Game picture generation method and device, electronic equipment and storage medium

Abstract

The invention discloses a game picture generation method and device, electronic equipment and a storage medium. The method comprises the steps that multi-dimensional equipment information of terminal equipment is collected in real time; based on the multi-dimensional equipment information, constructing a multi-dimensional performance portrait of the terminal equipment; dynamically adjusting rendering parameters in a rendering pipeline according to the multi-dimensional performance portrait, and rendering the game content based on the adjusted rendering parameters to obtain a rendered picture; and carrying out super-resolution processing on the rendered picture to obtain a super-resolution picture, and carrying out picture quality enhancement post-processing on the super-resolution picture to obtain an output game picture meeting a target picture quality standard. According to the method, the dynamic balance between the terminal equipment performance and the game image quality can be ensured, and the game image quality and the game fluency can be improved while the performance resource utilization rate of the terminal equipment is improved. In addition, the game development cost can be reduced.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, and in particular to a game screen generation and apparatus, electronic device and storage medium. Background Technology

[0002] With the rapid development of mobile internet and smart terminal technologies, games have gradually extended to a wide range of devices such as smartphones, tablets, and cloud gaming terminals, and users' demands for game graphics and interactive experience continue to rise.

[0003] Current technology primarily employs static rendering strategies to generate game visuals. This means developers typically pre-optimize and adapt fixed rendering parameters based on the target operating platform's hardware configuration during development, embedding these parameters into the game program. During runtime, the game content is rendered directly based on these fixed parameters. However, the same game often needs to run on a large number of different terminal devices, and the actual performance of these devices varies significantly. Using the above method for game visual generation makes it difficult to strike a balance between terminal device performance and game image quality. On one hand, on relatively high-performance terminal devices, using lower rendering parameters fails to fully utilize their computing power, resulting in wasted device resources and lower image quality. On the other hand, on relatively low-performance terminal devices, using higher rendering parameters, while ensuring image quality, can easily lead to frame rate drops, stuttering, or even frame drops due to rendering load exceeding available capabilities, thus reducing game smoothness. Summary of the Invention

[0004] This disclosure provides a method, apparatus, electronic device, and storage medium for generating game graphics. Its main objective is to ensure a dynamic balance between terminal device performance and game graphics quality, thereby improving game graphics quality and game smoothness while enhancing the utilization of terminal device performance resources.

[0005] According to a first aspect of this disclosure, a method for generating game screens is provided, comprising: Real-time acquisition of multi-dimensional device information from terminal devices, including various heterogeneous data reflecting the current performance status of the terminal devices; Based on the multi-dimensional device information, a multi-dimensional performance profile of the terminal device is constructed; Based on the multi-dimensional performance profile, the rendering parameters in the rendering pipeline are dynamically adjusted, and the game content is rendered based on the adjusted rendering parameters to obtain the rendered image. The rendered image is subjected to super-resolution processing to obtain a super-resolution image, and the super-resolution image is subjected to image quality enhancement post-processing to obtain an output game image that meets the target image quality standard.

[0006] Optionally, dynamically adjusting the rendering parameters in the rendering pipeline based on the multi-dimensional performance profile includes: Based on the multi-dimensional performance profile and the preset first mapping relationship, determine the image quality configuration level that matches the multi-dimensional performance profile; Based on the image quality configuration level and the preset second mapping relationship, determine the target rendering parameters that match the image quality configuration level; Based on the target rendering parameters, the rendering parameters in the rendering pipeline are dynamically adjusted.

[0007] Optionally, rendering the game content based on the adjusted rendering parameters includes: Determine the focal area in the screen corresponding to the terminal device; Based on the adjusted rendering parameters, the game content corresponding to the focus area is rendered using a first shading rate, and the game content corresponding to the non-focus area is rendered using a second shading rate, wherein the first shading rate is higher than the second shading rate.

[0008] Optionally, performing super-resolution processing on the rendered image to obtain a super-resolution image includes: Obtain the current rendered image and at least one historical rendered image, and construct a time-series rendered image sequence; The time-series rendered image sequence is input into a preset multi-resolution preprocessing model to obtain preprocessed images of multiple resolutions corresponding to the current rendered image; Select a preprocessed image of the target resolution from multiple preprocessed images and input it into a preset super-resolution processing model to obtain a super-resolution image.

[0009] Optionally, the multi-dimensional device information includes: hardware parameter information, operating status information, operating platform characteristic information, and user scenario information, and a multi-dimensional performance profile of the terminal device is constructed based on the multi-dimensional device information; Calculate the hardware performance score of the terminal device based on the hardware performance information; Calculate the operating load score of the terminal device based on the operating status information; Based on the operating platform characteristic information, calculate the operating platform compatibility score of the terminal device; Calculate the user scenario score of the terminal device based on the user scenario information; A multi-dimensional performance profile of the terminal device is constructed based on at least two of the hardware performance score, the operating load score, the operating platform adaptation score, and the user scenario score.

[0010] Optionally, the image enhancement post-processing includes: anti-aliasing optimization, dynamic resolution scaling compensation, and material detail enhancement. This post-processing enhances the super-resolution image to obtain an output game image that meets the target image quality standard, including: The super-resolution image quality is subjected to anti-aliasing optimization, and / or dynamic resolution scaling compensation, and / or material detail enhancement to obtain an output game screen that meets the target image quality standard.

[0011] Optionally, the method further includes: Real-time acquisition of game screen metrics during game runtime; Based on the game graphics metrics, the target graphics quality standard is dynamically adjusted, and the adjusted game graphics are output.

[0012] Optionally, the method further includes: Acquire and analyze user game operation habits data and image quality adjustment history data to obtain user image quality preferences; Based on the user's image quality preferences, the target image quality standard is dynamically adjusted, and the adjusted game screen is output.

[0013] According to a second aspect of this disclosure, a game screen generation apparatus is provided, comprising: The acquisition module is used to acquire multi-dimensional device information of the terminal device in real time. The multi-dimensional device information includes various heterogeneous data that reflect the current performance status of the terminal device. A construction module is used to construct a multi-dimensional performance profile of the terminal device based on the multi-dimensional device information; The adjustment module is used to dynamically adjust the rendering parameters in the rendering pipeline based on the multi-dimensional performance profile. The rendering module is used to render the game content based on the adjusted rendering parameters to obtain the rendered screen; The processing module is used to perform super-resolution processing on the rendered image to obtain a super-resolution image, and to perform image quality enhancement post-processing on the super-resolution image to obtain an output game image that meets the target image quality standard.

[0014] Optionally, the adjustment module is specifically used to determine, based on the multi-dimensional performance profile and a preset first mapping relationship, a quality configuration level matching the multi-dimensional performance profile; to determine, based on the quality configuration level and a preset second mapping relationship, a target rendering parameter matching the quality configuration level; and to dynamically adjust the rendering parameters in the rendering pipeline based on the target rendering parameter.

[0015] Optionally, the adjustment module is further configured to determine the focal area in the screen corresponding to the terminal device; based on the adjusted rendering parameters, render the game content corresponding to the focal area using a first shading rate, and render the game content corresponding to the non-focal area using a second shading rate, wherein the first shading rate is higher than the second shading rate.

[0016] Optionally, the processing module is specifically used to acquire the current rendered image and at least one historical rendered image, and construct a temporal rendered image sequence; input the temporal rendered image sequence into a preset multi-resolution preprocessing model to obtain preprocessed images of multiple resolutions corresponding to the current rendered image; select a preprocessed image of the target resolution from the multiple preprocessed images and input it into a preset super-resolution processing model to obtain a super-resolution image.

[0017] Optionally, the multi-dimensional device information includes: hardware parameter information, operating status information, operating platform characteristic information, and user scenario information. The construction module is further configured to: calculate a hardware performance score for the terminal device based on the hardware performance information; calculate an operating load score for the terminal device based on the operating status information; calculate an operating platform compatibility score for the terminal device based on the operating platform characteristic information; calculate a user scenario score for the terminal device based on the user scenario information; and construct a multi-dimensional performance profile of the terminal device based on at least two of the hardware performance score, the operating load score, the operating platform compatibility score, and the user scenario score.

[0018] Optionally, the image enhancement post-processing includes: anti-aliasing optimization processing, dynamic resolution scaling compensation processing, and material detail enhancement processing. The processing module is further used to perform anti-aliasing optimization processing, and / or dynamic resolution scaling compensation processing, and / or material detail enhancement processing on the super-resolution image quality to obtain an output game screen that meets the target image quality standard.

[0019] Optionally, the device further includes an acquisition module and an output module.

[0020] The acquisition module is used to acquire game screen metrics in real time during game operation; The adjustment module is also used to dynamically adjust the target image quality standard based on the game image indicators; The adjustment module is used to output the adjusted game screen.

[0021] Optionally, the acquisition module is further configured to acquire and analyze user's game operation habit data and image quality adjustment history data to obtain user image quality preferences; The adjustment module is also used to dynamically adjust the target image quality standard based on the user's image quality preferences; The adjustment module is also used to output the adjusted game screen.

[0022] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0023] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0024] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0025] The game screen generation method, apparatus, electronic device, and storage medium disclosed herein acquire multi-dimensional device information of a terminal device in real time and construct a multi-dimensional performance profile of the terminal device based on the multi-dimensional device information. This enables dynamic adjustment of rendering parameters in the rendering pipeline based on the multi-dimensional performance profile, and allows rendering of game content based on the adjusted rendering parameters to obtain a rendered screen. Furthermore, by performing super-resolution processing on the rendered screen, a super-resolution screen can be obtained, and post-processing for image quality enhancement on the super-resolution screen can output game screens that meet target image quality standards. Compared with existing technologies, because this disclosure dynamically adjusts rendering parameters based on the real-time multi-dimensional performance profile of the terminal device, it avoids using lower rendering parameters on high-performance terminals, maximizing the use of the terminal device's computing power to output the highest possible quality game screen, thereby improving the resource utilization of the terminal device. On the other hand, it allows the use of higher rendering parameters on low-performance terminals, preventing the rendering load from exceeding the current available performance, avoiding stuttering or even frame drops, and improving game smoothness. Furthermore, because this disclosure performs super-resolution processing and image enhancement post-processing on the rendered image after adaptive rendering of the game content, it can effectively compensate for the quality loss of the game image while reducing the original rendering load, ensuring that the output game image meets the target image quality standard. This ensures a dynamic balance between terminal device performance and game image quality, improving the resource utilization of the terminal device while enhancing game image quality and game smoothness. Moreover, compared with existing technologies, this disclosure does not require game developers to adapt different rendering strategies for different operating platforms, which can greatly reduce game development costs and time, significantly save manpower costs, and thus reduce the overall cost of game development.

[0026] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0027] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 A schematic flowchart illustrating a game screen generation method provided in an embodiment of this disclosure; Figure 2 A flowchart illustrating another game screen generation method provided in this embodiment of the present disclosure; Figure 3 This is a schematic diagram of an adaptive rendering process provided in an embodiment of the present disclosure; Figure 4 This is a schematic diagram of a post-rendering processing flow provided in an embodiment of the present disclosure; Figure 5 This is a schematic diagram of a dynamic adjustment mechanism provided in an embodiment of the present disclosure; Figure 6 This is a schematic diagram of the structure of a game screen generation device provided in an embodiment of the present disclosure; Figure 7 A schematic block diagram of an example electronic device 400 provided for embodiments of this disclosure. Detailed Implementation

[0028] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0029] With the rapid development of mobile internet and smart terminal technologies, games have gradually extended to a wide range of devices such as smartphones, tablets, and cloud gaming terminals, and users' demands for game graphics and visual quality continue to rise.

[0030] Current technologies primarily employ static game graphics rendering strategies to render and generate game graphics. That is, developers typically pre-optimize and adapt fixed rendering parameters based on the hardware configuration of the target operating platform during the development phase, and then embed these parameters into the game program. During runtime, the game content is rendered directly based on these fixed parameters. However, the same game often needs to run on a large number of heterogeneous terminal devices, and the actual performance of different devices varies significantly. If the above method is used to generate game graphics, it is difficult to find a balance between terminal device performance and game image quality. On the one hand, on relatively high-performance terminal devices, using lower rendering parameters cannot fully utilize their computing power, resulting in wasted terminal device performance resources and lower game image quality. On the other hand, on relatively low-performance terminal devices, using higher rendering parameters, while ensuring game image quality, can easily lead to frame rate drops, stuttering, or even frame drops due to rendering load exceeding the available capabilities, thus reducing game smoothness.

[0031] Furthermore, there are many operating platforms for terminal devices. To achieve game compatibility across different platforms, it is usually necessary to perform separate optimization and adaptation work for the hardware characteristics of each operating platform. In other words, game developers need to optimize and adapt fixed rendering parameters separately for different operating platforms. For example, the Metal API is used for graphics rendering optimization on the iOS platform, and the Vulkan API is used for adjustment on the Android platform. However, optimizing and adapting fixed rendering parameters separately for different operating platforms will greatly increase the game development cost and cycle, greatly increase the manpower cost, and limit the rapid cross-platform release and promotion of games, thus resulting in high game development costs.

[0032] Therefore, ensuring a dynamic balance between terminal device performance and game graphics quality—improving the utilization of terminal device performance resources while simultaneously enhancing game graphics and smoothness—is a pressing technical challenge for the gaming industry. Furthermore, achieving cross-platform compatibility for game content and reducing game development costs are also critical technical issues that need to be addressed.

[0033] This disclosure provides a game screen generation method, apparatus, electronic device, and storage medium, aiming to ensure a dynamic balance between terminal device performance and game image quality. This improves the utilization of terminal device performance resources while enhancing game image quality and smoothness. Simultaneously, it enables cross-platform adaptation of game content, reducing game development costs.

[0034] The following description, with reference to the accompanying drawings, outlines a method, apparatus, electronic device, and storage medium for generating game screens according to embodiments of the present disclosure.

[0035] Figure 1 This is a flowchart illustrating a game screen generation method provided in an embodiment of the present disclosure.

[0036] like Figure 1 As shown, the method includes the following steps: Step 101: Collect multi-dimensional device information from the terminal device in real time.

[0037] The multi-dimensional device information includes various heterogeneous data reflecting the current performance status of the terminal device. Specifically, this multi-dimensional device information includes: hardware parameter information, operating status information, operating platform characteristic information, and user scenario information.

[0038] For hardware parameter information, this can include: the number of CPU cores and CPU clock speed, which can be used to evaluate the computing power of the terminal device; the graphics processing unit (GPU) model, computing power (measured in trillions of floating-point operations per second, TFLOPS), and video memory capacity; and screen resolution. The GPU model and its computing power and video memory capacity are directly related to graphics processing capabilities. Screen resolution can be used to determine the output size and pixel density of the image. Specifically, the hardware parameter information of the terminal device can be obtained in real time through the system API.

[0039] Regarding operational status information, this information can include: system memory usage, battery voltage, temperature sensor data, etc. These metrics can help determine the current operational load and stability of the terminal device. Specifically, a background thread can be established to collect memory usage, battery voltage, and temperature sensor data with millisecond-level precision.

[0040] For operating platform feature information, this can include version support. The operating platform can be iOS (a mobile operating system developed by Apple Inc.) or Android (an open-source mobile operating system based on the Linux kernel). Version support can include features such as tiled rendering, parameter buffers (a technology used to optimize GPU resource binding and management), and rendering backend features. These features can optimize GPU resource utilization, improve graphics rendering efficiency, or reduce texture data footprint, thereby improving rendering performance. Specifically, operating platform features can be determined by detecting the operating platform version. Different versions enable different operating platform features, and the correspondence between versions and operating systems is pre-stored locally. For OS platforms, the Metal API version can be detected, and tiled rendering and parameter buffer features can be enabled accordingly. For Android platforms, Vulkan 1.3 support can be checked, and based on Vulkan 1.3 support, the optimal rendering backend can be automatically selected from the terminal device hardware, such as ASTC texture compression optimization for Mali GPUs to reduce texture data footprint and improve rendering performance.

[0041] Regarding user scenario information, this can include: whether the terminal device has power-saving mode enabled, the current game complexity, and the frequency of user operations. When power-saving mode is enabled, it indicates that subsequent adjustments to balance terminal device performance and game graphics quality will prioritize energy conservation. Specifically, the power-saving mode status can be monitored through the system interface.

[0042] Step 102: Based on the multi-dimensional device information of the terminal device, construct a multi-dimensional performance profile of the terminal device.

[0043] In this embodiment of the disclosure, the step of constructing a multi-dimensional performance profile may include: normalizing the multi-dimensional device information, fusing features from each dimension based on preset weights or a preset machine learning model, and generating a performance profile characterizing the current graphics rendering capability of the terminal device. The performance profile is used to drive the dynamic adjustment of subsequent rendering parameters. The multi-dimensional performance profile can be represented by a comprehensive score, a set of classification labels, or other forms. For example, if represented by a comprehensive score, it can be represented as "Performance Score: 85 / 100"; if represented by a set of classification labels, it can be represented as "High Load - Medium Temperature - Low Battery"; or if represented by a multi-dimensional vector, it can be represented as: [gpu_load=0.7, temp=0.6, mem_free=0.4].

[0044] Step 103: Based on the multi-dimensional performance profile of the terminal device, dynamically adjust the rendering parameters in the rendering pipeline, and render the game content based on the adjusted rendering parameters to obtain the rendered screen.

[0045] In computer graphics, the rendering pipeline refers to a series of operations used to generate images. This includes, but is not limited to, vertex processing, rasterization, and fragment shading. These stages can have their parameters adjusted to optimize the quality and efficiency of the final output image. Rendering parameters are specific settings that affect rendering effects and efficiency; for example, rendering parameters can include resolution, texture quality, shadow detail level, and anti-aliasing methods. Different combinations of rendering parameters directly impact the expressiveness and smoothness of the game visuals.

[0046] In this embodiment, the process of dynamically adjusting rendering parameters in the rendering pipeline based on the multi-dimensional performance profile of the terminal device essentially involves dynamically adjusting key rendering parameters such as resolution, texture quality, shadow detail level, and anti-aliasing mode based on hardware parameter information, operating status information, operating platform characteristic information, and user scenario information. Compared with the prior art that uses fixed rendering parameters, this embodiment constructs a performance profile based on at least two of the hardware parameter information, operating status information, operating platform characteristic information, and user scenario information. This allows for accurate perception of the instantaneous performance margin of the terminal device in the real-world usage environment, thereby dynamically adjusting key rendering parameters such as resolution, texture quality, shadow precision, and anti-aliasing level within milliseconds. This avoids resource waste or performance overload caused by a "one-size-fits-all" configuration.

[0047] Furthermore, in this embodiment, for high-performance terminal devices, the upper limit of the existing "high-quality" level can be broken, enabling higher resolution rendering, more complex post-processing effects, or higher frame rate targets, fully releasing their graphics processing potential. For medium- and low-performance terminal devices, redundant calculations can be trimmed without sacrificing game image quality, ensuring the expressiveness and smoothness of the game screen. In high-load scenarios, such as large-scale battles, complex particle effects, or when the device is under limited conditions such as high temperature or low power, the system can actively reduce non-core rendering overhead and prioritize frame rate stability. When the device cools down, is plugged in, or enters a lightweight scenario, the high-quality settings can be restored in time, thereby effectively reducing the probability of stuttering, frame drops, and game crashes, and significantly improving user operation responsiveness and immersion.

[0048] Step 104: Perform super-resolution processing on the rendered image to obtain a super-resolution image, and perform image quality enhancement post-processing on the super-resolution image to obtain an output game image that meets the target image quality standard.

[0049] Super-resolution processing refers to methods that use algorithms to reconstruct high-resolution images from low-resolution images, while restoring edge sharpness, texture details, and spatial structure. In other words, it uses algorithms to reconstruct high-frequency details from low-resolution images to obtain super-resolution visuals. Specifically, a pre-trained super-resolution processing model can be used to perform super-resolution processing on rendered images to obtain super-resolution visuals. Combining multiple frames of historical rendered images can also improve image stability. The pre-trained super-resolution processing model can be obtained through supervised learning of a convolutional neural network model using low-resolution and high-resolution game images as input and output samples. The convolutional neural network model can be lightweight. Post-processing for image enhancement includes at least one of the following operations: edge sharpening, color saturation adjustment, contrast enhancement or noise suppression, anti-aliasing optimization, dynamic resolution scaling compensation, and material detail enhancement. Further optimization of the super-resolution image can compensate for imperfections that super-resolution may introduce, such as artifacts, oversmoothing, and color deviation, and improve the overall game image quality.

[0050] In this embodiment, the rendered image can be obtained through low-load rendering. For example, the resolution of the rendered image can be 720p. After performing super-resolution processing on the rendered image, a super-resolution image of 1080p is obtained. The output game image that meets the target image quality standard can be equivalent to native 1080p image quality. By performing super-resolution reconstruction and image quality enhancement post-processing on the rendered image, it is possible to recover the image quality reduction caused by the compromise of terminal device performance without increasing the rendering burden. The final output is a smooth and high-definition game image, truly achieving a dynamic balance between terminal device performance and game image quality.

[0051] The game screen generation method provided in this disclosure collects multi-dimensional device information of a terminal device in real time and constructs a multi-dimensional performance profile of the terminal device based on the multi-dimensional device information. It can dynamically adjust the rendering parameters in the rendering pipeline according to the multi-dimensional performance profile and render game content based on the adjusted rendering parameters to obtain a rendered screen. Furthermore, by performing super-resolution processing on the rendered screen, a super-resolution screen can be obtained, and by performing image quality enhancement post-processing on the super-resolution screen, the output game screen can meet the target image quality standard. Compared with the prior art, since this disclosure dynamically adjusts the rendering parameters based on the real-time multi-dimensional performance profile of the terminal device, it can, on the one hand, avoid using lower rendering parameters on high-performance terminals, maximizing the use of the terminal device's computing power to output the highest possible quality game screen, thereby improving the resource utilization of the terminal device; on the other hand, it can use higher rendering parameters on low-performance terminals, avoiding rendering load exceeding the current available performance, preventing stuttering or even frame drops, and improving game smoothness. Furthermore, since this embodiment of the present disclosure performs super-resolution processing and image quality enhancement post-processing on the rendered image after adaptive rendering of the game content, it can effectively compensate for the quality loss of the game image while reducing the original rendering load, ensuring that the output game image meets the target image quality standard. This ensures a dynamic balance between terminal device performance and game image quality, improving the resource utilization of the terminal device while enhancing game image quality and game smoothness. Moreover, compared with the prior art, this embodiment of the present disclosure does not require game developers to adapt different rendering strategies for different operating platforms, which can greatly reduce game development costs and cycles, significantly save manpower costs, and accelerate the cross-platform release and promotion of games, thereby reducing high game development costs.

[0052] Figure 2 This is a flowchart illustrating a game screen generation method provided in an embodiment of the present disclosure.

[0053] like Figure 2 As shown, the method includes the following steps: Step 201: Collect multi-dimensional device information from the terminal device in real time.

[0054] Optionally, the multi-dimensional device information includes: hardware parameter information, operating status information, operating platform characteristic information, and user scenario information. For a detailed explanation of the multi-dimensional device information, please refer to step 101; this embodiment will not elaborate further here.

[0055] Step 202: Based on the multi-dimensional device information of the terminal device, construct a multi-dimensional performance profile of the terminal device.

[0056] Optionally, in some embodiments of this disclosure, the step of constructing a multi-dimensional performance profile of the terminal device based on the multi-dimensional device information may specifically include: calculating a hardware performance score of the terminal device based on the hardware performance information; calculating a runtime load score of the terminal device based on the running status information; calculating an operating platform adaptation score of the terminal device based on the operating platform characteristic information; calculating a user scenario score of the terminal device based on the user scenario information; and constructing a multi-dimensional performance profile of the terminal device based on at least two of the hardware performance score, the runtime load score, the operating platform adaptation score, and the user scenario score. Specifically, the multi-dimensional performance profile of the terminal device is generated by weighted fusion of at least two of the hardware performance score, the runtime load score, the operating platform adaptation score, and the user scenario score.

[0057] Optionally, in some embodiments of this disclosure, the step of constructing a multi-dimensional performance profile of the terminal device based on the multi-dimensional device information may specifically include inputting hardware parameter information, operating status information, operating platform characteristic information, and user scenario information into a pre-trained performance profile construction model, and outputting a multi-dimensional performance profile of the terminal device. The pre-trained performance profile construction model can be obtained by supervising the learning of a convolutional neural network model using hardware parameter information, operating status information, operating platform characteristic information, user scenario information, and the multi-dimensional performance profile as input and output samples.

[0058] Step 203: Determine the image quality configuration level that matches the multi-dimensional performance profile of the terminal device based on the multi-dimensional performance profile and the preset first mapping relationship.

[0059] The image quality configuration level reflects the amount of resources used during rendering and the final visual effect. It is predefined by the developer; for example, it can be an extreme image quality model, a performance mode, or an energy-saving mode. The preset first mapping relationship predefines the correspondence between different multi-dimensional performance profiles and image quality configuration levels. Through this preset mapping relationship, the most suitable image quality configuration level can be automatically selected based on the multi-dimensional performance profile of the terminal device. For example, when the multi-dimensional performance profile reflects a state of "low load, low temperature, high battery, and support for MetalFX," it maps to the extreme image quality mode's image quality configuration level; while when the profile reflects "high GPU load, high temperature, low battery, and low-end Android model," it maps to the energy-saving mode's image quality configuration level.

[0060] Step 204: Determine the target rendering parameters that match the image quality configuration level based on the image quality configuration level and the preset second mapping relationship.

[0061] The preset second mapping relationship can represent the correspondence between different image quality configuration levels and specific rendering parameters. Through this preset second mapping relationship, the target rendering parameters that match the most suitable image quality configuration level can be automatically selected. This ensures a dynamic balance between terminal device performance and game image quality. The target rendering parameters include internal rendering resolution, texture precision, shadow quality, and post-processing effects. The preset second mapping relationship can be represented by a preset mapping table. For example, Table 1 can be referenced, but the second mapping relationship is not limited to the contents shown in Table 1.

[0062] Table 1

[0063] Step 205: Based on the target rendering parameters, dynamically adjust the rendering parameters in the rendering pipeline, and based on the adjusted rendering parameters, render the game content to obtain the rendered image.

[0064] Alternatively, to reduce the overall rendering computation while maintaining game visual quality, Variable Rate Shading (VRS) technology can be introduced, such as... Figure 3 As shown, rendering game content based on adjusted rendering parameters includes: determining the focal area on the screen corresponding to the terminal device. Based on the adjusted rendering parameters, the game content corresponding to the focal area is rendered using a first shading rate, and the game content corresponding to the non-focal area is rendered using a second shading rate, wherein the first shading rate is higher than the second shading rate. Specifically, eye-tracking data (if the device supports it) or a simulated gaze point algorithm can be used to determine the focal area on the screen corresponding to the terminal device. The first shading rate can be expressed as the rate at which each pixel (1*1 pixel) is shaded and rendered individually, and the second shading rate can be expressed as the rate at which two adjacent pixels (2*2 pixels) or more adjacent pixels are merged into one pixel for shading and rendering.

[0065] It should be noted that an item describing VRS settings can be added to the preset second mapping relationship. This may include information such as enabling / disabling VRS and specifying the shading rate for different areas. For example, VRS may not be enabled in the ultimate image quality mode, or a lower shading rate may only be applied in areas with low visual sensitivity, such as the edges of the screen; while in performance mode, a lower shading rate can be applied more widely across the entire screen to improve the frame rate.

[0066] Step 206: Obtain the current rendered image and at least one historical rendered image, and construct a time-series rendered image sequence.

[0067] The current rendered image and the historical rendered images are sequential in time, resulting in a temporal rendered image sequence that contains information about temporal continuity. The first two or three rendered images can be selected to construct a temporal rendered image sequence, laying the foundation for obtaining a super-resolution image.

[0068] Step 207: Input the time-series rendering image sequence into the preset multi-resolution preprocessing model to obtain preprocessed images of multiple resolutions corresponding to the current rendering image.

[0069] Step 208: Select the target resolution preprocessed image from multiple preprocessed images and input it into the preset super-resolution processing model to obtain the super-resolution image.

[0070] The pre-defined super-resolution processing model can be an Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) model based on an attention mechanism. This model, building upon the classic ESRGAN architecture, introduces an attention mechanism, enabling the network to adaptively focus on regions or feature channels in the image that are more critical to visual perception. This allows for more efficient recovery of high-frequency details with limited computational resources, significantly improving the clarity and realism of the reconstructed image. The classic ESRGAN architecture includes a generator composed of multiple Residual-in-Residual Dense Blocks (RRDBs), a relativistic discriminator, and a perceptual loss function based on VGG features. Each RRDB module contains multiple densely connected convolutional layers with nested residual connections on the outer layers, thus significantly enhancing feature extraction capabilities and gradient propagation efficiency without introducing additional artifacts. An improved ESRGAN based on an attention mechanism can embed a channel attention mechanism in the RRDB module. The attention mechanism module enhances important features by calculating the attention weights of the feature map, thereby enhancing important features such as edges and textures in the image and improving the image's clarity and detail.

[0071] Step 209: Perform image enhancement post-processing on the super-resolution image to obtain an output game image that meets the target image quality standard. Optionally, in some embodiments of this disclosure, the image enhancement post-processing includes: anti-aliasing optimization processing, dynamic resolution scaling compensation processing, and texture detail enhancement processing to perform image enhancement post-processing on the super-resolution image to obtain an output game image that meets the target image quality standard, including: performing anti-aliasing optimization processing on the super-resolution image, and / or, dynamic resolution scaling compensation processing, and / or, texture detail enhancement processing, to obtain an output game image that meets the target image quality standard. That is, as... Figure 4 As shown, after obtaining the rendered image in step 205, the rendered image can be post-processed, that is, a temporal rendered image sequence can be constructed, a super-resolution image can be generated based on the attention mechanism-improved ESRGAN, and anti-aliasing optimization processing, and / or dynamic resolution scaling compensation processing, and / or material detail enhancement processing can be performed on the super-resolution image quality to obtain an output game image that meets the target image quality standard.

[0072] Specifically, regarding anti-aliasing optimization, to reduce image jaggedness while maintaining detail and sharpness and reducing computational burden, Temporal Anti-Aliasing Upscaling (TAAU) and Deep Learning Super Sampling (DLSS) techniques can be combined to perform anti-aliasing optimization on the super-resolution image quality. That is, TAAU can be enabled to perform preliminary temporal anti-aliasing and upsampling on the super-resolution image. Then, the TAAU-reconstructed image, the corresponding motion vector, the depth buffer, and the original low-resolution color buffer are fed into the DLSS neural network module to repair temporal blur or ghosting that TAAU may introduce, enhance high-frequency texture details, optimize edge sharpness, and avoid over-smoothing.

[0073] For dynamic resolution scaling compensation, the complexity of the game scene can be determined, and then the rendering resolution of the corresponding scene can be automatically adjusted based on the scene complexity. The more complex the actions of the characters in the scene, the more complex the scene; the more virtual characters in the scene, the more complex the scene. In complex scenes, the rendering resolution is automatically reduced to alleviate the computational burden, while maintaining a stable output resolution to ensure smooth game operation and avoid image quality degradation due to resolution changes. For enhancing material details, object simulation can be performed based on subsurface scattering of normal maps. Normal maps are used to define the surface details of objects, and subsurface scattering is combined to simulate the scattering of light inside objects, thereby improving the realism and detail of materials.

[0074] Optionally, in some embodiments of this disclosure, to further ensure a dynamic balance between terminal device performance and game image quality, a dynamic adjustment mechanism can also be constructed, such as... Figure 5As shown, the method further includes: acquiring game screen metrics during game runtime in real time; dynamically adjusting the target image quality standard based on the game screen metrics, and outputting the adjusted game screen.

[0075] The game's runtime visual metrics can include actual frame rate and latency. Specifically, based on these metrics, the graphics quality configuration level and effects level are dynamically adjusted to dynamically adjust the target graphics quality standard, and the adjusted game visuals are output. For example, when the frame rate is below a threshold, the graphics quality is automatically reduced to improve smoothness; when the frame rate is above a threshold, the graphics quality is increased to enhance visual effects; when the latency is above a latency threshold, the graphics quality is reduced; and when the latency is below a latency threshold, the graphics quality is increased.

[0076] Optionally, in some embodiments of this disclosure, to further ensure a dynamic balance between terminal device performance and game image quality, a user preference learning mechanism can be introduced. The method further includes: acquiring and analyzing user game operation habit data and image quality adjustment history data to obtain user image quality preferences; dynamically adjusting the target image quality standard based on user image quality preferences, and outputting the adjusted game screen. Specifically, user game operation habits and image quality adjustment history data are recorded, and then user preferences for image quality and smoothness are analyzed to personalize the balance between image quality and performance. For example, for users who prefer image quality, smoothness can be slightly reduced to improve visual effects; for users who prefer smoothness, image quality can be slightly reduced to ensure smooth game operation.

[0077] The game screen generation method provided in this disclosure collects multi-dimensional device information of a terminal device in real time and constructs a multi-dimensional performance profile of the terminal device based on the multi-dimensional device information. It can dynamically adjust the rendering parameters in the rendering pipeline according to the multi-dimensional performance profile and render game content based on the adjusted rendering parameters to obtain a rendered screen. Furthermore, by performing super-resolution processing on the rendered screen, a super-resolution screen can be obtained, and by performing image quality enhancement post-processing on the super-resolution screen, the output game screen can meet the target image quality standard. Compared with the prior art, since this disclosure dynamically adjusts the rendering parameters based on the real-time multi-dimensional performance profile of the terminal device, it can, on the one hand, avoid using lower rendering parameters on high-performance terminals, maximizing the use of the terminal device's computing power to output the highest possible quality game screen, thereby improving the resource utilization of the terminal device; on the other hand, it can use higher rendering parameters on low-performance terminals, avoiding rendering load exceeding the current available performance, preventing stuttering or even frame drops, and improving game smoothness. Furthermore, since this embodiment of the invention performs super-resolution processing and image quality enhancement post-processing on the rendered image after adaptive rendering of the game content, it can effectively compensate for the quality loss of the game image while reducing the original rendering load, ensuring that the output game image meets the target image quality standard. This ensures a dynamic balance between terminal device performance and game image quality, improving the resource utilization of the terminal device while enhancing game image quality and game smoothness. Moreover, compared with the prior art, this embodiment of the invention does not require game developers to adapt different rendering strategies for different operating platforms, which can greatly reduce game development costs and time, significantly save manpower costs, and thus reduce the overall game development cost.

[0078] Figure 6 This is a schematic diagram of the structure of a game screen generation device provided in an embodiment of the present disclosure, such as... Figure 6 As shown, it includes: acquisition module 31, construction module 32, adjustment module 33, rendering module 34 and processing module 35.

[0079] The acquisition module 31 is used to acquire multi-dimensional device information of the terminal device in real time. The multi-dimensional device information includes various heterogeneous data that reflect the current performance status of the terminal device. Construction module 32 is used to construct a multi-dimensional performance profile of the terminal device based on the multi-dimensional device information; The adjustment module 33 is used to dynamically adjust the rendering parameters in the rendering pipeline based on the multi-dimensional performance profile. Rendering module 34 is used to render the game content based on the adjusted rendering parameters to obtain the rendered screen; The processing module 35 is used to perform super-resolution processing on the rendered image to obtain a super-resolution image, and to perform image quality enhancement post-processing on the super-resolution image to obtain an output game image that meets the target image quality standard.

[0080] Optionally, the adjustment module 33 is specifically used to determine the image quality configuration level that matches the multi-dimensional performance profile based on the multi-dimensional performance profile and a preset first mapping relationship; determine the target rendering parameters that match the image quality configuration level based on the image quality configuration level and a preset second mapping relationship; and dynamically adjust the rendering parameters in the rendering pipeline based on the target rendering parameters.

[0081] Optionally, the adjustment module 33 is further configured to determine the focal area in the screen corresponding to the terminal device; based on the adjusted rendering parameters, to render the game content corresponding to the focal area using a first shading rate, and to render the game content corresponding to the non-focal area using a second shading rate, wherein the first shading rate is higher than the second shading rate.

[0082] Optionally, the processing module 35 is specifically used to acquire the current rendered image and at least one historical rendered image, and construct a temporal rendered image sequence; input the temporal rendered image sequence into a preset multi-resolution preprocessing model to obtain preprocessed images of multiple resolutions corresponding to the current rendered image; select a preprocessed image of the target resolution from the multiple preprocessed images and input it into a preset super-resolution processing model to obtain a super-resolution image.

[0083] Optionally, the multi-dimensional device information includes: hardware parameter information, operating status information, operating platform characteristic information, and user scenario information. The construction module 32 is further configured to: calculate the hardware performance score of the terminal device based on the hardware performance information; calculate the operating load score of the terminal device based on the operating status information; calculate the operating platform compatibility score of the terminal device based on the operating platform characteristic information; calculate the user scenario score of the terminal device based on the user scenario information; and construct a multi-dimensional performance profile of the terminal device based on at least two of the hardware performance score, the operating load score, the operating platform compatibility score, and the user scenario score.

[0084] Optionally, the image quality enhancement post-processing includes: anti-aliasing optimization processing, dynamic resolution scaling compensation processing, and material detail enhancement processing. The processing module 35 is further used to perform anti-aliasing optimization processing, and / or dynamic resolution scaling compensation processing, and / or material detail enhancement processing on the super-resolution image quality to obtain an output game screen that meets the target image quality standard.

[0085] Optionally, the device further includes an acquisition module and an output module.

[0086] The acquisition module is used to acquire game screen metrics in real time during game operation; The adjustment module 33 is also used to dynamically adjust the target image quality standard based on the game image indicators; The adjustment module 33 is used to output the adjusted game screen.

[0087] Optionally, the acquisition module is further configured to acquire and analyze user's game operation habit data and image quality adjustment history data to obtain user image quality preferences; The adjustment module 33 is also used to dynamically adjust the target image quality standard based on the user's image quality preferences; The adjustment module 33 is also used to output the adjusted game screen.

[0088] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of the embodiments of this disclosure, and the principle is the same. Therefore, the embodiments of this disclosure are not limited thereto.

[0089] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0090] According to embodiments of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform the aforementioned... Figure 1-2 The method described.

[0091] According to embodiments of this disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to perform the aforementioned... Figure 1-2 The method described.

[0092] According to embodiments of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the aforementioned... Figure 1-2 The method described.

[0093] The game screen generation apparatus provided in this disclosure collects multi-dimensional device information of a terminal device in real time and constructs a multi-dimensional performance profile of the terminal device based on the multi-dimensional device information. It can dynamically adjust the rendering parameters in the rendering pipeline according to the multi-dimensional performance profile and render game content based on the adjusted rendering parameters to obtain a rendered screen. Furthermore, by performing super-resolution processing on the rendered screen, a super-resolution screen can be obtained, and by performing image quality enhancement post-processing on the super-resolution screen, the output game screen can meet the target image quality standard. Compared with the prior art, since this disclosure dynamically adjusts the rendering parameters based on the real-time multi-dimensional performance profile of the terminal device, it can, on the one hand, avoid using lower rendering parameters on high-performance terminals, maximizing the use of the terminal device's computing power to output the highest possible quality game screen, thereby improving the resource utilization of the terminal device. On the other hand, it can use higher rendering parameters on low-performance terminals, avoiding rendering load exceeding the current available performance, preventing stuttering or even frame drops, and improving game smoothness. Furthermore, since this embodiment of the invention performs super-resolution processing and image quality enhancement post-processing on the rendered image after adaptive rendering of the game content, it can effectively compensate for the quality loss of the game image while reducing the original rendering load, ensuring that the output game image meets the target image quality standard. This ensures a dynamic balance between terminal device performance and game image quality, improving the resource utilization of the terminal device while enhancing game image quality and game smoothness. Moreover, compared with the prior art, this embodiment of the invention does not require game developers to adapt different rendering strategies for different operating platforms, which can greatly reduce game development costs and time, significantly save manpower costs, and thus reduce the high cost of game development.

[0094] Figure 7 A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0095] like Figure 7As shown, the electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 402 or a computer program loaded from storage unit 408 into RAM (Random Access Memory) 403. The RAM 403 can also store various programs and data required for the operation of the electronic device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via a bus 404. An I / O (Input / Output) interface 405 is also connected to the bus 404.

[0096] Multiple components in electronic device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of displays, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows electronic device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0097] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as game screen generation methods. For example, in some embodiments, the game screen generation method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the aforementioned game screen generation method by any other suitable means (e.g., by means of firmware).

[0098] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0099] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0100] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0101] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0102] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0103] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0104] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0105] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0106] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for generating game screens, characterized in that, include: Real-time collection of multi-dimensional device information from terminal devices; Based on the multi-dimensional device information, a multi-dimensional performance profile of the terminal device is constructed; Based on the multi-dimensional performance profile, the rendering parameters in the rendering pipeline are dynamically adjusted, and the game content is rendered based on the adjusted rendering parameters to obtain the rendered image. The rendered image is subjected to super-resolution processing to obtain a super-resolution image, and the super-resolution image is subjected to image quality enhancement post-processing to obtain an output game image that meets the target image quality standard.

2. The game screen generation method according to claim 1, characterized in that, The step of dynamically adjusting the rendering parameters in the rendering pipeline based on the multi-dimensional performance profile includes: Based on the multi-dimensional performance profile and the preset first mapping relationship, determine the image quality configuration level that matches the multi-dimensional performance profile; Based on the image quality configuration level and the preset second mapping relationship, determine the target rendering parameters that match the image quality configuration level; Based on the target rendering parameters, the rendering parameters in the rendering pipeline are dynamically adjusted.

3. The game screen generation method according to claim 1, characterized in that, The rendering of game content based on the adjusted rendering parameters includes: Determine the focal area in the screen corresponding to the terminal device; Based on the adjusted rendering parameters, the game content corresponding to the focus area is rendered using a first shading rate, and the game content corresponding to the non-focus area is rendered using a second shading rate, wherein the first shading rate is higher than the second shading rate.

4. The game screen generation method according to claim 1, characterized in that, The step of performing super-resolution processing on the rendered image to obtain a super-resolution image includes: Obtain the current rendered image and at least one historical rendered image, and construct a time-series rendered image sequence; The time-series rendered image sequence is input into a preset multi-resolution preprocessing model to obtain preprocessed images of multiple resolutions corresponding to the current rendered image; Select a preprocessed image of the target resolution from multiple preprocessed images and input it into a preset super-resolution processing model to obtain a super-resolution image.

5. The game screen generation method according to claim 1, characterized in that, The multi-dimensional device information includes: hardware parameter information, operating status information, operating platform characteristic information, and user scenario information. Based on the multi-dimensional device information, a multi-dimensional performance profile of the terminal device is constructed. Calculate the hardware performance score of the terminal device based on the hardware performance information; Calculate the operating load score of the terminal device based on the operating status information; Based on the operating platform characteristic information, calculate the operating platform compatibility score of the terminal device; Calculate the user scenario score of the terminal device based on the user scenario information; A multi-dimensional performance profile of the terminal device is constructed based on at least two of the hardware performance score, the operating load score, the operating platform adaptation score, and the user scenario score.

6. The game screen generation method according to any one of claims 1-5, characterized in that, The image enhancement post-processing includes: anti-aliasing optimization, dynamic resolution scaling compensation, and texture detail enhancement. This post-processing enhances the super-resolution image to obtain an output game image that meets the target image quality standard, including: The super-resolution image quality is subjected to anti-aliasing optimization, and / or dynamic resolution scaling compensation, and / or material detail enhancement to obtain an output game screen that meets the target image quality standard.

7. A game screen generation device, characterized in that, include: The acquisition module is used to acquire multi-dimensional device information of the terminal device in real time. The multi-dimensional device information includes various heterogeneous data that reflect the current performance status of the terminal device. A construction module is used to construct a multi-dimensional performance profile of the terminal device based on the multi-dimensional device information; The adjustment module is used to dynamically adjust the rendering parameters in the rendering pipeline based on the multi-dimensional performance profile. The rendering module is used to render the game content based on the adjusted rendering parameters to obtain the rendered screen; The processing module is used to perform super-resolution processing on the rendered image to obtain a super-resolution image, and to perform image quality enhancement post-processing on the super-resolution image to obtain an output game image that meets the target image quality standard.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-6.

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