WO2023108444A1

WO2023108444A1 - Image processing method, intelligent terminal, and storage medium

Info

Publication number: WO2023108444A1
Application number: PCT/CN2021/138111
Authority: WO
Inventors: 赵伟
Original assignee: 深圳传音控股股份有限公司
Priority date: 2021-12-14
Filing date: 2021-12-14
Publication date: 2023-06-22

Abstract

The present application provides an image processing method, an intelligent terminal, and a storage medium. The method comprises: obtaining at least one image area comprised in an original image; determining a target image area in the at least one image area; and adjusting attribute information of an image in the target image area, and confirming or generating a target image corresponding to the original image. The image processing method, the intelligent terminal, and the storage medium provided by the present application are used for improving the efficiency of obtaining the target image.

Description

Image processing method, intelligent terminal and storage medium

technical field

The present application relates to the technical field of image processing, and in particular to an image processing method, an intelligent terminal and a storage medium.

Background technique

In some implementations, part of the original image can be adjusted through the smart terminal, so that the adjusted original image is updated and beautiful.

During the process of conceiving and implementing this application, the inventors found that there are at least the following problems: the operator cuts out the original image through the smart terminal according to the experience of the cutout processing, and obtains part of the original image; secondly, the operator Adjustment operation experience, adjust part of the image through the smart terminal to obtain the adjusted part of the image; finally, the operator replaces part of the original image with the adjusted part of the image through the smart terminal to obtain the target image corresponding to the original image.

In the above-mentioned related technologies, the operator performs matting processing on the original image according to matting processing experience to obtain a partial image, which makes the operation of obtaining the target image complicated, resulting in low efficiency in obtaining the target image.

The foregoing description is provided to provide general background information and does not necessarily constitute prior art.

technical solution

In view of the above technical problems, the present application provides an image processing method, an intelligent terminal and a storage medium, so as to improve the efficiency of obtaining a target image.

In a first aspect, the present application provides an image processing method, comprising the following steps:

S10: Obtain at least one image region included in the original image;

S11: Determine a target image area in at least one image area;

S12: Adjust the attribute information of the image in the target image area to confirm or generate a target image corresponding to the original image.

Optionally, step S10 includes: performing pixel detection processing on the original image through a pixel detection model to obtain labels of each pixel in the original image; and obtaining at least one image region from the original image according to the labels of each pixel.

Optionally, obtaining at least one image region from the original image according to the label of each pixel includes: partitioning the original image according to the label of each pixel to obtain at least one second image region; Each pixel has the same label; the original image is partitioned by a pixel classification model to obtain at least one first image region; at least one first image region is segmented according to at least one second image partition to obtain at least one image region .

Optionally, performing partition processing on the original image through a pixel classification model to obtain at least one first image region includes: performing image detection processing on the original image through a pixel classification model to obtain at least one image category; according to at least one image category , performing partition processing on the original image to obtain at least a first image area; the first image area is an area corresponding to an image category.

Optionally, step S11 includes: displaying edges of each image area; receiving a touch command, where the touch command includes a target position; and determining an image area corresponding to an edge surrounding the target position in at least one image area as the target image area.

Optionally, step S11 includes: displaying the edges of each image area; receiving a touch instruction on the target edge; determining an image area surrounded by the target edge in at least one image area as the target image area;

The target edge is at least one of the following:

any one of the edges of the image regions;

According to the operation track of the drawing operation of the closed area input by the user, any one of the edges of each image area is adjusted.

Optionally, displaying the edge of each image area includes: displaying the edge of each image area according to a pre-stored preset format; or receiving a selection instruction for a target format in at least one preset format, and displaying the edge of each image area according to the target format edges of each image area.

Optionally, step S12 includes: displaying at least one style adjustment parameter set, the style adjustment parameter set includes preset attribute values corresponding to at least one attribute, at least one attribute includes brightness, contrast, hue, saturation, highlight, low At least one of light and clarity; receiving a selection instruction for selecting a target style adjustment parameter set from at least one style adjustment parameter set; using the target style adjustment parameter set to adjust the attribute information of the image in the target image area, confirm or Generate the target image corresponding to the original image.

Optionally, step S12 includes: receiving an attribute adjustment instruction for the image in the target image area, the attribute adjustment instruction includes a custom attribute value corresponding to at least one attribute, and at least one attribute includes brightness, contrast, hue, saturation, At least one of high light, low light, and sharpness; set the initial value corresponding to at least one attribute included in the attribute information of the image in the target image area to the custom attribute value corresponding to at least one attribute, confirm or generate The target image corresponding to the original image.

In a second aspect, the present application provides an image processing method, comprising the following steps:

S21: determine the image to be processed in the original image;

S22: Adjust the attribute information of the image to be processed to confirm or generate a target image corresponding to the original image.

Optionally, before S21, S20: acquire an original image may also be included. This application uses S20, S21, and S22 as examples for illustration.

Optionally, step S21 includes: performing image partition processing on the original image to obtain at least one image area;

Determine a target image area in at least one image area; determine an image in the target image area as an image to be processed.

Optionally, image partition processing is performed on the original image to obtain at least one image region, including: performing pixel detection processing on the original image through a pixel detection model to obtain the label of each pixel in the original image; according to the label of each pixel, from the original Get at least one image region in the image.

Optionally, obtaining at least one image region from the original image according to the label of each pixel includes: partitioning the original image according to the label of each pixel to obtain at least one second image region; The image is partitioned to obtain at least one first image area; according to at least one second image partition, the at least one first image area is segmented to obtain at least one image area.

Optionally, determining the target image area in at least one image area includes: displaying edges of each image area; receiving a touch command, where the touch command includes the target position; area, determined as the target image area.

Optionally, determining the target image area in at least one image area includes: displaying the edges of each image area; receiving a touch instruction on the target edge; determining the image area surrounded by the target edge in at least one image area as the target image area;

The target edge is at least one of the following:

any one of the edges of the image regions;

Optionally, step S22 includes: displaying at least one style adjustment parameter set, the style adjustment parameter set includes preset attribute values corresponding to at least one attribute, at least one attribute includes brightness, contrast, hue, saturation, highlight, low At least one of light and clarity; receiving a selection instruction for selecting a target style adjustment parameter set from at least one style adjustment parameter set; using the target style adjustment parameter set to adjust the attribute information of the image in the target image area, confirm or Generate the target image corresponding to the original image.

Optionally, step S22 includes: receiving an attribute adjustment instruction of the image to be processed, the attribute adjustment instruction includes a custom attribute value corresponding to at least one attribute, and at least one attribute includes brightness, contrast, hue, saturation, highlight, low At least one of light and clarity; the initial value corresponding to at least one attribute included in the attribute information of the image to be processed is set as the custom attribute value corresponding to at least one attribute, and the target corresponding to the original image is confirmed or generated image.

In a third aspect, the present application also provides an image processing device, including: a processing module; the processing module is used for:

Obtain at least one image region included in the original image;

determining a target image area in at least one image area;

Adjust the attribute information of the image in the target image area, confirm or generate the target image corresponding to the original image.

Optionally, the processing module is specifically configured to: use a pixel detection model to perform pixel detection processing on the original image to obtain a label of each pixel in the original image; obtain at least one image region from the original image according to the label of each pixel.

Optionally, the processing module is specifically configured to: partition the original image according to the label of each pixel to obtain at least one second image area; the labels of the pixels included in the second image area are the same; through the pixel classification model, the Partition processing is performed on the original image to obtain at least one first image region; according to at least one second image partition, at least one first image region is partitioned to obtain at least one image region.

Optionally, the processing module is specifically configured to: perform image detection processing on the original image through a pixel classification model to obtain at least one image category; perform partition processing on the original image according to at least one image category to obtain at least the first image region; An image area is an area corresponding to an image category.

Optionally, the processing module is specifically configured to: control the display module to display the edge of each image area; receive a touch command, the touch command includes the target position; determine the image area corresponding to the edge surrounding the target position in at least one image area as target image area.

Optionally, the processing module is specifically configured to: control the display module to display the edges of each image area; receive a touch instruction on the target edge; determine the image area surrounded by the target edge in at least one image area as the target image area;

The target edge is at least one of the following:

any one of the edges of the image regions;

Optionally, the processing module is specifically configured to: control the display module to display the edges of each image area according to a pre-stored preset format; or, receive a selection instruction for a target format in at least one preset format, and control the display module according to the target format. The display module displays edges of each image area.

Optionally, the processing module is specifically configured to: display at least one style adjustment parameter set, the style adjustment parameter set includes preset attribute values corresponding to at least one attribute, at least one attribute includes brightness, contrast, hue, saturation, highlight At least one of , low light, and sharpness; receiving a selection instruction for selecting a target style adjustment parameter set from at least one style adjustment parameter set; using the target style adjustment parameter set to adjust the attribute information of the image in the target image area, Confirm or generate the target image corresponding to the original image.

Optionally, the processing module is specifically configured to: receive an attribute adjustment instruction for the image in the target image area, the attribute adjustment instruction includes a custom attribute value corresponding to at least one attribute, and at least one attribute includes brightness, contrast, chroma, saturation At least one of brightness, high light, low light, and clarity; set the initial value corresponding to at least one attribute included in the attribute information of the image in the target image area to the custom attribute value corresponding to at least one attribute, and confirm Or generate the target image corresponding to the original image.

In the fourth aspect, the present application also provides an image processing device, including: a processing module; the processing module is used to: acquire the original image; determine the image to be processed in the original image; adjust the attribute information of the image to be processed, and confirm or generate the original image the corresponding target image.

Optionally, the processing module is specifically configured to: perform image partition processing on the original image to obtain at least one image region;

Optionally, the processing module is specifically configured to: perform partition processing on the original image according to the label of each pixel to obtain at least one second image region; perform partition processing on the original image through a pixel classification model to obtain at least one first image region ; Perform segmentation processing on at least one first image region according to at least one second image partition to obtain at least one image region.

The target edge is at least one of the following:

any one of the edges of the image regions;

Optionally, the processing module is specifically configured to: receive an attribute adjustment instruction of the image to be processed, the attribute adjustment instruction includes a custom attribute value corresponding to at least one attribute, at least one attribute includes brightness, contrast, hue, saturation, highlight At least one of , low light, and sharpness; set the initial value corresponding to at least one attribute included in the attribute information of the image to be processed as a custom attribute value corresponding to at least one attribute, and confirm or generate the original image corresponding to target image.

In the fifth aspect, the present application also provides an intelligent terminal, which includes: a memory and a processor; optionally, an image processing program is stored in the memory, and when the image processing program is executed by the processor, the first aspect or the second aspect is realized The steps of any one of the image processing methods.

In a sixth aspect, the present application further provides a computer storage medium, a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the image processing method in any one of the above-mentioned first aspect or the second aspect are realized.

In a seventh aspect, the present application further provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of the image processing method in any one of the above-mentioned first aspect or the second aspect are implemented.

The present application provides an image processing method, an intelligent terminal, and a storage medium, the method comprising: acquiring at least one image area included in an original image; determining a target image area in at least one image area; adjusting attribute information of an image in the target image area , confirm or generate the target image corresponding to the original image. In the above method, at least one image area included in the original image is acquired; the target image area is determined in at least one image area, which can avoid matting processing on the original image, simplifies the operation of obtaining the target image area, and improves the generation target. image efficiency.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description serve to explain the principles of the application. In order to more clearly illustrate the technical solutions of the embodiments of the present application, the accompanying drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, for those of ordinary skill in the art, the Under the premise, other drawings can also be obtained based on these drawings.

FIG. 1 is a schematic diagram of a hardware structure of an intelligent terminal implementing various embodiments of the present application;

FIG. 2 is a system architecture diagram of a communication network provided by an embodiment of the present application;

Fig. 3 is a schematic diagram of the hardware structure of the controller 140 shown according to the first embodiment;

Fig. 4 is a schematic diagram of a hardware structure of a network node 150 shown according to the first embodiment;

FIG. 5 is a schematic diagram of a hardware structure of a network node 160 shown according to the first embodiment;

FIG. 6 is a schematic diagram of the hardware structure of the controller 170 shown according to the second embodiment;

FIG. 7 is a schematic diagram of a hardware structure of a network node 180 according to a second embodiment;

FIG. 8 is a schematic diagram of an application scenario provided by this application;

FIG. 9 is a flowchart of an image processing method provided by the present application;

FIG. 10 is a schematic diagram of obtaining at least one image region according to labels provided by the present application;

FIG. 11 is a schematic diagram of obtaining at least one image region according to the image category provided by the present application;

FIG. 12 is a schematic diagram of an attribute control corresponding to each attribute provided by the present application;

FIG. 13 is a flowchart of a method for acquiring at least one image area provided by the present application;

FIG. 14 is a flowchart of another image processing method provided by the present application;

FIG. 15 is a schematic structural diagram of an image processing device provided by the present application;

FIG. 16 is a schematic diagram of the hardware of the smart terminal provided by the present application.

The realization, functional features and advantages of the present application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. By means of the above drawings, specific embodiments of the present application have been shown, which will be described in more detail hereinafter. These drawings and text descriptions are not intended to limit the scope of the concept of the application in any way, but to illustrate the concept of the application for those skilled in the art by referring to specific embodiments.

Embodiment of this application

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present application as recited in the appended claims.

It should be noted that, in this document, the term "comprising", "comprising" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article or apparatus comprising a set of elements includes not only those elements, It also includes other elements not expressly listed, or elements inherent in the process, method, article, or device. Without further limitations, an element defined by the statement "comprising a..." does not exclude the presence of other identical elements in the process, method, article, or device that includes the element. In addition, different implementations of the present application Components, features, and elements with the same name in the example may have the same meaning, or may have different meanings, and the specific meaning shall be determined based on the explanation in the specific embodiment or further combined with the context in the specific embodiment.

It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, the information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this document, first information may also be called second information, and similarly, second information may also be called first information. Depending on the context, the word "if" as used herein may be interpreted as "at" or "when" or "in response to a determination". Furthermore, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It should be further understood that the terms "comprising", "comprising" indicate the presence of features, steps, operations, elements, components, items, species, and/or groups, but do not exclude one or more other features, steps, operations, elements, The existence, occurrence, or addition of components, items, categories, and/or groups. The terms "or", "and/or", "comprising at least one of" and the like used in this application may be interpreted as inclusive, or mean any one or any combination. For example, "including at least one of the following: A, B, C" means "any of the following: A; B; C; A and B; A and C; B and C; A and B and C", another example, " A, B or C" or "A, B and/or C" means "any of the following: A; B; C; A and B; A and C; B and C; A and B and C". Exceptions to this definition will only arise when combinations of elements, functions, steps or operations are inherently mutually exclusive in some way.

It should be understood that although the various steps in the flow chart in the embodiment of the present application are displayed sequentially as indicated by the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the figure may include multiple sub-steps or multiple stages, these sub-steps or stages are not necessarily executed at the same time, but may be executed at different times, and the execution order is not necessarily sequential Instead, it may be performed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

Depending on the context, the words "if", "if" as used herein may be interpreted as "at" or "when" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrases "if determined" or "if detected (the stated condition or event)" could be interpreted as "when determined" or "in response to the determination" or "when detected (the stated condition or event) )" or "in response to detection of (a stated condition or event)".

It should be noted that, in this article, step codes such as S601, S602, and S603 are used, the purpose of which is to express the corresponding content more clearly and concisely, and does not constitute a substantive limitation on the order. , it is possible to execute S603 first and then execute S601 and S602, etc., but these should be within the scope of protection of this application. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

In the following description, the use of suffixes such as 'module', 'part' or 'unit' for denoting elements is only for facilitating the description of the present application and has no specific meaning by itself. Therefore, 'module', 'part' or 'unit' may be mixedly used.

Smart terminals can be implemented in various forms. For example, the intelligent terminal described in this application can include such as smart phones, personal computers (such as tablet computers, notebook computers, palmtop computers, PDA (Personal Digital Assistant, personal digital assistant), PMP (Portable Media Player, portable media player) ), netbooks, desktop computers), cameras, video cameras, virtual reality equipment, navigation devices, wearable devices, smart bracelets, pedometers and other smart terminals, as well as fixed terminals such as digital TVs and desktop computers.

In the subsequent description, a smart terminal will be taken as an example, and those skilled in the art will understand that, in addition to elements specially used for mobile purposes, the configurations according to the embodiments of the present application can also be applied to fixed-type terminals.

Please refer to FIG. 1, which is a schematic diagram of the hardware structure of a smart terminal implementing various embodiments of the present application. The smart terminal 100 may include: an RF (Radio Frequency, radio frequency) unit 101, a WiFi module 102, an audio output unit 103, an /V (audio/video) input unit 104, sensor 105, display unit 106, user input unit 107, interface unit 108, memory 109, processor 110, and power supply 111 and other components. Those skilled in the art can understand that the smart terminal structure shown in Figure 1 does not constitute a limitation on the smart terminal, and the smart terminal may include more or less components than shown in the figure, or combine certain components, or different components layout.

The following is a specific introduction to each component of the smart terminal in conjunction with Figure 1:

The radio frequency unit 101 can be used for sending and receiving information or receiving and sending signals during a call. Specifically, after receiving the downlink information of the base station, it is processed by the processor 110; in addition, the uplink data is sent to the base station. Generally, the radio frequency unit 101 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. In addition, the radio frequency unit 101 can also communicate with the network and other devices through wireless communication. The above wireless communication can use any communication standard or protocol, including but not limited to GSM (Global System of Mobile communication, Global System for Mobile Communications), GPRS (General Packet Radio Service, General Packet Radio Service), CDMA2000 (Code Division Multiple Access 2000 , Code Division Multiple Access 2000), WCDMA (Wideband Code Division Multiple Access, Wideband Code Division Multiple Access), TD-SCDMA (Time Division-Synchronous Code Division Multiple Access, Time Division Synchronous Code Division Multiple Access), FDD-LTE (Frequency Division Duplexing-Long Term Evolution, frequency division duplex long-term evolution), TDD-LTE (Time Division Duplexing-Long Term Evolution, time-division duplex long-term evolution) and 5G, etc.

WiFi is a short-distance wireless transmission technology. Through the WiFi module 102, the smart terminal can help users send and receive emails, browse web pages, and access streaming media, etc., and it provides users with wireless broadband Internet access. Although FIG. 1 shows the WiFi module 102, it can be understood that it is not a necessary component of the smart terminal, and can be completely omitted as required without changing the essence of the present application.

The audio output unit 103 can store the information received by the radio frequency unit 101 or the WiFi module 102 or stored in the memory 109 when the smart terminal 100 is in a call signal receiving mode, a call mode, a recording mode, a voice recognition mode, a broadcast receiving mode, or the like. The audio data is converted into an audio signal and output as sound. Moreover, the audio output unit 103 may also provide audio output related to specific functions performed by the smart terminal 100 (for example, call signal receiving sound, message receiving sound, etc.). The audio output unit 103 may include a speaker, a buzzer, and the like.

The A/V input unit 104 is used to receive audio or video signals. The A/V input unit 104 may include a GPU (Graphics Processing Unit, graphics processor) 1041 and a microphone 1042, and the graphics processor 1041 is used for still pictures obtained by an image capture device (such as a camera) in video capture mode or image capture mode Video image data is processed. The processed image frames may be displayed on the display unit 106 . The image frames processed by the graphics processor 1041 may be stored in the memory 109 (or other storage media) or sent via the radio frequency unit 101 or the WiFi module 102 . The microphone 1042 can receive sound (audio data) via the microphone 1042 in a phone call mode, a recording mode, a voice recognition mode, and the like operating modes, and can process such sound as audio data. The processed audio (voice) data can be converted into a format transmittable to a mobile communication base station via the radio frequency unit 101 for output in case of a phone call mode. The microphone 1042 may implement various types of noise cancellation (or suppression) algorithms to cancel (or suppress) noise or interference generated in the process of receiving and transmitting audio signals.

The smart terminal 100 also includes at least one sensor 105, such as a light sensor, a motion sensor, and other sensors. Optionally, the light sensor includes an ambient light sensor and a proximity sensor. Optionally, the ambient light sensor can adjust the brightness of the display panel 1061 according to the brightness of the ambient light, and the proximity sensor can turn off the display when the smart terminal 100 moves to the ear. panel 1061 and/or backlight. As a kind of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in various directions (generally three axes), and can detect the magnitude and direction of gravity when it is stationary, and can be used for applications that recognize the posture of mobile phones (such as horizontal and vertical screen switching, related Games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, tap), etc.; as for mobile phones, fingerprint sensors, pressure sensors, iris sensors, molecular sensors, gyroscopes, barometers, hygrometers, Other sensors such as thermometers and infrared sensors will not be described in detail here.

The display unit 106 is used to display information input by the user or information provided to the user. The display unit 106 may include a display panel 1061, and the display panel 1061 may be configured in the form of LCD (Liquid Crystal Display, liquid crystal display), OLED (Organic Light-Emitting Diode, organic light-emitting diode), and the like.

The user input unit 107 can be used to receive input numbers or character information, and generate key signal input related to user settings and function control of the smart terminal. Optionally, the user input unit 107 may include a touch panel 1071 and other input devices 1072 . The touch panel 1071, also referred to as a touch screen, can collect touch operations of the user on or near it (for example, the user uses any suitable object or accessory such as a finger or a stylus on the touch panel 1071 or near the touch panel 1071). operation), and drive the corresponding connection device according to the preset program. The touch panel 1071 may include two parts, a touch detection device and a touch controller. Optionally, the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device and converts it into contact coordinates , and then sent to the processor 110, and can receive the command sent by the processor 110 and execute it. In addition, the touch panel 1071 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 1071 , the user input unit 107 may also include other input devices 1072 . Optionally, other input devices 1072 may include, but are not limited to, one or more of physical keyboards, function keys (such as volume control buttons, switch buttons, etc.), trackballs, mice, joysticks, etc., which are not specifically described here. limited.

Optionally, the touch panel 1071 may cover the display panel 1061. When the touch panel 1071 detects a touch operation on or near it, it transmits to the processor 110 to determine the type of the touch event, and then the processor 110 determines the touch event according to the touch event. The corresponding visual output is provided on the display panel 1061 . Although in FIG. 1, the touch panel 1071 and the display panel 1061 are used as two independent components to realize the input and output functions of the smart terminal, in some embodiments, the touch panel 1071 and the display panel 1061 can be integrated. The implementation of the input and output functions of the smart terminal is not specifically limited here.

The interface unit 108 is used as an interface through which at least one external device can be connected with the smart terminal 100 . For example, an external device may include a wired or wireless headset port, an external power (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device with an identification module, audio input/output (I/O) ports, video I/O ports, headphone ports, and more. The interface unit 108 can be used to receive input from an external device (for example, data information, power, etc.) transfer data between devices.

The memory 109 can be used to store software programs as well as various data. The memory 109 can mainly include a storage program area and a storage data area. Optionally, the storage program area can store an operating system, at least one function required application program (such as a sound playback function, an image playback function, etc.) etc.; the storage data area can be Store data (such as audio data, phone book, etc.) created according to the use of the mobile phone. In addition, the memory 109 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices.

The processor 110 is the control center of the smart terminal, and uses various interfaces and lines to connect various parts of the whole smart terminal, by running or executing software programs and/or modules stored in the memory 109, and calling data stored in the memory 109 , execute various functions of the smart terminal and process data, so as to monitor the smart terminal as a whole. The processor 110 may include one or more processing units; preferably, the processor 110 may integrate an application processor and a modem processor. Optionally, the application processor mainly processes operating systems, user interfaces, and application programs, etc. The demodulation processor mainly handles wireless communication. It can be understood that the foregoing modem processor may not be integrated into the processor 110 .

The smart terminal 100 can also include a power supply 111 (such as a battery) for supplying power to various components. Preferably, the power supply 111 can be logically connected to the processor 110 through a power management system, so as to manage charging, discharging, and power consumption through the power management system. and other functions.

Although not shown in FIG. 1 , the smart terminal 100 may also include a Bluetooth module, etc., which will not be repeated here.

In order to facilitate understanding of the embodiments of the present application, the following describes the communication network system on which the smart terminal of the present application is based.

Please refer to FIG. 2. FIG. 2 is a structure diagram of a communication network system provided by an embodiment of the present application. The communication network system is an LTE system of general mobile communication technology. ) 201, E-UTRAN (Evolved UMTS Terrestrial Radio Access Network, Evolved UMTS Terrestrial Radio Access Network) 202, EPC (Evolved Packet Core, Evolved Packet Core Network) 203 and the operator's IP service 204.

Optionally, the UE 201 may be the above-mentioned terminal 100, which will not be repeated here.

E-UTRAN 202 includes eNodeB 2021 and other eNodeB 2022 and so on. Optionally, the eNodeB 2021 can be connected to other eNodeB 2022 through a backhaul (for example, X2 interface), the eNodeB 2021 is connected to the EPC 203 , and the eNodeB 2021 can provide access from the UE 201 to the EPC 203 .

EPC203 may include MME (Mobility Management Entity, Mobility Management Entity) 2031, HSS (Home Subscriber Server, Home Subscriber Server) 2032, other MME2033, SGW (Serving Gate Way, Serving Gateway) 2034, PGW (PDN Gate Way, packet data Network Gateway) 2035 and PCRF (Policy and Charging Rules Function, Policy and Charging Functional Entity) 2036, etc. Optionally, MME2031 is a control node that processes signaling between UE201 and EPC203, and provides bearer and connection management. HSS2032 is used to provide some registers to manage functions such as home location register (not shown in the figure), and save some user-specific information about service features and data rates. All user data can be sent through SGW2034, PGW2035 can provide UE201 IP address allocation and other functions, PCRF2036 is the policy and charging control policy decision point of business data flow and IP bearer resources, it is the policy and charging execution functional unit (not shown) Select and provide available policy and charging control decisions.

The IP service 204 may include Internet, Intranet, IMS (IP Multimedia Subsystem, IP Multimedia Subsystem) or other IP services.

Although the LTE system is used as an example above, those skilled in the art should know that this application is not only applicable to the LTE system, but also applicable to other wireless communication systems, such as GSM, CDMA2000, WCDMA, TD-SCDMA and future new wireless communication systems. The network system (such as 5G), etc., is not limited here.

Based on the above hardware structure of the smart terminal and the communication network system, various embodiments of the present application are proposed.

In the related technology, firstly, the operator performs matting processing on the original image through the smart terminal according to the matting processing experience, and obtains part of the original image; secondly, the operator uses the smart terminal to process the part of the image according to the image adjustment operation experience. Adjust to obtain the adjusted part of the image; finally, the operator replaces the part of the original image with the adjusted part of the image through the smart terminal to obtain the target image corresponding to the original image. In the above-mentioned related technologies, the operator performs matting processing on the original image according to matting processing experience to obtain a partial image, which makes the operation of obtaining the target image complicated, resulting in low efficiency in obtaining the target image.

In this application, in order to improve the efficiency of obtaining the target image, the applicant provides an image processing method in this application, which converts the original image into multiple partitions, and the user can select any one of the partitions according to needs, and adjust the The attribute information of the partition is used to obtain the target image, thereby simplifying the operation of obtaining the target image and improving the efficiency of obtaining the target image.

FIG. 3 is a schematic diagram of a hardware structure of a controller 140 provided in the present application. The controller 140 includes: a memory 1401 and a processor 1402, the memory 1401 is used to store program instructions, and the processor 1402 is used to call the program instructions in the memory 1401 to execute the steps performed by the controller in the first method embodiment above, and its implementation principle and beneficial effects are similar, and will not be repeated here.

Optionally, the foregoing controller further includes a communication interface 1403 , and the communication interface 1403 may be connected to the processor 1402 through a bus 1404 . The processor 1402 can control the communication interface 1403 to implement the receiving and sending functions of the controller 140 .

FIG. 4 is a schematic diagram of a hardware structure of a network node 150 provided in the present application. The network node 150 includes: a memory 1501 and a processor 1502, the memory 1501 is used to store program instructions, and the processor 1502 is used to call the program instructions in the memory 1501 to execute the steps performed by the first node in the first method embodiment above, and its implementation principle and beneficial effects are similar, and will not be repeated here.

Optionally, the foregoing controller further includes a communication interface 1503 , and the communication interface 1503 may be connected to the processor 1502 through a bus 1504 . The processor 1502 can control the communication interface 1503 to realize the functions of receiving and sending of the network node 150 .

FIG. 5 is a schematic diagram of a hardware structure of a network node 160 provided in the present application. The network node 160 includes: a memory 1601 and a processor 1602, the memory 1601 is used to store program instructions, and the processor 1602 is used to call the program instructions in the memory 1601 to execute the steps performed by the intermediate node and the tail node in the first method embodiment above, The implementation principles and beneficial effects are similar, and will not be repeated here.

Optionally, the foregoing controller further includes a communication interface 1603 , and the communication interface 1603 may be connected to the processor 1602 through a bus 1604 . The processor 1602 can control the communication interface 1603 to realize the functions of receiving and sending of the network node 160 .

FIG. 6 is a schematic diagram of a hardware structure of a controller 170 provided in the present application. The controller 170 includes: a memory 1701 and a processor 1702, the memory 1701 is used to store program instructions, and the processor 1702 is used to call the program instructions in the memory 1701 to execute the steps performed by the controller in the second method embodiment above, and its implementation principle and beneficial effects are similar, and will not be repeated here.

FIG. 7 is a schematic diagram of a hardware structure of a network node 180 provided in the present application. The network node 180 includes: a memory 1801 and a processor 1802, the memory 1801 is used to store program instructions, and the processor 1802 is used to invoke the program instructions in the memory 1801 to execute the steps performed by the head node in the second method embodiment above, and its implementation principle and beneficial effects are similar, and will not be repeated here.

The above-mentioned integrated modules implemented in the form of software function modules can be stored in a computer-readable storage medium. The above-mentioned software function modules are stored in a storage medium, and include several instructions to enable a computer device (which may be a personal computer, server, or network device, etc.) or a processor (English: processor) to execute the methods of the various embodiments of the present application. partial steps.

In the above embodiments, all or part of them may be implemented by software, hardware, firmware or any combination thereof. When implemented using software, it may be implemented in whole or in part in the form of a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions according to the embodiments of the present application will be generated in whole or in part. A computer can be a general purpose computer, special purpose computer, computer network, or other programmable device. Computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, e.g. Coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that can be accessed by a computer, or a data storage device such as a server, a data center, etc. integrated with one or more available media. Available media may be magnetic media (eg, floppy disk, hard disk, magnetic tape), optical media (eg, DVD), or semiconductor media (eg, solid state disk, SSD), etc.

The application scenario of the image processing method provided by the present application will be described below with reference to FIG. 8 .

FIG. 8 is a schematic diagram of an application scenario provided by this application. As shown in Figure 8, it includes: an original image 11, an original image 12 including at least one image partition, and a target image 13. For example, at least one image partition includes 4 image areas, namely 1, 2, 3, and 4.

Optionally, any image region in at least one image partition may be determined as the target image partition. For example, image region 4 is determined as the target image subregion. Further, the attribute information (such as color) of the target image partition (image area 4 ) is adjusted, and the target image 13 is confirmed or generated.

In this application, the target image area is determined in at least one image area, the attribute information of the target image area is adjusted, and the target image corresponding to the original image is confirmed or generated, which can avoid matting the original image to obtain a part of the original image , which simplifies the operation of obtaining the target image area, further simplifies the operation of obtaining the target image, and improves the efficiency of obtaining the target image.

The technical solution of the present application and how the technical solution of the present application solves the above technical problems will be described in detail with specific embodiments. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below in conjunction with the accompanying drawings. The execution subject of the image processing method provided in the present application may be a smart terminal, or an image processing device installed on the smart terminal, and the image processing device may be realized by a combination of software and/or hardware. Optionally, the smart terminal may be a wired terminal or a wireless terminal. For example, the wired terminal may be a desktop computer. For example, the wireless terminal may be a device such as a tablet computer, a notebook computer, a personal digital assistant (Personal Digital Assistant, PDA for short), and a mobile phone. The software can be, for example, any kind of image editing software.

FIG. 9 is a flowchart of an image processing method provided by the present application. As shown in Figure 9, the method includes:

Optionally, the execution subject of the image processing method provided in this application may be the above-mentioned smart terminal, or an image processing device installed in the smart terminal. The image processing device may be realized by a combination of software and/or hardware. The software includes but Not limited to various image (retouching) processing software.

S201. Acquire at least one image area included in an original image.

Optionally, at least one image region may be acquired in the following two manners (modes 11 and 12).

Mode 11: Perform pixel detection processing on the original image through the pixel detection model to obtain the label of each pixel in the original image; obtain at least one image region from the original image according to the label of each pixel.

Optionally, obtaining at least one image region from the original image according to the label of each pixel includes: performing partition processing on the original image according to the label of each pixel to obtain at least one image region. Optionally, the labels of the pixels included in each image region are the same.

Optionally, the pixel detection model may be a semantic segmentation (semantic segmentation) algorithm model. The label of the pixel can be, for example, a

preset number

1, 2, 3, 4, 5 and so on.

On the basis of the above method 11, the following describes obtaining at least one image region according to pixels with reference to FIG. 10 . FIG. 10 is a schematic diagram of obtaining at least one image region according to tags provided by the present application. As shown in FIG. 10 , it includes: the original image 31 and the labels of each pixel in the original image 31 . For example the label is 1, 2, 3, 4 or 5.

Further, according to the label, the original image is partitioned to obtain at least one image region. For example, pixels labeled 1 form one image region, and pixels labeled 2 form another image region.

Optionally, when pixels corresponding to the same label are not adjacent in the original image, the label may form N image areas in the at least one image area, where N is an integer greater than or equal to 1. For example, the label 5 may form two image areas in at least one image area, and the two image areas are respectively image areas bordered by dotted lines 32 and 33 .

Mode 12: Perform image detection processing on the original image by using a pixel classification model to obtain at least one image category; perform partition processing on the original image according to the at least one image category to obtain at least one image region.

Optionally, the pixel classification model may be an instance segmentation (Instance segmentation) algorithm model.

Optionally, at least one image category may include: a person category, a sky category, an ocean category, a grass category, a road category, a tree category, a building category, a vehicle category, and the like.

On the basis of the above method 12, the method of obtaining at least one image area according to the image category will be described below with reference to FIG. 11 . FIG. 11 is a schematic diagram of obtaining at least one image area according to image categories provided by the present application. As shown in FIG. 11 , it includes: an original image 41 and at least one image category in the original image 41 .

For example, when at least one image category includes: person category, sky category, road category, tree category, building category, and vehicle category, the image categories are distinguished by different colors as shown in FIG. 11 .

Optionally, each image category may correspond to M image areas in at least one image area, where M is an integer greater than or equal to 1. For example, the vehicle class corresponds to 2 image areas in at least one image area.

S202. Determine a target image area in at least one image area.

Optionally, the target image area can be determined in the following two ways (

modes

21, 22 and 23).

Mode 21, displaying edges of each image area; receiving a touch command, where the touch command includes a target position; determining an image area corresponding to an edge surrounding the target position in at least one image area as the target image area.

For example, on the basis of FIG. 10 , when the edge surrounding the target position is a dotted line 32 , then the image area bordered by the dotted line 32 is determined as the target image area.

Mode 22, displaying the edges of each image area; receiving a touch instruction on the target edge; determining an image area surrounded by the target edge in at least one image area as the target image area.

The target edge is at least one of the following: any one of the edges of each image area; an edge adjusted to any one of the edges of each image area according to the operation track of the closed area drawing operation input by the user.

Optionally, in practical applications, if there is no image area desired by the user in at least one image area, the operation track may be input, and the image area in the original image bordered by the operation track is determined as the target image area.

Mode 23, displaying the edges of each image area; in response to canceling the display operation, canceling the display of the edges of each image area; in response to the closed area drawing operation performed in the original image, obtaining the operation track of the closed area drawing operation, and converting the original image to The image area with the operation track as the edge is determined as the target image area.

The cancel operation may be a check operation of an input through a cancel control.

Optionally, the cancel operation may also be a cancel operation on any at least one edge of the edges of each image area. Optionally, in response to the cancel operation, the edge selected by the cancel operation is canceled from display.

Optionally, the edges of the respective image regions in the foregoing

manners

21, 22 and 23 may be displayed through the following manners 30, 31 or 32.

Mode 31, displaying edges of each image area according to a pre-stored preset format. Optionally, the preset format may include displaying the line type of the edge, the color and brightness of the line type, and the like.

Way 32, receiving a selection instruction for a target format in at least one preset format, and displaying edges of each image area according to the target format.

Optionally, at least one preset format includes a line type, a color of the line type, or brightness, etc., which are different.

Optionally, the target format can also be obtained in the following manner: in response to a selection operation of at least one target linear in linear, a selection operation of target color in at least one color, and a selection operation of target brightness in at least one brightness , determine the target linearity, target color, and target brightness as the target format.

S203. Adjust the attribute information of the image in the target image area, and confirm or generate a target image corresponding to the original image.

Optionally, the target image can be confirmed or generated in the following two ways (modes 51 and 52).

Mode 51, displaying at least one style adjustment parameter set, the style adjustment parameter set includes preset attribute values corresponding to at least one attribute, at least one attribute includes brightness, contrast, hue, saturation, high light, low light, and sharpness At least one of: receiving a selection instruction for selecting a target style adjustment parameter set from at least one style adjustment parameter set; using the target style adjustment parameter set, adjusting the attribute information of the image in the target image area, confirming or generating the original image corresponding target image.

Optionally, the style may correspond to the tags or image categories involved in this application. For example, when the label is 1 (for example, indicating a person), the style is a person style; when the image category is a person category, the style is a person style.

Mode 52, receiving an attribute adjustment instruction for the image in the target image area, the attribute adjustment instruction includes a custom attribute value corresponding to at least one attribute, and at least one attribute includes brightness, contrast, hue, saturation, highlight, low light, at least one of clarity;

Set the initial value corresponding to at least one attribute included in the attribute information of the image in the target image area as the custom attribute value corresponding to at least one attribute, and confirm or generate the target image corresponding to the original image.

Optionally, receiving an attribute adjustment instruction for the image in the target image area includes: displaying attribute controls corresponding to the above attributes; receiving an attribute adjustment instruction for the image in the target image area input through each attribute control.

Optionally, in mode 52, it is possible to save the attribute adjustment instruction including the custom attribute value corresponding to at least one attribute, and set the attribute adjustment instruction including the custom attribute value corresponding to at least one attribute as one of the mode 51 A style adjustment parameter set, so that at least one style adjustment parameter set is displayed in manner 51.

FIG. 12 is a schematic diagram of displaying property controls corresponding to various properties provided by the present application. As shown in Figure 12, it includes: an attribute control 51 corresponding to brightness, an attribute control 52 corresponding to contrast, an attribute control 53 corresponding to hue, an attribute control 54 corresponding to saturation, an attribute control 55 corresponding to high light, and an attribute corresponding to low light Control 56 , property control 57 corresponding to sharpness. Exemplarily, as shown in FIG. 8 , the attribute information of the image in the target image area 4 (image 12 ) in the original image 11 is adjusted to obtain the target image 13 . Compared with the target image 13 and the original image 11, the attribute information of the image in the target image area 4 is different.

The image processing method provided by the embodiment in FIG. 9 includes: acquiring at least one image area included in the original image; determining the target image area in at least one image area; adjusting the attribute information of the image in the target image area, confirming or generating the original image corresponding target image. In the above method, at least one image area included in the original image is acquired; the target image area is determined in at least one image area, which can avoid matting processing on the original image, simplifies the operation of obtaining the target image area, and improves the generation target. image efficiency.

On the basis of the above embodiments, at least one image region included in the original image may also be obtained through the following method, specifically, please refer to FIG. 13 .

Fig. 13 is a flowchart of a method for acquiring at least one image area provided by the present application. As shown in Figure 13, the method includes:

S601. Perform pixel detection processing on the original image by using a pixel detection model to obtain a label of each pixel in the original image.

S602. Perform partition processing on the original image according to the label of each pixel to obtain at least one second image area; the labels of the pixels included in the second image area are the same.

It should be noted that the obtained at least one second image area is similar to the at least one image area shown in FIG. 10 , and the execution methods of S601 to S602 are similar to the execution method of the above-mentioned method 11, which will not be repeated here.

S603. Using the pixel classification model, perform partition processing on the original image to obtain at least one first image region.

Optionally, S603 specifically includes: performing image detection processing on the original image through a pixel classification model to obtain at least one image category; performing partition processing on the original image according to at least one image category to obtain at least a first image region; the first image A region is a region corresponding to an image category.

It should be noted that the at least one first image area is similar to the at least one image area shown in FIG. 11 , and the specific execution method of S603 is similar to the above-mentioned manner 12, which will not be repeated here.

S604. Perform segmentation processing on at least one first image region according to at least one second image partition to obtain at least one image region.

It should be noted that the image area division according to the image category will divide different images belonging to the same image category into the same image partition. As shown in FIG. 11 , for different vehicle images in the original image, different vehicle images are located in the same image partition.

Therefore, in this application, by obtaining at least one second image region according to the label of the pixel, and performing segmentation processing on at least one first image region obtained according to the image category to obtain at least one image region, different images belonging to the same image category can be Segmentation is performed to improve the accuracy of obtaining at least one image region.

FIG. 14 is a flowchart of another image processing method provided by the present application. As shown in Figure 14, the method includes:

S701. Acquire an original image.

Optionally, the original image may be a target image among multiple images stored in the smart terminal.

Optionally, the target image can be determined by the following methods:

Display multiple images stored in the smart terminal;

receiving a selection instruction for any one of the multiple images, where the selection instruction includes an identification of the image;

The image with the identifier in the multiple images is determined as the target image.

S702. Determine an image to be processed in the original image.

Optionally, the image to be processed can be determined through the following two methods (methods 31 and 32).

Mode 31, displaying the original image; obtaining the operation trajectory of the closed area drawing operation in the original image; determining the image with the operation trajectory as the edge as the image to be processed.

Obtaining an operation track of the closed area drawing operation executed in the original image includes: in response to the closed area drawing operation performed in the original image, acquiring an operation track of the closed area drawing operation.

Mode 32, perform image partition processing on the original image to obtain at least one image area; determine a target image area in the at least one image area; determine the image in the target image area as an image to be processed.

Optionally, at least one image region may be obtained through the foregoing manner 11, or the foregoing manner 12, or the method shown in the foregoing embodiment in FIG. 13 . The execution process of performing image partition processing on the original image to obtain at least one image area will not be repeated here.

Optionally, the target image area may be determined in at least one image area by using the method shown in the foregoing manner 21, or the foregoing manner 22, or the foregoing manner 23. Here, the execution process of determining the target image area in at least one image area will not be described in detail.

S703. Adjust attribute information of the image to be processed, and confirm or generate a target image corresponding to the original image.

Optionally, S703 specifically includes: receiving an attribute adjustment instruction of the image to be processed; the attribute adjustment instruction includes a custom attribute value corresponding to at least one attribute, and at least one attribute includes brightness, contrast, hue, saturation, highlight, low At least one of light and clarity; the initial value corresponding to at least one attribute included in the attribute information of the image to be processed is set as the custom attribute value corresponding to at least one attribute, and the target corresponding to the original image is confirmed or generated image.

Optionally, S703 may also be performed by a method similar to the

above manners

51 and 52, so as to confirm or generate a target image corresponding to the original image. It should be noted that, the specific process of S703 is executed by a method similar to the

above manners

51 and 52, which will not be repeated here.

The method provided by the embodiment in FIG. 14 includes: acquiring an original image; determining an image to be processed in the original image; adjusting attribute information of the image to be processed, and confirming or generating a target image corresponding to the original image. In the above method, the image to be processed is determined in the original image, which can avoid matting processing on the original image, simplifies the operation of obtaining the target image area, and improves the efficiency of generating the target image.

Different from the existing technology, in the existing camera effect tuning, there is usually a problem that the scene parameters cannot be balanced. For example, in some scenes, only one effect of the characters and the background in the image can be guaranteed. If the background is adjusted to the desired If the desired effect is desired, the effect of the character will be shifted along with it, resulting in the poor effect of the character. In this application, through the image processing method, the characters and the background can be divided into different image areas, so as to adjust the effect of the background or the characters in a targeted manner, which not only ensures the accuracy of restoring the background color, but also makes the effect of the characters good.

Optionally, the image processing method provided in this application can be used in the standard (F.AWBE) Step 2 (Step 2) illumination indicator detection to realize the positioning and segmentation of the illumination indicator.

In the standard (F.AWBE), a 24-color card is usually used as an illumination indicator, and a series of calculations are performed on the data of the four gray blocks at the bottom of the color card to determine whether the image is a uniformly illuminated image. If the requirements are not met, then judge Non-uniform illumination images are discarded. This proposal can perform post-adjustment on non-uniform illumination images that do not meet the requirements, and perform secondary detection again. If the secondary detection meets the requirements, the adjusted image will be kept in the data set to achieve data expansion. set purpose.

FIG. 15 is a schematic structural diagram of an image processing device provided by the present application. As shown in Figure 15, the image processing device 10 includes: a processing module 11; the processing module 11 is used to: obtain at least one image area included in the original image; determine the target image area in at least one image area; adjust the image in the target image area The attribute information of the original image is confirmed or generated corresponding to the target image.

The image processing device 10 provided in the present application can execute the methods in the above method embodiments, and the implementation principles and beneficial effects are similar, and will not be repeated here.

Optionally, the processing module 11 is specifically configured to: use the pixel detection model to perform pixel detection processing on the original image to obtain the label of each pixel in the original image; obtain at least one image region from the original image according to the label of each pixel.

Optionally, the processing module 11 is specifically configured to: partition the original image according to the label of each pixel to obtain at least one second image area; the labels of the pixels included in the second image area are the same; through the pixel classification model, Partition processing is performed on the original image to obtain at least one first image region; according to at least one second image partition, at least one first image region is partitioned to obtain at least one image region.

Optionally, the processing module 11 is specifically configured to: perform image detection processing on the original image through a pixel classification model to obtain at least one image category; perform partition processing on the original image according to the at least one image category to obtain at least the first image region; The first image area is an area corresponding to the image category.

Optionally, the processing module 11 is specifically configured to: control the display module 12 to display the edge of each image area; the display module 12 is included in the image processing device 10; receive a touch command, and the touch command includes a target position; convert at least one image area The image area corresponding to the edge surrounding the target position in is determined as the target image area.

Optionally, the processing module 11 is specifically configured to: control the display module 12 to display the edge of each image area; receive a touch instruction on the target edge; determine an image area surrounded by the target edge in at least one image area as the target image area.

Optionally, the processing module 11 is specifically configured to: control the display module 12 to display the edges of each image area according to a pre-stored preset format; or, receive a selection instruction for a target format in at least one preset format, , control the display module 12 to display the edge of each image area.

Optionally, the processing module 11 is specifically configured to: display at least one style adjustment parameter set, the style adjustment parameter set includes preset attribute values corresponding to at least one attribute, at least one attribute includes brightness, contrast, hue, saturation, At least one of high light, low light, and clarity; receiving a selection instruction for selecting a target style adjustment parameter set from at least one style adjustment parameter set; using the target style adjustment parameter set to adjust the attribute information of the image in the target image area , confirm or generate the target image corresponding to the original image.

Optionally, the processing module 11 is specifically configured to: receive an attribute adjustment instruction for the image in the target image area, the attribute adjustment instruction includes a custom attribute value corresponding to at least one attribute, and at least one attribute includes brightness, contrast, chroma, At least one of saturation, high light, low light, and clarity; the initial value corresponding to at least one attribute included in the attribute information of the image in the target image area is set as a custom attribute value corresponding to at least one attribute, Confirm or generate the target image corresponding to the original image.

Optionally, the processing module 11 in the image processing device 10 provided by this application can also be used to: acquire the original image; determine the image to be processed in the original image; adjust the attribute information of the image to be processed, confirm or generate the corresponding target image.

Optionally, the processing module 11 is specifically configured to: perform image partition processing on the original image to obtain at least one image area; determine a target image area in the at least one image area; determine an image in the target image area as an image to be processed.

Optionally, the processing module 11 is specifically configured to: perform partition processing on the original image according to the label of each pixel to obtain at least one second image region; perform partition processing on the original image through a pixel classification model to obtain at least one first image Regions: performing segmentation processing on at least one first image region according to at least one second image partition to obtain at least one image region.

Optionally, the processing module 11 is specifically configured to: control the display module 12 to display the edge of each image area; receive a touch command, the touch command includes the target position; and set the image area corresponding to the edge surrounding the target position in at least one image area, Determined as the target image area.

Optionally, the processing module 11 is specifically configured to: control the display module 12 to display the edges of each image area; receive a touch instruction on the target edge; determine an image area surrounded by the target edge in at least one image area as the target image area.

Optionally, the processing module 11 is specifically configured to: receive an attribute adjustment instruction of the image to be processed, the attribute adjustment instruction includes a custom attribute value corresponding to at least one attribute, and at least one attribute includes brightness, contrast, hue, saturation, At least one of high light, low light, and sharpness; the initial value corresponding to at least one attribute included in the attribute information of the image to be processed is set as a custom attribute value corresponding to at least one attribute, and the original image is confirmed or generated the corresponding target image.

FIG. 16 is a schematic diagram of the hardware of the smart terminal provided by the present application. As shown in FIG. 16 , the smart terminal 20 may include: a transceiver 21 , a memory 22 and a processor 23 . Optionally, the transceiver 21 may include: a transmitter and/or a receiver. A transmitter may also be referred to as a sender, a transmitter, a send port, or a send interface, and similar descriptions. A receiver may also be referred to as a receiver, receiver, receiving port, or receiving interface, and similar descriptions. Exemplarily, each part of the transceiver 21, the memory 22, and the processor 23 is connected to each other through a bus.

The memory 22 is used to store computer-executable instructions. The processor 23 is configured to execute the computer-executed instructions stored in the memory 22, so that the processor 23 executes the above image processing method.

An embodiment of the present application further provides a computer-readable storage medium, on which an image processing program is stored, and when the image processing program is executed by a processor, the steps of the image processing method in any of the foregoing embodiments are implemented.

In the embodiments of the smart terminal and the computer-readable storage medium provided in the embodiments of the present application, all the technical features of the above-mentioned image processing method embodiments are included, and the expansion and explanation of the description are basically the same as the above-mentioned method embodiments. I won't repeat it here.

The embodiment of the present application further provides a computer program product, the computer program product includes computer program code, and when the computer program code is run on the computer, the computer is made to execute the image processing method in the above various possible implementation manners.

The embodiment of the present application also provides a chip, including a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the device installed with the chip executes the above various possible implementation modes. image processing method.

The serial numbers of the above embodiments of the present application are for description only, and do not represent the advantages and disadvantages of the embodiments. The steps in the methods of the embodiments of the present application can be adjusted, combined and deleted according to actual needs. The units in the device in the embodiment of the present application can be combined, divided and deleted according to actual needs.

In this application, descriptions of the same or similar terms, concepts, technical solutions and/or application scenarios are generally only described in detail when they appear for the first time, and when they appear repeatedly later, for the sake of brevity, they are generally not repeated. When understanding the technical solutions and other contents of the present application, for the same or similar term concepts, technical solutions and/or application scenario descriptions that are not described in detail later, you can refer to the previous relevant detailed descriptions.

In this application, the description of each embodiment has its own emphasis. For the parts that are not detailed or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

The various technical features of the technical solution of the present application can be combined arbitrarily. For the sake of concise description, all possible combinations of the various technical features in the above-mentioned embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, all It should be regarded as the scope described in this application.

Through the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware, but in many cases the former is better implementation. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence or in other words, the part that contributes to the prior art, and the computer software product is stored in one of the above storage media (such as ROM/RAM, magnetic CD, CD), including several instructions to make a terminal device (which may be a mobile phone, computer, server, controlled terminal, or network device, etc.) execute the method of each embodiment of the present application.

In the above embodiments, all or part of them may be implemented by software, hardware, firmware or any combination thereof. When implemented using software, it may be implemented in whole or in part in the form of a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions according to the embodiments of the present application will be generated in whole or in part. The computer can be a general purpose computer, special purpose computer, a computer network, or other programmable apparatus. Computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, e.g. Coaxial cable, optical fiber, digital subscriber line) or wireless (such as infrared, wireless, microwave, etc.) to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that can be accessed by a computer, or a data storage device such as a server, a data center, etc. integrated with one or more available media. Usable media may be magnetic media, (eg, floppy disk, memory disk, magnetic tape), optical media (eg, DVD), or semiconductor media (eg, Solid State Disk (SSD)), among others.

The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structures or equivalent process transformations made by using the description of the application and the accompanying drawings are directly or indirectly used in other related technical fields. , are all included in the patent protection scope of the present application in the same way.

Claims

A kind of image processing method, wherein, comprise the following steps:

S10: Obtain at least one image region included in the original image;

S11: Determine a target image area in the at least one image area;

S12: Adjust attribute information of images in the target image area to confirm or generate a target image corresponding to the original image.
The method according to claim 1, wherein the S10 step comprises:

performing pixel detection processing on the original image to obtain the label of each pixel in the original image;

Obtain the at least one image region from the original image according to the label of each pixel.
The method according to claim 2, wherein said obtaining said at least one image region from said original image according to said labels of each pixel comprises:

Perform partition processing on the original image according to the label of each pixel to obtain at least one second image area; the labels of the pixels included in the second image area are the same;

performing partition processing on the original image through a pixel classification model to obtain at least one first image region;

According to the at least one second image partition, the at least one first image area is segmented to obtain the at least one image area.
The method according to claim 3, wherein, performing partition processing on the original image through the pixel classification model to obtain at least one first image region, comprising:

performing image detection processing on the original image through a pixel classification model to obtain at least one image category;

Partitioning the original image according to the at least one image category to obtain the at least a first image area; the first image area is an area corresponding to the image category.
The method according to any one of claims 1 to 3, wherein the S11 step comprises:

display the edges of each image area;

receiving a touch command, where the touch command includes a target position;

An image area corresponding to an edge surrounding the target position in the at least one image area is determined as the target image area.
The method according to any one of claims 1 to 3, wherein the S11 step comprises:

display the edges of each image area;

Receive touch commands on the edge of the target;

determining an image area surrounded by the target edge in the at least one image area as the target image area;

The target edge is at least one of the following:

any one of the edges of the respective image areas;

According to the operation track of the drawing operation of the closed area input by the user, any one of the edges of each image area is adjusted.
The method according to claim 5 or 6, wherein said displaying the edges of each image area comprises:

Displays the edges of each image area, according to a preset format; or,

A selection instruction for a target format in at least one preset format is received, and edges of each image area are displayed according to the target format.
The method according to any one of claims 1 to 3, wherein the S12 step comprises:

receiving an attribute adjustment instruction for an image in the target image area, where the attribute adjustment instruction includes a custom attribute value corresponding to at least one attribute;

Set the initial value corresponding to the at least one attribute included in the attribute information of the image in the target image area as the custom attribute value corresponding to the at least one attribute, and confirm or generate the target corresponding to the original image image.
A kind of image processing method, wherein, comprise the following steps:

S21: determine the image to be processed in the original image;

S22: Adjust the attribute information of the image to be processed to confirm or generate a target image corresponding to the original image.
The method according to claim 9, wherein the S21 step comprises:

performing image partition processing on the original image to obtain at least one image area;

determining a target image area in the at least one image area;

An image in the target image area is determined as the image to be processed.
The method according to any one of claims 9 to 10, wherein said determining a target image area in said at least one image area comprises:

display the edges of each image area;

receiving a touch command, where the touch command includes a target position;

determining an image area corresponding to an edge surrounding the target position in the at least one image area as the target image area, and/or;

display the edges of each image area;

Receive touch commands on the edge of the target;

determining an image area surrounded by the target edge in the at least one image area as the target image area;

The target edge is at least one of the following:

any one of the edges of the image regions;

According to the operation track of the drawing operation of the closed area input by the user, any one of the edges of each image area is adjusted.
The method according to any one of claims 9 to 10, wherein the S22 step comprises:

displaying at least one style adjustment parameter set, the style adjustment parameter set including a preset attribute value corresponding to at least one attribute;

receiving a selection instruction for selecting a target style tuning parameter set from the at least one style tuning parameter set;

Using the target style adjustment parameter set, adjust the attribute information of the image in the target image area, and confirm or generate the target image corresponding to the original image.
The method according to any one of claims 9 to 10, wherein the S22 step comprises:

receiving an attribute adjustment instruction for the image to be processed, where the attribute adjustment instruction includes a custom attribute value corresponding to at least one attribute;

The initial value corresponding to the at least one attribute included in the attribute information of the image to be processed is set as the custom attribute value corresponding to the at least one attribute, and the target image corresponding to the original image is confirmed or generated.
An intelligent terminal, wherein, the intelligent terminal includes: a memory and a processor; optionally, an image processing program is stored on the memory, and when the image processing program is executed by the processor, the following claims 1 to 1 are implemented. Steps of the image processing method described in any one of 13.
A computer-readable storage medium, wherein a computer program is stored on the readable storage medium, 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 13 are realized .