Method for determining gamma data of OLED screen, and display screen

Abstract

A method for determining gamma data of an OLED screen, and a display screen. The determination method comprises: constructing a first gamma calculation model; and, on the basis of target reference gamma data and the first gamma calculation model, obtaining target gamma initial value data, and, on the basis of the target gamma initial value data, controlling an OLED screen to emit light, the target reference gamma data being a reference value for calculating the target gamma initial value data, and the target gamma initial value data comprising gamma initial values of all registers for controlling the OLED screen to emit light.

Description

Method for determining gamma data of OLED screen and display screen

[0001] Cross-reference to related applications

[0002] This application claims priority to Chinese Patent Application No. 202411392979.1, filed on September 30, 2024, entitled "Method for determining gamma data of OLED screen and display screen", the entire contents of which are incorporated herein by reference. TECHNICAL FIELD

[0003] The present application relates to the technical field of display, and in particular to a method for determining gamma data of an OLED screen and a display screen. BACKGROUND

[0004] The OTP (One-Time-Programming) initial value algorithm in an OLED module is a one-time programming process of writing initial parameters or specific data into the OLED module. The current OTP initial value algorithm in the OLED module can only determine gamma data in multiple band registers one by one. This serial calculation method results in a long OTP adjustment time. Moreover, the OTP adjustment time is greatly affected by the initial value of the gamma register, but the difference between the initial value of the gamma register and the actual value after the OTP adjustment is large, resulting in a large number of OTP adjustment times and a long process time. Therefore, the adjustment times of the OTP initial value algorithm in the OLED module in the related art are large, and the adjustment time is too long. SUMMARY

[0005] To solve the above technical problems, the present application provides a method for determining gamma data of an OLED screen and a display screen.

[0006] In a first aspect, an embodiment of the present application provides a method for determining gamma data of an OLED screen, comprising:

[0007] constructing a first gamma calculation model, wherein the first gamma calculation model is obtained by training a plurality of sets of training data, each set of training data in the plurality of sets of training data including historical reference gamma data and historical actual gamma data corresponding to the historical reference gamma data obtained in a historical time period, the historical actual gamma data being real gamma data used to control the OLED screen to emit light at a historical time, and the historical reference gamma data being a reference value used to calculate target gamma initial value data at the historical time;

[0008] According to the target reference gamma data and the first gamma calculation model, target gamma initial value data is obtained, and the OLED screen is controlled to emit light based on the target gamma initial value data, wherein the target reference gamma data is reference value for calculating the target gamma initial value data, and the target gamma initial value data includes gamma initial values of all registers for controlling the OLED screen to emit light.

[0009] In a second aspect, the embodiments of the present application provide a display screen, the brightness of the display screen is determined according to gamma data in each register, and the gamma data in each register is determined by the method for determining gamma data of the OLED screen in the first aspect.

[0010] Compared with related art, the technical solutions provided by the present application have the following advantages:

[0011] According to the technical solutions of the present application and the method for determining gamma data of the OLED screen, first, the reference value for calculating the target gamma initial value data at the historical moment and the real gamma data for controlling the OLED screen to emit light at the historical moment corresponding to the reference value are used to train the first gamma calculation model; then, according to the target reference gamma data and the first gamma calculation model, the target gamma initial value data is obtained, and the OLED screen is controlled to emit light based on the target gamma initial value data, wherein the target reference gamma data is reference value for calculating the target gamma initial value data, and the target gamma initial value data includes gamma initial values of all registers for controlling the OLED screen to emit light. This method can directly input the gamma data of the band0 register as the reference value of the gamma value of each band into the gamma calculation model, and output the gamma value of all band registers at the same time. Therefore, ten brightnesses can be adjusted in one time, the number of OTP adjustment times is reduced, the process time is greatly reduced, and the problem that the number of adjustment times of the OTP initial value algorithm in the OLED module is large and the adjustment time is too long in related art is solved. BRIEF DESCRIPTION OF DRAWINGS

[0012] The present application can be better understood from the following description of specific embodiments thereof, taken in conjunction with the accompanying drawings, which are included by way of illustration only and do not limit the scope of the application. Like or similar elements are designated with like reference numerals throughout the several views.

[0013] FIG. 1 shows a flow diagram of a method for determining gamma data of an OLED screen according to an embodiment of the present application;

[0014] FIG. 2 shows a structural diagram of a gray scale reactor model according to an embodiment of the present application;

[0015] FIG. 3 shows a structural diagram of a middle layer composition of a gray scale reactor model according to an embodiment of the present application;

[0016] FIG. 4 shows another flow diagram of a method for determining gamma data of an OLED screen according to an embodiment of the present application;

[0017] FIG. 5 shows an effect diagram of a method for determining gamma data of an OLED screen according to an embodiment of the present application;

[0018] FIG. 6 shows an effect diagram of another method for determining gamma data of an OLED screen according to an embodiment of the present application;

[0019] FIG. 7 shows an effect diagram of another method for determining gamma data of an OLED screen according to an embodiment of the present application;

[0020] FIG. 8 shows an effect diagram of another method for determining gamma data of an OLED screen according to an embodiment of the present application;

[0021] FIG. 9 shows an effect diagram of another method for determining gamma data of an OLED screen according to an embodiment of the present application;

[0022] FIG. 10 shows an effect diagram of another method for determining gamma data of an OLED screen according to an embodiment of the present application;

[0023] FIG. 11 shows a structural diagram of a display screen according to an embodiment of the present application.

[0024] Wherein, the above figures include the following reference signs: 100, display panel. DETAILED DESCRIPTION

[0025] The features and exemplary embodiments of the various aspects of the present application will be described in detail below. Numerous specific details are disclosed in the following detailed description to provide a thorough understanding of the present application. However, it will be apparent to one of ordinary skill in the art that the present application can be practiced without some or all of these specific details. The description of the embodiments is merely intended to provide a better understanding of the present application by showing examples of the present application. The present application is not limited to any particular configuration and algorithm disclosed below, but covers any modifications, replacements, and improvements of elements, components, and algorithms without departing from the spirit of the present application. In the accompanying drawings and the following description, well-known structures and techniques are not shown in order to avoid unnecessary obscuring of the present application.

[0026] For the convenience of description, the following describes some nouns or terms related to the embodiments of the present application:

[0027] One-Time Programmable Time, abbreviated as OTP time;

[0028] Gray Response Amplifier, abbreviated as GRA model.

[0029] As introduced in the background, the OTP initial value algorithm in the OLED module in the related art needs to determine the initial value data of gamma one by one, and adjust the gamma value in the band register one by one, that is, if ten luminances need to be adjusted, the initial value of the gamma in the band register needs to be determined in turn, and the gamma value is adjusted from the initial value to the target value in turn to control the display screen to display the corresponding luminance, which needs ten times of time to adjust ten luminances. This will cause the adjustment time to be too long. Moreover, the initial value of the gamma in the band register determined by the OTP initial value algorithm in the OLED module in the related art is quite different from the target value finally adjusted, which will cause the OTP adjustment times to be many and the process time to be long.

[0030] To solve the problem of many adjustment times and too long adjustment time of the OTP initial value algorithm in the OLED module in the related art, the embodiments of the present application provide a method for determining the gamma data of an OLED screen and a display screen.

[0031] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application.

[0032] In the embodiments, a method for determining the gamma data of an OLED screen running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that here.

[0033] FIG. 1 is a flowchart of a method for determining the gamma data of an OLED screen according to the embodiments of the present application. As shown in FIG. 1, the method includes the following steps: S101 and S102.

[0034] S101, a first gamma calculation model is constructed, wherein the first gamma calculation model is trained using a plurality of sets of training data, each set of training data including historical reference gamma data and historical actual gamma data corresponding to the historical reference gamma data obtained in a historical time period, the historical actual gamma data being real gamma data used to control the OLED screen to emit light at a historical time, and the historical reference gamma data being a reference value used to calculate target gamma initial value data;

[0035] Specifically, the band0 register in the OLED module is usually used to set the column address range of the OLED display screen. By setting the band0 register, the column address range of the OLED display screen can be specified, so as to control the position of the display content on the screen. The function of this register is to ensure that the display content can be correctly displayed on a specific position of the OLED display screen.

[0036] Among them, there are multiple band registers in the OLED module, i.e. band0~bandn, the historical reference gamma data is the gamma initial value data of the band0 register at a historical time for calculating the gamma values of other band registers, and the historical actual gamma data is the real gamma data of the band1~bandn registers for controlling the OLED screen to emit light at a historical time. By training the historical reference gamma data and the historical actual gamma data, the mapping relationship between the gamma initial value data of the band0 register and the real gamma data of the band1~bandn registers can be obtained.

[0037] In addition, the OTP initial value algorithm in the related art OLED module needs to determine the gamma initial value data of the band register one by one, and adjust the gamma value in the band register one by one, i.e. if ten luminances need to be adjusted, the gamma initial value of the band register needs to be determined in turn, and the gamma value needs to be adjusted from the initial value to the target value in turn to control the display screen to display the corresponding luminance, which requires ten times of time to adjust ten luminances. This will result in a long adjustment time. Moreover, the gamma initial value of the band register determined by the OTP initial value algorithm in the related art OLED module is quite different from the target value finally adjusted, which will result in a large number of OTP adjustment times and a long process time.

[0038] The first gamma calculation model can directly input the gamma data of the band0 register as the reference value of the gamma value of each band into the gamma calculation model, and output the gamma values of all band registers. When there are ten luminances to be adjusted, the first gamma calculation model inputs the gamma data of ten band0 registers and outputs the gamma values of ten band registers. In this way, ten luminances can be adjusted in one time. Moreover, since the first gamma calculation model is trained according to the historical reference gamma data and the historical actual gamma data, the gamma output value obtained by using the first gamma calculation model is closer to the target value to be adjusted, which reduces the number of OTP adjustment times and greatly reduces the process time.

[0039] Before constructing the first gamma calculation model, the method further includes the following steps:

[0040] S201, obtaining the running parameters of the target OLED screen, the running parameters at least including one of the size, contrast, resolution, and refresh rate of the OLED screen;

[0041] S202, obtaining a second mapping relationship, the second mapping relationship being a mapping relationship between the running parameters of the OLED screen and the reference gamma data;

[0042] S203, determining the target reference gamma data corresponding to the running parameters of the target OLED screen according to the running parameters of the target OLED screen and the second mapping relationship.

[0043] Specifically, the reference gamma data of the band register can be accurately determined through the running parameters of the OLED screen and the mapping relationship between the running parameters and the reference gamma data of the band register. The reference gamma data is data set in advance according to the running parameters of the OLED screen.

[0044] In the OLED module, the gamma data in the band0 register is used to control the brightness and color performance of the display screen. The gamma value is a nonlinear factor used to adjust the brightness and contrast of the display to make the display effect more realistic and natural. By adjusting the gamma value, the gray level and color saturation of the display screen can be improved, thereby improving the display effect and visual experience.

[0045] The first gamma calculation model is constructed, including the following steps: S301 to S303.

[0046] S301, acquire an initial gamma calculation model, the initial gamma calculation model is a model based on a gray scale reactor model;

[0047] The input data dimension of the initial gamma calculation model is the same as the output data dimension.

[0048] Specifically, the input data dimension of the initial gamma calculation model is the same as the output data dimension, which can greatly reduce the process time of determining gamma data, so that multiple brightness can be adjusted at the same time in a very short time.

[0049] S302, acquire historical reference gamma data and historical actual gamma data;

[0050] S303, input the historical reference gamma data and the historical actual gamma data into the initial gamma calculation model for iterative training, and determine the trained model as the first gamma calculation model.

[0051] Specifically, the gray reactor model (Gray Response Amplifier, referred to as GRA) is a gray scale processing technology widely used in OLED (Organic Light Emitting Diode) display screens. The model can adjust the gray level of the pixels of the OLED display screen, so as to realize more accurate and smooth gray scale performance, and improve the display effect and picture quality. The GRA model can improve the color accuracy and brightness uniformity of the OLED display screen, so that the display effect is more realistic and delicate.

[0052] The input of the historical reference gamma data and the historical actual gamma data into the initial gamma calculation model for iterative training includes the following steps: S401 to S403.

[0053] S401, input the historical reference gamma data into the initial gamma calculation model for forward propagation calculation to obtain predicted initial gamma data;

[0054] Each set of training data includes multiple historical reference gamma data, multiple historical actual gamma data, and multiple predicted initial gamma data. The historical reference gamma data, the historical actual gamma data, the predicted initial gamma data, and the register correspond one by one. The input of the historical reference gamma data and the historical actual gamma data into the initial gamma calculation model for iterative training, and the determination of the trained model as the first gamma calculation model include:

[0055] S4011, performing error function calculation on each of the predicted initial gamma data and the corresponding historical actual gamma data to obtain a plurality of sub-computation errors;

[0056] S4012, in the case that all of the sub-computation errors are less than a preset error value, determining that the iterative training of the initial gamma calculation model is completed, and determining the initial gamma calculation model at this time as the first gamma calculation model;

[0057] S4013, in the case that at least one of the sub-computation errors is greater than or equal to the preset error value, performing back propagation calculation on the predicted initial gamma data to continue the iterative training of the initial gamma calculation model until all of the sub-computation errors are less than the preset error value.

[0058] Specifically, the accuracy of the model can be accurately judged by the error function, and the model is continuously trained (i.e., continuously forward propagation and back propagation) according to the accuracy of the model. In the training process, the parameters and hyperparameters of the model are continuously adjusted, which can improve the performance of the model.

[0059] Among them, the parameters and hyperparameters of the algorithm are to help the algorithm learn and adjust the performance of the model. Parameters refer to model parameters such as weights and biases obtained by learning, which directly affect the output of the model. Hyperparameters are parameters that need to be set by humans before model training, such as learning rate, regularization parameter, etc. The selection of hyperparameters will directly affect the performance and training effect of the model. By adjusting the parameters and hyperparameters, the model can better fit the data and improve the generalization ability of the model, so as to obtain better prediction results. Therefore, the selection of parameters and hyperparameters needs to be carefully debugged and optimized.

[0060] S402, performing loss function calculation on the predicted initial gamma data and the corresponding historical actual gamma data to obtain a calculation error, the predicted initial gamma data and the historical actual gamma data corresponding to each other;

[0061] S403, determining whether the iterative training of the initial gamma calculation model is completed according to the size of the calculation error.

[0062] Specifically, the accuracy of the model can be accurately predicted by the error function, and the smaller the error, the higher the accuracy of the model.

[0063] The iteration training of the initial gamma calculation model is determined to be completed according to the size of the calculation error, including: in the case that the calculation error is less than a preset error value, the iteration training of the initial gamma calculation model is determined to be completed, and the initial gamma calculation model at this time is determined as the first gamma calculation model.

[0064] Specifically, since the purpose of the model is to make the predicted gamma data output by the model infinitely close to the actual gamma data, the accuracy of the initial gamma calculation model reaches the standard requirement in the case that the calculation error is less than the preset error value, and the initial gamma calculation model at this time is the first gamma calculation model.

[0065] The initial gamma calculation model includes an input layer, a hidden layer and an output layer, and whether the iteration training of the initial gamma calculation model is completed is determined according to the size of the calculation error, and further includes the following steps:

[0066] S4031, in the case that the calculation error is greater than or equal to the preset error value, the predicted initial gamma data is calculated by back propagation;

[0067] S4032, an optimizer is obtained, and the weights of each layer in the initial gamma calculation model are adjusted based on the calculation error and the optimizer, so as to continue to train the initial gamma calculation model by iteration until the calculation error is less than the preset error value.

[0068] Specifically, in the case that the calculation error is greater than or equal to the preset error value, it is proved that the accuracy of the initial gamma calculation model at this time does not meet the requirement, so the initial gamma calculation model needs to be trained to make the accuracy of the initial gamma calculation model meet the standard requirement. In the process of training the initial gamma calculation model, the weights of each layer in the initial gamma calculation model are adjusted by back propagation calculation, and the parameters and hyperparameters of the model are adjusted by using the optimizer, so as to optimize the performance of the model.

[0069] Wherein, as shown in Figure 2, the input X of the neural network model includes m data, and the output value Ypre is obtained by forward propagation through multiple n layers of processing, wherein Ypre and the dimension of X are the same, also including m data, the comparison of the loss function is carried out between the real value Yreal and the model output value Ypre, and the neural network model is trained according to the comparison result, wherein Ypre is the predicted initial gamma data, Yreal is the actual gamma data, layer1……layern are the first layer……the n-th layer of the neural network model respectively.

[0070] Wherein, the hidden layer of the initial gamma calculation model includes a batch normalization layer, a linear layer and an activation layer, the historical reference gamma data and the historical actual gamma data are input into the initial gamma calculation model for iterative training, including the following steps:

[0071] S501, based on the batch normalization layer, the historical reference gamma data is normalized to obtain normalized gamma data;

[0072] S502, based on the linear layer, the normalized gamma data is nonlinearly changed to obtain nonlinearly changed gamma data;

[0073] S503, based on the activation layer, the nonlinearly changed gamma data is processed for iterative training.

[0074] Specifically, in the neural network, the batch normalization layer can accelerate the training process of the neural network, reduce the problem of gradient disappearance or gradient explosion, and also can reduce the dependence of the neural network on the initial weight, improve the stability of the model, also can reduce the risk of overfitting, improve the generalization ability of the model, and also can make the neural network more easily converge to the optimal solution. The linear layer is a basic component in the neural network, which is used for linear transformation and feature extraction of input data, can realize weighted summation of input data, obtain new feature representation, and can learn the relationship and pattern between input data, thereby improving the expression ability of the model. The activation function in the activation layer can introduce nonlinearity, so that the neural network has stronger expression ability, can make the neural network learn nonlinear relationship and pattern, improve the fitting ability of the model, and can solve the problem of gradient disappearance or gradient explosion, so that the neural network training is more stable and efficient.

[0075] Wherein, as shown in Figure 3, the i-th layer of the neural network model is composed of a normalization layer, a linear layer and an activation layer, and the neural network model has n layers in total.

[0076] S102, obtaining target gamma initial value data according to the target reference gamma data and the first gamma calculation model, and controlling the OLED screen to emit light based on the target gamma initial value data, wherein the target reference gamma data is a reference value for calculating the target gamma initial value data, and the target gamma initial value data includes gamma initial values of all registers for controlling the OLED screen to emit light.

[0077] Specifically, the target reference gamma data is input into the first gamma calculation model, and the output target gamma initial value data is very close to the actual gamma value for finally controlling the OLED screen to emit light, which greatly reduces the adjustment times and adjustment time of the OTP.

[0078] According to the target reference gamma data and the first gamma calculation model, the target gamma initial value data is obtained, including the following steps: S601 to S603.

[0079] S601, extracting model parameters of the first gamma calculation model;

[0080] S602, importing the model parameters of the first gamma calculation model into the OTP algorithm to obtain a second gamma calculation model, wherein the second gamma calculation model is a calculation model with the same structure and parameters as the first gamma calculation model in the OTP algorithm;

[0081] The model parameters of the first gamma calculation model are imported into the OTP algorithm to obtain the second gamma calculation model, including importing forward propagation calculation parameters of the first gamma calculation model into the OTP algorithm to obtain the second gamma calculation model.

[0082] Specifically, the forward propagation calculation parameters of the neural network refer to the parameters used in the forward propagation process of the neural network, which are used to calculate the input data through each layer of neurons and finally obtain the output result. These parameters include weight and bias parameters of each layer, which are used to calculate the output of each layer. The back propagation calculation parameters refer to the parameters used in the back propagation process of the neural network, which are used to calculate the gradient and update the parameters of each layer according to the loss function to minimize the loss function. These parameters include gradient values and learning rates of each layer, which are used to calculate the update value of each layer parameter.

[0083] Therefore, the forward propagation parameters are used to calculate the output result of the neural network, while the back propagation parameters are used to update the parameters of the neural network to improve the performance of the model. Both of them play different but complementary roles in the training process of the neural network.

[0084] Since the first gamma calculation model is already a trained model, it only needs to input the forward propagation calculation parameters into the OTP algorithm to obtain a second gamma calculation model that can run without wasting computing resources and storage resources by transmitting back propagation calculation parameters.

[0085] S603, input the above target reference gamma data as an input value into the second gamma calculation model to obtain the output of the second gamma calculation model as the target gamma initial value data.

[0086] Specifically, importing the model parameters of the first gamma calculation model into the OTP algorithm can directly obtain the second gamma calculation model which is the same as the first gamma calculation model. Importing the model parameters of the first gamma calculation model into the OTP algorithm to obtain the second gamma calculation model can be applied in subsequent applications without separately executing the OTP algorithm and the first gamma calculation model. Instead, the gamma data of band0 is directly input into the OTP algorithm, and finally the gamma initial values of band1-bandn are obtained.

[0087] The role of the OTP algorithm initial value in the OLED module is to initialize and calibrate the OLED module. These initial values include the brightness, contrast, color and other parameters of the OLED. By adjusting these initial values, the OLED display effect can be more clear, accurate and stable. The role of these initial values is to ensure the consistency and stability of the OLED display effect, so that it can achieve the best display effect in different environments.

[0088] The OTP (One-Time-Programming) initial value algorithm in the OLED module is a one-time programming process for writing initial parameters or specific data to the OLED module. This algorithm is usually designed and implemented by the manufacturer of the OLED module, and its specific implementation method may vary depending on different OLED module models and manufacturers. Generally, this algorithm writes initial parameters or specific data into the OTP memory of the OLED module to ensure that the OLED module can work normally and have preset characteristics when it is shipped. This process is usually completed during the manufacturing process, and once it is completed, these data cannot be modified or erased, so it is called one-time programming.

[0089] There is a certain relationship between the OTP adjustment time and the gamma register initial value, because both the OTP adjustment time and the gamma register initial value are parameters used to adjust the display screen, thereby affecting the display effect. Generally speaking, the gamma register initial value affects the brightness and contrast of the display screen, while the OTP adjustment time affects the response speed and stability of the display screen. Therefore, there is a certain correlation between the two, and by adjusting the gamma register initial value, the display effect can be affected, thereby indirectly affecting the demand for OTP adjustment time. Therefore, the relationship between the adjustment time and the gamma register initial value needs to be analyzed and adjusted according to the specific display screen and requirements.

[0090] wherein the target reference gamma data has multiple, the target gamma initial value data has multiple, the target reference gamma data and the target gamma initial value data correspond one by one, each target gamma initial value data is the gamma initial value of the corresponding register, the target reference gamma data is input as an input value into the second gamma calculation model, and the output of the second gamma calculation model is the target gamma initial value data, comprising: inputting all target gamma reference data into the second gamma calculation model at the same time, so that the second gamma calculation model outputs all target gamma initial value data at the same time.

[0091] Specifically, this can simultaneously obtain all target gamma initial value data in one time, greatly saving the process time.

[0092] wherein, based on the target gamma initial value data, the OLED screen emits light, comprising the following steps: S701 and S702.

[0093] S701, input the target gamma initial value data into the OTP algorithm;

[0094] wherein, the target gamma initial value data of different registers is different.

[0095] Specifically, different band registers may have different purposes or functions, so their gamma initial value data will also be different. Gamma value is usually used to adjust the brightness and contrast of the display to ensure the accuracy and clarity of image display. Different band registers may require different gamma initial value data to meet specific display requirements or application scenarios. Therefore, even if the band registers are adjacent, their gamma initial value data may be different.

[0096] The absolute value of the difference between the target gamma initial value data of one of the registers and the corresponding target gamma data is less than or equal to a preset absolute value.

[0097] Specifically, since the second gamma calculation model is the same model as the first gamma calculation model, and the first gamma calculation model is trained by using the reference gamma data and the actual gamma data, the target gamma initial value data of the register obtained by using the second gamma calculation model is very close to the target gamma data finally used for controlling the OLED screen to emit light, which greatly reduces the adjustment times and adjustment time of the OTP.

[0098] S702, adjusting the gamma data of each of the registers by using the OTP algorithm and based on the target gamma initial value data corresponding to each of the registers, to obtain target gamma data corresponding to each of the registers, the target gamma data being used for controlling the OLED screen to display the target brightness.

[0099] Specifically, only the gamma initial value data of the register is obtained by using the second gamma calculation model, and the OTP algorithm needs to be used to adjust the gamma initial value data, so as to obtain the target gamma data finally used for controlling the OLED screen to display the target brightness. Since the target gamma initial value data is very close to the target gamma data finally used for controlling the OLED screen to emit light, the adjustment times and adjustment time of the OTP are greatly reduced.

[0100] The adjusting the gamma data of each of the registers by using the OTP algorithm and based on the target gamma initial value data corresponding to each of the registers, to obtain target gamma data corresponding to each of the registers, includes the following steps:

[0101] S7021, obtaining the target display brightness of the OLED screen;

[0102] S7022, obtaining a first mapping relationship, the first mapping relationship being a corresponding relationship between the display brightness of the OLED screen and the gamma data of each of the registers;

[0103] S7023, determining the target gamma data corresponding to each of the registers according to the target display brightness of the OLED screen and the first mapping relationship.

[0104] Specifically, since the gamma data in the band0 register is used to control the brightness and color performance of the display screen, and is used to adjust the brightness and contrast of the display, by adjusting the gamma value, the gray level and color saturation of the display screen can be improved, thereby improving the display effect and visual experience. Therefore, the target display brightness required by the OLED screen needs to be determined first, and then the numerical value of the gamma data required by each band register is determined, and the gamma data in the band register is adjusted based on the gamma numerical value.

[0105] The method further includes obtaining a plurality of data adjustment times, the data adjustment times corresponding to the registers one by one, the data adjustment time being an adjustment time for adjusting the gamma data of the register based on the corresponding target gamma initial value data using the OTP algorithm, and the data adjustment time being less than or equal to a preset time.

[0106] Specifically, since the target gamma initial value data is very close to the target gamma data used to control the OLED screen to emit light, the number of OTP adjustments and the adjustment time are greatly reduced, that is, the OTP adjustment time using the above embodiment is much less than the OTP adjustment time in the related art.

[0107] The above method for determining the gamma data of the OLED screen of the present application first trains the first gamma calculation model using the reference value used to calculate the target gamma initial value data at the historical moment and the real gamma data used to control the OLED screen to emit light at the historical moment corresponding thereto; then, the target gamma initial value data is obtained according to the target reference gamma data and the first gamma calculation model, and the OLED screen is controlled to emit light based on the target gamma initial value data, wherein the target reference gamma data is the reference value used to calculate the target gamma initial value data, and the target gamma initial value data includes the gamma initial value of all registers used to control the OLED screen to emit light. This method can directly input the gamma data of the band0 register as the reference value of the gamma value of each band into the gamma calculation model, and output the gamma value of all band registers at the same time, which can adjust ten brightness levels in one time, reduce the number of OTP adjustments, greatly reduce the process time, and solve the problems of too many adjustment times of the OTP initial value algorithm in the OLED module in the related art and too long adjustment time.

[0108] FIG. 4 is a flow diagram of another method for determining gamma data of an OLED screen. As shown in FIG. 4, the method first performs data analysis by an OTP algorithm to obtain historical reference gamma data and historical actual gamma data corresponding to the historical reference gamma data. Then, the historical reference gamma data and the historical actual gamma data corresponding to the historical reference gamma data are batch imported into a MySQL lightweight database system to obtain a gamma data table. Then, data in the gamma data table is read and different structure Ctorch framework algorithm models are established for each item to train a GRA algorithm model. Then, the GRA algorithm model is iteratively trained to obtain a trained GRA algorithm model as a first gamma calculation model. Model parameters of the first gamma calculation model are exported to an OTP program to obtain a GRA algorithm model with the same structure in the OTP as a second gamma calculation model. Then, gamma reference data of band0 is input into the second gamma calculation model to obtain model output as gamma initial value data of band1-bandn.

[0109] FIGS. 5-10 are effect diagrams of a method for determining gamma data of an OLED screen, which uses a large amount of data to verify the effect of the method for determining gamma data of the OLED screen.

[0110] As shown in FIG. 5, in the case of a gray value of 0, data with an error between the target gamma initial value data of the band1 register and the target gamma data within <5 accounts for 87% of the overall test data, data with an error between the target gamma initial value data of the band1 register and the target gamma data within >5 and <10 accounts for 12.86% of the overall test data, data with an error between the target gamma initial value data of the band1 register and the target gamma data within >10 and <15 accounts for 0.15% of the overall test data, and data with an error between the target gamma initial value data of the band1 register and the target gamma data within >15 accounts for 0% of the overall test data.

[0111] As shown in FIG. 6, in the case of a gray value of 1, data with an error between the target gamma initial value data of the band1 register and the target gamma data within <5 accounts for 99.25% of the overall test data, data with an error between the target gamma initial value data of the band1 register and the target gamma data within >5 and <10 accounts for 0.75% of the overall test data, and data with an error between the target gamma initial value data of the band1 register and the target gamma data within >10 accounts for 0% of the overall test data.

[0112] As shown in FIG. 7, in the case of the gray scale value of 2, the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of <5 accounts for 98.95% of the overall test data, the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of >5 and <10 accounts for 1.05% of the overall test data, and the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of >10 accounts for 0% of the overall test data.

[0113] As shown in FIG. 8, in the case of the gray scale value of 3, the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of <5 accounts for 95.37% of the overall test data, the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of >5 and <10 accounts for 4.63% of the overall test data, and the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of >10 accounts for 0% of the overall test data.

[0114] As shown in FIG. 9, in the case of the gray scale value of 4, the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of <5 accounts for 99.25% of the overall test data, the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of >5 and <10 accounts for 0.75% of the overall test data, and the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of >10 accounts for 0% of the overall test data.

[0115] As shown in FIG. 10, in the case of the gray scale value of 5, the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of <5 accounts for 98.8% of the overall test data, the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of >5 and <10 accounts for 1.2% of the overall test data, and the data whose error between the target gamma initial value data of the bandl register and the target gamma data is within the range of >10 accounts for 0% of the overall test data.

[0116] From the test data, it can be seen that the error between the target gamma initial value data of the band register and the target gamma data obtained by using the above OLED screen gamma data determination method is generally controlled within the range of less than 5, and the error of a small amount of data is within the range of greater than 5 and less than 10. It can be determined that the gamma initial value obtained by using the determination method of the present application will be closer to the target value to be finally adjusted, which will reduce the number of OTP adjustment times and adjustment time, and greatly reduce the process time.

[0117] In the embodiment, a display screen is also provided. FIG. 11 is a schematic diagram of the display screen provided in the embodiment of the present application. As shown in FIG. 11, the display screen also includes a display panel 100. The brightness of the display screen is determined according to the gamma data in each register, and the gamma data in each of the above registers is determined by using any one of the above OLED screen gamma data determination methods.

[0118] In addition to the OLED main screen, other bands in the OLED module can include components such as touch screens, fingerprint identifiers, cameras, speakers, microphones, etc. These components can be integrated with the OLED main screen to form a complete OLED module for use in devices such as mobile phones, tablets, smart watches, etc.

[0119] The brightness of the display screen of the present application is determined according to the gamma data in each register, and the gamma data in each of the above registers is determined by using any one of the above OLED screen gamma data determination methods. The display screen can directly input the gamma data of the band0 register as the reference value of the gamma value of each band into the gamma calculation model, and output the gamma value of all band registers at the same time. Ten brightnesses can be adjusted in one time, the number of OTP adjustment times is reduced, the process time is greatly reduced, and the problem of too many adjustment times and too long adjustment time of the OTP initial value algorithm in the OLED module in the related art is solved.

[0120] It should also be noted that the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusion, so that processes, methods, articles, or devices that include a series of elements not only include those elements, but also include other elements not explicitly listed, or other elements inherent to such processes, methods, articles, or devices. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article, or device that includes the element.

[0121] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0122] 1) The method for determining the gamma data of the OLED screen according to the present application, first, the reference value used for calculating the target gamma initial value data at the historical moment and the real gamma data used for controlling the OLED screen to emit light at the historical moment corresponding to the reference value are trained to obtain a first gamma calculation model; then, the target gamma initial value data is obtained according to the target reference gamma data and the first gamma calculation model, and the OLED screen is controlled to emit light based on the target gamma initial value data, wherein the target reference gamma data is the reference value used for calculating the target gamma initial value data, and the target gamma initial value data includes the gamma initial value of all registers for controlling the OLED screen to emit light. This method can directly input the gamma data of the band0 register as the reference value of the gamma value of each band into the gamma calculation model, and output the gamma value of all band registers at the same time, which can adjust ten luminances in one time, reduce the number of OTP adjustment times, greatly reduce the process time, and solve the problems of the related art that the adjustment number of the OTP initial value algorithm in the OLED module is large, and the adjustment time is too long.

[0123] 2) The display screen according to the present application, the luminance of which is determined according to the gamma data in each register, and the gamma data in each register is determined by using any one of the above-mentioned methods for determining the gamma data of the OLED screen. This display screen can directly input the gamma data of the band0 register as the reference value of the gamma value of each band into the gamma calculation model, and output the gamma value of all band registers at the same time, which can adjust ten luminances in one time, reduce the number of OTP adjustment times, greatly reduce the process time, and solve the problems of the related art that the adjustment number of the OTP initial value algorithm in the OLED module is large, and the adjustment time is too long.

[0124] Those skilled in the art should understand that the above-mentioned embodiments are all exemplary but not limiting. Different technical features appearing in different embodiments can be combined to achieve beneficial effects. Based on the drawings, the specification and the claims, those skilled in the art should understand and implement other changed embodiments of the disclosed embodiments. In the claims, the term "comprising" does not exclude other devices or steps; the article is intended to include one or more articles and can be used interchangeably with "one or more articles"; the terms "first", "second" are used to mark names and not to represent any specific order. Any reference signs in the claims should not be understood as limiting the scope of protection. The functions of multiple parts appearing in the claims can be implemented by a single hardware or software module. The fact that certain technical features appear in different dependent claims does not mean that these technical features cannot be combined to achieve beneficial effects.

Claims

1. A method for determining gamma data of an OLED screen, comprising: constructing a first gamma calculation model, wherein the first gamma calculation model is trained using a plurality of sets of training data, each set of training data including historical reference gamma data and historical actual gamma data corresponding to the historical reference gamma data obtained in a historical time period, the historical actual gamma data being real gamma data used to control the OLED screen to emit light at a historical time, and the historical reference gamma data being a reference value used to calculate target gamma initial value data; obtaining target gamma initial value data according to target reference gamma data and the first gamma calculation model, and controlling the OLED screen to emit light based on the target gamma initial value data, wherein the target reference gamma data is a reference value used to calculate target gamma initial value data, and the target gamma initial value data includes gamma initial values of all registers used to control the OLED screen to emit light.

2. The determination method according to claim 1, wherein constructing a first gamma calculation model, comprising: obtaining an initial gamma calculation model, the initial gamma calculation model being a model based on a gray scale reactor model; obtaining historical reference gamma data and historical actual gamma data; inputting the historical reference gamma data and the historical actual gamma data into the initial gamma calculation model for iterative training, and determining the trained model as the first gamma calculation model.

3. The determination method according to claim 2, wherein inputting the historical reference gamma data and the historical actual gamma data into the initial gamma calculation model for iterative training, comprising: inputting the historical reference gamma data into the initial gamma calculation model for forward propagation calculation to obtain predicted initial gamma data; performing loss function calculation on the predicted initial gamma data and corresponding historical actual gamma data to obtain a calculation error, the predicted initial gamma data and the historical actual gamma data corresponding one-to-one; determining whether the iterative training of the initial gamma calculation model is completed according to the size of the calculation error.

4. The determination method according to claim 3, wherein determining whether the iterative training of the initial gamma calculation model is completed according to the size of the calculation error, comprising: in a case where the calculation error is less than a preset error value, determining that the iterative training of the initial gamma calculation model is completed, and determining the initial gamma calculation model at this time as the first gamma calculation model.

5. The determination method according to claim 3, wherein the initial gamma calculation model includes an input layer, a hidden layer and an output layer, and determining whether the iterative training of the initial gamma calculation model is completed according to the size of the calculation error, comprising: in a case where the calculation error is greater than or equal to a preset error value, performing back propagation calculation on the predicted initial gamma data; An optimizer is acquired, and weights of each layer in the initial gamma calculation model are adjusted based on the calculation error and the optimizer to continue iterative training of the initial gamma calculation model until the calculation error is less than the preset error value.

6. The determination method according to claim 3, wherein Each set of training data includes a plurality of the historical reference gamma data, a plurality of the historical actual gamma data, and a plurality of the predicted initial gamma data, the historical reference gamma data, the historical actual gamma data, the predicted initial gamma data, and the register one-to-one corresponding, the historical reference gamma data and the historical actual gamma data are input into the initial gamma calculation model for iterative training, and a trained model is determined as the first gamma calculation model, including: An error function calculation is performed on each of the predicted initial gamma data and the corresponding historical actual gamma data to obtain a plurality of sub-calculated errors. In a case where all of the sub-calculated errors are less than a preset error value, it is determined that the iterative training of the initial gamma calculation model is completed, and the initial gamma calculation model at this time is determined as the first gamma calculation model. In a case where at least one of the sub-calculated errors is greater than or equal to the preset error value, back propagation calculation is performed on the predicted initial gamma data to continue iterative training of the initial gamma calculation model until all of the sub-calculated errors are less than the preset error value.

7. The determination method according to claim 2, wherein The input data dimension of the initial gamma calculation model is the same as the output data dimension.

8. The determination method according to claim 2, wherein The hidden layer of the initial gamma calculation model includes a batch normalization layer, a linear layer, and an activation layer, the historical reference gamma data and the historical actual gamma data are input into the initial gamma calculation model for iterative training, including: The historical reference gamma data is normalized based on the batch normalization layer to obtain normalized gamma data; The normalized gamma data is subjected to non-linear change based on the linear layer to obtain non-linearly changed gamma data; The non-linearly changed gamma data is processed based on the activation layer for iterative training.

9. The determination method according to claim 1, wherein, According to the target reference gamma data and the first gamma calculation model, target gamma initial value data is obtained, including: Model parameters of the first gamma calculation model are extracted; The model parameters of the first gamma calculation model are imported into an OTP algorithm to obtain a second gamma calculation model, the second gamma calculation model being a calculation model in the OTP algorithm that has the same structure and parameters as the first gamma calculation model; The target reference gamma data is input into the second gamma calculation model as an input value, and the output of the second gamma calculation model is the target gamma initial value data.

10. The determination method according to claim 9, wherein Importing model parameters of the first gamma calculation model into an OTP algorithm to obtain a second gamma calculation model, including: Importing forward propagation calculation parameters of the first gamma calculation model into the OTP algorithm to obtain the second gamma calculation model.

11. The determination method according to claim 9, wherein The target reference gamma data are multiple, the target gamma initial value data are multiple, the target reference gamma data correspond to the target gamma initial value data one by one, each target gamma initial value data is a gamma initial value of a corresponding register, the target reference gamma data are input into the second gamma calculation model as input values, and output of the second gamma calculation model is the target gamma initial value data, including: All the target gamma reference data are input into the second gamma calculation model at the same time, so that the second gamma calculation model outputs all the target gamma initial value data at the same time.

12. The determination method according to claim 1, wherein, Controlling the OLED screen to emit light based on the target gamma initial value data, including: Inputting the target gamma initial value data into the OTP algorithm; Adjusting gamma data of each register based on the target gamma initial value data corresponding to the register by using the OTP algorithm, to obtain target gamma data corresponding to the register, and the target gamma data are used to control the OLED screen to display a target brightness.

13. The determination method according to claim 12, wherein Adjusting gamma data of each register based on the target gamma initial value data corresponding to the register by using the OTP algorithm, to obtain target gamma data corresponding to the register, including: Obtaining a target display brightness of the OLED screen; Obtaining a first mapping relationship, the first mapping relationship being a corresponding relationship between display brightness of the OLED screen and gamma data of each register; Determining target gamma data corresponding to each register according to the target display brightness of the OLED screen and the first mapping relationship.

14. The determination method according to claim 12, wherein The target gamma initial value data of different registers are different.

15. The determination method according to claim 12, wherein, An absolute value of a difference between the target gamma initial value data of one register and corresponding target gamma data is less than or equal to a preset absolute value.

16. The determination method according to claim 12, further comprising: Obtaining multiple data adjustment times, the data adjustment times corresponding to the registers one by one, the data adjustment time being an adjustment time of adjusting gamma data of the register based on the target gamma initial value data corresponding to the register by using the OTP algorithm, and the data adjustment time being less than or equal to a preset time.

17. The determination method according to claim 1, before constructing the first gamma calculation model, the method further comprising: obtaining an operation parameter of a target OLED screen, the operation parameter comprising at least one of the following: size, contrast, resolution, refresh rate of the OLED screen; obtaining a second mapping relationship between the operation parameter of the OLED screen and reference gamma data, determining the target reference gamma data corresponding to the operation parameter of the target OLED screen according to the operation parameter of the target OLED screen and the second mapping relationship.

18. A display screen, brightness of the display screen being determined according to gamma data in each register, the gamma data in each register being determined by the method for determining gamma data of an OLED screen according to any one of claims 1 to 17.

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