CN113052751A - Artificial intelligence processing method - Google Patents
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- CN113052751A CN113052751A CN202110461703.4A CN202110461703A CN113052751A CN 113052751 A CN113052751 A CN 113052751A CN 202110461703 A CN202110461703 A CN 202110461703A CN 113052751 A CN113052751 A CN 113052751A
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Abstract
The application provides an artificial intelligence processing method, which is applied to a terminal, and the terminal comprises the following steps: the system comprises a processor, a memory, a camera and a display screen; the processor includes: a general processor, an image processor GPU and an AI processor; wherein the general processor, the image processor, and the AI processor are connected to each other. The technical scheme provided by the application has the advantage of high video processing speed.
Description
Technical Field
The application relates to the technical field of image processing, in particular to an artificial intelligence processing method.
Background
A Graphics processor (abbreviated as GPU), also called a display core, a visual processor, and a display chip, is a microprocessor that is specially used for image and Graphics related operations on a personal computer, a workstation, a game machine, and some mobile devices (such as a tablet computer, a smart phone, etc.).
The existing AI robot virtualized by GPU influences the processing speed of video.
Disclosure of Invention
The embodiment of the application provides an artificial intelligence processing method which has the advantage of high image processing speed.
In a first aspect, an embodiment of the present application provides an artificial intelligence processing method, where the method is applied to a terminal, and the terminal includes: the system comprises a processor, a memory, a camera and a display screen; the processor includes: a general processor, an image processor GPU and an AI processor; wherein the general processor, the image processor and the AI processor are connected to each other; the method comprises the following steps:
the general processor reads the first x frame data of the video from the memory and sends the first x frame data to the GPU;
the GPU carries out image processing on the previous x frame data to obtain the previous x frame picture data; sending each frame of picture of the previous x frames of picture data to an AI (Artificial intelligence) processor;
the AI processor identifies and determines a target object area and a background area of each frame of picture, and superposes the first x target object areas of the previous x frame of picture data to obtain the range of a first area of the video and the range of the background area of the video; sending the range of the first area to a general purpose processor;
the general processor determines subsequent data of the video x frame and sends partial data corresponding to the range of the first area in the subsequent data to the GPU;
and the GPU calculates the partial data to obtain partial picture data of subsequent data, and splices the partial picture data with data corresponding to the range of the background area of the video to obtain subsequent picture result data.
The embodiment of the application has the following beneficial effects:
it can be seen that, when the technical scheme provided by the application is used for processing a video, only the first x frames of pictures of the video are completely processed, then only partial data corresponding to the range of the first area is processed for subsequent data, and the pictures of the subsequent data are obtained after simple splicing, so that the processing amount of the subsequent data is reduced, the video processing efficiency is improved, the operation amount is reduced, and the video processing speed is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a terminal.
Fig. 2 is a schematic structural diagram of a processor according to an embodiment of the present application.
Fig. 3 is a schematic structural diagram of a GPU provided in the present application.
Fig. 4 is a schematic distribution diagram of a signaling sub-region, a data sub-region, and a composite sub-region provided in the present application.
Fig. 5 is a schematic structural diagram of an AI processor provided in the present application.
Fig. 6 is a schematic diagram of regions of two frames and a target object of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of this application and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, result, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Referring to fig. 1, fig. 1 provides a terminal (which may also be referred to as an AI robot management device or system based on GPU virtualization), which may specifically include: the device comprises a processor, a memory, a camera and a display screen, wherein the components can be connected through a bus or in other ways, and the application is not limited to the specific way of the connection.
Referring to fig. 2, the processor may specifically include: a general purpose processor, an image processor GPU and an AI processor. The artificial intelligence processing method comprises the following steps: service robot, intelligent fitting equipment.
The general processor, the image processor GPU and the AI processor are connected with each other in pairs.
Referring to fig. 3, fig. 3 provides a structure of a GPU, and referring to fig. 3 (taking m as 6, n as 6 as an example, m may be greater than 6, such as 12, 18, etc.), fig. 3 provides a structure of a GPU, which may specifically include: a storage unit 201, n control units 202, a calculation unit 203, a signaling forwarding unit 204, a data forwarding unit 205, and a composite forwarding unit 206; the sum of the number of the calculating unit 203, the signaling forwarding unit 204, the data forwarding unit 205 and the composite forwarding unit 206 is m × n;
wherein the n control units 202 are arranged in a column, the m × n control units are arranged in a matrix, where m is a row value of the matrix, n is a column value of the matrix, and the n control units 202 are respectively connected with the n control units in the first column of the m × n control units arranged in the matrix; the memory cells 201 are connected to the m cells in the last row of the matrix arrangement, respectively;
the m × n units arranged in the matrix comprise a common area 301, a signaling forwarding area 302, a data forwarding area 303 and a composite forwarding area 304; wherein, the normal area 301 only includes the calculating unit 203, and the signaling forwarding area 302 includes: a calculating unit and a signaling forwarding unit; the data forwarding area 303 includes: a computing unit and a data forwarding unit, the composite forwarding region 304 includes: a computing unit and a composite forwarding unit;
the control unit is used for sending a calculation instruction to the calculation unit, the signaling forwarding unit and the composite forwarding unit; for convenience of drawing, the connections of the control unit with the signaling forwarding unit and the composite forwarding unit are indicated by dotted lines,
a storage unit 201 for storing calculation data or calculation results;
the storage unit 201 has a plurality of IO (input/output) interfaces, and the plurality of IO interfaces are respectively connected to the m calculation units, the data forwarding units, and the composite forwarding unit in the last row of the matrix arrangement; for convenience of drawing, the connections of the storage unit to the data forwarding unit and the composite forwarding unit are indicated by dotted lines,
a calculation unit, configured to perform an operation (arithmetic operations such as addition, subtraction, multiplication, and division) on calculation data (which may be read or received calculation data) according to the calculation instruction to obtain a calculation result; sending the calculation result to a storage unit (if the calculation result is connected with the IO interface of the storage unit, the calculation result is directly sent to the storage unit, and if the calculation result is not directly connected with the IO interface of the storage unit, the calculation result is sent to the storage unit through a forwarding mode (the calculation unit can be directly connected with a composite forwarding unit or the storage unit);
the signaling forwarding unit is used for receiving the calculation instruction sent by the control unit and forwarding the calculation instruction to 8 calculation units at the edge of the 3 × 3 array of the control unit;
the data forwarding area comprises a plurality of data subregions, each data subregion is arranged in a 3 × 3 array (as shown in fig. 3), the data forwarding unit is located at the center of the 3 × 3 array and is respectively connected with 8 computing units at the edge of the 3 × 3 array, and the data forwarding unit is used for extracting the computing data of the storage unit and forwarding the computing data to 8 computing units at the edge of the 3 × 3 array of the control unit;
the composite forwarding area comprises a plurality of composite sub-areas, each composite sub-area is arranged in a 3 × 3 array (as shown in fig. 3), the composite forwarding unit is located at the center of the 3 × 3 array, and the composite forwarding unit is respectively connected with 8 computing units at the edge of the 3 × 3 array, and the composite forwarding unit is used for receiving computing instructions sent by the control unit, extracting computing data of the storage unit, and forwarding the computing instructions and the computing data to the 8 computing units at the edge of the 3 × 3 array.
M and n are integers greater than or equal to 5, and m is greater than or equal to n.
As shown in fig. 4, adjacent computing units are connected to each other, and the connection may be for transferring data or signaling. The adjacent positions can be vertically adjacent or horizontally adjacent.
The influence on the calculation speed mainly has 2 directions, the first direction is high in calculation speed, namely the same data calculation speed is high, the first direction is mainly related to the frequency of a processing circuit, the second direction is low in IO (input/output) overhead, namely the same data forwarding times are low, for the structure of the GPU, because the number of calculation units is large, if all the calculation units are directly connected with a control unit and a storage unit, the number of interfaces of the control unit and the storage unit is greatly increased, the cost is greatly increased, so that a large number of IO interfaces are not increased, the forwarding times are required to be reduced, based on the thought, 4 areas are divided, and different forwarding units (forwarding circuits) are respectively arranged for the characteristics of the 4 areas to realize different functions, so that the image processing speed is improved.
The technical effect of the technical scheme provided by the application is mainly to reduce the forwarding times of the calculation data or the calculation signaling, that is, the forwarding times of the calculation data or the calculation signaling are reduced by arranging corresponding forwarding units in different areas, so that the time delay of the calculation data and the calculation signaling is reduced, and the processing speed of the image is further improved.
Each of the above units may be implemented by a hardware circuit, which includes but is not limited to an FPGA, a CGRA, an ASIC, an analog circuit, a memristor, and the like.
Referring to fig. 5, fig. 5 provides a structure of an AI processor for performing a neural network forward operation; the neural network comprises n layers; the AI processor has a structure as shown in fig. 5, and includes:
the AI processor includes: the system comprises a main processing circuit, k branch processing circuits and k groups of basic processing circuits, wherein the main processing circuit is respectively connected with the k branch processing circuits, each branch processing circuit in the k branch processing circuits corresponds to one group of basic processing circuits in the k groups of basic processing circuits, and the group of basic processing circuits comprises at least one basic processing circuit.
Of course, in practical applications, the AI processor may also be a general AI processor, such as the processing chip 270.
The artificial intelligence processing method shown in fig. 1 may be specifically used for executing video processing, and specifically may include:
the general processor reads the first x frame data of the video from the memory and sends the first x frame data to the GPU;
the GPU carries out image processing on the previous x frame data to obtain the previous x frame picture data; sending each frame of picture of the previous x frames of picture data to an AI (Artificial intelligence) processor;
the above implementation manner of performing image processing on the previous x frame data to obtain the previous x frame picture data may specifically refer to the operation manner of the GPU structure shown in fig. 2 and 3, in this way, the calculation data in the GPU structure shown in fig. 2 and 3 may be the previous x frame data, and the calculation result may be the previous x frame picture data.
Of course, the image processing performed on the previous x frame data to obtain the previous x frame picture data may also be performed in a passing picture processing manner, which is not described herein again.
The AI processor identifies and determines a target object area and a background area of each frame of picture for each frame of picture, and superposes the first x target object areas of the previous x frame of picture data to obtain the range of a first area of the video (namely the set of areas where x target objects possibly appear obtained by identification) and the range of the background area of the video; sending the range of the first area to a general purpose processor;
specifically, the range of the first x target object areas of the preceding x frame picture data that are superposed to obtain the first area of the video may specifically include:
and determining all the area identifications of the first x target object areas, and determining all the area identifications as the range of the first area.
For example, the first x target object regions relate to region 3, region 4, and region 5, and then the first region may range from region 3, region 4, and region 5. The area range and the number of the areas contained in the picture can be set by a manufacturer, and due to the fixed background, the size of each frame of picture acquisition of the video frame is consistent, rectangular frames are established in the size, and each rectangular frame can represent one area.
The general processor determines subsequent data of the video x frame and sends partial data corresponding to the range of the first area in the subsequent data to the GPU;
the subsequent data may be data corresponding to a video frame after the xth frame of the video.
And the GPU calculates the partial data to obtain partial picture data of subsequent data, and splices the partial picture data with data corresponding to the range of the background area of the video to obtain subsequent picture result data.
The subsequent picture result data may include: data in different picture formats, such as JPGE, PDF, etc.
The above implementation manner of calculating the partial data to obtain the partial picture of the subsequent data may specifically refer to the operation manner of the GPU structure shown in fig. 2 and 3, in this way, the calculation data in the GPU structure shown in fig. 2 and 3 may be partial data, and the calculation result may be a partial picture.
Of course, the partial pictures obtained by calculating the partial data to obtain the subsequent data may also be processed in a through picture processing manner, which is not described herein again.
The value of x may be a small integer, for example, the value range of x is [ 10,100 ].
According to the technical scheme, when the video is processed, only the front x frame picture of the video is completely processed, then only partial data corresponding to the range of the first area is processed for the subsequent data, and the picture of the subsequent data is obtained by simply splicing, so that the processing amount of the subsequent data is reduced, the video processing efficiency is improved, the calculation amount is reduced, and the video processing speed is improved.
For example, in an alternative scheme, the method may further include:
the general processor establishes a mapping relation between each frame of data of the video and the area range in advance, and the mapping relation can be used for determining partial data corresponding to the range of the first area. The mapping relationship may specifically be a storage space set corresponding to the area identifier, and the range of the first area may be an area identifier set (the range of the background area may be an area identifier set other than the range of the first area in the video frame), for example, the range of the first area includes an area 3, an area 4, and an area 5, and then it is determined according to the mapping relationship that the storage space 3, the storage space 4, and the storage space 5 corresponding to the area 3, the area 4, and the area 5 determine that the part of data is data stored in the storage space 3, the storage space 4, and the storage space 5.
The video of the present application may specifically be a video with a fixed background, that is, a video with a camera that does not rotate in angle, for an artificial intelligence processing method, such as a common service robot in a shopping mall, although it may move, it is generally not moved during a time period operated by a user, and this captured video is a video with a fixed background (because the shooting angle and position are fixed), and for such a video, there is a feature that the background is fixed, but a target object (for example, a user) moves, but the area where the video is shot is specific, then for all frames of the video, only the area range of the target object in the video frame picture is different, as shown in fig. 6, from frame 1 to frame 2, the target object 601 actually moves only by a distance x, then, if a mapping relationship between each frame data of the video and the area range is established in advance, after the area range of the target object is determined by the AI processor, for the subsequent video frame, only the data corresponding to the area range of the target object needs to be subjected to image processing, and the other data directly uses the data corresponding to the background area range of the previous frame (i.e., the previous x frame), so that the operation times of the data corresponding to the background area range can be reduced, and further, the data amount of video operation is reduced.
Referring to fig. 6, the box in fig. 6 is a region, the inner number indicates the identification of each region, here, only 5 regions are identified, the dotted line in fig. 6 indicates the range of the target object 601 in the frame 1, and the solid line indicates the range of the target object 601 in the frame 2.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (7)
1. An artificial intelligence processing method is applied to a terminal, and the terminal comprises the following steps: the system comprises a processor, a memory, a camera and a display screen; the processor includes: a general processor, an image processor GPU and an AI processor; wherein the general processor, the image processor and the AI processor are connected to each other; characterized in that the method comprises:
the general processor reads the first x frame data of the video from the memory and sends the first x frame data to the GPU;
the GPU carries out image processing on the previous x frame data to obtain the previous x frame picture data; sending each frame of picture of the previous x frames of picture data to an AI (Artificial intelligence) processor;
the AI processor identifies and determines a target object area and a background area of each frame of picture, and superposes the first x target object areas of the previous x frame of picture data to obtain the range of a first area of the video and the range of the background area of the video; sending the range of the first area to a general purpose processor;
the general processor determines subsequent data of the video x frame and sends partial data corresponding to the range of the first area in the subsequent data to the GPU;
and the GPU calculates the partial data to obtain partial picture data of subsequent data, and splices the partial picture data with data corresponding to the range of the background area of the video to obtain subsequent picture result data.
2. The artificial intelligence process of claim 1,
the general processor establishes a mapping relation between each frame of data of the video and the area range in advance.
3. The artificial intelligence processing method of claim 1, wherein said overlaying the first x target object regions of the first x frame of picture data to obtain the first region of the video specifically comprises
And determining all the area identifications of the first x target object areas, and determining all the area identifications as the range of the first area.
4. The method according to any one of claims 1 to 3,
the AI processor includes: the system comprises a main processing circuit, k branch processing circuits and k groups of basic processing circuits, wherein the main processing circuit is respectively connected with the k branch processing circuits, each branch processing circuit in the k branch processing circuits corresponds to one group of basic processing circuits in the k groups of basic processing circuits, and the group of basic processing circuits comprises at least one basic processing circuit.
5. The method according to any one of claims 1 to 3,
the GPU comprises: the device comprises a storage unit, n control units, a calculation unit, a signaling forwarding unit, a data forwarding unit and a composite forwarding unit; the sum of the number of the computing unit, the number of the signaling forwarding unit, the number of the data forwarding unit and the number of the composite forwarding unit is m x n;
the n control units are arranged in columns, the m × n units are arranged in a matrix, wherein m is a row value of the matrix, n is a column value of the matrix, and the n control units are respectively connected with the n units in the first column of the m × n units arranged in the matrix; the memory cells are respectively connected with the m cells in the last row of the matrix arrangement;
the m-n units arranged in the matrix comprise a common area, a signaling forwarding area, a data forwarding area and a composite forwarding area; wherein, the normal area only includes the computational element, and the signaling forwarding area includes: a calculating unit and a signaling forwarding unit; the data forwarding area includes: the composite forwarding area comprises: a computing unit and a composite forwarding unit.
6. The artificial intelligence processing method of claim 5 wherein the data forwarding unit and the composite forwarding unit are each provided with a register.
7. The artificial intelligence process of claim 1,
the terminal is as follows: service robot, intelligent fitting equipment.
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