A method and system for automated testing of the effectiveness of a router game acceleration function

Abstract

The application provides a kind of router game acceleration function effectiveness automated testing method, comprising: reading user profile;Frame analysis and parameter statistical processing are carried out to the game video data before and after the game acceleration function of router is opened to tester;The processed data before and after the game acceleration function of router is opened are merged and analyzed, are classified and arranged and are drawn trend chart, and the data and chart that are arranged are written into Excel table and are saved, and final test report is obtained to complete this automated testing.The beneficial effects of the application: game experience data can be quantified, and test conclusion can be effectively supported;It is simple to operate, and only needs to configure the video path before and after the game acceleration function of router is opened into config.ini file one-key execution, so that video analysis, data analysis and test report generation can be completed, manpower cost and time cost are reduced, test efficiency is improved, and the influence of subjective feeling of tester on test result is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of test methods, in particular to a method and system for automatically testing the effectiveness of a router game acceleration function. BACKGROUND

[0002] A router (also known as a pather) is a computer network device that can transmit data to the destination through packaging and network transmission (selecting the transmission path of the data), which is called routing. A router is a device that connects two or more separate networks, and routing works in the third layer of the OSI model, i.e. the network layer.

[0003] The router game acceleration function is to recognize the characteristic code of a specific game application, and then forward the data stream of the application for processing, thereby reducing the game delay and improving the game experience effect. The current test method for the router game acceleration function in the industry is mainly based on manual operation, and there are two main methods:

[0004] One is based on subjective judgment, and the test personnel give the test conclusion of the function effectiveness according to the subjective feeling of the game experience before and after turning on and off the router game acceleration function;

[0005] The second is based on a small amount of data for quantitative judgment, and the test personnel manually take screenshots of the game screen during the game process before and after turning on and off the router game acceleration function, and then manually identify the latency (ms) and frame rate (fps) data in the game screen, calculate the related data of the latency and frame rate, such as maximum, minimum, average, median, etc. Quantitative data, and then give the conclusion of the function effectiveness.

[0006] The current router game acceleration function test method has the following disadvantages:

[0007] 1. Different test personnel have different subjective feelings of game experience and cannot be quantified, and the test conclusion has a lot of subjectivity, which is difficult to agree and not accurate enough;

[0008] 2. Manual screenshot during the game process is not efficient and difficult to operate, resulting in a small amount of data, and the quantitative data analyzed later cannot effectively support the test conclusion, resulting in an inaccurate test conclusion. SUMMARY

[0009] To solve the problems in the prior art, the application provides an automatic testing method and system for the effectiveness of a router game acceleration function, which can realize quantitative game experience data and effectively support test conclusions; the method is simple to operate, only needs to configure video paths before and after starting the router game acceleration function into a config.ini file, and after one-key execution, video analysis, data analysis and test report generation can be completed, which greatly reduces labor cost and time cost, improves test efficiency, reduces the influence of subjective feelings of testers on test results, and solves the problems in the prior art, i.e., strong subjectivity of manual testing of the router game acceleration function, difficulty in manual test operation, low efficiency, insufficient data samples and inaccurate test results.

[0010] The automatic testing method for the effectiveness of the router game acceleration function provided by the application comprises the following steps:

[0011] Step 1: The test system reads a user configuration file of a tester participating in the test of the effectiveness of the router game acceleration function.

[0012] Step 2: The test system performs frame extraction analysis and parameter statistical processing on game video data before the tester starts the router game acceleration function.

[0013] Step 3: The test system performs frame extraction analysis and parameter statistical processing on game video data after the tester starts the router game acceleration function.

[0014] Step 4: The test system performs combined analysis on the processed data before and after starting the router game acceleration function, classifies and arranges the data, draws a trend chart, writes the arranged data and chart into an Excel table and saves the table, and finally obtains a test report to complete the automatic test.

[0015] The application is further improved, and in the step 2, the following steps are further included,

[0016] Step 201: The test system extracts video frame pictures of the game video data before the tester starts the router game acceleration function according to a frame rate interval set by the user.

[0017] Step 202: The test system completes the cutting of the extracted pictures according to the positions of the game video parameter information to be recognized.

[0018] Step 203: The test system performs image-to-text recognition on the cut pictures to obtain a text list containing multiple game video parameters.

[0019] The application is further improved, and in the step 3, the following steps are further included,

[0020] Step 301: the test system extracts video frame pictures according to the frame rate interval set by the user after the test personnel turn on the router game acceleration function;

[0021] Step 302: the test system completes the cutting of the extracted pictures according to the position of the game video parameter information to be identified;

[0022] Step 303: the test system performs image-to-text recognition on the cut pictures to obtain a text list containing multiple game video parameters.

[0023] The application is further improved, and in the step 1, the user configuration file includes the test personnel name, mobile phone brand and model, video path and name before turning on the router game acceleration function, video path and name after turning on the router game acceleration function, sampling frequency, game time screenshot relative coordinates and frame rate delay relative coordinates.

[0024] The application is further improved, and in the step 1, the user configuration file includes the test personnel name, mobile phone brand and model, video path and name before turning on the router game acceleration function, video path and name after turning on the router game acceleration function, sampling frequency, game time screenshot relative coordinates and frame rate delay relative coordinates.

[0025] The application is further improved, and in the steps 201 and 301, the game video data is extracted according to the frame rate interval set by the user by using the video_to_frames method in the python third-party expansion library OpenCV to return a picture name list.

[0026] The application is further improved, and in the steps 202 and 302, the image_cut method in the python third-party expansion library PIL is used to cut the pictures in the picture name list according to the relative positions of the game time, frame rate and time delay information set by the user, and save the cut pictures.

[0027] The application is further improved, and in the steps 203 and 303, the image_to_text method in the python third-party expansion library pytesseract is used to perform image-to-text recognition on the cut pictures to return a text list containing game time, frame rate and time delay.

[0028] The application is further improved, in the step 4, the python third-party expansion library openpyxl is used to write the sorted data and chart into the Excel table and save, the test report is stored in the form of Excel document, including four workbooks, time delay comparison report, frame rate comparison report, time delay process data comparison before and after opening the router game acceleration function and the original data before and after opening the router game acceleration function.

[0029] The application also provides a test system for the automatic test method of the effectiveness of the router game acceleration function.

[0030] The system main logic control module is used for controlling the operation of the user configuration reading module, the video and image processing module and the data statistical drawing and report generation module.

[0031] The user configuration reading module is used for reading the user configuration file of the tester participating in the test of the effectiveness of the router game acceleration function.

[0032] The video and image processing module is used for extracting the video frame picture according to the frame rate interval set by the user, cutting the extracted picture according to the position of the game video parameter information to be recognized, and carrying out image-to-text recognition on the cut picture to obtain a text list containing multiple game video parameters.

[0033] The data statistical drawing and report generation module is used for merging and analyzing the processed data before and after the opening of the router game acceleration function, classifying and arranging the data, drawing a trend chart, writing the sorted data and chart into the Excel table and saving, obtaining the final test report and completing the automatic test.

[0034] The application has the beneficial effects that: the router game acceleration function effectiveness automatic test method and system provided by the application can extract key frames from game video data before and after starting the router game acceleration function, cut the key frames, identify the game time, frame rate and time delay in the video frame picture through the image-to-text technology, complete data analysis and statistics, generate data statistical report and chart, write into Excel table and save, obtain the final test report, avoid the influence of subjective feeling of the tester on the evaluation result, even if the game experience before and after starting the router game acceleration function is very close, the data and chart in the test report can still reflect the subtle difference, help the tester to obtain the test conclusion, realize the quantification of the game experience data, effectively support the test conclusion, the operation is simple, only needs to configure the video paths before and after starting the router game acceleration function into the config.ini file, one-key execution can complete video analysis, data analysis and test report generation, greatly reduces the labor cost and time cost, improves the test efficiency, reduces the influence of subjective feeling of the tester on the test result, solves the problems of strong subjectivity of the router game acceleration function manual test in the prior art, difficult test operation, low efficiency, insufficient data samples and inaccurate test result. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 The flowchart of the application is a router game acceleration function effectiveness automatic test method;

[0036] Figure 2 The flowchart of the application is a game video data processing flowchart before starting the router game acceleration function;

[0037] Figure 3 The flowchart of the application is a game video data processing flowchart after starting the router game acceleration function;

[0038] Figure 4 The flowchart of the application is the implementation logic of the user configuration reading module;

[0039] Figure 5 The flowchart of the application is the implementation logic of the video and image processing module;

[0040] Figure 6 The flowchart of the application is the implementation logic of the data statistical drawing and report generation module;

[0041] Figure 7 The application is a time delay comparison report workbook, and the acceleration before and after the time delay data are compared and analyzed in the time axis direction;

[0042] Figure 8The acceleration before and after frame rate data in the time axis direction of the time delay comparison report workbook of the application is compared and analyzed. DETAILED DESCRIPTION

[0043] The application will be further described in detail below in combination with the drawings and examples.

[0044] Please refer to Figures 1-6 The application relates to a router game acceleration function effectiveness automatic test method, which comprises the following steps.

[0045] Step 1: a test system reads a user configuration file of a test personnel participating in router game acceleration function effectiveness test; wherein, a configuration file config.ini file path imported from setting.py is read by using a GetValue method through a Python language to realize information acquisition in the user configuration file; the user configuration file read includes a test personnel name, a mobile phone brand and model, a video path and name before starting the router game acceleration function, a video path and name after starting the router game acceleration function, a sampling frequency, a game time screenshot relative coordinate and a frame rate delay relative coordinate.

[0046] Step 2: the test system carries out frame analysis and parameter statistical processing on game video data before the test personnel starts the router game acceleration function.

[0047] Step 3: the test system carries out frame analysis and parameter statistical processing on game video data after the test personnel starts the router game acceleration function.

[0048] Step 4: the test system carries out combined analysis on the processed data before and after the router game acceleration function is started, classifies and arranges and draws a trend chart, writes the arranged data and chart into an Excel table and saves, obtains a final test report, and completes the automatic test; wherein, the arranged data and chart are written into the Excel table and saved by using a python third-party extension library openpyxl, the test report is stored in the form of an Excel document, includes four workbooks, a time delay comparison report, a frame rate comparison report, a time delay process data comparison before and after the router game acceleration function is started, and original data before and after the router game acceleration function is started.

[0049] Please refer to Figure 2 In the step 2, the following steps are further included,

[0050] Step 201: The test system extracts video frame pictures from game video data before the test personnel turns on the router game acceleration function according to the frame rate interval set by the user; wherein the video_to_frames method in the OpenCV third-party expansion library of python is used to extract video frame pictures from game video data according to the frame rate interval set by the user, and a picture name list is returned.

[0051] Step 202: The test system completes the cutting of the extracted pictures according to the position of the game video parameter information to be recognized; wherein the image_cut method in the PIL third-party expansion library of python is used to cut the pictures in the picture name list according to the relative position of the game time, frame rate and time delay information set by the user, and save the pictures after cutting.

[0052] Step 203: The test system performs image-to-text recognition on the cut pictures to obtain a text list containing multiple game video parameters; wherein the image_to_text method in the pytesseract third-party expansion library of python is used to perform image-to-text recognition on the cut pictures, and a text list containing game time, frame rate and time delay is returned.

[0053] Please refer to Figure 3 In step 3, the following steps are further included,

[0054] Step 301: The test system extracts video frame pictures from game video data after the test personnel turns on the router game acceleration function according to the frame rate interval set by the user; wherein the video_to_frames method in the OpenCV third-party expansion library of python is used to extract video frame pictures from game video data according to the frame rate interval set by the user, and a picture name list is returned.

[0055] Step 302: The test system completes the cutting of the extracted pictures according to the position of the game video parameter information to be recognized; wherein the image_cut method in the PIL third-party expansion library of python is used to cut the pictures in the picture name list according to the relative position of the game time, frame rate and time delay information set by the user, and save the pictures after cutting.

[0056] Step 303: The test system performs image-to-text recognition on the cut pictures to obtain a text list containing multiple game video parameters; wherein the image_to_text method in the pytesseract third-party expansion library of python is used to perform image-to-text recognition on the cut pictures, and a text list containing game time, frame rate and time delay is returned.

[0057] Please refer toFigures 4-6 The application further provides a test system for the automatic test method of the router game acceleration function effectiveness.

[0058] A system main logic control module is configured to control the user configuration reading module, the video and image processing module, and the data statistics drawing and report generation module.

[0059] The user configuration reading module is configured to read the user configuration file of the tester participating in the router game acceleration function effectiveness test. In this embodiment, the implementation logic is shown in FIG. 2, wherein a Config class is defined to read the user configuration information; and the path of the config.ini file is imported from setting.py, and the tester name, mobile phone brand and model, video path and name before the router game acceleration function is turned on, video path and name after the router game acceleration function is turned on, sampling frequency, game time screenshot relative coordinates and frame rate delay relative coordinates are obtained through the GetValue method. Figure 4 The video and image processing module is configured to extract video frame pictures according to the frame rate interval set by the user, to crop the extracted pictures according to the position of the game video parameter information to be recognized, and to perform image-to-text recognition on the cropped pictures to obtain a text list containing multiple game video parameters. In this embodiment, the implementation logic is shown in FIG. 3, wherein an OCR class is defined to implement the processing of video images; the video_to_frames method in the class is used to convert the game video recording into pictures according to the sampling frequency set by the user, and return a picture name list; the image_cut method in the class is used to crop the pictures generated above according to the relative positions of the game time, frame rate and time delay information set by the user, and save the pictures; and the image_to_text method in the class is used to perform OCR (image-to-text) recognition on the cropped pictures, and return a text list containing the game time, frame rate and time delay.

[0060] Figure 5 The data statistics drawing and report generation module is configured to merge and analyze the processed data before and after the router game acceleration function is turned on, classify and arrange the data, draw a trend chart, write the arranged data and chart into an Excel table and save the data, and obtain a final test report to complete the automatic test.

[0061] In this embodiment, the implementation logic is shown in FIG. 4, wherein a Report class is defined to implement the drawing of the trend chart and the generation of the final test report; the draw_trend_chart method in the class is used to draw the trend chart according to the data before and after the router game acceleration function is turned on; and the generate_report method in the class is used to generate the final test report according to the trend chart.

[0062] In this embodiment, the implementation logic is shown in FIG. 4, wherein a Report class is defined to implement the drawing of the trend chart and the generation of the final test report; the draw_trend_chart method in the class is used to draw the trend chart according to the data before and after the router game acceleration function is turned on; and the generate_report method in the class is used to generate the final test report according to the trend chart. Figure 6 ​As shown, first define the Report class, which is used to implement the writing of the processed text list into an Excel table, and realize the solidification of data; the test report is stored in the form of an Excel document, including four workbooks, one is the time delay comparison report, which is used for comparison of time delay data before and after game acceleration; two is the frame rate comparison report, which is used for comparison of frame rate data before and after game acceleration; three is the comparison of time delay process data before and after game acceleration, which is more statistical and more accurate than the first workbook; four is the original data before and after game acceleration.

[0063] Among them, 1. Time delay comparison report workbook includes the following parts:

[0064] ① Time delay classification definition

[0065]

[0066] ② Acceleration before and after sampling data statistics

[0067]

[0068] ③ Acceleration before time delay statistics

[0069]

[0070] ④ Acceleration before network quality statistics

[0071]

[0072] ⑤ Acceleration before and after time delay data comparison analysis chart in time axis direction, as shown in Figure 7 .

[0073] 2. Frame rate comparison report workbook includes the following parts:

[0074] ① Frame rate classification definition (FPS)

[0075]

[0076] ② Acceleration before and after sampling data statistics

[0077]

[0078] ③ Acceleration before and after frame rate statistics

[0079]

[0080] ④ Acceleration before and after frame rate quality evaluation

[0081]

[0082] ⑤ Acceleration before and after frame rate data comparison analysis table in time axis direction, as shown in Figure 8 .

[0083] 3. The game acceleration before and after the time delay process data detailed comparison workbook includes the following parts:

[0084] ① Network quality statistics before and after acceleration (accurate)

[0085]

[0086] 4. The original data workbook before and after acceleration includes the following parts:

[0087] ① Original data table before and after acceleration

[0088]

[0089] In the embodiment, the test system is mainly written in Python language, the third-party expansion library OpenCV of python is used for parsing game video into images, the third-party expansion library PIL of python is used for image cropping, the third-party expansion library pytesseract of python is used for recognizing data information in the chart as text, the third-party expansion library pytesseract of python is used for generating a chart from the extracted data, and the Excel document reading and writing technology is used for reading and writing the excel table data.

[0090] As can be seen from the above, the present application has the following advantages: the present application provides a router game acceleration function effectiveness automatic test method and system, which can extract key frames from game video data before and after starting the router game acceleration function, crop the key frames, recognize the game time, frame rate and time delay in the video frame picture through image-to-text technology, complete data analysis and statistics, generate a data statistics report and a chart, write the chart into an Excel table and save, and obtain a final test report, thereby avoiding the influence of subjective feelings of the test personnel on the evaluation results, even if the game experience before and after starting the router game acceleration function is very close, the data and chart in the test report can still reflect the subtle differences, helping the test personnel to draw a test conclusion, the game experience data can be quantified, the test conclusion can be effectively supported, the operation is simple, the video paths before and after starting the router game acceleration function only need to be configured into a config.ini file, after one-key execution, video analysis, data analysis and test report generation can be completed, the labor cost and time cost are greatly reduced, the test efficiency is improved, the influence of subjective feelings of the test personnel on the test results is reduced, and the problems of strong subjectivity of manual test of the router game acceleration function in the prior art, difficulty in test conclusion, difficulty in manual test operation, low efficiency, insufficient data samples and inaccurate test results are solved.

[0091] The above described embodiments are the preferred embodiments of the present application, and are not intended to limit the specific implementation of the present application. The scope of the present application includes, but is not limited to, the above described embodiments. Any equivalent changes made in accordance with the present application are within the scope of the present application.

Claims

1. A method for automated testing of router game acceleration function effectiveness, characterized in that, Comprising the following steps, Step 1: the test system reads the user profile of the router game acceleration function effectiveness tester, and the read user profile includes the tester's name, mobile phone brand and model, video path and name before turning on the router game acceleration function, video path and name after turning on the router game acceleration function, sampling frequency, game time screenshot relative coordinates and frame rate delay relative coordinates; Step 2: the test system performs frame extraction analysis and parameter statistical processing on the game video data before the tester turns on the router game acceleration function; Step 3: the test system performs frame extraction analysis and parameter statistical processing on the game video data after the tester turns on the router game acceleration function; Step 4: the test system merges and analyzes the processed data before and after turning on the router game acceleration function, classifies and arranges and draws a trend chart, writes the arranged data and chart into an Excel table and saves, and obtains the final test report to complete the automatic test.

2. The method of claim 1, wherein the router game acceleration function effectiveness automated testing method is characterized by, In the step 2, further comprising the following steps, Step 201: the test system extracts video frame pictures according to the frame rate interval set by the user from the game video data before the tester turns on the router game acceleration function; Step 202: the test system completes the cutting of the extracted pictures according to the position of the game video parameter information to be recognized; Step 203: the test system performs image-to-text recognition on the cut pictures to obtain a text list containing multiple game video parameters.

3. The method of claim 2, wherein the router game acceleration function effectiveness is automatically tested by, In the step 3, further comprising the following steps, Step 301: the test system extracts video frame pictures according to the frame rate interval set by the user from the game video data after the tester turns on the router game acceleration function; Step 302: the test system completes the cutting of the extracted pictures according to the position of the game video parameter information to be recognized; Step 303: the test system performs image-to-text recognition on the cut pictures to obtain a text list containing multiple game video parameters.

4. The method of claim 3, wherein: In the step 1, the GetValue method is used to read the config.ini file path imported from the setting.py configuration file by using Python language, so as to realize the acquisition of information in the user profile.

5. The automated testing method for the effectiveness of router game acceleration function as described in claim 4, characterized in that: In the steps 201 and 301, the video_to_frames method in the OpenCV third-party extension library of python is used to extract video frame pictures according to the frame rate interval set by the user from the game video data, and a picture name list is returned.

6. The method of claim 5, wherein: the router game acceleration function effectiveness automated testing method is characterized by: In the steps 202 and 302, the image_cut method in the PIL third-party extension library of python is used to cut the pictures in the picture name list according to the relative positions of the game time, frame rate and delay information set by the user, and save the cut pictures.

7. The automated testing method for the effectiveness of router game acceleration function as described in claim 6, characterized in that: In the step 203 and the step 303, the image_to_text method in the python third-party extension library pytesseract is used for image-to-text recognition of the cropped picture, and a text list containing game time, frame rate and time delay is returned.

8. The automated testing method for the effectiveness of router game acceleration function as described in claim 7, characterized in that: In the step 4, the data and charts are written into an Excel table and saved by using the python third-party extension library openpyxl, and the test report is stored in the form of an Excel document, including four workbooks, a time delay comparison report, a frame rate comparison report, a comparison of time delay process data before and after the game acceleration function of the router is started, and original data before and after the game acceleration function of the router is started.

9. A test system for implementing the method of claim 1-8 for automating the testing of the effectiveness of the router game acceleration function, characterized in that, Comprise: A system main logic control module for controlling the user configuration reading module, the video and image processing module, the data statistical drawing and report generation module to run; A user configuration reading module for reading the user configuration file of the tester participating in the router game acceleration function effectiveness test; A video and image processing module for extracting video frame pictures according to the frame rate interval set by the user, for completing the cropping of the extracted pictures according to the position of the game video parameter information to be recognized, and for performing image-to-text recognition on the cropped pictures to obtain a text list containing multiple game video parameters; A data statistical drawing and report generation module for merging and analyzing the processed data before and after the router game acceleration function is started, classifying and arranging, drawing trend charts, writing the arranged data and charts into an Excel table and saving, and obtaining the final test report to complete the automatic test.

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