Image processing method and device, computer equipment and storage medium

Abstract

The invention provides an image processing method and device, computer equipment and a storage medium. The method comprises the steps that a to-be-processed image input by a user is acquired; acquiring editing description information set for the to-be-processed image; analyzing the editing description information, and determining at least one target editing instruction corresponding to the editing description information in a plurality of preset editing instructions; according to target editing parameters corresponding to the target editing instruction, the target editing instruction is executed to process the to-be-processed image, a target image conforming to the editing description information is obtained, and the target editing parameters corresponding to the target editing instruction are determined based on historical editing operation of the user. Through the method, rapid editing of the image can be realized, and the edited image can meet user requirements.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to an image processing method, apparatus, computer equipment and storage medium. Background Art

[0002] With the development of image beautification technology, more and more image beautification software has appeared on the market, and each image beautification software has various beautification functions. When using image beautification software to beautify images, users need to first understand the role of beautification functions and then select appropriate beautification functions for beautification processing. However, since there are many beautification functions and the same beautification function may have different names in different beautification software, users may not be able to quickly select the appropriate beautification function for image beautification, and the image processing speed is low. Summary of the invention

[0003] The embodiments of the present disclosure at least provide an image processing method, apparatus, computer equipment, and storage medium.

[0004] In a first aspect, an embodiment of the present disclosure provides an image processing method, including:

[0005] Get the image to be processed input by the user;

[0006] Obtaining editing description information set for the image to be processed;

[0007] Parsing the editing description information to determine at least one target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions;

[0008] According to the target editing parameters corresponding to the target editing instruction, the target editing instruction is executed to process the image to be processed to obtain a target image that conforms to the editing description information, wherein the target editing parameters corresponding to the target editing instruction are determined based on the user's historical editing operations.

[0009] In a possible implementation manner, the target editing parameters include a target editing position and / or a target editing force.

[0010] In a possible implementation manner, the method further includes determining a target editing parameter corresponding to each editing instruction according to the following method:

[0011] For any editing instruction, determining initial editing parameters corresponding to the editing instruction input by the user when editing different images to be processed;

[0012] The initial editing parameters are counted to determine the target editing parameters corresponding to the editing instruction.

[0013] In a possible implementation manner, when the image to be processed includes a user's face, the method further includes determining a target editing parameter corresponding to the target editing instruction according to the following method:

[0014] Identify a face identifier corresponding to a user's face in the image to be processed;

[0015] Determine the target editing parameters corresponding to the target editing instruction under the face identification.

[0016] In a possible implementation manner, when there are multiple editing instructions determined based on the editing description information, the method further includes determining the target editing instruction corresponding to the editing description information according to the following method:

[0017] Displaying instruction identifiers of multiple editing instructions for satisfying the editing description information;

[0018] In response to a selection operation for any instruction identifier, the editing instruction corresponding to the instruction identifier selected by the selection operation is used as the target editing instruction corresponding to the editing description information.

[0019] In a possible implementation manner, when there are multiple editing instructions that satisfy the same editing description information, the method further includes determining the target editing instruction corresponding to the editing description information according to the following method:

[0020] Get the user's historical editing records;

[0021] Determine, based on the historical editing records, weight information corresponding to a plurality of editing instructions that satisfy the editing description information;

[0022] The plurality of editing instructions are integrated based on the weight information to obtain the target editing instruction.

[0023] In a possible implementation manner, the parsing of the edit description information to determine a target edit instruction corresponding to the edit description information among a plurality of preset edit instructions includes:

[0024] The editing description information is input into a pre-trained instruction recognition network to determine a target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions.

[0025] In a possible implementation manner, the editing description information is text information;

[0026] The parsing of the editing description information to determine a target editing instruction corresponding to the editing description information among the preset multiple editing instructions includes:

[0027] Extracting keywords contained in the edit description information;

[0028] Based on the correspondence between the preset keywords and the editing instructions, a target editing instruction corresponding to the editing description information is determined among the preset multiple editing instructions.

[0029] In a second aspect, the present disclosure also provides an image processing device, including:

[0030] A first acquisition module, used to acquire an image to be processed input by a user;

[0031] A second acquisition module is used to acquire the edit description information set for the image to be processed;

[0032] A parsing module, used for parsing the editing description information, and determining at least one target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions;

[0033] An execution module is used to execute the target editing instruction to process the image to be processed according to the target editing parameters corresponding to the target editing instruction to obtain a target image that conforms to the editing description information, wherein the target editing parameters corresponding to the target editing instruction are determined based on the user's historical editing operations.

[0034] In a possible implementation manner, the target editing parameters include a target editing position and / or a target editing force.

[0035] In a possible implementation manner, the execution module is further configured to determine the target editing parameter corresponding to each editing instruction according to the following method:

[0036] For any editing instruction, determining initial editing parameters corresponding to the editing instruction input by the user when editing different images to be processed;

[0037] The initial editing parameters are counted to determine the target editing parameters corresponding to the editing instruction.

[0038] In a possible implementation manner, when the image to be processed includes a user's face, the execution module is further configured to determine the target editing parameter corresponding to the target editing instruction according to the following method:

[0039] Identify a face identifier corresponding to a user's face in the image to be processed;

[0040] Determine the target editing parameters corresponding to the target editing instruction under the face identification.

[0041] In a possible implementation, when there are multiple editing instructions determined based on the editing description information, the parsing module is further configured to determine the target editing instruction corresponding to the editing description information according to the following method:

[0042] Displaying instruction identifiers of multiple editing instructions for satisfying the editing description information;

[0043] In response to a selection operation for any instruction identifier, the editing instruction corresponding to the instruction identifier selected by the selection operation is used as the target editing instruction corresponding to the editing description information.

[0044] In a possible implementation manner, when there are multiple editing instructions that satisfy the same editing description information, the parsing module is further configured to determine the target editing instruction corresponding to the editing description information according to the following method:

[0045] Get the user's historical editing records;

[0046] Determine, based on the historical editing records, weight information corresponding to a plurality of editing instructions that satisfy the editing description information;

[0047] The plurality of editing instructions are integrated based on the weight information to obtain the target editing instruction.

[0048] In a possible implementation manner, the parsing module, when parsing the edit description information to determine a target edit instruction corresponding to the edit description information among a plurality of preset edit instructions, is configured to:

[0049] The editing description information is input into a pre-trained instruction recognition network to determine a target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions.

[0050] In a possible implementation manner, the editing description information is text information;

[0051] The parsing module, when parsing the edit description information and determining a target edit instruction corresponding to the edit description information among a plurality of preset edit instructions, is used to:

[0052] Extracting keywords contained in the edit description information;

[0053] Based on the correspondence between the preset keywords and the editing instructions, a target editing instruction corresponding to the editing description information is determined among the preset multiple editing instructions.

[0054] In a third aspect, an embodiment of the present disclosure further provides a computer device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the computer device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of the above-mentioned first aspect, or any possible implementation of the first aspect are performed.

[0055] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned first aspect or any possible implementation of the first aspect are executed.

[0056] In the image processing method, apparatus, computer equipment and storage medium provided by the embodiments of the present disclosure, after obtaining the image to be processed input by the user, after obtaining the image to be processed input by the user and the editing description information for the image to be processed, at least one target editing instruction corresponding to the editing description information can be automatically selected, and the corresponding target editing parameters can be selected for the target editing instruction in combination with the user's historical editing operations, and the target editing instruction is executed according to the target editing parameters. Through this method, on the one hand, the corresponding editing instruction can be quickly selected for the user to improve the image editing speed; on the other hand, the target editing parameters of the target editing instruction are determined based on the user's historical editing operations, so that after the editing of the image to be processed is completed, the user's editing habits can be adapted to meet the user's editing needs.

[0057] In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following is a brief introduction to the drawings required for use in the embodiments. The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used together with the specification to illustrate the technical solutions of the present disclosure. It should be understood that the following drawings only illustrate certain embodiments of the present disclosure and should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can also be obtained based on these drawings without creative work.

[0059] Figure 1 A flowchart of an image processing method provided by an embodiment of the present disclosure is shown;

[0060] Figure 2aA schematic diagram of an interface for obtaining an image to be processed and editing description information in the image processing method provided by an embodiment of the present disclosure is shown;

[0061] Figure 2b A schematic diagram of an image editing interface in an image processing method used in an embodiment of the present disclosure is shown;

[0062] Figure 3 A schematic diagram of an image processing device provided by an embodiment of the present disclosure is shown;

[0063] Figure 4 A schematic diagram of the structure of a computer device provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical scheme and advantages of the embodiments of the present disclosure clearer, the technical scheme in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. The components of the embodiments of the present disclosure generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the present disclosure for protection, but merely represents the selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present disclosure.

[0065] With the development of image beautification technology, more and more image beautification software has appeared on the market, and each image beautification software has various beautification functions. When using image beautification software to beautify images, users need to first understand the role of beautification functions and then select appropriate beautification functions for beautification processing. However, since there are many beautification functions and the same beautification function may have different names in different beautification software, users may not be able to quickly select the appropriate beautification function for image beautification, and the image processing speed is low.

[0066] However, with the development of artificial intelligence generated content (AIGC) technology, some people have begun to use AI drawing to beautify images. For example, users may input editing requirements, and then the neural network can generate images that meet the user's editing requirements. When this method is applied to image beautification, it may not be able to adapt to the beautification habits of different users because the image is generally beautified in a fixed way, or the generated image content accounts for too large a proportion, resulting in a large difference from the original image.

[0067] Based on the above research, the present disclosure provides an image processing method, device, computer equipment and storage medium. After obtaining the image to be processed input by the user, after obtaining the image to be processed input by the user and the editing description information for the image to be processed, at least one target editing instruction corresponding to the editing description information can be automatically selected, and the corresponding target editing parameters can be selected for the target editing instruction in combination with the user's historical editing operations, and the target editing instruction is executed according to the target editing parameters. Through this method, on the one hand, the corresponding editing instruction can be quickly selected for the user to improve the image editing speed; on the other hand, the target editing parameters of the target editing instruction are determined based on the user's historical editing operations, so that after the editing of the image to be processed is completed, the user's editing habits can be adapted to meet the user's editing needs.

[0068] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0069] The term "and / or" herein only describes an association relationship, indicating that three relationships may exist. For example, A and / or B may represent the following three situations: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C may represent including any one or more elements selected from the set consisting of A, B, and C.

[0070] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0071] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0072] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0073] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0074] To facilitate understanding of the present embodiment, an image processing method disclosed in the present embodiment is first introduced in detail. The execution subject of the image processing method provided in the present embodiment is generally a computer device with certain computing capabilities, and the computer device includes, for example: a terminal device or a server or other processing device, and the terminal device can be a user equipment (User Equipment, UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. In some possible implementations, the image processing method can be implemented by a processor calling a computer-readable instruction stored in a memory.

[0075] See also Figure 1 FIG. 1 is a flowchart of an image processing method provided by an embodiment of the present disclosure, wherein the method includes steps 101 to 104, wherein:

[0076] Step 101: Obtain an image to be processed input by a user.

[0077] Step 102: Obtain editing description information set for the image to be processed.

[0078] Step 103: parse the editing description information to determine at least one target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions.

[0079] Step 104: execute the target editing instruction to process the image to be processed according to the target editing parameters corresponding to the target editing instruction to obtain a target image that conforms to the editing description information, wherein the target editing parameters corresponding to the target editing instruction are determined based on the user's historical editing operations.

[0080] The following is a detailed description of the above steps.

[0081] For step 101,

[0082] The image to be processed may refer to an image to be beautified. Exemplarily, the image to be processed may be an image containing an entity to be beautified. The entity to be beautified may be the user himself or any other entity object. Alternatively, the image to be processed may be an image such as a natural landscape that does not contain a specific entity.

[0083] The obtaining of the image to be processed input by the user may refer to receiving the image to be processed uploaded by the user, and the image to be processed may be stored locally on the user side; alternatively, the obtaining of the image to be processed input by the user may refer to obtaining the image to be processed taken by the user. For example, the method provided in the present disclosure may be applied to an application, and the user may use the "take photo" button of the application to call the camera of the device to take the image to be processed.

[0084] Here, the process of obtaining the image to be processed may be obtained after authorization by the user. The specific authorization process is described above and will not be repeated here.

[0085] For step 102,

[0086] The editing description information set for the image to be processed may refer to information for indicating how to edit the image to be processed. For example, the editing description information may be information for intuitively describing the editing effect, such as "increase the brightness of the photo", "remove the table", etc. Alternatively, the editing description information may be information for indirectly describing the editing effect, such as "edit the person in the photo to look cooler", "edit the photo to look warmer", etc. Alternatively, the editing description information may be information for describing the problems existing in the image to be processed, such as "the photo is too dark", "the face in the picture is unclear", etc.

[0087] In a possible implementation manner, the edit description information set for the image to be processed may refer to text information set for the image to be processed. For example, a first text box may be displayed on the interface for uploading the information to be processed, and the user may enter the edit description information in the second text box. In this way, the edit description information may be obtained synchronously when the image to be processed is obtained. The exemplary interface may be as follows: Figure 2a shown.

[0088] Alternatively, in another possible implementation, after acquiring the image to be processed, the image to be processed can be displayed on an image editing interface, as well as a second text box for inputting the editing description information, wherein the second text box can be a text input or a voice input; the image editing interface can also display a manual editing area, and the user can perform manual editing by triggering the manual editing area.

[0089] In this way, the user can combine the automatic editing and manual editing methods to edit the image to be processed. Figure 2b shown.

[0090] For step 103,

[0091] Different editing instructions are used to achieve different editing effects. For example, the editing instructions can be instructions for local editing, such as adding blush instructions, enlarging eyes instructions, slimming face instructions, etc.; or they can be instructions for editing the image as a whole, such as increasing picture brightness instructions, increasing image contrast instructions, etc.

[0092] The target editing instruction may refer to at least one instruction selected from a plurality of pre-set editing instructions and used to achieve the image effect described by the editing description information, or at least one instruction used to solve the image problem indicated by the editing description information.

[0093] In one possible implementation, when parsing the editing description information and determining at least one target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions, the editing description information can be input into a pre-trained instruction recognition network to determine the target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions.

[0094] The instruction recognition network may be trained in a supervised manner. Exemplarily, the specific training process may be: obtaining a sample text and an instruction label corresponding to the sample text, wherein the instruction label is used to indicate the type of instruction corresponding to the sample text; then inputting the sample text into the instruction recognition network to be trained to determine the corresponding predicted instruction; and then training the instruction recognition network to be trained based on the predicted instruction and the instruction label.

[0095] Optionally, the instruction recognition network may be a Large Language Model (LLM).

[0096] Alternatively, in another possible implementation, the editing description information is text information. When parsing the editing description information and determining at least one target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions, the keywords contained in the editing description information can be extracted, and then based on the correspondence between the pre-set keywords and the editing instructions, the target editing instruction corresponding to the editing description information among the plurality of pre-set editing instructions can be determined.

[0097] Exemplarily, if the keyword contained in the editing description information is "freckle and acne removal", the target editing instruction may be a "skin smoothing instruction"; if the keyword contained in the editing description information is "make expression more lively", the target editing instruction may be a "big eyes instruction"; if the editing description information is "look cooler", the target editing instruction may be a combination of a "slim face instruction", a "slim chin instruction", a "thin eyes instruction", and a "reduce image saturation instruction".

[0098] In another possible implementation, when determining at least one target editing instruction corresponding to the editing description information from a plurality of pre-set editing instructions, it is also possible to combine the historical editing operations of multiple users, the editing tags corresponding to the multiple historical editing operations, and the keywords contained in the editing description information.

[0099] For example, after editing an image, a user may add a text description to the edited image and publish it. In this case, the user's method of editing the image may be applied to other users.

[0100] Specifically, when a user edits an image, the user may perform multiple operations on the image, and the multiple operations performed by the user can be considered as the historical editing operations; the editing tags corresponding to the multiple historical editing operations can be determined by text descriptions associated with the image, such as the topic tags carried when the image is published.

[0101] For any edited image that meets the preset conditions, the editing tag corresponding to the image can be determined based on the text description associated with the image, and the editing operation in the editing process corresponding to the image can be stored in correspondence with the editing tag. After any user inputs editing description information, the editing description information can be matched with the editing tag, and the instruction corresponding to the editing operation stored in correspondence with the successfully matched editing tag is used as the target editing instruction.

[0102] The preset condition may exemplarily refer to that the heat value exceeds a preset value, or that the user performing the editing operation is a target user (such as a photo editing expert, etc.).

[0103] For example, if the editing description information is "the person looks cool", the keywords "person" and "cool" can be extracted from the editing description information; if a certain editing tag is "cool beauty", the instruction corresponding to the editing operation stored corresponding to the editing tag can be used as the target editing instruction.

[0104] In a possible implementation, when there are multiple editing instructions determined based on the editing description information, the target editing instruction may also be determined in combination with the user's selection.

[0105] Specifically, when there are multiple editing instructions determined based on the editing description information, instruction identifiers (for example, instruction names) for the multiple editing instructions that satisfy the editing description information can be displayed, and then in response to a selection operation on any instruction identifier, the editing instruction corresponding to the instruction identifier selected by the selection operation can be used as the target editing instruction corresponding to the editing description information.

[0106] Here, if there are multiple editing instructions determined based on the editing description information, it may be caused by an error in parsing the editing description information. Therefore, in order to improve the image editing effect, the instruction identifiers of multiple editing instructions can be displayed to the user, and the operation of determining the target editing instruction can be left to the user to select.

[0107] In another possible implementation, the multiple editing instructions determined based on the editing description information may mean that multiple editing instructions can individually satisfy the editing description information, that is, any editing instruction can satisfy the editing description information. In this case, since the image effects that can be achieved by the determined multiple editing instructions are the same, there is no need to repeatedly execute multiple editing instructions to achieve the same image effect.

[0108] For example, if the editing description information is "remove acne on the face", the editing instruction "skin resurfacing" and the editing instruction "acne removal" can both achieve the image effect described by the editing description information. Therefore, in this case, the instruction identifier of the editing instruction can be displayed, and the user can select the target editing instruction.

[0109] In another possible implementation, when there are multiple editing instructions that satisfy the same editing description information, the target editing instruction may be determined in combination with the user's historical editing records.

[0110] Specifically, you can do it through the following steps:

[0111] Step b1: Obtain the user's historical editing records.

[0112] Step b2: Determine weight information corresponding to multiple editing instructions that satisfy the editing description information based on the historical editing records.

[0113] Step b3: Integrate the multiple editing instructions based on the weight information to obtain the target editing instruction.

[0114] Here, obtaining the user's historical editing records may refer to obtaining the number of times the user executes each editing instruction; for a certain editing instruction, the more times the user uses it in the historical editing process, the image edited based on the editing instruction can better meet the user's needs.

[0115] Optionally, when determining the weight information respectively corresponding to a plurality of editing instructions satisfying the editing description information based on the historical editing records, the ratio of the number of executions of each editing instruction may be used as the weight information.

[0116] For example, if the editing instructions that satisfy the same editing description information are editing instruction A and editing instruction B, and the number of executions of editing instruction A in the historical editing records is 90 times, and the number of executions of editing instruction B in the historical editing records is 10 times, then the weight information of editing instruction A is 90%, and the weight information of editing instruction B is 10%.

[0117] When the plurality of editing instructions are integrated based on the weight information, each editing instruction may be weighted and superimposed according to the corresponding weight information. Continuing with the above example, the target editing instruction is editing instruction A*90%+editing instruction B*10%.

[0118] Here, it should be noted that the above-mentioned editing instructions are weighted and superimposed according to the corresponding weight information, which is not equivalent to the target editing strength in the target editing parameters. For any target editing instruction, its corresponding target editing strength is unique, and when a target editing instruction is obtained by superimposing multiple editing instructions, the target editing strengths of the superimposed multiple editing instructions are the same.

[0119] Continuing with the above example, if the target editing instruction is editing instruction A*90%+editing instruction B*10%, and the editing strength is 50%, then when the target editing instruction is executed, it is executed according to editing instruction A*90%*50%+editing instruction B*10%*50%.

[0120] For step 104,

[0121] The target editing parameter may refer to a relevant parameter of the target editing instruction when editing the image to be processed. Exemplarily, the target editing parameter may include a target editing position and / or a target editing strength.

[0122] The target editing position may refer to the position when the target editing instruction is executed in the image to be processed. Here, the target editing position does not refer to the specific area coordinates in the image to be processed, but refers to the type of position to be identified in the image to be processed, such as the cheek area, eyebrow area, etc.; the target editing strength may refer to the degree of execution of the target editing instruction, for example, the target editing strength when fully executed may be 100%, and the target editing strength when half executed may be 50%.

[0123] In a possible implementation, for a specific editing instruction, its target editing parameter may be set separately. For example, for the editing instruction "lipstick", its corresponding target editing parameter may include "color", and for the editing instruction "eyebrow", its corresponding target editing parameter may include "eyebrow shape", etc. The parameter types of the target editing parameters of different editing instructions may not be completely the same.

[0124] In AIGC, the editing intensity is generally the default. For example, if the editing instruction is "increase image brightness", the editing intensity is generally the default increase of N brightness values, where N is a preset positive integer; or, if the editing instruction is "add blush", the editing position is generally the cheek position.

[0125] However, different users may have different image editing needs. For example, when user A adds blush, he usually adds blush to the cheeks, while when user B adds blush, he usually adds blush to the chin and nose. If the target editing instruction is executed according to the same target editing parameters, it may not meet the personalized editing needs of the users. Therefore, based on this, the present disclosure proposes to determine the target editing parameters corresponding to the target editing instruction based on the user's historical editing operations.

[0126] In a possible implementation, when determining the target editing parameters corresponding to each editing instruction, the following steps may be performed:

[0127] Step a1: for any editing instruction, determine the initial editing parameters corresponding to the editing instruction input by the user when editing different images to be processed.

[0128] Step a2: Count the initial editing parameters to determine the target editing parameters corresponding to the editing instruction.

[0129] Here, the initial editing parameters may be of the same category as the target editing parameters, including editing position and / or editing strength.

[0130] Optionally, different pictures may be edited with different editing parameters due to different shooting scenes. For example, for the editing instruction of increasing the image brightness, if the shooting scene of the picture is bright, the adjustment force may be smaller when adjusting the image brightness; and if the shooting scene of the picture is dark, the adjustment force may be smaller when adjusting the image brightness.

[0131] Therefore, when determining the target editing parameters corresponding to each editing instruction, the editing parameters after editing can be counted. For example, for the editing instruction of image brightness, the brightness of the adjusted image can be counted, and for the editing instruction of face thinning, the size of the adjusted facial area under each depth information can be counted.

[0132] In one possible scenario, different users may have different editing needs. If the image to be processed includes multiple users at the same time, different users have different editing needs. The target editing parameters are determined according to the historical editing operations of a certain user. Then, directly editing all users according to the target editing parameters may not meet the needs of all users.

[0133] Therefore, in a possible implementation, a face identifier corresponding to the user face among the users to be processed may be identified, and then a target editing parameter corresponding to the target editing instruction under the face identifier may be determined.

[0134] Here, when determining the target editing parameters of each editing operation according to the above method, the facial identification contained in the image when each editing operation is performed can be synchronously recorded, and then when determining the target editing parameters corresponding to the target editing instructions, the target editing parameters corresponding to the target editing instructions under each facial identification can be determined.

[0135] Correspondingly, when the image to be processed includes multiple user faces, the same target editing parameter of the target editing instruction may have multiple parameter values. For example, if the target editing instruction is "add blush", then for the target editing parameter of "target editing position", there may be multiple values. For example, user A's blush needs to be added on the cheeks, and user B's blush needs to be added on the chin and the tip of the nose.

[0136] It should be noted that the above-mentioned need to distinguish facial identification is because different user faces have different requirements when editing. For editing instructions such as image brightness, image contrast, etc. that require overall adjustment of the image, they can be edited according to the target editing parameters of a certain user.

[0137] Alternatively, when determining the target editing parameters corresponding to the target editing instruction, when the target editing instruction includes a character editing instruction, the face identifier corresponding to the user's face in the image to be processed can be further identified, and then the target editing parameters corresponding to the character editing instruction under the face identifier can be determined. For non-character editing instructions, they can be directly executed according to the preset target editing parameters, or according to the target editing parameters determined based on the historical editing operations of a certain user.

[0138] In another possible implementation, when there are multiple target editing instructions corresponding to the editing description information, after executing multiple target editing instructions to process the image to be processed, a certain target editing instruction may be revoked.

[0139] Specifically, after executing multiple target editing instructions, in response to editing description information input again by the user, if it is determined that the target editing instruction corresponding to the editing description information input again is any target editing instruction executed last time, and the editing description information input again contains a negative word, the editing effect of the target editing instruction can be revoked.

[0140] For example, if the editing description information is "I want to add lipstick to a person's face and whiten it", the corresponding target editing instruction is "lipstick" + "whitening"; after executing the target editing instruction, the user can also enter "I want to remove the lipstick I just added", then the editing effect of the target editing instruction "lipstick" can be undone.

[0141] In one possible implementation, the editing description information can be executed multiple times. For example, after the user inputs the editing description information, the corresponding target editing instruction can be determined based on the above method, and the image to be processed can be processed according to the corresponding target editing parameters. After the processing is completed, the user can also input other editing description information, and based on the image to be processed that was processed last time, execute the target editing instruction corresponding to the newly input editing description information, repeat multiple times, and the final generated image is the target image.

[0142] In the above method, after obtaining the image to be processed input by the user, after obtaining the image to be processed input by the user and the editing description information for the image to be processed, at least one target editing instruction corresponding to the editing description information can be automatically selected, and the corresponding target editing parameters can be selected for the target editing instruction in combination with the user's historical editing operations, and the target editing instruction is executed according to the target editing parameters. Through this method, on the one hand, the corresponding editing instruction can be quickly selected for the user to improve the image editing speed; on the other hand, the target editing parameters of the target editing instruction are determined based on the user's historical editing operations, so that after the editing of the image to be processed is completed, the user's editing habits can be adapted to meet the user's editing needs.

[0143] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0144] Based on the same inventive concept, an image processing device corresponding to the image processing method is also provided in the embodiment of the present disclosure. Since the principle of solving the problem by the device in the embodiment of the present disclosure is similar to the above-mentioned image processing method in the embodiment of the present disclosure, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0145] Reference Figure 3 , which is a schematic diagram of the architecture of an image processing device provided by an embodiment of the present disclosure, the device comprises: a first acquisition module 301, a second acquisition module 302, a parsing module 303 and an execution module 304; wherein,

[0146] The first acquisition module 301 is used to acquire an image to be processed input by a user;

[0147] The second acquisition module 302 is used to acquire the edit description information set for the image to be processed;

[0148] A parsing module 303, configured to parse the edit description information and determine at least one target edit instruction corresponding to the edit description information among a plurality of preset edit instructions;

[0149] The execution module 304 is used to execute the target editing instruction to process the image to be processed according to the target editing parameters corresponding to the target editing instruction to obtain a target image that conforms to the editing description information, wherein the target editing parameters corresponding to the target editing instruction are determined based on the user's historical editing operations.

[0150] In a possible implementation manner, the target editing parameters include a target editing position and / or a target editing force.

[0151] In a possible implementation manner, the execution module 304 is further configured to determine the target editing parameter corresponding to each editing instruction according to the following method:

[0152] For any editing instruction, determining initial editing parameters corresponding to the editing instruction input by the user when editing different images to be processed;

[0153] The initial editing parameters are counted to determine the target editing parameters corresponding to the editing instruction.

[0154] In a possible implementation manner, when the image to be processed includes a user's face, the execution module 304 is further configured to determine the target editing parameter corresponding to the target editing instruction according to the following method:

[0155] Identify a face identifier corresponding to a user's face in the image to be processed;

[0156] Determine the target editing parameters corresponding to the target editing instruction under the face identification.

[0157] In a possible implementation, when there are multiple editing instructions determined based on the editing description information, the parsing module 303 is further configured to determine the target editing instruction corresponding to the editing description information according to the following method:

[0158] Displaying instruction identifiers of multiple editing instructions for satisfying the editing description information;

[0159] In response to a selection operation for any instruction identifier, the editing instruction corresponding to the instruction identifier selected by the selection operation is used as the target editing instruction corresponding to the editing description information.

[0160] In a possible implementation, when there are multiple editing instructions that satisfy the same editing description information, the parsing module 303 is further configured to determine the target editing instruction corresponding to the editing description information according to the following method:

[0161] Get the user's historical editing records;

[0162] Determine, based on the historical editing records, weight information corresponding to a plurality of editing instructions that satisfy the editing description information;

[0163] The plurality of editing instructions are integrated based on the weight information to obtain the target editing instruction.

[0164] In a possible implementation manner, the parsing module 303, when parsing the edit description information to determine a target edit instruction corresponding to the edit description information among the preset multiple edit instructions, is configured to:

[0165] The editing description information is input into a pre-trained instruction recognition network to determine a target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions.

[0166] In a possible implementation manner, the editing description information is text information;

[0167] The parsing module 303, when parsing the edit description information and determining a target edit instruction corresponding to the edit description information among the preset multiple edit instructions, is used to:

[0168] Extracting keywords contained in the edit description information;

[0169] Based on the correspondence between the preset keywords and the editing instructions, a target editing instruction corresponding to the editing description information is determined among the preset multiple editing instructions.

[0170] For descriptions of the processing flow of each module in the device and the interaction flow between each module, reference may be made to the relevant descriptions in the above method embodiment, which will not be described in detail here.

[0171] Based on the same technical concept, the embodiment of the present disclosure also provides a computer device. Figure 4, which is a schematic diagram of the structure of a computer device 400 provided in an embodiment of the present disclosure. The computer device in the embodiment of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc., or various forms of servers, such as independent servers or server clusters. Figure 4 The computer device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0172] like Figure 4 As shown, the computer device 400 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to a program stored in a read-only storage device (ROM) 402 or a program loaded from a storage device 405 to a random access storage device (RAM) 403. Various programs and data required for the operation of the computer device 400 are also stored in the RAM 403. The processing device 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0173] Typically, the following devices may be connected to the I / O interface 405: input devices 406 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 408 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 409. The communication devices 409 may allow the computer device 400 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 4 The computer device 400 is shown with various devices, but it should be understood that it is not required to implement or have all the devices shown. More or fewer devices may be implemented or have instead.

[0174] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing a method for recommending words. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device 409, or installed from a storage device 408, or installed from a ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0175] The present disclosure also provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the steps of the image processing method described in the above method embodiment are executed. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0176] The present disclosure also provides a computer program product that carries a program code. The program code includes instructions that can be used to execute the steps of the image processing method described in the above method embodiment. For details, please refer to the above method embodiment, which will not be repeated here.

[0177] The computer program product may be implemented in hardware, software or a combination thereof. In one optional embodiment, the computer program product is implemented as a computer storage medium. In another optional embodiment, the computer program product is implemented as a software product, such as a software development kit (SDK).

[0178] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in the present disclosure, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0179] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0180] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0181] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0182] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The protection scope of the present disclosure is not limited thereto. Although the present disclosure is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed in the present disclosure, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. An image processing method, characterized in that: include: Get the image to be processed input by the user; Obtaining editing description information set for the image to be processed; Parsing the editing description information, and determining at least one target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions; According to the target editing parameters corresponding to the target editing instruction, the target editing instruction is executed to process the image to be processed to obtain a target image that conforms to the editing description information, wherein the target editing parameters corresponding to the target editing instruction are determined based on the user's historical editing operations.

2. The method according to claim 1, characterized in that: The target editing parameters include a target editing position and / or a target editing force.

3. The method according to claim 1 or 2, characterized in that: The method further includes determining the target editing parameters corresponding to each editing instruction according to the following method: For any editing instruction, determining initial editing parameters corresponding to the editing instruction input by the user when editing different images to be processed; The initial editing parameters are counted to determine the target editing parameters corresponding to the editing instruction.

4. The method according to claim 3, characterized in that In the case where the image to be processed includes a user's face, the method further includes determining a target editing parameter corresponding to the target editing instruction according to the following method: Identify a face identifier corresponding to a user's face in the image to be processed; Determine the target editing parameters corresponding to the target editing instruction under the face identification.

5. The method according to claim 1, characterized in that In the case where there are multiple editing instructions determined based on the editing description information, the method further includes determining the target editing instruction corresponding to the editing description information according to the following method: Displaying instruction identifiers of multiple editing instructions for satisfying the editing description information; In response to a selection operation for any instruction identifier, the editing instruction corresponding to the instruction identifier selected by the selection operation is used as the target editing instruction corresponding to the editing description information.

6. The method according to claim 1, characterized in that In the case where there are multiple editing instructions that satisfy the same editing description information, the method further includes determining the target editing instruction corresponding to the editing description information according to the following method: Get the user's historical editing records; Determine, based on the historical editing records, weight information corresponding to a plurality of editing instructions that satisfy the editing description information; The plurality of editing instructions are integrated based on the weight information to obtain the target editing instruction.

7. The method according to claim 1, characterized in that The parsing of the editing description information to determine a target editing instruction corresponding to the editing description information among the preset multiple editing instructions includes: The editing description information is input into a pre-trained instruction recognition network to determine a target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions.

8. The method according to claim 1, characterized in that: The editing description information is text information; The parsing of the editing description information to determine a target editing instruction corresponding to the editing description information among the preset multiple editing instructions includes: Extracting keywords contained in the edit description information; Based on the correspondence between the preset keywords and the editing instructions, a target editing instruction corresponding to the editing description information is determined among the preset multiple editing instructions.

9. An image processing device, characterized in that: include: A first acquisition module, used to acquire an image to be processed input by a user; A second acquisition module is used to acquire the edit description information set for the image to be processed; A parsing module, used for parsing the editing description information, and determining at least one target editing instruction corresponding to the editing description information among a plurality of pre-set editing instructions; An execution module is used to execute the target editing instruction to process the image to be processed according to the target editing parameters corresponding to the target editing instruction to obtain a target image that conforms to the editing description information, wherein the target editing parameters corresponding to the target editing instruction are determined based on the user's historical editing operations.

10. A computer device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the computer device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of the image processing method according to any one of claims 1 to 8 are performed.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the image processing method according to any one of claims 1 to 8 are executed.

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