Makeup scheme generation method and device, equipment and storage medium

Abstract

The invention discloses a makeup scheme generation method and device, equipment and a storage medium, and belongs to the field of artificial intelligence. The method comprises the following steps: receiving a user appearance image and makeup description information of a target user sent by a user terminal, wherein the makeup description information indicates a makeup effect expected by the target user; based on the user appearance image and the makeup description information, generating at least one user makeup image through a trained makeup effect generation model, the at least one user makeup image being a makeup image generated by applying at least one makeup effect to the user appearance image; and sending the at least one user makeup image to the user terminal to instruct the user terminal to display the at least one user makeup image. Namely, the makeup effect generation model can be utilized, the real situation of the makeup effect application on the appearance of the user can be visually displayed to the user, and the user can conveniently judge whether the makeup is suitable for himself or herself.

Description

[0001] This application claims priority to Chinese patent application No. 202310786246.5 filed on June 29, 2023, with invention name “Beauty makeup tracing method, device, equipment, storage medium and computer program”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of artificial intelligence, and in particular to a makeup plan generation method, device, equipment and storage medium. Background Art

[0003] With the improvement of living standards, people's pursuit of fashion is getting higher and higher. They will not only show their charm through exquisite makeup, but also design their own clothing according to the needs of the occasion. Usually, in order to achieve better makeup effects, people will imitate the beauty and dressing schemes shown by some bloggers or models to make up and dress. However, the beauty and dressing schemes shown by bloggers or models may only be applicable to the blogger or model, and may not be applicable to other people. If you simply refer to and copy it, you may not be able to achieve the ideal makeup effect due to individual differences. Therefore, there is an urgent need for a makeup scheme generation method that can generate "customized" beauty and dressing schemes suitable for people who love beauty. Summary of the invention

[0004] The present application provides a makeup plan generation method, device, equipment and storage medium, which can generate personalized and customized makeup plans for users. The technical solution is as follows:

[0005] In a first aspect, a makeup scheme generation method is provided, which is applied to a server, and the method comprises:

[0006] Receive a user appearance image and makeup description information of a target user sent by a user terminal, wherein the makeup description information indicates a makeup effect desired by the target user; based on the user appearance image and the makeup description information, generate at least one user makeup image through a trained makeup effect generation model, wherein the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image; send the at least one user makeup image to the user terminal to instruct the user terminal to display the at least one user makeup image.

[0007] It can be seen that the server generates at least one user makeup image through a makeup effect generation model based on the user appearance image of the target user and the makeup description information provided by the target user. Since the user appearance image can accurately reflect the appearance characteristics of the target user, and at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image, the makeup effect in the user makeup image has a higher degree of fit with the user's appearance, and the original characteristics of the user's appearance are not changed, and the generated user makeup image is more realistic. Since the user makeup image can reflect the actual situation of the makeup effect applied to the appearance of the target user, the target user can analyze and judge whether the makeup effect corresponding to the makeup description information is suitable for him / her based on the at least one user makeup image, and obtain a makeup plan suitable for him / her by modifying the makeup description information.

[0008] Optionally, based on the user appearance image and the makeup description information, generating at least one user makeup image through a trained makeup effect generation model includes: obtaining a first geometric grid image corresponding to the user appearance image; based on the user appearance image, the first geometric grid image and the makeup description information, generating at least one user makeup image through a trained makeup effect generation model.

[0009] That is, considering that the user's facial features and body shape not only have height information and width information, but also depth information, therefore, in order to ensure that the makeup effect is more in line with the user's actual face shape and body shape, when generating the user makeup image, it is also necessary to obtain the first geometric grid image of the target user to reflect the depth information of the target user's appearance, so that the makeup effect of the user makeup image output by the makeup effect generation model is better.

[0010] Optionally, the at least one user makeup image is generated by a trained makeup effect generation model based on the user appearance image, the first geometric grid image and the makeup description information, comprising: determining a target prompt template from a prompt template library based on the makeup description information, the prompt template library comprising a plurality of makeup prompt templates, each makeup prompt template comprising a plurality of makeup prompts describing a makeup effect; inputting the target prompt template, the user appearance image and the first geometric grid image into the makeup effect generation model to obtain the at least one user makeup image output by the makeup effect generation model.

[0011] That is, based on the makeup description information provided by the target user, the server can first enrich and improve the makeup description information provided by the target user through the prompt template library before analyzing the makeup effect expected by the target user, so as to improve the accuracy of the makeup description information and make the user makeup image output by the makeup effect generation model more accurate.

[0012] Optionally, before sending the at least one user makeup image to the user terminal, the method also includes: determining the display priority of each user makeup image in the at least one user makeup image; sorting the at least one user makeup image based on the display priority of the at least one user makeup image to obtain an image display order of the at least one user makeup image; sending the at least one user makeup image to the user terminal includes: sending the at least one user makeup image and the image display order to the user terminal to instruct the user terminal to display the at least one user makeup image according to the image display order.

[0013] Since user makeup images with higher display priorities are most likely to be makeup effects that target users like, the user terminal can display user makeup images with higher display priorities in front according to the image display order, which makes it easier to guess user preferences and increase target user satisfaction.

[0014] Optionally, the method also includes: receiving a target makeup image sent by the user terminal, wherein the target makeup image is a makeup image determined by the target user based on the at least one user makeup image; determining a makeup implementation plan corresponding to the target makeup image, wherein the makeup implementation plan includes a plurality of sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step; and sending the makeup implementation plan to the user terminal to instruct the user terminal to display the makeup implementation plan.

[0015] When the target user provides a target makeup image, the server can use the trained makeup solution analysis model to infer the makeup implementation solution corresponding to the target makeup image, so that the target user can imitate makeup based on the makeup implementation solution. Moreover, the makeup implementation solution includes multiple sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step. The target user can refer to the makeup prompt information corresponding to each makeup implementation step in turn, and complete the entire makeup implementation solution in a similar "tracing" manner, which greatly improves the efficiency of users imitating makeup and increases user satisfaction.

[0016] Optionally, determining the makeup implementation solution corresponding to the target makeup image includes: inputting the target makeup image into a trained makeup solution analysis model, and obtaining the makeup implementation solution corresponding to the target makeup image output by the makeup solution analysis model.

[0017] That is, based on the trained makeup solution analysis model, the server can quickly determine the makeup implementation solution corresponding to the target makeup image. The makeup implementation solution includes multiple sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step.

[0018] Optionally, the sending of the makeup implementation plan to the user terminal to instruct the user terminal to display the makeup implementation plan includes: sending makeup prompt information corresponding to a first makeup implementation step to the user terminal, the first makeup implementation step being any one of the makeup implementation steps in the makeup implementation plan; if a step jump instruction for skipping the first makeup implementation step sent by the user terminal is received, in response to the step jump instruction, sending makeup prompt information corresponding to a second makeup implementation step to the user terminal to instruct the user terminal to display the makeup prompt information corresponding to the second makeup implementation step, the second makeup implementation step being the next makeup implementation step adjacent to the first makeup implementation step in the makeup implementation plan.

[0019] When displaying the second makeup effect picture, the present application does not mechanically continue to overlay the makeup texture data corresponding to the second makeup implementation step on the makeup effect picture corresponding to the first makeup implementation step, but obtains the real-time appearance image of the target user, and generates the makeup effect picture corresponding to the second makeup implementation step based on the real-time appearance image and the makeup texture data corresponding to the second makeup implementation step. In this way, the makeup effect pictures corresponding to each makeup implementation step are generated in real time according to the actual makeup progress of the user, which improves the real-time and accuracy of the makeup effect pictures corresponding to the makeup implementation steps.

[0020] Optionally, the makeup prompt information corresponding to the makeup implementation step includes one or more of step description information, makeup map data, makeup product information and auxiliary tool information required for the makeup implementation step; wherein, the makeup map data includes makeup contour information and map positioning information, the makeup contour information indicates the contour of the makeup effect corresponding to the makeup implementation step, and the map positioning information indicates the position of the makeup effect corresponding to the makeup implementation step.

[0021] That is, displaying makeup prompt information in different areas can help users intuitively and comprehensively understand the specific implementation methods of the makeup implementation steps, so as to effectively imitate makeup.

[0022] In a second aspect, a makeup scheme generation method is provided, which is applied to a user terminal, and the method includes:

[0023] Acquire a user appearance image and makeup description information of a target user, wherein the makeup description information indicates a makeup effect desired by the target user; send the user appearance image and the makeup description information to a server to instruct the server to generate at least one user makeup image based on the user appearance image and the makeup description information through a trained makeup effect generation model, wherein the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image; receive and display the at least one user makeup image sent by the server.

[0024] Optionally, before displaying the at least one user makeup image, the method further includes: receiving an image display order of the at least one user makeup image sent by the server; and displaying the at least one user makeup image includes: displaying the at least one user makeup image according to the image display order.

[0025] Optionally, after displaying the at least one user makeup image, the method further includes: determining a target makeup image based on the at least one user makeup image; sending the target makeup image to the server to instruct the server to determine a makeup implementation plan corresponding to the target makeup image, the makeup implementation plan comprising a plurality of sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step; receiving and displaying the makeup implementation plan sent by the server.

[0026] Optionally, the receiving and displaying the makeup implementation plan sent by the server includes: receiving and displaying makeup prompt information corresponding to a first makeup implementation step sent by the server, the first makeup implementation step being any one of the makeup implementation steps in the makeup implementation plan; in response to a step jump operation triggered by the target user for skipping the first makeup implementation step, sending a step jump instruction to the server, the step jump instruction being used to request makeup prompt information corresponding to a second makeup implementation step, the second makeup implementation step being the next makeup implementation step adjacent to the first makeup implementation step in the makeup implementation plan; receiving and displaying makeup prompt information corresponding to the second makeup implementation step sent by the server.

[0027] Optionally, the makeup prompt information of the makeup implementation step includes one or more of step description information, makeup map data, makeup product information and auxiliary tool information required for the makeup implementation step; wherein, the makeup map data includes makeup contour information and map positioning information, the makeup contour information indicates the contour of the makeup effect corresponding to the makeup implementation step, and the map positioning information indicates the position of the makeup effect corresponding to the makeup implementation step.

[0028] Optionally, the makeup prompt information of the makeup implementation step includes the makeup map data; the display of the makeup prompt information corresponding to the second makeup implementation step includes: obtaining a real-time appearance image of the target user; based on the makeup map data corresponding to the second makeup implementation step, rendering the real-time appearance image with makeup effects to obtain a makeup rendering corresponding to the second makeup implementation step; and displaying the makeup rendering corresponding to the second makeup implementation step.

[0029] Optionally, based on the makeup map data corresponding to the second makeup implementation step, the real-time appearance image is rendered with makeup effects to obtain a makeup rendering image corresponding to the second makeup implementation step, including: generating a second geometric grid image corresponding to the real-time appearance image; determining a makeup rendering position in the real-time appearance image based on the map positioning information corresponding to the second makeup implementation step and the second geometric grid image; based on the makeup rendering position, the real-time appearance image is rendered with makeup effects according to the makeup contour information corresponding to the second makeup implementation step to obtain a makeup rendering image corresponding to the second makeup implementation step.

[0030] Optionally, the makeup prompt information of the makeup implementation step also includes the step description information, the makeup product information and the auxiliary tool information; the method also includes: displaying the step description information corresponding to the second makeup implementation step, the makeup product information corresponding to the second makeup implementation step and the auxiliary tool information corresponding to the second makeup implementation step; wherein, the makeup effect picture, the step description information, the makeup product information and the auxiliary tool information are respectively displayed in different areas, and the display areas of the step description information, the makeup product information and the auxiliary tool information surround the display area of ​​the makeup effect picture.

[0031] In a third aspect, a makeup scheme generating device is provided, wherein the makeup scheme generating device has the function of implementing the makeup scheme generating method in the first aspect. The makeup scheme generating device comprises at least one module, and the at least one module is used to implement the makeup scheme generating method provided in the first aspect.

[0032] In a fourth aspect, a makeup scheme generating device is provided, wherein the makeup scheme generating device has the function of implementing the makeup scheme generating method in the second aspect. The makeup scheme generating device comprises at least one module, and the at least one module is used to implement the makeup scheme generating method provided in the second aspect.

[0033] In a fifth aspect, a server is provided, wherein the server is a computing device cluster, the computing device cluster includes at least one computing device, and each computing device includes a processor and a memory;

[0034] The processor of the at least one computing device is used to execute computer program instructions stored in the memory of the at least one computing device, so that the computing device cluster implements the makeup plan generation method described in the first aspect above.

[0035] In a sixth aspect, a terminal is provided, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute computer program instructions stored in the memory, so that the terminal implements the makeup plan generating method described in the second aspect above.

[0036] In a seventh aspect, a computer-readable storage medium is provided, wherein the storage medium stores computer program instructions. When the computer program instructions are executed on a server, the server executes the makeup plan generating method described in the first aspect.

[0037] In an eighth aspect, a computer-readable storage medium is provided, wherein the storage medium stores computer program instructions, and when the computer program instructions are executed on a terminal, the terminal executes the makeup plan generating method described in the second aspect.

[0038] In a ninth aspect, a computer program product comprising instructions is provided, and when the instructions are executed on a server, the server executes the steps of the makeup scheme generating method described in the first aspect. In other words, a computer program is provided, and when the computer program is executed on a server, the server executes the makeup scheme generating method described in the first aspect.

[0039] In a tenth aspect, a computer program product comprising instructions is provided, and when the instructions are executed on a terminal, the terminal executes the steps of the makeup scheme generating method described in the second aspect. In other words, a computer program is provided, and when the computer program is executed on a terminal, the terminal executes the makeup scheme generating method described in the second aspect.

[0040] The technical effects obtained in the above-mentioned third to tenth aspects are similar to the technical effects obtained by the corresponding technical means in the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic diagram of an implementation environment provided by an embodiment of the present application;

[0042] Figure 2 It is a flowchart of a makeup plan generation method provided in an embodiment of the present application;

[0043] Figure 3 is a flowchart of another makeup plan generation method provided in an embodiment of the present application;

[0044] Figure 4 It is a schematic diagram of displaying makeup prompt information provided by an embodiment of the present application;

[0045] Figure 5 It is a schematic diagram of the architecture of a makeup plan generation system provided in an embodiment of the present application;

[0046] Figure 6 It is a schematic diagram of a process for generating a user beauty effect picture provided by an embodiment of the present application;

[0047] Figure 7 It is a flowchart of a makeup implementation solution for generating beauty products provided in an embodiment of the present application;

[0048] Figure 8 It is a schematic diagram of a process of generating a user's dressing effect diagram provided by an embodiment of the present application;

[0049] Fig. 9 It is a structural schematic diagram of a makeup scheme generating device provided in an embodiment of the present application;

[0050] Fig.10 is a schematic diagram of the structure of another makeup scheme generating device provided in an embodiment of the present application;

[0051] Fig.11 is a schematic diagram of the structure of a computing device provided in an embodiment of the present application;

[0052] Fig.12 is a schematic diagram of the structure of a computing device cluster provided in an embodiment of the present application;

[0053] Fig.13 is a schematic diagram of a network connection relationship of a computing device provided in an embodiment of the present application;

[0054] Fig.14 It is a structural diagram of a terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the implementation methods of the present application will be further described in detail below in conjunction with the accompanying drawings.

[0056] Before explaining in detail the makeup plan generation method provided in the embodiment of the present application, the application scenarios and implementation environment involved in the embodiment of the present application are first introduced.

[0057] As people's living standards continue to improve, beauty and daily dressing have become a special concern for people who love beauty, and they have to complete their work every day. Most people who love beauty rely on self-learning to complete it alone. Take beauty as an example. Since there are many styles in the field of beauty, such as European and American makeup, Korean makeup, Hong Kong style, etc., and beauty styles are constantly being innovated; at the same time, everyone's face shape, skin color, and preferences are also different. Therefore, applying a favorite beauty style to a specific individual is a typical personalized and customized solution design, as well as a specific implementation process.

[0058] In other words, if you need to apply a certain makeup style to a specific user and achieve a satisfactory effect for the user, you must ensure that the makeup style is suitable for the user's face shape, skin color, preferences, etc.; at the same time, you must ensure that the user can use the makeup products to successfully complete the makeup process so as to apply the makeup style to their own face shape.

[0059] Various makeup hosts / bloggers promote makeup products by showing makeup skills and their own charm, but it is difficult to determine whether these makeup products that "look good" on others are suitable for viewers / buyers. It may be that the makeup products and makeup styles are not suitable for the personal situation of the viewers / buyers; it may also be that there are too many makeup steps and the implementation of the makeup steps is too complicated, making it difficult for viewers / buyers to use the same makeup products and achieve the same makeup effect.

[0060] As an example, when a beauty anchor is doing live streaming to sell products, he or she will showcase the beauty products through product introductions, personal charm, and the effects of the anchor's use. A beauty product that looks good on the beauty anchor's face may not necessarily be suitable for viewers / buyers.

[0061] Similarly, for e-commerce of beauty products, the product introduction page also uses preset model pictures to show the makeup test effect. The seemingly perfect makeup effect is limited to the overall style of the model and may not be suitable for the buyer. Therefore, even if the buyer purchases the same beauty product, he may choose to return it because the expected beauty effect is not achieved, or give up trying it because he does not get the desired beauty effect.

[0062] As another example, after introducing a beauty product, a beauty blogger will use the corresponding beauty product to put on makeup on the spot and explain the makeup steps to demonstrate the beauty effect of the beauty product. However, since the makeup skills of the viewer / buyer are different from those of the beauty blogger, even if the viewer / buyer imitates the makeup steps of the beauty blogger, he / she still cannot achieve the same beauty makeup.

[0063] In addition to the beauty field, outfit of the day (OOTD) is also a hot topic on Internet applications. Bloggers / models show some dressing suggestions and experiences to provide reference and suggestions to buyers. However, similar to beauty, the display results seen by viewers / buyers are bloggers or models, not themselves; and everyone's body shape and dressing style are also very different. The viewer / buyer may not be suitable for the dressing style of the blogger / model, and his / her body shape cannot achieve the same effect as the blogger / model.

[0064] To sum up, the existing recommendation / display methods of beauty and clothing are all to show the makeup plans of bloggers / models, rather than viewers / buyers. As a result, viewers / buyers may find it difficult to achieve the desired makeup effects due to personal differences, makeup abilities, etc. after simply referring to and copying them.

[0065] Based on this, the embodiment of the present application provides a method for generating a makeup plan, which generates a makeup plan suitable for the target user through the makeup effects of some models accumulated by the large model, the experience and skills explained by the anchor / bloggers, etc., so that the target user can complete the makeup through a method similar to "tracing" (a traditional method of learning calligraphy, which refers to copying on paper printed with red characters or hollow red characters, and is one of the best training methods for beginners to learn writing).

[0066] In other words, the makeup plan generating method provided in the embodiment of the present application can act as an image consultant for the target user based on a large number of existing makeup effects, makeup experience and makeup skills, so as to provide the target user with personalized and customized makeup plans according to the actual needs of the target user, and can also guide the user to complete the entire makeup process based on the makeup plan.

[0067] Please refer to Figure 1 , Figure 1 It is a schematic diagram of an implementation environment shown in the embodiment itself, and the implementation environment includes at least one user terminal 110 and a server 120, and the user terminal 110 can be connected to the server 120 for communication. The communication connection can be a wired or wireless connection, which is not limited in the embodiment of the present application.

[0068] In some embodiments, the user terminal 110 is used to intelligently interact with the target user, collect the user appearance image of the target user, and the makeup description information of the target user describing the desired makeup effect, and then send the user appearance image to the server 120. After receiving the user appearance image and the makeup description information, the server 120 first determines at least one makeup effect based on the makeup description information; then applies the at least one makeup effect to the user appearance image to generate at least one user makeup image; and then sends the at least one user makeup image to the user terminal 110. The user terminal 110 receives and displays the at least one user makeup image sent by the server 120 for the target user to browse and select.

[0069] In some embodiments, the user terminal 110 may determine a target makeup image and send the target makeup image to the server 120 to request the server 120 to provide a makeup implementation solution corresponding to the target makeup image. After receiving the target makeup image, the server 120 determines the makeup implementation solution corresponding to the target makeup image, the makeup implementation solution including a plurality of sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step, and sends the makeup implementation solution to the user terminal 110. The user terminal 110 receives and displays the makeup implementation solution sent by the server 120 for the target user to imitate and perform makeup.

[0070] In a specific implementation, the user terminal 110 may be any electronic product that can interact with the user through one or more methods such as a keyboard, a touchpad, a touch screen, a remote control, voice interaction or a handwriting device, for example, a personal computer (PC), a mobile phone, a smart phone, a personal digital assistant (PDA), a handheld computer (PPC), a tablet computer, a smart car machine, a smart TV, etc. The server 120 may be an independent server, or a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms, or a cloud computing service center.

[0071] Those skilled in the art should understand that the above-mentioned user terminal 110 and server 120 are only examples, and other existing or future terminals or servers that may appear, if applicable to the embodiments of the present application, should also be included in the protection scope of the embodiments of the present application and are included here by reference.

[0072] It should be noted that the application scenarios and implementation environments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Ordinary technicians in this field can know that with the emergence of new application scenarios and the evolution of the implementation environment, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0073] Next, the makeup plan generation method provided in the embodiment of the present application is explained in detail.

[0074] Please refer to Figure 2 The embodiment of the present application provides a makeup solution generation method to generate at least one user makeup image according to the user appearance image and makeup description information. The at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image. Figure 1 Taking the user terminal 110 and the server 120 as an example, the makeup plan generating method may include the following steps 201 to 205.

[0075] Step 201: The user terminal obtains the user appearance image and makeup description information of the target user.

[0076] The makeup description information indicates the makeup effect expected by the target user. The makeup description information may include multiple makeup description words, or may be a paragraph of makeup description content, which is not limited in the present embodiment.

[0077] In a possible implementation, the process of obtaining the user appearance image of the target user is as follows: the user terminal can collect the video data of the target user in real time through its own camera or a camera connected to the user terminal, so as to determine the user appearance image of the target user based on the video data; or the target user uploads a user appearance image of himself to the user terminal, and the user appearance image can be an image taken by other devices at other times. The embodiments of the present application are not limited to this.

[0078] In a possible implementation, the process of obtaining the makeup description information of the target user is as follows: the user terminal collects the makeup description information input by the target user through a voice receiving device provided by the user terminal or a voice receiving device connected to the user terminal; or the target user manually inputs the makeup description information in the user terminal interface. This embodiment of the application does not limit this.

[0079] It should be noted that in all embodiments of the present application, "makeup" includes at least two dimensions: beauty makeup and dressing style. Therefore, the makeup description information can be understood as beauty description information, which is used to indicate the beauty effect that the target user expects in facial makeup; the makeup description information can also be understood as dressing description information, which is used to indicate the styling effect that the target user expects in clothing.

[0080] In some embodiments, in order to accurately identify specific makeup parts and obtain a more accurate user image, when the makeup description information is beauty makeup description information, the user appearance image can be a facial image of the target user to highlight the facial features of the target user. When the makeup description information is clothing description information, the user appearance image can be a full-body image of the target user to highlight the body features of the target user.

[0081] Of course, the user terminal may also obtain a partial image of the target user's corresponding part according to the makeup description information provided by the target user, and use it as the user's appearance image; or the user terminal may directly obtain a full-body image of the target user, and then determine the specific part that needs to be made up according to the makeup description information provided by the target user, and then determine the partial area image of the makeup part in the full-body image as the user's appearance image. The embodiments of the present application are not limited to this.

[0082] Step 202: The user terminal sends a user appearance image and makeup description information to the server to instruct the server to generate at least one user makeup image.

[0083] The user terminal can directly send the user's appearance image and makeup description information to the server, and the server automatically executes the following step 203 after receiving the user's appearance image and makeup description information. The user terminal can also send a makeup design request to the server, and carry the user's appearance image and makeup description information in the request. The server responds to the makeup design request and executes the following step 203 based on the carried user's appearance image and makeup description information. The embodiment of the present application does not limit the way in which the user terminal sends the user's appearance image and makeup description information.

[0084] Step 203: The server receives the user appearance image and makeup description information sent by the user terminal, and generates at least one user makeup image based on the user appearance image and the makeup description information through a trained makeup effect generation model.

[0085] Among them, at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image. That is, the facial features and bone point structure of the user appearance image are kept unchanged, and at least one makeup effect is superimposed on the corresponding part of the user appearance image by texture rendering to generate the user makeup image, rather than regenerating an image that satisfies the makeup effect based on at least one makeup effect and the user appearance image as the user makeup image, so that the authenticity of the user makeup image can be guaranteed.

[0086] In some embodiments, considering that the user's facial features and body shape have not only height information and width information, but also depth information, therefore, in order to ensure that the makeup effect is more in line with the user's actual face shape and body shape, when generating the user makeup image, it is also necessary to obtain the first geometric grid image of the target user to reflect the depth information of the target user's appearance, so that the makeup effect of the user makeup image output by the makeup effect generation model is better.

[0087] In a possible implementation, the implementation process of step 203 may be: obtaining a first geometric grid image corresponding to the user appearance image; and generating at least one user makeup image through a trained makeup effect generation model based on the user appearance image, the first geometric grid image and the makeup description information.

[0088] The first geometric mesh image can be generated by a two-dimensional user appearance image. For example, based on the Mesh data corresponding to the user appearance image, a mesh surface map is generated to obtain the first geometric mesh image corresponding to the user appearance image. The embodiment of the present application does not limit the method of generating the first geometric mesh image, and reference may be made to the relevant mesh generation algorithm.

[0089] Optionally, the hardware information of the user terminal may be adjusted so that the user terminal can directly obtain the three-dimensional user appearance features, thereby generating a first geometric grid image of the target user based on the three-dimensional user appearance features. For example, the user terminal is connected to a depth camera, and the three-dimensional user appearance image is captured by the depth camera to generate the first geometric grid image, so that the appearance details of the target user are richer and the portrait is more three-dimensional and natural.

[0090] It should be noted that the first geometric grid image can be generated by the user terminal and then sent to the server, or the server can generate the first geometric grid image corresponding to the user appearance image based on the user appearance image. The embodiment of the present application does not impose any restrictions on this.

[0091] In some embodiments, based on the user appearance image, the first geometric grid image and the makeup description information, the implementation process of generating at least one user makeup image through a makeup effect generation model includes the following steps (1)-(2).

[0092] (1) Based on the makeup description information, determine the target prompt template from the prompt template library.

[0093] The prompt template library includes a plurality of makeup prompt templates, and each makeup prompt template includes a plurality of makeup prompts describing a makeup effect.

[0094] It should be noted that for different users, the makeup description information for the same makeup effect is different. For users engaged in makeup design, the makeup description information used to describe a makeup effect will be detailed, comprehensive, and accurate; while for ordinary users, the makeup description information used to describe a makeup effect may be relatively monotonous, incomplete, and inaccurate. Based on this, based on the makeup description information provided by the target user, the server can enrich and improve the makeup description information provided by the target user based on the prompt template library before analyzing the makeup effect expected by the target user, so as to improve the accuracy of the makeup description information, so that the user makeup image output by the makeup effect generation model is more accurate.

[0095] In one possible implementation, keyword matching is performed between the makeup description information and multiple makeup prompt templates in the prompt template library, the number of matching words between each makeup prompt template and the makeup description information is determined, and the makeup prompt template with the largest number of matching words is determined as the target prompt template.

[0096] Optionally, at least one candidate prompt template may be first determined from a plurality of makeup prompt templates based on a matching word threshold, and then a target prompt template may be determined from the at least one candidate prompt template based on a template selection strategy.

[0097] In another possible implementation, semantic matching is performed between the makeup description information and multiple makeup prompt templates in the prompt template library, the semantic similarity between each makeup prompt template and the makeup description information is determined, and the makeup prompt template with the highest semantic similarity is determined as the target prompt template.

[0098] Optionally, at least one candidate prompt template may be first determined from a plurality of makeup prompt templates based on a similarity threshold, and then a target prompt template may be determined from the at least one candidate prompt template based on a template selection strategy.

[0099] As an example, the above template selection strategy can be user preference, template score, number of template uses, makeup difficulty, etc., and the embodiments of the present application do not limit this.

[0100] In some embodiments, the number of target prompt templates may be one or more. When a large number of user makeup images need to be output, multiple target prompt templates may be selected from the prompt template library to increase the diversity of makeup effects, so that the number of user makeup images output by the makeup effect generation model is larger and more accurate, and the embodiments of the present application do not limit this.

[0101] (2) Inputting the target prompt template, the user appearance image and the first geometric grid image into the makeup effect generation model to obtain at least one user makeup image output by the makeup effect generation model.

[0102] It should be understood that the makeup effect generation model is equivalent to an expert system in the field of beauty / dressing, which may include at least one network model. The makeup effect generation model is a model trained with a large number of users' makeup styles, makeup plans, beauty products, clothing items and other information / pictures. It has the ability to generate personalized and customized makeup effects based on user appearance images and makeup prompts, and render the makeup effects on the user's appearance images, so that users can intuitively understand their actual makeup after using the makeup.

[0103] In one possible implementation, the makeup effect generation model first generates at least one makeup effect based on the target prompt template; then, based on the first geometric grid image and the user appearance image, renders the at least one makeup effect on the user appearance image to generate at least one user makeup image.

[0104] Since the user makeup image is an image output by the makeup effect generation model, the number of user makeup images can be adjusted by adjusting the output amount of the makeup effect generation model. For example, if the output amount of the makeup effect generation model is set to 10, the makeup effect generation model outputs 10 user makeup images based on the target prompt template, the user appearance image and the first geometric grid image.

[0105] It should be noted that, in the at least one user makeup image, the makeup effects of each user makeup image are not completely the same. Since the "makeup" in the embodiment of the present application includes beauty makeup and / or dressing, the makeup effects are not completely the same means that the beauty makeup effects are not completely the same, and / or the dressing effects are different.

[0106] As an example, if the makeup effect is a beauty makeup effect, in the 10 output user beauty makeup images, the lip beauty makeup effects of the first user beauty makeup image and the second user beauty makeup image can be the same, and the eye makeup effects of the third user beauty makeup image, the fourth user beauty makeup image, and the seventh user beauty makeup image can be the same. That is, as long as there is one different beauty makeup effect in each user beauty makeup image, the two user beauty makeup images are considered different.

[0107] As another example, if the makeup effect is a dressing effect, in the 10 output user dressing images, the first user dressing image and the second user dressing image are matched with the same shirt, and the third user dressing image, the fourth user dressing image and the seventh user dressing image are matched with the same pants. That is, as long as there is one different dressing item in each user dressing image, the two user dressing images are considered different.

[0108] Step 204: The server sends at least one user makeup image to the user terminal to instruct the user terminal to display the at least one user makeup image.

[0109] In some embodiments, based on the generated at least one user makeup image, the server may also determine the display priority of each user makeup image in the at least one user makeup image; based on the display priority of the at least one user makeup image, the at least one user makeup image is sorted to obtain the image display order of the at least one user makeup image. At this time, the implementation process of the server sending at least one user makeup image to the user terminal is: sending at least one user makeup image and the image display order to the user terminal to instruct the user terminal to display the at least one user makeup image according to the image display order.

[0110] Among them, the display priority of each user's makeup image can be determined based on a preset evaluation mechanism and continuous feedback from users using various makeup templates, and the embodiments of the present application do not limit this.

[0111] As an example, the evaluation mechanism may include makeup complexity, user style matching, etc. The higher the makeup complexity, the lower the display priority; the higher the user style matching, the higher the display priority.

[0112] In a possible implementation, based on the display priority of the at least one user makeup image, the at least one user makeup image may be sorted in order of display priority from high to low to obtain an image display order of the at least one user makeup image. Since the user makeup image with a higher display priority is likely to be the makeup effect that the target user likes, the user terminal may display the user makeup image with a higher display priority in front according to the image display order, making it easier to guess the user's preference, thereby increasing the target user's satisfaction.

[0113] Step 205: The user terminal receives and displays at least one user makeup image sent by the server.

[0114] In some embodiments, if the server also sends an image display order of at least one user makeup image, the implementation process of step 205 includes: receiving the image display order of the at least one user makeup image sent by the server, and displaying the at least one user makeup image according to the image display order.

[0115] In some embodiments, if the server does not send the image display order and only sends the at least one user makeup image, the implementation process of step 205 includes: receiving the at least one user makeup image sent by the server, and the user terminal displays the at least one user makeup image in a random order; or, the user terminal may also display the at least one user makeup image in sequence according to the receiving order; or, the user terminal may also determine the display priority of each user makeup image according to user preferences, historical data, etc. in the above manner, and then determine the image display order of the at least one user makeup image based on the display priority of each user makeup image, and then display the at least one user makeup image according to the image display order.

[0116] That is, the operation of determining the image display order can be performed by the server or by the user terminal, and the embodiment of the present application does not limit this.

[0117] In an embodiment of the present application, the server generates at least one user makeup image through a makeup effect generation model based on the user appearance image of the target user and the makeup description information provided by the target user. Since the user appearance image can accurately reflect the appearance characteristics of the target user, and the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image, the makeup effect in the user makeup image has a higher degree of fit with the user's appearance, and the original characteristics of the user's appearance are not changed, and the generated user makeup image is more realistic. Since the user makeup image can reflect the actual situation of the makeup effect applied to the appearance of the target user, the target user can analyze and judge whether the makeup effect corresponding to the makeup description information is suitable for him / her based on the at least one user makeup image, and obtain a makeup plan suitable for him / her by modifying the makeup description information.

[0118] Based on the above examples, please refer to Figure 3 , the embodiment of the present application also provides another makeup scheme generation method, which generates a makeup implementation scheme corresponding to the target makeup image according to the target makeup image, and the makeup implementation scheme includes a plurality of sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step. Figure 1 Taking the user terminal 110 and the server 120 as an example, the makeup plan generating method may include the following steps 206 to 210.

[0119] Step 206: The user terminal determines a target makeup image based on at least one user makeup image.

[0120] The target makeup image is a makeup image determined by the target user based on the at least one user makeup image. Therefore, the process of determining the target makeup image includes the following methods.

[0121] In a first implementation manner, after the user terminal displays at least one user makeup image, a user makeup image selected by a target user is determined as a target makeup image.

[0122] In a second implementation manner, if the target user does not select a target makeup image from at least one displayed user makeup image within a preset time period, the first user makeup image displayed in the front is determined as the target makeup image.

[0123] For the first and second implementations, the target makeup image is one of at least one user makeup image provided by the server. At this time, steps 206 to 210 are continuous with steps 201 to 205 in time, that is, steps 201 to 210 are executed in sequence to complete the entire makeup solution generation method.

[0124] In a third implementation, after the user terminal displays at least one user makeup image, the target user browses the at least one user makeup image and fails to select a satisfactory user makeup image from among them. At this time, the target user can upload a makeup image of himself on the user terminal as the target makeup image. That is, the target makeup image is a makeup image uploaded by the target user.

[0125] For the third implementation, if the target makeup image is a makeup image uploaded by the user, step 206 may be discontinuous with step 205. That is, the above steps 201 to 205 are performed independently to provide the target user with at least one user makeup image, so that the target user can understand the application of a certain makeup effect on himself. Steps 206 to 210 are performed independently to generate a makeup implementation plan corresponding to the target makeup image for the target user, so as to facilitate the target user to perform makeup.

[0126] Step 207: The user terminal sends the target makeup image to the server to instruct the server to determine a makeup implementation solution corresponding to the target makeup image.

[0127] The makeup implementation scheme is a specific implementation scheme for achieving the makeup effect of the target makeup image. In other words, the makeup implementation scheme is the description information of the specific implementation process for guiding the target user to restore / imitate the same makeup effect on his / her own appearance.

[0128] In some embodiments, the makeup implementation scheme includes a plurality of sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step.

[0129] As an example, taking the target makeup image as a beauty effect applied to the user appearance image of the target user, the makeup implementation solution may include specific makeup steps for achieving the beauty effect on the face of the target user, as well as specific instructions for each makeup step.

[0130] As another example, taking the target makeup image as a dressing effect applied to the user appearance image of the target user, the makeup implementation plan may include specific dressing steps for achieving the dressing effect on the target user's appearance, as well as specific instructions for each dressing step.

[0131] Step 208: The server receives the target makeup image sent by the user terminal, and determines a makeup implementation solution corresponding to the target makeup image.

[0132] In some embodiments, the process of determining the makeup implementation solution corresponding to the target makeup image is as follows: inputting the target makeup image into a trained makeup solution analysis model, and obtaining the makeup implementation solution corresponding to the target makeup image output by the makeup solution analysis model.

[0133] In a possible implementation, the makeup prompt information corresponding to the makeup implementation step includes one or more of step description information, makeup texture data, makeup product information and auxiliary tool information required for the makeup implementation step. The makeup texture data includes makeup contour information and texture positioning information, the makeup contour information indicates the contour of the makeup effect corresponding to the makeup implementation step, and the texture positioning information indicates the position of the makeup effect corresponding to the makeup implementation step.

[0134] As an example, taking the makeup map data as eye shadow map data, since applying eye shadow often involves multiple steps and different colors need to be superimposed / smudged at different positions around the eyes, the makeup contour information in the eye shadow map data can be the specific application shape of each color of eye shadow, and the map positioning information indicates the specific application position of each color of eye shadow.

[0135] Step 209: The server sends the makeup implementation plan to the user terminal to instruct the user terminal to display the makeup implementation plan.

[0136] It should be noted that when the server sends the makeup implementation plan to the user terminal, it can send the entire makeup implementation plan to the user terminal at one time to instruct the user terminal to sequentially display the makeup prompt information corresponding to each makeup implementation step in the makeup implementation plan. Of course, the server can also send makeup prompt information corresponding to any makeup implementation step to the user terminal according to the makeup needs of the target user, and this embodiment of the application does not limit this.

[0137] Step 210: The user terminal receives and displays the makeup implementation solution sent by the server.

[0138] In some embodiments, the process in which the server sends the makeup implementation scheme step by step by interacting with the user terminal is as follows: the server sends makeup prompt information corresponding to the first makeup implementation step to the user terminal, and the user terminal receives and displays the makeup prompt information corresponding to the first makeup implementation step. In response to the step jump operation triggered by the target user to skip the first makeup implementation step, the user terminal sends a step jump instruction to the server, and the step jump instruction is used to request the makeup prompt information corresponding to the second makeup implementation step. After receiving the step jump instruction sent by the user terminal to skip the first makeup implementation step, the server sends the makeup prompt information corresponding to the second makeup implementation step to the user terminal in response to the step jump instruction, and the user terminal receives and displays the makeup prompt information corresponding to the second makeup implementation step.

[0139] The first makeup implementation step is any one of the makeup implementation steps in the makeup implementation scheme, and the second makeup implementation step is the next makeup implementation step adjacent to the first makeup implementation step in the makeup implementation scheme.

[0140] It should be understood that the step jump instruction for skipping the first makeup implementation step can be triggered after the target user browses and executes the specific makeup corresponding to the first makeup implementation step. At this time, the target user executes the first makeup implementation step in the process of imitating the makeup, that is, the sequence jumps to the second makeup implementation step. The step jump instruction for skipping the first makeup implementation step can also be triggered when the target user browses the makeup prompt information of the first makeup implementation step but does not execute the specific makeup. At this time, the target user does not execute the first makeup implementation step in the process of imitating the makeup, that is, the first makeup implementation step is skipped.

[0141] As an example, if the makeup implementation scheme includes makeup implementation step 1, makeup implementation step 2, makeup implementation step 3, makeup implementation step 4 and makeup implementation step 5, then the process of the server and the user terminal sending the makeup implementation scheme step by step can be: the server sends makeup prompt information a corresponding to makeup implementation step 1 to the user terminal, and after the user terminal receives and displays the makeup prompt information a, it detects whether the target user triggers a step jump operation for skipping the first makeup implementation step. If the user terminal detects that the target user has triggered the step jump operation, it sends a step jump instruction to the server. The server receives and responds to the step jump instruction, and sends makeup prompt information b corresponding to makeup implementation step 2 to the user terminal, and after the user terminal receives and displays the makeup prompt information b, it continues to execute the step of detecting whether the target user has triggered the step jump operation. In this way, through the interaction between the server and the user terminal, the user terminal is instructed to display the makeup implementation plan to the target user, that is, to display the makeup prompt information a corresponding to makeup implementation step 1, the makeup prompt information b corresponding to makeup implementation step 2, the makeup prompt information c corresponding to makeup implementation step 3, the makeup prompt information d corresponding to makeup implementation step 4 and the makeup prompt information e corresponding to makeup implementation step 5 in sequence.

[0142] As described above, the makeup prompt information of the makeup implementation step includes one or more of step description information, makeup texture data, makeup product information and auxiliary tool information required for the makeup implementation step. Among them, the makeup texture data includes makeup contour information and texture positioning information. The makeup contour information indicates the contour of the makeup effect corresponding to the makeup implementation step, and the texture positioning information indicates the position of the makeup effect corresponding to the makeup implementation step.

[0143] As an example, for the same makeup implementation step, based on the step description information corresponding to the makeup implementation step, the low-rank adaptation of large language lodels (LORA) mapping model of the large language model is used to generate the corresponding makeup contour information and mapping positioning information, and the makeup mapping data corresponding to the makeup implementation step is obtained. The specific implementation process can be referred to the relevant existing technology, which will not be described in detail here.

[0144] Among them, the LORA model is a model that can be trained with a small amount of data. When generating pictures, the LORA model will be used in combination with the large model to adjust the output picture results. For example, the large model is like a person without makeup, and the LORA model is like the person without makeup has put on makeup, plastic surgery or role-playing (cosplay), but its inner nature is still based on the large model. Of course, the LORA model is not limited to characters, there are corresponding LORA models for various scenes, animations, and styles.

[0145] When the makeup prompt information of the second makeup implementation step includes makeup map data, the user terminal can display the makeup effect map corresponding to the second makeup implementation step, and the implementation process includes the following steps (1)-(3).

[0146] (1) Obtain the real-time appearance image of the target user.

[0147] In a possible implementation, the user terminal may collect the appearance image of the target user in real time through a camera built into the user terminal or a camera connected to the user terminal to obtain a real-time appearance image of the target user at the current moment.

[0148] As described above, if the step jump instruction is triggered after the target user browses and executes the specific makeup corresponding to the first makeup implementation step, at this time, the target user has already executed the first makeup implementation step in the process of imitating the makeup, and the real-time appearance image is the makeup image of the target user after completing the first makeup implementation step. If the step jump instruction is triggered when the target user browses the makeup prompt information of the first makeup implementation step but does not execute the specific makeup, at this time, the target user has not executed the first makeup implementation step in the process of imitating the makeup, and the real-time appearance image is the makeup image of the target user before browsing the first makeup implementation step.

[0149] That is, after receiving the makeup prompt information corresponding to the second makeup step, the user terminal executes the above step (1) to obtain the real-time appearance image of the target user, and then executes the following step (2) based on the real-time appearance image and the makeup prompt information corresponding to the second makeup step.

[0150] (2) Based on the makeup map data corresponding to the second makeup implementation step, the real-time appearance image is rendered with makeup effects to obtain a makeup effect image corresponding to the second makeup implementation step.

[0151] The makeup effect picture corresponding to the second makeup implementation step is generated based on the makeup texture data corresponding to the second makeup implementation step, by applying the makeup effect corresponding to the second makeup implementation step to the real-time appearance image.

[0152] Taking into account that the user's facial features and body shape not only have height and width information, but also depth information, in order to ensure that the makeup effect is more in line with the user's actual appearance, when generating the makeup rendering, it is also necessary to obtain the second geometric grid image corresponding to the real-time appearance image to reflect the depth information of the target user's current appearance, so that the makeup effect presented in the makeup rendering is better.

[0153] The second geometric grid image can be generated by a two-dimensional real-time appearance image. For example, based on the Mesh data corresponding to the real-time appearance image, a grid surface map is generated to obtain the second geometric grid image corresponding to the real-time appearance image. The embodiment of the present application does not limit the method for generating the second geometric grid image, and reference may be made to the relevant grid generation algorithm.

[0154] In one possible implementation, the implementation process of generating a makeup effect map corresponding to the second makeup implementation step is: generate a second geometric grid image corresponding to the real-time appearance image; then, based on the texture positioning information corresponding to the second makeup implementation step and the second geometric grid image, determine the makeup rendering position in the real-time appearance image; then, based on the makeup rendering position, perform makeup effect rendering on the real-time appearance image according to the makeup contour information corresponding to the second makeup implementation step, and obtain the makeup effect map corresponding to the second makeup implementation step.

[0155] Among them, the texture positioning information may include texture position coordinates, texture position corresponding to human bone points, etc. Based on the texture positioning information and the second geometric grid image, the makeup rendering position indicated by the texture positioning information can be determined in the real-time appearance image.

[0156] It should be noted that, for the specific implementation method of determining the rendering position in the real-time appearance image based on the map position coordinates and the map position corresponding to the human skeleton point, reference can be made to the relevant prior art, and the embodiments of the present application do not limit this.

[0157] In addition, after determining the makeup rendering position, the augmented reality kit (AR Kit) that comes with / installed on the user terminal can be used to render the makeup effect on the real-time appearance image according to the makeup contour information corresponding to the second makeup implementation step, thereby achieving mixed rendering of the virtual content layer and the real-time content layer.

[0158] (3) Display the makeup effect diagram corresponding to the second makeup implementation step.

[0159] The user terminal displays the makeup effect diagram corresponding to the second makeup implementation step in the display interface, which is convenient for the user to imitate the makeup.

[0160] Based on the above steps (1)-(3), it can be known that considering that the target user may have performed the makeup of the first makeup implementation step or may not have performed the makeup of the first makeup implementation step, when displaying the second makeup effect picture, the embodiment of the present application does not mechanically continue to superimpose the makeup texture data corresponding to the second makeup implementation step on the makeup effect picture corresponding to the first makeup implementation step, but obtains the real-time appearance image of the target user, and generates the makeup effect picture corresponding to the second makeup implementation step based on the real-time appearance image and the makeup texture data corresponding to the second makeup implementation step. In this way, the makeup effect pictures corresponding to each makeup implementation step are generated in real time according to the actual makeup progress of the user, which improves the real-time and accuracy of the makeup effect pictures corresponding to the makeup implementation steps.

[0161] In the case where the makeup prompt information of the makeup implementation step also includes step description information, makeup product information, and auxiliary tool information, the user terminal can simultaneously display the step description information, makeup effect diagram, makeup product information, and auxiliary tool information corresponding to the second makeup implementation step. The makeup effect diagram, step description information, makeup product information, and auxiliary tool information are displayed in different areas, and the display areas of the step description information, makeup product information, and auxiliary tool information surround the display area of ​​the makeup effect diagram.

[0162] As an example, see Figure 4 , dividing the display interface of the user terminal into five areas, namely, top, middle, bottom, left and right, to simultaneously display the step description information, makeup effect diagram, makeup product information and auxiliary tool information corresponding to the second makeup implementation step.

[0163] Among them, the middle area, as the largest display area, can be used to display the makeup effect diagram of the second makeup implementation step, that is, the rendered image after the real-time appearance image of the target user is superimposed with the makeup map data, so as to facilitate the user to imitate the makeup. The upper area displays the step description information of the second makeup implementation step, and the step description information is used to indicate the specific implementation process of the second makeup implementation step. Optionally, the key information in the step description information can be displayed visually, and at the same time, more detailed and friendly step description information can be provided to the target user through voice prompts. The left area is used to display the makeup product information of the second makeup implementation step, and the makeup product information may include product schematics, brands, specifications and other information of specific recommended products determined based on the context. The right area is used to display the auxiliary tool information when implementing the second makeup step, such as beauty brushes, eyebrow pencils, accessories, etc.; if there is no specific recommended brand, the type and characteristics of the specific tool are clearly displayed, and this embodiment of the application does not limit this.

[0164] Optionally, the current completion progress of the makeup implementation plan can also be displayed on the left side of the lower area, which can be displayed in the form of a percentage; the right side of the lower area can present a comparison between the second makeup implementation step and the total makeup implementation step, so that the target user can understand the current makeup step and the overall makeup progress.

[0165] In an embodiment of the present application, the user terminal can also obtain a target makeup image determined by the target user, and send the target makeup image to the server to request the server to provide a makeup implementation solution corresponding to the target makeup image. That is, when the target user provides a target makeup image, the server can use the trained makeup solution analysis model to infer the makeup implementation solution corresponding to the target makeup image, so that the target user can imitate makeup based on the makeup implementation solution. Moreover, the makeup implementation solution includes a plurality of sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step. The target user can refer to the makeup prompt information corresponding to each makeup implementation step in turn, and complete the entire makeup implementation solution in a manner similar to "tracing", which greatly improves the efficiency of the user's imitation of makeup and increases user satisfaction.

[0166] Based on the makeup plan generation method shown in the above embodiment, the present application can generate personalized and customized user makeup effect pictures for users based on two trained AI generated content (AI generated content, AIGC) models, namely the makeup effect generation model and the makeup plan analysis model; it can also generate a makeup implementation plan based on the target makeup image provided by the user, and guide the user to imitate and complete the entire makeup.

[0167] Among them, the makeup effect generation model and makeup solution analysis model may include multiple sub-models, which require a lot of learning and a lot of computational analysis to complete the task of generating user makeup images and makeup implementation solutions. Therefore, considering the computing power requirements and resource consumption, the makeup effect generation model and makeup solution analysis model can be deployed in the cloud server, that is, the above Figure 1-3 The server shown is a cloud server, or a cloud computing server center.

[0168] See also Figure 5The makeup scheme generation system shown in the figure includes a user terminal and a cloud server. Among them, the user terminal includes: image acquisition equipment (such as a camera), image output equipment (such as a display screen), audio input equipment (such as a microphone), audio output equipment (such as a speaker) and a user-side processing system, etc.; the user-side processing system includes an interconnected image acquisition and Mesh generation system, an intelligent interactive feedback system and an AR layered rendering system, etc. The cloud server includes a cloud processing system, which includes an AIGC large model, a prompt template library, a recommendation and evaluation system, a task control and scheduling system, etc. Among them, the AIGC large model includes a makeup effect generation model and a makeup scheme analysis model.

[0169] On the user terminal side, the image acquisition and mesh generation system is connected to the image acquisition device and the image output device to acquire user appearance images, real-time appearance images, etc., and generate corresponding geometric mesh images. The intelligent interactive feedback system is respectively connected to the image acquisition device, the image output device, the audio input device, and the audio output device, etc., to interact with the target user and acquire information such as text and voice commands input by the user. Among them, the image acquisition device is used to acquire video data of the target user; the image output device is used to display images and information, such as displaying at least one user makeup image and makeup generation plan; the audio input device is used to acquire voice interaction commands of the target user; the audio output device is used to play audio by voice, such as playing step-by-step instructions for makeup implementation steps.

[0170] When the user-side processing system executes the makeup scheme generation method, the image acquisition and mesh generation system is used to receive the user appearance image / video data of the target user sent by the image acquisition device in the first stage, generate a first geometric mesh image corresponding to the user appearance image, and then transmit the first geometric mesh image to the intelligent interactive feedback system; in the second stage, the image acquisition and mesh generation system is also used to receive the real-time appearance image / video data of the target user sent by the image acquisition device, generate a second geometric mesh image corresponding to the real-time appearance image, and then transmit the second geometric mesh image to the AR layered rendering system. The intelligent interactive feedback system is used to receive the user appearance image of the target user sent by the image acquisition device, receive the makeup description information of the target user sent by the audio input device, and feedback at least one user makeup image to the image output device in the first stage; in the second stage, the intelligent interactive feedback system is also used to receive the target makeup image determined by the target user, receive the step jump instruction sent by the audio input device, feedback the makeup implementation scheme corresponding to the target makeup image to the image output device, and feedback the step description information of the makeup implementation step in the makeup implementation scheme to the audio output device. The AR layered rendering system is used to receive the makeup texture data corresponding to any makeup implementation step sent by the cloud server in the second stage, and based on the makeup texture data, perform makeup effect rendering on the real-time user appearance image provided by the image acquisition device to generate a makeup effect image corresponding to the makeup implementation step.

[0171] On the cloud server side, the task control and scheduling system is used to receive input information such as instructions, videos, and images from the user terminal, and perform task decomposition and scheduling to coordinate the AIGC large model (including the makeup effect generation model and the makeup solution analysis model) at the back end, the prompt template library, the recommendation and evaluation system, etc. to complete a complex personalized makeup solution generation task, and feed back the final result to the user terminal. The prompt template library includes multiple makeup prompt templates, which are used to enrich and refine the makeup description information in the first stage to determine the target prompt template corresponding to the makeup description information. The makeup effect generation model is used to generate at least one user makeup image according to the user appearance image, the first geometric grid image corresponding to the user appearance image, and the target prompt template in the first stage. The recommendation and evaluation system is used to evaluate the display priority of each user makeup image in the first stage, so as to determine the image display order of at least one user makeup image based on the display priority of at least one user image. The makeup solution analysis model is used to generate the makeup implementation solution corresponding to the target makeup image according to the target makeup image provided by the user terminal in the second stage.

[0172] To sum up, the user terminal and the cloud server implement the makeup plan generation method provided in the embodiment of the present application through end-cloud collaboration. In this way, by utilizing the powerful computing power of the cloud, personalized makeup plan generation services can be provided to multiple user terminals at the same time.

[0173] Since the makeup scheme generation method of the present application includes two scenarios: beauty makeup and dressing, and its implementation process includes two stages, the first stage generates a user makeup image, which may include a user beauty makeup image and a user dressing image; the second stage generates a makeup implementation plan, which may include a beauty makeup implementation plan and a dressing implementation plan.

[0174] Next, the specific process of executing the makeup plan generation method in two scenarios is described in detail.

[0175] Based on the above Figure 5 , taking the generation of personalized beauty plans as an example, the process of generating user beauty images in the first stage and generating beauty implementation plans in the second stage are explained in detail.

[0176] See also Figure 6 ,In the first stage, the user terminal interacts with the cloud server and ,provides the target user with the user’s beauty image including the ,following steps 1-6.

[0177] 1. The user terminal obtains the target user's facial image and beauty description information.

[0178] The beauty description information indicates the beauty effect expected by the target user. For example, the beauty description information may be Korean makeup, suitable for work on weekdays, friendly and energetic, etc.

[0179] 2. The image acquisition and mesh generation system generates a corresponding facial mesh image based on the facial image of the target user.

[0180] 3. The intelligent interactive feedback system sends the target user’s facial image, facial mesh image, and beauty description information to the cloud server.

[0181] 4. Based on the beauty description information, the cloud server determines the target beauty template through the prompt template library and sends the target beauty template to the makeup effect generation model.

[0182] 5. The makeup effect generation model generates at least one user makeup image based on the facial image, the facial mesh image and the target makeup template.

[0183] In a specific implementation, the makeup effect generation model may be a beauty makeup effect generation model to generate at least one user beauty makeup image.

[0184] 6. The recommendation and evaluation system evaluates the display priority of each user's beauty image, thereby determining the image display order of the at least one user's beauty image, and sends the at least one user's beauty image and the image display order to the user terminal.

[0185] The user terminal receives at least one user beauty makeup image and displays the at least one user beauty makeup image in the order in which the images are displayed. The target user interacts with the user terminal through the intelligent interactive feedback system to determine the target beauty makeup image. If the target user is satisfied with the currently displayed user beauty makeup image and selects the target beauty makeup image from it, the process proceeds to stage 2. If the target user is not satisfied with the currently displayed user beauty makeup image and cannot select the target beauty makeup image from it, the target user can provide some new beauty makeup description information through the intelligent interactive feedback system. In response to the newly provided beauty makeup description information, the user terminal jumps to step 3 above and executes the subsequent steps in a loop until the target user selects the target beauty makeup image from the at least one user beauty makeup image displayed on the user terminal.

[0186] See also Figure 7 ,In the second stage, the user terminal interacts with the cloud server and ,provides a beauty implementation solution for the target user including the ,following steps 1-6.

[0187] 1. The user terminal obtains the real-time facial image of the target user.

[0188] 2. The image acquisition and mesh generation system generates a corresponding real-time facial mesh image based on the real-time facial image of the target user.

[0189] 3. An intelligent interactive feedback system interacts with the target user in a way that any user terminal can understand, such as natural language and text, to obtain the target beauty image determined by the target user and send the target beauty image to the cloud server.

[0190] 4. The cloud server determines the beauty implementation plan corresponding to the target beauty image through the makeup plan analysis model. The beauty implementation plan includes multiple sequentially related beauty implementation steps and beauty prompt information corresponding to each beauty implementation step.

[0191] 5. The makeup solution analysis model sends the makeup prompt information corresponding to the Mth makeup implementation step to the user terminal. The makeup prompt information includes makeup map data, step description information, makeup product information and auxiliary tool information.

[0192] In a specific implementation, the makeup solution analysis model may be a beauty makeup solution analysis model to generate a beauty makeup implementation solution corresponding to a target beauty makeup image.

[0193] 6. The AR layered rendering system of the user terminal performs makeup effect rendering on the real-time facial image of the target user based on the makeup map data corresponding to the Mth beauty makeup implementation step, obtains the makeup effect picture corresponding to the Mth beauty makeup implementation step, and displays the makeup effect picture, step description information, makeup product information and auxiliary tool information.

[0194] In this way, the target user refers to the makeup effect picture corresponding to the Mth beauty makeup implementation step, follows the step description information corresponding to the Mth beauty makeup implementation step, and uses the makeup product information and auxiliary tool information corresponding to the Mth beauty makeup implementation step to "trace" to complete the makeup operation of the Mth beauty makeup implementation step.

[0195] Among them, the above-mentioned Mth beauty makeup implementation step is any beauty makeup implementation step in the beauty makeup implementation plan.

[0196] In addition, the intelligent interactive feedback system is also used to detect the target user's feedback on the Mth makeup implementation step, and in response to the step jump operation triggered by the target user, send a step jump instruction to the server. Among them, the target user's feedback on the current process may include: repeating the current step, skipping the current step, entering the next step, etc., which is not limited in the embodiment of the present application, and the corresponding instructions are not limited to the above-mentioned step jump instructions.

[0197] That is, when displaying the makeup implementation plan, the target user can independently control the display progress, making it easier for them to apply makeup through a method similar to "tracing".

[0198] The beauty solution analysis model in the server receives and responds to the step jump instruction, and sends the beauty prompt information corresponding to the M+1th beauty implementation step to the user terminal. In this way, the user terminal loops through steps 4-6 until the entire beauty implementation solution is displayed to the target user.

[0199] To sum up, the makeup solution generation method provided by the present application is applied in beauty makeup scenarios. It can not only generate personalized user makeup images according to the actual needs of the target users, so that users can understand their own beauty makeup effects; it can also provide specific and complete beauty makeup implementation solutions based on the target beauty makeup images, so that the target users can use a similar "tracing" method to apply makeup to achieve the desired beauty makeup effect.

[0200] Based on the above Figure 5Next, taking the generation of a personalized dressing plan as an example, the process of generating a user dressing image is described in detail. Since the dressing implementation plan does not involve a sophisticated and complex implementation process, the user can complete the dressing process by following the instructions. That is, after generating the user dressing image, the target user can refer to the dressing items in the user dressing image and select similar, self-owned items to complete the dressing process. Therefore, when generating a personalized dressing plan for the target user, only the first stage can be executed to generate at least one user dressing image, and there is no need to execute the second stage.

[0201] See also Figure 8 ,The process of the user terminal interacting with the cloud server and providing the target user with the ,user outfit images includes the following steps 1-6.

[0202] 1. The user terminal obtains the full-body image and outfit description information of the target user.

[0203] 2. The image acquisition and mesh generation system generates a corresponding full-body mesh image based on the full-body image of the target user.

[0204] 3. The intelligent interactive feedback system sends the target user’s full-body image, full-body mesh image, and outfit description information to the cloud server.

[0205] The outfit description information indicates the outfit effect expected by the target user, for example, today's outfit recommendation, American style, working lady, moderate price, etc.

[0206] 4. Based on the outfit description information, the cloud server determines the target outfit template through the prompt template library and sends the target outfit template to the makeup effect generation model.

[0207] 5. The makeup effect generation model generates at least one user dressing image based on the full-body image, the full-body mesh image and the target dressing template.

[0208] In a specific implementation, the makeup effect generation model can be a dressing effect generation model to generate at least one user dressing image.

[0209] 6. The recommendation and evaluation system evaluates the display priority of each user's outfit image, thereby determining the image display order of the at least one user's outfit image, and sends the at least one user's outfit image and the image display order to the user terminal.

[0210] Among them, the display priority of each user's outfit images can be determined based on the historical data of the target user, current fashion trends, etc.

[0211] The user terminal receives at least one user outfit image and displays the at least one user outfit image in the order in which the images are displayed. The target user interacts with the user terminal through the intelligent interactive feedback system to determine the target outfit image. If the target user is satisfied with the currently displayed user outfit image and selects the target outfit image from it, the operation ends. If the target user is not satisfied with the currently displayed user outfit image and cannot select the target outfit image from it, the target user can provide some new outfit description information through the intelligent interactive feedback system. In response to the newly provided outfit description information, the user terminal jumps to step 3 above and executes the subsequent steps in a loop until the target user can select the target outfit image from at least one user outfit image displayed on the user terminal.

[0212] It should be noted that for complex dressing styles such as layering, if the user cannot complete the entire dressing process based on the target dressing image, the user can also send the target dressing image to the cloud server and enter the second stage to obtain the dressing implementation solution corresponding to the target dressing image. This embodiment of the application does not limit this.

[0213] To sum up, the makeup plan generation method provided in this application is applied in the dressing scene, and can generate personalized user dressing images according to the actual body shape and dressing needs of the target user, so that the user can understand the dressing effect in his or her actual dressing situation, and thus quickly find a dressing style that satisfies and suits him or her.

[0214] In addition, although the makeup scheme generation method provided in the embodiment of the present application focuses on the two scenarios of "beauty makeup" and "dressing up", any scenario involving personalized and customized scheme generation and the matching of multiple items is applicable to the inventive concept of the present application. For example, interior decoration, indoor furniture matching, etc.

[0215] Please refer to Fig. 9 , Fig. 9 900 is a schematic diagram of a makeup scheme generating device provided in an embodiment of the present application. The makeup scheme generating device 900 can be implemented by software, hardware or a combination of both. Figure 1-8 The makeup scheme generating device 900 comprises: a receiving module 901 , a makeup image generating module 902 and a sending module 903 .

[0216] A receiving module 901 is used to receive a user appearance image and makeup description information of a target user sent by a user terminal, where the makeup description information indicates a makeup effect desired by the target user;

[0217] A makeup image generation module 902, configured to generate at least one user makeup image based on the user appearance image and the makeup description information by using a trained makeup effect generation model, wherein the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image;

[0218] The sending module 903 is used to send at least one user makeup image to the user terminal to instruct the user terminal to display the at least one user makeup image.

[0219] Optionally, the makeup image generation module 902 includes:

[0220] A grid image acquisition unit, used to acquire a first geometric grid image corresponding to the user's appearance image;

[0221] The makeup image generation unit is used to generate at least one user makeup image based on the user appearance image, the first geometric grid image and the makeup description information through a trained makeup effect generation model.

[0222] Optionally, the makeup image generating unit includes:

[0223] A template selection subunit, used to determine a target prompt template from a prompt template library based on the makeup description information, wherein the prompt template library includes a plurality of makeup prompt templates, each of which includes a plurality of makeup prompts describing a makeup effect;

[0224] The makeup image generation subunit is used to input the target prompt template, the user appearance image and the first geometric grid image into the makeup effect generation model to obtain at least one user makeup image output by the makeup effect generation model.

[0225] Optionally, the sending module 903 is further used for:

[0226] Determining a display priority of each user makeup image in at least one user makeup image;

[0227] sorting the at least one user makeup image based on the display priority of the at least one user makeup image to obtain an image display order of the at least one user makeup image;

[0228] At least one user makeup image and an image display order are sent to a user terminal to instruct the user terminal to display the at least one user makeup image according to the image display order.

[0229] Optionally, the device 900 further includes:

[0230] The receiving module 901 is further configured to receive a target makeup image sent by a user terminal, where the target makeup image is a makeup image determined by a target user based on at least one user makeup image;

[0231] A makeup scheme generating module, used to determine a makeup implementation scheme corresponding to a target makeup image, wherein the makeup implementation scheme includes a plurality of sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step;

[0232] The sending module 903 is further used to send the makeup implementation plan to the user terminal to instruct the user terminal to display the makeup implementation plan.

[0233] Optionally, the makeup plan generation module is specifically used to:

[0234] The target makeup image is input into the trained makeup solution analysis model to obtain a makeup implementation solution corresponding to the target makeup image output by the makeup solution analysis model.

[0235] Optionally, the sending module 903 is further configured to:

[0236] Sending makeup prompt information corresponding to a first makeup implementation step to a user terminal, where the first makeup implementation step is any one of the makeup implementation steps in the makeup implementation scheme;

[0237] If a step jump instruction for skipping a first makeup implementation step is received from a user terminal, in response to the step jump instruction, makeup prompt information corresponding to a second makeup implementation step is sent to the user terminal to instruct the user terminal to display the makeup prompt information corresponding to the second makeup implementation step, the second makeup implementation step being the next makeup implementation step adjacent to the first makeup implementation step in the makeup implementation scheme.

[0238] Optionally, the makeup prompt information corresponding to the makeup implementation step includes one or more of step description information, makeup texture data, makeup product information required for the makeup implementation step, and auxiliary tool information;

[0239] The makeup map data includes makeup contour information and map positioning information. The makeup contour information indicates the contour of the makeup effect corresponding to the makeup implementation step, and the map positioning information indicates the position of the makeup effect corresponding to the makeup implementation step.

[0240] In an embodiment of the present application, the makeup scheme generating device 900 generates at least one user makeup image through a makeup effect generating model based on the user appearance image of the target user and the makeup description information provided by the target user. Since the user appearance image can accurately reflect the appearance characteristics of the target user, and the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image, the makeup effect in the user makeup image has a higher degree of fit with the user's appearance, and the original characteristics of the user's appearance are not changed, and the generated user makeup image is more realistic. Since the user makeup image can reflect the actual situation of the makeup effect applied to the appearance of the target user, the target user can analyze and judge whether the makeup effect corresponding to the makeup description information is suitable for him / her based on the at least one user makeup image, and obtain a makeup scheme suitable for him / her by modifying the makeup description information.

[0241] It should be noted that: when the makeup solution generation device 900 provided in the above embodiment generates at least one user makeup image based on the user appearance image and makeup description information, or generates a makeup implementation solution corresponding to the target makeup image based on the target makeup image, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the makeup solution generation device 900 provided in the above embodiment and the makeup solution generation method embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0242] Among them, the receiving module 901, the makeup image generation module 902 and the sending module 903 can all be implemented by software, or can be implemented by hardware. Exemplarily, the implementation of the makeup image generation module 902 is introduced below by taking the makeup image generation module 902 as an example. Similarly, the implementation of the receiving module 901 and the sending module 903 can refer to the implementation of the makeup image generation module 902.

[0243] As an example of a software functional unit, the makeup image generation module 902 may include code running on a computing instance. Among them, the computing instance may include at least one of a physical host (computing device), a virtual machine, and a container. Furthermore, the above-mentioned computing instance may be one or more. For example, the makeup image generation module 902 may include code running on multiple hosts / virtual machines / containers. It should be noted that the multiple hosts / virtual machines / containers used to run the code may be distributed in the same region (region) or in different regions. Furthermore, the multiple hosts / virtual machines / containers used to run the code may be distributed in the same availability zone (AZ) or in different AZs, each AZ including one data center or multiple data centers with close geographical locations. Among them, usually a region may include multiple AZs.

[0244] Similarly, multiple hosts / virtual machines / containers used to run the code can be distributed in the same virtual private cloud (VPC) or in multiple VPCs. Usually, a VPC is set up in a region. For cross-region communication between two VPCs in the same region and between VPCs in different regions, a communication gateway needs to be set up in each VPC to achieve interconnection between VPCs through the communication gateway.

[0245] As an example of a hardware functional unit, the makeup image generation module 902 may include at least one computing device, such as a server, etc. Alternatively, the makeup image generation module 902 may also be a device implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD). The PLD may be a complex programmable logical device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0246] The multiple computing devices included in the makeup image generation module 902 can be distributed in the same region or in different regions. The multiple computing devices included in the makeup image generation module 902 can be distributed in the same AZ or in different AZs. Similarly, the multiple computing devices included in the makeup image generation module 902 can be distributed in the same VPC or in multiple VPCs. The multiple computing devices can be any combination of computing devices such as servers, ASICs, PLDs, CPLDs, FPGAs, and GALs.

[0247] It should be noted that, in other embodiments, the makeup image generation module 902 can be used to execute any step in the makeup plan generation method, the receiving module 901 can be used to execute any step in the makeup plan generation method, and the sending module 903 can be used to execute any step in the makeup plan generation method. The steps that the receiving module 901, the makeup image generation module 902 and the sending module 903 are responsible for implementing can be specified as needed. The full functions of the makeup plan generation device are realized by respectively implementing different steps in the makeup plan generation method through the receiving module 901, the makeup image generation module 902 and the sending module 903.

[0248] Please refer to Fig.10 , Fig.10 is a schematic diagram of a makeup scheme generating device provided in an embodiment of the present application. The makeup scheme generating device 1000 can be implemented by software, hardware or a combination of both. Figure 1-8 The makeup scheme generating device 1000 comprises: an acquisition module 1001 , a sending module 1002 and a receiving module 1003 .

[0249] An acquisition module 1001 is used to acquire a user appearance image and makeup description information of a target user, where the makeup description information indicates a makeup effect desired by the target user;

[0250] The sending module 1002 is used to send the user appearance image and the makeup description information to the server, so as to instruct the server to generate at least one user makeup image based on the user appearance image and the makeup description information by using the trained makeup effect generation model, wherein the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image;

[0251] The receiving module 1003 is used to receive and display at least one user makeup image sent by the server.

[0252] Optionally, the receiving module 1003 is further configured to:

[0253] Receiving an image display order of at least one user makeup image sent by a server;

[0254] At least one user makeup image is displayed in an image display order.

[0255] Optionally, the device 1000 further includes:

[0256] A determination module, configured to determine a target makeup image based on at least one user makeup image;

[0257] The sending module 1002 is further used to send the target makeup image to the server to instruct the server to determine the makeup implementation scheme corresponding to the target makeup image, where the makeup implementation scheme includes a plurality of sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step;

[0258] The receiving module 1003 is also used to receive and display the makeup implementation plan sent by the server.

[0259] Optionally, the receiving module 1003 is further configured to:

[0260] A first receiving unit is used to receive and display makeup prompt information corresponding to a first makeup implementation step sent by a server, where the first makeup implementation step is any one of the makeup implementation steps in the makeup implementation scheme;

[0261] a control unit, configured to respond to a step jump operation triggered by a target user for skipping a first makeup implementation step, and to send a step jump instruction to a server, wherein the step jump instruction is used to request makeup prompt information corresponding to a second makeup implementation step, wherein the second makeup implementation step is a next makeup implementation step adjacent to the first makeup implementation step in the makeup implementation scheme;

[0262] The second receiving unit is used to receive and display makeup prompt information corresponding to the second makeup implementation step sent by the server.

[0263] Optionally, the makeup prompt information of the makeup implementation step includes one or more of step description information, makeup map data, makeup product information required for the makeup implementation step, and auxiliary tool information;

[0264] The makeup map data includes makeup contour information and map positioning information. The makeup contour information indicates the contour of the makeup effect corresponding to the makeup implementation step, and the map positioning information indicates the position of the makeup effect corresponding to the makeup implementation step.

[0265] Optionally, the makeup prompt information of the makeup implementation step includes makeup map data; the second receiving unit is specifically used to:

[0266] An image acquisition subunit, used to acquire a real-time appearance image of a target user;

[0267] A rendering subunit, configured to perform makeup effect rendering on the real-time appearance image based on the makeup map data corresponding to the second makeup implementation step, to obtain a makeup effect map corresponding to the second makeup implementation step;

[0268] The display subunit is used to display the makeup effect diagram corresponding to the second makeup implementation step.

[0269] Optionally, the rendering subunit is specifically used for:

[0270] generating a second geometric mesh image corresponding to the real-time appearance image;

[0271] Determining a makeup rendering position in the real-time appearance image based on the texture positioning information corresponding to the second makeup implementation step and the second geometric mesh image;

[0272] Based on the makeup rendering position, the makeup effect rendering is performed on the real-time appearance image according to the makeup contour information corresponding to the second makeup implementation step to obtain a makeup effect image corresponding to the second makeup implementation step.

[0273] Optionally, the makeup prompt information of the makeup implementation steps also includes step description information, makeup product information and auxiliary tool information; the second receiving unit is further used to:

[0274] Displaying step description information corresponding to the second makeup implementation step, makeup product information corresponding to the second makeup implementation step, and auxiliary tool information corresponding to the second makeup implementation step;

[0275] Among them, the makeup effect picture, step description information, makeup product information and auxiliary tool information are displayed in different areas respectively, and the display areas of the step description information, makeup product information and auxiliary tool information surround the display area of ​​the makeup effect picture.

[0276] In the embodiment of the present application, the makeup scheme generating device 1000 can interact with the server, provide the target user's user appearance image and makeup description information to the server, instruct the server to generate at least one user makeup image, and then receive and display the at least one user makeup image for the user to browse and select. Since the user appearance image can accurately reflect the appearance characteristics of the target user, and the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image, the makeup effect in the user makeup image has a higher degree of fit with the user's appearance, and the original characteristics of the user's appearance are not changed, and the generated user makeup image is more realistic. Since the user makeup image can reflect the actual situation of the makeup effect applied to the target user's appearance, the target user can analyze and judge whether the makeup effect corresponding to the makeup description information is suitable for him / her based on the at least one user makeup image, and obtain a makeup scheme suitable for him / her by modifying the makeup description information.

[0277] It should be noted that: the makeup solution generation device 1000 provided in the above embodiment only uses the division of the above functional modules as an example when providing a user appearance image and makeup description information and displaying at least one user makeup image, or providing a target makeup image and displaying a makeup implementation solution corresponding to the target makeup image. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the makeup solution generation device 1000 provided in the above embodiment belongs to the same concept as the makeup solution generation method embodiment. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0278] See also Fig.11 , Fig.11 11 is a schematic diagram of the structure of a computing device provided in an embodiment of the present application. At least one computing device can constitute a server that implements the makeup plan generation method provided in an embodiment of the present application. The computing device 1100 includes: a bus 1102, a processor 1104, a memory 1106, and a communication interface 1108. The processor 1104, the memory 1106, and the communication interface 1108 communicate with each other via the bus 1102. The embodiment of the present application does not limit the number of processors and memories in the computing device 1100.

[0279] The bus 1102 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.11 The bus 1102 may include a path for transmitting information between various components of the computing device 1100 (eg, the memory 1106, the processor 1104, and the communication interface 1108).

[0280] The processor 1104 may include any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0281] The memory 1106 may include a volatile memory, such as a random access memory (RAM). The processor 1104 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD).

[0282] In the embodiment of the present application, the memory 1106 stores executable program codes, and the processor 1104 executes the executable program codes to respectively implement the functions of the aforementioned receiving module 901, the makeup image generating module 902, and the sending module 903, thereby implementing Figure 1-8 That is, the memory 1106 stores the method for executing the above Figure 1-8 The server shown executes computer program instructions of the makeup plan generation method.

[0283] The communication interface 1108 uses a transceiver module such as, but not limited to, a network interface card or a transceiver to implement communication between the computing device 1100 and other devices or a communication network.

[0284] The embodiment of the present application also provides a computing device cluster, which constitutes a server for executing the makeup scheme generation method provided in the embodiment of the present application. The computing device cluster includes at least one computing device. The computing device can be a server, for example, a central server, an edge server, or a local server in a local data center. In some embodiments, the computing device can also be a terminal device such as a desktop computer, a laptop computer, or a smart phone.

[0285] like Fig.12 As shown, the computing device cluster includes at least one computing device 1100. The memory 1106 in one or more computing devices 1100 in the computing device cluster may store the same Figure 1-8 The computer program instructions of the makeup plan generation method executed by the server are shown.

[0286] In some possible implementations, the memory 1106 of one or more computing devices 1100 in the computing device cluster may also store partial instructions for executing the makeup scheme generation method by the server. In other words, the combination of one or more computing devices 1100 may jointly execute the instructions for executing Figure 1-8 The computer program instructions of the makeup plan generation method executed by the server are shown.

[0287] It should be noted that the memory 1106 in different computing devices 1100 in the computing device cluster can store different instructions, which are respectively used to execute part of the functions of the makeup scheme generating device 900. That is, the instructions stored in the memory 1106 in different computing devices 1100 can implement the functions of one or more modules among the receiving module 901, the makeup image generating module 902 and the sending module 903.

[0288] In some possible implementations, one or more computing devices in the computing device cluster may be connected via a network, which may be a wide area network or a local area network, etc. Fig.13 A possible implementation is shown, such as Fig.13 As shown, two computing devices 1100A and 1100B are connected via a network. Specifically, they are connected to the network via a communication interface in each computing device.

[0289] The server composed of a computing device cluster executes the above Figure 1-8 As an example, in the makeup scheme generation method shown in Fig.13 In the illustrated implementation, the memory 1106 in the computing device 1100A stores instructions for executing the functions of the receiving module 901 and the sending module 903. Meanwhile, the memory 1106 in the computing device 1100B stores instructions for executing the functions of the makeup image generating module 902.

[0290] Fig.13 The connection method between the computing device clusters shown can be based on the consideration that the makeup plan generation method provided in the present application may require the use of a large amount of computing resources and AIGC models to generate makeup plans for users. Therefore, it is considered that the functions implemented by the makeup image generation module 902 are handed over to the computing device 1100B to execute, so as to reduce the computing power of the computing device 1100A.

[0291] It should be understood that Fig.13 The functions of the computing device 1100A shown in FIG. 1100A may also be completed by multiple computing devices 1100. Similarly, the functions of the computing device 1100B may also be completed by multiple computing devices 1100.

[0292] The present application embodiment also provides another computing device cluster. The connection relationship between the computing devices in the computing device cluster can be similar to that of Fig.12 and Fig.13 Connection mode of computing device cluster. The difference is that the memory 1106 in one or more computing devices 1100 in the computing device cluster may store the same instructions for executing the video processing method.

[0293] In some possible implementations, the memory 1106 of one or more computing devices 1100 in the computing device cluster may also store some computer program instructions for executing the makeup scheme generation method. In other words, the combination of one or more computing devices 1100 may store computer program instructions for executing the makeup scheme generation method.

[0294] Fig.14 is a block diagram of a terminal provided in an embodiment of the present application. The terminal 1400 may be Figure 1-8 The user terminal shown is, for example, a smart phone, a tablet computer, an MP3 player (moving picture experts group audio layer III, dynamic image expert compression standard audio layer 3), an MP4 (moving picture experts group audio layer IV, dynamic image expert compression standard audio layer 4) player, a laptop or a desktop computer. The terminal 1400 may also be called a user device, a portable terminal, a laptop terminal, a desktop terminal, or other names.

[0295] Typically, the terminal 1400 includes a processor 1401 and a memory 1402 .

[0296] The processor 1401 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 1401 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 1401 may also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a central processing unit (CPU); the coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 1401 may be integrated with a graphics processing unit (GPU), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 1401 may also include an artificial intelligence (AI) processor, which is used to process computing operations related to machine learning.

[0297] The memory 1402 may include one or more computer-readable storage media, which may be non-transitory. The memory 1402 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 1402 is used to store at least one computer program instruction, which is used to be executed by the processor 1401 to implement the makeup scheme generation method provided in the method embodiment of the present application.

[0298] In some embodiments, the terminal 1400 may also optionally include: a peripheral device interface 1403 and at least one peripheral device. The processor 1401, the memory 1402 and the peripheral device interface 1403 may be connected via a bus or a signal line. Each peripheral device may be connected to the peripheral device interface 1403 via a bus, a signal line or a circuit board. Specifically, the peripheral device includes: at least one of a radio frequency circuit 1404, a touch display screen 1405, a camera 1406, an audio circuit 1407, a positioning component 1408 and a power supply 1409.

[0299] The peripheral device interface 1403 may be used to connect at least one peripheral device related to input / output (I / O) to the processor 1401 and the memory 1402. In some embodiments, the processor 1401, the memory 1402, and the peripheral device interface 1403 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 1401, the memory 1402, and the peripheral device interface 1403 may be implemented on a separate chip or circuit board, which is not limited in this embodiment.

[0300] The radio frequency circuit 1404 is used to receive and transmit radio frequency (RF) signals, also known as electromagnetic signals. The radio frequency circuit 1404 communicates with the communication network and other communication devices through electromagnetic signals. The radio frequency circuit 1404 converts the electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 1404 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The radio frequency circuit 1404 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: the World Wide Web, a metropolitan area network, an intranet, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network and / or a WiFi network. In some embodiments, the radio frequency circuit 1404 may also include circuits related to near field communication (NFC), which is not limited in the embodiments of the present application.

[0301] The display screen 1405 is used to display a user interface (UI). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 1405 is a touch display screen, the display screen 1405 also has the ability to collect touch signals on the surface or above the surface of the display screen 1405. The touch signal can be input to the processor 1401 as a control signal for processing. At this time, the display screen 1405 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the display screen 1405 can be one, and the front panel of the terminal 1400 is set; in other embodiments, the display screen 1405 can be at least two, which are respectively set on different surfaces of the terminal 1400 or are folded; in some embodiments, the display screen 1405 can be a flexible display screen, which is set on the curved surface or folded surface of the terminal 1400. Even, the display screen 1405 can also be set as a non-rectangular irregular shape, that is, a special-shaped screen. The display screen 1405 can be made of materials such as liquid crystal display (LCD) and organic light-emitting diode (OLED).

[0302] The camera assembly 1406 is used to capture images or videos. Optionally, the camera assembly 1406 includes a front camera and a rear camera. Typically, the front camera is arranged on the front panel of the terminal, and the rear camera is arranged on the back of the terminal. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, a wide-angle camera, and a telephoto camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, the fusion of the main camera and the wide-angle camera to realize panoramic shooting and virtual reality (VR) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 1406 may also include a flash. The flash can be a monochrome temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0303] The audio circuit 1407 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals and input them into the processor 1401 for processing, or input them into the radio frequency circuit 1404 to achieve voice communication. For the purpose of stereo acquisition or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the terminal 1400. The microphone may also be an array microphone or an omnidirectional acquisition microphone. The speaker is used to convert the electrical signal from the processor 1401 or the radio frequency circuit 1404 into sound waves. The speaker may be a traditional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 1407 may also include a headphone jack.

[0304] Positioning component 1408 is used to locate the current geographic location of terminal 1400 to implement navigation or location based service (LBS). Positioning component 1408 can be a positioning component based on the global positioning system (GPS) of the United States, the Beidou system of China, or the Galileo system of Russia.

[0305] The power supply 1409 is used to power various components in the terminal 1400. The power supply 1409 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 1409 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery charged through a wired line, and a wireless rechargeable battery is a battery charged through a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0306] In some embodiments, the terminal 1400 further includes one or more sensors 1410. The one or more sensors 1410 include, but are not limited to: an acceleration sensor, a gyroscope sensor, a pressure sensor, a fingerprint sensor, an optical sensor, and a proximity sensor.

[0307] Those skilled in the art will understand that Fig.14 The structure shown in the figure does not constitute a limitation on the terminal 1400, and the terminal 1400 may include more or less components than those shown in the figure, or combine some components, or adopt a different component arrangement.

[0308] The present application also provides a computer program product containing instructions. The computer program product can be software or program products running on a server or stored in any available medium. When the computer program product is running on the server, the server executes the above Figure 1-8 The makeup plan generation method shown.

[0309] The present application also provides a computer program product including instructions. The computer program product can be software or a program product that runs on a terminal or is stored in any available medium. When the computer program product runs on a terminal, the terminal executes the above Figure 1-8 The makeup plan generation method shown.

[0310] The embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that can be stored by a computing device or a data storage device such as a data center that contains one or more available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid-state hard disk), etc. The computer-readable storage medium includes instructions that instruct the server to execute the makeup plan generation method shown in Figure 8 above, or instruct the terminal to execute the makeup plan generation method shown in Figure 8 above.

[0311] It should be understood that the "multiple" mentioned herein refers to two or more. In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in order to facilitate the clear description of the technical solution of the embodiments of the present application, in the embodiments of the present application, the words "first", "second" and the like are used to distinguish between the same items or similar items with basically the same functions and effects. Those skilled in the art can understand that the words "first", "second" and the like do not limit the quantity and execution order, and the words "first", "second" and the like do not limit them to be necessarily different.

[0312] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in the embodiments of the present application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0313] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present application.

Claims

1. A makeup plan generation method, characterized in that: Applied to a server, the method comprises: Receiving a user appearance image and makeup description information of a target user sent by a user terminal, wherein the makeup description information indicates a makeup effect desired by the target user; Based on the user appearance image and the makeup description information, generating at least one user makeup image by using a trained makeup effect generation model, wherein the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image; The at least one user makeup image is sent to the user terminal to instruct the user terminal to display the at least one user makeup image.

2. The method according to claim 1, characterized in that The generating at least one user makeup image based on the user appearance image and the makeup description information by using a trained makeup effect generation model comprises: Acquire a first geometric grid image corresponding to the user appearance image; Based on the user appearance image, the first geometric grid image and the makeup description information, at least one user makeup image is generated by a trained makeup effect generation model.

3. The method according to claim 2, characterized in that The generating the at least one user makeup image by using a trained makeup effect generation model based on the user appearance image, the first geometric grid image and the makeup description information comprises: Based on the makeup description information, determining a target prompt template from a prompt template library, wherein the prompt template library includes a plurality of makeup prompt templates, each of which includes a plurality of makeup prompts describing a makeup effect; The target prompt template, the user appearance image and the first geometric grid image are input into the makeup effect generation model to obtain the at least one user makeup image output by the makeup effect generation model.

4. The method according to any one of claims 1 to 3, characterized in that: Before sending the at least one user makeup image to the user terminal, the method further includes: Determining a display priority of each user makeup image in the at least one user makeup image; sorting the at least one user makeup image based on the display priority of the at least one user makeup image to obtain an image display order of the at least one user makeup image; The sending the at least one user makeup image to the user terminal includes: The at least one user makeup image and the image display order are sent to the user terminal to instruct the user terminal to display the at least one user makeup image according to the image display order.

5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: receiving a target makeup image sent by the user terminal, wherein the target makeup image is a makeup image determined by the target user based on the at least one user makeup image; Determine a makeup implementation scheme corresponding to the target makeup image, wherein the makeup implementation scheme includes a plurality of makeup implementation steps associated in sequence and makeup prompt information corresponding to each makeup implementation step; The makeup implementation plan is sent to the user terminal to instruct the user terminal to display the makeup implementation plan.

6. The method according to claim 5, characterized in that The step of determining a makeup implementation scheme corresponding to the target makeup image comprises: The target makeup image is input into a trained makeup solution analysis model to obtain a makeup implementation solution corresponding to the target makeup image output by the makeup solution analysis model.

7. The method according to claim 5, characterized in that The sending the makeup implementation scheme to the user terminal to instruct the user terminal to display the makeup implementation scheme includes: Sending makeup prompt information corresponding to a first makeup implementation step to the user terminal, where the first makeup implementation step is any one of the makeup implementation steps in the makeup implementation scheme; If a step jump instruction for skipping the first makeup implementation step is received from the user terminal, in response to the step jump instruction, makeup prompt information corresponding to the second makeup implementation step is sent to the user terminal to instruct the user terminal to display the makeup prompt information corresponding to the second makeup implementation step, and the second makeup implementation step is the next makeup implementation step adjacent to the first makeup implementation step in the makeup implementation plan.

8. The method according to claim 5, characterized in that The makeup prompt information corresponding to the makeup implementation step includes one or more of step description information, makeup map data, makeup product information and auxiliary tool information required for the makeup implementation step; The makeup map data includes makeup contour information and map positioning information, wherein the makeup contour information indicates the contour of the makeup effect corresponding to the makeup implementation step, and the map positioning information indicates the position of the makeup effect corresponding to the makeup implementation step.

9. A method for generating a makeup plan, characterized in that: Applied to a user terminal, the method comprises: Acquire a user appearance image and makeup description information of a target user, wherein the makeup description information indicates a makeup effect desired by the target user; Sending the user appearance image and the makeup description information to a server to instruct the server to generate at least one user makeup image based on the user appearance image and the makeup description information through a trained makeup effect generation model, wherein the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image; Receive and display the at least one user makeup image sent by the server.

10. The method according to claim 9, characterized in that Before displaying the at least one user makeup image, the method further includes: receiving an image display order of the at least one user makeup image sent by the server; The displaying of the at least one user makeup image comprises: The at least one user makeup image is displayed in the image display order.

11. The method according to claim 9 or 10, characterized in that After displaying the at least one user makeup image, the method further includes: determining a target makeup image based on the at least one user makeup image; Sending the target makeup image to the server to instruct the server to determine a makeup implementation scheme corresponding to the target makeup image, wherein the makeup implementation scheme includes a plurality of sequentially associated makeup implementation steps and makeup prompt information corresponding to each makeup implementation step; Receive and display the makeup implementation plan sent by the server.

12. The method according to claim 11, characterized in that The receiving and displaying the makeup implementation scheme sent by the server includes: receiving and displaying makeup prompt information corresponding to a first makeup implementation step sent by the server, wherein the first makeup implementation step is any one of the makeup implementation steps in the makeup implementation scheme; In response to a step jump operation triggered by the target user for skipping the first makeup implementation step, a step jump instruction is sent to the server, wherein the step jump instruction is used to request makeup prompt information corresponding to a second makeup implementation step, where the second makeup implementation step is the next makeup implementation step adjacent to the first makeup implementation step in the makeup implementation scheme; Receive and display makeup prompt information corresponding to the second makeup implementation step sent by the server.

13. The method according to claim 12, characterized in that The makeup prompt information of the makeup implementation step includes one or more of step description information, makeup map data, makeup product information and auxiliary tool information required for the makeup implementation step; The makeup map data includes makeup contour information and map positioning information, wherein the makeup contour information indicates the contour of the makeup effect corresponding to the makeup implementation step, and the map positioning information indicates the position of the makeup effect corresponding to the makeup implementation step.

14. The method according to claim 13, characterized in that The makeup prompt information of the makeup implementation step includes the makeup map data; the display of the makeup prompt information corresponding to the second makeup implementation step includes: Acquire a real-time appearance image of the target user; Based on the makeup map data corresponding to the second makeup implementation step, rendering the real-time appearance image with makeup effects to obtain a makeup effect image corresponding to the second makeup implementation step; Display the makeup effect diagram corresponding to the second makeup implementation step.

15. The method according to claim 14, characterized in that The step of rendering the real-time appearance image with makeup effects based on the makeup map data corresponding to the second makeup implementation step to obtain a makeup effect map corresponding to the second makeup implementation step includes: generating a second geometric grid image corresponding to the real-time appearance image; Determining a makeup rendering position in the real-time appearance image based on the texture positioning information corresponding to the second makeup implementation step and the second geometric grid image; Based on the makeup rendering position, the real-time appearance image is rendered with makeup effects according to the makeup contour information corresponding to the second makeup implementation step to obtain a makeup effect image corresponding to the second makeup implementation step.

16. The method according to claim 14 or 15, characterized in that The makeup prompt information of the makeup implementation steps also includes the step description information, the makeup product information and the auxiliary tool information; the method also includes: Displaying step description information corresponding to the second makeup implementation step, makeup product information corresponding to the second makeup implementation step, and auxiliary tool information corresponding to the second makeup implementation step; Among them, the makeup effect picture, the step description information, the makeup product information and the auxiliary tool information are respectively displayed in different areas, and the display areas of the step description information, the makeup product information and the auxiliary tool information surround the display area of ​​the makeup effect picture.

17. A makeup plan generating device, characterized in that: Included in a server, the device comprises: A receiving module, configured to receive a user appearance image and makeup description information of a target user sent by a user terminal, wherein the makeup description information indicates a makeup effect desired by the target user; a makeup image generation module, configured to generate at least one user makeup image based on the user appearance image and the makeup description information by using a trained makeup effect generation model, wherein the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image; The sending module is used to send the at least one user makeup image to the user terminal to instruct the user terminal to display the at least one user makeup image.

18. A makeup plan generating device, characterized in that: Included in a user terminal, the device includes: An acquisition module, used to acquire a user appearance image and makeup description information of a target user, wherein the makeup description information indicates a makeup effect desired by the target user; a sending module, configured to send the user appearance image and the makeup description information to a server, so as to instruct the server to generate at least one user makeup image based on the user appearance image and the makeup description information through a trained makeup effect generation model, wherein the at least one user makeup image is a makeup image generated by applying at least one makeup effect to the user appearance image; The receiving module is used to receive and display the at least one user makeup image sent by the server.

19. A server, characterized in that: The server is a computing device cluster, the computing device cluster includes at least one computing device, each computing device includes a processor and a memory; The processor of the at least one computing device is used to execute computer program instructions stored in the memory of the at least one computing device, so that the computing device cluster executes the makeup plan generation method as described in any one of items 1-8.

20. A terminal, characterized in that: The terminal includes a memory and a processor, the memory is used to store a computer program, and the processor is used to execute computer program instructions stored in the memory, so that the terminal executes the makeup plan generating method described in any one of claims 9-16.

21. A computer-readable storage medium, characterized in that: The storage medium stores computer program instructions, and when the computer program instructions are executed on the server, the server executes the makeup plan generating method as described in any one of claims 1-8.

22. A computer-readable storage medium, characterized in that: The storage medium stores computer program instructions, and when the computer program instructions are executed on the terminal, the terminal executes the makeup plan generating method as described in any one of claims 9 to 16.

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