White screen detection method and device, equipment and medium

Abstract

The invention relates to the technical field of white screen detection, and discloses a white screen detection method and device, equipment and a medium, and the method comprises the steps: if it is detected that loading of a webpage is completed, intercepting the webpage to generate picture data; preprocessing the picture data to remove interference data in the picture data to obtain a target picture; and determining whether the webpage is in a white screen or not according to the target picture. And the accuracy of white screen detection is improved.

Description

Technical Field

[0001] The present invention relates to the field of white screen detection technology, and in particular to a white screen detection method, device, equipment and medium. Background Art

[0002] WebView is a view control used to display web content in applications. It is a browser control based on the Webkit engine that can load and display web pages, HTML files, PDF files, etc. The webView control provides developers with an embedded browser environment that enables applications to display rich web content while maintaining the application's user interface and interaction logic. WebView refers to the client's web page container. When an exception occurs in webView, such as a kernel crash, execution exception, or 404 error, the entire web page will be displayed blank. Therefore, it is necessary to monitor web pages to facilitate timely detection of white screens on web pages. The traditional monitoring method is to identify and determine white screens by traversing pixels.

[0003] The inventors realized that traditional monitoring methods cannot accurately identify the background color of an image, resulting in a low accuracy rate. Summary of the invention

[0004] The present invention provides a white screen detection method, device, computer equipment and medium to solve the technical problem of low accuracy of traditional white screen monitoring methods.

[0005] In a first aspect, a white screen detection method is provided, comprising:

[0006] If it is detected that the web page has been loaded, intercepting the web page to generate image data;

[0007] Preprocessing the image data to remove interference data in the image data to obtain a target image;

[0008] Determine whether the web page is blank according to the target image.

[0009] In a second aspect, a white screen detection device is provided, comprising:

[0010] A generating module, for capturing the web page to generate image data if it is detected that the web page has been loaded;

[0011] A preprocessing module, used for preprocessing the image data to remove interference data in the image data to obtain a target image;

[0012] The confirmation module is used to confirm whether the web page is a white screen according to the target image.

[0013] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned white screen detection method when executing the computer program.

[0014] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned white screen detection method are implemented.

[0015] In the scheme implemented by the above-mentioned white screen detection method, device, computer equipment and storage medium, the web page can be monitored and intercepted after the web page is loaded to generate image data, and the generated image data is preprocessed to eliminate interference data in the image data to improve the accuracy of the image data, and then the target image is obtained. Finally, it is confirmed whether there is a white screen on the web page based on the target image. In the present invention, the target image is obtained by preprocessing the image data, and the interference data in the image data has been eliminated. When identifying whether there is a white screen on the web page through the target image, the accuracy can be significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0017] Figure 1 is a schematic diagram of an application environment of a white screen detection method in an embodiment of the present invention;

[0018] Figure 2 is a flow chart of a white screen detection method according to an embodiment of the present invention;

[0019] Figure 3 yes Figure 2 A schematic flow chart of a specific implementation of step S10;

[0020] Figure 4 yes Figure 3 A schematic flow chart of a specific implementation of step S12;

[0021] Figure 5 yes Figure 2 A schematic flow chart of a specific implementation of step S20;

[0022] Figure 6 yes Figure 2 A schematic flow chart of a specific implementation of step S30;

[0023] Figure 7 yes Figure 6 Another specific implementation flow diagram of step S30;

[0024] Figure 8 is a structural schematic diagram of a white screen detection device in one embodiment of the present invention;

[0025] Fig. 9 is a schematic diagram of a structure of a computer device in one embodiment of the present invention;

[0026] Fig.10 It is another structural schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] The white screen detection method provided by the embodiment of the present invention can be applied in the following aspects: Figure 1 In an application environment, after the web page is loaded, the web page can be monitored and intercepted to generate image data, the generated image data can be preprocessed to eliminate interference data in the image data to improve the accuracy of the image data, and then the target image can be obtained, and finally, it can be confirmed whether there is a white screen on the web page according to the target image. In the present invention, the target image is obtained by preprocessing the image data, and the interference data in the image data has been eliminated. When the target image is used to identify whether there is a white screen on the web page, the accuracy can be significantly improved. Among them, the computer device can be but not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The present invention is described in detail below through specific embodiments.

[0029] See also Figure 2 As shown, Figure 2 A schematic flow chart of a white screen detection method provided in an embodiment of the present invention includes the following steps:

[0030] S10: If it is detected that the web page is loaded completely, the web page is intercepted to generate image data.

[0031] The white screen detection method provided by the present invention is mainly used for white screen detection of web pages, and can be applied to any computer device. When it is detected that the web page is loaded, the web page is monitored in real time, and the web page can be periodically intercepted to generate image data.

[0032] For example, for the webView control, when the webView control receives the didFinish proxy method, it starts to monitor the web page. Among them, didFinish is a proxy method of webView, and the specific name is webViewDidFinishLoad. When webView completes loading the web page, the didFinish method will be called. After the webView control receives the didFinish proxy method, it can immediately monitor the web page to determine whether it has a white screen, or it can monitor the web page at intervals after receiving the didFinish proxy method to avoid unfinished transactions in the webView control. Preferably, the web page can be monitored 0.5 seconds after the webView control receives the didFinish proxy method.

[0033] In addition, an exit monitoring mechanism can also be set up, that is, when an exit event is detected, the monitoring of the web page is stopped. The exit event may include one or more events including detecting content on the current web page, detecting that the user has left the current web page, and the current application exiting to the background.

[0034] For example, when a user opens a web page of an application, the webView control starts to load the web page. When the webView control receives the didFinish proxy method, it starts to monitor the web page loaded by the webView control after an interval of 0.5 seconds, and intercepts the web page to generate image data. When content appears in the web page or the user leaves the current page, the monitoring of the web page stops until a new web page is opened.

[0035] It should be understood that after the webView control loads the web page, it is necessary to take a screenshot of the web page to determine whether there is a white screen on the current web page. Figure 3 As shown, in step S10, that is, intercepting the web page to generate image data, the following steps are included:

[0036] S11: Create an automatic release pool block according to a preset configuration method.

[0037] S12: performing a screenshot operation on the web page in the automatic release pool block to obtain the image data.

[0038] For steps S11-S12, the automatic release pool block is used to ensure that all temporary objects created in the screenshot process can be correctly released at the end of the block, thereby avoiding memory leaks. Therefore, when intercepting a web page, it is necessary to first create an automatic release pool block, for example, the @autoreleasepool function can be used to create an automatic release pool block. After the automatic release pool block is created, the web page is screenshoted in the automatic release pool block to obtain image data.

[0039] It should be understood that the purpose of taking a screenshot of a web page is mainly to capture the state of the current web page, so as to facilitate the determination of whether there is a white screen on the current web page. Figure 4 As shown, in step S12, that is, taking a screenshot of the web page in the automatic release pool block to obtain the image data, includes the following steps:

[0040] S121: Create an image context and confirm picture parameters through the image context.

[0041] S122: Acquire the window corresponding to the webpage, and render the layer corresponding to the window into the image context.

[0042] S123: Acquire the picture data from the rendered image context.

[0043] For steps S121-S123, the image context is used to confirm the image parameters, which include but are not limited to the image size, whether it is transparent, and the scaling factor, so that the parameters of the image data can be determined. The image context can be created by the UIGraphicsBeginImageContextWithOptions function. After the image context is created, the window of the web page is obtained, and the corresponding layer is confirmed according to the window, and then the layer is rendered into the image context. Finally, the image data is obtained from the image context through the UIGraphicsBeginImageContextWithOptions function, thereby completing the screenshot operation of the web page.

[0044] After obtaining the image data, you can end the image context through the UIGraphicsBeginImageContextWithOptions function to release related resources and avoid memory leaks.

[0045] S20: Preprocess the image data to remove interference data in the image data to obtain a target image.

[0046] The image data captured from the web page may contain interference data, including but not limited to navigation bars, pop-up windows, and various banners. After obtaining the image data, the image data needs to be pre-processed to remove interference data such as navigation bars, pop-up windows, and various banners from the image data to obtain the target image, that is, the target image obtained is the image data after removing the interference data.

[0047] It should be understood that when removing interfering data, it can be removed by cropping, deleting, etc. For example, for a picture data, it includes a navigation area, and the navigation area is provided with a navigation bar. Then, the navigation area can be identified through the picture and cropped, so as to remove the navigation area from the picture data. Figure 5 As shown, in step S20, that is, preprocessing the image data to remove interference data in the image data to obtain a target image, the following steps are included:

[0048] S21: Performing image recognition on the image data to confirm that an interference region containing interference data exists in the image data.

[0049] S22: Crop the image data to remove the interference area from the image data.

[0050] S23: compressing the image data after removing the interference area to obtain the target image.

[0051] For steps S21-S23, the interference area where the interference data in the image data is located can be identified by image recognition or other methods, and then the interference area can be removed from the image data by cropping or deleting, thereby completing the filtering of the image data. After the filtering of the image data is completed, the image data can be compressed to improve the performance and speed of recognition. It can be understood that the compression mentioned above can be a compression method commonly used in the art to compress images, and its specific method is not limited here.

[0052] S30: Determine whether the web page is blank according to the target image.

[0053] After obtaining the target image, you can confirm whether the current web page has a white screen based on the target image. For example, after obtaining the target image, you can perform text detection on the target image. If there is no text content in the target image, it is confirmed that the target image has a white screen. If there is text content in the target image, it is confirmed that the target image does not have a white screen. In addition to using text content, you can also convert the target image into a grayscale image and detect the pixels of the grayscale image to confirm whether the web page has a white screen.

[0054] It should be understood that when confirming whether a web page has a white screen through a target image, in addition to confirming through pixel points, it can also be confirmed through text detection. Figure 6 As shown, in step S30, that is, confirming whether the web page is blank according to the target image, includes the following steps:

[0055] S31: inputting the target image into a preset text detection model and performing text detection on the target image through the preset text detection model.

[0056] S32: If the preset text detection model detects text information in the target image, confirm that the web page is a white screen.

[0057] S33: If the preset text detection model does not detect text information in the target image, confirm that the web page is not blank.

[0058] For steps S31-S33, the preset text detection model is used to detect whether the image contains text information, including but not limited to text, tables, patterns, etc. The preset text model can be obtained by training a neural network model, or an existing model can be directly used. For example, text detection can be performed on the target image through the Vision framework.

[0059] When text information is detected in the target image, it indicates that the current web page has text information and the web page is not blank. When no text information is detected in the target image, it indicates that the current web page does not have text information and the web page is blank.

[0060] For example, when any specific text information is detected in the target image, it indicates that there is text information on the current web page and the web page is not blank. When any information including text, table and pattern is not detected in the target image, it indicates that there is no text information on the current web page and the web page is blank.

[0061] It should be understood that when a blank screen is detected on a web page, the degree of blank screen on the web page can be divided into different levels. Figure 7 As shown, in step S30, that is, after confirming that the web page is blank, the following steps are included:

[0062] S40: If the duration of the white screen of the web page is less than or equal to the first preset time, it is determined that the web page is a slightly white screen.

[0063] S50: If the duration of the white screen of the web page is greater than the first preset time and less than or equal to the second preset time, it is determined that the web page is a moderate white screen.

[0064] S60: If the duration of the white screen of the web page is greater than the second preset time and less than or equal to the third preset time, confirm that the web page is a severe white screen, wherein the third preset time is greater than the second preset time, and the second preset time is greater than the first preset time.

[0065] For steps S40-S60, when a white screen is detected on a web page, it can be a periodic detection. When a white screen is detected on the web page in the first cycle, continue to wait for the detection of the next cycle. If a white screen is still detected on the web page, it indicates that a white screen is detected on the web page for two consecutive cycles. If a white screen is not detected on the web page, it indicates that a white screen is detected on the web page only in one cycle, and the duration of the white screen of the web page is short. The degree of the white screen is divided according to the duration of the white screen of the web page.

[0066] For example, if the detection cycle is 3 seconds, the web page can be detected for white screen at the 3rd second, the 6th second and the 9th second respectively. If a white screen is detected on the web page at the 3rd second, the web page will be detected for white screen at the 6th second. If a white screen is not detected on the web page at the 3rd second, the degree of white screen can be assessed as mild. If a white screen is detected on the web page at the 6th second, the web page can continue to be detected at the 9th second. If a white screen is not detected on the web page at the 6th second, the degree of white screen can be assessed as moderate. If a white screen is detected on the web page at the 9th second, the degree of white screen can be assessed as severe.

[0067] In the above example, the first preset time corresponds to 3 seconds, the second preset time corresponds to 6 seconds, and the third preset time corresponds to 9 seconds. That is, when the duration of the white screen is less than or equal to 3 seconds, the degree of the white screen is mild, when the duration of the white screen is less than or equal to 6 seconds and greater than 3 seconds, the degree of the white screen is moderate, and when the duration of the white screen is greater than 6 seconds and less than or equal to 9 seconds, the degree of the white screen is severe.

[0068] It can be seen that in the above scheme, when it is detected that the web page has been loaded, a screenshot of the web page can be taken to generate image data, and then the image data can be preprocessed to eliminate interference data to obtain the target image, and finally, it is confirmed based on the target image whether there is a white screen on the web page, thereby improving the accuracy of detection.

[0069] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0070] In one embodiment, a white screen detection device is provided, which corresponds one-to-one to the white screen detection method in the above embodiment. Figure 8As shown, the white screen detection device includes a generation module 101, a preprocessing module 102 and a confirmation module 103. The functional modules are described in detail as follows:

[0071] The generating module 101 is used to intercept the web page to generate image data if it is detected that the web page is loaded;

[0072] A preprocessing module 102, configured to preprocess the image data to remove interference data in the image data to obtain a target image;

[0073] The confirmation module 103 is used to confirm whether the web page is blank according to the target image.

[0074] In one embodiment, the generating module 101 is specifically configured to:

[0075] Create an automatic release pool block according to the preset configuration method;

[0076] A screenshot operation is performed on the web page in the automatic release pool block to obtain the image data.

[0077] In one embodiment, the generating module 101 is further used for:

[0078] Creating an image context and confirming image parameters through the image context;

[0079] Obtaining the window corresponding to the webpage, and rendering the layer corresponding to the window into the image context;

[0080] The image data is obtained from the rendered image context.

[0081] In one embodiment, the preprocessing module 102 is specifically configured to:

[0082] Performing image recognition on the image data to confirm an interference region in the image data where interference data exists;

[0083] Cropping the image data to remove the interference area from the image data;

[0084] The image data from which the interference area is removed is compressed to obtain the target image.

[0085] In one embodiment, the confirmation module 103 is specifically configured to:

[0086] Inputting the target image into a preset text detection model and performing text detection on the target image through the preset text detection model;

[0087] If the preset text detection model detects text information in the target image, confirming that the web page is blank;

[0088] If the preset text detection model does not detect text information in the target image, it is confirmed that the web page is not a white screen.

[0089] In one embodiment, the confirmation module 103 is specifically configured to:

[0090] If the duration of the white screen of the web page is less than or equal to the first preset time, then confirming that the web page is a slightly white screen;

[0091] If the duration of the white screen of the web page is greater than the first preset time and less than or equal to the second preset time, then confirming that the web page is a moderate white screen;

[0092] If the duration of the white screen of the web page is greater than the second preset time and less than or equal to the third preset time, the web page is confirmed to be a severe white screen, wherein the third preset time is greater than the second preset time, and the second preset time is greater than the first preset time.

[0093] The present invention provides a white screen detection device, which first obtains preliminary ranking results of candidate questions through semantic matching, and then proposes a solution for optimizing a question-answering engine based on entity alignment. The ranking results of candidate questions are sorted again through entity alignment, so that more matching candidate questions are selected, which can effectively avoid the generalization ability defects of the model, greatly and efficiently improve the effect of entity matching, and improve the effect of the question-answering engine.

[0094] For the specific limitations of the white screen detection device, please refer to the limitations of the white screen detection method above, which will not be repeated here. Each module in the above-mentioned white screen detection device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0095] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig. 9As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a white screen detection method server side.

[0096] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as follows: Fig.10 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server through a network connection. When the computer program is executed by the processor, it realizes the functions or steps of the client side of a white screen detection method

[0097] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0098] If it is detected that the web page has been loaded, intercepting the web page to generate image data;

[0099] Preprocessing the image data to remove interference data in the image data to obtain a target image;

[0100] Determine whether the web page is blank according to the target image.

[0101] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0102] If it is detected that the web page has been loaded, intercepting the web page to generate image data;

[0103] Preprocessing the image data to remove interference data in the image data to obtain a target image;

[0104] Determine whether the web page is blank according to the target image.

[0105] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0106] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0107] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0108] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A white screen detection method, characterized in that: include: If it is detected that the web page has been loaded, intercepting the web page to generate image data; Preprocessing the image data to remove interference data in the image data to obtain a target image; Determine whether the web page is blank according to the target image.

2. The method according to claim 1, characterized in that The step of intercepting the web page to generate image data includes: Create an automatic release pool block according to the preset configuration method; A screenshot operation is performed on the web page in the automatic release pool block to obtain the image data.

3. The method according to claim 2, characterized in that The performing a screenshot operation on the web page in the automatic release pool block to obtain the image data includes: Creating an image context and confirming image parameters through the image context; Obtaining the window corresponding to the webpage, and rendering the layer corresponding to the window into the image context; The image data is obtained from the rendered image context.

4. The method according to claim 1, characterized in that The preprocessing of the image data to remove interference data in the image data to obtain a target image includes: Performing image recognition on the image data to confirm an interference region in the image data where interference data exists; Cropping the image data to remove the interference area from the image data; The image data from which the interference area is removed is compressed to obtain the target image.

5. The method according to claim 1, characterized in that The step of confirming whether the webpage is blank according to the target image includes: Inputting the target image into a preset text detection model and performing text detection on the target image through the preset text detection model; If the preset text detection model detects text information in the target image, it is confirmed that the web page is a white screen.

6. The method according to claim 5, characterized in that After inputting the target image into a preset text detection model and performing text detection on the target image through the preset text detection model, the following steps are included: If the preset text detection model does not detect text information in the target image, it is confirmed that the web page is not a white screen.

7. The method according to claim 5, characterized in that After confirming that the webpage is blank, the method further includes: If the duration of the white screen of the web page is less than or equal to the first preset time, then confirming that the web page is a slightly white screen; If the duration of the white screen of the web page is greater than the first preset time and less than or equal to the second preset time, then confirming that the web page is a moderate white screen; If the duration of the white screen of the web page is greater than the second preset time and less than or equal to the third preset time, the web page is confirmed to be a severe white screen, wherein the third preset time is greater than the second preset time, and the second preset time is greater than the first preset time.

8. A white screen detection device, characterized in that: include: A generating module, for capturing the web page to generate image data if it is detected that the web page has been loaded; A preprocessing module, used for preprocessing the image data to remove interference data in the image data to obtain a target image; The confirmation module is used to confirm whether the web page is a white screen according to the target image.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the white screen detection method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the white screen detection method according to any one of claims 1 to 7 are implemented.

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