system

Abstract

A system is provided.SOLUTION: A system, comprising: means for receiving an input image; means for performing an analysis on the input image; means for converting the input image to a set particular form based on the analysis; means for storing the converted image; means for generating an access URL to the stored converted image; and means for providing the access URL to a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, with the spread of photo editing and social networking services, there has been an increasing demand for people to edit their own photos in an interesting way. However, conventional photo editing requires advanced techniques and specialized software, and is not necessarily easy for everyone to use. Therefore, there has been a demand for a method that allows general users without special skills to easily edit and modify photos. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, the present invention provides the following means. First, a means for receiving an input image from a user is provided. Next, a means for analyzing the received image is provided, and a means for converting the image into a specific set form based on the analysis is provided. Further, a means for saving the converted image is provided, and a means for generating an access URL for the saved image is provided. Finally, a system is constructed that includes a means for providing this access URL to the user. This allows users to easily transform their own photos into interesting ones and share them via social media or messaging without requiring any special skills.

[0006] "Input Image" refers to a photograph or image file that a user uploads to the system.

[0007] "Means" refers to the methods, devices, and software components required for the system to achieve a specific function.

[0008] "Analysis" refers to the process of analyzing the features and elements contained in the input image and extracting the information necessary for conversion.

[0009] "Conversion" refers to the process of changing an input image into a specific set form (such as a celebrity, character, or animal).

[0010] "Saving" refers to recording the converted image file in a fixed location.

[0011] "Access URL" refers to the web address that a user uses to access a saved converted image.

[0012] "Providing" refers to showing information or results to the user.

[0013] A "system" refers to an overall framework in which multiple means are combined and work together to achieve a specific purpose. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] The system of the present invention provides an automated process for users to upload and transform their photos. The following is a specific embodiment of the system.

[0036] Server-side programs

[0037] The server mainly receives user photos, transforms them using a generative AI model, and provides the results to users. Specifically, the server has the following functions:

[0038] 1. Receiving photos

[0039] The server receives the photo file uploaded by the user, along with the conversion options the user wants to convert (e.g., "cat").

[0040] 2. Photo analysis and transformation

[0041] The received photo is analyzed by a generative AI model on the server, which then transforms the photo into a specific form of your choosing (e.g., "cat").

[0042] 3. Save the converted photo

[0043] The converted photos will be saved in a specified folder on the server.

[0044] 4. Generate an access URL

[0045] An access URL for the saved converted photo is generated, which the user can use to access the converted photo.

[0046] 5. Sending the Response

[0047] The generated access URL will be provided to the user, allowing them to view and share the converted photos.

[0048] Client-side programs

[0049] The terminal provides a user interface, accepts user operations, sends requests to the server, and displays the results. Specifically, it has the following functions:

[0050] 1. Providing a user interface

[0051] The terminal displays a form on a web page that allows the user to select a photo and set conversion options.

[0052] 2. Submitting form data

[0053] When the user clicks the "Transform Photo" button, the selected photo file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[0054] 3. Displaying the conversion results

[0055] Based on the response received from the server (the URL of the converted photo), the converted photo is displayed on the device.

[0056] Example of operation

[0057] Suppose a user accesses an AI photo transformation app using a web browser. The user clicks the "Select photo" button and selects a photo of their face. Then, they select "Cat" from the "Transformation type" drop-down menu. Next, when the user clicks the "Transform Photo" button, the device sends the selected photo and transformation options to the server.

[0058] The server saves the received photo in a specified folder and inputs it into the generative AI model. The generative AI model uses the photo to convert the face photo into the form of a cat. The converted photo is saved as a new one, and an access URL for the photo is generated. This URL is returned to the user as a response. The device receives this URL and displays the photo to the user. This allows the user to view and share the image in which their face photo has been converted into a cat.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] User

[0062] Open your web browser and access the AI ​​Photo Converter app.

[0063] Click the "Select photo" button and select the photo you want to convert from your local files.

[0064] From the "Transformation type" drop-down menu, select a transformation option (e.g., "Cat").

[0065] Step 2:

[0066] Terminal

[0067] The user clicks the "Transform Photo" button.

[0068] A submit event is triggered and the selected photo and conversion options are packed into a FormData object.

[0069] A POST request is made to the server using the FormData object.

[0070] URL: / upload_photo

[0071] Method: POST

[0072] Body: FormData (photo and conversion options)

[0073] Step 3:

[0074] server

[0075] The server receives a POST request at the / upload_photo endpoint.

[0076] Get the photo file and conversion options from the request.

[0077] Save the photo files to the specified temporary folder . / uploads / .

[0078] Filename: Use the filename of the uploaded photo (e.g. photo.jpg).

[0079] Step 4:

[0080] server

[0081] The path to the saved photo file and conversion options are used to instruct the generative AI model on the conversion process.

[0082] Model: A pre-trained generative AI model.

[0083] Input: The path to the saved photo file (e.g. . / uploads / photo.jpg).

[0084] Conversion option: The option selected by the user (e.g., "cat").

[0085] Step 5:

[0086] server

[0087] A generative AI model processes the photo to transform it into a specific form.

[0088] Example: Converting a face photo into a cat form.

[0089] The converted photo is generated.

[0090] Step 6:

[0091] server

[0092] The converted photos will be saved in the specified folder . / transformed / .

[0093] Filename: transformed_<original filename> (e.g., transformed_photo.jpg).

[0094] Step 7:

[0095] server

[0096] Generate a URL to access the converted photo.

[0097] Example: http: / / example.com / transformed / transformed_photo.jpg.

[0098] The generated URL is returned to the client as a response.

[0099] Step 8:

[0100] Terminal

[0101] Process the response received from the server.

[0102] Extract the URL of the converted photo from the response.

[0103] Step 9:

[0104] Terminal

[0105] Web page Update the tag's src attribute to the extracted URL.

[0106] The converted photo is displayed to the user.

[0107] After these steps, your photos will be converted based on the conversion options you selected, and you can then view and share the converted photos.

[0108] Example 1

[0109] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0110] Conventional image conversion systems lack the functionality to automatically convert images according to user-specified conversion options, and the conversion process is complex and difficult to use. In particular, image analysis and generation of conversion results require numerous manual operations, reducing user convenience.

[0111] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0112] In this invention, the server includes means for receiving an input image, means for analyzing the input image using a generative AI model, means for converting the input image into a specific format based on the analysis, means for saving the converted image, means for generating an access URL for the saved converted image, and means for providing the access URL to a user, thereby simplifying the automatic image conversion process and enabling fast and accurate conversion based on user-specified conversion options.

[0113] An "input image" is an image file that a user uploads to the system.

[0114] A "generative AI model" is an artificial intelligence model that uses machine learning and artificial intelligence techniques to analyze and transform images.

[0115] "Analysis" refers to the process of using a generative AI model to extract features from an input image and obtain information for transformation.

[0116] "Transformation" refers to the process of changing an input image into a specific, predetermined form.

[0117] "Storage" means that the converted image is kept in a storage device on the server.

[0118] "Access URL" means a web address for accessing the saved converted image via the Internet.

[0119] A "user interface" refers to the screen and input device that a user uses to operate a system.

[0120] "Conversion options" refer to the type and style of image conversion specified by the user.

[0121] The system of the present invention provides an automated process for users to upload their images and convert them into specific formats, specific embodiments of which are described in detail below.

[0122] Server-side programs

[0123] The server mainly receives images from users, transforms them using a generative AI model, and provides the results to users. Each function of the server is explained below.

[0124] 1. Receiving photos

[0125] The server receives the image file uploaded by the user, along with the conversion options specified by the user (e.g., "cat"). This allows the server to convert the image according to the user's intentions.

[0126] 2. Photo analysis and transformation using generative AI models

[0127] The received image is analyzed by a generative AI model (such as the DeepArt model or StyleGAN) on the server. After analysis, the image is transformed into a specific, specified form. The generative AI model uses machine learning and artificial intelligence to extract image features and perform the transformation.

[0128] 3. Save the converted image

[0129] The converted images are saved to a specified folder on the server (e.g. " / uploads / converted / "), providing a basis for users to access them later.

[0130] 4. Generate an access URL

[0131] An access URL for the saved converted image is generated. This URL is used by the user to access the converted image. By generating this URL, it is possible to provide the image to the user quickly.

[0132] 5. Sending the Response

[0133] The generated access URL is provided to the user, allowing them to view the converted image and share it if desired.

[0134] Client-side programs

[0135] The terminal provides a user interface, accepts user operations, sends requests to the server, and displays the results. Each function of the terminal is explained below.

[0136] 1. Providing a user interface

[0137] The device displays a form on a web page, allowing the user to select an image and set conversion options, providing an intuitive user experience.

[0138] 2. Submitting form data

[0139] When the user clicks the "Transform Photo" button, the selected image file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[0140] 3. Displaying the conversion results

[0141] Based on the response received from the server, the converted image is displayed on the device, allowing the user to check how their image has been converted.

[0142] Example of operation

[0143] For example, the following prompt sentence can be input to a generative AI model:

[0144] Prompt: "Transform the user's face into a cat."

[0145] (Example scenario)

[0146] A user accesses the AI ​​photo transformation app using a web browser. The user clicks the "Select photo" button and selects a photo of their face. Then, they select "Cat" from the "Transformation type" drop-down menu. Next, the user clicks the "Transform Photo" button, and the selected image and transformation options are sent by the device to the server.

[0147] The server saves the received image file in a specified folder and inputs it into the generative AI model. The generative AI model uses the image to convert the face photo into the shape of a cat. The converted image is saved as a new image, and an access URL for that image is generated. This URL is returned to the user as a response.

[0148] The device receives this URL and displays the image to the user, who can then view and share the image in which their face has been transformed into a cat.

[0149] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0150] Step 1: User access

[0151] Users access the AI ​​photo conversion app through a web browser. Users access the app for image conversion and first see the interface on the main page.

[0152] Step 2: Select a photo

[0153] The user clicks the "Select photo" button and selects their own image (e.g., a photo of their face). This puts the selected image file from the user's device into a waiting state for upload.

[0154] Input: An image file selected by the user.

[0155] Output: Image files waiting to be uploaded

[0156] Step 3: Select conversion options

[0157] The user selects a transformation option, such as "cat," from the "Transformation type" dropdown menu, which tells the system what transformation to perform based on the user's request.

[0158] Input: User selected conversion options

[0159] Output: Selected conversion options

[0160] Step 4: Submit a conversion request

[0161] The user clicks the "Transform Photo" button, which causes the device to send the selected image file and transformation options to the server as a POST request.

[0162] Input: Selected image file and conversion options

[0163] Output: POST request to the server

[0164] Step 5: Receiving photos and options (server side)

[0165] The server receives the image file and conversion options sent from the device, and stores the received data in a temporary folder.

[0166] Input: Image file and conversion options sent by the user

[0167] Output: Image files stored in a temporary folder and conversion options

[0168] Step 6: Prepare input for the generative AI model

[0169] The server saves the received image files in a specified folder and prepares the data to be input to the generative AI model. Specifically, it converts the image file path and conversion options into a format that can be passed to the generative AI model.

[0170] Input: Image file saved in temporary folder and conversion options

[0171] Output: Input data for a generative AI model

[0172] Step 7: Transformation with a generative AI model

[0173] A generative AI model (such as the DeepArt model or StyleGAN) on the server analyzes the image based on the input data and converts it into the specified form. During this process, the generative AI model extracts the features of the input image and converts it into the specified form.

[0174] Input: Input data for the generative AI model

[0175] Output: The converted image data

[0176] Step 8: Save the converted image

[0177] The converted image data will be saved in a specified folder on the server (e.g. " / uploads / converted / "). This operation establishes a foundation for future access.

[0178] Input: Transformed image data

[0179] Output: Saved converted image file

[0180] Step 9: Generate an access URL

[0181] The server generates an access URL for the saved converted image, which the user can use to access the converted image.

[0182] Input: Saved converted image file

[0183] Output: Access URL

[0184] Step 10: Sending the Response

[0185] A response including the generated access URL is sent from the server to the user's device, allowing the user to access the converted image.

[0186] Input: Access URL

[0187] Output: The response sent to the user's device

[0188] Step 11: Receiving the response (terminal side)

[0189] The device receives the response sent from the server and obtains the access URL from the data included in the response.

[0190] Input: Response from the server

[0191] Output: The obtained access URL

[0192] Step 12: View the conversion results

[0193] The device uses the obtained access URL to display the converted image on the user interface, allowing the user to check the converted image and share it if necessary.

[0194] Input: The obtained access URL

[0195] Output: The converted image displayed in the user interface.

[0196] The above are the processing steps of this system and their specific operation details.

[0197] (Application example 1)

[0198] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0199] Conventional photo conversion systems require manual human intervention to convert user-supplied images into specific formats, which is time-consuming and labor-intensive. Furthermore, the conversion options are limited, making it difficult to meet the diverse needs of users. Furthermore, the system lacks functionality for easily sharing the converted images. This makes it difficult for users to express themselves more flexibly and quickly create content.

[0200] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0201] In this invention, the server includes means for receiving an input image, means for analyzing the input image, means for converting the input image into a specific format based on the analysis, means for saving the converted image, means for generating an access URL for the saved converted image, means for providing the access URL to a user, means for converting the image using a generative AI model based on a specific prompt, and means for displaying the converted image on a user interface. This allows photos uploaded by users to be quickly converted into various styles using the generative AI model and easily shared.

[0202] "Input images" are photographs or image data that users upload to the system.

[0203] "Analysis" is the process of data processing and analysis performed on an input image to recognize specific features or morphology.

[0204] A "particular form" is a form, such as a set style, character, or theme, into which an input image is transformed using a generative AI model.

[0205] "Saving" means that the converted image is stored in a specified folder on the server.

[0206] "Access URL" is the web address generated to allow users to access the converted image.

[0207] "Provision" refers to the process of informing the user of the generated access URL through a communication means.

[0208] A "generative AI model" is a machine learning algorithm and data model used to transform an input image into a specified form.

[0209] A "prompt" is text that describes the instructions that the generative AI model should follow when converting an image.

[0210] A "user interface" is the part of the software that provides the screen display and input means for the user to operate the system.

[0211] MODE FOR CARRYING OUT THE INVENTION

[0212] The present invention provides an automated process for users to upload their own photos and convert them into a specific format. Specific embodiments for implementing the present invention are as follows:

[0213] Server-side programs

[0214] Hardware and Software

[0215] Server: The server receives photos, converts them using the generative AI model, saves the converted images, and generates an access URL. The server uses Python (Flask or Django).

[0216] Generative AI models: For example, use StyleGAN or DALL-E. These models are machine learning algorithms that transform input images into a specified form.

[0217] Program processing

[0218] The server receives photos uploaded by users. Once the photos are sent, a generative AI model on the server converts them into a specific format according to the specified prompt. The converted images are stored on the server, and a generated access URL is provided to the user.

[0219] Specific examples of processing

[0220] A user accesses the Style Change Photo Maker app on their smartphone, uploads a photo of their face, and specifies transformation options such as "Halloween style." The following prompt is then passed to the generative AI model:

[0221] "Give me this photo and transform it into a Halloween style."

[0222] The generative AI model follows the prompt, detects the facial area, applies Halloween-themed makeup and backgrounds, and saves the converted photo on a server, generating an access URL for it. This URL is then sent to the user as a response.

[0223] Client-side programs

[0224] Hardware and Software

[0225] Smartphone: Provides a client-side user interface. Applications are developed using JavaScript (React Native).

[0226] Program processing

[0227] Users upload photos and select conversion options through the smartphone app. Once the selection is complete, the form data is sent to the server. The server returns an access URL for the converted image, which the app displays, allowing users to view and share the converted photo.

[0228] Specific examples of processing

[0229] The user clicks the "Select photo" button, selects their own photo, and then selects "Anime character" from the "Transformation type" drop-down menu. Then, by clicking the "Transform Photo" button, the selected photo and the option to transform it into an "Anime character" are sent to the server. The generative AI model follows the prompt:

[0230] "Give me this photo and turn it into an anime character."

[0231] The generative AI model converts the photo into an anime character-like image, saves it, and sends the user an access URL. The app receives this URL and displays the converted photo to the user, allowing the user to freely share the photo.

[0232] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0233] Step 1:

[0234] Application launch and user photo selection

[0235] The user launches the "Style Change Photo Maker" app on their smartphone. The user clicks the "Select photo" button in the app and selects a photo from their gallery. The selected photo is then imported into the app.

[0236] Input: A photo file selected by the user

[0237] Output: The selected photo is saved in the app's memory.

[0238] Step 2:

[0239] Selecting conversion options

[0240] The user selects any transformation option (e.g., "Halloween" or "Anime Character") from the "Transformation type" drop-down menu.

[0241] Input: User selected conversion options

[0242] Output: Specific conversion options are stored in memory

[0243] Step 3:

[0244] Submitting form data

[0245] When the user clicks the "Transform Photo" button, the selected photo file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[0246] Input: Photo files and conversion options

[0247] Output: Packaged into a FormData object and sent to the server

[0248] Step 4:

[0249] Receiving photos

[0250] The server receives the HTTP POST request from the user, parses the photo file and conversion options, and temporarily stores the received photo on the server.

[0251] Input: HTTP POST request sent by the user

[0252] Output: Photo files and conversion options are saved to the server.

[0253] Step 5:

[0254] Photo analysis and transformation with generative AI models

[0255] The server launches a generative AI model based on the received photo file and conversion options. It generates a prompt (e.g., "Give me this photo, please convert it into a Halloween style.") and inputs it into the generative AI model. The generative AI model then converts the photo into the specified format based on the prompt.

[0256] Input: saved photo file, conversion options, generated prompt text

[0257] Output: Image data transformed by the generative AI model

[0258] Step 6:

[0259] Saving the converted image

[0260] The converted image data is saved in a specified folder on the server.

[0261] Input: Image data transformed by the generative AI model

[0262] Output: Converted image files saved on the server

[0263] Step 7:

[0264] Generating an access URL

[0265] An access URL for the saved converted image file will be generated.

[0266] Input: The destination location for the converted image file

[0267] Output: Generated access URL

[0268] Step 8:

[0269] Sending a response

[0270] The generated access URL is sent from the server to the user as an HTTP response.

[0271] Input: Generated access URL

[0272] Output: The HTTP response sent to the user

[0273] Step 9:

[0274] Viewing the converted image

[0275] The user receives the access URL sent from the server within the app, and the converted image is displayed in the app via this URL. The user can view, save, and share this image.

[0276] Input: Received access URL

[0277] Output: The converted image is displayed in the user's app.

[0278] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0279] The system of the present invention provides an automated process for users to upload and transform their own photos. In particular, by combining an emotion engine that recognizes the user's emotions, more personalized photo transformations can be achieved. The following is a specific embodiment of the system.

[0280] Server-side programs

[0281] Receiving photos

[0282] The server has the function of receiving the photo file uploaded by the user, along with the conversion option the user wants to convert (e.g., "cat"), and also receives emotion data to recognize the user's emotion.

[0283] Photo analysis and transformation

[0284] The received photo is analyzed by a generative AI model on the server. Based on this analysis, the photo is transformed into a specific, predefined form (e.g., "cat"). The emotion engine can also analyze the user's emotion data and automatically select appropriate transformation options. Additional effects may also be applied based on the emotion data.

[0285] Save the converted photo

[0286] The converted photos will be saved in a specified folder on the server, with a file name generated based on the original image.

[0287] Generating an access URL

[0288] An access URL for the saved converted photo is generated, which is used by the user to access the converted photo.

[0289] Sending a response

[0290] The generated access URL will be provided to the user, allowing them to view and share the converted photos.

[0291] Client-side programs

[0292] Providing a user interface

[0293] The device displays a form on a web page, allowing the user to select a photo, set conversion options, and enter emotion data, which may be automatically derived from the user's facial expressions or manually selected by the user.

[0294] Submitting form data

[0295] When the user clicks the "Transform Photo" button, the selected photo file, conversion options, and emotion data are bundled into a FormData object and sent to the server as a POST request.

[0296] Displaying the conversion results

[0297] Based on the response received from the server, the device displays the converted photo, which the user can then view and share via social media or messaging.

[0298] Example of operation

[0299] When a user accesses the AI ​​photo transformation app using a web browser, a form is displayed. The user clicks the "Select photo" button and selects a photo of their face. Next, the user selects "cat" from the "Transformation type" drop-down menu and enters emotion data. Emotion data indicates states such as "happy" or "sad."

[0300] When the user clicks the "Transform Photo" button, the device sends the selected photo, transformation options, and emotion data to the server.

[0301] The server saves the received photos in a designated folder and inputs them into the generative AI model, which then converts the face photo into a cat-like form based on the photo. Furthermore, the emotion engine analyzes the user's emotional data and adds a bright and cheerful effect to the photo based on the "happy" emotion, for example.

[0302] The converted photo is saved and a URL to access the photo is generated. This URL is returned to the user as a response. The device receives this URL and displays the photo to the user. This allows the user to view an image in which their face has been converted into a cat, and enjoy the effects applied to the image.

[0303] The processing flow will be explained below.

[0304] Step 1:

[0305] User

[0306] Open your web browser and access the AI ​​Photo Converter app.

[0307] Click the "Select photo" button and select a photo of your face from your local files.

[0308] From the "Transformation type" drop-down menu, select a transformation option (e.g., "Cat").

[0309] From the "Emotion" drop-down menu, select your emotion (e.g., "fun").

[0310] Step 2:

[0311] Terminal

[0312] The user clicks the "Transform Photo" button.

[0313] The submit event is triggered and the selected photo, conversion options, and emotion data are bundled into a FormData object.

[0314] A POST request is made to the server using the FormData object.

[0315] URL: / upload_photo

[0316] Method: POST

[0317] Body: FormData(photo, conversion options, emotion data)

[0318] Step 3:

[0319] server

[0320] The server receives a POST request at the / upload_photo endpoint.

[0321] Get the photo file, conversion options, and emotion data from the request.

[0322] Save the photo files to the specified temporary folder . / uploads / .

[0323] Filename: Use the filename of the uploaded photo (e.g. photo.jpg).

[0324] Step 4:

[0325] server

[0326] The path to the saved photo file and conversion options are used to instruct the generative AI model on the conversion process.

[0327] Model: A pre-trained generative AI model.

[0328] Input: The path to the saved photo file (e.g. . / uploads / photo.jpg).

[0329] Conversion option: The option selected by the user (e.g., "cat").

[0330] Step 5:

[0331] server

[0332] The emotion engine analyzes the user's emotion data and determines the appropriate conversion option settings and additional effects.

[0333] Example: If the user's emotion is "happy", add a bright color effect to the photo.

[0334] Step 6:

[0335] server

[0336] A generative AI model processes the photo to transform it into a specific form.

[0337] Example: Converting a face photo into a cat form.

[0338] The emotion engine applies the determined effect to the transformed photo.

[0339] Example: Adding bright color effects.

[0340] Step 7:

[0341] server

[0342] The converted photos will be saved in the specified folder . / transformed / .

[0343] Filename: transformed_<original filename> (e.g., transformed_photo.jpg).

[0344] Step 8:

[0345] server

[0346] Generate a URL to access the converted photo.

[0347] Example: http: / / example.com / transformed / transformed_photo.jpg.

[0348] The generated URL is returned to the user as a response.

[0349] Step 9:

[0350] Terminal

[0351] Process the response received from the server.

[0352] Extract the URL of the converted photo from the response.

[0353] Step 10:

[0354] Terminal

[0355] Web page Update the tag's src attribute to the extracted URL.

[0356] The converted photo is displayed to the user.

[0357] After completing the above steps, users can view and share their photos after they have been converted based on the selected conversion options and emotion data.

[0358] Example 2

[0359] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0360] Conventional image conversion systems simply convert images provided by users into another format, but lack the ability to personalize the service by taking into account the user's emotions. Furthermore, they do not consider adding effects based on the user's emotions to the converted image. As a result, the quality of the user experience is not sufficiently improved, making it difficult to provide personalized services.

[0361] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for a user to upload an input image, means for receiving the input image, conversion options, and emotion data, means for performing analysis using a generative AI model, means for analyzing the emotion data using an emotion engine and adding appropriate effects, means for saving the converted image, means for generating an access URL for the saved converted image, means for providing the access URL to the user, and means for displaying the converted image to the user. This enables personalized image conversion that takes into account the user's emotions and the addition of effects according to the emotions.

[0362] A "user" is an individual or entity that utilizes the system to upload input images and provide transformation options and emotion data.

[0363] An "input image" is the original photograph or image data that a user uploads to the system.

[0364] The "conversion option" is an item that indicates the type of conversion selected by the user, such as conversion into a specific form such as a person, character, or animal.

[0365] "Emotion data" is data that represents the user's emotion, and is information that indicates an emotional state such as "happy" or "sad," for example.

[0366] A "generative AI model" is an artificial intelligence algorithm or program that analyzes an input image and transforms it into a specific, specified form.

[0367] An "emotion engine" is a program or algorithm that has the ability to analyze emotional data and add appropriate effects to images based on the results.

[0368] An "effect" is a visual modification or enhancement that is added to a transformed image based on emotional data.

[0369] A "server" is a computer system that receives, analyzes, converts, and stores data sent by users, and provides the results of the conversion.

[0370] "Access URL" is the web address for accessing the saved converted image.

[0371] A "terminal" is a device such as a computer, smartphone, or tablet that a user uses to access the system.

[0372] "Saving" means storing the converted image data as a file in a specified location.

[0373] "Display" means showing the converted image to the user on the screen of the terminal.

[0374] The system of the present invention automates a series of processes in which users upload their own photos, convert them into a specified format, and add effects based on emotional data.

[0375] The system consists of a server and a terminal, where the server is responsible for the main data processing and analysis, and the terminal provides the user interface.

[0376] Server-side features

[0377] The server provides the following functionality:

[0378] 1. Receiving photos:

[0379] The server receives the photo uploaded by the user, the transformation option (e.g., "cat"), and the emotion data (e.g., "fun"). The photo file is saved in the temporary folder / uploads.

[0380] 2. Photo analysis and conversion:

[0381] The server inputs the stored photo into a generative AI model and converts it into the specified form (e.g., "cat"). This generative AI model uses technologies such as "StyleGAN."

[0382] 3. Emotion data analysis and effect addition:

[0383] The server analyzes the emotion data using an emotion engine and adds appropriate effects to the converted image (e.g., a bright filter for the "happy" emotion). The emotion engine used is "EmotionAPI" or similar.

[0384] 4. Save the converted photo and generate an access URL:

[0385] The converted photos are saved in a new folder, for example, / transformed-photos. The server generates an access URL based on the file path of the saved photos.

[0386] 5. Sending the response:

[0387] The server provides the generated access URL to the user, which allows the user to access the converted photo.

[0388] Client-side features

[0389] The terminal provides the following features:

[0390] 1. Providing the user interface:

[0391] The device displays a form on a web page, allowing the user to select a photo and enter a transformation option (e.g., "cat") and emotional data (e.g., "fun"), which can be manually entered by the user or automatically obtained from facial expressions.

[0392] 2. Submitting form data:

[0393] When the user clicks the "Transform Photo" button, the device sends the selected photo file, conversion options, and emotion data to the server as a FormData object.

[0394] 3. View the conversion results:

[0395] The device displays the converted photo in the browser based on the access URL received from the server. The user can then check the converted photo and share it via social media or messaging apps.

[0396] Specific examples

[0397] A user accesses the AI ​​photo transformation app using a browser, selects their own photo from the "Select photo" button in the form, selects "Cat" in the "Transformation type" and "Fun" in the "Emotion" drop-down menu, and clicks the "Transform Photo" button, sending the selected photo file, transformation options, and emotion data to the server.

[0398] The server inputs the received photo file into the generative AI model and converts it into a cat's form. The emotion engine then adds a bright effect to the photo based on the "happy" emotion. The converted image is saved and a URL is generated. This URL is provided to the user, who can then view the converted photo on their device.

[0399] Prompt Sentence Examples

[0400] Here are some examples of specific prompts:

[0401] "Create a program that lets users take selfies with happy emotions and transform them into a cat style photo. Add a brightening effect to the resulting photo."

[0402] As described above, by using this system, users can convert their own facial photos into the form of cats that reflect happy emotions.

[0403] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0404] Step 1:

[0405] A user visits a web page and sees a form with a "Select photo" button, a "Transformation type" drop-down menu, and an "Emotion" drop-down menu. The user uploads their photo, chooses a transformation option (e.g., "cat"), and enters emotion data (e.g., "fun"). The inputs for this operation are the photo file, the transformation option, and the emotion data.

[0406] Step 2:

[0407] When the user clicks the "Transform Photo" button, the device sends the selected photo file, conversion options, and emotion data as a FormData object to the server. The input is the aforementioned FormData object, and the output is an HTTP POST request.

[0408] Step 3:

[0409] The server receives an HTTP POST request and parses the photo file, conversion options, and emotion data. The photo file is saved in the temporary folder / uploads, and the conversion options and emotion data are stored in memory variables. The input is the HTTP POST request, and the output is the saved image file and memory variables.

[0410] Step 4:

[0411] The server inputs the saved photo file into a generative AI model and converts it into the specified form (e.g., "cat"). The generative AI model used is, for example, "StyleGAN." The input is the photo file and conversion options, and the output is the converted image data.

[0412] Step 5:

[0413] The server uses an emotion engine to analyze the emotion data and add appropriate effects to the converted image (e.g., a bright filter for the "happy" emotion). The emotion engine uses "EmotionAPI" or similar. The input is the converted image data and emotion data, and the output is the converted image with the added effect.

[0414] Step 6:

[0415] The server saves the converted image, for example, in the / transformed-photos folder. The server generates an access URL based on the path of this saved file. The input is the converted image with the effect added, and the output is the saved image file and the access URL.

[0416] Step 7:

[0417] The server sends the generated access URL to the user as an HTTP response. The response body contains data in JSON format such as { "url": "www.example.com / transformed / photos / 123.jpg"}. The input is the generated access URL, and the output is the HTTP response.

[0418] Step 8:

[0419] The device analyzes the access URL received from the server and displays the converted image on the browser. The user can then check the converted image and share it via social media or messaging apps. The input is the access URL received as an HTTP response, and the output is the displayed converted image.

[0420] (Application example 2)

[0421] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0422] While conventional photo conversion systems can convert photos uploaded by users into individual formats, they have the problem of not applying personalized effects that take the user's emotions into account. Furthermore, while there is a demand in the advertising field for a system that can automatically generate advertising photos that reflect the user's emotions, no such system exists. The present invention aims to solve these problems by providing a system that enables the automatic generation of personalized advertising photos by applying effects based on the user's emotional data.

[0423] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0424] In this invention, the server includes means for receiving an input image, means for analyzing the input image, means for converting the input image into a specific set form, means for acquiring emotion data from the input image, means for applying an additional effect to the converted image based on the emotion data, means for saving the converted image, means for generating an access URL for the saved converted image, and means for providing the access URL to the user. This enables automatic generation of advertising photos that take user emotions into consideration.

[0425] "Input image" refers to a photograph or image uploaded by a user.

[0426] "Means for performing analysis" refers to the technical means for analyzing the input image and understanding its content and characteristics.

[0427] "Specific form" refers to the specific transformation form set by the generative AI model, including, for example, transformation into animals or products.

[0428] "Emotion data" refers to data generated based on the user's facial expressions and input emotion information.

[0429] "Additional effects" refer to visual effects that are further applied to an image that has been transformed based on emotion data.

[0430] "Storing means" refers to the technical means of recording the converted images in designated storage on a server.

[0431] "Access URL" refers to the web address where users can access the converted image.

[0432] A "generative AI model" refers to an artificial intelligence model that generates new images based on input images.

[0433] System Configuration

[0434] The system of the present invention automates the process of users uploading photos, converting the photos into specific forms, and applying effects based on the user's emotional data. The system is composed of a server and a user terminal.

[0435] Hardware and Software

[0436] Hardware: Smartphones, servers

[0437] Software: Cloud services used for servers (e.g., AWS), generative AI models (e.g., GAN), sentiment analysis engines (e.g., Microsoft Azure's Face API), and web front-end technologies (HTML, CSS, JavaScript).

[0438] Server-side processing

[0439] 1. Receiving photos

[0440] The server receives the photos uploaded by the user, as well as the transformation options (e.g., animals, products) selected by the user and the acquired emotion data.

[0441] 2. Acquiring Emotion Data

[0442] The server generates emotion data based on the user's facial expression data and input emotion information, using an emotion analysis engine for this process.

[0443] 3. Photo conversion

[0444] The server inputs the received photo into a generative AI model and converts it into an image of a specific set form (e.g., a cat, a product for advertising).

[0445] 4. Applying Effects

[0446] Apply an additional effect to the converted image based on the emotion data, which gives different visual effects depending on the emotion data (e.g., happiness).

[0447] 5. Save the converted image

[0448] The converted image is saved on the server and a URL for the saved image is generated.

[0449] 6. Providing an access URL

[0450] The generated URL is provided to the user, who can then access the converted image.

[0451] Processing on the user terminal side

[0452] 1. Upload a photo

[0453] Users launch the application on their smartphone, upload a photo, and select the product category (e.g., cosmetics) for the advertisement.

[0454] 2. Acquiring Emotion Data

[0455] The user device uses a camera function to capture the user's facial expressions and obtain emotional data in real time, which is also sent to the server.

[0456] 3. Displaying the conversion results

[0457] The user's device receives the access URL provided by the server and displays the converted image. The user can check the results and share them if necessary.

[0458] Specific examples

[0459] For example, suppose User A uses the application to upload a photo of themselves and selects the cosmetics category. Because User A is smiling, the sentiment analysis engine recognizes this as "happiness." The photo, transformation options, and the "happiness" emotion data are sent to the server. The server then transforms the photo using a generative AI model to regenerate it into an image suitable for advertising. It also applies a bright, energetic effect based on "happiness." The resulting URL is provided to the user, who can view it on their smartphone.

[0460] Prompt Sentence Examples

[0461] Examples of prompts used by generative AI models include:

[0462] "Upload user photos and transform them into ad designs for the cosmetics category. The user emotion is happiness, so add a bright effect to reflect that."

[0463] In this way, the system realizes the automatic generation of personalized advertising photos that take into account the user's emotions.

[0464] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0465] Step 1: Upload a photo

[0466] A user launches the app on their smartphone, selects and uploads their own photo, and also inputs the product category (e.g., cosmetics) to be advertised. The uploaded photo and the selected category are then sent to the server.

[0467] Input: User photo, Product category

[0468] Output: Sending photo data and category data to the server

[0469] Step 2: Obtaining emotion data

[0470] The user device uses the smartphone's camera to capture the user's facial expressions in real time, and an emotion analysis engine (e.g., Microsoft Azure's Face API) is used to analyze the facial expressions and generate emotion data, which is also sent to the server.

[0471] Input: Real-time facial expression data of the user

[0472] Output: Generate emotion data and send it to the server

[0473] Step 3: Receiving photos

[0474] The server receives the photo data, product category, and emotion data sent from the user terminal.

[0475] Input: Photo data, category data, emotion data

[0476] Output: Saving and preparing data on the server

[0477] Step 4: Analyze and convert photos

[0478] The server inputs the received photo data into a generative AI model (e.g., GAN) and converts it into an image of a specific set form (e.g., a cat, a product for advertising). The generative AI model converts the photo based on the prompt text.

[0479] Input: Photo data, generative AI model, prompt

[0480] Output: Transformed image data

[0481] Step 5: Apply effects

[0482] The server applies additional effects to the transformed image based on the emotion data, for example, if the emotion is "happy," it applies a bright effect. This process is performed using an emotion engine.

[0483] Input: Converted image data, emotion data

[0484] Output: Final image data with effects applied

[0485] Step 6: Save the converted image

[0486] The server saves the final image data with the effect applied to the specified folder and generates an access URL for the save destination.

[0487] Input: Image data with effects applied

[0488] Output: Saved image data, generated access URL

[0489] Step 7: Provide an access URL

[0490] The server returns the generated access URL to the user's device as a response. The user's device receives this URL and displays the converted image.

[0491] Input: Access URL

[0492] Output: Receives the access URL and displays the image on the user's device

[0493] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0494] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0495] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0496] [Second embodiment]

[0497] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0498] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0499] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0500] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0501] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0502] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0503] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0504] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0505] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0506] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0507] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0508] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0509] The system of the present invention provides an automated process for users to upload and transform their photos. The following is a specific embodiment of the system.

[0510] Server-side programs

[0511] The server mainly receives user photos, transforms them using a generative AI model, and provides the results to users. Specifically, the server has the following functions:

[0512] 1. Receiving photos

[0513] The server receives the photo file uploaded by the user, along with the conversion options the user wants to convert (e.g., "cat").

[0514] 2. Photo analysis and transformation

[0515] The received photo is analyzed by a generative AI model on the server, which then transforms the photo into a specific form of your choosing (e.g., "cat").

[0516] 3. Save the converted photo

[0517] The converted photos will be saved in a specified folder on the server.

[0518] 4. Generate an access URL

[0519] An access URL for the saved converted photo is generated, which the user can use to access the converted photo.

[0520] 5. Sending the Response

[0521] The generated access URL will be provided to the user, allowing them to view and share the converted photos.

[0522] Client-side programs

[0523] The terminal provides a user interface, accepts user operations, sends requests to the server, and displays the results. Specifically, it has the following functions:

[0524] 1. Providing a user interface

[0525] The terminal displays a form on a web page that allows the user to select a photo and set conversion options.

[0526] 2. Submitting form data

[0527] When the user clicks the "Transform Photo" button, the selected photo file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[0528] 3. Displaying the conversion results

[0529] Based on the response received from the server (the URL of the converted photo), the converted photo is displayed on the device.

[0530] Example of operation

[0531] Suppose a user accesses an AI photo transformation app using a web browser. The user clicks the "Select photo" button and selects a photo of their face. Then, they select "Cat" from the "Transformation type" drop-down menu. Next, when the user clicks the "Transform Photo" button, the device sends the selected photo and transformation options to the server.

[0532] The server saves the received photo in a specified folder and inputs it into the generative AI model. The generative AI model uses the photo to convert the face photo into the form of a cat. The converted photo is saved as a new one, and an access URL for the photo is generated. This URL is returned to the user as a response. The device receives this URL and displays the photo to the user. This allows the user to view and share the image in which their face photo has been converted into a cat.

[0533] The processing flow will be explained below.

[0534] Step 1:

[0535] User

[0536] Open your web browser and access the AI ​​Photo Converter app.

[0537] Click the "Select photo" button and select the photo you want to convert from your local files.

[0538] From the "Transformation type" drop-down menu, select a transformation option (e.g., "Cat").

[0539] Step 2:

[0540] Terminal

[0541] The user clicks the "Transform Photo" button.

[0542] A submit event is triggered and the selected photo and conversion options are packed into a FormData object.

[0543] A POST request is made to the server using the FormData object.

[0544] URL: / upload_photo

[0545] Method: POST

[0546] Body: FormData (photo and conversion options)

[0547] Step 3:

[0548] server

[0549] The server receives a POST request at the / upload_photo endpoint.

[0550] Get the photo file and conversion options from the request.

[0551] Save the photo files to the specified temporary folder . / uploads / .

[0552] Filename: Use the filename of the uploaded photo (e.g. photo.jpg).

[0553] Step 4:

[0554] server

[0555] The path to the saved photo file and conversion options are used to instruct the generative AI model on the conversion process.

[0556] Model: A pre-trained generative AI model.

[0557] Input: The path to the saved photo file (e.g. . / uploads / photo.jpg).

[0558] Conversion option: The option selected by the user (e.g., "cat").

[0559] Step 5:

[0560] server

[0561] A generative AI model processes the photo to transform it into a specific form.

[0562] Example: Converting a face photo into a cat form.

[0563] The converted photo is generated.

[0564] Step 6:

[0565] server

[0566] The converted photos will be saved in the specified folder . / transformed / .

[0567] Filename: transformed_<original filename> (e.g., transformed_photo.jpg).

[0568] Step 7:

[0569] server

[0570] Generate a URL to access the converted photo.

[0571] Example: http: / / example.com / transformed / transformed_photo.jpg.

[0572] The generated URL is returned to the client as a response.

[0573] Step 8:

[0574] Terminal

[0575] Process the response received from the server.

[0576] Extract the URL of the converted photo from the response.

[0577] Step 9:

[0578] Terminal

[0579] Web page Update the tag's src attribute to the extracted URL.

[0580] The converted photo is displayed to the user.

[0581] After these steps, your photos will be converted based on the conversion options you selected, and you can then view and share the converted photos.

[0582] Example 1

[0583] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0584] Conventional image conversion systems lack the functionality to automatically convert images according to user-specified conversion options, and the conversion process is complex and difficult to use. In particular, image analysis and generation of conversion results require numerous manual operations, reducing user convenience.

[0585] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0586] In this invention, the server includes means for receiving an input image, means for analyzing the input image using a generative AI model, means for converting the input image into a specific format based on the analysis, means for saving the converted image, means for generating an access URL for the saved converted image, and means for providing the access URL to a user, thereby simplifying the automatic image conversion process and enabling fast and accurate conversion based on user-specified conversion options.

[0587] An "input image" is an image file that a user uploads to the system.

[0588] A "generative AI model" is an artificial intelligence model that uses machine learning and artificial intelligence techniques to analyze and transform images.

[0589] "Analysis" refers to the process of using a generative AI model to extract features from an input image and obtain information for transformation.

[0590] "Transformation" refers to the process of changing an input image into a specific, predetermined form.

[0591] "Storage" means that the converted image is kept in a storage device on the server.

[0592] "Access URL" means a web address for accessing the saved converted image via the Internet.

[0593] A "user interface" refers to the screen and input device that a user uses to operate a system.

[0594] "Conversion options" refer to the type and style of image conversion specified by the user.

[0595] The system of the present invention provides an automated process for users to upload their images and convert them into specific formats, specific embodiments of which are described in detail below.

[0596] Server-side programs

[0597] The server mainly receives images from users, transforms them using a generative AI model, and provides the results to users. Each function of the server is explained below.

[0598] 1. Receiving photos

[0599] The server receives the image file uploaded by the user, along with the conversion options specified by the user (e.g., "cat"). This allows the server to convert the image according to the user's intentions.

[0600] 2. Photo analysis and transformation using generative AI models

[0601] The received image is analyzed by a generative AI model (such as the DeepArt model or StyleGAN) on the server. After analysis, the image is transformed into a specific, specified form. The generative AI model uses machine learning and artificial intelligence to extract image features and perform the transformation.

[0602] 3. Save the converted image

[0603] The converted images are saved to a specified folder on the server (e.g. " / uploads / converted / "), providing a basis for users to access them later.

[0604] 4. Generate an access URL

[0605] An access URL for the saved converted image is generated. This URL is used by the user to access the converted image. By generating this URL, it is possible to provide the image to the user quickly.

[0606] 5. Sending the Response

[0607] The generated access URL is provided to the user, allowing them to view the converted image and share it if desired.

[0608] Client-side programs

[0609] The terminal provides a user interface, accepts user operations, sends requests to the server, and displays the results. Each function of the terminal is explained below.

[0610] 1. Providing a user interface

[0611] The device displays a form on a web page, allowing the user to select an image and set conversion options, providing an intuitive user experience.

[0612] 2. Submitting form data

[0613] When the user clicks the "Transform Photo" button, the selected image file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[0614] 3. Displaying the conversion results

[0615] Based on the response received from the server, the converted image is displayed on the device, allowing the user to check how their image has been converted.

[0616] Example of operation

[0617] For example, the following prompt sentence can be input to a generative AI model:

[0618] Prompt: "Transform the user's face into a cat."

[0619] (Example scenario)

[0620] A user accesses the AI ​​photo transformation app using a web browser. The user clicks the "Select photo" button and selects a photo of their face. Then, they select "Cat" from the "Transformation type" drop-down menu. Next, the user clicks the "Transform Photo" button, and the selected image and transformation options are sent by the device to the server.

[0621] The server saves the received image file in a specified folder and inputs it into the generative AI model. The generative AI model uses the image to convert the face photo into the shape of a cat. The converted image is saved as a new image, and an access URL for that image is generated. This URL is returned to the user as a response.

[0622] The device receives this URL and displays the image to the user, who can then view and share the image in which their face has been transformed into a cat.

[0623] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0624] Step 1: User access

[0625] Users access the AI ​​photo conversion app through a web browser. Users access the app for image conversion and first see the interface on the main page.

[0626] Step 2: Select a photo

[0627] The user clicks the "Select photo" button and selects their own image (e.g., a photo of their face). This puts the selected image file from the user's device into a waiting state for upload.

[0628] Input: An image file selected by the user.

[0629] Output: Image files waiting to be uploaded

[0630] Step 3: Select conversion options

[0631] The user selects a transformation option, such as "cat," from the "Transformation type" dropdown menu, which tells the system what transformation to perform based on the user's request.

[0632] Input: User selected conversion options

[0633] Output: Selected conversion options

[0634] Step 4: Submit a conversion request

[0635] The user clicks the "Transform Photo" button, which causes the device to send the selected image file and transformation options to the server as a POST request.

[0636] Input: Selected image file and conversion options

[0637] Output: POST request to the server

[0638] Step 5: Receiving photos and options (server side)

[0639] The server receives the image file and conversion options sent from the device, and stores the received data in a temporary folder.

[0640] Input: Image file and conversion options sent by the user

[0641] Output: Image files stored in a temporary folder and conversion options

[0642] Step 6: Prepare input for the generative AI model

[0643] The server saves the received image files in a specified folder and prepares the data to be input to the generative AI model. Specifically, it converts the image file path and conversion options into a format that can be passed to the generative AI model.

[0644] Input: Image file saved in temporary folder and conversion options

[0645] Output: Input data for a generative AI model

[0646] Step 7: Transformation with a generative AI model

[0647] A generative AI model (such as the DeepArt model or StyleGAN) on the server analyzes the image based on the input data and converts it into the specified form. During this process, the generative AI model extracts the features of the input image and converts it into the specified form.

[0648] Input: Input data for the generative AI model

[0649] Output: The converted image data

[0650] Step 8: Save the converted image

[0651] The converted image data will be saved in a specified folder on the server (e.g. " / uploads / converted / "). This operation establishes a foundation for future access.

[0652] Input: Transformed image data

[0653] Output: Saved converted image file

[0654] Step 9: Generate an access URL

[0655] The server generates an access URL for the saved converted image, which the user can use to access the converted image.

[0656] Input: Saved converted image file

[0657] Output: Access URL

[0658] Step 10: Sending the Response

[0659] A response including the generated access URL is sent from the server to the user's device, allowing the user to access the converted image.

[0660] Input: Access URL

[0661] Output: The response sent to the user's device

[0662] Step 11: Receiving the response (terminal side)

[0663] The device receives the response sent from the server and obtains the access URL from the data included in the response.

[0664] Input: Response from the server

[0665] Output: The obtained access URL

[0666] Step 12: View the conversion results

[0667] The device uses the obtained access URL to display the converted image on the user interface, allowing the user to check the converted image and share it if necessary.

[0668] Input: The obtained access URL

[0669] Output: The converted image displayed in the user interface.

[0670] The above are the processing steps of this system and their specific operation details.

[0671] (Application example 1)

[0672] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0673] Conventional photo conversion systems require manual human intervention to convert user-supplied images into specific formats, which is time-consuming and labor-intensive. Furthermore, the conversion options are limited, making it difficult to meet the diverse needs of users. Furthermore, the system lacks functionality for easily sharing the converted images. This makes it difficult for users to express themselves more flexibly and quickly create content.

[0674] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0675] In this invention, the server includes means for receiving an input image, means for analyzing the input image, means for converting the input image into a specific format based on the analysis, means for saving the converted image, means for generating an access URL for the saved converted image, means for providing the access URL to a user, means for converting the image using a generative AI model based on a specific prompt, and means for displaying the converted image on a user interface. This allows photos uploaded by users to be quickly converted into various styles using the generative AI model and easily shared.

[0676] "Input images" are photographs or image data that users upload to the system.

[0677] "Analysis" is the process of data processing and analysis performed on an input image to recognize specific features or morphology.

[0678] A "particular form" is a form, such as a set style, character, or theme, into which an input image is transformed using a generative AI model.

[0679] "Saving" means that the converted image is stored in a specified folder on the server.

[0680] "Access URL" is the web address generated to allow users to access the converted image.

[0681] "Provision" refers to the process of informing the user of the generated access URL through a communication means.

[0682] A "generative AI model" is a machine learning algorithm and data model used to transform an input image into a specified form.

[0683] A "prompt" is text that describes the instructions that the generative AI model should follow when converting an image.

[0684] A "user interface" is the part of the software that provides the screen display and input means for the user to operate the system.

[0685] MODE FOR CARRYING OUT THE INVENTION

[0686] The present invention provides an automated process for users to upload their own photos and convert them into a specific format. Specific embodiments for implementing the present invention are as follows:

[0687] Server-side programs

[0688] Hardware and Software

[0689] Server: The server receives photos, converts them using the generative AI model, saves the converted images, and generates an access URL. The server uses Python (Flask or Django).

[0690] Generative AI models: For example, use StyleGAN or DALL-E. These models are machine learning algorithms that transform input images into a specified form.

[0691] Program processing

[0692] The server receives photos uploaded by users. Once the photos are sent, a generative AI model on the server converts them into a specific format according to the specified prompt. The converted images are stored on the server, and a generated access URL is provided to the user.

[0693] Specific examples of processing

[0694] A user accesses the Style Change Photo Maker app on their smartphone, uploads a photo of their face, and specifies transformation options such as "Halloween style." The following prompt is then passed to the generative AI model:

[0695] "Give me this photo and transform it into a Halloween style."

[0696] The generative AI model follows the prompt, detects the facial area, applies Halloween-themed makeup and backgrounds, and saves the converted photo on a server, generating an access URL for it. This URL is then sent to the user as a response.

[0697] Client-side programs

[0698] Hardware and Software

[0699] Smartphone: Provides a client-side user interface. Applications are developed using JavaScript (React Native).

[0700] Program processing

[0701] Users upload photos and select conversion options through the smartphone app. Once the selection is complete, the form data is sent to the server. The server returns an access URL for the converted image, which the app displays, allowing users to view and share the converted photo.

[0702] Specific examples of processing

[0703] The user clicks the "Select photo" button, selects their own photo, and then selects "Anime character" from the "Transformation type" drop-down menu. Then, by clicking the "Transform Photo" button, the selected photo and the option to transform it into an "Anime character" are sent to the server. The generative AI model follows the prompt:

[0704] "Give me this photo and turn it into an anime character."

[0705] The generative AI model converts the photo into an anime character-like image, saves it, and sends the user an access URL. The app receives this URL and displays the converted photo to the user, allowing the user to freely share the photo.

[0706] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0707] Step 1:

[0708] Application launch and user photo selection

[0709] The user launches the "Style Change Photo Maker" app on their smartphone. The user clicks the "Select photo" button in the app and selects a photo from their gallery. The selected photo is then imported into the app.

[0710] Input: A photo file selected by the user

[0711] Output: The selected photo is saved in the app's memory.

[0712] Step 2:

[0713] Selecting conversion options

[0714] The user selects any transformation option (e.g., "Halloween" or "Anime Character") from the "Transformation type" drop-down menu.

[0715] Input: User selected conversion options

[0716] Output: Specific conversion options are stored in memory

[0717] Step 3:

[0718] Submitting form data

[0719] When the user clicks the "Transform Photo" button, the selected photo file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[0720] Input: Photo files and conversion options

[0721] Output: Packaged into a FormData object and sent to the server

[0722] Step 4:

[0723] Receiving photos

[0724] The server receives the HTTP POST request from the user, parses the photo file and conversion options, and temporarily stores the received photo on the server.

[0725] Input: HTTP POST request sent by the user

[0726] Output: Photo files and conversion options are saved to the server.

[0727] Step 5:

[0728] Photo analysis and transformation with generative AI models

[0729] The server launches a generative AI model based on the received photo file and conversion options. It generates a prompt (e.g., "Give me this photo, please convert it into a Halloween style.") and inputs it into the generative AI model. The generative AI model then converts the photo into the specified format based on the prompt.

[0730] Input: saved photo file, conversion options, generated prompt text

[0731] Output: Image data transformed by the generative AI model

[0732] Step 6:

[0733] Saving the converted image

[0734] The converted image data is saved in a specified folder on the server.

[0735] Input: Image data transformed by the generative AI model

[0736] Output: Converted image files saved on the server

[0737] Step 7:

[0738] Generating an access URL

[0739] An access URL for the saved converted image file will be generated.

[0740] Input: The destination location for the converted image file

[0741] Output: Generated access URL

[0742] Step 8:

[0743] Sending a response

[0744] The generated access URL is sent from the server to the user as an HTTP response.

[0745] Input: Generated access URL

[0746] Output: The HTTP response sent to the user

[0747] Step 9:

[0748] Viewing the converted image

[0749] The user receives the access URL sent from the server within the app, and the converted image is displayed in the app via this URL. The user can view, save, and share this image.

[0750] Input: Received access URL

[0751] Output: The converted image is displayed in the user's app.

[0752] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0753] The system of the present invention provides an automated process for users to upload and transform their own photos. In particular, by combining an emotion engine that recognizes the user's emotions, more personalized photo transformations can be achieved. The following is a specific embodiment of the system.

[0754] Server-side programs

[0755] Receiving photos

[0756] The server has the function of receiving the photo file uploaded by the user, along with the conversion option the user wants to convert (e.g., "cat"), and also receives emotion data to recognize the user's emotion.

[0757] Photo analysis and transformation

[0758] The received photo is analyzed by a generative AI model on the server. Based on this analysis, the photo is transformed into a specific, predefined form (e.g., "cat"). The emotion engine can also analyze the user's emotion data and automatically select appropriate transformation options. Additional effects may also be applied based on the emotion data.

[0759] Save the converted photo

[0760] The converted photos will be saved in a specified folder on the server, with a file name generated based on the original image.

[0761] Generating an access URL

[0762] An access URL for the saved converted photo is generated, which is used by the user to access the converted photo.

[0763] Sending a response

[0764] The generated access URL will be provided to the user, allowing them to view and share the converted photos.

[0765] Client-side programs

[0766] Providing a user interface

[0767] The device displays a form on a web page, allowing the user to select a photo, set conversion options, and enter emotion data, which may be automatically derived from the user's facial expressions or manually selected by the user.

[0768] Submitting form data

[0769] When the user clicks the "Transform Photo" button, the selected photo file, conversion options, and emotion data are bundled into a FormData object and sent to the server as a POST request.

[0770] Displaying the conversion results

[0771] Based on the response received from the server, the device displays the converted photo, which the user can then view and share via social media or messaging.

[0772] Example of operation

[0773] When a user accesses the AI ​​photo transformation app using a web browser, a form is displayed. The user clicks the "Select photo" button and selects a photo of their face. Next, the user selects "cat" from the "Transformation type" drop-down menu and enters emotion data. Emotion data indicates states such as "happy" or "sad."

[0774] When the user clicks the "Transform Photo" button, the device sends the selected photo, transformation options, and emotion data to the server.

[0775] The server saves the received photos in a designated folder and inputs them into the generative AI model, which then converts the face photo into a cat-like form based on the photo. Furthermore, the emotion engine analyzes the user's emotional data and adds a bright and cheerful effect to the photo based on the "happy" emotion, for example.

[0776] The converted photo is saved and a URL to access the photo is generated. This URL is returned to the user as a response. The device receives this URL and displays the photo to the user. This allows the user to view an image in which their face has been converted into a cat, and enjoy the effects applied to the image.

[0777] The processing flow will be explained below.

[0778] Step 1:

[0779] User

[0780] Open your web browser and access the AI ​​Photo Converter app.

[0781] Click the "Select photo" button and select a photo of your face from your local files.

[0782] From the "Transformation type" drop-down menu, select a transformation option (e.g., "Cat").

[0783] From the "Emotion" drop-down menu, select your emotion (e.g., "fun").

[0784] Step 2:

[0785] Terminal

[0786] The user clicks the "Transform Photo" button.

[0787] The submit event is triggered and the selected photo, conversion options, and emotion data are bundled into a FormData object.

[0788] A POST request is made to the server using the FormData object.

[0789] URL: / upload_photo

[0790] Method: POST

[0791] Body: FormData(photo, conversion options, emotion data)

[0792] Step 3:

[0793] server

[0794] The server receives a POST request at the / upload_photo endpoint.

[0795] Get the photo file, conversion options, and emotion data from the request.

[0796] Save the photo files to the specified temporary folder . / uploads / .

[0797] Filename: Use the filename of the uploaded photo (e.g. photo.jpg).

[0798] Step 4:

[0799] server

[0800] The path to the saved photo file and conversion options are used to instruct the generative AI model on the conversion process.

[0801] Model: A pre-trained generative AI model.

[0802] Input: The path to the saved photo file (e.g. . / uploads / photo.jpg).

[0803] Conversion option: The option selected by the user (e.g., "cat").

[0804] Step 5:

[0805] server

[0806] The emotion engine analyzes the user's emotion data and determines the appropriate conversion option settings and additional effects.

[0807] Example: If the user's emotion is "happy", add a bright color effect to the photo.

[0808] Step 6:

[0809] server

[0810] A generative AI model processes the photo to transform it into a specific form.

[0811] Example: Converting a face photo into a cat form.

[0812] The emotion engine applies the determined effect to the transformed photo.

[0813] Example: Adding bright color effects.

[0814] Step 7:

[0815] server

[0816] The converted photos will be saved in the specified folder . / transformed / .

[0817] Filename: transformed_<original filename> (e.g., transformed_photo.jpg).

[0818] Step 8:

[0819] server

[0820] Generate a URL to access the converted photo.

[0821] Example: http: / / example.com / transformed / transformed_photo.jpg.

[0822] The generated URL is returned to the user as a response.

[0823] Step 9:

[0824] Terminal

[0825] Process the response received from the server.

[0826] Extract the URL of the converted photo from the response.

[0827] Step 10:

[0828] Terminal

[0829] Web page Update the tag's src attribute to the extracted URL.

[0830] The converted photo is displayed to the user.

[0831] After completing the above steps, users can view and share their photos after they have been converted based on the selected conversion options and emotion data.

[0832] Example 2

[0833] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0834] Conventional image conversion systems simply convert images provided by users into another format, but lack the ability to personalize the service by taking into account the user's emotions. Furthermore, they do not consider adding effects based on the user's emotions to the converted image. As a result, the quality of the user experience is not sufficiently improved, making it difficult to provide personalized services.

[0835] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for a user to upload an input image, means for receiving the input image, conversion options, and emotion data, means for performing analysis using a generative AI model, means for analyzing the emotion data using an emotion engine and adding appropriate effects, means for saving the converted image, means for generating an access URL for the saved converted image, means for providing the access URL to the user, and means for displaying the converted image to the user. This enables personalized image conversion that takes into account the user's emotions and the addition of effects according to the emotions.

[0836] A "user" is an individual or entity that utilizes the system to upload input images and provide transformation options and emotion data.

[0837] An "input image" is the original photograph or image data that a user uploads to the system.

[0838] The "conversion option" is an item that indicates the type of conversion selected by the user, such as conversion into a specific form such as a person, character, or animal.

[0839] "Emotion data" is data that represents the user's emotion, and is information that indicates an emotional state such as "happy" or "sad," for example.

[0840] A "generative AI model" is an artificial intelligence algorithm or program that analyzes an input image and transforms it into a specific, specified form.

[0841] An "emotion engine" is a program or algorithm that has the ability to analyze emotional data and add appropriate effects to images based on the results.

[0842] An "effect" is a visual modification or enhancement that is added to a transformed image based on emotional data.

[0843] A "server" is a computer system that receives, analyzes, converts, and stores data sent by users, and provides the results of the conversion.

[0844] "Access URL" is the web address for accessing the saved converted image.

[0845] A "terminal" is a device such as a computer, smartphone, or tablet that a user uses to access the system.

[0846] "Saving" means storing the converted image data as a file in a specified location.

[0847] "Display" means showing the converted image to the user on the screen of the terminal.

[0848] The system of the present invention automates a series of processes in which users upload their own photos, convert them into a specified format, and add effects based on emotional data.

[0849] The system consists of a server and a terminal, where the server is responsible for the main data processing and analysis, and the terminal provides the user interface.

[0850] Server-side features

[0851] The server provides the following functionality:

[0852] 1. Receiving photos:

[0853] The server receives the photo uploaded by the user, the transformation option (e.g., "cat"), and the emotion data (e.g., "fun"). The photo file is saved in the temporary folder / uploads.

[0854] 2. Photo analysis and conversion:

[0855] The server inputs the stored photo into a generative AI model and converts it into the specified form (e.g., "cat"). This generative AI model uses technologies such as "StyleGAN."

[0856] 3. Emotion data analysis and effect addition:

[0857] The server analyzes the emotion data using an emotion engine and adds appropriate effects to the converted image (e.g., a bright filter for the "happy" emotion). The emotion engine used is "EmotionAPI" or similar.

[0858] 4. Save the converted photo and generate an access URL:

[0859] The converted photos are saved in a new folder, for example, / transformed-photos. The server generates an access URL based on the file path of the saved photos.

[0860] 5. Sending the response:

[0861] The server provides the generated access URL to the user, which allows the user to access the converted photo.

[0862] Client-side features

[0863] The terminal provides the following features:

[0864] 1. Providing the user interface:

[0865] The device displays a form on a web page, allowing the user to select a photo and enter a transformation option (e.g., "cat") and emotional data (e.g., "fun"), which can be manually entered by the user or automatically obtained from facial expressions.

[0866] 2. Submitting form data:

[0867] When the user clicks the "Transform Photo" button, the device sends the selected photo file, conversion options, and emotion data to the server as a FormData object.

[0868] 3. View the conversion results:

[0869] The device displays the converted photo in the browser based on the access URL received from the server. The user can then check the converted photo and share it via social media or messaging apps.

[0870] Specific examples

[0871] A user accesses the AI ​​photo transformation app using a browser, selects their own photo from the "Select photo" button in the form, selects "Cat" in the "Transformation type" and "Fun" in the "Emotion" drop-down menu, and clicks the "Transform Photo" button, sending the selected photo file, transformation options, and emotion data to the server.

[0872] The server inputs the received photo file into the generative AI model and converts it into a cat's form. The emotion engine then adds a bright effect to the photo based on the "happy" emotion. The converted image is saved and a URL is generated. This URL is provided to the user, who can then view the converted photo on their device.

[0873] Prompt Sentence Examples

[0874] Here are some examples of specific prompts:

[0875] "Create a program that lets users take selfies with happy emotions and transform them into a cat style photo. Add a brightening effect to the resulting photo."

[0876] As described above, by using this system, users can convert their own facial photos into the form of cats that reflect happy emotions.

[0877] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0878] Step 1:

[0879] A user visits a web page and sees a form with a "Select photo" button, a "Transformation type" drop-down menu, and an "Emotion" drop-down menu. The user uploads their photo, chooses a transformation option (e.g., "cat"), and enters emotion data (e.g., "fun"). The inputs for this operation are the photo file, the transformation option, and the emotion data.

[0880] Step 2:

[0881] When the user clicks the "Transform Photo" button, the device sends the selected photo file, conversion options, and emotion data as a FormData object to the server. The input is the aforementioned FormData object, and the output is an HTTP POST request.

[0882] Step 3:

[0883] The server receives an HTTP POST request and parses the photo file, conversion options, and emotion data. The photo file is saved in the temporary folder / uploads, and the conversion options and emotion data are stored in memory variables. The input is the HTTP POST request, and the output is the saved image file and memory variables.

[0884] Step 4:

[0885] The server inputs the saved photo file into a generative AI model and converts it into the specified form (e.g., "cat"). The generative AI model used is, for example, "StyleGAN." The input is the photo file and conversion options, and the output is the converted image data.

[0886] Step 5:

[0887] The server uses an emotion engine to analyze the emotion data and add appropriate effects to the converted image (e.g., a bright filter for the "happy" emotion). The emotion engine uses "EmotionAPI" or similar. The input is the converted image data and emotion data, and the output is the converted image with the added effect.

[0888] Step 6:

[0889] The server saves the converted image, for example, in the / transformed-photos folder. The server generates an access URL based on the path of this saved file. The input is the converted image with the effect added, and the output is the saved image file and the access URL.

[0890] Step 7:

[0891] The server sends the generated access URL to the user as an HTTP response. The response body contains data in JSON format such as { "url": "www.example.com / transformed / photos / 123.jpg"}. The input is the generated access URL, and the output is the HTTP response.

[0892] Step 8:

[0893] The device analyzes the access URL received from the server and displays the converted image on the browser. The user can then check the converted image and share it via social media or messaging apps. The input is the access URL received as an HTTP response, and the output is the displayed converted image.

[0894] (Application example 2)

[0895] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0896] While conventional photo conversion systems can convert photos uploaded by users into individual formats, they have the problem of not applying personalized effects that take the user's emotions into account. Furthermore, while there is a demand in the advertising field for a system that can automatically generate advertising photos that reflect the user's emotions, no such system exists. The present invention aims to solve these problems by providing a system that enables the automatic generation of personalized advertising photos by applying effects based on the user's emotional data.

[0897] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0898] In this invention, the server includes means for receiving an input image, means for analyzing the input image, means for converting the input image into a specific set form, means for acquiring emotion data from the input image, means for applying an additional effect to the converted image based on the emotion data, means for saving the converted image, means for generating an access URL for the saved converted image, and means for providing the access URL to the user. This enables automatic generation of advertising photos that take user emotions into consideration.

[0899] "Input image" refers to a photograph or image uploaded by a user.

[0900] "Means for performing analysis" refers to the technical means for analyzing the input image and understanding its content and characteristics.

[0901] "Specific form" refers to the specific transformation form set by the generative AI model, including, for example, transformation into animals or products.

[0902] "Emotion data" refers to data generated based on the user's facial expressions and input emotion information.

[0903] "Additional effects" refer to visual effects that are further applied to an image that has been transformed based on emotion data.

[0904] "Storing means" refers to the technical means of recording the converted images in designated storage on a server.

[0905] "Access URL" refers to the web address where users can access the converted image.

[0906] A "generative AI model" refers to an artificial intelligence model that generates new images based on input images.

[0907] System Configuration

[0908] The system of the present invention automates the process of users uploading photos, converting the photos into specific forms, and applying effects based on the user's emotional data. The system is composed of a server and a user terminal.

[0909] Hardware and Software

[0910] Hardware: Smartphones, servers

[0911] Software: Cloud services used for servers (e.g., AWS), generative AI models (e.g., GAN), sentiment analysis engines (e.g., Microsoft Azure's Face API), and web front-end technologies (HTML, CSS, JavaScript).

[0912] Server-side processing

[0913] 1. Receiving photos

[0914] The server receives the photos uploaded by the user, as well as the transformation options (e.g., animals, products) selected by the user and the acquired emotion data.

[0915] 2. Acquiring Emotion Data

[0916] The server generates emotion data based on the user's facial expression data and input emotion information, using an emotion analysis engine for this process.

[0917] 3. Photo conversion

[0918] The server inputs the received photo into a generative AI model and converts it into an image of a specific set form (e.g., a cat, a product for advertising).

[0919] 4. Applying Effects

[0920] Apply an additional effect to the converted image based on the emotion data, which gives different visual effects depending on the emotion data (e.g., happiness).

[0921] 5. Save the converted image

[0922] The converted image is saved on the server and a URL for the saved image is generated.

[0923] 6. Providing an access URL

[0924] The generated URL is provided to the user, who can then access the converted image.

[0925] Processing on the user terminal side

[0926] 1. Upload a photo

[0927] Users launch the application on their smartphone, upload a photo, and select the product category (e.g., cosmetics) for the advertisement.

[0928] 2. Acquiring Emotion Data

[0929] The user device uses a camera function to capture the user's facial expressions and obtain emotional data in real time, which is also sent to the server.

[0930] 3. Displaying the conversion results

[0931] The user's device receives the access URL provided by the server and displays the converted image. The user can check the results and share them if necessary.

[0932] Specific examples

[0933] For example, suppose User A uses the application to upload a photo of themselves and selects the cosmetics category. Because User A is smiling, the sentiment analysis engine recognizes this as "happiness." The photo, transformation options, and the "happiness" emotion data are sent to the server. The server then transforms the photo using a generative AI model to regenerate it into an image suitable for advertising. It also applies a bright, energetic effect based on "happiness." The resulting URL is provided to the user, who can view it on their smartphone.

[0934] Prompt Sentence Examples

[0935] Examples of prompts used by generative AI models include:

[0936] "Upload user photos and transform them into ad designs for the cosmetics category. The user emotion is happiness, so add a bright effect to reflect that."

[0937] In this way, the system realizes the automatic generation of personalized advertising photos that take into account the user's emotions.

[0938] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0939] Step 1: Upload a photo

[0940] A user launches the app on their smartphone, selects and uploads their own photo, and also inputs the product category (e.g., cosmetics) to be advertised. The uploaded photo and the selected category are then sent to the server.

[0941] Input: User photo, Product category

[0942] Output: Sending photo data and category data to the server

[0943] Step 2: Obtaining emotion data

[0944] The user device uses the smartphone's camera to capture the user's facial expressions in real time, and an emotion analysis engine (e.g., Microsoft Azure's Face API) is used to analyze the facial expressions and generate emotion data, which is also sent to the server.

[0945] Input: Real-time facial expression data of the user

[0946] Output: Generate emotion data and send it to the server

[0947] Step 3: Receiving photos

[0948] The server receives the photo data, product category, and emotion data sent from the user terminal.

[0949] Input: Photo data, category data, emotion data

[0950] Output: Saving and preparing data on the server

[0951] Step 4: Analyze and convert photos

[0952] The server inputs the received photo data into a generative AI model (e.g., GAN) and converts it into an image of a specific set form (e.g., a cat, a product for advertising). The generative AI model converts the photo based on the prompt text.

[0953] Input: Photo data, generative AI model, prompt

[0954] Output: Transformed image data

[0955] Step 5: Apply effects

[0956] The server applies additional effects to the transformed image based on the emotion data, for example, if the emotion is "happy," it applies a bright effect. This process is performed using an emotion engine.

[0957] Input: Converted image data, emotion data

[0958] Output: Final image data with effects applied

[0959] Step 6: Save the converted image

[0960] The server saves the final image data with the effect applied to the specified folder and generates an access URL for the save destination.

[0961] Input: Image data with effects applied

[0962] Output: Saved image data, generated access URL

[0963] Step 7: Provide an access URL

[0964] The server returns the generated access URL to the user's device as a response. The user's device receives this URL and displays the converted image.

[0965] Input: Access URL

[0966] Output: Receives the access URL and displays the image on the user's device

[0967] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0968] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0969] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0970] [Third embodiment]

[0971] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0972] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0973] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0974] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0975] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0976] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0977] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0978] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0979] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0980] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0981] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0982] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0983] The system of the present invention provides an automated process for users to upload and transform their photos. The following is a specific embodiment of the system.

[0984] Server-side programs

[0985] The server mainly receives user photos, transforms them using a generative AI model, and provides the results to users. Specifically, the server has the following functions:

[0986] 1. Receiving photos

[0987] The server receives the photo file uploaded by the user, along with the conversion options the user wants to convert (e.g., "cat").

[0988] 2. Photo analysis and transformation

[0989] The received photo is analyzed by a generative AI model on the server, which then transforms the photo into a specific form of your choosing (e.g., "cat").

[0990] 3. Save the converted photo

[0991] The converted photos will be saved in a specified folder on the server.

[0992] 4. Generate an access URL

[0993] An access URL for the saved converted photo is generated, which the user can use to access the converted photo.

[0994] 5. Sending the Response

[0995] The generated access URL will be provided to the user, allowing them to view and share the converted photos.

[0996] Client-side programs

[0997] The terminal provides a user interface, accepts user operations, sends requests to the server, and displays the results. Specifically, it has the following functions:

[0998] 1. Providing a user interface

[0999] The terminal displays a form on a web page that allows the user to select a photo and set conversion options.

[1000] 2. Submitting form data

[1001] When the user clicks the "Transform Photo" button, the selected photo file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[1002] 3. Displaying the conversion results

[1003] Based on the response received from the server (the URL of the converted photo), the converted photo is displayed on the device.

[1004] Example of operation

[1005] Suppose a user accesses an AI photo transformation app using a web browser. The user clicks the "Select photo" button and selects a photo of their face. Then, they select "Cat" from the "Transformation type" drop-down menu. Next, when the user clicks the "Transform Photo" button, the device sends the selected photo and transformation options to the server.

[1006] The server saves the received photo in a specified folder and inputs it into the generative AI model. The generative AI model uses the photo to convert the face photo into the form of a cat. The converted photo is saved as a new one, and an access URL for the photo is generated. This URL is returned to the user as a response. The device receives this URL and displays the photo to the user. This allows the user to view and share the image in which their face photo has been converted into a cat.

[1007] The processing flow will be explained below.

[1008] Step 1:

[1009] User

[1010] Open your web browser and access the AI ​​Photo Converter app.

[1011] Click the "Select photo" button and select the photo you want to convert from your local files.

[1012] From the "Transformation type" drop-down menu, select a transformation option (e.g., "Cat").

[1013] Step 2:

[1014] Terminal

[1015] The user clicks the "Transform Photo" button.

[1016] A submit event is triggered and the selected photo and conversion options are packed into a FormData object.

[1017] A POST request is made to the server using the FormData object.

[1018] URL: / upload_photo

[1019] Method: POST

[1020] Body: FormData (photo and conversion options)

[1021] Step 3:

[1022] server

[1023] The server receives a POST request at the / upload_photo endpoint.

[1024] Get the photo file and conversion options from the request.

[1025] Save the photo files to the specified temporary folder . / uploads / .

[1026] Filename: Use the filename of the uploaded photo (e.g. photo.jpg).

[1027] Step 4:

[1028] server

[1029] The path to the saved photo file and conversion options are used to instruct the generative AI model on the conversion process.

[1030] Model: A pre-trained generative AI model.

[1031] Input: The path to the saved photo file (e.g. . / uploads / photo.jpg).

[1032] Conversion option: The option selected by the user (e.g., "cat").

[1033] Step 5:

[1034] server

[1035] A generative AI model processes the photo to transform it into a specific form.

[1036] Example: Converting a face photo into a cat form.

[1037] The converted photo is generated.

[1038] Step 6:

[1039] server

[1040] The converted photos will be saved in the specified folder . / transformed / .

[1041] Filename: transformed_<original filename> (e.g., transformed_photo.jpg).

[1042] Step 7:

[1043] server

[1044] Generate a URL to access the converted photo.

[1045] Example: http: / / example.com / transformed / transformed_photo.jpg.

[1046] The generated URL is returned to the client as a response.

[1047] Step 8:

[1048] Terminal

[1049] Process the response received from the server.

[1050] Extract the URL of the converted photo from the response.

[1051] Step 9:

[1052] Terminal

[1053] Web page Update the tag's src attribute to the extracted URL.

[1054] The converted photo is displayed to the user.

[1055] After these steps, your photos will be converted based on the conversion options you selected, and you can then view and share the converted photos.

[1056] Example 1

[1057] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1058] Conventional image conversion systems lack the functionality to automatically convert images according to user-specified conversion options, and the conversion process is complex and difficult to use. In particular, image analysis and generation of conversion results require numerous manual operations, reducing user convenience.

[1059] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1060] In this invention, the server includes means for receiving an input image, means for analyzing the input image using a generative AI model, means for converting the input image into a specific format based on the analysis, means for saving the converted image, means for generating an access URL for the saved converted image, and means for providing the access URL to a user, thereby simplifying the automatic image conversion process and enabling fast and accurate conversion based on user-specified conversion options.

[1061] An "input image" is an image file that a user uploads to the system.

[1062] A "generative AI model" is an artificial intelligence model that uses machine learning and artificial intelligence techniques to analyze and transform images.

[1063] "Analysis" refers to the process of using a generative AI model to extract features from an input image and obtain information for transformation.

[1064] "Transformation" refers to the process of changing an input image into a specific, predetermined form.

[1065] "Storage" means that the converted image is kept in a storage device on the server.

[1066] "Access URL" means a web address for accessing the saved converted image via the Internet.

[1067] A "user interface" refers to the screen and input device that a user uses to operate a system.

[1068] "Conversion options" refer to the type and style of image conversion specified by the user.

[1069] The system of the present invention provides an automated process for users to upload their images and convert them into specific formats, specific embodiments of which are described in detail below.

[1070] Server-side programs

[1071] The server mainly receives images from users, transforms them using a generative AI model, and provides the results to users. Each function of the server is explained below.

[1072] 1. Receiving photos

[1073] The server receives the image file uploaded by the user, along with the conversion options specified by the user (e.g., "cat"). This allows the server to convert the image according to the user's intentions.

[1074] 2. Photo analysis and transformation using generative AI models

[1075] The received image is analyzed by a generative AI model (such as the DeepArt model or StyleGAN) on the server. After analysis, the image is transformed into a specific, specified form. The generative AI model uses machine learning and artificial intelligence to extract image features and perform the transformation.

[1076] 3. Save the converted image

[1077] The converted images are saved to a specified folder on the server (e.g. " / uploads / converted / "), providing a basis for users to access them later.

[1078] 4. Generate an access URL

[1079] An access URL for the saved converted image is generated. This URL is used by the user to access the converted image. By generating this URL, it is possible to provide the image to the user quickly.

[1080] 5. Sending the Response

[1081] The generated access URL is provided to the user, allowing them to view the converted image and share it if desired.

[1082] Client-side programs

[1083] The terminal provides a user interface, accepts user operations, sends requests to the server, and displays the results. Each function of the terminal is explained below.

[1084] 1. Providing a user interface

[1085] The device displays a form on a web page, allowing the user to select an image and set conversion options, providing an intuitive user experience.

[1086] 2. Submitting form data

[1087] When the user clicks the "Transform Photo" button, the selected image file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[1088] 3. Displaying the conversion results

[1089] Based on the response received from the server, the converted image is displayed on the device, allowing the user to check how their image has been converted.

[1090] Example of operation

[1091] For example, the following prompt sentence can be input to a generative AI model:

[1092] Prompt: "Transform the user's face into a cat."

[1093] (Example scenario)

[1094] A user accesses the AI ​​photo transformation app using a web browser. The user clicks the "Select photo" button and selects a photo of their face. Then, they select "Cat" from the "Transformation type" drop-down menu. Next, the user clicks the "Transform Photo" button, and the selected image and transformation options are sent by the device to the server.

[1095] The server saves the received image file in a specified folder and inputs it into the generative AI model. The generative AI model uses the image to convert the face photo into the shape of a cat. The converted image is saved as a new image, and an access URL for that image is generated. This URL is returned to the user as a response.

[1096] The device receives this URL and displays the image to the user, who can then view and share the image in which their face has been transformed into a cat.

[1097] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1098] Step 1: User access

[1099] Users access the AI ​​photo conversion app through a web browser. Users access the app for image conversion and first see the interface on the main page.

[1100] Step 2: Select a photo

[1101] The user clicks the "Select photo" button and selects their own image (e.g., a photo of their face). This puts the selected image file from the user's device into a waiting state for upload.

[1102] Input: An image file selected by the user.

[1103] Output: Image files waiting to be uploaded

[1104] Step 3: Select conversion options

[1105] The user selects a transformation option, such as "cat," from the "Transformation type" dropdown menu, which tells the system what transformation to perform based on the user's request.

[1106] Input: User selected conversion options

[1107] Output: Selected conversion options

[1108] Step 4: Submit a conversion request

[1109] The user clicks the "Transform Photo" button, which causes the device to send the selected image file and transformation options to the server as a POST request.

[1110] Input: Selected image file and conversion options

[1111] Output: POST request to the server

[1112] Step 5: Receiving photos and options (server side)

[1113] The server receives the image file and conversion options sent from the device, and stores the received data in a temporary folder.

[1114] Input: Image file and conversion options sent by the user

[1115] Output: Image files stored in a temporary folder and conversion options

[1116] Step 6: Prepare input for the generative AI model

[1117] The server saves the received image files in a specified folder and prepares the data to be input to the generative AI model. Specifically, it converts the image file path and conversion options into a format that can be passed to the generative AI model.

[1118] Input: Image file saved in temporary folder and conversion options

[1119] Output: Input data for a generative AI model

[1120] Step 7: Transformation with a generative AI model

[1121] A generative AI model (such as the DeepArt model or StyleGAN) on the server analyzes the image based on the input data and converts it into the specified form. During this process, the generative AI model extracts the features of the input image and converts it into the specified form.

[1122] Input: Input data for the generative AI model

[1123] Output: The converted image data

[1124] Step 8: Save the converted image

[1125] The converted image data will be saved in a specified folder on the server (e.g. " / uploads / converted / "). This operation establishes a foundation for future access.

[1126] Input: Transformed image data

[1127] Output: Saved converted image file

[1128] Step 9: Generate an access URL

[1129] The server generates an access URL for the saved converted image, which the user can use to access the converted image.

[1130] Input: Saved converted image file

[1131] Output: Access URL

[1132] Step 10: Sending the Response

[1133] A response including the generated access URL is sent from the server to the user's device, allowing the user to access the converted image.

[1134] Input: Access URL

[1135] Output: The response sent to the user's device

[1136] Step 11: Receiving the response (terminal side)

[1137] The device receives the response sent from the server and obtains the access URL from the data included in the response.

[1138] Input: Response from the server

[1139] Output: The obtained access URL

[1140] Step 12: View the conversion results

[1141] The device uses the obtained access URL to display the converted image on the user interface, allowing the user to check the converted image and share it if necessary.

[1142] Input: The obtained access URL

[1143] Output: The converted image displayed in the user interface.

[1144] The above are the processing steps of this system and their specific operation details.

[1145] (Application example 1)

[1146] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1147] Conventional photo conversion systems require manual human intervention to convert user-supplied images into specific formats, which is time-consuming and labor-intensive. Furthermore, the conversion options are limited, making it difficult to meet the diverse needs of users. Furthermore, the system lacks functionality for easily sharing the converted images. This makes it difficult for users to express themselves more flexibly and quickly create content.

[1148] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1149] In this invention, the server includes means for receiving an input image, means for analyzing the input image, means for converting the input image into a specific format based on the analysis, means for saving the converted image, means for generating an access URL for the saved converted image, means for providing the access URL to a user, means for converting the image using a generative AI model based on a specific prompt, and means for displaying the converted image on a user interface. This allows photos uploaded by users to be quickly converted into various styles using the generative AI model and easily shared.

[1150] "Input images" are photographs or image data that users upload to the system.

[1151] "Analysis" is the process of data processing and analysis performed on an input image to recognize specific features or morphology.

[1152] A "particular form" is a form, such as a set style, character, or theme, into which an input image is transformed using a generative AI model.

[1153] "Saving" means that the converted image is stored in a specified folder on the server.

[1154] "Access URL" is the web address generated to allow users to access the converted image.

[1155] "Provision" refers to the process of informing the user of the generated access URL through a communication means.

[1156] A "generative AI model" is a machine learning algorithm and data model used to transform an input image into a specified form.

[1157] A "prompt" is text that describes the instructions that the generative AI model should follow when converting an image.

[1158] A "user interface" is the part of the software that provides the screen display and input means for the user to operate the system.

[1159] MODE FOR CARRYING OUT THE INVENTION

[1160] The present invention provides an automated process for users to upload their own photos and convert them into a specific format. Specific embodiments for implementing the present invention are as follows:

[1161] Server-side programs

[1162] Hardware and Software

[1163] Server: The server receives photos, converts them using the generative AI model, saves the converted images, and generates an access URL. The server uses Python (Flask or Django).

[1164] Generative AI models: For example, use StyleGAN or DALL-E. These models are machine learning algorithms that transform input images into a specified form.

[1165] Program processing

[1166] The server receives photos uploaded by users. Once the photos are sent, a generative AI model on the server converts them into a specific format according to the specified prompt. The converted images are stored on the server, and a generated access URL is provided to the user.

[1167] Specific examples of processing

[1168] A user accesses the Style Change Photo Maker app on their smartphone, uploads a photo of their face, and specifies transformation options such as "Halloween style." The following prompt is then passed to the generative AI model:

[1169] "Give me this photo and transform it into a Halloween style."

[1170] The generative AI model follows the prompt, detects the facial area, applies Halloween-themed makeup and backgrounds, and saves the converted photo on a server, generating an access URL for it. This URL is then sent to the user as a response.

[1171] Client-side programs

[1172] Hardware and Software

[1173] Smartphone: Provides a client-side user interface. Applications are developed using JavaScript (React Native).

[1174] Program processing

[1175] Users upload photos and select conversion options through the smartphone app. Once the selection is complete, the form data is sent to the server. The server returns an access URL for the converted image, which the app displays, allowing users to view and share the converted photo.

[1176] Specific examples of processing

[1177] The user clicks the "Select photo" button, selects their own photo, and then selects "Anime character" from the "Transformation type" drop-down menu. Then, by clicking the "Transform Photo" button, the selected photo and the option to transform it into an "Anime character" are sent to the server. The generative AI model follows the prompt:

[1178] "Give me this photo and turn it into an anime character."

[1179] The generative AI model converts the photo into an anime character-like image, saves it, and sends the user an access URL. The app receives this URL and displays the converted photo to the user, allowing the user to freely share the photo.

[1180] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1181] Step 1:

[1182] Application launch and user photo selection

[1183] The user launches the "Style Change Photo Maker" app on their smartphone. The user clicks the "Select photo" button in the app and selects a photo from their gallery. The selected photo is then imported into the app.

[1184] Input: A photo file selected by the user

[1185] Output: The selected photo is saved in the app's memory.

[1186] Step 2:

[1187] Selecting conversion options

[1188] The user selects any transformation option (e.g., "Halloween" or "Anime Character") from the "Transformation type" drop-down menu.

[1189] Input: User selected conversion options

[1190] Output: Specific conversion options are stored in memory

[1191] Step 3:

[1192] Submitting form data

[1193] When the user clicks the "Transform Photo" button, the selected photo file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[1194] Input: Photo files and conversion options

[1195] Output: Packaged into a FormData object and sent to the server

[1196] Step 4:

[1197] Receiving photos

[1198] The server receives the HTTP POST request from the user, parses the photo file and conversion options, and temporarily stores the received photo on the server.

[1199] Input: HTTP POST request sent by the user

[1200] Output: Photo files and conversion options are saved to the server.

[1201] Step 5:

[1202] Photo analysis and transformation with generative AI models

[1203] The server launches a generative AI model based on the received photo file and conversion options. It generates a prompt (e.g., "Give me this photo, please convert it into a Halloween style.") and inputs it into the generative AI model. The generative AI model then converts the photo into the specified format based on the prompt.

[1204] Input: saved photo file, conversion options, generated prompt text

[1205] Output: Image data transformed by the generative AI model

[1206] Step 6:

[1207] Saving the converted image

[1208] The converted image data is saved in a specified folder on the server.

[1209] Input: Image data transformed by the generative AI model

[1210] Output: Converted image files saved on the server

[1211] Step 7:

[1212] Generating an access URL

[1213] An access URL for the saved converted image file will be generated.

[1214] Input: The destination location for the converted image file

[1215] Output: Generated access URL

[1216] Step 8:

[1217] Sending a response

[1218] The generated access URL is sent from the server to the user as an HTTP response.

[1219] Input: Generated access URL

[1220] Output: The HTTP response sent to the user

[1221] Step 9:

[1222] Viewing the converted image

[1223] The user receives the access URL sent from the server within the app, and the converted image is displayed in the app via this URL. The user can view, save, and share this image.

[1224] Input: Received access URL

[1225] Output: The converted image is displayed in the user's app.

[1226] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1227] The system of the present invention provides an automated process for users to upload and transform their own photos. In particular, by combining an emotion engine that recognizes the user's emotions, more personalized photo transformations can be achieved. The following is a specific embodiment of the system.

[1228] Server-side programs

[1229] Receiving photos

[1230] The server has the function of receiving the photo file uploaded by the user, along with the conversion option the user wants to convert (e.g., "cat"), and also receives emotion data to recognize the user's emotion.

[1231] Photo analysis and transformation

[1232] The received photo is analyzed by a generative AI model on the server. Based on this analysis, the photo is transformed into a specific, predefined form (e.g., "cat"). The emotion engine can also analyze the user's emotion data and automatically select appropriate transformation options. Additional effects may also be applied based on the emotion data.

[1233] Save the converted photo

[1234] The converted photos will be saved in a specified folder on the server, with a file name generated based on the original image.

[1235] Generating an access URL

[1236] An access URL for the saved converted photo is generated, which is used by the user to access the converted photo.

[1237] Sending a response

[1238] The generated access URL will be provided to the user, allowing them to view and share the converted photos.

[1239] Client-side programs

[1240] Providing a user interface

[1241] The device displays a form on a web page, allowing the user to select a photo, set conversion options, and enter emotion data, which may be automatically derived from the user's facial expressions or manually selected by the user.

[1242] Submitting form data

[1243] When the user clicks the "Transform Photo" button, the selected photo file, conversion options, and emotion data are bundled into a FormData object and sent to the server as a POST request.

[1244] Displaying the conversion results

[1245] Based on the response received from the server, the device displays the converted photo, which the user can then view and share via social media or messaging.

[1246] Example of operation

[1247] When a user accesses the AI ​​photo transformation app using a web browser, a form is displayed. The user clicks the "Select photo" button and selects a photo of their face. Next, the user selects "cat" from the "Transformation type" drop-down menu and enters emotion data. Emotion data indicates states such as "happy" or "sad."

[1248] When the user clicks the "Transform Photo" button, the device sends the selected photo, transformation options, and emotion data to the server.

[1249] The server saves the received photos in a designated folder and inputs them into the generative AI model, which then converts the face photo into a cat-like form based on the photo. Furthermore, the emotion engine analyzes the user's emotional data and adds a bright and cheerful effect to the photo based on the "happy" emotion, for example.

[1250] The converted photo is saved and a URL to access the photo is generated. This URL is returned to the user as a response. The device receives this URL and displays the photo to the user. This allows the user to view an image in which their face has been converted into a cat, and enjoy the effects applied to the image.

[1251] The processing flow will be explained below.

[1252] Step 1:

[1253] User

[1254] Open your web browser and access the AI ​​Photo Converter app.

[1255] Click the "Select photo" button and select a photo of your face from your local files.

[1256] From the "Transformation type" drop-down menu, select a transformation option (e.g., "Cat").

[1257] From the "Emotion" drop-down menu, select your emotion (e.g., "fun").

[1258] Step 2:

[1259] Terminal

[1260] The user clicks the "Transform Photo" button.

[1261] The submit event is triggered and the selected photo, conversion options, and emotion data are bundled into a FormData object.

[1262] A POST request is made to the server using the FormData object.

[1263] URL: / upload_photo

[1264] Method: POST

[1265] Body: FormData(photo, conversion options, emotion data)

[1266] Step 3:

[1267] server

[1268] The server receives a POST request at the / upload_photo endpoint.

[1269] Get the photo file, conversion options, and emotion data from the request.

[1270] Save the photo files to the specified temporary folder . / uploads / .

[1271] Filename: Use the filename of the uploaded photo (e.g. photo.jpg).

[1272] Step 4:

[1273] server

[1274] The path to the saved photo file and conversion options are used to instruct the generative AI model on the conversion process.

[1275] Model: A pre-trained generative AI model.

[1276] Input: The path to the saved photo file (e.g. . / uploads / photo.jpg).

[1277] Conversion option: The option selected by the user (e.g., "cat").

[1278] Step 5:

[1279] server

[1280] The emotion engine analyzes the user's emotion data and determines the appropriate conversion option settings and additional effects.

[1281] Example: If the user's emotion is "happy", add a bright color effect to the photo.

[1282] Step 6:

[1283] server

[1284] A generative AI model processes the photo to transform it into a specific form.

[1285] Example: Converting a face photo into a cat form.

[1286] The emotion engine applies the determined effect to the transformed photo.

[1287] Example: Adding bright color effects.

[1288] Step 7:

[1289] server

[1290] The converted photos will be saved in the specified folder . / transformed / .

[1291] Filename: transformed_<original filename> (e.g., transformed_photo.jpg).

[1292] Step 8:

[1293] server

[1294] Generate a URL to access the converted photo.

[1295] Example: http: / / example.com / transformed / transformed_photo.jpg.

[1296] The generated URL is returned to the user as a response.

[1297] Step 9:

[1298] Terminal

[1299] Process the response received from the server.

[1300] Extract the URL of the converted photo from the response.

[1301] Step 10:

[1302] Terminal

[1303] Web page Update the tag's src attribute to the extracted URL.

[1304] The converted photo is displayed to the user.

[1305] After completing the above steps, users can view and share their photos after they have been converted based on the selected conversion options and emotion data.

[1306] Example 2

[1307] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1308] Conventional image conversion systems simply convert images provided by users into another format, but lack the ability to personalize the service by taking into account the user's emotions. Furthermore, they do not consider adding effects based on the user's emotions to the converted image. As a result, the quality of the user experience is not sufficiently improved, making it difficult to provide personalized services.

[1309] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for a user to upload an input image, means for receiving the input image, conversion options, and emotion data, means for performing analysis using a generative AI model, means for analyzing the emotion data using an emotion engine and adding appropriate effects, means for saving the converted image, means for generating an access URL for the saved converted image, means for providing the access URL to the user, and means for displaying the converted image to the user. This enables personalized image conversion that takes into account the user's emotions and the addition of effects according to the emotions.

[1310] A "user" is an individual or entity that utilizes the system to upload input images and provide transformation options and emotion data.

[1311] An "input image" is the original photograph or image data that a user uploads to the system.

[1312] The "conversion option" is an item that indicates the type of conversion selected by the user, such as conversion into a specific form such as a person, character, or animal.

[1313] "Emotion data" is data that represents the user's emotion, and is information that indicates an emotional state such as "happy" or "sad," for example.

[1314] A "generative AI model" is an artificial intelligence algorithm or program that analyzes an input image and transforms it into a specific, specified form.

[1315] An "emotion engine" is a program or algorithm that has the ability to analyze emotional data and add appropriate effects to images based on the results.

[1316] An "effect" is a visual modification or enhancement that is added to a transformed image based on emotional data.

[1317] A "server" is a computer system that receives, analyzes, converts, and stores data sent by users, and provides the results of the conversion.

[1318] "Access URL" is the web address for accessing the saved converted image.

[1319] A "terminal" is a device such as a computer, smartphone, or tablet that a user uses to access the system.

[1320] "Saving" means storing the converted image data as a file in a specified location.

[1321] "Display" means showing the converted image to the user on the screen of the terminal.

[1322] The system of the present invention automates a series of processes in which users upload their own photos, convert them into a specified format, and add effects based on emotional data.

[1323] The system consists of a server and a terminal, where the server is responsible for the main data processing and analysis, and the terminal provides the user interface.

[1324] Server-side features

[1325] The server provides the following functionality:

[1326] 1. Receiving photos:

[1327] The server receives the photo uploaded by the user, the transformation option (e.g., "cat"), and the emotion data (e.g., "fun"). The photo file is saved in the temporary folder / uploads.

[1328] 2. Photo analysis and conversion:

[1329] The server inputs the stored photo into a generative AI model and converts it into the specified form (e.g., "cat"). This generative AI model uses technologies such as "StyleGAN."

[1330] 3. Emotion data analysis and effect addition:

[1331] The server analyzes the emotion data using an emotion engine and adds appropriate effects to the converted image (e.g., a bright filter for the "happy" emotion). The emotion engine used is "EmotionAPI" or similar.

[1332] 4. Save the converted photo and generate an access URL:

[1333] The converted photos are saved in a new folder, for example, / transformed-photos. The server generates an access URL based on the file path of the saved photos.

[1334] 5. Sending the response:

[1335] The server provides the generated access URL to the user, which allows the user to access the converted photo.

[1336] Client-side features

[1337] The terminal provides the following features:

[1338] 1. Providing the user interface:

[1339] The device displays a form on a web page, allowing the user to select a photo and enter a transformation option (e.g., "cat") and emotional data (e.g., "fun"), which can be manually entered by the user or automatically obtained from facial expressions.

[1340] 2. Submitting form data:

[1341] When the user clicks the "Transform Photo" button, the device sends the selected photo file, conversion options, and emotion data to the server as a FormData object.

[1342] 3. View the conversion results:

[1343] The device displays the converted photo in the browser based on the access URL received from the server. The user can then check the converted photo and share it via social media or messaging apps.

[1344] Specific examples

[1345] A user accesses the AI ​​photo transformation app using a browser, selects their own photo from the "Select photo" button in the form, selects "Cat" in the "Transformation type" and "Fun" in the "Emotion" drop-down menu, and clicks the "Transform Photo" button, sending the selected photo file, transformation options, and emotion data to the server.

[1346] The server inputs the received photo file into the generative AI model and converts it into a cat's form. The emotion engine then adds a bright effect to the photo based on the "happy" emotion. The converted image is saved and a URL is generated. This URL is provided to the user, who can then view the converted photo on their device.

[1347] Prompt Sentence Examples

[1348] Here are some examples of specific prompts:

[1349] "Create a program that lets users take selfies with happy emotions and transform them into a cat style photo. Add a brightening effect to the resulting photo."

[1350] As described above, by using this system, users can convert their own facial photos into the form of cats that reflect happy emotions.

[1351] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1352] Step 1:

[1353] A user visits a web page and sees a form with a "Select photo" button, a "Transformation type" drop-down menu, and an "Emotion" drop-down menu. The user uploads their photo, chooses a transformation option (e.g., "cat"), and enters emotion data (e.g., "fun"). The inputs for this operation are the photo file, the transformation option, and the emotion data.

[1354] Step 2:

[1355] When the user clicks the "Transform Photo" button, the device sends the selected photo file, conversion options, and emotion data as a FormData object to the server. The input is the aforementioned FormData object, and the output is an HTTP POST request.

[1356] Step 3:

[1357] The server receives an HTTP POST request and parses the photo file, conversion options, and emotion data. The photo file is saved in the temporary folder / uploads, and the conversion options and emotion data are stored in memory variables. The input is the HTTP POST request, and the output is the saved image file and memory variables.

[1358] Step 4:

[1359] The server inputs the saved photo file into a generative AI model and converts it into the specified form (e.g., "cat"). The generative AI model used is, for example, "StyleGAN." The input is the photo file and conversion options, and the output is the converted image data.

[1360] Step 5:

[1361] The server uses an emotion engine to analyze the emotion data and add appropriate effects to the converted image (e.g., a bright filter for the "happy" emotion). The emotion engine uses "EmotionAPI" or similar. The input is the converted image data and emotion data, and the output is the converted image with the added effect.

[1362] Step 6:

[1363] The server saves the converted image, for example, in the / transformed-photos folder. The server generates an access URL based on the path of this saved file. The input is the converted image with the effect added, and the output is the saved image file and the access URL.

[1364] Step 7:

[1365] The server sends the generated access URL to the user as an HTTP response. The response body contains data in JSON format such as { "url": "www.example.com / transformed / photos / 123.jpg"}. The input is the generated access URL, and the output is the HTTP response.

[1366] Step 8:

[1367] The device analyzes the access URL received from the server and displays the converted image on the browser. The user can then check the converted image and share it via social media or messaging apps. The input is the access URL received as an HTTP response, and the output is the displayed converted image.

[1368] (Application example 2)

[1369] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1370] While conventional photo conversion systems can convert photos uploaded by users into individual formats, they have the problem of not applying personalized effects that take the user's emotions into account. Furthermore, while there is a demand in the advertising field for a system that can automatically generate advertising photos that reflect the user's emotions, no such system exists. The present invention aims to solve these problems by providing a system that enables the automatic generation of personalized advertising photos by applying effects based on the user's emotional data.

[1371] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1372] In this invention, the server includes means for receiving an input image, means for analyzing the input image, means for converting the input image into a specific set form, means for acquiring emotion data from the input image, means for applying an additional effect to the converted image based on the emotion data, means for saving the converted image, means for generating an access URL for the saved converted image, and means for providing the access URL to the user. This enables automatic generation of advertising photos that take user emotions into consideration.

[1373] "Input image" refers to a photograph or image uploaded by a user.

[1374] "Means for performing analysis" refers to the technical means for analyzing the input image and understanding its content and characteristics.

[1375] "Specific form" refers to the specific transformation form set by the generative AI model, including, for example, transformation into animals or products.

[1376] "Emotion data" refers to data generated based on the user's facial expressions and input emotion information.

[1377] "Additional effects" refer to visual effects that are further applied to an image that has been transformed based on emotion data.

[1378] "Storing means" refers to the technical means of recording the converted images in designated storage on a server.

[1379] "Access URL" refers to the web address where users can access the converted image.

[1380] A "generative AI model" refers to an artificial intelligence model that generates new images based on input images.

[1381] System Configuration

[1382] The system of the present invention automates the process of users uploading photos, converting the photos into specific forms, and applying effects based on the user's emotional data. The system is composed of a server and a user terminal.

[1383] Hardware and Software

[1384] Hardware: Smartphones, servers

[1385] Software: Cloud services used for servers (e.g., AWS), generative AI models (e.g., GAN), sentiment analysis engines (e.g., Microsoft Azure's Face API), and web front-end technologies (HTML, CSS, JavaScript).

[1386] Server-side processing

[1387] 1. Receiving photos

[1388] The server receives the photos uploaded by the user, as well as the transformation options (e.g., animals, products) selected by the user and the acquired emotion data.

[1389] 2. Acquiring Emotion Data

[1390] The server generates emotion data based on the user's facial expression data and input emotion information, using an emotion analysis engine for this process.

[1391] 3. Photo conversion

[1392] The server inputs the received photo into a generative AI model and converts it into an image of a specific set form (e.g., a cat, a product for advertising).

[1393] 4. Applying Effects

[1394] Apply an additional effect to the converted image based on the emotion data, which gives different visual effects depending on the emotion data (e.g., happiness).

[1395] 5. Save the converted image

[1396] The converted image is saved on the server and a URL for the saved image is generated.

[1397] 6. Providing an access URL

[1398] The generated URL is provided to the user, who can then access the converted image.

[1399] Processing on the user terminal side

[1400] 1. Upload a photo

[1401] Users launch the application on their smartphone, upload a photo, and select the product category (e.g., cosmetics) for the advertisement.

[1402] 2. Acquiring Emotion Data

[1403] The user device uses a camera function to capture the user's facial expressions and obtain emotional data in real time, which is also sent to the server.

[1404] 3. Displaying the conversion results

[1405] The user's device receives the access URL provided by the server and displays the converted image. The user can check the results and share them if necessary.

[1406] Specific examples

[1407] For example, suppose User A uses the application to upload a photo of themselves and selects the cosmetics category. Because User A is smiling, the sentiment analysis engine recognizes this as "happiness." The photo, transformation options, and the "happiness" emotion data are sent to the server. The server then transforms the photo using a generative AI model to regenerate it into an image suitable for advertising. It also applies a bright, energetic effect based on "happiness." The resulting URL is provided to the user, who can view it on their smartphone.

[1408] Prompt Sentence Examples

[1409] Examples of prompts used by generative AI models include:

[1410] "Upload user photos and transform them into ad designs for the cosmetics category. The user emotion is happiness, so add a bright effect to reflect that."

[1411] In this way, the system realizes the automatic generation of personalized advertising photos that take into account the user's emotions.

[1412] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1413] Step 1: Upload a photo

[1414] A user launches the app on their smartphone, selects and uploads their own photo, and also inputs the product category (e.g., cosmetics) to be advertised. The uploaded photo and the selected category are then sent to the server.

[1415] Input: User photo, Product category

[1416] Output: Sending photo data and category data to the server

[1417] Step 2: Obtaining emotion data

[1418] The user device uses the smartphone's camera to capture the user's facial expressions in real time, and an emotion analysis engine (e.g., Microsoft Azure's Face API) is used to analyze the facial expressions and generate emotion data, which is also sent to the server.

[1419] Input: Real-time facial expression data of the user

[1420] Output: Generate emotion data and send it to the server

[1421] Step 3: Receiving photos

[1422] The server receives the photo data, product category, and emotion data sent from the user terminal.

[1423] Input: Photo data, category data, emotion data

[1424] Output: Saving and preparing data on the server

[1425] Step 4: Analyze and convert photos

[1426] The server inputs the received photo data into a generative AI model (e.g., GAN) and converts it into an image of a specific set form (e.g., a cat, a product for advertising). The generative AI model converts the photo based on the prompt text.

[1427] Input: Photo data, generative AI model, prompt

[1428] Output: Transformed image data

[1429] Step 5: Apply effects

[1430] The server applies additional effects to the transformed image based on the emotion data, for example, if the emotion is "happy," it applies a bright effect. This process is performed using an emotion engine.

[1431] Input: Converted image data, emotion data

[1432] Output: Final image data with effects applied

[1433] Step 6: Save the converted image

[1434] The server saves the final image data with the effect applied to the specified folder and generates an access URL for the save destination.

[1435] Input: Image data with effects applied

[1436] Output: Saved image data, generated access URL

[1437] Step 7: Provide an access URL

[1438] The server returns the generated access URL to the user's device as a response. The user's device receives this URL and displays the converted image.

[1439] Input: Access URL

[1440] Output: Receives the access URL and displays the image on the user's device

[1441] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1442] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1443] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1444] [Fourth embodiment]

[1445] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1446] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1447] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1448] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1449] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1450] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1451] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1452] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1453] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1454] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1455] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1456] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1457] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1458] The system of the present invention provides an automated process for users to upload and transform their photos. The following is a specific embodiment of the system.

[1459] Server-side programs

[1460] The server mainly receives user photos, transforms them using a generative AI model, and provides the results to users. Specifically, the server has the following functions:

[1461] 1. Receiving photos

[1462] The server receives the photo file uploaded by the user, along with the conversion options the user wants to convert (e.g., "cat").

[1463] 2. Photo analysis and transformation

[1464] The received photo is analyzed by a generative AI model on the server, which then transforms the photo into a specific form of your choosing (e.g., "cat").

[1465] 3. Save the converted photo

[1466] The converted photos will be saved in a specified folder on the server.

[1467] 4. Generate an access URL

[1468] An access URL for the saved converted photo is generated, which the user can use to access the converted photo.

[1469] 5. Sending the Response

[1470] The generated access URL will be provided to the user, allowing them to view and share the converted photos.

[1471] Client-side programs

[1472] The terminal provides a user interface, accepts user operations, sends requests to the server, and displays the results. Specifically, it has the following functions:

[1473] 1. Providing a user interface

[1474] The terminal displays a form on a web page that allows the user to select a photo and set conversion options.

[1475] 2. Submitting form data

[1476] When the user clicks the "Transform Photo" button, the selected photo file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[1477] 3. Displaying the conversion results

[1478] Based on the response received from the server (the URL of the converted photo), the converted photo is displayed on the device.

[1479] Example of operation

[1480] Suppose a user accesses an AI photo transformation app using a web browser. The user clicks the "Select photo" button and selects a photo of their face. Then, they select "Cat" from the "Transformation type" drop-down menu. Next, when the user clicks the "Transform Photo" button, the device sends the selected photo and transformation options to the server.

[1481] The server saves the received photo in a specified folder and inputs it into the generative AI model. The generative AI model uses the photo to convert the face photo into the form of a cat. The converted photo is saved as a new one, and an access URL for the photo is generated. This URL is returned to the user as a response. The device receives this URL and displays the photo to the user. This allows the user to view and share the image in which their face photo has been converted into a cat.

[1482] The processing flow will be explained below.

[1483] Step 1:

[1484] User

[1485] Open your web browser and access the AI ​​Photo Converter app.

[1486] Click the "Select photo" button and select the photo you want to convert from your local files.

[1487] From the "Transformation type" drop-down menu, select a transformation option (e.g., "Cat").

[1488] Step 2:

[1489] Terminal

[1490] The user clicks the "Transform Photo" button.

[1491] A submit event is triggered and the selected photo and conversion options are packed into a FormData object.

[1492] A POST request is made to the server using the FormData object.

[1493] URL: / upload_photo

[1494] Method: POST

[1495] Body: FormData (photo and conversion options)

[1496] Step 3:

[1497] server

[1498] The server receives a POST request at the / upload_photo endpoint.

[1499] Get the photo file and conversion options from the request.

[1500] Save the photo files to the specified temporary folder . / uploads / .

[1501] Filename: Use the filename of the uploaded photo (e.g. photo.jpg).

[1502] Step 4:

[1503] server

[1504] The path to the saved photo file and conversion options are used to instruct the generative AI model on the conversion process.

[1505] Model: A pre-trained generative AI model.

[1506] Input: The path to the saved photo file (e.g. . / uploads / photo.jpg).

[1507] Conversion option: The option selected by the user (e.g., "cat").

[1508] Step 5:

[1509] server

[1510] A generative AI model processes the photo to transform it into a specific form.

[1511] Example: Converting a face photo into a cat form.

[1512] The converted photo is generated.

[1513] Step 6:

[1514] server

[1515] The converted photos will be saved in the specified folder . / transformed / .

[1516] Filename: transformed_<original filename> (e.g., transformed_photo.jpg).

[1517] Step 7:

[1518] server

[1519] Generate a URL to access the converted photo.

[1520] Example: http: / / example.com / transformed / transformed_photo.jpg.

[1521] The generated URL is returned to the client as a response.

[1522] Step 8:

[1523] Terminal

[1524] Process the response received from the server.

[1525] Extract the URL of the converted photo from the response.

[1526] Step 9:

[1527] Terminal

[1528] Web page Update the tag's src attribute to the extracted URL.

[1529] The converted photo is displayed to the user.

[1530] After these steps, your photos will be converted based on the conversion options you selected, and you can then view and share the converted photos.

[1531] Example 1

[1532] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1533] Conventional image conversion systems lack the functionality to automatically convert images according to user-specified conversion options, and the conversion process is complex and difficult to use. In particular, image analysis and generation of conversion results require numerous manual operations, reducing user convenience.

[1534] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1535] In this invention, the server includes means for receiving an input image, means for analyzing the input image using a generative AI model, means for converting the input image into a specific format based on the analysis, means for saving the converted image, means for generating an access URL for the saved converted image, and means for providing the access URL to a user, thereby simplifying the automatic image conversion process and enabling fast and accurate conversion based on user-specified conversion options.

[1536] An "input image" is an image file that a user uploads to the system.

[1537] A "generative AI model" is an artificial intelligence model that uses machine learning and artificial intelligence techniques to analyze and transform images.

[1538] "Analysis" refers to the process of using a generative AI model to extract features from an input image and obtain information for transformation.

[1539] "Transformation" refers to the process of changing an input image into a specific, predetermined form.

[1540] "Storage" means that the converted image is kept in a storage device on the server.

[1541] "Access URL" means a web address for accessing the saved converted image via the Internet.

[1542] A "user interface" refers to the screen and input device that a user uses to operate a system.

[1543] "Conversion options" refer to the type and style of image conversion specified by the user.

[1544] The system of the present invention provides an automated process for users to upload their images and convert them into specific formats, specific embodiments of which are described in detail below.

[1545] Server-side programs

[1546] The server mainly receives images from users, transforms them using a generative AI model, and provides the results to users. Each function of the server is explained below.

[1547] 1. Receiving photos

[1548] The server receives the image file uploaded by the user, along with the conversion options specified by the user (e.g., "cat"). This allows the server to convert the image according to the user's intentions.

[1549] 2. Photo analysis and transformation using generative AI models

[1550] The received image is analyzed by a generative AI model (such as the DeepArt model or StyleGAN) on the server. After analysis, the image is transformed into a specific, specified form. The generative AI model uses machine learning and artificial intelligence to extract image features and perform the transformation.

[1551] 3. Save the converted image

[1552] The converted images are saved to a specified folder on the server (e.g. " / uploads / converted / "), providing a basis for users to access them later.

[1553] 4. Generate an access URL

[1554] An access URL for the saved converted image is generated. This URL is used by the user to access the converted image. By generating this URL, it is possible to provide the image to the user quickly.

[1555] 5. Sending the Response

[1556] The generated access URL is provided to the user, allowing them to view the converted image and share it if desired.

[1557] Client-side programs

[1558] The terminal provides a user interface, accepts user operations, sends requests to the server, and displays the results. Each function of the terminal is explained below.

[1559] 1. Providing a user interface

[1560] The device displays a form on a web page, allowing the user to select an image and set conversion options, providing an intuitive user experience.

[1561] 2. Submitting form data

[1562] When the user clicks the "Transform Photo" button, the selected image file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[1563] 3. Displaying the conversion results

[1564] Based on the response received from the server, the converted image is displayed on the device, allowing the user to check how their image has been converted.

[1565] Example of operation

[1566] For example, the following prompt sentence can be input to a generative AI model:

[1567] Prompt: "Transform the user's face into a cat."

[1568] (Example scenario)

[1569] A user accesses the AI ​​photo transformation app using a web browser. The user clicks the "Select photo" button and selects a photo of their face. Then, they select "Cat" from the "Transformation type" drop-down menu. Next, the user clicks the "Transform Photo" button, and the selected image and transformation options are sent by the device to the server.

[1570] The server saves the received image file in a specified folder and inputs it into the generative AI model. The generative AI model uses the image to convert the face photo into the shape of a cat. The converted image is saved as a new image, and an access URL for that image is generated. This URL is returned to the user as a response.

[1571] The device receives this URL and displays the image to the user, who can then view and share the image in which their face has been transformed into a cat.

[1572] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1573] Step 1: User access

[1574] Users access the AI ​​photo conversion app through a web browser. Users access the app for image conversion and first see the interface on the main page.

[1575] Step 2: Select a photo

[1576] The user clicks the "Select photo" button and selects their own image (e.g., a photo of their face). This puts the selected image file from the user's device into a waiting state for upload.

[1577] Input: An image file selected by the user.

[1578] Output: Image files waiting to be uploaded

[1579] Step 3: Select conversion options

[1580] The user selects a transformation option, such as "cat," from the "Transformation type" dropdown menu, which tells the system what transformation to perform based on the user's request.

[1581] Input: User selected conversion options

[1582] Output: Selected conversion options

[1583] Step 4: Submit a conversion request

[1584] The user clicks the "Transform Photo" button, which causes the device to send the selected image file and transformation options to the server as a POST request.

[1585] Input: Selected image file and conversion options

[1586] Output: POST request to the server

[1587] Step 5: Receiving photos and options (server side)

[1588] The server receives the image file and conversion options sent from the device, and stores the received data in a temporary folder.

[1589] Input: Image file and conversion options sent by the user

[1590] Output: Image files stored in a temporary folder and conversion options

[1591] Step 6: Prepare input for the generative AI model

[1592] The server saves the received image files in a specified folder and prepares the data to be input to the generative AI model. Specifically, it converts the image file path and conversion options into a format that can be passed to the generative AI model.

[1593] Input: Image file saved in temporary folder and conversion options

[1594] Output: Input data for a generative AI model

[1595] Step 7: Transformation with a generative AI model

[1596] A generative AI model (such as the DeepArt model or StyleGAN) on the server analyzes the image based on the input data and converts it into the specified form. During this process, the generative AI model extracts the features of the input image and converts it into the specified form.

[1597] Input: Input data for the generative AI model

[1598] Output: The converted image data

[1599] Step 8: Save the converted image

[1600] The converted image data will be saved in a specified folder on the server (e.g. " / uploads / converted / "). This operation establishes a foundation for future access.

[1601] Input: Transformed image data

[1602] Output: Saved converted image file

[1603] Step 9: Generate an access URL

[1604] The server generates an access URL for the saved converted image, which the user can use to access the converted image.

[1605] Input: Saved converted image file

[1606] Output: Access URL

[1607] Step 10: Sending the Response

[1608] A response including the generated access URL is sent from the server to the user's device, allowing the user to access the converted image.

[1609] Input: Access URL

[1610] Output: The response sent to the user's device

[1611] Step 11: Receiving the response (terminal side)

[1612] The device receives the response sent from the server and obtains the access URL from the data included in the response.

[1613] Input: Response from the server

[1614] Output: The obtained access URL

[1615] Step 12: View the conversion results

[1616] The device uses the obtained access URL to display the converted image on the user interface, allowing the user to check the converted image and share it if necessary.

[1617] Input: The obtained access URL

[1618] Output: The converted image displayed in the user interface.

[1619] The above are the processing steps of this system and their specific operation details.

[1620] (Application example 1)

[1621] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1622] Conventional photo conversion systems require manual human intervention to convert user-supplied images into specific formats, which is time-consuming and labor-intensive. Furthermore, the conversion options are limited, making it difficult to meet the diverse needs of users. Furthermore, the system lacks functionality for easily sharing the converted images. This makes it difficult for users to express themselves more flexibly and quickly create content.

[1623] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1624] In this invention, the server includes means for receiving an input image, means for analyzing the input image, means for converting the input image into a specific format based on the analysis, means for saving the converted image, means for generating an access URL for the saved converted image, means for providing the access URL to a user, means for converting the image using a generative AI model based on a specific prompt, and means for displaying the converted image on a user interface. This allows photos uploaded by users to be quickly converted into various styles using the generative AI model and easily shared.

[1625] "Input images" are photographs or image data that users upload to the system.

[1626] "Analysis" is the process of data processing and analysis performed on an input image to recognize specific features or morphology.

[1627] A "particular form" is a form, such as a set style, character, or theme, into which an input image is transformed using a generative AI model.

[1628] "Saving" means that the converted image is stored in a specified folder on the server.

[1629] "Access URL" is the web address generated to allow users to access the converted image.

[1630] "Provision" refers to the process of informing the user of the generated access URL through a communication means.

[1631] A "generative AI model" is a machine learning algorithm and data model used to transform an input image into a specified form.

[1632] A "prompt" is text that describes the instructions that the generative AI model should follow when converting an image.

[1633] A "user interface" is the part of the software that provides the screen display and input means for the user to operate the system.

[1634] MODE FOR CARRYING OUT THE INVENTION

[1635] The present invention provides an automated process for users to upload their own photos and convert them into a specific format. Specific embodiments for implementing the present invention are as follows:

[1636] Server-side programs

[1637] Hardware and Software

[1638] Server: The server receives photos, converts them using the generative AI model, saves the converted images, and generates an access URL. The server uses Python (Flask or Django).

[1639] Generative AI models: For example, use StyleGAN or DALL-E. These models are machine learning algorithms that transform input images into a specified form.

[1640] Program processing

[1641] The server receives photos uploaded by users. Once the photos are sent, a generative AI model on the server converts them into a specific format according to the specified prompt. The converted images are stored on the server, and a generated access URL is provided to the user.

[1642] Specific examples of processing

[1643] A user accesses the Style Change Photo Maker app on their smartphone, uploads a photo of their face, and specifies transformation options such as "Halloween style." The following prompt is then passed to the generative AI model:

[1644] "Give me this photo and transform it into a Halloween style."

[1645] The generative AI model follows the prompt, detects the facial area, applies Halloween-themed makeup and backgrounds, and saves the converted photo on a server, generating an access URL for it. This URL is then sent to the user as a response.

[1646] Client-side programs

[1647] Hardware and Software

[1648] Smartphone: Provides a client-side user interface. Applications are developed using JavaScript (React Native).

[1649] Program processing

[1650] Users upload photos and select conversion options through the smartphone app. Once the selection is complete, the form data is sent to the server. The server returns an access URL for the converted image, which the app displays, allowing users to view and share the converted photo.

[1651] Specific examples of processing

[1652] The user clicks the "Select photo" button, selects their own photo, and then selects "Anime character" from the "Transformation type" drop-down menu. Then, by clicking the "Transform Photo" button, the selected photo and the option to transform it into an "Anime character" are sent to the server. The generative AI model follows the prompt:

[1653] "Give me this photo and turn it into an anime character."

[1654] The generative AI model converts the photo into an anime character-like image, saves it, and sends the user an access URL. The app receives this URL and displays the converted photo to the user, allowing the user to freely share the photo.

[1655] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1656] Step 1:

[1657] Application launch and user photo selection

[1658] The user launches the "Style Change Photo Maker" app on their smartphone. The user clicks the "Select photo" button in the app and selects a photo from their gallery. The selected photo is then imported into the app.

[1659] Input: A photo file selected by the user

[1660] Output: The selected photo is saved in the app's memory.

[1661] Step 2:

[1662] Selecting conversion options

[1663] The user selects any transformation option (e.g., "Halloween" or "Anime Character") from the "Transformation type" drop-down menu.

[1664] Input: User selected conversion options

[1665] Output: Specific conversion options are stored in memory

[1666] Step 3:

[1667] Submitting form data

[1668] When the user clicks the "Transform Photo" button, the selected photo file and conversion options are packaged in a FormData object and sent to the server as a POST request.

[1669] Input: Photo files and conversion options

[1670] Output: Packaged into a FormData object and sent to the server

[1671] Step 4:

[1672] Receiving photos

[1673] The server receives the HTTP POST request from the user, parses the photo file and conversion options, and temporarily stores the received photo on the server.

[1674] Input: HTTP POST request sent by the user

[1675] Output: Photo files and conversion options are saved to the server.

[1676] Step 5:

[1677] Photo analysis and transformation with generative AI models

[1678] The server launches a generative AI model based on the received photo file and conversion options. It generates a prompt (e.g., "Give me this photo, please convert it into a Halloween style.") and inputs it into the generative AI model. The generative AI model then converts the photo into the specified format based on the prompt.

[1679] Input: saved photo file, conversion options, generated prompt text

[1680] Output: Image data transformed by the generative AI model

[1681] Step 6:

[1682] Saving the converted image

[1683] The converted image data is saved in a specified folder on the server.

[1684] Input: Image data transformed by the generative AI model

[1685] Output: Converted image files saved on the server

[1686] Step 7:

[1687] Generating an access URL

[1688] An access URL for the saved converted image file will be generated.

[1689] Input: The destination location for the converted image file

[1690] Output: Generated access URL

[1691] Step 8:

[1692] Sending a response

[1693] The generated access URL is sent from the server to the user as an HTTP response.

[1694] Input: Generated access URL

[1695] Output: The HTTP response sent to the user

[1696] Step 9:

[1697] Viewing the converted image

[1698] The user receives the access URL sent from the server within the app, and the converted image is displayed in the app via this URL. The user can view, save, and share this image.

[1699] Input: Received access URL

[1700] Output: The converted image is displayed in the user's app.

[1701] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1702] The system of the present invention provides an automated process for users to upload and transform their own photos. In particular, by combining an emotion engine that recognizes the user's emotions, more personalized photo transformations can be achieved. The following is a specific embodiment of the system.

[1703] Server-side programs

[1704] Receiving photos

[1705] The server has the function of receiving the photo file uploaded by the user, along with the conversion option the user wants to convert (e.g., "cat"), and also receives emotion data to recognize the user's emotion.

[1706] Photo analysis and transformation

[1707] The received photo is analyzed by a generative AI model on the server. Based on this analysis, the photo is transformed into a specific, predefined form (e.g., "cat"). The emotion engine can also analyze the user's emotion data and automatically select appropriate transformation options. Additional effects may also be applied based on the emotion data.

[1708] Save the converted photo

[1709] The converted photos will be saved in a specified folder on the server, with a file name generated based on the original image.

[1710] Generating an access URL

[1711] An access URL for the saved converted photo is generated, which is used by the user to access the converted photo.

[1712] Sending a response

[1713] The generated access URL will be provided to the user, allowing them to view and share the converted photos.

[1714] Client-side programs

[1715] Providing a user interface

[1716] The device displays a form on a web page, allowing the user to select a photo, set conversion options, and enter emotion data, which may be automatically derived from the user's facial expressions or manually selected by the user.

[1717] Submitting form data

[1718] When the user clicks the "Transform Photo" button, the selected photo file, conversion options, and emotion data are bundled into a FormData object and sent to the server as a POST request.

[1719] Displaying the conversion results

[1720] Based on the response received from the server, the device displays the converted photo, which the user can then view and share via social media or messaging.

[1721] Example of operation

[1722] When a user accesses the AI ​​photo transformation app using a web browser, a form is displayed. The user clicks the "Select photo" button and selects a photo of their face. Next, the user selects "cat" from the "Transformation type" drop-down menu and enters emotion data. Emotion data indicates states such as "happy" or "sad."

[1723] When the user clicks the "Transform Photo" button, the device sends the selected photo, transformation options, and emotion data to the server.

[1724] The server saves the received photos in a designated folder and inputs them into the generative AI model, which then converts the face photo into a cat-like form based on the photo. Furthermore, the emotion engine analyzes the user's emotional data and adds a bright and cheerful effect to the photo based on the "happy" emotion, for example.

[1725] The converted photo is saved and a URL to access the photo is generated. This URL is returned to the user as a response. The device receives this URL and displays the photo to the user. This allows the user to view an image in which their face has been converted into a cat, and enjoy the effects applied to the image.

[1726] The processing flow will be explained below.

[1727] Step 1:

[1728] User

[1729] Open your web browser and access the AI ​​Photo Converter app.

[1730] Click the "Select photo" button and select a photo of your face from your local files.

[1731] From the "Transformation type" drop-down menu, select a transformation option (e.g., "Cat").

[1732] From the "Emotion" drop-down menu, select your emotion (e.g., "fun").

[1733] Step 2:

[1734] Terminal

[1735] The user clicks the "Transform Photo" button.

[1736] The submit event is triggered and the selected photo, conversion options, and emotion data are bundled into a FormData object.

[1737] A POST request is made to the server using the FormData object.

[1738] URL: / upload_photo

[1739] Method: POST

[1740] Body: FormData(photo, conversion options, emotion data)

[1741] Step 3:

[1742] server

[1743] The server receives a POST request at the / upload_photo endpoint.

[1744] Get the photo file, conversion options, and emotion data from the request.

[1745] Save the photo files to the specified temporary folder . / uploads / .

[1746] Filename: Use the filename of the uploaded photo (e.g. photo.jpg).

[1747] Step 4:

[1748] server

[1749] The path to the saved photo file and conversion options are used to instruct the generative AI model on the conversion process.

[1750] Model: A pre-trained generative AI model.

[1751] Input: The path to the saved photo file (e.g. . / uploads / photo.jpg).

[1752] Conversion option: The option selected by the user (e.g., "cat").

[1753] Step 5:

[1754] server

[1755] The emotion engine analyzes the user's emotion data and determines the appropriate conversion option settings and additional effects.

[1756] Example: If the user's emotion is "happy", add a bright color effect to the photo.

[1757] Step 6:

[1758] server

[1759] A generative AI model processes the photo to transform it into a specific form.

[1760] Example: Converting a face photo into a cat form.

[1761] The emotion engine applies the determined effect to the transformed photo.

[1762] Example: Adding bright color effects.

[1763] Step 7:

[1764] server

[1765] The converted photos will be saved in the specified folder . / transformed / .

[1766] Filename: transformed_<original filename> (e.g., transformed_photo.jpg).

[1767] Step 8:

[1768] server

[1769] Generate a URL to access the converted photo.

[1770] Example: http: / / example.com / transformed / transformed_photo.jpg.

[1771] The generated URL is returned to the user as a response.

[1772] Step 9:

[1773] Terminal

[1774] Process the response received from the server.

[1775] Extract the URL of the converted photo from the response.

[1776] Step 10:

[1777] Terminal

[1778] Web page Update the tag's src attribute to the extracted URL.

[1779] The converted photo is displayed to the user.

[1780] After completing the above steps, users can view and share their photos after they have been converted based on the selected conversion options and emotion data.

[1781] Example 2

[1782] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1783] Conventional image conversion systems simply convert images provided by users into another format, but lack the ability to personalize the service by taking into account the user's emotions. Furthermore, they do not consider adding effects based on the user's emotions to the converted image. As a result, the quality of the user experience is not sufficiently improved, making it difficult to provide personalized services.

[1784] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for a user to upload an input image, means for receiving the input image, conversion options, and emotion data, means for performing analysis using a generative AI model, means for analyzing the emotion data using an emotion engine and adding appropriate effects, means for saving the converted image, means for generating an access URL for the saved converted image, means for providing the access URL to the user, and means for displaying the converted image to the user. This enables personalized image conversion that takes into account the user's emotions and the addition of effects according to the emotions.

[1785] A "user" is an individual or entity that utilizes the system to upload input images and provide transformation options and emotion data.

[1786] An "input image" is the original photograph or image data that a user uploads to the system.

[1787] The "conversion option" is an item that indicates the type of conversion selected by the user, such as conversion into a specific form such as a person, character, or animal.

[1788] "Emotion data" is data that represents the user's emotion, and is information that indicates an emotional state such as "happy" or "sad," for example.

[1789] A "generative AI model" is an artificial intelligence algorithm or program that analyzes an input image and transforms it into a specific, specified form.

[1790] An "emotion engine" is a program or algorithm that has the ability to analyze emotional data and add appropriate effects to images based on the results.

[1791] An "effect" is a visual modification or enhancement that is added to a transformed image based on emotional data.

[1792] A "server" is a computer system that receives, analyzes, converts, and stores data sent by users, and provides the results of the conversion.

[1793] "Access URL" is the web address for accessing the saved converted image.

[1794] A "terminal" is a device such as a computer, smartphone, or tablet that a user uses to access the system.

[1795] "Saving" means storing the converted image data as a file in a specified location.

[1796] "Display" means showing the converted image to the user on the screen of the terminal.

[1797] The system of the present invention automates a series of processes in which users upload their own photos, convert them into a specified format, and add effects based on emotional data.

[1798] The system consists of a server and a terminal, where the server is responsible for the main data processing and analysis, and the terminal provides the user interface.

[1799] Server-side features

[1800] The server provides the following functionality:

[1801] 1. Receiving photos:

[1802] The server receives the photo uploaded by the user, the transformation option (e.g., "cat"), and the emotion data (e.g., "fun"). The photo file is saved in the temporary folder / uploads.

[1803] 2. Photo analysis and conversion:

[1804] The server inputs the stored photo into a generative AI model and converts it into the specified form (e.g., "cat"). This generative AI model uses technologies such as "StyleGAN."

[1805] 3. Emotion data analysis and effect addition:

[1806] The server analyzes the emotion data using an emotion engine and adds appropriate effects to the converted image (e.g., a bright filter for the "happy" emotion). The emotion engine used is "EmotionAPI" or similar.

[1807] 4. Save the converted photo and generate an access URL:

[1808] The converted photos are saved in a new folder, for example, / transformed-photos. The server generates an access URL based on the file path of the saved photos.

[1809] 5. Sending the response:

[1810] The server provides the generated access URL to the user, which allows the user to access the converted photo.

[1811] Client-side features

[1812] The terminal provides the following features:

[1813] 1. Providing the user interface:

[1814] The device displays a form on a web page, allowing the user to select a photo and enter a transformation option (e.g., "cat") and emotional data (e.g., "fun"), which can be manually entered by the user or automatically obtained from facial expressions.

[1815] 2. Submitting form data:

[1816] When the user clicks the "Transform Photo" button, the device sends the selected photo file, conversion options, and emotion data to the server as a FormData object.

[1817] 3. View the conversion results:

[1818] The device displays the converted photo in the browser based on the access URL received from the server. The user can then check the converted photo and share it via social media or messaging apps.

[1819] Specific examples

[1820] A user accesses the AI ​​photo transformation app using a browser, selects their own photo from the "Select photo" button in the form, selects "Cat" in the "Transformation type" and "Fun" in the "Emotion" drop-down menu, and clicks the "Transform Photo" button, sending the selected photo file, transformation options, and emotion data to the server.

[1821] The server inputs the received photo file into the generative AI model and converts it into a cat's form. The emotion engine then adds a bright effect to the photo based on the "happy" emotion. The converted image is saved and a URL is generated. This URL is provided to the user, who can then view the converted photo on their device.

[1822] Prompt Sentence Examples

[1823] Here are some examples of specific prompts:

[1824] "Create a program that lets users take selfies with happy emotions and transform them into a cat style photo. Add a brightening effect to the resulting photo."

[1825] As described above, by using this system, users can convert their own facial photos into the form of cats that reflect happy emotions.

[1826] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1827] Step 1:

[1828] A user visits a web page and sees a form with a "Select photo" button, a "Transformation type" drop-down menu, and an "Emotion" drop-down menu. The user uploads their photo, chooses a transformation option (e.g., "cat"), and enters emotion data (e.g., "fun"). The inputs for this operation are the photo file, the transformation option, and the emotion data.

[1829] Step 2:

[1830] When the user clicks the "Transform Photo" button, the device sends the selected photo file, conversion options, and emotion data as a FormData object to the server. The input is the aforementioned FormData object, and the output is an HTTP POST request.

[1831] Step 3:

[1832] The server receives an HTTP POST request and parses the photo file, conversion options, and emotion data. The photo file is saved in the temporary folder / uploads, and the conversion options and emotion data are stored in memory variables. The input is the HTTP POST request, and the output is the saved image file and memory variables.

[1833] Step 4:

[1834] The server inputs the saved photo file into a generative AI model and converts it into the specified form (e.g., "cat"). The generative AI model used is, for example, "StyleGAN." The input is the photo file and conversion options, and the output is the converted image data.

[1835] Step 5:

[1836] The server uses an emotion engine to analyze the emotion data and add appropriate effects to the converted image (e.g., a bright filter for the "happy" emotion). The emotion engine uses "EmotionAPI" or similar. The input is the converted image data and emotion data, and the output is the converted image with the added effect.

[1837] Step 6:

[1838] The server saves the converted image, for example, in the / transformed-photos folder. The server generates an access URL based on the path of this saved file. The input is the converted image with the effect added, and the output is the saved image file and the access URL.

[1839] Step 7:

[1840] The server sends the generated access URL to the user as an HTTP response. The response body contains data in JSON format such as { "url": "www.example.com / transformed / photos / 123.jpg"}. The input is the generated access URL, and the output is the HTTP response.

[1841] Step 8:

[1842] The device analyzes the access URL received from the server and displays the converted image on the browser. The user can then check the converted image and share it via social media or messaging apps. The input is the access URL received as an HTTP response, and the output is the displayed converted image.

[1843] (Application example 2)

[1844] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1845] While conventional photo conversion systems can convert photos uploaded by users into individual formats, they have the problem of not applying personalized effects that take the user's emotions into account. Furthermore, while there is a demand in the advertising field for a system that can automatically generate advertising photos that reflect the user's emotions, no such system exists. The present invention aims to solve these problems by providing a system that enables the automatic generation of personalized advertising photos by applying effects based on the user's emotional data.

[1846] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1847] In this invention, the server includes means for receiving an input image, means for analyzing the input image, means for converting the input image into a specific set form, means for acquiring emotion data from the input image, means for applying an additional effect to the converted image based on the emotion data, means for saving the converted image, means for generating an access URL for the saved converted image, and means for providing the access URL to the user. This enables automatic generation of advertising photos that take user emotions into consideration.

[1848] "Input image" refers to a photograph or image uploaded by a user.

[1849] "Means for performing analysis" refers to the technical means for analyzing the input image and understanding its content and characteristics.

[1850] "Specific form" refers to the specific transformation form set by the generative AI model, including, for example, transformation into animals or products.

[1851] "Emotion data" refers to data generated based on the user's facial expressions and input emotion information.

[1852] "Additional effects" refer to visual effects that are further applied to an image that has been transformed based on emotion data.

[1853] "Storing means" refers to the technical means of recording the converted images in designated storage on a server.

[1854] "Access URL" refers to the web address where users can access the converted image.

[1855] A "generative AI model" refers to an artificial intelligence model that generates new images based on input images.

[1856] System Configuration

[1857] The system of the present invention automates the process of users uploading photos, converting the photos into specific forms, and applying effects based on the user's emotional data. The system is composed of a server and a user terminal.

[1858] Hardware and Software

[1859] Hardware: Smartphones, servers

[1860] Software: Cloud services used for servers (e.g., AWS), generative AI models (e.g., GAN), sentiment analysis engines (e.g., Microsoft Azure's Face API), and web front-end technologies (HTML, CSS, JavaScript).

[1861] Server-side processing

[1862] 1. Receiving photos

[1863] The server receives the photos uploaded by the user, as well as the transformation options (e.g., animals, products) selected by the user and the acquired emotion data.

[1864] 2. Acquiring Emotion Data

[1865] The server generates emotion data based on the user's facial expression data and input emotion information, using an emotion analysis engine for this process.

[1866] 3. Photo conversion

[1867] The server inputs the received photo into a generative AI model and converts it into an image of a specific set form (e.g., a cat, a product for advertising).

[1868] 4. Applying Effects

[1869] Apply an additional effect to the converted image based on the emotion data, which gives different visual effects depending on the emotion data (e.g., happiness).

[1870] 5. Save the converted image

[1871] The converted image is saved on the server and a URL for the saved image is generated.

[1872] 6. Providing an access URL

[1873] The generated URL is provided to the user, who can then access the converted image.

[1874] Processing on the user terminal side

[1875] 1. Upload a photo

[1876] Users launch the application on their smartphone, upload a photo, and select the product category (e.g., cosmetics) for the advertisement.

[1877] 2. Acquiring Emotion Data

[1878] The user device uses a camera function to capture the user's facial expressions and obtain emotional data in real time, which is also sent to the server.

[1879] 3. Displaying the conversion results

[1880] The user's device receives the access URL provided by the server and displays the converted image. The user can check the results and share them if necessary.

[1881] Specific examples

[1882] For example, suppose User A uses the application to upload a photo of themselves and selects the cosmetics category. Because User A is smiling, the sentiment analysis engine recognizes this as "happiness." The photo, transformation options, and the "happiness" emotion data are sent to the server. The server then transforms the photo using a generative AI model to regenerate it into an image suitable for advertising. It also applies a bright, energetic effect based on "happiness." The resulting URL is provided to the user, who can view it on their smartphone.

[1883] Prompt Sentence Examples

[1884] Examples of prompts used by generative AI models include:

[1885] "Upload user photos and transform them into ad designs for the cosmetics category. The user emotion is happiness, so add a bright effect to reflect that."

[1886] In this way, the system realizes the automatic generation of personalized advertising photos that take into account the user's emotions.

[1887] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1888] Step 1: Upload a photo

[1889] A user launches the app on their smartphone, selects and uploads their own photo, and also inputs the product category (e.g., cosmetics) to be advertised. The uploaded photo and the selected category are then sent to the server.

[1890] Input: User photo, Product category

[1891] Output: Sending photo data and category data to the server

[1892] Step 2: Obtaining emotion data

[1893] The user device uses the smartphone's camera to capture the user's facial expressions in real time, and an emotion analysis engine (e.g., Microsoft Azure's Face API) is used to analyze the facial expressions and generate emotion data, which is also sent to the server.

[1894] Input: Real-time facial expression data of the user

[1895] Output: Generate emotion data and send it to the server

[1896] Step 3: Receiving photos

[1897] The server receives the photo data, product category, and emotion data sent from the user terminal.

[1898] Input: Photo data, category data, emotion data

[1899] Output: Saving and preparing data on the server

[1900] Step 4: Analyze and convert photos

[1901] The server inputs the received photo data into a generative AI model (e.g., GAN) and converts it into an image of a specific set form (e.g., a cat, a product for advertising). The generative AI model converts the photo based on the prompt text.

[1902] Input: Photo data, generative AI model, prompt

[1903] Output: Transformed image data

[1904] Step 5: Apply effects

[1905] The server applies additional effects to the transformed image based on the emotion data, for example, if the emotion is "happy," it applies a bright effect. This process is performed using an emotion engine.

[1906] Input: Converted image data, emotion data

[1907] Output: Final image data with effects applied

[1908] Step 6: Save the converted image

[1909] The server saves the final image data with the effect applied to the specified folder and generates an access URL for the save destination.

[1910] Input: Image data with effects applied

[1911] Output: Saved image data, generated access URL

[1912] Step 7: Provide an access URL

[1913] The server returns the generated access URL to the user's device as a response. The user's device receives this URL and displays the converted image.

[1914] Input: Access URL

[1915] Output: Receives the access URL and displays the image on the user's device

[1916] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1917] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1918] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1919] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1920] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1921] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1922] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1923] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1924] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1925] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1926] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1927] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1928] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1929] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1930] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1931] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1932] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1933] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1934] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1935] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1936] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1937] The following is further disclosed regarding the above embodiment.

[1938] (Claim 1)

[1939] means for receiving an input image;

[1940] means for performing analysis on the input image;

[1941] means for converting the input image into a specific predetermined form based on the analysis;

[1942] means for storing the transformed image;

[1943] means for generating an access URL for the stored converted image;

[1944] means for providing the access URL to a user;

[1945] A system including:

[1946] (Claim 2)

[1947] 10. The system of claim 1, further comprising means for specifying a conversion option.

[1948] (Claim 3)

[1949] 3. The system of claim 2, wherein the conversion options include at least one of celebrities, characters, and animals.

[1950] "Example 1"

[1951] (Claim 1)

[1952] means for receiving an input image;

[1953] means for analyzing the input image using a generative AI model;

[1954] means for converting the input image into a specific predetermined form based on the analysis;

[1955] means for storing the transformed image;

[1956] means for generating an access URL for the stored converted image;

[1957] means for providing the access URL to a user;

[1958] A system including:

[1959] (Claim 2)

[1960] 10. The system of claim 1, further comprising means for specifying conversion options through a user interface.

[1961] (Claim 3)

[1962] 3. The system of claim 2, wherein the conversion options include at least one of a human, a non-human character, and an animal.

[1963] "Application Example 1"

[1964] (Claim 1)

[1965] means for receiving an input image;

[1966] means for performing analysis on the input image;

[1967] means for converting the input image into a specific predetermined form based on the analysis;

[1968] means for storing the transformed image;

[1969] means for generating an access URL for the stored converted image;

[1970] means for providing the access URL to a user;

[1971] a means for converting the text using a generative AI model based on a specific prompt;

[1972] means for displaying the transformed image on a user interface;

[1973] A system including:

[1974] (Claim 2)

[1975] 10. The system of claim 1, further comprising means for specifying a conversion option.

[1976] (Claim 3)

[1977] 3. The system of claim 2, wherein the conversion options include at least one of celebrities, characters, and animals.

[1978] (Claim 4)

[1979] The system of claim 1, further comprising means for performing processing based on a specific prompt sentence for transformation by the generative AI model.

[1980] "Example 2: Combining Emotion Engines"

[1981] (Claim 1)

[1982] a means for a user to upload an input image;

[1983] means for receiving an input image, transformation options, and emotion data;

[1984] means for analyzing the input image using a generative AI model;

[1985] means for converting the input image into a specific predetermined form based on the analysis;

[1986] A means to analyze emotional data using an emotion engine and add appropriate effects;

[1987] means for storing the transformed image;

[1988] means for generating an access URL for the stored converted image;

[1989] means for providing the access URL to a user;

[1990] means for displaying the converted image to a user;

[1991] A system including:

[1992] (Claim 2)

[1993] 10. The system of claim 1, further comprising means for specifying the conversion options.

[1994] (Claim 3)

[1995] The system according to claim 1, wherein the conversion options include at least one of a person, a character, and an animal.

[1996] "Application example 2 when combining emotion engines"

[1997] (Claim 1)

[1998] means for receiving an input image;

[1999] means for performing analysis on the input image;

[2000] means for converting the input image into a specific predetermined form based on the analysis;

[2001] means for acquiring emotion data from the input image;

[2002] means for applying an additional effect to the transformed image based on the emotion data;

[2003] means for storing the transformed image;

[2004] means for generating an access URL for the stored converted image;

[2005] means for providing the access URL to a user;

[2006] A system including:

[2007] (Claim 2)

[2008] 10. The system of claim 1, further comprising means for specifying a conversion option.

[2009] (Claim 3)

[2010] 10. The system of claim 1, wherein the conversion options include at least one of a celebrity, a character, an animal, and a product. [Explanation of symbols]

[2011] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving an input image; means for performing analysis on the input image; means for converting the input image into a specific predetermined form based on the analysis; means for storing the transformed image; means for generating an access URL for the stored converted image; means for providing the access URL to a user; A system including:

2. 10. The system of claim 1, further comprising means for specifying conversion options.

3. 3. The system of claim 2, wherein the conversion options include at least one of celebrities, characters, and animals.

Images