain the user try-on model;

[0068] The display unit is used to display the obtained user try-on model.

[0069] When providing clothing fitting services, the user's body shape data and facial image data are first obtained, and a user basic model corresponding to the user's body parameters, proportions and skin color is constructed based on the user's facial image data and body shape data. The generated user basic model reflects the user's real body size through pixel size and can truly display the user's body proportions. At the same time, a corresponding map is generated based on the clothing that the user selects to try on and the selected size. In the generated clothing map, the pixel size of the clothing is adjusted according to the actual size information of the clothing, and the generated clothing map is integrated into the user basic model. Since the pixel sizes of the user basic model and the clothing map are both corresponding to the actual length size, the user basic model integrated with the clothing map can truly reflect the real effect of the size of the clothing after actual wearing. By displaying the user basic model, the user can have a real understanding of the effect of clothing of different sizes after wearing it, and select the appropriate size as an important reference.

[0070] In one scenario, when a user needs to choose between L-size and XL-size clothing, the user can try on the clothing online. First, the user enters his / her height, shoulder width and other information into the system, and the system generates a user standard model corresponding to the user's body shape. At the same time, according to the L-size and XL-size clothing selected by the user, corresponding maps are generated according to the clothing length, shoulder width and other dimensions corresponding to the L-size and XL-size, respectively, and the maps are integrated into the user standard model, so that the user can understand the effects of the two sizes after wearing them according to the model and choose the appropriate size. For example, when the user finds that the map of the L-size clothing cannot cover the shoulder width of the model when it is integrated into the user standard model, it can be judged that the L-size clothing will be too small, but the map of the XL-size clothing is consistent with the user standard model, so the user can choose the XL-size clothing as the final purchase or rental option according to the result of the try-on. The intuitive try-on display through the user standard model matching and clothing map can help users intuitively understand the effects of clothes of different sizes after "wearing", provide a basis for users to choose clothing sizes, and improve user experience.

[0071] In one implementation, the user model generation unit includes:

[0072] According to the preset conversion standard, the length dimension parameters in the user's body shape parameters are converted into pixel dimension parameters, and the corresponding feature parameters in the standard model are adjusted to the corresponding pixel dimension to obtain the user basic model.

[0073] In one embodiment, the acquired basic information of the user further includes a full-body image of the user;

[0074] The user model generation unit also includes: extracting a user full body model according to the obtained user full body image, adjusting the user full body model to a corresponding pixel size according to the obtained user full body model and user body shape parameters, and obtaining a user basic model.

[0075] In one scenario, the user's height is 170 cm. According to the preset conversion standard: 1 cm = 4 pixels, the standard model is stretched to 680 pixels in the vertical direction to complete the height adjustment of the standard model.

[0076] The generated user basic model can be implemented by applying a pre-set standard model, or it can be directly adjusted based on the extracted user full-body image, which can meet the needs of generating user basic models in different scenarios. The basic model generated based on the extracted user full-body image has a higher degree of restoration of the user's real situation, which helps to further improve the accuracy and display effect of subsequent clothing fitting based on the user standard model.

[0077] In order to further improve the effect of trying on clothes, for example, users can use their own body shape information, face image or full body image as parameters for generating user standard models; or when users choose clothes for others, they can also use other people's body shape information, face image or full body image as parameters to generate user standard models, so as to improve the level of personalization when trying on clothes according to user standard models to meet the needs of different users.

[0078] In one embodiment, the user model generation unit further includes a full body image acquisition unit, an extraction unit and an adjustment unit; wherein,

[0079] The full body image acquisition unit is used to acquire a full body image of the user transmitted by the user;

[0080] The extraction unit is used to extract and segment the user area contour according to the acquired user full body image to obtain a user full body model;

[0081] The adjustment unit is used to adjust the height pixel size and width pixel size of the user's full body model according to the user's body parameters, including the user's height and shoulder width, to obtain the user's basic model.

[0082] In one scenario, when the user's full body model is obtained by performing regional contour extraction and segmentation based on the acquired user's full body image, a segmentation algorithm based on edge detection or a threshold segmentation algorithm can be used to complete the task, and the present invention does not make specific limitations here. According to the obtained user's full body model, combined with the user's height of 170 cm and the standard of 1 cm = 4 pixels, the maximum longitudinal size of the user's full body model is adjusted to 680 pixels, and combined with the user's shoulder width of 40 cm, the horizontal size of the user's full body model is adjusted according to the standard of 160 pixels according to the width of the corresponding shoulder to obtain the user's basic model.

[0083] Among them, for the full-body image of the user, when the user takes or collects the full-body image of the user, the background is usually not guaranteed to be a pure color background; therefore, the uneven information contained in the complex background, especially the uneven brightness information, is likely to cause deviations in the subsequent extraction of the user's full-body model, affecting the effect of generating the user's basic model.

[0084] In one implementation, the user model generation unit further includes: an image optimization unit;

[0085] The image optimization unit is used to optimize the acquired full-body image of the user, weaken the influence of uneven brightness in the background, and obtain an optimized full-body image of the user;

[0086] The extraction unit further extracts and segments the user area contour based on the optimized user full-body image to obtain a user full-body model.

[0087] The image optimization unit optimizes the acquired full-body image of the user, specifically including:

[0088] (1) Convert the acquired full-body image of the user into the Lab color space to obtain a luminance component sub-image Pic of the full-body image of the user L ;

[0089] (2) Based on the obtained brightness component sub-image Pic L , detect the first light source pixel point in the image, where the first light source pixel point detection function used is:

[0090] check1(x, y): L(x, y) ≥ T1

[0091] Wherein, check1(x, y) is the first detection function. When the pixel point (x, y) meets the first detection function, the pixel point is marked as the first light source pixel point (x, y)∈Li1, L(x, y) is the brightness component level of the pixel point (x, y), and T1 is the set brightness component level threshold, where 90≤T1≤95;

[0092] (3) Perform diffusion detection based on the obtained pixel point of the first light source, wherein the diffusion detection function used is:

[0093] check2(a,b): d[(a,b),(c,d)]=1 and |L(a,b)-L(c,d)|<T2

[0094] st(c,d)∈Li1

[0095] Wherein, check2(a, b) is the second detection function. When the pixel point (a, b) meets the second detection function, the pixel point is marked as the first light source pixel point (a, b)∈Li1, d[(a, b), (c, d)]=1 means that the distance from the pixel point (a, b) to the pixel point (c, d) is 1, the pixel point (c, d) is any first light source pixel point, L(a, b) and L(c, d) are the brightness component levels of the pixel point (a, b) and the pixel point (c, d), respectively, and T2 is the set brightness component level threshold, wherein 3≤T2≤6;

[0096] (4) Iteratively repeat step (3) until no new first light source pixel point is detected, then output the current first light source pixel point set Li1;

[0097] (5) Detect the second light source pixel from the remaining pixel, wherein the second light source pixel detection function used is:

[0098] check3(x, y): max(L(x, y)-L(e, f))>T3

[0099] std[(x, y), (e, f)]≤DT

[0100] Wherein, check3(x, y) is the third detection function. When the pixel point (x, y) meets the third detection function, the pixel point is marked as the second light source pixel point (x, y)∈Li2. L(x, y) and L(e, f) are the brightness component levels of the pixel point (x, y) and the pixel point (e, f), respectively. The pixel point (e, f) satisfies that the distance between the pixel point (e, f) and the pixel point (x, y) is less than or equal to DT. DT is the set distance threshold, where 2≤DT≤7, and max(*) is the maximum value function. T3 is the set brightness component level threshold, where 20≤T3≤30.

[0101] (6) Brightness adjustment processing is performed according to the obtained first light source pixel point and second light source pixel point, wherein the brightness adjustment function used is:

[0102]

[0103]

[0104] Among them, L ad (x, y) is the brightness component level of the pixel point (x, y) after brightness adjustment processing, st is the condition that is satisfied, (x, y)∈Li1 means that the pixel point (x, y) is the first light source pixel point, represents the average brightness component level of the pixels that do not belong to the first light source pixel within the v×v neighborhood centered on the pixel point (x, y); st is the condition that the parameter satisfies, and They respectively represent the number of non-first light source pixels and first light source pixels within a v×v neighborhood centered on the pixel point (x, y);

[0105]

[0106] st(x, y)∈Li2; (m, n)=argmax(L(x, y)-L(m, n))

[0107] Among them, L ad (x, y) is the brightness component level of the pixel (x, y) after brightness adjustment processing, st is the condition satisfied by the parameter, (x, y)∈Li2 indicates that the pixel (x, y) is the second light source pixel, L(x, y) and L(m, n) are the brightness component levels of the pixel (x, y) and the pixel (m, n), respectively, d[(x, y), (m, n)] is the distance from the pixel (x, y) to the pixel (m, n), and DT is the set distance threshold;

[0108] (7) After the brightness adjustment processing of the first light source pixel point and the second light source pixel point is completed, according to the current brightness component sub-image The brightness balance of all pixels is further adjusted, and the brightness balance adjustment function used is:

[0109]

[0110] Among them, L bd (x, y) is the brightness component level of the pixel (x, y) after brightness balance adjustment, L ad (x, y) is the current brightness component level of the pixel (x, y), L ad-mean is the current overall average brightness component level, T4 is the set standard brightness component level, where T4 = 65;

[0111] (8) Brightness component sub-image after brightness balance adjustment Reconstruction is performed to obtain an optimized full-body image of the user.

[0112] In view of the problem that the acquired full-body image of the user is easily affected by the uneven brightness in the background, thereby affecting the feature display of the full-body image area of ​​the user in the image. The present invention particularly proposes a technical solution for optimizing the full-body image of the user, wherein the full-body image of the user is converted into the Lab color space and the brightness component sub-graph is extracted as the basis for brightness optimization. According to the obtained brightness optimization sub-graph, the first light source pixel point in the image is first detected to detect the exposure area caused by the natural light source (such as direct light, reflection, etc.) in the image, wherein in the detection process, considering that the exposure area of ​​the natural light source has the characteristics of not obvious brightness change and large influence range in the image, therefore, especially after the light source area is detected according to the proposed first detection function, iterative diffusion detection is further performed according to the detected light source area to accurately obtain the exposure area in the image. In addition, after completing the detection of the first light source pixel point, the second light source pixel point in the image is further detected to detect the brightness change information caused by the light source in the image, and accurately obtain the brightness leap area in the image. After completing the detection of the first light source area and the second light source area, different brightness adjustment functions are proposed to adjust the light source pixels according to different light source areas. Considering the characteristics of the first light source with large coverage and unclear change information, the first light source pixel points are specially considered to reduce the exposure effect of the first light source area by smoothing the area when adjusting the brightness, and reduce the impact of the exposure area on the boundary of the user's whole body model; and for the second light source area, considering that the brightness boundary of the light source is easy to cause interference in the subsequent extraction of the user's whole body model, the boundary area where the second light source is located is specially adjusted to be stepped to reduce the interference of the user's whole body area boundary extraction caused by the brightness leap; improve the representation level of the user's whole body model features. Finally, by adjusting the overall brightness balance of the global image, the clarity of the user's whole body image is further improved, and the accuracy of the user's whole body model extraction and the effect of the subsequent user basic model generation are improved.

[0113] In one embodiment, the clothing map generation unit includes:

[0114] According to the clothing length size information corresponding to the clothing picture, the clothing picture is scaled, the clothing map is adjusted to a pixel size corresponding to the length size, the clothing map is obtained, and the clothing map is added to the corresponding clothing file.

[0115] In one scenario, during the entry stage, corresponding clothing pictures are entered as records for each size of clothing. When trying on clothes, clothing pictures of corresponding sizes are called, and the clothing pictures are converted into pixel sizes according to actual length dimensions to generate corresponding clothing maps. For example, the waist circumference of size S pants is 66cm, the hip circumference is 83cm, the thigh circumference is 47cm, the trouser leg width is 17cm, and the trouser length is 99cm. Then, pixel conversion is continued according to the actual length, 1cm=4 pixels, and the trouser picture is adjusted to a suitable pixel size to generate a clothing map of size S pants.

[0116] In another scenario, when entering clothing pictures, you can also enter only one size of pants picture as the basis. For example, the entered pants picture is the corresponding S size pants, where the S size pants has a waist circumference of 66cm, hip circumference 83cm, thigh circumference 47cm, trouser leg width 17cm, and trouser length 99cm. Then, according to the actual length, continue to convert pixels, 1cm=4 pixels, and adjust the pants picture to a suitable pixel size for saving; when in the online try-on process, when the user selects the S size of the pants to try on, the picture of the pants file is directly called as the texture; and when the user selects the L size of the pants to try on, According to the length dimensions of L-size pants (waist circumference 74cm, hip circumference 90cm, thigh circumference 53cm, trouser leg width 23cm, trouser length 101cm), the S-size pants texture is adjusted according to the length dimension ratio, and each part is adjusted to the corresponding pixel (for example, according to the clothing texture of S-size pants, the trouser length is adjusted from 396 pixels to 404 pixels, the thigh position of the trouser leg width is adjusted from 120 pixels ((47*4=188)*2 pixels / Π) to 134 pixels (212*2 pixels / Π), and the trouser leg width is adjusted from 44 pixels (68*2 pixels / Π) to 58 pixels (99*2 pixels / Π)), to generate a clothing texture for L-size pants.

[0117] When users are not sure how to choose the size of clothing, they can use the online wearing method to display clothing maps of different sizes together with the user's actual data to generate a user standard model for display. This will help users understand the actual wearing conditions of different sizes based on the try-on model, thereby assisting users in choosing the correct size for purchase or rental, and improving the reliability and intelligence of online clothing rental and purchase.

[0118] Among them, the user basic model, clothing map, and user fitting model are all two-dimensional images.

[0119] In one embodiment, the order management module includes an order management unit and a logistics management unit; wherein,

[0120] The order management unit is used to manage the user's clothing rental and sales order after the user places an order for the specified clothing;

[0121] The logistics management unit is used to initiate logistics distribution based on clothing rental and sales orders.

[0122] When the user selects the favorite clothing and corresponding size based on the results of trying on, the order information is generated based on the selected information. After the user completes the order payment, the merchant can arrange the shipment of the order through the logistics management unit and deliver the clothing to the user.

[0123] It should be noted that each functional unit / module in each embodiment of the present invention may be integrated into one processing unit / module, or each unit / module may exist physically separately, or two or more units / modules may be integrated into one unit / module. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of software functional unit / module.

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should analyze that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.

Claims

1. An intelligent clothing rental and retail management system, characterized in that: It includes clothing information entry module, clothing rental and sales service module and order management module; The clothing information input module is used to input basic information and picture information of each rental and sale clothing, wherein the basic information includes the name of the clothing, rental and sale information, size information, dimension information, sheet material information and inventory information; The clothing rental and sales service module is used to obtain the user's clothing demand information, and screen matching clothing according to the clothing demand information for display to the user; And according to the try-on instructions initiated by the user, provide users with online try-on services for designated clothing, so that users can complete the rental and sale orders of clothing based on the try-on results; The order management module is used to manage the user's clothing rental and sales orders and complete the delivery of the specified clothing according to the order information; The clothing rental and sales service module includes a demand acquisition unit, a demand matching unit and a clothing fitting unit; The demand acquisition unit is used to acquire the user's clothing demand information, wherein the clothing demand information includes clothing category, clothing size and rental and sale category demand information; The demand matching unit is used to extract the corresponding demand tag according to the acquired clothing demand unit, match the corresponding clothing archive from the clothing archive according to the obtained demand tag, and classify and display the matched clothing archive; The clothing fitting unit is used to obtain basic user information and target fitting clothing information according to the user's fitting instruction, wherein the basic user information includes the user's body shape parameters, and the target fitting clothing information includes the target fitting clothing and corresponding size information; generate a basic user model according to the obtained user body shape parameters; generate a corresponding clothing map according to the target fitting clothing information, integrate the clothing map into the basic user model, obtain a user fitting model, and display the user fitting model; The clothing fitting unit includes a target user unit, a target clothing unit, a user model generation unit, a clothing map generation unit, an integration unit and a display unit; wherein, The target user unit is used to obtain basic information of the user according to the user's fitting instruction, wherein the basic information includes a user's face image and user's body parameters; wherein the user's body parameters include gender, height, weight, shoulder width, waist circumference, chest circumference, leg length, and hip circumference; The target clothing unit is used to obtain target try-on clothing information according to the user's try-on instruction, wherein the target try-on clothing includes clothing name and corresponding size information; The user model generation unit is used to apply the user face image to the specified position of the standard model according to the obtained user basic information, and adjust the size parameters of the corresponding position of the standard model according to the obtained body shape parameters, so that the pixel size ratio of the adjusted standard model corresponds to the user body shape parameters, thereby generating a user basic model; The clothing map generation unit is used to call the corresponding clothing picture according to the target clothing information, and adjust the pixel size of the clothing picture according to the size parameter to generate the corresponding clothing map; The integration unit is used to integrate the obtained clothing map into the user basic model to obtain the user try-on model; The display unit is used to display the obtained user try-on model; The obtained basic user information also includes a full-body image of the user; The user model generation unit also includes a full body image acquisition unit, an extraction unit and an adjustment unit; wherein, The full body image acquisition unit is used to acquire a full body image of the user transmitted by the user; The extraction unit is used to extract and segment the user area contour according to the acquired user full body image to obtain a user full body model; The adjustment unit is used to adjust the high pixel size and the wide pixel size of the user's full body model according to the user's body parameters, including the user's height and shoulder width, to obtain a basic model of the user; Wherein, the user model generation unit further includes: an image optimization unit; The image optimization unit is used to optimize the acquired full-body image of the user, weaken the influence of uneven brightness in the background, and obtain an optimized full-body image of the user; The extraction unit further extracts and segments the user area contour based on the optimized user full body image to obtain a user full body model; The image optimization unit optimizes the acquired full-body image of the user, specifically including: (1) Convert the acquired full-body image of the user into the Lab color space to obtain a luminance component sub-image Pic of the full-body image of the user L ; (2) Based on the obtained brightness component sub-image Pic L , detect the first light source pixel point in the image, where the first light source pixel point detection function used is: check1(x,y):L(x,y)≥T1 Wherein, check1(x,y) is the first detection function. When the pixel point (x,y) meets the first detection function, the pixel point is marked as the first light source pixel point (x,y)∈Li1, L(x,y) is the brightness component level of the pixel point (x,y), and T1 is the set brightness component level threshold, where 90≤T1≤95; (3) Perform diffusion detection based on the obtained pixel point of the first light source, wherein the diffusion detection function used is: check2(a,b): d[(a,b),(c,d)]=1 and |L(a,b)-L(c,d)| <T2 st(c,d)∈Li1 Wherein, check2(a,b) is the second detection function. When the pixel point (a,b) satisfies the second detection function, the pixel point is marked as the first light source pixel point (a,b)∈Li1. d[(a,b),(c,d)]=1 means that the distance from the pixel point (a,b) to the pixel point (c,d) is 1. The pixel point (c,d) is any first light source pixel point. L(a,b) and L(c,d) are the brightness component levels of the pixel point (a,b) and the pixel point (c,d), respectively. T2 is the set brightness component level threshold, where 3≤T2≤6. (4) Iteratively repeat step (3) until no new first light source pixel point is detected, then output the current first light source pixel point set Li1; (5) Detect the second light source pixel from the remaining pixel, wherein the second light source pixel detection function used is: check3(x,y):max(L(x,y)-L(e,f))>T3 std[(x,y),(e,f)]≤DT Wherein, check3(x,y) is the third detection function. When the pixel point (x,y) meets the third detection function, the pixel point is marked as the second light source pixel point (x,y)∈Li2. L(x,y) and L(e,f) are the brightness component levels of the pixel point (x,y) and the pixel point (e,f), respectively. The pixel point (e,f) satisfies that the distance between the pixel point (e,f) and the pixel point (x,y) is less than or equal to DT. DT is the set distance threshold, where 2≤DT≤7, and max(*) is the maximum value function. T3 is the set brightness component level threshold, where 20≤T3≤30. (6) Brightness adjustment processing is performed according to the obtained first light source pixel point and second light source pixel point, wherein the brightness adjustment function used is: Among them, L ad (x, y) is the brightness component level of the pixel point (x, y) after brightness adjustment processing, st is the condition that is satisfied, (x, y)∈Li1 means that the pixel point (x, y) is the first light source pixel point, represents the average brightness component level of the pixels that do not belong to the first light source pixel within the v×v neighborhood centered on the pixel point (x, y); st is the condition that the parameter satisfies, and They respectively represent the number of non-first light source pixels and first light source pixels within a v×v neighborhood centered on the pixel point (x, y); st(x,y)∈Li2;(m,n)=argmax(L(x,y)-L(m,n)) Among them, L ad (x,y) is the brightness component level of the pixel (x,y) after brightness adjustment processing, st is the condition satisfied by the parameter, (x,y)∈Li2 means that the pixel (x,y) is the second light source pixel, L(x,y) and L(m,n) are the brightness component levels of the pixel (x,y) and the pixel (m,n) respectively, d[(x,y),(m,n)] is the distance from the pixel (x,y) to the pixel (m,n), and DT is the set distance threshold; (7) After the brightness adjustment processing of the first light source pixel point and the second light source pixel point is completed, according to the current brightness component sub-image The brightness balance of all pixels is further adjusted, and the brightness balance adjustment function used is: Among them, L bd (x, y) is the brightness component level of the pixel (x, y) after brightness balance adjustment, L ad (x, y) is the current brightness component level of the pixel (x, y), L ad-mean is the current overall average brightness component level, T4 is the set standard brightness component level, where T4 = 65; (8) Brightness component sub-image after brightness balance adjustment Reconstruction is performed to obtain an optimized full-body image of the user.

2. The intelligent clothing rental and retail management system according to claim 1 is characterized in that: The clothing information input module includes a basic information input unit, a picture input unit and a status management unit; wherein, The basic information input unit is used to input the basic information of clothing, input the basic information of clothing into the system according to the clothing actually rented and sold, and establish a corresponding clothing file for each clothing; The picture input unit is used to obtain actual picture information of clothing, and to benchmark the collected picture information with the size information and dimension information corresponding to the clothing, and to add the clothing picture information to the clothing file of the corresponding clothing; The state management unit is used to update and manage the state of the clothing according to the basic information of the clothing, wherein the clothing state includes rentable, sellable, remaining stock, and out of stock.

3. The intelligent clothing rental and retail management system according to claim 1 is characterized in that: The user model production unit comprises: According to the preset conversion standard, the length dimension parameters in the user's body shape parameters are converted into pixel dimension parameters, and the corresponding feature parameters in the standard model are adjusted to the corresponding pixel dimension to obtain the user basic model.

4. The intelligent clothing rental and retail management system according to claim 1 is characterized in that: The order management module includes an order management unit and a logistics management unit; wherein, The order management unit is used to manage the user's clothing rental and sales order after the user places an order for the specified clothing; The logistics management unit is used to initiate logistics distribution according to clothing rental and sales orders.

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