CN113011932A

CN113011932A - Fitting mirror system, image processing method, device and equipment

Info

Publication number: CN113011932A
Application number: CN201911315732.9A
Authority: CN
Inventors: 李鹏宇
Original assignee: Alibaba Group Holding Ltd
Current assignee: Alibaba Group Holding Ltd
Priority date: 2019-12-19
Filing date: 2019-12-19
Publication date: 2021-06-22

Abstract

The embodiment of the invention provides a fitting mirror system, an image processing method, an image processing device and fitting mirror equipment. The fitting mirror system includes: the image acquisition equipment is used for acquiring image information of a user and sending the image information to the server; the server is in communication connection with the image acquisition equipment and is used for acquiring image information and analyzing the image information by utilizing a machine learning model so as to identify height parameters and identification points of user images in the image information; the machine learning model is trained for recognizing height parameters and recognition points of a user image in the image information; rendering the image information based on the height parameter and the identification point, generating a rendered image, and sending the rendered image to a display; the display is in communication connection with the server and is used for acquiring and displaying the rendered image. The technical scheme provided by the embodiment can ensure the quality and effect of rendering the user image, and the rendered image is displayed through the display, thereby being beneficial to improving the offline volume of the product.

Description

Fitting mirror system, image processing method, device and equipment

Technical Field

The invention relates to the technical field of data processing, in particular to a fitting mirror system, an image processing method, an image processing device and fitting mirror equipment.

Background

In an online store, in order to promote sales, a fitting mirror of a beauty type may be installed in a store of clothes, and the fitting mirror is generally used for beautifying the shape of a user against the mirror by an optical principle (refer to a haar mirror), for example: beautifying operation of waist slimming, leg lengthening and the like. However, the American fitting mirror based on the optical principle has the following defects: the structure of the beauty fitting mirror is fixed, so that the region with beautified body can be fixed, and the beautification operation of the body in the region with beautified body can be realized. However, this only meets a small range of height/stature beautification, the opposite being true when the person looking into the mirror is above or below the threshold (and so is the stature) area.

Disclosure of Invention

The embodiment of the invention provides a fitting mirror system, an image processing method, a fitting mirror device and fitting mirror equipment, which can ensure the quality and effect of rendering a user image of a mirror.

In a first aspect, an embodiment of the present invention provides a fitting mirror system, including:

the image acquisition equipment is used for acquiring image information of a user and sending the image information to the server;

the server is in communication connection with the image acquisition equipment and is used for acquiring the image information and analyzing the image information by utilizing a machine learning model so as to identify height parameters and identification points of user images in the image information; wherein the machine learning model is trained to identify height parameters and identification points of a user image in the image information; rendering the image information based on the height parameter and the identification point, generating a rendered image, and sending the rendered image to a display;

and the display is in communication connection with the server and is used for acquiring and displaying the rendered image.

In a second aspect, an embodiment of the present invention provides an image processing method, including:

acquiring image information;

analyzing the image information by using a machine learning model to identify height parameters and identification points of a user image in the image information, wherein the machine learning model is trained to identify the height parameters and the identification points of the user image in the image information;

rendering the image information based on the height parameter and the identification point, and generating a rendered image.

In a third aspect, an embodiment of the present invention provides an image processing apparatus, including:

the acquisition module is used for acquiring the application to be processed;

a generation module for generating a migratable root key corresponding to the application to be processed;

and the processing module is used for sending the migratable root key to at least one client corresponding to the application to be processed, so that the at least one client can utilize the migratable root key to carry out encryption management on the data key of the application to be processed.

In a fourth aspect, an embodiment of the present invention provides an electronic device, including: a memory, a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the image processing method of the second aspect.

In a fifth aspect, an embodiment of the present invention provides a computer storage medium for storing a computer program, where the computer program is used to make a computer implement the image processing method in the second aspect when executed.

According to the fitting mirror system, the image processing method, the image processing device and the fitting mirror system, the image information of the user is acquired through the image acquisition equipment, the server can acquire the image information, the image information can be analyzed through the machine learning model to identify the height parameters and the identification points of the user image in the image information, the image information is rendered based on the height parameters and the identification points to generate a rendered image, and the rendered image can be sent to the display to be displayed.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.

Fig. 1 is a schematic structural diagram of a fitting mirror system according to an embodiment of the present invention;

fig. 2 is a schematic diagram of a fitting mirror system according to an embodiment of the present invention;

fig. 3 is a first flowchart of an image processing method according to an embodiment of the present invention;

fig. 4 is a flowchart of a second image processing method according to an embodiment of the present invention;

fig. 5 is a flowchart of a third image processing method according to an embodiment of the present invention;

fig. 6 is a fourth flowchart of an image processing method according to an embodiment of the present invention;

fig. 7 is a flowchart of a fifth image processing method according to an embodiment of the present invention;

fig. 8 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present invention;

fig. 9 is a schematic structural diagram of an electronic device corresponding to the image processing apparatus provided in the embodiment shown in fig. 8.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, and "a" and "an" generally include at least two, but do not exclude at least one, unless the context clearly dictates otherwise.

It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

The words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.

It is also noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a commodity or system that includes the element.

In addition, the sequence of steps in each method embodiment described below is only an example and is not strictly limited.

In order to facilitate understanding of the technical solutions of the present application, the following briefly describes the prior art:

the traditional fitting mirror only stays at the stage of changing clothes, so that a user can see the appearance of simulating wearing of specific clothes through the mirror and can give a proposal for clothes wearing matching of the user. The bargaining amount of an internet merchant can be promoted through the fitting mirror, and the shopping experience of a user on the internet can also be increased. However, the conventional fitting mirror cannot serve the off-line entity merchant, and cannot improve the user's off-line shopping experience.

Therefore, in an online store, in order to promote sales of products, a beauty fitting mirror may be installed in a store of clothing, and the beauty fitting mirror is generally used for beautifying the body of a user in comparison with a mirror by using an optical principle (refer to a haar mirror). However, the American fitting mirror based on the optical principle has the following defects:

(1) the fixing of the beautified area can be achieved, so that only a small range of height/stature beautification can be met, and the opposite effect can be achieved when the person looking into the mirror is higher or lower than the threshold (same stature) area, for example: for users with lower height, the form beautifying operation on the upper body of the user can be realized in the middle of the fitting mirror, and the form beautifying operation on the waist of the user is realized in the lower part of the fitting mirror. However, beautification strategies differ from body part to body part, and therefore, beautification is easily counterproductive.

(2) The optical beauty fitting glasses with fixed beautifying modes cannot simultaneously meet the beautifying requirements of men and women due to different body beautifying effects and requirements of men and women, so that the optical beauty fitting glasses cannot be used for fashionable stores with mixed men and women.

(3) Cannot be beautified according to the gas preference of the user. For example: pure women prefer to be long, sexy women prefer to be full, and the like.

(4) No customized beautification of garments of different styles is possible, for example: the beautification requirements of different styles of clothes, such as leisure, business, sports, etc., are different.

Some embodiments of the invention are described in detail below with reference to the accompanying drawings. The features of the embodiments and examples described below may be combined with each other without conflict between the embodiments.

Fig. 1 is a schematic structural diagram of a fitting mirror system according to an embodiment of the present invention; in order to solve the above technical problem, referring to fig. 1, the present embodiment provides a fitting mirror system, which may include:

the image acquisition equipment 101 is used for acquiring image information of a user and sending the image information to the server 102;

the server 102 is in communication connection with the image acquisition equipment 101 and is used for acquiring image information and analyzing the image information by utilizing a machine learning model so as to identify height parameters and identification points of user images in the image information; wherein the machine learning model is trained for identifying height parameters and identification points of the user image in the image information; rendering the image information based on the height parameter and the identification point, generating a rendered image, and sending the rendered image to the display 103;

and the display 103 is in communication connection with the server 102 and is used for acquiring and displaying the rendered image.

The image capturing device 101 may refer to any device having an image capturing function, for example, the image capturing device 101 may be any one of the following: cameras, video cameras, scanners, other devices with a photographing function (mobile phones, tablet computers, etc.).

In some examples, to improve the quality and effect of the image captured by the image capturing device 101, the image capturing device 101 may be disposed in the middle of the upper end of the display 103. In some examples, there may be one image capturing device 101, or there may be a plurality of image capturing devices 101, and when there are a plurality of image capturing devices 101, the plurality of image capturing devices 101 may be uniformly disposed in the middle of the upper end of the display 103. It is understood that when there are a plurality of image capturing devices 101, a plurality of pieces of image information captured by the plurality of image capturing devices 101 may be subjected to fusion processing, so that one piece of image capturing information corresponding to the plurality of image capturing devices 101 may be obtained, where the image capturing information may be a video frame image in the video information or may also be image information. Preferably, the image information may be a video frame image in the video information.

Server 102 refers to a device that can provide computational processing services in a network virtual environment, and generally refers to a server that utilizes a network for information planning. In physical implementation, the server 102 may be any device capable of providing computing services, responding to service requests, and performing processing, and may be, for example, a conventional server, a cloud host, a virtual center, and the like. The server 102 mainly includes a processor, a hard disk, a memory, a system bus, and the like, and is similar to a general computer architecture.

The display 103 may refer to any device having an image display function, for example, the display 103 may be a display of a Cathode Ray Tube (CRT), a liquid crystal display, a Light Emitting Diode (LED) display, or the like. It should be noted that, in order to ensure that the user's mirror-viewing effect is achieved through the display 103, the height and width of the display 103 need to meet preset requirements, so that the user's image in proportion to the height of the user can be displayed in the display 103.

In some embodiments, the image capture device 101 may have a network connection with the server 102, which may be a wireless or wired network connection. If the image capturing device 101 is communicatively connected to the server 102, the network format of the mobile network may be any one of 2G (gsm), 2.5G (gprs), 3G (WCDMA, TD-SCDMA, CDMA2000, UTMS), 4G (LTE), 4G + (LTE +), WiMax, and the like. Similarly, the display 103 may also have a network connection with the server 102, which may be a wireless or wired network connection. If the display 103 is communicatively connected to the server 102, the network format of the mobile network may be any one of 2G (gsm), 2.5G (gprs), 3G (WCDMA, TD-SCDMA, CDMA2000, UTMS), 4G (LTE), 4G + (LTE +), WiMax, and the like.

Specifically, after the image acquisition device 101 acquires the image information, the server 102 may acquire the image information sent by the image acquisition device 101. After the image information is obtained, the image information may be analyzed by using a machine learning model to identify height parameters and identification points of the user image in the image information, wherein the machine learning model is trained to identify the height parameters and the identification points of the user image in the image information, and specifically, the identification point information may include at least one of: head identification points, shoulder identification points, arm identification points, hand identification points, abdomen identification points, waist identification points, leg identification points, and the like. After the height parameter and the identification point of the user image are obtained, the image information can be rendered based on the height parameter and the identification point to generate a rendered image, and then the rendered image can be sent to the display 103 to be displayed.

The embodiment provides a fitting mirror system, the image information of a user is acquired through the image acquisition device 101, the server 102 can acquire the image information, the image information can be analyzed through the machine learning model, the height parameter and the identification point of the user image in the image information are identified, the image information is rendered based on the height parameter and the identification point, the rendered image is generated, the rendered image can be sent to the display 103 to be displayed, the quality and the effect of rendering the acquired user image can be effectively guaranteed, the rendered image can be displayed through the display, the beautification rendering effect of the fitting mirror system is further improved, and the offline volume of finished products is favorably improved.

Based on the foregoing embodiment, with continued reference to fig. 1, when the server 102 renders the image information based on the height parameter and the identification point, and generates a rendered image, the server 102 is configured to: determining an image rendering parameter corresponding to the user image based on the height parameter and the identification point; and rendering the user image in the image information by using the image rendering parameters to generate a rendered image.

Specifically, after the server 102 obtains the height parameter and the identification point information, an avatar rendering parameter corresponding to the user avatar may be obtained based on the height parameter and the identification point, and the avatar rendering parameter may include: after the image rendering parameters are obtained, rendering processing can be performed on the user image in the image information, so that a rendered image can be generated.

In a specific application, in the process of rendering image information, in order to give a user sufficient acceptance and right of awareness, the server 102 and the display 103 in this embodiment may be further configured to perform the following steps:

the server 102 is further used for sending the image rendering parameters to the display 103;

the display 103 is further used for displaying the avatar rendering parameters in the preset area.

After the server 102 generates the rendered image, the avatar rendering parameters may be sent to the display 103, and then the display 103 may display the avatar rendering parameters in a preset area (e.g., the upper left area, the upper right area, the lower left area, or the lower right area of the display, etc.), for example: the waist rendering parameter is 0.8 times of the thin waist, the leg rendering parameter is 1.2 times of the elongated leg, and the like.

In some examples, the server 102 and the display 103 in this embodiment may be further configured to perform the following steps:

the server 102 is further configured to obtain, through the display 103, an execution operation input by a user for the avatar rendering parameter, obtain image information that is not subjected to rendering processing according to the execution operation, and send the image information to the display 103;

and the display 103 is also used for acquiring and displaying image information.

After the image rendering parameters are displayed on the display 103, a user can input corresponding execution operation to the image rendering parameters on the display 103, the server 102 can acquire the execution operation input by the user for the image rendering parameters through the display 103, and when the execution operation is to close the rendering effect, the server 102 can acquire image information which is not subjected to rendering processing according to the execution operation, and then send the image information which is not subjected to rendering processing to the display 103 for displaying, so that different application requirements of the user are met. Similarly, when the operation is performed to maintain the rendering effect, the rendered image may continue to be displayed.

The fitting mirror system provided by the embodiment can not only perform rendering beautification treatment on a user of the mirror, but also give the user sufficient informed rights and selection rights, fully considers the acceptance of the user, can enable the user willing to use the rendering beautification treatment effect to use and display the rendered image, resists against the user and can autonomously select and display the image information which is not subjected to rendering treatment, meets the use requirements of different users, and further improves the flexibility and reliability of the use of the fitting mirror system.

Fig. 2 is a schematic diagram of a fitting mirror system according to an embodiment of the present invention; on the basis of the foregoing embodiments, with continuing reference to fig. 1-fig. 2, the server 102 in this embodiment may further be configured to perform the following steps:

analyzing the image information by using a machine learning model to identify at least one of gender information of the user image, quality and style information of the user image and clothing information in the image information; wherein the machine learning model is trained to identify gender information, quality style information, and clothing information of the user image in the image information;

rendering the image information based on at least one of the gender information, the gas style information and the clothing information, the height parameter and the identification point, and generating a rendered image.

With the first application scenario, after the image information is acquired, the image information may be analyzed by using a machine learning model to identify the gender information of the user image in the image information, and at this time, the machine learning model is trained to identify the gender information of the user image in the image information. After the gender information of the user image is obtained, the image information can be rendered based on the gender information, the height parameter and the identification point information, and specifically, the user information with different genders can have different rendering effects.

For example, when the gender information of the user image is female, a first image rendering parameter corresponding to the female may be determined according to the gender information, the height parameter and the identification point information, and then the user image may be rendered using the first image rendering parameter, so that a rendered image may be generated. When the gender information of the user image is male, determining an image rendering parameter II corresponding to the male according to the gender information, the height parameter and the identification point information, and then rendering the user image by using the image rendering parameter II, so that a rendered image can be generated.

And in the second application scenario, after the image information is acquired, analyzing the image information by using a machine learning model, and recognizing the gas and quality style information of the user image in the image information, where the machine learning model is trained to recognize the gas and quality style information of the user image in the image information, where the female gas and quality style information may generally include: clear, sexy, strong and graceful, etc.; the male's temperament information may generally include: sincere, strength, sunlight, wisdom, etc. Specifically, when the machine learning model is learned and trained, the wearing collocation of the user image in the image information can be combined to determine the gas style information of the user image.

Further, when analyzing and recognizing the user image by using the machine learning model, the method may obtain the weight information corresponding to the user image in terms of all the quality style information, and then determine the quality style information corresponding to the user image based on all the weight information, for example: when analyzing and identifying the user image by using the machine learning model, it can be obtained that the weight information of the user image belonging to the pure clear quality is 50%, the weight information belonging to the sexually sensitive quality is 10%, the weight information belonging to the bodybuilding quality is 5%, and the weight information belonging to the gentle quality is 35%, and then based on the weight information corresponding to all the quality style information, the quality style information corresponding to the user image is the pure clear quality.

After the gas quality style information of the user image is acquired, the image information can be rendered based on the gas quality style information, the height parameter and the identification point information of the user image, specifically, the user information with different gas quality style information can have different rendering effects, for example, when the gas quality style information of the user image is pure gas, the first image rendering parameter can be determined according to the pure gas quality, the height parameter and the identification point information, and then the user image is rendered by using the first image rendering parameter, so that a rendered image conforming to the pure gas quality style can be generated. When the gas style information of the user image is gentle gas, determining a second image rendering parameter according to the gentle gas, the height parameter and the identification point information, and then rendering the user image by using the second image rendering parameter, so that a rendered image conforming to the gentle gas style can be generated.

And after the image information is acquired, analyzing the image information by using a machine learning model, and identifying the clothing information corresponding to the user image in the image information, wherein the clothing information may include at least one of the following items: garment brand information, garment type information (type of operation, type of leisure, type of business, etc.), garment size information, etc., at which time the machine learning model is trained to identify garment information corresponding to user imagery in the image information.

After the clothing information corresponding to the user image is obtained, the image information can be rendered based on the clothing information, the height parameter and the identification point information, specifically, different clothing information can have different rendering effects, for example, when the clothing information of the user image is a sport type clothing, the image rendering parameter a can be determined according to the clothing information, the height parameter and the identification point information, and then the image rendering parameter a is used for rendering the user image, so that a rendered image can be generated. When the clothes information of the user image is leisure clothes, the image rendering parameter b can be determined according to the clothes information, the height parameter and the identification point information, and then the user image is rendered by using the image rendering parameter b, so that a rendered image can be generated.

Furthermore, after the garment information of the user image is obtained and the image rendering parameters are generated, garment rendering parameters corresponding to the garment information can be generated, and then the user image and the garment information in the image information are rendered respectively by using the image rendering parameters and the garment rendering parameters, so that a rendered image can be generated, and the quality and the effect of rendering the image information are effectively improved.

And in the application scenario four, after the image information is acquired, the image information can be analyzed by using a machine learning model, the gender information of the user image, the gas style information of the user image and the clothing information in the image information are identified, and at the moment, the machine learning model is trained to be used for identifying the gender information of the user image, the gas style information of the user image and the clothing information in the image information. After acquiring the gender information of the user image, the gas style information of the user image, and the clothing information, the image information may be rendered based on the gender information, the gas style information of the user image, the clothing information, the height parameter, and the identification point information. Specifically, different image rendering parameters can be generated according to different gender information, the gas and style information of the user image, the clothing information, the height parameter and the identification point information, and then the user image is rendered by using the different image rendering parameters, so that a rendered image can be generated.

In this embodiment, the server 102 analyzes the image information through the machine learning model to identify at least one of gender information of the user image, quality and style information of the user image, and clothing information in the image information; then, rendering the image information based on at least one of the gender information, the quality and style information and the clothing information, the height parameter and the identification point to generate a rendered image, thereby effectively realizing the image rendering operation of the image information of the user including the whole body high posture, the full gender information and the full quality and style information, not only meeting the favorite style of the user, but also realizing the customized aesthetic rendering of the style of the clothing tried on by the user, and further improving the aesthetic rendering effect of the fitting mirror system.

On the basis of any of the above embodiments, with continued reference to fig. 1-2, the server 102 in this embodiment may further be configured to:

analyzing the image information by using the machine learning model to identify skin color information of a user image in the image information; wherein the machine learning model is trained to identify skin color information of a user image in the image information;

rendering the image information based on the skin color information, the height parameter and the identification point, and generating a rendered image.

Specifically, after the image information is acquired, the image information may be analyzed by using a machine learning model to identify skin color information of the user image in the image information, for example: the skin color information of the user image is yellow, white, black and the like; at this time, the machine learning model is trained for recognizing skin color information of the user character in the image information. After the skin color information of the user image is obtained, the image information can be rendered based on the skin color information, the height parameter and the identification point information, and specifically, the user information with different skin color information can have different rendering effects.

For example, when the skin color information of the user image is black, the first image rendering parameter corresponding to the female can be determined according to the skin color information, the height parameter and the identification point information, and then the user image and the skin color information of the user image are rendered by using the first image rendering parameter, so that a rendered image can be generated. When the skin color information of the user image is yellow, determining an image rendering parameter II corresponding to the user image according to the skin color information, the height parameter and the identification point information, and then rendering the user image and the skin color information of the user image by using the image rendering parameter II, so that a rendered image can be generated.

In this embodiment, the server 102 analyzes the image information through the machine learning model to identify the skin color information of the user image in the image information; then, the image information is rendered based on the skin color information, the height parameter and the identification point to generate a rendered image, so that the image rendering operation of the image information of the user with the whole skin color information can be effectively realized, the favorite style of the user is met, the customized beauty rendering of the style of clothes try-on of the user can be realized, and the beauty rendering effect of the fitting mirror system is further improved.

acquiring the inclination angle of the display 103 relative to the horizontal plane;

the setting angle of the image capturing apparatus 101 with respect to the display 103 is determined based on the tilt angle, and the image capturing apparatus 101 is controlled based on the setting angle to ensure the display effect of the image information in the display 103.

In order to facilitate application and setting of the fitting mirror system, the setting angle of the image capturing device 101 relative to the display 103 in the fitting mirror system can be automatically adjusted based on the inclination angle of the display 103 relative to the horizontal plane. Firstly, the server 102 may obtain an inclination angle of the display 103 relative to a horizontal plane, and in a specific implementation, a sensor may be disposed in the display 103, the inclination angle of the display 103 relative to the horizontal plane is collected by the sensor, and then the sensor transmits the collected inclination angle to the server 102, so that the server 102 may obtain the inclination angle of the display 103 relative to the horizontal plane. After the inclination angle is acquired, the setting angle of the image acquisition device 101 relative to the display 103 can be determined based on the inclination angle, and then the image acquisition device 101 can be controlled based on the determined setting angle, at this time, after the image acquisition device 101 acquires the image information, the display effect of the image information in the display 103 can be effectively ensured, specifically, the definition, the inclination degree, the size and the like of the image information in the display 103 can be ensured, and the user can experience the same feeling as looking into a mirror.

In this embodiment, the server 102 obtains the inclination angle of the display 103 relative to the horizontal plane, determines the setting angle of the image capturing device 101 relative to the display 103 based on the inclination angle, and controls the image capturing device 101 based on the setting angle to ensure the display effect of the image information in the display 103, thereby effectively realizing the setting and application of the fitting mirror system, and ensuring the use effect of the fitting mirror system.

Further, the fitting mirror system in this embodiment may also be applied to other application scenarios, for example: an application scenario for a gym; specifically, when the fitting mirror system is arranged in an application scene of a gym, image information of a user can be acquired through the image acquisition device 101, the image information is sent to the server 102, the server 102 acquires the image information, analyzes and identifies the image information by using a machine learning model to acquire height parameters and identification points of images of the user, then renders the image information based on the height parameters and the identification points, specifically, renders the body shape, muscle parameters, body fat parameters and the like of the user to increase or reduce the body fat, so as to generate a rendered image, and displays the rendered image based on the display 103, wherein the displayed rendered image can include a current body-building effect of the user and/or a future body-building effect of the user, and the displayed current body-building effect and/or the future body-building effect of the user, can effectively increase the body building power and confidence of the user.

In addition, after the server 102 acquires the image information, the image information may be analyzed by using the machine learning model to identify at least one of gender information of the user image, quality and style information of the user image, and clothing information in the image information; wherein the machine learning model is trained to identify gender information, gas style information, and clothing information of a user image in the image information; rendering the image information based on at least one of the gender information, the gas style information and the clothing information, the height parameter and the identification point, and generating a rendered image. Specifically, the specific implementation principle and the implementation effect in this embodiment are similar to those in the above embodiment, and the above statements may be specifically referred to, and are not repeated herein.

In addition, when the fitting mirror system is arranged in an application scene of a gymnasium, the fitting mirror system can also be used for storing relevant fitness data of a user, and specifically, the server 102 can comprise a memory for storing fitness information of the user; after the user uses the fitting mirror system, the current body-building effect and/or the future body-building effect of the user can be displayed, historical body-building information can be looked up, at least one body-building comparison effect is generated based on the historical body-building information and the current body-building information, and the at least one body-building comparison effect is displayed.

For example, when the user uses the fitting mirror system, the image acquisition device 101 may acquire image information of the user, and may acquire all historical fitness information associated with the user based on the image information of the user; then, the current image information can be analyzed and identified to obtain the current body-building effect; furthermore, at least one historical fitness effect may be generated based on the historical fitness information, at least one comparative fitness effect may be generated based on the at least one historical fitness effect and the current fitness effect, and then the current fitness effect and/or the at least one comparative fitness effect may be displayed via the display 103. It can be understood that when there are a plurality of comparison fitness effects, the plurality of comparison fitness effects may be sequentially displayed according to the execution operation input by the user, for example, the user may execute the operation for the plurality of comparison fitness effect inputs, and when the user inputs the operation of sliding left or right, the previous comparison fitness effect or the next comparison fitness effect on the display 103 may be displayed; therefore, the user can quickly acquire and check the contrast fitness effects in different periods, and the fitness power and the confidence of the user are further increased.

generating recommendation information based on the height parameters and the identification points of the user image, and sending the recommendation information to the display 103;

the display 103 is configured to obtain and display the recommendation information.

Specifically, in order to improve the practicability of the fitting mirror system, the server 102 of the fitting mirror system may be further configured to generate recommendation information based on the height parameter and the identification point of the user image; it is understood that different recommendation information may be generated in different application scenarios. For example, when the fitting mirror system is used in an application scene of a clothing store online, after height parameters and identification points of a user image are obtained, clothing recommendation information corresponding to the user image can be generated, wherein the clothing recommendation information comprises recommended clothing matched with the user image; then, after the clothing recommendation information is generated, the clothing recommendation information may be sent to the display 103, and at this time, the clothing recommendation information may be acquired and displayed in the display 103.

It should be noted that when the display 103 displays the clothing recommendation information, it can be realized that the clothing recommendation information can be displayed in other areas of the rendered image, such as: the rendered image is displayed in the middle of the display 103, and the clothing recommendation information is displayed in other areas of the display 103 (e.g., upper left, upper right, lower left, or lower right areas). Alternatively, the generated clothing recommendation information may be displayed in combination in the rendered image, for example: when the rendered image is displayed on the display 103, the user image in the rendered image has the clothing information corresponding to the clothing recommendation information worn thereon. When the clothing recommendation information is multiple, multiple rendered images may be generated, at this time, the user may input a click or slide operation to the display 103, and the multiple rendered images are switched and displayed through the received click or slide operation, where clothing information corresponding to the clothing recommendation information is worn on a user image in each rendered image.

In addition, when the display 103 displays the clothing recommendation information, the clothing modification operation input by the user for the clothing recommendation information can be received, the modified customized clothing information is generated based on the clothing modification operation, and then the recommended clothing included in the clothing recommendation information can be cut on line to generate clothing products corresponding to the customized clothing information, so that the off-line customized clothing operation is effectively realized, and the use requirements of different users are favorably met.

In another application scenario, the fitting mirror system can be applied to an application scenario of a gymnasium, specifically, in the application scenario of the gymnasium, after height parameters and identification points of a user image are acquired, fitness recommendation information corresponding to the user image can be generated, the fitness recommendation information can be matched with the current user image, and the fitness recommendation information can be 'increase exercises for chest, shoulder, back, leg and other parts'; after the fitness recommendation information is generated, the fitness recommendation information can be sent to the display 103, and at this time, the fitness recommendation information can be acquired and displayed in the display 103, so that a fitness user can adjust a fitness plan in time through the fitness recommendation information, and the fitness effect can be increased or improved.

Fig. 3 is a first flowchart of an image processing method according to an embodiment of the present invention; referring to fig. 3, in order to overcome the above technical problem, the present embodiment provides an image processing method, the execution subject of which is an image processing apparatus, it is understood that the image processing apparatus may be a server, and the server may be implemented as software, or a combination of software and hardware; specifically, the method may include:

s301: image information is acquired.

S302: analyzing the image information with a machine learning model to identify height parameters and identification points of the user image in the image information, wherein the machine learning model is trained to identify the height parameters and identification points of the user image in the image information.

S303: rendering the image information based on the height parameter and the identification point, and generating a rendered image.

The image information can be image information acquired in real time through image acquisition equipment, after the image information is acquired, the image information can be analyzed through a machine learning model, so that height parameters and identification point information of a user image in the image information can be identified, then the image information can be rendered based on the height parameters and the identification points, and accordingly a rendered image can be generated. Specifically, rendering the image information based on the height parameter and the identification point, and generating the rendered image may include:

s3031: and determining an image rendering parameter corresponding to the user image based on the height parameter and the identification point.

S3032: and rendering the user image in the image information by using the image rendering parameters to generate a rendered image.

After the height parameters and the identification points are obtained, the height parameters and the identification points can be analyzed for coarse grain, so that image rendering parameters corresponding to user images can be determined, and it can be understood that different height parameters and identification point information can correspond to different image rendering parameters. After the image rendering parameters are obtained, the user image in the image information can be rendered by using the image rendering parameters, so that rendered parameters are generated.

It is understood that the method in this embodiment may further include:

s801: and sending the rendered image to a display to display the rendered image through the display.

After the rendered image is acquired, the rendered image can be sent to a display, so that a user can directly see the rendered image through the display, the user has mirror-looking experience, and the user can obtain the wearing effect of the garment through the display.

According to the image processing method provided by the embodiment, the height parameter and the identification point of the user image in the image information are identified by acquiring the image information and analyzing the image information by using the machine learning model, then the image information is rendered based on the height parameter and the identification point, and the rendered image is generated, so that the quality and the effect of rendering the acquired user image can be effectively ensured, the stability and the reliability of the method are further improved, and the offline volume of the product is favorably improved.

In some examples, the method in this embodiment may further include:

s400: and sending the image rendering parameters to the display so that the display displays the image rendering parameters in the preset area.

After generating the rendered image, the avatar rendering parameters may be sent to the display, which may then display the avatar rendering parameters in a preset area, such as: the waist rendering parameter is 0.8 times of the thin waist, the leg rendering parameter is 1.2 times of the elongated leg, and the like.

In some examples, referring to fig. 4, the method in this embodiment may further include:

s401: acquiring an execution operation input by a user aiming at the image rendering parameter through a display;

s402: and acquiring image information which is not subjected to rendering processing according to the execution operation, and sending the image information to the display so as to enable the display to display the image information.

Specifically, after the image rendering parameters are displayed on the display, a user can input corresponding execution operation to the image rendering parameters on the display, the server can acquire the execution operation input by the user for the image rendering parameters through the display, when the execution operation is to close the rendering effect, the server can acquire the image information which is not subjected to rendering processing according to the execution operation, and then the image information which is not subjected to rendering processing is sent to the display to be displayed, so that different application requirements of the user are met. Similarly, when the operation is performed to maintain the rendering effect, the rendered image may continue to be displayed.

The method provided by the embodiment not only can perform rendering beautification processing on the user of the mirror, but also gives the user sufficient informed rights and selection rights, fully considers the acceptance of the user, can enable the user willing to use the rendering beautification processing effect to use and display the rendered image, and can enable the resisting user to independently select and display the image information which is not subjected to rendering processing, thereby meeting the use requirements of different users and further improving the flexibility and reliability of the use of the method.

Fig. 5 is a flowchart of a third image processing method according to an embodiment of the present invention; on the basis of any of the above embodiments, with reference to fig. 5, the method in this embodiment may further include:

s501: analyzing the image information by using a machine learning model to identify the gender information of the user image in the image information; wherein the machine learning model is trained for identifying gender information of the user image in the image information.

S502: rendering the image information based on the gender information, the height parameter and the identification point, and generating a rendered image.

Specifically, after the image information is acquired, the image information may be analyzed using a machine learning model to identify the gender information of the user image in the image information, at which time the machine learning model is trained to identify the gender information of the user image in the image information. After the gender information of the user image is obtained, the image information can be rendered based on the gender information, the height parameter and the identification point information, and specifically, the user information with different genders can have different rendering effects.

Fig. 6 is a fourth flowchart of an image processing method according to an embodiment of the present invention; on the basis of any one of the above embodiments, with reference to fig. 6, the method in this embodiment may further include:

s601: analyzing the image information by using a machine learning model to identify the gas style information of the user image in the image information; wherein the machine learning model is trained to recognize the gas-like style information of the user image in the image information.

S602: rendering the image information based on the gas style information, the height parameter and the identification point, and generating a rendered image.

After the image information is obtained, the image information may be analyzed by using a machine learning model to identify the quality style information of the user image in the image information, at this time, the machine learning model is trained to identify the quality style information of the user image in the image information, wherein the female quality style information may generally include: clear, sexy, strong and graceful, etc.; the male's temperament information may generally include: sincere, strength, sunlight, wisdom, etc. Specifically, when the machine learning model is learned and trained, the wearing collocation of the user image in the image information can be combined to determine the gas style information of the user image.

Fig. 7 is a flowchart of a fifth image processing method according to an embodiment of the present invention; on the basis of any of the above embodiments, with continued reference to fig. 7, the method in this embodiment may further include:

s701: analyzing the image information by using a machine learning model to identify clothing information in the image information; wherein the machine learning model is trained to recognize clothing information in the image information.

S702: rendering the image information based on the clothing information, the height parameter and the identification point, and generating a rendered image.

After the image information is acquired, the image information may be analyzed by using a machine learning model, and clothing information corresponding to a user image in the image information is identified, where the clothing information may include at least one of: garment brand information, garment type information (type of operation, type of leisure, type of business, etc.), garment size information, etc., at which time the machine learning model is trained to identify garment information corresponding to user imagery in the image information.

It is understood that the method in the present application may further include: analyzing the image information by using a machine learning model to identify the gender information of the user image, the gas style information of the user image and the clothing information in the image information; wherein the machine learning model is trained to identify gender information, quality style information, and clothing information of the user image in the image information; rendering the image information based on the gender information, the gas style information, the clothing information, the height parameter and the identification point, and generating a rendered image.

After the image information is obtained, the image information may be analyzed using a machine learning model to identify gender information of the user image, quality and style information of the user image, and clothing information in the image information, at which time the machine learning model is trained to identify gender information of the user image, quality and style information of the user image, and clothing information in the image information. After acquiring the gender information of the user image, the gas style information of the user image, and the clothing information, the image information may be rendered based on the gender information, the gas style information of the user image, the clothing information, the height parameter, and the identification point information. Specifically, different image rendering parameters can be generated according to different gender information, the gas and style information of the user image, the clothing information, the height parameter and the identification point information, and then the user image is rendered by using the different image rendering parameters, so that a rendered image can be generated.

In this embodiment, the server analyzes the image information through the machine learning model to identify at least one of gender information of the user image, quality and style information of the user image, and clothing information in the image information; then, rendering the image information based on at least one of the gender information, the quality and style information and the clothing information, the height parameter and the identification point to generate a rendered image, thereby effectively realizing the image rendering operation of the image information of the user including the whole body high posture, the full gender information and the full quality and style information, not only meeting the favorite style of the user, but also realizing the customized aesthetic rendering of the style of the clothing tried on by the user, and further improving the effect of the aesthetic rendering of the image information.

On the basis of any one of the above embodiments, when the image information is acquired by the image acquisition device, the image acquisition device is in communication connection with the server, and the server is in communication connection with the display. Specifically, the method in this example may further include:

s801: the inclination angle of the display relative to the horizontal plane is obtained.

S802: and determining a setting angle of the image acquisition equipment relative to the display based on the inclination angle, and controlling the image acquisition equipment based on the setting angle so as to ensure the display effect of the image information in the display.

In order to collect the image information and ensure the display effect of the image information, the setting angle of the image collecting device relative to the display can be adjusted by itself based on the inclination angle of the display 103 relative to the horizontal plane. Firstly, the inclination angle of the display relative to the horizontal plane can be obtained by the server, when the inclination angle is specifically realized, the sensor can be arranged in the display, the inclination angle of the display relative to the horizontal plane is collected through the sensor, then the collected inclination angle is sent to the server by the sensor, and therefore the inclination angle of the display relative to the horizontal plane can be obtained by the server. After the inclination angle is acquired, the setting angle of the image acquisition equipment relative to the display can be determined based on the inclination angle, then the image acquisition equipment can be controlled based on the determined setting angle, at the moment, after the image acquisition equipment acquires the image information, the display effect of the image information in the display can be effectively ensured, specifically, the definition, the inclination degree, the size and the like of the image information in the display can be ensured, and the user can experience the same feeling as looking into the mirror.

In the embodiment, the inclination angle of the display relative to the horizontal plane is obtained through the server, the setting angle of the image acquisition equipment relative to the display is determined based on the inclination angle, and the image acquisition equipment is controlled based on the setting angle so as to ensure the display effect of the image information in the display, thereby effectively realizing the convenience of acquiring the image information and ensuring the flexible and reliable degree of the method.

On the basis of any one of the above embodiments, the method in this embodiment may further include:

s901: generating recommendation information based on the height parameters and the identification points of the user image;

s902: and sending the recommendation information to a display to display the recommendation information through the display.

Specifically, in order to improve the practicability of the method, after the image information is acquired, the method can be further used for generating recommendation information based on the height parameters and the identification points of the user image, and it can be understood that different recommendation information can be generated in different application scenes.

For example, in an application scene of a clothing store, after height parameters and identification points of a user image are acquired, clothing recommendation information corresponding to the user image can be generated, wherein the clothing recommendation information comprises recommended clothing matched with the user image; and then after the clothing recommendation information is generated, the clothing recommendation information can be sent to a display, and at the moment, the clothing recommendation information can be acquired and displayed in the display.

It should be noted that when the display displays the clothing recommendation information, it is possible to display the clothing recommendation information in other areas of the rendered image, such as: the rendered image is displayed in the middle of the display, and the clothing recommendation information is displayed in other areas (the areas such as the upper left corner, the upper right corner, the lower left corner or the lower right corner) of the display. Alternatively, the generated clothing recommendation information may be displayed in combination in the rendered image, for example: when the rendered image is displayed on the display, the user image in the rendered image is worn with the clothing information corresponding to the clothing recommendation information. When the clothing recommendation information is multiple, multiple rendered images can be generated, at this time, a user can input clicking or sliding operation to the display, the multiple rendered images are switched and displayed through the received clicking or sliding operation, and clothing information corresponding to the clothing recommendation information is worn on the user image in each rendered image.

In addition, when the display displays the clothing recommendation information, clothing modification operation input by a user aiming at the clothing recommendation information can be received, the modified customized clothing information is generated based on the clothing modification operation, then the recommended clothing included in the clothing recommendation information can be cut on line, and clothing products corresponding to the customized clothing information are generated, so that the off-line customized clothing operation is effectively realized, and the use requirements of different users are favorably met.

In another application scenario, the method can be applied to an application scenario of a gymnasium, and specifically, in the application scenario of the gymnasium, after height parameters and identification points of a user image are acquired, fitness recommendation information corresponding to the user image can be generated, the fitness recommendation information is adapted to the user image, and the fitness recommendation information can be 'increase exercises on parts such as chest, shoulders, back, legs and the like'; after the fitness recommendation information is generated, the fitness recommendation information can be sent to the display, and at the moment, the fitness recommendation information can be obtained and displayed in the display, so that a fitness user can adjust a fitness plan in time through the fitness recommendation information, and the fitness effect is increased or improved.

s1001: analyzing the image information by using the machine learning model to identify skin color information of a user image in the image information; wherein the machine learning model is trained to identify skin color information of a user image in the image information;

s1002: rendering the image information based on the skin color information, the height parameter and the identification point, and generating a rendered image.

Specifically, after the image information is obtained, the image information may be analyzed by using a machine learning model to identify the skin color information of the user image in the image information, at which time the machine learning model is trained to identify the skin color information of the user image in the image information. After the skin color information of the user image is obtained, the image information can be rendered based on the skin color information, the height parameter and the identification point information, and specifically, the user information with different skin color information can have different rendering effects.

In the embodiment, the image information is analyzed through a machine learning model so as to identify the skin color information of the user image in the image information; then, the image information is rendered based on the skin color information, the height parameter and the identification point to generate a rendered image, so that the image rendering operation of the image information of the user comprising the whole skin color information is effectively realized, the favorite style of the user is met, the customized beauty rendering of the style of the clothes try-on of the user can be realized, and the beauty rendering effect used by the method is further improved.

Fig. 8 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present invention; referring to fig. 8, the present embodiment provides an image processing apparatus, which can execute the image processing method of fig. 4, and specifically, the image processing apparatus can include:

an obtaining module 11, configured to obtain an application to be processed;

a generating module 12, configured to generate a migratable root key corresponding to the application to be processed;

the processing module 13 is configured to send the migratable root key to at least one client corresponding to the application to be processed, so that the at least one client performs encryption management on the data key of the application to be processed by using the migratable root key.

In some examples, when the processing module 13 renders the image information based on the height parameter and the identification point to generate a rendered image, the processing module 13 may be configured to perform: determining an image rendering parameter corresponding to the user image based on the height parameter and the identification point; and rendering the user image in the image information by using the image rendering parameters to generate a rendered image.

In some examples, the processing module 13 in this embodiment may be configured to perform: and sending the image rendering parameters to the display so that the display displays the image rendering parameters in the preset area.

In some examples, the processing module 13 in this embodiment may be configured to perform: acquiring an execution operation input by a user aiming at the image rendering parameter through a display; and acquiring image information which is not subjected to rendering processing according to the execution operation, and sending the image information to the display so as to enable the display to display the image information.

In some examples, the processing module 13 in this embodiment may be configured to perform: analyzing the image information by using a machine learning model to identify the gender information of the user image in the image information; wherein the machine learning model is trained for identifying gender information of the user image in the image information; rendering the image information based on the gender information, the height parameter and the identification point, and generating a rendered image.

In some examples, the processing module 13 in this embodiment may be configured to perform: analyzing the image information by using a machine learning model to identify the gas style information of the user image in the image information; wherein the machine learning model is trained to identify the air quality style information of the user image in the image information; rendering the image information based on the gas style information, the height parameter and the identification point, and generating a rendered image.

In some examples, the processing module 13 in this embodiment may be configured to perform: analyzing the image information by using a machine learning model to identify clothing information in the image information; wherein the machine learning model is trained to identify clothing information in the image information; rendering the image information based on the clothing information, the height parameter and the identification point, and generating a rendered image.

In some examples, the processing module 13 in this embodiment may be configured to perform: and sending the rendered image to a display to display the rendered image through the display.

In some examples, the processing module 13 in this embodiment may be configured to perform: acquiring the inclination angle of the display relative to the horizontal plane; and determining a setting angle of the image acquisition equipment relative to the display based on the inclination angle, and controlling the image acquisition equipment based on the setting angle so as to ensure the display effect of the image information in the display.

In some examples, the processing module 13 in this embodiment may be configured to perform: generating recommendation information based on the height parameters and the identification points of the user image; and sending the recommendation information to a display to display the recommendation information through the display.

In some examples, the processing module 13 in this embodiment may be configured to perform: analyzing the image information by using the machine learning model to identify skin color information of a user image in the image information; wherein the machine learning model is trained to identify skin color information of a user image in the image information; rendering the image information based on the skin color information, the height parameter and the identification point, and generating a rendered image.

The apparatus shown in fig. 8 can perform the method of the embodiment shown in fig. 4-7, and the detailed description of this embodiment can refer to the related description of the embodiment shown in fig. 4-7. The implementation process and technical effect of the technical solution are described in the embodiments shown in fig. 4 to 7, and are not described herein again.

In one possible design, the structure of the image processing apparatus shown in fig. 8 may be implemented as an electronic device, which may be a mobile phone, a tablet computer, a server, or other devices. As shown in fig. 9, the electronic device may include: a processor 21 and a memory 22. Wherein the memory 22 is used for storing a program for executing the image processing method provided in the above-mentioned embodiments shown in fig. 4-7 by the corresponding electronic device, and the processor 21 is configured for executing the program stored in the memory 22.

The program comprises one or more computer instructions which, when executed by the processor 21, are capable of performing the steps of:

acquiring image information;

analyzing the image information by using a machine learning model to identify height parameters and identification points of the user image in the image information, wherein the machine learning model is trained to identify the height parameters and the identification points of the user image in the image information;

Further, the processor 21 is also configured to perform all or part of the steps in the embodiments shown in fig. 4-7.

The electronic device may further include a communication interface 23 for communicating with other devices or a communication network.

In addition, the embodiment of the present invention provides a computer storage medium for storing computer software instructions for an electronic device, which includes a program for executing the image processing method in the method embodiments shown in fig. 4 to 7.

The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by adding a necessary general hardware platform, and of course, can also be implemented by a combination of hardware and software. With this understanding in mind, the above-described aspects and portions of the present technology which contribute substantially or in part to the prior art may be embodied in the form of a computer program product, which may be embodied on one or more computer-usable storage media having computer-usable program code embodied therein, including without limitation disk storage, CD-ROM, optical storage, and the like.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. A fitting mirror system, comprising:

2. The system of claim 1, wherein when the server generates the rendered image by rendering the image information based on the height parameter and the identification point, the server is configured to:

determining an image rendering parameter corresponding to the user image based on the height parameter and the identification point;

and rendering the user image in the image information by using the image rendering parameters to generate the rendered image.

3. The system of claim 2,

the server is also used for sending the image rendering parameters to a display;

the display is further used for displaying the image rendering parameters in a preset area.

4. The system of claim 3,

the server is further used for acquiring an execution operation input by a user aiming at the image rendering parameter through the display, acquiring image information which is not subjected to rendering processing according to the execution operation, and sending the image information to the display;

the display is also used for acquiring and displaying the image information.

5. The system of claim 1, wherein the server is further configured to:

analyzing the image information by using the machine learning model to identify at least one of gender information, gas style information and clothing information of the user image in the image information; wherein the machine learning model is trained to identify gender information, gas style information, and clothing information of a user image in the image information;

6. The system according to any one of claims 1-5, wherein the image capturing device is disposed in a middle upper portion of the display.

7. The system according to any one of claims 1-5, wherein the number of the image capturing devices is multiple, and the multiple image capturing devices are uniformly arranged in the middle of the upper end of the display.

8. The system of any one of claims 1-5, wherein the server is further configured to:

acquiring the inclination angle of the display relative to a horizontal plane;

and determining a setting angle of the image acquisition equipment relative to the display based on the inclination angle, and controlling the image acquisition equipment based on the setting angle so as to ensure the display effect of the image information in the display.

9. The system of any one of claims 1-5, wherein the server is further configured to:

generating recommendation information based on the height parameters and the identification points of the user image, and sending the recommendation information to the display;

and the display is used for acquiring and displaying the recommendation information.

10. The system of any one of claims 1-5, wherein the server is further configured to:

11. An image processing method, comprising:

acquiring image information;

12. The method of claim 11, wherein rendering the image information based on the height parameter and an identification point, generating a rendered image, comprises:

13. The method of claim 12, further comprising:

and sending the image rendering parameters to a display so that the display displays the image rendering parameters in a preset area.

14. The method of claim 13, further comprising:

acquiring an execution operation input by a user aiming at the avatar rendering parameter through the display;

and obtaining image information which is not subjected to rendering processing according to the execution operation, and sending the image information to the display so as to enable the display to display the image information.

15. The method according to any one of claims 11-14, further comprising:

analyzing the image information by using the machine learning model to identify gender information of a user image in the image information; wherein the machine learning model is trained to identify gender information of a user image in the image information;

rendering the image information based on the gender information, the height parameter and the identification point, and generating a rendered image.

16. The method according to any one of claims 11-14, further comprising:

analyzing the image information by using the machine learning model to identify the gas style information of the user image in the image information; wherein the machine learning model is trained to recognize the gas-style information of a user image in the image information;

rendering the image information based on the gas style information, the height parameter and the identification point, and generating a rendered image.

17. The method according to any one of claims 11-14, further comprising:

analyzing the image information by using the machine learning model to identify clothing information in the image information; wherein the machine learning model is trained to identify clothing information in image information;

rendering the image information based on the clothing information, the height parameter and the identification point, and generating a rendered image.

18. The method according to any one of claims 11-14, further comprising:

and sending the rendered image to a display so as to display the rendered image through the display.

19. The method according to any one of claims 11-14, further comprising:

generating recommendation information based on the height parameters and the identification points of the user image;

and sending the recommendation information to a display to display the recommendation information through the display.

20. The method according to any one of claims 11-14, further comprising:

21. An image processing apparatus characterized by comprising:

the acquisition module is used for acquiring the application to be processed;

22. An electronic device, comprising: a memory, a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the image processing method of any of claims 11-20.