WO2019120028A1

WO2019120028A1 - Intelligent screen brightness adjustment method and apparatus, and storage medium and mobile terminal

Info

Publication number: WO2019120028A1
Application number: PCT/CN2018/116794
Authority: WO
Inventors: 陈岩; 刘耀勇
Original assignee: Oppo广东移动通信有限公司
Priority date: 2017-12-20
Filing date: 2018-11-21
Publication date: 2019-06-27
Also published as: CN109951594A

Abstract

Disclosed are an intelligent screen brightness adjustment method and apparatus, and a storage medium and a mobile terminal. The method comprises: acquiring an intensity value of ambient light, an application identifier of an application program running in the foreground, and a terminal state; when a pre-set brightness adjustment event is triggered, determining, by means of a pre-configured brightness prediction model, a target brightness value corresponding to the intensity value, the application program and the terminal state, wherein the brightness prediction model is a deep learning model trained according to a historical brightness adjustment record; and adjusting the screen brightness according to the target brightness value.

Description

Intelligent adjustment method, device, storage medium and mobile terminal for screen brightness

The present application claims the priority of the Chinese Patent Application No. PCT Application No.

Technical field

The embodiment of the present invention relates to a mobile terminal technology, for example, to an intelligent adjustment method, device, storage medium, and mobile terminal for screen brightness.

Background technique

At present, mobile terminals are increasingly used in life, and users are staring at the screen of the mobile terminal for a long time. If the brightness of the screen is not suitable, the user's eyes will be stimulated. In order to solve the problem, the current mobile terminal can automatically adjust the brightness of the screen according to the ambient light intensity. However, the screen brightness adjustment scheme provided in the related art has defects, and cannot meet the actual requirements of the screen brightness of the mobile terminal user. Manual adjustments are made on the basis of automatic adjustment to achieve the desired brightness effect, which limits the intelligence of the screen brightness adjustment.

Summary of the invention

The embodiment of the present invention provides an intelligent adjustment method, device, storage medium, and mobile terminal for screen brightness, which can optimize the adjustment scheme of the screen brightness in the related technology, and improve the intelligence of the mobile terminal.

In a first aspect, an embodiment of the present application provides an intelligent adjustment method for screen brightness, including: acquiring an intensity value of ambient light, an application identifier of an application running in a foreground, and a terminal state; when a preset brightness adjustment event is triggered. Determining, by a pre-configured brightness prediction model, a target brightness value corresponding to the intensity value, an application, and a terminal state, wherein the brightness prediction model is a deep learning model based on historical brightness adjustment recording training; and according to the target The brightness value adjusts the screen brightness.

In a second aspect, the embodiment of the present application further provides an intelligent adjusting device for screen brightness, the device comprising: a state acquiring module, configured to acquire an intensity value of ambient light, an application identifier of an application running in a foreground, and a terminal state; a value determining module, configured to determine, by a pre-configured brightness prediction model, a target brightness value corresponding to the intensity value, an application, and a terminal state, when the preset brightness adjustment event is triggered, wherein the brightness prediction model is A depth learning model for recording training according to historical brightness adjustment; and a brightness adjustment module configured to adjust the brightness of the screen according to the target brightness value.

In a third aspect, the embodiment of the present application further provides a computer readable storage medium, where the computer program is stored, and when the program is executed by the processor, the smart adjustment method of the screen brightness as described in the first aspect above is implemented.

In a fourth aspect, the embodiment of the present application further provides a mobile terminal, including a memory, a processor, and a computer program stored in the memory and executable by the processor, where the processor executes the computer program as described above An intelligent adjustment method for screen brightness as described on the one hand.

An embodiment of the present application provides an intelligent adjustment scheme for screen brightness, which obtains an intensity value of ambient light, an application identifier of an application running in the foreground, and a terminal state; and when a preset brightness adjustment event is triggered, the preset brightness is adopted. The prediction model determines a target brightness value corresponding to the intensity value, the application, and the terminal state, and adjusts the screen brightness according to the target brightness value, and implements a historical brightness adjustment record based on the state of the user currently using the terminal, and analyzes the user preference. The target brightness value, and automatically adjusts the screen brightness based on the target brightness value, and the adjustment result is more in line with the user's actual experience requirements. The above technical solution solves the problem that the adjustment result of the screen brightness adjustment scheme in the related art is inconsistent with the user's expectation of brightness, resulting in multiple adjustments, and improves the intelligence of the mobile terminal in adjusting the brightness of the screen.

DRAWINGS

FIG. 1 is a flowchart of a method for intelligently adjusting screen brightness according to an embodiment of the present application.

FIG. 2 is a flowchart of another method for intelligently adjusting screen brightness according to an embodiment of the present application.

FIG. 3 is a structural block diagram of an intelligent adjusting device for screen brightness according to an embodiment of the present application.

FIG. 4 is a structural block diagram of a mobile terminal according to an embodiment of the present application.

FIG. 5 is a structural block diagram of a smart phone according to an embodiment of the present application.

Detailed ways

The present application will be described in conjunction with the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting. In addition, it should be noted that, for the convenience of description, only some but not all of the structures related to the present application are shown in the drawings.

It should be noted that prior to discussing the exemplary embodiments, some exemplary embodiments are described as a process or method depicted as a flowchart. Although the flowchart depicts multiple steps as a sequential process, many of the steps can be implemented in parallel, concurrently, or concurrently. In addition, the order of the multiple steps can be rearranged. The process may be terminated when its operation is completed, but may also have additional steps not included in the figures. The processing may correspond to methods, functions, procedures, subroutines, subroutines, and the like.

It should be noted that the brightness prediction model is a deep learning model based on the historical brightness adjustment record training of the mobile terminal user. Exemplarily, the number of hidden layers and the number of nodes of each layer of the input layer, the hidden layer and the output layer may be preset, and the first parameter of the deep neural network is initialized, wherein the first parameter includes the offset value and the edge of each layer. The weight of the initial, deep learning model. Then, using the sample set corresponding to the historical brightness adjustment record, the deep learning model is trained in two stages of forward propagation and backward propagation; when the error calculated by the backward propagation training reaches the expected error value, the training ends and is obtained. Brightness prediction model. Since the brightness prediction model is learned by the mobile terminal user's large number of historical screen brightness adjustment operations and adjustment operations, the foreground function is learned, thereby learning the screen brightness according to the user's preference, and improving the current based on the current The state predicts the accuracy of the screen brightness. When the brightness adjustment event is satisfied, the current ambient light intensity value, the current running application in the foreground, and the historical adjustment record of the screen backlight brightness are integrated, and the screen brightness parameter suitable for the current scene is obtained through artificial intelligence technology analysis.

It should be noted that, in the embodiment of the present application, network parameters such as the number of layers of the neural network model, the number of neurons, the convolution kernel, and/or the weight are not limited.

It should be noted that the construction of the brightness prediction model may be performed by the mobile terminal, and the implementation of the model construction operation is not limited in this embodiment.

The source of the sample set is the relevant data of the mobile terminal user when performing the screen brightness adjustment operation. Each time the user performs screen brightness adjustment, the mobile terminal records and records the following information as a historical brightness adjustment record: the current ambient light intensity value (which can also be recorded as light intensity), the application running in the foreground, and the screen adjustment operation before the operation. The first screen brightness, the system time for performing the screen brightness adjustment operation (may be referred to simply as the adjustment time), the current network environment status (which may be the network identification), and the second screen brightness after performing the screen adjustment operation. The network identifier may be a name of a network accessed by the mobile terminal, including but not limited to the name of the accessed WIFI (Wireless Fidelity). It should be noted that the above adjustment time may select a time to start the screen brightness adjustment operation, or select a time when the screen brightness adjustment operation is completed, or select an intermediate time between the start time and the end time of the screen brightness adjustment operation. The mobile terminal can store the above historical brightness adjustment record in the form of a data table. The data table is stored in a mobile terminal database.

Table 1 Historical brightness adjustment record

光强Light intensity	应用程序application	第一屏幕亮度First screen brightness	调节时间Adjustment time	网络标识Network identification	第二屏幕亮度Second screen brightness
300300	QQQQ	20％最大亮度20% maximum brightness	14975906954691497590695469	SSID1SSID1	30％最大亮度30% maximum brightness
500500	微信WeChat	40％最大亮度40% maximum brightness	14976091079221497609107922	SSID2SSID2	50％最大亮度50% maximum brightness
......	......	......	......	......	......

It should be noted that one row of data in the above table may be used as a piece of sample data, and the features listed in the above table include the intensity value of the current ambient light (corresponding to the light intensity in the table), the application program, and the operation before the screen brightness adjustment operation is performed. First screen brightness, time to perform screen brightness adjustment operation (corresponding to adjustment time in the table), network identification of access network (may be SSID, Service Set Identifier, service set identifier, indicating WIFI name) and performing screen brightness adjustment operation The second screen brightness after the second, but the historical brightness adjustment record is not limited to the above features, and features such as remaining power and/or position information may be increased according to actual needs of the model construction. In addition, the adjustment time in Table 1 above can be converted into the year, month, day, hour, minute, and second format. For example, 1497590695469 is converted to year, month, day, hour, minute and second format as 2017/6/16 13:24:55.

It can be understood that the data in the above table needs to be preprocessed to obtain a sample matrix, and the sample matrix is trained to construct a brightness prediction model. In the embodiment of the present application, the pre-processing may be:

The program number of the application in the mobile terminal is matched according to a preset rule, and the application includes all applications (ie, APPs) installed by the user in the mobile terminal, and each application is given a non-repeating number. Assume that the application installed by the user includes QQ, WeChat, Today's headline, Weibo, etc., and each application is assigned a program number, that is, the APP ID, and the application is replaced by the APP ID. For example, the program number assigned to QQ is 0, the program number assigned to WeChat is 1, and the program number assigned to today's headlines is 2, ....., and the maximum number of program numbers depends on the number of applications installed by the user. Optionally, it may also be numbered based on the application described in Table 1, that is, multiple non-repeating applications appearing in Table 1 are respectively assigned non-repeating numbers, as the program number, the maximum number of the program number depends on the table. The number of applications in 1.

Matching the network ID of the network identifier of the mobile terminal according to the preset rule, where the network identifier includes, but is not limited to, the SSID information of the WIFI that is recorded by the mobile terminal in the background (also can be understood as the name of all the used WIFIs of the user). Each SSID is given a number that does not overlap. It can be understood that the network number u ∈ [0, 1, 2...], the maximum network number depends on how many different WIFIs the mobile terminal has accessed in total. Optionally, the number may be numbered according to the SSID of the WIFI accessed by the mobile terminal described in Table 1, and the different SSIDs appearing in Table 1 are assigned non-repeating numbers as the network number, and the maximum network number depends on Table 1. How many different SSIDs have appeared.

The 24-hour natural day is divided into several time periods in advance. For example, if the interval is 1 hour, then a natural day has 24 time periods of 24 hours, and 24 time segments are sequentially numbered. The time number corresponding to the access time is t∈[0,1,2,3.. .23], that is, the screen brightness adjustment operation detected between 0:00 am and 1 am is given time number 0, and the screen brightness adjustment operation detected between 1 am and 2 am is given time number 1. ..... gives the time number 23 for the screen brightness adjustment operation detected between 23 o'clock and 24 o'clock. Thereby, the time number is determined according to the time period to which the adjustment time belongs. For example, when the mobile terminal detects that QQ is running in the foreground, the user inputs a brightness adjustment indication, and the adjustment time of the adjustment operation is 13:24:55, and it can be determined that the time number corresponding to the adjustment time is 13.

It can be understood that, since the user cannot use the mobile terminal 24 hours a day, the time interval in which the user uses the mobile terminal can be divided according to the usage habit of the user. For example, if the user is in a sleep state between 12 am and 6 am, and the mobile terminal is not used, the time interval outside the rest time interval can be divided to obtain a time period.

The feature set is composed of the intensity value of the ambient light, the program number, the time number, the first screen brightness value and the network number, and the second screen brightness value constitutes a set of expected results, and the feature set and the expected result set form a sample set for use. The supervised learning method trains the pre-designed deep learning network through the sample set to form a brightness prediction model. Illustratively, the maximum brightness is the maximum screen brightness, which is related to the screen attributes. If the maximum brightness is represented by I _max , the data of Table 1 is preprocessed according to the above method, and the following sample set table is obtained.

Table 2 Sample Collection Table

光强Light intensity	应用程序application	第一屏幕亮度First screen brightness	调节时间Adjustment time	网络标识Network identification	第二屏幕亮度Second screen brightness
300300	00	20％I _max 20% I _max	1313	00	30％I _max 30% I _max
500500	11	40％I _max 40% I _max	1313	11	50％I _max 50% I _max
......	......	......	......	......	......

The sample matrix D corresponding to the sample set table described in Table 2 is:

The sample set table and the sample matrix do not enumerate all historical brightness adjustment records, and the ellipsis represents the omitted historical brightness adjustment record.

FIG. 1 is a flowchart of a method for intelligently adjusting screen brightness according to an embodiment of the present application. The method can be performed by an intelligent adjustment device for screen brightness, wherein the device can be implemented by software and/or hardware, and can generally be integrated in a mobile terminal. As shown in FIG. 1, the method includes: Step 110 - Step 130.

In step 110, the intensity value of the ambient light, the application identifier of the application running in the foreground, and the terminal status are acquired.

It should be noted that the intensity value of the ambient light in the embodiment of the present application is a value indicating that the ambient light intensity is weak. This value can be acquired by a setting sensor built into the mobile terminal. Wherein, the setting sensor includes but is not limited to an ambient light sensor. For example, the intensity value of the ambient light is acquired by the ambient light sensor at a set sampling interval. According to the intensity value, it can be determined whether the preset brightness adjustment event is triggered.

Illustratively, determining whether the preset brightness adjustment event in the mobile terminal is triggered according to the first intensity value collected by the current sampling time setting sensor and the second intensity value collected by the previous sampling time setting sensor. The manner of determining whether the preset brightness adjustment event is triggered may be: using the value output by the ambient light sensor at the current sampling time as the first intensity value of the current sampling time. Reading a second intensity value output by the ambient light sensor at the last sampling time in the set storage space, calculating a deviation amount between the first intensity value and the second intensity value; determining the brightness when the deviation amount exceeds the set threshold The adjustment event is triggered. It can be understood that the setting threshold may be the system default, or may be set by the user according to actual needs, and the setting threshold is used to determine whether to trigger the execution of the screen brightness adjustment event.

When it is determined that the preset brightness adjustment event is triggered, the application identifier of the application running in the foreground is obtained to determine which application is running in the foreground. And obtaining the current system time, the current brightness value of the screen, and the network identifier as the terminal status, where the network identifier is a name (may be an SSID) of the wireless network accessed by the terminal. When it is determined that the preset brightness adjustment event is not triggered, the value output by the ambient light sensor is obtained according to the set sampling interval, and the application identifier of the application running in the foreground and the current terminal state are not obtained, so as to reduce the occupation of the detection data. The storage space of the mobile terminal.

It can be understood that the application running in the foreground refers to an application displayed in the display interface of the mobile terminal, and the user can operate the application running in the foreground. For example, the application A, the application B, and the application C are simultaneously run in the mobile terminal, wherein only the application A is the application displayed in the current mobile terminal display interface, and the application A can be determined to be running in the foreground. The application, application B and application C are determined to be running applications in the background. It should be noted that the application identifier is a character that can uniquely determine the application, including but not limited to the application package name, the application's username (UID), or the application's process name (PID).

Generally, the terminal may be a mobile terminal equipped with an operating system, including but not limited to a smart phone, a tablet computer, a handheld game console, a notebook computer, and a smart watch. It should be noted that the terminal status includes at least one of a network identifier, a brightness value before the screen brightness adjustment operation (ie, a current screen brightness value), a current system time, a remaining power amount, and location information. In the embodiment of the present application, the current terminal status includes the current WIFI SSID, the current system time, and the current screen brightness value.

In step 120, when the preset brightness adjustment event is triggered, the target brightness value corresponding to the intensity value, the application, and the terminal state is determined by the pre-configured brightness prediction model.

It should be noted that the brightness prediction model is a deep learning model based on historical brightness adjustment recording training. The construction method of the brightness prediction model may be implemented in the manner described in the embodiments of the present application, or may be constructed in other manners, which is not limited herein.

In the embodiment of the present application, the application, the system time, and the SSID of the time when the brightness adjustment event is triggered are preprocessed to meet the input requirement of the brightness preset model, and the intensity value, the application program, the system time, and the ambient light are obtained. A model input record of the SSID and the current screen brightness value (may also be considered as the state of the terminal currently used by the user, including the status of the terminal itself, usage, ambient light conditions, etc.). The method for pre-processing the application, the system time, and the SSID includes: matching the program number a of the current foreground running application according to the preset first rule, and a∈[0, 1, 2...] Matching the network number u of the SSID according to the preset second rule, and u∈[0,1,2...]; according to the above description, it is known that the preset time interval in the natural day is equally divided to obtain the time period, The time segment is associated with the time number and stored in the whitelist. The whitelist is queried according to the time period to which the current system time belongs, and the time number corresponding to the time segment is determined. The intensity value, the program number, the time number, the current brightness value of the screen, and the network number are input to a pre-configured brightness prediction model to calculate a target brightness value by the brightness prediction model.

In step 130, the screen brightness is adjusted according to the target brightness value.

In the embodiment of the present application, adjusting the brightness of the screen according to the target brightness value may directly replace the current brightness value of the screen by using the target brightness value. However, the adjustment method here is relatively blunt, and if the target brightness value differs greatly from the current brightness value, direct replacement may result in poor user experience. Optionally, a preset number of intermediate values may be set between the target brightness value and the current brightness value to avoid a situation in which the brightness of the screen suddenly jumps to make the human eye feel uncomfortable. For example, calculating a difference between the target brightness value and the current brightness value; when the difference exceeds the set adjustment interval value, dividing the difference into at least two value intervals according to a brightness deviation from the target brightness value; The numerical interval is used to smoothly adjust the screen brightness. Optionally, the at least two value intervals may be a result of equally dividing the interval between the current brightness value and the target brightness value. It is also possible to adjust the current brightness away from the target brightness value with a small value change according to actual needs, and increase the value change amount when approaching the target brightness value. For example, if the target brightness value is 500 and the current brightness value is 400, it can be determined that the difference between the target brightness value and the current brightness value is 100, and the difference can be divided into 4 parts to set the screen brightness every set time interval. The value is increased by 25 to gradually adjust the current brightness value to reach the target brightness value. Optionally, a change adjustment strategy may be set according to actual needs, for example, before the current brightness value reaches 460, the screen brightness is increased by 10 every set time interval, after the current brightness reaches 460, Adjust the screen brightness by 20 in the set time interval.

The technical solution of the embodiment obtains the intensity value of the ambient light, the application identifier of the application running in the foreground, and the terminal state; when the preset brightness adjustment event is triggered, the brightness value is determined by the pre-configured brightness prediction model. The target brightness value corresponding to the application and the terminal state is adjusted according to the target brightness value, and the historical brightness adjustment record based on the user's current use terminal state is combined with the user's historical brightness adjustment record, and the target brightness value of the user preference is analyzed, and based on The target brightness value automatically adjusts the screen brightness, and the adjustment result is more in line with the user's actual experience requirements. The above technical solution solves the problem that the adjustment result of the screen brightness adjustment scheme in the related art is inconsistent with the user's expectation of brightness, resulting in multiple adjustments, and improves the intelligence of the mobile terminal in adjusting the brightness of the screen.

FIG. 2 is a flowchart of another method for intelligently adjusting screen brightness according to an embodiment of the present application. As shown in FIG. 2, the method includes: Step 201 - Step 212.

In step 201, the acquired value of the ambient light sensor is used as the intensity value of the ambient light according to the set sampling interval.

It can be understood that there are many ways to obtain the intensity value of the ambient light. It is not limited to the above-listed acquisition by the ambient light sensor. It is also possible to capture an image of the external environment through the camera and analyze the image to obtain the intensity value of the ambient light. and many more.

In step 202, it is determined whether the preset brightness adjustment event is triggered according to the intensity value of the ambient light. If the brightness adjustment event is triggered, step 203 is performed; if the brightness adjustment event is not triggered, return to step 201.

In the embodiment of the present application, calculating a deviation between a first intensity value collected by the ambient light sensor acquired at the current sampling time and a second intensity value acquired by the ambient light sensor acquired at the previous sampling time; where the deviation amount is greater than or equal to When the threshold is determined, step 203 is performed; when the deviation value is less than the set threshold, step 201 is performed.

Optionally, the current system time may also be obtained, and the time interval between the current system time and the time of the last screen brightness adjustment operation may be determined. When the time interval exceeds the set time threshold, the brightness adjustment event may also be triggered. It should be noted that, each time the screen brightness adjustment operation is completed, the start timer starts timing to record the time interval between the current time and the time of the last screen brightness adjustment operation. The time threshold may be set by the system or set by the user according to actual needs, and is used to trigger a brightness adjustment event. For example, the set time interval may be 1 hour, the reading of the timer is obtained, and it is determined whether the time interval exceeds 1 hour. When the timer reaches the preset time threshold, the control timer is cleared to re-time after the screen brightness adjustment operation is completed.

In step 203, the application identifier of the application running in the foreground is obtained, and the system time, the current brightness value of the screen, and the network identifier are obtained as the terminal status.

In step 204, the program number of the application is matched according to a preset first rule.

It should be noted that the first rule may be to assign different numbers to different applications installed in the mobile terminal as program numbers.

In step 205, the network number of the network identifier is matched according to a preset second rule.

It should be noted that the second rule may be to assign different numbers to the SSIDs of different WIFIs accessed by the mobile terminal as the network number.

In step 206, the time number is determined according to the time period to which the system time belongs.

In step 207, the intensity value, the program number, the time number, the current brightness value of the screen, and the network number are input to the pre-configured brightness prediction model.

In step 208, a target brightness value output by the brightness prediction model is acquired, and a difference between the current brightness value and the target brightness value is calculated.

In step 209, it is determined whether the difference exceeds the set adjustment interval value. If the set adjustment interval value is exceeded, step 210 is performed; if the set adjustment interval value is not exceeded, step 211 is performed.

It should be noted that the above adjustment interval value may be analyzed and determined according to the screen brightness history adjustment record of a large number of user groups. For example, after the operation of adjusting the brightness from the current brightness to the target brightness value, the user manually adjusts the brightness of the screen, and it is considered that the brightness deviation between the current brightness value and the target brightness value is larger in the current screen brightness adjustment operation, according to the Regularity, analyze the screen brightness history adjustment record, and determine the setting adjustment interval value.

In step 210, the difference is divided into at least two numerical intervals according to the deviation of the real-time luminance value acquired during the screen brightness adjustment process from the target luminance value, and the screen brightness is smoothly adjusted according to the numerical interval.

It should be noted that the above numerical interval may be divided according to the numerical interval corresponding to the difference. The dividing basis may further be that, during the screen brightness adjustment process, the value interval corresponding to the difference is divided into at least two numerical intervals according to the deviation between the real-time acquired screen brightness value and the target brightness value. For example, in the screen brightness adjustment process, the screen brightness is acquired in real time (hereinafter referred to as the real-time screen brightness), and when the real-time screen brightness is far from the target brightness value, the smaller value interval is used for smooth adjustment, in the real-time screen. When the brightness is closer to the target brightness value, the brightness is adjusted using a larger value interval. For example, the target brightness value is 500, the current screen brightness is 400, and a threshold value is set to 460. When the real-time screen brightness is less than the threshold value 460 during the adjustment process, it is determined that the real-time screen brightness is far from the target brightness value, and the first A numerical interval (such as a numerical interval of 10) adjusts the brightness of the screen. After adjusting 6 times, the real-time screen brightness 460 is equal to the threshold value, and it is determined that the real-time screen brightness is closer to the target brightness value, and the second numerical interval (such as the numerical interval is 20) is used to adjust the screen brightness, and after adjusting 2 times, the screen is adjusted. The brightness reaches the target brightness value.

It should be noted that after the execution of this step is completed, step 212 is performed.

In step 211, the current brightness value is replaced with the target brightness value.

It can be understood that, since the difference between the target brightness value and the current brightness value is not large, the screen brightness can be adjusted by using a direct replacement method. After the step is performed, step 212 is performed.

In step 212, a target image brightness value corresponding to the target brightness value is acquired, and a brightness of the current display content is adjusted according to the target image brightness value.

It can be understood that in some scenarios, the factor that affects the user's perception of the screen is not only the brightness of the screen, but also the content displayed on the screen affects the viewing experience of the user. With this in mind, a set number of user groups are collected for the historical setting operation of the screen brightness and the brightness of the image displayed on the screen, and the above-mentioned history setting operation is analyzed by using data analysis means to obtain the brightness of the display image matching the screen brightness. And pre-configured in the mobile terminal. For example, the correspondence between the above screen brightness and the image brightness may be stored in the form of a white list.

In the embodiment of the present application, after acquiring the target brightness value, the white list is queried according to the target brightness value, the corresponding image brightness value is determined, and the brightness of the current display content is adjusted according to the image brightness value.

It should be noted that when the deviation between the current image brightness value and the target image brightness value is large (for example, the difference between the current image brightness value and the target image brightness value is greater than the image brightness adjustment interval value), it may be adjusted according to the brightness adjustment process. Deviating the real-time image brightness value from the target image brightness value, the difference interval (the range of the difference between the current image brightness value and the target image brightness value) is divided into at least two sub-intervals, and the image brightness is smoothly adjusted according to the sub-interval, The image brightness adjustment process for realizing the display content is adapted to the smoothness of the screen brightness. For example, the target image brightness value is 800, the current image brightness value is 600, and the image brightness adjustment interval value is 150. The difference between the current image brightness value and the target image brightness value is 200, which is greater than the image brightness adjustment interval value, and the deviation between the current image brightness value and the target image brightness value is considered to be large. In the image brightness adjustment process, when a threshold value is set to 750 and the real-time image brightness is less than the threshold value 750, it is determined that the real-time image brightness is far from the target image brightness value, and the first numerical interval (eg, the numerical interval is 20) is used. The screen brightness is adjusted. After adjusting 8 times, if the real-time screen brightness 760 is greater than the threshold value, it is determined that the real-time image brightness is closer to the target image brightness value, and the second numerical value interval (such as the numerical interval is 40) is used to adjust the image brightness, and after adjusting once, The image brightness reaches the target image brightness value.

It should be noted that this step is not a necessary step of the embodiment of the present application, that is, the step 212 may or may not be performed. Meanwhile, the execution order of step 212 is not limited to the case described in the embodiment of the present application, and step 212 may be performed after determining the target brightness value.

In the technical solution of the embodiment, by acquiring the target image brightness value corresponding to the target brightness value, and adjusting the brightness of the current display content according to the target image brightness value, adjusting the brightness of the display content in addition to adjusting the brightness of the screen, Good to meet the user's feelings, effectively avoiding adjusting the screen brightness multiple times and improving the execution efficiency of the mobile terminal.

FIG. 3 is a structural block diagram of an intelligent adjusting device for screen brightness according to an embodiment of the present application. The device may be implemented by software and/or hardware, and may be integrated into the mobile terminal for performing an intelligent adjustment method of the screen brightness provided by the embodiment of the present application. As shown in FIG. 3, the device includes a state acquisition module 310, a target value determination module 320, and a brightness adjustment module 330.

The state obtaining module 310 is configured to acquire an intensity value of the ambient light, an application identifier of the application running in the foreground, and a terminal state.

The target value determining module 320 is configured to determine a target brightness value corresponding to the intensity value, an application, and a terminal state by a pre-configured brightness prediction model when the preset brightness adjustment event is triggered, wherein the brightness prediction model A deep learning model for training training is adjusted according to historical brightness.

The brightness adjustment module 330 is configured to adjust the brightness of the screen according to the target brightness value.

The technical solution of the embodiment provides an intelligent adjusting device for screen brightness, which realizes the historical brightness adjustment record based on the user's current use state combined with the user, analyzes the target brightness value preferred by the user, and automatically adjusts the screen brightness based on the target brightness value. Adjustment, and the adjustment results are more in line with the user's actual experience requirements. The above technical solution solves the problem that the adjustment result of the screen brightness adjustment scheme in the related art is inconsistent with the user's expectation of brightness, resulting in multiple adjustments, and improves the intelligence of the mobile terminal in adjusting the brightness of the screen.

Optionally, the state obtaining module 310 is further configured to obtain, according to the set sampling interval, a value output by the ambient light sensor as an intensity value of the ambient light;

The screen brightness intelligent adjusting device further includes: an event determining module.

After the state acquisition module acquires the intensity value of the ambient light, the event determination module is configured to determine whether the preset brightness adjustment event is triggered according to the intensity value.

Optionally, the event determining module is further configured to calculate a deviation amount between the first intensity value corresponding to the current sampling time and the second intensity value corresponding to the previous sampling time; and determine the brightness adjustment when the deviation exceeds the set threshold The event is triggered.

Optionally, the state obtaining module 310 is further configured to: when the brightness adjustment event is triggered, acquire an application identifier of an application running in the foreground, and obtain a system time, a current brightness value of the screen, and a network identifier as a terminal state, where The network identifier is the name of the wireless network accessed by the terminal.

Optionally, the screen brightness intelligent adjusting device further includes: a preprocessing module and a model input module.

After the state obtaining module obtains the intensity value of the ambient light, the application identifier of the application running in the foreground, and the terminal state, the pre-processing module is configured to match the program number of the application according to the preset first rule; according to the preset second rule Matching the network number of the network identifier; determining a time number according to the time period to which the system time belongs, wherein the time period is obtained by equally dividing the preset time interval in the natural day, and the time period is stored in association with the time number;

The model input module is configured to input the intensity value, the program number, the time number, the current brightness value of the screen, and the network number into a pre-configured brightness prediction model.

Optionally, the brightness adjustment module 330 is further configured to calculate a difference between the current brightness value and the target brightness value; and when the difference exceeds the set adjustment interval value, according to a brightness deviation from the target brightness value The difference is divided into at least two numerical intervals; and the screen brightness is smoothly adjusted according to the numerical interval. When the difference does not exceed the set adjustment interval value, the current brightness value is directly replaced with the target brightness value to achieve adjustment of the screen brightness.

Optionally, the screen brightness intelligent adjusting device further includes: a content brightness adjusting module.

The content brightness adjustment module is configured to acquire a target image brightness value corresponding to the target brightness value, and adjust a brightness of the current display content according to the target image brightness value.

Optionally, the content brightness adjustment module is further configured to: calculate a difference between the current image brightness value and the target image brightness value; and when the difference exceeds a set image brightness adjustment interval value, adjust according to the brightness The deviation of the real-time image luminance value acquired in the process from the target image luminance value divides the difference into at least two numerical intervals; and smooth adjustment of image brightness according to the numerical interval.

Embodiments of the present application also provide a storage medium including computer executable instructions for performing an intelligent adjustment method of screen brightness when executed by a computer processor, the method comprising: acquiring ambient light The intensity value, the application identifier of the application running in the foreground, and the terminal status; when the preset brightness adjustment event is triggered, determining the target brightness value corresponding to the intensity value, the application, and the terminal state by using the pre-configured brightness prediction model The brightness prediction model is a depth learning model that is based on historical brightness adjustment recording training; and the screen brightness is adjusted according to the target brightness value.

Storage medium Any of various types of memory devices or storage devices. The term "storage medium" is intended to include: a mounting medium such as a CD-ROM, a floppy disk or a tape device; a computer system memory or a random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc. Non-volatile memory, such as flash memory, magnetic media (such as hard disk or optical storage); registers or other similar types of memory elements, and the like. The storage medium may also include other types of memory or a combination thereof. Additionally, the storage medium may be located in a first computer system in which the program is executed, or may be located in a different second computer system, the second computer system being coupled to the first computer system via a network, such as the Internet. The second computer system can provide program instructions to the first computer for execution. The term "storage medium" can include two or more storage media that can reside in different locations (eg, in different computer systems connected through a network). A storage medium may store program instructions (eg, embodied as a computer program) executable by one or more processors.

Certainly, a storage medium containing computer executable instructions provided by the embodiments of the present application, the computer executable instructions are not limited to the intelligent adjustment operation of the screen brightness as described above, and may also execute the screen provided by any embodiment of the present application. Related operations in the intelligent adjustment method of brightness.

The embodiment of the present application provides a mobile terminal, which has an operating system, and the smart adjustment device of the screen brightness provided by the embodiment of the present application can be integrated into the mobile terminal. The mobile terminal can be a smart phone, a PAD (tablet), a handheld game machine, or the like. FIG. 4 is a structural block diagram of a mobile terminal according to an embodiment of the present application. As shown in FIG. 4, the memory 410 and the processor 420. The memory 410 is configured to store a computer program, a brightness prediction model, and a historical intensity value, etc.; the central processor 420 reads and executes a computer program stored in the memory 410. The processor 420, when executing the computer program, implements the following steps: acquiring an intensity value of ambient light, an application identifier of an application running in the foreground, and a terminal status; and pre-configuring when a preset brightness adjustment event is triggered. The brightness prediction model determines a target brightness value corresponding to the intensity value, an application, and a terminal state, wherein the brightness prediction model is a depth learning model based on historical brightness adjustment recording training; and the screen brightness is performed according to the target brightness value Adjustment.

The memory and processor listed in the above examples are all components of the mobile terminal, and the mobile terminal may further include other components. Taking a smart phone as an example, the possible structure of the above mobile terminal will be described. FIG. 5 is a structural block diagram of a smart phone according to an embodiment of the present application. As shown in FIG. 5, the smart phone may include: a memory 501, a central processing unit (CPU) 502 (also referred to as a processor, hereinafter referred to as a CPU), a peripheral interface 503, and an RF (Radio Frequency) circuit. 505, audio circuit 506, speaker 511, display 512, power management chip 508, input/output (I/O) subsystem 509, other input/control devices 510, and external port 504, through one or more communication buses or Signal line 507 is in communication.

It should be understood that the illustrated smartphone 500 is merely one example of a mobile terminal, and that the smartphone 500 may have more or fewer components than those shown in the figures, and two or more components may be combined. Or it can have different component configurations. The various components shown in the figures can be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and/or application specific integrated circuits.

A detailed description will be given below of a smart phone integrated with an intelligent adjustment device for screen brightness provided by the embodiment.

The memory 501 can be accessed by the CPU 502, the peripheral interface 503, etc., and the memory 501 can include a high speed random access memory, and can also include a non-volatile memory, such as one or more disk storage devices, flash memory. Devices, or other volatile solid-state storage devices. The computer program is stored in the memory 511, and a face state understanding model, a face image, a white list, and the like can also be stored.

Peripheral interface 503 can connect the input and output peripherals of the device to CPU 502 and memory 501.

I/O subsystem 509 can connect input and output peripherals on the device, such as screen 512 and other input/control devices 510, to peripheral interface 503. The I/O subsystem 509 can include a display controller 5091 and one or more input controllers 5092 for controlling other input/control devices 510. Wherein, one or more input controllers 5092 receive electrical signals from other input/control devices 510 or transmit electrical signals to other input/control devices 510, and other input/control devices 510 may include physical buttons (press buttons, rocker buttons, etc.) ), dial, slide switch, joystick, click wheel. It is worth noting that the input controller 5092 can be connected to any of the following: a keyboard, an infrared port, a USB interface, and a pointing device such as a mouse.

Screen 512 is an input interface and an output interface between the user terminal and the user, and displays the visual output to the user. The visual output may include graphics, text, icons, video, and the like.

Display controller 5051 in I/O subsystem 509 receives an electrical signal from screen 512 or an electrical signal to screen 512. Screen 512 detects contact on the screen, display controller 5091 converts the detected contact into interaction with a user interface object displayed on screen 512, i.e., enables human-computer interaction, and the user interface object displayed on screen 512 can be run The icon of the game, the icon of the network to the corresponding network, and the like. It is worth noting that the device may also include a light mouse, which is a touch sensitive surface that does not display a visual output, or an extension of a touch sensitive surface formed by the screen.

The RF circuit 505 establishes communication between the mobile phone and the wireless network (ie, the network side) to implement data reception and transmission between the mobile phone and the wireless network. For example, sending and receiving short messages, emails, and the like. Optionally, the RF circuit 505 receives and transmits an RF signal, also referred to as an electromagnetic signal, and the RF circuit 505 converts the electrical signal into an electromagnetic signal or converts the electromagnetic signal into an electrical signal, and through the electromagnetic signal to the communication network and others The device communicates. RF circuitry 505 may include known circuitry for performing these functions including, but not limited to, an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a CODEC ( COder-DE Coder, Chipset, Subscriber Identity Module (SIM), etc.

The audio circuit 506 receives audio data from the peripheral interface 503, converts the audio data into an electrical signal, and transmits the electrical signal to the speaker 511.

The speaker 511 restores the voice signal received by the mobile phone from the wireless network through the RF circuit 505 to sound and plays the sound to the user.

The power management chip 508 provides power and power management for the hardware connected to the CPU 502, the I/O subsystem, and the peripheral interface.

The mobile terminal provided by the embodiment of the present application can realize the historical brightness adjustment record based on the user's current use state and the user's historical brightness adjustment value, and automatically adjust the screen brightness based on the target brightness value, and adjust The result is more in line with the user's actual experience requirements, thereby improving the user experience.

The intelligent adjustment device, the storage medium and the mobile terminal provided in the above embodiments can perform the intelligent adjustment method of the screen brightness provided by any embodiment of the present application, and have the corresponding functional modules and beneficial effects of performing the method. For details of the technical details that are not described in detail in the above embodiments, reference may be made to the intelligent adjustment method of the screen brightness provided by any embodiment of the present application.

Claims

An intelligent adjustment method for screen brightness, including:

Obtaining the intensity value of the ambient light, the application identifier of the application running in the foreground, and the terminal status;

When the preset brightness adjustment event is triggered, the target brightness value corresponding to the intensity value, the application, and the terminal state is determined by a pre-configured brightness prediction model, wherein the brightness prediction model is based on the historical brightness adjustment record training Deep learning model;

The screen brightness is adjusted according to the target brightness value.
The method of claim 1 wherein

Obtaining the intensity value of the ambient light, comprising: obtaining the value output by the ambient light sensor according to the set sampling interval, and using the value as the intensity value of the ambient light;

After acquiring the intensity value of the ambient light, the method further includes: determining, according to the intensity value, whether the preset brightness adjustment event is triggered.
The method according to claim 2, wherein determining whether the preset brightness adjustment event is triggered according to the intensity value comprises:

Calculating a deviation between a first intensity value of the ambient light sensor output obtained at the current sampling time and a second intensity value output by the ambient light sensor acquired at the previous sampling time;

When the amount of deviation exceeds a set threshold, it is determined that the brightness adjustment event is triggered.
The method according to claim 2, wherein the application identifier and the terminal status of the application running in the foreground are obtained, including:

When the brightness adjustment event is triggered, the application identifier of the application running in the foreground is obtained, and the obtained system time, the current brightness value of the screen, and the network identifier are used as the terminal status, where the network identifier is the terminal access The name of the wireless network.
The method of claim 4, after acquiring the intensity value of the ambient light, the application identifier of the application running in the foreground, and the terminal status, the method further includes:

Matching the program number of the application according to a preset first rule;

Matching the network number of the network identifier according to a preset second rule;

Determining a time number according to a time period to which the system time belongs, wherein the time period is obtained by equally dividing the preset time interval in the natural day, and the time period is stored in association with the time number;

The intensity value, the program number, the time number, the current brightness value of the screen, and the network number are input to the pre-configured brightness prediction model.
The method of claim 5, wherein adjusting the brightness of the screen according to the target brightness value comprises:

Calculating a difference between the current brightness value and the target brightness value;

When the difference exceeds the set adjustment interval value, the difference is divided into at least two value intervals according to a deviation of the real-time screen brightness value acquired during the brightness adjustment process from the target brightness value;

The screen brightness is smoothly adjusted according to the numerical interval.
The method of claim 6, wherein the current brightness value is replaced with the target brightness value when the difference does not exceed a set adjustment interval value.
A method according to any one of claims 1 to 7, further comprising:

Obtaining a target image brightness value corresponding to the target brightness value, and adjusting a brightness of the current display content according to the target image brightness value.
The method of claim 8, wherein adjusting the brightness of the currently displayed content according to the target image brightness value comprises:

Calculating a difference between the current image brightness value and the target image brightness value;

When the difference exceeds the set image brightness adjustment interval value, dividing the difference into at least two value intervals according to a deviation of the real-time image brightness value obtained during the brightness adjustment process from the target image brightness value;

The image brightness is smoothly adjusted according to the numerical interval.
An intelligent adjustment device for screen brightness, comprising:

The state obtaining module is configured to obtain an intensity value of the ambient light, an application identifier of the application running in the foreground, and a terminal state;

a target value determining module configured to determine a target brightness value corresponding to the intensity value, an application, and a terminal state by a pre-configured brightness prediction model when the preset brightness adjustment event is triggered, wherein the brightness prediction model a deep learning model for training training based on historical brightness adjustment;

The brightness adjustment module is configured to adjust the brightness of the screen according to the target brightness value.
The device according to claim 10, wherein the state obtaining module is configured to: obtain a value output by the ambient light sensor according to the set sampling interval, and use the value as the intensity value of the ambient light;

After the state obtaining module acquires the intensity value of the ambient light, the method further includes: an event determining module, configured to determine, according to the intensity value, whether the preset brightness adjustment event is triggered.
The apparatus of claim 11 wherein said event determination module is configured to:

Calculating a deviation between a first intensity value of the ambient light sensor output obtained at the current sampling time and a second intensity value output by the ambient light sensor acquired at the previous sampling time;

When the amount of deviation exceeds a set threshold, it is determined that the brightness adjustment event is triggered.
The apparatus of claim 11, wherein the state acquisition module is configured to:

When the brightness adjustment event is triggered, the application identifier of the application running in the foreground is obtained, and the obtained system time, the current brightness value of the screen, and the network identifier are used as the terminal status, where the network identifier is the terminal access The name of the wireless network.
The device of claim 13, after the state acquisition module acquires the intensity value of the ambient light, the application identifier of the application running in the foreground, and the terminal state, the method further includes:

a pre-processing module, configured to: match a program number of the application according to a preset first rule; match a network number of the network identifier according to a preset second rule; and determine a time number according to a time period to which the system time belongs, The time period is obtained by equally dividing the preset time interval in the natural day, and the time period is stored in association with the time number;

The model input module is configured to input the intensity value, the program number, the time number, the current brightness value of the screen, and the network number into the pre-configured brightness prediction model.
The apparatus of claim 14 wherein the brightness adjustment module is configured to:

Calculating a difference between the current brightness value and the target brightness value;

When the difference exceeds the set adjustment interval value, the difference is divided into at least two value intervals according to a deviation of the real-time screen brightness value acquired during the brightness adjustment process from the target brightness value;

The screen brightness is smoothly adjusted according to the numerical interval.
The apparatus of claim 15 wherein said brightness adjustment module is configured to:

When the difference does not exceed the set adjustment interval value, the target brightness value is used to replace the current brightness value.
The apparatus according to any one of claims 10 to 16, further comprising: a content brightness adjustment module, configured to:

Obtaining a target image brightness value corresponding to the target brightness value, and adjusting a brightness of the current display content according to the target image brightness value.
The apparatus of claim 17 wherein said content brightness adjustment module is configured to:

Calculating a difference between the current image brightness value and the target image brightness value;

When the difference exceeds the set image brightness adjustment interval value, dividing the difference into at least two value intervals according to a deviation of the real-time image brightness value obtained during the brightness adjustment process from the target image brightness value;

The image brightness is smoothly adjusted according to the numerical interval.
A computer readable storage medium having stored thereon a computer program for performing an intelligent adjustment method of screen brightness according to any one of claims 1 to 9 when executed by a processor.
A mobile terminal comprising a memory, a processor, and a computer program stored on the memory and operable by the processor, the processor executing the computer program to implement the screen of any one of claims 1 to 9. Intelligent adjustment method of brightness.