Picture processing method, electronic device, and electronic device cluster

Abstract

The present application relates to the technical field of computers. Embodiments of the present application provide a picture processing method, an electronic device, and an electronic device cluster. The picture processing method provided in the embodiments of the present application is applied to an electronic device. Specifically, the picture processing method provided in the embodiments of the present application comprises: displaying at least one first picture comment, wherein one first picture comment corresponds to one visual effect attribute, and the first picture comment comprises information describing that a first picture does not meet a corresponding visual effect standard; and displaying a second picture, wherein the second picture is generated by editing the first picture by using all or some of the visual effect attributes corresponding to the at least one first picture comment as an editing object. In the method of the embodiments of the present application, image optimization can be performed on the image defect in the picture while an image defect in a picture is described to a user, thereby reducing the difficulty of picture editing and improving the user experience of picture editing while assisting the user in improving the recognition capability of the user on the picture beautification direction and expanding the picture aesthetic knowledge of the user.

Description

An image processing method, an electronic device, and a cluster of electronic devices.

[0001] This application claims priority to Chinese Patent Application No. 202411463322.X, filed on October 18, 2024, entitled "A Method for Image Processing, Electronic Device and Cluster of Electronic Devices", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of computer technology, and in particular to an image processing method, an electronic device, and a cluster of electronic devices. Background Technology

[0003] With the development of computer technology, the processing performance of terminal devices (such as mobile phones, tablets, or personal computers) is constantly improving, and the application functions that terminal devices can support are becoming more and more diversified.

[0004] In existing technology applications, many terminal devices offer image editing functions, meaning that users input images, and the terminal device can edit the images to improve the visual effect of the photos.

[0005] However, in the aforementioned image editing application scenarios, the terminal device merely provides image editing tools, and the image editing process still relies on manual operation by the user. This makes the image editing process cumbersome, and the effect of image editing depends on the user's proficiency in operating the image editing tools and the user's personal aesthetic sense, resulting in a less than ideal final image editing effect.

[0006] Therefore, an image processing method is needed to simplify the image editing process and improve the editing effect. Summary of the Invention

[0007] To address the issues of simplifying the image editing process and improving the image editing effect, this application provides an image processing method, an electronic device, and an electronic device cluster. This application also provides an image processing apparatus, a program product, and a computer-readable storage medium.

[0008] The embodiments of this application adopt the following technical solutions:

[0009] In a first aspect, this application provides an image processing method applied to an electronic device, the method comprising:

[0010] The electronic device displays at least one first image commentary, wherein:

[0011] The first image review is based on the visual effect standards corresponding to the visual effect attributes, and is derived from the analysis of the first image.

[0012] One first-image comment corresponds to one visual effect attribute;

[0013] The first image review includes information describing how the first image does not meet the corresponding visual standards.

[0014] Specifically, in one implementation of the first aspect, when the visual effect of the first image on a certain visual effect attribute does not meet one or more visual effect standards corresponding to that visual effect attribute, a comment on the first image for that visual effect attribute is generated. Based on the comment on the first image, the user can know the visual effect standards that the first image does not meet.

[0015] Based on the first approach, self-service analysis can be performed on the visual effect attributes of images, pointing out visual effect attributes that do not meet the visual effect standards to users, thereby helping users improve their ability to identify the direction of image beautification and expanding their knowledge of image aesthetics.

[0016] In the implementation of the first aspect, various different methods can be used to define visual effect attributes and determine the visual effect standards corresponding to the visual effect attributes.

[0017] In one implementation of the first aspect, the electronic device can be configured to perform the analysis of visual effect attributes based on the currently achievable beautification dimensions, with each beautification dimension corresponding to a visual effect attribute.

[0018] For example, configuring electronic devices can enable the analysis of visual attributes, including but not limited to:

[0019] A combination of any one or more of the following: texture, composition, lighting, style, and blurring.

[0020] In one implementation of the first aspect, for a visual effect attribute, there exists one or more sets of visual effect standards, and each set of visual effect standards contains one or more visual effect standards.

[0021] In one implementation of the first aspect, those skilled in the art can pre-design visual effect standards corresponding to visual effect attributes according to the actual needs of the application scenario, and uniformly apply the designed visual effect standards to multiple electronic devices.

[0022] In another implementation of the first aspect, before the electronic device implements the method of the embodiments of this application, the user of the electronic device may also set the visual effect standard used by the current electronic device according to their own needs.

[0023] In another implementation of the first aspect, the same visual effect attribute of multiple images that meet the visual effect requirements is summarized to obtain a visual effect standard for that visual effect attribute.

[0024] Furthermore, in one implementation of the first aspect, the image processing method further includes the electronic device displaying a second image, wherein:

[0025] The second image is generated by editing the first image, using all or part of the visual effect attributes corresponding to at least one of the first image comments as the editing object;

[0026] Regarding the visual effect attributes of the object being edited, the second image meets the corresponding visual effect standards.

[0027] Based on the above implementation method of the first aspect, image optimization can be performed on the image defects of the image while describing them to the user, thereby reducing the difficulty of image editing, improving the user's ability to identify the direction of image beautification, and enhancing the user experience of image editing.

[0028] In order to display at least one first image comment, in one implementation of the first aspect:

[0029] Using the visual effect attributes of the first number of images as the analysis object, analyze the first image and generate a second number of comments on the first image.

[0030] The second number of first image comments will be displayed to the user.

[0031] Specifically, in the second number of first image comments, each first image comment corresponds to one visual effect attribute in the first number of visual effect attributes.

[0032] Considering that the first image commentary is used to describe visual effect criteria that the first image does not meet, if the first image meets the visual effect criteria, a first image commentary is not generated for visual effect attributes that meet the visual effect criteria. Therefore, in one implementation of the first aspect, the second quantity is less than or equal to the first quantity.

[0033] In one implementation of the first aspect, the first number of visual effect attributes is all the visual effect attributes that the electronic device can analyze.

[0034] Furthermore, in another implementation of the first aspect, the first number of visual effect attributes is a subset of all visual effect attributes that the electronic device can analyze.

[0035] Electronic devices can determine the visual effects attributes that need to be analyzed based on actual needs, thereby reducing the amount of data processing and improving analysis efficiency while meeting application requirements.

[0036] Furthermore, in another implementation of the first aspect, the electronic device determines the visual effect attributes that need to be analyzed based on user instructions, thereby matching the analysis results with user needs and improving the user experience.

[0037] Specifically, in another implementation of the first aspect:

[0038] Receive a first selection instruction, which is used to point to a first number of visual effect attributes;

[0039] Based on the first selection instruction, a first number of visual effect attributes are determined from all visual effect attributes that can be analyzed.

[0040] In order to generate a second number of first image comments, in one implementation of the first aspect:

[0041] Taking a first number of visual effect attributes as the analysis object, analyze the first image and obtain the first analysis result. The first analysis result includes whether the first image meets or does not meet the corresponding visual effect standard for any one of the first number of visual effect attributes.

[0042] Based on the results of the first analysis, a second number of first image comments are generated.

[0043] Specifically, based on the first analysis results, when the first image does not meet the visual effect standard, a commentary on the first image corresponding to that visual effect attribute is generated; when the first image meets the visual effect standard, no commentary is generated for that visual effect attribute.

[0044] Based on the above implementation method of the first aspect, and based on the first analysis result, a first image commentary corresponding to the visual effect attribute is generated only when the first image does not meet the visual effect standard. Under the premise of ensuring that sufficient image commentary information is provided to the user, the amount of data processing is effectively controlled, the amount of data output to the user is reduced, and redundant output is avoided, which may cause user annoyance and improve the user experience.

[0045] Furthermore, for the same image, the desired aesthetic effect will differ depending on the image's expressive objective. In other words, when analyzing the aesthetic effect of an image, even for the same visual effect attribute, different visual effect standards are required.

[0046] Therefore, in order to obtain accurate first analysis results, in one implementation of the first aspect:

[0047] Perform intent recognition on the first image to obtain the image's intended meaning;

[0048] Based on the image's intended meaning, invoke the visual effect standards corresponding to the first number of visual effect attributes;

[0049] Using the first number of visual effect attributes as the analysis object, and based on the visual effect standards corresponding to the first number of visual effect attributes, the first image is analyzed to obtain the first analysis result.

[0050] Based on the above implementation method of the first aspect, the intent recognition of the image is performed to obtain the image's expressive intent. The corresponding visual effect standard is called to analyze the image based on the image's expressive intent, which can improve the accuracy of the image analysis results, thereby generating more accurate image comments in the future and improving the user experience.

[0051] Furthermore, in order to accurately identify the expressive intent of the image, in one implementation of the first aspect, the electronic device provides an image intent input interface, which is used to obtain intent information input by the user, and the intent information is used to describe the expressive purpose of the first image.

[0052] Specifically, in one implementation of the first aspect:

[0053] Receive intent information from user input;

[0054] Performing intent recognition on the first image to obtain the image's expressive intent includes performing intent recognition on the first image based on intent information to obtain the image's expressive intent.

[0055] According to the above implementation method of the first aspect, obtaining the intent information input by the user and recognizing the image expression intent of the first image based on the intent information input by the user can improve the recognition accuracy of the image expression intent, thereby obtaining accurate first analysis results in the subsequent process.

[0056] In order to display the second image, in one implementation of the first aspect:

[0057] Determine a third number of visual effect attributes, wherein the third number of visual effect attributes includes all or part of the visual effect attributes corresponding to the second number of first image comments;

[0058] Using the third visual effect attribute as the editing object, edit the first image to generate the second image.

[0059] Specifically, in one implementation of the first aspect, the third number of visual effect attributes is all the visual effect attributes corresponding to the second number of first image comments.

[0060] Based on the above implementation method of the first aspect, by using all the visual effect attributes corresponding to the first image commentary as the editing object, the image can be edited. The parts of the first image that do not meet the visual effect standards presented to the user through the first image commentary can be edited to meet the visual effect standards, thereby realizing the process of automatically raising and automatically solving aesthetic problems, reducing the difficulty of image editing, and improving the user experience of image editing.

[0061] Specifically, in one implementation of the first aspect, the third number of visual effect attributes is a portion of the visual effect attributes corresponding to the second number of first image comments.

[0062] Based on the above implementation method of the first aspect, by using the visual effect attributes corresponding to the first image commentary as the editing object, the image can be edited in a targeted manner. This allows for the editing of a portion of the first image that does not meet the visual effect standards to meet them. On the basis of realizing the process of automatically raising and automatically solving aesthetic problems, the image editing is more targeted, more flexible, and the user experience of image editing is improved.

[0063] Specifically, in one implementation of the first aspect, the third number of visual effect attributes also includes other visual effect attributes besides those corresponding to the first image commentary in the second number.

[0064] Based on the above implementation method of the first aspect, using visual effect attributes other than the visual effect attributes corresponding to the first image comment as the editing object to edit the image can improve the editing effect of image editing, enhance the freedom of image editing, and improve the user experience of image editing.

[0065] Specifically, in one implementation of the first aspect, the electronic device determines the visual effect attributes of the object to be edited based on user instructions.

[0066] Specifically, in one implementation of the first aspect:

[0067] Receive the user's second selection instruction, which is used to point to a third number of visual effect attributes;

[0068] Based on the second selection instruction, determine the third number of visual effect attributes.

[0069] Based on the above implementation method of the first aspect, the visual effect attributes of the editing object are determined based on user instructions. This allows for image editing according to user needs, increasing the freedom of image editing, making the image editing results more in line with user needs, and improving the user experience of image editing.

[0070] Furthermore, in one implementation of the first aspect, a neural network model is used to perform image analysis and / or image editing.

[0071] In one implementation of the first aspect, two neural network models are used to perform image analysis and editing.

[0072] Specifically, image processing methods include:

[0073] Displaying at least one first image comment includes inputting a first image into a first neural network model and obtaining at least one first image comment output by the first neural network model;

[0074] Displaying the second image includes inputting the first image and a second selection instruction into the second neural network model, and obtaining the second image output by the second neural network model.

[0075] Based on the above implementation method of the first aspect, two neural network models are used to implement image analysis and editing respectively. The first neural network model and the second neural network model can be trained, adjusted and replaced independently according to actual needs, which improves the freedom and flexibility of the method implementation.

[0076] In another implementation of the first aspect, a neural network model is used to perform analysis and editing of the image.

[0077] Specifically, image processing methods include:

[0078] Displaying at least one first image comment includes inputting a first image into a third neural network model and obtaining at least one first image comment output by the third neural network model;

[0079] Displaying the second image includes inputting a second selection instruction into the third neural network model and obtaining the second image output by the third neural network model.

[0080] Based on the above implementation method of the first aspect, a neural network model is used to implement the analysis and editing of images, which reduces the processing resource consumption during the training of the neural network model and reduces the difficulty of implementing the method.

[0081] Furthermore, in one implementation of the first aspect, the first image commentary also includes explanatory information that describes why the first image does not meet the visual effect standards.

[0082] Based on the explanatory information in the first image review, users can learn detailed information about why an image does not meet the visual effect standards, such as which part of the image does not meet the visual effect standards and why.

[0083] Based on the above implementation method of the first aspect, the reasons why the first image does not meet the visual effect standards can be explained through the explanatory information in the image commentary, thereby accurately expressing the visual effect defects of the image to the user, helping the user understand image enhancement knowledge, and improving the user experience of image processing.

[0084] Furthermore, in one implementation of the first aspect, the first image review also includes image editing suggestions, which describe the operation process of editing the image, and the operation process of editing the image is used to edit the first image so that the first image meets the visual effect standards.

[0085] Based on the image editing suggestions in the first image review, users can learn how to edit images to meet visual standards.

[0086] Based on the implementation method described above in the first aspect, the editing process of the first image can be explained through the image editing suggestions in the image commentary, thereby helping users understand the specific methods of image editing and improving the user experience of image processing.

[0087] Furthermore, in one implementation of the first aspect, a poster effect is added to the second image generated by editing.

[0088] Specifically, in one implementation of the first aspect, after displaying the second image, the method further includes:

[0089] Display at least one second image commentary, and display a third image, wherein:

[0090] The second image review is based on the visual effect standards corresponding to the visual effect attributes, and is derived from the analysis of the second image.

[0091] The second image review includes information describing whether the second image meets and / or does not meet visual effect standards;

[0092] The third image is an image obtained by synthesizing the second image and all or part of the second image comments in at least one second image commentary.

[0093] Based on the above implementation method of the first aspect, image comments can be added to the edited image to provide users with a poster-like image, which expands the editing function of the image editor, improves the editing effect of the image editor, and enhances the user experience of the image editor.

[0094] Furthermore, in order to display at least one second image commentary, in one implementation of the first aspect:

[0095] Using the visual effect attributes of the fourth quantity as the analysis object, analyze the second image and generate the commentary of the second image in the fifth quantity;

[0096] The commentary on the second image shows the fifth number.

[0097] Specifically, in one implementation of the first aspect, the fourth number of visual effect attributes is the third number of visual effect attributes.

[0098] Since the third set of visual effect attributes are those used for editing, and the purpose of image editing is to generate a second image that meets the visual effect criteria, the second image meets the corresponding visual effect criteria for each of the fourth set of visual effect attributes. In other words, each of the fifth set of second image comments describes how the second image meets the visual effect criteria.

[0099] Based on the above implementation method of the first aspect, a positive review describing the second image as meeting the visual effect standard is generated, thereby enabling the final poster effect to be positively evaluated and improving the user experience of the poster effect.

[0100] Furthermore, in order to display the third image, in one implementation of the first aspect:

[0101] Determine the sixth number of second image comments, where the sixth number of second image comments is all or part of the fifth number of second image comments;

[0102] Combine the sixth image with the second image to generate the third image.

[0103] Specifically, in one implementation of the first aspect, the electronic device determines a sixth number of second image comments based on a user instruction. For example, the electronic device receives a fourth selection instruction from the user, which points to a sixth number of second image comments; the electronic device determines the sixth number of second image comments based on the fourth selection instruction.

[0104] Based on the above implementation method of the first aspect, the image comments included in the poster effect are determined based on user instructions. The poster effect can be realized according to user needs, increasing the freedom of the poster effect, making the poster effect more in line with user needs, and improving the user experience of the poster effect.

[0105] Secondly, based on the method in the first aspect, this application also provides an image processing method for use in electronic devices.

[0106] Specifically, image processing methods include:

[0107] Display at least one third image commentary, and display a fifth image, wherein:

[0108] The third image commentary is based on the visual effect standards corresponding to the visual effect attributes, and analyzes the fourth image accordingly;

[0109] The third image review includes information describing whether the fourth image meets and / or does not meet the visual effect criteria;

[0110] The fifth image is an image obtained by combining the fourth image and all or part of the third image comments in at least one third image commentary.

[0111] The second method can add poster effects to images, expand the editing functions of image editing, improve the editing effect of image editing, and enhance the user experience of image editing.

[0112] Thirdly, based on the method of the first aspect, this application also provides an image processing apparatus for implementing the image processing method of the first aspect.

[0113] Specifically, in one implementation of the third aspect, the image processing device includes a display module, which is used for:

[0114] Display at least one first image commentary, where:

[0115] The first image review is based on the visual effect standards corresponding to the visual effect attributes, and is derived from the analysis of the first image.

[0116] One first-image comment corresponds to one visual effect attribute;

[0117] The first image review includes information describing how the first image does not meet the corresponding visual standards.

[0118] In one implementation of the third aspect, the display module is also used for:

[0119] The second image is shown, in which:

[0120] The second image is generated by editing the first image, using all or part of the visual effect attributes corresponding to at least one of the first image comments as the editing object;

[0121] Regarding the visual effect attributes of the object being edited, the second image meets the corresponding visual effect standards.

[0122] Furthermore, in one implementation of the third aspect, the image processing apparatus further includes an image analysis module, which is used for:

[0123] Using the first set of visual effect attributes as the analysis object, analyze the first image and generate a second set of comments on the first image.

[0124] The display module of the image processing device displays a second number of comments on the first image to the user.

[0125] Specifically, in the second number of first image comments generated by the image analysis module, each first image comment corresponds to one visual effect attribute in the first number of visual effect attributes.

[0126] Since the first image commentary is used to describe visual effect criteria that the first image does not meet, and if the first image meets the visual effect criteria, a first image commentary is not generated for visual effect attributes that meet the visual effect criteria. Therefore, in one implementation of the third aspect, the second quantity is less than or equal to the first quantity.

[0127] In one implementation of the third aspect, the image analysis module is used to analyze a first number of visual effect attributes of the first image, and the image analysis module can analyze all visual effect attributes.

[0128] In another implementation of the first aspect, the image analysis module is used to analyze a first number of visual effect attributes of the first image, and the image analysis module can analyze a portion of all visual effect attributes.

[0129] In another implementation of the first aspect, the image analysis module determines the visual effect attributes to be analyzed based on user instructions, thereby matching the analysis results with user needs and improving user experience.

[0130] Specifically, the image analysis module receives a first selection instruction, which is used to point to a first number of visual effect attributes;

[0131] Based on the first selection instruction, the image analysis module determines a first number of visual effect attributes from all visual effect attributes that can be analyzed.

[0132] To achieve the generation of a second number of first image comments, in one implementation of the third aspect, the image analysis module is configured as follows:

[0133] Taking a first number of visual effect attributes as the analysis object, analyze the first image and obtain the first analysis result. The first analysis result includes whether the first image meets or does not meet the corresponding visual effect standard for any one of the first number of visual effect attributes.

[0134] Based on the results of the first analysis, a second number of first image comments are generated.

[0135] Furthermore, in order to obtain accurate first analysis results, in one implementation of the third aspect, the image analysis module is configured as follows:

[0136] Perform intent recognition on the first image to obtain the image's intended meaning;

[0137] Based on the image's intended meaning, invoke the visual effect standards corresponding to the first number of visual effect attributes;

[0138] Using the first number of visual effect attributes as the analysis object, and based on the visual effect standards corresponding to the first number of visual effect attributes, the first image is analyzed to obtain the first analysis result.

[0139] Furthermore, in order to accurately identify the expressive intent of the image, in one implementation of the third aspect, the image analysis module provides an image intent input interface, which is used to obtain the intent information input by the user, and the intent information is used to describe the expressive purpose of the first image.

[0140] Specifically, in one implementation of the third aspect, the image analysis module is configured as follows:

[0141] Receive intent information from user input;

[0142] Performing intent recognition on the first image to obtain the image's expressive intent includes performing intent recognition on the first image based on intent information to obtain the image's expressive intent.

[0143] To enable the display of the second image, in one implementation of the third aspect, the image processing device further includes an image editing module, which is used for:

[0144] Determine a third number of visual effect attributes, wherein the third number of visual effect attributes includes all or part of the visual effect attributes corresponding to the second number of first image comments;

[0145] Using the third visual effect attribute as the editing object, edit the first image to generate the second image.

[0146] Specifically, in one implementation of the third aspect, the image editing module edits the third number of visual effect attributes of the first image to be all the visual effect attributes corresponding to the second number of comments on the first image.

[0147] Specifically, in another implementation of the third aspect, the image editing module edits the third number of visual effect attributes of the first image to be part of the visual effect attributes corresponding to the second number of comments on the first image.

[0148] Specifically, in another implementation of the third aspect, the third number of visual effect attributes targeted by the image editing module for editing the first image also includes other visual effect attributes besides those corresponding to the visual effect attributes of the second number of first image comments.

[0149] Specifically, in one implementation of the third aspect, the image editing module determines the visual effect attributes of the object to be edited based on user instructions. Specifically, the image editing module is configured as follows:

[0150] Receive the user's second selection instruction, which is used to point to a third number of visual effect attributes;

[0151] Based on the second selection instruction, determine the third number of visual effect attributes.

[0152] Furthermore, in one implementation of the third aspect, the image analysis module performs image analysis based on a neural network model, and / or the image editing module performs image editing based on a neural network model.

[0153] In one implementation of the third aspect, image analysis and editing are achieved based on two neural network models.

[0154] Specifically, in one implementation of the third aspect:

[0155] The image analysis module takes the first image as input to the first neural network model and obtains at least one comment on the first image output by the first neural network model.

[0156] The image editing module inputs the first image and the second selection instruction into the second neural network model, and obtains the second image output by the second neural network model.

[0157] In another implementation of the third aspect, the analysis and editing of images are based on a neural network model.

[0158] Specifically, in one implementation of the third aspect:

[0159] The image analysis module takes the first image as input to the third neural network model and obtains at least one comment on the first image output by the third neural network model.

[0160] The image editing module inputs the second selection command to the third neural network model and obtains the second image output by the third neural network model.

[0161] Furthermore, in one implementation of the third aspect, the first image commentary output by the image analysis module also includes explanatory information, which describes why the first image does not meet the visual effect standards.

[0162] Based on the explanatory information in the first image review, users can learn detailed information about why an image does not meet the visual effect standards, such as which part of the image does not meet the visual effect standards and why.

[0163] Furthermore, in one implementation of the third aspect, the first image review output by the image analysis module also includes image editing suggestions. The image editing suggestions describe the operation process of editing the image, and the operation process of editing the image is used to edit the first image so that the first image meets the visual effect standards.

[0164] Based on the image editing suggestions in the first image review, users can learn how to edit images to meet visual standards.

[0165] Furthermore, in one implementation of the third aspect, the image processing device also adds a poster effect to the edited second image.

[0166] Specifically, in one implementation of the third aspect, the display module is also used for:

[0167] Display at least one second image commentary, and display a third image, wherein:

[0168] The second image review is based on the visual effect standards corresponding to the visual effect attributes, and is derived from the analysis of the second image.

[0169] The second image review includes information describing whether the second image meets and / or does not meet visual effect standards;

[0170] The third image is an image obtained by synthesizing the second image and all or part of the second image comments in at least one second image commentary.

[0171] Furthermore, in order to display at least one second image commentary, in one implementation of the third aspect, the image analysis module is also configured as follows:

[0172] Using the visual effect attributes of the fourth quantity as the analysis object, analyze the second image and generate the commentary of the second image in the fifth quantity;

[0173] The display module is used to display the commentary on the fifth image.

[0174] Specifically, in one implementation of the third aspect, the fourth number of visual effect attributes is the third number of visual effect attributes.

[0175] Furthermore, in order to display the third image, in one implementation of the third aspect, the image editing module is also configured as follows:

[0176] Determine the sixth number of second image comments, where the sixth number of second image comments is all or part of the fifth number of second image comments;

[0177] Combine the sixth image with the second image to generate the third image.

[0178] Fourthly, based on the method of the second aspect, this application also provides an image processing apparatus for implementing the image processing method of the second aspect.

[0179] Specifically, the image processing device includes a display module, which is used for:

[0180] Display at least one third image commentary, and display a fifth image, wherein:

[0181] The third image commentary is based on the visual effect standards corresponding to the visual effect attributes, and analyzes the fourth image accordingly;

[0182] The third image review includes information describing whether the fourth image meets and / or does not meet the visual effect criteria;

[0183] The fifth image is an image obtained by combining the fourth image and all or part of the third image commentary in at least one third image commentary.

[0184] Fifthly, embodiments of this application also provide an electronic device for implementing the apparatus of the third or fourth aspect of this application.

[0185] Specifically, in one implementation of the fifth aspect, the electronic device includes a memory and a processor;

[0186] The processor is used to execute instructions stored in memory to cause the electronic device to perform the method described in the first or second aspect.

[0187] In a sixth aspect, embodiments of this application also provide an electronic device cluster, which includes at least one electronic device, wherein the at least one electronic device in the electronic device cluster is used to implement the means of the third or fourth aspect of this application.

[0188] Specifically, in one implementation of the sixth aspect, the electronic device cluster includes at least one electronic device, each electronic device including a memory and a processor;

[0189] A processor of at least one electronic device is used to execute instructions stored in the memory of at least one electronic device to cause a cluster of electronic devices to perform the method of the first aspect or the second aspect.

[0190] In a seventh aspect, embodiments of this application also provide a computer program product containing instructions that, when executed by an electronic device system, cause the electronic device cluster to perform the method as described in the first or second aspect.

[0191] Eighthly, embodiments of this application also provide a computer-readable storage medium including computer program instructions, which, when executed by a computer system, enable the computer system to perform the method as described in the first or second aspect. Attached Figure Description

[0192] Figure 1 is a flowchart of a method according to an embodiment of this application;

[0193] Figure 2 is a schematic diagram of an image processing apparatus according to an embodiment of this application;

[0194] Figure 3 is a flowchart of a method according to an embodiment of this application;

[0195] Figure 4 is a schematic diagram of a neural network model according to an embodiment of this application;

[0196] Figure 5 is a schematic diagram of a module according to an embodiment of this application;

[0197] Figure 6 is a schematic diagram of modules according to an embodiment of this application;

[0198] Figure 7 is a schematic diagram of modules according to an embodiment of this application;

[0199] Figure 8 is a schematic diagram of modules according to an embodiment of this application;

[0200] Figure 9 is a schematic diagram of a module according to an embodiment of this application;

[0201] Figure 10 is a schematic diagram of modules according to an embodiment of this application;

[0202] Figure 11 is a schematic diagram of modules according to an embodiment of this application;

[0203] Figure 12 is a flowchart of a method according to an embodiment of this application;

[0204] Figure 13 is a flowchart of a method according to an embodiment of this application;

[0205] Figure 14 is a flowchart of a method according to an embodiment of this application;

[0206] Figure 15 is a flowchart of a method according to an embodiment of this application;

[0207] Figure 16 is a flowchart of a method according to an embodiment of this application;

[0208] Figure 17 is a schematic diagram of a mobile phone screen display interface according to an embodiment of this application;

[0209] Figure 18 is a schematic diagram of a mobile phone screen display interface according to an embodiment of this application;

[0210] Figure 19 is a schematic diagram of an electronic device structure according to an embodiment of this application;

[0211] Figure 20 is a schematic diagram of an electronic device cluster according to an embodiment of this application;

[0212] Figure 21 is a schematic diagram of an electronic device cluster network connection according to an embodiment of this application. Detailed Implementation

[0213] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0214] The terminology used in the implementation section of this application is for the purpose of explaining specific embodiments of this application only, and is not intended to limit this application.

[0215] To simplify the image editing process and improve its effectiveness, a feasible solution is to pre-design corresponding image editing schemes for different image content / types. When image editing is needed, the appropriate scheme is applied to the image. This eliminates the need for users to manually navigate the image editing process, simplifying the operation and reducing the complexity of image editing.

[0216] While the aforementioned image editing methods enable simple and quick image editing, pre-designed image editing schemes are typically automatically generated based on one or more manually defined strategies or rules. For example, filter schemes often establish a fixed relationship between scene categories and filter categories, such as food versus vibrant filters. This results in rigid, unadaptable effects that fail to achieve the desired visual impact. Furthermore, pre-designed image editing schemes often fail to align with user aesthetics and are not readily understood by users. They cannot explain why a particular effect is aesthetically pleasing, leaving users with only the option to accept or reject it. Consequently, the final image editing result may not meet user needs.

[0217] To address the aforementioned problems, this application provides an image processing method. The method provided in this application is applied to electronic devices.

[0218] In this application, no specific limitations are placed on the electronic device used to execute the method provided in this application. Those skilled in the art can select a suitable electronic device to execute the method flow provided in this application according to actual needs.

[0219] For example, in one embodiment, the electronic device performing the method provided in the embodiments of this application includes, but is not limited to:

[0220] Any terminal device that can interact with users through images, such as mobile phones, tablets, laptops, desktops, augmented reality (AR) devices, and virtual reality (VR) devices.

[0221] Figure 1 is a flowchart of a method according to an embodiment of this application.

[0222] The electronic device executes the method flow shown in Figure 1 to process the image.

[0223] S110, the electronic device displays at least one first image commentary, wherein:

[0224] The first image review is based on the visual effect standards corresponding to the visual effect attributes, and is derived from the analysis of the first image.

[0225] In at least one first image commentary, each first image commentary corresponds to a visual effect attribute;

[0226] In at least one first image commentary, each first image commentary includes information describing that the first image does not meet the corresponding visual effect criteria.

[0227] In the embodiments of this application, the visual effect attribute refers to a dimension that can be analyzed independently when analyzing the visual effect and / or aesthetic features of an image.

[0228] In this embodiment, no specific limitations are placed on the visual effect attributes that the electronic device can perform image analysis. Those skilled in the art can configure the visual effect attributes that the electronic device can perform analysis according to the needs of actual application scenarios.

[0229] Specifically, in one embodiment, the electronic device can be configured to perform analysis of visual effect attributes based on the currently achievable beautification dimensions, with each beautification dimension corresponding to a visual effect attribute.

[0230] For example, the visual effect of an image can be evaluated from five aesthetic dimensions: texture, composition, lighting, style, and blur, and the image can be edited based on these five dimensions. Therefore, in one embodiment, configuring an electronic device can enable the analysis of visual effect attributes including, but not limited to, any one or a combination of texture, composition, lighting, style, and blur.

[0231] In this embodiment of the application, the visual effect standard corresponding to a certain visual effect attribute is used to describe the standard that an image needs to achieve to satisfy a preset aesthetic effect for that visual effect attribute. That is, for a certain visual effect attribute, when an image meets the corresponding visual effect standard, the visual effect of the image for that visual effect attribute can achieve the expected aesthetic effect.

[0232] For each visual effect attribute, there are one or more sets of visual effect standards, and each set of visual effect standards contains one or more visual effect standards. Different sets of visual effect standards correspond to different image types.

[0233] For example, regarding composition, there can be a set of visual effect standards for corresponding portrait photos. For example, the set of visual effect standards for corresponding portrait photos includes the standard for the position of the face image in the picture and the standard for the proportion of the body image in the picture.

[0234] For example, regarding composition, there can be a set of visual effect standards for corresponding landscape photos. For instance, the set of visual effect standards for corresponding landscape photos includes the standard for the proportion of the sky image in the picture, and the standard for the proportion relationship between the sky / mountains / trees in the picture.

[0235] In this embodiment of the application, no specific restrictions are placed on the visual effect standards corresponding to the visual effect attributes.

[0236] For example, in one embodiment, those skilled in the art can pre-design visual effect standards corresponding to visual effect attributes according to the actual needs of the application scenario, and uniformly apply the designed visual effect standards to multiple electronic devices.

[0237] For example, in another embodiment, before the electronic device implements the method of the present application embodiment, the user of the electronic device can also set the visual effect standard used by the current electronic device according to their own needs.

[0238] Furthermore, in one embodiment, the corresponding visual effect standard can be input for each visual effect attribute via data input.

[0239] For example, since the visual effects and aesthetic features of an image can be analyzed from the perspective of composition, composition can be considered a visual effect attribute of an image.

[0240] Composition is treated as a visual effect attribute, and compositional features that meet aesthetic requirements are defined as the visual effect standards corresponding to the visual effect attribute (composition). For example, the visual effect standards corresponding to composition can be set as follows: the main subject is located in a prominent position in the frame; the main subject occupies a larger proportion of the frame than background objects; the proportion of open background such as the sky in the frame should not exceed that of the main subject, etc.

[0241] For example, since the visual effects and aesthetic features of an image can be analyzed from the perspective of light and shadow, light and shadow can be considered a visual effect attribute of an image.

[0242] Light and shadow are treated as a visual effect attribute, and the characteristics of light and shadow that meet aesthetic requirements are set as the visual effect standards corresponding to the visual effect attribute (light and shadow). For example, the visual effect standards corresponding to light and shadow can be set as follows: the light and shadow effects of the main subject and the background need to be different in order to distinguish the main subject from the background; under the premise that there are no special requirements for light and shadow effects, the light and shadow effects on the face of the main subject should not obscure the facial features, etc.

[0243] Furthermore, in another embodiment, the same visual effect attribute of multiple images that meet the visual effect requirements is summarized to obtain a visual effect standard for that visual effect attribute.

[0244] For example, by using multiple images whose compositions meet visual effect requirements as sample data, and summarizing the common characteristics of the compositions of these images, the following visual effect standards for the corresponding compositions can be obtained:

[0245] For portrait images that do not contain key background features, the portrait occupies 50% to 70% of the entire image, and the head of the portrait is located in the center of the image;

[0246] For portrait images that do not contain key background features, ensure that key background features are included, and that the portrait occupies 20% to 50% of the entire image;

[0247] For images containing sky and other backgrounds, where the sky background does not contain key background features and the other backgrounds do contain key background features, the proportion of the sky background is less than 20% of the image.

[0248] ......

[0249] In one embodiment, in S110, analyzing the first image based on the visual effect standard corresponding to the visual effect attribute means comparing the visual effect of the first image on a certain visual effect attribute with the visual effect standard corresponding to that visual effect attribute to obtain an analysis result. This analysis result includes at least whether the visual effect of the first image on a certain visual effect attribute satisfies or does not satisfy a certain visual effect standard corresponding to that visual effect attribute.

[0250] In one embodiment, in S110, at least one first image commentary corresponds to different visual effect attributes. The first image commentary includes information describing that the first image does not meet the corresponding visual effect criteria. That is, when the visual effect of the first image on a certain visual effect attribute does not meet one or more visual effect criteria corresponding to that visual effect attribute, a first image commentary for that visual effect attribute is generated. Based on this first image commentary, the user can know the visual effect criteria that the first image does not meet.

[0251] This application does not limit the specific content of the first image commentary. In some embodiments, the first image commentary may be a statement directly stating that the first image does not meet the corresponding visual effect standard, such as "chaotic composition" or "unreasonable composition." In other embodiments, the first image commentary may be a statement indirectly implying that the first image does not meet the corresponding visual effect standard, such as "optimize the composition" or "the composition can be optimized." Regardless of how the first image commentary is expressed, based on this commentary, the user can obtain information that the first image does not meet the corresponding visual effect standard.

[0252] It should be noted that for a certain visual effect attribute, there may be multiple visual effect standards. The first image may not meet all the visual effect standards corresponding to that attribute, or may not meet some of the visual effect standards corresponding to that attribute. The first image commentary is used to describe the visual effect standards that the first image does not meet.

[0253] Specifically, in one embodiment, in S110, the electronic device analyzes the first image using a first number of visual effect attributes as the analysis object, and generates a second number of comments on the first image, wherein:

[0254] The visual effect attributes in the first number of visual effect attributes are all different;

[0255] In the second number of first image comments, each first image comment corresponds to one of the visual effect attributes in the first number of visual effect attributes.

[0256] Considering that the first image commentary is used to describe visual effect criteria that the first image does not meet, and that the first image meets the visual effect criteria, a first image commentary is not generated for visual effect attributes that meet the visual effect criteria. Therefore, in one embodiment, the second quantity is less than or equal to the first quantity.

[0257] S111, the electronic device displays a second image, in which:

[0258] The second image is an image generated by editing the first image, using all or part of the visual effect attributes corresponding to at least one of the first image comments as the editing object;

[0259] Regarding the visual effect attributes of the object being edited, the second image meets the corresponding visual effect standards.

[0260] In one embodiment, in S111, the electronic device determines the visual effect attributes of the editing object, which include at least one partial or all visual effect attributes corresponding to the first image commentary.

[0261] The electronic device edits the first image based on the visual effect standard corresponding to the visual effect attribute of the edited object, so that the image editing result meets the visual effect standard corresponding to the visual effect attribute of the edited object, thereby obtaining the second image.

[0262] Specifically, in one embodiment, in S111, the electronic device determines a third number of visual effect attributes, wherein the third number of visual effect attributes includes all or part of the visual effect attributes corresponding to the second number of first image comments; the electronic device edits the first image with the third number of visual effect attributes as the editing object.

[0263] According to the method in the embodiments of this application, a self-service analysis of the visual effect attributes of an image can be performed, pointing out to the user the visual effect attributes that do not meet the visual effect standards, thereby helping the user improve their ability to identify the direction of image beautification and expanding the user's knowledge of image aesthetics.

[0264] According to the method in this application embodiment, while describing the image defects of an image to the user, image optimization can be performed on the image defects, thereby reducing the difficulty of image editing, improving the user's ability to identify the direction of image beautification, and enhancing the user experience of image editing.

[0265] Furthermore, embodiments of this application also provide an image processing apparatus for implementing an image processing method. In one embodiment, the image processing apparatus includes at least a display module for displaying at least one first image commentary and a second image.

[0266] Figure 2 is a schematic diagram of an image processing apparatus according to an embodiment of this application.

[0267] In one embodiment, as shown in FIG2, the image processing apparatus 100 includes:

[0268] Image acquisition module 101 is used to acquire the first image.

[0269] Image analysis module 102 is used to analyze a first image based on the visual effect standards corresponding to the visual effect attributes, taking a first number of visual effect attributes as the analysis object, and generate a second number of comments on the first image.

[0270] Image editing module 103 is used for:

[0271] Determine the third number of visual effect attributes (visual effect attributes that need to be edited), wherein the third number of visual effect attributes are some or all of the visual effect attributes corresponding to the second number of first image comments;

[0272] For the third set of visual effect attributes, edit the first image to generate a second image that meets the visual effect standards.

[0273] Display module 104 is used to display the second number of first image comments generated by image analysis module 102 and the second image generated by image editing module 103 to the user.

[0274] Figure 3 is a flowchart of a method according to an embodiment of this application.

[0275] In one embodiment, the image processing apparatus 100 shown in FIG2 executes the following process shown in FIG3, displaying one or more image comments to the user for the image to be edited, in order to assist the user in editing and beautifying the image to be edited.

[0276] S200, Image Acquisition Module 101 acquires the first image.

[0277] Specifically, in one embodiment, in S200, the first image acquired by the image acquisition module 101 is an image stored locally or online.

[0278] For example, a user opens their local photo library and selects one of the images as the first image.

[0279] For example, a user opens a shared image library in the cloud and selects one of the images as the first image.

[0280] In another embodiment, in S200, the first image acquired by the image acquisition module 101 is the image being captured by the camera.

[0281] For example, when a user opens a camera app, the image captured by the camera is displayed in the viewfinder on the screen. The image acquisition module 101 acquires the image displayed in the viewfinder (the image to be captured) as the first image. At this time, the camera app has not performed a photo-taking operation; the image captured by the camera is merely displayed in the viewfinder and has not been saved locally or to the cloud.

[0282] S201, the image analysis module 102 analyzes the first image based on the visual effect standard corresponding to the visual effect attribute, taking the first number of visual effect attributes as the analysis object, and generates a second number of comments on the first image.

[0283] In S201, in the second number of first image comments, each first image comment corresponds to one visual effect attribute in the first number of visual effect attributes. That is, each first image comment is used to describe a visual effect attribute of the first image that does not meet the visual effect criteria, and each first image comment corresponds to one or more visual effect criteria that the first image does not meet.

[0284] Furthermore, in one embodiment, the first number of visual effect attributes is all visual effect attributes that the image analysis module 102 can analyze.

[0285] For example, the image analysis module 102 is configured to analyze an image based on five visual effect attributes: texture, composition, lighting, style, and blur. In S201, the image analysis module 102 analyzes the first image based on the five visual effect attributes: texture, composition, lighting, style, and blur.

[0286] In another embodiment, the first number of visual effect attributes is a subset of all visual effect attributes that the image analysis module 102 can analyze.

[0287] Specifically, in one embodiment, in S201:

[0288] Image analysis module 102 receives a first selection instruction from the user, which is used to point to a first number of visual effect attributes;

[0289] The image analysis module 102 determines a first number of visual effect attributes from all visual effect attributes that can be analyzed, based on the first selection instruction.

[0290] For example, the image analysis module 102 is configured to analyze an image from five visual effect attributes: texture, composition, lighting, style, and blur. In S201, the image analysis module 102 receives a first selection instruction from the user, which is used to select three visual effect attributes: texture, composition, and lighting. Based on the first selection instruction, the image analysis module 102 analyzes the first image for each of the three visual effect attributes: texture, composition, and lighting (the first selection is three).

[0291] Furthermore, in one embodiment, in S201:

[0292] The image analysis module 102 takes a first number of visual effect attributes as the analysis object, analyzes the first image, obtains a first analysis result, and generates a second number of first image comments based on the first analysis result. The first analysis result includes whether the first image meets or does not meet the corresponding visual effect standard for any one of the first number of visual effect attributes.

[0293] The image analysis module 102 generates a second number of first image comments based on the first analysis results.

[0294] Specifically, for any one of the first number of visual effect attributes, the image analysis module 102 analyzes it based on the visual effect standard corresponding to that attribute to determine whether the first image meets the visual effect standard. When the first image does not meet the visual effect standard, a commentary on the first image corresponding to that visual effect attribute is generated; when the first image meets the visual effect standard, no commentary is generated for that visual effect attribute.

[0295] For example, the first number of visual effect attributes includes at least the first visual effect attribute, and the visual effect standard corresponding to the first visual effect attribute is the first visual effect standard.

[0296] In S201, the image analysis module 102 analyzes the first image based on the first visual effect standard and the first visual effect attribute. When the first image does not meet the first visual effect standard, the image analysis module 102 generates a first image comment based on the first visual effect attribute. The first image comment is used to describe that the first image does not meet the first visual effect standard.

[0297] After the image analysis module 102 has completed the analysis of the first image for all visual effect attributes of the first number of visual effect attributes, it generates a second number of comments on the first image.

[0298] For example, in S201, the image analysis module 102 analyzes the first image (the first quantity is five) for five visual effect attributes: texture, composition, lighting, style, and blur, and obtains the first analysis result. In the first analysis result, the first image does not meet the visual effect standards of the three visual effect attributes: texture, composition, and lighting. Based on the first analysis results of the three visual effect attributes, the image analysis module 102 generates three corresponding comments for the first image (the second quantity is three).

[0299] According to the method of this application embodiment, based on the first analysis result, a first image commentary corresponding to the visual effect attribute is generated only when the first image does not meet the visual effect standard. Under the premise of ensuring that sufficient image commentary information is provided to the user, the amount of data processing is effectively controlled, the amount of data output to the user is reduced, and the output redundancy is avoided, which may cause user annoyance and improve the user experience.

[0300] Furthermore, in one embodiment, in S201, the first image comment includes first explanatory information, which describes the reason why the first image does not meet the visual effect standard.

[0301] Based on the first explanatory information in the first image commentary, users can learn detailed information about why an image does not meet the visual effect standards, such as which part of the image does not meet the visual effect standards and why.

[0302] For example, in one embodiment, the visual effect standard for the corresponding composition is set as follows:

[0303] For images that do not contain key background features, when the person is the key target of the image, the image of the person occupies 50% to 70% of the entire image, and the head of the person is located in the middle of the image.

[0304] For portrait images that do not contain key background features, ensure that key background features are included, and that the portrait occupies 20% to 50% of the entire image;

[0305] For images containing sky and other backgrounds, where the sky background does not contain key background features but the other backgrounds do contain key background features, the proportion of the sky background is less than 20% of the image.

[0306] The first image contains trees, sky, and people, with people being the key subject. Images of people occupy 5% of the first image, sky images occupy 85%, and tree images occupy 10%.

[0307] The first image does not meet the visual effect standards corresponding to the composition. The image analysis module 102 generates a comment on the composition of the first image: the proportion of the human figure in the composition of the first image is too low, and the proportion of the sky image is too high.

[0308] According to one embodiment of the method of this application, the reason why the first image does not meet the visual effect standard can be explained by the explanatory information in the image commentary, thereby accurately expressing the visual effect defects of the image to the user, assisting the user in understanding image enhancement knowledge, and improving the user experience of image processing.

[0309] Furthermore, in one embodiment, in S201, the first image review includes image editing suggestions, which describe the specific operation process for editing the first image, and the operation of editing the first image is used to make the image editing result meet the visual effect standard.

[0310] Based on the image editing suggestions in the first image review, users can learn how to edit images to meet visual standards.

[0311] Specifically, in one embodiment, image editing suggestions are generated based on the first analysis results.

[0312] For example, the comment on the first image: The proportion of the human figure in the composition of the first image is too low and needs to be adjusted to more than 50%; the proportion of the sky is too high and needs to be adjusted to less than 20%.

[0313] According to one embodiment of the method in this application, the process of editing a first image can be explained through image editing suggestions in the image commentary, thereby helping users understand the specific methods of image editing and improving the user experience of image processing.

[0314] Furthermore, for the same image, the desired aesthetic effect will differ depending on the image's expressive objective.

[0315] For example, when framing an image that includes both people and background, if the image's purpose is to depict a person, the composition should emphasize the person in the image; while if the image's purpose is to depict the background, the composition should include the complete background image and highlight the relationship between the person and the background.

[0316] For example, when dealing with images containing human faces, if the goal of the image is to describe facial features, then in terms of lighting, it is necessary to ensure that the face is adequately lit; however, if the goal of the image is to showcase a specific lighting effect, then in terms of lighting, it is necessary to enhance the overall contrast between light and dark in the image.

[0317] In other words, when analyzing the aesthetic effects of an image, even for the same visual effect attribute, different visual effect standards are required when expressing different goals.

[0318] Therefore, in order to obtain accurate first analysis results, in one embodiment:

[0319] Image analysis module 102 performs intent recognition on the first image to obtain the image expression intent of the first image;

[0320] Based on the image expression intent of the first image, the image analysis module 102 calls the visual effect standard corresponding to the first number of visual effect attributes of the first image;

[0321] The image analysis module 102 takes the first number of visual effect attributes as the analysis object, analyzes the first image based on the visual effect standard corresponding to the first number of visual effect attributes called previously, and obtains the first analysis result.

[0322] According to the method in the embodiments of this application, the image is subjected to intent recognition to obtain the image's expressive intent. The corresponding visual effect standard is called to analyze the image based on the image's expressive intent, which can improve the accuracy of the image analysis results, thereby generating more accurate image comments in the future and improving the user experience.

[0323] Furthermore, in one embodiment, in order to accurately identify the expressive intent of the image, the image analysis module 102 also provides an image intent input interface, which is used to obtain the intent information input by the user, and the intent information is used to describe the expressive purpose of the first image.

[0324] Specifically, in one embodiment:

[0325] The image analysis module 102 receives the intent information input by the user;

[0326] The image analysis module 102 performs intent recognition on the first image based on the intent information input by the user, and obtains the image expression intent of the first image.

[0327] For example, the first image contains trees, sky, and people, with people being the key subject. Images of people occupy 5% of the first image, images of the sky occupy 85%, and images of trees occupy 10%.

[0328] If the user inputs the intent: "Describe a person under an open sky," the image analysis module 102 identifies the image's intended meaning as "emphasizing the sky background." Based on this intent, the module analyzes the composition according to the corresponding visual effect standards. If the first image meets the visual effect standards in terms of composition, no comment is generated for the first image.

[0329] If the user inputs the intent information: "Describe a person", the image analysis module 102 identifies the image's intended meaning as "emphasizing the description of a person" based on this intent information. Based on this intended meaning, the module analyzes the composition according to the corresponding visual effect standards and finds that the first image does not meet the visual effect standards in terms of composition. Therefore, a comment is generated on the composition of the first image: the proportion of the person image in the composition of the first image is too low, and the proportion of the sky image is too high.

[0330] According to the method of this application embodiment, obtaining user-input intent information and recognizing the image expression intent of the first image based on the user-input intent information can improve the recognition accuracy of image expression intent, thereby enabling the acquisition of accurate first analysis results in the subsequent process.

[0331] Furthermore, in one embodiment, the image analysis module 102 is implemented based on a neural network model (e.g., a multimodal large language model).

[0332] For example, text and image notes, various photography books, and various video tutorials can be processed into aesthetic knowledge. This aesthetic knowledge includes image feature descriptions of images that meet the visual aesthetic requirements of different application scenarios. Based on this aesthetic knowledge, visual effect attributes corresponding to visual aesthetic requirements can be summarized, as well as visual effect standards corresponding to the requirements of different application scenarios.

[0333] A neural network model is trained using aesthetic knowledge as training sample data, enabling it to analyze visual effect attributes and identify visual effect problems in images.

[0334] For example, training a neural network model to analyze images and obtain objective descriptions (tokens) of the images:

[0335] 1) Character description;

[0336] 2) Environmental description;

[0337] ...

[0338] Aesthetic questions (tokens) are derived from objective descriptions of the images:

[0339] 1) The character's skin tone is too dark;

[0340] 2) The composition is too crowded;

[0341] ...

[0342] Provide aesthetic advice (tokens) for aesthetic issues:

[0343] 1) Reduce highlights and enhance shadows;

[0344] 2) Secondary cutting;

[0345] ...

[0346] The aesthetic problems and suggestions obtained from the neural network model are processed to generate the first image commentary.

[0347] In one embodiment, in S201, the image analysis module 102 calls the trained multimodal neural network model (first neural network model), takes the first image as input, inputs it into the first neural network model, and obtains the second number of first image comments output by the first neural network model.

[0348] Figure 4 is a schematic diagram of a neural network model according to an embodiment of this application.

[0349] As shown in Figure 4, in one embodiment, the input of the neural network model 301 is an image 302 (e.g., a first image), and the output is a first image comment 303 (e.g., a second number of first image comments) for the input image.

[0350] In another embodiment, the input to the neural network model 301 further includes a first selection instruction 304.

[0351] In another embodiment, the input to the neural network model 301 also includes intent information 305.

[0352] S202, the display module 104 displays the second number of first image comments generated by the image analysis module 102 to the user.

[0353] Furthermore, in one embodiment:

[0354] In S201, the image analysis module 102 also generates a fourth image commentary, which is the tenth number, based on the first analysis result;

[0355] In S202, the display module 104 displays the commentary on the tenth fourth image generated by the image analysis module 102 to the user.

[0356] Specifically, the fourth image commentary describes the visual effect attributes in the first image that meet the visual effect criteria. Furthermore, in the tenth number of fourth image comments, each fourth image commentary corresponds to one of the visual effect attributes in the first number of visual effect attributes. That is, each fourth image commentary describes a visual effect attribute of the first image that meets the visual effect criteria, and each fourth image commentary corresponds to one or more visual effect criteria that the first image meets.

[0357] Furthermore, in one embodiment, in S201, the fourth image commentary includes second explanatory information, which describes why the first image meets the visual effect criteria.

[0358] S203, the image editing module 103 determines a third number of visual effect attributes (visual effect attributes to be edited), wherein the third number of visual effect attributes includes all or part of the visual effect attributes corresponding to the second number of first image comments.

[0359] Optionally, in one embodiment, all visual effect attributes corresponding to the second number of first image comments are the third number of visual effect attributes.

[0360] In S203, the image editing module 103 determines a third number of visual effect attributes based on the visual effect attributes corresponding to the second number of first image comments generated by the image analysis module 102.

[0361] Specifically, the second number of first image comments generated by the image analysis module 102 correspond to a second number of visual effect attributes. The image editing module 103 uses the second number of visual effect attributes corresponding to the second number of first image comments as the third number of visual effect attributes.

[0362] For example, in S201, the image analysis module 102 analyzes the first image for five visual effect attributes: texture, composition, lighting, style, and blur, and obtains the first analysis result. In the first analysis result, the first image does not meet the visual effect standards for the three visual effect attributes of texture, composition, and lighting. The image analysis module 102 generates three comments on the first image for the three visual effect attributes of texture, composition, and lighting, respectively.

[0363] In S203, the image editing module 103 determines, based on the three first image reviews generated by the image analysis module 102, that the first image needs to be edited for three visual effect attributes: texture, composition, and lighting.

[0364] According to the method of this application embodiment, all visual effect attributes corresponding to the first image review are used as the editing object to edit the image. This can edit the parts of the first image that do not meet the visual effect standards presented to the user through the first image review to meet the visual effect standards, thereby realizing the process of automatically raising and automatically solving aesthetic problems, reducing the difficulty of image editing, and improving the user experience of image editing.

[0365] In one embodiment, the image analysis module 102 outputs a second number of first image comments to the image editing module 103, and the image editing module 103 determines the visual effect attributes corresponding to the second number of first image comments based on the second number of first image comments.

[0366] In another embodiment, the image analysis module 102 outputs notification information to the image editing module 103, which describes the visual effect attributes corresponding to the second number of first image comments.

[0367] Furthermore, in another embodiment, in S203, the image editing module 103 obtains the first analysis result obtained by the image analysis module 102 in S201, determines the visual effect attributes corresponding to the second number of first image comments generated by the image analysis module 102 based on the obtained first analysis result, and further determines a third number of visual effect attributes based on the visual effect attributes corresponding to the second number of first image comments generated by the image analysis module 102.

[0368] Specifically, the first analysis result includes whether the first image meets the visual effect standard and / or whether the first image does not meet the visual effect standard. Based on the portion of the first image that does not meet the visual effect standard in the first analysis result, the image editing module 103 determines the visual effect attributes corresponding to the second number of first image comments generated by the image analysis module 102.

[0369] Optionally, in one embodiment, in S201, the image analysis module 102 outputs the first analysis result obtained to the image editing module 103.

[0370] Optionally, in another embodiment, the image editing module 103 executes the steps performed by the image analysis module 102 (refer to S201), analyzes the first image based on the visual effect standards corresponding to the visual effect attributes, takes a first number of visual effect attributes as the analysis object, and obtains a first analysis result.

[0371] Optionally, in another embodiment, the third number of visual effect attributes is a subset of all visual effect attributes corresponding to the second number of first image comments.

[0372] Specifically, the third number of visual effect attributes is a portion of the user-specified visual effect attributes corresponding to the second number of first image comments; or, the third number of visual effect attributes is a portion of the preset editable objects among all the visual effect attributes corresponding to the second number of first image comments.

[0373] For example, in S201, the image analysis module 102 analyzes the first image for five visual effect attributes: texture, composition, lighting, style, and blur, and obtains the first analysis result. In the first analysis result, the first image does not meet the visual effect standards for the three visual effect attributes of texture, composition, and lighting. The image analysis module 102 generates three comments on the first image for the three visual effect attributes of texture, composition, and lighting, respectively.

[0374] Image editing module 103 is preset to allow editing of three visual effect attributes: composition, lighting, and style.

[0375] In S203, the image editing module 103 determines that among the three visual effect attributes of texture, composition, and lighting corresponding to the three first image comments, the composition and lighting attributes can be used as editing objects. Therefore, in S203, the image editing module 103 determines that the first image needs to be edited based on the texture and composition visual effect attributes.

[0376] According to the method of this application embodiment, the image is edited by taking the visual effect attributes corresponding to the first image review as the editing object. This can specifically edit a portion of the first image that does not meet the visual effect standards to meet them. Based on the process of automatically raising and solving aesthetic problems, this method improves the targeting of image editing, enhances the freedom of image editing, and improves the user experience of image editing.

[0377] Optionally, in another embodiment, the third number of visual effect attributes includes not only all or part of the visual effect attributes corresponding to the second number of first image comments, but also other visual effect attributes besides those corresponding to the second number of first image comments.

[0378] For example, in S201, the image analysis module 102 analyzes the first image for three visual effect attributes: composition, lighting, and blur, and obtains a first analysis result. In the first analysis result, the first image does not meet the visual effect standards for the composition and lighting attributes. The image analysis module 102 generates two comments on the first image for the composition and lighting attributes, respectively.

[0379] The user-preset image editing module 103 requires optimization of image texture during image editing.

[0380] In S203, the image editing module 103 identifies the composition and lighting attributes corresponding to the two first image comments as editing objects, and also identifies the user-preset texture that must be optimized as an editing object. Therefore, in S203, the image editing module 103 determines that the first image needs to be edited based on the three visual effect attributes of texture, composition, and lighting.

[0381] According to the method of this application embodiment, visual effect attributes other than those corresponding to the visual effect attributes of the first image comment are used as editing objects to edit the image, which can improve the editing effect of image editing, enhance the freedom of image editing, and improve the user experience of image editing.

[0382] Optionally, in another embodiment, the user inputs a second selection instruction, which is used to point to a third number of visual effect attributes.

[0383] Furthermore, in one embodiment, the third number of visual effect attributes pointed to by the second selection instruction is all or part of the visual effect attributes corresponding to the second number of first image comments.

[0384] In another embodiment, the third number of visual effect attributes pointed to by the second selection instruction includes not only all or part of the visual effect attributes corresponding to the second number of first image comments, but also other visual effect attributes besides those corresponding to the second number of first image comments.

[0385] According to the method of this application embodiment, the visual effect attributes of the editing object are determined based on user instructions. This allows for image editing according to user needs, increasing the freedom of image editing, making the image editing results more in line with user needs, and improving the user experience of image editing.

[0386] Optionally, in one embodiment, in S203:

[0387] Image editing module 103 receives a second selection instruction from the user, which is used to point to a third number of visual effect attributes;

[0388] The image editing module 103 determines a third number of visual effect attributes based on the user's second selection instruction.

[0389] For example, in S201, the image analysis module 102 analyzes the first image for five visual effect attributes: texture, composition, lighting, style, and blur, and obtains the first analysis result. In the first analysis result, the first image does not meet the visual effect standards for the three visual effect attributes of texture, composition, and lighting. The image analysis module 102 generates three comments on the first image for the three visual effect attributes of texture, composition, and lighting, respectively.

[0390] In S203, the image editing module 103 receives a second selection instruction from the user, which points to two visual effect attributes: texture and composition. In S203, the image editing module 103 determines that the first image needs to be edited based on the two visual effect attributes of texture and composition.

[0391] For example, the image analysis module 102 is designed to analyze images based on five visual effect attributes: texture, composition, lighting, style, and blur. In S201, the image analysis module 102 receives a first selection instruction, which points to three visual effect attributes: texture, composition, and lighting. Based on the first selection instruction, the image analysis module 102 analyzes the first image for each of the three visual effect attributes (texture, composition, and lighting) and obtains a first analysis result. In the first analysis result, the first image does not meet the visual effect standards for the composition and lighting attributes. The image analysis module 102 then generates two reviews of the first image, one for the composition and one for the lighting attributes.

[0392] In S203, the image editing module 103 receives a second selection instruction from the user, which points to two visual effect attributes: style and composition. In S203, the image editing module 103 determines a third set of visual effect attributes as the style and composition attributes.

[0393] Optionally, in another embodiment:

[0394] The image analysis module 102 determines a third number of visual effect attributes based on the user's second selection instruction;

[0395] Based on the first analysis result obtained in S201, the image analysis module 102 generates corresponding image editing execution parameters for the third number of visual effect attributes. The image editing execution parameters correspond to the specific operation process of editing the first image. The operation of editing the first image is used to make the image editing result meet the visual effect standard.

[0396] In S203, the image analysis module 102 outputs the image editing execution parameters to the image editing module 103, and the image editing module 103 determines the third number of visual effect attributes based on the image editing execution parameters.

[0397] S204, the image editing module 103 edits the first image using the third number of visual effect attributes as the editing object, in order to generate a second image that meets the visual effect standards.

[0398] Optionally, in one embodiment, in S204, the image editing module 103 edits the first image based on the visual effect standard corresponding to the visual effect attribute, targeting a third number of visual effect attributes, to generate the second image.

[0399] For example, Figure 5 is a schematic diagram of a module according to an embodiment of this application.

[0400] As shown in Figure 5, the first image 401 is input into the image analysis module 402, and the image analysis module 402 outputs a second number of comments 403 on the first image.

[0401] After the first image comment 403 of the second quantity is displayed to the user, the second selection instruction 405 generated according to the user's selected operation is input to the image editing module 404.

[0402] Image editing module 404 determines a third number of visual effect attributes based on the second selection instruction.

[0403] The first image 401 is input into the image editing module 404.

[0404] Image editing module 404 edits the first image based on the visual effect standard corresponding to the third visual effect attribute for the third number of visual effect attributes, and outputs the second image 406.

[0405] Optionally, in another embodiment, in S202, the first image review output by the image analysis module 102 includes image editing suggestions. The image editing suggestions describe the specific operation process for editing the first image, and these operations are designed to ensure that the image editing result meets visual effect standards.

[0406] In S204:

[0407] The image editing module 103 generates image editing execution parameters for visual effect attributes based on the image editing suggestions output by the image analysis module 102;

[0408] Image editing module 103 executes the corresponding image editing operation according to the image editing execution parameters to edit the first image and generate the second image.

[0409] Optionally, in another embodiment, in S202, in addition to outputting a second number of first image comments, the image analysis module 102 also outputs independent image editing execution parameters. These image editing execution parameters correspond to the specific operation flow for editing the first image, and this operation is used to ensure that the image editing result meets visual effect standards.

[0410] In S204, the image editing module 103 performs the corresponding image editing operation according to the image editing execution parameters output by the image analysis module 102, and edits the first image to generate the second image.

[0411] Optionally, in another embodiment, the image analysis module 102 outputs the first analysis result obtained in S201 to the image editing module 103. This first analysis result includes a comparison of the parameter values ​​of the visual effect attributes of the first image with the numerical values ​​of the corresponding visual effect standards.

[0412] In S204:

[0413] The image editing module 103 generates image editing execution parameters for visual effect attributes based on the first analysis result;

[0414] Image editing module 103 executes the corresponding image editing operation according to the image editing execution parameters to edit the first image and generate the second image.

[0415] Optionally, in another embodiment, the image editing module 103 automatically obtains an analysis result consistent with the first analysis result based on the process in S201. This analysis result includes a comparison of the parameter values ​​of the visual effect attributes of the first image with the corresponding numerical values ​​of the visual effect standards.

[0416] In S204:

[0417] The image editing module 103 generates image editing execution parameters for visual effect attributes based on the analysis results it acquires;

[0418] Image editing module 103 executes the corresponding image editing operation according to the image editing execution parameters to edit the first image and generate the second image.

[0419] For example, Figure 6 is a schematic diagram of a module according to an embodiment of this application.

[0420] As shown in Figure 6, the first image 501 is input into the image analysis module 502, and the image analysis module 502 outputs a second number of comments on the first image 503.

[0421] Image analysis module 502 also outputs image editing execution parameters 505 corresponding to the second number of visual effect attributes to image editing module 504.

[0422] After the first image comment 503 of the second quantity is displayed to the user, the second selection instruction 506 generated according to the user's selected operation is input to the image editing module 504.

[0423] Image editing module 504 determines a third number of visual effect attributes based on second selection instruction 506.

[0424] The first image 501 is input into the image editing module 504.

[0425] The image editing module 504 determines the image editing execution parameters to be executed from the input image editing execution parameters 505 based on the third number of visual effect attributes, edits the first image according to the required image editing execution parameters, and outputs the second image 507.

[0426] For example, Figure 7 is a schematic diagram of a module according to an embodiment of this application.

[0427] As shown in Figure 7, the first image 601 is input into the image analysis module 602, and the image analysis module 602 outputs a second number of comments on the first image 603.

[0428] After the first image comment 603 of the second quantity is displayed to the user, the second selection instruction 606 generated according to the user's selected operation is input to the image analysis module 602.

[0429] Image analysis module 602 determines a third number of visual effect attributes based on second selection instruction 606.

[0430] Image analysis module 602 generates image editing execution parameters 605 for the third number of visual effect attributes, and outputs image editing execution parameters 605 to image editing module 604.

[0431] The first image 601 is input into the image editing module 604.

[0432] The image editing module 604 determines a third number of visual effect attributes based on the image editing execution parameters 605, executes the image editing execution parameters 605 to edit the first image, and outputs the second image 607.

[0433] For example, Figure 8 is a schematic diagram of a module according to an embodiment of this application.

[0434] As shown in Figure 8, the first image 701 is input into the image analysis module 702, the image analysis module 702 generates the first analysis result 703, the image analysis module 702 generates a second number of first image comments 704 based on the first analysis result 703, and the image analysis module 702 outputs the second number of first image comments 704.

[0435] The image analysis module 702 outputs the first analysis result 703 to the image editing module 705.

[0436] After the first image comment 704 of the second quantity is displayed to the user, the second selection instruction 706 generated according to the user's selected operation is input to the image editing module 705.

[0437] The first image 701 is input into the image editing module 705.

[0438] Image editing module 705 determines a third number of visual effect attributes based on the second selection instruction 706.

[0439] The image editing module 705 generates image editing execution parameters based on the first analysis result 703 for the third number of visual effect attributes.

[0440] Image editing module 705 executes image editing parameters, edits the first image, and outputs the second image 707.

[0441] Furthermore, in one embodiment, image editing is performed on one or more visual effect attributes by invoking an image editing tool.

[0442] For example, the image editing module 103 calls the image cropping tool to edit the composition of the first image.

[0443] Furthermore, in one embodiment, image editing for one or more visual effect attributes is achieved by calling a neural network model.

[0444] For example, the image editing module 103 calls the style adjustment model to edit the style of the first image.

[0445] For example, Figure 9 is a schematic diagram of a module according to an embodiment of this application.

[0446] Image 801 is input into image editing module 802, image editing module 802 edits image 801, and generates image 808.

[0447] Image editing module 802 calls image cropping tool 803 to edit the composition of the image.

[0448] Image editing module 802 calls light adjustment tool 804 to edit the light and shadow of the image.

[0449] Image editing module 802 calls texture adjustment model 805 to edit the texture of the image.

[0450] Image editing module 802 calls style adjustment model 806 to edit the style of the image.

[0451] Image editing module 802 calls blur tool 807 to perform blurring editing on the image.

[0452] Furthermore, in one embodiment, the functions of the image analysis module 102 and the image editing module 103 are implemented based on different multimodal neural network models.

[0453] That is, displaying at least one first image comment includes inputting a first image into a first neural network model and obtaining at least one first image comment output by the first neural network model;

[0454] And, displaying the second image includes inputting the first image and the second selection instruction into the second neural network model, and obtaining the second image output by the second neural network model.

[0455] For example, Figure 10 is a schematic diagram of a module according to an embodiment of this application.

[0456] As shown in Figure 10, in one embodiment, the input of the neural network model 901 (first neural network model) is an image 902 (e.g., a first image), and the output is a first image comment 903 (e.g., a second number of first image comments) for the input image.

[0457] The neural network model 906 (the second neural network model) takes image 902 (e.g., the first image) as input and a second selection instruction 907 as output, and outputs image 908 (e.g., the second image).

[0458] In another embodiment, the input to the neural network model 901 further includes a first selection instruction 904.

[0459] In another embodiment, the inputs to neural network model 901 and neural network model 906 also include intent information 905.

[0460] According to the method of this application embodiment, two neural network models are used to realize the analysis and editing of images respectively. The first neural network model and the second neural network model can be independently trained, adjusted and replaced according to actual needs, which improves the freedom and flexibility of the method implementation.

[0461] In some embodiments, displaying a second image includes:

[0462] M first image comments are determined according to the second selection instruction; where M is an integer greater than or equal to 2; the M first image comments include X first type first image comments and Y second type first image comments, where X is an integer greater than or equal to 1 and Y is an integer greater than or equal to 1.

[0463] First editing instructions and second editing instructions are generated based on M first image comments; wherein, the first editing instructions are used to instruct the image editing module to edit the first image based on the visual effect attributes corresponding to the first image and X first image comments of the first type to generate a first intermediate image; the second editing instructions are used to instruct that the first image and Y first image comments of the second type be input into the second neural network model to obtain the second intermediate image output by the second neural network model;

[0464] A first intermediate image is generated based on a first editing instruction, and a second intermediate image is generated based on a second editing instruction;

[0465] A second image is generated based on the first and second intermediate images.

[0466] In some embodiments, displaying a second image includes:

[0467] According to the second selection instruction, M first image comments are determined, where M is an integer greater than or equal to 2; the M first image comments include X first type first image comments and Y second type first image comments, where X is an integer greater than or equal to 1 and Y is an integer greater than or equal to 1.

[0468] A first editing instruction is generated based on M first image comments; wherein, the first editing instruction is used to instruct the image editing module to edit the first image based on the first image and the visual effect attributes corresponding to X first image comments of the first type, so as to generate a first intermediate image;

[0469] Input the first intermediate image and Y second-type first images into the second neural network model, and obtain the second image output by the second neural network model.

[0470] Furthermore, in one embodiment, the functions of the image analysis module 102 and the image editing module 103 are integrated into the same multimodal neural network model.

[0471] That is, displaying at least one comment on the first image includes inputting the first image into the third neural network model and obtaining at least one comment on the first image output by the third neural network model;

[0472] Displaying the second image includes inputting a second selection instruction into the third neural network model and obtaining the second image output by the third neural network model.

[0473] For example, Figure 11 is a schematic diagram of a module according to an embodiment of this application.

[0474] As shown in Figure 11, in one embodiment, the input of the neural network model 1001 (the third neural network model) is an image 1002 (e.g., the first image), and the output is a first image commentary 1003 (e.g., a second number of first image comments) for the input image.

[0475] The input to the neural network model 1001 also includes a second selection instruction 1007, and the output of the neural network model 1001 also includes an image 1008 (e.g., a second image).

[0476] In another embodiment, the input to the neural network model 1001 further includes a first selection instruction 1004.

[0477] In another embodiment, the input to the neural network model 1001 also includes intent information 1005.

[0478] The method according to the embodiments of this application uses a neural network model to perform image analysis and editing, which reduces the processing resource consumption during neural network model training and reduces the difficulty of implementing the method.

[0479] S205, the display module 104 displays the second image to the user.

[0480] Furthermore, in one embodiment, after S111, effects can be added to the edited image (second image), such as adding frames, puzzles, text bubbles, stamps, and other effects.

[0481] Furthermore, in one embodiment, after S111, image commentary information is added to the edited image (second image) to generate an image with a poster-like feel.

[0482] Figure 12 is a flowchart of a method according to an embodiment of this application.

[0483] In one embodiment, the electronic device performs the following process shown in FIG12 to assist the user in editing and beautifying the image to be edited.

[0484] S1210, the electronic device displays at least one first image commentary. (Refer to S110)

[0485] S1211, The electronic device displays the second image. (Refer to S111)

[0486] S1212, the electronic device displays at least one second image commentary, wherein:

[0487] The second image review is based on the visual effect standards corresponding to the visual effect attributes, and is derived from the analysis of the second image.

[0488] The second image review includes information describing whether the second image meets or does not meet visual effect criteria.

[0489] Specifically, in one embodiment, in S1212, in at least one second image comment, one or more second image comments correspond to a visual effect attribute.

[0490] Specifically, in one embodiment, in S1212, the visual effect attribute targeted by the second image is analyzed, which is the visual effect attribute of the editing object used to edit the first image in S1211. In at least one second image comment, one or more second image comments correspond to a visual effect attribute of the editing object used in S1211.

[0491] In S1212, the second picture review includes information describing whether the second picture meets the visual effect criteria, that is, each second picture review describes the visual effect advantages and / or visual effect disadvantages of a visual effect attribute of the third picture.

[0492] For example, the commentary on the second image includes the visual advantages of its composition: "The person stands out, and the background is clean."

[0493] For example, the commentary on the second image included a visual flaw in its composition: "The sky takes up too much space, making the image feel empty."

[0494] S1213, the electronic device displays a third image, wherein the third image is an image obtained by synthesizing the second image and all or part of the second image comments in at least one second image comment.

[0495] Specifically, in one embodiment, in S1213:

[0496] The electronic device determines at least one second image comment that needs to be synthesized from at least one second image comment displayed;

[0497] The electronic device combines at least one second image commentary that needs to be synthesized with the second image to generate a third image.

[0498] The method according to the embodiments of this application can add image comments to the edited image to provide users with a poster-like image, thereby expanding the editing functions of image editing, improving the editing effect of image editing, and enhancing the user experience of image editing.

[0499] Figure 13 is a flowchart of a method according to an embodiment of this application.

[0500] In one embodiment, the image processing device 100 shown in FIG2 executes the following process shown in FIG13 to assist the user in editing and beautifying the image to be edited.

[0501] S1100, Image acquisition module 101 acquires the first image. (Refer to S200)

[0502] S1101, the image analysis module 102 analyzes the first image based on the visual effect standards corresponding to the visual effect attributes, taking a first number of visual effect attributes as the analysis object, obtaining a first analysis result, and generating a second number of first image comments based on the first analysis result. (Refer to S201)

[0503] S1102, the display module 104 displays the second number of first image comments generated by the image analysis module 102 to the user. (Refer to S202)

[0504] S1103, Image editing module 103 determines the third number of visual effect attributes. (Refer to S203)

[0505] S1104, the image editing module 103 edits the first image using the third number of visual effect attributes as the editing object, to generate a second image that meets the visual effect standards. (Refer to S204)

[0506] S1105, display module 104 displays the second image to the user. (Refer to S205)

[0507] S1106, the image analysis module 102 analyzes the second image using the fourth visual effect attribute as the analysis object, obtains the second analysis result, and generates the fifth commentary on the second image based on the second analysis result.

[0508] In S1106:

[0509] The visual effect attributes in the fourth set of visual effect attributes are all different;

[0510] Each second image comment corresponds to one of the visual effects attributes in the fourth number of visual effects attributes.

[0511] In one embodiment, referring to the first number of visual effect attributes in the embodiment shown in FIG3, the fourth number of visual effect attributes are all or some of the visual effect attributes that the image analysis module 102 can analyze.

[0512] In one embodiment, in S1106, the image analysis module 102 receives a third selection instruction from the user, which is used to point to a fourth number of visual effect attributes; the image analysis module 102 determines the fourth number of visual effect attributes based on the third selection instruction.

[0513] In one embodiment, in the fifth number of second image comments, one or more second image comments correspond to one of the fourth number of visual effect attributes.

[0514] In one embodiment, in the fifth number of second image comments, each second image comment is used to describe the visual advantages and / or visual disadvantages of a visual attribute of the third image.

[0515] For example, the commentary on the second image includes the visual advantages of its composition: "The person stands out, and the background is clean."

[0516] For example, the commentary on the second image included a visual flaw in its composition: "The sky takes up too much space, making the image feel empty."

[0517] For example, image analysis module 102 is configured to analyze images from five visual effect attributes: texture, composition, lighting, style, and blur. In S1106, image analysis module 102 receives a third selection instruction from the user, which is used to select the three visual effect attributes: texture, composition, and lighting. Based on the third selection instruction, image analysis module 102 analyzes a third image (fourth, three images) for each of the three visual effect attributes: texture, composition, and lighting, generating six second image reviews (fifth, six reviews). The six second image reviews include: composition advantage 1, composition advantage 2, composition disadvantage 1, texture advantage 1, lighting disadvantage 1, and lighting disadvantage 2.

[0518] Specifically, in one embodiment, the image analysis module 102 analyzes the third image based on the visual effect standards corresponding to the visual effect attributes, for each of the fourth number of visual effect attributes, to obtain a second analysis result, and generates a fifth number of second image comments based on the second analysis result, wherein:

[0519] The second analysis result includes the third image meeting the visual effect criteria and / or the first image not meeting the visual effect criteria.

[0520] Furthermore, in one embodiment, the second image commentary is used only to describe the visual advantages of a visual effect attribute of the third image.

[0521] Based on the visual effect attributes of the third image that meet the visual effect criteria in the second analysis results, the image analysis module 102 generates a fifth number of second image comments, wherein each of the fifth number of second image comments is used to describe the visual effect advantages of the third image in a visual effect attribute.

[0522] For example, image analysis module 102 is configured to analyze images from five visual effect attributes: texture, composition, lighting, style, and blur. In S1106, image analysis module 102 receives a third selection instruction from the user, which is used to select one of the three visual effect attributes: texture, composition, and lighting. Based on the third selection instruction, image analysis module 102 analyzes a third image (the fourth selection is three) for each of the three visual effect attributes: texture, composition, and lighting, and obtains a second analysis result.

[0523] Based on the visual effect attributes (texture, composition) of the third image in the second analysis results, the image analysis module 102 generates three comments on the second image (the fifth image has three comments). The three comments on the second image include: composition advantage 1, composition advantage 2, and texture advantage 1.

[0524] Furthermore, in one embodiment, in S1106, the fourth number of visual effect attributes is the third number of visual effect attributes in S1103.

[0525] In S1106, the image analysis module 102 analyzes the third image based on the visual effect standards corresponding to the visual effect attributes, for each visual effect attribute in the fourth number of visual effect attributes (the third number of visual effect attributes), obtains the second analysis result, and generates the fifth number of second image comments based on the second analysis result, wherein:

[0526] The fifth quantity is greater than or equal to the fourth quantity, and each visual effect attribute in the fourth quantity corresponds to one or more second image comments in the fifth quantity of second image comments;

[0527] Each of the second image comments in the fifth number is used to describe the visual advantages of a visual attribute of the third image.

[0528] Specifically, since the fourth set of visual effect attributes are the visual effect attributes edited in S204, and the purpose of image editing in S204 is to generate a second image that meets the visual effect standards, the second image meets the corresponding visual effect standards for each of the fourth set of visual effect attributes. In other words, in the fifth set of second image comments, each second image comment describes that the second image meets the visual effect standards.

[0529] For example, the image analysis module 102 is configured to analyze an image from five visual effect attributes: texture, composition, lighting, style, and blur. In S201, the image analysis module 102 receives a first selection instruction from the user, which points to three visual effect attributes: texture, composition, and lighting. Based on the first selection instruction, the image analysis module 102 analyzes the first image for each of the three visual effect attributes (the first number is three), generating two comments on the first image for each of the three attributes (the second number is two). In S204, the image editing module 103 edits the first image for each of the three attributes (composition and lighting), generating a second image whose composition and lighting meet the visual effect standards.

[0530] In S1106, the image analysis module 102 analyzes the second image (third image) based on the visual effect standards corresponding to the visual effect attributes, respectively, for composition and lighting (the fourth number of visual effect attributes are composition and lighting), obtains the second analysis results, and generates a fifth number of second image comments for composition and lighting (the fifth number is greater than or equal to two) based on the second analysis results.

[0531] For example, the second image commentary of the fifth number includes: composition advantage 1, composition advantage 2, composition advantage 3 (for example, after editing the above composition disadvantage 1 to eliminate the disadvantage and convert it into an advantage), light and shadow advantage 1 (for example, after editing the above light and shadow disadvantage 1 to eliminate the disadvantage and convert it into an advantage), and light and shadow advantage 2 (for example, after editing the above light and shadow disadvantage 2 to eliminate the disadvantage and convert it into an advantage).

[0532] According to one embodiment of this application, a positive review describing the second image as meeting visual effect standards is generated, thereby enabling the final poster effect to be positively evaluated and improving the user experience of the poster effect.

[0533] S1107, the display module 104 displays the fifth number of second image comments generated by the image analysis module 102 to the user.

[0534] S1108, the image editing module 103 determines the sixth number of second image comments, which are all or part of the fifth number of second image comments.

[0535] Specifically, in one embodiment, a fourth selection instruction from the user is received, which points to a sixth number of second image comments. The image editing module 103 determines the sixth number of second image comments based on the fourth selection instruction.

[0536] In another embodiment, in S1103, the image editing module 103 receives a fifth selection instruction from the user, which is used to point to multiple visual effect attributes. Based on the fifth selection instruction, the image editing module 103 determines that, among the fifth number of second image comments, the second image comment corresponding to the multiple visual effect attributes pointed to by the fifth selection instruction is the sixth number of second image comments.

[0537] S1109, the image editing module 103 synthesizes the sixth number of second image comments and the second image, and generates the third image.

[0538] S1110, the display module 104 displays the third image to the user.

[0539] Furthermore, in one embodiment, image comments can be directly attached to the original image to provide the user with the original image of the poster effect.

[0540] Figure 14 is a flowchart of a method according to an embodiment of this application.

[0541] In one embodiment, the electronic device performs the following process shown in FIG14 to assist the user in editing and beautifying the image to be edited.

[0542] S1220, the electronic device displays at least one third image commentary, wherein:

[0543] The third image commentary is based on the visual effect standards corresponding to the visual effect attributes, and analyzes the fourth image accordingly;

[0544] The third image review includes information describing whether the fourth image meets or does not meet visual quality standards.

[0545] Specifically, the execution of S1220 can be referred to S1212, and the commentary on the third image can be referred to the commentary on the second image.

[0546] S1221, the electronic device displays a fifth picture, wherein the fifth picture is a picture obtained by synthesizing the fourth picture and all or part of the third picture comments in at least one third picture comment.

[0547] Specifically, the execution of S1221 can be referred to S1213, and the commentary on the third image can be referred to the commentary on the second image.

[0548] The method according to the embodiments of this application can add poster effects to images, expand the editing functions of image editing, improve the editing effect of image editing, and enhance the user experience of image editing.

[0549] Figure 15 is a flowchart of a method according to an embodiment of this application.

[0550] In one embodiment, the image processing apparatus 100 shown in FIG2 executes the following process shown in FIG15 to assist the user in editing and beautifying the image to be edited.

[0551] S1200, Image acquisition module 101 acquires the fourth image. (Refer to S200)

[0552] S1201, the image analysis module 102 analyzes the fourth image using the seventh visual effect attribute as the analysis object, and generates the eighth commentary on the third image.

[0553] Specifically, the execution of S1201 can refer to S1106, where the visual effect attribute of the seventh number refers to the visual effect attribute of the fourth number, and the third image commentary of the eighth number refers to the second image commentary of the fifth number.

[0554] S1202, the display module 104 displays the eighth number of third image comments generated by the image analysis module 102 to the user.

[0555] S1203, the image editing module 103 determines the ninth number of third image comments, wherein the ninth number of third image comments is all or part of the eighth number of third image comments.

[0556] Specifically, the execution of S1203 can refer to S1108, where the third picture commentary of the ninth number refers to the second picture commentary of the sixth number.

[0557] S1204, the image editing module 103 combines the ninth number of third image comments and the fourth image to generate the fifth image.

[0558] S1205, the display module 104 displays the fifth image to the user.

[0559] The method provided in this application is applied to electronic devices. This application does not limit the type of electronic device that can implement the method proposed in this application. Those skilled in the art can select the appropriate electronic device to implement the method provided in this application according to the application scenario requirements.

[0560] For example, in one embodiment, the device can be implemented using a terminal device that includes a display device and an image acquisition device. This terminal device can be any interactive terminal device such as a mobile phone, tablet computer, laptop computer, desktop computer, augmented reality (AR) device, or VR device.

[0561] Furthermore, this application does not impose specific limitations on the form of the interactive interface for implementing the method proposed in this application. Those skilled in the art can design and implement the interactive interface for the method proposed in this application according to the application scenario requirements and the type of electronic device that implements the method provided in this application.

[0562] For example, in one embodiment, the method proposed in this application is implemented using a mobile phone.

[0563] Figure 16 is a flowchart of a method according to an embodiment of this application.

[0564] S1300: Users launch a photo editing application on their mobile phone.

[0565] S1301, the phone displays the picture management interface.

[0566] S1302: The mobile phone determines the first picture that the user wants to edit based on the user's operation.

[0567] For example, Figure 17 is a schematic diagram of a mobile phone screen display interface according to an embodiment of this application.

[0568] It should be noted that the mobile phone interface and interface transition process shown in Figure 17 and subsequent Figure 18 are merely examples of the method flow of the embodiments of this application. The method of the embodiments of this application may employ mobile phone interfaces and interface transition processes shown in Figure 17 and subsequent Figure 18, including but not limited to those shown.

[0569] The mobile phone screen displays the interface shown at 1400 in Figure 17. The user clicks the image editing application icon 1401 to launch the image editing application.

[0570] After the photo editing application is launched, the phone screen displays the interface shown in Figure 17, 1410. In 1410, thumbnails of images from the local gallery are displayed.

[0571] When a user clicks on a thumbnail (for example, clicking on thumbnail 1411), the phone will use the image corresponding to the thumbnail clicked by the user as the first image that the user wants to edit, and the phone will enter the image editing page 1420.

[0572] Image editing page 1420 provides a display window 1421.

[0573] Display window 1421 is used to display the image (first image) that the user wants to edit.

[0574] The image editing page 1420 also provides a "back" button 1422.

[0575] The user clicks the "Back" button 1422 to return to the interface 1410 and reselect the image to be edited.

[0576] In the example shown in Figure 17, the user activates an image editing application. The image editing application calls the browser of the local gallery shown in 1410 to display images in the local gallery to the user, allowing the user to select the local image to be edited in the local gallery.

[0577] In this embodiment, the method provided for the user to select an image to be edited is not limited to the embodiment shown in Figure 17.

[0578] For example, in another embodiment, the user activates an image editing application that invokes a web browser, allowing the user to select the web image to be edited within the web browser.

[0579] For example, in another embodiment, when a user selects an image in this map library application or web browsing application and clicks the edit option, the image editing application is launched, and the image editing page shown in 1420 is entered.

[0580] S1303, The mobile phone confirms the visual effect attributes that need to be analyzed (the first number of visual effect attributes).

[0581] As shown in Figure 17, the image editing page 1420 also provides a settings button 1423.

[0582] When the user clicks the settings button 1423, the phone enters the visual effects attribute selection interface 1430.

[0583] The visual effect attribute selection interface 1430 provides all visual effect attributes that can be analyzed on the mobile phone. Users can select the visual effect attributes to be analyzed by clicking the checkboxes.

[0584] For example, as shown in Figure 17, 1430, the user selects texture, composition, lighting, style, and blur.

[0585] The visual effects attribute selection interface 1430 also provides an "OK" button 1431.

[0586] When the user clicks the "OK" button 1431, the phone confirms that the currently selected visual effect attribute is the visual effect attribute that needs to be analyzed, and the phone returns to the image editing page 1420.

[0587] In the example shown in Figure 17, the user selects the visual effect attribute to be analyzed from all the visual effect attributes that can be analyzed on the mobile phone.

[0588] Furthermore, in one embodiment, after the image editing application is launched for the first time, all visual effect attributes in 1430 are checked. That is, after the image editing application is launched for the first time, if the user does not change the checked state of the visual effect attributes in 1430, the default visual effect attributes to be analyzed are all visual effect attributes that can be analyzed.

[0589] Furthermore, in one embodiment, after the image editing application is launched, the checkbox state of the visual effect attributes in 1430 retains the final checkbox state of the visual effect attributes in 1430 when the image editing application was launched last time. In another embodiment, after each launch of the image editing application, all visual effect attributes in 1430 are checked. That is, after each launch of the image editing application, if the user does not change the checkbox state of the visual effect attributes in 1430, the default visual effect attributes to be analyzed are all visual effect attributes that can be analyzed.

[0590] Furthermore, in another embodiment, the image editing application does not provide a settings button 1423 or a visual effect attribute selection interface 1430. The image editing application defaults to analyzing all available visual effect attributes.

[0591] Furthermore, in another embodiment, the image editing application does not provide a visual effects attribute selection interface 1430. When the user clicks the settings button 1423, a visual effects attribute selection window pops up on the phone. The visual effects attribute selection window floats above the image editing page 1420.

[0592] The visual effects attribute selection window provides all visual effects attributes that can be analyzed on the mobile phone, as well as an "OK" button (refer to the visual effects attribute selection interface 1430). Users can select the visual effects attributes to be analyzed by clicking the checkboxes in the visual effects attribute selection window.

[0593] When the user clicks the "OK" button in the visual effects attribute selection window, the phone confirms that the currently selected visual effects attribute in the visual effects attribute selection window is the visual effects attribute that needs to be analyzed, and the phone cancels the display of the visual effects attribute selection window.

[0594] The image editing page 1420 also provides a "Manual Edit" button 1425.

[0595] When a user clicks the "Manual Edit" button (1425), the phone enters the manual editing interface. This interface offers various editing tools, such as cropping, lighting adjustment, color adjustment, and blurring tools. Users can manually edit the image using this interface.

[0596] S1304, the mobile phone analyzes the image (first image) that the user wants to edit for each of the visual effect attributes (the first number of visual effect attributes) that need to be analyzed, obtains the first analysis result, generates a second number of first image comments based on the first analysis result, and displays the second number of first image comments to the user.

[0597] For example, Figure 18 is a schematic diagram of a mobile phone screen display interface according to an embodiment of this application.

[0598] The image editing page 1420 shown in Figure 17 also provides a "Smart Analysis" button 1424.

[0599] When the user clicks the "Intelligent Analysis" button 1424, the phone analyzes the visual effect attributes selected in the visual effect attribute selection interface 1430 for the image (first image) that the user wants to edit, generates a second number of comments for the first image, and the phone enters the image comment display interface shown in Figure 18 at 1500.

[0600] Furthermore, in another embodiment, the image editing page 1420 also provides an input box for inputting intent information. The user can input intent information in the input box (or choose not to input it). When the user clicks the "Intelligent Analysis" button 1424, the phone selects the visual effect attributes chosen on the visual effect attribute selection interface 1430. Based on the user's input intent information, the phone analyzes the image (first image) the user wishes to edit and generates a second number of first image comments. The phone then enters the image comment display interface shown at 1500 in Figure 18.

[0601] Image commentary display interface 1500 provides display window 1501.

[0602] Display window 1501 is used to display the image (first image) that the user wants to edit.

[0603] The image commentary display interface 1500 also provides a display window 1502.

[0604] Display window 1502 is used to display the first image commentary for the second number of images.

[0605] For example, as shown in the image comment display interface 1500 of Figure 18, display window 1502 displays:

[0606] Commentary on the first image regarding "composition" (too much white space, cluttered background; the subject is not prominent enough);

[0607] The first image review regarding "light and shadow" (the color tone is dark and unpleasant; there is no contrast between light and shadow).

[0608] In another embodiment, to maintain a clean interface, the full content of the first image review is not displayed in display window 1502. For example, the visual effect attribute corresponding to the first image review is displayed in display window 1502. When the user clicks on the visual effect attribute displayed in display window 1502, the phone pops up the first image review display window, which floats above the image review display interface 1500. The first image review display window displays the full content of the first image review corresponding to the visual effect attribute clicked by the user.

[0609] The image comment display interface 1500 also provides a "back" button 1503.

[0610] The user clicks the "Back" button 1503 to return to the image editing page 1420 shown in Figure 17.

[0611] Furthermore, in one embodiment, clicking on the image displayed in display window 1502 causes the phone to enter a full-screen display interface, displaying the image (first image) that the user wishes to edit in full screen. Additionally, comments for the first image are marked on the corresponding portion of the image displayed in the full-screen display interface.

[0612] For example, in the sky area of ​​an image displayed in full-screen mode, mark it as "too much white space"; in the people area of ​​an image displayed in full-screen mode, mark it as "the people are not prominent enough" and "there is no contrast between light and shadow"; in the background trees area of ​​an image displayed in full-screen mode, mark it as "cluttered background" and "dark and unpleasant color tone".

[0613] Furthermore, in one embodiment, the image comment display interface 1500 also displays an arrow pointing from the first image comment in the display window 1502 to the image displayed in the display window 1502.

[0614] An arrow points from a first image comment in display window 1502 to the image portion of the image displayed in display window 1502 that corresponds to the first image comment.

[0615] For example, the arrow points from the first image comment on “composition” (too much white space) to the sky portion of the image displayed in display window 1502.

[0616] For example, the arrow points from the first image commentary on "composition" (cluttered background) to the background trees in the image displayed in display window 1502.

[0617] For example, the arrow points from the first image comment on "composition" (the person is not prominent enough) to the person in the image displayed in display window 1502.

[0618] For example, the arrow points from the first image comment on "light and shadow" (the tone is dark and unpleasant) to the background trees in the image displayed in display window 1502.

[0619] For example, the arrow points from the first image commentary on "light and shadow" (without light and shadow contrast) to the human figure in the image displayed in display window 1502.

[0620] S1305, the phone confirms the visual effects attributes that need to be edited.

[0621] As shown in the image comment display interface 1500 of Figure 18, the display window 1502 provides corresponding checkboxes for each first image comment displayed. Users can select the corresponding visual effect attribute as the visual effect attribute that needs to be edited by checking the checkboxes.

[0622] For example, as shown in the image comment display interface 1500 of Figure 18, the user selects "Composition" and "Light and Shadow" in the display window 1502.

[0623] S1306, the mobile phone edits the image (first image) that the user expects to edit based on the third number of visual effect attributes, in order to generate a second image that meets the visual effect standards, and displays the second image to the user.

[0624] As shown in the image comment display interface 1500 in Figure 18, the image comment display interface 1500 also provides a "Smart Beautification" button 1504.

[0625] When the user clicks the "Smart Beautification" button 1504, the phone uses the visual effect attributes selected by the user in the display window 1502 as the visual effect attributes to be edited, edits the image the user wants to edit (the first image), and generates a second image that meets the visual effect standards. The second image is then displayed in the display window 1502.

[0626] The image comment display interface 1500 also provides a "Save" button 1506.

[0627] When the user clicks the "Save" button 1506, the phone will save the image displayed in window 1502 to the local device or the cloud.

[0628] Furthermore, in another embodiment, the image comment display interface 1500 also provides a manual editing button.

[0629] When a user clicks the "Manual Edit" button on the image comment display screen (1500), the phone enters the manual editing interface. This interface offers various editing tools, such as cropping, lighting adjustment, color adjustment, and blurring tools. Users can then manually edit the image using this interface.

[0630] After the second image is displayed in display window 1502, the user can change the visual effect attributes selected in display window 1502. After the user changes the visual effect attributes selected in display window 1502, the user clicks the "Smart Enhancement" button 1504, and the second image displayed in display window 1502 is refreshed accordingly.

[0631] S1307: Based on the visual effect standard corresponding to the visual effect attribute, the mobile phone analyzes the second image for each visual effect attribute in the edited visual effect attribute, obtains the second analysis result, generates the fifth second image comment based on the second analysis result, and displays the fifth second image comment to the user.

[0632] As shown in the image comment display interface 1500 of Figure 18, the image comment display interface 1500 also provides an "Effects" button 1505.

[0633] When the user clicks the "Effects" button 1505, the phone enters the effects editing interface shown in 1510.

[0634] The special effects editing interface 1510 provides a display window 1512.

[0635] When the phone moves from the image comment display interface 1500 to the special effects editing interface 1510, the display window 1512 is used to display the second image displayed in the display window 1502.

[0636] The effects editing interface 1510 also provides an effects selection window 1511.

[0637] The effects selection window 1511 includes a "Poster Effects" button 1513, a "Frame" button, a "Puzzle" button, a "Speech Bubble" button, a "Stamp" button, a "Doodle" button, and so on.

[0638] Furthermore, in another embodiment, the image editing application does not provide an effects editing interface 1510. When the user clicks the "Effects" button 1505, the phone displays an effects selection window 1511. The effects selection window 1511 floats above the image comment display interface 1500.

[0639] When a user taps an area outside the effects selection window 1511 on the screen, the phone will disable the display of the visual effects attribute selection window.

[0640] When a user clicks the "Poster Effects" button 1513, the phone enters the poster effect editing interface shown in 1520.

[0641] The poster effect editing interface 1520 provides a display window 1521.

[0642] Display window 1521 is used to display the second image displayed in display window 1502 of the image commentary display interface 1500.

[0643] The poster effect editing interface 1520 also provides a display window 1522.

[0644] Display window 1522 is used to display the commentary on the fifth second image. For example, as shown in the poster effect editing interface 1520 of Figure 18, display window 1522 displays:

[0645] Regarding the visual advantages of the composition, "The image shows a little girl in a blue and yellow dress observing leaves in a sunny, green environment";

[0646] Regarding the visual advantages of the composition, "the person is centered, the background is clean, and the focus is on the hand holding the leaf, which makes the person see a very compelling portrait."

[0647] Regarding the visual advantages of light and shadow, "the sunlight shines from the side and rear, highlighting the vivid face of the character."

[0648] S1308, the mobile phone determines the sixth of the fifth number of second image comments in the second image comment.

[0649] As shown in the poster effect editing interface 1520 of Figure 18, the display window 1522 provides a corresponding checkbox for each displayed second image comment. Users can select the sixth number of second image comments by checking the checkboxes.

[0650] S1309, the mobile phone combines the second image commentary (the sixth image) with the second image to generate a fourth image, which is then displayed to the user.

[0651] As shown in the poster effect editing interface 1520 of Figure 18, the poster effect editing interface 1520 also provides a "Generate Poster" button 1523.

[0652] When the user clicks the "Generate Poster" button 1523, the phone will display all the selected second image comments in the display window 1522 as the sixth number of second image comments, combine the sixth number of second image comments and the second image to generate the fourth image, which will be displayed in the display window 1521.

[0653] After the fourth image is displayed in display window 1521, the user can change the description of the second image selected in display window 1522. After the user changes the description of the second image selected in display window 1522, the user clicks the "Generate Poster" button 1523, and the fourth image displayed in display window 1521 is refreshed accordingly.

[0654] The poster effect editing interface 1520 also provides an "OK" button 1524.

[0655] The user clicks the "OK" button 1524, and the phone confirms the image editing effect in the display window 1521. The phone then returns to the special effects editing interface 1510. At this time, the fourth image from the display window 1521 is displayed in the display window 1512 of the special effects editing interface 1510.

[0656] The poster effect editing interface 1520 also provides a "Cancel" button 1525.

[0657] When the user clicks the "Cancel" button 1525, the phone abandons the image editing effects in the display window 1521 and returns to the effects editing interface 1510. At this time, the second image displayed in the display window 1502 is shown in the display window 1512 of the effects editing interface 1510.

[0658] The effects editing interface 1510 also provides a "Save" button 1517.

[0659] When a user clicks the "Save" button 1517, the phone will save the image displayed in window 1512 to the local device or the cloud.

[0660] The effects editing interface 1510 also provides a "back" button 1518.

[0661] When the user clicks the "Back" button (1518), the phone returns to the image comment display interface (1500).

[0662] Furthermore, in another embodiment, the poster effect editing interface 1520 also provides an input window for the user to input image comments. The user can enter their own edited image comments in the input window (or choose not to enter any). After the user clicks the "Generate Poster" button 1523, the mobile phone displays all the checked second image comments in the display window 1522 as the sixth number of second image comments, combines the sixth number of second image comments, the user-input image comments, and the second image to generate a fourth image, which is then displayed in the display window 1521.

[0663] In the description of the embodiments of this application, for the sake of convenience, the device is described by dividing it into various modules according to its functions. The division of each module is only a logical functional division. When implementing the embodiments of this application, the functions of each module can be implemented in one or more software and / or hardware.

[0664] Specifically, the apparatus proposed in this application can be fully or partially integrated onto a single physical entity (e.g., a GPU or other type of processor), or it can be physically separated. These modules can be implemented entirely in software via processing element calls; entirely in hardware; or some modules can be implemented in software via processing element calls, while others are implemented in hardware. For example, the detection module can be a separate processing element or integrated into a chip in an electronic device. The implementation of other modules is similar. Furthermore, these modules can be fully or partially integrated together or implemented independently. During implementation, each step of the above method or each of the above modules can be completed through integrated logic circuits in the hardware of the processor element or through software instructions.

[0665] For example, these modules can be one or more integrated circuits configured to implement the above methods, such as one or more application-specific integrated circuits (ASICs), one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs). Alternatively, these modules can be integrated together as a system-on-a-chip (SOC).

[0666] In one embodiment, the image processing apparatus provided in this application can be implemented on an electronic device, which includes all the modules of the image processing apparatus provided in this application.

[0667] An embodiment of this application also proposes an electronic device (e.g., a mobile phone, AR glasses). This electronic device is used to execute the method flow or part of the method flow described in the embodiments of this application.

[0668] Figure 19 is a schematic diagram of an electronic device structure according to an embodiment of this application.

[0669] As shown in Figure 19, the electronic device 2400 includes a bus 2404, a processor 2401, a memory 2402, and a communication interface 2403. The processor 2401, the memory 2402, and the communication interface 2403 communicate with each other via the bus 2404.

[0670] Electronic device 2400 may be a server or a terminal device. It should be understood that this application does not limit the number of processors or memories in electronic device 2400.

[0671] It is understood that the structural description of the electronic device 2400 in this application does not constitute a specific limitation on the electronic device 2400. In other embodiments of this application, the electronic device 2400 may include other components besides the processor 2401 and the memory 2402.

[0672] Bus 2404 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, only one line is used in Figure 19, but this does not imply that there is only one bus or one type of bus. Bus 2404 can include pathways for transmitting information between various components of electronic device 2400 (e.g., memory 2402, processor 2401, communication interface 2403).

[0673] Processor 2401 may include any one or more processors such as a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0674] The processor 2401 may be an on-chip device (SOC) that may include a central processing unit (CPU) and may further include other types of processors.

[0675] The processor 2401 may include, for example, a CPU, DSP, microcontroller, or digital signal processor, and may also include a GPU, embedded neural network processing units (NPUs), and image signal processors (ISPs). The processor may also include necessary hardware accelerators or logic processing hardware circuitry, such as an ASIC, or one or more integrated circuits for controlling the execution of the program in this application. Furthermore, the processor may have the function of operating one or more software programs, which may be stored in a storage medium.

[0676] Processor 2401 may include one or more processing units. For example, a processor may include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural network processing unit (NPU). Different processing units may be independent components or integrated into one or more processors. In some embodiments, electronic device 2400 may also include one or more processors 2401. The controller can generate operation control signals based on instruction opcodes and timing signals to control instruction fetching and execution.

[0677] In some embodiments, the processor 2401 may include one or more interfaces. These interfaces may include an inter-integrated circuit (I2C) interface, an integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a SIM card interface, and / or a USB interface, etc. The USB interface is a USB standard-compliant interface, specifically a Mini USB interface, a Micro USB interface, a USB Type-C interface, etc. The USB interface can be used to connect a charger to charge the electronic device, and can also be used for data transfer between the electronic device and peripheral devices.

[0678] The memory 2402 may include volatile memory, such as random access memory (RAM). The processor 2401 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0679] The memory 2402 stores executable program code, and the processor 2401 executes the executable program code to implement the aforementioned functions, thereby realizing the image processing method proposed in the embodiments of this application. That is, the memory 2402 stores instructions for executing the image processing method proposed in the embodiments of this application.

[0680] The memory 2402 may include a code storage area and a data storage area. The code storage area may store the operating system. The data storage area may store data created during the use of the electronic device 2400. Furthermore, the memory 2402 may include high-speed random access memory, and may also include non-volatile memory, such as one or more disk storage components, flash memory components, universal flash storage (UFS), etc.

[0681] The memory 2402 may be a read-only memory (ROM), other types of static storage devices capable of storing static information and instructions, random access memory (RAM), or other types of dynamic storage devices capable of storing information and instructions. It may also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices. Alternatively, it may be any computer-readable medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer.

[0682] Processor 2401 and memory 2402 can be combined into a single processing device, but more commonly they are separate components.

[0683] The communication interface 2403 uses transceiver modules such as, but not limited to, network interface cards and transceivers to enable communication between the electronic device 2400 and other devices or communication networks.

[0684] The electronic device 2400 may also include an external memory interface for connecting an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device. The external memory card communicates with the processor 2401 through the external memory interface to perform data storage functions. For example, music, video, and other files can be stored on the external memory card.

[0685] Furthermore, in one embodiment, the electronic device 2400 may also include a display screen, which is connected to the processor 2401 via a bus 2404. The display screen is used to display images that need to be shown to the user in the method flow provided in this application embodiment, such as a first image commentary and a second image; or, for example, a third image.

[0686] Furthermore, in another embodiment, the electronic device 2400 is connected to the display device, for example, via a communication interface 2403, or via a display interface of the processor 2401. The electronic device 2400 outputs image data of the image to be displayed in the method flow provided in this application embodiment to the display device, and the display device displays the corresponding image to the user.

[0687] In another embodiment, the image processing apparatus provided in this application can be implemented on multiple electronic devices. For example, the image processing apparatus provided in this application can be implemented through a terminal device including a display device and a cloud server connected to the terminal device.

[0688] An embodiment of this application also proposes an electronic device cluster. The electronic device cluster includes at least one electronic device.

[0689] Any one of the electronic devices in the electronic device cluster can refer to the electronic device shown in FIG19. Each electronic device in the electronic device cluster includes a memory and a processor; the processor of at least one electronic device in the electronic device cluster is used to execute instructions stored in the memory of at least one electronic device in the electronic device cluster, so that the electronic device cluster performs the method as described in the embodiments of this application.

[0690] For example, in one embodiment, the electronic device cluster includes a first electronic device, which is a terminal device, such as a mobile phone or AR glasses. The electronic device cluster also includes a second electronic device, which is a cloud server.

[0691] The first electronic device implements the functions of the image acquisition module 101 and the display module 104 of the image processing device shown in Figure 2. The second electronic device implements the functions of the image analysis module 102 and the image editing module 103 of the image processing device shown in Figure 2.

[0692] For example, in one embodiment, the electronic device cluster includes a first electronic device, which is a terminal device, such as a mobile phone or AR glasses. The electronic device cluster also includes a second electronic device and a third electronic device, which are electronic devices of a cloud server.

[0693] The first electronic device is used to implement the functions of the image acquisition module 101 and the display module 104 of the image processing device shown in FIG2. The second and third electronic devices are used to cooperate in data processing to implement the functions of the image analysis module 102 and the image editing module 103 of the image processing device shown in FIG2.

[0694] Figure 20 is a schematic diagram of an electronic device cluster according to an embodiment of this application.

[0695] As shown in Figure 20, the electronic device cluster includes at least one electronic device 2500 (the structure of electronic device 2500 can be referenced to electronic device 2400). Electronic device 2500 can be a server device or a terminal device. Each electronic device 2500 includes: a bus 2504 (refer to bus 2404), a processor 2501 (refer to processor 2401), a memory 2502 (refer to memory 2402), and a communication interface 2503 (refer to communication interface 2403).

[0696] The memory 2501 of one or more electronic devices in the electronic device cluster may contain the same instructions for executing the image processing method proposed in the embodiments of this application.

[0697] In some possible implementations, the memory 2501 of one or more electronic devices 2500 in the electronic device cluster may also store partial instructions for executing the glasses try-on method proposed in the embodiments of this application. In other words, a combination of one or more electronic devices 2500 can jointly execute instructions for performing the method proposed in the embodiments of this application.

[0698] It should be noted that the memory 2501 in different electronic devices 2500 in the electronic device cluster can store different instructions, which are used to execute some functions of the model training device proposed in the embodiments of this application. That is, the instructions stored in the memory 2502 in different electronic devices 2500 can realize the functions of one or more modules among the image acquisition module 101, display module 104, image analysis module 102, and image editing module 103.

[0699] In some possible implementations, one or more electronic devices in an electronic device cluster can be connected via a network. This network can be a wide area network (WAN) or a local area network (LAN), etc.

[0700] Figure 21 is a schematic diagram of an electronic device cluster network connection according to an embodiment of this application.

[0701] As shown in Figure 21, the two electronic devices 2600A and 2600B are connected via a network. Specifically, they are connected to the network through the communication interfaces in each electronic device. The structures of electronic devices 2600A and 2600B can be referenced from electronic device 2400.

[0702] Electronic device 2600A includes: bus 2604A (refer to bus 2404), processor 2601A (refer to processor 2401), memory 2602A (refer to memory 2402) and communication interface 2603A (refer to communication interface 2403).

[0703] Electronic device 2600B includes: bus 2604B (refer to bus 2404), processor 2601B (refer to processor 2401), memory 2602B (refer to memory 2402) and communication interface 2603B (refer to communication interface 2403).

[0704] In one embodiment, electronic device 2600A is a terminal device, and electronic device 2600B is a server.

[0705] It should be understood that the function of electronic device 2600A shown in Figure 21 can also be performed by multiple electronic devices. Similarly, the function of electronic device 2500B can also be performed by multiple electronic devices.

[0706] An embodiment of this application also provides an electronic chip. This electronic chip is used to execute the method flow or part of the method flow described in the embodiments of this application.

[0707] Specifically, the electronic chip includes a processor for executing program instructions. When the computer program instructions are executed by the processor, the electronic chip is triggered to perform the steps described in the embodiments of this application. The processor of the electronic chip can refer to the processor of the above-described electronic device.

[0708] The devices, apparatuses, and modules described in the embodiments of this application can be implemented by computer chips or physical entities, or by products with certain functions.

[0709] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media containing computer-usable program code.

[0710] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0711] Specifically, one embodiment of this application also provides a computer-readable storage medium storing a computer program that, when run on a computer, causes the computer to execute the method provided in the embodiment of this application.

[0712] An embodiment of this application also provides a computer program product, which includes a computer program that, when run on a computer, causes the computer to perform the method provided in the embodiment of this application.

[0713] The embodiments described in this application are described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more flowchart illustrations and / or one or more block diagrams.

[0714] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0715] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0716] It should also be noted that in the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0717] In this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0718] This application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0719] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0720] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments of this application can be implemented using electronic hardware, computer software, or a combination of electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0721] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0722] The above description is merely a specific embodiment of this application. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application. The protection scope of this application should be determined by the protection scope of the claims.

Claims

1. An image processing method, characterized in that, The method includes: Display at least one first image comment, wherein: each first image comment corresponds to a visual effect attribute; the first image comment includes information describing that the first image does not meet the corresponding visual effect criteria; Displaying a second image, wherein: the second image is generated by editing the first image, using all or part of the visual effect attributes corresponding to the at least one first image comment as the editing object.

2. The method according to claim 1, characterized in that, The first image review is based on the visual effect standards corresponding to the visual effect attributes, and is obtained by analyzing the first image. The second image, in terms of the visual effect attributes of the object being edited, meets the corresponding visual effect standards.

3. The method according to claim 1 or 2, characterized in that, The display of at least one first image commentary includes: Taking a first number of visual effect attributes as the analysis object, the first image is analyzed to generate a second number of first image comments, wherein: in the second number of first image comments, each first image comment corresponds to one of the visual effect attributes in the first number of visual effect attributes. The commentary on the first image is displayed in the second quantity.

4. The method according to claim 3, characterized in that, The second quantity is less than or equal to the first quantity.

5. The method according to claim 3, characterized in that, The method further includes: Receive a first selection instruction, which is used to point to the first number of visual effect attributes; Based on the first selection instruction, the first number of visual effect attributes are determined from all visual effect attributes that can be analyzed.

6. The method according to claim 3, characterized in that, The step of analyzing the first image using a first number of visual effect attributes as the analysis object and generating a second number of comments on the first image includes: Using the first number of visual effect attributes as the analysis object, the first image is analyzed to obtain a first analysis result, wherein the first analysis result includes whether the first image meets or does not meet the corresponding visual effect standard for any one of the first number of visual effect attributes. The second number of first image comments are generated based on the first analysis results.

7. The method according to claim 6, characterized in that, The step of analyzing the first image using the first number of visual effect attributes as the analysis object and obtaining the first analysis result includes: Perform intent recognition on the first image to obtain the image expression intent of the first image; Based on the image's intended meaning, the visual effect standards corresponding to the first number of visual effect attributes are invoked; Using the first number of visual effect attributes as the analysis object, and based on the visual effect standards corresponding to the first number of visual effect attributes, the first image is analyzed to obtain the first analysis result.

8. The method according to claim 7, characterized in that, The method further includes: Receive intent information from user input; The step of performing intent recognition on the first image to obtain the image expression intent of the first image includes performing intent recognition on the first image based on the intent information to obtain the image expression intent.

9. The method according to claim 3, characterized in that, The display of the second image includes: Determine a third number of visual effect attributes, wherein the third number of visual effect attributes includes all or part of the visual effect attributes corresponding to the second number of first image comments; Using the third number of visual effect attributes as the editing object, edit the first image to generate the second image.

10. The method according to claim 9, characterized in that, The determination of the third number of visual effect attributes includes: Receive a second selection instruction, which is used to point to the third number of visual effect attributes; The third number of visual effect attributes is determined according to the second selection instruction.

11. The method according to claim 10, characterized in that: The third quantity of visual effect attributes is some or all of the visual effect attributes corresponding to the second quantity of first image comments. Alternatively, the third number of visual effect attributes may also include other visual effect attributes besides those corresponding to the second number of first image comments.

12. The method according to claim 1 or 2, characterized in that: The step of displaying at least one first image comment includes inputting the first image into a first neural network model and obtaining the at least one first image comment output by the first neural network model.

13. The method according to claim 1 or 2, characterized in that: The step of displaying the second image includes inputting the first image and the second selection instruction into the second neural network model, and obtaining the second image output by the second neural network model.

14. The method according to claim 1 or 2, characterized in that: The step of displaying at least one first image comment includes inputting the first image into a third neural network model and obtaining the at least one first image comment output by the third neural network model. The process of displaying the second image includes inputting the second selection instruction into the third neural network model and obtaining the second image output by the third neural network model.

15. The method according to claim 1 or 2, characterized in that, The first image commentary also includes explanatory information, which describes why the first image does not meet the visual effect standard.

16. The method according to claim 1 or 2, characterized in that, The first image review also includes image editing suggestions, which describe the operation process for editing the image and are used to edit the first image so that the first image meets the visual effect standard.

17. The method according to any one of claims 1-16, characterized in that, The method further includes: Display at least one second image commentary, wherein: the second image commentary is obtained by analyzing the second image based on visual effect criteria corresponding to visual effect attributes; the second image commentary includes information describing whether the second image meets and / or does not meet the visual effect criteria; Display a third image, wherein the third image is an image obtained by combining the second image and all or part of the second image comments in the at least one second image commentary.

18. The method according to claim 17, characterized in that, The display of at least one second image commentary includes: Using the fourth visual effect attribute as the analysis object, analyze the second image and generate the fifth image commentary; The commentary on the second image shows the fifth number of images.

19. The method according to claim 18, characterized in that, The fourth number of visual effect attributes is the same as the third number of visual effect attributes.

20. The method according to claim 17, characterized in that, The display of the third image includes: Determine a sixth number of second image comments, wherein the sixth number of second image comments is all or part of the fifth number of second image comments; The sixth number of second image comments and the second image are combined to generate the third image.

21. An image processing method, characterized in that, The method includes: Display at least one third image commentary, wherein: the third image commentary is obtained by analyzing the fourth image based on the visual effect criteria corresponding to the visual effect attributes; the third image commentary includes information describing whether the fourth image meets and / or does not meet the visual effect criteria; The fifth image is displayed, wherein the fifth image is an image obtained by combining the fourth image and all or part of the third image comments in the at least one third image commentary.

22. An electronic device, characterized in that, The electronic device includes a memory and a processor; The processor is configured to execute instructions stored in the memory to cause the electronic device to perform the method as described in any one of claims 1-20 or claim 21.

23. An electronic equipment cluster, characterized in that, The electronic device cluster includes at least one electronic device, each electronic device including a memory and a processor; The processor of the at least one electronic device is configured to execute instructions stored in the memory of the at least one electronic device to cause the cluster of electronic devices to perform the method as described in any one of claims 1-20 or claim 21.

24. A computer program product containing instructions, characterized in that, When the instruction is executed by the electronic device system, it causes the electronic device cluster to perform the method as described in any one of claims 1-20 or claim 21.

25. A computer-readable storage medium, characterized in that, It includes computer program instructions, which, when executed by a computer system, perform the method as described in any one of claims 1-20 or claim 21.

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