Method and apparatus for deploying a gray mark

Abstract

The application discloses a method and device for deploying gray-scale marks, and relates to the technical field of software testing, and the method comprises the following steps: crawling a homepage screenshot from an application; searching a picture from a gray-scale real address server; comparing the homepage screenshot with the searched picture, selecting a picture with the highest matching degree with the homepage screenshot as an object of gray-scale marking; and marking the object in a preset mode and sending the object to the gray-scale real address server. The application can automatically deploy gray-scale marks in a gray-scale publishing scene, and improves the searching and deploying efficiency.

Description

Technical Field

[0001] This invention relates to the field of software testing technology, and more particularly to a method and apparatus for deploying grayscale markers. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] As technology and information system architectures become increasingly complex, transaction chains expand significantly, and business logic rules become more intricate, current business testing faces challenges such as canary releases and opaque business information. Testers are unaware whether the transactions they are testing are in canary or non-canary environments, or whether the scenarios meet production deployment requirements. Checking logs to confirm the environment is cumbersome. While existing technologies allow technicians to manually add "canary" text to fixed images on the application's homepage to differentiate environments, this is limited by full version releases, as the images are overwritten after each update, resulting in extremely high manual maintenance costs.

[0004] Therefore, there is currently a lack of a fully automated and efficient solution for deploying grayscale marking. Summary of the Invention

[0005] This invention provides a method for deploying grayscale markers, used to automatically deploy grayscale markers in grayscale release scenarios, thereby improving retrieval and deployment efficiency. The method includes:

[0006] Scrape screenshots of the application's homepage;

[0007] Retrieve images from a grayscale real address server;

[0008] The homepage screenshot is compared with the retrieved images, and the image with the highest matching degree with the homepage screenshot is selected as the object for grayscale labeling;

[0009] The object is tagged according to a preset method and sent to the grayscale real address server.

[0010] This invention also provides an apparatus for deploying grayscale markers, used to automatically deploy grayscale markers in grayscale publishing scenarios, thereby improving retrieval and deployment efficiency. The apparatus includes:

[0011] The homepage screenshot crawling module is used to crawl homepage screenshots from the application.

[0012] The retrieval module is used to retrieve images from the grayscale real address server;

[0013] The tagging object detection module is used to compare the homepage screenshot with the retrieved images and select the image with the highest matching degree with the homepage screenshot as the grayscale tagging object;

[0014] The grayscale marking module is used to mark the object according to a preset method and send it to the grayscale real address server.

[0015] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for deploying grayscale markers.

[0016] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for deploying grayscale markers.

[0017] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for deploying grayscale markers.

[0018] In this embodiment of the invention, a homepage screenshot is crawled from the application; images are retrieved from a grayscale real address server; the homepage screenshot is compared with the retrieved images, and the image with the highest matching degree with the homepage screenshot is selected as the object for grayscale tagging; the object is tagged according to a preset method and sent to the grayscale real address server. Compared with the existing technology of manually performing grayscale tagging, this embodiment of the invention achieves fully automatic grayscale tagging by automatically crawling homepage screenshots, automatically retrieving images, and automatically matching homepage screenshots with images, thereby improving the efficiency of image retrieval and grayscale tag deployment. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0020] Figure 1 This is a flowchart of a method for deploying grayscale markers in an embodiment of the present invention;

[0021] Figure 2 This is another flowchart of the method for deploying grayscale markers in an embodiment of the present invention;

[0022] Figure 3 This is a flowchart illustrating the process of crawling a homepage screenshot from an application in an embodiment of the present invention;

[0023] Figure 4 This is a flowchart illustrating the process of retrieving images from a grayscale real address server in an embodiment of the present invention;

[0024] Figure 5 This is a flowchart illustrating how the image with the highest matching degree to the homepage screenshot is selected as the object for grayscale labeling in this embodiment of the invention.

[0025] Figure 6 This is a flowchart illustrating how the object is tagged and sent to the corresponding grayscale real address server in a preset manner, as described in this embodiment of the invention.

[0026] Figure 7 This is a schematic diagram of a device for deploying grayscale markers in an embodiment of the present invention;

[0027] Figure 8 This is a schematic diagram of a computer device in an embodiment of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0029] Figure 1 A flowchart of a method for deploying grayscale markers in an embodiment of the present invention includes:

[0030] Step 101: Crawl a screenshot of the homepage from the application;

[0031] Step 102: Retrieve the image from the grayscale real address server;

[0032] Step 103: Compare the homepage screenshot with the retrieved images, and select the image with the highest matching degree with the homepage screenshot as the object for grayscale labeling;

[0033] Step 104: Mark the object according to a preset method and send it to the grayscale real address server.

[0034] In this embodiment of the invention, compared with the existing method of manually performing grayscale labeling, this embodiment of the invention achieves fully automatic grayscale labeling by automatically crawling homepage screenshots, automatically retrieving images, and automatically matching homepage screenshots with images, thereby improving the efficiency of image retrieval and grayscale labeling deployment.

[0035] Each step is described in detail below.

[0036] In step 101, a screenshot of the homepage is crawled from the application;

[0037] To accelerate automation, embodiments of the present invention can pre-enter grayscale retrieval information, see [link to relevant documentation]. Figure 2 In one embodiment, the method further includes:

[0038] Step 201: Pre-enter grayscale retrieval information and store it in the database table APP_MESSAGE. The grayscale retrieval information includes the domain name, image storage information, and grayscale marking method.

[0039] The domain name includes the application access address (URL) and the gray-scale real address server IP address (IAAS_IP);

[0040] The image storage information includes first image storage information IAAS_LOCAL_NAME (local path + filename + pixels), second image storage information IAAS_REMOTE_NAME (grayscale real address server path + filename + pixels) and homepage screenshot storage information (path + filename). The first image storage information is the storage information of the image downloaded to the local machine, and the second image storage information is the storage information of the image on the grayscale real address server.

[0041] The grayscale marking method GRAYWAY is either grayscale text or a pop-up reminder.

[0042] The above pre-entry steps enable automatic deployment of grayscale markers based on domain names. During storage, the URL is used as the primary key, and neither the URL nor the IaaS_IP address can be empty.

[0043] In one embodiment, a screenshot of the homepage is crawled from the application; see [link to relevant documentation]. Figure 3 ,include:

[0044] Step 301, create a browser connection;

[0045] Step 302: Access the application's address via a browser and log in to the application's homepage;

[0046] Step 303: Obtain a screenshot of the application's homepage;

[0047] Step 304: Save the homepage screenshot to local storage;

[0048] Step 305: Update the homepage screenshot storage information in the database table. The homepage screenshot storage information includes the storage path, file name, and pixels.

[0049] In a specific implementation, the webdriver module of Python is mainly used to crawl screenshots of the homepage from the application. The algorithm is as follows:

[0050] FOR url in URL:

[0051] Browser = webdriver.Chrome() / / Create browser connection

[0052] Browser.get(url) / / Access the application via browser, log in to the application homepage

[0053] Browser.manimize_windows() / / Get a screenshot of the application's homepage.

[0054] Browser.save_screenshot(PATH+FILENAME) / / Saves the homepage screenshot to local storage.

[0055] Update the homepage screenshot storage information HOMEPAGE in the database table. The homepage screenshot storage information includes the storage path, file name and pixels, that is, update the HOMEPAGE field to PATH+FILENAME+pixels;

[0056] In step 102, the image is retrieved from the grayscale real address server;

[0057] The real-address server has a fixed IP address and can be accessed directly via SSH. The Paramiko module in Python can be used to connect to the server and download files to the local machine. Gray-scale retrieval information also includes the program deployment directory; see [link / reference]. Figure 4 Retrieve images from the grayscale real address server, including:

[0058] Step 401: Connect to the database and obtain the program deployment directory jspath corresponding to the grayscale real address server IP address;

[0059] Step 402: Connect to the grayscale real address server via SSH using the grayscale real address server's IP address;

[0060] Step 403: If the program deployment directory is not empty, retrieve the image from the grayscale real address server according to the program deployment directory and obtain the retrieval results;

[0061] Step 404: If the program deployment directory is empty, retrieve the image from the grayscale real address server based on the root directory to obtain the retrieval results;

[0062] Step 405: Based on the search results, update the first image storage information and the second image search information in the database table.

[0063] In one embodiment, updating the first image storage information and the second image retrieval information in the database table based on the retrieval results includes:

[0064] If the search results are not empty, the retrieved images are stored locally, the storage information of the first image in the database table is updated, and the retrieval information of the second image is updated according to the search results.

[0065] If the search result is empty, update the second image search information to "no image format content".

[0066] against Figure 4 The specific algorithm is as follows:

[0067] FOR ip in IAAS_IP:

[0068] Connect to the database to obtain the jspath corresponding to the IP address.

[0069] ssh = paramiko.SSHClient()

[0070] Connect to the server using ssh.connect(ip)

[0071] If jspath IS NOT NULL:

[0072] First, navigate to the jspath directory using `cd`, then execute the `find` command to match common image formats such as JPG, PNG, TIF, GIF, PCX, BMP, and TGA. The result will be returned as a search result.

[0073] If result IS NOT NULL:

[0074] The GET command retrieves the image and stores it locally, storing the first image retrieval information of the image in IAAS_LOCAL_NAME.

[0075] Store the path, filename, and pixel values ​​from the result in the IAAS_REMOTE_NAME field of the database.

[0076] Else:

[0077] Record "No image format content" in the IAAS_REMOTE_NAME field.

[0078] Else:

[0079] First, navigate to the root directory using the `cd` command, then execute the `find` command to match common image formats such as JPG, PNG, TIF, GIF, PCX, BMP, and TGA. The result will be the search result.

[0080] If result IS NOT NULL:

[0081] The GET command retrieves the image and stores it locally, storing the first image retrieval information of the image in IAAS_LOCAL_NAME.

[0082] Store the path, filename, and pixel values ​​from the result in the IAAS_REMOTE_NAME field of the database.

[0083] Else:

[0084] Record "No image format content" in the IAAS_REMOTE_NAME field.

[0085] In step 103, the homepage screenshot is compared with the retrieved images, and the image with the highest matching degree with the homepage screenshot is selected as the object for grayscale labeling;

[0086] See Figure 5 The homepage screenshot is compared with the retrieved images, and the image with the highest matching degree with the homepage screenshot is selected as the object for grayscale labeling, including:

[0087] Step 501: Read the homepage screenshot storage information from the database table and obtain the homepage screenshot;

[0088] Step 502: Read the first image storage information from the database table;

[0089] Step 503: For each item in the first image storage information, obtain the corresponding image, open the homepage screenshot and the image using pixel image, and convert them into NP group;

[0090] Step 504: For each NP group, starting from each pixel of the homepage screenshot as the starting position, crop an area of ​​the same size as the image of the NP group, compare the area with the RGB domain target of each pixel in the image, obtain the contrast difference of each pixel, and add the contrast differences of all pixels in the area to obtain the total difference. If the total difference is below the preset threshold, use the image as the object for grayscale labeling.

[0091] Step 505: Update the second image storage information in the database table based on all grayscale-marked objects.

[0092] Figure 5 The specific algorithm flow is as follows:

[0093] FOR iaas_local_name IN IAAS_LOCAL NAME:

[0094] FOR I IN iaas_local_name:

[0095] Open the corresponding homepage screenshot (e.g., 200*200) and image I (30*30) using pixel images and convert them into NP groups;

[0096] Starting from each pixel of the homepage screenshot, crop a region of the same size as image I (30*30). Compare this region with the RGB domain target of each pixel in the image to obtain the comparison difference of each pixel. Add the comparison differences of all pixels in the region to obtain the total difference.

[0097] If the total difference is below the preset threshold, the image will be used as the object for grayscale labeling.

[0098] Based on all objects with grayscale markings, update the second image storage information IAAS_REMOTE_NAME in the database table.

[0099] In step 104, the object is tagged in a preset manner and sent to the grayscale real address server.

[0100] See Figure 6 The process includes tagging the object according to a preset method and sending it to the corresponding grayscale real address server, including:

[0101] Step 601: Read the second image storage information from the database table;

[0102] Step 602: Determine whether the second image storage information is content without image format;

[0103] If not, in step 603, mark the object according to the pop-up reminder;

[0104] If so, in step 604, all objects corresponding to the second image storage information are tagged according to the grayscale label, and the tagged objects are sent to the grayscale real address server according to the second image storage information.

[0105] against Figure 6 The specific process algorithm is as follows:

[0106] FOR iaas_remote_name IN IAAS_REMOTE_NAME:

[0107] If iaas_remote_name = "No image format content"

[0108] Tag the object according to the pop-up notification.

[0109] Else:

[0110] All objects corresponding to the stored information in the second image are tagged using grayscale labels.

[0111] The tagged object is sent to the grayscale real address server according to the storage information of the second image.

[0112] The grayscale marking deployment can be completed after the above steps. The initial deployment may be a bit slow. This invention also has an iterative update design to improve the deployment efficiency of subsequent grayscale marking deployments. Except for the first execution of the full process, subsequent deployments only need to execute steps 101-104. That is, after obtaining the homepage screenshot, it can be compared with the local image. If they are consistent, the grayscale marking is directly marked according to the grayscale marking method recorded in GRAYWAY. The processed image is then uploaded as a grayscale marked image according to the information recorded in iaas_remote_name. If they are inconsistent, proceed to step 201, that is, execute the process of steps 201-104.

[0113] Normally, the homepage style is not easily changed, so in most cases, it only takes a long time during the first deployment, and the efficiency of subsequent deployments and gray-scale tagging will be greatly improved.

[0114] In summary, the method proposed in this embodiment of the invention involves: crawling homepage screenshots from the application; retrieving images from a grayscale real address server; comparing the homepage screenshots with the retrieved images, selecting the image with the highest matching degree as the object for grayscale tagging; tagging the object according to a preset method and sending it to the grayscale real address server. Compared with the existing technology of manually performing grayscale tagging, this embodiment of the invention achieves fully automatic grayscale tagging by automatically crawling homepage screenshots, automatically retrieving images, and automatically matching homepage screenshots with images, thus improving the efficiency of image retrieval and grayscale tagging deployment. Furthermore, with continuous iteration of result storage, the retrieval and deployment efficiency will continue to increase. In addition, this invention has high versatility and can be deployed in most applications with visual pages.

[0115] This invention also provides an apparatus for deploying grayscale markers, as described in the following embodiments. Since the principle by which this apparatus solves the problem is similar to the method for deploying grayscale markers, the implementation of this apparatus can be found in the implementation of the method for deploying grayscale markers; repeated details will not be elaborated further.

[0116] Figure 7 This is a schematic diagram of a device for deploying grayscale markers in an embodiment of the present invention, including:

[0117] The homepage screenshot crawling module 701 is used to crawl homepage screenshots from the application.

[0118] Retrieval module 702 is used to retrieve images from a grayscale real address server;

[0119] The tagging object detection module 703 is used to compare the homepage screenshot with the retrieved images and select the image with the highest matching degree with the homepage screenshot as the grayscale tagging object;

[0120] The grayscale marking module 704 is used to mark the object according to a preset method and send it to the grayscale real address server.

[0121] In one embodiment, the device further includes an input module 705, used for:

[0122] Grayscale retrieval information is pre-entered and stored in a database table. The grayscale retrieval information includes domain name, image storage information, and grayscale marking method.

[0123] The domain name includes the application access address and the grayscale real address server IP address;

[0124] The image storage information includes first image storage information, second image storage information, and homepage screenshot storage information, wherein the first image storage information is the storage information of images downloaded to the local machine, and the second image storage information is the storage information of images on the grayscale real address server;

[0125] The grayscale marking method is grayscale text or pop-up reminder.

[0126] In one embodiment, the homepage screenshot crawling module is specifically used for:

[0127] Create a browser connection;

[0128] Access the application's URL through a browser and log in to the application's homepage;

[0129] Get a screenshot of the application's homepage;

[0130] Save the homepage screenshot locally;

[0131] Update the homepage screenshot storage information in the database table. The homepage screenshot storage information includes the storage path, file name, and pixels.

[0132] In one embodiment, the grayscale retrieval information also includes a program deployment directory;

[0133] The search module is specifically used for:

[0134] Connect to the database and obtain the program deployment directory corresponding to the IP address of the grayscale real address server;

[0135] Connect to the grayscale real address server via SSH using the grayscale real address server's IP address;

[0136] If the program deployment directory is not empty, retrieve the image from the grayscale real address server based on the program deployment directory to obtain the search results;

[0137] If the program deployment directory is empty, retrieve images from the grayscale real address server based on the root directory to obtain the search results;

[0138] Based on the search results, update the first image storage information and the second image retrieval information in the database table.

[0139] In one embodiment, the retrieval module is specifically used for:

[0140] If the search results are not empty, the retrieved images are stored locally, the storage information of the first image in the database table is updated, and the retrieval information of the second image is updated according to the search results.

[0141] If the search result is empty, update the second image search information to "no image format content".

[0142] In one embodiment, the marking object detection module is specifically used for:

[0143] Read the homepage screenshot storage information from the database table and retrieve the homepage screenshot;

[0144] Read the first image storage information from the database table;

[0145] For each item in the first image storage information, obtain the corresponding image, open the homepage screenshot and the image using pixel image, and convert them into NP genus groups;

[0146] For each NP group, starting from each pixel of the homepage screenshot, crop a region of the same size as the image of that NP group. Compare this region with the RGB domain target of each pixel in the image to obtain the contrast difference of each pixel. Add the contrast differences of all pixels in the region to obtain the total difference. If the total difference is below a preset threshold, use the image as the object for grayscale labeling.

[0147] Update the second image storage information in the database table based on all objects with grayscale markings.

[0148] In one embodiment, the grayscale marking module is specifically used for:

[0149] Read the second image storage information from the database table;

[0150] Determine whether the stored information of the second image is content without image formatting;

[0151] If not, mark the object according to the pop-up prompt;

[0152] If so, all objects corresponding to the second image storage information are tagged according to the grayscale label, and the tagged objects are sent to the grayscale real address server according to the second image storage information.

[0153] In summary, the device proposed in this embodiment of the invention crawls homepage screenshots from the application; retrieves images from a grayscale real address server; compares the homepage screenshots with the retrieved images, and selects the image with the highest matching degree as the object for grayscale tagging; tags the object according to a preset method and sends it to the grayscale real address server. Compared with the existing technology of manually performing grayscale tagging, this embodiment of the invention achieves fully automatic grayscale tagging by automatically crawling homepage screenshots, automatically retrieving images, and automatically matching homepage screenshots with images, thus improving the efficiency of image retrieval and grayscale tagging deployment. Furthermore, with continuous iteration of result storage, the retrieval and deployment efficiency will continue to increase. In addition, this invention has high versatility and can be deployed in most applications with visual pages.

[0154] This invention also provides a computer device. Figure 8 This is a schematic diagram of a computer device in an embodiment of the present invention. The computer device 800 includes a memory 810, a processor 820, and a computer program 830 stored in the memory 810 and executable on the processor 820. When the processor 820 executes the computer program 830, it implements the above-described method for deploying grayscale markers.

[0155] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for deploying grayscale markers.

[0156] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for deploying grayscale markers.

[0157] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0158] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0159] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0160] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0161] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method of deploying a grayscale marker, the method comprising: include: Scrape screenshots of the application's homepage; Retrieve images from a grayscale real address server; The homepage screenshot is compared with the retrieved images, and the image with the highest matching degree with the homepage screenshot is selected as the object for grayscale labeling; The object is tagged according to a preset method and sent to the grayscale real address server; The method further includes: Grayscale retrieval information is pre-entered and stored in a database table. The grayscale retrieval information includes domain name, image storage information, and grayscale marking method. The domain name includes the application access address and the grayscale real address server IP address; The image storage information includes first image storage information, second image storage information, and homepage screenshot storage information, wherein the first image storage information is the storage information of images downloaded to the local machine, and the second image storage information is the storage information of images on the grayscale real address server; The grayscale marking method is either grayscale text or a pop-up reminder; The grayscale retrieval information also includes the program deployment directory; The process of retrieving images from a grayscale real address server includes: Connect to the database and obtain the program deployment directory corresponding to the IP address of the grayscale real address server; Connect to the grayscale real address server via SSH using the grayscale real address server's IP address; If the program deployment directory is not empty, retrieve images from the grayscale real address server according to the program deployment directory to obtain the retrieval results; If the program deployment directory is empty, retrieve the image from the grayscale real address server based on the root directory to obtain the retrieval result; Based on the search results, update the first image storage information and the second image search information in the database table.

2. The method of claim 1, wherein, Scrape screenshots of the application's homepage, including: Create a browser connection; Access the application's URL through a browser and log in to the application's homepage; Get a screenshot of the application's homepage; Save the homepage screenshot locally; Update the homepage screenshot storage information in the database table. The homepage screenshot storage information includes the storage path, file name, and pixels.

3. The method of claim 1, wherein, Based on the search results, update the first image storage information and the second image retrieval information in the database table, including: If the search results are not empty, the retrieved images are stored locally, the storage information of the first image in the database table is updated, and the retrieval information of the second image is updated according to the search results. If the search result is empty, update the second image search information to "no image format content".

4. The method of claim 1, wherein, The homepage screenshot is compared with the retrieved images, and the image with the highest matching degree to the homepage screenshot is selected as the object for grayscale labeling, including: Read the homepage screenshot storage information from the database table and retrieve the homepage screenshot; Read the first image storage information from the database table; For each item in the first image storage information, obtain the corresponding image, open the homepage screenshot and the image using pixel image, and convert them into NP genus groups; For each NP group, starting from each pixel of the homepage screenshot, crop a region of the same size as the image of that NP group. Compare this region with the RGB domain target of each pixel in the image to obtain the contrast difference of each pixel. Add the contrast differences of all pixels in the region to obtain the total difference. If the total difference is below a preset threshold, use the image as the object for grayscale labeling. Update the second image storage information in the database table based on all objects marked with grayscale.

5. The method of claim 1, wherein, The process of tagging the object according to a preset method and sending it to the corresponding grayscale real address server includes: Read the second image storage information from the database table; Determine whether the stored information of the second image is content without image formatting; If not, mark the object according to the pop-up prompt; If so, all objects corresponding to the second image storage information are tagged according to the grayscale label, and the tagged objects are sent to the grayscale real address server according to the second image storage information.

6. An apparatus for deploying a grayscale marker, the apparatus comprising: include: The homepage screenshot crawling module is used to crawl homepage screenshots from the application. The retrieval module is used to retrieve images from the grayscale real address server; The tagging object detection module is used to compare the homepage screenshot with the retrieved images and select the image with the highest matching degree with the homepage screenshot as the grayscale tagging object; The grayscale marking module is used to mark the object according to a preset method and send it to the grayscale real address server; The device further includes an input module for: Grayscale retrieval information is pre-entered and stored in a database table. The grayscale retrieval information includes domain name, image storage information, and grayscale marking method. The domain name includes the application access address and the grayscale real address server IP address; The image storage information includes first image storage information, second image storage information, and homepage screenshot storage information, wherein the first image storage information is the storage information of images downloaded to the local machine, and the second image storage information is the storage information of images on the grayscale real address server; The grayscale marking method is either grayscale text or a pop-up reminder; The grayscale retrieval information also includes the program deployment directory; The retrieval module is specifically used to: connect to the database and obtain the program deployment directory corresponding to the grayscale real address server IP address; Connect to the grayscale real address server via SSH using the grayscale real address server's IP address; If the program deployment directory is not empty, retrieve images from the grayscale real address server according to the program deployment directory to obtain the retrieval results; If the program deployment directory is empty, retrieve the image from the grayscale real address server based on the root directory to obtain the retrieval result; Based on the search results, update the first image storage information and the second image search information in the database table.

7. 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, it implements the method of any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 5.

9. A computer program product, characterised in that, The computer program product comprises a computer program which, when executed by a processor, implements the method of any one of claims 1 to 5.

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