Method and device for determining starting time of in-vehicle infotainment application, test system and equipment

Abstract

The invention discloses a method and a device for determining the starting time of an in-vehicle infotainment application, and a test system and equipment. The method comprises the following steps: acquiring a reference image after the starting of a target application is completed; under the condition that a starting instruction of a target application is received, obtaining a starting frame identifier of the target application based on a recording frame of a screen recording current moment; obtaining an ending frame identifier of starting completion of the target program based on the sequence of video frames recorded on the screen and the reference image; and determining the starting time of the target application based on the starting frame identifier, the ending frame identifier, the recording duration of screen recording and the total number of recording frames. Therefore, according to the method, the starting frame identifier of the target application and the ending frame identifier after starting are obtained through screen recording, and the starting time of the target application is determined in combination with the recording duration and the total recording frame number of screen recording, so that automatic testing of the starting time of the vehicle-mounted terminal application is realized, and the testing precision of the starting time is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle computer applications, and in particular to a method for determining a vehicle computer application startup time, a device for determining a vehicle computer application startup time, a system for testing a vehicle computer application startup time, a computer-readable storage medium, and a terminal device. Background Art

[0002] With the development of intelligent vehicles, people's demand for car computers has not only stopped at early audio playback and navigation, but also has been widely pursued for intelligent and information-based car computer equipment. For example, 360-degree panoramic view, online music, real-time traffic conditions, online movies and TV, APP Store and other applications are essential for car computers. In order to meet user experience, performance parameters such as cold / hot start time and page switching time of car computer applications also need to meet certain indicators. Summary of the invention

[0003] One of the purposes of the present invention is to propose a method for determining the startup time of a vehicle-mounted application. The startup frame identifier of the target application obtained by screen recording and the end frame identifier of the startup completion are combined with the recording duration and the total number of recording frames of the screen recording to determine the startup time of the target application, thereby realizing automated testing of the startup time of the vehicle-mounted application and improving the testing accuracy of the startup time. The second purpose is to propose a device for determining the startup time of a vehicle-mounted application. The third purpose is to propose a testing system for the startup time of a vehicle-mounted application. The fourth purpose is to propose a computer-readable storage medium. The fifth purpose is to propose a terminal device.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0005] A method for determining the startup time of a vehicle computer application, the method comprising: obtaining a reference image after the target application is started; upon receiving a startup instruction of the target application, obtaining a startup frame identifier of the target application based on a recording frame of a screen recording at a current moment; obtaining an end frame identifier of the target program startup completion based on a video frame sequence of the screen recording and the reference image; and determining the startup time of the target application based on the startup frame identifier, the end frame identifier, the recording duration of the screen recording, and the total number of recorded frames.

[0006] According to the above technical means, first obtain the reference image after the target application is started, and when the start instruction of the target application is received, obtain the start frame identifier of the target application based on the recording frame of the current moment of the screen recording, and obtain the end frame identifier of the target program after the start is completed based on the video frame sequence of the screen recording and the reference image, and then determine the start time of the target application based on the start frame identifier, the end frame identifier, the recording duration of the screen recording and the total number of recorded frames. Thus, the method determines the start time of the target application by obtaining the start frame identifier of the target application through screen recording, the end frame identifier of the start completion, and combining the recording duration of the screen recording and the total number of recorded frames, thereby realizing the automated test of the start time of the vehicle computer application and improving the test accuracy of the start time.

[0007] Furthermore, the startup time of the target application is determined based on the startup frame identifier, the end frame identifier, the recording duration of the screen recording and the total number of recorded frames, including: obtaining the identifier difference between the startup frame identifier and the end frame identifier; obtaining the ratio between the identifier difference and the total number of recorded frames; and determining the startup time of the target application based on the product of the ratio and the recording duration.

[0008] Furthermore, an end frame identifier of the completion of the startup of the target program is obtained based on the video frame sequence of the screen recording and the benchmark image, including: matching the current frame image with the benchmark image based on a feature point matching algorithm to obtain a target matching feature point pair; calculating the homography transformation matrix of the current frame image and the benchmark image based on the target matching feature point pair; calculating the similarity between the current frame image and the benchmark image based on the homography transformation matrix; and when the similarity is greater than or equal to a preset similarity threshold, using the identifier of the current frame image as the end identifier of the completion of the startup of the target program.

[0009] Furthermore, the current frame image is matched with the reference image based on a feature point matching algorithm to obtain a target matching feature point pair, including: grayscale processing of the reference image, and extracting a first feature point set of the grayscaled reference image based on a feature point matching algorithm; grayscale processing of the current frame image, and extracting a second feature point set of the grayscaled current frame image based on a feature point matching algorithm; performing K-nearest neighbor matching on the first feature point set and the second feature point set to obtain a matching feature point pair; and filtering the matching feature point pairs based on a random sampling consistency algorithm to obtain a target matching feature point pair.

[0010] Furthermore, the similarity between the current frame image and the reference image is calculated based on the homography transformation matrix, including: mapping the current frame image to the plane where the reference image is located based on the homography matrix; performing mask processing on the mapped current frame image based on the reference image; and calculating the similarity between the current frame image after mask processing and the reference image.

[0011] Furthermore, the method for determining the startup time of a vehicle computer application also includes: determining the startup time of multiple startups of the target application by means of loop recording and asynchronous data processing; and determining a startup time test result of the target application based on an average value of the startup time of multiple startups and a preset threshold.

[0012] A device for determining the startup time of a vehicle-mounted application, the device comprising: a first acquisition module, used to acquire a reference image after the target application is started; a second acquisition module, used to acquire a startup frame identifier of the target application based on a recording frame of a screen recording at a current moment when a startup instruction of the target application is received; a third acquisition module, used to acquire an end frame identifier of the completion of the startup of the target program based on a video frame sequence of the screen recording and the reference image; and a determination module, used to determine the startup time of the target application based on the startup frame identifier, the end frame identifier, the recording duration of the screen recording and the total number of recorded frames.

[0013] According to the above technical means, the first acquisition module acquires the reference image after the target application is started, the second acquisition module acquires the start frame identifier of the target application based on the recording frame of the current screen recording when receiving the start instruction of the target application, the third acquisition module acquires the end frame identifier of the target program after the start is completed based on the video frame sequence of the screen recording and the reference image, and the determination module determines the start time of the target application based on the start frame identifier, the end frame identifier, the recording duration of the screen recording and the total number of recorded frames. Thus, the device determines the start time of the target application by obtaining the start frame identifier of the target application through the screen recording, the end frame identifier of the start completion, and combining the recording duration of the screen recording and the total number of recorded frames, so as to realize the automated test of the start time of the vehicle computer application and improve the test accuracy of the start time.

[0014] A system for testing the startup time of a vehicle-machine application comprises: a host computer, a vehicle-machine device, a vehicle-machine display screen and a programmable high-speed camera, wherein the host computer is connected to the programmable high-speed camera via an interface, and the host computer is configured to execute the above-mentioned method for determining the startup time of the vehicle-machine application.

[0015] According to the above technical means, the host computer is connected to the programmable high-speed camera through an interface, and the host computer executes the above method for determining the startup time of the vehicle computer application. Based on the above method for determining the startup time of the vehicle computer application, the startup frame identifier of the target application and the end frame identifier of the startup completion are obtained through screen recording, and the startup time of the target application is determined in combination with the recording duration and the total number of recording frames of the screen recording, so as to realize the automated test of the startup time of the vehicle computer application and improve the test accuracy of the startup time.

[0016] A computer-readable storage medium stores a program for determining the startup time of a vehicle-machine application. When the program for determining the startup time of a vehicle-machine application is executed by a processor, the method for determining the startup time of a vehicle-machine application is implemented.

[0017] According to the above-mentioned technical means, when the program for determining the startup time of the vehicle-computer application is executed by the processor, the above-mentioned method for determining the startup time of the vehicle-computer application is implemented. Based on the above-mentioned method for determining the startup time of the vehicle-computer application, the startup frame identifier of the target application obtained by screen recording and the end frame identifier of the startup completion are combined with the recording duration and the total number of recording frames of the screen recording to determine the startup time of the target application, thereby realizing automated testing of the startup time of the vehicle-computer application and improving the test accuracy of the startup time.

[0018] A terminal device includes a memory, a processor, and a vehicle application startup time determination program stored in the memory and executable on the processor. When the processor executes the vehicle application startup time determination program, the vehicle application startup time determination method described above is implemented.

[0019] According to the above-mentioned technical means, when the processor executes the program for determining the startup time of the vehicle-computer application, the above-mentioned method for determining the startup time of the vehicle-computer application is implemented. Based on the above-mentioned method for determining the startup time of the vehicle-computer application, the startup frame identifier of the target application obtained through screen recording and the end frame identifier of the startup completion are combined with the recording duration and the total number of recording frames of the screen recording to determine the startup time of the target application, thereby realizing automated testing of the startup time of the vehicle-computer application and improving the test accuracy of the startup time.

[0020] Beneficial effects of the present invention:

[0021] (1) The present invention obtains the start frame identifier of the target application and the end frame identifier of the start completion through screen recording, and determines the start time of the target application in combination with the recording duration and the total number of recorded frames of the screen recording, thereby realizing an automated test of the start time of the vehicle computer application and improving the test accuracy of the start time;

[0022] (2) The present invention matches the current frame image with the reference image based on a feature point matching algorithm, and can cope with matching failures caused by scene changes such as device screen movement, rotation, or lighting changes. At the same time, the image similarity is calculated based on the image after homography transformation. A unified threshold can be set for different applications to cope with the conceptual error that the feature point matching algorithm similarity only calculates point domain similarity rather than image similarity, thereby avoiding the conceptual error that may cause the program to believe that the match is successful but is actually not the reference image.

[0023] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flow chart of a method for determining a vehicle machine application startup time according to an embodiment of the present invention;

[0025] Figure 2 A connection diagram of a system for testing the startup time of a vehicle-mounted computer application according to an embodiment of the present invention;

[0026] Figure 3 A flowchart of obtaining a reference image according to an embodiment of the present invention;

[0027] Figure 4 A flowchart of starting video recording for an application according to an embodiment of the present invention;

[0028] Figure 5 A flowchart for obtaining an end frame identifier of application startup completion according to an embodiment of the present invention;

[0029] Figure 6 This is a flow chart of automatic testing of application startup time according to an embodiment of the present invention;

[0030] Figure 7 It is a flowchart of a method for determining the startup time of a vehicle machine application according to a specific embodiment of the present invention;

[0031] Figure 8 A connection diagram of a device for determining a vehicle machine application startup time according to an embodiment of the present invention;

[0032] Fig. 9 FIG. 4 is a block diagram of a terminal device according to an embodiment of the present invention.

[0033] Among them, 10 is a host computer; 20 is a vehicle equipment; 30 is a vehicle display screen; 40 is a programmable high-speed camera; 50 is a first acquisition module; 60 is a second acquisition module; 70 is a third acquisition module; 80 is a determination module; 100 is a terminal device; 110 is a memory; and 120 is a processor. DETAILED DESCRIPTION

[0034] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0035] The following describes, with reference to the accompanying drawings, a method for determining a vehicle application startup time, a device for determining a vehicle application startup time, a system for testing a vehicle application startup time, a computer-readable storage medium, and a terminal device proposed in embodiments of the present invention.

[0036] Figure 1 The figure is a flow chart of a method for determining a vehicle machine application startup time according to an embodiment of the present invention.

[0037] The method for determining the startup time of the vehicle machine application can be Figure 2 The test system implementation shown includes a host computer 10, a vehicle device 20, a vehicle display screen 30 and a programmable high-speed camera 40, wherein the host computer 10 is connected to the programmable high-speed camera 40 through an interface, the vehicle device 20 is used to control the application startup based on the received control instruction, and display it through the vehicle display screen 30, the programmable high-speed camera 40 is used to obtain the image displayed on the vehicle display screen 30, and the host computer 10 executes the method for determining the startup time of the vehicle application based on the image information obtained by the programmable high-speed camera 40 and the application startup instruction.

[0038] The method for determining the vehicle machine application startup time of the present invention is described in detail below with reference to the accompanying drawings.

[0039] like Figure 1 As shown, the method for determining the startup time of a vehicle-mounted computer application according to an embodiment of the present invention may include:

[0040] S1, obtaining a reference image after the target application is started;

[0041] S2, when receiving a start instruction of the target application, obtaining a start frame identifier of the target application based on a recording frame of the screen recording at the current moment;

[0042] S3, obtaining an end frame identifier of the target program startup completion based on the video frame sequence of the screen recording and the reference image;

[0043] S4, determining the start time of the target application based on the start frame identifier, the end frame identifier, the recording duration of the screen recording, and the total number of recorded frames.

[0044] Specifically, the startup instruction of the target application is a control action instruction for the target application, which can be an instruction to control the application to start running, or a page switching instruction, a function click instruction, etc., so as to be applied to automated performance tests such as the startup time, page switching time, and response delay time of the start of running. For example, when the startup instruction is an instruction to start working, the reference image is the image when the target application starts working and the startup is completed; when the startup instruction is a page switching instruction, the reference image is the image when the target application page switches to the target page.

[0045] The following describes in detail the method for determining the startup time of the vehicle computer application of the present invention by taking the startup instruction as a control instruction for controlling the target application to start running as an example.

[0046] The criterion for judging whether the application is fully started is that the last element page of the application is loaded. The actual completion of the startup needs to be determined according to the product design form. The benchmark image needs to select a characteristic area, which can be determined based on the target application to determine whether the target application has been fully started. That is, when the benchmark image appears for the first time in the target application, it is considered that the application is fully started, that is, the startup display interface of the current time and version application is obtained, which is not affected by changes in the vehicle version, UI resource replacement and time.

[0047] Specifically, before the test, the target application is started and controlled. After the target application is fully started, the reference image is obtained by calibrating the ROI (Region of Interest). The ROI refers to a specific area selected from the image, which is the focus of image analysis. By delineating the ROI, further image processing or analysis can be performed, thereby improving processing efficiency and reducing the amount of calculation.

[0048] by Figure 3 For example, the method for obtaining the benchmark image of the target application is as follows:

[0049] S101, read the configuration file. The configuration file is used to determine the ROI area for evaluating whether the target application is fully started, and may include parameters such as the position and size of the ROI area. The configuration file needs to include the reference ROI area under different conditions to handle the changes in the ROI area of ​​the judgment standard due to prior conditions or software design changes of different applications, such as whether the application is connected to the network, whether a USB flash drive is inserted, whether Bluetooth is connected, etc.

[0050] Among them, for the case where the baseline page is the same every time most applications are started, it is necessary to determine the full startup time of the application according to the product design form for different applications. For example, navigation needs to wait for the GPS (Global Positioning System) positioning update to be completed, and Bluetooth phone needs to wait for the communication record synchronization to be completed, etc., and the ROI area where the page is last loaded is written into the configuration file.

[0051] For some applications, the baseline page is inconsistent each time it is launched, such as real-time updated weather, recommended playlists for online music, etc., these applications need to limit the update time of the cloud interface or configure the return value to a fixed value. In addition, the application code can be modified to display a fixed page, and then the fixed page ROI area can be selected and written into the configuration file.

[0052] S102, ADB (Android Debug Bridge) starts the application.

[0053] S103, capturing an image after the application is started by using an adb screenshot command.

[0054] S104, cropping the ROI area according to the configuration file, that is, cropping the image.

[0055] S105: Acquire a reference image.

[0056] Then, after acquiring the reference image, the host PC sends the startup command of the target application and obtains the ID of the current frame of the camera at the same time, which can be directly used as the startup frame ID. The interaction between the host PC and the camera is based on the interface provided by the programmable camera. After testing, the time error from the PC sending the command to the device executing the command does not exceed 5ms.

[0057] Specifically, combined Figure 4 As shown, the host computer reads the configuration file, which must include the application startup, shutdown and exit methods, which is used to ensure the application startup preconditions. For example, before measuring the cold start, the application must be exited or killed to ensure that the application is opened for the first time. When measuring the hot start, only the application is closed to ensure that the application is still running in the background.

[0058] When the host computer receives the start instruction of the target application, the host computer controls the programmable high-speed camera to start, so as to record the screen of the vehicle computer through the programmable high-speed camera. It should be noted that the start of the target application can be achieved through ADB commands, and for the Android system, the application can be directly pulled up through the package name and its Main.Activity, or the application can be started by simulating a click, and there is no specific restriction.

[0059] When controlling the camera to start recording the vehicle display screen, an ID number is assigned to each frame acquired by the camera in the order of the video stream as a name. The file name is also stored according to this rule, and the frame sequence is obtained by storing by frame. In addition, in order to ensure the complete recording of the video started by the application, it is necessary to start the high-speed camera in advance to start recording. When executing the ADB command to start the target application, the ID of the frame currently being recorded by the camera is recorded as the startup frame IDS of the target application, that is, the startup frame identifier.

[0060] In addition, the data transmission link between the camera and the host PC is the high-speed camera buffer area -> PC buffer area -> PC physical storage area. Affected by the transmission speed and write speed, adding a stack buffer in the host PC can reduce the pressure on the camera buffer. In addition, it can also reduce the recording time and appropriately reduce the image resolution. Multiple groups of application startup time tests are required, so the video recording process and the data processing process are separated, and the subsequent data processing process can be performed in multiple threads.

[0061] Then, the video frame encoding sequence is compared with the reference image to find the first frame that reaches the matching threshold with the reference image, and the video frame ID is used as the end frame identifier of the target program startup completion. Among them, searching in sequence can avoid the situation where the startup time of the same application changes at different times due to network fluctuations or application optimization.

[0062] Finally, the startup time of the target application is calculated based on the startup frame identifier, the end frame identifier, the recording duration of the screen recording, and the total number of recorded frames to achieve automated testing of the startup implementation.

[0063] In one embodiment of the present invention, an end frame identifier of the completion of the startup of a target program is obtained based on a video frame sequence of screen recording and a reference image, including: matching a current frame image with a reference image based on a feature point matching algorithm to obtain a target matching feature point pair; calculating a homography transformation matrix of the current frame image and the reference image based on the target matching feature point pair; calculating the similarity between the current frame image and the reference image based on the homography transformation matrix; and when the similarity is greater than or equal to a preset similarity threshold, using the identifier of the current frame image as the end identifier of the completion of the startup of the target program.

[0064] Specifically, combined Figure 5 As shown, since the device screen and high-speed camera are not necessarily completely fixed - small-scale displacement, rotation or scale changes may occur during other tests, and the automated test system is not necessarily completely masked - it may be affected by changes in illumination, a feature point matching algorithm such as SIFT (Scale Invariant Feature Transform) is used to match the current frame image with the reference image to avoid the above effects and obtain the target matching feature point pair. In addition, in the actual execution process, other faster algorithms such as SURF (Speeded Up Robust Features) can also be used. If there is no scale change, FAST (Features from Accelerated Segment Test) can also be used.

[0065] Taking the SIFT algorithm as an example of the feature point matching algorithm, the locally stored frame sequence is loaded in order and processed one by one. The current frame image imgi is matched with the reference image img0 using the SIFT algorithm to obtain the target matching feature point pair. Then, the homography transformation matrix H of img0 and img_i is calculated based on the screened matching point pairs. The similarity th_i between the current frame image img_i and the reference image img0 is calculated based on the homography transformation matrix H. If the similarity th_i is greater than or equal to the preset similarity threshold th, the current frame ID is recorded as the end identifier of the completion of the startup of the target program; otherwise, i+1 is added, and the above steps are returned to continue until the calculated similarity thi is greater than or equal to the preset similarity threshold th, and the end identifier of the completion of the startup of the target program is obtained.

[0066] This embodiment matches the current frame image with the reference image based on a feature point matching algorithm, and can cope with matching failures caused by scene changes such as device screen movement, rotation, or lighting changes. At the same time, image similarity is calculated based on the image after homography transformation. A unified threshold can be set for different applications to cope with the conceptual error that the feature point matching algorithm similarity only calculates point domain similarity rather than image similarity, thereby avoiding the conceptual error that may cause the program to believe that the match is successful but is actually not the reference image.

[0067] In one embodiment of the present invention, the current frame image is matched with the reference image based on a feature point matching algorithm to obtain a target matching feature point pair, including: grayscale processing of the reference image, and extracting a first feature point set of the grayscaled reference image based on the feature point matching algorithm; grayscale processing of the current frame image, and extracting a second feature point set of the grayscaled current frame image based on the feature point matching algorithm; performing K-nearest neighbor matching on the first feature point set and the second feature point set to obtain a matching feature point pair; filtering the matching feature point pairs based on a random sampling consistency algorithm to obtain a target matching feature point pair.

[0068] Specifically, first convert the reference image img0 into a grayscale image, use the SIFT algorithm to extract all its feature points kp0 and calculate its descriptor desc0 to obtain the first feature point set of the reference image. Then convert the i-th frame image img_i of the sequence into a grayscale image, use the SIFT algorithm to extract all its feature points kp_i and calculate its descriptor desc_i to obtain the second feature point set of the current frame image. Among them, i starts from 0. Then perform k-nearest neighbor matching on desc0 and desc_i to obtain the most similar description of each descriptor, and calculate the matching feature point pairs based on the matching descriptors. Finally, perform the RANSAC (Random Sample Consensus) screening algorithm on the matched feature point pairs to filter out the matching point pairs that are not on the same projection plane to obtain the target matching feature point pairs.

[0069] In one embodiment of the present invention, the similarity between the current frame image and the reference image is calculated based on the homography transformation matrix, including: mapping the current frame image to the plane where the reference image is located based on the homography matrix; performing mask processing on the mapped current frame image based on the reference image; and calculating the similarity between the current frame image after mask processing and the reference image.

[0070] Specifically, after calculating the homography transformation matrix H of img0 and img_i based on the screened matching point pairs, img_i is mapped to the plane where img0 is located according to the homography matrix H to obtain img_trans_i. Then, img_trans_i is masked with img0 to remove the extra area captured by the camera, and the similarity th_i between img_trans_i and the reference image img0 is calculated.

[0071] In one embodiment of the present invention, the startup time of the target application is determined based on the startup frame identifier, the end frame identifier, the recording duration of the screen recording and the total number of recorded frames, including: obtaining the identifier difference between the startup frame identifier and the end frame identifier; obtaining the ratio between the identifier difference and the total number of recorded frames; and determining the startup time of the target application based on the product of the ratio and the recording duration.

[0072] Specifically, the calculation formula for the startup time of the target application is:

[0073]

[0074] Wherein, t is the startup time of the target application (in ms); T is the recording time of the camera (in ms), which means the total time from the start of recording to the end of recording, which is read from the configuration file and determined by T=bT+cT, where cT represents the estimated startup time of the application, and bT is a general value, which is estimated based on the performance of the current vehicle computer version and the network status; IDE is the end frame identifier, IDS is the startup frame identifier, and n is the total number of recorded frames.

[0075] In one embodiment of the present invention, the method for determining the startup time of a vehicle computer application also includes: determining the startup time of multiple startups of the target application by means of loop recording and asynchronous data processing; and determining the startup time test result of the target application based on the average startup time of multiple startups and a preset threshold.

[0076] That is to say, in addition to the above calculation of the single startup time of a single application, you can also start a single application multiple times to get the average startup time through loop recording and asynchronous data processing. By adding the application to be tested in the configuration file, you can start different applications in the program to test their average cold / hot startup time and output the test results. The program uses data processing scripts to count and process the test results and directly output the startup test report. For example, Figure 6 As shown, the following steps may be included:

[0077] S201, read application configuration file.

[0078] S202, acquiring a reference image.

[0079] S203, start the height camera and start the application to be tested.

[0080] S204, acquiring a frame sequence.

[0081] S205: Calculate the startup time of the application to be tested.

[0082] S206, determine whether the startup times limit of the application to be tested is reached. If yes, determine that the test is completed and execute step S207. If no, execute step S203, execute the application startup action again, and obtain the next startup time.

[0083] S207, outputting the average test result of the application to be tested.

[0084] S208, determine whether all application tests are completed. If yes, execute step S209; if no, execute step S201 to continue to execute multiple startup tests on the next application.

[0085] S209, data processing script.

[0086] S210, outputting all application test reports.

[0087] As a specific embodiment of the present invention, Figure 7 As shown, the method for determining the vehicle machine application startup time may include the following steps:

[0088] S301, obtaining a reference image after the target application is started.

[0089] S302, grayscale processing is performed on the reference image, and a first feature point set of the grayscale reference image is extracted based on a feature point matching algorithm. Step S305 is executed.

[0090] S303: upon receiving a start instruction of the target application, obtaining a start frame identifier of the target application based on a recording frame of the screen recording at the current moment.

[0091] S304, grayscale processing is performed on the current frame image, and a second feature point set of the grayscaled current frame image is extracted based on a feature point matching algorithm.

[0092] S305 , performing K-nearest neighbor matching on the first feature point set and the second feature point set to obtain matching feature point pairs.

[0093] S306, filtering the matched feature point pairs based on the random sampling consistency algorithm to obtain target matching feature point pairs.

[0094] S307, calculating the homography transformation matrix of the current frame image and the reference image according to the target matching feature point pairs.

[0095] S308 , mapping the current frame image to the plane where the reference image is located based on the homography matrix.

[0096] S309: performing mask processing on the mapped current frame image based on the reference image.

[0097] S310, calculating the similarity between the current frame image after mask processing and the reference image.

[0098] S311, determine whether the similarity is greater than or equal to a preset similarity threshold. If yes, execute step S312; if not, select the next frame image as the current frame image in sequence, and continue to execute step S304.

[0099] S312: Using the identifier of the current frame image as the end identifier of the completion of starting the target program.

[0100] S313, obtaining an identifier difference between the start frame identifier and the end frame identifier.

[0101] S314, obtaining a ratio between the identifier difference and the total number of recorded frames.

[0102] S315: Determine the start time of the target application according to the product of the ratio and the recording duration.

[0103] In summary, according to the method for determining the startup time of a vehicle-mounted computer application in an embodiment of the present invention, first, a reference image after the target application is started is obtained, and when the startup instruction of the target application is received, the startup frame identifier of the target application is obtained based on the recording frame of the screen recording at the current moment, and the end frame identifier of the target program after the startup is completed is obtained based on the video frame sequence of the screen recording and the reference image, and then, the startup time of the target application is determined based on the startup frame identifier, the end frame identifier, the recording duration of the screen recording, and the total number of recorded frames. Thus, the method determines the startup time of the target application through the startup frame identifier of the target application obtained by screen recording, the end frame identifier of the startup completion, and the recording duration of the screen recording and the total number of recorded frames, thereby realizing automated testing of the startup time of the vehicle-mounted computer application and improving the test accuracy of the startup time.

[0104] Corresponding to the above embodiment, the present invention further proposes a device for determining the startup time of a vehicle-mounted application.

[0105] like Figure 8 As shown, the device for determining the startup time of a vehicle-mounted application according to an embodiment of the present invention may include: a first acquisition module 50 , a second acquisition module 60 , a third acquisition module 70 and a determination module 80 .

[0106] Among them, the first acquisition module 50 is used to obtain the reference image after the target application is started. The second acquisition module 60 is used to obtain the start frame identifier of the target application based on the recording frame of the current screen recording when the start instruction of the target application is received. The third acquisition module 70 is used to obtain the end frame identifier of the target program startup completion based on the video frame sequence of the screen recording and the reference image. The determination module 80 is used to determine the start time of the target application based on the start frame identifier, the end frame identifier, the recording duration of the screen recording and the total number of recorded frames.

[0107] According to one embodiment of the present invention, the determination module 80 determines the startup time of the target application based on the startup frame identifier, the end frame identifier, the recording duration of the screen recording and the total number of recorded frames, and is specifically used to: obtain the identifier difference between the startup frame identifier and the end frame identifier; obtain the ratio between the identifier difference and the total number of recorded frames; and determine the startup time of the target application based on the product of the ratio and the recording duration.

[0108] According to one embodiment of the present invention, the third acquisition module 70 obtains the end frame identifier of the completion of the startup of the target program based on the video frame sequence of the screen recording and the reference image, and is specifically used for: matching the current frame image with the reference image based on the feature point matching algorithm to obtain the target matching feature point pair; calculating the homography transformation matrix of the current frame image and the reference image according to the target matching feature point pair; calculating the similarity between the current frame image and the reference image based on the homography transformation matrix; when the similarity is greater than or equal to the preset similarity threshold, using the identifier of the current frame image as the end identifier of the completion of the startup of the target program.

[0109] According to one embodiment of the present invention, the third acquisition module 70 matches the current frame image with the reference image based on a feature point matching algorithm to obtain a target matching feature point pair, and is specifically used for: performing grayscale processing on the reference image, and extracting a first feature point set of the grayscaled reference image based on a feature point matching algorithm; performing grayscale processing on the current frame image, and extracting a second feature point set of the grayscaled current frame image based on a feature point matching algorithm; performing K-nearest neighbor matching on the first feature point set and the second feature point set to obtain matching feature point pairs; filtering the matching feature point pairs based on a random sampling consistency algorithm to obtain target matching feature point pairs.

[0110] According to one embodiment of the present invention, the third acquisition module 70 calculates the similarity between the current frame image and the reference image based on the homography transformation matrix, and is specifically used for: mapping the current frame image to the plane where the reference image is located based on the homography matrix; performing mask processing on the mapped current frame image based on the reference image; and calculating the similarity between the current frame image after mask processing and the reference image.

[0111] According to one embodiment of the present invention, the determination module 80 is also used to: determine the startup time of multiple startups of the target application by means of loop recording and asynchronous data processing; determine the startup time test result of the target application based on the average startup time of multiple startups and a preset threshold.

[0112] It should be noted that for details not disclosed in the device for determining the startup time of a vehicle-machine application in an embodiment of the present invention, please refer to the details disclosed in the method for determining the startup time of a vehicle-machine application in the above-mentioned embodiment of the present invention, and the details will not be repeated here.

[0113] According to the device for determining the startup time of a vehicle-mounted computer application of an embodiment of the present invention, a reference image after the target application is started is acquired through a first acquisition module, a startup frame identifier of the target application is acquired based on the recording frame of the screen recording at the current moment when the startup instruction of the target application is received through a second acquisition module, and an end frame identifier of the target program after the startup is completed is acquired through a third acquisition module based on the video frame sequence of the screen recording and the reference image, and the determination module determines the startup time of the target application based on the startup frame identifier, the end frame identifier, the recording duration of the screen recording, and the total number of recorded frames. Thus, the device determines the startup time of the target application through the startup frame identifier and the end frame identifier of the target application acquired through screen recording, and in combination with the recording duration of the screen recording and the total number of recorded frames, thereby realizing automated testing of the startup time of the vehicle-mounted computer application and improving the test accuracy of the startup time.

[0114] Corresponding to the above embodiment, the present invention further proposes a system for testing the startup time of vehicle-mounted computer applications.

[0115] like Figure 2 As shown, the vehicle application startup time testing system of an embodiment of the present invention includes: a host computer 10, a vehicle device 20, a vehicle display screen 30 and a programmable high-speed camera 40, wherein the host computer 10 is connected to the programmable high-speed camera 40 through an interface, and the host computer 10 is configured to execute the above-mentioned vehicle application startup time determination method.

[0116] According to the test system for the startup time of a vehicle-mounted computer application according to an embodiment of the present invention, a host computer is connected to a programmable high-speed camera through an interface, and the host computer executes the above-mentioned method for determining the startup time of the vehicle-mounted computer application. Based on the above-mentioned method for determining the startup time of the vehicle-mounted computer application, the startup frame identifier of the target application and the end frame identifier of the startup completion are obtained through screen recording, and the startup time of the target application is determined in combination with the recording duration and the total number of recording frames of the screen recording, thereby realizing automated testing of the startup time of the vehicle-mounted computer application and improving the test accuracy of the startup time.

[0117] Corresponding to the above embodiment, the present invention also proposes a computer-readable storage medium.

[0118] The computer-readable storage medium of the embodiment of the present invention stores a program for determining the startup time of a vehicle-machine application. When the program for determining the startup time of a vehicle-machine application is executed by a processor, the method for determining the startup time of a vehicle-machine application is implemented.

[0119] According to the computer-readable storage medium of an embodiment of the present invention, the above-mentioned method for determining the startup time of the vehicle-computer application is implemented when the program for determining the startup time of the vehicle-computer application is executed by the processor. Based on the above-mentioned method for determining the startup time of the vehicle-computer application, the startup frame identifier of the target application obtained by screen recording and the end frame identifier of the startup completion are combined with the recording duration and the total number of recording frames of the screen recording to determine the startup time of the target application, thereby realizing automated testing of the startup time of the vehicle-computer application and improving the test accuracy of the startup time.

[0120] Corresponding to the above embodiment, the present invention also proposes a terminal device.

[0121] like Fig. 9 As shown, the terminal device 100 of an embodiment of the present invention includes a memory 110, a processor 120, and a program for determining the startup time of a vehicle-machine application stored in the memory 110 and executable on the processor. When the processor 120 executes the program for determining the startup time of the vehicle-machine application, the above-mentioned method for determining the startup time of the vehicle-machine application is implemented.

[0122] According to the terminal device of an embodiment of the present invention, when the processor executes the program for determining the startup time of the vehicle-machine application, the above-mentioned method for determining the startup time of the vehicle-machine application is implemented. Based on the above-mentioned method for determining the startup time of the vehicle-machine application, the startup frame identifier of the target application obtained through screen recording and the end frame identifier of the startup completion are combined with the recording duration and the total number of recording frames of the screen recording to determine the startup time of the target application, thereby realizing automated testing of the startup time of the vehicle-machine application and improving the test accuracy of the startup time.

[0123] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0124] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0125] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0126] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0127] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0128] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for determining the startup time of a vehicle computer application, characterized in that: The method comprises: Get the baseline image after the target application is started; When receiving the start instruction of the target application, obtaining the start frame identifier of the target application based on the recording frame of the screen recording at the current moment; Acquire an end frame identifier of the completion of the startup of the target program based on the video frame sequence of the screen recording and the reference image; The start time of the target application is determined based on the start frame identifier, the end frame identifier, the recording duration of the screen recording, and the total number of recorded frames.

2. The method for determining the startup time of a vehicle computer application according to claim 1, characterized in that: Determining the start time of the target application based on the start frame identifier, the end frame identifier, the recording duration of the screen recording, and the total number of recorded frames includes: Obtaining an identifier difference between the start frame identifier and the end frame identifier; Obtaining a ratio between the identifier difference and the total number of recorded frames; The start time of the target application is determined according to the product of the ratio and the recording duration.

3. The method for determining the startup time of a vehicle computer application according to claim 1, characterized in that: Acquiring an end frame identifier of the target program startup completion based on the video frame sequence of the screen recording and the reference image, including: Matching the current frame image with the reference image based on a feature point matching algorithm to obtain a target matching feature point pair; Calculating a homography transformation matrix of the current frame image and the reference image according to the target matching feature point pair; Calculating the similarity between the current frame image and the reference image based on the homography transformation matrix; When the similarity is greater than or equal to a preset similarity threshold, the identifier of the current frame image is used as an end identifier of the completion of starting the target program.

4. The method for determining the vehicle computer application startup time according to claim 3, characterized in that: The current frame image is matched with the reference image based on a feature point matching algorithm to obtain a target matching feature point pair, including: Performing grayscale processing on the reference image, and extracting a first feature point set of the grayscaled reference image based on the feature point matching algorithm; Performing grayscale processing on the current frame image, and extracting a second feature point set of the grayscaled current frame image based on the feature point matching algorithm; Performing K-nearest neighbor matching on the first feature point set and the second feature point set to obtain matching feature point pairs; The matched feature point pairs are filtered based on a random sampling consistency algorithm to obtain target matching feature point pairs.

5. The method for determining the vehicle computer application startup time according to claim 3, characterized in that: Calculating the similarity between the current frame image and the reference image based on the homography transformation matrix includes: Based on the homography matrix, mapping the current frame image to the plane where the reference image is located; Performing mask processing on the mapped current frame image based on the reference image; The similarity between the current frame image after mask processing and the reference image is calculated.

6. The method for determining the startup time of a vehicle computer application according to claim 1, characterized in that: The method further comprises: Determining the startup time of multiple startups of the target application by means of loop recording and asynchronous data processing; The startup time test result of the target application is determined based on an average value of the startup time of multiple startups and a preset threshold.

7. A device for determining the startup time of a vehicle computer application, characterized in that: The device comprises: A first acquisition module is used to acquire a reference image after the target application is started; A second acquisition module is used to acquire a startup frame identifier of the target application based on a recording frame at a current moment of screen recording when a startup instruction of the target application is received; A third acquisition module is used to acquire an end frame identifier of the completion of the startup of the target program based on the video frame sequence of the screen recording and the reference image; A determination module is used to determine the start time of the target application based on the start frame identifier, the end frame identifier, the recording duration of the screen recording and the total number of recorded frames.

8. A system for testing the startup time of vehicle-mounted applications, characterized in that: include: A host computer, a vehicle device, a vehicle display screen and a programmable high-speed camera, wherein the host computer is connected to the programmable high-speed camera via an interface, and the host computer is configured to execute the method for determining the startup time of a vehicle application as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: A program for determining the startup time of a vehicle-machine application is stored thereon, and when the program for determining the startup time of a vehicle-machine application is executed by a processor, a method for determining the startup time of a vehicle-machine application according to any one of claims 1-6 is implemented.

10. A terminal device, characterized in that: It includes a memory, a processor, and a program for determining the startup time of a vehicle-machine application stored in the memory and executable on the processor. When the processor executes the program for determining the startup time of the vehicle-machine application, a method for determining the startup time of the vehicle-machine application according to any one of claims 1-6 is implemented.

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