Image processing method and apparatus, device, and storage medium

Abstract

The present invention provides an image processing method and apparatus, a device, and a storage medium. The method comprises: in response to a preset image processing request for an image to be processed, identifying a target object on the image to be processed; receiving target description information corresponding to the image to be processed, and generating a target avatar on the basis of the target description information; and then adding the target avatar into the image to be processed to obtain a processing result image corresponding to the image to be processed. According to the embodiments of the present invention, a target avatar is generated for a target object on the basis of target description information, and the image to be processed is processed into a processing result image for displaying the target object on the basis of the target avatar.

Description

Image processing method, device, equipment and storage medium

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of Chinese Patent Application No. 202311055793.2 filed on August 21, 2023. The entire teachings of the above application are incorporated herein by reference. Technical Field

[0003] The present disclosure relates to the field of data processing, and in particular to an image processing method, apparatus, device, and storage medium. Background Art

[0004] With the development of e-commerce platforms, more and more people choose to shop online. In order to display and promote products, merchants will shoot real models to show the effects of the products, such as shooting real models wearing clothes and jewelry to display and promote the products.

[0005] However, using real models to shoot product renderings is expensive and time-consuming, so how to obtain renderings for displaying products more efficiently and conveniently is an urgent problem that needs to be solved.

[0006] Summary of the Invention

[0007] In order to solve the above technical problems, an embodiment of the present disclosure provides an image processing method.

[0008] In a first aspect, the present disclosure provides an image processing method, the method comprising:

[0009] In response to a preset image processing request for an image to be processed, identifying a target object on the image to be processed;

[0010] receiving target description information corresponding to the image to be processed, and generating a target virtual image based on the target description information;

[0011] The target virtual image is added to the image to be processed to obtain a processing result image corresponding to the image to be processed; wherein the processing result image displays the target object on the image to be processed.

[0012] In an optional embodiment, before adding the target virtual image to the image to be processed to obtain a processing result image corresponding to the image to be processed, the method further includes:

[0013] Acquiring display area information of the target object on the image to be processed;

[0014] Accordingly, the step of adding the target virtual image to the image to be processed to obtain a processing result image corresponding to the image to be processed includes:

[0015] Based on the display area information of the target object on the image to be processed, the target virtual image is added to the image to be processed to obtain a processing result image corresponding to the image to be processed.

[0016] In an optional embodiment, the adding the target virtual image to the image to be processed based on the display area information of the target object on the image to be processed to obtain a processing result image corresponding to the image to be processed includes:

[0017] Based on the display area information of the target object on the image to be processed, obtaining a partial image corresponding to the target object in the image to be processed;

[0018] The target virtual image and the partial image corresponding to the target object are spliced ​​together to obtain a processing result image corresponding to the image to be processed.

[0019] In an optional implementation, obtaining display position information of the target object on the image to be processed includes:

[0020] Based on the recognition result of the target object, the image to be processed is binarized to obtain a binary image corresponding to the image to be processed; wherein the binary image is used to identify the display area of ​​the target object on the image to be processed.

[0021] In an optional embodiment, the adding the target virtual image to the image to be processed based on the display area information of the target object on the image to be processed to obtain a processing result image corresponding to the image to be processed includes:

[0022] Based on the binary image corresponding to the image to be processed and the target virtual image, a mask is redrawn on the image to be processed to obtain a processing result image corresponding to the image to be processed.

[0023] In an optional implementation, the method further includes:

[0024] The binary image corresponding to the image to be processed, the processing result image and the image to be processed are input into a preset edge processing model. After the preset edge processing model processes the edge of the target object in the processing result image, the edge processing result image corresponding to the image to be processed is obtained.

[0025] In an optional implementation, generating a target virtual image based on the target description information includes:

[0026] The target description information is input into a virtual image generation model, and after being processed by the virtual image generation model, a target virtual image is generated; wherein the virtual image generation model is trained based on virtual image image samples with text description information.

[0027] In an optional implementation manner, before identifying the target object on the image to be processed, the method further includes:

[0028] Performing image quality compression processing on the image to be processed;

[0029] And / or, sampling processing is performed on the length and width pixel points in the image to be processed.

[0030] In a second aspect, the present disclosure provides an image processing device, the device comprising:

[0031] an identification module, configured to identify a target object on the image to be processed in response to a preset image processing request for the image to be processed;

[0032] A generating module, configured to receive target description information corresponding to the image to be processed, and generate a target virtual image based on the target description information; wherein the target description information is used to describe features of the target virtual image;

[0033] An adding module is used to add the target virtual image to the image to be processed to obtain a processing result image corresponding to the image to be processed; wherein the processing result image is used to display the target object based on the target virtual image.

[0034] In a third aspect, the present disclosure provides a computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium. When the instructions are executed on a terminal device, the terminal device implements the above method.

[0035] In a fourth aspect, the present disclosure provides an image processing device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method when executing the computer program.

[0036] In a fifth aspect, the present disclosure provides a computer program product, which includes a computer program / instructions, and the computer program / instructions implement the above method when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0038] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0039] FIG1 is a flow chart of an image processing method provided by an embodiment of the present disclosure;

[0040] FIG2 is a schematic diagram of an interactive interface for selecting an image feature tag provided by an embodiment of the present disclosure;

[0041] FIG3 is a schematic diagram of a binary image provided by an embodiment of the present disclosure;

[0042] FIG4 is a schematic diagram of an interactive interface provided by an embodiment of the present disclosure;

[0043] FIG5 is a schematic diagram of another interactive interface provided by an embodiment of the present disclosure;

[0044] FIG6 is a schematic diagram of data interaction provided by an embodiment of the present disclosure;

[0045] FIG7 is a schematic structural diagram of an image processing device provided by an embodiment of the present disclosure;

[0046] FIG8 is a schematic structural diagram of an image processing device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0047] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features therein can be combined with each other in the absence of conflict.

[0048] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0049] In the e-commerce sector, new products are constantly being released. To facilitate product display and promotion, products are often presented by capturing product images of real models wearing them. However, this method is expensive and time-consuming, and fails to meet the needs of merchants and users for efficient and convenient product images.

[0050] To this end, an embodiment of the present disclosure provides an image processing method, which first responds to a preset image processing request for an image to be processed, identifies a target object on the image to be processed, receives target description information corresponding to the image to be processed, and generates a target virtual image based on the target description information, wherein the target description information is used to describe the characteristics of the target virtual image. Then, the target virtual image is added to the image to be processed to obtain a processing result image corresponding to the image to be processed, wherein the processing result image is used to display the target object based on the target virtual image. The embodiment of the present disclosure generates a target virtual image for the target object based on the target description information, and processes the image to be processed into a processing result image that displays the target object based on the target virtual image. It can be seen that the embodiment of the present disclosure does not require shooting with a real model, but rather generates a rendering for displaying the target object more efficiently and conveniently based on image processing, thereby meeting user needs.

[0051] Based on this, an embodiment of the present disclosure provides an image processing method. Referring to FIG1 , which is a flow chart of an image processing method provided by an embodiment of the present disclosure, the method specifically includes:

[0052] S101: In response to a preset image processing request for an image to be processed, identifying a target object on the image to be processed.

[0053] The image to be processed may be selected from the user's photo album and uploaded, or may be captured and uploaded, which is not limited in the present embodiment. The image to be processed may display a target object, which may be a displayable item such as clothing, jewelry, a backpack, glasses, etc.

[0054] The image processing method provided by the embodiment of the present disclosure can be applied to the server.

[0055] In the embodiment of the present disclosure, when a preset image processing request for an image to be processed is received from a client, a target object on the image to be processed is first identified. The preset image processing request is used to request the server to perform a preset processing on the target object on the image to be processed.

[0056] S102: Receive target description information corresponding to the image to be processed, and generate a target virtual image based on the target description information.

[0057] In the embodiment of the present disclosure, the target description information is used to describe the characteristics of the target virtual image, and may include appearance feature description information, expression description information, etc. for the target virtual image; in addition, the target description information may also include scene description information and environment description information, such as indoor, outdoor, and other scene feature information.

[0058] In an optional implementation, the target description information may be user-defined feature information. Specifically, the user customizes the target description information by selecting an image feature tag on the interactive interface.

[0059] Figure 2 shows an interactive interface for selecting avatar feature tags, provided in an embodiment of the present disclosure. Specifically, the interface displays multiple selectable facial feature tags for an avatar, as well as multiple selectable scene feature tags. Users can customize the avatar's avatar feature tags by clicking on the tags. This allows users to customize avatars of different styles based on their needs, enhancing the presentation of the target object.

[0060] As shown in FIG2 , the image feature labels currently selected by the user include: short hair, smile, indoors, etc. Correspondingly, the target description information corresponding to the image to be processed includes: short hair, smile, indoors, etc.

[0061] In the disclosed embodiment, after receiving the user-selected image feature tags, the client sends the descriptive information corresponding to the selected image feature tags to the server as the target description information of the image to be processed. After receiving the target description information corresponding to the image to be processed, the server generates a target virtual image based on the target description information. The target virtual image can be generated by an artificial intelligence model and have a face and body that resembles a real person.

[0062] In one optional embodiment, a target avatar is generated based on the target description information. Specifically, an artificial intelligence model can be used to generate a target avatar that matches the target description characteristics based on the target description information. The artificial intelligence model can be a trained avatar generation model, specifically, a avatar generation model trained using avatar image samples with text description information.

[0063] During the application of the virtual image generation model, the target description information is input into the virtual image generation model, and after being processed by the virtual image generation model, the target virtual image is generated.

[0064] S103: adding the target virtual image to the image to be processed to obtain a processing result image corresponding to the image to be processed;

[0065] The processing result image is used to display the target object based on the target virtual image, and the processing result image displays the target object on the image to be processed.

[0066] In the embodiment of the present disclosure, it is necessary to first obtain the display area information of the target object on the image to be processed, and then add the target virtual image to the image to be processed to obtain a processing result image corresponding to the image to be processed.

[0067] The target object display area information on the image to be processed is used to identify the display position, display range, etc. of the target object on the image to be processed.

[0068] In an optional embodiment, the display area information of the target object on the image to be processed may include coordinate information of the area occupied by the target object on the image to be processed, for example, coordinate information of edge pixels of the area occupied by the target object on the image to be processed.

[0069] In another optional embodiment, the display position information of the target object on the image to be processed can be obtained by segmenting the target object from other content other than the target object (also called background content) through an image segmentation model, and then generating a binary image (such as a grayscale image) through binarization processing to identify the display area information of the target object on the image to be processed.

[0070] In the embodiment of the present disclosure, based on the recognition result of the target object, the image to be processed is binarized to obtain a binary image corresponding to the image to be processed, wherein the binary image can be used to identify the display area of ​​the target object on the image to be processed.

[0071] For example, in a binary image, the pixels in the area occupied by the target object can be set to the pixel values ​​corresponding to black, and the pixels corresponding to the image other than the target object can be set to the pixel values ​​corresponding to white. Specifically, the specific pixel values ​​set for the pixels in the binary image are not limited in the embodiments of the present disclosure.

[0072] As shown in FIG3 , it is a schematic diagram of a binary image provided by an embodiment of the present disclosure, specifically a black and white grayscale image, wherein the white area is used to identify the display area of ​​the target object on the image to be processed.

[0073] On the basis of the above embodiment, based on the display area information of the target object on the image to be processed, the target virtual image is added to the image to be processed to obtain a processing result image corresponding to the image to be processed.

[0074] In an optional embodiment, based on the display area information of the target object on the image to be processed, a partial image corresponding to the target object is obtained from the image to be processed, and then the target virtual image and the partial image are spliced ​​to obtain a processing result image corresponding to the image to be processed.

[0075] The partial image corresponding to the target object refers to the smallest image on the image to be processed that contains the target object. For example, the image to be processed shows a model wearing a long skirt (target object) and a background image (such as a live broadcast scene). The smallest image on the image to be processed that contains the target object is the target object itself, so the partial image corresponding to the target object refers to the image of the area where the long skirt is displayed. Optionally, the target virtual image and the partial image corresponding to the target object can be spliced ​​together using any image processing technology, and the embodiments of the present disclosure do not limit this.

[0076] In another optional embodiment, a mask can be redrawn on the image to be processed based on the binary image corresponding to the image to be processed and the target virtual image, thereby obtaining a processed result image corresponding to the image to be processed. In this disclosed embodiment, the binary image is used as a mask to draw the target virtual object in an area outside the display area of ​​the target object identified in the binary image.

[0077] In an embodiment of the present disclosure, by responding to a preset image processing request for an image to be processed, a target object on the image to be processed is identified, target description information corresponding to the image to be processed is received, and a target virtual image is generated based on the target description information, wherein the target description information is used to describe the characteristics of the target virtual image, and the target virtual image is added to the image to be processed to obtain a processing result image corresponding to the image to be processed, wherein the processing result image is used to display the target object based on the target virtual image. The embodiment of the present disclosure generates a target virtual image for the target object based on the target description information, and processes the image to be processed into a processing result image that displays the target object based on the target virtual image. It can be seen that the embodiment of the present disclosure does not require shooting with a real model, but rather generates a rendering for displaying the target object more efficiently and conveniently based on image processing, thereby meeting user needs.

[0078] In actual applications, after the stitching processing of the partial images corresponding to the target virtual image and the target object, the stitching edges of the processed result image may have poor edge fusion effect. Therefore, in order to further improve the quality of the processed image, the embodiment of the present disclosure can also perform edge processing on the stitching edges in the processed result image corresponding to the image to be processed.

[0079] Specifically, based on the display area information of the target object on the image to be processed, edge recognition is performed on the target object in the image to be processed to obtain an edge recognition result. Then, based on the edge recognition result, edge processing is performed on the processing result image corresponding to the image to be processed, so that the splicing edge effect of the target virtual image and the target object in the processing result image after edge processing is more realistic.

[0080] In one optional embodiment, a binary image corresponding to the image to be processed, a processed image, and the original image of the image to be processed are input into a preset edge processing model. After processing by the preset edge processing model, an edge-processed image corresponding to the image to be processed is obtained. Specifically, the preset edge processing model processes the edges of the target object in the processed image to achieve a more realistic edge effect when splicing the target virtual image with the target object.

[0081] In another optional embodiment, a neural network model can be used to perform edge detection and identification on the target object in the image to be processed based on the display area of ​​the target object in the image to be processed, obtain an edge recognition result, and then perform edge processing on the processing result image corresponding to the image to be processed based on the edge recognition result. The specific type of neural network model is not limited.

[0082] In the embodiment of the present disclosure, by performing edge processing on the processing result image corresponding to the processed image, the splicing edge between the target object and the target virtual image in the processing result image is made softer and smoother, closer to the real image, and the quality of the generated image is improved.

[0083] In practical applications, to improve image processing efficiency, the image to be processed can be compressed, and the number of pixels in the image's length and width can be sampled. This can improve image processing efficiency by reducing image quality. In the disclosed embodiments, when a preset image processing request is received for an image to be processed, the image to be processed is compressed, and / or the length and width pixels in the image to be processed are sampled. By appropriately compressing the image to be processed, the server's image processing computational load is reduced, the image generation speed is increased, and image processing efficiency is improved.

[0084] In order to facilitate understanding of the above embodiment, the embodiment of the present disclosure introduces it from the perspective of the client. As shown in Figure 4, it is a schematic diagram of an interactive interface provided by the embodiment of the present disclosure. First, after receiving the target description information determined by the user based on the interface shown in Figure 2, the client uploads it to the server. In addition, after the user uploads the image to be processed (assuming it is a real-life clothing picture) to the server through the interactive interface, the interface state shown in Figure 4 is displayed on the interactive interface, presenting a prompt message waiting for the server to process the image, such as "working hard to generate a model".

[0085] After receiving the preset image processing request from the client, the server performs image quality compression processing on the received image to be processed, and then identifies the target object. According to the recognition result, the target object (clothing) on ​​the image to be processed is segmented from the background content. For example, the image to be processed is binarized to obtain a black and white grayscale image, where the black and white grayscale image is used to identify the display area information of the target object (clothing) on ​​the image to be processed.

[0086] The server can use the black and white grayscale image as a mask and draw the target virtual image based on the target description information to obtain the processing result image corresponding to the image to be processed, that is, the processing result image showing the target object based on the target virtual image.

[0087] After the server completes processing the image to be processed, it transmits the generated processing result image back to the client. After the client receives the processing result image, it displays it on the interactive interface, as shown in Figure 5, which is a schematic diagram of another interactive interface provided in an embodiment of the present disclosure. The interactive interface displays an image of the target object (clothing) based on the target virtual image (model).

[0088] When the server performs splicing processing on the target virtual image and the target object based on the display area information of the target object on the image to be processed, the processed result image may have poor edge processing effect. In order to make the edges of the processed result image smoother, the server can further perform edge processing on the processed result image and then transmit it to the client. The client displays the processed result image on the interactive interface for the user to view.

[0089] To facilitate a user's further understanding of the image processing method provided by the present embodiment, the present embodiment provides a specific application method. FIG6 shows a data interaction diagram provided by the present embodiment. Specifically, the image processing method of the present embodiment can be implemented based on data interaction between the client and the server. The server deploys the trained first and second models.

[0090] First, the user selects an image feature description tag on the client interactive interface, and then the client forms target description information based on the image feature description tag selected by the user and sends the target description information to the server; the user uploads the image to be processed through the client (assuming it is a picture of a real person in clothing) and sends a preset image processing request for the image to be processed to the server.

[0091] After receiving the preset image processing request from the client, the server uses the first model to identify the target object (clothing) on ​​the image to be processed, and based on the recognition result of the target object, performs binarization on the image to be processed to obtain a binary image corresponding to the image to be processed as a mask; in order to enable the user to perceive the progress of the image processing and enhance the human-computer interaction experience, the image that only shows the target object obtained based on the binary image corresponding to the image to be processed can be transmitted to the client first, and the client displays the image on the client after receiving the image.

[0092] To avoid slow execution due to large processing logic, and to prevent the entire processing process from stalling due to a vulnerability in one of the processing logics, separate interfaces can be deployed for different logical units during the application process. For example, a separate interface can be deployed for edge processing of the image to be processed. In actual applications, the embodiments of this disclosure do not limit the implementation architecture deployment method of the server.

[0093] As shown in FIG6 above, the client sends the image to be processed and the binary image corresponding to the image to be processed to the server again through a separate interface. Then, after receiving the image to be processed and the binary image corresponding to the image to be processed, the server performs edge processing on the image to be processed through the second model based on the binary image corresponding to the image to be processed and the target virtual image, and obtains the processing result image corresponding to the image to be processed. Finally, the image to be processed is transmitted back to the client and displayed on the client.

[0094] Based on the above method embodiment, the present disclosure further provides an image processing device. Referring to FIG7 , which is a schematic structural diagram of an image processing device provided by the present disclosure, the device includes:

[0095] The recognition module 701 is configured to recognize a target object on the image to be processed in response to a preset image processing request for the image to be processed;

[0096] A generating module 702 is configured to receive target description information corresponding to the image to be processed, and generate a target virtual image based on the target description information; wherein the target description information is used to describe the characteristics of the target virtual image;

[0097] The adding module 703 is used to add the target virtual image to the image to be processed to obtain a processing result image corresponding to the image to be processed; wherein the processing result image is used to display the target object based on the target virtual image.

[0098] In an optional embodiment, the device further includes:

[0099] A first acquisition module acquires display area information of the target object on the image to be processed;

[0100] Accordingly, the adding module is specifically used to:

[0101] Based on the display area information of the target object on the image to be processed, the target virtual image is added to the image to be processed to obtain a processing result image corresponding to the image to be processed.

[0102] In an optional implementation, the adding module includes:

[0103] A first acquisition submodule is configured to acquire a partial image corresponding to the target object in the image to be processed based on display area information of the target object on the image to be processed;

[0104] The first splicing submodule is used to splice the target virtual image and the partial image corresponding to the target object to obtain a processing result image corresponding to the image to be processed.

[0105] In an optional implementation manner, the first acquisition module is specifically configured to:

[0106] Based on the recognition result of the target object, the image to be processed is binarized to obtain a binary image corresponding to the image to be processed; wherein the binary image is used to identify the display area of ​​the target object on the image to be processed.

[0107] In an optional implementation manner, the adding module is specifically configured to:

[0108] Based on the binary image corresponding to the image to be processed and the target virtual image, a mask is redrawn on the image to be processed to obtain a processing result image corresponding to the image to be processed.

[0109] In an optional embodiment, the device further includes:

[0110] An edge processing module is used to input the binary image corresponding to the image to be processed, the processing result image and the image to be processed into a preset edge processing model, and after the preset edge processing model processes the edge of the target object in the processing result image, an edge processing result image corresponding to the image to be processed is obtained.

[0111] In an optional implementation manner, the generating module is specifically configured to:

[0112] The target description information is input into a virtual image generation model, and after being processed by the virtual image generation model, a target virtual image is generated; wherein the virtual image generation model is trained based on virtual image image samples with text description information.

[0113] In an optional embodiment, the device further includes:

[0114] An image processing module, configured to perform image quality compression processing on the image to be processed;

[0115] And / or, an image sampling module, used to sample the length and width pixels in the image to be processed.

[0116] In the image processing method provided by the embodiment of the present disclosure, first, in response to a preset image processing request for the image to be processed, the target object on the image to be processed is identified, target description information corresponding to the image to be processed is received, and a target virtual image is generated based on the target description information; wherein the target description information is used to describe the characteristics of the target virtual image, and then the target virtual image is added to the image to be processed to obtain a processing result image corresponding to the image to be processed, wherein the processing result image is used to display the target object based on the target virtual image. The embodiment of the present disclosure generates a target virtual image for the target object based on the target description information, and processes the image to be processed into a processing result image that displays the target object based on the target virtual image. It can be seen that the embodiment of the present disclosure does not require shooting with a real model, but rather generates a rendering for displaying the target object more efficiently and conveniently based on image processing, thereby meeting user needs.

[0117] In addition to the above-mentioned method and apparatus, the embodiments of the present disclosure further provide a computer-readable storage medium, which stores instructions. When the instructions are executed on a terminal device, the terminal device implements the image processing method described in the embodiments of the present disclosure.

[0118] The embodiments of the present disclosure further provide a computer program product, which includes a computer program / instructions. When the computer program / instructions are executed by a processor, the image processing method described in the embodiments of the present disclosure is implemented.

[0119] In addition, the embodiment of the present disclosure further provides an image processing device, as shown in FIG8 , which may include:

[0120] Processor 801, memory 802, input device 803, and output device 808. The image processing device may include one or more processors 801, with one processor being used as an example in FIG8 . In some embodiments of the present disclosure, processor 801, memory 802, input device 803, and output device 808 may be connected via a bus or other means, with FIG8 using a bus as an example.

[0121] The memory 802 can be used to store software programs and modules. The processor 801 executes the various functional applications and data processing of the image processing device by running the software programs and modules stored in the memory 802. The memory 802 may primarily include a program storage area and a data storage area. The program storage area may store an operating system, at least one application required for a function, and the like. Furthermore, the memory 802 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. The input device 803 may be used to receive input digital or character information and generate signal input related to user settings and function control of the image processing device.

[0122] Specifically in this embodiment, the processor 801 will load the executable files corresponding to the processes of one or more applications into the memory 802 according to the following instructions, and the processor 801 will run the applications stored in the memory 802, thereby realizing the various functions of the above-mentioned image processing device.

[0123] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0124] The foregoing description is intended only to provide specific embodiments of the present disclosure, intended to enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the embodiments described herein, but rather to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

Claims

1. An image processing method, comprising: In response to a preset image processing request for an image to be processed, identifying a target object on the image to be processed; Receive target description information corresponding to the image to be processed, and generate a target virtual image based on the target description information; wherein the target description information is used to describe the characteristics of the target virtual image; The target virtual image is added to the image to be processed to obtain a processing result image corresponding to the image to be processed; wherein the processing result image is used to display the target object based on the target virtual image.

2. The method according to claim 1, wherein before adding the target virtual image to the image to be processed to obtain the processing result image corresponding to the image to be processed, the method further comprises: Acquire display area information of the target object on the image to be processed; Correspondingly, the step of adding the target virtual image to the image to be processed to obtain a processing result image corresponding to the image to be processed includes: Based on the display area information of the target object on the image to be processed, the target virtual image is added to the image to be processed to obtain a processing result image corresponding to the image to be processed.

3. The method according to claim 2, wherein the step of adding the target virtual image to the image to be processed based on the display area information of the target object on the image to be processed to obtain a processing result image corresponding to the image to be processed comprises: Based on the display area information of the target object on the image to be processed, acquiring a partial image corresponding to the target object in the image to be processed; The target virtual image and the partial image corresponding to the target object are spliced ​​to obtain a processing result image corresponding to the image to be processed.

4. The method according to claim 2, wherein the obtaining the display area information of the target object on the image to be processed comprises: Based on the recognition result of the target object, the image to be processed is binarized to obtain a binary image corresponding to the image to be processed; wherein the binary image is used to identify a display area of ​​the target object on the image to be processed.

5. The method according to claim 4, wherein the step of adding the target virtual image to the image to be processed based on the display area information of the target object on the image to be processed to obtain a processing result image corresponding to the image to be processed comprises: Based on the binary image corresponding to the image to be processed and the target virtual image, a mask is redrawn on the image to be processed to obtain a processing result image corresponding to the image to be processed.

6. The method according to claim 4, further comprising: The binary image corresponding to the image to be processed, the processing result image and the image to be processed are input into a preset edge processing model. After the preset edge processing model processes the edge of the target object in the processing result image, an edge processing result image corresponding to the image to be processed is obtained.

7. The method according to claim 1, wherein generating a target virtual image based on the target description information comprises: The target description information is input into a virtual image generation model, and after being processed by the virtual image generation model, a target virtual image is generated; wherein the virtual image generation model is trained based on virtual image image samples with text description information.

8. The method according to claim 1, wherein before identifying the target object on the image to be processed, the method further comprises: Performing image quality compression processing on the image to be processed; And / or, sampling processing is performed on the length and width pixel points in the image to be processed.

9. An image processing device, comprising: An identification module, configured to identify a target object on the image to be processed in response to a preset image processing request for the image to be processed; A generating module is used to receive the target description information corresponding to the image to be processed, and based on Generating a target virtual image based on the target description information; wherein the target description information is used to describe the characteristics of the target virtual image; An adding module is used to add the target virtual image to the image to be processed to obtain a processing result image corresponding to the image to be processed; wherein the processing result image is used to display the target object based on the target virtual image.

10. A computer-readable storage medium, wherein the computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device implements the method according to any one of claims 1 to 8.

11. An image processing device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

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