OLED (Organic Light Emitting Diode) display brightness and contrast ratio combined adjusting system based on artificial intelligence

Abstract

The invention relates to the technical field of adjustment control, and discloses an OLED display brightness and contrast combined adjustment system based on artificial intelligence. According to the system, a sample set is constructed by collecting OLED display brightness data and contrast data under the condition that the brightness is not changed, the OLED display brightness data collected in the sample set is preprocessed, and a brightness adjustment relation model is established based on the preprocessed OLED display brightness data; based on the established brightness adjustment relation model and a contrast adjustment algorithm, establishing a contrast and brightness combined adjustment model; after the contrast and brightness combined adjustment model is established, the established contrast and brightness combined adjustment model is optimized through a genetic algorithm, and the brightness and contrast combined adjustment of the OLED display is realized based on the optimized contrast and brightness combined adjustment model, so that the intelligence and high efficiency of the brightness and contrast combined adjustment of the OLED display are ensured.

Description

Technical Field

[0001] The present invention relates to the field of regulation and control technology, in particular to an artificial intelligence-based OLED display brightness and contrast combination regulation system. Background Art

[0002] With the continuous development of science and technology, various electronic products have been manufactured and widely used in various fields of civil, medical and social life. As an important component of most electronic products, displays are also constantly updated. Brightness and contrast adjustment are key factors that determine whether the display can display effectively, but the brightness and contrast adjustment of existing displays can often only be fixed, which cannot meet user expectations.

[0003] Existing technologies such as Chinese patent application CN106707861A collect the light intensity of the surrounding environment through a light intensity collection unit, and convert the collected light intensity into a corresponding electrical signal value, and compare the electrical signal value with the last stored electrical signal value. If the change in the electrical signal values ​​of the two exceeds a set threshold, the electrical signal value is stored, and an interrupt signal is generated and sent to a central processing control unit. When the central processing control unit receives the interrupt signal, it reads the stored electrical signal value and controls the power management unit to output a corresponding power supply voltage to the display unit according to the electrical signal value; the display unit controls the display brightness of the display screen according to the received power supply voltage, which only realizes brightness adjustment and does not take into account the contrast adjustment of the display screen, which has great limitations. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides an artificial intelligence-based OLED display brightness and contrast combination adjustment system, which has the advantages of intelligence and high efficiency, and solves the problem that the brightness and contrast adjustment of existing displays can often only be achieved in a fixed manner.

[0006] (II) Technical solution

[0007] In order to solve the technical problem that the brightness and contrast of the above-mentioned existing displays can only be adjusted in a fixed manner, the present invention provides the following technical solutions:

[0008] The present invention discloses an artificial intelligence-based OLED display brightness and contrast combination adjustment method, which specifically includes the following steps:

[0009] S1, collecting brightness data of the OLED display and contrast data when the brightness remains unchanged, and constructing a sample set based on the collected brightness data of the OLED display and contrast data when the brightness remains unchanged;

[0010] The OLED display brightness data includes: user input brightness data and display display brightness data;

[0011] The user inputs brightness data in the range of [0%, 100%], and the display brightness data is represented by the brightness quantization of the three colors R, G, and B, and the brightness quantization range of the three colors R, G, and B is [0, 255];

[0012] S2, preprocessing the OLED display brightness data in the sample set to obtain the preprocessed OLED display brightness data and establish a brightness adjustment relationship model;

[0013] S3, establishing a contrast and brightness combination adjustment model based on the established brightness adjustment relationship model and contrast adjustment algorithm;

[0014] S4, based on the collected OLED display brightness data and the contrast data when the brightness remains unchanged, the contrast and brightness combination adjustment model is processed by a genetic algorithm to obtain an optimal contrast and brightness combination adjustment model;

[0015] S5. Combining and adjusting the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combination adjustment model;

[0016] The combined adjustment of the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combined adjustment model includes:

[0017] By inputting the user input brightness data into the obtained optimal contrast and brightness combination adjustment model, the optimal contrast and brightness combination adjustment model will adjust the display brightness and contrast based on the user input brightness data.

[0018] The present invention constructs a sample set by collecting OLED display brightness data and contrast data under the condition of unchanged brightness, and preprocesses the OLED display brightness data collected in the sample set, and establishes a brightness adjustment relationship model based on the preprocessed OLED display brightness data, and establishes a contrast and brightness combination adjustment model based on the established brightness adjustment relationship model and a contrast adjustment algorithm; after the contrast and brightness combination adjustment model is established, the established contrast and brightness combination adjustment model is optimized through a genetic algorithm, and the brightness and contrast combination adjustment of the OLED display is realized based on the optimized contrast and brightness combination adjustment model, thereby ensuring the intelligence and efficiency of the brightness and contrast combination adjustment of the OLED display.

[0019] Preferably, the preprocessing of the OLED display brightness data collected in the sample set to obtain the preprocessed OLED display brightness data and establish a brightness adjustment relationship model comprises the following steps:

[0020] S21, filtering the OLED display brightness data in the sample set to obtain filtered OLED display brightness data;

[0021] The user input brightness data and the display brightness data in the OLED display brightness data are set to correspond one to one. When the user input brightness data or the display brightness data in the OLED display brightness data is missing, the missing user input brightness data or the display brightness data is deleted, and the user input brightness data or the display brightness data corresponding to the missing data is deleted to achieve filtering. The remaining OLED display brightness data in the sample set is the filtered OLED display brightness data.

[0022] S22, sorting the filtered OLED display brightness data to obtain pre-processed OLED display brightness data and establishing a brightness adjustment relationship model.

[0023] Preferably, the step of arranging the filtered OLED display brightness data to obtain pre-processed OLED display brightness data and establishing a brightness adjustment relationship model comprises the following steps:

[0024] Arrange the filtered brightness data of the OLED display in descending order, and determine the grayscale level of the current OLED display based on the number of bits of the current processor. When the processor is 8 bits, the grayscale level of the corresponding OLED display is 2 to the 8th power, which is 256 grayscale levels;

[0025] For a 64-level grayscale OLED display, the number of bits representing the brightness of each color in the brightness data displayed by the display converted into binary brightness data is 6 bits;

[0026] The brightness adjustment algorithm formula is as follows:

[0027] Y=K×X

[0028] Wherein, Y is the output 6-bit binary brightness data, indicating the brightness value expected to be achieved after adjustment, X is the input 6-bit binary brightness data, and K is the user input brightness data;

[0029] A brightness adjustment relationship model is constructed based on the brightness adjustment algorithm. The formula of the brightness adjustment relationship model is as follows:

[0030] L=L min +(L max -L min )×(Y / 255)2

[0031] Among them, L represents the actual brightness value after adjustment, L max Indicates the maximum brightness, L min Indicates minimum brightness.

[0032] The present invention cleans and filters the OLED display brightness data collected in the sample set, and establishes a brightness adjustment relationship model according to a brightness adjustment algorithm based on the filtered and sorted data, thereby ensuring the accuracy of the brightness adjustment of the OLED display.

[0033] Preferably, the step of establishing a contrast and brightness combination adjustment model based on the established brightness adjustment relationship model and contrast adjustment algorithm comprises the following steps:

[0034] For a 64-level grayscale OLED display, the contrast adjustment algorithm formula is as follows:

[0035] D=64(X÷64) γ

[0036] Wherein, X is the input 6-bit binary brightness data, D is the output 6-bit binary brightness data, which represents the expected contrast value after adjustment. The contrast value represents the ratio of the maximum brightness to the minimum brightness of the OLED display, and γ is the contrast adjustment variable;

[0037] The contrast and brightness combination adjustment model is as follows:

[0038] Q=K(L÷64) γ

[0039] Among them, Q is the 6-bit binary brightness data output after the contrast and brightness are adjusted, indicating the desired contrast and brightness adjustment value after adjustment, K is the user input brightness data, γ is the contrast adjustment variable, and L indicates the actual brightness value achieved after adjustment.

[0040] The present invention realizes the establishment of a contrast and brightness combination adjustment model by establishing a brightness adjustment relationship model and a contrast adjustment algorithm, thereby ensuring the reliability of the establishment of the contrast and brightness combination adjustment model.

[0041] Preferably, the processing of the contrast and brightness combination adjustment model by a genetic algorithm based on the collected OLED display brightness data and the contrast data when the brightness is unchanged comprises the following steps:

[0042] S41, randomly select the pre-processed brightness data and contrast data of the OLED display, select N processed brightness data and contrast data and number them in sequence to obtain chromosome codes, and the chromosome code set is:

[0043] {1(225,225,225,400:1),2(200,200,225,400:1),...,N(255,255,255,600:1)}

[0044] Among them, 1 represents the chromosome encoding of the brightness data and contrast data after processing numbered 1, N represents the chromosome encoding of the brightness data and contrast data after processing numbered N, 225, 225, 225 represent the brightness quantization values ​​of R, G, and B respectively, 400:1 represents the contrast value at the current brightness, 200, 200, 225 represent the brightness quantization values ​​of R, G, and B respectively, 255, 255, 255 represent the brightness quantization values ​​of R, G, and B respectively, and 600:1 represents the contrast value at the current brightness;

[0045] S42, performing population initialization;

[0046] S43, establishing a fitness function;

[0047] S44, genetic operator selection operation;

[0048] S45, chromosome crossover operation;

[0049] S46, iteratively executing steps S42-S45 until the contrast adjustment variable converges, and outputting the optimal individual under each group of brightness;

[0050] The converged contrast adjustment variable is used as the contrast adjustment variable in the calculation of the current contrast and brightness combination adjustment model, so as to obtain the optimal contrast and brightness combination adjustment model.

[0051] Preferably, the population initialization comprises the following steps:

[0052] Select 4 chromosome codes from the N processed brightness data and contrast data that have been numbered to generate an initial population;

[0053] Sort the data in the generated initial population by number;

[0054] By setting the initial value of the contrast adjustment variable in the contrast and brightness combination adjustment model, the data in the sorted initial population is adjusted based on the contrast and brightness combination adjustment model with the set initial value of the contrast adjustment variable to obtain the data after contrast and brightness combination adjustment.

[0055] Preferably, the step of establishing the fitness function comprises the following steps:

[0056] In the process of adjusting the data in the sorted initial population by the contrast and brightness combination adjustment model, when the user is satisfied with the brightness of the OLED display after the current contrast and brightness combination adjustment, the fitness value after the contrast and brightness combination adjustment is determined by the user touching the OLED display;

[0057] When the contrast and brightness combination adjustment model is adjusting the data in the sorted initial population, if the user does not touch the OLED display to determine the fitness value after the contrast and brightness combination adjustment, a new population is selected and processed by the genetic algorithm;

[0058] Recording the fitness value after the determined contrast and brightness combination is adjusted, and setting the fitness value after the determined contrast and brightness combination is adjusted as a genetic operator;

[0059] Constructing a fitness function based on the determined fitness value after adjusting the contrast and brightness combination;

[0060] The fitness function is set as follows:

[0061]

[0062] Among them, Fix(i) represents the fitness of the i-th group of contrast and brightness in the initialization population, Q i Represents the contrast and brightness combination adjustment value of the i-th contrast and brightness of the initialized population in the fitness function.

[0063] Preferably, the genetic operator selection operation comprises the following steps:

[0064] By randomly selecting the genetic operator in a roulette wheel manner, the probability of each set of contrast and brightness being selected is proportional to the fitness, and the contrast and brightness with the highest fitness are selected;

[0065] The probability formula for the genetic operator to be selected is as follows:

[0066]

[0067] Where I represents the population size, Fix(i) represents the fitness of the i-th contrast and brightness group in the initialization population, and p(i) represents the probability of the i-th contrast and brightness group being selected in the initialization population.

[0068] Preferably, the chromosome crossover operation comprises the following steps:

[0069] The chromosome codes of the selected genetic operators are copied to generate offspring populations, the chromosome codes in the generated offspring populations are randomly paired, and crossover points are randomly selected. The genetic operators in the generated offspring populations are cross-bred by sequential crossover to generate a pair of new chromosome codes;

[0070] The newly generated chromosome codes are also used as data to participate in the iteration.

[0071] The present invention optimizes the established contrast and brightness combination adjustment model by using a genetic algorithm, performing chromosome encoding, population initialization, establishing a fitness function, and genetic operator selection crossover operations on brightness data, contrast data under the condition of constant brightness, and the established contrast and brightness combination adjustment model, thereby ensuring the accuracy and reliability of the brightness contrast combination adjustment method for an OLED display.

[0072] The present invention discloses an artificial intelligence-based OLED display brightness contrast combination adjustment system, comprising: a data collection module, a database, a brightness contrast combination adjustment module, an adjustment optimization module and a display module;

[0073] The data collection module is used to collect brightness data of the OLED display and contrast data when the brightness remains unchanged;

[0074] The database is used to store the brightness data of the OLED display collected by the data collection module and the contrast data when the brightness remains unchanged;

[0075] The brightness contrast combination adjustment module is used to establish a contrast and brightness combination adjustment model through a brightness adjustment algorithm and a contrast adjustment algorithm;

[0076] The adjustment optimization module is used to optimize the established contrast and brightness combination adjustment model through a genetic algorithm;

[0077] The display module is used to display the brightness data and contrast data adjusted by the contrast and brightness combination adjustment model.

[0078] (III) Beneficial effects

[0079] Compared with the prior art, the present invention provides an artificial intelligence-based OLED display brightness and contrast combination adjustment system, which has the following beneficial effects:

[0080] 1. The invention constructs a sample set by collecting brightness data of an OLED display and contrast data when the brightness remains unchanged, and preprocesses the brightness data of the OLED display collected in the sample set, and establishes a brightness adjustment relationship model based on the preprocessed brightness data of the OLED display, and establishes a contrast and brightness combination adjustment model based on the established brightness adjustment relationship model and contrast adjustment algorithm; after establishing the contrast and brightness combination adjustment model, the established contrast and brightness combination adjustment model is optimized through a genetic algorithm, and the brightness and contrast combination adjustment of the OLED display is realized based on the optimized contrast and brightness combination adjustment model, thereby ensuring the intelligence and efficiency of the brightness and contrast combination adjustment of the OLED display.

[0081] 2. The invention cleans and filters the OLED display brightness data collected in the sample set, and establishes a brightness adjustment relationship model according to the brightness adjustment algorithm based on the filtered and sorted data, thereby ensuring the accuracy of the brightness adjustment of the OLED display.

[0082] 3. The invention realizes the establishment of a contrast and brightness combination adjustment model by establishing a brightness adjustment relationship model and a contrast adjustment algorithm, thereby ensuring the reliability of the establishment of the contrast and brightness combination adjustment model.

[0083] 4. The invention optimizes the established contrast and brightness combination adjustment model by using a genetic algorithm to perform chromosome encoding, population initialization, fitness function establishment, and genetic operator selection crossover on brightness data and contrast data under the condition of unchanged brightness and the established contrast and brightness combination adjustment model, thereby ensuring the accuracy and reliability of the brightness contrast combination adjustment method of the OLED display. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 It is a schematic diagram of the structure of the process of the artificial intelligence OLED display brightness contrast combination adjustment method of the present invention;

[0085] Figure 2 This is a flow chart for optimizing the contrast and brightness combination adjustment model of the present invention. DETAILED DESCRIPTION

[0086] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0087] The present invention discloses an artificial intelligence-based OLED display brightness and contrast combination adjustment method, which specifically includes the following steps:

[0088] S1, collecting brightness data of the OLED display and contrast data when the brightness remains unchanged, and constructing a sample set based on the collected brightness data of the OLED display and contrast data when the brightness remains unchanged;

[0089] The OLED display brightness data includes: user input brightness data and display display brightness data;

[0090] The user inputs brightness data in the range of [0%, 100%], and the display brightness data is represented by the brightness quantization of the three colors R, G, and B, and the brightness quantization range of the three colors R, G, and B is [0, 255];

[0091] S2, preprocessing the OLED display brightness data in the sample set to obtain the preprocessed OLED display brightness data and establish a brightness adjustment relationship model;

[0092] Preprocessing the OLED display brightness data collected in the sample set to obtain the preprocessed OLED display brightness data and establish a brightness adjustment relationship model includes the following steps:

[0093] S21, filtering the OLED display brightness data collected in the sample set to obtain filtered OLED display brightness data;

[0094] The user input brightness data and the display brightness data in the OLED display brightness data are set to correspond one to one. When the user input brightness data or the display brightness data in the OLED display brightness data is missing, the missing user input brightness data or the display brightness data is deleted, and the user input brightness data or the display brightness data corresponding to the missing data is deleted to achieve filtering. The remaining OLED display brightness data in the sample set is the filtered OLED display brightness data.

[0095] S22, sorting the filtered OLED display brightness data to obtain pre-processed OLED display brightness data and establishing a brightness adjustment relationship model;

[0096] Arrange the filtered brightness data of the OLED display in descending order, and determine the grayscale level of the current OLED display based on the number of bits of the current processor. When the processor is 8 bits, the grayscale level of the corresponding OLED display is 2 to the 8th power, which is 256 grayscale levels;

[0097] For a 64-level grayscale OLED display, the number of bits representing the brightness of each color in the brightness data displayed by the display converted into binary brightness data is 6 bits;

[0098] The brightness adjustment algorithm formula is as follows:

[0099] Y=K×X

[0100] Wherein, Y is the output 6-bit binary brightness data, indicating the brightness value expected to be achieved after adjustment, X is the input 6-bit binary brightness data, and K is the user input brightness data;

[0101] A brightness adjustment relationship model is constructed based on the brightness adjustment algorithm. The formula of the brightness adjustment relationship model is as follows:

[0102] L=L min +(L max -L min )×(Y / 255) 2

[0103] Among them, L represents the actual brightness value after adjustment, L max Indicates the maximum brightness, L min Indicates the minimum brightness;

[0104] S3, establishing a contrast and brightness combination adjustment model based on the established brightness adjustment relationship model and contrast adjustment algorithm;

[0105] Based on the established brightness adjustment relationship model and contrast adjustment algorithm, establishing a contrast and brightness combination adjustment model includes the following steps:

[0106] For a 64-level grayscale OLED display, the contrast adjustment algorithm formula is as follows:

[0107] D=64(X÷64) γ

[0108] Wherein, X is the input 6-bit binary brightness data, D is the output 6-bit binary brightness data, which represents the expected contrast value after adjustment. The contrast value represents the ratio of the maximum brightness to the minimum brightness of the OLED display, and γ is the contrast adjustment variable;

[0109] The contrast and brightness combination adjustment model is as follows:

[0110] Q=K(L÷64) γ

[0111] Wherein, Q is the 6-bit binary brightness data output after contrast and brightness are adjusted, indicating the desired contrast and brightness adjustment value after adjustment, K is the user input brightness data, γ is the contrast adjustment variable, and L indicates the actual brightness value after adjustment;

[0112] S4, based on the collected OLED display brightness data and the contrast data when the brightness remains unchanged, the contrast and brightness combination adjustment model is processed by a genetic algorithm to obtain an optimal contrast and brightness combination adjustment model;

[0113] Based on the collected OLED display brightness data and contrast data when the brightness remains unchanged, the contrast and brightness combination adjustment model is processed by genetic algorithm, including the following steps:

[0114] S41, randomly select the pre-processed brightness data and contrast data of the OLED display, select N processed brightness data and contrast data and number them in sequence to obtain chromosome codes, and the chromosome code set is:

[0115] {1(225,225,225,400:1),2(200,200,225,400:1),...,N(255,255,255,600:1)}

[0116] Among them, 1 represents the chromosome encoding of the brightness data and contrast data after processing numbered 1, N represents the chromosome encoding of the brightness data and contrast data after processing numbered N, 225, 225, 225 represent the brightness quantization values ​​of R, G, and B respectively, 400:1 represents the contrast value at the current brightness, 200, 200, 225 represent the brightness quantization values ​​of R, G, and B respectively, 255, 255, 255 represent the brightness quantization values ​​of R, G, and B respectively, and 600:1 represents the contrast value at the current brightness;

[0117] S42, performing population initialization;

[0118] Select 4 chromosome codes from the N processed brightness data and contrast data that have been numbered to generate an initial population;

[0119] Furthermore, the data in the generated initial population are sorted according to the numbers;

[0120] Further, by setting an initial value of a contrast adjustment variable in the contrast and brightness combination adjustment model, the data in the sorted initial population is adjusted based on the contrast and brightness combination adjustment model with the initial value of the contrast adjustment variable set, to obtain data after contrast and brightness combination adjustment;

[0121] S43, establishing a fitness function;

[0122] In the process of adjusting the data in the sorted initial population by the contrast and brightness combination adjustment model, when the user is satisfied with the brightness of the OLED display after the current contrast and brightness combination adjustment, the fitness value after the contrast and brightness combination adjustment is determined by the user touching the OLED display;

[0123] When the contrast and brightness combination adjustment model performs cyclic adjustment on the data in the sorted initial population, if the user does not touch the OLED display to determine the fitness value after the contrast and brightness combination adjustment, a new population is selected and processed by a genetic algorithm;

[0124] Further, recording the fitness value after the determined contrast and brightness combination is adjusted, and setting the fitness value after the determined contrast and brightness combination is adjusted as a genetic operator;

[0125] Constructing a fitness function based on the determined fitness value after adjusting the contrast and brightness combination;

[0126] The fitness function is set as follows:

[0127]

[0128] Among them, Fix(i) represents the fitness of the i-th group of contrast and brightness in the initialization population, Q i represents the contrast and brightness combination adjustment value of the i-th contrast and brightness of the initialized population in the fitness function;

[0129] S44, genetic operator selection operation;

[0130] By randomly selecting the genetic operator in a roulette wheel manner, the probability of each set of contrast and brightness being selected is proportional to the fitness, and the contrast and brightness with the highest fitness are selected;

[0131] The probability formula for the genetic operator to be selected is as follows:

[0132]

[0133] Where I represents the population size, Fix(i) represents the fitness of the i-th contrast and brightness group in the initialization population, and p(i) represents the probability of the i-th contrast and brightness group being selected in the initialization population;

[0134] S45, chromosome crossover operation;

[0135] The chromosome codes of the selected genetic operators are copied to generate offspring populations, the chromosome codes in the generated offspring populations are randomly paired, and crossover points are randomly selected. The genetic operators in the generated offspring populations are cross-bred by sequential crossover to generate a pair of new chromosome codes;

[0136] Furthermore, the generated new chromosome code is also used as data to participate in the iteration;

[0137] S46, iteratively executing steps S42-S45 until the contrast adjustment variable converges, and outputting the optimal individual under each group of brightness;

[0138] Further, the converged contrast adjustment variable is used as the contrast adjustment variable in the calculation of the current contrast and brightness combination adjustment model, so as to obtain the optimal contrast and brightness combination adjustment model;

[0139] S5. Combining and adjusting the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combination adjustment model;

[0140] The combined adjustment of the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combined adjustment model includes:

[0141] By inputting the user input brightness data into the obtained optimal contrast and brightness combination adjustment model, the optimal contrast and brightness combination adjustment model will adjust the display brightness and contrast of the display based on the user input brightness data;

[0142] The present invention discloses an artificial intelligence-based OLED display brightness contrast combination adjustment system, comprising: a data collection module, a database, a brightness contrast combination adjustment module, an adjustment optimization module and a display module;

[0143] The data collection module is used to collect brightness data of the OLED display and contrast data when the brightness remains unchanged;

[0144] The database is used to store the brightness data of the OLED display collected by the data collection module and the contrast data when the brightness remains unchanged;

[0145] The brightness contrast combination adjustment module is used to establish a contrast and brightness combination adjustment model through a brightness adjustment algorithm and a contrast adjustment algorithm;

[0146] The adjustment optimization module is used to optimize the established contrast and brightness combination adjustment model through a genetic algorithm;

[0147] The display module is used to display the brightness data and contrast data adjusted by the contrast and brightness combination adjustment model.

[0148] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for adjusting brightness and contrast of an OLED display based on artificial intelligence, characterized in that: The following steps are involved: S1. Collecting brightness data of the OLED display and contrast data when the brightness remains unchanged, and constructing a sample set based on the collected brightness data of the OLED display and contrast data when the brightness remains unchanged; The OLED display brightness data includes: user input brightness data and display display brightness data; The user inputs brightness data in the range of [0%, 100%], and the display brightness data is represented by the brightness quantization of the three colors R, G, and B, and the brightness quantization range of the three colors R, G, and B is [0, 255]; S2, preprocessing the OLED display brightness data in the sample set to obtain the preprocessed OLED display brightness data and establish a brightness adjustment relationship model; S3, establishing a contrast and brightness combination adjustment model based on the established brightness adjustment relationship model and contrast adjustment algorithm; S4, based on the collected OLED display brightness data and the contrast data when the brightness remains unchanged, the contrast and brightness combination adjustment model is processed by a genetic algorithm to obtain an optimal contrast and brightness combination adjustment model; S5. Combining and adjusting the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combination adjustment model; The combined adjustment of the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combined adjustment model includes: By inputting the user input brightness data into the obtained optimal contrast and brightness combination adjustment model, the optimal contrast and brightness combination adjustment model will adjust the display brightness and contrast based on the user input brightness data.

2. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 1, characterized in that: The preprocessing of the OLED display brightness data in the sample set to obtain the preprocessed OLED display brightness data and establish a brightness adjustment relationship model comprises the following steps: S21, filtering the OLED display brightness data in the sample set to obtain filtered OLED display brightness data; The user input brightness data and the display brightness data in the OLED display brightness data are set to correspond one to one. When the user input brightness data or the display brightness data in the OLED display brightness data is missing, the missing user input brightness data or the display brightness data is deleted, and the user input brightness data or the display brightness data corresponding to the missing data is deleted to achieve filtering. The remaining OLED display brightness data in the sample set is the filtered OLED display brightness data. S22, sorting the filtered OLED display brightness data to obtain pre-processed OLED display brightness data and establishing a brightness adjustment relationship model.

3. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 2, characterized in that: The filtering and sorting of the OLED display brightness data to obtain the pre-processed OLED display brightness data and establish a brightness adjustment relationship model comprises the following steps: Arrange the filtered brightness data of the OLED display in descending order, and determine the grayscale level of the current OLED display based on the number of bits of the current processor. When the processor is 8 bits, the grayscale level of the corresponding OLED display is 2 to the 8th power, which is 256 grayscale levels; For a 64-level grayscale OLED display, the number of bits representing the brightness of each color in the brightness data displayed by the display converted into binary brightness data is 6 bits; The brightness adjustment algorithm formula is as follows: Y=K×X Wherein, Y is the output 6-bit binary brightness data, indicating the brightness value expected to be achieved after adjustment, X is the input 6-bit binary brightness data, and K is the user input brightness data; A brightness adjustment relationship model is constructed based on the brightness adjustment algorithm. The formula of the brightness adjustment relationship model is as follows: L=L min +(L max -L min )×(Y / 255) 2 Among them, L represents the actual brightness value after adjustment, L max Indicates the maximum brightness, L min Indicates minimum brightness.

4. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 1, characterized in that: The step of establishing a contrast and brightness combination adjustment model based on the established brightness adjustment relationship model and contrast adjustment algorithm includes the following steps: For a 64-level grayscale OLED display, the contrast adjustment algorithm formula is as follows: D=64(X÷64) γ Wherein, X is the input 6-bit binary brightness data, D is the output 6-bit binary brightness data, which represents the expected contrast value after adjustment. The contrast value represents the ratio of the maximum brightness to the minimum brightness of the OLED display, and γ is the contrast adjustment variable; The contrast and brightness combination adjustment model is as follows: Q=K(L÷64) γ Among them, Q is the 6-bit binary brightness data output after the contrast and brightness are adjusted, indicating the desired contrast and brightness adjustment value after adjustment, K is the user input brightness data, γ is the contrast adjustment variable, and L indicates the actual brightness value achieved after adjustment.

5. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 1, characterized in that: The method of processing the contrast and brightness combination adjustment model by a genetic algorithm based on the collected OLED display brightness data and the contrast data when the brightness is unchanged includes the following steps: S41, randomly select the pre-processed brightness data and contrast data of the OLED display, select N processed brightness data and contrast data and number them in sequence to obtain chromosome codes, and the chromosome code set is: {1(225,225,225,400:1),2(200,200,225,400:1),...,N(255,255,255,600:1)} Among them, 1 represents the chromosome encoding of the brightness data and contrast data after processing numbered 1, N represents the chromosome encoding of the brightness data and contrast data after processing numbered N, 225, 225, 225 represent the brightness quantization values ​​of R, G, and B respectively, 400:1 represents the contrast value at the current brightness, 200, 200, 225 represent the brightness quantization values ​​of R, G, and B respectively, 255, 255, 255 represent the brightness quantization values ​​of R, G, and B respectively, and 600:1 represents the contrast value at the current brightness; S42, performing population initialization; S43, establishing a fitness function; S44, genetic operator selection operation; S45, chromosome crossover operation; S46, iteratively executing steps S42-S45 until the contrast adjustment variable converges; The converged contrast adjustment variable is used as the contrast adjustment variable in the calculation of the current contrast and brightness combination adjustment model, so as to obtain the optimal contrast and brightness combination adjustment model.

6. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 5, characterized in that: The population initialization comprises the following steps: Select 4 chromosome codes from the N processed brightness data and contrast data that have been numbered to generate an initial population; Sort the data in the generated initial population by number; An initial value of a contrast adjustment variable in a contrast and brightness combination adjustment model is set, and data in the sorted initial population is adjusted based on the contrast and brightness combination adjustment model with the initial value of the contrast adjustment variable set, to obtain data after contrast and brightness combination adjustment.

7. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 5, characterized in that: The establishment of the fitness function comprises the following steps: In the process of adjusting the data in the sorted initial population by the contrast and brightness combination adjustment model, when the user is satisfied with the brightness of the OLED display after the current contrast and brightness combination adjustment, the fitness value after the contrast and brightness combination adjustment is determined by the user touching the OLED display; When the contrast and brightness combination adjustment model is adjusting the data in the sorted initial population, if the user does not touch the OLED display to determine the fitness value after the contrast and brightness combination adjustment, a new population is selected and processed by the genetic algorithm; Recording the fitness value after the determined contrast and brightness combination is adjusted, and setting the fitness value after the determined contrast and brightness combination is adjusted as a genetic operator; Constructing a fitness function based on the determined fitness value after adjusting the contrast and brightness combination; The fitness function is set as follows: Among them, Fix(i) represents the fitness of the i-th group of contrast and brightness in the initialization population, Q i Represents the contrast and brightness combination adjustment value of the i-th contrast and brightness of the initialized population in the fitness function.

8. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 5, characterized in that: The genetic operator selection operation comprises the following steps: By randomly selecting the genetic operator in a roulette wheel manner, the probability of each set of contrast and brightness being selected is proportional to the fitness, and the contrast and brightness with the highest fitness are selected; The probability formula for the genetic operator to be selected is as follows: Where I represents the population size, Fix(i) represents the fitness of the i-th contrast and brightness group in the initialization population, and p(i) represents the probability of the i-th contrast and brightness group being selected in the initialization population.

9. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 5, characterized in that: The chromosome crossover operation comprises the following steps: The chromosome codes of the selected genetic operators are copied to generate offspring populations, the chromosome codes in the generated offspring populations are randomly paired, and crossover points are randomly selected. The genetic operators in the offspring populations are cross-bred by sequential crossover to generate a new pair of chromosome codes. The newly generated chromosome codes are also used as data to participate in the iteration.

10. A system for implementing the artificial intelligence-based OLED display brightness contrast combination adjustment method according to any one of claims 1 to 9, characterized in that: include: Data collection module, database, brightness contrast combination adjustment module, adjustment optimization module and display module; The data collection module is used to collect brightness data of the OLED display and contrast data when the brightness remains unchanged; The database is used to store the brightness data of the OLED display collected by the data collection module and the contrast data when the brightness remains unchanged; The brightness contrast combination adjustment module is used to establish a contrast and brightness combination adjustment model through a brightness adjustment algorithm and a contrast adjustment algorithm; The adjustment optimization module is used to optimize the established contrast and brightness combination adjustment model through a genetic algorithm; The display module is used to display the brightness data and contrast data adjusted by the contrast and brightness combination adjustment model.

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