Image sharing method and device, computer equipment and storage medium

Abstract

The invention provides an image sharing method and device, computer equipment and a storage medium. The method comprises the steps that a first prompt message is generated, a confirmation instruction input by a user based on the first prompt message is received, and the first prompt message is used for prompting the user to confirm whether an image in an image library is shared or not; and in response to the confirmation instruction, indicating to share part or all of the images in the image library, and uploading the part or all of the images to a sharing platform, so that the part or all of the images are shared on the sharing platform. According to the image sharing method provided by the invention, the image sharing process is greatly simplified, an image library and a sharing platform are opened, the development of the image sharing field is facilitated, and the user experience is greatly improved.

Description

Technical Field

[0001] The present disclosure relates to the field of information sharing technology, and particularly to an image sharing method, apparatus, computer device, and storage medium. Background Art

[0002] With the rapid development of the digital media and creative industries, image sharing platforms have achieved remarkable development in the past few years. They mainly provide high-quality resources such as images, illustrations, and video materials for personal, institutional, and creative industry professionals. For example, various creators, including photographers, can register and upload their photographic works on such sharing platforms and then license these works to individuals, institutions, or creative industry professionals who need to use these materials.

[0003] In recent years, many manufacturers have made efforts in the camera modules of mobile devices such as mobile phones and tablets, making the imaging capabilities of mobile phones increasingly approaching those of cameras. Currently, the photo quality of many mobile devices is already high enough to meet the needs of many media, advertising, and creative projects. However, in related technologies, traditional modes are usually still adopted for image sharing on mobile devices such as mobile phones, with a long and cumbersome process and poor user experience, which even restricts the development of the image sharing field. Summary of the Invention

[0004] To overcome the problems existing in related technologies, the present disclosure provides an image sharing method, apparatus, computer device, and storage medium.

[0005] In a first aspect of the present disclosure, an image sharing method is provided. The method includes:

[0006] Generating a first prompt message and receiving a confirmation instruction input by a user based on the first prompt message, where the first prompt message is used to prompt the user to confirm whether to share images in the gallery;

[0007] In response to the confirmation instruction indicating sharing some or all of the images in the gallery, uploading the some or all of the images to a sharing platform so that the some or all of the images are shared on the sharing platform.

[0008] Optionally, the step of in response to the confirmation instruction indicating sharing some or all of the images in the gallery and uploading the some or all of the images to a sharing platform includes:

[0009] In response to the confirmation instruction indicating sharing some or all of the images in the gallery, uploading the some or all of the images and preset type information corresponding to the some or all of the images to the sharing platform.

[0010] Optionally, the method further includes:

[0011] Determine at least one qualified image in the image library, where the qualified image is an image that meets a preset condition;

[0012] The first prompt message is used to prompt the user to confirm whether to share the image in the at least one qualified image.

[0013] Optionally, the method further includes:

[0014] Train an initial deep learning model based on at least one image and the qualified information of the at least one image on at least one sub - condition in the preset condition to obtain a trained deep learning model, where the qualified information includes qualified and unqualified;

[0015] The determining at least one qualified image in the image library includes:

[0016] Use the trained deep learning model to determine at least one qualified image in the image library.

[0017] Optionally, the preset condition includes at least one of the following sub - conditions:

[0018] The imaging quality of the image is greater than a quality threshold;

[0019] The estimated value of the image is greater than a value threshold;

[0020] The image does not contain personal privacy;

[0021] The legal risk of the image is less than a risk threshold.

[0022] Optionally, the imaging quality of the image includes at least one of the following dimensions:

[0023] The resolution of the image, the noise of the image, the format of the image, the file size of the image.

[0024] Optionally, the estimated value of the image includes at least one of the following dimensions:

[0025] The number of images taken at the same shooting location as the image in the sharing platform, the number of images carrying the same shooting content as the image in the sharing platform.

[0026] Optionally, the responding to the confirmation instruction to indicate sharing some or all of the images in the image library and uploading the some or all of the images to the sharing platform includes:

[0027] Responding to the confirmation instruction to indicate sharing some or all of the images in the image library, correcting the some or all of the images based on an image correction model, and uploading the some or all of the images to the sharing platform, where the image correction model is used to correct the defects existing in the image.

[0028] The second aspect of the present disclosure provides an image sharing device, which includes:

[0029] A confirmation module, configured to generate a first prompt message and receive a confirmation instruction input by a user based on the first prompt message, where the first prompt message is used to prompt the user to confirm whether to share an image in the gallery;

[0030] An upload module, configured to, in response to the confirmation instruction indicating to share some or all of the images in the gallery, upload the some or all of the images to a sharing platform, so that the some or all of the images are shared on the sharing platform.

[0031] Optionally, when the upload module is configured to upload the some or all of the images to a sharing platform in response to the confirmation instruction indicating to share some or all of the images in the gallery, it is configured to:

[0032] In response to the confirmation instruction indicating to share some or all of the images in the gallery, upload the some or all of the images and preset category information corresponding to the some or all of the images to the sharing platform.

[0033] Optionally, the device further includes:

[0034] A screening module, configured to determine at least one qualified image in the gallery, where the qualified image is an image that meets a preset condition;

[0035] The first prompt message is used to prompt the user to confirm whether to share an image in the at least one qualified image.

[0036] Optionally, the device further includes:

[0037] A training module, configured to train an initial deep learning model based on at least one image and qualified information of the at least one image on at least one sub-condition in the preset condition, to obtain a trained deep learning model, where the qualified information includes qualified and unqualified;

[0038] When the screening module is configured to determine at least one qualified image in the gallery, it is configured to:

[0039] Use the trained deep learning model to determine at least one qualified image in the gallery.

[0040] Optionally, the preset condition includes at least one of the following sub-conditions:

[0041] The imaging quality of the image is greater than a quality threshold;

[0042] The estimated value of the image is greater than a value threshold;

[0043] The image does not contain personal privacy;

[0044] The legal risk of the image is less than the risk threshold.

[0045] Optionally, the imaging quality of the image includes at least one of the following dimensions:

[0046] The resolution of the image, the noise of the image, the format of the image, the file size of the image.

[0047] Optionally, the estimated value of the image includes at least one of the following dimensions:

[0048] The number of images taken at the same shooting location as the image in the sharing platform, the number of images carrying the same shooting content as the image in the sharing platform.

[0049] Optionally, when the uploading module is used to respond to the confirmation instruction to indicate sharing some or all of the images in the image library and upload the some or all of the images to the sharing platform, it is used for:

[0050] Responding to the confirmation instruction to indicate sharing some or all of the images in the image library, correcting the some or all of the images based on an image correction model, and uploading the some or all of the images to the sharing platform, where the image correction model is used to correct defects existing in the image.

[0051] The third aspect of the present disclosure provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the method described in the first aspect is implemented.

[0052] The fourth aspect of the present disclosure provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the method described in the first aspect is implemented.

[0053] The technical solutions provided by the embodiments of the present disclosure may include the following beneficial effects:

[0054] In the embodiments of the present disclosure, a device for executing a method automatically generates a first prompt message based on an image in a gallery, and receives a confirmation instruction input by a user based on the first prompt message, where the first prompt message is used to prompt the user to confirm whether to share the image in the gallery; next, in response to the confirmation instruction indicating to share some or all of the images in the gallery, the some or all of the images are uploaded to a sharing platform so that the some or all of the images are shared on the sharing platform. The present disclosure provides a complete and user-friendly image sharing procedure. Based on this, the image sharing process has been extended from the user taking the initiative to understand the field and registering and uploading based on the initiative willingness to the device recommending and automatically uploading. Even if the user does not understand the fields of image appreciation, sharing or selling, after viewing the first prompt message, the user can directly upload and share some or all of the images in the gallery, greatly simplifying the image sharing process, connecting the gallery and the sharing platform, being beneficial to the development of the image sharing field, and significantly improving the user experience.

[0055] It should be understood that the above general description and subsequent detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings herein are incorporated into the specification and constitute a part of the present disclosure, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure.

[0057] Figure 1 is a flowchart of an image sharing method shown in some exemplary embodiments.

[0058] Figure 2 is a flowchart of another image sharing method shown in some exemplary embodiments.

[0059] Figure 3 is a flowchart of yet another image sharing method shown in some exemplary embodiments.

[0060] Figure 4 is a selection branch diagram of an image sharing method shown in some exemplary embodiments.

[0061] Figure 5 is a block diagram of an image sharing device shown in some exemplary embodiments.

[0062] Figure 6 is a hardware structure diagram of a computer device where the image sharing device is located shown in some exemplary embodiments. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0063] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0064] The terms used in the present disclosure are for the purpose of describing particular embodiments only and are not intended to limit the present disclosure. The singular forms "a", "the", and "said" used in the present disclosure and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0065] It should be understood that although the terms first, second, third, etc. may be used in the present disclosure to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present disclosure, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to determining".

[0066] With the rapid development of the digital media and creative industries, image sharing platforms have achieved remarkable development in the past few years, mainly providing high-quality resources such as images, illustrations, video materials, etc. for individuals, institutions, and creative industry professionals. These platforms provide a convenient and fast way for designers, advertisers, media practitioners, etc. to obtain materials. For example, various creators, including photographers, can register and upload their photographic works on such sharing platforms, and then license these works to individuals, institutions, or creative industry professionals who need to use these materials.

[0067] In recent years, many manufacturers have focused on the camera modules of mobile devices such as mobile phones and tablets, making the imaging capabilities of mobile phones increasingly approaching those of cameras. Currently, the photo quality of many mobile devices is already high enough to meet the needs of many media, advertising, and creative projects, and many sharing platforms allow photographers to upload and sell their mobile phone photographic works on the platform.

[0068] In the related art, the sharing process of images usually includes at least stages such as registering an account on a specific website, creating a new work, filling in information, selecting a file and uploading it, etc., which is long and cumbersome, resulting in a poor user experience and even restricting the development of the image sharing field.

[0069] In view of this, the present disclosure provides an image sharing method, apparatus, computer device, and storage medium.

[0070] Among them, the image sharing method can be executed by the system layer of the device. In the present disclosure, an image can include a single frame of content, such as an image in JPEG (Joint Photographic Experts Group) format, PNG (Portable Network Graphics) format, etc., or can also include multiple frames of content, such as an image in GIF (Graphics Interchange Format), APNG (Animated Portable Network Graphics), AVI (Audio Video Interleave) format, etc.

[0071] The image library can contain image files in a local file library associated with the device executing the method or a cloud file library (such as a network storage space logged in to the same device manufacturer account). Preferably, it can contain images taken by the user using the device camera or through other means and stored in the local file library or cloud file library associated with the device executing the method.

[0072] The sharing platform is a platform with an image sharing function (i.e., sharing images to other devices or users). It can be a single platform or a logical platform composed of multiple modules or platforms combined; its data transmission can be realized based on the network or other interaction means such as Bluetooth connection; in addition, in addition to the image sharing function, the sharing platform can also have an auditing function, a correction function (such as beautifying the image), a selling function, a sharing function (such as distributing all or part of the amount obtained from selling the image to the uploader's account), etc. The present disclosure does not limit this.

[0073] In addition, according to different actual settings, "greater than or equal to" used in the present disclosure can also be "greater than", "less than or equal to" can also be "less than", or, according to the different meanings of the threshold, the judgment conditions of the method provided by the present disclosure can also be adaptively reversed. The present disclosure does not limit this.

[0074] Next, the embodiments of the present disclosure will be described in detail.

[0075] The first aspect of the present disclosure provides an image sharing method. Please refer to Figure 1 , which includes the following steps:

[0076] Step S101: Generate a first prompt message and receive a confirmation instruction input by the user based on the first prompt message. The first prompt message is used to prompt the user to confirm whether to share the images in the gallery.

[0077] The first prompt message can be presented to the user in the form of a visual pop-up window or a visual page, or in the form of text combined with image numbers or image features, and prompt the user to confirm whether to share the images in the gallery. The user can input a confirmation instruction based on the first prompt message. The confirmation instruction can select all or part of the images in the images carried by the first prompt message for sharing, or reject sharing the images. In addition, the first prompt message can also provide controls and functions such as an option to upload image information (such as prompting the user to select information such as the shooting location, shooting subject, and camera parameters of the image, or filling in the information by themselves). The present disclosure does not limit this.

[0078] Step S102: In response to the confirmation instruction indicating to share some or all of the images in the gallery, upload the some or all of the images to a sharing platform so that the some or all of the images are shared on the sharing platform.

[0079] When the confirmation instruction indicates to share some or all of the images in the gallery (for example, the user selects one or more images in the images carried by the first prompt message and confirms sharing), upload the images indicated to be shared by the user instruction to the sharing platform. In addition, when uploading the images to the sharing platform, the location information, name information, image description information, and EXIF (Exchangeable Image File Format) information of the images can also be uploaded to the sharing platform so that other users of the sharing platform can more easily find and understand these works, thereby improving the pertinence and dissemination of image sharing and further enhancing the user experience. The types of this information can be selected by the user themselves, or be preset information types, or be determined by combining the two (for example, the information is divided into preset necessary information and supplementary information that the user can select by themselves). That is, in response to the confirmation instruction indicating to share some or all of the images in the gallery, uploading the some or all of the images to the sharing platform includes:

[0080] In response to the confirmation instruction indicating to share some or all of the images in the gallery, upload the some or all of the images and the preset type information corresponding to the some or all of the images to the sharing platform.

[0081] In addition, when the confirmation instruction indicates sharing some or all of the images in the image library, the images can also be corrected based on an image correction model to make the uploaded images more beautiful and improve the image quality in the sharing platform. That is, in response to the confirmation instruction indicating sharing some or all of the images in the image library, uploading the some or all of the images to the sharing platform includes:

[0082] In response to the confirmation instruction indicating sharing some or all of the images in the image library, correcting the some or all of the images based on an image correction model, and uploading the some or all of the images to the sharing platform, where the image correction model is used to correct defects existing in the images.

[0083] Among them, the image correction model is used to correct or beautify images. For example, operations such as denoising, sharpening, and color correction are performed on the images. Exemplarily, a deep learning model can be trained based on a generative adversarial network (GAN). A set of original images is used as a training set and input into a generator. The generator attempts to generate beautified images, while the discriminator is responsible for judging the difference between the images generated by the generator and the real images. Through adversarial training of the generator and the discriminator, a generator model with the function of beautifying images (i.e., the image correction model) is finally obtained. Another example is that based on a convolutional neural network (CNN, such as VGGNet or ResNet) and combined with image enhancement technology, an image enhancement layer and a classification layer are added on top of the basic model, and the image correction model is obtained by training with an image dataset with beautifying effects.

[0084] In the embodiments of the present disclosure, the device executing the method automatically generates a first prompt message based on the images in the image library and receives a confirmation instruction input by the user based on the first prompt message, where the first prompt message is used to prompt the user to confirm whether to share the images in the image library; next, in response to the confirmation instruction indicating sharing some or all of the images in the image library, the some or all of the images are uploaded to the sharing platform so that the some or all of the images are shared on the sharing platform. The present disclosure provides a complete and user-friendly image sharing step. Based on this, the image sharing process is extended from the user taking the initiative to understand the field and uploading based on the initiative to the device recommending and automatically uploading. Even if the user does not understand the field of image appreciation, sharing, or selling, after viewing the first prompt message, the user can directly upload and share some or all of the images in the image library, greatly simplifying the image sharing process, connecting the image library and the sharing platform, being beneficial to the development of the image sharing field, and greatly improving the user experience.

[0085] In some embodiments of the present disclosure, in order to further ensure the quality and dissemination applicability (i.e., whether it is suitable for large-scale dissemination) of the images shared on the sharing platform, the images uploaded to the sharing platform by the image sharing method may be reviewed by the image library. That is, in response to the confirmation instruction indicating to share some or all of the images in the image library, uploading some or all of the images to the sharing platform includes:

[0086] In response to the confirmation instruction indicating to share some or all of the images in the image library, uploading some or all of the images to the sharing platform for review, so that the images that pass the review among the some or all of the images are shared on the sharing platform.

[0087] The review of the images by the sharing platform may include a single review or multiple reviews. Among them, the review may be completed manually or by a pre-trained deep learning model. In addition, the images may be pre-reviewed by the deep learning model, and the images that pass the pre-review are handed over to manual review to save human resources to the greatest extent. Or, first generate a pre-review result (which may include scoring, classification, etc.) based on the deep learning model, and present the pre-review result and the images to the manual reviewer together, so that the manual reviewer can use the pre-review result as a reference. The dimensions considered in the review may include the imaging quality of the images, the estimated value of the images, whether the images contain personal privacy, the legal risks of the images, etc. Specific details regarding this will be elaborated in detail later.

[0088] In some embodiments of the present disclosure, please refer to Figure 2 , the method further includes:

[0089] Step S201, in response to the existence of images that do not pass the review among the some or all of the images, presenting a second prompt message, so that the user can correct the images that do not pass the review and / or supplement the preset type information corresponding to the images that do not pass the review based on the reasons for not passing the review carried by the second prompt message.

[0090] In other words, when the sharing platform fails to pass the review of an image, the image can be returned with the reason for the failure to pass the review. The reason for the failure to pass the review can be that the image has defects (for example, there are many noise points in the image or there is a large area of watermark in the image), or the image lacks necessary information. For example, the sharing platform can set the location information where the image is taken as necessary information, but the user may, due to device configuration reasons or media reasons, upload an image that does not carry location information. In this case, the sharing platform can return the image. When the device determines that there is an image that fails to pass the review in the part or all of the images, a message can be presented to the user, and the reason for the failure to pass the review of the image can be carried in the message, so that the user can correct the image (for example, remove the watermark) and supplement the preset type of information (for example, supplement the location information) based on the reason for the failure to pass the review. Based on this, the quality of the images on the sharing platform can be guaranteed, and when the quality of the images uploaded by the user is unqualified, the user can correct and re-upload the images in an intuitive and simple manner, which is conducive to realizing a robust and sustainable image sharing function while ensuring the user experience.

[0091] In some embodiments of the present disclosure, the image sharing method provided by the present disclosure can also perform preliminary screening on the images and prompt the screened images to the user, so that the user can obtain a smaller number of higher-quality images. That is, please refer to Figure 3 , the method further includes:

[0092] Step S301, determine at least one qualified image in the image library, where the qualified image is an image that meets the preset conditions;

[0093] When the method includes the above steps, the first prompt message can be used to prompt the user to confirm whether to share the image in the at least one qualified image. In other words, the first prompt message can prompt the screened images to the user, so that when the user selects an image, the user can obtain a smaller number of images with a higher qualified probability, suitable for sharing or selling, which is convenient for the user to select and confirm the images and further improves the user experience.

[0094] Among them, the screening step can be performed manually, that is, manually screen locally, or upload the images or part of the images in the image library to the server (such as the sharing platform), and make the manual screen in the cloud, and return the screened results to the device executing the method to confirm whether the user agrees to share these screened images.

[0095] In some embodiments of the present disclosure, the above screening step can be completed by a deep learning model, that is, the method further includes:

[0096] Training an initial deep learning model based on at least one image and the qualified information on at least one sub - condition among the preset conditions to obtain a trained deep learning model, where the qualified information includes qualified and unqualified;

[0097] Determining at least one qualified image in the image library includes:

[0098] Using the trained deep learning model to determine at least one qualified image in the image library.

[0099] Specifically, the device executing the method can complete the screening of images in the cloud by calling the server interface (such as uploading and sharing platforms or calling the image screening interface provided by the device manufacturer). In addition, preferably, the locally deployed deep learning model can also be called to avoid the risk of user privacy leakage. For example, image pre - training models such as ResNet and MobileNet or lightweight models such as MobileNet and ShuffleNet can be selected as the initial model, and lightweight processing such as pruning, quantization, and knowledge distillation can be performed on the model to make the finally obtained deep learning model more suitable for mobile devices and lightweight devices. It should be noted that when the method needs to pre - read the images in the user's image library and perform steps such as evaluation and screening, preferably, a preset protocol (such as a privacy protection protocol and an information reading protocol) can be provided to the user, and the file reading permission can also be requested from the user. When the user agrees to the preset protocol, at least one qualified image can be determined in the image library to ensure that the user is informed, improve the user experience, and reduce the legal risk of the method.

[0100] In some embodiments of the present disclosure, exemplary reference dimensions for the preset conditions are provided, such as the following four dimensions.

[0101] Dimension 1: The imaging quality of the image is greater than the quality threshold. As an example, Dimension 1 can refer to the following sub - dimensions: the resolution of the image, the noise of the image, the format of the image, and the file size of the image. For example, if the resolution of the image is lower than the resolution threshold, the number or density of noise in the image is higher than the noise threshold, the format of the image is a format not supported by the sharing platform, or the file size of the image exceeds the preset file size range of the sharing platform, it can be determined that the presentation quality of the image is not greater than the quality threshold, that is, it can be determined that this image is not a qualified image. Based on this, the image quality on the sharing platform can be guaranteed.

[0102] Dimension 2: The estimated value of the image is greater than the value threshold. As an example, Dimension 2 may refer to the following sub-dimensions: the number of images taken at the same shooting location as the image in the sharing platform, and the number of images carrying the same shooting content as the image in the sharing platform. Among them, preferably, both the number of images taken at the same shooting location as the image in the sharing platform and the number of images carrying the same shooting content as the image in the sharing platform are negatively correlated with the estimated value of the image. In other words, if the number of images of the same shooting subject (which can be determined by various methods such as manual calibration, deep learning model recognition, and customer pre-filling) or taken at the same location in the sharing platform is extremely large, the estimated value of this image is relatively low (a large number of homogeneous photos are usually born in scenic spots and commercial areas with extremely large traffic).

[0103] Dimension 3: The image does not contain personal privacy. As an example, ID images, document images, chat record images, body part images, etc. are usually considered personal privacy. Based on this, it is possible to ensure that user privacy is not leaked, and at the same time, the image quality on the sharing platform can be ensured to be stable.

[0104] Dimension 4: The legal risk of the image is less than the risk threshold. As an example, the possibility of infringing the right of portrait (for example, the image contains a human portrait), and the possibility of infringing intellectual property rights (for example, the image may infringe the trademark law and the copyright law) can both be used as sub-dimensions of Dimension 4 and are positively correlated with the legal risk of the image.

[0105] The specific evaluation criteria for the above dimensions can be adjusted according to actual applications, and the present disclosure does not limit this. In actual applications, the above dimensions can be comprehensively applied. For example, taking the case where a user device uploads an image to a sharing platform for sale, the review dimensions and corresponding descriptions shown in Table 1 can be used as a guide to review and screen the images in the image library.

[0106] Table 1 Example Table of Review Dimensions

[0107]

[0108] The following combines Figure 4 the selection branch diagram shown to illustrate at least one of the above embodiments by taking a user taking a photo as an example (that is, there is one image in the image library).

[0109] First, the device introduces a preset protocol related to the image sharing function to the user. After the user agrees and signs the protocol, the device can perform a local preliminary review of the photos taken by the user based on a deep learning model. If the photo is not a qualified image, the process terminates. If the photo is qualified, a first prompt message can be generated according to the score of this photo by the deep learning model to prompt the user to upload this photo, or prompt the user to perform post-processing on this photo and upload this photo after processing.

[0110] Second, if the user does not agree to upload this photo, the process terminates. If the user agrees to upload this photo, the photo and the corresponding preset type information (such as the shooting location of the photo) are uploaded to the sharing platform, so that the sharing platform can review this photo and its related information. If the reason for the review failure is an insurmountable defect in the image, the process can terminate. If the reason for the review failure is that the image quality does not meet the standard or the image lacks necessary types of information, the photo can be returned, and the device presents a second prompt message, so that the user can correct the unqualified image and / or supplement the preset type information corresponding to the unqualified image based on the reason for the review failure carried in the second prompt message.

[0111] Third, after the sharing platform passes the review, the image is put online on the sharing platform for sharing or selling, and the user is given a share of the proceeds after the sale.

[0112] In summary, the embodiments of the present disclosure provide a complete and user-friendly image sharing process, which is convenient for users to create and share or sell image-based content, improves the user experience, and is conducive to the healthy development of the image sharing and selling fields. For the specific details and beneficial effects of the above exemplary steps, please refer to the foregoing embodiments and will not be elaborated here.

[0113] Corresponding to the embodiments of the foregoing method, the present disclosure also provides embodiments of a device and a terminal to which the device is applied.

[0114] A second aspect of the present disclosure provides an image sharing device. Please refer to Figure 5 , the device includes:

[0115] A confirmation module 501, configured to generate a first prompt message and receive a confirmation instruction input by the user based on the first prompt message, where the first prompt message is used to prompt the user to confirm whether to share an image in the gallery;

[0116] An upload module 502, configured to, in response to the confirmation instruction indicating to share some or all of the images in the gallery, upload the some or all of the images to the sharing platform, so that the some or all of the images are shared on the sharing platform.

[0117] Optionally, when the uploading module 502 is used to upload some or all of the images in the picture gallery in response to the confirmation instruction indicating sharing, it is used for:

[0118] In response to the confirmation instruction indicating sharing some or all of the images in the picture gallery, upload some or all of the images and the preset type information corresponding to some or all of the images to the sharing platform.

[0119] Optionally, the device further includes:

[0120] A screening module, configured to determine at least one qualified image in the picture gallery, where the qualified image is an image that meets the preset conditions;

[0121] The first prompt message is used to prompt the user to confirm whether to share the images in at least one qualified image.

[0122] Optionally, the device further includes:

[0123] A training module, configured to train an initial deep learning model based on at least one image and the qualified information of at least one sub-condition in the preset conditions of the at least one image, to obtain a trained deep learning model, where the qualified information includes qualified and unqualified;

[0124] When the screening module is used to determine at least one qualified image in the picture gallery, it is used for:

[0125] Use the trained deep learning model to determine at least one qualified image in the picture gallery.

[0126] Optionally, the preset conditions include at least one of the following sub-conditions:

[0127] The imaging quality of the image is greater than the quality threshold;

[0128] The estimated value of the image is greater than the value threshold;

[0129] The image does not contain personal privacy;

[0130] The legal risk of the image is less than the risk threshold.

[0131] Optionally, the imaging quality of the image includes at least one of the following dimensions:

[0132] The resolution of the image, the noise of the image, the format of the image, the file size of the image.

[0133] Optionally, the estimated value of the image includes at least one of the following dimensions:

[0134] The number of images taken at the same shooting location as the image in the sharing platform, and the number of images carrying the same shooting content as the image in the sharing platform.

[0135] Optionally, when the uploading module 502 is used to respond to the confirmation instruction to indicate sharing some or all of the images in the image library and upload the some or all of the images to the sharing platform, it is used for:

[0136] Respond to the confirmation instruction to indicate sharing some or all of the images in the image library, correct the some or all of the images based on an image correction model, and upload the some or all of the images to the sharing platform, where the image correction model is used to correct defects existing in the images.

[0137] For the implementation processes of the functions and roles of each module in the above device, please refer to the implementation processes of the corresponding steps in the above method for details and will not be elaborated here.

[0138] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can refer to the partial descriptions of the method embodiments. The device embodiments described above are only illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the present disclosure solution. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0139] In a third aspect, the embodiments of the image sharing device provided by the present disclosure can be applied to a computer device. Please refer to the attached Figure 6 , which exemplarily shows a hardware schematic diagram of a computer device. For example, the device 600 can be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0140] The device 600 can include one or more of the following components: a processing component 601, a memory 602, a power component 603, a multimedia component 604, an audio component 605, an input / output (I / O) interface 606, a sensor component 607, and a communication component 608.

[0141] The processing component 601 generally controls the overall operation of the device 600, such as operations associated with display, telephone calls, data communication, camera operations, and recording operations. The processing component 601 may include one or more processors 609 to execute instructions to complete all or part of the steps of the above methods. In addition, the processing component 601 may include one or more modules to facilitate the interaction between the processing component 601 and other components. For example, the processing component 601 may include a multimedia module to facilitate the interaction between the multimedia component 604 and the processing component 601.

[0142] The memory 602 is configured to store various types of data to support the operation of the device 600. Examples of such data include instructions for any application or method operating on the device 600, contact data, phone book data, messages, images, videos, etc. The memory 602 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disks, or optical disks.

[0143] The power component 603 provides power to various components of the device 600. The power component 603 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the device 600.

[0144] The multimedia component 604 includes a screen that provides an output interface between the device 600 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can not only sense the boundaries of touch or swipe actions, but also detect the duration and pressure associated with the touch or swipe operation. In some embodiments, the multimedia component 604 includes a front camera and / or a rear camera. When the device 600 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front camera and the rear camera can be a fixed optical lens system or have focal length and optical zoom capabilities.

[0145] The audio component 605 is configured to output and / or input audio signals. For example, the audio component 605 includes a microphone (MIC) that is configured to receive external audio signals when the device 600 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals can be further stored in the memory 602 or transmitted via the communication component 608. In some embodiments, the audio component 605 further includes a speaker for outputting audio signals.

[0146] The I / O interface 606 provides an interface between the processing component 601 and peripheral interface modules, and the peripheral interface modules may be a keyboard, a click wheel, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a power button, and a lock button.

[0147] The sensor component 607 includes one or more sensors for providing an assessment of various aspects of the state of the device 600. For example, the sensor component 607 can detect the on / off state of the device 600, the relative positioning of components, such as the display and keypad of the device 600. The sensor component 607 can also detect a change in the position of the device 600 or a component of the device 600, the presence or absence of user contact with the device 600, the orientation or acceleration / deceleration of the device 600, and the temperature change of the device 600. The sensor component 607 may also include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor component 607 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor component 607 may further include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0148] The communication component 608 is configured to facilitate communication between the device 600 and other devices in a wired or wireless manner. The device 600 can access a wireless network based on communication standards, such as WiFi, 2G or 3G, 4G or 5G, or a combination thereof. In an exemplary embodiment, the communication component 608 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 608 further includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0149] In an exemplary embodiment, the device 600 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the image sharing method of the above computer device.

[0150] In a fourth aspect, in an exemplary embodiment of the present disclosure, there is also provided a non-transitory computer-readable storage medium including instructions, such as a memory 602 including instructions, and the above instructions can be executed by a processor 609 of the device 600 to complete the image sharing method of the above computer device. For example, the non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0151] The above describes specific embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0152] Those skilled in the art will readily conceive of other embodiments of the present disclosure after considering the specification and practicing the invention herein. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure, which follow the general principles of the present disclosure and include known common knowledge or conventional technical means in the technical field not claimed in the present disclosure. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of the present disclosure are pointed out by the following claims.

[0153] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the figures, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

[0154] The above are only the preferred embodiments of the present disclosure and are not intended to limit the present disclosure. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present disclosure shall be included within the scope of protection of the present disclosure.

Claims

1. An image sharing method, characterized in that, The method includes: Generating a first prompt message and receiving a confirmation instruction input by the user based on the first prompt message, where the first prompt message is used to prompt the user to confirm whether to share images in the gallery; In response to the confirmation instruction indicating sharing some or all of the images in the gallery, uploading the some or all of the images to a sharing platform so that the some or all of the images are shared on the sharing platform.

2. The image sharing method according to claim 1, wherein The step of, in response to the confirmation instruction indicating sharing some or all of the images in the gallery, uploading the some or all of the images to a sharing platform includes: In response to the confirmation instruction indicating sharing some or all of the images in the gallery, uploading the some or all of the images and the preset type information corresponding to the some or all of the images to a sharing platform.

3. The image sharing method according to any one of claims 1 or 2, characterized in that, The step of, in response to the confirmation instruction indicating sharing some or all of the images in the gallery, uploading the some or all of the images to a sharing platform includes: In response to the confirmation instruction indicating sharing some or all of the images in the gallery, uploading the some or all of the images to a sharing platform for review so that the images that pass the review among the some or all of the images are shared on the sharing platform.

4. The image sharing method according to claim 3, wherein The method further includes: In response to there being images that do not pass the review among the some or all of the images, presenting a second prompt message so that the user can correct the images that do not pass the review and / or supplement the preset type information corresponding to the images that do not pass the review based on the reasons for not passing the review carried by the second prompt message.

5. The image sharing method according to claim 1, wherein The method further includes: Determining at least one qualified image in the gallery, where the qualified image is an image that meets a preset condition; The first prompt message is used to prompt the user to confirm whether to share the images in the at least one qualified image.

6. The image sharing method according to claim 5, wherein The method further includes: Training an initial deep learning model based on at least one image and the qualified information of the at least one image on at least one sub-condition in the preset condition to obtain a trained deep learning model, where the qualified information includes qualified and unqualified; The step of determining at least one qualified image in the gallery includes: Using the trained deep learning model to determine at least one qualified image in the gallery.

7. The image sharing method according to claim 5, wherein The preset condition includes at least one of the following sub-conditions: The imaging quality of the image is greater than a quality threshold; The estimated value of the image is greater than a value threshold; The image does not contain personal privacy; The legal risk of the image is less than a risk threshold.

8. The image sharing method according to claim 7, wherein The imaging quality of the image includes at least one of the following dimensions: The resolution of the image, the noise of the image, the format of the image, the file size of the image.

9. The image sharing method according to claim 7, wherein The estimated value of the image includes at least one of the following dimensions: The number of images taken at the same shooting location as the image in the sharing platform, the number of images carrying the same shooting content as the image in the sharing platform.

10. The image sharing method according to claim 1, characterized in that, The step of, in response to the confirmation instruction indicating sharing some or all of the images in the gallery, uploading the some or all of the images to a sharing platform includes: In response to the confirmation instruction indicating to share some or all of the images in the image library, correct the some or all of the images based on an image correction model, and upload the some or all of the images to a sharing platform, where the image correction model is used to correct defects existing in the images.

11. An image sharing device, characterized in that, The device includes: a confirmation module, configured to generate a first prompt message and receive a confirmation instruction input by a user based on the first prompt message, where the first prompt message is used to prompt the user to confirm whether to share images in the image library; an upload module, configured to upload the some or all of the images to a sharing platform in response to the confirmation instruction indicating to share the some or all of the images in the image library, so that the some or all of the images are shared on the sharing platform.

12. A computer device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the method according to any one of claims 1 to 10 when executing the program.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method according to any one of claims 1 to 10.

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