An image processing method, apparatus, electronic device, storage medium, and program product

Abstract

Embodiments of the present disclosure provide an image processing method and device, electronic equipment, storage medium and program product. The specific implementation scheme comprises: determining detection information corresponding to an image; determining rendering information of the object according to the detection information; determining resource information corresponding to the rendering information; acquiring resources corresponding to the resource information; and rendering the object based on the resources. According to the detection information of the part in the image, the rendering information is determined, and the object to be rendered in the image is not generally rendered, but the rendering information is dynamically selected according to the rendering information of the object to be rendered, so as to reduce the redundant calculation and performance overhead in the rendering process. Then, the resource information is determined according to the rendering information, and the rendering is realized accordingly, the resource information required for dynamic selection of rendering is realized, the additional resource waste is reduced, and the performance of the overall rendering is optimized.

Description

Technical Field

[0001] This disclosure relates to computer technology, and more particularly to an image processing method, apparatus, electronic device, storage medium, and program product. Background Technology

[0002] Existing mobile rendering methods can be implemented in two parts: one is driven by the mobile engine, and the other is resource delivery on the server side. During the mobile rendering process, the mobile engine drives the rendering pipeline to render the corresponding content based on the delivered resources.

[0003] However, in real-world mobile rendering scenarios, the subject often appears larger in the foreground and smaller in the background due to changes in the distance between the subject and the camera. Current rendering methods use end-to-end rendering, a generic rendering approach that doesn't differentiate between the size of the subject and the rendering process. This generic rendering leads to unnecessary resource downloads during the rendering process, resulting in wasted performance resources. Summary of the Invention

[0004] This disclosure provides an image processing method, apparatus, electronic device, storage medium, and program product to achieve selective rendering and reduce resource waste and performance consumption during the rendering process.

[0005] In a first aspect, embodiments of this disclosure provide an image processing method, including:

[0006] Determine the detection information corresponding to the image, the detection information including information associated with the parts of the object in the image;

[0007] Based on the detection information, determine the rendering information of the object;

[0008] Determine the resource information corresponding to the rendering information;

[0009] Obtain the resource corresponding to the resource information;

[0010] The object is rendered based on the resources.

[0011] Secondly, embodiments of this disclosure also provide an image processing apparatus, comprising:

[0012] The first determining module is used to determine the detection information corresponding to the image, the detection information including information associated with the part of the object in the image;

[0013] The second determining module is used to determine the rendering information of the object based on the detection information;

[0014] The third determining module is used to determine the resource information corresponding to the rendering information;

[0015] The acquisition module is used to acquire the resources corresponding to the resource information;

[0016] The rendering module is used to render the object based on the resource.

[0017] Thirdly, embodiments of this disclosure also provide an electronic device, including:

[0018] One or more processing devices;

[0019] Storage device for storing one or more programs.

[0020] When the one or more programs are executed by the one or more processing devices, the one or more processing devices implement any of the image processing methods described in this disclosure.

[0021] Fourthly, embodiments of this disclosure also provide a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform any of the image processing methods described in this disclosure.

[0022] Fifthly, embodiments of this disclosure also provide a computer program product, including a computer program that, when executed by a processor, implements the image processing method described in any one of the present disclosures.

[0023] The technical solution of this disclosure first determines the detection information corresponding to the image, the detection information including information associated with a part of an object in the image; then, based on the detection information, it determines the rendering information of the object; secondly, it determines the resource information corresponding to the rendering information; then, it acquires the resources corresponding to the resource information; and finally, it renders the object based on the resources. The image processing method provided in this disclosure determines the rendering information based on the detection information of a part in the image. This disclosure does not perform general rendering on the object to be rendered in the image, but rather dynamically selects the rendering information based on the rendering information of the object to be rendered, thereby reducing unnecessary computation and performance overhead during the rendering process. Then, it determines the resource information based on the rendering information and performs rendering accordingly, realizing dynamic selection of the resource information required for rendering, reducing additional resource waste, and optimizing the overall rendering performance. Attached Figure Description

[0024] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0025] Figure 1This is a schematic flowchart of an image processing method provided in an embodiment of this disclosure;

[0026] Figure 2 This is a schematic diagram of an image rendering method provided in an embodiment of this disclosure;

[0027] Figure 3 This is a schematic flowchart of a rendering information determination method provided in an embodiment of this disclosure;

[0028] Figure 4 This is a schematic diagram of the structure of an image processing device provided in an embodiment of this disclosure;

[0029] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0030] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0031] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0032] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0033] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0034] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0035] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0036] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0037] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.

[0038] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0039] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0040] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0041] Taking mobile rendering in a live streaming scenario as an example, in actual mobile rendering scenarios, the subject being rendered (also known as the object to be rendered) often appears larger when closer to the camera and smaller when farther away. For example, live streaming typically has two scenarios:

[0042] a. Scene A: Rendering a close-up of the main characters chatting; b. Scene B: Rendering a full-body shot of the main characters performing a talent show.

[0043] In a rendering process that doesn't differentiate between general processes, there will be some additional performance overhead, such as:

[0044] 1. In scene A, some full-body rendering effects will not be drawn, but the distribution and resource parsing of this part will be involved, resulting in additional waste of performance resources;

[0045] 2. In scene B, some material effects will cause redundant calculation and rendering of multiple vertices due to the distance of the scene and the limited screen size;

[0046] Regardless of scene A or scene B, there will be issues with downloading unnecessary resources. This disclosure calculates the number of skeletal key points to distinguish the size of the objects to be rendered in the image, selectively renders the required resources, reduces rendering precision, and reduces performance consumption.

[0047] In scene A, you need to use more detailed resources for a certain part of the object, but you can discard the special effects related to the parts that are not displayed; in scene B, you don't need to draw very detailed corner points.

[0048] This disclosure addresses scenarios A and B, distinguishing between different scenarios and dynamically selecting different resources for rendering to optimize overall performance and reduce rendering overhead. The image processing method provided in this disclosure is described below: Figure 1 This is a schematic flowchart of an image processing method provided by an embodiment of the present disclosure. The embodiments of the present disclosure are applicable to the rendering of images. The method can be executed by an image processing device, which can be implemented in the form of software and / or hardware. Optionally, it can be implemented by an electronic device, such as a mobile terminal, a PC, or a server.

[0049] like Figure 1 As shown, the method includes:

[0050] S110. Determine the detection information corresponding to the image, wherein the detection information includes information associated with the part of the object in the image.

[0051] In this embodiment, the image can be captured by an acquisition device, such as a camera, and may include an object to be rendered. The object to be rendered can be understood as an object in a scene that needs rendering processing. This scene can be a scene where the parts included in the object are rendered, such as a live streaming scene. Detection information can be understood as information associated with the state of the object to be rendered in the image. Detection information can be a judgment on whether the object to be rendered contains a defined part, or it can be the calculated proportion of the defined part in the image. The proportion information can represent the size of the defined part in the image. The proportion information can be determined by the ratio between the area occupied by the defined part and the image area, or by the ratio of the number of keypoints included in the defined part to the number of keypoints included in the image. Keypoints can be key location points of the skeleton in the image. This embodiment does not limit the specific type of object; different application scenarios can correspond to different objects. In a live streaming scene, the object can be an object associated with live streaming.

[0052] The designated area can be understood as one or more parts of the object to be rendered. There is no limitation on the specific area; it can be any part of the object that needs to be blended with media elements during the rendering process. Media elements can be considered as elements in the application that represent media, including images, audio, video, and text. When rendering the object, media elements can be blended into it, such as into the designated area, to add effects to the object.

[0053] This operation acquires an image containing the object to be rendered. This image can be a live stream image of the object, or a live stream image containing the object. Then, it detects the object in the acquired image to obtain detection information about whether the object contains that part, or the proportion of that part in the image. This detection information can be used to determine the information needed for subsequent rendering.

[0054] S120. Determine the rendering information of the object based on the detection information.

[0055] Rendering information can be understood as the different levels of detail used in rendering the object being rendered. Rendering information can be determined by both keypoint information and detection information, or it can be determined solely by detection information. Higher precision in the rendering information indicates higher levels of detail or information involved in the rendering process, and vice versa.

[0056] In this embodiment, the detection information may indicate whether the image includes a defined part of an object, or it may indicate the proportion of the object to be rendered in the image. Different detection information leads to different methods of determining the rendering information. In response to the detection information indicating the proportion of the object to be rendered in the image, the rendering information can be determined based on the detection information. Alternatively, in response to the detection information indicating whether the image includes a defined part of an object, the key point information of the object to be rendered in the image can be collected to determine the rendering information.

[0057] Keypoint information can be understood as information about key points in an image, such as their quantity. Keypoint information can refer to the number of skeletal keypoints, which are key parts of a skeletal system with specific locations and functions. These key parts can include joints or connection points, and they can be used to describe the pose and motion of the object being rendered. Depending on the application scenario, different joints or connection points can be selected as skeletal keypoints as needed.

[0058] In one embodiment, the number of skeletal keypoints of the object to be rendered in the image is determined as keypoint information. Predefined parts on the object in the image are identified to obtain detection information. The keypoint information and detection information are used as criteria for determining the rendering information.

[0059] In one embodiment, a graphic, such as a rectangle, is determined in the image to identify a designated area. The area of ​​the graphic is then determined to occupy the area of ​​the image, yielding proportion information. The size of this proportion information is then analyzed to determine rendering information.

[0060] In this operation, the distance of the object to be rendered in the image can be measured based on key point information, and the presence of a part in the image can be characterized by detection information. This part can be a part related to the rendering information.

[0061] In this operation, the size of a part in the image can be measured based on the proportion of the set part in the image. The proportion of the part in the image can be characterized by detection information, thereby determining the rendering information of the object to be rendered where the part is located.

[0062] If the detection information indicates that the object to be rendered can be rendered with low precision, then the rendering information can be determined as low-precision rendering. Otherwise, the rendering information can be determined as high-precision rendering.

[0063] This embodiment does not limit the division of rendering information, such as dividing it into high-precision rendering and low-precision rendering, or dividing it into rendering with at least two precisions.

[0064] During the rendering process, the key point information in the image is continuously checked and the corresponding detection information is determined. When changes occur, the rendering information of the object to be rendered is switched in real time according to the changed results.

[0065] S130. Determine the resource information corresponding to the rendering information.

[0066] In this embodiment, resource information can be understood as information used to render the object to be rendered, and may include information about the rendering algorithm and information about the media elements to be merged into the object.

[0067] In one embodiment, this operation can obtain a description file from the server. Different rendering information corresponds to different resource information. Higher-level rendering information indicates higher-level resource information, and vice versa. The description file can be understood as a file indicating different media elements corresponding to different rendering information. The description file can be obtained from the server. The description file can indicate the resources required to render the object corresponding to different rendering information.

[0068] This operation can locate the resource information corresponding to the rendering information in the description file, so as to obtain the corresponding resources based on the resource information. There is no limitation on the resources here; they can be resources required for rendering, such as media elements and / or the rendering algorithms used.

[0069] For example, the rendering description file can be obtained from the server. When obtaining the description file, resources may not be retrieved, or the resources corresponding to lower precision of the rendering information may be included, or default resources may be included. The default resources can be determined based on rendering information in most cases. During the rendering of the object to be rendered, its rendering information needs to be determined in real time, and when the rendering information changes, the resources corresponding to the rendering information should be switched promptly.

[0070] S140. Obtain the resource corresponding to the resource information.

[0071] In this embodiment, the resource information can refer to resources obtained locally or from a server. This resource can be used to perform rendering operations on the object to be rendered. The resource information can be used to indicate resources. The resource information can be included in a description file. After determining the resource information based on the description file, the resource indicated by the resource information can be obtained from the electronic device's local storage or the server.

[0072] For example, the resource corresponding to the resource information can be obtained from either the local machine or the server. You can first try to obtain the resource from the local machine; if the local machine does not store the resource, you can obtain it from the server. Resources can be templates, models, or data used when rendering an object. These resources can be rendered into the image corresponding to the object to be rendered, displaying the rendered image, such as an image with added effects.

[0073] S150. Render the object based on the resource.

[0074] This operation renders the object to be rendered based on the template, model, and data indicated by the resource. Different resources will be used in different ways during the rendering process. When the resource is a rendering algorithm, the object can be rendered based on that algorithm. When the resource is a media element, the media element can be rendered directly with the object or processed before being rendered with the object to add special effects and create the desired visual or auditory effects. If the resource is a media element, the resource is matched and adjusted with the object to be rendered to make them fit as closely as possible, resulting in an object containing the media element. The rendered object retains the original features, shape, and posture of the object to be rendered, and adds the features indicated by the resource.

[0075] For example, rendering an object to be rendered can be done by adding effects indicated by resources to the object, such as decorations, lighting, etc.

[0076] The technical solution of this disclosure first determines the detection information corresponding to the image, the detection information including information associated with a part of an object in the image; then, based on the detection information, it determines the rendering information of the object; secondly, it determines the resource information corresponding to the rendering information; then, it acquires the resources corresponding to the resource information; and finally, it renders the object based on the resources. The image processing method provided in this disclosure determines the rendering information based on the detection information of a part in the image. This disclosure does not perform general rendering on the object to be rendered in the image, but rather dynamically selects the rendering information based on the rendering information of the object to be rendered, thereby reducing unnecessary computation and performance overhead during the rendering process. Then, it determines the resource information based on the rendering information and performs rendering accordingly, realizing dynamic selection of the resource information required for rendering, reducing additional resource waste, and optimizing the overall rendering performance.

[0077] Based on the above embodiments, modified embodiments of the above embodiments are proposed. It should be noted that, in order to keep the description brief, only the differences from the above embodiments are described in the modified embodiments.

[0078] In one embodiment, the correspondence between different rendering information and different levels of resource information is indicated by a description file.

[0079] In this embodiment, different levels of resource information are assigned to different rendering information. The levels of resource information can include high precision and low precision; higher precision resource information corresponds to higher precision resources. For example, when rendering a part, the textures, meshes, and skeletal nodes of that part are drawn in greater detail. The description file stores different levels of resource information corresponding to different rendering information; the higher the precision of the rendering information, the higher the level of the corresponding resource information.

[0080] In one embodiment, the resources include one or more of the following:

[0081] The image processing algorithm used in the image;

[0082] Shaders;

[0083] Media elements;

[0084] Grid structure.

[0085] In this embodiment, the image processing algorithm can be understood as an algorithm used to process the image containing the object to be rendered. This image processing algorithm can merge media elements to be blended into the image containing the object to be rendered, and can also perform image segmentation, etc. A shader can be understood as a program used to handle various tasks during image rendering. A shader can define information such as pixels and vertices of the image. A mesh structure can be understood as a type of geometric structure data that can represent the structure and shape of the object to be rendered in space.

[0086] For example, Figure 2 This is a schematic diagram of an image rendering method provided in an embodiment of this disclosure. Figure 2 As shown, when selecting the selected effect corresponding to the object to be rendered in the client, a description file can be requested or retrieved from the server. Resources can include image processing algorithms, media elements, shaders, and mesh structures. The image processing algorithm matting can apply a segmentation detection switch, which can indicate whether to segment the image or control the segmentation accuracy. For example... Figure 2 As shown, for low-precision scenes, the corresponding resources may include low-precision image processing algorithms, low-precision media elements consisting of one or more low-resolution image resources or low-bitrate video resources, low-precision shaders, and low-precision mesh structures. Similarly, for high-precision scenes, the corresponding resources may include high-precision image processing algorithms, high-precision media elements consisting of one or more high-resolution image resources or high-bitrate video resources, high-precision shaders, and high-precision mesh structures.

[0087] The low-precision image processing algorithm may include a sixth-precision face fitting algorithm and a seventh-precision segmentation algorithm. The high-precision image processing algorithm may include an eighth-precision face fitting algorithm and a ninth-precision segmentation algorithm. The magnitude of each precision is not limited here, as long as the corresponding precision of image processing can be guaranteed. For example, the sixth precision can be greater than the eighth precision, and the seventh precision can be less than the ninth precision.

[0088] In one embodiment, before determining the detection information of the part of the object to be rendered in the image, the method further includes:

[0089] In response to the addition of media elements to the page, retrieve the description file from the server.

[0090] The page can be considered the page that triggers the addition of media elements. The addition operation can be considered as adding media elements to an object. The addition operation is not limited here; it can be a click operation on the identifier corresponding to a media element on the page. Adding media elements in this disclosure can be considered as adding media elements during the rendering process of an object, or adding processed media elements to achieve the addition of special effects.

[0091] In response to an add operation, this embodiment retrieves a description file from the server to blend media elements into the object to be rendered with the required precision.

[0092] Taking a special effects scene as an example, the process involves capturing the addition of media elements to an element on the page—that is, capturing a click on a specific effect—which triggers the addition of the media element to the object to be rendered. During this process, a description file is first retrieved from the server. Based on this description file, combined with detection information and keypoint information, rendering information, or the proportion of a defined part in the image, is determined. Next, resource information is determined, and the corresponding resources are acquired. Finally, the media elements included in these resources are integrated into the object to be rendered.

[0093] In one embodiment, the image processing method further includes:

[0094] In response to the addition of media elements to the page, retrieve the resources corresponding to the default rendering information.

[0095] In this embodiment, the default rendering information can be considered as rendering information judged based on experience. For an object to be rendered, the default rendering information can be rendering information that is applicable in most scenarios.

[0096] In this embodiment, in response to the add operation, in addition to obtaining the description file, the resources corresponding to the default rendering information can also be obtained at the same time, so as to obtain resources more quickly in the future and improve the rendering speed.

[0097] For example, in most cases, the rendering information is determined to be of lower precision, so this lower precision rendering information can be used as the default rendering information. The resources corresponding to the default rendering information are obtained synchronously when the rendering description file is acquired. This allows for faster rendering of the object to be rendered using the resources corresponding to the default rendering information. When a change in rendering information is detected, the resources corresponding to the rendering information are switched promptly, including switching low-precision media elements, low-precision shaders, and low-precision mesh structures to high-resolution media elements, high-precision shaders, and high-precision mesh structures.

[0098] In one embodiment, obtaining the resource corresponding to the resource information includes:

[0099] Determine whether the resource corresponding to the resource information is stored locally;

[0100] If so, retrieve the resource corresponding to the resource information from the local machine; otherwise, retrieve the resource corresponding to the resource information from the server.

[0101] In this embodiment, after determining the resource information corresponding to the rendering information, it is necessary to obtain the corresponding resource. First, it is determined whether the resource corresponding to the resource information is stored locally, that is, whether the image processing algorithm, media elements, shaders, and mesh structure are stored locally. If the resource corresponding to the resource information is already stored locally, the resource is directly obtained from the local storage; if the resource corresponding to the resource information is not stored locally, it is necessary to match or request the resource corresponding to the resource information from the server.

[0102] In one embodiment, determining the detection information corresponding to the image includes:

[0103] Obtain the live image of the object;

[0104] The selected parts of the object in the live image are detected to obtain detection information.

[0105] In this embodiment, a live image can be understood as an image captured from the live stream of the object to be rendered. The live image can be image content transmitted in real time over a network.

[0106] This operation can capture an image from the live stream of an object to be rendered, which can include a defined portion of the object to be rendered. The state of this defined portion within the live stream image is then detected, yielding detection information. This detection operation can involve calculating the proportion of the area of ​​the graphic containing that portion within the total area of ​​the live stream image.

[0107] In one embodiment, the detection information indicates the proportion of a defined portion of the object in the image.

[0108] In this embodiment, the proportion information can be understood as the proportion or share of a certain part in the whole, which can be the proportion information between the area of ​​the set part and the overall area of ​​the image.

[0109] This operation allows you to use a regular shape, such as a rectangle or circle, within an image to contain a specified area. It then determines the area of ​​the shape containing the area, calculates the ratio of that area to the image area, and uses this ratio as the proportion of the specified area on the object within the image.

[0110] In one embodiment, determining the rendering information of the object based on the detection information includes:

[0111] In response to the fact that the percentage information is greater than the first value, the rendering information is determined to be of the fourth precision;

[0112] In response to the fact that the percentage information is less than the second value, the rendering information is determined to be of the fifth precision;

[0113] In response to the fact that the percentage information is greater than the second value and less than the first value, the rendering information is determined to be the precision of the previous determination;

[0114] The fourth precision is greater than the fifth precision, and the first value is greater than the second value.

[0115] In this embodiment, both the first and second values ​​can be understood as values ​​set to distinguish the rendering information of the object to be rendered. Both the first and second values ​​can represent different proportions of the set part in the image. Specifically, the first and second values ​​must be set to different values, and the first value must be set to a value larger than the second value. The fourth and fifth precision can both be understood as a type of rendering information. In this embodiment, different proportion information can correspond to different rendering information.

[0116] In this embodiment, the rendering information corresponding to the first value is the fourth precision, and the rendering information corresponding to the second value is the fifth precision. The fourth precision can be a higher precision than the rendering information corresponding to the fifth precision. When the proportion information is greater than the first value, the set part occupies a large proportion in the image, and can be considered as a foreground in the image. A higher rendering information, such as the fourth precision, can be used to render the object to be rendered. When the proportion information is less than the second value, the set part occupies a small proportion in the image, and can be considered as a background in the image. A lower rendering information, such as the fifth precision, can be used to render the object to be rendered. When the proportion information is greater than the second value and less than the first value, it indicates that the part is of a moderate size in the image. At this time, the rendering information can be determined as the precision determined last time. Specifically: when the proportion information was previously determined to be greater than the first value, the current rendering information is set to the fourth precision; when the proportion information was previously determined to be less than the second value, the current rendering information is set to the fifth precision.

[0117] For example, the first value can be set to 0.1, and the second value can be set to 0.02. The fourth precision can be rendering information used when rendering close-up views, and the fifth precision can be rendering information used when rendering distant views.

[0118] Therefore, in response to a percentage information > 0.1, the rendering information is set to the fourth precision; in response to a percentage information < 0.02, the rendering information is set to the fifth precision; and in response to 0.02 < percentage information < 0.1, the rendering information is set to the precision determined last time.

[0119] In one embodiment, the detection information indicates whether the image contains a defined portion of the object, and determining the rendering information of the object based on the detection information includes:

[0120] The rendering information of the object is determined based on the key point information in the image and the detection information.

[0121] In this embodiment, the number of skeletal keypoints of the object to be rendered in the image is determined as keypoint information. The keypoint information and detection information are used as criteria for determining the rendering information. Detection information measures whether a defined region is present in the image, while keypoint information measures the distance of the object to be rendered corresponding to that defined region within the image.

[0122] Figure 3 This is a schematic flowchart of a rendering information determination method provided in this embodiment of the present disclosure, which refines the determination of rendering information.

[0123] like Figure 3 As shown, the method includes:

[0124] S210. Determine the detection information corresponding to the image, the detection information including information associated with the part of the object in the image, and execute S220, or S230, or S240.

[0125] To determine whether an image contains a part of an object to be rendered, we can check if most or all of the corresponding skeletal keypoints are located in the image. If so, the image is considered to contain the part. If the corresponding skeletal keypoints are absent or only a very small number are located in the image, the image is considered not to contain the part.

[0126] S220: In response to the fact that the number of key points indicated by the key point information in the image is greater than or equal to a set threshold, and the detection information indicates that the image contains the part, the rendering information of the object is determined to be of first precision, and S250 is executed.

[0127] In this embodiment, the threshold setting can be understood as a preset value used to determine the number of key points indicated by the key point information, thereby representing the critical value of the distance of the object in the image. The threshold setting can be an empirical value set manually.

[0128] The first precision can be understood as a type of rendering information. In this embodiment, different detection information and different quantities may correspond to different precisions.

[0129] For example, the set threshold is denoted as T, and the number of key points indicated by the key point information in the image is denoted as N. As Figure 2 shown, when N≥T is satisfied and the detection information indicates that the image includes the part of the object to be rendered, it may be considered that the object in the image is in a long-distance shooting state, and the image includes the part of interest, and the rendering information may be set to the first precision. The first precision may be a moderate type of rendering information.

[0130] S230: In response to the number of key points indicated by the key point information in the image being greater than or equal to the set threshold, and the detection information indicating that the image does not have the part, determine that the rendering information of the object is the second precision, and execute S250.

[0131] For example, as Figure 2 shown, when N≥T is satisfied and the detection information indicates that the image does not include the part of the object to be rendered, it may be considered that the object in the image is in a long-distance shooting state, and the image does not include the part of interest, and the rendering information may be set to the second precision. The second precision may also be a precision that is lower than or equal to the rendering information corresponding to the first precision.

[0132] S240: In response to the key point information in the image being less than the set threshold, and the detection information indicating that the image includes the part, determine that the rendering information of the object is the third precision, and execute S250.

[0133] The third precision is greater than the first precision, and the first precision is greater than or equal to the second precision.

[0134] For example, as Figure 2 shown, when N<T is satisfied and the detection information indicates that the image includes the part of the object to be rendered, it may be considered that the object is in a close-shot state, and the image includes the part of interest, and the rendering information may be set to the third precision. The third precision may be rendering information corresponding to rendering with a relatively high precision.

[0135] S250: Determine resource information corresponding to the rendering information.

[0136] S260: Acquire a resource corresponding to the resource information.

[0137] S270: Render the object based on the resource.

[0138] The technical solution of this disclosure, in response to the number of key points indicated by key point information in the image being greater than or equal to a set threshold, and the detection information indicating that the image contains the part, determines the rendering information of the object to be of a first precision; in response to the number of key points indicated by key point information in the image being greater than or equal to the set threshold, and the detection information indicating that the image does not contain the part, determines the rendering information of the object to be of a second precision; in response to the number of key points indicated by key point information in the image being less than the set threshold, and the detection information indicating that the image contains the part, determines the rendering information of the object to be of a third precision; wherein, the third precision is greater than the first precision, and the first precision is greater than or equal to the second precision. This refines the method for determining the rendering information of an object based on key point information and detection information in an image. By using the key point information in the image and the judgment result of whether a part of the object to be rendered exists, different rendering information can be determined. Rendering the object to be rendered according to different rendering information can reduce additional performance resource waste and improve overall rendering performance.

[0139] Figure 4 This is a schematic diagram of the structure of an image processing apparatus provided in an embodiment of the present disclosure, as shown below. Figure 4 As shown, the device includes: a first determining module 310, a second determining module 320, a third determining module 330, an acquisition module 340, and a rendering module 350.

[0140] The first determining module 310 is used to determine the detection information corresponding to the image, the detection information including information associated with the part of the object in the image.

[0141] The second determining module 320 is used to determine the rendering information of the object based on the detection information.

[0142] The third determining module 330 is used to determine the resource information corresponding to the rendering information.

[0143] The acquisition module 340 is used to acquire the resource corresponding to the resource information.

[0144] Rendering module 350 is used to render the object based on the resource.

[0145] The technical solution provided in this disclosure first determines the detection information corresponding to the image through a first determining module. The detection information includes information associated with a part of an object in the image. Next, a second determining module determines the rendering information of the object based on the detection information. Then, a third determining module determines the resource information corresponding to the rendering information. Next, an acquiring module acquires the resources corresponding to the resource information. Finally, a rendering module renders the object based on the resources. Through the cooperation between these modules, rendering information is determined based on the detection information of parts in the image. This disclosure does not perform general rendering on the object to be rendered in the image, but rather dynamically selects the rendering information based on the rendering information of the object to be rendered, thereby reducing unnecessary computation and performance overhead during the rendering process. Then, resource information is determined based on the rendering information, and rendering is performed accordingly. This achieves dynamic selection of the resource information required for rendering, reduces additional resource waste, and optimizes the overall rendering performance.

[0146] In one embodiment, the detection information indicates whether the image contains a defined region on the object, and the second determining module 320 includes:

[0147] The determining unit is used to determine the rendering information of the object based on the key point information in the image and the detection information.

[0148] In one embodiment, the determining unit is specifically used for:

[0149] In response to the fact that the number of key points indicated by the key point information in the image is greater than or equal to a set threshold, and the detection information indicates that the image contains the part, the rendering information of the object is determined to be of a first precision.

[0150] In response to the fact that the number of key points indicated by the key point information in the image is greater than or equal to the set threshold, and the detection information indicates that the part is not in the image, the rendering information of the object is determined to be of the second precision;

[0151] In response to the fact that the number of key points indicated by the key point information in the image is less than the set threshold, and the detection information indicates that the image contains the part, the rendering information of the object is determined to be of third precision;

[0152] Wherein, the third precision is greater than the first precision, and the first precision is greater than or equal to the second precision.

[0153] In one embodiment, the resources include one or more of the following:

[0154] The image processing algorithm used in the image;

[0155] Shaders;

[0156] Media elements;

[0157] Grid structure.

[0158] In one embodiment, the image processing apparatus further includes an adding module, comprising:

[0159] The first acquisition unit is used to retrieve the description file from the server in response to the addition of media elements on the page.

[0160] In one embodiment, the first acquisition unit further includes a second acquisition subunit, specifically used for:

[0161] In response to the addition of media elements to the page, retrieve the resources corresponding to the default rendering information.

[0162] In one embodiment, the acquisition module 340 is specifically used for:

[0163] Determine whether the resource corresponding to the resource information is stored locally;

[0164] If so, retrieve the resource corresponding to the resource information from the local machine; otherwise, retrieve the resource corresponding to the resource information from the server.

[0165] In one embodiment, the first determining module 310 is specifically used for:

[0166] Obtain the live image of the object;

[0167] The selected parts of the object in the live image are detected to obtain detection information.

[0168] In one embodiment, the detection result indicates the proportion of a defined part of the object in the image.

[0169] In one embodiment, the second determining module 320 is specifically used for:

[0170] In response to the fact that the percentage information is greater than the first value, the rendering information is determined to be of the fourth precision;

[0171] In response to the fact that the percentage information is less than the second value, the rendering information is determined to be of the fifth precision;

[0172] In response to the fact that the percentage information is greater than the second value and less than the first value, the rendering information is determined to be the precision of the previous determination;

[0173] The fourth precision is greater than the fifth precision, and the first value is greater than the second value.

[0174] The image processing apparatus provided in this disclosure can execute the image processing method provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects for executing the method.

[0175] It is worth noting that the various units and modules included in the above-mentioned device are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the protection scope of the embodiments of this disclosure.

[0176] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Refer to the following... Figure 5 It illustrates an electronic device suitable for implementing embodiments of the present disclosure (e.g., Figure 5 A structural diagram of the terminal device or server in the 500.

[0177] Electronic equipment 500, including:

[0178] One or more processing devices 501;

[0179] Storage device 508, for storing one or more programs,

[0180] When the one or more programs are executed by the one or more processing devices 501, the one or more processing devices 501 implement any of the methods provided in this disclosure.

[0181] The terminal devices in this disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0182] like Figure 5 As shown, electronic device 500 may include a processing unit (e.g., central processing unit, graphics processor, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from storage device 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of electronic device 500. The processing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. An edit / output (I / O) interface 505 is also connected to bus 504.

[0183] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0184] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, it performs the functions defined in the methods of embodiments of this disclosure.

[0185] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0186] The electronic device provided in this embodiment and the image processing method provided in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0187] This disclosure provides a computer storage medium storing a computer program that, when executed by a processor, implements the image processing method provided in the above embodiments.

[0188] It should be noted that the computer-readable medium described above in this disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination thereof.

[0189] The computer storage medium may be a storage medium for computer-executable instructions, which, when executed by a computer processor, are used to perform the methods provided in this disclosure.

[0190] Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0191] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0192] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0193] The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: acquire at least two Internet Protocol (IP) addresses; send a node evaluation request including the at least two IP addresses to a node evaluation device, wherein the node evaluation device selects an IP address from the at least two IP addresses and returns it; and receive the IP address returned by the node evaluation device; wherein the acquired IP address indicates an edge node in a content delivery network.

[0194] Alternatively, the aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: receive a node evaluation request including at least two Internet Protocol (IP) addresses; select an IP address from the at least two IP addresses; and return the selected IP address; wherein the received IP address indicates an edge node in the content delivery network.

[0195] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0196] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0197] The modules or units described in the embodiments of this disclosure can be implemented in software or hardware. The names of modules or units do not necessarily limit the specific unit; for example, the first determining module can also be described as a "detection information determining unit".

[0198] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0199] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0200] A computer program product includes a computer program that, when executed by a processor, implements the image processing method provided in this disclosure.

[0201] According to one or more embodiments of this disclosure, [Example 1] provides an image processing method, including:

[0202] Determine the detection information corresponding to the image, the detection information including information associated with the parts of the object in the image;

[0203] Based on the detection information, determine the rendering information of the object;

[0204] Determine the resource information corresponding to the rendering information;

[0205] Obtain the resource corresponding to the resource information;

[0206] The object is rendered based on the resources.

[0207] According to one or more embodiments of this disclosure, [Example 2] provides the method of Example 1, wherein the detection information indicates whether the image contains a defined portion of the object, and the step of determining the rendering information of the object based on the detection information includes:

[0208] The rendering information of the object is determined based on the key point information in the image and the detection information.

[0209] According to one or more embodiments of this disclosure, [Example 3] provides the method of Example 2, wherein determining the rendering information of the object based on key point information in the image and the detection information includes:

[0210] In response to the fact that the number of key points indicated by the key point information in the image is greater than or equal to a set threshold, and the detection information indicates that the image contains the part, the rendering information of the object is determined to be of a first precision.

[0211] In response to the fact that the number of key points indicated by the key point information in the image is greater than or equal to the set threshold, and the detection information indicates that the part is not in the image, the rendering information of the object is determined to be of the second precision;

[0212] In response to the fact that the number of key points indicated by the key point information in the image is less than the set threshold, and the detection information indicates that the image contains the part, the rendering information of the object is determined to be of third precision;

[0213] Wherein, the third precision is greater than the first precision, and the first precision is greater than or equal to the second precision.

[0214] According to one or more embodiments of this disclosure, [Example 4] provides the method described in Example 1, wherein the resources include one or more of the following:

[0215] The image processing algorithm used in the image;

[0216] Shaders;

[0217] Media elements;

[0218] Grid structure.

[0219] According to one or more embodiments of this disclosure, Example 5 provides the method described in Example 1, wherein the correspondence between different rendering information and different levels of resource information is indicated by a description file.

[0220] According to one or more embodiments of this disclosure, [Example 6] provides the method of Example 5, which further includes, before determining the detection information of the part of the object to be rendered in the image:

[0221] In response to the addition of media elements to the page, retrieve the description file from the server.

[0222] According to one or more embodiments of this disclosure, Example 7 provides the method described in Example 6, further comprising:

[0223] In response to the addition of media elements to the page, retrieve the resources corresponding to the default rendering information.

[0224] According to one or more embodiments of this disclosure, [Example 8] provides the method described in Example 1, wherein obtaining the resource corresponding to the resource information includes:

[0225] Determine whether the resource corresponding to the resource information is stored locally;

[0226] If so, retrieve the resource corresponding to the resource information from the local machine; otherwise, retrieve the resource corresponding to the resource information from the server.

[0227] According to one or more embodiments of this disclosure, [Example 9] provides the method of Example 1, wherein determining the detection information corresponding to the image includes:

[0228] Obtain the live image of the object;

[0229] The selected parts of the object in the live image are detected to obtain detection information.

[0230] According to one or more embodiments of this disclosure, [Example 10] provides the method of Example 1, wherein the detection information indicates the proportion of a defined part of the object in the image.

[0231] According to one or more embodiments of this disclosure, Example 11 provides a method for determining rendering information of the object based on the detection information, including:

[0232] In response to the fact that the percentage information is greater than the first value, the rendering information is determined to be of the fourth precision;

[0233] In response to the fact that the percentage information is less than the second value, the rendering information is determined to be of the fifth precision;

[0234] In response to the fact that the percentage information is greater than the second value and less than the first value, the rendering information is determined to be the precision of the previous determination;

[0235] The fourth precision is greater than the fifth precision, and the first value is greater than the second value.

[0236] According to one or more embodiments of this disclosure, [Example 12] a data processing apparatus is provided, comprising:

[0237] The first determining module is used to determine the detection information corresponding to the image, the detection information including information associated with the part of the object in the image;

[0238] The second determining module is used to determine the rendering information of the object based on the detection information;

[0239] The third determining module is used to determine the resource information corresponding to the rendering information;

[0240] The acquisition module is used to acquire the resources corresponding to the resource information;

[0241] The rendering module is used to render the object based on the resource.

[0242] According to one or more embodiments of this disclosure, [Example 13] an electronic device is provided, the electronic device comprising:

[0243] One or more processing devices;

[0244] Storage device for storing one or more programs.

[0245] When the one or more programs are executed by the one or more processing devices, the one or more processing devices implement the image processing method as described in any of Examples 1-11.

[0246] According to one or more embodiments of this disclosure, [Example 14] provides a storage medium containing computer-executable instructions that, when executed by a computer processor, are used to perform an image processing method as described in any of Examples 1-11.

[0247] According to one or more embodiments of this disclosure, [Example 15] provides a computer program product including a computer program that, when executed by a processor, implements the image processing method according to any one of Examples 1-11.

[0248] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0249] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0250] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. An image processing method, characterized in that, include: Determine the detection information corresponding to the image, the detection information including information associated with the parts of the object in the image; Based on the detection information, determine the rendering information of the object; Determine the resource information corresponding to the rendering information; Obtain the resource corresponding to the resource information; The object is rendered based on the resources.

2. The method according to claim 1, characterized in that, The detection information indicates whether the image contains a defined portion of the object. Determining the rendering information of the object based on the detection information includes: The rendering information of the object is determined based on the key point information in the image and the detection information.

3. The method according to claim 2, characterized in that, Determining the rendering information of the object based on the key point information in the image and the detection information includes: In response to the fact that the number of key points indicated by the key point information in the image is greater than or equal to a set threshold, and the detection information indicates that the image contains the part, the rendering information of the object is determined to be of a first precision. In response to the fact that the number of key points indicated by the key point information in the image is greater than or equal to the set threshold, and the detection information indicates that the part is not in the image, the rendering information of the object is determined to be of the second precision; In response to the fact that the number of key points indicated by the key point information in the image is less than the set threshold, and the detection information indicates that the image contains the part, the rendering information of the object is determined to be of third precision; Wherein, the third precision is greater than the first precision, and the first precision is greater than or equal to the second precision.

4. The method according to claim 1, characterized in that, The resources include one or more of the following: The image processing algorithm used in the image; Shaders; Media elements; Grid structure.

5. The method according to claim 1, characterized in that, The correspondence between different rendering information and different levels of resource information is indicated by the description file.

6. The method according to claim 5, characterized in that, Before determining the detection information of the part of the object to be rendered in the image, the method further includes: In response to the addition of media elements to the page, retrieve the description file from the server.

7. The method according to claim 6, characterized in that, Also includes: In response to the addition of media elements to the page, retrieve the resources corresponding to the default rendering information.

8. The method according to claim 1, characterized in that, The resource corresponding to the resource information obtained includes: Determine whether the resource corresponding to the resource information is stored locally; If so, retrieve the resource corresponding to the resource information from the local machine; otherwise, retrieve the resource corresponding to the resource information from the server.

9. The method according to claim 1, characterized in that, The detection information corresponding to the determined image includes: Obtain the live image of the object; The selected parts of the object in the live image are detected to obtain detection information.

10. The method according to claim 1, characterized in that, The detection information indicates the proportion of a specific part of the object in the image.

11. The method according to claim 10, characterized in that, Determining the rendering information of the object based on the detection information includes: In response to the fact that the percentage information is greater than the first value, the rendering information is determined to be of the fourth precision; In response to the fact that the percentage information is less than the second value, the rendering information is determined to be of the fifth precision; In response to the fact that the percentage information is greater than the second value and less than the first value, the rendering information is determined to be the precision of the previous determination; The fourth precision is greater than the fifth precision, and the first value is greater than the second value.

12. An image processing apparatus, characterized in that, include: The first determining module is used to determine the detection information corresponding to the image, the detection information including information associated with the part of the object in the image; The second determining module is used to determine the rendering information of the object based on the detection information; The third determining module is used to determine the resource information corresponding to the rendering information; The acquisition module is used to acquire the resources corresponding to the resource information; The rendering module is used to render the object based on the resource.

13. An electronic device, characterized in that, The electronic device includes: One or more processing devices; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processing devices, the one or more processing devices implement the image processing method as described in any one of claims 1-11.

14. A storage medium comprising computer-executable instructions, which, when executed by a computer processor, are used to perform the image processing method as described in any one of claims 1-11.

15. A computer program product comprising a computer program that, when executed by a processor, implements the image processing method according to any one of claims 1-11.

Images