CN117041534B - Binding performance testing method for intelligent camera - Google Patents
Binding performance testing method for intelligent camera Download PDFInfo
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- CN117041534B CN117041534B CN202311289543.5A CN202311289543A CN117041534B CN 117041534 B CN117041534 B CN 117041534B CN 202311289543 A CN202311289543 A CN 202311289543A CN 117041534 B CN117041534 B CN 117041534B
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- 238000012360 testing method Methods 0.000 title claims abstract description 79
- 230000003993 interaction Effects 0.000 claims abstract description 69
- 238000000034 method Methods 0.000 claims abstract description 21
- 230000002159 abnormal effect Effects 0.000 claims abstract description 13
- 238000012545 processing Methods 0.000 claims abstract description 6
- 238000011056 performance test Methods 0.000 claims description 6
- 238000012986 modification Methods 0.000 abstract description 8
- 230000004048 modification Effects 0.000 abstract description 8
- 230000005856 abnormality Effects 0.000 description 5
- 230000002093 peripheral effect Effects 0.000 description 3
- 230000002452 interceptive effect Effects 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
- H04M1/72406—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality by software upgrading or downloading
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
- H04M1/72409—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality by interfacing with external accessories
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention relates to the technical field of electric digital data processing, in particular to a binding energy testing method of an intelligent camera, which comprises a testing step and an exception handling step, wherein when the testing step is abnormal, the testing step is stopped to enter the exception handling step, and the exception handling step is as follows: and screenshot is carried out on a corresponding page of the mobile phone app and is transmitted to a computer, the computer stores interaction data comprising operation data, text information and screenshot information, then the interaction data is processed, a test progress value is solved, and the reason and the positioning of the binding failure are queried in an operation dictionary stored in the computer in advance according to the test progress value. When binding failure occurs, the method provided by the invention can automatically give out failure operation positioning and reasons through reasoning on test data, thereby greatly facilitating the rapid positioning and modification of abnormal logic by software developers, and the test process is automatically controlled, and the test is efficient and rapid.
Description
Technical Field
The invention relates to the technical field of electric digital data processing, in particular to a binding performance testing method of an intelligent camera.
Background
The intelligent camera product generally needs the user to bind the equipment with the account thereof, and the binding success rate and binding time become important indexes for measuring the performance of the product, and are also effective means for improving the user experience as a reference.
One of the current binding performance test schemes for intelligent camera products is to manually operate a mobile phone app, input a WIFI name and a password to be bound according to the mobile phone app, and record the binding time and whether the binding is successful or not by a manual stopwatch. The method has inaccurate measurement results, larger errors, easy fatigue during manual observation, low mass test efficiency and higher test cost. And secondly, programming by mobile phone app automation technology, and automatically testing intelligent camera products. The problem of this solution is that only the test result can be marked as "success" or "failure", but the failure position and reason of this test cannot be automatically located, and a manual backtracking determination is required. Because the data interaction of mobile phone app, cloud terminal and equipment designed in the smart camera binding process is complex, once failure occurs, specific reasons are difficult to locate, and when a developer solves bug, the developer cannot quickly locate an abnormal logic position and the efficiency is low.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a binding performance testing method for intelligent cameras, which can automatically and efficiently test binding performance of intelligent camera products in large quantity, stores operation data of mobile phone apps, mobile phone screenshots, app document information and other data when binding failure occurs, then infers the test data, automatically gives out failure operation positioning and reasons, and greatly facilitates quick positioning and modification of abnormal logic by software developers.
The invention is realized by the following technical scheme:
a binding energy test method of an intelligent camera comprises a test step and an exception handling step, wherein when the test step is abnormal, the test step is stopped to enter the exception handling step;
the testing step comprises the following steps:
s1: the computer controls the intelligent camera to be tested to enter an initialized binding state, and starts the mobile phone app to enable the mobile phone app to enter a scanning surrounding equipment page;
s2: after searching the intelligent camera to be detected, the mobile phone app enters a WIFI setting page, automatically inputs a set WIFI name and password and transmits WIFI information to the intelligent camera to be detected, and the mobile phone app enters a binding waiting page;
s3: if the intelligent camera images are successfully connected within the set time, the mobile phone app enters a live broadcast page of the intelligent camera, and the intelligent camera to be detected is successfully bound;
the exception handling steps are as follows:
s4: and screenshot is carried out on a corresponding page of the mobile phone app and is transmitted to a computer, the computer stores interaction data comprising operation data, text information and screenshot information, then the interaction data is processed, a test progress value is solved, and the reason and the positioning of the binding failure are queried in an operation dictionary stored in the computer in advance according to the test progress value.
Further, the step S4 of processing the interactive data by the computer to solve the progress value of the test specifically includes the following steps:
s4-1: extracting feature points of the images from the screenshot, extracting feature point data of icons in the images, storing the feature point data to form an icon feature point vector set, and finally forming a plurality of groups of operation interaction data [ operation information, text information and feature point vector set ];
s4-2: comparing each group of operation interaction data with standard interaction data stored in a computer in advance, calculating the similarity of the corresponding operation interaction data, and eliminating operation interaction data which do not meet the requirements;
s4-3: the progress value of the test is solved by dividing the number of satisfactory operational interaction data by the total number of standard operational interaction data.
Further, when the screenshot is extracted from the image feature point in step S4-1, the screenshot is first decomposed into a plurality of icon buttons by using an image edge algorithm, and then each icon button is extracted from the image feature point by using any one of SIFT, SURF or Freak algorithm.
Further, when calculating the similarity of the operation interaction data in step S4-2, the operation information, the document information and the feature point vector set in the operation interaction data are respectively compared with the operation information, the document information and the feature point vector set in the standard interaction data to obtain the similarity of the operation information, the document information and the feature point vector set, and then the similarity of a group of operation interaction data is calculated according to the weights given to the operation information, the document information and the feature point vector set.
Further, in step S4, if the reason and the location of the binding failure are queried in the operation dictionary according to the progress value of the test, the query result is fed back to the test report, if the reason and the location of the binding failure are not queried in the operation dictionary under the corresponding progress value of the test, the reason and the location of the binding failure are manually checked and found, and the result is supplemented to the operation dictionary.
Preferably, the time set in step S3 is 60 seconds.
Further, in step S1, when the computer controls the intelligent camera to be tested to enter the initialized binding state, the computer sends an instruction to the reset device, and the reset device presses the reset key of the intelligent camera to be tested to enable the intelligent camera to be tested to enter the initialized binding state.
The invention has the beneficial effects that:
the binding performance testing method for the intelligent camera can automatically, largely and efficiently test binding performance of intelligent camera products, stores operation data of mobile phone apps, mobile phone screenshots, app document information and other data when binding failure occurs, infers test data, automatically gives out failure operation positioning and reasons, and greatly facilitates quick positioning and modification of abnormal logic by software developers.
Drawings
FIG. 1 is a schematic flow chart of the method of the invention.
Detailed Description
The specific flow chart of the binding performance testing method of the intelligent camera is shown in fig. 1, and the binding performance testing method comprises a testing step and an exception handling step, wherein when the testing step is abnormal, the testing step is stopped to enter the exception handling step;
the testing step comprises the following steps:
s1: the computer controls the intelligent camera to be tested to enter an initialized binding state, and starts the mobile phone app to enable the mobile phone app to enter a scanning surrounding equipment page; if the abnormality occurs mainly when the mobile phone app enters the scanning peripheral equipment page or when the mobile phone app still does not enter the scanning peripheral equipment page beyond a set time length, the set time length is generally 60 seconds, so that sufficient waiting time can be ensured to enable the mobile phone app to enter the scanning peripheral equipment page, and the test efficiency can be considered.
S2: after searching the intelligent camera to be detected, the mobile phone app enters a WIFI setting page, automatically inputs a set WIFI name and password and transmits WIFI information to the intelligent camera to be detected, and the mobile phone app enters a binding waiting page; if the abnormality occurs, the mobile phone app does not enter the binding waiting page or the waiting time for entering the binding waiting page exceeds the set time length, and the set time length is 60 seconds generally, so that the mobile phone app can enter the binding waiting page with enough waiting time, and the test efficiency can be considered.
S3: if the intelligent camera images are successfully connected within the set time, the mobile phone app enters a live broadcast page of the intelligent camera, and the intelligent camera to be detected is successfully bound; if the abnormality occurs, the mobile phone app does not enter the intelligent camera live page or the waiting time for entering the intelligent camera live page exceeds the set time length, and the set time length is 60 seconds generally, so that the mobile phone app can enter the intelligent camera live page with enough waiting time, and the test efficiency can be considered;
the exception handling steps are as follows:
s4: and screenshot is carried out on a corresponding page of the mobile phone app and is transmitted to a computer, the computer stores interaction data comprising operation data, text information and screenshot information, then the interaction data is processed, a test progress value is solved, and the reason and the positioning of the binding failure are queried in an operation dictionary stored in the computer in advance according to the test progress value.
Further, the step S4 of processing the interactive data by the computer to solve the progress value of the test specifically includes the following steps:
s4-1: extracting feature points of the images from the screenshot, extracting feature point data of icons in the images, storing the feature point data to form an icon feature point vector set, and finally forming a plurality of groups of operation interaction data [ operation information, text information and feature point vector set ];
when the screenshot is specifically extracted from the image feature points, the screenshot can be decomposed into a plurality of icon buttons by using an image edge algorithm, then each icon button is respectively extracted from the image feature points by using any one of SIFT, SURF or Freak algorithm, so that feature point data of the icons in the image are extracted and stored to form an icon feature point vector set, and then a group of operation interaction data is formed together with corresponding operation information and text information. The image edge algorithm, SIFT or SURF or Freak algorithm here are all prior art.
S4-2: comparing each group of operation interaction data with standard interaction data stored in a computer in advance, calculating the similarity of the corresponding operation interaction data, and eliminating operation interaction data which do not meet the requirements;
specifically, when calculating the similarity of the operation interaction data, the operation information, the document information and the feature point vector set in the operation interaction data can be respectively compared with the operation information, the document information and the feature point vector set in the standard interaction data to obtain the similarity of the operation information, the document information and the feature point vector set, then the similarity of a group of operation interaction data is calculated according to the weights given to the operation information, the document information and the feature point vector set, when comparing, the operation information in the first group of operation interaction data is compared with the corresponding operation information in the standard interaction data, the document information in the first group of operation interaction data is compared with the corresponding document information in the standard interaction data, the feature point vector set in the first group of operation interaction data is compared with the corresponding feature point vector set in the standard interaction data to obtain the respective similarity, then different weights are given to the similarity of the operation information, the document information and the feature point vector set to solve the similarity of the group of operation interaction data, and the similarity of the group of operation interaction data can be solved by using the formula (1):
（1）；
wherein:indicate->Similarity of group operation interaction data, +.>A group number representing the operational interaction data,indicate->Similarity of operation information in group operation interaction data, < ->Indicate->Similarity of file information in group operation interaction data, < ->Indicate->Similarity of feature point vector set in group operation interaction data, +.>Similarity weight representing operation information, +.>Similarity weight representing document information, +.>Representing the similarity weight of the feature point vector set.
And calculating the similarity of each group of operation interaction data according to the method until the similarity of all operation interaction data is calculated.
The undesirable operation interaction data refers to that the calculated similarity of the group of operation interaction data is smaller than a set value, the set value is generally 0.9, if the similarity is greater than or equal to 0.9, the group of operation is considered to be the same as the standard interaction operation, and the purpose of doing so is mainly to remove noise in the interaction data, and mainly to remove operations which are irrelevant to binding, such as some mobile phone app popup windows or notifications of a mobile phone system.
S4-3: the progress value of the test is solved by dividing the number of satisfactory operational interaction data by the total number of standard operational interaction data.
Specifically, the calculation formula of the progress value of the test is shown in formula (2):
（2）；
wherein:for the accuracy value of the test, +.>For the amount of operational interaction data that meets the requirements, +.>The total number of interaction data for standard operations.
The method comprises the steps of calculating the similarity of operation interaction data, removing operation which is not in accordance with requirements, namely removing noise in the interaction data, mainly removing some operation which is not in accordance with the requirements, such as some mobile phone app popup windows or mobile phone system notifications, stopping testing once abnormality occurs in the testing process, dividing the number of the operation interaction data which is in accordance with the requirements by the total number of standard operation interaction data to solve the progress value of the testing, namely the progress when the abnormality occurs, so that the operation positioning of the corresponding progress can be accurately found by corresponding the solved progress value with the progress which is pre-stored in an operation dictionary of a computer, namely the reason of operation failure is found, and software developers can quickly position and modify abnormal logic.
The operation dictionary pre-stored in the computer is shown in a first table, and comprises progress values, operation positioning or failure reasons and problem parties, wherein the calculated progress values correspond to the progress values in the first table during inquiry, and the operation positioning/failure reasons and problem parties corresponding to the corresponding progress values in the first table are the abnormal operation positioning or failure reasons and problem parties in the testing process.
List-an operation dictionary stored in advance in a computer
According to the binding performance testing method for the intelligent camera, when binding failure occurs, operation data of the mobile phone app, mobile phone screenshot, app document information and other data are stored, then test data are inferred, failure operation positioning and reasons are automatically given, rapid positioning and modification of abnormal logic by software developers are greatly facilitated, automatic control can be achieved in the whole testing process, the testing process is efficient and rapid, and the binding performance testing method can be applied to large-scale intelligent camera binding performance testing.
Further, in step S4-3, if the reason and location of the binding failure are queried in the operation dictionary according to the tested progress value, the query result is fed back to the test report, if the reason and location of the binding failure are not queried in the operation dictionary under the corresponding tested progress value, the reason and location of the binding failure are manually checked and found, the result is supplemented to the operation dictionary, the operation dictionary is continuously supplemented and updated in the actual test process, the next time of query of the problem is facilitated, along with accumulation and enrichment of the error reporting dictionary, the automatic location of the binding failure reason is more and more accurate, and rapid location and modification of abnormal logic by software developers are further facilitated.
Further, in step S1, when the computer controls the intelligent camera to be tested to enter the initialized binding state, the computer sends an instruction to the reset device, the reset device is an instrument capable of simulating pressing the physical reset key of the intelligent camera, and the computer controls the reset device to press the reset key of the intelligent camera to be tested, so that the intelligent camera to be tested can automatically enter the initialized binding state, the degree of automation of the testing method is further improved, and the automatic, large-scale and efficient binding energy testing for intelligent camera products is facilitated.
In summary, according to the binding performance testing method for the intelligent camera, when binding failure occurs, operation data of the mobile phone app, screenshot of the mobile phone, app document information and other data are stored, then reasoning is carried out on the testing data, positioning and reasons of failure operation are automatically given, rapid positioning and modification of abnormal logic by a software developer are greatly facilitated, automatic control of a testing process is carried out, and testing is efficient and rapid.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A binding performance testing method of an intelligent camera is characterized in that: the method comprises a testing step and an exception handling step, wherein when the testing step is abnormal, the testing step is stopped to enter the exception handling step;
the testing step comprises the following steps:
s1: the computer controls the intelligent camera to be tested to enter an initialized binding state, and starts the mobile phone app to enable the mobile phone app to enter a scanning surrounding equipment page;
s2: after searching the intelligent camera to be detected, the mobile phone app enters a WIFI setting page, automatically inputs a set WIFI name and password and transmits WIFI information to the intelligent camera to be detected, and the mobile phone app enters a binding waiting page;
s3: if the intelligent camera images are successfully connected within the set time, the mobile phone app enters a live broadcast page of the intelligent camera, and the intelligent camera to be detected is successfully bound;
the exception handling steps are as follows:
s4: the method comprises the steps of carrying out screenshot on a corresponding page of a mobile phone app and transmitting the screenshot to a computer, processing the interaction data after the computer stores the interaction data comprising operation data, text information and screenshot information, solving a test progress value, inquiring and positioning reasons and positioning failure of an operation dictionary stored in the computer in advance according to the test progress value, and processing the interaction data by the computer to solve the test progress value, wherein the method specifically comprises the following steps of:
s4-1: extracting feature points of the images from the screenshot, extracting feature point data of icons in the images, storing the feature point data to form an icon feature point vector set, and finally forming a plurality of groups of operation interaction data [ operation information, text information and feature point vector set ];
s4-2: comparing each group of operation interaction data with standard interaction data stored in a computer in advance, calculating the similarity of the corresponding operation interaction data, and eliminating operation interaction data which do not meet the requirements;
s4-3: the progress value of the test is solved by dividing the number of satisfactory operational interaction data by the total number of standard operational interaction data.
2. The binding performance test method of an intelligent camera according to claim 1, wherein: when the screenshot is extracted from the image feature points in the step S4-1, the screenshot is decomposed into a plurality of icon buttons by using an image edge algorithm, and then each icon button is extracted from the image feature points by using any algorithm of SIFT, SURF or Freak.
3. The binding performance test method of an intelligent camera according to claim 1, wherein: and S4-2, when the similarity of the operation interaction data is calculated, comparing the operation information, the document information and the characteristic point vector set in the operation interaction data with the operation information, the document information and the characteristic point vector set in the standard interaction data respectively to obtain the similarity of the operation information, the document information and the characteristic point vector set, and then calculating the similarity of a group of operation interaction data according to the weights given to the operation information, the document information and the characteristic point vector set.
4. The binding performance test method of an intelligent camera according to claim 1, wherein: in step S4, if the reason and location of the binding failure are queried in the operation dictionary according to the progress value of the test, the query result is fed back to the test report, if the reason and location of the binding failure are not queried in the operation dictionary under the corresponding progress value of the test, the reason and location of the binding failure are found out by manual checking, and the result is supplemented to the operation dictionary.
5. The binding performance test method of an intelligent camera according to claim 1, wherein: step S3 sets the time to 60 seconds.
6. The binding performance test method of an intelligent camera according to claim 1, wherein: in the step S1, when the computer controls the intelligent camera to be detected to enter an initialized binding state, the computer sends an instruction to the reset device, and the reset device presses a reset key of the intelligent camera to be detected to enable the intelligent camera to be detected to enter the initialized binding state.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005333506A (en) * | 2004-05-21 | 2005-12-02 | Funai Electric Co Ltd | Automatic communication test device of user's apparatus in remote watching system |
| JP2014053870A (en) * | 2012-09-10 | 2014-03-20 | Nec Networks & System Integration Corp | Operation test program of mobile terminal device |
| KR20160021419A (en) * | 2014-08-14 | 2016-02-25 | 엔에이치엔엔터테인먼트 주식회사 | Mobile terminal test system and mobile terminal test method using the system |
| CN108647141A (en) * | 2018-04-26 | 2018-10-12 | 腾讯科技（深圳）有限公司 | Automatic test approach, device, computer-readable medium and electronic equipment |
| CN112492294A (en) * | 2019-09-12 | 2021-03-12 | 北京地平线机器人技术研发有限公司 | Application program testing method, device and system, network camera and medium |
| CN113595824A (en) * | 2021-07-27 | 2021-11-02 | 深圳信息通信研究院 | Method for testing distribution network reliability of Wi-Fi Internet of things equipment and readable storage medium |
| CN115033487A (en) * | 2022-06-22 | 2022-09-09 | 中国平安财产保险股份有限公司 | Automatic testing method and device based on image recognition, computer equipment and storage medium |
| CN115278223A (en) * | 2022-09-29 | 2022-11-01 | 天津华来科技股份有限公司 | Camera product connection performance test method and system, storage device and processing terminal |
| CN116264613A (en) * | 2021-12-13 | 2023-06-16 | 深圳Tcl新技术有限公司 | Distribution network testing method and system for intelligent camera, computer equipment and medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110944146B (en) * | 2018-09-21 | 2022-04-12 | 华为技术有限公司 | Intelligent analysis equipment resource adjusting method and device |
-
2023
- 2023-10-08 CN CN202311289543.5A patent/CN117041534B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005333506A (en) * | 2004-05-21 | 2005-12-02 | Funai Electric Co Ltd | Automatic communication test device of user's apparatus in remote watching system |
| JP2014053870A (en) * | 2012-09-10 | 2014-03-20 | Nec Networks & System Integration Corp | Operation test program of mobile terminal device |
| KR20160021419A (en) * | 2014-08-14 | 2016-02-25 | 엔에이치엔엔터테인먼트 주식회사 | Mobile terminal test system and mobile terminal test method using the system |
| CN108647141A (en) * | 2018-04-26 | 2018-10-12 | 腾讯科技（深圳）有限公司 | Automatic test approach, device, computer-readable medium and electronic equipment |
| CN112492294A (en) * | 2019-09-12 | 2021-03-12 | 北京地平线机器人技术研发有限公司 | Application program testing method, device and system, network camera and medium |
| CN113595824A (en) * | 2021-07-27 | 2021-11-02 | 深圳信息通信研究院 | Method for testing distribution network reliability of Wi-Fi Internet of things equipment and readable storage medium |
| CN116264613A (en) * | 2021-12-13 | 2023-06-16 | 深圳Tcl新技术有限公司 | Distribution network testing method and system for intelligent camera, computer equipment and medium |
| CN115033487A (en) * | 2022-06-22 | 2022-09-09 | 中国平安财产保险股份有限公司 | Automatic testing method and device based on image recognition, computer equipment and storage medium |
| CN115278223A (en) * | 2022-09-29 | 2022-11-01 | 天津华来科技股份有限公司 | Camera product connection performance test method and system, storage device and processing terminal |
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