Hierarchical storage and display method and device of test data, medium and equipment

Abstract

The embodiment of the invention provides a hierarchical storage and display method and device of test data, a medium and equipment. The method comprises the steps of performing scene data statistics on test data of each test scene according to a preset period to obtain corresponding first-level feature data, and performing grading feature statistics on the first-level feature data according to a preset grading rule and / or a self-learning grading rule to obtain at least one second-level feature data; the first-level feature data and the second-level feature data corresponding to each test scene and the corresponding real-time face detection data are associated and stored in a hierarchical mode; and according to a received data viewing request, reading and displaying the first-level feature data or the second-level feature data corresponding to the data viewing request, and meanwhile, pre-loading the second-level feature data corresponding to the first-level feature data or the real-time face detection data corresponding to the second-level feature data into a memory. According to the technical scheme provided by the embodiment of the invention, abnormal data can be quickly positioned, and the response speed during data viewing is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, medium and equipment for hierarchical storage and display of test data. Background Art

[0002] In the security field, face algorithm detection technology is widely used in many scenarios such as identity authentication, monitoring, and access control. With the development of technology, the accuracy and efficiency of face algorithm detection have been significantly improved, but it also brings new challenges. Especially in large-scale deployment and long-term operation environments, face algorithm detection equipment needs to process and store a large amount of data, which includes not only real-time face detection results, but also detailed detection data for analyzing and optimizing algorithms. However, since face detection equipment needs to cover multiple scenarios during testing to ensure the robustness and accuracy of the algorithm, the test cycle is long and the test data surges, making it difficult to locate and trace abnormal data, and the response speed is slow when viewing data. Summary of the invention

[0003] The embodiments of the present application provide a method, apparatus, medium and device for hierarchical storage and display of test data, thereby being able to quickly locate abnormal data, at least to a certain extent, and improving the response speed when viewing data.

[0004] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0005] According to one aspect of an embodiment of the present application, a method for hierarchical storage and display of test data is provided, comprising:

[0006] In the process of testing the face detection device, for each test scene, scene data statistics are performed according to a predetermined period to obtain primary feature data corresponding to each test scene;

[0007] For the test data of each of the test scenarios, performing classification feature statistics on the test data according to a preset classification rule and / or a self-learning classification rule to obtain at least one secondary feature data corresponding to each of the test scenarios;

[0008] Associating the primary feature data, the secondary feature data and the corresponding real-time face detection data corresponding to each of the test scenes and storing them in a hierarchical manner;

[0009] According to the received data viewing request, the primary feature data or the secondary feature data corresponding to the data viewing request is read and displayed, and while displaying, the secondary feature data corresponding to the currently displayed primary feature data or the real-time face detection data corresponding to the currently displayed secondary feature data is pre-loaded into the memory for viewing.

[0010] According to one aspect of an embodiment of the present application, a hierarchical storage and display device for test data is provided, comprising:

[0011] A first statistical module is used to perform scene data statistics for each test scene according to a predetermined period during the process of testing the face detection device, so as to obtain primary feature data corresponding to each test scene;

[0012] A second statistical module is used to perform classification feature statistics on the test data of each of the test scenarios according to a preset classification rule and / or a self-learning classification rule to obtain at least one secondary feature data corresponding to each of the test scenarios;

[0013] A storage module, used for associating and hierarchically storing the primary feature data, the secondary feature data and the corresponding real-time face detection data corresponding to each of the test scenes;

[0014] The processing module is used to read and display the primary feature data or the secondary feature data corresponding to the data viewing request according to the received data viewing request, and at the same time, pre-load the secondary feature data corresponding to the currently displayed primary feature data or the real-time face detection data corresponding to the currently displayed secondary feature data into the memory for viewing.

[0015] According to one aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the hierarchical storage and display method of test data as described in the above embodiment is implemented.

[0016] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the hierarchical storage and display method of test data as described in the above embodiments.

[0017] According to one aspect of an embodiment of the present application, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the hierarchical storage and display method of test data provided in the above embodiment.

[0018] In the technical solutions provided in some embodiments of the present application, during the process of testing the face detection device, for each test scene, scene data statistics are performed according to a predetermined period to obtain the primary feature data corresponding to each test scene, and for the test data of each test scene, hierarchical feature statistics are performed according to preset grading rules and / or self-learning grading rules to obtain at least one secondary feature data corresponding to each test scene, then, the primary feature data, secondary feature data and corresponding real-time face detection data corresponding to each test scene are associated and stored hierarchically, and then, according to the received data viewing request, the primary feature data or secondary feature data corresponding to the data viewing request is read and displayed, and at the same time, the secondary feature data corresponding to the currently displayed primary feature data or the real-time face detection data corresponding to the currently displayed secondary feature data is pre-loaded into the memory for viewing. In this way, by performing statistics on the test data to generate the corresponding primary feature data and secondary feature data, it is convenient for users to quickly locate abnormal data based on the two, and by storing hierarchically and pre-loading the next level data into the memory when displaying, the response speed when users view data can be improved.

[0019] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0021] Figure 1 A schematic diagram showing a process of a method for hierarchical storage and display of test data according to an embodiment of the present application is shown;

[0022] Figure 2 A block diagram of a device for hierarchical storage and display of test data according to an embodiment of the present application is shown;

[0023] Figure 3 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0024] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0025] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0026] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0027] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0028] Figure 1 A schematic diagram of a process of hierarchical storage and display method of test data according to an embodiment of the present application is shown.

[0029] The method can be applied to a terminal device or a server, wherein the terminal device may include but is not limited to one or more of a smart phone, a tablet computer, a portable computer, and a desktop computer; the server may be a physical server or a cloud server.

[0030] Please refer to Figure 1 The hierarchical storage and display method of the test data at least includes steps S110 to S140, which are described in detail as follows (the following description is made by taking the application of the method to a server as an example):

[0031] In step S110, during the process of testing the face detection device, scene data statistics are performed for each test scene according to a predetermined period to obtain primary feature data corresponding to each test scene.

[0032] Among them, the face detection device can be an electronic device that uses a face detection algorithm to perform face recognition on videos or images.

[0033] In this embodiment, the tester can connect the face detection device to be tested to the server. During the test, the server can receive the face detection data (such as the degree of eye opening, the degree of mouth opening, etc.) uploaded in real time by the face detection device. When the server receives the test data, it can perform scene data statistics according to a predetermined period (such as the maximum value, minimum value, average value, etc. of the degree of eye opening within a predetermined period), so as to obtain the corresponding primary feature data. It should be understood that one predetermined period corresponds to one primary feature data. The predetermined period can be predetermined by those skilled in the art based on prior experience. For example, the predetermined period can be 10 minutes, 30 minutes, one hour, etc., and the present application does not make any special limitation on this.

[0034] It should be noted that the test scenarios correspond to the test purposes one by one, and different test purposes correspond to different test scenarios.

[0035] In step S120, for the test data of each of the test scenarios, classification feature statistics are performed according to preset classification rules and / or self-learning classification rules to obtain at least one secondary feature data corresponding to each of the test scenarios.

[0036] The preset classification rules may be rules pre-set by a person skilled in the art for classifying or grading data, such as detection duration, fatigue duration, or yawn duration, etc.

[0037] The self-learning classification rules may be classification rules automatically learned and generated by the server, and used to dynamically adjust the classification or classification of data. For example, when the value of the test data suddenly increases or decreases or the detection state changes, classification feature data is generated. The sudden increase or decrease in the value of the test data may be when the change in the value of the test data exceeds a certain threshold.

[0038] In this embodiment, for the test data of each test scenario, the server can perform hierarchical feature statistics on the test data according to preset grading rules and / or self-learning grading rules, thereby obtaining at least one secondary feature data corresponding to each test scenario. It should be noted that one primary feature data can correspond to one or more secondary feature data.

[0039] It should be noted that the "and / or" mentioned in this application means that the server can perform grading feature statistics only according to preset grading rules, or can perform grading feature statistics only according to self-learning grading rules. The server can also perform grading feature statistics according to both preset grading rules and self-learning grading rules.

[0040] In step S130, the primary feature data, the secondary feature data and the corresponding real-time face detection data corresponding to each of the test scenes are associated and stored in a hierarchical manner.

[0041] In this embodiment, the server can sequentially associate and hierarchically store the primary feature data, secondary feature data, and corresponding real-time face detection data corresponding to each test scene. In this way, when viewing the data later, the server can quickly determine the corresponding secondary feature data based on the primary feature data, and quickly determine the corresponding real-time face detection data based on the secondary feature data. In addition, the server can use a multi-level cache structure to hierarchically store the primary feature data, secondary feature data, and real-time face detection data, thereby avoiding the server from searching for the required data in a large amount of test data, thereby improving the response speed.

[0042] In step S140, according to the received data viewing request, the primary feature data or the secondary feature data corresponding to the data viewing request is read and displayed, and while displaying, the secondary feature data corresponding to the currently displayed primary feature data or the real-time face detection data corresponding to the currently displayed secondary feature data is pre-loaded into the memory for viewing.

[0043] In this embodiment, when it is necessary to view the test data, the user can send a corresponding data viewing request to the server through the terminal device. The data viewing request can include the data identifier of the test data to be viewed (such as the test scenario identifier, etc.), and the server can respond to the data viewing request, read the corresponding primary feature data or secondary feature data and display it. In addition, during the display process, the server can pre-load the next level data corresponding to the currently displayed data into the memory, so that it can quickly respond and display when it is necessary to view the next level data.

[0044] Specifically, when the data to be viewed is primary feature data, since the primary feature data is scene statistical data, the server can quickly load the primary feature data to be viewed into the memory and display it. At the same time, the server can load the secondary feature data corresponding to the primary feature data into the memory in real time. In this way, when the user wants to view the secondary feature data of the corresponding time period or corresponding area (such as a certain area in a chart) based on the primary feature data, the server can quickly read the corresponding secondary feature data from the memory and display it.

[0045] After all the secondary feature data are loaded into the memory or when the user is viewing the secondary feature data, the server can pre-load the corresponding real-time face detection data into the memory. In this way, when the user wants to view the real-time face detection data corresponding to a certain secondary feature data, the server can quickly read and display it from the memory.

[0046] Therefore, based on Figure 1 In the embodiment shown, during the process of testing the face detection device, for each test scene, scene data statistics are performed according to a predetermined period to obtain the primary feature data corresponding to each test scene, and for the test data of each test scene, hierarchical feature statistics are performed according to a preset grading rule and / or a self-learning grading rule to obtain at least one secondary feature data corresponding to each test scene, then, the primary feature data, secondary feature data and corresponding real-time face detection data corresponding to each test scene are associated and stored hierarchically, and then, according to the received data viewing request, the primary feature data or secondary feature data corresponding to the data viewing request is read and displayed, and at the same time, the secondary feature data corresponding to the currently displayed primary feature data or the real-time face detection data corresponding to the currently displayed secondary feature data is pre-loaded into the memory for viewing. In this way, by performing statistics on the test data to generate the corresponding primary feature data and secondary feature data, it is convenient for users to quickly locate abnormal data based on the two, and by storing hierarchically and pre-loading the next level of data into the memory when displaying, the response speed when users view data can be improved.

[0047] In some embodiments of the present application, the method further includes:

[0048] When the next level of data needs to be displayed, the secondary feature data or real-time face detection data within a predetermined time period before and after the specified time is obtained from the memory for display.

[0049] In this embodiment, when the user wants to view the next level of data, the server can respond to the user's viewing request, obtain the secondary feature data or real-time face detection data within a predetermined time period before and after the specified time determined by the user from the memory and display it. For example, when the user is viewing the primary feature data, he further selects the secondary feature data of a certain time period for viewing, and the server can obtain the secondary feature data of fifteen minutes before and after the start time of the time period from the memory for display. The predetermined time period can be predetermined by those skilled in the art based on prior experience to avoid displaying too much data at the same time and affecting the user's viewing experience.

[0050] In some embodiments of the present application, the method further includes:

[0051] When the previous level of data needs to be viewed, the previous level of data is obtained from the memory and displayed.

[0052] In this embodiment, while the user is viewing data, the server can retain the primary feature data and secondary feature data that have been loaded into the memory, so that when the user needs to view the previous level of data, the primary feature data or secondary feature data can be quickly obtained from the memory to ensure response speed.

[0053] In some embodiments of the present application, when the data being viewed is primary feature data or secondary feature data, a corresponding data chart is generated and displayed based on the read primary feature data or secondary feature data.

[0054] In this embodiment, when the data being viewed is primary feature data or secondary feature data, since it is scene statistical data or hierarchical statistical data, the server can generate corresponding data charts based on the primary feature data and secondary feature data, so that the user can intuitively and quickly understand the general situation of the data. When the next level of data needs to be viewed, the user can click on the corresponding area in the data chart, and the server can read the corresponding next level of data and display it according to the area selected by the user.

[0055] In some embodiments of the present application, if the data currently being viewed is real-time face detection data, the method further includes:

[0056] The real-time face detection data that has been viewed is cleared from the memory, and the real-time face detection data that has not been displayed is continuously loaded into the memory.

[0057] In this embodiment, if the data currently being viewed is real-time face detection data, the server can clear the viewed (i.e., displayed) real-time face detection data from the memory, thereby saving a certain amount of memory space to facilitate loading other real-time face detection data and avoid memory exhaustion due to excessive real-time face detection data.

[0058] In some embodiments of the present application, the method further includes:

[0059] In response to an edit request for a preset grading rule, displaying a grading rule editing interface;

[0060] According to the editing information received by the grading rule editing interface, a preset grading rule is generated and stored.

[0061] In this embodiment, the present application also provides a classification rule editing interface. The server can respond to an editing request for a preset classification rule and display the classification rule editing interface on the display interface of the user's terminal device. The classification rule editing interface includes at least one editing option. The user can edit the preset classification rule through the at least one editing option. The server can generate and store the corresponding preset classification rule based on the editing information received by the classification rule editing interface. In this way, the user can edit the classification rule according to the actual implementation needs to improve the user experience.

[0062] The following describes an embodiment of the device of the present application, which can be used to execute the hierarchical storage and display method of test data in the above embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the hierarchical storage and display method of test data in the above embodiment of the present application.

[0063] Figure 2 A block diagram of a device for hierarchical storage and presentation of test data according to an embodiment of the present application is shown.

[0064] Reference Figure 2 As shown, a hierarchical storage and display device for test data according to an embodiment of the present application includes:

[0065] A first statistical module is used to perform scene data statistics for each test scene according to a predetermined period during the process of testing the face detection device, so as to obtain primary feature data corresponding to each test scene;

[0066] A second statistical module is used to perform classification feature statistics on the test data of each of the test scenarios according to a preset classification rule and / or a self-learning classification rule to obtain at least one secondary feature data corresponding to each of the test scenarios;

[0067] A storage module, used for associating and hierarchically storing the primary feature data, the secondary feature data and the corresponding real-time face detection data corresponding to each of the test scenes;

[0068] The processing module is used to read and display the primary feature data or the secondary feature data corresponding to the data viewing request according to the received data viewing request, and at the same time, pre-load the secondary feature data corresponding to the currently displayed primary feature data or the real-time face detection data corresponding to the currently displayed secondary feature data into the memory for viewing.

[0069] In some embodiments of the present application, the processing module is further configured to:

[0070] When the next level of data needs to be displayed, the secondary feature data or real-time face detection data within a predetermined time period before and after the specified time is obtained from the memory for display.

[0071] In some embodiments of the present application, the processing module is also used to: when the viewed data is primary feature data or secondary feature data, generate and display a corresponding data chart based on the read primary feature data or secondary feature data.

[0072] In some embodiments of the present application, the processing module is further used to: when it is necessary to view the previous level data, obtain the previous level data from the memory and display it.

[0073] In some embodiments of the present application, if the data currently being viewed is real-time face detection data, the processing module is also used to: clear the viewed real-time face detection data from the memory, and continue to load the real-time face detection data that has not yet been displayed into the memory.

[0074] In some embodiments of the present application, the processing module is further used to: in response to an edit request for a preset grading rule, display a grading rule editing interface;

[0075] According to the editing information received by the grading rule editing interface, a preset grading rule is generated and stored.

[0076] Figure 3 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0077] It should be noted that Figure 3 The computer system of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0078] like Figure 3 As shown, the computer system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0079] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, etc.; an output section 307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0080] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 309, and / or installed from a removable medium 311. When the computer program is executed by a central processing unit (CPU) 301, various functions defined in the system of the present application are executed.

[0081] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0082] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0083] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not constitute limitations on the units themselves in some cases.

[0084] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the above embodiment.

[0085] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0086] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0087] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0088] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for hierarchical storage and display of test data, characterized in that: include: In the process of testing the face detection device, for each test scene, scene data statistics are performed according to a predetermined period to obtain primary feature data corresponding to each test scene; For the test data of each of the test scenarios, performing classification feature statistics on the test data according to a preset classification rule and / or a self-learning classification rule to obtain at least one secondary feature data corresponding to each of the test scenarios; Associating the primary feature data, the secondary feature data and the corresponding real-time face detection data corresponding to each of the test scenes and storing them in a hierarchical manner; According to the received data viewing request, the primary feature data or the secondary feature data corresponding to the data viewing request is read and displayed, and while displaying, the secondary feature data corresponding to the currently displayed primary feature data or the real-time face detection data corresponding to the currently displayed secondary feature data is pre-loaded into the memory for viewing.

2. The method according to claim 1, characterized in that The method further comprises: When the next level of data needs to be displayed, the secondary feature data or real-time face detection data within a predetermined time period before and after the specified time is obtained from the memory for display.

3. The method according to claim 2, characterized in that The method further comprises: When the previous level of data needs to be viewed, the previous level of data is obtained from the memory and displayed.

4. The method according to any one of claims 1 to 3, characterized in that When the data being viewed is primary characteristic data or secondary characteristic data, a corresponding data chart is generated and displayed based on the read primary characteristic data or secondary characteristic data.

5. The method according to any one of claims 1 to 3, characterized in that: If the data currently being viewed is real-time face detection data, the method further includes: The real-time face detection data that has been viewed is cleared from the memory, and the real-time face detection data that has not been displayed is continuously loaded into the memory.

6. The method according to claim 1, characterized in that The method further comprises: In response to an edit request for a preset grading rule, displaying a grading rule editing interface; According to the editing information received by the grading rule editing interface, a preset grading rule is generated and stored.

7. A hierarchical storage and display device for test data, characterized in that: include: A first statistical module is used to perform scene data statistics for each test scene according to a predetermined period during the process of testing the face detection device, so as to obtain primary feature data corresponding to each test scene; A second statistical module is used to perform classification feature statistics on the test data of each of the test scenarios according to a preset classification rule and / or a self-learning classification rule to obtain at least one secondary feature data corresponding to each of the test scenarios; A storage module, used for associating and hierarchically storing the primary feature data, the secondary feature data and the corresponding real-time face detection data corresponding to each of the test scenes; The processing module is used to read and display the primary feature data or the secondary feature data corresponding to the data viewing request according to the received data viewing request, and at the same time, pre-load the secondary feature data corresponding to the currently displayed primary feature data or the real-time face detection data corresponding to the currently displayed secondary feature data into the memory for viewing.

8. A computer readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for hierarchical storage and display of test data according to any one of claims 1 to 6 is implemented.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the hierarchical storage and display method for test data as described in any one of claims 1 to 6.

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