Image cutting method and device, intelligent learning equipment and storage medium

Abstract

The invention relates to the field of internet teaching, and discloses an image cutting method and device, intelligent learning equipment and a storage medium. The image cutting method is applied to the intelligent learning equipment, and comprises the following steps: when a screen mode of a current application is detected to be a vertical screen mode, obtaining a vertical screen parameter corresponding to the vertical screen mode; when it is detected that the camera shooting function of the current application is started, controlling a camera of the intelligent learning equipment to collect images according to the vertical screen parameters; obtaining a preset cutting mode for the current application, and cutting the image according to the preset cutting mode to obtain a target image; and displaying the target image to the current application. According to the image cutting method, when the current application is in the vertical screen mode, the vertical screen parameters are configured, and the image collected by the camera is cut according to the preset cutting mode, so that the adaptation degree of the image and the current application is improved.

Description

Technical Field

[0001] The present application relates to the field of Internet teaching, and specifically to an image cropping method, device, intelligent learning equipment and storage medium. Background Art

[0002] With the continuous development of the field of Internet teaching, smart learning devices are becoming more and more popular. It is common to install various applications on smart learning devices for students to use. Since students are usually teenagers, eye protection factors need to be taken into consideration. The screen size of smart learning devices is usually designed to be larger and fixed to horizontal screen use. However, many current third-party applications need to be used in portrait mode. When adapted to smart learning devices, once the smart learning device turns on the camera function, the collected graphics often cannot be well adapted to the third-party application because the smart learning device is a fixed horizontal screen, which can easily cause problems such as the image shooting area being too narrow and the image being deformed. Summary of the invention

[0003] The embodiments of the present application aim to provide an image cropping method, apparatus, intelligent learning device and storage medium to solve the technical problem in the prior art that when the intelligent learning device is in portrait mode, the image captured by the camera is not well adapted to the application.

[0004] In a first aspect, an embodiment of the present application provides an image cropping method, which is applied to an intelligent learning device, and the method includes: when it is detected that the screen mode of a current application is a portrait mode, obtaining portrait parameters corresponding to the portrait mode; when it is detected that the current application turns on a camera function, controlling the camera of the intelligent learning device to capture an image according to the portrait parameters; obtaining a preset cropping mode for the current application, and cropping the image according to the preset cropping mode to obtain a target image; and displaying the target image to the current application.

[0005] Optionally, the method also includes: when it is detected that the screen mode of the current application is the landscape mode, obtaining landscape parameters corresponding to the landscape mode, and the landscape parameters are the default screen parameters of the intelligent learning device; when it is detected that the current application turns on the camera function, controlling the camera of the intelligent learning device to capture a landscape image according to the landscape parameters; and displaying the landscape image to the current application.

[0006] Optionally, the portrait screen parameters are screen parameters simulated by the intelligent learning device for the portrait screen mode, and the portrait screen parameters include at least: any one or more of screen angle, camera angle information, and gravity sensor information when the screen state is in the portrait state.

[0007] Optionally, the step of obtaining a preset cropping mode for the current application and cropping the image according to the preset cropping mode to obtain a target image includes: obtaining a preset cropping mode for the current application, controlling the camera to crop and / or scale the captured image according to the preset cropping mode to obtain a preview image; and adjusting the preview image according to the screen state of the intelligent learning terminal to obtain a target image. Optionally, the step of adjusting the preview image according to the screen state of the intelligent learning terminal to obtain a target image includes: rotating the preview image according to a preset rotation angle according to the screen state of the intelligent learning terminal to obtain a target image.

[0008] Optionally, the method further includes: when it is detected that the user performs a first change operation of a preset cropping mode on the current application, changing the preset cropping mode according to the first change operation, and taking effect when the camera captures the next frame of image.

[0009] Optionally, the method also includes: when a change in the screen state of the intelligent learning device is detected, displaying a prompt message in a pop-up window, wherein the prompt message is used to remind the user whether to change the screen mode of the current application; if a second change operation of the user to change the screen mode is detected, the screen mode of the current application is changed according to the second change operation.

[0010] In a second aspect, an image cropping device is provided, the device comprising:

[0011] An acquisition module is used to acquire the vertical screen parameters corresponding to the vertical screen mode when it is detected that the screen mode of the current application is the vertical screen mode; an acquisition module is used to control the camera of the intelligent learning device to acquire images according to the vertical screen parameters when it is detected that the current application turns on the camera function; a cropping module is used to acquire the preset cropping mode for the current application, and crop the image according to the preset cropping mode to obtain a target image; a display module is used to display the target image to the current application.

[0012] In a third aspect, an intelligent learning device is provided, comprising a memory and a processor, wherein the memory is connected to the processor, and the processor is used to execute one or more computer programs stored in the memory, and when the processor executes the one or more computer programs, the intelligent learning device implements the method described in the first aspect.

[0013] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the method as described in the first aspect.

[0014] In the image cropping method provided in the embodiment of the present application, when it is detected that the screen mode of the current application is the portrait mode, the portrait parameters corresponding to the portrait mode are obtained. When the current application turns on the camera function, the camera of the intelligent learning device is controlled to capture images according to the portrait parameters, and the preset cropping mode for the current application is obtained. The image is cropped according to the preset cropping mode to obtain the target image, and the target image is displayed on the current application. Through the above-mentioned image cropping method, when the current application is in the portrait mode, the portrait parameters can be configured, and the image captured by the camera can be cropped according to the preset cropping mode, thereby improving the degree of adaptation of the image to the current application. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0016] Figure 1A A schematic diagram of an application interface of an existing intelligent learning device;

[0017] Figure 1B A schematic diagram of an application interface of another existing intelligent learning device;

[0018] Figure 2 A schematic diagram of a process of an image cropping method provided in an embodiment of the present application;

[0019] Figure 3 A schematic diagram of a flow chart of another image cropping method provided in an embodiment of the present application;

[0020] Figure 4 A schematic diagram of the effect of a preset cropping mode provided in an embodiment of the present application;

[0021] Figure 5 A schematic diagram of the effect of another preset cropping mode provided in an embodiment of the present application;

[0022] Figure 6 A schematic diagram of another image rotation effect provided in an embodiment of the present application;

[0023] Figure 7 A schematic diagram of the structure of an image cropping device provided in an embodiment of the present application;

[0024] Figure 8 A schematic diagram of the structure of an intelligent learning device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0026] It should be noted that, if there is no conflict, the various features in the embodiments of the present application can be combined with each other, all within the scope of protection of the present application. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order from the module division in the device or the flow chart. Furthermore, the words "first", "second", "third", etc. used in this application do not limit the data and execution order, but only distinguish the same items or similar items with basically the same functions and effects.

[0027] To describe the present application in more detail, we first introduce a smart learning device involved in the present application. The smart learning device refers to a learning device with an independent operating system, from which users can download the required learning resources by themselves, and can install software, games and other applications provided by third-party service providers. Such applications can continuously expand the functions of the smart learning device, and wireless network access can be achieved through mobile communication networks and other means. Since the users of the smart learning device are usually students, and most of the students are teenagers, eye protection factors need to be considered. Therefore, the screen size of the smart learning device is usually designed to be larger (such as 15.6 inches, 16 inches, etc.), and it is fixed in horizontal use (such as a screen resolution of 1930*1080, 2560*1600, etc.). Please refer to Figure 1A , which is a schematic diagram of an application interface of an existing intelligent learning device, Figure 1A The interface shown is a display effect of the smart learning device when the application supports landscape mode. It can be seen that when the application supports landscape mode, if the camera function is turned on in the application, the image captured by the camera can be better and more completely displayed in the application because the landscape mode is compatible with the landscape screen of the smart learning device itself.

[0028] See also Figure 1B , which is a schematic diagram of the application interface of another existing intelligent learning device, Figure 1B The interface shown is a display effect of the smart learning device when the application is in portrait mode. It can be seen that when the application is in portrait mode, since the smart learning device itself is in landscape mode, the application can only be displayed in the middle area of ​​the display screen of the smart learning device. At this time, if the camera function is turned on in the application, the application screen is usually displayed in window mode (such as Figure 1B The middle shaded dotted area of ​​the image is then captured by intercepting the middle area of ​​the image actually captured by the camera (such as Figure 1B The entire display screen shown is the area where the camera actually captures the image. Figure 1B The middle dotted area is the middle area of ​​the actual captured image), and the image of this middle area is sent to the application layer for display to ensure that the image of the application is not stretched in the vertical screen mode.

[0029] However, the above method uses the method of cutting out the middle area of ​​the image. Although it ensures that the image is not stretched to a certain extent, since students are usually close to the smart learning device when using the smart learning device (such as 30-40cm), the middle cutting method will cause the shooting area to be too narrow and may not be able to capture the front of the student, which is not conducive to observing the real-time situation of the student.

[0030] In view of this, the present application proposes an image cropping method, apparatus, intelligent learning device and storage medium, which are used to improve the adaptability between the application and the camera image in the vertical screen mode. Figure 2 , is a flow chart of an image cropping method provided by the present application, which is applied to an intelligent learning device, Figure 2 The image cropping method shown may include:

[0031] S201: Detect whether the application is started.

[0032] It should be noted that the application refers to an application program installed on the smart learning device, which can be an application that comes with the smart learning device or a third-party application provided by a third-party service provider. Specifically, the application can be a teaching application, a game application, etc., and this application does not impose any restrictions on this.

[0033] S202: Determine whether the screen mode of the application is the horizontal screen mode.

[0034] As a feasible implementation method, the screen mode of the application can be a landscape mode or a portrait mode. The landscape mode means that the screen display direction of the application is landscape, that is, the width of the displayed image is greater than the height. The portrait mode means that the screen display direction of the application is portrait, that is, the height of the displayed image is greater than the width. It is understandable that some applications can support both landscape mode and portrait mode, but some applications may only provide a more optimized user experience in a specific mode, and therefore may only support landscape mode or only support portrait mode.

[0035] S203: If yes, return the horizontal screen parameters of the intelligent learning device.

[0036] It is agreed in this article that the horizontal screen parameters involved in this application refer to the default screen parameters of the smart learning device.

[0037] As a feasible implementation method, when the application is opened, the intelligent learning device can obtain information such as screen information, camera installation angle, gravity sensor, etc. When it is detected that the screen mode of the current application is horizontal mode, the default screen parameters of the intelligent learning device, that is, the horizontal screen parameters (which may include the above-mentioned default screen information, camera installation angle, gravity sensor) can be returned, and the following steps S205-S206 and S209-S210 are executed.

[0038] S204: If not, obtain the vertical screen parameters of the intelligent learning device.

[0039] In a feasible implementation, when the intelligent learning device detects that the screen mode of the current application is the portrait mode, a set of screen parameters for the portrait mode, namely the portrait parameters, can be obtained to influence the behavior of the application through the portrait parameters.

[0040] It is agreed in this article that the vertical screen parameters involved in this application refer to a set of screen parameters simulated by the smart learning device for the vertical screen mode, and the vertical screen parameters include at least: any one or more of the screen angle, camera angle information, and gravity sensor information when the screen is in the vertical screen state.

[0041] S205: Detect that the current application turns on the camera function.

[0042] In a feasible implementation, when the smart learning device detects that the current application turns on the camera function, it can synchronously control the camera configured by the smart learning device to start, and can pass the currently acquired horizontal screen parameters or vertical screen parameters to the camera to enable the camera to perform corresponding initialization.

[0043] S206: Call the camera to capture a horizontal screen image according to the horizontal screen parameter, and display the horizontal screen image in the current application.

[0044] For example, when the current application is in landscape mode, the camera calls the camera to capture a landscape image according to the default landscape parameters of the smart learning device (for example, the camera angle information in the landscape parameters). Since the landscape image is adapted to the screen of the smart learning device, it can be fully displayed in the current application, and the display effect can be as follows: Figure 1A shown.

[0045] S207: Obtain a mark X of a preset cropping mode.

[0046] In a feasible implementation, the user can set a preset cropping mode in advance, and mark different Xs according to different preset cropping modes, such as preset cropping mode A, preset cropping mode B, preset cropping mode C, etc. In some embodiments, the user may not set the preset cropping mode, in which case the intelligent learning device may default to a preset cropping mode.

[0047] For example, the smart learning device can configure a setting module for a preset cropping mode on the application installed on the smart learning device. When the application is opened, the user can quickly set the preset cropping mode through the setting module. After setting, the smart learning terminal can obtain the preset cropping mode and it will take effect when the next frame of the camera is received. In this way, the image conversion can be completed without reopening the camera, meeting the scene requirements of different applications.

[0048] S208 , executing a corresponding image cropping method according to the mark X of the preset cropping mode to obtain a target image.

[0049] In a feasible implementation manner, the intelligent learning device can execute different image cropping modes through a mark X of a preset cropping mode, and crop the image captured by the camera accordingly to obtain the target image.

[0050] S209: Display the target image in the current application.

[0051] S210: Detect whether to turn off the camera function.

[0052] In a feasible implementation manner, the user can turn off the camera function at any time according to his / her own needs in the current application.

[0053] S211, if yes, stop calling the camera and end this process.

[0054] It can be seen that the above-mentioned image cropping method, when the current application is in landscape mode, returns the landscape parameters such as the real placement angle and camera installation angle of the intelligent learning device, calls the camera to capture the landscape image according to the real landscape parameters and displays it in the current application; when the current application is in portrait mode, by obtaining the vertical parameters such as the device information and camera parameter information when simulating the vertical state, after the camera captures the image, the image is cropped according to the preset cropping mode to obtain the target image, and returns it to the current application. Through the above-mentioned image cropping method, on the one hand, the image captured by the camera can be better adapted to the application in landscape mode or portrait mode; on the other hand, the present application provides different preset cropping modes, which can solve the problem of too narrow viewing angle of the application in portrait mode, and further improve the degree of adaptation between the camera and the application.

[0055] See below Figure 3 , is a flowchart of another image cropping method provided in this application. Figure 3 The image cropping method shown may include:

[0056] S301. When it is detected that the screen mode of the current application is the portrait mode, obtain portrait parameters corresponding to the portrait mode.

[0057] It should be noted that the current application refers to the application currently displayed on the smart learning device, which can be a built-in application of the smart learning device or a third-party application provided by a third-party service provider. Specifically, the current application can be a teaching application, a game application, etc., and this application does not impose any restrictions on this.

[0058] In one embodiment, the vertical screen parameters are screen parameters simulated by the intelligent learning device for the vertical screen mode, and the vertical screen parameters include at least: any one or more of screen angle, camera angle information, and gravity sensor information when the screen state is in the vertical screen state.

[0059] In a feasible real-time manner, the intelligent learning terminal can preset a set of screen parameters, which include the default horizontal screen parameters of the intelligent learning device and the vertical screen parameters of the simulated screen in the vertical screen state. Among them, the screen parameters of the intelligent learning device can include any one or more of the screen angle, camera angle information, and gravity sensor information. The intelligent learning device can preset the value range of the above screen parameters in advance to distinguish whether the current screen is in the horizontal screen state or the vertical screen state.

[0060] It is agreed in this article that the screen state of the intelligent learning terminal involved in this application refers to whether the intelligent learning terminal is currently placed in a horizontal state or a vertical state. If it is placed in a horizontal state, the screen state is a horizontal screen state, and if it is placed in a vertical state, the screen state is a vertical state. The screen mode involved in this application refers to the screen display direction of the current application. If horizontal display is supported (that is, the height of the display screen is greater than the width), the screen mode is a horizontal screen mode, and if vertical display is supported (that is, the width of the display screen is greater than the height), the screen mode is a vertical screen mode.

[0061] S302: When it is detected that the current application turns on the camera function, control the camera of the intelligent learning device to capture images according to the vertical screen parameters.

[0062] In some feasible implementations, when the smart learning device detects that the current application turns on the camera function, it can synchronously control the camera configured on the smart learning device to start, and can pass the currently acquired horizontal screen parameters to the camera, so that the camera can be initialized accordingly according to the horizontal screen parameters to make the captured image adapt to the current vertical screen mode.

[0063] S303: Acquire a preset cropping mode for the current application, and crop the image according to the preset cropping mode to obtain a target image.

[0064] This article stipulates that the preset cropping mode refers to the regulations on how to crop and / or scale the image captured by the camera. The preset cropping mode can be set by the user or by default by the smart learning device.

[0065] In one embodiment, when the preset cropping mode is set by the user, the method further includes: when it is detected that the user performs a first change operation of the preset cropping mode on the current application, changing the preset cropping mode according to the first change operation, and taking effect when the camera captures the next frame of image.

[0066] For example, the smart learning device can configure a setting module for a preset cropping mode on the application installed on the smart learning device. When the current application is opened, the user can quickly set the preset cropping mode through the setting module. After setting, the smart learning terminal can obtain the preset cropping mode and it will take effect when the next frame of the camera is received. In this way, the image conversion can be completed without reopening the camera, meeting the scene requirements of different applications.

[0067] In some possible implementations, Figure 1B The cropping method shown may be one of the preset cropping modes shown in the present application, and the intelligent learning device may mark the preset cropping mode as preset cropping mode A. In other feasible implementations, please refer to Figure 4 and Figure 5 , which is a schematic diagram of the effects of the two preset cropping modes provided in this application. Figure 4 The preset cropping mode shown can be marked as preset cropping mode B in the intelligent learning device. The preset cropping mode B adjusts the entire image captured by the camera according to Figure 4 Scale in the direction of the dotted line, and finally scale the image to Figure 4 The "Camera Display Area" shown in . Figure 4 The preset cropping mode shown only scales the image captured by the camera, and can completely retain the original image captured by the camera.

[0068] Figure 5The preset cropping mode shown in the figure can be marked as preset cropping mode C in the intelligent learning device, which is a cropping mode combining the preset cropping mode A and the preset cropping mode B, that is, the original image collected by the camera can cover the entire screen on the display screen. Figure 5 The "camera shooting area" shown in the figure is cropped (for example, it can be blacked out, that is, this part of the picture is discarded), and the remaining part is scaled in the direction of the dotted line, and finally the image is scaled to Figure 5 The "Camera Display Area" shown in the figure. Figure 5 The preset cropping mode shown, based on partially cropping the image captured by the camera, scales the remaining image, which can simultaneously take into account the maximum retention of important image information and the size adaptability of the image screen.

[0069] In one embodiment, the obtaining of a preset cropping mode for the current application and cropping the image according to the preset cropping mode to obtain a target image includes: obtaining a preset cropping mode for the current application, controlling the camera to crop and / or scale the captured image according to the preset cropping mode to obtain a preview image; and adjusting the preview image according to the screen status of the intelligent learning terminal to obtain a target image.

[0070] For example, the intelligent learning device can obtain the preset cropping mode of the current application and pass the preset cropping mode to the camera. After receiving the preset cropping mode, the camera will crop and / or scale the captured original image according to the preset cropping mode to obtain a preview image, and return the preview image to the current application. When the current application receives the preview image, it determines whether the current screen state of the intelligent terminal is in a horizontal state or a vertical state. If it is in a horizontal state, since the current application is in a vertical mode at this time, the preview image adjusted according to the preset cropping mode can be directly used as the target image and displayed in the current application; if it is in a vertical state, since the current application is also in a vertical mode at this time, the preview image can be rotated, enlarged or reduced, etc., to obtain a target image to better adapt to the current display mode.

[0071] In one embodiment, adjusting the preview image according to the screen state of the intelligent learning terminal to obtain the target image includes: adjusting the preview image according to a preset rotation angle according to the screen state of the intelligent learning terminal to obtain the target image.

[0072] For example, see Figure 6When the smart learning device is in landscape mode and the current application is in portrait mode, since the current application may not be adapted to the landscape freefrom mode of the smart learning device, the smart learning device can first rotate the preview image 270 degrees, then rotate it 90 degrees, and zoom in or out according to the size of the image display area to obtain the target image; when the smart learning device is in portrait mode and the current application is in portrait mode, the smart learning device can rotate the preview image 90 degrees counterclockwise, and zoom in or out accordingly to obtain the target image.

[0073] S304: Display the target image to the current application.

[0074] In one embodiment, the method also includes: when it is detected that the screen mode of the current application is the landscape mode, obtaining landscape parameters corresponding to the landscape mode, and the landscape parameters are the default screen parameters of the intelligent learning device; when it is detected that the current application turns on the camera function, controlling the camera of the intelligent learning device to capture a landscape image according to the landscape parameters; and displaying the landscape image to the current application.

[0075] For example, when the screen mode of the current application is in landscape mode, when it is detected that the current application has turned on the camera function, the smart learning device can control the camera to call the camera to capture a landscape image according to the default landscape parameters of the smart learning device (for example, the camera angle information in the landscape parameters). Since the landscape image is adapted to the screen of the smart learning device itself, it can be fully displayed in the current application, and the display effect can be as follows: Figure 1A shown.

[0076] In one embodiment, the method also includes: when a change in the screen state of the intelligent learning device is detected, a prompt message is displayed in a pop-up window, and the prompt message is used to remind the user whether to change the screen mode of the current application; if a second change operation of the user to change the screen mode is detected, the screen mode of the current application is changed according to the second change operation.

[0077] For example, the smart terminal can detect changes in the screen state of the smart learning device in real time. Once it detects that the screen state changes from landscape to portrait, or from portrait to landscape, the smart learning terminal can send a prompt message to the user in the form of a pop-up window, prompting the user whether to change the screen mode of the current application. If the user rotates and changes, the smart learning terminal can change the screen mode of the current application.

[0078] It can be understood that the above-mentioned operation of changing the screen mode can be used when the current application supports both landscape mode and portrait mode. If the current application only supports one of the modes, the prompt message may not be issued to reduce unnecessary human-computer interaction.

[0079] It can be seen that through the image cropping method shown in this application, when it is detected that the screen mode of the current application is the portrait mode, the portrait parameters corresponding to the portrait mode are obtained. When the current application turns on the camera function, the camera of the intelligent learning device is controlled to capture images according to the portrait parameters, and the preset cropping mode for the current application is obtained. The image is cropped according to the preset cropping mode to obtain the target image, and the target image is displayed on the current application. Through the above-mentioned image cropping method, when the current application is in the portrait mode, the portrait parameters can be configured, and the image captured by the camera can be cropped according to the preset cropping mode, thereby improving the degree of adaptation of the image to the current application.

[0080] The following is an introduction to an image cropping device involved in this application. Figure 7 , is an image cropping device 70 provided in an embodiment of the present application, and the image cropping device 70 may include:

[0081] The acquisition module 701 is used to acquire the vertical screen parameters corresponding to the vertical screen mode when detecting that the screen mode of the current application is the vertical screen mode.

[0082] The acquisition module 702 is used to control the camera of the intelligent learning device to acquire images according to the vertical screen parameters when it is detected that the current application turns on the camera function.

[0083] The cropping module 703 is used to obtain a preset cropping mode for the current application, and crop the image according to the preset cropping mode to obtain a target image.

[0084] The display module 704 is configured to display the target image on the current application.

[0085] In a possible design, the acquisition module 701 is also used to: when it is detected that the screen mode of the current application is the horizontal screen mode, obtain the horizontal screen parameters corresponding to the horizontal screen mode, and the horizontal screen parameters are the default screen parameters of the intelligent learning device. The acquisition module 702 is also used to control the camera of the intelligent learning device to capture a horizontal screen image according to the horizontal screen parameters when it is detected that the current application turns on the camera function. The display module 704 is also used to display the horizontal screen image to the current application.

[0086] In a possible design, the vertical screen parameters are screen parameters simulated by the intelligent learning device for the vertical screen mode, and the vertical screen parameters include at least: any one or more of the screen angle, camera angle information, and gravity sensor information when the screen is in a vertical state.

[0087] In a possible design, the cropping module 703, when used to obtain a preset cropping mode for the current application and crop the image according to the preset cropping mode to obtain a target image, is specifically used to: obtain the preset cropping mode for the current application, control the camera to crop and / or scale the captured image according to the preset cropping mode to obtain a preview image; adjust the preview image according to the screen status of the intelligent learning terminal to obtain a target image.

[0088] In a possible design, the cropping module 703, when used to adjust the preview image according to the screen state of the intelligent learning terminal to obtain the target image, is specifically used to: rotate the preview image according to a preset rotation angle according to the screen state of the intelligent learning terminal to obtain the target image.

[0089] In one possible design, the image cropping device 70 also includes: a change module, which is used to change the preset cropping mode according to the first change operation when it is detected that the user performs a first change operation on the preset cropping mode on the current application, and the change takes effect when the camera captures the next frame of image.

[0090] In a possible design, the image cropping device 70 further includes: a prompt module, which is used to display a prompt message in a pop-up window when a change in the screen state of the intelligent learning device is detected, and the prompt message is used to remind the user whether to change the screen mode of the current application. The change module is also used to change the screen mode of the current application according to the second change operation if a second change operation of the user for changing the screen mode is detected.

[0091] It can be seen that, through the image cropping device shown in the present application, when it is detected that the screen mode of the current application is in portrait mode, the portrait parameters corresponding to the portrait mode can be obtained. When the current application turns on the camera function, the camera of the intelligent learning device is controlled to capture images according to the portrait parameters, and the preset cropping mode for the current application is obtained. The image is cropped according to the preset cropping mode to obtain the target image, and the target image is displayed on the current application. Through the above-mentioned image cropping device, when the current application is in portrait mode, the portrait parameters can be configured, and the image captured by the camera can be cropped according to the preset cropping mode, thereby improving the degree of adaptation of the image to the current application.

[0092] The following is an introduction to an intelligent learning device designed by this application. Figure 8 , is a structural diagram of an intelligent learning device 80 provided in an embodiment of the present application. The intelligent learning device 80 may include: a processor 801, a memory 802, a display screen 803, and a camera 804.

[0093] Those skilled in the art will understand that Figure 8 The structure of the intelligent learning device 80 shown in the figure does not constitute a limitation on the intelligent learning device, and may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. Those skilled in the art will understand that the display screen 803 belongs to the user interface (UI).

[0094] The processor 801 is the control center of the intelligent learning device 80. It uses various interfaces and lines to connect the various parts of the entire intelligent learning device. By running or executing software programs and / or modules stored in the memory 802, and calling the data stored in the memory 802, it executes various functions of the intelligent learning device 80 and processes data, thereby monitoring the intelligent learning device as a whole. Optionally, the processor 801 may include one or more processing units; preferably, the processor 801 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communication and wired communication. It is understandable that the above-mentioned modem processor may not be integrated into the processor 801.

[0095] The memory 802 can be used to store software programs and modules. The processor 801 executes various functional applications and data processing of the intelligent learning device 80 by running the software programs and modules stored in the memory 802. The memory 802 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function, etc.; the data storage area can store data created according to the use of the intelligent learning device 80, etc. In addition, the memory 802 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0096] The main screen 803 may include a human-computer interaction module for receiving interactive selection operations input by the user and displaying the current screen of the intelligent learning device 80. Specifically, the main screen 803 may include a display panel and a touch panel. The display panel may be configured in the form of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), etc. The touch panel may collect the user's contact or non-contact operation on or near it (such as the user's operation on or near the touch panel using any suitable object or accessory such as a finger, stylus, etc., and may also include somatosensory operation; the operation includes single-point control operation, multi-point control operation and other operation types.), and drive the corresponding connection device according to a pre-set program. Optionally, the touch panel may include two parts: a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch position and posture, detects the touch signal brought by the touch operation, and transmits the touch signal to the processor 801 for processing. In addition, the touch panel can be implemented by various types such as resistive, capacitive, infrared and surface acoustic wave, and any technology developed in the future can be used to implement the touch panel. Further, the touch panel can cover the display panel, and the user can operate on or near the touch panel covered on the display panel according to the content displayed on the display panel (the display content includes but is not limited to soft keyboard, virtual mouse, virtual button, icon, etc.), and the touch panel detects the operation on or near it, and transmits it to the processor 801 through the I / O subsystem to determine the user input, and then the processor 801 provides corresponding visual output on the display screen through the I / O subsystem according to the user input.

[0097] The camera 804 can be used as a camera module for collecting real-time images. In this application, the camera 804 is mainly used to collect images to display on the current application. The camera 804 can be configured just above the main screen 803 or integrated under the main screen. This application does not impose any restrictions on this.

[0098] Although not shown, the intelligent learning device 80 may also include a communication interface, such as a Type C interface, a USB interface, a graphics card interface, a Bluetooth module, a WIFI module, a mobile communication module, etc. The intelligent learning device 80 may also include a power supply (such as a battery) for powering each component. Preferably, the power supply may be logically connected to the processor 801 through a power management system, so that the power management system can manage charging, discharging, and power consumption. The intelligent learning device 80 may also include a camera, a Bluetooth module, an external mouse, etc., which will not be repeated here.

[0099] The processor 801 may call the program code to perform the following operations:

[0100] When detecting that the screen mode of the current application is a portrait mode, obtaining a portrait parameter corresponding to the portrait mode;

[0101] When it is detected that the current application turns on the camera function, controlling the camera of the intelligent learning device to capture an image according to the vertical screen parameter;

[0102] Acquire a preset cropping mode for the current application, and crop the image according to the preset cropping mode to obtain a target image;

[0103] The target image is displayed to the current application.

[0104] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method described in the above embodiment.

[0105] It should be noted that, in each of the above-mentioned embodiments, there is not necessarily a certain order between the above-mentioned steps. A person skilled in the art can understand, based on the description of the embodiments of the present application, that in different embodiments, the above-mentioned steps may have different execution orders, that is, they may be executed in parallel, may be executed interchangeably, and so on.

[0106] The above described device or equipment embodiments are merely illustrative, wherein the unit modules described as separate components may or may not be physically separated, and the components displayed as module units may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network module units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0107] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, or of course by hardware. Based on this understanding, the above technical solution, in essence or in other words, the part that contributes to the relevant technology, can be embodied in the form of a computer software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for enabling an intelligent learning device to execute the methods described in each embodiment or some parts of the embodiment.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Under the concept of the present application, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes in different aspects of the present application as described above, which are not provided in detail for the sake of simplicity. Although the present application has been described in detail with reference to the aforementioned embodiments, a person of ordinary skill in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features can be replaced by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. An image cropping method, characterized in that: Applied to an intelligent learning device, the method comprises: When detecting that the screen mode of the current application is a portrait mode, obtaining a portrait parameter corresponding to the portrait mode; When it is detected that the current application turns on the camera function, controlling the camera of the intelligent learning device to capture an image according to the vertical screen parameter; Acquire a preset cropping mode for the current application, and crop the image according to the preset cropping mode to obtain a target image; The target image is displayed to the current application.

2. The method according to claim 1, characterized in that The method further comprises: When it is detected that the screen mode of the current application is the horizontal screen mode, obtaining horizontal screen parameters corresponding to the horizontal screen mode, wherein the horizontal screen parameters are default screen parameters of the intelligent learning device; When it is detected that the current application turns on the camera function, controlling the camera of the intelligent learning device to capture a horizontal screen image according to the horizontal screen parameter; And display the horizontal screen image to the current application.

3. The method according to claim 1, characterized in that The vertical screen parameters are screen parameters simulated by the intelligent learning device for the vertical screen mode, and the vertical screen parameters include at least one or more of screen angle, camera angle information, and gravity sensor information when the screen state is in the vertical screen state.

4. The method according to claim 1, characterized in that The acquiring a preset cropping mode for the current application and cropping the image according to the preset cropping mode to obtain a target image includes: Acquire a preset cropping mode for the current application, and control the camera to crop and / or scale the captured image according to the preset cropping mode to obtain a preview image; According to the screen status of the intelligent learning terminal, the preview image is adjusted to obtain a target image.

5. The method according to claim 4, characterized in that The step of adjusting the preview image according to the screen state of the intelligent learning terminal to obtain a target image includes: According to the screen state of the intelligent learning terminal, the preview image is rotated according to a preset rotation angle to obtain a target image.

6. The method according to claim 1, characterized in that The method further comprises: When it is detected that the user performs a first change operation of the preset cropping mode on the current application, the preset cropping mode is changed according to the first change operation and takes effect when the camera captures the next frame of image.

7. The method according to claim 1, characterized in that The method further comprises: When a change in the screen state of the intelligent learning device is detected, a prompt message is displayed in a pop-up window, and the prompt message is used to remind the user whether to change the screen mode of the current application; If a second change operation of the user for changing the screen mode is detected, the screen mode of the current application is changed according to the second change operation.

8. An image cropping device, characterized in that: The device comprises: An acquisition module, configured to acquire a vertical screen parameter corresponding to the vertical screen mode when detecting that the screen mode of the current application is the vertical screen mode; A collection module, configured to control the camera of the intelligent learning device to collect images according to the vertical screen parameters when detecting that the current application turns on the camera function; A cropping module, used for acquiring a preset cropping mode for the current application, and cropping the image according to the preset cropping mode to obtain a target image; A display module is used to display the target image to the current application.

9. An intelligent learning device, characterized in that: The intelligent learning device comprises a memory and a processor, wherein the memory is connected to the processor, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the intelligent learning device implements the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 7.

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