Multi-channel video stream exporting method and system based on multi-agent visual simulation, electronic equipment and storage medium

Abstract

The invention provides a multi-channel video stream exporting method and system based on multi-agent visual simulation, electronic equipment and a storage medium. The exporting method comprises the following steps: generating a corresponding simulation image group according to a simulation image corresponding to each agent exported by a visual simulation end based on a preset exporting frequency; the simulation image group is processed through the simulation processing end to obtain data information of the simulation image group, and the data information comprises image information and a preset character string image; storing the data information into a preset database through the simulation processing end; establishing a communication connection between the stream pushing end and a preset database, so that the stream pushing end obtains a preset character string image from the data information; decoding the preset character string image into image byte stream type data through a stream pushing end; pushing the image byte stream type data to a message queue of the stream pushing end in a preset mode through the stream pushing end; asynchronously writing the image byte stream type data into a preset cache region through a stream pushing end so as to push the image byte stream type data to a preset stream pushing center; and pulling the video stream corresponding to each agent from a preset stream pushing center through the stream pulling end.

Description

Technical Field

[0001] The present application relates to the technical field of visual simulation, and in particular to a method and system for exporting multi-channel video streams based on multi-agent visual simulation, an electronic device and a storage medium. Background Art

[0002] Visual simulation technology is a combination of computer graphics technology and virtual reality technology. It expresses and simulates various information by constructing three-dimensional models or reproducing real environments.

[0003] Visual simulation software (UnrealEngine or AirSim open source simulation platform) is a basic tool for creating and experiencing three-dimensional virtual environments. It can integrate multiple core technologies such as graphics rendering and physical simulation. Through the switching application of virtual cameras, users can accurately simulate various scenes in the real world (such as urban landscapes, space environment exploration, etc.), interactions between objects or actions (such as walking, driving or equipment operation training, etc.).

[0004] In a multi-agent visual simulation scenario (including multiple interacting individual agents), in order to fully perceive the virtual environment situation, the visual simulation software needs to support the simultaneous export of real-time video streams of multiple agents.

[0005] However, the inventors of this application have found that most current visual simulation software can only support virtual camera perspective switching and image export functions. They can generally only store the recorded images of each virtual camera as video files, but do not support the export function of multiple real-time video streams.

[0006] In addition, although some visual simulation software can support the export of real-time video streams, it has relatively high requirements for the video export frequency (such as 25-60HZ), which makes it easy for the simulation computer machine rendering or IO performance bottleneck to be encountered when exporting multiple real-time video streams at the same time, so that the number of real-time video streams is limited (such as limited to 8 channels), and the export of multiple video streams cannot be realized. Summary of the invention

[0007] According to one aspect of the present application, the present application provides a method for exporting multiple video streams based on multi-agent visual simulation, including generating a corresponding simulation image group according to the simulation image corresponding to each agent exported by the visual simulation end based on a preset export frequency; processing the simulation image group through the simulation processing end to obtain data information of the simulation image group, the data information including image information and preset string images; storing the data information in a preset database through the simulation processing end; establishing a communication connection between the push stream end and the preset database, so that the push stream end obtains the preset string image from the data information; decoding the preset string image into image byte stream data through the push stream end; pushing the image byte stream data to the message queue of the push stream end in a preset manner through the push stream end; asynchronously writing the image byte stream data into a preset cache area through the push stream end to push the image byte stream data to a preset push stream center; and pulling the video stream corresponding to each agent from the preset push stream center through the pull stream end.

[0008] According to some embodiments of the present application, generating a corresponding simulation image group based on the simulation image corresponding to each intelligent agent exported by the visual simulation terminal based on a preset export frequency includes: generating a simulation image group based on the simulation image through the visual simulation terminal, or generating a simulation image group based on the simulation image through a file monitoring service.

[0009] According to some embodiments of the present application, processing a simulation image group through a simulation processing end to obtain data information of the simulation image group includes: parsing the simulation image group through the simulation processing end to obtain image information of the simulation image group; converting the simulation image group into a byte array format through the simulation processing end; converting the simulation image group in the byte array format into a preset string image through the simulation processing end.

[0010] According to some embodiments of the present application, the preset method is a sampling method with increased frequency.

[0011] According to another aspect of the present application, the present application provides a multi-channel video stream export system based on multi-agent visual simulation, the export system includes an image processing module, a communication connection module, a push stream processing module and a pull stream processing module. The image processing module generates a corresponding simulation image group according to the simulation image corresponding to each agent exported by the visual simulation end based on the preset export frequency, processes the simulation image group through the simulation processing end to obtain data information of the simulation image group, the data information includes image information and preset string images, and stores the data information in a preset database through the simulation processing end; the communication connection module establishes a communication connection between the push stream end and the preset database, so that the push stream end obtains the preset string image from the data information; the push stream processing module decodes the preset string image into image byte stream data through the push stream end, pushes the image byte stream data to the message queue of the push stream end in a preset manner through the push stream end, and asynchronously writes the image byte stream data into a preset cache area through the push stream end, so as to push the image byte stream data to the preset push stream center; the pull stream processing module pulls the video stream corresponding to each agent from the preset push stream center through the pull stream end.

[0012] According to some embodiments of the present application, the image processing module generates a simulation image group based on the simulation image through the visual simulation terminal; or the image processing module generates a simulation image group based on the simulation image through the file monitoring service.

[0013] According to some embodiments of the present application, the image processing module parses the simulation image group through the simulation processing end to obtain image information of the simulation image group; the image processing module converts the simulation image group into a byte array format through the simulation processing end; the image processing module converts the simulation image group in the byte array format into a preset string image through the simulation processing end.

[0014] According to some embodiments of the present application, the preset method is a sampling method with increased frequency.

[0015] According to another aspect of the present application, the present application further provides an electronic device. The electronic device includes: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors can implement the export method described above.

[0016] According to another aspect of the present application, the present application further provides a non-volatile computer-readable storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, the derivation method described above can be implemented.

[0017] The present application can convert a low-frequency image data stream into a real-time video stream by exporting images of the simulation image group on the visual simulation end, monitoring and parsing the simulation image group through the program of the simulation processing end, and processing through the asynchronous control program on the streaming computer side.

[0018] The method for exporting multiple video streams based on multi-agent visual simulation provided by the present application can prevent the multiple video streams from interfering with each other during the export process. Under the same performance load, the present application can export multiple video streams and realize the export of multiple video streams, thereby providing users with more accurate and comprehensive virtual environment perception capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in 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 only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A schematic diagram showing a flow chart of the export method according to an embodiment of the present application;

[0021] Figure 2 Another schematic diagram showing a flow chart of the export method according to an embodiment of the present application;

[0022] Figure 3 A schematic diagram showing the structure of an export system according to an embodiment of the present application is shown.

[0023] Description of reference numerals:

[0024] Export system 1; image processing module 10; communication connection module 20; push stream processing module 30; pull stream processing module 40. DETAILED DESCRIPTION

[0025] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this application will be comprehensive and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted.

[0026] The described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of these specific details, or other modes, components, materials, devices, etc. may be adopted. In these cases, known structures, methods, devices, implementations, materials or operations will not be shown or described in detail.

[0027] In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0028] The terms "first", "second" and the like in the specification and claims of this application and the above drawings are used to distinguish different objects rather than to describe a specific order.

[0029] The following is a clear and complete description of the technical solution of the present application in conjunction with the drawings 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 those skilled in the art without creative work are within the scope of protection of the present application.

[0030] According to one aspect of the present application, the present application provides a method for exporting multi-channel video streams based on multi-agent visual simulation. Figure 1 A schematic diagram of a flow chart of the export method of an embodiment of the present application is shown. Figure 1 As shown, the export method includes steps S100-S800.

[0031] Exemplarily, the export method may be executed by an export system for multiple video streams based on multi-agent visual simulation that has computing capabilities.

[0032] According to an example embodiment, the export system may include a visual simulation end, a simulation processing end, a streaming end, and a streaming end. Exemplarily, the simulation processing end may be a simulation computer, and the visual simulation end may be visual simulation software disposed on the simulation computer.

[0033] According to an exemplary embodiment, in step S100, the export system generates a corresponding simulation image group according to the simulation image corresponding to each agent exported by the visual simulation terminal based on a preset export frequency.

[0034] For example, the preset export frequency is the image export frequency preset by the visual simulation software. The intelligent agent is a virtual simulation target in the visual simulation environment, and the visual simulation environment may include multiple intelligent agents.

[0035] The visual simulation software can export the simulated image of each intelligent agent in real time according to a preset low-frequency image export frequency (such as 1-25HZ). The low-frequency image export frequency can reduce the pressure of rendering and IO performance when exporting the virtual camera image of each intelligent agent.

[0036] Exemplarily, each agent's simulated image is provided with a corresponding image export name (including agent-related information) and a folder name of a target save location. The formats of the simulated images include, but are not limited to, PNG, JPG and other format images.

[0037] The export system generates a simulation image group from the simulation image corresponding to each intelligent agent.

[0038] Optionally, in step S100, the export system generates a simulation image group based on the simulation image through the visual simulation terminal, or generates a simulation image group based on the simulation image through the file monitoring service.

[0039] For example, when the internal program of the visual simulation software includes an image processing program, the export system directly generates a simulation image group through the visual simulation software; when the internal program of the visual simulation software does not include an image processing program, the export system obtains the simulation image group by reading the image file through the file monitoring service.

[0040] Exemplarily, the export system starts a file monitoring service based on an image processing program through a simulation computer, and reads the latest generated and written simulation image through monitoring.

[0041] In step S200, the export system processes the simulation image group through the simulation processing end to obtain data information of the simulation image group, where the data information includes image information and a preset character string image.

[0042] For example, the image information includes but is not limited to image generation time information and agent related information. The preset string image may be a base64 string type image.

[0043] Figure 2 Another flow chart of the export method of the embodiment of the present application is shown. Figure 2 As shown, step S200 may further include steps S210-S230.

[0044] In step S210, the export system parses the simulation image group through the simulation processing end to obtain image information of the simulation image group.

[0045] In step S220, the export system converts the simulation image group into a byte array format through the simulation processing end.

[0046] In step S230, the export system converts the simulation image group in the byte array format into a preset character string image through the simulation processing end.

[0047] For example, the export system parses the accompanying information of the simulation image based on the image processing program through the simulation computer to obtain the simulation image information (such as the image generation time and agent related information). And the export system converts the simulation image into a byte array format through the simulation computer, and then converts the simulation image in the byte array format into a base64 string image, and compresses the image size.

[0048] In step S300, the export system stores the data information into a preset database through the simulation processing terminal.

[0049] For example, the export system stores image generation time information, agent related information, and base64 string type image light field data into a preset database through a simulation computer.

[0050] Exemplarily, the preset database is set according to user needs. The preset database can be set on a simulation computer or on a streaming end, and this application does not limit it.

[0051] In step S400, the export system establishes a communication connection between the streaming end and the preset database, so that the streaming end obtains the preset character string image from the data information.

[0052] For example, the streaming end obtains the communication information of the preset database and configures the connection service of the preset database according to the communication information, so that the communication connection between the streaming end and the preset database can be realized for data transmission interaction.

[0053] In step S500, the export system decodes the preset character string image into image byte stream data through the streaming end.

[0054] For example, the export system starts the first control service, namely, the low-frame image data stream acquisition task, through the streaming end. The export system obtains the latest preset string image (image of the virtual camera) of each intelligent agent in the preset database through the streaming end, and determines whether the current preset string image has been updated.

[0055] When the current preset string image has not been updated, the export system continuously updates and obtains the preset string image through the streaming end at a preset time frequency; when the current preset string image has been updated and is not empty, the export system decodes the preset string image (i.e., base64 string type image) into image byte stream data through the streaming end.

[0056] In step S600, the export system pushes the image byte stream data to the message queue of the streaming end in a preset manner through the streaming end.

[0057] Optionally, in step S600, the preset method may be a sampling method with an increased frequency.

[0058] For example, the export system starts the second control service, i.e., the message queue creation task, through the push stream end to temporarily store the image message queue. The preset method may be an increased frequency sampling method, and the export system pushes the image byte stream data to the message queue through the push stream end in an increased frequency sampling method.

[0059] It can be understood here that a general low-frequency image stream cannot be directly converted into an RTSP (Real-Time Streaming Protocol) video stream, and the conversion of the low-frequency image stream can be achieved through a high-frequency sampling method.

[0060] In step S700, the export system asynchronously writes the image byte stream data into a preset buffer area through the streaming end, so as to stream the image byte stream to a preset streaming center.

[0061] For example, the export system starts the third control service, namely the streaming task, through the streaming end. The export system establishes a streaming sub-service (such as RTSP) through the streaming end and creates a ffmpeg (FastForward Moving Picture Experts Group, an open source computer program) process service.

[0062] The export system obtains the image byte stream data from the message queue on the push end, writes the image byte stream data to the stdin buffer (standard input buffer) through asynchronous writing, and continuously updates the standard input byte stream of the stdin buffer to generate the pushed video stream. The export system pushes the video stream to the RTSP push center through the push service support based on ffmpeg on the push end.

[0063] In step S800, the export system pulls the video stream corresponding to each intelligent agent from the preset streaming center through the streaming end.

[0064] For example, the export system subscribes to the video stream corresponding to each of the multiple agents in the RTSP streaming center through the streaming end based on the perception algorithm or the client through the RTSP URL.

[0065] According to the example embodiment, the first control service, the second control service and the third control service are asynchronous coroutine sub-services, and the three control services can be run separately at the same time. Such a setting can enable the three control services to run independently without blocking each other.

[0066] Through the above embodiments, the present application can convert a low-frequency image data stream into a real-time video stream by exporting the images of the simulation image group of the visual simulation end, monitoring and parsing the simulation image group through the program of the simulation processing end, and processing the asynchronous control program on the streaming computer side.

[0067] The method for exporting multiple video streams based on multi-agent visual simulation provided by the present application can prevent the multiple video streams from interfering with each other during the export process. Under the same performance load, the present application can export multiple video streams and realize the export of multiple video streams, thereby providing users with more accurate and comprehensive virtual environment perception capabilities.

[0068] According to another aspect of the present application, the present application provides a system for exporting multiple video streams based on multi-agent visual simulation. Figure 3 A schematic diagram showing the structure of an export system according to an embodiment of the present application is shown.

[0069] According to an example embodiment, Figure 3 As shown, the export system 1 includes an image processing module 10 , a communication connection module 20 , a push stream processing module 30 and a pull stream processing module 40 .

[0070] According to an exemplary embodiment, the export system 1 may include a visual simulation end, a simulation processing end, a streaming end, and a streaming end. Exemplarily, the simulation processing end may be a simulation computer, and the visual simulation end may be visual simulation software disposed on the simulation computer.

[0071] According to an exemplary embodiment, in step S100 , the image processing module 10 generates a corresponding simulation image group according to the simulation image corresponding to each agent derived by the vision simulation terminal based on a preset derivation frequency.

[0072] For example, the preset export frequency is the image export frequency preset by the visual simulation software. The intelligent agent is a virtual simulation target in the visual simulation environment, and the visual simulation environment may include multiple intelligent agents.

[0073] The visual simulation software can export the simulated image of each intelligent agent in real time according to a preset low-frequency image export frequency (such as 1-25HZ). The low-frequency image export frequency can reduce the pressure of rendering and IO performance when exporting the virtual camera image of each intelligent agent.

[0074] Exemplarily, each agent's simulated image is provided with a corresponding image export name (including agent-related information) and a folder name of a target save location. The formats of the simulated images include, but are not limited to, PNG, JPG and other format images.

[0075] Optionally, the image processing module 10 generates a simulation image group based on the simulation image through a vision simulation terminal, or generates a simulation image group based on the simulation image through a file monitoring service.

[0076] For example, when the internal program of the visual simulation software includes an image processing program, the image processing module 10 directly generates a simulation image group through the visual simulation software; when the internal program of the visual simulation software does not include an image processing program, the image processing module 10 obtains the simulation image group by reading the image file through the file monitoring service.

[0077] Exemplarily, the image processing module 10 starts the file monitoring service based on the image processing program through the simulation computer, and reads the latest generated and written simulation image through monitoring.

[0078] According to an exemplary embodiment, the image processing module 10 processes the simulation image group through the simulation processing end to obtain data information of the simulation image group, where the data information includes image information and a preset character string image.

[0079] For example, the image information includes but is not limited to image generation time information and agent related information. The preset string image may be a base64 string type image.

[0080] Optionally, the image processing module 10 analyzes the simulation image group through the simulation processing end to obtain image information of the simulation image group.

[0081] The image processing module 10 converts the simulation image group into a byte array format through the simulation processing end.

[0082] The image processing module 10 converts the simulation image group in the byte array format into a preset character string image through the simulation processing end.

[0083] For example, the image processing module 10 parses the accompanying information of the simulation image based on the image processing program through the simulation computer to obtain the simulation image information (such as the image generation time and agent related information). The image processing module 10 converts the simulation image into a byte array format through the simulation computer, and then converts the simulation image in the byte array format into a base64 string image, and compresses the image size.

[0084] According to an exemplary embodiment, the image processing module 10 stores the data information into a preset database through a simulation processing terminal.

[0085] For example, the image processing module 10 stores the image generation time information, agent related information and base64 character string type image field data into a preset database through a simulation computer.

[0086] Exemplarily, the preset database is set according to user needs. The preset database can be set on a simulation computer or on a streaming end, and this application does not limit it.

[0087] According to an exemplary embodiment, the communication connection module 20 establishes a communication connection between the streaming end and a preset database, so that the streaming end obtains a preset character string image from the data information.

[0088] For example, the streaming end obtains the communication information of the preset database and configures the connection service of the preset database according to the communication information, so that the communication connection between the streaming end and the preset database can be realized for data transmission interaction.

[0089] According to an exemplary embodiment, the streaming processing module 30 decodes the preset character string image into image byte stream data through the streaming end.

[0090] For example, the streaming processing module 30 starts the first control service, namely, the low-frame image data stream acquisition task, through the streaming end. The streaming processing module 30 obtains the latest preset string image (image of the virtual camera) of each intelligent agent in the preset database through the streaming end, and determines whether the current preset string image has been updated.

[0091] When the current preset string image has not been updated, the streaming processing module 30 continuously updates and obtains the preset string image through the streaming end at a preset time frequency; when the current preset string image has been updated and is not empty, the streaming processing module 30 decodes the preset string image (i.e., base64 string type image) into image byte stream data through the streaming end.

[0092] According to an exemplary embodiment, the streaming processing module 30 pushes the image byte stream data to the message queue of the streaming end in a preset manner through the streaming end.

[0093] Optionally, the preset method may be a sampling method with an increased frequency.

[0094] For example, the push stream processing module 30 starts the second control service, i.e., the message queue creation task, through the push stream end, for temporarily storing the image message queue. The preset method may be an increased frequency sampling method, and the push stream processing module 30 pushes the image byte stream data to the message queue through the push stream end in an increased frequency sampling method.

[0095] It can be understood here that a general low-frequency image stream cannot be directly converted into an RTSP (Real-Time Streaming Protocol) video stream, and the conversion of the low-frequency image stream can be achieved through a high-frequency sampling method.

[0096] According to an exemplary embodiment, the streaming processing module 30 asynchronously writes the image byte stream data into a preset buffer area through the streaming end, so as to stream the image byte stream to a preset streaming center.

[0097] For example, the streaming processing module 30 starts the third control service, namely the streaming task, through the streaming end. The export system establishes a streaming sub-service (such as RTSP) through the streaming end and creates a ffmpeg (Fast Forward Moving Picture Experts Group, an open source computer program) process service.

[0098] The push stream processing module 30 obtains the image byte stream data in the message queue through the push stream end, writes the image byte stream data into the stdin buffer (standard input buffer) by asynchronous writing, and continuously updates the standard input byte stream of the stdin buffer to generate the pushed video stream. The push stream processing module 30 pushes the video stream to the RTSP push stream center through the push stream service support based on ffmpeg of the push stream end.

[0099] According to an exemplary embodiment, the stream pulling processing module 40 pulls the video stream corresponding to each agent from a preset stream pushing center through a stream pulling end.

[0100] For example, the stream pulling processing module 40 subscribes to the video stream corresponding to each of the multiple agents in the RTSP streaming center through the stream pulling end based on the perception algorithm or the client through the RTSP URL.

[0101] According to the example embodiment, the first control service, the second control service and the third control service are asynchronous coroutine sub-services, and the three control services can be run separately at the same time. Such a setting can enable the three control services to run independently without blocking each other.

[0102] Through the above embodiments, the present application can convert a low-frequency image data stream into a real-time video stream by exporting the images of the simulation image group of the visual simulation end, monitoring and parsing the simulation image group through the program of the simulation processing end, and processing the asynchronous control program on the streaming computer side.

[0103] The method for exporting multiple video streams based on multi-agent visual simulation provided by the present application can prevent the multiple video streams from interfering with each other during the export process. Under the same performance load, the present application can export multiple video streams and realize the export of multiple video streams, thereby providing users with more accurate and comprehensive virtual environment perception capabilities.

[0104] According to another aspect of the present application, the present application further provides an electronic device. The electronic device includes: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors can implement the export method described above.

[0105] According to another aspect of the present application, the present application further provides a non-volatile computer-readable storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, the derivation method described above can be implemented.

[0106] Finally, it should be noted that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Although the present application is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions of the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for deriving multi-channel video streams based on multi-agent visual simulation, characterized in that: include: Generate a corresponding simulation image group according to the simulation image corresponding to each intelligent agent derived by the visual simulation terminal based on the preset export frequency; Processing the simulation image group through a simulation processing end to obtain data information of the simulation image group, wherein the data information includes image information and a preset character string image; The data information is stored in a preset database through a simulation processing terminal; Establishing a communication connection between the streaming end and the preset database so that the streaming end obtains the preset character string image from the data information; Decoding the preset character string image into image byte stream data through the streaming end; Pushing the image byte stream data to the message queue of the streaming end in a preset manner through the streaming end; Asynchronously writing the image byte stream data into a preset buffer area through a streaming end, so as to stream the image byte stream data to a preset streaming center; The video stream corresponding to each intelligent agent is pulled from the preset streaming center through the streaming end.

2. The derivation method according to claim 1, characterized in that: The generating of a corresponding simulation image group according to the simulation image corresponding to each intelligent agent derived by the visual simulation terminal based on the preset derivation frequency comprises: The simulation image group is generated based on the simulation image by the vision simulation terminal, or the simulation image group is generated based on the simulation image by a file monitoring service.

3. The derivation method according to claim 1, characterized in that: The step of processing the simulation image group through the simulation processing end to obtain data information of the simulation image group includes: parsing the simulation image group through the simulation processing end to obtain the image information of the simulation image group; Converting the simulation image group into a byte array format through the simulation processing end; The simulation processing end converts the simulation image group in the byte array format into the preset character string image.

4. The derivation method according to claim 1, characterized in that: The preset method is a sampling method with increased frequency.

5. A multi-channel video stream export system based on multi-agent visual simulation, characterized in that: include: An image processing module generates a corresponding simulation image group according to the simulation image corresponding to each agent derived by the visual simulation end based on the preset export frequency, processes the simulation image group through the simulation processing end to obtain data information of the simulation image group, the data information includes image information and a preset character string image, and stores the data information in a preset database through the simulation processing end; A communication connection module is used to establish a communication connection between the streaming end and the preset database, so that the streaming end can obtain the preset character string image from the data information; A streaming processing module, which decodes the preset character string image into image byte stream data through the streaming end, pushes the image byte stream data to the message queue of the streaming end in a preset manner through the streaming end, and asynchronously writes the image byte stream data into a preset buffer area through the streaming end, so as to stream the image byte stream data to a preset streaming center; The stream pulling processing module pulls the video stream corresponding to each intelligent agent from the preset stream pushing center through the stream pulling end.

6. The export system according to claim 5, characterized in that: The image processing module generates the simulation image group based on the simulation image through the visual simulation terminal; or The image processing module generates the simulation image group based on the simulation image through a file monitoring service.

7. The export system according to claim 5, characterized in that: The image processing module analyzes the simulation image group through the simulation processing end to obtain the image information of the simulation image group; The image processing module converts the simulation image group into a byte array format through the simulation processing end; The image processing module converts the simulation image group in the byte array format into the preset character string image through the simulation processing end.

8. The export system according to claim 5, characterized in that: The preset method is a sampling method with increased frequency.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the export method as described in any one of claims 1 to 4.

10. A non-volatile computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the derivation method according to any one of claims 1 to 4 is implemented.

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