Graphic processor management method and device, equipment and storage medium
By performing the difference detection of image encoding and decoding on the graphics processor, the problem of abnormalities occurring in the video encoding and decoding process of graphics processor is solved, and image quality improvement and user experience improvement are achieved.
Patent Information
- Application Number
- CN202411508275.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-25
- Publication Date
- 2025-02-25
AI Technical Summary
In the prior art, graphics processors are prone to abnormalities during video encoding and decoding, resulting in reduced image quality and inability to detect and process in time, affecting user experience.
By acquiring a plurality of first preset images, encoding and decoding them using a graphics processor, comparing the difference between the second preset image obtained after encoding and decoding and the original image. If an abnormal image is found, a prompt information is output to notify the staff to process.
It realizes rapid detection of the graphics processor and prompts staff to handle abnormal graphics processors in a timely manner, thereby ensuring the improvement of image quality during video encoding and decoding.
Smart Images
Figure CN119515788A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of graphics processor technology, and in particular to a management method, device, equipment and storage medium for a graphics processor. Background Art
[0002] Currently, NVIDIA GPUs (Graphics Processing Units) are widely used in video encoding and decoding. GPUs are deployed in data processing centers, and in general, a large number of GPUs are still deployed in data processing centers after the warranty period has expired. In actual applications, GPUs that have expired are prone to problems. For example, when accelerating the encoding and decoding of a video, abnormal stripes will appear. These stripes are not the original video content and are generally displayed at random positions in the video.
[0003] In the related art, due to the large number of graphics processors, it is impossible to perform regular maintenance on each graphics processor, which makes it easy for the graphics processor to have abnormalities in the video encoding and decoding process after long-term use, resulting in poor output image quality and reducing the user experience. Summary of the invention
[0004] The main purpose of this application is to provide a management method, device, equipment and storage medium for a graphics processor, which promptly prompts staff to handle abnormal graphics processors, ensuring that the graphics processor outputs images with good quality during video encoding and decoding.
[0005] In a first aspect, the present application provides a method for managing a graphics processor, comprising:
[0006] Acquire a plurality of first preset images;
[0007] Encoding the first plurality of preset images by a graphics processor to obtain a video;
[0008] Decoding the video to obtain a plurality of second preset images;
[0009] determining, according to an image feature of the first preset image, whether the plurality of second preset images include an abnormal image;
[0010] When the plurality of second preset images include an abnormal image, prompt information corresponding to the graphics processor is output, where the prompt information is used to prompt that an abnormality exists in the graphics processor.
[0011] In a second aspect, the present application further provides a graphics processor management device, comprising:
[0012] An acquisition module, used for acquiring a plurality of first preset images;
[0013] An encoding module, configured to encode the plurality of first preset images through a graphics processor to obtain a video;
[0014] A decoding module, used for decoding the video to obtain a plurality of second preset images;
[0015] an image determination module, configured to determine whether the plurality of second preset images include an abnormal image according to an image feature of the first preset image;
[0016] The prompt module is used to output prompt information corresponding to the graphics processor when the plurality of second preset images include an abnormal image, wherein the prompt information is used to prompt that the graphics processor is abnormal.
[0017] In a third aspect, the present application further provides a computer device, the computer device comprising a memory and a processor;
[0018] The memory is used to store computer programs;
[0019] The processor is used to execute the computer program and implement the above-mentioned graphics processor management method when executing the computer program.
[0020] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the management method of the graphics processor as described above are implemented.
[0021] The present application provides a management method, device, equipment and storage medium for a graphics processor, wherein the method comprises: obtaining a plurality of first preset images; encoding the plurality of first preset images by a graphics processor to obtain a video; decoding the video to obtain a plurality of second preset images; determining whether the plurality of second preset images include abnormal images according to the image features of the first preset images; when the plurality of second preset images include abnormal images, outputting prompt information corresponding to the graphics processor, the prompt information is used to prompt that the graphics processor has an abnormality. The present application can determine whether the plurality of second preset images obtained after encoding and decoding include abnormal images according to the image features of the acquired first preset images, thereby determining whether the graphics processor that processes the first preset images has an abnormality, and the detection method is fast and simple; furthermore, when there is an abnormal image in the plurality of second preset images, the prompt information corresponding to the graphics processor that processes the abnormal image can be output, so as to prompt the staff to process the abnormal graphics processor in time, thereby ensuring that the graphics processor outputs images of good quality during the video encoding and decoding process. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0023] Figure 1 A flowchart of a method for managing a graphics processor provided in an embodiment of the present application;
[0024] Figure 2 A schematic diagram of the connection between the server and the terminal device provided in the embodiment of the present application;
[0025] Figure 3 A schematic block diagram of a graphics processor management device provided in an embodiment of the present application;
[0026] Figure 4 A schematic block diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0027] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0028] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.
[0029] The embodiments of the present application provide a management method, device, equipment and storage medium for a graphics processor, wherein the management method for the graphics processor can be applied to a terminal device, which can be a mobile phone, a tablet computer, a laptop computer, a desktop computer and the like. It can also be applied to a server, which can be a separate server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.
[0030] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.
[0031] See also Figure 1 , Figure 1 A flowchart of a method for managing a graphics processor provided in an embodiment of the present application is provided. It should be noted that the method for managing a graphics processor provided in an embodiment of the present application can be used in a terminal device, and of course can also be used in a server.
[0032] like Figure 2 As shown, the management method of the graphics processor is applied to the server, the server and the terminal device are connected in communication, and the prompt information obtained by the management method of the graphics processor can be sent to the terminal device through the server. Of course, it is not limited to this and is not limited here.
[0033] In specific implementation, the terminal device includes but is not limited to: any one of a mobile phone, a tablet computer, a laptop computer, and a desktop computer; the server can be a single server or a server cluster, or a cloud server that provides cloud computing services.
[0034] like Figure 1 As shown, the management method of the graphics processor includes steps S101 to S104.
[0035] Step S101: Acquire a plurality of first preset images.
[0036] For example, the multiple first preset images in the embodiment of the present application may be the same image. In addition, the resolutions of the multiple first preset images may also be the same. For example, the resolutions of the multiple first preset images may all be 1080p.
[0037] In an exemplary embodiment, the first preset image is an image in a lossless format.
[0038] The first preset image in the embodiment of the present application may be an image in a lossless format. An image in a lossless format mainly refers to a picture format that does not lose image quality during compression. Specifically, the image size is reduced by using a specific compression algorithm, but after decompression, the image quality is substantially the same as the original image.
[0039] Exemplarily, the lossless format image may include a PNG (Portable Network Graphics) image, a GIF (Graphics Interchange Format) image, a TAG (Tagged Graphics) image, and the like.
[0040] For example, the first preset image in the embodiment of the present application may be a PNG image, which is a lossless compressed bitmap graphic format that can reduce the file size without losing image quality, thereby saving storage space and network bandwidth.
[0041] Step S102: encoding a plurality of first preset images by a graphics processor to obtain a video.
[0042] It should be noted that encoding images into videos means combining a series of static images in a certain order and rate to form a dynamic video that is played continuously. Encoding images into videos is one part of video encoding. The goal of image encoding is to reduce the amount of data as much as possible while maintaining image quality.
[0043] A graphics processor, or GPU (Graphics Processing Unit), is also called a visual processor, display chip, etc. It is a microprocessor that performs image-related operations. For example, the main function of a graphics processor is to render and process images and graphics.
[0044] For example, the graphics processor plays an important role in video encoding, and it has parallel processing capabilities and supports hardware acceleration. Specifically, during the video encoding process, the graphics processor needs to perform color space conversion, filtering, motion estimation and other processing operations on each frame of the image. In addition, the graphics processor can complete the task more quickly, significantly shortening the video encoding time.
[0045] Specifically, when the graphics processor encodes multiple first preset images, it is necessary to perform preprocessing operations on the multiple first preset images, for example, performing color space conversion (from RGB color space to YUV color space), resizing, denoising and other preprocessing operations on the first preset images, which helps to better represent image information in the subsequent encoding process. The graphics processor can use inter-frame prediction technology to compare the differences between consecutive frames and reduce data redundancy by calculating these differences. In addition, it can convert multiple first preset images into a set of frequency domain coefficients to achieve data compression by retaining high-frequency and low-frequency components. Then, the transformed frequency domain coefficients are quantized to approximate continuous values to reduce data accuracy and reduce the amount of information, thereby achieving compression. Finally, the quantized coefficients are encoded, and the data is further compressed using Huffman coding or other entropy coding techniques to generate a final encoded data stream.
[0046] The embodiment of the present application can encode multiple first preset images through a graphics processor to obtain a video. In the actual application scenario, the embodiment of the present application can first number the multiple first preset images in sequence, set the frame rate and time of the video playback, and then encode the multiple first preset images into a video of a corresponding format through a graphics processor. For example, the number of first preset images is 250, and the 250 first preset images are numbered in sequence, and the video frame rate is set to 25fps and the time is 10 seconds. Then, the video encoding command is executed to program the 250 first preset images into a video of a corresponding format (a video in H264 format).
[0047] Step S103: Decode the video to obtain a plurality of second preset images.
[0048] It should be noted that decoding a video into images means extracting each frame (ie, each static image) in a video file to obtain multiple separate images.
[0049] Specifically, the embodiment of the present application can open the video through a decoding tool and parse the basic information in the video, such as frame rate, width, height, encoding format, etc. The video is read frame by frame, and each frame in the video is decoded. The process of video decoding mainly involves entropy decoding, inverse quantization, inverse transformation, motion compensation, etc. The decoded frame generally exists in the form of an image. After decoding, it is also necessary to reconstruct the image sequence, for example, the decoded images are reordered in chronological order to form an image sequence to ensure the coherence and accuracy between the multiple second preset images obtained by decoding.
[0050] After the decoded image is obtained, the decoded image can be deblocked and filtered to reduce image distortion caused by compression and improve the visual quality of the image. In addition, the decoded image can be scaled and cropped according to actual conditions to adapt to different display resolutions or processing requirements.
[0051] In an exemplary implementation, step S103 may include: decoding the video based on a CPU to obtain a plurality of second preset images.
[0052] Specifically, different encoding formats require different decoders for decoding. Therefore, before decoding the video, it is necessary to determine the encoding format of the video, for example, H264, H265, MPEG-4, etc. The decoder can be a software decoder or a hardware decoder (such as a decoder built into the CPU).
[0053] Among them, the software decoder is a software device that can decode the digital video data stream and restore it to an analog video signal. In the process of information transmission, the video and other signals are encoded by the encoder and then transmitted through the IP network as a stream, and then the software decoder decodes it. Software decoders can include FLV decoders, DVD decoders, and RM decoders.
[0054] A hardware decoder is a device that restores compressed video data to the original signal. A hardware decoder may include a decoder built into the CPU. The decoder built into the CPU is a dedicated circuit integrated into the CPU, which is used to accelerate tasks such as video decoding. It implements a decoding algorithm through an integrated circuit to quickly restore compressed video data to the original signal. The decoder built into the CPU can achieve efficient decoding, and decoding by the decoder built into the CPU generally does not cause hardware anomalies. Based on this, the embodiment of the present application can decode the video based on the decoder built into the CPU to obtain multiple second preset images.
[0055] In an exemplary embodiment, the second preset image is a lossless format image.
[0056] For example, the second preset image in the embodiment of the present application may be an image in a lossless format. For example, the second preset image may be a PNG image.
[0057] Step S104, according to the image features of the first preset image, determine whether the multiple second preset images include abnormal images. It should be noted that the image features may include color features, texture features, shape features and spatial relationship features. Among them, the color feature is a global feature, which describes the surface properties of the scene corresponding to the image or image area, and the color feature is a feature based on pixels. The texture feature is also a global feature, which is different from the color feature, and the texture feature is not a feature based on pixels, but needs to be statistically calculated in an area containing multiple pixels. The shape feature describes the shape information of the object or area in the image. There are two types of representation methods, one is the contour feature, which is mainly aimed at the outer boundary of the object, and the other is the regional feature, which describes the local shape feature in the image. The spatial relationship feature refers to the spatial position or relative direction relationship between multiple targets segmented from the image. These relationships can be divided into adjacency relationships, overlapping relationships, and inclusion relationships.
[0058] Based on this, the difference between the second preset image and the first preset image may be determined according to the color feature, texture feature, shape feature or spatial relationship feature of the first preset image.
[0059] In actual applications, a large number of graphics processors will be deployed in data processing centers for a long time, and once the graphics processor is out of warranty, it is easy to have problems. For example, when the graphics processor encodes a video in H264 format, it is easy to cause abnormal stripes in the image of the video, and these stripes do not belong to the content of the video, resulting in a reduced user experience. Based on this, the embodiment of the present application encodes multiple first preset images through a graphics processor, and then determines whether the second preset image includes an abnormal image based on the difference between the color features, texture features, shape features or spatial relationship features of the first preset image and the second preset image obtained through encoding and decoding.
[0060] Step S105: when the plurality of second preset images include an abnormal image, outputting prompt information corresponding to the graphics processor, where the prompt information is used to prompt that the graphics processor is abnormal.
[0061] Exemplarily, when it is determined that the plurality of second preset images include an abnormal image, prompt information corresponding to the graphics processor may be output, the prompt information being used to indicate that the graphics processor is abnormal, thereby prompting staff to process the abnormal graphics processor in a timely manner.
[0062] Exemplarily, when it is determined that the second preset image includes an abnormal image, an alarm log can be generated, which can record the number of the abnormal graphics processor and send the alarm log to the staff's terminal device to prompt the staff to process the abnormal graphics processor in time.
[0063] In an exemplary implementation, step S104 may include step S401 and step S402.
[0064] Step S401: Detect the preset unit areas of each second preset image to determine whether image features of the preset unit areas and image features of areas corresponding to the preset unit areas in the first preset image meet preset conditions.
[0065] Step S402: When the image feature of the preset unit area and the image feature of the area corresponding to the preset unit area in the first preset image meet a preset condition, determine that the plurality of second preset images include an abnormal image.
[0066] For example, the preset unit area may be each row of pixels or each column of pixels in the second preset image, etc. The preset condition may be that the color feature of the preset unit area is different from the color feature of the area corresponding to the preset unit area in the first preset image; or the texture feature of the preset unit area is different from the texture feature of the area corresponding to the preset unit area in the first preset image.
[0067] Exemplarily, the embodiment of the present application can detect each row of pixels or each column of pixels of each second preset image to determine whether the color characteristics of the preset unit area and the color characteristics of the corresponding area of the preset unit area in the first preset image meet the preset conditions. When the preset conditions are met, it can be determined that there is a large difference between the second preset image and the first preset image, so that it can be determined that multiple second preset images include abnormal images. For example, if the color displayed by one or more rows of pixels in the second preset image is different from the color displayed by the corresponding area in the first preset image, it can be determined that the second preset image is an abnormal image.
[0068] In an exemplary implementation, step S104 may further include step S403.
[0069] Step S403: when the image features of the preset unit area and the image features of the area corresponding to the preset unit area in the first preset image meet a preset condition, stop detecting the plurality of second preset images.
[0070] When it is determined that the image features of the preset unit area and the image features of the area corresponding to the preset unit area in the first preset image meet the preset conditions, the embodiment of the present application can stop detecting the other remaining second preset images. Specifically, the embodiment of the present application can detect each row of pixels of the second preset image by row. When it is detected that the color displayed by the pixels of the third row is different from the color displayed by the pixels of the row corresponding to the third row in the first preset image, it can be determined that the current second preset image is an abnormal image and the detection of the remaining second preset images is stopped. After detecting the abnormal image, the embodiment of the present application can determine that the corresponding graphics processor has an abnormality, and there is no need to detect the remaining second preset images. This can reduce unnecessary work processes, thereby improving the efficiency of detection.
[0071] In an exemplary embodiment, the first preset image is an image of a first color, and the image features of the preset unit area and the image features of the area corresponding to the preset unit area in the first preset image meet the preset conditions, which may include:
[0072] At least a portion of the preset unit area is presented in a second color, and the second color and the first color meet a preset condition.
[0073] For example, if the color presented by the preset unit area of the second preset image is the same as the color presented by the first preset image, that is, both are black, it means that the plurality of second preset images do not include an abnormal image.
[0074] For example, the first color in the embodiment of the present application may be black, that is, the colors of the plurality of first preset images are all black. The second color may be other colors except black, for example, white or gray.
[0075] The second color and the first color meet the preset condition, that is, the second color is different from the first color. Specifically, when at least part of the preset unit area of the second preset image is white or gray, it is obviously different from the color of the black first preset image, that is, the second color and the first color meet the preset condition. Therefore, it can be determined that there are abnormal images in the multiple second preset images. By detecting the colors of the corresponding areas of the first preset image and the second preset image, it is possible to more quickly detect whether there are abnormal images in the multiple second preset images, and the detection method is relatively simple.
[0076] In an exemplary embodiment, the second color and the first color satisfy a preset condition, which may include:
[0077] The RGB value of the first color is within a preset range, and the RGB value of the second color is outside the preset range.
[0078] It should be noted that RGB is a color mode that represents the three channels of red, green and blue. In practical applications, various colors can be obtained by adjusting and changing the three color channels of red, green and blue and superimposing them on each other. Generally, the range of R value, G value and B value in RGB value is 0-255.
[0079] For example, the embodiment of the present application can set a preset range. If the RGB value of the first color is within the preset range and the RGB value of the second color exceeds the preset range, it can be determined that the second color and the first color meet the preset condition. For example, the first color of the first preset image is black, and the RGB value of black is 0. For videos in H264 format, it is a lossy compression format. Therefore, the black image may not be all zero values after encoding. Therefore, a preset range of 0-50 RGB values can be set. If the second color displayed by a row of pixels in the second preset image is white, and the RGB value of white is 255, which exceeds the preset range, the second preset image will have an abnormal situation of white stripes, and the second preset image can be determined to be an abnormal image.
[0080] In an exemplary implementation, step S401 may include: step S4011 and step S4012.
[0081] Step S4011: split each second preset image into a first color image, a second color image, and a third color image according to the three RGB color channels.
[0082] Step S4012: Detect the preset unit area of the first color image, the preset unit area of the second color image, and the preset unit area of the third color image.
[0083] In an embodiment of the present application, each second preset image can be split into a first color image (R image), a second color image (G image) and a third color image (B image) according to the three RGB color channels, and then each row of pixels of the first color image (R image), each row of pixels of the second color image (G image) and each row of pixels of the third color image (B image) are detected. When the R value of at least one row of pixels in the first color image (R image) exceeds the preset range, or the G value of at least one row of pixels in the second color image (G image) exceeds the preset range, or the value of at least one row of pixels in the third color image (B image) exceeds the preset range, the second preset image can be determined to be an abnormal image. In an embodiment of the present application, the second preset image is split into three color images according to the three RGB color channels, and then the R value, G value and B value corresponding to the three color images are respectively detected to further improve the detection accuracy.
[0084] The management method of the graphics processor provided in the above embodiment includes: obtaining multiple first preset images; encoding multiple first preset images through a graphics processor to obtain a video; decoding the video to obtain multiple second preset images; determining whether the multiple second preset images include abnormal images according to the image features of the first preset images; when the multiple second preset images include abnormal images, outputting prompt information corresponding to the graphics processor, and the prompt information is used to prompt that the graphics processor has an abnormality. The embodiment of the present application can determine whether the multiple second preset images obtained after encoding and decoding include abnormal images according to the image features of the acquired first preset image, so as to determine whether the graphics processor processing the first preset image has an abnormality, and the detection method is fast and simple; furthermore, when there is an abnormal image in the multiple second preset images, the prompt information corresponding to the graphics processor processing the abnormal image can be output, so as to prompt the staff to process the abnormal graphics processor in time, thereby ensuring that the graphics processor outputs images with better quality during the video encoding and decoding process.
[0085] See also Figure 3 , Figure 3 A schematic block diagram of a graphics processor management device provided in an embodiment of the present application. The graphics processor management device can be configured in a server or a terminal device to execute the aforementioned graphics processor management method.
[0086] like Figure 3 As shown, the management device of the graphics processor includes: an acquisition module 110 , an encoding module 120 , a decoding module 130 , an image determination module 140 and a prompt module 150 .
[0087] The acquisition module 110 is used to acquire a plurality of first preset images.
[0088] The encoding module 120 is configured to encode a plurality of first preset images through a graphics processor to obtain a video.
[0089] The decoding module 130 is used to decode the video to obtain a plurality of second preset images.
[0090] The image determination module 140 is used to determine whether the plurality of second preset images include an abnormal image according to the image feature of the first preset image.
[0091] The prompt module 150 is used to output prompt information corresponding to the graphics processor when the plurality of second preset images include an abnormal image, where the prompt information is used to prompt that the graphics processor is abnormal.
[0092] In an exemplary embodiment, the image determination module 140 includes a detection submodule and an abnormality determination submodule.
[0093] The detection submodule is used to detect the preset unit area of each second preset image to determine whether the image features of the preset unit area and the image features of the area corresponding to the preset unit area in the first preset image meet the preset conditions.
[0094] The abnormality determination submodule is used to determine that the plurality of second preset images include an abnormal image when the image features of the preset unit area and the image features of the area corresponding to the preset unit area in the first preset image meet preset conditions.
[0095] In an exemplary embodiment, the first preset image is an image of a first color, and the image features of the preset unit area and the image features of the area corresponding to the preset unit area in the first preset image meet preset conditions, including:
[0096] At least a portion of the preset unit area is presented in a second color, and the second color and the first color meet a preset condition.
[0097] In an exemplary embodiment, the second color and the first color meet a preset condition, including:
[0098] The RGB value of the first color is within a preset range, and the RGB value of the second color is outside the preset range.
[0099] In an exemplary embodiment, the detection submodule may include a segmentation submodule and a region detection submodule.
[0100] The splitting submodule is used to split each second preset image into a first color image, a second color image and a third color image according to the three RGB color channels.
[0101] The area detection submodule is used to detect the preset unit area of the first color image, the preset unit area of the second color image, and the preset unit area of the third color image.
[0102] In an exemplary embodiment, the image determination module 140 may further include a detection stop submodule.
[0103] The detection stopping submodule is used to stop detecting the plurality of second preset images when the image features of the preset unit area and the image features of the area corresponding to the preset unit area in the first preset image meet preset conditions.
[0104] In an exemplary implementation, the video is decoded based on a CPU to obtain a plurality of second preset images.
[0105] It should be noted that technicians in the relevant field can clearly understand that for the convenience and simplicity of description, the specific working processes of the above-described devices and modules and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.
[0106] The method of the present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.
[0107] Exemplarily, the above method and apparatus may be implemented in the form of a computer program, which may be run on a computer device.
[0108] See also Figure 4 , Figure 4 A schematic block diagram of the structure of a computer device provided in an embodiment of the present application. The computer device may be a server or a terminal device.
[0109] like Figure 4 As shown, the computer device includes a processor, a memory, and a network interface connected via a system bus, wherein the memory may include a storage medium and an internal memory.
[0110] The storage medium can store an operating system and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute the steps of any one of the management methods of the graphics processor.
[0111] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.
[0112] The internal memory provides an environment for the operation of the computer program in the storage medium. When the computer program is executed by the processor, the processor can execute the steps of any one of the management methods of the graphics processor.
[0113] The network interface is used for network communication, such as sending assigned tasks.
[0114] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.
[0115] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.
[0116] In one embodiment, the processor is used to execute a computer program and implement the following steps when executing the computer program:
[0117] Acquire a plurality of first preset images;
[0118] Encoding a plurality of first preset images by a graphics processor to obtain a video;
[0119] Decoding the video to obtain a plurality of second preset images;
[0120] determining, according to an image feature of the first preset image, whether the plurality of second preset images include an abnormal image;
[0121] When the plurality of second preset images include an abnormal image, prompt information corresponding to the graphics processor is output, where the prompt information is used to prompt that an abnormality exists in the graphics processor.
[0122] In an exemplary embodiment, determining whether the plurality of second preset images include an abnormal image according to an image feature of the first preset image includes:
[0123] Detecting the preset unit areas of each second preset image to determine whether image features of the preset unit areas and image features of areas corresponding to the preset unit areas in the first preset image meet preset conditions;
[0124] When the image feature of the preset unit area and the image feature of the area corresponding to the preset unit area in the first preset image meet a preset condition, it is determined that the plurality of second preset images include an abnormal image.
[0125] In an exemplary embodiment, the first preset image is an image of a first color, and the image features of the preset unit area and the image features of the area corresponding to the preset unit area in the first preset image meet preset conditions, including:
[0126] At least a portion of the preset unit area is presented in a second color, and the second color and the first color meet a preset condition.
[0127] In an exemplary embodiment, the second color and the first color meet a preset condition, including:
[0128] The RGB value of the first color is within a preset range, and the RGB value of the second color is outside the preset range.
[0129] In an exemplary embodiment, detecting the preset unit area of each second preset image includes:
[0130] According to the three color channels of RGB, each second preset image is split into a first color image, a second color image and a third color image;
[0131] The preset unit area of the first color image, the preset unit area of the second color image, and the preset unit area of the third color image are detected.
[0132] In an exemplary embodiment, the method further comprises:
[0133] When the image feature of the preset unit area and the image feature of the area corresponding to the preset unit area in the first preset image meet a preset condition, the detection of the plurality of second preset images is stopped.
[0134] In an exemplary implementation, decoding a video to obtain a plurality of second preset images includes:
[0135] The video is decoded based on the CPU to obtain a plurality of second preset images.
[0136] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the management of the graphics processor described above can refer to the corresponding process in the embodiment of the aforementioned graphics processor management method, and will not be repeated here.
[0137] The embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. The method implemented when the computer program is executed by a processor can refer to the various embodiments of the management method of the graphics processor of the present application.
[0138] The computer-readable storage medium may be an internal storage unit of the computer device of the aforementioned embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device.
[0139] It should be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.
[0140] It should also be understood that the term "and / or" used in the specification of this application and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, including these combinations. It should be noted that, in this article, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "including a..." does not exclude the presence of other identical elements in the process, method, article or system including the element.
[0141] The serial numbers of the embodiments of the present application are for description only and do not represent the advantages and disadvantages of the embodiments. The above description is only a specific implementation mode of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.
Claims
1. A method for managing a graphics processor, characterized in that: include: Acquire a plurality of first preset images; Encoding the first plurality of preset images by a graphics processor to obtain a video; Decoding the video to obtain a plurality of second preset images; determining, according to an image feature of the first preset image, whether the plurality of second preset images include an abnormal image; When the plurality of second preset images include an abnormal image, prompt information corresponding to the graphics processor is output, where the prompt information is used to prompt that an abnormality exists in the graphics processor.
2. The method for managing a graphics processor according to claim 1, characterized in that: The determining, based on the image feature of the first preset image, whether the plurality of second preset images include an abnormal image comprises: Detecting each preset unit area of the second preset image to determine whether image features of the preset unit area and image features of an area corresponding to the preset unit area in the first preset image meet preset conditions; When the image feature of the preset unit area and the image feature of the area corresponding to the preset unit area in the first preset image meet the preset condition, it is determined that the plurality of second preset images include an abnormal image.
3. The method for managing a graphics processor according to claim 2, wherein: The first preset image is an image of a first color, and the image features of the preset unit area and the image features of the area corresponding to the preset unit area in the first preset image meet preset conditions, including: At least a portion of the preset unit area is presented in a second color, and the second color and the first color meet a preset condition.
4. The method for managing a graphics processor according to claim 3, characterized in that: The second color and the first color satisfy a preset condition, including: The RGB value of the first color is within a preset range, and the RGB value of the second color is beyond the preset range.
5. The method for managing a graphics processor according to claim 2, wherein: The detecting of the preset unit areas of each of the second preset images includes: According to the three color channels of RGB, each of the second preset images is split into a first color image, a second color image and a third color image; The preset unit area of the first color image, the preset unit area of the second color image, and the preset unit area of the third color image are detected.
6. The method for managing a graphics processor according to claim 2, characterized in that: The method further comprises: When the image feature of the preset unit area and the image feature of the area corresponding to the preset unit area in the first preset image meet the preset condition, the detection of the plurality of second preset images is stopped.
7. The method for managing a graphics processor according to any one of claims 1 to 5, characterized in that: The decoding of the video to obtain a plurality of second preset images includes: The video is decoded based on the CPU to obtain a plurality of second preset images.
8. A graphics processor management device, characterized in that: include: An acquisition module, used for acquiring a plurality of first preset images; An encoding module, configured to encode the plurality of first preset images through a graphics processor to obtain a video; A decoding module, used for decoding the video to obtain a plurality of second preset images; an image determination module, configured to determine whether the plurality of second preset images include an abnormal image according to an image feature of the first preset image; The prompt module is used to output prompt information corresponding to the graphics processor when the plurality of second preset images include an abnormal image, wherein the prompt information is used to prompt that the graphics processor is abnormal.
9. A computer device, characterized in that: The computer device includes a memory and a processor; The memory is used to store computer programs; The processor is used to execute the computer program and implement the graphics processor management method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for managing a graphics processor according to any one of claims 1 to 7 are implemented.