Parameter processing method, device, equipment and storage medium

Abstract

The present invention discloses a parameter processing method, apparatus, device, and storage medium. The method includes: inputting industrial parameters and service level agreement (SLA) indicator parameters; the industrial parameters represent relevant parameters of industrial camera equipment; the SLA indicator parameters represent the detection success rate of images captured by the industrial camera equipment; mapping the input industrial parameters and SLA indicator parameters to obtain network indicators; the network indicators represent the network requirements required to transmit images captured by the industrial camera equipment to a network device; and outputting the network indicators.

Description

Technical Field

[0001] The present invention relates to the field of wireless technology, and in particular to a parameter processing method, apparatus, device and storage medium. Background Art

[0002] With the rapid development of network slicing technology, the service level agreement (SLA) requirement decomposition can be achieved through the Communication Service Management Function (CSMF) entity and the Network Slice Management Function (NSMF) entity in the slicing architecture. The process of SLA requirement decomposition may include: first, inputting the universal slicing template into the CSMF entity; then, the CSMF entity uses the input universal slicing template to decompose the SLA requirement to obtain an end-to-end indicator configuration file, and sends it to the NSMF entity; finally, the NSMF entity decomposes the received end-to-end indicator configuration file to obtain a domain-specific indicator configuration file. However, since the various network indicators in the universal slicing template are manually input, it is impossible to achieve automatic conversion from industrial parameters to network indicators, and it is also impossible to achieve SLA requirement decomposition in industrial machine vision scenarios. Summary of the Invention

[0003] In view of this, embodiments of the present invention are intended to provide a parameter processing method, apparatus, device, and storage medium.

[0004] The technical solution of the embodiment of the present invention is achieved as follows:

[0005] At least one embodiment of the present invention provides a parameter processing method, the method comprising:

[0006] Input industrial parameters and SLA indicator parameters; the industrial parameters represent relevant parameters of the industrial shooting equipment; the SLA indicator parameters represent the detection success rate of the images collected by the industrial shooting equipment;

[0007] Mapping the input industrial parameters and SLA indicator parameters to obtain network indicators; the network indicators represent the network requirements required to transmit images collected by the industrial camera to the network device;

[0008] Outputs the network metrics.

[0009] Furthermore, according to at least one embodiment of the present invention, the industrial parameters include signal source parameters of the industrial camera and processing capability parameters of the industrial camera; and mapping the input industrial parameters and SLA indicator parameters to obtain network indicators includes:

[0010] Quantify the input signal source parameters and SLA indicator parameters to obtain business indicators;

[0011] The service indicator is mapped into a network indicator using the processing capability parameter.

[0012] Furthermore, according to at least one embodiment of the present invention, quantifying the input signal source parameters and SLA indicator parameters to obtain the service indicator includes:

[0013] Quantifying the input source parameters to obtain a first service indicator and a second service indicator; the first service indicator represents the data volume of a single frame image; the second service indicator represents the end-to-end service delay allowed for a single frame image;

[0014] The SLA indicator parameters are quantified to obtain a third service indicator; the third service indicator represents the packet loss rate allowed by the service.

[0015] In addition, according to at least one embodiment of the present invention, the information source parameters include a first parameter, a second parameter, and a third parameter; and quantizing the input information source parameters to obtain the first service indicator and the second service indicator includes:

[0016] The first parameter is quantified to obtain a first business indicator; the first parameter represents the resolution of the industrial shooting device; the second parameter and the third parameter are quantified to obtain a second business indicator; the second parameter represents the time interval for the industrial shooting device to capture images; the third parameter represents the number of images captured by the industrial shooting device per unit time.

[0017] Furthermore, according to at least one embodiment of the present invention, mapping the service indicator to a network indicator using the processing capability parameter includes:

[0018] Mapping the first business indicator to a first network indicator using the processing capability parameter; the first network indicator represents a network transmission rate required for transmitting images captured by the industrial shooting device;

[0019] Mapping the second business indicator to a second network indicator using the processing capability parameter; wherein the second network indicator represents a network transmission delay required for transmitting the image captured by the industrial shooting device;

[0020] The third business indicator is mapped to a third network indicator using the processing capability parameter; the third network indicator represents the network reliability required for transmitting images captured by the industrial shooting device.

[0021] Furthermore, according to at least one embodiment of the present invention, the processing capability parameter includes a bit depth of an image captured by the industrial camera and a compression rate of the image compressed by the industrial camera; and mapping the first business indicator to a first network indicator using the processing capability parameter includes:

[0022] A first operation is performed on the bit depth, the compression rate, and the numerical values ​​corresponding to the first service indicator to obtain an operation result; and the obtained operation result is used as the first network indicator.

[0023] Furthermore, according to at least one embodiment of the present invention, the processing capability parameter includes a first delay for the industrial camera to capture an image, a second delay for the industrial camera to compress the image, and a third delay for the industrial camera to analyze and process the image; and mapping the second service indicator to a second network indicator using the processing capability parameter includes:

[0024] Perform a second operation on the values ​​corresponding to the first delay, the second delay, the third delay and the second service indicator to obtain an operation result; and use the obtained operation result as the second network indicator.

[0025] Furthermore, according to at least one embodiment of the present invention, the processing capability parameter includes a bit depth of an image captured by the industrial camera; and mapping the third business indicator to a third network indicator using the processing capability parameter includes:

[0026] Performing a third operation on the bit depth and the value corresponding to the third service indicator to obtain an operation result;

[0027] The calculation result is used as the third network indicator.

[0028] At least one embodiment of the present invention provides a parameter processing device, including:

[0029] An input unit, configured to input industrial parameters and SLA indicator parameters; the industrial parameters represent relevant parameters of the industrial shooting equipment; the SLA indicator parameters represent the detection success rate of the images captured by the industrial shooting equipment;

[0030] A processing unit, configured to map the input industrial parameters and SLA indicator parameters to obtain network indicators; the network indicators represent network requirements required to transmit images captured by the industrial camera to a network device;

[0031] An output unit is used to output the network indicator.

[0032] At least one embodiment of the present invention provides a communication device, including:

[0033] A communication interface for inputting industrial parameters and SLA indicator parameters; the industrial parameters represent relevant parameters of the industrial shooting equipment; the SLA indicator parameters represent the detection success rate of the images collected by the industrial shooting equipment;

[0034] A processor configured to map the input industrial parameters and SLA indicator parameters to obtain network indicators, wherein the network indicators represent network requirements for transmitting images captured by the industrial camera to a network device;

[0035] The communication interface is also used to output the network indicators.

[0036] At least one embodiment of the present invention provides a communication device, comprising a processor and a memory for storing a computer program that can be run on the processor, wherein the processor is configured to execute the steps of any of the above-mentioned methods on the communication device side when running the computer program.

[0037] At least one embodiment of the present invention provides a storage medium having a computer program stored thereon, wherein the computer program implements the steps of any of the above methods when executed by a processor.

[0038] The parameter processing method, apparatus, device, and storage medium provided by the embodiments of the present invention input industrial parameters and SLA indicator parameters; the industrial parameters represent relevant parameters of industrial photography equipment; the SLA indicator parameters represent the detection success rate of images captured by the industrial photography equipment; the input industrial parameters and SLA indicator parameters are mapped to obtain network indicators; the network indicators represent the network requirements required to transmit the images captured by the industrial photography equipment to the network equipment; and the network indicators are output. Using the technical solution provided by the embodiments of the present invention, the input industrial parameters and SLA indicator parameters are automatically converted to output network indicators, eliminating the need for manual operation to set network indicators. This enables automated conversion of industrial parameters to network indicators, thus enabling SLA requirement decomposition in industrial machine vision scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a schematic diagram of the implementation process of decomposing SLA requirements in related technologies;

[0040] Figure 2 1 is a schematic diagram of the implementation flow of the parameter processing method according to an embodiment of the present invention;

[0041] Figure 3 is a schematic diagram of mapping input industrial parameters and SLA indicator parameters into network indicators according to an embodiment of the present invention;

[0042] Figure 4 This is a schematic diagram of a specific implementation flow of the parameter processing method according to an embodiment of the present invention;

[0043] Figure 5 is a schematic diagram of an embodiment of the present invention in which an industrial camera is used to capture an image;

[0044] Figure 6 This is a schematic diagram of an implementation process of quantifying input industrial parameters and SAL indicator parameters and mapping them into network indicators according to an embodiment of the present invention;

[0045] Figure 7 Schematic diagram of the structure of a parameter processing device according to an embodiment of the present invention;

[0046] Figure 8 The figure is a schematic diagram of the composition structure of the network device according to the embodiment of the present invention. DETAILED DESCRIPTION

[0047] Before introducing the technical solutions of the embodiments of the present invention, the relevant technologies are first described.

[0048] Figure 1 This is a schematic diagram of the decomposition of SLA requirements in related technologies, such as Figure 1 As shown, SLA requirement decomposition is achieved through the CSMF entity and the NSMF entity. Specifically, first, the network-level indicators input to the CSMF entity are constrained based on the general slice template (GST). Then, the CSMF entity decomposes the input SLA requirements using the GST template to obtain the end-to-end indicator profile serviceProfile, and inputs the serviceProfile profile to the NSMF entity. Finally, the NSMF entity decomposes the serviceProfile profile to obtain the indicator profile sliceprofile of the subdomain (wireless subdomain, transmission subdomain, core network subdomain). The essence of SLA requirement decomposition through the CSMF entity and the NSMF entity is the mapping of network requirements to network requirements.

[0049] However, in the process of decomposing SLA requirements, there are technical defects:

[0050] First, the CSMF input template GST directly specifies network-level indicators such as isolation, cell capacity, and transmission rate, and cannot translate and decompose requirements based on the original industrial business model and industrial-level business needs.

[0051] Second, the various network parameters in the GST template are obtained by converting industrial requirements into network requirements. The process of converting industrial requirements into network requirements is a manual, offline, and static process. In other words, it is impossible to achieve automated conversion from industrial language to network language.

[0052] Third, the SLA requirement decomposition process must be implemented based on the entire slicing management architecture, namely through the CSMF and NSMF entities in the large network and the NSSMF entities in the subdomains. Because the entire slicing system is not yet mature enough for commercial use, it will not be able to meet the requirements of lightweight provisioning, rapid deployment, and service integration in local scenarios for the time being. However, 5G+ industrial Internet applications are developing rapidly, especially in industrial machine vision quality inspection scenarios that leverage 5G's high bandwidth. Therefore, how to achieve requirement decomposition in industrial machine vision scenarios is becoming a growing trend.

[0053] Based on this, in an embodiment of the present invention, industrial parameters and SLA indicator parameters are input; the industrial parameters represent relevant parameters of the industrial shooting equipment; the SLA indicator parameters represent the detection success rate of the images collected by the industrial shooting equipment; the input industrial parameters and SLA indicator parameters are mapped to obtain network indicators; the network indicators represent the network requirements required to transmit the images collected by the industrial shooting equipment to the network equipment; and the network indicators are output.

[0054] The implementation process of the parameter processing method according to the embodiment of the present invention is described below with reference to specific embodiments.

[0055] Figure 2 FIG. 1 is a flow chart illustrating an implementation of a parameter processing method according to an embodiment of the present invention. Figure 2 As shown, the method includes steps 201 to 203:

[0056] Step 201: input industrial parameters and SLA indicator parameters; the industrial parameters represent relevant parameters of industrial shooting equipment; the SLA indicator parameters represent the detection success rate of images collected by the industrial shooting equipment.

[0057] It can be understood that the industrial shooting equipment may refer to an industrial camera in a machine vision detection scenario.

[0058] It can be understood that the relevant parameters of the industrial shooting equipment, namely industrial parameters, may include: camera frame rate, shooting rhythm, camera resolution, image bit depth, image compression rate, image acquisition delay, compression processing delay, analysis and reasoning delay, etc.

[0059] It is understandable that the detection success rate of the images captured by the industrial shooting equipment, i.e., the SLA indicator parameter, can be obtained through the following steps:

[0060] Step 1: Collect a certain number of images using the industrial photography equipment;

[0061] Step 2: extracting information from a certain number of images captured by the industrial photography equipment, and using the extracted information to detect whether the corresponding images are qualified;

[0062] Step 3: Count the ratio of the number of qualified images to the total number of images to obtain the detection success rate.

[0063] Step 202: Mapping the input industrial parameters and SLA indicator parameters to obtain network indicators; the network indicators represent the network requirements required for transmitting the images collected by the industrial shooting equipment to the network equipment.

[0064] It is understandable that mapping the input industrial parameters and SLA indicator parameters to obtain network indicators may include the following steps:

[0065] Step 1: Quantify the input industrial parameters and SLA indicator parameters to obtain business indicators;

[0066] The service indicators may refer to service-level indicators, and specifically may be service quality parameters that are close to user experience and proposed for specific services.

[0067] Step 2: Map the business indicators to obtain network indicators.

[0068] The network indicator may refer to an indicator at the network level, and specifically may be a network requirement for transmitting images captured by the industrial shooting device to a network device.

[0069] It can be understood that, considering that there can be many types of input industrial parameters, one type of industrial parameters can be correlated with industrial shooting equipment, and another type of industrial parameters can be correlated with the performance of industrial shooting equipment in processing images. In this way, industrial parameters can be divided into two categories, one type of industrial parameters is called the source parameters of industrial shooting equipment, and the other type of industrial parameters is called the processing capability parameters of industrial shooting equipment.

[0070] That is to say, after the input industrial parameters are divided into two categories, the signal source parameters and SLA indicator parameters of the industrial shooting equipment can be quantified to obtain business indicators; and the processing capacity parameters of the industrial shooting equipment can be used to map the obtained business indicators to obtain network indicators, such as Figure 3 shown.

[0071] Step 203: Output the network indicator.

[0072] It is understood that the output network indicators may specifically include:

[0073] Network transmission rate;

[0074] Network transmission delay;

[0075] Network transmission reliability.

[0076] It is understandable that the network indicators can be output to the CSMF entity in the slice architecture so that the CSMF entity can implement the decomposed SLA requirements.

[0077] It should be noted that the parameter processing method proposed in the embodiments of the present invention can be applied in industrial machine vision inspection scenarios. The principle of machine vision is that industrial cameras capture images and transmit them to a dedicated image analysis and processing system. The system analyzes and processes key image features to guide object feature recognition and determination. In the Industrial Internet, this technology is widely used in fields such as process monitoring, finished product inspection, and quality control.

[0078] It should be noted that in the embodiment of the present invention, there is no need to manually set network indicators for the input industrial parameters. Instead, the input industrial parameters and SLA indicator parameters are automatically converted to output network indicators, thereby realizing automated demand decomposition.

[0079] In other words, taking the input industrial parameters and SLA indicator parameters as the target, decompose the various business indicators associated with the input; then map each business indicator to the corresponding network indicator.

[0080] Figure 4 FIG. 1 is a flow chart illustrating an implementation of a parameter processing method according to an embodiment of the present invention. Figure 4 As shown, the method includes steps 401 to 406:

[0081] Step 401: Input the signal source parameters of the industrial shooting equipment, the processing capability parameters of the industrial shooting equipment, and the SLA indicator parameters.

[0082] It is understandable that the signal source parameters of the input industrial shooting equipment may be determined by the accuracy of the industrial shooting equipment and the business production rhythm.

[0083] Table 1 shows the input signal source parameters, processing capability parameters, and SLA indicator parameters for industrial camera equipment. The input signal source parameters for the industrial camera equipment include camera frame rate, cycle time, resolution, bit depth, and image compression ratio. The input processing capability parameters for the industrial camera equipment include image acquisition latency, compression processing latency, and analysis and inference latency. The input SLA indicator parameters include the photo detection success rate.

[0084]

[0085] Table 1

[0086] Step 402: quantify the input source parameters to obtain a first service indicator and a second service indicator.

[0087] It can be understood that the first service indicator represents the data size of a single frame image; and the second service indicator represents the end-to-end service delay allowed for a single frame image.

[0088] In one embodiment, the information source parameters include a first parameter, a second parameter, and a third parameter; and quantizing the input information source parameters to obtain the first service indicator and the second service indicator includes:

[0089] quantifying a first parameter to obtain a first business indicator; wherein the first parameter represents a resolution of the industrial shooting device;

[0090] The second parameter and the third parameter are quantified to obtain a second business indicator; the second parameter represents the time interval for the industrial shooting device to capture images; the third parameter represents the number of images captured by the industrial shooting device per unit time.

[0091] It is understandable that the first parameter can be quantified according to formula (1) to obtain the first business indicator, which is as follows:

[0092] Q=Pv×Ph (1)

[0093] Q represents the first business indicator, namely the data size of a single frame image, measured in bytes, where one byte represents one pixel. Pv × Ph represents the first parameter, namely the resolution of the industrial camera. The detection accuracy requirement can determine the parameter specification of the industrial camera, namely, the resolution.

[0094] It is understandable that the second parameter and the third parameter can be quantified according to formula (2) to obtain the second business indicator, which is as follows:

[0095]

[0096] Among them, t E The second service indicator is the end-to-end service latency allowed for a single frame. Cycle time represents the second parameter, namely, the time interval between image captures by the industrial camera. f represents the third parameter, namely, the number of images captured by the industrial camera per unit time. Cycle time and f determine the required inspection time. Maintaining a certain inspection rhythm requires completing image capture, transmission, processing, and analysis results within the interval between captures.

[0097] Step 403: quantify the SLA indicator parameters to obtain a third service indicator.

[0098] It can be understood that the third service indicator represents the packet loss rate allowed by the service.

[0099] It is understandable that the SLA indicator parameters can be quantified according to formula (3) to obtain the third service indicator, which is as follows:

[0100] L≤n×(1-S) (3)

[0101] Where L represents the third service indicator, namely the acceptable packet loss rate. S represents the SLA parameter, namely the detection success rate. The ratio of photos with failed or abnormal detection is (1-S). Assume that when n packets are lost in each frame, resulting in image blur, it is considered a detection anomaly.

[0102] Step 404: Map the first service indicator to a first network indicator using the processing capability parameter.

[0103] It can be understood that the first network indicator represents the network transmission rate required to transmit the image captured by the industrial shooting device.

[0104] In one embodiment, the processing capability parameter includes a bit depth of an image captured by the industrial camera and a compression rate of the image compressed by the industrial camera; and mapping the first business indicator to a first network indicator using the processing capability parameter includes:

[0105] Performing a first operation on the bit depth, the compression ratio, and a value corresponding to the first service indicator to obtain an operation result;

[0106] The obtained calculation result is used as the first network indicator.

[0107] It is understandable that in order to ensure detection accuracy, industrial machine vision detection scenarios usually use industrial camera equipment with more than 5 million pixels to capture high-definition images, which places high demands on the transmission bandwidth. To facilitate transmission, compression coding technology is usually used to compress high-definition images before transmission. When the compression rate is C, the first business indicator can be mapped to the first network indicator according to formula (4), as follows:

[0108]

[0109] Where v represents the first network indicator, namely, the network transmission rate required to transmit the image captured by the industrial camera. Q represents the first service indicator, namely, the data volume of a single frame. B represents the bit depth of the image captured by the industrial camera, and C represents the compression ratio of the image compressed by the industrial camera.

[0110] Step 405: Map the second service indicator to a second network indicator using the processing capability parameter.

[0111] It can be understood that the second network indicator represents the network transmission delay required to transmit the image captured by the industrial shooting device.

[0112] In one embodiment, the processing capability parameter includes a first delay for the industrial camera to capture an image, a second delay for the industrial camera to compress the image, and a third delay for the industrial camera to analyze and process the image; and mapping the second service indicator to a second network indicator using the processing capability parameter includes:

[0113] Performing a second operation on the first delay, the second delay, the third delay, and the values ​​corresponding to the second service indicator to obtain an operation result;

[0114] The obtained calculation result is used as the second network indicator.

[0115] It is understandable that the complete machine vision inspection process includes image acquisition, image compression, network transmission, image reception and recognition processing, which reduces the end-to-end delay of the business segment of a single frame image to t E Decomposed into image acquisition delay t1 + image compression processing delay t2 + network transmission delay t + analysis and reasoning delay t3, the second business indicator can be mapped to the second network indicator according to formula (5), as follows:

[0116]

[0117] Wherein, t represents the second network indicator, that is, the network transmission delay required to transmit the image captured by the industrial shooting equipment. E represents the second service indicator, that is, the end-to-end service delay allowed for a single frame of image. t1 represents the first delay, t2 represents the first delay, and t3 represents the third delay.

[0118] Step 406: Map the third service indicator to a third network indicator using the processing capability parameter.

[0119] It can be understood that the third network indicator represents the network reliability required for transmitting the images captured by the industrial shooting equipment.

[0120] In one embodiment, the processing capability parameter includes a bit depth of an image captured by the industrial camera; and mapping the third business indicator to a third network indicator using the processing capability parameter includes:

[0121] Performing a third operation on the bit depth and the value corresponding to the third service indicator to obtain an operation result;

[0122] The calculation result is used as the third network indicator.

[0123] It can be understood that the image file size Q is divided into packets according to MTU = 1500 bytes, and is divided into Q / 1500 = m data packets. Each packet loss results in the loss of 1500 pixels. The third service indicator can be mapped to the third network indicator according to formula (6), as follows:

[0124]

[0125] Where r represents the third network indicator, namely, the network reliability required to transmit the images captured by the industrial camera. L represents the third service indicator, namely, the packet loss rate allowed by the service. B represents the bit depth of the images captured by the industrial camera.

[0126] It should be noted that in the embodiment of the present invention, the input industrial parameters and SAL index parameters are quantified and mapped into network indicators, which has the following advantages:

[0127] (1) It can directly map industrial language to network language. Compared with related technologies that require a lot of manual offline communication and decomposition of requirements, as well as large-scale deployment of CSMF-NSMF-NSSMF end-to-end systems, it can achieve automated and real-time demand decomposition, and obtain industrial network requirements more quickly and at a lower cost.

[0128] (2) The calculation and acquisition of industrial demand for the network realizes an online automation process, improves the efficiency of demand acquisition, and reduces the cost of human communication and the complexity of calculation.

[0129] (3) It facilitates flexible adjustment and derivation of industry demands for the network; in addition, obtaining industry demands for the network in real time helps to achieve real-time network security and make the network more agile.

[0130] Taking the QR code traceability detection scenario as an example, the implementation principle of the parameter processing method is explained in detail.

[0131] Business model: Use a 5M (500w pixel) industrial camera for photo detection, with a resolution of 2448×2048 and 8-bit bit depth, and take a BMP format picture per second for uncompressed transmission. Figure 5 As shown, if data packet loss occurs, black lines will appear, resulting in false detection or missed detection. Assuming that in this scenario, if one data packet is lost per frame (n=1), it is considered a detection anomaly. The detection success rate is required to reach 99.99%.

[0132] The process of quantifying the input industrial parameters and SAL indicator parameters and mapping them into network indicators, such as Figure 6 As shown, the following steps are included:

[0133] Step 601: Input industrial parameters and SAL indicator parameters; the industrial parameters include the signal source parameters of the industrial shooting device and the processing capability parameters of the industrial shooting device.

[0134] The first parameter, ie, the resolution of the industrial shooting device Pv×Ph=2448×2048, is determined according to the detection accuracy of the industrial camera.

[0135] According to the detection time of the industrial camera, the second parameter is determined, that is, the time interval for the industrial shooting device to collect images, cycle time = 1s = 1000ms, and the third parameter is determined, that is, the number of images collected by the industrial shooting device in unit time, f = 1fps.

[0136] According to the detection success rate requirement of the industrial camera, the detection success rate S=99.99% is determined.

[0137] Step 602: quantify the input signal source parameters and SLA indicator parameters to obtain service indicators;

[0138] It is understandable that the business indicator may refer to a key quality indicator (KQI, Key Quality Indicator) at the business level.

[0139] The first business indicator is the data size of a single frame image:

[0140] Q=Pv×Ph=2448×2048=5013504 bytes.

[0141] The second service indicator is the end-to-end service delay allowed for a single frame of image:

[0142]

[0143] The third service indicator is the packet loss rate allowed by the service:

[0144] L=n×(1-S)=0.0001.

[0145] Step 603: Map the service indicator to a network indicator using the processing capability parameter.

[0146] It is understandable that the network indicator may refer to a key performance indicator (KPI) at the network level.

[0147] The first network indicator is the network transmission rate required to transmit the images captured by the industrial shooting equipment:

[0148]

[0149] The second network indicator is the network transmission delay required to transmit the images captured by the industrial shooting equipment:

[0150] t=t E -t1-t2-t3≤960ms

[0151] The third network indicator is the network reliability required to transmit the images captured by the industrial shooting equipment:

[0152]

[0153] By adopting the technical solution provided by the embodiment of the present invention, the input industrial parameters and SLA indicator parameters are automatically converted to output network indicators, without the need for manual operation to set network indicators. The automatic conversion of industrial parameters to network indicators can be realized, thus realizing SLA demand decomposition in industrial machine vision scenarios.

[0154] In order to implement the parameter processing method of the embodiment of the present invention, the embodiment of the present invention also provides a parameter processing device, Figure 7 FIG. 1 is a schematic diagram showing the structure of a parameter processing device according to an embodiment of the present invention; FIG. Figure 7 As shown, the device includes:

[0155] An input unit 71 is configured to input industrial parameters and SLA indicator parameters; the industrial parameters represent relevant parameters of the industrial photographing device; and the SLA indicator parameters represent the detection success rate of the images captured by the industrial photographing device.

[0156] The processing unit 72 is configured to map the input industrial parameters and SLA indicator parameters to obtain network indicators; the network indicators represent the network requirements required to transmit the images captured by the industrial camera to the network device;

[0157] The output unit 73 is configured to output the network indicator.

[0158] In one embodiment, the industrial parameters include the signal source parameters of the industrial shooting device and the processing capability parameters of the industrial shooting device; the processing unit 72 is specifically configured to:

[0159] Quantify the input signal source parameters and SLA indicator parameters to obtain business indicators;

[0160] The service indicator is mapped into a network indicator using the processing capability parameter.

[0161] In one embodiment, the processing unit 72 is specifically configured to:

[0162] Quantifying the input source parameters to obtain a first service indicator and a second service indicator; the first service indicator represents the data volume of a single frame image; the second service indicator represents the end-to-end service delay allowed for a single frame image;

[0163] The SLA indicator parameters are quantified to obtain a third service indicator; the third service indicator represents the packet loss rate allowed by the service.

[0164] In one embodiment, the information source parameters include a first parameter, a second parameter, and a third parameter; the processing unit 72 is specifically configured to:

[0165] quantifying a first parameter to obtain a first business indicator; wherein the first parameter represents a resolution of the industrial shooting device;

[0166] The second parameter and the third parameter are quantified to obtain a second business indicator; the second parameter represents the time interval for the industrial shooting device to capture images; the third parameter represents the number of images captured by the industrial shooting device per unit time.

[0167] In one embodiment, the processing unit 72 is specifically configured to:

[0168] Mapping the first business indicator to a first network indicator using the processing capability parameter; the first network indicator represents a network transmission rate required for transmitting images captured by the industrial shooting device;

[0169] Mapping the second business indicator to a second network indicator using the processing capability parameter; wherein the second network indicator represents a network transmission delay required for transmitting the image captured by the industrial shooting device;

[0170] The third business indicator is mapped to a third network indicator using the processing capability parameter; the third network indicator represents the network reliability required for transmitting images captured by the industrial shooting device.

[0171] In one embodiment, the processing capability parameter includes the bit depth of the image captured by the industrial photographing device and the compression rate of the image compressed by the industrial photographing device; the processing unit 72 is specifically configured to:

[0172] Performing a first operation on the bit depth, the compression ratio, and a value corresponding to the first service indicator to obtain an operation result;

[0173] The obtained calculation result is used as the first network indicator.

[0174] In one embodiment, the processing capability parameters include a first delay for the industrial camera to capture an image, a second delay for the industrial camera to compress the image, and a third delay for the industrial camera to analyze and process the image; the processing unit 72 is specifically configured to:

[0175] Performing a second operation on the first delay, the second delay, the third delay, and the values ​​corresponding to the second service indicator to obtain an operation result;

[0176] The obtained calculation result is used as the second network indicator.

[0177] In one embodiment, the processing capability parameter includes the bit depth of the image captured by the industrial camera; the processing unit 72 is specifically configured to:

[0178] Performing a third operation on the bit depth and the value corresponding to the third service indicator to obtain an operation result;

[0179] The calculation result is used as the third network indicator.

[0180] In actual application, the input unit 71 and the output unit 73 can be implemented by a communication interface in the parameter processing device; and the processing unit 72 can be implemented by a processor in the parameter processing device.

[0181] It should be noted that the parameter processing device provided in the above embodiment only uses the division of the above-mentioned program modules as an example to illustrate parameter processing. In actual applications, the above-mentioned processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the above-described processing. In addition, the parameter processing device provided in the above embodiment and the parameter processing method embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0182] The embodiment of the present invention also provides a network device, such as Figure 8 As shown, including:

[0183] Communication interface 81, capable of exchanging information with other devices;

[0184] The processor 82 is connected to the communication interface 81 and is used to execute the method provided by one or more technical solutions on the smart device side when running a computer program. The computer program is stored in the memory 83.

[0185] It should be noted that the specific processing procedures of the processor 82 and the communication interface 81 are detailed in the method embodiment and will not be repeated here.

[0186] Of course, in actual application, the various components in the network device 80 are coupled together through the bus system 84. It is understood that the bus system 84 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 104 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 8 Various buses are labeled as bus system 84 .

[0187] The memory 83 in the embodiment of the present application is used to store various types of data to support the operation of the network device 80. Examples of such data include: any computer program used to operate on the network device 80.

[0188] The methods disclosed in the above embodiments of the present application can be applied to the processor 82 or implemented by the processor 82. The processor 82 may be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the above methods can be completed by hardware integrated logic circuits in the processor 82 or by instructions in the form of software. The above processor 82 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present application can be directly implemented as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium located in the memory 103. The processor 102 reads the information in the memory 103 and completes the steps of the above methods in conjunction with its hardware.

[0189] In an exemplary embodiment, the network device 80 can be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to perform the aforementioned method.

[0190] It can be understood that the memory (memory 83) of the embodiment of the present application can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a magnetic disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM).The memories described in the embodiments of this application are intended to include, but are not limited to, these and any other suitable types of memories.

[0191] In an exemplary embodiment, the present invention further provides a storage medium, namely, a computer storage medium, specifically, a computer-readable storage medium, including, for example, a first memory 81 storing a computer program. The computer program can be executed by the first processor 102 of the terminal 100 to complete the steps of the aforementioned terminal-side method. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, or CD-ROM.

[0192] It should be noted that: "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0193] In addition, the technical solutions described in the embodiments of the present invention can be arbitrarily combined without conflict.

[0194] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention.

Claims

1. A parameter processing method, characterized in that: The method comprises: Input industrial parameters and service level agreement (SLA) indicator parameters; the industrial parameters represent relevant parameters of the industrial shooting equipment; the SLA indicator parameters represent the detection success rate of the images collected by the industrial shooting equipment; Mapping the input industrial parameters and SLA indicator parameters to obtain network indicators; the network indicators represent the network requirements required to transmit images collected by the industrial camera to the network device; Outputting the network indicators; The industrial parameters include the signal source parameters of the industrial shooting device and the processing capability parameters of the industrial shooting device; the input industrial parameters and SLA indicator parameters are mapped to obtain network indicators, including: Quantify the input signal source parameters and SLA indicator parameters to obtain business indicators; The service indicator is mapped into a network indicator using the processing capability parameter.

2. The method according to claim 1, characterized in that The input signal source parameters and SLA indicator parameters are quantified to obtain service indicators, including: Quantifying the input source parameters to obtain a first service indicator and a second service indicator; the first service indicator represents the data volume of a single frame image; the second service indicator represents the end-to-end service delay allowed for a single frame image; The SLA indicator parameters are quantified to obtain a third service indicator; the third service indicator represents the packet loss rate allowed by the service.

3. The method according to claim 2, characterized in that The information source parameters include a first parameter, a second parameter, and a third parameter; and the quantization of the input information source parameters to obtain the first service indicator and the second service indicator includes: quantifying a first parameter to obtain a first business indicator; wherein the first parameter represents a resolution of the industrial shooting device; The second parameter and the third parameter are quantified to obtain a second business indicator; the second parameter represents the time interval for the industrial shooting device to capture images; the third parameter represents the number of images captured by the industrial shooting device per unit time.

4. The method according to claim 2 or 3, characterized in that Mapping the service indicator to a network indicator by using the processing capability parameter includes: Mapping the first business indicator to a first network indicator using the processing capability parameter; the first network indicator represents a network transmission rate required for transmitting images captured by the industrial shooting device; Mapping the second business indicator to a second network indicator using the processing capability parameter; wherein the second network indicator represents a network transmission delay required for transmitting the image captured by the industrial shooting device; The third business indicator is mapped to a third network indicator using the processing capability parameter; the third network indicator represents the network reliability required for transmitting images captured by the industrial shooting device.

5. The method according to claim 4, characterized in that The processing capability parameter includes a bit depth of an image captured by the industrial camera and a compression rate of the image compressed by the industrial camera; and mapping the first business indicator to a first network indicator using the processing capability parameter includes: Performing a first operation on the bit depth, the compression ratio, and a value corresponding to the first service indicator to obtain an operation result; The obtained calculation result is used as the first network indicator.

6. The method according to claim 4, characterized in that The processing capability parameter includes a first delay for the industrial camera to capture an image, a second delay for the industrial camera to compress the image, and a third delay for the industrial camera to analyze and process the image. Mapping the second service indicator to a second network indicator using the processing capability parameter includes: Performing a second operation on the first delay, the second delay, the third delay, and the values ​​corresponding to the second service indicator to obtain an operation result; The obtained calculation result is used as the second network indicator.

7. The method according to claim 4, characterized in that The processing capability parameter includes a bit depth of an image captured by the industrial shooting device; and mapping the third business indicator to a third network indicator using the processing capability parameter includes: Performing a third operation on the bit depth and the value corresponding to the third service indicator to obtain an operation result; The calculation result is used as the third network indicator.

8. A parameter processing device, characterized in that: include: An input unit, used to input industrial parameters and SLA indicator parameters; the industrial parameters represent relevant parameters of the industrial shooting equipment; The SLA indicator parameter represents the detection success rate of the images collected by the industrial shooting equipment; A processing unit, configured to map the input industrial parameters and SLA indicator parameters to obtain network indicators; the network indicators represent network requirements required to transmit images captured by the industrial camera to a network device; An output unit, configured to output the network indicator; Among them, the industrial parameters include the signal source parameters of the industrial shooting equipment and the processing capability parameters of the industrial shooting equipment; the processing unit is specifically used to: quantify the input signal source parameters and SLA indicator parameters to obtain business indicators; and use the processing capability parameters to map the business indicators into network indicators.

9. A network device, characterized in that: include: A communication interface for inputting industrial parameters and SLA indicator parameters; the industrial parameters represent relevant parameters of the industrial shooting equipment; The SLA indicator parameter represents the detection success rate of the images collected by the industrial shooting equipment; A processor configured to map the input industrial parameters and SLA indicator parameters to obtain network indicators, wherein the network indicators represent network requirements for transmitting images captured by the industrial camera to a network device; The communication interface is further used to output the network indicator; Among them, the industrial parameters include the signal source parameters of the industrial shooting equipment and the processing capability parameters of the industrial shooting equipment; the processor is specifically used to: quantify the input signal source parameters and SLA indicator parameters to obtain business indicators; and use the processing capability parameters to map the business indicators into network indicators.

10. A network device, characterized in that: comprising a processor and a memory for storing a computer program capable of being executed on the processor, Wherein, when the processor is used to run the computer program, it executes the steps of the method according to any one of claims 1 to 7.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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