Image processing method, device, equipment, medium and program product

Abstract

The embodiment of the invention relates to an image processing method and device, equipment, a medium and a program product. The method comprises the following steps: determining a target image material from at least one image material related to an object, wherein the target image material comprises the object; for at least one user group type, determining at least one description text and at least one template corresponding to the target image material, each template being configured to at least define a layout of the image material and the description text; respectively adapting the target image material and the description text to at least one template to obtain at least one image for each user group type; and providing the at least one image to a user group of the at least one user group type.

Description

Technical Field

[0001] Example embodiments of the present disclosure generally relate to the field of computers, and particularly to methods, apparatuses, devices, computer-readable storage media, and computer program products for image processing. Background Art

[0002] Currently, more and more platforms require users to display objects by posting visual content such as images and videos. Taking an online platform as an example, different online platforms may all need to present images related to an object and highlight some characteristics of the object through the images, so as to facilitate users to quickly obtain relevant information about the object. Such images need to be obtained through optimized processing of image materials. It is desired to process image materials more efficiently and generate higher-quality images. Summary of the Invention

[0003] In a first aspect of the present disclosure, a method for image processing is provided. The method includes: determining a target image material from at least one image material related to an object, the target image material including the object; for at least one user group type, determining at least one description text and at least one template corresponding to the target image material, each template being configured to at least define the layout of the image material and the description text; adapting the target image material and the description text to the at least one template respectively to obtain at least one image for each user group type; and providing the at least one image to user groups of the at least one user group type.

[0004] In a second aspect of the present disclosure, an apparatus for image processing is provided. The apparatus includes: a first determination module configured to determine a target image material from at least one image material related to an object, the target image material including the object; a second determination module configured to, for at least one user group type, determine at least one description text and at least one template corresponding to the target image material, each template being configured to at least define the layout of the image material and the description text; an adaptation module configured to adapt the target image material and the description text to the at least one template respectively to obtain at least one image for each user group type; and a provision module configured to provide the at least one image to user groups of the at least one user group type.

[0005] In a third aspect of the present disclosure, an electronic device is provided. The device includes at least one processor; and at least one memory coupled to the at least one processor and storing instructions for execution by the at least one processor. The instructions, when executed by the at least one processor, cause the device to execute the method of the first aspect.

[0006] In a fourth aspect of the present disclosure, a computer-readable storage medium is provided. Computer instructions are stored on the computer-readable storage medium, and the computer instructions can be executed by a processor to implement the method of the first aspect.

[0007] In a fifth aspect of the present disclosure, a computer program product is provided. The computer program product includes a computer program, and when the computer program is executed by a processor, it implements the method according to the first aspect of the present disclosure.

[0008] It should be understood that the content described in this part is not intended to define the key features or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In conjunction with the accompanying drawings and with reference to the following detailed description, the above and other features, advantages, and aspects of the embodiments of the present disclosure will become more apparent. In the drawings, the same or similar reference numerals denote the same or similar elements, where:

[0010] Figure 1 A schematic diagram showing an example environment in which embodiments according to the present disclosure can be implemented;

[0011] Figure 2 A flowchart showing a process for image processing according to some embodiments of the present disclosure;

[0012] Figure 3 A flowchart showing a process for image processing according to some embodiments of the present disclosure;

[0013] Figure 4A A schematic diagram showing an example of template filling according to some embodiments of the present disclosure;

[0014] Figure 4B A schematic diagram showing an example of the adjustment of a target image material during the template adaptation process according to some embodiments of the present disclosure;

[0015] Figures 5A to 5C A schematic diagram showing an example interface according to some embodiments of the present disclosure;

[0016] Figure 6 A flowchart showing an example process for image processing according to some embodiments of the present disclosure;

[0017] Figure 7 A schematic structural block diagram showing an example device for image processing according to some embodiments of the present disclosure; and

[0018] Figure 8A block diagram of an electronic device in which one or more embodiments of the present disclosure can be implemented is shown. Detailed implementation manners

[0019] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not used to limit the protection scope of the present disclosure.

[0020] It should be noted that the titles of any sections / subsections provided herein are not restrictive. Various embodiments are described throughout this document, and any type of embodiment can be included under any section / subsection. In addition, the embodiments described in any section / subsection can be combined with any other embodiments described in the same section / subsection and / or different sections / subsections in any manner.

[0021] In the description of the embodiments of the present disclosure, the term "including" and its like should be understood as an open inclusion, that is, "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "an embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". There may also be other explicit and implicit definitions hereinafter. Terms such as "first", "second", etc. may refer to different or the same objects. There may also be other explicit and implicit definitions hereinafter.

[0022] In this document, unless otherwise specified, performing a step "in response to A" does not mean that the step is immediately performed after "A", but may include one or more intermediate steps.

[0023] The embodiments of the present disclosure may involve user data, data acquisition and / or use, etc. These aspects all comply with the corresponding laws, regulations and related provisions. In the embodiments of the present disclosure, all data collection, acquisition, processing, processing, forwarding, use, etc. are carried out on the premise that the user is aware and confirms. Accordingly, when implementing the embodiments of the present disclosure, the types, usage scopes, usage scenarios, etc. of the data or information that may be involved should be informed to the user and the user's authorization should be obtained through appropriate means according to the relevant laws and regulations. The specific informing and / or authorization methods may vary according to the actual situation and application scenarios, and the scope of the present disclosure is not limited in this regard.

[0024] In the solutions described in this specification and the embodiments, if personal information processing is involved, it will be processed on the premise of having a legal basis (such as obtaining the consent of the personal information subject, or being necessary for performing a contract, etc.), and will only be processed within the specified or agreed scope. If a user refuses to process personal information other than the necessary information required for basic functions, it will not affect the user's use of the basic functions.

[0025] As used herein, the term "model" can learn the corresponding association relationship between inputs and outputs from training data, so that after training is completed, for a given input, a corresponding output can be generated. The generation of the model can be based on machine learning techniques. Deep learning is a machine learning algorithm that processes inputs and provides corresponding outputs by using multiple layers of processing units. A neural network model is an example of a model based on deep learning. In this document, "model" can also be referred to as "machine learning model", "learning model", "machine learning network", or "learning network", and these terms are used interchangeably herein.

[0026] Figure 1 A schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented is shown. In environment 100, electronic device 110 can run application 120. Application 120 can be a platform capable of delivering visual content such as images, videos, etc. containing an object to achieve the conversion of the object. As an example, application 120 can include, for example, an online platform, and correspondingly, the object can include, for example, a commodity. In such an example, the conversion of the object can include, for example, clicks, purchases, etc. of the commodity on the online platform, which are not limited herein. It should be understood that application 120 can be any suitable type of application capable of delivering visual content, and no limitation is intended herein.

[0027] In some embodiments, user 140 can interact with application 120 via electronic device 110 and / or its attached devices. As an example, user 140 can include an operator user of the platform of application 120. Taking application 120 as an online platform as an example, user 140 can include, for example, a merchant user for operating commodities. In some embodiments, user 140 can upload image materials such as images, video frames, etc. containing an object to application 120, and application 120 can process the image materials to generate an image for presentation on application 120.

[0028] In some embodiments, the electronic device 110 communicates with the server 130 to implement the supply of services for the application 120. The electronic device 110 can be any type of mobile terminal, fixed terminal, or portable terminal, including mobile phones, desktop computers, laptop computers, notebook computers, netbook computers, tablet computers, media computers, multimedia tablets, handheld computers, portable game terminals, VR / AR devices, Personal Communication System (PCS) devices, personal navigation devices, Personal Digital Assistant (PDA), audio / video players, digital cameras / camcorders, positioning devices, television receivers, radio broadcast receivers, e-book devices, game devices, or any combination of the foregoing, including accessories and peripherals of these devices or any combination thereof. In some embodiments, the electronic device 110 can also support any type of user interface (such as a "wearable" circuit, etc.).

[0029] The server 130 can be an independent physical server, a server cluster or 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, and big data and artificial intelligence platforms. The server 130 can include, for example, a computing system / server, such as a mainframe, an edge computing node, a computing device in a cloud environment, and so on. The server 130 can provide background services for the application 120 that supports virtual scenarios in the electronic device 110.

[0030] A communication connection can be established between the server 130 and the electronic device 110. The communication connection can be established by wired or wireless means. The communication connection can include, but is not limited to, Bluetooth connection, mobile network connection, Universal Serial Bus (USB) connection, Wireless Fidelity (WiFi) connection, etc., and the embodiments of the present disclosure are not limited in this regard. In the embodiments of the present disclosure, the server 130 and the electronic device 110 can implement signaling interaction through the communication connection therebetween.

[0031] It should be understood that the structures and functions of the various elements in the environment 100 are described only for exemplary purposes, without implying any limitation on the scope of the present disclosure.

[0032] Currently, in some platforms that require a large number of images (such as online platforms), operator users (such as merchant users) need to create images by themselves. However, many operator users do not have the ability to create good images and optimize image materials (including static images and video frames, etc.). This may lead to a situation where after the operator users create an object (such as a product) on the platform, the sales volume of the operator's object may be affected due to the poor quality of the image materials containing the object and the lack of prominent information points to be conveyed.

[0033] Generally speaking, in order to improve the quality of images, operator users need to manually replace the background in the image materials, add core information points about the object on the image materials, etc. to generate images. However, the images optimized manually may not be able to meet the differentiated needs of different user groups, and there are also differences in image quality, resulting in limited improvement in the conversion of images containing the object. In addition, the way operator users create images manually will consume a large amount of time cost and operation cost.

[0034] In view of this, embodiments of the present disclosure propose a solution for image processing. According to this solution, a target image material is determined from at least one image material related to an object, and the target image material contains the object; for at least one user group type, at least one description text and at least one template corresponding to the target image material are determined, and each template is configured to at least define the layout of the image material and the description text; the target image material and the description text are respectively adapted to at least one template to obtain at least one image for each user group type; and at least one image is provided to the user groups of at least one user group type.

[0035] In this way, a complete set of automated processes from at least one image material to generating images and providing images to user groups is achieved. This can avoid problems such as uncontrollable quality of operator users' image materials, poor screening of target image materials, and poor quality of the produced images. This solution can provide corresponding images for each user group to meet the concerns of the corresponding user group, and thus meet the interactive needs of different user groups.

[0036] Some exemplary embodiments of the present disclosure will be further described below with reference to the accompanying drawings.

[0037] Figure 2 A schematic diagram of a process 200 for image processing according to some embodiments of the present disclosure is shown. For ease of discussion, these embodiments will be described with reference to Figure 1 an environment 100. These embodiments can be implemented in Figure 1 an electronic device 110.

[0038] At block 210, the electronic device 110 may obtain at least one image material related to an object. As an example, for the applications 120 with different functions in the electronic device 110, the types of objects may be different. For example, for e-commerce applications, the objects may include products. For ease of understanding, the following specific embodiments will describe the exemplary process of the present disclosure by taking the object as a product as an example.

[0039] As an example, the image material may include any suitable type of image material such as static image material, video frame material, etc. Taking the object as a product as an example, the image material may, for example, include the image material containing a certain product, and may also include, for example, the video frame material containing the product intercepted from the video for the product, and so on.

[0040] In an e-commerce scenario, at least one image material may be uploaded by the operator user 140 (such as a merchant) to the application 120. The electronic device 110 may obtain the uploaded at least one image material, and then process these image materials to generate high-quality images for the operator user to display the images containing the object.

[0041] At block 220, the electronic device 110 determines a target image material from at least one image material related to the object, and the target image material contains the object. In some embodiments, when determining the target image material, the electronic device 110 may determine the target image material that meets the quality requirements from at least one image material, and the target image material may be determined based on the first image material in at least one image material. The quality requirement may be a predetermined quality requirement. As an example, based on the quality requirement, high-quality target image materials may be selected from at least one image material.

[0042] In some embodiments, when determining the target image material that meets the quality requirements from at least one image material, the electronic device 110 may determine the quality levels respectively corresponding to at least one image material among multiple quality levels. The quality requirement corresponding to the first quality level among the multiple quality levels meets the predetermined quality requirement. The first quality level may be the quality level with the highest quality requirement among the multiple quality levels. Taking the image material including image material and video frame material as an example, the quality requirement corresponding to the first quality level may, for example, include that the object displayed on the material should be prominent and complete, and the background should be clean, etc. The object being complete may, for example, include that the edge of the object is complete, not cropped, not blocked, etc. The background being clean may, for example, include that the background is simple and not cluttered, the background is pure (for example, the background is a solid color), the background elements are blurred to make the object prominent, and so on. It should be understood that this is only an example and is not intended to be any limitation.

[0043] As an example, in addition to the first quality level, the multiple quality levels may further include a second quality level corresponding to a slightly defective quality condition, a third quality level corresponding to a defective quality condition, and so on. The slightly defective quality condition corresponding to the second quality level may include, for example, the presence of other interfering elements or incomplete background in the background part of the material, and so on. The defective quality condition corresponding to the third quality level may include, for example, the object part in the material being blocked by some elements, and so on. It should be understood that these are only examples, and the multiple quality levels may further include any other suitable quality levels except the lowest quality level.

[0044] As an example, the image material corresponding to the lowest quality level will not be adopted, that is, it will not be selected as the target image material. For example, for cases of poor quality such as the object main part in the material being too large, or the material emphasizing a certain detail part of the object, etc., it may correspond to the lowest quality level. It should be noted that the selected target image material is used as the main image for the display related to the object. Therefore, for example, a material emphasizing the details of the object may not be considered as the main image, that is, it will not be selected as the target image material.

[0045] In some embodiments, if it is determined that the first image material in at least one image material corresponds to the first quality level, the electronic device 110 may determine the first image material as the target image material. As an example, if one target image material needs to be selected and there are multiple image materials corresponding to the first quality level in at least one image material, one image material may be screened out from the multiple image materials as the target image material in a suitable manner. For example, one image material may be randomly selected from the multiple image materials, or the first image material in the arrangement order may be selected, etc. The method is not limited herein.

[0046] In some embodiments, if it is determined that at least one image material all corresponds to other quality levels except the first quality level among the multiple quality levels, a quality adjustment process is performed on the at least one image material to obtain the adjusted at least one image material, and the target image material is determined from the adjusted at least one image material. For example, the adjusted first image material may be selected from the adjusted at least one image material as the target image material. In other embodiments, the quality adjustment process may also be performed on the first image material in at least one image material, and then the adjusted first image material is directly determined as the target image material.

[0047] For ease of understanding, the following will take the quality conditions corresponding to the second quality level and the third quality level listed above as examples to further discuss the quality adjustment processing method. For the slightly defective quality condition corresponding to the second quality level, for example, a machine learning model can be used to replace the poor-quality background in the image material, so that the image or video frame material with slightly defective quality becomes high-quality material. For the defective quality condition corresponding to the third quality level, for example, by identifying the object main body in the material, other complete parts except the occluded part are intercepted from the object main body as the updated image material, so that the updated image material becomes high-quality material. It should be understood that such a quality adjustment processing method is only an example, and in actual situations, any appropriate quality adjustment processing method can be adopted to adjust the image material with unqualified quality into high-quality image material.

[0048] In block 230, for at least one user group type, the electronic device 110 determines at least one description text and at least one template corresponding to the target image material. It should be noted that for each user group type, the electronic device 110 can determine the description text and at least one template corresponding to the target image material. Each template is configured to at least define the layout of the image material and the description text. The layout can include, for example, the border style of the image material in the template, the position of the object in the image material in the template, the position and style of the description text in the template, etc., which are not limited here. It should be understood that in the case where there are multiple templates corresponding to each user group type, the layouts of the multiple templates can be different.

[0049] In an e-commerce scenario, the user group can include consumers, for example. Different types of user groups can be divided according to corresponding classification criteria, which are not limited here. User groups of the same type may have the same or similar interests in objects or goods. Different user group types can correspond to different description texts to meet the attention information required by the corresponding user group.

[0050] In some embodiments, when determining the description text corresponding to the target image material, the electronic device 110 can obtain the description information related to the object. The electronic device 110 can extract at least one target description information corresponding to at least one user group type from the description information, and based on the at least one target description information, determine at least one description text corresponding to the target image material. As an example, each user group type can correspond to one target description information and one description text.

[0051] Taking commodities as an example, the description information may include, for example, the commodity name, origin information, ingredient information, shipping information, marketing campaign information, etc., without limitation. Different target description information can be extracted from the description information for different user groups. For example, for user group A, target description information such as "free shipping" and "promotion" can be extracted from the description information. For user group B, target description information such as "low calorie" and "healthy" can be extracted from the description information. It should be understood that these are merely examples and are not intended to be limiting.

[0052] By extracting the target description information from the description information for each user group type and then generating corresponding descriptive text, the key information of each user group can be directly displayed on the corresponding main image, saving time and costs for users in each user group when making decisions on objects. This also helps improve the conversion rate of objects, such as click-through rate and purchase rate.

[0053] In some embodiments, when determining at least one template corresponding to the target image material, electronic device 110 may determine a template style corresponding to at least one user group type. For each user group type, based on the template style corresponding to each user group type, electronic device 110 may determine at least one template corresponding to the target image material.

[0054] Still using products as an example, for user group A, the template style might be cartoon-style. For user group B, the template style might be simple, and so on. It should be understood that the template style can be any appropriate style that matches the characteristics of the corresponding user group. By using templates with corresponding styles for different user groups, the attention of users in the corresponding user groups can be increased, thereby facilitating conversion of the product.

[0055] In block 240, the electronic device 110 adapts the target image material and the description text to at least one template to obtain at least one image for each user group type. As an example, a corresponding image can be presented on each adapted template. Figure 3 、 Figure 4A and Figure 4B Let's discuss in detail how to adapt the template.

[0056] Figure 3 FIG. 3 is a flow chart showing a process 300 for image processing according to some embodiments of the present disclosure. The process 300 may be implemented in Figure 1in the environment 100. The process 300 may be a specific implementation example of some steps in the process 200. In the process 300, for ease of understanding, the template adaptation process for at least one user group type is discussed in detail by taking the first user group type, the second user group type, and the third user group type as examples respectively. It should be understood that the number of user group types is not limited.

[0057] In block 311, the electronic device 110 may obtain at least one first template for the first user group type. Correspondingly, in block 321, the electronic device 110 may obtain at least one second template for the second user group type. In block 331, the electronic device 110 may obtain at least one third template for the third user group type.

[0058] In some embodiments, each template may at least include a first region for an object in the image material and a second region for the description text. When adapting the target image material and the description text to at least one template respectively to obtain at least one image for each user group type, for each user group type, the electronic device 110 may fill the target image material into at least one template and fill the description text into the second region in the corresponding template.

[0059] Figure 4A A schematic diagram of an example 400A for template filling according to some embodiments of the present disclosure is shown. The steps of block 312, block 313, block 322, block 323, block 332, and block 333 in the process 300 may be implemented by using the example 400A respectively.

[0060] As Figure 4A shown, the example template 410 may include a first region 412 for presenting the object main body and a second region 414 for presenting the description text. In the example target image material 420, the main body of the example object 425 is presented in the frame 425. The example target image material 420 and the description text may be filled into the template 410 respectively, and the main body of the object 425 is located in the first region 412.

[0061] Returning to the reference Figure 3, for filling at least one first template of the first user group type, at block 312, the target image material can be filled into at least one first template. At block 313, the first description text can be filled into the second area of each first template. For filling at least one second template of the second user group type, at block 322, the target image material can be filled into at least one second template. At block 323, the second description text can be filled into the second area of each second template. For filling at least one third template of the third user group type, at block 332, the target image material can be filled into at least one third template. At block 333, the third description text can be filled into the second area of each third template.

[0062] Further, in some embodiments, the electronic device 110 can adjust the target image material in at least one template respectively. In some embodiments, when adjusting the target image material in at least one template respectively, for each template, the electronic device 110 can adjust the size and / or position of the target image material in the template so that the object in the target image material is located in the first area of the template. If there is a blank area in the template after this adjustment, the electronic device 110 can perform content expansion on the target image material to fill the blank area. For ease of understanding, the following will be combined with Figure 4B to show the adjustment of the target image material in the template.

[0063] Figure 4B FIG. shows a schematic diagram of an example 400B of the adjustment of the target image material during the template adaptation according to some embodiments of the present disclosure. The steps of block 314, block 324, and block 334 in process 300 can be implemented by example 400B respectively.

[0064] As Figure 4B shown, after filling the example target image material 430 into the example template 410, the size of the example target image material 430 can be reduced to obtain the example target image material 430'. Then, the example target image material 430' can be moved to a position that can cover the first area 412 so that the object therein is located in the first area 412. This results in a blank area in the template. Then, content expansion can be performed on the example target image material 430', for example, background expansion can be performed, or other suitable expansion methods that do not affect the object main body can be used to fill the blank area.

[0065] Further, in some embodiments, based on at least one adjustment result for each user group type, at least one image for at least one user group type can be obtained. Each adjustment result in the at least one adjustment result can at least indicate that the object in the target image material is located in the first region. For example, after performing background expansion on the example target image material 430', the example image 441 can be obtained. Similarly, for other templates, after completion of filling and adjustment, example images such as example image 442 and example image 443 can be obtained.

[0066] Return reference Figure 3 , after filling at least one first template for the first user group type, at block 314, adjust the target image material to obtain at least one first image for the first user group type (such as example image 441). After filling at least one second template for the second user group type, at block 324, adjust the target image material to obtain at least one second image for the second user group type (such as example image 442). After filling at least one third template for the third user group type, at block 334, adjust the target image material to obtain at least one third image for the third user group type (such as example image 443).

[0067] Thus, by adapting the target image material and the descriptive text to at least one template respectively, it can be ensured that the main body of the object is completely displayed without being blocked, making the overall picture of the generated image complete. This improves the quality of the generated image.

[0068] Return reference Figure 2 , at block 250, the electronic device 110 provides at least one image to the user groups of at least one user group type. In some embodiments, the electronic device 110 can provide the corresponding image in the at least one image to the user groups of each user group type in the at least one user group type. For example, for user group A, if there are multiple images, the multiple images can be simultaneously and separately delivered to different users in user group A. The different images in the multiple images can also be separately delivered to the same user in user group A at multiple time periods. Of course, if there is only one corresponding image for user group A, then the image is directly delivered to the users in user group A. It should be understood that these delivery methods are only examples and are not limited herein.

[0069] In some embodiments, based on a viewing request for the object, the electronic device 110 can provide at least one image to the user groups of at least one user group type. As an example, the viewing request can be triggered based on the browsing, refreshing, etc. of one or more images presented by the electronic device 110 by the users in the user group.

[0070] At block 260, the electronic device 110 may select target images corresponding to each user group from at least one image. In some embodiments, if at least one image is provided to user groups of at least one user group type, the electronic device 110 may obtain at least one interaction metric related to an object within a predetermined time period, and each interaction metric may indicate the interaction result performed by the corresponding user group on the corresponding image. Based on the at least one interaction metric, the electronic device 110 may select a target image from the at least one image for providing to user groups of at least one user group type in a subsequent time period.

[0071] For example, the predetermined time period may be two days, one week, or any other suitable time period, which is not limited herein. The subsequent time period may be a time period after the predetermined time period. As an example, the interaction of users in a user group with an image may include, for example, clicking on the image, adding an object in the image to a virtual shopping cart, purchasing an object in the image, and so on. Correspondingly, the at least one interaction metric may include, for example, a click-through rate, a rate of adding to the virtual shopping cart, a purchase rate, and so on. As an example, the image corresponding to the highest interaction metric may be used as the target image for the corresponding user group. For example, at least one interaction metric related to an object within one week (or other predetermined time period) may be obtained, and then the image corresponding to the highest interaction metric may be selected for providing to the corresponding user group within a subsequent period of time (such as one month or other time period).

[0072] Return reference Figure 3 , at block 315, for the first user group, a first target image may be selected from at least one first image. At block 325, for the second user group, a second target image may be selected from at least one second image. At block 335, for the third user group, a third target image may be selected from at least one third image.

[0073] Return reference Figure 2 , at block 270, the electronic device 110 may provide the target image to the corresponding user group. In combination Figure 3 , at block 316, the first target image may be provided to the first user group. At block 326, the second target image may be provided to the second user group. At block 336, the third target image may be provided to the third user group.

[0074] Figures 5A to 5C Exemplary interfaces 500A to 500C according to some embodiments of the present disclosure are shown. It should be understood that the interfaces shown in the drawings are merely examples, and various interface designs may actually exist. Each graphical element in the interface may have different arrangements and different visual representations, one or more of which may be omitted or replaced, and one or more other elements may also exist. Embodiments of the present disclosure are not limited in this regard.

[0075] Interfaces 500A to 500C can be, for example, example delivery interfaces for the first user group, the second user group, and the third user group respectively. For example, for the same object, the target image in interface 500A can be example image 441, the target image in interface 500B can be example image 442, and the target image in interface 500C can be example image 443. Thus, the embodiments of the present disclosure achieve delivering different images to different user groups for the same object.

[0076] The embodiments of the present disclosure implement the entire process from extracting image materials to optimizing image materials, then to matching user groups and presenting them to user groups, ensuring the connection of each link, and automatically helping operator users complete the final result of material optimization. It avoids the problems of uncontrollable quality of image materials of operator users and lack of screening-optimization logic. It can meet the different demands of different audience groups for the object, and let different audience groups see the object information they hope to see.

[0077] Figure 6 The flowchart of an example process 600 for image processing according to some embodiments of the present disclosure is shown. Process 600 can be implemented at Figure 1 electronic device 110 therein. The following describes process 600 with reference to Figure 1 it.

[0078] As shown, at block 610, electronic device 110 determines a target image material from at least one image material related to an object, and the target image material includes the object.

[0079] At block 620, for at least one user group type, electronic device 110 determines at least one description text and at least one template corresponding to the target image material, and each template is configured to at least define the layout of the image material and the description text. <s

[0080] At block 630, electronic device 110 adapts the target image material and the description text to at least one template respectively to obtain at least one image for each user group type.

[0081] At block 640, electronic device 110 provides at least one visual content to the user groups of at least one user group type.

[0082] In some embodiments, process 600 further includes: in response to at least one image being provided to the user groups of at least one user group type, obtaining at least one interaction metric for the object within a predetermined time period, where each interaction metric indicates the interaction result of the corresponding user group on the corresponding image; and based on at least one interaction metric, selecting a target image from at least one image for providing to the user groups of at least one user group type in a subsequent time period.

[0083] In some embodiments, determining target image materials includes: determining target image materials that meet quality requirements from at least one image material, where the target image materials are determined based on a first image material among the at least one image material.

[0084] In some embodiments, determining target image materials that meet quality requirements from at least one image material includes: determining the quality levels respectively corresponding to the at least one image material among multiple quality levels, where the quality requirements corresponding to the first quality level among the multiple quality levels meet the quality requirements; and in response to determining that the first image material among the at least one image material corresponds to the first quality level, determining the first image material as the target image material; or in response to determining that all of the at least one image material corresponds to other quality levels other than the first quality level among the multiple quality levels, performing quality adjustment processing on the at least one image material to obtain the adjusted at least one image material, and determining target image materials from the adjusted at least one image material.

[0085] In some embodiments, determining at least one description text corresponding to the target image materials includes: obtaining description information related to an object; extracting at least one target description information corresponding to the at least one user group type from the description information; and based on the at least one target description information, determining the at least one description text corresponding to the target image materials.

[0086] In some embodiments, determining at least one template corresponding to the target image materials includes: determining the template styles respectively corresponding to the at least one user group type; and for each user group type, based on the template style corresponding to each user group type, determining at least one template corresponding to the target image materials.

[0087] In some embodiments, each template includes at least a first region for an object in the image material and a second region for the description text, and where adapting the target image materials and the description text to at least one template respectively to obtain at least one image for each user group type includes: for each user group type, filling the target image materials into at least one template, and filling the description text into the second region in the corresponding template; respectively adjusting the target image materials in the at least one template; and based on at least one adjustment result for each user group type, obtaining at least one image for the at least one user group type, where each adjustment result in the at least one adjustment result indicates at least that the object in the target image materials is located in the first region.

[0088] In some embodiments, adjusting the target image material in at least one template respectively includes: for each template, adjusting the size and / or position of the target image material in the template so that the object in the target image material is located in the first area of the template; and in response to the existence of a blank area in the adjusted template, performing content expansion on the target image material to fill the blank area.

[0089] Embodiments of the present disclosure also provide corresponding devices for implementing the above methods or processes. Figure 7 A schematic structural block diagram of an example device 700 for image processing according to some embodiments of the present disclosure is shown. The device 700 may be implemented as or included in an electronic device 110. Each module / component in the device 700 may be implemented by hardware, software, firmware, or any combination thereof.

[0090] As shown in the figure, the device 700 includes a first determination module 710 configured to determine a target image material from at least one image material related to an object, the target image material including the object; a second determination module 720 configured to determine at least one description text and at least one template corresponding to the target image material for at least one user group type, each template being configured to at least define the layout of the image material and the description text; an adaptation module 730 configured to adapt the target image material and the description text to at least one template respectively to obtain at least one image for each user group type; and a provision module 740 configured to provide at least one image to the user groups of at least one user group type.

[0091] In some embodiments, the device 700 further includes an interaction module configured to, in response to at least one image being provided to the user groups of at least one user group type, obtain at least one interaction metric related to the object within a predetermined time period, each interaction metric indicating the interaction result of the corresponding user group on the corresponding image; and select a target image from at least one image based on at least one interaction metric for providing to the user groups of at least one user group type in a subsequent time period.

[0092] In some embodiments, the first determination module 710 is further configured to determine a target image material meeting quality requirements from at least one image material, the target image material being determined based on the first image material in at least one image material. [[ID=A]]

[0093] In some embodiments, the apparatus 700 is further configured to determine, among a plurality of quality levels, the quality levels corresponding to at least one piece of image material respectively, wherein the quality requirements corresponding to the first quality level among the plurality of quality levels meet the quality requirements; and in response to determining that the first piece of image material among the at least one piece of image material corresponds to the first quality level, determine the first piece of image material as the target image material; or in response to determining that all of the at least one piece of image material correspond to other quality levels other than the first quality level among the plurality of quality levels, perform quality adjustment processing on the at least one piece of image material to obtain the at least one piece of adjusted image material, and determine the target image material from the at least one piece of adjusted image material.

[0094] In some embodiments, the second determination module 720 is further configured to obtain description information related to an object; extract at least one target description information corresponding to the at least one user group type from the description information; and based on the at least one target description information, determine the at least one description text corresponding to the target image material.

[0095] In some embodiments, the second determination module 720 is further configured to determine the template style corresponding to each of the at least one user group type; and for each user group type among the at least one user group type, based on the template style corresponding to each user group type, determine at least one template corresponding to the target image material.

[0096] In some embodiments, each template includes at least a first region for an object in the image material and a second region for the description text, and the adaptation module 730 is further configured to, for each user group type, fill the target image material into at least one template, and fill the description text into the second region in the corresponding template; adjust the target image material in at least one template respectively; and based on at least one adjustment result for each user group type, obtain at least one image for the at least one user group type, wherein each adjustment result in the at least one adjustment result indicates at least that the object in the target image material is located in the first region.

[0097] In some embodiments, the apparatus 700 is further configured to, for each template, adjust the size and / or position of the target image material in the template so that the object in the target image material is located in the first region of the template; and in response to there being a blank region in the adjusted template, perform content expansion on the target image material to fill the blank region.

[0098] The units and / or modules included in apparatus 700 can be implemented in various ways, including software, hardware, firmware, or any combination thereof. In some embodiments, one or more units and / or modules can be implemented using software and / or firmware, such as machine-executable instructions stored on a storage medium. In addition to or in place of the machine-executable instructions, some or all of the units and / or modules in apparatus 700 can be implemented at least in part by one or more hardware logic components. By way of example and not limitation, exemplary types of hardware logic components that can be used include field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0099] Figure 8 FIG. shows a block diagram of an electronic device 800 in which one or more embodiments of the present disclosure can be implemented. It should be understood that Figure 8 the illustrated electronic device 800 is merely exemplary and should not impose any limitation on the functionality and scope of the embodiments described herein. Figure 8 The illustrated electronic device 800 can be used to implement Figure 1 electronic device 110.

[0100] As Figure 8 shown, the electronic device 800 is in the form of a general-purpose electronic device. The components of the electronic device 800 can include, but are not limited to, one or more processors or processing units 810, a memory 820, a storage device 830, one or more communication units 840, one or more input devices 850, and one or more output devices 860. The processing unit 810 can be an actual or virtual processor and is capable of performing various processes according to the programs stored in the memory 820. In a multi-processor system, multiple processing units execute computer-executable instructions in parallel to improve the parallel processing ability of the electronic device 800.

[0101] The electronic device 800 generally includes multiple computer storage media. Such media can be any accessible media that can be obtained by the electronic device 800, including but not limited to volatile and non-volatile media, removable and non-removable media. The memory 820 can be volatile memory (such as registers, caches, random access memory (RAM)), non-volatile memory (such as read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. The storage device 830 can be removable or non-removable media and can include machine-readable media, such as flash drives, magnetic disks, or any other media that can be used to store information and / or data and can be accessed within the electronic device 800.

[0102] The electronic device 800 may further include additional removable / non-removable, volatile / non-volatile storage media. Although not shown in Figure 8 , a disk drive for reading from and writing to a removable, non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading from and writing to a removable, non-volatile optical disk may be provided. In these cases, each drive may be connected to a bus (not shown) by one or more data media interfaces. The memory 820 may include a computer program product 828 having one or more program modules configured to perform the various methods or actions of the various embodiments of the present disclosure.

[0103] The communication unit 840 enables communication with other electronic devices via a communication medium. Additionally, the functions of the components of the electronic device 800 may be implemented by a single computing cluster or multiple computer machines capable of communicating via a communication connection. Thus, the electronic device 800 may operate in a networked environment using a logical connection to one or more other servers, network personal computers (PCs), or another network node.

[0104] The input device 850 may be one or more input devices such as a mouse, keyboard, trackball, etc. The output device 860 may be one or more output devices such as a display, speaker, printer, etc. The electronic device 800 may also communicate with one or more external devices (not shown) as needed via the communication unit 840, such as a storage device, a display device, etc., communicate with one or more devices that enable a user to interact with the electronic device 800, or communicate with any device that enables the electronic device 800 to communicate with one or more other electronic devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface (not shown).

[0105] According to an exemplary implementation of the present disclosure, a computer-readable storage medium is provided, on which computer-executable instructions are stored, where the computer-executable instructions are executed by a processor to implement the method described above. According to an exemplary implementation of the present disclosure, a computer program product is also provided, the computer program product being tangibly stored on a non-transitory computer-readable medium and including computer-executable instructions, and the computer-executable instructions being executed by a processor to implement the method described above.

[0106] Aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of methods, apparatuses, devices, and computer program products implemented according to the present disclosure. It should be understood that each block of the flowcharts and / or block diagrams, and the combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0107] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that the instructions, when executed by the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in one or more boxes of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, a programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises a manufacture including instructions that implement various aspects of the functions / acts specified in one or more boxes of the flowchart and / or block diagram.

[0108] The computer-readable program instructions may be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other devices to produce a computer-implemented process such that the instructions executed on the computer, other programmable data processing apparatus, or other devices implement the functions / acts specified in one or more boxes of the flowchart and / or block diagram.

[0109] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various implementations of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of code, or a portion of an instruction, and the module, segment of code, or portion of an instruction contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two consecutive blocks may in fact be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by special-purpose hardware-based systems that perform the specified functions or acts, or by combinations of special-purpose hardware and computer instructions.

[0110] The implementations of the present disclosure have been described above. The description is exemplary, not exhaustive, and is not limited to the disclosed implementations. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described implementations. The choice of terms used herein is intended to best explain the principles of the implementations, the practical application, or improvements made to the technology in the marketplace, or to enable other ordinary skilled persons in the art to understand the implementations disclosed herein.

Claims

1. A method for image processing, comprising: Determining a target image material from at least one image material related to an object, the target image material including the object; For at least one user group type, determining at least one description text and at least one template corresponding to the target image material, each template being configured to at least define the layout of the image material and the description text; Adapting the target image material and the description text to the at least one template respectively to obtain at least one image for each user group type; And Providing the at least one image to the user groups of the at least one user group type.

2. The method according to claim 1, further comprising: In response to the at least one image being provided to the user groups of the at least one user group type, obtaining at least one interaction metric for the object within a predetermined time period, each interaction metric indicating the interaction result performed by the corresponding user group on the corresponding image; And Based on the at least one interaction metric, selecting a target image from the at least one image for providing to the user groups of the at least one user group type in a subsequent time period.

3. The method according to claim 1, wherein determining the target image material includes: Determining the target image material that meets the quality requirements from the at least one image material, the target image material being determined based on the first image material among the at least one image material.

4. The method according to claim 3, wherein determining the target image material that meets the quality requirements from the at least one image material includes: Among multiple quality levels, determining the quality levels corresponding to the at least one image material respectively, and the quality requirements corresponding to the first quality level among the multiple quality levels meet the quality requirements; And In response to determining that the first image material among the at least one image material corresponds to the first quality level, determining the first image material as the target image material; Or In response to determining that all of the at least one image material corresponds to other quality levels except the first quality level among the multiple quality levels, Performing quality adjustment processing on the at least one image material to obtain at least one adjusted image material, and Determining the target image material from the at least one adjusted image material.

5. The method according to claim 1, wherein determining the at least one description text corresponding to the target image material includes: Obtaining description information related to the object; Extracting at least one target description information corresponding to the at least one user group type from the description information; And Based on the at least one target description information, determining the at least one description text corresponding to the target image material.

6. The method according to claim 1, wherein determining the at least one template corresponding to the target image material includes: Determining the template styles corresponding to the at least one user group type respectively; And For each user group type, based on the template style corresponding to each user group type, determining the at least one template corresponding to the target image material.

7. The method according to claim 1, wherein each of the templates includes at least a first region for the object in the image material and a second region for the descriptive text, and Wherein, adapting the target image material and the description text to the at least one template respectively to obtain at least one image for each user group type includes: for each type of user group, filling the target image material into the at least one template, and filling the descriptive text into the second region in the corresponding template; adjusting the target image material in the at least one template respectively; and based on at least one adjustment result for each type of user group, obtaining at least one image for the at least one type of user group, each adjustment result in the at least one adjustment result indicating at least that the object in the target image material is located in the first region.

8. The method according to claim 7, wherein adjusting the target image material in the at least one template respectively includes: for each template, adjusting the size and / or position of the target image material in the template so that the object in the target image material is located in the first region of the template; and in response to there being a blank area in the template after the adjustment, performing content expansion on the target image material to fill the blank area.

9. An apparatus for image processing, comprising: a first determination module configured to determine a target image material from at least one image material related to an object, the target image material including the object; a second determination module configured to determine, for at least one type of user group, at least one descriptive text and at least one template corresponding to the target image material, each template being configured to at least define the layout of the image material and the descriptive text; an adaptation module configured to adapt the target image material and the descriptive text to the at least one template respectively to obtain at least one image for each type of user group; and a providing module configured to provide the at least one image to user groups of the at least one type of user group.

10. An electronic device, comprising: at least one processor; and at least one memory coupled to the at least one processor and storing instructions for execution by the at least one processor, the instructions, when executed by the at least one processor, causing the electronic device to perform the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having stored thereon computer instructions executable by a processor to implement the method according to any one of claims 1 to 8.

12. A computer program product tangibly stored in a computer storage medium and including computer-executable instructions that, when executed by a device, cause the device to perform the method according to any one of claims 1 to 8.

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