Image processing method and device, electronic equipment and medium

Abstract

The embodiment of the invention provides an image processing method and device, electronic equipment and a medium, and the method comprises the steps: obtaining image description information provided by a user, or directly obtaining an image input by the user, and extracting the image description information based on the image. Then, key parameters required by image shooting are determined by analyzing the image description information; and then, according to the identified shooting parameters, carrying out image shooting. According to the embodiment of the invention, not only is the operation process of the user in the image processing and shooting process simplified, but also the intelligent level of the system and the accurate capturing capability required by the user are enhanced, the image shooting parameters can be customized in real time according to the requirements of the user, and the diversified requirements of the user are met.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to an image processing method, device, electronic equipment and medium. Background Art

[0002] With the advancement of photography technology, the functions of cameras are increasing, and users' requirements for photo quality are also increasing. Although the AI ​​function of current mobile phone cameras provides some mode options, these modes are fixed and the selection range is limited. Users often feel bored after the first try. There is a lack of personalized options and it cannot meet the diverse needs of users. Summary of the invention

[0003] In view of the above problems, embodiments of the present invention are proposed to provide an image processing method, device, electronic device and medium that overcome the above problems or at least partially solve the above problems.

[0004] In order to solve the above problem, an embodiment of the present invention discloses an image processing method, including:

[0005] Obtaining image description information input by a user, and / or obtaining an image input by a user and obtaining image description information based on the image;

[0006] Determining image capture parameters according to the image description information;

[0007] An image is captured according to the image capturing parameters.

[0008] Optionally, the method further comprises:

[0009] Determining image screening conditions according to the image description information;

[0010] Classifying the preset image according to the image screening condition to obtain the category to which the preset image belongs;

[0011] An album is created according to the category to which the preset image belongs, and images belonging to different categories are classified into corresponding albums.

[0012] Optionally, determining image capture parameters according to the image description information includes:

[0013] Generating initial image shooting parameters according to the image description information;

[0014] According to the modification operation of the user, the initial image shooting parameters are modified to obtain the target image shooting parameters.

[0015] Optionally, obtaining image description information according to the image includes:

[0016] When the image includes multiple images, respectively obtain image description information of the multiple images; the image description information includes at least one description feature;

[0017] A target description feature is selected from the description features included in the image description information of the multiple images.

[0018] Optionally, selecting a target description feature from description features included in the image description information of the multiple images includes:

[0019] determining weights of the plurality of images;

[0020] According to the weights of the multiple images, a target description feature is selected from the description features included in the image description information of the multiple images.

[0021] Optionally, determining the weights of the multiple images includes:

[0022] Determining the order in which the user arranges the plurality of images;

[0023] The weights of the multiple images are determined according to the arrangement order of the multiple images.

[0024] Optionally, selecting a target description feature from description features included in the image description information of the multiple images includes:

[0025] Determine common description features among the description features included in the image description information of the multiple images, and use the common description features as target description features.

[0026] Accordingly, an embodiment of the present invention further discloses an image processing device, comprising:

[0027] A description information acquisition module, used to acquire image description information input by a user, and / or acquire an image input by a user and obtain image description information based on the image;

[0028] A shooting parameter determination module, used to determine image shooting parameters according to the image description information;

[0029] An image capturing module is used to capture images according to the image capturing parameters.

[0030] Optionally, the device further comprises:

[0031] A screening condition determination module, used to determine image screening conditions according to the image description information;

[0032] An image category acquisition module, used to classify the preset image according to the image screening condition to obtain the category to which the preset image belongs;

[0033] The image classification module is used to create an album according to the category to which the preset image belongs, and classify images belonging to different categories into corresponding albums.

[0034] Optionally, the shooting parameter determination module includes:

[0035] A parameter generation submodule, used to generate initial image shooting parameters according to the image description information;

[0036] The target parameter generation submodule is used to modify the initial image shooting parameters according to the user's modification operation to obtain the target image shooting parameters.

[0037] Optionally, the description information acquisition module includes:

[0038] A description information acquisition submodule, used for respectively acquiring image description information of the plurality of images when the image includes a plurality of images; the image description information includes at least one description feature;

[0039] The description feature determination submodule is used to select a target description feature from the description features included in the image description information of the multiple images.

[0040] Optionally, the description feature determination submodule includes:

[0041] A weight determination unit, used to determine the weights of the multiple images;

[0042] The first target description feature determination unit is used to select a target description feature from the description features included in the image description information of the multiple images according to the weights of the multiple images.

[0043] Optionally, determining the weights of the multiple images includes:

[0044] Determining the order in which the user arranges the plurality of images;

[0045] The weights of the multiple images are determined according to the arrangement order of the multiple images.

[0046] Optionally, the description feature determination submodule includes:

[0047] The second target description feature determination unit is used to determine common description features among the description features included in the image description information of the multiple images, and use the common description features as target description features.

[0048] The embodiments of the present invention include the following advantages:

[0049] In an embodiment of the present invention, firstly, the image description information provided by the user is obtained, and / or, the image input by the user is obtained, and the image description information is extracted based on the image; then, by analyzing the image description information, the key parameters required for image shooting are determined; then, the image is shot according to the identified shooting parameters. In this way, the embodiment of the present invention can comprehensively, quickly and accurately identify and process the relationship between user needs and image shooting parameters, enhance the intelligence of image shooting, realize the accurate capture of user needs, and can perform real-time personalized customization of image shooting parameters according to user needs to meet the diverse needs of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a flowchart of the steps of an image processing method provided by an embodiment of the present invention;

[0051] Figure 2 is a flowchart of another image processing method provided by an embodiment of the present invention;

[0052] Figure 3 This is a flowchart of the specific steps of an image processing method provided by an embodiment of the present invention.

[0053] Figure 4 is a schematic diagram of an image capturing interface provided by an embodiment of the present invention;

[0054] Figure 5 is a schematic diagram of another image capturing interface provided by an embodiment of the present invention;

[0055] Figure 6 is a schematic diagram of another image capturing interface provided by an embodiment of the present invention;

[0056] Figure 7 is a schematic diagram of an album interface provided by an embodiment of the present invention;

[0057] Figure 8 It is a structural block diagram of an image processing device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0058] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0059] With the advancement of photography technology, the functions of cameras are increasing, and users' requirements for photo quality are also increasing. However, although the AI ​​functions of current mobile phone cameras provide some mode options, these modes are fixed and the selection range is limited. Users often feel bored after the first try. There is a lack of personalized options and it cannot meet the diverse needs of users.

[0060] Traditional countermeasures seem to be inadequate. These problems not only involve the expansion of camera functions, but also the complexity of shooting parameter management. Traditional camera systems fail to make full use of information and digital technologies to analyze and optimize shooting parameters in real time, thus failing to effectively improve users' shooting experience and bringing inconvenience to people's daily lives.

[0061] One of the core concepts of an embodiment of the present invention is that it is possible to obtain image description information provided by a user in real time, and / or to obtain an image input by a user, and to extract image description information based on the image. At the same time, it is possible to accurately identify and handle abnormal shooting parameters by controlling the camera or linking other devices. By accurately analyzing these description information, the relationship between user needs and shooting parameters can be accurately identified. Based on these identification results, the camera system will display the corresponding processing strategy for rapid response. In this way, abnormal shooting parameters can be quickly and accurately identified and handled, and personalized shooting effects can be intelligently achieved to ensure that users have the best visual experience.

[0062] Reference Figure 1 , shows a flowchart of an image processing method provided by an embodiment of the present invention, and the method may specifically include the following steps:

[0063] Step 101, obtaining image description information input by a user, and / or obtaining an image input by a user, and obtaining image description information according to the image;

[0064] The method of the embodiment of the present invention can be applied to an intelligent photography system or terminal device. The camera of the intelligent photography system or terminal device can be fixed in various positions, and the camera used to shoot the image can be an ordinary camera, a panoramic camera, an AI camera, or a mobile phone camera, etc. The image description information can include the type of image, such as: landscape, food, portrait, etc., and can also include focal length, shooting angle, filter, light condition, color saturation, contrast, etc.

[0065] In some examples, the image description information input by the user can be obtained by using voice recognition, gesture recognition, text input, etc. to obtain the user's needs. Among them, large language models, image analysis and other technologies can be used to identify the intent of the image description information input by the user.

[0066] In some examples, a method for obtaining an image input by a user and obtaining image description information based on the image may be that the user uploads a reference photo on his own initiative and uses a preset image analysis technology to parse the image information.

[0067] In some examples, the camera can upload a reference image while the user is describing the image information using voice recognition, gesture recognition, text input, etc., and integrate image analysis technology to comprehensively determine user needs.

[0068] Step 102, determining image capture parameters according to the image description information;

[0069] In the embodiment of the present invention, the camera can determine specific parameters of image capture according to preset rules based on the image description information analyzed in step 101. Image capture parameters may include: exposure time, shutter speed, ISO value, white balance, focus mode, etc. These parameters can be adjusted according to different shooting intentions and scenes.

[0070] In some examples, the camera's built-in sensors (such as light sensors and color temperature sensors) can be used to sense the current shooting environment; based on the sensed environmental information, the selected template parameters are fine-tuned to adapt to the current light conditions, color temperature, etc.

[0071] In some examples, when the camera generates at least one set of shooting parameters, the user can directly select or further adjust the parameters according to his or her personal preferences, such as brightness preference, color preference, etc., to achieve a satisfactory effect.

[0072] Step 103: capture an image according to the image capture parameters.

[0073] In the embodiment of the present invention, after the user confirms, a set of parameters generated in step 102 can be input into the shooting settings of the camera to perform shooting.

[0074] In some examples, the user can perform pre-shooting according to the image capture parameters and preview the picture to be captured. If the user is not satisfied with the effect, the camera can also automatically adjust the parameters for the preview picture based on the user's needs.

[0075] In some instances, after shooting is completed, the camera can provide users with photo editing options. Users can edit photos by themselves or provide requirements and the camera will perform intelligent editing.

[0076] In some examples, users can evaluate their satisfaction with the shooting results, and these evaluations will be used for subsequent algorithm iteration and optimization.

[0077] The embodiments of the present invention not only improve the efficiency of image acquisition and processing, but also dynamically adjust the image description information and shooting parameters according to the user's input, so as to better adapt to different scenarios and needs. By combining the image description information input by the user or the image directly acquired, real-time analysis of the image content and parameter optimization are achieved, thereby improving the accuracy and flexibility of image capture. In addition, through automated image processing and parameter adjustment, it is possible to quickly respond and generate high-quality images, and the image capture parameters can be customized in real time according to user needs to meet the diverse needs of users.

[0078] Reference Figure 2 , shows a flowchart of another image processing method provided by an embodiment of the present invention, and the method may specifically include the following steps:

[0079] Step 201, obtaining image description information input by a user, and / or obtaining an image input by a user, and when the image includes multiple images, obtaining image description information of the multiple images respectively; the image description information includes at least one description feature;

[0080] In an embodiment of the present invention, the image description information input by the user may be a password or a keyword of the user. For example, the user may input a password through the application interface, such as descriptive words or phrases such as "landscape", "portrait", "night scene", etc., or a sentence with complex commands such as "a photo of a person with wheat skin color taken from above at the seaside at night". For example, if the user inputs "shoot from above with legs stretched out", the camera can automatically adjust the shooting angle and perspective effect, and can change the perspective to an upward angle, and change the body proportions of the user to meet the needs of the user. For example, if the user inputs "beach under sunset", the camera can automatically adjust to parameter settings suitable for shooting sunset beach, such as exposure, color saturation, white balance, etc.

[0081] In some examples, the camera can use natural language processing (NLP) technology to segment the password entered by the user and identify keywords; then remove words or symbols that are not related to the shooting parameters; and finally convert the keywords into a unified format.

[0082] In some instances, the camera can use a pre-trained intent recognition model (such as a deep learning-based classifier) ​​to recognize the intent of the user-entered command to identify the shooting effect the user wants to achieve, such as landscape, portrait, food, macro, etc. It can also extract shooting-related features such as lighting conditions, color saturation, contrast, depth of field, etc. based on the recognized intent.

[0083] In some examples, users can adjust commands or keywords in real time during shooting, and the camera can immediately update and further fine-tune shooting parameters based on the new input to achieve dynamic adjustment of shooting effects. For example, users can optimize shooting effects by entering commands such as "increase exposure time" or "reduce noise" based on the "night scene mode" generated by the camera. This fine-tuning function makes camera photography more flexible and personalized, and can meet the diverse needs of users in different scenarios.

[0084] In the embodiment of the present invention, the user may also input an image and perform image description information analysis through the image analysis mode.

[0085] In some examples, the user can open the camera and preview the captured image. The camera can use preset rules to perform image recognition and classification on the preview image. For example, it can identify the captured scene as landscape, food, portrait, etc. The camera can also analyze the light conditions and color distribution in the preview image, such as hue, color temperature, brightness, exposure, etc.

[0086] Commonly used image analysis techniques may include:

[0087] 1. Image recognition and classification: Use deep learning algorithms to recognize and classify images and determine the subject and background in the image. For example, identify animals, plants, buildings, etc. in the image.

[0088] 2. Feature extraction and matching: Extract key features from the image, such as texture, shape, color, etc. Match the extracted features with the preset template or features in the database to determine the category or style of the image.

[0089] 3. Light and color analysis: Analyze the light conditions and color distribution in the image. Use algorithms to adjust image exposure, white balance, contrast and other parameters to optimize light and color effects.

[0090] 4. Scene recognition and optimization: Identify the shooting scenes in the image, such as landscape, portrait, night scene, etc. According to the scene type, automatically adjust the shooting parameters to optimize the shooting effect.

[0091] In the embodiment of the present invention, the user may also input multiple images and parse the image description information through the image-by-image mode.

[0092] In some examples, users can import images to be synthesized into the camera, and the camera can specify the target effect of the images to be synthesized, such as natural fusion, artistic effect, etc.; then, the camera can automatically select the most suitable layer blending mode based on the image material and synthesis target input by the user; finally, the opacity of each layer is automatically adjusted according to the image content and synthesis requirements.

[0093] In some examples, users can use advanced masking techniques to precisely control the blending areas between layers as needed, and can also automatically adjust the color properties of each layer to ensure the color consistency of the composite image.

[0094] In some examples, the camera parses the image after image mixing and image synthesis to obtain image description information, such as color temperature, hue, image type, etc.

[0095] The image blending (layer blending) technology in the embodiment of the present invention is an innovative method related to the field of image processing. The image blending technology is usually used to merge two or more image materials into one, and create a composite image with artistic sense or specific visual effects by adjusting the blending mode and opacity of each layer and using tools such as masks. The following is a detailed description of the image blending technology in the present invention:

[0096] The image blending technology in this invention is an innovative method that combines advanced image processing algorithms and artificial intelligence technology. This technology aims to improve the efficiency and effect of image synthesis, allowing users to achieve seamless blending between images more easily and accurately.

[0097] The image mixing technology in the present invention has the following technical features:

[0098] 1. Intelligent hybrid mode selection:

[0099] In the embodiment of the present invention, an artificial intelligence algorithm is used to automatically select the most suitable layer blending mode according to the image material input by the user and the specified synthesis target, thereby avoiding the tedious process of the user manually trying different blending modes and improving work efficiency.

[0100] 2. Adaptive opacity adjustment:

[0101] According to the image content and synthesis requirements, the embodiment of the present invention can automatically adjust the opacity of each layer to achieve a more natural transition and fusion effect. This adaptive adjustment can ensure that the synthesized image is more harmonious and unified visually.

[0102] 3. Advanced masking technology:

[0103] The present invention introduces advanced masking technology, allowing users to control the blending area between layers in a more sophisticated way. By drawing or selecting a specific mask shape, users can accurately hide or show certain areas, thereby achieving more complex image synthesis effects.

[0104] 4. Color matching and correction:

[0105] In order to ensure the color consistency of the composite image, the embodiments of the present invention provide color matching and correction functions, which can automatically adjust the color properties of each layer to keep it consistent with the overall image style.

[0106] 5. Real-time preview and editing:

[0107] In the synthesis process, the embodiment of the present invention provides a real-time preview function, so that the user can immediately see the adjusted effect. In addition, editing operations such as undo and redo are also supported so that the user can fine-tune the synthesis effect at any time.

[0108] In the embodiment of the present invention, the camera obtains the password or the image separately to perform image analysis, or combines the password and the image to jointly analyze and identify the user's needs.

[0109] By combining natural language processing (NLP) technology and image analysis technology, the intelligent capture of user needs and dynamic adjustment of image processing are realized, significantly improving the efficiency and flexibility of image shooting and synthesis. Users can enter passwords, keywords or images, and the system automatically parses and generates suitable shooting parameters or synthesis effects, reducing the tedious operation of manual adjustment and enhancing the personalization and scene adaptability of shooting. In addition, through intelligent blending mode selection, adaptive opacity adjustment, advanced masking technology, color matching and correction and other functions, the system can achieve seamless synthesis and optimization of images, ensuring that the visual effect of the final image is more natural and unified. This intelligent and automated image processing method not only simplifies user operations, but also improves the quality and efficiency of image processing, providing users with a more convenient, efficient and personalized user experience.

[0110] Step 202: Select a target description feature from the description features included in the image description information of the multiple images.

[0111] In some embodiments, step 202 may include the following sub-steps:

[0112] Sub-step 21, determining weights of the multiple images;

[0113] Determining the order in which the user arranges the plurality of images;

[0114] Determining weights of the multiple images according to the arrangement order of the multiple images;

[0115] In the embodiment of the present invention, when the camera recognizes that the user has uploaded multiple images, the camera turns on the mixed image mode, and the user can sort the different photos according to his or her personal preferences. The uploaded photos can be different photos of the same type or different photos of different types.

[0116] Next, the camera can calculate the weights based on the user's arrangement order of multiple photos and the user's needs, either according to a specific standard or according to standards set according to personalized needs.

[0117] Sub-step 22, selecting a target description feature from the description features included in the image description information of the multiple images according to the weights of the multiple images.

[0118] In the embodiment of the present invention, the camera can obtain common features of the same attribute from different images, or obtain different obvious features of different attributes from different images, according to the weights of the multiple images.

[0119] For example, when uploading three photos of food, the user ranks the food photos in descending order of preference. When the user defines the image features that require a similar filter, the camera can parse the parameters of the three images separately, and then use the parameters of the first image as the first reference target, combined with the parameters of the other two photos for comparison and weighted mixing into a new set of target description features.

[0120] Alternatively, when uploading one food photo, one landscape photo, and one portrait photo, the user sorts the photos as food, landscape, and portrait respectively. At this time, the user requires the composition of the food photo, the contrast of the landscape photo, and the color temperature of the portrait photo. The camera can obtain the feature parameters of the three images respectively, and weightedly fuse them into a new set of target description features.

[0121] Sub-step 23, determining common description features among the description features included in the image description information of the multiple images, and using the common description features as target description features.

[0122] In the embodiment of the present invention, the camera can parse out the feature information of multiple images uploaded by the user, and then parse out the common description features in combination with the user's needs, and use the common description features as the target description features.

[0123] By introducing intelligent image weight calculation and feature selection mechanisms, the flexibility and accuracy of image processing and synthesis are significantly improved. After the user uploads multiple images, the weight of each image can be automatically calculated according to the user's order of image arrangement and personalized needs, and the target description features can be parsed in combination with user needs. Whether it is extracting common features from multiple images of the same type, or extracting features of different attributes from different types of images, the system can generate new target description features through weighted fusion, thereby realizing personalized customization of image processing. In addition, the system can also parse the common descriptive features of multiple images, further optimize the image processing strategy, and ensure that the generated image meets user expectations. This intelligent image processing method not only simplifies user operations, but also improves the quality and efficiency of image processing, providing users with a more convenient, efficient and personalized user experience.

[0124] Step 203, generating initial image shooting parameters according to the image description information;

[0125] In the embodiment of the present invention, the camera may generate initial image capture parameters according to the image description information. The image capture parameters may include:

[0126] 1. The image’s resolution, format (such as JPEG, PNG), size (in KB or MB), etc. This information helps understand the image’s clarity and storage requirements.

[0127] 2. Camera parameter information (such as EXIF ​​information): shooting time, date, location (GPS coordinates); phone model used, camera specifications (such as aperture, focal length); whether flash, anti-shake function is used, etc. This information helps to understand the shooting environment and conditions of the image.

[0128] 3. Image content information: Identification of the subject, background, foreground and other elements in the image; extraction of features such as color, shape, line, texture, etc. This information helps to understand the theme and style of the image, as well as possible emotional expression.

[0129] 4. Light and color information: light intensity, direction, color temperature, etc. in the image; color distribution, saturation, contrast, etc. in the image.

[0130] Through intelligent analysis of image description information, comprehensive initial image shooting parameters can be generated, thus providing strong technical support for image processing and shooting. The system can not only analyze the basic properties of the image, such as resolution, format and size, but also extract camera parameter information, including shooting time, location, equipment specifications and shooting function usage, to help users fully understand the shooting environment and conditions of the image. In addition, the system can also identify image content information, including the recognition of elements such as subject, background, foreground, and the extraction of features such as color, shape, line and texture, so as to deeply analyze the theme and style of the image, and even capture potential emotional expressions.

[0131] In terms of light and color information, the system can analyze parameters such as light intensity, direction, color temperature, and details such as color distribution, saturation, and contrast in the image, ensuring that the image's light and shadow effects and color performance are more accurate and meet user needs. Through this comprehensive image description information, the system can generate highly optimized initial image shooting parameters, providing a solid foundation for subsequent image processing and shooting, significantly improving the level of intelligent image processing and user experience.

[0132] Step 204, modifying the initial image shooting parameters according to the user's modification operation to obtain target image shooting parameters;

[0133] In the embodiment of the present invention, the camera can adjust the initial image shooting parameters according to the modification operation of the user to generate the target image shooting parameters. The target image shooting parameters are suggestions and operation guidelines for optimizing image shooting provided by the camera to the user, which can help the user adjust the image shooting parameters according to actual needs to ensure that the shooting effect meets expectations.

[0134] In some examples, modifying image capture parameters may include the following types:

[0135] Adjust exposure parameters: If the user thinks the image is underexposed or overexposed, the user can choose to adjust the exposure parameters. The robot teaching pendant will automatically adjust the exposure value according to the user's operation to ensure that the image brightness is moderate;

[0136] Adjust the focal length: If the user wants to change the clarity or viewing angle of the image, he can choose to adjust the focal length. The robot teaching pendant will automatically adjust the lens focal length according to the user's operation to meet the user's shooting needs;

[0137] Adjust white balance: If the user thinks the color deviation of the image is large, he can choose to adjust the white balance. The robot teaching pendant will automatically adjust the white balance parameters according to the user's operation to ensure that the image color is truly restored;

[0138] Adjust shooting mode: Users can choose different shooting modes, such as automatic mode, manual mode or scene mode. The robot teaching pendant will automatically switch the shooting mode according to the user's operation to adapt to different shooting scenes;

[0139] Save parameter settings: Users can choose to save the current target image shooting parameters. The robot teaching pendant will record the user's operations and save the parameter settings as default values ​​for direct use in subsequent shooting;

[0140] Restore default parameters: If the user wants to restore the initial image capture parameters, he can choose to restore the default parameters. The robot teaching pendant will restore the parameters to the factory settings based on the user's operation so that the adjustment can be restarted.

[0141] In some examples, the camera can also automatically recommend target image shooting parameters based on the user's operation history. For example, when the user adjusts the exposure parameters multiple times, the camera can automatically generate suitable exposure parameters based on the user's preferences to simplify the user's operation process.

[0142] Step 205, capturing an image according to the image capturing parameters;

[0143] In the embodiment of the present invention, the camera may capture images according to the image capturing parameters determined in step 204 .

[0144] In some examples, the camera can intelligently recommend a password or shooting mode that suits the user's taste based on the user's historical shooting data and preferences combined with the currently generated image shooting parameters, thereby improving the user's shooting efficiency and satisfaction. The camera can continuously learn and optimize the user's password input habits to improve the accuracy and efficiency of password parsing. The camera can also memorize the user's commonly used password and shooting parameter combinations to form a personalized shooting mode library, which is convenient for the user to quickly call when shooting in the future.

[0145] In some examples, when the user presses the shutter button, the camera can shoot according to the generated shooting parameters. After shooting, the camera can provide a preview and editing options for the shooting results. The user can also rate the satisfaction of the shooting results, and these ratings will be used for subsequent algorithm iteration and optimization.

[0146] Through the above process, personalized shooting parameters can be generated according to the user's shooting needs, shooting environment, personal preferences and other information, and the shooting effect can be automatically optimized. This provides users with a more intelligent and convenient shooting experience.

[0147] Step 206, determining image screening conditions according to the image description information;

[0148] In an embodiment of the present invention, the image description information can be generated by an image analysis module, and the image analysis module extracts key information of the image through a preset algorithm and image content analysis. The image processing system and the image analysis module can work together. The image analysis module determines whether it is necessary to generate filtering conditions based on the content of the image and the needs of the user. If necessary, the image filtering conditions can be generated and sent to the image processing system. The image processing system filters the images according to the received filtering conditions, and uploads the filtering results to the user interface through a data transmission protocol. The user can view the filtered images according to the preset rules, and finally generate a set of images that meet the needs.

[0149] Step 207, classifying the preset image according to the image screening condition to obtain the category to which the preset image belongs;

[0150] In the embodiment of the present invention, the screening conditions may include the following types:

[0151] 1. Shooting time: Users can filter photos based on the shooting time. For example, if you select a time period such as "last week", "last month", or "this year", the camera will filter out photos that meet the time conditions. You can also set a specific date, such as "May 1, 2023", to filter out all photos on that date.

[0152] 2. Shooting location: The camera can identify and filter photos taken at a specific location through GPS information or the location manually marked by the user. The user can enter the location name or select a location on the map as the filtering condition.

[0153] 3. People recognition: The camera uses facial recognition technology to identify people in photos and filter out photos containing specific people based on the conditions set by the user. Users can add or delete recognized people to filter photos more accurately.

[0154] 4. Photo type: Users can filter by photo type, such as "landscape", "portrait", "selfie", etc.

[0155] 5. Other tags: Users can also add custom tags to photos, such as "travel", "family gathering", "work", etc.

[0156] These tags can be used as filters to help users quickly find photos of specific themes or scenes. Users can also combine multiple tags as filters.

[0157] Step 208: Create an album according to the category to which the preset image belongs, and classify the images belonging to different categories into corresponding albums.

[0158] In an embodiment of the present invention, the camera will intelligently filter the photos in the photo library according to the category to which the preset image belongs. The camera will traverse all the photos, check whether they meet the filtering conditions, and add the photos that meet the conditions to the smart album.

[0159] In some examples, when users take and store new photos, the camera will automatically check whether these photos meet the set filter criteria. If they do, the system will automatically classify the new photos into the corresponding smart album to ensure that the photo library is neat and orderly.

[0160] In some instances, users can personalize smart albums, such as naming, cover selection, etc. Users can also modify filter conditions or add new filter conditions at any time as needed to meet more diverse photo management needs.

[0161] Through rich filtering conditions and efficient classification process, the custom album function in the camera provides users with a convenient and intelligent photo management experience.

[0162] The embodiments of the present invention not only improve the efficiency of image processing and shooting, but also enable the system to dynamically adjust the image description information and shooting parameters according to the user's input and needs, so as to better adapt to the diverse scenes and user needs. By obtaining the image description information input by the user or directly obtaining the image input by the user, the system realizes the real-time analysis and feature extraction of multiple images, and intelligently selects the target description features according to the user's arrangement order and weight of the images. In addition, the system further optimizes the image processing strategy by analyzing the common description features to ensure that the generated image shooting parameters are more accurate and meet the user's expectations. By combining the user's modification operation, the system can flexibly adjust the initial image shooting parameters, generate the final target image shooting parameters, and shoot the image according to the parameters. This process not only improves the flexibility and accuracy of image shooting, but also reduces the user's operation burden during image processing and shooting. At the same time, the system can also automatically generate image screening conditions according to the image description information, intelligently classify the preset images, and create albums to classify images of different categories, thereby improving the efficiency of image management and user experience.

[0163] The embodiments of the present invention not only reduce the time and energy investment of users through automated image processing, parameter optimization and classification management, but also significantly improve the intelligence level of image processing. Image shooting parameters and album classification can be customized in real time according to user needs to meet the diverse needs of users.

[0164] Reference Figure 3 , shows a flowchart of specific steps of an image processing method provided by an embodiment of the present invention, and the method may specifically include the following steps:

[0165] First, the user opens the camera and taps on the shooting mode;

[0166] Users can choose different shooting modes according to their needs, including keyword generation, image analysis, and mixed image mode.

[0167] The camera generates different image shooting parameters based on keyword generation, image analysis, and image-mixing mode;

[0168] The user can select the effect that he or she is satisfied with according to the different image shooting parameters generated. If the user is not satisfied, he or she can re-operate and generate, or choose to enter the more satisfactory effect and adjust the parameter settings;

[0169] Next, shoot using the selected parameters;

[0170] Finally, the photos are classified and intelligently categorized according to the filtering criteria.

[0171] Figure 4-Figure 6 Schematic diagrams showing three image capture interfaces:

[0172] Figure 4 Generate patterns for keywords:

[0173] When the user selects the keyword generation method, the user enters the keyword or password of the picture they want to shoot, and clicks to generate. Or first upload the reference image of the desired final effect as a mat, the user describes the keyword, and clicks to generate. The picture size can be selected by the system default standard or customized. For example: when the user takes a portrait, enter "clean the facial features, remove dark circles, white skin, and slender figure" to generate the corresponding shooting mode, and the user can shoot. When the user takes a landscape photo, enter "a vast sea, the water is very blue" and the system generates the corresponding shooting mode, such as wide angle and cold color to facilitate the user to shoot.

[0174] Figure 5 In the image analysis mode, users can choose to upload the final effect image they want to shoot or search for similar images in the system. The system will interpret multiple related prompts based on the image uploaded by the user, and the user can regenerate the shooting mode based on the interpreted prompts. For example: if a user uploads a portrait shot from above, the image analysis will copy the corresponding parameters to the camera to facilitate the user to take pictures.

[0175] Figure 6 For the mixed-image mode, users can upload multiple photos they like, which can be photos of different environments, weather and locations, or different photos of the same type, or different types of photos. Users can upload 2-5 images for mixed images, and users can sort the photos according to their degree of preference. The higher the ranking, the higher the weight. The features of the photos with higher weights are combined with the user's preferences to finally generate multiple different shooting modes for users to choose from.

[0176] Figure 7 A schematic diagram of an album interface is shown:

[0177] This page is a new way to create a smart album folder. Users click the "+" sign, create a new album folder they like, select the pre-set filter conditions, which can be any one or more conditions, and click Done. For example, when the user wants to organize all "group photos", he can create a new smart album and set the filter conditions: the smart album will automatically filter the photos that meet the conditions according to the user's settings, and every group photo collected by the user will be automatically classified into it.

[0178] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0179] Reference Figure 8 , shows a structural block diagram of an image processing device provided by an embodiment of the present invention, which may specifically include the following modules:

[0180] The description information acquisition module 301 is used to acquire image description information input by a user, and / or acquire an image input by a user and obtain image description information based on the image;

[0181] A shooting parameter determination module 302, used to determine image shooting parameters according to the image description information;

[0182] The image capturing module 303 is configured to capture an image according to the image capturing parameters.

[0183] In an embodiment of the present invention, the device further includes:

[0184] A screening condition determination module, used to determine image screening conditions according to the image description information;

[0185] An image category acquisition module, used to classify the preset image according to the image screening condition to obtain the category to which the preset image belongs;

[0186] The image classification module is used to create an album according to the category to which the preset image belongs, and classify images belonging to different categories into corresponding albums.

[0187] In an embodiment of the present invention, the shooting parameter determination module includes:

[0188] A parameter generation submodule, used to generate initial image shooting parameters according to the image description information;

[0189] The target parameter generation submodule is used to modify the initial image shooting parameters according to the user's modification operation to obtain the target image shooting parameters.

[0190] In an embodiment of the present invention, the description information acquisition module includes:

[0191] A description information acquisition module, used for respectively acquiring image description information of the plurality of images when the image includes a plurality of images; the image description information includes at least one description feature;

[0192] The description feature determination module is used to select a target description feature from the description features included in the image description information of the multiple images.

[0193] In an embodiment of the present invention, the description feature determination module includes:

[0194] A weight determination unit, used to determine the weights of the multiple images;

[0195] The first target description feature determination unit is used to select a target description feature from the description features included in the image description information of the multiple images according to the weights of the multiple images.

[0196] In the embodiment of the present invention, determining the weights of the multiple images includes:

[0197] Determining the order in which the user arranges the plurality of images;

[0198] The weights of the multiple images are determined according to the arrangement order of the multiple images.

[0199] In an embodiment of the present invention, the description feature determination module includes:

[0200] The second target description feature determination unit is used to determine common description features among the description features included in the image description information of the multiple images, and use the common description features as target description features.

[0201] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0202] An embodiment of the present invention further provides an electronic device, including:

[0203] It includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned image processing method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0204] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned image processing method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0205] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0206] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0207] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0208] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0209] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0210] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0211] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0212] The above is a detailed introduction to an image processing method, device, electronic device and medium provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An image processing method, characterized in that: include: Obtaining image description information input by a user, and / or obtaining an image input by a user and obtaining image description information based on the image; Determining image capture parameters according to the image description information; An image is captured according to the image capturing parameters.

2. The method according to claim 1, characterized in that Also includes: Determining image screening conditions according to the image description information; Classifying the preset image according to the image screening condition to obtain the category to which the preset image belongs; An album is created according to the category to which the preset image belongs, and images belonging to different categories are classified into corresponding albums.

3. The method according to claim 1, characterized in that The step of determining image capture parameters according to the image description information includes: Generating initial image shooting parameters according to the image description information; According to the modification operation of the user, the initial image shooting parameters are modified to obtain the target image shooting parameters.

4. The method according to claim 1, characterized in that: The obtaining image description information according to the image includes: When the image includes multiple images, respectively obtain image description information of the multiple images; the image description information includes at least one description feature; A target description feature is selected from the description features included in the image description information of the multiple images.

5. The method according to claim 4, characterized in that The selecting a target description feature from the description features included in the image description information of the plurality of images includes: determining weights of the plurality of images; According to the weights of the multiple images, a target description feature is selected from the description features included in the image description information of the multiple images.

6. The method according to claim 5, characterized in that Determining the weights of the plurality of images includes: Determining the order in which the user arranges the plurality of images; The weights of the multiple images are determined according to the arrangement order of the multiple images.

7. The method according to claim 4, characterized in that The selecting a target description feature from the description features included in the image description information of the plurality of images includes: Determine common description features among the description features included in the image description information of the multiple images, and use the common description features as target description features.

8. An image processing device, characterized in that: include: A description information acquisition module, used to acquire image description information input by a user, and / or acquire an image input by a user and obtain image description information based on the image; A shooting parameter determination module, used to determine image shooting parameters according to the image description information; An image capturing module is used to capture images according to the image capturing parameters.

9. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of the image processing method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the image processing method according to any one of claims 1 to 7 are implemented.

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