Method for obtaining USB microphone and camera device through electronic whiteboard screen projection program

Abstract

The invention relates to a method for acquiring a USB microphone and a camera device through an electronic whiteboard screen projection program, and belongs to the technical field of electronic whiteboard screen projection. The method comprises the following steps: obtaining original electronic whiteboard video data, obtaining electronic whiteboard equipment information by a macOS computer end through an mDNS electronic whiteboard model, obtaining electronic whiteboard selection equipment by establishing an equipment list data transmission model according to the electronic whiteboard equipment information, and sending the electronic whiteboard selection equipment to the macOS computer end; electronic whiteboard audio data and electronic whiteboard video data are obtained through an audio and video data channel model according to the electronic whiteboard selection equipment, and are transmitted to a macOS virtual sound card input end through an audio compression transmission model according to the electronic whiteboard audio data; and transmitting the electronic whiteboard video data to the input end of a macOS virtual camera through a video compression transmission model according to the electronic whiteboard video data. Safe, low-delay and high-quality data transmission of the USB microphone and the camera equipment between the electronic whiteboard and the macOS is realized.

Description

Technical Field

[0001] The invention belongs to the field of electronic whiteboard projection, and in particular relates to a method for an electronic whiteboard projection program to obtain USB microphone and camera devices. Background Art

[0002] With the popularity of modern education and conference systems, screen projection software on electronic whiteboards has been widely used as an interactive tool. Due to the different operating systems used on electronic whiteboards, it is difficult to collect data from USB microphones and cameras. At the same time, uploading the collected video data and audio data to the computer requires a large amount of memory, which affects the processing and use of the computer.

[0003] Traditional acquisition methods usually use USB microphones and cameras to connect directly to computers to collect audio and video data in real time. However, due to the different operating systems used by electronic whiteboards and computers, the drivers of USB microphones and cameras cannot run seamlessly on all operating systems, which leads to instability in the data acquisition process. At the same time, traditional methods usually do not compress the collected audio and video data, resulting in a large data volume, which not only increases the bandwidth requirements for data transmission, but also slows down the transmission speed. Traditional video compression technology pursues high compression rates, which affects the quality of the video. Therefore, none of the above methods can well collect USB microphone and camera data on electronic whiteboards, affecting the overall performance of the system. Summary of the invention

[0004] In order to solve the above problems existing in the prior art, the present invention provides a method for an electronic whiteboard projection program to obtain USB microphone and camera devices.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method for an electronic whiteboard projection program to obtain USB microphone and camera devices, comprising:

[0007] Obtain the original electronic whiteboard video data, and the macOS computer obtains the electronic whiteboard device information through the mDNS electronic whiteboard model, wherein the electronic whiteboard device information includes the electronic whiteboard device ID and the electronic whiteboard device IP address;

[0008] According to the electronic whiteboard device information, an electronic whiteboard selection device is obtained by establishing a device list data transmission model;

[0009] According to the electronic whiteboard selection device, the electronic whiteboard audio data and the electronic whiteboard video data are obtained through the audio and video data channel model;

[0010] According to the electronic whiteboard audio data, the audio data is transmitted to the input end of the macOS virtual sound card through the audio compression transmission model;

[0011] The electronic whiteboard video data is transmitted to the macOS virtual camera input terminal through a video compression transmission model.

[0012] Preferably, the mDNS electronic whiteboard model specifically includes a macOS computer broadcasting a device in a local area network through an mDNS protocol multicast method to obtain a local area network device list, wherein the local area network device list carries a device quantity tag;

[0013] Determine whether the device quantity tag is 0, if yes, check the network connection, electronic whiteboard device status, and macOS status;

[0014] If not, the electronic whiteboard device information is obtained by parsing the LAN device list.

[0015] Preferably, obtaining the electronic whiteboard selection device by establishing a device list data transmission model according to the electronic whiteboard device information comprises:

[0016] Establishing a data transmission connection channel through data verification based on the electronic whiteboard device information and the local area network device information, wherein the local area network device information is the information of the electronic whiteboard in the local area network;

[0017] Obtaining a data transmission encrypted connection channel through the TLS encryption protocol according to the data transmission connection channel;

[0018] Obtaining a USB peripheral list data packet by sending a device query request according to the data transmission encryption connection channel;

[0019] The electronic whiteboard selection device is obtained by parsing the USB peripheral list data packet.

[0020] Preferably, the data verification judgment includes:

[0021] Determine whether the electronic whiteboard device information is equal to the local area network device information, if yes, then establish the data transmission encrypted connection channel;

[0022] If not, reconnect macOS and the electronic whiteboard.

[0023] Preferably, obtaining the electronic whiteboard audio data and the electronic whiteboard video data through the audio and video data channel model according to the electronic whiteboard selection device includes:

[0024] Sending a data connection request to the macOS according to the electronic whiteboard selection device, wherein the data connection request carries a connection success tag;

[0025] Determine the establishment of an audio and video data channel by sending a data connection request according to the connection success tag;

[0026] According to the audio and video data channel, an audio and video data enhancement channel is obtained through the WebRTC protocol, wherein the WebRTC protocol is a protocol that ensures low latency and high quality of data transmission;

[0027] The electronic whiteboard audio data and the electronic whiteboard video data are obtained by receiving according to the audio and video data enhancement channel.

[0028] Preferably, the determination of sending a data connection request includes:

[0029] Determine whether the connection success tag is 1, if yes, then establish the audio and video data channel;

[0030] If not, reconnect macOS and the electronic whiteboard.

[0031] Preferably, the transmitting the electronic whiteboard audio data to the macOS virtual sound card input terminal through the audio compression transmission model includes:

[0032] According to the electronic whiteboard audio data, AAC encoding is performed to obtain electronic whiteboard AAC audio data, wherein the electronic whiteboard AAC audio data carries an audio data quantity tag;

[0033] According to the electronic whiteboard AAC audio data, the audio data quantity label is used to determine whether the audio data is uploaded to the macOS virtual sound card input terminal.

[0034] Preferably, the audio data quantity label determination includes:

[0035] Determine whether the audio data quantity tag is 0, if yes, re-encode the electronic whiteboard audio data by AAC;

[0036] If not, the electronic whiteboard AAC audio data is transmitted to the macOS virtual sound card input terminal through the socket.

[0037] Preferably, the transmitting the electronic whiteboard video data to the macOS virtual camera input terminal through a video compression transmission model comprises:

[0038] Obtain electronic whiteboard compressed video data by using a deep learning autoencoder video compression method according to the electronic whiteboard video data;

[0039] The electronic whiteboard compressed video data is transmitted to the macOS virtual camera input terminal through the socket.

[0040] Preferably, the step of obtaining electronic whiteboard compressed video data by using a deep learning autoencoder video compression method according to the electronic whiteboard video data comprises:

[0041] Obtaining an original electronic whiteboard video data feature map by convolution according to the original electronic whiteboard video data;

[0042] The original electronic whiteboard video data feature map is subjected to maximum value pooling to obtain an original electronic whiteboard video data pooling feature map;

[0043] The pooled feature map of the original electronic whiteboard video data is passed through a fully connected layer to obtain the original electronic whiteboard compressed video data;

[0044] Obtain original electronic whiteboard deep learning video data through an electronic whiteboard video data deconvolution neural network according to the original electronic whiteboard deep learning video data;

[0045] Obtaining an original electronic whiteboard video data loss value through an original electronic whiteboard perception loss function according to the original electronic whiteboard deep learning video data and the original electronic whiteboard video data;

[0046] According to the loss value of the original electronic whiteboard video data, the trained electronic whiteboard video data convolutional neural network is obtained by updating the parameters of the original electronic whiteboard video data;

[0047] Obtaining electronic whiteboard compressed video data through the trained electronic whiteboard video data convolutional neural network according to the electronic whiteboard video data, wherein the electronic whiteboard compressed video data carries a video data quantity label;

[0048] The electronic whiteboard compressed video data is uploaded to the macOS virtual camera input terminal through the video data quantity tag.

[0049] Preferably, the calculation formula of the original electronic whiteboard perception loss function is:

[0050]

[0051] Among them, L perceptual is the loss value of the original electronic whiteboard video data, x is the original electronic whiteboard video data, is the original electronic whiteboard deep learning video data, l represents the lth layer of the convolutional neural network, Φ l represents the feature map at the lth layer extracted from the convolutional neural network, α is the weight parameter, and β is the weight parameter.

[0052] Preferably, the expression for updating the original electronic whiteboard video data parameters is:

[0053]

[0054] Among them, θ eis the convolutional neural network parameter of the electronic whiteboard video data, θ d is the deconvolution neural network parameter of the electronic whiteboard video data, argmin means taking the original electronic whiteboard video data parameter update function with the minimum value of θ e and θ d , N represents the number of original electronic whiteboard video data, x (i) represents the i-th original electronic whiteboard video data, g represents the electronic whiteboard video data deconvolution neural network, f represents the electronic whiteboard video data convolution neural network, represents the updated θ by the original electronic whiteboard video data parameters e , represents the updated θ by the original electronic whiteboard video data parameters d .

[0055] Preferably, the video data quantity label determination includes:

[0056] Determine whether the video data quantity label is 0, if yes, re-pass the trained electronic whiteboard video data convolutional neural network on the electronic whiteboard video data;

[0057] If not, the electronic whiteboard compressed video data is transmitted to the macOS virtual camera input terminal through the socket.

[0058] An electronic whiteboard projection program acquires a USB microphone and a camera device system based on a method for acquiring USB microphone and camera devices by an electronic whiteboard projection program, comprising an information acquisition module, a connection establishment module, a data acquisition module, an audio transmission module, and a video transmission module, including:

[0059] The information acquisition module is used to obtain the original electronic whiteboard video data. The macOS computer terminal obtains the electronic whiteboard device information through the mDNS electronic whiteboard model. The electronic whiteboard device information includes the electronic whiteboard device ID and the electronic whiteboard device IP address;

[0060] The connection establishment module is used to obtain the electronic whiteboard selection device by establishing a device list data transmission model according to the electronic whiteboard device information;

[0061] The data acquisition module is used to obtain the electronic whiteboard audio data and the electronic whiteboard video data through the audio and video data channel model according to the electronic whiteboard selection device;

[0062] The audio transmission module is used to transmit the electronic whiteboard audio data to the macOS virtual sound card input terminal through an audio compression transmission model;

[0063] The video transmission module is used to transmit the electronic whiteboard video data to the macOS virtual camera input terminal through a video compression transmission model.

[0064] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for obtaining a USB microphone and a camera device by the electronic whiteboard projection program is implemented.

[0065] A storage medium containing computer executable instructions, which, when executed by a computer processor, are used to execute the above-mentioned electronic whiteboard projection program to obtain a USB microphone and camera device method.

[0066] The beneficial effects of the present invention are:

[0067] (1) The stability and accuracy of data transmission are ensured through the data verification judgment, the sending data connection request judgment, the audio data quantity label judgment, and the video data quantity label judgment;

[0068] (2) The data transmission connection channel is encrypted through the TLS encryption protocol to prevent unauthorized access, tampering, and leakage of data during transmission, thereby ensuring the security and integrity of data during transmission;

[0069] (3) Through the point-to-point connection of the WebRTC protocol, real-time, low-latency audio and video transmission is achieved. At the same time, SRTP and DTLS encryption are used to ensure the security of audio and video data transmission, and to achieve secure data transmission between different operating systems;

[0070] (4) The electronic whiteboard video data is compressed by a deep learning autoencoder video compression method, thereby accelerating the transmission efficiency of the electronic whiteboard video data and ensuring the quality of the electronic whiteboard video data. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0072] Figure 1 The invention discloses a method for an electronic whiteboard screen projection program to obtain USB microphone and camera devices. DETAILED DESCRIPTION

[0073] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0074] See also Figure 1, a method for an electronic whiteboard projection program to obtain USB microphone and camera devices, comprising:

[0075] S1: Obtaining the original electronic whiteboard video data, the macOS computer obtains the electronic whiteboard device information through the mDNS electronic whiteboard model, and the electronic whiteboard device information includes the electronic whiteboard device ID and the electronic whiteboard device IP address;

[0076] S2: obtaining an electronic whiteboard selection device by establishing a device list data transmission model according to the electronic whiteboard device information;

[0077] S3: According to the electronic whiteboard selection device, obtain the electronic whiteboard audio data and the electronic whiteboard video data through the audio and video data channel model;

[0078] S4: Transmitting the electronic whiteboard audio data to the macOS virtual sound card input terminal through an audio compression transmission model;

[0079] S5: Transmitting the electronic whiteboard video data to the macOS virtual camera input terminal through a video compression transmission model.

[0080] In step S1, the mDNS electronic whiteboard model specifically includes the following steps:

[0081] The macOS computer broadcasts devices in the LAN through the mDNS protocol multicast mode to obtain a LAN device list, wherein the LAN device list carries a device quantity label, and the mDNS is a protocol for automatically discovering devices and services in the LAN;

[0082] Determine whether the device quantity tag is 0. If it is 0, check the network connection, electronic whiteboard device status, and macOS status;

[0083] If it is not 0, the electronic whiteboard device information is obtained by parsing according to the LAN device list.

[0084] In step S2, obtaining the electronic whiteboard selection device ID by establishing a device list data transmission model according to the electronic whiteboard device information specifically includes the following steps:

[0085] S201: Establishing a data transmission connection channel through data verification based on the electronic whiteboard device information and the local area network device information, wherein the local area network device information includes the information of the electronic whiteboard in the local area network;

[0086] S202: obtaining a data transmission encrypted connection channel according to the data transmission connection channel through the TLS encryption protocol, wherein the TLS encryption protocol is a protocol for ensuring confidentiality, integrity and identity authentication of data during transmission;

[0087] S203: Obtaining a USB peripheral list data packet by sending a device query request according to the data transmission encryption connection channel;

[0088] S204: Obtain the electronic whiteboard selection device by parsing the USB peripheral list data packet.

[0089] In this embodiment, the specific steps of the data verification judgment are:

[0090] Determine whether the electronic whiteboard device information is equal to the local area network device information, and if they are equal, establish the data transmission encryption connection channel;

[0091] If they are not equal, reconnect macOS and the electronic whiteboard.

[0092] In step S3, the specific steps of obtaining the electronic whiteboard audio data and the electronic whiteboard video data through the audio and video data channel model according to the electronic whiteboard selection device are as follows:

[0093] S301: Sending a data connection request to the macOS according to the electronic whiteboard selection device, wherein the data connection request carries a connection success tag;

[0094] S302: Determine the establishment of an audio and video data channel by sending a data connection request according to the connection success tag;

[0095] The specific steps of sending the data connection request judgment are:

[0096] Determine the connection success tag, and if the connection success tag is 1, establish the audio and video data channel;

[0097] If the connection success tag is 0, reconnect macOS and the electronic whiteboard;

[0098] S303: obtaining an audio and video data enhancement channel according to the audio and video data channel through the WebRTC protocol, where the WebRTC protocol is a protocol that ensures low latency and high quality of data transmission;

[0099] S304: Obtain the electronic whiteboard audio data and the electronic whiteboard video data by receiving according to the audio and video data enhancement channel.

[0100] It should be noted that in step S203, the sending device query request is an instruction issued by the macOS; in step S302, the sending data connection request is also an instruction issued by the macOS; in step S304, the electronic whiteboard audio data is PCM format data, and the electronic whiteboard video data is in YUV420 format.

[0101] In step S4, the specific steps of transmitting the electronic whiteboard audio data to the macOS virtual sound card input terminal through the audio compression transmission model are as follows:

[0102] S401: obtaining electronic whiteboard AAC audio data through AAC encoding according to the electronic whiteboard audio data, wherein the electronic whiteboard AAC audio data carries an audio data quantity tag;

[0103] S402: Determine whether the audio data quantity tag is 0. If it is 0, re-encode the electronic whiteboard audio data in AAC;

[0104] If it is not 0, the electronic whiteboard AAC audio data is transmitted to the macOS virtual sound card input terminal through the socket.

[0105] In step S5, the electronic whiteboard video data is transmitted to the macOS virtual camera input terminal through the video compression transmission model by the following steps:

[0106] S501: Obtaining electronic whiteboard compressed video data by using a deep learning autoencoder video compression method according to the electronic whiteboard video data;

[0107] S502: Transmitting the compressed video data of the electronic whiteboard to the input terminal of the macOS virtual camera through a socket.

[0108] In this embodiment, the deep learning autoencoder video compression method is specifically as follows:

[0109] S501-1: The deep learning autoencoder video compression method includes a trained electronic whiteboard video data convolutional neural network, wherein the trained electronic whiteboard video data convolutional neural network requires training of an electronic whiteboard video data convolutional neural network and an electronic whiteboard video data deconvolutional neural network;

[0110] S501-2: Obtaining an original electronic whiteboard video data feature map by convolution according to the original electronic whiteboard video data;

[0111] S501-3: Perform maximum value pooling on the original electronic whiteboard video data feature map to obtain an original electronic whiteboard video data pooling feature map;

[0112] S501-4: The original electronic whiteboard video data pooling feature map is passed through a fully connected layer to obtain original electronic whiteboard compressed video data;

[0113] S501-5: Obtain original electronic whiteboard deep learning video data through an electronic whiteboard video data deconvolution neural network according to the original electronic whiteboard deep learning video data;

[0114] S501-6: Obtaining the original electronic whiteboard video data loss value through the original electronic whiteboard perception loss function according to the original electronic whiteboard deep learning video data and the original electronic whiteboard video data. The calculation formula of the original electronic whiteboard perception loss function is:

[0115]

[0116] Among them, L perceptual is the loss value of the original electronic whiteboard video data, x is the original electronic whiteboard video data, is the original electronic whiteboard deep learning video data, l represents the lth layer of the convolutional neural network, Φ l represents the feature map at layer l extracted from the convolutional neural network, α is a weight parameter, and β is a weight parameter;

[0117] S501-7: Obtain a trained electronic whiteboard video data convolutional neural network by updating the original electronic whiteboard video data parameters according to the original electronic whiteboard video data loss value.

[0118] The expression for updating the original electronic whiteboard video data parameters is:

[0119]

[0120] Among them, θ e is the convolutional neural network parameter of the electronic whiteboard video data, θ d is the deconvolution neural network parameter of the electronic whiteboard video data, argmin means taking the original electronic whiteboard video data parameter update function with the minimum value of θ e and θ d , N represents the number of original electronic whiteboard video data, x (i) represents the i-th original electronic whiteboard video data, g represents the electronic whiteboard video data deconvolution neural network, f represents the electronic whiteboard video data convolution neural network, represents the updated θ by the original electronic whiteboard video data parameters e , represents the updated θ by the original electronic whiteboard video data parameters d ;

[0121] S501-8: Obtaining electronic whiteboard compressed video data through the trained electronic whiteboard video data convolutional neural network according to the electronic whiteboard video data, wherein the electronic whiteboard compressed video data carries a video data quantity label;

[0122] S501-9: Determine whether the video data quantity label is 0. If it is 0, re-pass the trained electronic whiteboard video data convolutional neural network on the electronic whiteboard video data;

[0123] If it is not 0, the electronic whiteboard compressed video data is transmitted to the macOS virtual camera input terminal through the socket.

[0124] An electronic whiteboard projection program acquires a USB microphone and a camera device system based on a method for acquiring USB microphone and camera devices by an electronic whiteboard projection program, comprising an information acquisition module, a connection establishment module, a data acquisition module, an audio transmission module, and a video transmission module, including:

[0125] The information acquisition module is used to obtain the original electronic whiteboard video data. The macOS computer terminal obtains the electronic whiteboard device information through the mDNS electronic whiteboard model. The electronic whiteboard device information includes the electronic whiteboard device ID and the electronic whiteboard device IP address;

[0126] The connection establishment module is used to obtain the electronic whiteboard selection device by establishing a device list data transmission model according to the electronic whiteboard device information;

[0127] The data acquisition module is used to obtain the electronic whiteboard audio data and the electronic whiteboard video data through the audio and video data channel model according to the electronic whiteboard selection device;

[0128] The audio transmission module is used to transmit the electronic whiteboard audio data to the macOS virtual sound card input terminal through an audio compression transmission model;

[0129] The video transmission module is used to transmit the electronic whiteboard video data to the macOS virtual camera input terminal through a video compression transmission model.

[0130] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0131] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0132] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0133] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for an electronic whiteboard projection program to obtain USB microphone and camera devices, characterized in that: The following steps are involved: Obtain the original electronic whiteboard video data, and the macOS computer obtains the electronic whiteboard device information through the mDNS electronic whiteboard model, wherein the electronic whiteboard device information includes the electronic whiteboard device ID and the electronic whiteboard device IP address; According to the electronic whiteboard device information, an electronic whiteboard selection device is obtained by establishing a device list data transmission model; According to the electronic whiteboard selection device, the electronic whiteboard audio data and the electronic whiteboard video data are obtained through the audio and video data channel model; According to the electronic whiteboard audio data, the audio data is transmitted to the input end of the macOS virtual sound card through the audio compression transmission model; The electronic whiteboard video data is transmitted to the macOS virtual camera input terminal through a video compression transmission model.

2. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 1, characterized in that: The mDNS electronic whiteboard model specifically includes a macOS computer broadcasting a device in a local area network through the mDNS protocol multicast method to obtain a local area network device list, wherein the local area network device list carries a device quantity tag; Determine whether the device quantity tag is 0, if yes, check the network connection, electronic whiteboard device status, and macOS status; If not, the electronic whiteboard device information is obtained by parsing the LAN device list.

3. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 1, characterized in that: The step of obtaining the electronic whiteboard selection device by establishing a device list data transmission model according to the electronic whiteboard device information comprises: Establishing a data transmission connection channel through data verification based on the electronic whiteboard device information and the local area network device information, wherein the local area network device information is the information of the electronic whiteboard in the local area network; Obtaining a data transmission encrypted connection channel through the TLS encryption protocol according to the data transmission connection channel; Obtaining a USB peripheral list data packet by sending a device query request according to the data transmission encryption connection channel; The electronic whiteboard selection device is obtained by parsing the USB peripheral list data packet.

4. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 3, characterized in that: The data verification judgment includes: Determine whether the electronic whiteboard device information is equal to the local area network device information, if yes, then establish the data transmission encrypted connection channel; If not, reconnect macOS and the electronic whiteboard.

5. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 1, characterized in that: The step of obtaining the electronic whiteboard audio data and the electronic whiteboard video data through the audio and video data channel model according to the electronic whiteboard selection device comprises: Sending a data connection request to the macOS according to the electronic whiteboard selection device, wherein the data connection request carries a connection success tag; Determine the establishment of an audio and video data channel by sending a data connection request according to the connection success tag; According to the audio and video data channel, an audio and video data enhancement channel is obtained through the WebRTC protocol, wherein the WebRTC protocol is a protocol that ensures low latency and high quality of data transmission; The electronic whiteboard audio data and the electronic whiteboard video data are obtained by receiving according to the audio and video data enhancement channel.

6. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 5, characterized in that: The determination of sending a data connection request comprises: Determine whether the connection success tag is 1, if yes, then establish the audio and video data channel; If not, reconnect macOS and the electronic whiteboard.

7. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 1, characterized in that: The method of transmitting the electronic whiteboard audio data to the macOS virtual sound card input terminal through the audio compression transmission model includes: According to the electronic whiteboard audio data, AAC encoding is performed to obtain electronic whiteboard AAC audio data, wherein the electronic whiteboard AAC audio data carries an audio data quantity tag; According to the electronic whiteboard AAC audio data, the audio data quantity label is used to determine whether the audio data is uploaded to the macOS virtual sound card input terminal.

8. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 7, characterized in that: The audio data quantity label determination includes: Determine whether the audio data quantity tag is 0, if yes, re-encode the electronic whiteboard audio data by AAC; If not, the electronic whiteboard AAC audio data is transmitted to the macOS virtual sound card input terminal through the socket.

9. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 1, characterized in that: The transmitting of the electronic whiteboard video data to the macOS virtual camera input terminal through the video compression transmission model includes: Obtain electronic whiteboard compressed video data by using a deep learning autoencoder video compression method according to the electronic whiteboard video data; The electronic whiteboard compressed video data is transmitted to the macOS virtual camera input terminal through the socket.

10. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 9, characterized in that: The method of obtaining electronic whiteboard compressed video data by using a deep learning autoencoder video compression method according to the electronic whiteboard video data comprises: Obtaining an original electronic whiteboard video data feature map by convolution according to the original electronic whiteboard video data; The original electronic whiteboard video data feature map is subjected to maximum value pooling to obtain an original electronic whiteboard video data pooling feature map; The pooled feature map of the original electronic whiteboard video data is passed through a fully connected layer to obtain the original electronic whiteboard compressed video data; Obtain original electronic whiteboard deep learning video data through an electronic whiteboard video data deconvolution neural network according to the original electronic whiteboard deep learning video data; Obtaining an original electronic whiteboard video data loss value through an original electronic whiteboard perception loss function according to the original electronic whiteboard deep learning video data and the original electronic whiteboard video data; According to the loss value of the original electronic whiteboard video data, the trained electronic whiteboard video data convolutional neural network is obtained by updating the parameters of the original electronic whiteboard video data; Obtaining electronic whiteboard compressed video data through the trained electronic whiteboard video data convolutional neural network according to the electronic whiteboard video data, wherein the electronic whiteboard compressed video data carries a video data quantity label; The electronic whiteboard compressed video data is uploaded to the macOS virtual camera input terminal through the video data quantity tag.

11. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 10, characterized in that: The calculation formula of the original electronic whiteboard perception loss function is: Among them, L perceptual is the loss value of the original electronic whiteboard video data, x is the original electronic whiteboard video data, is the original electronic whiteboard deep learning video data, l represents the lth layer of the convolutional neural network, Φ l represents the feature map at the lth layer extracted from the convolutional neural network, α is the weight parameter, and β is the weight parameter.

12. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 10, characterized in that: The expression for updating the original electronic whiteboard video data parameters is: Among them, θ e is the convolutional neural network parameter of the electronic whiteboard video data, θ d is the deconvolution neural network parameter of the electronic whiteboard video data, argmin means taking the original electronic whiteboard video data parameter update function with the minimum value of θ e and θ d , N represents the number of original electronic whiteboard video data, x (i) represents the i-th original electronic whiteboard video data, g represents the electronic whiteboard video data deconvolution neural network, f represents the electronic whiteboard video data convolution neural network, represents the updated θ by the original electronic whiteboard video data parameters e , represents the updated θ by the original electronic whiteboard video data parameters d .

13. The method for obtaining USB microphone and camera devices by the electronic whiteboard projection program according to claim 10, characterized in that: The video data quantity label determination includes: Determine whether the video data quantity label is 0, if yes, re-pass the trained electronic whiteboard video data convolutional neural network on the electronic whiteboard video data; If not, the electronic whiteboard compressed video data is transmitted to the macOS virtual camera input terminal through the socket.

14. A method for obtaining USB microphone and camera devices by using the electronic whiteboard projection program of claim 1, comprising an information collection module, a connection establishment module, a data acquisition module, an audio transmission module, and a video transmission module, characterized in that: include: The information acquisition module is used to obtain the original electronic whiteboard video data. The macOS computer terminal obtains the electronic whiteboard device information through the mDNS electronic whiteboard model. The electronic whiteboard device information includes the electronic whiteboard device ID and the electronic whiteboard device IP address; The connection establishment module is used to obtain the electronic whiteboard selection device by establishing a device list data transmission model according to the electronic whiteboard device information; The data acquisition module is used to obtain the electronic whiteboard audio data and the electronic whiteboard video data through the audio and video data channel model according to the electronic whiteboard selection device; The audio transmission module is used to transmit the electronic whiteboard audio data to the macOS virtual sound card input terminal through an audio compression transmission model; The video transmission module is used to transmit the electronic whiteboard video data to the macOS virtual camera input terminal through a video compression transmission model.

15. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, it implements the method for obtaining USB microphone and camera devices based on the electronic whiteboard projection program as described in any one of claims 1-14.

16. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions, when executed by a computer processor, are used to execute the method for obtaining USB microphone and camera devices based on an electronic whiteboard projection program as described in any one of claims 1-14.

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