Large-screen self-adaptive rendering method and device, equipment and storage medium

Abstract

This invention provides a method, apparatus, device, and storage medium for adaptive rendering of large screens, belonging to the interdisciplinary field of intelligent connected vehicles and digital twins. The method includes: acquiring the resolution, refresh rate, and color gamut parameters of the large screen in real time; regenerating a configuration file when parameter changes are detected and trigger preset conditions; dynamically adjusting the resolution and mapping the color gamut according to the configuration file; determining a corresponding rendering strategy based on the adjusted resolution; and monitoring system resource utilization in real time, implementing the determined rendering strategy with different rendering precisions based on different system resource utilization rates. Through the technical solution of this invention, the problem of inconsistent rendering effects on large screens of different levels can be solved by combining resolution scaling and color gamut mapping strategies.

Description

Technical Field

[0001] This invention relates to the field of intelligent connected vehicles and digital twin technology, and in particular to a large-screen adaptive rendering method, apparatus, device and storage medium. Background Technology

[0002] With the development of vehicle-road-cloud integration technology, digital twin display platforms have become a core component in scenarios such as smart transportation and autonomous driving. For example, digital twin systems deployed in some areas need to simultaneously support the rendering requirements of 8K large screens in command centers, 4K screens on roadside terminals, and 1080P screens in vehicles.

[0003] However, the hardware parameters of large screens at different levels vary significantly. Traditional rendering methods use fixed pipelines, resulting in the same digital twin model exhibiting detail loss on an 8K screen, jagged edges on a 4K screen, and color distortion on a 1080P screen. For example, in some areas, there are significant discrepancies between the vehicle trajectories displayed on 8K surveillance screens and 4K screens on roadside terminals. Existing solutions rely on manual configuration of rendering parameters and cannot dynamically respond to screen switching or parameter changes.

[0004] Therefore, there is an urgent need to propose a solution that can adapt to different large screen parameters in order to solve the problem of inconsistent rendering effects on large screens of different levels. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art, and proposes a large-screen adaptive rendering method, apparatus, device and storage medium.

[0006] In a first aspect, embodiments of the present invention provide a large-screen adaptive rendering method, including:

[0007] The system acquires the resolution, refresh rate, and color gamut parameters of the large screen in real time, and regenerates the configuration file when a parameter change is detected and a preset condition is triggered.

[0008] Based on the configuration file, dynamic resolution adjustment and color gamut mapping are performed; at the same time, the corresponding rendering strategy is determined based on the adjusted resolution.

[0009] The system monitors system resource utilization in real time and executes the determined rendering strategy with different rendering precision based on different system resource utilization rates.

[0010] In some embodiments, the process of regenerating the configuration file includes:

[0011] When the resolution change of the large screen is detected multiple times in succession and triggers the first preset condition, the deviation of each detected resolution change is obtained; and / or, when the refresh rate fluctuation of the large screen is detected multiple times in succession and exceeds the second preset condition, the deviation of each detected refresh rate fluctuation is obtained.

[0012] If the deviation of each detected resolution change is less than a preset first deviation threshold, the configuration file is regenerated; and / or, if the deviation of each detected refresh rate fluctuation is less than a preset second deviation threshold, the configuration file is regenerated.

[0013] In some embodiments, the real-time acquisition of the screen's resolution, refresh rate, and color gamut parameters includes:

[0014] Sample the digital signal from the HDMI or DP interface;

[0015] Convert the time-domain signal to the frequency domain and calculate the amplitude and phase of each frequency component;

[0016] Identify the clock frequency components corresponding to the resolution and refresh rate, and parse to obtain the color gamut parameters.

[0017] In some embodiments, the process of mapping the color gamut includes:

[0018] Based on the CIE-Lab color space, sRGB color gamut data is converted to the DCI-P3 color gamut supported by large screens; and after mapping to the DCI-P3 color gamut, it is converted back to sRGB for display.

[0019] In some embodiments, determining the corresponding rendering strategy based on the adjusted resolution includes:

[0020] Depending on the adjusted resolution, enable either an anti-aliasing strategy or a tiled rendering strategy.

[0021] In some embodiments, the process of adopting different rendering precisions based on different system resource utilization rates includes:

[0022] If the system resource utilization rate exceeds the preset utilization rate threshold, a non-critical area precision reduction strategy will be triggered.

[0023] If the system resource utilization rate is less than or equal to the preset utilization rate threshold, it will be displayed with the baseline precision.

[0024] In some embodiments, after triggering the non-critical area downsampling strategy, the method further includes:

[0025] By using Kalman filtering to predict frame rate fluctuations, the deviation between the actual frame rate and the set value is stabilized within a pre-defined deviation range.

[0026] Secondly, embodiments of the present invention provide a large-screen adaptive rendering device, comprising:

[0027] The configuration generation module is used to obtain the resolution, refresh rate and color gamut parameters of the large screen in real time, and regenerate the configuration file when the parameter changes are detected and the parameter changes trigger preset conditions.

[0028] The strategy determination module is used to dynamically adjust the resolution and map the color gamut according to the configuration file; and at the same time, determine the corresponding rendering strategy according to the adjusted resolution.

[0029] The strategy execution module is used to monitor the system resource utilization rate in real time and execute the determined rendering strategy with different rendering precision according to the different system resource utilization rates.

[0030] Thirdly, embodiments of the present invention provide an electronic device, the electronic device comprising:

[0031] At least one processor; and a memory communicatively connected to the at least one processor;

[0032] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the steps of the method according to any embodiment of the present invention.

[0033] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions that are used to cause a processor to execute the steps of any embodiment of the method of the present invention.

[0034] Compared with the prior art, the present invention has the following advantages:

[0035] The large-screen adaptive rendering method provided by this invention first acquires the resolution, refresh rate, and color gamut parameters of the large screen in real time. When a parameter change is detected and triggers a preset condition, a new configuration file is generated. Then, based on the configuration file, dynamic resolution adjustment and color gamut mapping are performed. Simultaneously, a corresponding rendering strategy is determined based on the adjusted resolution. Finally, system resource utilization is monitored in real time, and different rendering precisions are applied to execute the determined rendering strategy based on varying system resource utilization. This technical solution, by acquiring large-screen parameters in real time and combining resolution scaling and color gamut mapping strategies, solves the problem of inconsistent rendering effects on different levels of large screens. Furthermore, by dynamically adjusting rendering precision based on system resource utilization, it ensures rendering quality in critical areas while reducing overall system power consumption. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only preferred embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 A flowchart illustrating a large-screen adaptive rendering method provided in an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of a process for regenerating a configuration file, provided as an embodiment of the present invention.

[0039] Figure 3 This is a schematic diagram of a process for real-time acquisition of large screen parameters provided in an embodiment of the present invention;

[0040] Figure 4 This is a structural block diagram of a large-screen adaptive rendering device provided in an embodiment of the present invention;

[0041] Figure 5 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0043] To enable those skilled in the art to better understand the technical solutions of the present invention, exemplary embodiments of the present invention are described below in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0044] Where there is no conflict, the various embodiments of the present invention and the features thereof may be combined with each other.

[0045] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0046] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Terms such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0047] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having the meaning consistent with their meaning in the context of the relevant art and the invention, and will not be interpreted as having an idealized or overly formal meaning unless expressly so defined herein.

[0048] In the technical solution of this invention, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information all comply with relevant laws and regulations and do not violate public order and good morals. The use of user data in this technical solution follows relevant national laws and regulations (e.g., the "Information Security Technology - Personal Information Security Specification"). For example: appropriate measures are taken for personal information access control; restrictions are imposed on the display of personal information; the purpose of using personal information does not exceed the scope of direct or reasonable association; and explicit identity targeting is eliminated when using personal information to avoid precisely locating a specific individual.

[0049] Figure 1 This is a flowchart illustrating a large-screen adaptive rendering method provided in an embodiment of the present invention. This method is particularly suitable for scenarios where digital twin models are displayed on multi-level large screens. The method can be executed by a large-screen adaptive rendering device, which can be implemented in software and / or hardware and can be configured in an electronic device.

[0050] like Figure 1 As shown, the method specifically includes:

[0051] S1 acquires the resolution, refresh rate, and color gamut parameters of the large screen in real time, and regenerates the configuration file when a parameter change is detected and a preset condition is triggered.

[0052] Traditional systems obtain large-screen parameters through preset configuration files and cannot read dynamic parameters from HDMI or DP interfaces in real time. When the large screen switches resolutions due to a malfunction, such as downgrading from 8K to 4K, the system takes 3-5 minutes to detect the change, during which time the image may be stretched or compressed.

[0053] In this embodiment, the system can read the resolution, refresh rate, and color gamut parameters of the large screen in real time via an HDMI or DP interface. HDMI (High-Definition Multimedia Interface) refers to a high-definition multimedia interface used to transmit high-definition video and audio signals, supporting 1080P, 4K, and 8K resolutions. DP (Display Port) refers to a display port, a high-definition digital display interface standard that supports high refresh rates and wide color gamuts.

[0054] The resolution of a large screen refers to the total number of pixels horizontally and vertically on the screen. It is a core indicator of the screen's clarity and sharpness; the higher the value, the more detailed the image, the fewer jagged edges, and the clearer the details. Examples include 1080P resolution, 4K resolution, and 8K resolution.

[0055] The refresh rate of a large screen refers to the number of times the screen can refresh the displayed images per second, measured in Hertz (Hz). The higher the refresh rate, the smoother the picture, the less ghosting, and the more fluid the motion. Examples include 60Hz and 120Hz.

[0056] The color gamut parameter of a large screen refers to the range or total number of colors that the screen can display. A higher value indicates more, more vibrant, and more realistic colors that can be displayed. Examples include sRGB and DCI-P3. sRGB (Standard Red, Green, Blue) refers to the standard red, green, and blue color space. DCI-P3 (Digital Cinema Initiatives-P3) refers to the wide color gamut standard for digital cinema, with a color gamut range greater than sRGB.

[0057] Figure 2 This is a schematic diagram of a process for regenerating a configuration file according to an embodiment of the present invention, such as... Figure 2 As shown, in some embodiments, the process of regenerating the configuration file includes:

[0058] S101, when the resolution change of the large screen is detected multiple times in succession and triggers the first preset condition, the deviation of each detected resolution change is obtained; and / or, when the refresh rate fluctuation of the large screen is detected multiple times in succession and exceeds the second preset condition, the deviation of each detected refresh rate fluctuation is obtained.

[0059] The first preset condition can be set as: a resolution change exceeding 10%, for example, a resolution change from 4K to 8K. When the first preset condition is triggered multiple times, the deviation of each detected resolution change is obtained. For example, multiple consecutive triggers are set to three consecutive times; when the resolution change of the large screen is detected to exceed 10% three times consecutively, the deviation between these three consecutive detected resolutions is obtained.

[0060] The second preset condition can be set as: refresh rate fluctuation exceeding 5Hz. When the second preset condition is triggered multiple times, the deviation of the detected refresh rate fluctuation is obtained for each instance. For example, multiple times is set to three consecutive times; when the refresh rate fluctuation of the large screen is detected to exceed 5Hz three consecutive times, the deviation between these three consecutive detected refresh rates is obtained.

[0061] S102, if the deviation of the detected resolution change is less than the preset first deviation threshold, the configuration file is regenerated; and / or, if the deviation of the detected refresh rate fluctuation is less than the preset second deviation threshold, the configuration file is regenerated.

[0062] If the deviation between three consecutive detected resolutions is less than a preset deviation threshold, for example, if the deviation is less than 0.5%, the configuration file is regenerated; and / or, if the deviation between three consecutive detected refresh rates is less than a preset deviation threshold, for example, if the deviation is less than 0.5%, the configuration file is regenerated.

[0063] Figure 3 This is a flowchart illustrating a real-time acquisition of large screen parameters provided by an embodiment of the present invention, as shown below. Figure 3 As shown, in some embodiments, the process of acquiring the resolution, refresh rate, and color gamut parameters of the large screen in real time includes:

[0064] S1011 samples the digital signal from the HDMI or DP interface.

[0065] S1012 converts the time-domain signal into the frequency domain and calculates the amplitude and phase of each frequency component.

[0066] S1013 identifies the main frequency components corresponding to the resolution and refresh rate, and parses and obtains the color gamut parameters.

[0067] In this embodiment, the interface signals of the HDMI or DP interface can be analyzed by using the FFT algorithm to ensure that the parameter reading accuracy error is less than 0.5%. The FFT algorithm, or Fast Fourier Transform, is used to convert time-domain signals into frequency-domain signals for signal analysis.

[0068] The spectrum analysis process includes: sampling the digital signals from the HDMI or DP interface at a frequency of 1 GHz to ensure full signal coverage, and applying a Hanning window to reduce spectral leakage with a window function length of 1024 points; using an FFT algorithm to convert the time-domain signal to the frequency domain and calculating the amplitude and phase of each frequency component; identifying the main frequency components corresponding to the resolution and refresh rate using a peak detection algorithm, and obtaining color gamut parameters by combining protocol analysis.

[0069] Finally, when parameter changes are detected three times consecutively with a deviation of less than 0.5%, the configuration file is updated to avoid misjudgment.

[0070] One of the core aspects of this embodiment is: by dynamically adapting hardware parameters such as resolution, refresh rate, and color gamut parameters of different levels of large screens, the allocation of rendering resources is optimized to solve the problems of poor display consistency and excessive resource consumption of multiple terminals in vehicle-road-cloud scenarios. It is especially suitable for scenarios such as intelligent transportation command centers, vehicle-road cooperative demonstration zone monitoring platforms, and cockpit displays of autonomous vehicles.

[0071] S2 dynamically adjusts the resolution and maps the color gamut according to the configuration file; at the same time, it determines the corresponding rendering strategy based on the adjusted resolution.

[0072] Based on the configuration file, the input digital twin model undergoes dynamic resolution adjustment. For example, bilinear interpolation is used to upscale the resolution to 8K, while edge detection algorithms preserve key details.

[0073] During bilinear interpolation, for the target pixel... Its grayscale value From the four nearest pixels in the source image , , and The weighted calculation yields the following result:

[0074]

[0075] in, , , , .

[0076] In the edge detection process, the Canny algorithm is used to detect edges. The specific steps include: removing noise by Gaussian filtering; calculating the gradient magnitude and direction in the x and y directions; thinning the edges by non-maximum suppression; and setting a dual threshold to connect the edges, with a high threshold and a low threshold.

[0077] In some embodiments, the process of color gamut mapping includes: converting sRGB color gamut data to the DCI-P3 color gamut supported by the large screen based on the CIE-Lab color space, and then converting it back to sRGB for display after mapping to the DCI-P3 color gamut. During the mapping process, the mapping effect can be optimized using the GMSIM quality assessment algorithm to ensure that the color difference value is less than a preset threshold.

[0078] Based on the CIE-Lab color space, sRGB color values ​​are converted to XYZ tristimulus values ​​to calculate lightness. Red-green color And yellow-blue :

[0079]

[0080]

[0081]

[0082] Where X, Y, and Z represent the XYZ tristimulus values ​​of a pixel, which are the fundamental physical values ​​for all colors. , , The XYZ values ​​(white point) represent the standard white field. This indicates the relative brightness of the current color.

[0083] In some embodiments, determining a corresponding rendering strategy based on the adjusted resolution includes: enabling an anti-aliasing strategy or a tiled rendering strategy based on the adjusted resolution.

[0084] For example, a 4K large screen enables 4*MSAA anti-aliasing, while an 8K large screen divides the image into 1024*1024 pixel blocks, employing block culling and compact processing techniques to reduce GPU memory usage by 30%. During block rendering, the 8K image is first divided into 1024*1024 pixel blocks, totaling 64 blocks; then, each pixel block undergoes frustum clipping and backface culling, rendering only visible pixels; finally, Morton coding is used to sort the pixel blocks, optimizing memory access locality.

[0085] S3 monitors system resource utilization in real time and executes the determined rendering strategy with different rendering precision based on different system resource utilization rates.

[0086] In some embodiments, different rendering precisions are adopted based on different system resource utilization rates, including:

[0087] If the system resource utilization rate exceeds the preset utilization rate threshold, a non-critical area precision reduction strategy will be triggered.

[0088] If the system resource utilization rate is less than or equal to the preset utilization rate threshold, it will be displayed with the baseline precision.

[0089] In some embodiments, after triggering the non-critical area downsampling strategy, the method further includes:

[0090] By using Kalman filtering to predict frame rate fluctuations, the deviation between the actual frame rate and the set value is stabilized within a pre-defined deviation range.

[0091] For example, CPU utilization is monitored in real time. When CPU usage exceeds 70% for 5 consecutive seconds, a precision reduction strategy for non-critical areas is triggered. For instance, the polygon count of distant buildings is reduced by 50%, while Kalman filtering is used to predict frame rate fluctuations, ensuring that the deviation between the actual frame rate and the set value is less than or equal to ±2fps. This module dynamically adjusts the priority of rendering tasks to stabilize GPU utilization within the 80%-90% range.

[0092] The process of predicting frame rate fluctuations using Kalman filtering includes: constructing a state equation to establish the relationship between the frame rate setpoint and the rendering parameter adjustment; constructing an observation equation to establish the relationship between the actual frame rate and the frame rate setpoint; and adjusting the rendering parameters based on the Kalman gain.

[0093] The state equation is expressed as: ,in, For the current state (i.e., the frame rate setting), A is the state transition matrix, and B is the control matrix. To control the input (i.e., the amount of rendering parameter adjustment). This represents system noise.

[0094] The observation equation is expressed as: ,in, C is the observation value (i.e., the actual frame rate), and C is the observation matrix. To observe noise.

[0095] According to Kalman gain Adjust rendering parameters, such as lowering the LOD level of non-critical areas or reducing the number of shadow samples.

[0096] In some embodiments, after stabilizing the deviation between the actual frame rate and the set value within a preset deviation range, the method further includes: predicting frame rate fluctuations using Kalman filtering, and triggering a secondary adjustment when the deviation between the actual frame rate and the set value exceeds a third deviation threshold. For example, further reducing the number of shadow samples.

[0097] By reducing the LOD level of non-critical areas or reducing the number of shadow samples, the deviation between the actual frame rate and the set value is limited to a preset deviation range, and the number of shadow samples is further reduced when the deviation exceeds the third deviation threshold.

[0098] The technical solution in this invention addresses the issue of inconsistent rendering effects on different levels of large screens by using HDMI or DP interfaces to identify large screen parameters in real time. Combined with resolution scaling and color gamut mapping algorithms, it eliminates the need for engine switching and improves response speed. Simultaneously, it dynamically adjusts rendering precision based on system resource utilization, ensuring rendering quality in critical areas (such as vehicle models) while reducing overall system power consumption and enhancing frame rate stability. Furthermore, the solution supports unified deployment on PCs, mobile devices, and 8K large screens, meeting the real-time rendering requirements of autonomous driving.

[0099] Based on the same inventive concept, embodiments of the present invention also provide a large-screen adaptive rendering device. Figure 4 A structural block diagram of a large-screen adaptive rendering device provided in an embodiment of the present invention is shown below. Figure 4 As shown, the device specifically includes: a configuration generation module 100, a policy determination module 200, and a policy execution module 300.

[0100] The configuration generation module 100 is used to obtain the resolution, refresh rate and color gamut parameters of the large screen in real time, and regenerate the configuration file when the parameter changes are detected and the parameter changes trigger preset conditions.

[0101] The strategy determination module 200 is used to perform dynamic resolution adjustment and color gamut mapping according to the configuration file; and at the same time, determine the corresponding rendering strategy according to the adjusted resolution.

[0102] The strategy execution module 300 is used to monitor the system resource utilization rate in real time and execute the determined rendering strategy with different rendering precision according to the different system resource utilization rates.

[0103] Based on the same inventive concept, embodiments of the present invention also provide an electronic device. Figure 5 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Figure 5 As shown, an embodiment of the present invention provides an electronic device including: one or more processors 101, a memory 102, and one or more I / O interfaces 103. The memory 102 stores one or more programs, which, when executed by the one or more processors, enable the one or more processors to implement any of the large-screen adaptive rendering methods described in the above embodiments; the one or more I / O interfaces 103 are connected between the processor and the memory, configured to enable information interaction between the processor and the memory.

[0104] The processor 101 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 102 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read / write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, including but not limited to a data bus (BUS).

[0105] In some embodiments, the processor 101, memory 102, and I / O interface 103 are interconnected via bus 104, and thus connected to other components of the computing device.

[0106] In some embodiments, the one or more processors 101 include a field-programmable gate array.

[0107] This invention also provides a computer-readable medium. The computer-readable medium stores a computer program, which, when executed by a processor, implements the steps of any of the large-screen adaptive rendering methods described in the above embodiments. The computer-readable storage medium can be volatile or non-volatile.

[0108] This invention also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code. When the computer-readable code is run in the processor of an electronic device, the processor in the electronic device executes the above-described large-screen adaptive rendering method.

[0109] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable storage medium, which may include computer storage media (or non-transitory media) and communication media (or transient media).

[0110] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0111] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0112] The computer program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions. This electronic circuitry can execute the computer-readable program instructions to implement various aspects of the invention.

[0113] The computer program product described herein can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0114] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0115] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0116] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0117] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0118] Example embodiments have been disclosed herein, and while specific terminology has been used, it is for illustrative purposes only and should be construed as such, and is not intended to be limiting. In some instances, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in conjunction with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in conjunction with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of the invention as set forth in the appended claims.

Claims

1. A large-screen adaptive rendering method, characterized in that, include: The system acquires the resolution, refresh rate, and color gamut parameters of the large screen in real time, and regenerates the configuration file when a parameter change is detected and a preset condition is triggered. Based on the configuration file, dynamic resolution adjustment and color gamut mapping are performed; At the same time, determine the corresponding rendering strategy based on the adjusted resolution; The system monitors system resource utilization in real time and executes the determined rendering strategy with different rendering precision based on different system resource utilization rates.

2. The method according to claim 1, characterized in that, The process of regenerating the configuration file includes: When the resolution change of the large screen is detected multiple times in succession and triggers the first preset condition, the deviation of each detected resolution change is obtained; and / or, when the refresh rate fluctuation of the large screen is detected multiple times in succession and exceeds the second preset condition, the deviation of each detected refresh rate fluctuation is obtained. If the deviation of each detected resolution change is less than a preset first deviation threshold, the configuration file is regenerated; and / or, if the deviation of each detected refresh rate fluctuation is less than a preset second deviation threshold, the configuration file is regenerated.

3. The method according to claim 1, characterized in that, The real-time acquisition of the large screen's resolution, refresh rate, and color gamut parameters includes: Sample the digital signal from the HDMI or DP interface; Convert the time-domain signal to the frequency domain and calculate the amplitude and phase of each frequency component; Identify the clock frequency components corresponding to the resolution and refresh rate, and parse to obtain the color gamut parameters.

4. The method according to claim 1, characterized in that, The process of mapping the color gamut includes: Based on the CIE-Lab color space, sRGB color gamut data is converted to the DCI-P3 color gamut supported by large screens; and after mapping to the DCI-P3 color gamut, it is converted back to sRGB for display.

5. The method according to claim 1, characterized in that, The step of determining the corresponding rendering strategy based on the adjusted resolution includes: Depending on the adjusted resolution, enable either an anti-aliasing strategy or a tiled rendering strategy.

6. The method according to claim 1, characterized in that, The process of adopting different rendering precisions based on different system resource utilization rates includes: If the system resource utilization rate exceeds the preset utilization rate threshold, a non-critical area precision reduction strategy will be triggered. If the system resource utilization rate is less than or equal to the preset utilization rate threshold, it will be displayed with the baseline precision.

7. The method according to claim 6, characterized in that, After triggering the accuracy reduction strategy in non-critical areas, the following is also included: By using Kalman filtering to predict frame rate fluctuations, the deviation between the actual frame rate and the set value is stabilized within a pre-defined deviation range.

8. A large-screen adaptive rendering device, characterized in that, The apparatus is configured to implement the method according to any one of claims 1-7, the apparatus comprising: The configuration generation module is used to obtain the resolution, refresh rate and color gamut parameters of the large screen in real time, and regenerate the configuration file when the parameter changes are detected and the parameter changes trigger preset conditions. The strategy determination module is used to dynamically adjust the resolution and map the color gamut according to the configuration file; and at the same time, determine the corresponding rendering strategy according to the adjusted resolution. The strategy execution module is used to monitor the system resource utilization rate in real time and execute the determined rendering strategy with different rendering precision according to the different system resource utilization rates.

9. An electronic device, characterized in that, The electronic device includes: At least one processor, and a memory communicatively connected to said at least one processor; The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to perform the steps of the method according to any one of claims 1-7.

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