An image display method and electronic device

Abstract

An image display method and electronic device are disclosed. This method can be applied to fields such as artificial intelligence (AI) and human-computer interaction. The method includes: detecting an input operation (S1001); responding to the input operation by displaying an image selection interface on a screen (S1002); determining at least one image related to the input operation from a set of associated images stored locally or in the cloud (S1003); displaying a thumbnail of the at least one image in the image selection interface and hiding the remaining images (S1004); detecting a first operation for selecting a first thumbnail in the image selection interface (S1005); and performing a processing flow corresponding to the input operation on the first thumbnail (S1006). This method eliminates the need for users to select a target image from a vast number of images, simplifying user operation.

Description

[0001] Cross-references to related applications

[0002] This application claims priority to Chinese Patent Application No. 201910683677.2, filed on July 26, 2019, entitled "An Image Display Method and Electronic Device", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of terminal technology, and in particular to an image display method and electronic device. Background Technology

[0004] With the advancement of terminal technology, the functions of electronic devices have become increasingly sophisticated. Taking mobile phones as an example, image capture is one of the most frequently used functions by users. Therefore, mobile phones may store a large number of pictures.

[0005] However, if a user wants to perform an action on a particular image (such as sharing or deleting it), they need to manually find that image from a massive collection of photos, which is cumbersome and results in a poor user experience. Summary of the Invention

[0006] This application provides an image display method and an electronic device, which can help users quickly locate target images and facilitate user operation.

[0007] In a first aspect, embodiments of this application provide an image display method, which can be executed by an electronic device. The method includes: detecting an input operation; responding to the input operation by displaying an image selection interface on a display screen; determining at least one image related to the input operation from an associated set of images in local storage or cloud storage; displaying a thumbnail of the at least one image in the image selection interface and hiding the remaining images; detecting a first operation of selecting a first thumbnail in the image selection interface; and performing a processing flow corresponding to the input operation on the first thumbnail.

[0008] In some embodiments, an electronic device can determine at least one image associated with an input operation from a set of images based on that input operation. When the electronic device detects that a user has selected a target image from at least one image, it can perform a processing flow corresponding to the input operation on that target image. In this method, the electronic device can filter images that meet the criteria (related to the input operation) from a massive number of images, and then the user can search for the target image from the images filtered by the electronic device, facilitating user operation and improving the user experience.

[0009] In one possible design, hiding the remaining images includes: hiding the other images in the set of images excluding the at least one image.

[0010] In some embodiments, the electronic device can determine at least one image associated with an input operation from a set of images based on the input operation. When the electronic device displays the at least one image, other images in the set of images can be hidden for user convenience, helping the user quickly locate the target image and facilitating user operation.

[0011] In one possible design, the electronic device may also display labeling information that indicates the at least one image is associated with the input operation.

[0012] In some embodiments, the electronic device may display marker information to help users quickly locate the target image and facilitate user operation.

[0013] In one possible design, the display of the marking information includes: displaying the marking information on a thumbnail of each of the at least one image; or, displaying the marking information in an area of ​​the image selection interface where the at least one image is not displayed.

[0014] It should be understood that electronic devices can display the marking information in any form, as long as the marking information can characterize that the at least one image is related to the input operation. This application embodiment does not limit this.

[0015] In one possible design, the marking information includes one or more of icons, text, and images; or, the marking information is displayed on a thumbnail of each of the at least one image, including: highlighting the edges of the thumbnail of each of the at least one image.

[0016] It should be understood that the above are merely examples of several types of identification information, and are not intended to be limiting.

[0017] In one possible design, the associated set of images includes: a set of images containing the same subject; and / or a set of images with a shooting time difference of less than a preset time difference; and / or a set of images taken at the same location; and / or a set of images belonging to the same album; and / or a set of images containing the same content but with different resolutions; and / or a set of images obtained by retouching the same image using different methods.

[0018] It should be understood that the above description of a set of images is merely an example and not a limitation.

[0019] In one possible design, prior to detecting the input operation, the electronic device may also pre-set an associated image for each type of input operation.

[0020] In some embodiments, the electronic device can pre-set associated images for each type of input operation. This allows the electronic device to determine at least one image corresponding to the input operation after detecting it. This method eliminates the need for users to search for target images from a vast database, simplifying operation and improving the user experience.

[0021] In one possible design, the input operation is an operation for publishing an image, performing a processing flow corresponding to the input operation on the first thumbnail, including: performing an image publishing process on the image corresponding to the first thumbnail; or the input operation is an operation for sending an image to a contact, performing a processing flow corresponding to the input operation on the first thumbnail, including: sending the image corresponding to the first thumbnail to the contact.

[0022] In some embodiments, when an electronic device detects an operation to publish an image, a thumbnail of at least one image associated with that operation is displayed. When the electronic device detects that a user has viewed a first thumbnail from the thumbnails of at least one image, it can execute the publishing process for the image corresponding to the first thumbnail. Alternatively, when an electronic device detects an operation to send an image to a contact, a thumbnail of at least one image associated with that operation is displayed. When the electronic device detects that a user has viewed a first thumbnail from the thumbnails of at least one image, it can send the image corresponding to the first thumbnail to the contact. Through this method, the electronic device can filter images related to an input operation based on that operation; that is, the electronic device can filter images that meet the criteria (related to the input operation) from a large number of images. Then, the user can select a target image from the images already filtered by the electronic device, facilitating user operation and improving the user experience.

[0023] In one possible design, determining at least one image associated with the input operation from an associated set of images in local or cloud storage includes: determining the operation type of the input operation; and determining at least one image associated with the operation type based on the operation type.

[0024] For example, when an input operation is to publish an image, the electronic device determines an image suitable for publication. As another example, when an input operation is to share an image with a contact, the electronic device determines an image suitable for sharing with that contact.

[0025] In one possible design, determining the operation type of the input operation includes: determining that the input operation is an operation for publishing an image; and determining at least one image associated with the operation type, based on the operation type, includes: determining at least one image suitable for publishing based on the operation type.

[0026] In some embodiments, electronic devices can determine at least one image suitable for publication from a large number of images, eliminating the need for users to search for the target image from a massive number of images, thus facilitating user operation and improving user experience.

[0027] In one possible design, determining the operation type of the input operation includes: determining that the input operation is an operation for communicating with other contacts; and determining at least one image associated with the operation type, based on the operation type, includes: determining at least one image suitable for sending to other contacts, based on the operation type.

[0028] In some embodiments, electronic devices can determine at least one image suitable for sharing with a contact from a large number of images, eliminating the need for users to search for a target image from a vast number of images, thus simplifying user operation and improving the user experience.

[0029] In one possible design, the at least one image suitable for publication includes: an image of the same type as an previously published image; and / or at least one image that has been edited a preset number of times.

[0030] It should be understood that the above are merely examples of images suitable for publication, and are not limitations. In practical applications, electronic devices can also determine which images are suitable for publication through other means.

[0031] In one possible design, the image suitable for sending to other contacts includes: an image that includes the other contact; and / or an image of the same type as an image previously sent to the other contact.

[0032] It should be understood that the above are merely examples of suitable images for posting, and are not limitations. In practical applications, electronic devices can also determine which images are suitable for sharing with contacts through other means.

[0033] In one possible design, determining at least one image related to the input operation from an associated set of images in local or cloud storage includes: determining information related to the application to which the input operation is targeted; and determining at least one image associated with the relevant information of the application based on the application's information.

[0034] In some embodiments, an electronic device can determine at least one image associated with relevant information of the application based on application-related information. This method eliminates the need for users to search for target images from a vast database, simplifying operation and improving the user experience.

[0035] In one possible design, determining relevant information about the application to which the input operation is targeted includes: determining the type or function of the application to which the input operation is targeted; and determining at least one image associated with the relevant information about the application, based on the relevant information about the application, including: determining at least one image that matches the type or function of the application.

[0036] In some embodiments, the electronic device can determine at least one image based on the type or function of the application. This method eliminates the need for users to search for a target image from a vast number of images, simplifying operation and improving the user experience.

[0037] In one possible design, determining relevant information about the application to which the input operation is targeted includes: determining a history of images posted or shared by the application to which the input operation is targeted; and determining at least one image associated with the relevant information about the application, including: determining at least one image that matches the history of the application.

[0038] In some embodiments, electronic devices can determine at least one image based on the application's history. This method eliminates the need for users to search for a target image from a vast database, simplifying operation and improving the user experience.

[0039] In one possible design, determining at least one image related to the input operation from an associated set of images in local or cloud storage includes: determining time information corresponding to the input operation; and determining at least one image that matches the time information.

[0040] In some embodiments, the electronic device can determine at least one image based on the timing information of the input operation. This method eliminates the need for users to search for a target image from a vast number of images, simplifying operation and improving the user experience.

[0041] In one possible design, determining at least one image related to the input operation from an associated set of images in local storage or cloud storage includes: reading or loading all images from the associated set of images in local storage or cloud storage; determining at least one image related to the input operation from all images in the set of images; and displaying a thumbnail of at least one image in the image selection interface and hiding the remaining images, including: displaying a thumbnail of the at least one image in the image selection interface and not displaying thumbnails of the other images in the image selection interface.

[0042] In some embodiments, the electronic device can read all images from a set of images from local storage or cloud storage, and then select at least one image from all the read images. The electronic device may display only a thumbnail of the selected at least one image in the image selection interface, without displaying thumbnails of other images, for example, other images may be discarded.

[0043] In one possible design, displaying a thumbnail of at least one image in the image selection interface and hiding the remaining images includes: reading or loading the at least one image from the local storage or cloud storage, and displaying a thumbnail of the at least one image in the image selection interface; not reading or loading any other images from the set of images except for the at least one image from the local storage or cloud storage.

[0044] In some embodiments, the electronic device may read only one image related to the input operation from local memory or cloud storage, without reading other images. Therefore, the electronic device may display only a thumbnail of the read at least one image in the image selection interface, without displaying thumbnails of other images.

[0045] In one possible design, displaying a thumbnail of at least one image in the image selection interface and hiding the remaining images includes: preloading the thumbnail of the at least one image from the local storage or cloud storage, without preloading the thumbnails of the other images in the set excluding the at least one image; and displaying the thumbnail of at least one image in the image selection interface.

[0046] In some embodiments, the electronic device may not fully load any images, but instead preload a thumbnail of at least one image related to the input operation, without preloading thumbnails of other images. Therefore, the electronic device can display a thumbnail of at least one preloaded image in the image selection interface, without displaying thumbnails of other images.

[0047] Secondly, embodiments of this application also provide an electronic device. The electronic device includes a display screen, at least one processor, and a memory; the memory is used to store one or more computer programs; when the one or more computer programs stored in the memory are executed by the at least one processor, the electronic device is able to implement the technical solutions described in the first aspect and any possible design of the first aspect.

[0048] Thirdly, embodiments of this application also provide an electronic device, which includes modules / units for performing the methods described in the first aspect or any possible design of the first aspect; these modules / units can be implemented in hardware or by hardware executing corresponding software.

[0049] Fourthly, embodiments of this application also provide a chip, which is coupled to a memory in an electronic device, for calling a computer program stored in the memory and executing the first aspect of the embodiments of this application and any possible design of the first aspect; in the embodiments of this application, "coupling" means that two components are directly or indirectly combined with each other.

[0050] Fifthly, embodiments of this application also provide a computer-readable storage medium, the computer-readable storage medium including a computer program, which, when run on an electronic device, causes the electronic device to execute the first aspect of the embodiments of this application and any possible design of the first aspect.

[0051] Sixthly, a program product according to an embodiment of this application includes instructions that, when the program product is run on an electronic device, cause the electronic device to execute the technical solution of the first aspect of the embodiment of this application and any possible design of the first aspect. Attached Figure Description

[0052] Figure 1A A schematic diagram of the hardware structure of a mobile phone 100 provided in an embodiment of this application;

[0053] Figure 1B A schematic diagram of the software structure of a mobile phone 100 provided in an embodiment of this application;

[0054] Figure 2A A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0055] Figure 2B A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0056] Figure 3A A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0057] Figure 3B A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0058] Figure 4A A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0059] Figure 4B A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0060] Figure 5A A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0061] Figure 5BA schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0062] Figure 6 A schematic diagram illustrating the flow of an image classification method provided in an embodiment of this application;

[0063] Figure 7 A schematic diagram of a model provided in an embodiment of this application;

[0064] Figure 8 A schematic diagram illustrating a model training process provided in one embodiment of this application;

[0065] Figure 9A A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0066] Figure 9B A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0067] Figure 9C A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0068] Figure 9D A schematic diagram of a user graphical interface of a mobile phone 100 provided in an embodiment of this application;

[0069] Figure 10 This is a schematic flowchart of an image display method provided in an embodiment of this application. Detailed Implementation

[0070] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0071] The following explanations of some terms used in the embodiments of this application are provided to facilitate understanding by those skilled in the art.

[0072] The application (app) involved in the embodiments of this application is a software program capable of performing one or more specific functions. Typically, multiple applications can be installed on a terminal. Examples include camera apps, gallery apps, SMS apps, MMS apps, various email apps, WeChat, Tencent QQ, WhatsApp Messenger, Line, Instagram, Kakao Talk, DingTalk, etc. The applications mentioned below can be those pre-installed at the terminal's factory or those downloaded by the user from the network or obtained from other terminals during terminal use.

[0073] The social applications (or social platforms) involved in this application are applications that enable content (such as images and text) sharing. Examples include Facebook, Twitter, Weibo, WeChat, Instagram, Zhihu, LinkedIn, Douban, Tianya, and Xiaohongshu.

[0074] The image selection interface (also known as the image candidate interface) involved in the embodiments of this application can display thumbnails of multiple images for the user to select from, for example, as described below. Figure 2B Interface 203, or Figure 3B The interface 305, etc.

[0075] The thumbnails involved in this application are incomplete images created to facilitate user browsing or to display more images. Incompleteness can refer to compressed images, images reduced in size, images obtained by sampling only a portion of pixels from an image, images displaying only a portion of an image, or images stored in the cloud where only a blurred outline can be displayed locally (images not downloaded from the cloud). For example... Figure 2B Interface 203, or Figure 3B In interfaces such as 305, thumbnails can be displayed, allowing users to select images from the thumbnails.

[0076] The multiple instances mentioned in the embodiments of this application refer to two or more.

[0077] It should be noted that the term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship. Also, in the description of the embodiments in this application, words such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0078] The following describes an electronic device, a graphical user interface (GUI) for such an electronic device, and embodiments for using such an electronic device. In some embodiments of this application, the electronic device may be a portable terminal including a display screen, such as a mobile phone, tablet computer, etc. Exemplary embodiments of the portable electronic device include, but are not limited to, carrying... Alternatively, it could be a portable electronic device with another operating system. The aforementioned portable electronic device could also be other portable electronic devices, such as a digital camera. It should also be understood that in some other embodiments of this application, the aforementioned electronic device may not be a portable electronic device, but rather a desktop computer with a display screen, etc.

[0079] Typically, electronic devices support a variety of applications. These may include one or more of the following: camera apps, instant messaging apps, photo management apps, etc. Instant messaging apps can be varied, such as WeChat, Weibo, QQ, WhatsApp Messenger, Line, Instagram, Kakao Talk, and DingTalk. Through instant messaging apps, users can send text, voice messages, images, video files, and other files to other contacts (or other contacts); alternatively, users can use instant messaging apps to make video or audio calls with other contacts.

[0080] The following text uses a mobile phone as an example of an electronic device. Figure 1A A structural schematic diagram of mobile phone 100 is shown.

[0081] Mobile phone 100 may include processor 110, external memory interface 120, internal memory 121, universal serial bus (USB) interface 130, charging management module 140, power management module 141, battery 142, antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, sensor module 180, buttons 190, motor 191, indicator 192, camera 193, display screen 194, and subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, a barometric pressure sensor 180C, a magnetic sensor 180D, an accelerometer sensor 180E, a distance sensor 180F, a proximity sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0082] Processor 110 may include one or more processing units, such as: application processor (AP), modem processor, graphics processing unit (GPU), image signal processor (ISP), controller, memory, video codec, digital signal processor (DSP), baseband processor, and / or neural network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0083] The controller can serve as the central nervous system and command center of the mobile phone 100. Based on the instruction operation code and timing signals, the controller generates operation control signals to control the fetching and execution of instructions.

[0084] The processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. This memory can store instructions or data that the processor 110 has just used or that are used repeatedly. If the processor 110 needs to use the instruction or data again, it can retrieve it directly from the memory. This avoids repeated accesses, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0085] The processor 100 can run the software code of the image sharing algorithm provided in the embodiments of this application to implement the image sharing process.

[0086] USB port 130 is a USB standard compliant interface, which can be a Mini USB port, Micro USB port, USB Type-C port, etc. USB port 130 can be used to connect a charger to charge mobile phone 100, and can also be used for data transfer between mobile phone 100 and peripheral devices.

[0087] The charging management module 140 receives charging input from the charger. The power management module 141 connects to the battery 142, and the charging management module 140 connects to the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140 to power the processor 110, internal memory 121, external memory, display 194, camera 193, and wireless communication module 160, etc.

[0088] The wireless communication function of mobile phone 100 can be realized through antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, modem processor and baseband processor.

[0089] Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in mobile phone 100 can be used to cover one or more communication frequency bands. Different antennas can also be reused to improve antenna utilization. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In some other embodiments, the antennas can be used in conjunction with a tuning switch.

[0090] The mobile communication module 150 can provide solutions for wireless communication applications including 2G / 3G / 4G / 5G on the mobile phone 100. The mobile communication module 150 may include at least one filter, switch, power amplifier, low-noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves via antenna 1, and perform filtering, amplification, and other processing on the received electromagnetic waves before transmitting them to a modem processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modem processor and convert it into electromagnetic waves for radiation via antenna 1. In some embodiments, at least some functional modules of the mobile communication module 150 may be housed in the processor 110. In some embodiments, at least some functional modules of the mobile communication module 150 and at least some modules of the processor 110 may be housed in the same device.

[0091] The wireless communication module 160 can provide solutions for wireless communication applications on the mobile phone 100, including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared (IR) technologies. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via antenna 2, performs frequency modulation and filtering of the electromagnetic wave signals, and sends the processed signal to processor 110. The wireless communication module 160 can also receive signals to be transmitted from processor 110, perform frequency modulation and amplification, and convert them into electromagnetic waves for radiation via antenna 2.

[0092] In some embodiments, antenna 1 of mobile phone 100 is coupled to mobile communication module 150, and antenna 2 is coupled to wireless communication module 160, enabling mobile phone 100 to communicate with networks and other devices via wireless communication technology. The wireless communication technology may include Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Time Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technologies, etc. The GNSS may include the Global Positioning System (GPS), the Global Navigation Satellite System (GLONASS), the BeiDou Navigation Satellite System (BDS), the Quasi-Zenith Satellite System (QZSS), and / or satellite-based augmentation systems (SBAS).

[0093] The mobile phone 100 implements display functions through a GPU, a display screen 194, and an application processor. The GPU is a microprocessor for image processing, connected to the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations and for graphics rendering. The processor 110 may include one or more GPUs, which execute program instructions to generate or modify display information.

[0094] Display screen 194 is used to display images, videos, etc. Display screen 194 includes a display panel. The display panel may be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a miniature LED, a microLED, a quantum dot light-emitting diode (QLED), etc. In some embodiments, mobile phone 100 may include one or N displays 194, where N is a positive integer greater than 1.

[0095] Camera 193 is used to capture still images or videos. Camera 193 may include a front-facing camera and a rear-facing camera.

[0096] The internal memory 121 can be used to store computer executable program code, which includes instructions. The processor 110 executes various functional applications and data processing of the mobile phone 100 by running the instructions stored in the internal memory 121. The internal memory 121 may include a program storage area and a data storage area. The program storage area may store the operating system and software code for at least one application (such as a camera application, WeChat application, etc.). The data storage area may store data generated during the use of the mobile phone 100 (such as images, videos, etc.). Furthermore, the internal memory 121 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, universal flash storage (UFS), etc.

[0097] The internal memory 121 can also store the software code of the image sharing method provided in the embodiments of this application. When the processor 110 runs the software code, it executes the process steps of the image sharing method to realize the image sharing process.

[0098] The internal memory 121 can also store captured images, models, image classification tags, etc.

[0099] The external storage interface 120 can be used to connect an external storage card, such as a Micro SD card, to expand the storage capacity of the mobile phone 100. The external storage card communicates with the processor 110 through the external storage interface 120 to perform data storage functions. For example, music, video, and other files can be saved on the external storage card.

[0100] Of course, the software code for the image sharing method provided in this application embodiment can also be stored in external memory. The processor 110 can run the software code through the external memory interface 120 to execute the process steps of the image sharing method and realize the image sharing process. Images, models, image classification tags, etc., captured by the mobile phone 100 can also be stored in external memory.

[0101] It should be understood that the user can specify whether to store the image in the internal memory 121 or the external memory. For example, when the mobile phone 100 is currently connected to the external memory, if the mobile phone 100 captures an image, a prompt message can pop up to prompt the user whether to store the image in the external memory or the internal memory 121; of course, there are other ways to specify the storage method, which are not limited in this embodiment; or, when the mobile phone 100 detects that the memory amount of the internal memory 121 is less than a preset amount, it can automatically store the image in the external memory.

[0102] The mobile phone 100 can achieve audio functions such as music playback and recording through the audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, and application processor.

[0103] The pressure sensor 180A is used to sense pressure signals and can convert the pressure signals into electrical signals. In some embodiments, the pressure sensor 180A may be disposed on the display screen 194.

[0104] The gyroscope sensor 180B can be used to determine the motion attitude of the mobile phone 100. In some embodiments, the angular velocity of the mobile phone 100 about three axes (i.e., the x, y, and z axes) can be determined by the gyroscope sensor 180B. The gyroscope sensor 180B can be used for image stabilization.

[0105] The barometric pressure sensor 180C is used to measure air pressure. In some embodiments, the mobile phone 100 calculates altitude using the air pressure value measured by the barometric pressure sensor 180C to assist in positioning and navigation.

[0106] The magnetic sensor 180D includes a Hall sensor. The mobile phone 100 can use the magnetic sensor 180D to detect the opening and closing of the flip cover. In some embodiments, when the mobile phone 100 is a flip phone, the mobile phone 100 can detect the opening and closing of the flip cover using the magnetic sensor 180D. Then, based on the detected opening and closing state of the cover or the flip cover, features such as automatic flip unlocking can be set.

[0107] The 180E accelerometer can detect the magnitude of acceleration of the mobile phone 100 in various directions (typically three axes). When the mobile phone 100 is stationary, it can detect the magnitude and direction of gravity. It can also be used to identify the posture of electronic devices and applied to applications such as screen orientation switching and pedometers.

[0108] A distance sensor 180F is used to measure distance. The mobile phone 100 can measure distance via infrared or laser. In some embodiments, during a shooting scenario, the mobile phone 100 can utilize the distance sensor 180F to measure distance for fast focusing.

[0109] The proximity sensor 180G may include, for example, a light-emitting diode (LED) and a light detector, such as a photodiode. The LED may be an infrared LED. The mobile phone 100 emits infrared light outward through the LED. The mobile phone 100 uses the photodiode to detect infrared reflected light from nearby objects. When sufficient reflected light is detected, it can be determined that there is an object near the mobile phone 100. When insufficient reflected light is detected, the mobile phone 100 can determine that there is no object near the mobile phone 100. The mobile phone 100 can use the proximity sensor 180G to detect when the user holds the mobile phone 100 close to their ear for a call, so as to automatically turn off the screen to save power. The proximity sensor 180G can also be used in folding case mode and pocket mode for automatic unlocking and screen locking.

[0110] The ambient light sensor 180L is used to detect ambient light levels. The phone 100 can adaptively adjust the brightness of its display 194 based on the detected ambient light. The ambient light sensor 180L can also be used to automatically adjust the white balance when taking photos. The ambient light sensor 180L can also work in conjunction with the proximity sensor 180G to detect whether the phone 100 is in a pocket, preventing accidental touches.

[0111] The fingerprint sensor 180H is used to collect fingerprints. The phone 100 can use the collected fingerprint characteristics to achieve fingerprint unlocking, app access lock, fingerprint photography, fingerprint answering of calls, etc.

[0112] Temperature sensor 180J is used to detect temperature. In some embodiments, mobile phone 100 uses the temperature detected by temperature sensor 180J to execute a temperature handling strategy. For example, when the temperature reported by temperature sensor 180J exceeds a threshold, mobile phone 100 reduces the performance of the processor located near temperature sensor 180J to reduce power consumption and implement thermal protection. In other embodiments, when the temperature is below another threshold, mobile phone 100 heats battery 142 to prevent abnormal shutdown of mobile phone 100 due to low temperature. In still other embodiments, when the temperature is below yet another threshold, mobile phone 100 boosts the output voltage of battery 142 to prevent abnormal shutdown caused by low temperature.

[0113] Touch sensor 180K, also known as a "touch panel," can be located on display screen 194. The touch sensor 180K and display screen 194 together form a touchscreen, also known as a "touchscreen." Touch sensor 180K detects touch operations applied to or near it. The touch sensor can transmit the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through display screen 194. In other embodiments, touch sensor 180K may also be located on the surface of mobile phone 100, in a different position than display screen 194.

[0114] The bone conduction sensor 180M can acquire vibration signals. In some embodiments, the bone conduction sensor 180M can acquire vibration signals from vibrating bone fragments in the human vocal cords. The bone conduction sensor 180M can also contact the human pulse to receive blood pressure signals.

[0115] Keypad 190 includes a power button, volume buttons, etc. Keypad 190 can be a mechanical keypad or a touch keypad. Mobile phone 100 can receive keypad input and generate key signal inputs related to user settings and function control of mobile phone 100.

[0116] Motor 191 can generate vibration alerts. Motor 191 can be used for incoming call vibration alerts or for touch vibration feedback. For example, different vibration feedback effects can be corresponding to touch operations applied to different applications (such as taking photos, playing audio, etc.).

[0117] Indicator 192 can be an indicator light, used to indicate charging status, power changes, or to indicate messages, missed calls, notifications, etc.

[0118] The SIM card interface 195 is used to connect the SIM card. The SIM card can be inserted into or removed from the SIM card interface 195 to make contact with or separate from the mobile phone 100.

[0119] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the mobile phone 100. In other embodiments of this application, the mobile phone 100 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0120] It should be noted that in existing technology, mobile phones 100 store a massive number of images. When a mobile phone 100 detects an input operation (such as posting an image or sending an image to other contacts), it displays thumbnails of all images. Users need to select the target image from this vast number of thumbnails, which is cumbersome. Furthermore, thumbnails often do not clearly display the image content, so users cannot accurately select the target image thumbnail with the naked eye. They typically need to click on a thumbnail to display that image, then swipe left or right to display other images before finally selecting the target image. This process is cumbersome and results in a poor user experience.

[0121] In this embodiment, the mobile phone 100 can analyze the user's image operation behavior and categorize the images into different image types based on this behavior. For example, it can categorize images as "user likes" and "user dislikes"; or as "suitable for posting" and "unsuitable for posting"; or as "suitable for sending to other contacts" and "unsuitable for sending to other contacts," and so on. When the mobile phone 100 detects an operation to post an image, it can recommend "user likes" or "suitable for posting" images to the user; when the mobile phone 100 detects an operation to send an image to other contacts, it can recommend "user likes" or "suitable for sending to other contacts" images to the user. Therefore, the mobile phone 100 can recommend images related to the user's input operation, eliminating the need to search for images in a vast database, thus facilitating user operation.

[0122] In some embodiments, the software system of mobile phone 100 may adopt a layered architecture, event-driven architecture, microkernel architecture, microservice architecture, or cloud architecture. The following embodiments use the layered architecture Android system as an example to illustrate the software structure of mobile phone 100.

[0123] Figure 1BThis is a software structure block diagram of the mobile phone 100 provided in this application embodiment. The layered architecture divides the software into several layers, each with a clear role and division of labor. Layers communicate with each other through software interfaces. In some embodiments, the Android system can be divided into four layers, from top to bottom: the application layer, the application framework layer, the Android runtime and system libraries, and the kernel layer. The application layer may include a series of application packages. For example... Figure 1B As shown, the application package can include applications such as camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, and SMS. The application framework layer provides application programming interfaces (APIs) and programming frameworks for the applications in the application layer. The application framework layer includes some predefined functions.

[0124] like Figure 1B As shown, the application framework layer may include a window manager, content provider, view system, phone manager, resource manager, notification manager, etc. The window manager manages window programs. It can obtain the screen size, determine if a status bar is present, lock the screen, and capture the screen. The content provider stores and retrieves data, making this data accessible to applications. This data may include videos, images, audio, made and received calls, browsing history and bookmarks, phone books, etc. The view system includes visual controls, such as controls for displaying text and controls for displaying images. The view system can be used to build applications. The display interface can consist of one or more views. For example, a display interface including a text notification icon may include a view for displaying text and a view for displaying images. The phone manager provides communication functions for the mobile phone, such as managing call status (including connection, hang-up, etc.). The resource manager provides various resources for the application, such as localized strings, icons, images, layout files, video files, etc. The notification manager allows the application to display notification information in the status bar, which can be used to convey informational messages and can disappear automatically after a short pause without user interaction. For example, the notification manager is used to notify users of download completions and message alerts. The notification manager can also display notifications as icons or scrolling text in the system's top status bar, such as notifications from background applications, or as dialog boxes on the screen. Examples include displaying text messages in the status bar, emitting alert sounds, causing electronic devices to vibrate, and flashing indicator lights.

[0125] The Android Runtime comprises the core libraries and the virtual machine. The Android Runtime is responsible for scheduling and managing the Android system. The core libraries consist of two parts: one part contains the functionalities that Java calls, and the other part is the core Android library itself. The application layer and application framework layer run within the virtual machine. The virtual machine executes the Java files from the application layer and application framework layer as binary files. The virtual machine is used for managing object lifecycles, stack management, thread management, security and exception management, and garbage collection, among other functions.

[0126] The system library can include multiple functional modules. For example: a surface manager, media libraries, 3D graphics processing libraries (e.g., OpenGL ES), and 2D graphics engines (e.g., SGL). The surface manager manages the display subsystem and provides fusion of 2D and 3D layers for multiple applications. The media libraries support playback and recording of various common audio and video formats, as well as still image files. The media libraries support various audio and video encoding formats, such as MPEG4, H.264, MP3, AAC, AMR, JPG, and PNG. The 3D graphics processing libraries are used to implement 3D graphics drawing, image rendering, compositing, and layer processing. The 2D graphics engine is the drawing engine for 2D graphics.

[0127] The kernel layer is the layer between hardware and software. The kernel layer contains at least the display driver, camera driver, audio driver, and sensor driver.

[0128] In the embodiments of this application, see Figure 1B The system library may also include an image processing library. When an operation is detected targeting an image, the image can be classified. For example, when an operation is detected targeting at least one image in an associated set of images, that at least one image is classified. When an input operation is detected again, the image processing library can determine at least one image related to that input operation from the associated set of images and recommend that at least one image.

[0129] For ease of understanding, the following embodiments of this application will be described using the following methods: Figure 1A and Figure 1B Taking a mobile phone with the structure shown as an example, the image display method provided by the embodiments of this application will be specifically described in conjunction with the accompanying drawings. The implementation process of the technical solution of this application will be introduced below according to different application scenarios.

[0130] Scenario 1 - Gallery Application.

[0131] See Figure 2AAs shown in (a), mobile phone 100 displays a main interface 201, which includes application icons for multiple applications (camera application, gallery application, WeChat application, etc.). When mobile phone 100 detects that the user triggers the operation of the gallery application icon 202, mobile phone 100 displays the gallery application interface 203, as shown in (a). Figure 2A As shown in (b) of the diagram.

[0132] See Figure 2A As shown in (b), the gallery application interface 203 displayed on the mobile phone 100 includes thumbnails of the pictures stored on the mobile phone 100. Figure 2A In (b) of the example, three thumbnails of images are used.

[0133] In one example, the thumbnails of "user-liked" images display a label indicating that the image is a "user-liked" image type; that is, images with the label on their thumbnails are "user-liked" image types, while images without the label are "user-disliked" image types. See also Figure 2A As shown in (b), image 204 displays label 207 and image 206 displays label 208, meaning that images 204 and 205 are "user-favorited" image types.

[0134] For example, when mobile phone 100 detects that the user has triggered the operation of marker 207, it displays a prompt message. This prompt message is used to inform the user that image 204 is an image the user likes. See [link to relevant documentation]. Figure 2A As shown in (c), the mobile phone 100 can also display a confirm control and a cancel control. When the confirm control is triggered, the mobile phone 100 determines that the image 204 is the type the user likes. When the cancel control is triggered, the mobile phone 100 determines that the image 204 is not the type the user likes, and then cancels the display of mark 207 on the image 204.

[0135] See other examples. Figure 2B As shown in (a), the thumbnails of "user-favorited" images have thickened edges, while the thumbnails of other images do not; in some other examples, the thumbnails of "user-favorited" images are larger, while the thumbnails of other images are smaller, for example, see [link to example]. Figure 2B As shown in (b) of the diagram, thumbnails 204 and 206 are larger than thumbnail 205. See also some other examples. Figure 2B As shown in (c), the gallery application interface 203 includes a "picture categorization" control 210. When the control 210 is triggered, the mobile phone 100 displays multiple options. See [link to image description]. Figure 2BAs shown in (d), mobile phone 100 displays option 211 for "User-favorited pictures," option 212 for "Collected pictures," option 213 for "Pictures suitable for posting," and option 214 for "Pictures suitable for sending to other contacts." Assuming option 211 is selected, mobile phone 100 only displays pictures "User-favorited," see [reference]. Figure 2B As shown in (d), only images 204 and 206 are displayed.

[0136] In Scenario 1, in the gallery application interface, different types of images display different identification information, making it convenient for users to quickly find images. Moreover, the image categories are divided by the phone based on the user's image operation behavior, so the classification of image categories conforms to the user's operating habits and helps to improve the user experience.

[0137] Scenario 2 - Social Platforms.

[0138] See Figure 3A As shown in (a), mobile phone 100 displays the WeChat application interface 301, which includes a control 302. When the control 302 is triggered, mobile phone 100 displays a camera option 303 and a picture selection option 304 from the gallery. See also Figure 3A As shown in (b) of the diagram.

[0139] When phone 100 detects that the option 304 to select a picture from the gallery has been selected, phone 100 displays the picture selection interface 305, such as... Figure 3A As shown in (c) in the image selection interface 305, there are one or more images.

[0140] As an example, see Figure 3A As shown in (c), the image selection interface 305 includes thumbnails of multiple images from the image library of the mobile phone 100. Images whose thumbnails are "liked by the user" may display a marker, while images whose thumbnails do not contain a marker are images whose thumbnails are "disliked by the user." Alternatively, the image selection interface 305 includes thumbnails of multiple images from the image library of the mobile phone 100, where images whose thumbnails are "suitable for publication" display a marker, while images whose thumbnails are "unsuitable for publication" do not display a marker. Alternatively, the image selection interface 305 includes thumbnails of multiple images from the image library of the mobile phone 100, where images whose thumbnails are "liked by the user" display a first marker, and images whose thumbnails are "suitable for publication" display a second marker, the first and second markers being different.

[0141] like Figure 3A As shown in (c), the thumbnails of images 306 and 308 display markers indicating whether images 306 and 308 are "user-favorited" or "suitable for posting." When mobile phone 100 detects that image 308 has been selected, it displays as shown below. Figure 3A The interface shown in (d) is shown in the image.

[0142] See also some other examples. Figure 3B As shown in (a), in the image selection interface 305, the thumbnails of the images that are "liked by the user" or "suitable for publication" (such as images 306 and 308) are larger than the thumbnails of other images (such as image 307).

[0143] For example, see Figure 3B In (b) of the image selection interface 305, the edges of the thumbnails of the images that are "liked by the user" or "suitable for publication" (images 306 and 308) are thickened.

[0144] For example, see Figure 3B As shown in (c), the image selection interface 305 only includes thumbnails of two images. These two images are selected by the mobile phone 100 from a large number of images in its gallery as "user-favorites" and / or "suitable for posting." In this example, the image selection interface 305 only includes recommended images and does not include unrecommended images; for example, unrecommended images can be hidden. Of course, see [further details omitted]. Figure 3B As shown in (c), the image selection interface 305 includes a "View More" control. When the mobile phone 100 detects that the control has been triggered, the mobile phone 100 displays more thumbnails.

[0145] For example, see Figure 3B As shown in (d) of the image selection interface 305, the "Image Type" control displays multiple options on the mobile phone 100 when triggered: "Images the User Likes" option 311, "Images in Favorites" option 312, "Images Suitable for Posting" option 313, and "Images Suitable for Sending to Other Contacts" option 314. Assuming option 311 is selected, the mobile phone 100 only displays images from the "User Likes" list. (See [reference]). Figure 3B As shown in (d), mobile phone 100 only displays pictures 306 and 308.

[0146] For example, see Figure 3B As shown in (e), different areas of the image selection interface 305 display different types of images. The first area displays images that the user likes. The second area displays images suitable for publication. In some embodiments, the same image may exist in both the user's favorite image and the suitable image for publication.

[0147] exist Figure 3A and Figure 3BTaking WeChat Moments as an example, similar approaches can be used for other social media platforms (such as Weibo, Xiaohongshu, Facebook, Twitter, etc.), which will not be elaborated further.

[0148] In scenario 2, when the phone detects an action to post an image on a social platform, it can display images that are "suitable for posting" or "liked by the user," or display different identifiers for different types of images (e.g., "suitable for posting" images display the first identifier, and "liked by the user" images display the second identifier). This makes it easier for users to quickly find images. Moreover, the image categories are categorized by the phone based on the user's image operation behavior, so the classification of image categories conforms to the user's operating habits and helps to improve the user experience.

[0149] Scenario 3 - Instant Messaging Applications.

[0150] See Figure 4A As shown in (a), mobile phone 100 displays an interface 401 of the SMS application, which is the communication interface between the user and other contacts. Interface 401 includes a control 402, and when mobile phone 100 detects that control 402 is triggered, it displays a gallery control 403 and a camera control 404.

[0151] As an example, when phone 100 detects that the user has triggered the gallery control 403, it displays as follows: Figure 4A The interface 405 shown in (b) includes thumbnails of multiple images. Image 406 is marked with a label 407 to indicate that it is a "user-favorited" image, and image 411 is marked with a label 412 to indicate that it is a "user-favorited" image. Alternatively, label 407 indicates that image 406 is "suitable for sending to other contacts," and label 412 indicates that image 411 is "suitable for sending to other contacts." Alternatively, images 406 and 411 may display different labels. For example, image 406 may display a first label, and image 411 a second label. The first label indicates that image 406 is a "user-favorited" image, and the second label indicates that image 411 is "suitable for sending to other contacts." If mobile phone 100 detects that image 406 is selected and then detects that the user triggers the "send" control 408, then mobile phone 100 sends image 406 to the contact, and mobile phone 100 displays as shown below. Figure 4A Interface 409 is shown in (c) in the diagram. No markers are displayed on image 410 in interface 409.

[0152] In some embodiments, mobile phone 100 can determine the type of image "suitable to send to a specific contact". A specific contact may include contacts of a specific type, or a particular contact, etc. A specific type of contact can be contacts belonging to the same group / group. For example, in WeChat, a specific type of contact could be all contacts in the same WeChat chat group, or all contacts in the same group (e.g., family members), or all contacts in WeChat whose nicknames share a common word (e.g., teacher). A specific contact can be a specific contact, and the electronic device can determine whether a contact is a specific contact based on the contact's nickname. For example, a specific contact could include contacts whose nicknames are "Dad" or "Mom". For example, if mobile phone 100 learns that certain images (e.g., landscape photos or portrait photos) are frequently sent to a specific contact, it determines that these images are "suitable to send to a specific contact". When mobile phone 100 displays a chat interface with a specific contact (e.g., a WeChat chat interface or a text message chat interface), and detects an operation to send an image, mobile phone 100 displays an image suitable for sending to the specific contact. For example, if mobile phone 100 detects that landscape images are frequently sent to contacts labeled "Dad" or "Mom," mobile phone 100 determines that landscape images are suitable for sending to "Dad" or "Mom." Similarly, if it learns that images of people are frequently sent to contacts labeled "Amy," mobile phone 100 determines that portrait images are suitable for sending to Amy. When mobile phone 100 displays a chat interface with "Dad" or "Mom," or a group chat containing "Dad" and / or "Mom," and detects an operation to send an image, mobile phone 100 can display a thumbnail of an image suitable for sending to "Dad" or "Mom."

[0153] See also some other examples. Figure 4B As shown in (a), the thumbnails of the "user's favorite" or "suitable for sending to other contacts" images in interface 405 (such as images 406 and 411) are larger than the thumbnails of other images.

[0154] For example, see Figure 4B In (b) of the interface 305, the thumbnails of the "User's Favorites" or "Suitable for Sending to Other Contacts" images (images 406 and 411) are thickened, while the edges of other images are thickened.

[0155] For example, see Figure 4BAs shown in (c), interface 405 includes only thumbnails of two images. These two images are selected by phone 100 from a large number of images in its gallery as "user favorites" and / or "suitable for sending to other contacts." In this example, interface 305 does not include other images. Of course, see [link to relevant documentation] for more details. Figure 4B As shown in (c), interface 405 includes a "View More" control. When mobile phone 100 detects an operation on this control, mobile phone 100 displays more thumbnails.

[0156] For example, see Figure 4B As shown in (d) of the diagram, the "Image Type" control in interface 305 displays multiple options on mobile phone 100 when triggered: "Images the User Likes," "Images in Favorites," "Images Suitable for Posting," and "Images Suitable for Sending to Other Contacts." Assuming the "Images Suitable for Sending to Other Contacts" option is selected, mobile phone 100 only displays images suitable for sending to other contacts.

[0157] It should be understood that, Figure 4A Taking SMS applications as an example, a similar approach can be used for other instant messaging applications, which will not be elaborated further.

[0158] It should be noted that, Figure 4A In the illustrated embodiment, when the mobile phone 100 detects an operation to send an image to other contacts, it can display an image that is "suitable for sending to other contacts" or an image that the user likes, or display different identification information for different types of images (e.g., an image that is "suitable for sending to other contacts" displays a first identification, and an image that the user likes displays a second identification). This makes it convenient for the user to quickly find the image. Moreover, the image types are classified by the mobile phone 100 based on the user's image operation behavior, so the classification of image types conforms to the user's operating habits and helps to improve the user experience.

[0159] Scene 4 - Taking pictures.

[0160] See Figure 5A As shown in (a), the mobile phone 100 displays a main interface 501, which includes application icons for multiple applications. When the mobile phone 100 detects that the user has triggered the camera application icon 502, the mobile phone 100 displays the camera application interface 503, as shown in (a). Figure 5A As shown in (b) of the diagram.

[0161] In one example, see Figure 5AAs shown in (b), the camera application interface 503 includes a preview image. The preview image is an image captured by the mobile phone 100 based on preset shooting parameters of the camera. These preset shooting parameters can be shooting parameters analyzed by the mobile phone 100 based on images the user prefers. For example, if the mobile phone 100 learns that the user prefers images with high brightness, it will adjust the camera's shooting parameters, such as increasing the exposure value. Therefore, in this method, after the mobile phone 100 launches the camera application, it defaults to capturing images with preset shooting parameters, making the captured images more likely to be images the user prefers.

[0162] In another example, see Figure 5B As shown in (a), the camera application interface 503 includes a control 504. When the mobile phone 100 detects that the control 504 has been triggered, a prompt message 505 is displayed on the interface 503. The prompt message 505 prompts the user that the mobile phone 100 should take a picture using a picture the user likes as a template. The mobile phone 100 adjusts the shooting parameters to the shooting parameters analyzed based on the picture the user likes.

[0163] In yet another example, see Figure 5B As shown in (b), the camera application interface 503 includes a control 504. When the mobile phone 100 detects that the control 504 has been triggered, the interface 503 displays a shooting mode selection box. The shooting mode selection box includes controls corresponding to various shooting modules, including a control 505 for "using a user's favorite picture as a template". When the mobile phone 100 detects that the control 505 has been triggered, the mobile phone 100 adjusts the shooting parameters to the shooting parameters analyzed based on the user's favorite picture.

[0164] In yet another example, see Figure 5B As shown in (c), the camera application interface 503 includes a "glowing stick" control 504. When the mobile phone 100 detects that the "glowing stick" control 504 is triggered, the mobile phone 100 displays one or more options, such as the "use favorite picture as template" option 505. When the mobile phone 100 detects that option 505 is selected, the mobile phone 100 adjusts the shooting parameters to the shooting parameters analyzed based on the user's favorite picture.

[0165] The following example describes the process by which mobile phone 100 divides stored images into two image types: "user likes" and "user dislikes".

[0166] See Figure 6 The diagram shown is a schematic representation of the image classification process provided in an embodiment of this application. Figure 6 As shown, the process may include:

[0167] S601: Mobile phone 100 detects operations on images, including actions such as deleting, viewing, sharing, saving, and editing images.

[0168] Assuming that phone 100 stores a large number of pictures, some of which have been viewed frequently by users, or some of which have been edited (e.g., using photo editing software); and some of which have been deleted or not viewed for a long time, phone 100 can track the user actions for each picture.

[0169] For example, see Table 1, which provides an example of the operational behavior for each image as recorded by Mobile Phone 100.

[0170] Image logo Operational behavior Image ID1 Viewed 3 times / day Image ID2 Share to WeChat Moments Image ID3 delete Image ID4 Viewed 0 times / day

[0171] Table 1

[0172] S602: Based on this operation, mobile phone 100 categorizes images into "user-liked" images and "user-disliked" images.

[0173] It should be understood that there are multiple ways for Mobile 100 to categorize images. For example, Mobile 100 can use artificial intelligence (AI) learning (such as using AI models) to divide the images in its gallery into "user-liked" and "user-disliked" images, then add a "like" tag to the "user-liked" images and a "disliked" tag to the "user-disliked" images.

[0174] For example, taking the action of viewing as an example, mobile phone 100 can mark images viewed more than a preset number of times as images the user likes, and images viewed less than or equal to a preset number of times as images the user dislikes. Similarly, taking the action of sharing as an example, mobile phone 100 can mark images shared more than a preset number of times as images the user likes, and images shared less than or equal to a preset number of times as images the user dislikes.

[0175] For example, see Table 2, which provides an example of how mobile phone 100 determines a user's level of liking for each picture.

[0176] Image logo Operational behavior Liking Image ID1 Viewed 3 times / day like Image ID2 Share to a social media app like Image ID3 delete dislike Image ID4 Viewed 0 times / day dislike

[0177] Table 2

[0178] It should be noted that the degree of liking can be represented by "yes" or "no", with "yes" indicating liking and "no" indicating disliking; or, the degree of liking can also be represented by a score, with a higher score indicating a greater degree of liking and a lower score indicating a lesser degree of liking; the score can be a 10-point system, a 100-point system, etc., and this application embodiment does not limit it.

[0179] The following example illustrates the process by which mobile phone 100 uses an AI model to classify images into "user-liked" and "user-disliked" image types.

[0180] In some embodiments, the model can be, for example, a neural network unit, a machine learning model, etc. Typically, the model can include model parameters. Using the input parameters, model parameters, and related algorithms, the mobile phone 100 can obtain an output result, which can be a classification label. See also Figure 7 The image shows an example of an algorithm related to model parameters:

[0181]

[0182] Where x1, x2-xn are multiple input parameters; w1, w2-wn are the coefficients (also called weights) of each input parameter; b is the offset of each input parameter (used to indicate the intercept of u with respect to the origin); f is a function (such as the Sigmoid function, tanh function, etc.) used to ensure that the output value range is within the interval [0,1]. In some embodiments, the input parameter is x, and the model parameter is the weight w. i The output parameter is y, along with the offset b. When specific values ​​for w, b, and x are given, the output result y can be obtained using the above formula. It should be noted that... Figure 7 This is merely an example of a pattern for ease of understanding and is not intended to limit the pattern of this application.

[0183] It should be understood that in the embodiments of this application, the input parameter x is one or more images (hereinafter referred to as: input images). Given a determined model parameter, an output result can be obtained through a model-related algorithm. This output result can be the category label to which one or more input images belong. For example, the category label can be "user likes" or "user dislikes". The model usage process can be as follows: using one or more images as input parameters, using the model parameters (e.g., the trained model parameters), running a model-related algorithm, and obtaining an output result. This output result can be the label of the input image, such as "yes" or "no". In some embodiments, the output result can also be obtained based on the probability that the input image belongs to the "like" label (or the probability that it belongs to the "dislike" label). For example, if the probability that an image belongs to the "like" label is 0.9, and the mobile phone 100 can determine that the input image belongs to the "user likes" category label, then the output result can be "yes".

[0184] It should be noted that model usage is divided into the "training process" and the "usage process." The model training process refers to the process of determining the model parameters. The following examples illustrate the model training process. See also... Figure 8 The training process of the model can include:

[0185] S801: Get a set of related images.

[0186] In some embodiments, a "correlated" set of images can be at least two images, and "correlated" can mean that the images are associated with each other in terms of content, shooting time, shooting location, etc. As an example, if mobile phone 100 takes three consecutive photos, then these three images are a related set of images. As other examples, if mobile phone 100 takes three photos of the same object, that is, if these three images contain the same object (also called the subject), then these three images are also a related set of images. As yet another example, if mobile phone 100 takes three photos within a certain time period (e.g., within 30 minutes), then these three images can be a related set of images.

[0187] S802: Detect the operation behavior for the first image in the set of images.

[0188] Users can perform different operations on images within a related set of images. For example, if a related set of images includes three images featuring the same person, and the phone detects an image posting operation (such as posting to WeChat Moments) on one of these images, the phone determines that the image is a "suitable for posting" type. The phone can then add tags to the image, such as a "suitable for posting" tag.

[0189] S803: Add a label to the first image according to the operation behavior.

[0190] It should be understood that the mobile phone 100 can determine the image type of an image based on the user's operation behavior on an image in a related set of images, and then add appropriate tags to the image.

[0191] S804: Using the first image as input parameters, determine the initial model parameters, run calculations related to the model parameters, and obtain the output result, which may be the label of the first image.

[0192] S805: Determine whether the output result is the same as the label of the first image determined in S803. If yes, training ends; otherwise, execute S806.

[0193] S806: Adjust model parameters.

[0194] S807: Using the first image as input parameters, run the algorithm related to the model parameters using the adjusted model parameters to obtain a new output result.

[0195] by Figure 7 For example, the model training process: given x... i In the case of y, determine w i The process of b. In some embodiments, when x is known i In the case of determining initial w0 and b0, calculate the above formula (1) to obtain y0, and compare whether the difference between y0 and the known y is small. If so, the model training is complete; otherwise, adjust the initial w0 and b0, for example, to w1 and b1, and then, given x... i Given w1 and b1, calculate formula (1) again to obtain y1, and then compare the difference between y1 and the known y. The model training ends when the difference between the obtained yn and the known y is small.

[0196] S808: Determine whether the output result is the same as the label of the first image determined in S803. If yes, training ends; otherwise, execute S806.

[0197] For example, if a mobile phone captures two related images, and the mobile phone detects that the user posted the first image on their WeChat Moments but did not post the second image, then the first image is labeled as an image the user likes, and the second image is labeled as an image the user dislikes. The mobile phone uses the first image as the positive training set and the second image as the negative training set.

[0198] Mobile Phone 100 takes the first and second images as input parameters, uses model parameters, and runs a model-related algorithm to obtain a first output result and a second output result. If the first output result indicates that the first image is a picture the user likes, and the second output result indicates that the second image is a picture the user dislikes (i.e., the labels of the first and second output results are consistent), then Mobile Phone 100 does not need to adjust the model parameters. If the labels of the first and second output results are inconsistent, or the labels of the first and second output results are inconsistent, then the model parameters are adjusted until the labels of the first and second output results are consistent, at which point model training ends.

[0199] In the above process, the labels used by the mobile phone 100 during model training are either images that the user likes or images that the user dislikes. Therefore, the function of the trained model parameters is to classify images into categories that the user likes or dislikes. In some embodiments, the mobile phone 100 may store one or more models. If multiple models are stored, each model may have a different function. For example, one model may be used to classify images into categories that the user likes or dislikes, while another model may be used to classify images into categories that the user deems suitable for posting or unsuitable for posting.

[0200] In some embodiments, after model training is completed, the process of using the model includes: the mobile phone 100 using one or more images as input parameters to the model, and then using known model parameters (determined during model training, for example, w)... i In cases b), the model-related algorithm is run to determine the output, which is the classification label of one or more input images.

[0201] In some embodiments, the mobile phone 100 may periodically train the model or use the model to classify images, or the mobile phone 100 may train the model or use the model to classify images when idle (e.g., when the user has not operated the mobile phone 100 for a long time). This application embodiment does not limit the scope of the invention.

[0202] Below are some examples of how Mobile100 uses AI models to categorize images as either liked or disliked by the user.

[0203] Example 1:

[0204] The phone captured three images; see below. Figure 9AAs shown, the user deleted the first two images and kept the third image (or the user viewed the third image more often than the first two, or the third image was modified (e.g., photo editing), while the first two images remained unchanged). The phone detects the user's different actions on these three images, determining that the user prefers the third image. The first two images are then used as the positive training set, and the third image as the negative training set to train the AI ​​model, resulting in a trained model. This trained model can then classify images with fewer people in the background as liked by the user, and images with more people in the background as disliked by the user.

[0205] If the mobile phone 100 takes another picture, it can input the picture into the AI ​​model and run the AI ​​model to perform calculations. If it determines that there are few people in the background of the picture, it will output "yes"; if there are many people, it will output "no". "Yes" indicates that the user likes it, and "no" indicates that the user dislikes it.

[0206] Optionally, for images that the user likes, the mobile phone 100 displays a label on the image's thumbnail. For images whose output result is "no", the mobile phone 100 can output a prompt message to remind the user to delete the image.

[0207] Example 2:

[0208] The phone captured three images, as shown below. Figure 9B As shown, the user deleted the first two images and kept the third. The phone detected the user's different actions on these three images, determining that the user preferred the third image. The first two images were then used as the positive training set, and the third image as the negative training set to train the AI ​​model, resulting in a trained model. This trained model can then classify images without watermarks as images the user likes and images with watermarks as images the user dislikes.

[0209] After the phone takes another picture, it inputs the picture into the AI ​​model and runs the AI ​​model to perform calculations. If the model determines that there is no watermark on the picture, it outputs "yes"; if there is, it outputs "no". "Yes" indicates that the user likes it, and "no" indicates that the user does not like it.

[0210] Example 3:

[0211] The phone captured three images, as shown below. Figure 9CAs shown, the user deleted the first two images and kept the third. The phone detected the user's different actions on these three images, determining that the user preferred the third image. The first two images were then used as the positive training set, and the third image as the negative training set to train the AI ​​model, resulting in a trained model. This trained model can then classify images with no shadows on faces as images the user likes, and images with shadows on faces as images the user dislikes.

[0212] After the phone takes another picture, it inputs the image into the AI ​​model and runs the AI ​​model to perform calculations. If the model determines that there is no shadow on the face of the person in the picture, it outputs "yes"; otherwise, it outputs "no". "Yes" indicates that the user likes it, and "no" indicates that the user does not like it.

[0213] Example 4:

[0214] The phone captured three images, as shown below. Figure 9D As shown, the user deleted the first two images and kept the third. The phone detected the user's different actions on these three images, determining that the user preferred the third image. The first two images were then used as the positive training set, and the third image as the negative training set to train the AI ​​model, resulting in a trained model. This trained model can then classify images with suitable brightness and high clarity as images the user prefers, and images that are too bright or too dark, or have low clarity, as images the user dislikes.

[0215] After the phone takes another picture, it inputs the image into the AI ​​model and runs the AI ​​model to calculate. If the model determines that the image has high clarity and moderate brightness, it outputs "yes". If the image has high or low brightness and low clarity, it outputs "no". "Yes" indicates that the user likes it and "no" indicates that the user does not like it.

[0216] Example 5:

[0217] Taking selfies as an example, people often take photos from multiple angles, such as a 60° left profile, a 30° left profile, a front view, a 30° right profile, a 60° right profile, and so on. Typically, after taking multiple photos, users will filter them, keeping the selected images and deleting others. Alternatively, users may share, save, or repeatedly view a particular image. The phone detects these different user actions on multiple images and can determine the images the user prefers (e.g., determining that shared, saved, or saved images are those the user likes). For example, the phone uses AI learning to determine that the facial angle in images the user prefers is usually a 60° left profile.

[0218] When a user takes another selfie with their phone 100, if the phone 100 determines that the angle of the face in the image is 60 degrees to the left, it can recommend that the user keep the image (or prompt the user that the image can be shared). If the phone 100 determines that the angle of the face in the image is not 60 degrees to the left, it can prompt the user to delete the image.

[0219] Example 5 only uses the angle of a face in a selfie as an example. In practical applications, the phone 100 can also learn the facial expressions, postures, and positioning in group photos that the user likes. For instance, if the user's favorite image features a smiling face and a standing or centered posture, then after capturing an image, if the phone 100 determines that the face in the image is smiling and the posture is standing or centered, the phone 100 will retain the image (or may prompt the user that the image can be shared, etc.).

[0220] The above lists four processes by which the mobile phone 100 learns which types of images the user likes based on the user's image interaction behavior. In practical applications, the mobile phone 100 can learn using any one or more of the above methods in combination, and this application embodiment does not limit this.

[0221] It should be noted that when the phone 100 identifies an image as "disliked by the user" using its AI model, it can output a prompt message to remind the user to delete the image, or automatically delete the image. Alternatively, after detecting that the image has been backed up to the cloud, the phone 100 can automatically delete all images tagged "disliked by the user." Or, after detecting that the image has been backed up to the cloud, the phone 100 can output a prompt message to remind the user whether to delete the image tagged "disliked by the user." Or, after detecting that the image has been backed up to the cloud, the phone 100 can display a control that, when triggered, will delete all "disliked by the user" images.

[0222] The following example describes the process by which mobile phone 100 divides images into "suitable for publication" and "unsuitable for publication".

[0223] Similarly, Mobile100 can use AI models to determine which images are "suitable for publication" and which images are "unsuitable for publication".

[0224] Mobile phone 100 detects the first feature information of previously published images in the stored image library. When mobile phone 100 acquires an image, it determines whether the second feature information of the image satisfies the first feature information. If it does, mobile phone 100 adds a "suitable for publication" tag to the image; otherwise, it adds a "not suitable for publication" tag. For example, if mobile phone 100 detects that a landscape image has been published in the stored image library, after acquiring an image, if the image is a landscape image, mobile phone 100 adds a "suitable for publication" tag to the image.

[0225] It should be noted that in the embodiments of this application, the tag can also be "user likes and is suitable for publication", "user likes but is not suitable for publication", "user dislikes but is suitable for publication", or "user dislikes and is not suitable for publication". That is to say, when the model identifies the tag of the image, it can identify multiple categories of the image, and the embodiments of this application are not limited thereto.

[0226] When the phone detects an action to post an image, it recommends images tagged "suitable for posting" to the user. Figure 3A For example, in (b), when the mobile phone 100 detects that the user has triggered the "Select from Gallery" option 304, it displays thumbnails of multiple images, some of which have a mark on the thumbnails indicating that the image belongs to the "suitable for posting" image category.

[0227] Below is an example of how Mobile100 categorizes images as "suitable for posting" or "unsuitable for posting".

[0228] Example 6:

[0229] The phone stores three images: the first two have been published (or published frequently), and the third has not been published (or published infrequently). The phone detects different user actions on these three images, determining that the first two are suitable for publication, while the third is not. The first two images are then used as the positive training set, and the third as the negative training set, to train an AI model. The trained model can then determine whether an input image meets the criteria for being suitable for publication (e.g., it matches the features of previously published images). If it does, the image is categorized as suitable for publication; otherwise, it is categorized as unsuitable for publication.

[0230] After the mobile phone takes another picture, it inputs the picture into the AI ​​model and runs the AI ​​model to calculate. If the picture is determined to meet the conditions for being suitable for publication, the output result is "yes"; if the picture does not meet the conditions for being suitable for publication, the output result is "no".

[0231] Example 7:

[0232] In some embodiments, the mobile phone 100 can divide an animated image into multiple static images at a time interval of 100ms (this value is an example and is not limited in this application embodiment), input each static image into an AI model, and obtain the output result of each frame image, such as the probability of each frame image belonging to the category tag "user likes". The mobile phone 100 selects the image with the highest probability as the cover image of the animated image.

[0233] The following describes how the phone 100 categorizes images into "suitable for sending to contacts" and "unsuitable for sending to contacts".

[0234] Similarly, Mobile 100 can use AI models to determine which images are "suitable for sending to contacts" and which images are "unsuitable for sending to contacts".

[0235] In some embodiments, the mobile phone 100 detects first feature information of images among all stored images that have been sent to one or more contacts (which can be any contact). When the mobile phone 100 acquires an image, it determines whether second feature information on the image satisfies the first feature information. If it does, the mobile phone 100 adds a "suitable for sending to contacts" tag to the image; otherwise, it adds a "not suitable for sending to contacts" tag to the image. For example, if the mobile phone 100 detects that a screenshot of a stored image has been sent to a contact, and after acquiring an image, if the image is a screenshot of the mobile phone 100, then the mobile phone 100 adds a "suitable for sending to contacts" tag to the image.

[0236] When the phone detects an action to send an image to other contacts, it recommends images tagged "Suitable for sending to contacts" to the user. Figure 4A For example, in (a), when the mobile phone 100 detects that the user has triggered the operation of photo 403, it displays multiple images, some of which have icons on their thumbnails. These icons are used to indicate that the image is suitable to be sent to a contact.

[0237] In other embodiments, the mobile phone 100 can also use an AI model to determine which images are "suitable for sending to a specific contact". A specific contact can include a contact of a specific type, or a particular contact, etc. A specific type of contact can be contacts belonging to the same group / group. Taking WeChat as an example, a specific type of contact could be all contacts in the same WeChat chat group, or all contacts in the same group, or all contacts in the WeChat application whose nicknames share a common word (e.g., teacher). A particular contact can be a specific contact, and the electronic device can determine whether a contact is a specific contact based on the contact's nickname. For example, the mobile phone 100 can detect the first feature information of images sent to a specific contact (e.g., parents) from all stored images. When the mobile phone 100 acquires an image, it determines whether the second feature information on the image satisfies the first feature information. If so, the mobile phone 100 adds a "suitable for sending to a specific contact" tag to the image.

[0238] The various embodiments of this application can be combined arbitrarily to achieve different technical effects.

[0239] In conjunction with the above embodiments and related drawings, this application provides an image display method, which can be used in situations such as... Figure 1A This is implemented in the mobile phone 100 or other electronic devices shown. For example... Figure 10 As shown, the method may include the following steps:

[0240] 1001, Input operation detected.

[0241] As an example, with Figure 3A For example, in (b) of the above, the input operation can be clicking the "Select from Gallery" control 304.

[0242] 1002, in response to the input operation, an image selection interface is displayed on the screen.

[0243] In some embodiments, the image selection interface (also known as the image candidate interface) can display thumbnails of multiple images for the user to select from, for example, Figure 2B Interface 203, or Figure 3B The interface 305, etc.

[0244] 1003, determine at least one image related to the input operation from an associated set of images in local storage or cloud storage.

[0245] In some embodiments, local storage may be internal storage within the electronic device. Images stored in the cloud may be images stored by the electronic device on a cloud server.

[0246] In some embodiments, the associated set of images includes: a set of images containing the same subject, such as... Figure 9C The three images shown; and / or, a set of images with a shooting time difference less than a preset time difference; and / or, a set of images taken at the same location; and / or, a set of images belonging to the same album; and / or, a set of images containing the same content but with different resolutions; and / or, a set of images obtained by applying different editing methods to the same image.

[0247] In some embodiments, the electronic device may determine the image type of each image based on user actions on the images. For example, the electronic device acquires a set of associated images; detects actions performed on each image in the set; the actions include one or more of deleting, retaining, retouching, posting the image, and sending it to a contact; and determines the image type of each image based on the actions; the image type includes an image type suitable for posting or an image type suitable for sending to other contacts.

[0248] For example, electronic devices acquire Figure 9C Of the three images shown, if the third image is determined to be posted on a social media platform, then the third image is considered to be of a suitable type for posting.

[0249] For example, electronic devices obtain Figure 9A If the third image shown is selected from the three images, then the third image is determined to be of a type suitable for sending to other contacts.

[0250] One possible implementation is that the electronic device can determine the operation type of the input operation; and based on the operation type, determine at least one image associated with the operation type. As an example, the electronic device determines that the input operation is for publishing an image; and based on the operation type, determines at least one suitable image for publishing. That is, after detecting an operation for publishing an image, the electronic device can only display thumbnails of the determined suitable images for publishing, for the user's convenience. As another example, the electronic device determines that the input operation is for communicating with other contacts; and based on the operation type, determines at least one image suitable for sending to other contacts. That is, when the electronic device detects an operation for sending an image to other contacts, it can only display thumbnails of the images suitable for sending to other contacts, for the user's convenience.

[0251] In some embodiments, the at least one image suitable for publication may include: at least one previously published image; it may also include images of the same type as previously published images; for example, if at least one previously published image is a portrait (e.g., the person in the image occupies a large area), then portrait images are suitable for publication; or, for example, if at least one previously published image is an image with elongated legs, then the electronic device determines that the image with elongated legs is temporally suitable for publication. The at least one image suitable for publication may also include at least one image that has been edited a preset number of times.

[0252] In some embodiments, the at least one image suitable for sending to other contacts includes: an image that includes the other contact; it may also include an image of the same type as an image previously sent to the other contact. For example, if an image previously sent to a contact was a screenshot, then the image obtained from the screenshot is suitable for sending to that contact.

[0253] Another possible implementation is that the electronic device determines relevant information about the application to which the input operation is targeted; and based on the relevant information about the application, determines at least one image associated with the relevant information about the application.

[0254] As an example, an electronic device can determine the type or function of the application to which the input operation is targeted; and, based on the type or function of the application, determine at least one image that matches the type or function.

[0255] For example, if the input operation targets an application like Baihe.com, the electronic device determines that at least one image matching the application is at least one selfie. As another example, if the input operation targets a game application, the electronic device determines that at least one image matching the application is at least one image of a game scene.

[0256] As other examples, the electronic device can also determine a history of images posted or shared by the application to which the input operation is targeted; and, based on the application's history, determine at least one image that matches the history.

[0257] For example, if an electronic device detects that the last image a user posted on WeChat Moments came from the "My" album, then the electronic device determines, based on this historical record, that the at least one image is at least one image from the "My" album.

[0258] Other possibilities include the electronic device determining time information corresponding to the input operation; and based on the time information, at least one image matching the time information. The time information may include date information, time information (e.g., 12:10), etc.

[0259] For example, if an electronic device determines that the current time information is May 1, the electronic device can determine that at least one image corresponding to that time information is at least one image taken on May 1, or at least one image published / shared on May 1 last year, or at least one image that includes 5.1.

[0260] In some embodiments, prior to step 1001, i.e., before the electronic device detects an input operation, associated images for each type of input operation can be pre-set. For example, for an input operation to send an image to a contact, the electronic device determines that the associated image for that input operation is a specific image, such as an image that has been heavily edited; or, for an input operation to distribute on a social media platform, the electronic device determines that the associated image for that input operation is a specific image, such as an image that elongates legs. Therefore, after the electronic device detects an input operation, at least one image associated with the detected input operation is determined from the pre-set images associated with the input operation.

[0261] 1004, Display a thumbnail of at least one image in the image selection interface and hide the remaining images.

[0262] As an example, with Figure 3B (b) and Figure 3B For example, in (c) of the above, the image selection interface only displays the thumbnail of the selected image related to the input operation, and does not display thumbnails of other images. For instance, if a set of images includes three images, and the electronic device selects the image associated with the input operation, then the image selection interface will only display that image and not the other two images.

[0263] Optionally, the electronic device may also display marking information in the image selection interface, the marking information being used to mark the at least one image as being related to the input operation. As an example, the electronic device displays the marking information on a thumbnail of each of the at least one image, for example... Figure 2A The markings are displayed on thumbnails 204 and 206 in the image selection interface; or, the marking information is displayed in the area where the at least one image is not displayed in the image selection interface.

[0264] Optionally, the marking information includes one or more of icons, text, and images; or, the marking information is displayed on the thumbnail of each of the at least one image, including: highlighting the edges of the thumbnail of each of the at least one image, for example, Figure 3B The edges of thumbnails 306 and 308 are highlighted.

[0265] One possible scenario is that the electronic device can read or load all images from the associated set of images from local storage or cloud storage; determine at least one image related to the input operation from all images in the set of images; and then display a thumbnail of the at least one image on the image selection interface, without displaying thumbnails of the other images on the image selection interface.

[0266] For example, suppose the image is stored in cloud storage. Figure 3B For example, in (c), the phone can download all images from a related set of images from cloud storage, but only display thumbnails of the two images relevant to the input operation in interface 305. When the phone detects an operation to view more controls, it can display thumbnails of the other images besides the two images.

[0267] Another possibility is that the electronic device can read or load at least one image associated with the input operation from local storage or cloud storage, and display a thumbnail of the at least one image on the image selection interface; other images besides the at least one image are not read or loaded from the local storage or cloud storage.

[0268] For example, assume the image is stored in cloud storage. Continuing... Figure 3B For example, in (c), the phone can download only two images related to the input operation from the cloud storage and then display thumbnails of these two images in interface 305. When the phone detects an operation to view more controls, it can download other images from the cloud storage and display thumbnails of those other images.

[0269] In other possible scenarios, the electronic device may preload only the thumbnail of the at least one image from local storage or cloud storage; without preloading the other images in the set of images excluding the at least one image; and then display the thumbnail of the at least one image in the image selection interface.

[0270] For example, assume the image is stored in cloud storage. Continuing... Figure 3B Taking (c) as an example, the phone can preload only the thumbnails of the two images related to the input operation from cloud storage, without needing to download the original images of these two images completely (the thumbnails are less sharp than the original images), and without needing to preload thumbnails of other images. The phone can then display these two image thumbnails in interface 305. When the phone detects an operation to view more controls, it can preload thumbnails of other images from cloud storage and display those thumbnails.

[0271] 1005, A first operation was detected, which is used to select a first thumbnail in the image selection interface.

[0272] 1006, Perform the processing flow corresponding to the input operation on the first thumbnail.

[0273] In some embodiments, the input operation can be an operation for publishing an image. In this case, after the electronic device selects a first thumbnail, it can perform an image publishing process on the first thumbnail. Taking a microblogging application as an example, the image publishing process may include the electronic device sending the image to the server corresponding to the microblogging application, so that the image can be published to the microblogging platform through the server. In other embodiments, the input operation can be an operation for sending an image to a contact. In this case, after the electronic device selects a first thumbnail, it can send the image corresponding to the first thumbnail to the contact.

[0274] In the embodiments provided above, the methods provided by the present application are described from the perspective of an electronic device (mobile phone 100) as the executing entity. To implement the functions of the methods provided in the embodiments of the present application, the terminal device may include hardware structures and / or software modules, implementing the above functions in the form of hardware structures, software modules, or a combination of hardware structures and software modules. Whether a particular function is executed in the form of hardware structures, software modules, or a combination of hardware structures and software modules depends on the specific application and design constraints of the technical solution.

[0275] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0276] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0277] For purposes of explanation, the foregoing description has been given with reference to specific embodiments. However, the exemplary discussion above is not intended to be exhaustive, nor is it intended to limit the application to the precise forms disclosed. Many modifications and variations are possible based on the teachings above. The embodiments were chosen and described to fully elucidate the principles of the application and its practical application, thereby enabling others skilled in the art to fully utilize the application and its various embodiments with various modifications suitable for the particular intended use.

Claims

1. An image display method, applied to an electronic device having a display screen, characterized in that, The method includes: Input operation detected; In response to the input operation, an image selection interface is displayed on the screen; From a set of associated images stored in local storage or cloud storage, determine at least one image, the at least one image being associated with the operation type of the input operation; In the image selection interface, a thumbnail of at least one image is displayed, while the remaining images are hidden; A first operation is detected, the first operation being used to select a first thumbnail on the image selection interface; The processing flow corresponding to the input operation is performed on the first thumbnail.

2. The method as described in claim 1, characterized in that, The process of hiding the remaining images includes: Hide the other images in the set of images after removing at least one image.

3. The method as described in claim 1, characterized in that, The method further includes: Displaying labeling information, which is used to mark the at least one image as being related to the input operation.

4. The method as described in claim 3, characterized in that, The display marker information includes: The marking information is displayed on a thumbnail of each of the at least one images; or, The marking information is displayed in the area where the at least one image is not displayed in the image selection interface.

5. The method as described in claim 3, characterized in that, The marking information includes one or more of icons, text, and images; or, The marking information is displayed on a thumbnail of each of the at least one images, including: The edges of the thumbnails of each of the at least one images are highlighted.

6. The method according to any one of claims 1-5, characterized in that, The associated set of images includes: a set of images containing the same subject; and / or a set of images with a shooting time difference of less than a preset time difference; and / or a set of images taken at the same location; and / or a set of images belonging to the same album; and / or a set of images containing the same content but with different resolutions; and / or a set of images obtained by using different retouching methods on the same image.

7. The method according to any one of claims 1-5, characterized in that, Prior to the detection of the input operation, the method also includes: pre-setting an associated image for each type of input operation.

8. The method according to any one of claims 1-5, characterized in that, The input operation is an operation for publishing an image. A processing flow corresponding to the input operation is executed on the first thumbnail, including: performing an image publishing process on the image corresponding to the first thumbnail; or The input operation is an operation for sending an image to a contact. The processing flow corresponding to the input operation is performed on the first thumbnail, including: sending the image corresponding to the first thumbnail to the contact.

9. The method as described in claim 1, characterized in that, Determining the operation type of the input operation includes: It is determined that the input operation is for publishing an image; Determining at least one image associated with the operation type based on the operation type includes: Based on the operation type, determine at least one image suitable for publication.

10. The method as described in claim 1, characterized in that, Determining the operation type of the input operation includes: It is determined that the input operation is an operation for communicating with other contacts; Determining at least one image associated with the operation type based on the operation type includes: Based on the operation type, determine at least one image suitable for sending to the other contacts.

11. The method as described in claim 9, characterized in that, The at least one image suitable for publication includes: Images of the same type as previously published images; and / or At least one image that has been edited to the preset number of times.

12. The method as described in claim 10, characterized in that, The at least one image suitable for sending to other contacts includes: The image includes images of the other contacts; and / or Images that are of the same type as those previously sent to the other contacts.

13. The method according to any one of claims 1-5, characterized in that, Determining at least one image related to the input operation from an associated set of images stored locally or in the cloud includes: Determine relevant information about the application to which the input operation is targeted; Based on the relevant information of the application, determine at least one image associated with the relevant information of the application.

14. The method as described in claim 13, characterized in that, Determine relevant information about the application to which the input operation is targeted, including: Determine the type or function of the application to which the input operation is targeted; Based on the relevant information of the application, determine at least one image associated with the relevant information of the application, including: Based on the type or function of the application, determine at least one image that matches the type or function.

15. The method as described in claim 13, characterized in that, Determine relevant information about the application to which the input operation is targeted, including: Determine the history of images published or shared by the application to which the input operation is targeted; Based on the relevant information of the application, determine at least one image associated with the relevant information of the application, including: Based on the application's history, identify at least one image that matches the history.

16. The method according to any one of claims 1-5, characterized in that, Determining at least one image related to the input operation from an associated set of images stored locally or in the cloud includes: Determine the time information corresponding to the input operation; Based on the time information, and at least one image that matches the time information.

17. The method according to any one of claims 1-5, characterized in that, Determining at least one image related to the input operation from an associated set of images stored locally or in the cloud, including: Read or load all images from the associated set of images from the local storage or cloud storage; Determine at least one image related to the input operation from all images in the set of images; The image selection interface displays a thumbnail of at least one image and hides the remaining images, including: The thumbnail of at least one image is displayed on the image selection interface, while the thumbnails of the other images are not displayed on the image selection interface.

18. The method according to any one of claims 1-5, characterized in that, The image selection interface displays a thumbnail of at least one image and hides the remaining images, including: Read or load the at least one image from the local storage or cloud storage, and display a thumbnail of the at least one image on the image selection interface; do not read or load any other images from the set of images except the at least one image.

19. The method according to any one of claims 1-5, characterized in that, The image selection interface displays a thumbnail of at least one image and hides the remaining images, including: Thumbnails of the at least one image are preloaded from the local storage or cloud storage; thumbnails of the other images in the set of images excluding the at least one image are not preloaded. The image selection interface displays a thumbnail of at least one image.

20. An electronic device, characterized in that, include: Display screen; One or more processors; Memory; One or more programs; The one or more programs are stored in the memory, and the one or more programs include instructions that, when executed by the electronic device, cause the electronic device to perform the steps of the method as described in any one of claims 1-19.

21. A computer-readable storage medium, characterized in that, Includes computer instructions that, when executed on an electronic device, cause the electronic device to perform the method as described in any one of claims 1-19.

22. A program product, characterized in that, When the program product is run on an electronic device, the electronic device performs the method as described in any one of claims 1-19.

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