Touch data processing method and device, electronic equipment and storage medium

Abstract

The application discloses a kind of touch data processing method, device, electronic equipment and storage medium.Therein, the method includes: obtaining current touch data generated in touch screen, wherein the current touch data is used to indicate whether touch medium performs touch operation at different touch coordinate points of the touch screen, and the current touch data includes pressing force information and touch coordinate point information;Using data recognition model to identify the current touch data, to obtain recognition result;When the recognition result is that the touch medium does not contact the touch screen, it is determined that the touch coordinate point information does not need to be reported to the target host;When the recognition result is that the touch medium contacts the touch screen, it is determined that the touch coordinate point information is reported to the target host.The application solves the technical problem that the accuracy of processing touch data of the touch screen in the prior art is low, which leads to a high writing level of the touch screen.

Description

Technical Field

[0001] This invention relates to the field of data processing, and more specifically, to a method, apparatus, electronic device, and storage medium for processing touch data. Background Technology

[0002] Currently, in the field of touch screens, the biggest factor affecting the user's writing experience is the writing height. The writing height is the maximum distance between the pen / finger and the screen when the pen / finger can write on the screen (i.e., the system can recognize the pen / finger touch). Obviously, the lower the writing height, the better the user experience.

[0003] In existing technologies, 1) capacitive touchscreens can achieve zero-height writing, but since capacitive touchscreens rely on fingers for writing / touching, fingers are too thick to achieve the fine calligraphy required, necessitating the use of expensive electronic pens. 2) In the field of infrared touch, the common methods for reducing writing height currently focus on structural / transparent materials to narrow the light path as much as possible, allowing infrared light to propagate close to the glass screen. While this method can reduce writing height to some extent, it reduces the amount of light emitted due to the narrowed light path, requiring further increases in emission power, which is not energy-efficient. Furthermore, the glass is not completely flat; according to actual measurements, the glass on large-size screens (such as 86 inches) is uneven, with an average indentation of about 5mm. This means that even in the indented areas of the screen, the writing height remains relatively high, failing to fundamentally solve the writing height problem.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a method, apparatus, electronic device, and storage medium for processing touch data, in order to at least solve the technical problem in the prior art where the accuracy of processing touch data on a touch screen is low, resulting in a high writing height on the touch screen.

[0006] According to one aspect of the present invention, a method for processing touch data is provided, comprising: acquiring current touch data generated on a touch screen, wherein the current touch data is used to characterize whether a touch medium performs a touch operation at different touch coordinate points on the touch screen, and the current touch data includes: pressure information and touch coordinate point information; identifying the current touch data using a data recognition model to obtain a recognition result; determining that it is unnecessary to report the touch coordinate point information to a target host when the recognition result indicates that the touch medium is not in contact with the touch screen; and determining that the touch coordinate point information is reported to the target host when the recognition result indicates that the touch medium is in contact with the touch screen.

[0007] Optionally, before acquiring the touch data generated on the touchscreen and the reported data, the method further includes: acquiring sample touch data of the touchscreen, wherein the sample touch data is used to characterize whether the touch medium performs a touch operation at different touch coordinate points on the touchscreen, and the sample touch data includes: pressure information and touch coordinate point information; performing data calibration processing on the sample touch data to obtain calibrated sample data, wherein the calibrated sample data includes: first sample data, second sample data, and third sample data, wherein the first sample data is the data when the touch medium is not in contact with the touchscreen, and the second and third sample data are the data when the touch medium is in contact with the touchscreen, and the contact pressure level of the second sample data is lower than the contact pressure level of the third sample data; and using the calibrated sample data to train the neural network model to be trained to obtain the data recognition model.

[0008] Optionally, the process of using a data recognition model to identify the current touch data and obtain the recognition result includes: inputting the current touch data into the data recognition model; using the data recognition model to identify the touch coordinate point information in the current touch data to determine whether the touch medium is in contact with the touch screen; and when it is identified that the touch medium is in contact with the touch screen, using the data recognition model to identify the pressure information in the current touch data to determine the contact pressure level when the touch medium is in contact with the touch screen.

[0009] Optionally, determining to report the aforementioned touch coordinate point information to the aforementioned target host includes: detecting whether the aforementioned touch screen outputs the aforementioned touch coordinate point information to the aforementioned target host; if the detection result is yes, then determining to report the aforementioned touch coordinate point information to the aforementioned target host.

[0010] Optionally, after determining to report the aforementioned touch coordinate point information to the aforementioned target host, the method further includes: obtaining the aforementioned contact pressure level identified by the aforementioned data recognition model; and reporting the aforementioned touch coordinate point information and the aforementioned contact pressure level to the aforementioned target host.

[0011] Optionally, after reporting the touch coordinate point information and the contact pressure level to the target host, the method further includes: receiving writing control information returned by the target host, wherein the target host determines the writing control information based on the touch coordinate point information and the contact pressure level; and generating writing on the touch screen corresponding to the writing control information.

[0012] According to another aspect of the present invention, a touch data processing apparatus is also provided, comprising: a first acquisition module, configured to acquire current touch data generated on a touch screen, wherein the current touch data is used to characterize whether a touch medium performs a touch operation at different touch coordinate points on the touch screen, and the current touch data includes: pressure information and touch coordinate point information; an identification module, configured to identify the current touch data using a data identification model to obtain an identification result; and a processing module, configured to determine that, when the identification result indicates that the touch medium has not touched the touch screen, it is not necessary to report the touch coordinate point information to a target host; and to determine that, when the identification result indicates that the touch medium has touched the touch screen, it is necessary to report the touch coordinate point information to the target host.

[0013] Optionally, the above device further includes: a second acquisition module, used to acquire sample touch data of the touch screen, wherein the sample touch data is used to characterize whether the touch medium performs a touch operation at different touch coordinate points of the touch screen, and the sample touch data includes: pressure information and touch coordinate point information; a calibration processing module, used to perform data calibration processing on the sample touch data to obtain calibrated sample data, wherein the calibrated sample data includes: first sample data, second sample data, and third sample data, wherein the first sample data is the data when the touch medium is not in contact with the touch screen, and the second and third sample data are the data when the touch medium is in contact with the touch screen, and the contact pressure level of the second sample data is lower than the contact pressure level of the third sample data; and a training module, used to train the neural network model to be trained using the calibrated sample data to obtain the data recognition model.

[0014] According to another aspect of the present invention, a non-volatile storage medium is also provided, wherein the non-volatile storage medium stores a plurality of instructions, the instructions being adapted to be loaded by a processor and executed any one of the above-described touch data processing methods.

[0015] According to another aspect of the present invention, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform any of the above-described touch data processing methods.

[0016] In this embodiment of the invention, by acquiring current touch data generated on the touch screen, wherein the current touch data is used to characterize whether the touch medium performs a touch operation at different touch coordinate points on the touch screen, the current touch data includes: pressure information and touch coordinate point information; the current touch data is identified using a data recognition model to obtain a recognition result; when the recognition result indicates that the touch medium is not in contact with the touch screen, it is determined that there is no need to report the touch coordinate point information to the target host; when the recognition result indicates that the touch medium is in contact with the touch screen, it is determined that the touch coordinate point information is reported to the target host, thereby improving the accuracy of touch data processing on the touch screen, thus achieving the technical effect of reducing the writing height of the touch screen, and solving the technical problem in the prior art where the accuracy of touch data processing on the touch screen is low, resulting in a high writing height on the touch screen. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0018] Figure 1 This is a flowchart of a touch data processing method according to an embodiment of the present invention;

[0019] Figure 2 This is a schematic diagram of an implementation system for an optional touch data processing method according to an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of a touch data processing device according to an embodiment of the present invention. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0023] Example 1

[0024] According to an embodiment of the present invention, an embodiment of a method for processing touch data is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0025] Figure 1 This is a flowchart of a touch data processing method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0026] Step S102: Obtain the current touch data generated on the touch screen. The current touch data is used to characterize whether the touch medium performs a touch operation at different touch coordinate points on the touch screen. The current touch data includes: pressure information and touch coordinate point information.

[0027] Step S104: Use a data recognition model to recognize the current touch data and obtain the recognition result;

[0028] Step S106: When the identification result indicates that the touch medium is not in contact with the touch screen, it is determined that there is no need to report the touch coordinate point information to the target host; when the identification result indicates that the touch medium is in contact with the touch screen, it is determined that the touch coordinate point information is reported to the target host.

[0029] In this embodiment of the invention, by acquiring current touch data generated on the touch screen, wherein the current touch data is used to characterize whether the touch medium performs a touch operation at different touch coordinate points on the touch screen, the current touch data includes: pressure information and touch coordinate point information; the current touch data is identified using a data recognition model to obtain a recognition result; when the recognition result indicates that the touch medium is not in contact with the touch screen, it is determined that there is no need to report the touch coordinate point information to the target host; when the recognition result indicates that the touch medium is in contact with the touch screen, it is determined that the touch coordinate point information is reported to the target host, thereby improving the accuracy of touch data processing on the touch screen, thus achieving the technical effect of reducing the writing height of the touch screen, and solving the technical problem in the prior art where the accuracy of touch data processing on the touch screen is low, resulting in a high writing height on the touch screen.

[0030] Optionally, the aforementioned touch medium can be a stylus or a finger. In the embodiments of the application, when the user touches the glass surface of the touch screen with a stylus / finger, it causes deformation. The slight deformation of the glass causes regular changes in the data of continuous local areas (infrared detection frames on the touch screen). In the embodiments of this application, the pressure information and touch coordinate point information are obtained based on the aforementioned slight deformation.

[0031] Optionally, the data recognition model mentioned above can be an artificial intelligence model, a supervised deep learning model such as a convolutional neural network (CNN) model. In this embodiment, an artificial intelligence CNN model is used for supervised deep learning and training. The model is pre-trained to learn the rules of change in sample touch data, thereby identifying whether the pen / finger is in contact with the touch screen, improving the accuracy of processing touch data on the touch screen, and thereby reducing the writing height of the touch screen.

[0032] Optionally, the above-mentioned sample touch data is two-dimensional data, namely real-time infrared frame basic data; in this embodiment of the application, by adopting a data recognition model such as a convolutional neural network model, the above-mentioned calibrated sample data is used as the input parameter of the data recognition model, and the output information is whether it is in contact or not, and the contact pressure level when in contact.

[0033] Optionally, in this embodiment of the application, reporting the above-mentioned touch coordinate point information to the target host can be understood as system reporting. System reporting means that when a finger / pen touches the touch screen, the touch frame system in the touch screen (referring to the hardware and software system deployed on the display screen, a positioning system specifically used to detect the finger / pen) directly locates the position of the finger / pen and reports the coordinates to the system host.

[0034] Optionally, the aforementioned target host is the system host. As an optional embodiment, the touch data processing method provided in this application is applied to the MaxHub large-screen conference machine. For example, if the writing software is opened under the Android system, then the system host refers to the motherboard computer system running Android. For example, if some high-end MaxHub large-screen conference machines come with a PC module (running a Windows system), and the PC module is running and the writing is done in the software on the PC, then the aforementioned system host refers to the PC module.

[0035] In an optional embodiment, before acquiring the touch data generated on the touchscreen and the reported data, the above method further includes:

[0036] Step S202: Obtain sample touch data of the touch screen, wherein the sample touch data is used to characterize whether the touch medium performs touch operation at different touch coordinate points of the touch screen, and the sample touch data includes: pressure information and touch coordinate point information;

[0037] Step S204: Perform data calibration processing on the above-mentioned sample touch data to obtain calibrated sample data. The calibrated sample data includes: first sample data, second sample data, and third sample data. The first sample data is the data when the touch medium is not in contact with the touch screen. The second and third sample data are the data when the touch medium is in contact with the touch screen. The contact pressure level of the second sample data is lower than that of the third sample data.

[0038] Step S206: Use the calibrated sample data to train the neural network model to be trained, and obtain the data recognition model.

[0039] In this embodiment of the application, the above-mentioned data calibration process is used to calibrate whether the above-mentioned sample touch data is data when the above-mentioned touch medium is not in contact with the above-mentioned touch screen, and the contact pressure level when the above-mentioned touch medium is in contact with the above-mentioned touch screen, that is, to calibrate which data is data when the touch medium is in contact with the touch screen, and the contact pressure level when in contact, and which data is data when the touch medium is not in contact with the touch screen.

[0040] Optionally, the first sample data mentioned above, which is the data when the pen / finger is not touching the screen, is data with a large background value. It is data after the infrared light is blocked. For example, it may be due to the background noise caused by other smaller data, which can be ignored.

[0041] Optionally, the second sample data mentioned above refers to the slight deformation of the glass caused by the pen / finger just touching the touch screen. Because of the glass deformation, in addition to the data obscured by the background, a large area of ​​floating data (a small negative data) appears. This data is because the glass deformation changes the light path of infrared light, forming a large area of ​​floating data.

[0042] Optionally, the second sample data mentioned above refers to the pen / finger touching the glass and applying a certain amount of pressure, causing a large deformation of the glass, thus resulting in more data floating up and a larger amount of data change.

[0043] As an alternative embodiment, the actual data clearly shows that when a pen / finger touches the glass, the slight deformation of the glass causes data changes in continuous local areas, thus laying the foundation for CNN network models to achieve low writing height or even pressure level sensing.

[0044] It should be noted that CNN stands for Convolutional Neural Network, which belongs to the field of deep learning and is a supervised deep learning algorithm. It has strong learning capabilities in classification, recognition, and other fields, and can achieve high recognition rates as long as the data has certain features. In addition to using the CNN model, other deep learning models such as recurrent neural networks and recurrent neural networks can also be used in the embodiments of this application. Even simple machine learning models such as classification / regression models can be used. That is, as long as it can accurately identify whether the data is in contact with the screen and the features of screen deformation, it is acceptable. It is not limited to the above-mentioned data recognition models.

[0045] Optionally, in the embodiments of this application, the format of the label may be, but is not limited to, contact / no contact, pressure level. For example, 0 / 1 may be used to represent contact / no contact, and 0 / 1 / 2 / 3 / 4 / 5 may be used to represent the contact pressure level when the touch medium contacts the touch medium.

[0046] In this embodiment of the application, by training a neural network model to be trained, such as the Mobel Net CNN network, a specific data recognition model with certain judgment capabilities can be trained. Using this data recognition model, it is possible to determine whether the newly input current touch data is data where the touch medium is not in contact with the touch screen, or data where the touch medium is in contact with the touch screen.

[0047] As an optional implementation, the trained data recognition model can be deployed through computer software programming. The input is the current touch data generated on the touch screen in real time, and the output is the recognition results such as contact / non-contact / pressure level.

[0048] In one optional embodiment, the identification result obtained by using a data recognition model to identify the aforementioned current touch data includes:

[0049] Step S302: Input the current touch data into the data recognition model.

[0050] Step S304: Use the above data recognition model to identify the touch coordinate point information in the current touch data to determine whether the touch medium is in contact with the touch screen.

[0051] Step S306: When it is identified that the touch medium is in contact with the touch screen, the data recognition model is used to identify the pressure information in the current touch data to determine the contact pressure level when the touch medium contacts the touch screen.

[0052] Through the embodiments of this application, since the data recognition model is trained and learned in a supervised manner during training, the trained data recognition model is used to identify the current touch data. For example, the data recognition model identifies the touch coordinate point information in the current touch data to determine whether the touch medium is in contact with the touch screen. Furthermore, when it is identified that the touch medium is in contact with the touch screen, the data recognition model identifies the pressure information in the current touch data to determine the contact pressure level when the touch medium contacts the touch screen. Thus, based on the recognition results, it can be accurately determined whether the touch coordinate point information needs to be reported to the target host, thereby realizing low writing height and writing pressure sensitivity detection of the touch screen.

[0053] In the embodiments of this application, in the prior art, the touch frame system detects writing (significant changes in two-dimensional data) even before the user's finger / pen touches the screen, and the computer will then consider that there is writing.

[0054] Taking the above data recognition model as a CNN model as an example, this application embodiment uses the CNN model to further recognize the current touch data and outputs whether the finger / pen is in contact with the touch screen and the contact pressure level information when it is in contact with the touch screen. Before reporting the point to the computer system, the output result of the CNN is combined to make a logical judgment. If the touch medium is indeed in contact with the touch screen, the touch screen can be allowed to report the point to the computer. If it is not in contact, the touch screen is not allowed to report the point to the computer, which can be used to reduce the writing height.

[0055] In one optional embodiment, determining to report the aforementioned touch coordinate point information to the aforementioned target host includes:

[0056] Step S402: Detect whether the touch screen outputs the touch coordinate point information to the target host.

[0057] Step S404: If the detection result is yes, then determine to report the above-mentioned touch coordinate point information to the above-mentioned target host.

[0058] Figure 2 This is a schematic diagram of an implementation system for an optional touch data processing method according to an embodiment of the present invention, as shown below. Figure 2 As shown in the embodiment of this application, after obtaining the current touch data, a pre-trained CNN model is used to determine whether there is contact and the level of contact pressure when there is contact. Then, a comprehensive logical judgment is made in combination with the reporting status of the touch screen, and a decision is made on whether to report the touch point to the target host. That is, it is to detect whether the touch screen outputs the above touch coordinate point information to the target host. If the detection result is yes, the above touch coordinate point information is reported to the target host.

[0059] In this embodiment, by adding a CNN model to accurately identify the current touch data, the accuracy of processing touch data on the touch screen can be improved, thereby achieving the technical effect of reducing the writing height of the touch screen.

[0060] In an optional embodiment, after determining that the touch coordinate point information should be reported to the target host, the method further includes:

[0061] Step S502: Obtain the contact pressure level identified by the data recognition model.

[0062] Step S504: Report the above-mentioned touch coordinate point information and the above-mentioned contact pressure level to the above-mentioned target host.

[0063] Optionally, in this embodiment of the application, after determining to report the above-mentioned touch coordinate point information to the above-mentioned target host, the above-mentioned contact pressure level identified by the above-mentioned data recognition model can also be obtained, and the above-mentioned touch coordinate point information and the above-mentioned contact pressure level can be reported to the above-mentioned target host at the same time.

[0064] In an optional embodiment, after reporting the touch coordinate point information and the contact pressure level to the target host, the method further includes:

[0065] Step S602: Receive writing control information returned by the target host, wherein the target host determines the writing control information based on the touch coordinate point information and the contact pressure level.

[0066] Step S604: Generate handwriting on the touch screen corresponding to the writing control information.

[0067] In this embodiment of the application, after the touch coordinate point information and the contact pressure level are reported to the target host, since the target host determines the writing control information based on the touch coordinate point information and the contact pressure level, it can also receive the writing control information returned by the target host and generate writing strokes corresponding to the writing control information on the touch screen.

[0068] Optionally, in this embodiment, writing control information can be combined to control the thickness of the characters written on the touch screen.

[0069] Example 2

[0070] According to an embodiment of the present invention, an apparatus embodiment for implementing the above-described touch data processing method is also provided. Figure 3 This is a schematic diagram of the structure of a touch data processing device according to an embodiment of the present invention, as shown below. Figure 3 As shown, the above-mentioned touch data processing device includes: a first acquisition module 30, a recognition module 32, and a processing module 34, wherein:

[0071] The first acquisition module 30 is used to acquire current touch data generated on the touch screen, wherein the current touch data is used to characterize whether the touch medium performs a touch operation at different touch coordinate points on the touch screen, and the current touch data includes: pressure information and touch coordinate point information; the recognition module 32 is used to recognize the current touch data using a data recognition model to obtain a recognition result; the processing module 34 is used to determine that it is not necessary to report the touch coordinate point information to the target host when the recognition result is that the touch medium has not touched the touch screen; and to determine that the touch coordinate point information is reported to the target host when the recognition result is that the touch medium has touched the touch screen.

[0072] In an optional embodiment, the device further includes: a second acquisition module, configured to acquire sample touch data of the touch screen, wherein the sample touch data is used to characterize whether the touch medium performs a touch operation at different touch coordinate points of the touch screen, and the sample touch data includes: pressure information and touch coordinate point information; a calibration processing module, configured to perform data calibration processing on the sample touch data to obtain calibrated sample data, wherein the calibrated sample data includes: first sample data, second sample data, and third sample data, wherein the first sample data is data when the touch medium is not in contact with the touch screen, and the second and third sample data are data when the touch medium is in contact with the touch screen, and the contact pressure level of the second sample data is lower than the contact pressure level of the third sample data; and a training module, configured to train the neural network model to be trained using the calibrated sample data to obtain the data recognition model.

[0073] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0074] It should be noted that the first acquisition module 30, the identification module 32, and the processing module 34 mentioned above correspond to steps S102 to S106 in Embodiment 1. The instances and application scenarios implemented by the above modules and their corresponding steps are the same, but they are not limited to the content disclosed in Embodiment 1. It should also be noted that the above modules, as part of the device, can run on a computer terminal.

[0075] It should be noted that the optional or preferred implementation methods of this embodiment can be found in the relevant description in Embodiment 1, and will not be repeated here.

[0076] The aforementioned touch data processing device may further include a processor and a memory. The first acquisition module 30, the recognition module 32, and the processing module 34 are all stored in the memory as program units, and the processor executes the aforementioned program units stored in the memory to realize the corresponding functions.

[0077] The processor contains a core that retrieves corresponding program units from memory. One or more cores may be configured. Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory includes at least one memory chip.

[0078] According to an embodiment of this application, an embodiment of a non-volatile storage medium is also provided. Optionally, in this embodiment, the non-volatile storage medium includes a stored program, wherein, when the program runs, it controls the device where the non-volatile storage medium is located to execute any of the touch data processing methods described above.

[0079] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals, and the non-volatile storage medium includes stored programs.

[0080] Optionally, during program execution, the device containing the non-volatile storage medium performs the following functions: acquiring current touch data generated on the touchscreen, wherein the current touch data is used to characterize whether the touch medium performs touch operations at different touch coordinate points on the touchscreen, and the current touch data includes: pressure information and touch coordinate point information; identifying the current touch data using a data recognition model to obtain a recognition result; determining that it is unnecessary to report the touch coordinate point information to the target host when the recognition result indicates that the touch medium is not in contact with the touchscreen; and determining that the touch coordinate point information is reported to the target host when the recognition result indicates that the touch medium is in contact with the touchscreen.

[0081] Optionally, during program execution, the device containing the non-volatile storage medium performs the following functions: acquiring sample touch data of the touch screen, wherein the sample touch data is used to characterize whether the touch medium performs touch operations at different touch coordinate points of the touch screen, and the sample touch data includes: pressure information and touch coordinate point information; performing data calibration processing on the sample touch data to obtain calibrated sample data, wherein the calibrated sample data includes: first sample data, second sample data, and third sample data, wherein the first sample data is the data when the touch medium is not in contact with the touch screen, and the second and third sample data are the data when the touch medium is in contact with the touch screen, and the contact pressure level of the second sample data is lower than the contact pressure level of the third sample data; and using the calibrated sample data to train the neural network model to be trained to obtain the data recognition model.

[0082] Optionally, during program execution, the device containing the non-volatile storage medium is controlled to perform the following functions: inputting the current touch data into the data recognition model; using the data recognition model to identify the touch coordinate point information in the current touch data to determine whether the touch medium is in contact with the touch screen; when it is identified that the touch medium is in contact with the touch screen, using the data recognition model to identify the pressure information in the current touch data to determine the contact pressure level when the touch medium contacts the touch screen.

[0083] Optionally, during program execution, the device containing the non-volatile storage medium is controlled to perform the following functions: detect whether the touch screen outputs the touch coordinate point information to the target host; if the detection result is yes, then determine to report the touch coordinate point information to the target host.

[0084] Optionally, during program execution, the device containing the non-volatile storage medium is controlled to perform the following functions: obtain the contact pressure level identified by the data recognition model; and report the touch coordinate point information and the contact pressure level to the target host.

[0085] Optionally, during program execution, the device containing the non-volatile storage medium is controlled to perform the following functions: receiving writing control information returned by the target host, wherein the target host determines the writing control information based on the touch coordinate point information and the contact pressure level; and generating writing on the touch screen corresponding to the writing control information.

[0086] According to an embodiment of this application, an embodiment of a processor is also provided. Optionally, in this embodiment, the processor is used to run a program, wherein the program executes any of the above-described touch data processing methods during runtime.

[0087] According to an embodiment of this application, an embodiment of an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to perform any of the above-described touch data processing methods.

[0088] According to an embodiment of this application, an embodiment of a computer program product is also provided, which, when executed on a data processing device, is adapted to execute a program that initializes the processing method steps for touch data having any of the above-described steps.

[0089] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0090] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units described above can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0092] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0093] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0094] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a non-volatile storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned non-volatile storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0095] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for processing touch data, characterized in that, include: Acquire current touch data generated on the touch screen, wherein the current touch data is used to characterize whether the touch medium performs touch operation at different touch coordinate points on the touch screen, and the current touch data includes: pressure information and touch coordinate point information; The current touch data is identified using a data recognition model to obtain the recognition result; When the identification result indicates that the touch medium is not in contact with the touch screen, it is determined that there is no need to report the touch coordinate point information to the target host; when the identification result indicates that the touch medium is in contact with the touch screen, it is determined that the touch coordinate point information is reported to the target host. The method further includes, before acquiring and reporting touch data generated on the touchscreen, the following steps: acquiring sample touch data from the touchscreen, wherein the sample touch data characterizes whether the touch medium performs touch operations at different touch coordinate points on the touchscreen, and the sample touch data includes: pressure information and touch coordinate point information; performing data calibration processing on the sample touch data to obtain calibrated sample data, wherein the calibrated sample data includes: first sample data, second sample data, and third sample data, wherein the first sample data is data when the touch medium is not in contact with the touchscreen, and the second and third sample data are data when the touch medium is in contact with the touchscreen, and the contact pressure level of the second sample data is lower than the contact pressure level of the third sample data; and using the calibrated sample data to train the neural network model to be trained to obtain the data recognition model. The step of using a data recognition model to identify the current touch data and obtain the recognition result includes: inputting the current touch data into the data recognition model; using the data recognition model to identify the touch coordinate point information in the current touch data to determine whether the touch medium is in contact with the touch screen; and when it is identified that the touch medium is in contact with the touch screen, using the data recognition model to identify the pressure information in the current touch data to determine the contact pressure level when the touch medium is in contact with the touch screen.

2. The method according to claim 1, characterized in that, Determining to report the touch coordinate point information to the target host includes: Detect whether the touch screen outputs the touch coordinate point information to the target host; If the detection result is yes, then the touch coordinate point information will be reported to the target host.

3. The method according to claim 1, characterized in that, After determining that the touch coordinate point information should be reported to the target host, the method further includes: Obtain the contact pressure level identified by the data recognition model; The touch coordinate point information and the contact pressure level are reported to the target host.

4. The method according to claim 3, characterized in that, After reporting the touch coordinate point information and the contact pressure level to the target host, the method further includes: The system receives writing control information returned by the target host, wherein the target host determines the writing control information based on the touch coordinate point information and the contact pressure level. The handwriting corresponding to the writing control information is generated on the touch screen.

5. A touch data processing device, characterized in that, include: The first acquisition module is used to acquire current touch data generated on the touch screen, wherein the current touch data is used to characterize whether the touch medium performs touch operation at different touch coordinate points on the touch screen, and the current touch data includes: pressure information and touch coordinate point information; The recognition module is used to recognize the current touch data using a data recognition model to obtain the recognition result; The processing module is configured to determine that, when the identification result indicates that the touch medium is not in contact with the touch screen, it is not necessary to report the touch coordinate point information to the target host; and to determine that, when the identification result indicates that the touch medium is in contact with the touch screen, it is necessary to report the touch coordinate point information to the target host. The device further includes: a second acquisition module for acquiring sample touch data of the touch screen, wherein the sample touch data is used to characterize whether the touch medium performs touch operations at different touch coordinate points on the touch screen, and the sample touch data includes: pressure information and touch coordinate point information; a calibration processing module for performing data calibration processing on the sample touch data to obtain calibrated sample data, wherein the calibrated sample data includes: first sample data, second sample data, and third sample data, wherein the first sample data is data when the touch medium is not in contact with the touch screen, the second sample data and the third sample data are data when the touch medium is in contact with the touch screen, and the contact pressure level of the second sample data is less than the contact pressure level of the third sample data; and a training module for training a neural network model to be trained using the calibrated sample data to obtain the data recognition model.

6. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores multiple instructions, which are adapted to be loaded by a processor and executed by the method for processing touch data according to any one of claims 1 to 4.

7. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the touch data processing method according to any one of claims 1 to 4.

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