Image processing method, cloud service method, device, electronic device and storage medium

Abstract

The embodiment of the present invention provides an image processing method, a cloud service method, an apparatus, an electronic device and a storage medium. The image processing method comprises: controlling an application to browse a target long page through a cloud real machine to obtain multiple cloud real machine screenshots; splicing the multiple cloud real machine screenshots to generate a long screenshot of the target long page in the application. In the scheme of the embodiment of the present invention, since the cloud real machine screenshot is obtained by controlling the application to browse the target long page, and the screenshot function is a capability of the cloud real machine, the generation of the long page screenshot by splicing the cloud real machine screenshots avoids code intrusion caused by integrating the long page screenshot function in the application.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of computer technology, and in particular to an image processing method, a cloud service method, an apparatus, an electronic device, and a storage medium. Background Art

[0002] The following situation may occur on the pages of some application websites: due to the need to carry a large number of brands, products, service objects and other content, the page length is very long. Such pages are generally called "long pages".

[0003] Usually, such long pages need to be tested or verified before being published to achieve the desired display effect. However, there is no solution in the prior art to ensure the display effect of such long pages. Summary of the invention

[0004] In view of this, embodiments of the present invention provide an image processing method, a cloud service method, an apparatus, an electronic device, and a storage medium to solve or alleviate the above-mentioned problems.

[0005] According to a first aspect of an embodiment of the present invention, a method for image processing is provided, including: browsing a target long page through a cloud real machine control application to obtain multiple cloud real machine screenshots; splicing the multiple cloud real machine screenshots to generate a page long screenshot of the target long page in the application.

[0006] According to a second aspect of an embodiment of the present invention, a cloud service method is provided, including: obtaining a long screenshot service request, the long screenshot service request being used to request multiple page long screenshots of a target long page in multiple applications respectively; controlling the multiple applications to browse the target long page through a cloud real machine, and obtaining multiple groups of cloud real machine screenshots; splicing the multiple groups of cloud real machine screenshots to generate and return the multiple page long screenshots.

[0007] According to a third aspect of an embodiment of the present invention, a cloud service method is provided, including: obtaining a long screenshot service request, the long screenshot service request being used to request multiple page long screenshots of a target application long page corresponding to multiple application accounts; browsing the target application long page based on multiple application accounts through a cloud real machine, and obtaining multiple groups of cloud real machine screenshots; splicing the multiple groups of cloud real machine screenshots to generate and return the multiple page long screenshots.

[0008] According to a fourth aspect of an embodiment of the present invention, a method for image processing is provided, including: browsing a target long page through a cloud real machine control application and recording a browsing video clip; splicing multiple video frames of the browsing video clip to generate a long screenshot of the target long page in the application.

[0009] According to a fifth aspect of an embodiment of the present invention, there is provided an image processing device, including: a recording control module, which controls an application to browse a target long page through a cloud real machine and records a browsing video clip; a screenshot generation module, which splices multiple video frames of the browsing video clip to generate a long screenshot of the target long page in the application.

[0010] According to the sixth aspect of an embodiment of the present invention, there is provided an image processing device, including: a screenshot acquisition module, which controls an application program through a cloud real machine to browse a target long page and acquires multiple cloud real machine screenshots; a long screenshot generation module, which splices the multiple cloud real machine screenshots and generates a long screenshot of the target long page in the application program.

[0011] According to the seventh aspect of an embodiment of the present invention, a cloud service device is provided, including: a service request acquisition module, which acquires a long screenshot service request, wherein the long screenshot service request is used to request multiple long screenshots of a target long page in multiple applications respectively; a screenshot acquisition module, which controls the multiple applications to browse the target long page through a cloud real machine, and acquires multiple groups of cloud real machine screenshots; and a long screenshot generation module, which splices the multiple groups of cloud real machine screenshots, generates and returns the multiple page long screenshots.

[0012] According to an eighth aspect of an embodiment of the present invention, a cloud service device is provided, including: a service request acquisition module, which acquires a long screenshot service request, wherein the long screenshot service request is used to request multiple page long screenshots of a target application long page corresponding to multiple application accounts; a screenshot acquisition module, which browses the target application long page based on multiple application accounts through a cloud real machine to acquire multiple groups of cloud real machine screenshots; and a long screenshot generation module, which splices the multiple groups of cloud real machine screenshots to generate and return the multiple page long screenshots.

[0013] According to a ninth aspect of an embodiment of the present invention, there is provided an electronic device, comprising: one or more processors; and a computer-readable medium configured to store 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 method described in any one of the first to fourth aspects.

[0014] According to a tenth aspect of an embodiment of the present invention, a computer-readable medium is provided, on which a computer program is stored. When the program is executed by a processor, the method described in any one of the first to fourth aspects is implemented.

[0015] In the scheme of the embodiment of the present invention, since the cloud real machine screenshot is obtained by controlling the application to browse the target long page, and the screenshot function is a capability of the cloud real machine, the long page screenshot is generated by splicing the cloud real machine screenshots, thereby avoiding code intrusion caused by integrating the long page screenshot function in the application. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the embodiments of the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0017] Figure 1 A schematic diagram of a cloud-to-real-machine service network architecture applicable to an image processing method, a cloud service method, an image processing device, and a cloud service device according to an embodiment of the present invention;

[0018] Figure 2A is a schematic flow chart of a picture processing method according to another embodiment of the present invention;

[0019] Figure 2B is a schematic flow chart of a picture processing method according to another embodiment of the present invention;

[0020] Figure 3A is a schematic diagram of a picture processing method according to another embodiment of the present invention;

[0021] Figure 3B is a schematic diagram of a picture processing method according to another embodiment of the present invention;

[0022] Figure 4A is a schematic flow chart of a cloud service method according to another embodiment of the present invention;

[0023] Figure 4B A schematic diagram of a cloud service method according to another embodiment of the present invention;

[0024] Figure 5A is a schematic flow chart of a cloud service method according to another embodiment of the present invention;

[0025] Figure 5B A schematic diagram of a cloud service method according to another embodiment of the present invention;

[0026] Fig. 6A is a schematic block diagram of a picture processing device according to another embodiment of the present invention;

[0027] Figure 6B is a schematic block diagram of a picture processing device according to another embodiment of the present invention;

[0028] Figure 7 is a schematic block diagram of a cloud service device according to another embodiment of the present invention;

[0029] Figure 8 is a schematic block diagram of a cloud service device according to another embodiment of the present invention;

[0030] Fig. 9 is a schematic structural diagram of an electronic device according to another embodiment of the present invention;

[0031] Fig.10 The present invention is another embodiment of the hardware structure of an electronic device. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in the field based on the embodiments in the embodiments of the present invention should fall within the scope of protection of the embodiments of the present invention.

[0033] The specific implementation of the embodiment of the present invention is further described below in conjunction with the accompanying drawings of the embodiment of the present invention. Figure 1 FIG. 1 is a schematic diagram of a cloud-to-real-machine service network architecture applicable to an image processing method, a cloud service method, an image processing device, and a cloud service device according to an embodiment of the present invention. Figure 1 As shown, the cloud real machine service network architecture includes a cloud real machine service platform server 20 and execution nodes 31 and 32 managed by the cloud real machine service platform server 20. The user 10 can access the cloud real machine service platform server 20 through a web client, an App client, etc., so as to further access cloud real machines 311, 312, 313 and 314 managed by the execution node 31 and multiple cloud real machines 312, 322, 323 and 324 managed by the execution node 32.

[0034] In this example, the cloud real machine service platform includes a file storage module 21, a message management module 22, a web service module and a websocket service module 24. Among them, through the web client, the ability to call the web service module through a transport layer protocol such as the http protocol, the user 10 can operate in the web client, such as on a web page, in operations such as for selecting a matching cloud real machine, etc. Cloud real machine refers to a remote terminal device used for testing. For example, the object to be tested is an application software, and the test goal is to detect the operation of the application software in smart terminals of different manufacturers and different models. In this case, the multiple cloud real machines connected to the server can be multiple smart terminals of different manufacturers and different models located in different geographical locations. In addition, cloud real machines can include but are not limited to embedded devices such as mobile phones and platform computers, and desktop devices such as PCs. The above-mentioned embedded devices can be configured with the same or different underlying operating environments. For example, the same or different embedded operating systems, or different versions of the same embedded operating system, can be configured. For example, the same or different processor architectures, chips with specific functions from the same manufacturer or different manufacturers can be configured. The above-mentioned cloud real machine can also be installed with the same or different applications, or different versions of the same application, such as a test version or a release version. The above-mentioned application can be stored in the file storage module 21 accordingly. For example, the metadata of the application is stored in the file storage module 21, and the file storage module is associated with a storage medium such as an object-oriented storage medium. When receiving an access request, the file storage module 21 can pull the corresponding target file from the object-oriented storage medium. The message management module 22 can be an intermediary connecting the above-mentioned cloud real machine and the cloud real machine service platform server 20, and is used to process messages such as the operation of the screen of the cloud real machine and the state change of the mobile phone. For example, before the user 10 establishes a connection with the cloud real machine through the web client, the ability of the web service module 23 (for example, as an http proxy) can be called to access the corresponding data. For example, after the user 10 establishes a connection with the cloud real machine through the web client, the ability of the websocket service module 24 (for example, as a websocket proxy) can be called to access the corresponding data, or receive data such as video streams pushed by the websocket service module 24.

[0035] In this example, the web client includes a client that interacts with the server through a web page, such as a browser in a computer, and the user's operation based on the web client can be a conventional web page operation, such as a web page operation implemented by an input device such as a mouse and a keyboard. The App client includes an application installed in a smart terminal, and the smart terminal includes a smart phone, a tablet, a portable wearable device, etc., such as an App pre-installed in an Android phone, and the user's operation based on the App client can be a conventional smart terminal operation, such as gesture operations such as sliding, touching and clicking. Among them, the server can be implemented by an independent server or by a server cluster composed of multiple servers.

[0036] In one example, for user interface testing, the App client can be used to receive a new screen image, and based on the new screen image, update the screen image of the target cloud real machine displayed through its user interface. The web client can be used to receive the new screen image, and based on the new screen image, update the screen image of the target cloud real machine displayed through the web page. Before receiving the operation instructions for setting the software in the target cloud real machine through the App client, it is also necessary to select one of the multiple cloud real machines as the target cloud real machine through the App client to participate in the current software test, and obtain the screen image of the target cloud real machine. The user can perform any conventional cloud real machine operations based on the screen image of the target cloud real machine displayed by the App client, such as installing software, uninstalling software, changing themes, etc. In addition, user 10 can also perform other tests such as compatibility testing through the web client. It should be understood that Figure 1 The network architecture shown is only an example of a cloud real machine service platform. In other examples, other network architectures may also be used, and tests may be performed based on other test types or test purposes.

[0037] Figure 2A FIG. 4 is a schematic flow chart of a picture processing method according to another embodiment of the present invention. Figure 2A The image processing method of the present invention can be executed by any appropriate electronic device with data processing capabilities, including but not limited to: servers, mobile terminals (such as mobile phones, PADs, etc.) and PCs (such as desktop personal computers). Preferably, the image processing method of the present invention is executed by a cloud real machine service platform. The method includes:

[0038] 210: Browse the target long page through the cloud real machine control application and obtain multiple cloud real machine screenshots.

[0039] It should be understood that the cloud real machine service platform can browse the target long page through the cloud real machine control application. In one example, this can be achieved by the client sending a control instruction to the cloud real machine service platform. In another example, the client can install a control instruction simulation program to the cloud real machine service platform, and the cloud real machine service platform runs the control instruction simulation program.

[0040] In addition, for the control of the cloud real machine, in one scenario, a sliding control instruction can be sent to the cloud real machine service platform through the client, and a screenshot control instruction simulation program can be installed on the cloud real machine service platform. In another scenario, a sliding control instruction simulation program can be installed on the cloud real machine service platform, and a screenshot control instruction can be sent to the cloud real machine service platform through the client. In another scenario, a screenshot selection instruction can be sent to the cloud real machine service platform to determine multiple cloud real machine screenshots from a set of screenshots completed automatically or manually.

[0041] In addition, the application can be installed in the cloud real machine through the cloud real machine service platform. For example, through the installation instructions of the client, one or more applications are obtained from the cloud storage node managed by the cloud real machine service platform. The one or more applications can be updated in the cloud storage node. In addition, multiple applications can refer to multiple applications, or multiple versions of an application (for example, a test version or a release version, etc.). And can be the same application logged in to multiple accounts. In addition, the cloud real machine in the text can be one or more cloud real machines. Multiple cloud real machines can be used to control multiple applications to browse the target long page. It is also possible to use a cloud real machine to control multiple applications to browse the target long page. It is also possible to use multiple cloud real machines to control an application to browse the target long page. It is also possible to use a cloud real machine to control multiple application accounts logged in to the target application to browse the target long page. It is also possible to use multiple cloud real machines to control multiple application accounts logged in to the target application to browse the target long page. The embodiment of the present invention is not limited to this.

[0042] 220: Splice multiple cloud real machine screenshots to generate a long screenshot of the target long page in the application.

[0043] It should be understood that multiple cloud real machine screenshots can be spliced ​​based on the similarity between the multiple cloud real machine screenshots. The similarity between the multiple cloud real machine screenshots can be determined based on the image recognition algorithm. In addition, determining the similarity between multiple cloud real machine screenshots and obtaining multiple cloud real machine screenshots can be performed in parallel. For example, determining the similarity between multiple cloud real machine screenshots can be performed after obtaining multiple cloud real machine screenshots. For another example, determining the similarity between multiple cloud real machine screenshots can also be performed while obtaining multiple cloud real machine screenshots. For another example, determining the similarity between multiple cloud real machine screenshots can also be performed before obtaining multiple cloud real machine screenshots.

[0044] In addition, the generated long screenshot of the page can also be displayed or sent to the client. In another example, the execution node can return a visualization file of the long screenshot to the client, and the user can operate and view it on the client. In another example, the execution node can return a rendering file (e.g., in XML or JSON format) of the long screenshot to the client, and the client performs local rendering (e.g., web rendering or native rendering).

[0045] In addition, for access to the cloud real machine, in a scenario, such as operating the cloud real machine through the cloud real machine service platform (e.g., cloud real machine selection, platform application installation, cloud real machine execution task creation), the client sends a cloud real machine service request to the cloud real machine service platform through a half-duplex transport layer protocol (e.g., HTTP protocol) (through the cloud real machine management execution node). The cloud real machine service platform can generate a proxy access request based on the cloud real machine service request. The cloud real machine service platform can send a proxy access request to the access proxy node through a half-duplex transport layer protocol (e.g., HTTP protocol).

[0046] In another scenario, such as when the cloud machine is used by the client (e.g., mobile network environment monitoring, user interface operation, etc.), the client sends an operation request to the cloud machine service platform through a full-duplex transport layer protocol (e.g., websocket protocol), and the cloud machine service platform can forward the operation request to the cloud machine. In addition, the cloud machine can respond to the operation request and send an operation response (e.g., user interface status) to the client (e.g., forwarded by the cloud machine service platform). The cloud machine can also actively report cloud machine status information (e.g., interface status, user data, etc.) in real time or non-periodically.

[0047] In the scheme of the embodiment of the present invention, since the cloud real machine screenshot is obtained by controlling the application to browse the target long page, and the screenshot function is a capability of the cloud real machine, the long page screenshot is generated by splicing the cloud real machine screenshots, thereby avoiding code intrusion caused by integrating the long page screenshot function in the application.

[0048] In the scheme of the embodiment of the present invention, since the cloud real machine screenshot is obtained by controlling the application to browse the target long page, and the screenshot function is a capability of the cloud real machine, the long page screenshot is generated by splicing the cloud real machine screenshots, thereby avoiding code intrusion caused by integrating the long page screenshot function in the application.

[0049] In one scenario, the target long page can be an advertisement long page, an activity promotion long page, a product promotion long page, etc., and multiple applications can be installed in multiple cloud real machines (the multiple applications can be applications of the same or different categories, for example, social network applications, recommendation applications, e-commerce applications, etc.). For example, the target long page can be accessed on multiple cloud real machines to obtain multiple long page data (the multiple long page data can be the same, different, or partially the same). By loading and accessing the multiple long page data, multiple groups of cloud real machine screenshots are obtained respectively. For another example, multiple applications can also be installed (or run simultaneously) in a single cloud real machine to obtain multiple long page data (the multiple long page data can be the same, different, or partially the same). For another example, multiple applications can also be installed in sequence (or installed at the same time, but run in sequence) in a single cloud real machine to obtain multiple long page data (the multiple long page data can be the same, different, or partially the same). In addition, accessing a long page in the text can refer to generating a target long page based on the loaded long page data and / or the data in the application.

[0050] In another scenario, the target long page may be an advertisement long page, an activity promotion long page, a product promotion long page, etc. It should be understood that multiple applications may all have accounts logged in, some have accounts logged in, or all have accounts logged in. Multiple applications may also have the same or different accounts logged in. In addition, the above-mentioned multiple long page data may be associated with multiple applications and / or multiple accounts logged in to multiple applications.

[0051] In addition, stitching multiple groups of cloud real machine screenshots may include: stitching multiple groups of cloud real machine screenshots based on the same or different image recognition algorithms. For example, stitching multiple groups of cloud real machine screenshots may be performed based on multiple image recognition algorithms. For example, each image recognition algorithm may be associated with at least one of the corresponding applications or application accounts. In addition, the image recognition algorithm may also be associated with a sliding operation. A specific sliding operation may be used for each application or each application account.

[0052] In addition, multiple long page screenshots are returned, and the multiple long page screenshots are sent or displayed to the client. For example, a comparison chart of multiple long page screenshots is generated and presented to the user. For example, a target comparison dimension can be determined for multiple long page screenshots, and a comparison chart of multiple long page screenshots is generated based on the target comparison dimension.

[0053] In another implementation of the present invention, a target long page is browsed through a cloud real machine control application to obtain multiple cloud real machine screenshots, including: forwarding a group of user screenshot operation instructions to the cloud real machine to obtain a group of cloud real machine screenshots of the target long page in the application from the cloud real machine; according to the user picture selection instruction, multiple cloud real machine screenshots are screened out from the group of cloud real machine screenshots.

[0054] Since the user operates the cloud real machine through a set of user screenshot operation instructions and obtains a set of cloud real machine screenshots, the user's screenshot operation on the cloud real machine is realized. In addition, since multiple cloud real machine screenshots can be screened out from a set of cloud real machine screenshots according to the user picture selection instruction, the user can select multiple cloud real machine screenshots, which is conducive to the purpose of personalized picture stitching.

[0055] In another implementation of the present invention, a target long page is browsed by controlling an application program through a cloud real machine to obtain multiple cloud real machine screenshots, including: sending multiple screenshot operation simulation instructions to the cloud real machine, the multiple screenshot operation simulation instructions instructing to take screenshots of the target long page at multiple browsing positions in the application program to obtain multiple cloud real machine screenshots; and obtaining multiple cloud real machine screenshots from the cloud real machine.

[0056] Since multiple screenshot operation simulation instructions are sent to the cloud real machine to obtain multiple cloud real machine screen screenshots, the automatic screenshot operation is realized by utilizing the configuration of the cloud real machine itself, thereby preventing the screenshot code from intruding into the cloud real machine application or cloud real machine system software.

[0057] In another implementation of the present invention, a target long page is browsed through a cloud real machine control application to obtain multiple cloud real machine screenshots, and it also includes: before the current screenshot operation simulation instruction is sent, a current sliding operation simulation instruction is sent to the cloud real machine, and the current sliding operation simulation instruction indicates sliding from the previous browsing position to the current browsing position based on a preset sliding step length.

[0058] Since the sliding operation simulation instruction is sent before the screenshot operation simulation instruction is sent, the sliding operation and the screenshot operation are alternately implemented, thereby realizing a single screenshot operation.

[0059] In another implementation of the present invention, the target long page is browsed through the cloud real machine control application to obtain multiple cloud real machine screenshots, and it also includes: after the current screenshot operation simulation instruction is sent, based on the similarity between the completed screenshots, it is determined whether to send the next sliding operation simulation instruction to the cloud real machine.

[0060] In another implementation of the present invention, based on the similarity between the completed screenshots, it is determined whether to send the next sliding operation simulation instruction to the cloud real machine, including: comparing the similarity between at least two completed screenshots through a first image recognition algorithm; if the similarity is greater than a predetermined threshold, stop sending the next sliding operation simulation instruction.

[0061] Since multiple screenshots with high similarity are less efficient for image stitching, the similarity between the completed screenshots is used to determine whether to send the next sliding operation simulation instruction to the cloud real machine, thereby achieving effective screenshot operation for image stitching.

[0062] In another implementation of the present invention, multiple cloud real machine screenshots are spliced ​​to generate a page long screenshot of the target long page in the application, including: determining the similar areas between the multiple cloud real machine screenshots through a second image recognition algorithm; based on the similar areas, splicing the multiple cloud real machine screenshots to generate a page long screenshot of the target long page in the application.

[0063] Since the image recognition algorithm can effectively identify similar areas and quickly realize long screenshots of pages through similar areas, the efficiency of splicing long screenshots of pages is improved.

[0064] Figure 2B FIG. 4 is a schematic flow chart of a picture processing method according to another embodiment of the present invention. Figure 2B The image processing method includes:

[0065] 230: Browse the target long page through the cloud real machine control application and record the browsing video clip;

[0066] 240: Splice multiple video frames of the browsed video clip to generate a long screenshot of the target long page in the application.

[0067] In one example, a target operation mode can be used to browse a target long page, and accordingly, a target interception mode can be used to intercept multiple video frames from the browsed video clip. For example, the target operation mode is unidirectional page browsing, and the target interception mode is to continuously capture video frames in a unit time period to obtain multiple video frames. Preferably, the product of the speed of unidirectional page browsing and the unit time is not greater than the length of the screen.

[0068] Figure 3ASchematic diagram of an image processing method according to another embodiment of the present invention. In the method of this example, a cloud real machine execution node can control the cloud real machine execution, and the cloud real machine execution node performs image stitching on the screenshots.

[0069] In step 301, an initial position screenshot is obtained based on the top of the loaded page. For example, the screen resolution w*h (width x height) of the cloud real machine that is automatically returned is obtained. It should be understood that in subsequent steps, the sliding step length is determined based on the screen resolution, but in other examples, other methods can also be used to determine the sliding step length.

[0070] In step 302, based on the current position screenshot, by sliding with a preset sliding step length, a screenshot of the next position is obtained. For example, sliding upward by 50%, the sliding coordinates are (3 / 4h, 1 / 2w) -> (1 / 4h, 1 / 2w). The sliding speed, sliding direction or sliding delay can also be set based on the system parameters of the user interface of the cloud real machine.

[0071] In step 303, it is determined whether the page has reached the bottom. If yes, the process proceeds to step 304; if no, the process returns to step 302. For example, an image recognition algorithm may be used to compare the last multiple screenshots (e.g., two screenshots). If the image similarity is greater than a predetermined threshold (e.g., r>=99%), the page may be considered to have reached the bottom, and the last screenshot is not recorded. Otherwise, the process returns to step 302 to take further screenshots.

[0072] In step 304, the multiple screenshots are spliced ​​together to obtain a long screenshot.

[0073] Figure 3B FIG. 1 is a schematic diagram of a method for processing an image according to another embodiment of the present invention. As shown in the figure, the schematic diagram of the screenshots of multiple positions in this example can be Figure 3A . In order to facilitate intuitive distinction of the location of the screenshots, the shaded part is marked. In this example, half the length of the cloud real machine screen is used as the sliding step length, and four consecutive screenshots are obtained based on the initial screenshot of the left figure. The right figure is the completed screenshot. It should be understood that the number of screenshots, screenshot positions, sliding order, and sliding step length in this example are all exemplary. In other examples, screenshots can be taken in similar or different ways. For example, an image recognition algorithm can be collected to compare the similarity of multiple screenshots, and the images can be spliced ​​based on the similarity.

[0074] Figure 4AFIG4 is a schematic flow chart of a cloud service method of another embodiment of the present invention. The cloud service method of FIG4 can be executed by any appropriate electronic device with data processing capabilities, including but not limited to: a server, a mobile terminal (such as a mobile phone, a PAD, etc.) and a PC (such as a desktop personal computer). Preferably, the cloud service method of the present invention is executed by a cloud real machine service platform. The method includes:

[0075] 410: Get long screenshot service request, where the long screenshot service request is used to request multiple long screenshots of a target long page in multiple applications.

[0076] 420: Use cloud real machine to control multiple applications to browse the target long page and obtain multiple sets of cloud real machine screenshots.

[0077] 430: Combine multiple groups of cloud real machine screenshots to generate and return multiple long screenshots of the page.

[0078] In the scheme of the embodiment of the present invention, since the cloud real machine screenshot is obtained by controlling the application to browse the target long page, and the screenshot function is a capability of the cloud real machine, the long page screenshot is generated by splicing the cloud real machine screenshots, thereby avoiding code intrusion caused by integrating the long page screenshot function in the application.

[0079] In one scenario, the target long page can be an advertisement long page, an activity promotion long page, a product promotion long page, etc., and multiple applications can be installed in multiple cloud real machines (the multiple applications can be applications of the same or different categories, for example, social network applications, recommendation applications, e-commerce applications, etc.). For example, the target long page can be accessed on multiple cloud real machines to obtain multiple long page data (the multiple long page data can be the same, different, or partially the same). By loading and accessing the multiple long page data, multiple groups of cloud real machine screenshots are obtained respectively. For another example, multiple applications can also be installed (or run simultaneously) in a single cloud real machine at the same time to obtain multiple long page data (the multiple long page data can be the same, different, or partially the same). For another example, multiple applications can also be installed in sequence (or installed at the same time, but run in sequence) in a single cloud real machine to obtain multiple long page data (the multiple long page data can be the same, different, or partially the same). In addition, accessing a long page in the text can refer to generating a target long page based on the loaded long page data and / or the data in the application. For e-commerce applications such as push activity pages, it can be determined whether multiple target long pages have the same keywords and key images. For example, it can be determined whether the above keywords and key images are in the same position. If they are in the same position, it is considered that the verification or test has passed. For a social application that pushes products, different users may have different pushed products. It can be determined whether the above keywords and key images are in the same position. If they are in the same position, it is considered that the verification or test has failed.

[0080] In another scenario, the target long page may be an advertisement long page, an activity promotion long page, a product promotion long page, etc. It should be understood that multiple applications may all have accounts logged in, some have accounts logged in, or all have accounts logged in. Multiple applications may also have the same or different accounts logged in. In addition, the above-mentioned multiple long page data may be associated with multiple applications and / or multiple accounts logged in to multiple applications.

[0081] In addition, stitching multiple groups of cloud real machine screenshots may include: stitching multiple groups of cloud real machine screenshots based on the same or different image recognition algorithms. For example, stitching multiple groups of cloud real machine screenshots may be performed based on multiple image recognition algorithms. For example, each image recognition algorithm may be associated with at least one of the corresponding applications or application accounts. In addition, the image recognition algorithm may also be associated with a sliding operation. A specific sliding operation may be used for each application or each application account.

[0082] In addition, multiple long page screenshots are returned, and the multiple long page screenshots are sent or displayed to the client. For example, a comparison chart of multiple long page screenshots is generated and presented to the user. For example, a target comparison dimension can be determined for multiple long page screenshots, and a comparison chart of multiple long page screenshots is generated based on the target comparison dimension.

[0083] Figure 4B This is a schematic diagram of a cloud service method according to another embodiment of the present invention. As shown in the figure, in this example, two cloud real machines respectively install and run different application programs 1 and 2.

[0084] In step 401, the client sends a long screenshot request to the execution node. For example, the client sends a long screenshot request to the server of the cloud real machine service platform (for example, via the HTTP protocol), and the server forwards the long screenshot request to the execution node (for example, via the HTTP protocol). In other examples, the client can send a long screenshot request to the server, and the server generates a long screenshot sub-request based on the long screenshot request, and sends the long screenshot sub-request to the execution node (for example, via the HTTP protocol). In other examples, the client can establish a transport layer full-duplex (websocket protocol) connection with the execution node based on a transport layer half-duplex (HTTP protocol) connection. The client can send a long screenshot request to the execution node based on the transport layer full-duplex connection.

[0085] In step 402, the execution node sends a first screenshot instruction to the cloud real machine where application 1 is installed.

[0086] In step 403, the cloud real machine with application 1 installed returns the screenshot to the execution node.

[0087] In step 404 , the execution node sends a first screenshot instruction to the cloud real machine where application 2 is installed.

[0088] It should be understood that sending the first screenshot instruction and sending the second screenshot instruction in step 402 and step 404 may be parallel steps. For example, the first screenshot instruction and the second screenshot instruction may be generated based on the long screenshot request. Instructions may be sent sequentially for different applications. For example, the second screenshot instruction may be sent after the first screenshot instruction is sent, or the second screenshot instruction may be sent first and then the first screenshot instruction.

[0089] In step 405, the cloud real machine with application 2 installed returns the screenshot to the execution node.

[0090] It should be understood that returning the first screenshot and returning the second screenshot in step 403 and step 405 can be parallel steps. For example, step 403 can be performed first, and then step 405. Step 405 can also be performed first, and then step 403.

[0091] It should be understood that step 402 may also be performed after step 405. Step 404 may also be performed after step 403.

[0092] In step 406, the execution node performs screenshot stitching to obtain a long screenshot.

[0093] It should be understood that step 406 can be divided into two sub-steps of stitching the first screenshot and stitching the second screenshot.

[0094] In step 407, the execution node returns the long screenshot to the client. In one example, the execution node can display the long screenshot to the client. In another example, the execution node can return a visualization file of the long screenshot to the client, and the user can operate and view it on the client. In another example, the execution node can return a rendering file (e.g., in XML or JSON format) of the long screenshot to the client, and the client performs local rendering (e.g., web rendering or native rendering).

[0095] Figure 5A FIG5 is a schematic flow chart of a cloud service method of another embodiment of the present invention. The cloud service method of FIG5 can be executed by any appropriate electronic device with data processing capabilities, including but not limited to: a server, a mobile terminal (such as a mobile phone, a PAD, etc.) and a PC (such as a desktop personal computer). Preferably, the cloud service method of the present invention is executed by a cloud real machine service platform. The method includes:

[0096] 510: Get a long screenshot service request, where the long screenshot service request is used to request a target application long page to take multiple long screenshots of multiple application accounts.

[0097] 520: Browse the target application long page based on multiple application accounts through the cloud real machine and obtain multiple sets of cloud real machine screenshots.

[0098] 530: Combine multiple groups of cloud real machine screenshots to generate and return multiple long screenshots of the page.

[0099] In the scheme of the embodiment of the present invention, since the cloud real machine screenshot is obtained by controlling the application to browse the target long page, and the screenshot function is a capability of the cloud real machine, the long page screenshot is generated by splicing the cloud real machine screenshots, thereby avoiding code intrusion caused by integrating the long page screenshot function in the application.

[0100] In the scheme of the embodiment of the present invention, since the cloud real machine screenshot is obtained by controlling the application to browse the target long page, and the screenshot function is a capability of the cloud real machine, the long page screenshot is generated by splicing the cloud real machine screenshots, thereby avoiding code intrusion caused by integrating the long page screenshot function in the application.

[0101] In one scenario, the target long page can be an advertisement long page, an activity promotion long page, a product promotion long page, etc., and applications can be installed in multiple cloud real machines (applications can be social network applications, recommendation applications, e-commerce applications, etc.). For example, the target long page can be accessed through multiple application accounts on multiple cloud real machines to obtain multiple long page data (multiple long page data can be the same, different, or partially the same). By loading and accessing the multiple long page data, multiple groups of cloud real machine screenshots are obtained respectively. For another example, an application can also be installed in a single cloud real machine, and multiple long page data can be obtained through multiple application accounts (multiple long page data can be the same, different, or partially the same). In addition, accessing a long page in the text can refer to generating a target long page based on the loaded long page data and / or the data in the application. In addition, the above-mentioned application can be one or more applications, or one or more applications. Multiple application accounts can log in to one or more applications, or they can log in to one or more applications.

[0102] In another scenario, the target long page may be an advertisement long page, an activity promotion long page, a product promotion long page, etc. It should be understood that multiple applications may all have accounts logged in, some have accounts logged in, or all have accounts logged in. Multiple applications may also have the same or different accounts logged in. In addition, the above-mentioned multiple long page data may be associated with multiple applications and / or multiple accounts logged in to multiple applications.

[0103] In addition, stitching multiple groups of cloud real machine screenshots may include: stitching multiple groups of cloud real machine screenshots based on the same or different image recognition algorithms. For example, stitching multiple groups of cloud real machine screenshots may be performed based on multiple image recognition algorithms. For example, each image recognition algorithm may be associated with at least one of the corresponding applications or application accounts. In addition, the image recognition algorithm may also be associated with a sliding operation. A specific sliding operation may be used for each application or each application account.

[0104] In addition, multiple long page screenshots are returned, and the multiple long page screenshots are sent or displayed to the client. For example, a comparison chart of multiple long page screenshots is generated and presented to the user. For example, a target comparison dimension can be determined for multiple long page screenshots, and a comparison chart of multiple long page screenshots is generated based on the target comparison dimension.

[0105] Figure 5B This is a schematic diagram of a cloud service method according to another embodiment of the present invention. As shown in the figure, in this example, two cloud real machines respectively install and run the same application program, Account 1 and Account 2.

[0106] In step 501, the client sends a long screenshot request to the execution node. For example, the client sends a long screenshot request to the server of the cloud real machine service platform (for example, via the HTTP protocol), and the server forwards the long screenshot request to the execution node (for example, via the HTTP protocol). In other examples, the client can send a long screenshot request to the server, and the server generates a long screenshot sub-request based on the long screenshot request, and sends the long screenshot sub-request to the execution node (for example, via the HTTP protocol). In other examples, the client can establish a transport layer full-duplex (websocket protocol) connection with the execution node based on a transport layer half-duplex (HTTP protocol) connection. The client can send a long screenshot request to the execution node based on the transport layer full-duplex connection.

[0107] In step 502, the execution node sends a first screenshot instruction to the cloud real machine where the application account 1 is installed.

[0108] In step 503, the cloud real machine with application account 1 installed returns the screenshot to the execution node.

[0109] In step 504 , the execution node sends a first screenshot instruction to the cloud real machine where the application account 2 is installed.

[0110] It should be understood that sending the first screenshot instruction and sending the second screenshot instruction in step 502 and step 504 can be parallel steps. For example, the first screenshot instruction and the second screenshot instruction can be generated based on the long screenshot request. Instructions can be sent sequentially for different applications. For example, the second screenshot instruction can be sent after the first screenshot instruction is sent, or the second screenshot instruction can be sent first and then the first screenshot instruction.

[0111] In step 505, the cloud real machine with application account 2 installed returns the screenshot to the execution node.

[0112] It should be understood that returning the first screenshot and returning the second screenshot in step 503 and step 505 can be parallel steps. For example, step 503 can be performed first, and then step 505. Step 505 can also be performed first, and then step 503.

[0113] It should be understood that step 502 may also be performed after step 505. Step 504 may also be performed after step 503.

[0114] In step 506, the execution node performs screenshot stitching to obtain a long screenshot.

[0115] It should be understood that step 506 can be divided into two sub-steps of stitching the first screenshot and stitching the second screenshot.

[0116] In step 507, the execution node returns the long screenshot to the client. In one example, the execution node can display the long screenshot to the client. In another example, the execution node can return a visualization file of the long screenshot to the client, and the user can operate and view it on the client. In another example, the execution node can return a rendering file (e.g., in XML or JSON format) of the long screenshot to the client, and the client performs local rendering (e.g., web rendering or native rendering).

[0117] Fig. 6A FIG. 4 is a schematic block diagram of a picture processing device according to another embodiment of the present invention. Fig. 6A The image processing device of the present invention can be any appropriate electronic device with data processing capabilities, including but not limited to: servers, mobile terminals (such as mobile phones, PADs, etc.) and PCs (such as desktop personal computers). Preferably, the image processing device of the present invention can be a cloud real machine service platform. The device includes:

[0118] The screenshot acquisition module 610 controls the application to browse the target long page through the cloud real machine and acquires multiple cloud real machine screenshots;

[0119] The long screenshot generation module 620 performs splicing processing on multiple cloud real machine screen screenshots to generate a long screenshot of the target long page in the application.

[0120] In the scheme of the embodiment of the present invention, since the cloud real machine screenshot is obtained by controlling the application to browse the target long page, and the screenshot function is a capability of the cloud real machine, the long page screenshot is generated by splicing the cloud real machine screenshots, thereby avoiding code intrusion caused by integrating the long page screenshot function in the application.

[0121] In another implementation of the present invention, the screenshot acquisition module is specifically used to: forward a set of user screenshot operation instructions to the cloud real machine to obtain a set of cloud real machine screenshots of the target long page in the application from the cloud real machine; and filter out multiple cloud real machine screenshots from a set of cloud real machine screenshots according to user picture selection instructions.

[0122] In another implementation of the present invention, the screenshot acquisition module is specifically used to: send multiple screenshot operation simulation instructions to the cloud real machine, and the multiple screenshot operation simulation instructions indicate to take screenshots of the target long page at multiple browsing locations in the application to obtain multiple cloud real machine screenshots; obtain multiple cloud real machine screenshots from the cloud real machine.

[0123] In another implementation of the present invention, the screenshot acquisition module is also used to: send a current sliding operation simulation instruction to the cloud real machine before the current screenshot operation simulation instruction is sent, and the current sliding operation simulation instruction indicates sliding from the previous browsing position to the current browsing position based on a preset sliding step.

[0124] In another implementation of the present invention, the screenshot acquisition module is also used to: after the current screenshot operation simulation instruction is sent, based on the similarity between the completed screenshots, determine whether to send the next sliding operation simulation instruction to the cloud real machine.

[0125] In another implementation of the present invention, the screenshot acquisition module is specifically used to: compare the similarity between at least two completed screenshots through a first image recognition algorithm; if the similarity is greater than a predetermined threshold, stop sending the next sliding operation simulation instruction.

[0126] In another implementation of the present invention, the long screenshot generation module is specifically used to: determine the similar areas between multiple cloud real machine screenshots through a second image recognition algorithm; based on the similar areas, splice multiple cloud real machine screenshots to generate a long screenshot of the target long page in the application.

[0127] The device of this embodiment is used to implement the corresponding methods in the aforementioned multiple method embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here. In addition, the functional implementation of each module in the device of this embodiment can refer to the description of the corresponding parts in the aforementioned method embodiments, which will not be repeated here.

[0128] Figure 6B FIG. 4 is a schematic block diagram of a picture processing device according to another embodiment of the present invention. Figure 6B The image processing device comprises:

[0129] The recording control module 630 controls the application to browse the target long page through the cloud real machine and records the browsing video clip;

[0130] The screenshot generation module 640 performs splicing processing on multiple video frames of the browsing video clip to generate a long screenshot of the target long page in the application.

[0131] In one example, a target operation mode can be used to browse a target long page, and accordingly, a target interception mode can be used to intercept multiple video frames from the browsed video clip. For example, the target operation mode is unidirectional page browsing, and the target interception mode is to continuously capture video frames in a unit time period to obtain multiple video frames. Preferably, the product of the speed of unidirectional page browsing and the unit time is not greater than the length of the screen.

[0132] Figure 7 A schematic block diagram of a cloud service device according to another embodiment of the present invention. Figure 7 The cloud service device of the present invention can be any appropriate electronic device with data processing capabilities, including but not limited to: servers, mobile terminals (such as mobile phones, PADs, etc.) and PCs (such as desktop personal computers). Preferably, the cloud service device of the present invention can be a cloud real machine service platform, including:

[0133] A service request acquisition module 710 is used to acquire a long screenshot service request, where the long screenshot service request is used to request long screenshots of multiple pages of a target long page in multiple applications.

[0134] The screenshot acquisition module 720 controls multiple applications to browse the target long page through the cloud real machine, and acquires multiple groups of cloud real machine screenshots;

[0135] The long screenshot generation module 730 performs splicing processing on multiple groups of cloud real machine screenshots to generate and return multiple page long screenshots.

[0136] In the scheme of the embodiment of the present invention, since the cloud real machine screenshot is obtained by controlling the application to browse the target long page, and the screenshot function is a capability of the cloud real machine, the long page screenshot is generated by splicing the cloud real machine screenshots, thereby avoiding code intrusion caused by integrating the long page screenshot function in the application.

[0137] The device of this embodiment is used to implement the corresponding methods in the aforementioned multiple method embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here. In addition, the functional implementation of each module in the device of this embodiment can refer to the description of the corresponding parts in the aforementioned method embodiments, which will not be repeated here.

[0138] Figure 8 A schematic block diagram of a cloud service device according to another embodiment of the present invention. Figure 8The cloud service device of the present invention can be any appropriate electronic device with data processing capabilities, including but not limited to: servers, mobile terminals (such as mobile phones, PADs, etc.) and PCs (such as desktop personal computers). Preferably, the cloud service device of the present invention can be a cloud real machine service platform, including:

[0139] The service request acquisition module 810 acquires a long screenshot service request, where the long screenshot service request is used to request long screenshots of multiple pages of a target application corresponding to multiple application accounts;

[0140] The screenshot acquisition module 820 browses the target application long page based on multiple application accounts through the cloud real machine to obtain multiple groups of cloud real machine screenshots;

[0141] The long screenshot generation module 830 performs splicing processing on multiple groups of cloud real machine screenshots to generate and return multiple page long screenshots.

[0142] In the scheme of the embodiment of the present invention, since the cloud real machine screenshot is obtained by controlling the application to browse the target long page, and the screenshot function is a capability of the cloud real machine, the long page screenshot is generated by splicing the cloud real machine screenshots, thereby avoiding code intrusion caused by integrating the long page screenshot function in the application.

[0143] The device of this embodiment is used to implement the corresponding methods in the aforementioned multiple method embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here. In addition, the functional implementation of each module in the device of this embodiment can refer to the description of the corresponding parts in the aforementioned method embodiments, which will not be repeated here.

[0144] Fig. 9 This is a schematic diagram of the structure of an electronic device according to another embodiment of the present invention; the electronic device may include:

[0145] One or more processors 901;

[0146] The computer readable medium 902 may be configured to store one or more programs,

[0147] When the one or more programs are executed by the one or more processors, the one or more processors implement the methods described in the above embodiments.

[0148] Fig.10 The hardware structure of the electronic device of another embodiment of the present invention is as follows; Fig.10 As shown, the hardware structure of the electronic device may include: a processor 1001, a communication interface 1002, a computer readable medium 1003 and a communication bus 1004;

[0149] The processor 1001, the communication interface 1002, and the computer-readable medium 1003 communicate with each other via a communication bus 1004;

[0150] Optionally, the communication interface 1002 may be an interface of a communication module;

[0151] The processor 1001 can be specifically configured to: browse the target long page through the cloud real machine control application to obtain multiple cloud real machine screenshots; splice the multiple cloud real machine screenshots to generate a page long screenshot of the target long page in the application, or,

[0152] Obtain a long screenshot service request, the long screenshot service request is used to request multiple long screenshots of a target long page in multiple applications; control the multiple applications to browse the target long page through a cloud real machine, and obtain multiple groups of cloud real machine screenshots; splice the multiple groups of cloud real machine screenshots to generate and return the multiple long page screenshots, or,

[0153] Obtain a long screenshot service request, wherein the long screenshot service request is used to request multiple page long screenshots of a target application long page corresponding to multiple application accounts; browse the target application long page based on multiple application accounts through a cloud real machine to obtain multiple groups of cloud real machine screenshots; splice the multiple groups of cloud real machine screenshots to generate and return the multiple page long screenshots.

[0154] The processor 1001 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It may implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0155] The computer readable medium 1003 can be, but is not limited to, a random access memory medium (RAM), a read-only memory medium (ROM), a programmable read-only memory medium (PROM), an erasable read-only memory medium (EPROM), an electrically erasable read-only memory medium (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.

[0156] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code configured to execute the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through a communication part, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), the above functions defined in the method of the present invention are executed. It should be noted that the computer-readable medium of the present invention can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, 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 conductors, a portable computer disk, a hard disk, a random access storage medium (RAM), a read-only storage medium (ROM), an erasable programmable read-only storage medium (EPROM or flash memory), an optical fiber, a portable compact disk read-only storage medium (CD-ROM), an optical storage medium, a magnetic storage medium, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus or a device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code 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. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program configured to be used by or in combination with an instruction execution system, an apparatus or a device. The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0157] Computer program code configured to perform the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0158] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment, or a part of a code, and the module, program segment, or a part of the code contains one or more executable instructions configured to implement the specified logical function. There are specific sequential relationships in the above-mentioned specific embodiments, but these sequential relationships are only exemplary. When the specific implementation is implemented, these steps may be less, more or the execution order may be adjusted. That is, 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 and / or flowchart, and the combination of boxes in the block diagram and / 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.

[0159] The modules involved in the embodiments of the present invention may be implemented by software or hardware. The names of these modules do not limit the modules themselves in some cases.

[0160] As another aspect, the present invention further provides a computer-readable medium having a computer program stored thereon, which implements the method described in the above embodiment when the program is executed by a processor.

[0161] As another aspect, the present invention further provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by the device, the device: browses the target long page through the cloud real machine control application and obtains multiple cloud real machine screenshots; splices the multiple cloud real machine screenshots to generate a page long screenshot of the target long page in the application, or,

[0162] Obtain a long screenshot service request, the long screenshot service request is used to request multiple long screenshots of a target long page in multiple applications; control the multiple applications to browse the target long page through a cloud real machine, and obtain multiple groups of cloud real machine screenshots; splice the multiple groups of cloud real machine screenshots to generate and return the multiple long page screenshots, or,

[0163] Obtain a long screenshot service request, wherein the long screenshot service request is used to request multiple page long screenshots of a target application long page corresponding to multiple application accounts; browse the target application long page based on multiple application accounts through a cloud real machine to obtain multiple groups of cloud real machine screenshots; splice the multiple groups of cloud real machine screenshots to generate and return the multiple page long screenshots.

[0164] The expressions "first", "second", "the first" or "the second" used in various embodiments of the present disclosure may modify various components regardless of order and / or importance, but these expressions do not limit the corresponding components. The above expressions are only configured for the purpose of distinguishing an element from other elements. For example, a first user device and a second user device represent different user devices, although both are user devices. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element without departing from the scope of the present disclosure.

[0165] When one element (e.g., a first element) is referred to as being "(operably or communicatively) coupled" or "(operably or communicatively) coupled to" or "connected to" another element (e.g., a second element), it is understood that the one element is directly connected to the other element or the one element is indirectly connected to the other element via yet another element (e.g., a third element). Conversely, it is understood that when an element (e.g., a first element) is referred to as being "directly connected" or "directly coupled" to another element (the second element), no element (e.g., a third element) is interposed between the two.

[0166] The above description is only a preferred embodiment of the present invention and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present invention is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present invention (but not limited to) to form a technical solution.

Claims

1. A method for processing an image, comprising: After sending a current screenshot operation simulation instruction among a plurality of screenshot operation simulation instructions to the cloud real machine, comparing similarities between at least two completed screenshots by a first image recognition algorithm, wherein the plurality of screenshot operation simulation instructions instruct to take screenshots of a target long page at a plurality of browsing positions in the application program, so as to obtain a plurality of cloud real machine screen screenshots; If the similarity is greater than a predetermined threshold, stopping sending the next sliding operation simulation instruction among the multiple screenshot operation simulation instructions; Acquire the plurality of cloud real machine screenshots from the cloud real machine; The multiple cloud real machine screenshots are spliced ​​to generate a long screenshot of the target long page in the application.

2. The method according to claim 1, wherein: Also includes: Before the current screenshot operation simulation instruction is sent, the current sliding operation simulation instruction is sent to the cloud real machine, and the current sliding operation simulation instruction indicates sliding from the previous browsing position to the current browsing position based on a preset sliding step length.

3. The method according to claim 1, wherein: The step of splicing the plurality of cloud real machine screenshots to generate a long screenshot of the target long page in the application program includes: Determine, by a second image recognition algorithm, similar regions between the plurality of cloud real machine screenshots; Based on the similar areas, the multiple cloud real machine screenshots are spliced ​​to generate a long screenshot of the target long page in the application.

4. A cloud service method, comprising: Obtaining a long screenshot service request, wherein the long screenshot service request is used to request multiple long screenshots of a target long page in multiple applications; After sending a current screenshot operation simulation instruction among a plurality of screenshot operation simulation instructions to the cloud real machine, comparing similarities between at least two completed screenshots by a first image recognition algorithm, the plurality of screenshot operation simulation instructions instructing to take screenshots of the target long page at a plurality of browsing positions of each application in the plurality of applications, so as to obtain a plurality of groups of cloud real machine screen screenshots; If the similarity is greater than a predetermined threshold, stopping sending the next sliding operation simulation instruction among the multiple screenshot operation simulation instructions; Acquire the plurality of groups of cloud real machine screenshots from the cloud real machine; The multiple groups of cloud real machine screenshots are spliced ​​together to generate and return the multiple page long screenshots.

5. A cloud service method, comprising: Obtaining a long screenshot service request, wherein the long screenshot service request is used to request multiple long screenshots of a target application long page corresponding to multiple application accounts; After sending a current screenshot operation simulation instruction among a plurality of screenshot operation simulation instructions to the cloud real machine, comparing similarities between at least two completed screenshots by a first image recognition algorithm, wherein the plurality of screenshot operation simulation instructions instruct to take screenshots of the target application long page at a plurality of browsing positions of each application account among the plurality of application accounts, so as to obtain a plurality of groups of cloud real machine screen screenshots; If the similarity is greater than a predetermined threshold, stopping sending the next sliding operation simulation instruction among the multiple screenshot operation simulation instructions; Acquire the plurality of groups of cloud real machine screenshots from the cloud real machine; The multiple groups of cloud real machine screenshots are spliced ​​together to generate and return the multiple page long screenshots.

6. A picture processing device, comprising: A screenshot acquisition module, after sending a current screenshot operation simulation instruction among multiple screenshot operation simulation instructions to a cloud real machine, compares the similarity between at least two completed screenshots through a first image recognition algorithm, and stops sending the next sliding operation simulation instruction among the multiple screenshot operation simulation instructions if the similarity is greater than a predetermined threshold, and acquires multiple cloud real machine screenshots from the cloud real machine, wherein the multiple screenshot operation simulation instructions instruct to take screenshots of a target long page at multiple browsing positions in an application program, so as to obtain multiple cloud real machine screenshots; The long screenshot generation module performs splicing processing on the multiple cloud real machine screenshots to generate a long screenshot of the target long page in the application.

7. A cloud service device, comprising: A service request acquisition module is used to acquire a long screenshot service request, wherein the long screenshot service request is used to request long screenshots of multiple pages of a target long page in multiple applications; A screenshot acquisition module, after sending a current screenshot operation simulation instruction among multiple screenshot operation simulation instructions to a cloud real machine, compares the similarity between at least two completed screenshots through a first image recognition algorithm, and stops sending the next sliding operation simulation instruction among the multiple screenshot operation simulation instructions if the similarity is greater than a predetermined threshold, and acquires multiple cloud real machine screenshots from the cloud real machine, wherein the multiple screenshot operation simulation instructions instruct to take screenshots of the target long page at multiple browsing positions of each application in the multiple applications, so as to obtain multiple groups of cloud real machine screenshots; The long screenshot generation module performs splicing processing on the multiple groups of cloud real machine screenshots to generate and return the multiple page long screenshots.

8. A cloud service device, comprising: A service request acquisition module, which acquires a long screenshot service request, wherein the long screenshot service request is used to request a plurality of long screenshots of a target application long page corresponding to a plurality of application accounts; A screenshot acquisition module, after sending a current screenshot operation simulation instruction among multiple screenshot operation simulation instructions to a cloud real machine, compares the similarity between at least two completed screenshots through a first image recognition algorithm, and if the similarity is greater than a predetermined threshold, stops sending the next sliding operation simulation instruction among the multiple screenshot operation simulation instructions, and acquires multiple cloud real machine screenshots from the cloud real machine, wherein the multiple screenshot operation simulation instructions instruct to take screenshots of the target application long page at multiple browsing positions of each application account among the multiple application accounts, so as to obtain multiple groups of cloud real machine screenshots; The long screenshot generation module performs splicing processing on the multiple groups of cloud real machine screenshots to generate and return the multiple page long screenshots.

9. An electronic device, comprising: one or more processors; A computer readable medium configured to store one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method according to any one of claims 1 to 5.

10. A computer readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

Images