System

Abstract

A system is provided.SOLUTION: Means for a user to select an image file from a terminal, means for the terminal to transmit the selected image file to a server, means for the server to receive the transmitted image file, means for the server to provide the received image file to a generation AI model and apply a customization element to generate an original stamp, means for the server to transmit the generated original stamp to the terminal, means for the terminal to display the transmitted original stamp to a user and receive a correction request, means for the server to transmit the correction request to the generation AI model again, A system, comprising: means for generating a modified original sticker; means for saving, by a server, a finally generated original sticker in an account of a user; and means for displaying, by a terminal, the finally saved original sticker for the user to use in a communication platform.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] The traditional method of creating stamps required users to individually edit images and create stamps using separate software, which was time-consuming and labor-intensive. Furthermore, the number of stamps available was limited, making it difficult to customize to meet individual user needs. Another problem is that the number of situations in which stamps are used is decreasing, reducing the platform's appeal as a communication tool. [Means for solving the problem]

[0005] This invention provides a means for a user to select an image file from a device and send the selected image file to a server. The server analyzes the received image file and uses a generative AI model to generate an original stamp with customized elements applied. The generated original stamp is sent to the device, where the user can review it and make correction requests. The server then sends the correction request back to the generative AI model, generating a modified original stamp and saving it in the user's account. This allows users to quickly and easily create original stamps tailored to their individual needs and use them within the communication platform. This solves the existing problems, increases the number of situations in which stamps can be used, and improves the platform's appeal.

[0006] A "terminal" is a device operated by a user, including smartphones, tablets, and personal computers.

[0007] A "server" refers to a computer system that has the function of receiving data sent from a terminal via a network, processing it, and returning a response.

[0008] An "image file" refers to a file saved in a visual data format such as a photograph or illustration.

[0009] "Generative AI models" refer to algorithms or programs that use artificial intelligence technology to process and customize images.

[0010] "Customization Elements" refers to modifications or changes applied to an image file, such as changing the background or adding a message, or other specific elements requested by a user.

[0011] "Stamps" refer to small images or icons used within messaging apps and communication platforms.

[0012] "Original stamp" refers to a stamp with a unique design that is generated based on image files and customization elements provided by the user.

[0013] A "request for correction" refers to a request from a user to reprocess or change a generated stamp.

[0014] A "communication platform" refers to an online service that enables users to send and receive messages and share content. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] This invention is a system that allows users to select image files from their devices and generate original LINE stamps using a generative AI model. Specific embodiments of the invention are described in detail below.

[0037] System configuration

[0038] The system mainly consists of the following components:

[0039] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[0040] 2. Server - Receives data sent from the device via the network and processes the images using generative AI models.

[0041] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[0042] Processing flow

[0043] The following shows the process from when the user selects an image file to when an original stamp is generated.

[0044] 1. User selects an image file

[0045] The user opens the device's gallery and selects the image they want to use as an original stamp.

[0046] 2. The device sends the image file to the server

[0047] The terminal transmits the selected image file to the server.

[0048] The transmitted image file is temporarily stored in the device's storage and then uploaded to the server via an HTTP request.

[0049] 3. The server receives and analyzes the image file.

[0050] The server receives the image file and temporarily stores it in storage.

[0051] The server calls the generated AI model and begins image analysis.

[0052] 4. Generative AI model generates stamps

[0053] The generative AI model analyzes the characteristics of the image file and applies the customization elements you set (changing the background, adding a message, etc.) to generate an original stamp.

[0054] The generated stamp image is returned to the server.

[0055] 5. The server sends the generated stamp to the device.

[0056] The server transmits the generated original stamp to the terminal.

[0057] The device receives the stamp image and displays it to the user.

[0058] 6. The user checks the stamp and requests corrections

[0059] The user checks the generated stamp image and specifies correction requests as necessary.

[0060] The revision requests include specific changes to the message or background.

[0061] 7. The server generates the stamp again

[0062] The server sends the correction request again to the generation AI model, which generates the corrected stamp.

[0063] 8. The server saves the final stamp and notifies the device.

[0064] The server then stores the final generated stamp in the user's account.

[0065] A notification will be sent to the device when the save is complete, making the stamp immediately available to the user as a LINE stamp.

[0066] Specific examples

[0067] For example, let's say a user creates an original LINE stamp using a photo of their beloved dog.

[0068] 1. User selects a photo

[0069] Select a photo of your dog from your smartphone gallery.

[0070] 2. The device sends the photo

[0071] The selected photo is sent to the server.

[0072] 3. The server receives the photo and analyzes it with the generative AI model

[0073] The server receives the photo and provides it to the generative AI model to begin analysis.

[0074] 4. Generative AI model generates stamps

[0075] After analyzing the photo, a stamp was generated with the background changed to a park and the message "Let's go for a walk" added.

[0076] 5. The server sends the stamp to the device.

[0077] The generated stamp is sent to the terminal and displayed to the user.

[0078] 6. The user checks the stamp and requests corrections

[0079] The user requests that the message be changed to "Let's play!"

[0080] 7. The server generates the stamp again

[0081] The server then has the AI ​​model generate stamps again based on the correction request.

[0082] 8. The server saves the final stamp and notifies the device.

[0083] The modified stamps will be saved to the user's LINE account and made available for use.

[0084] In this way, users can quickly create original LINE stamps using images stored on their smartphones and use them instantly, significantly reducing the time and effort required for creating stamps and increasing the number of ways stamps can be used.

[0085] The processing flow will be explained below.

[0086] Step 1:

[0087] The user opens the device's gallery.

[0088] The user selects the image file they want to use as an original stamp.

[0089] The device temporarily saves the selected image file.

[0090] Step 2:

[0091] The terminal creates a request to notify the server that the image file selection has been completed.

[0092] The terminal sends the selected image file to the server in the form of an HTTP request.

[0093] Verify that the server received the request.

[0094] Step 3:

[0095] The server temporarily stores the received image file in storage.

[0096] Set the parameters for the server to call the API for the generated AI model.

[0097] Step 4:

[0098] The server sends the image file as input data to the generative AI model.

[0099] A generative AI model analyzes image files and extracts features.

[0100] Step 5:

[0101] The generative AI model applies the specified customization elements (changing the background, adding a message, etc.) to generate original stamps.

[0102] The stamp image generated by the generative AI model is returned to the server.

[0103] Step 6:

[0104] The server receives the returned stamp image and temporarily stores it.

[0105] The server creates a request to send the generated original stamp to the terminal.

[0106] Step 7:

[0107] The terminal displays the stamp image received from the server to the user.

[0108] The user reviews the stamp and requests corrections if necessary.

[0109] Step 8:

[0110] The device receives the user's modification request and creates a request to send to the server.

[0111] The terminal sends a modification request to the server.

[0112] Step 9:

[0113] The server receives the correction request and sets the parameters to call the API for the generated AI model again.

[0114] Based on the modification request, the server sends the image file and customization elements to the generative AI model.

[0115] Step 10:

[0116] The generative AI model recreates the original stamp reflecting the requested modifications.

[0117] The generative AI model returns the corrected stamp image to the server.

[0118] Step 11:

[0119] The server receives the corrected stamp image and temporarily stores it again.

[0120] The server initiates the process to store the final generated original stamp in the user's account.

[0121] Step 12:

[0122] The server creates a request to notify the terminal that the stamp saving process has been completed.

[0123] The device receives a notification from the server and displays to the user that the final stamp has been saved.

[0124] Step 13:

[0125] The user opens the LINE app on their device and confirms that the generated original stamps are available.

[0126] The user sends an original stamp in a LINE chat and checks that it displays as intended.

[0127] The above are the specific processing steps for a user to select an image file, generate, modify, save, and finally use an original LINE stamp using the generative AI model.

[0128] Example 1

[0129] 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."

[0130] Conventional stamp generation systems require users to manually design stamps, which is time-consuming and labor-intensive. Furthermore, the quality of the generated stamps is inconsistent, and any corrections required can require additional work. Furthermore, applying user-specified customization elements is difficult, resulting in a lack of flexibility.

[0131] 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.

[0132] In this invention, the server includes: means for a user to select an image file from the device; means for the device to transmit the selected image file to a network server; means for the network server to receive the transmitted image file; means for the network server to provide the received image file to an image generation model and apply customization elements to generate an original stamp; means for the network server to transmit the generated original stamp to the device; means for the device to display the transmitted original stamp to the user and accept a modification request; means for the network server to transmit the modification request again to the image generation model and generate a modified original stamp; means for the network server to save the finally generated original stamp in the user's account; and means for the device to display the finally saved original stamp and make it available to the user within the communication platform. This enables users to easily generate and customize high-quality original stamps.

[0133] "User" refers to the entity that uses the system, an individual or organization that selects image files and gives instructions for customization.

[0134] "Device" refers to equipment operated by a user, such as a smartphone, tablet, or computer.

[0135] "Network Server" refers to a centralized management system for receiving and processing data sent from devices.

[0136] "Image File" refers to digital image data selected by a User and provided to the System.

[0137] "Image generation model" refers to algorithms and programs for generating new images based on input images.

[0138] "Customization Elements" refers to modifications or additions (e.g., changing the background, adding text) that are applied to the generated image based on the user's specifications.

[0139] "Custom Stamp" refers to a unique image generated based on the image and customization elements provided by the user.

[0140] "Communication platform" refers to a place where users can exchange messages with other users using original stamps they have created, and generally refers to a messaging application.

[0141] A "modification request" refers to an instruction from a user requesting changes or additions to an already generated original stamp.

[0142] "Account" means the ID and related information that enables a User to access the System and manage their personal data and settings.

[0143] The system of this invention allows users to select an image file from their device and then executes a series of processes to generate original stamps using a generative AI model. The elements of the system are as follows:

[0144] Hardware and Software

[0145] The system mainly consists of the following hardware and software:

[0146] 1. Device:

[0147] Smartphones, tablets, computers, etc. operated by users.

[0148] It has the function of sending image files to a network server.

[0149] 2. Network Server:

[0150] It receives and processes data sent from the device and sends the generated stamp back to the device.

[0151] It uses a generative AI model to analyze images and generate stamps.

[0152] 3. Generative AI Model:

[0153] Algorithms and programs for image generation, such as OpenAI's DALL-E and Stable Diffusion.

[0154] Operation of each element

[0155] This section explains how each element operates and what data processing and calculations are performed.

[0156] device

[0157] The user selects an image file using the device. The selected image file is sent to the network server using an HTTP request. The device has a storage device that temporarily stores data, and the data is temporarily saved before being sent.

[0158] Network Server

[0159] The network server receives the image file sent from the device and temporarily stores it in storage. It then calls the generative AI model to analyze the image. The analyzed data is used to generate a stamp by applying customization elements (changing the background, adding a message, etc.). The generated stamp image is then sent back to the device. If the user makes a modification request, the network server sends this modification request again to the generative AI model, which then generates a new stamp.

[0160] Specific examples

[0161] For example, below is a scenario in which a user creates original LINE stamps using a photo of their beloved dog.

[0162] 1. User selects a photo:

[0163] The user opens the gallery on their smartphone and selects a photo of their dog.

[0164] 2. The device sends the photo:

[0165] The user selects a photo of their dog and sends it to the server using an HTTP POST request.

[0166] 3. The network server analyzes the photo using the generated AI model:

[0167] The photos received by the server are temporarily saved in the " / tmp" directory, and a generative AI model (e.g., DALL-E) is called to analyze them.

[0168] 4. Generative AI model generates stamps:

[0169] For the analyzed photo, a stamp is generated by changing the background to a park and adding the message "Let's go for a walk."

[0170] 5. The network server sends the generated stamp to the device:

[0171] The generated stamp image is sent back to the device as an HTTP response.

[0172] 6. User checks stamp and requests correction:

[0173] The user checks the generated stamp and operates the device to request that the message be changed to "Let's play!"

[0174] 7. The network server generates the stamp again:

[0175] The server sends the correction request again to the image generation model to generate the corrected stamp.

[0176] Prompt Sentence Examples

[0177] Here are some examples of prompts based on user input:

[0178] Photo Analysis: Photos of your beloved dog

[0179] Change background: Park

[0180] Added message: "Let's go for a walk?"

[0181] By passing this prompt text to a generative AI model, an original stamp is generated based on the specified elements.

[0182] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0183] Step 1:

[0184] The user opens the device's gallery and selects the image file they want to use as an original stamp. When the user taps on the image in the smartphone's photo app to select it, the selected image file is saved in temporary storage on the device.

[0185] Input: An image file selected by the user from the gallery

[0186] Output: Image file saved to temporary storage on device

[0187] Step 2:

[0188] The device sends the selected image file to the network server using an HTTP POST request. The device uploads the selected image file to the server.

[0189] Input: Image file saved on device

[0190] Output: Image file sent to network server

[0191] Step 3:

[0192] The server receives the image file and temporarily stores it in storage. The server receives the HTTP request and stores the received image file in the " / tmp" directory.

[0193] Input: Image file sent from device to server

[0194] Output: Image file saved in temporary storage on the server

[0195] Step 4:

[0196] The server invokes the generative AI model and begins analyzing the received image file. The server uses a Python script to pass the image file to the generative AI model (e.g., DALL-E) for analysis.

[0197] Input: Image file saved in the " / tmp" directory

[0198] Output: Analysis results returned from the generative AI model

[0199] Step 5:

[0200] The generative AI model analyzes the characteristics of the image file and applies customization elements to generate original stamps. The generative AI model generates stamp images based on prompts such as "change the background to a park" and "add the text 'Let's go for a walk.'"

[0201] Input: Image file to be analyzed and prompt text containing customization elements

[0202] Output: Stamp image generated by the generative AI model

[0203] Step 6:

[0204] The server sends the generated original stamp to the device. The server returns the generated stamp image as an HTTP response, which is received by the device.

[0205] Input: Stamp image received from the generative AI model

[0206] Output: Stamp image sent to device

[0207] Step 7:

[0208] The user checks the generated original stamp and requests a correction. The user operates the device to request a correction to the stamp content (for example, to change the text to "Let's play!").

[0209] Input: Stamp image displayed on device

[0210] Output: Correction request entered by the user

[0211] Step 8:

[0212] The server sends the correction request to the image generation model again, and generates the corrected original stamp. Based on the correction request, the server passes the necessary parameters to the generation AI model again, and generates the corrected stamp.

[0213] Input: Correction request submitted by the user

[0214] Output: Stamp image generated after correction by the generative AI model

[0215] Step 9:

[0216] The server saves the final generated original stamp to the user's account. The server saves the modified stamp image to the database and assigns it to the user's account.

[0217] Input: Modified stamp image

[0218] Output: Final stamp image saved in the user's account

[0219] Step 10:

[0220] The device will then display the original stamps and make them available to the user within their communication platform. The device will then receive the final stamps and import them into messaging apps such as LINE, making them available for use.

[0221] Input: The final stamp image saved in the user's account

[0222] Output: Stamp image available within the communication platform

[0223] (Application example 1)

[0224] 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."

[0225] Conventional stamp generation systems allow users to easily create custom designs using their image files, but lack the functionality to apply the created designs to products and order them through e-commerce sites, making it difficult to quickly provide products with original designs.

[0226] 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.

[0227] In this invention, the server includes means for providing the received image file to a generative AI model and applying customization elements to generate an original design, means for sending the generated original design to the terminal, means for sending a modification request to the generative AI model again to generate a modified original design, and means for saving the final generated original design to the user's account and applying it to a product, thereby enabling users to easily generate custom designs using their own image files and order products based on those designs.

[0228] "User" means a person who uses the System to select image files, generate customized designs, and order products.

[0229] "Terminal" refers to a device operated by a user, such as a smartphone, tablet, or PC.

[0230] An "image file" is image data such as a photograph or illustration that is selected by the user from the terminal and sent to the server.

[0231] A "server" is a computer system that receives image files sent from a terminal via a network, processes the images using a generative AI model, and provides the final generated design to the user.

[0232] A "generative AI model" is an algorithm and program that analyzes the characteristics of a received image file and applies customization elements to generate an original design.

[0233] "Customization elements" are design items, such as changing the background or adding a message, that the generative AI model applies to the image file.

[0234] An "original design" is a design image with customization elements applied, generated by a generative AI model.

[0235] A "modification request" is a request for changes made by a user to the generated original design.

[0236] "Products" are items such as t-shirts, mugs, and phone cases with custom designs applied.

[0237] "E-commerce Site" means an online platform through which users can order products using the final generated Original Design.

[0238] This invention relates to an e-commerce system that allows users to create original designs using images uploaded by users and order them as custom products. Specifically, the system is implemented as follows using a server, a terminal, and a generative AI model.

[0239] First, the user selects an image file using their device. The selected image file is sent to the server via an HTTP request. The server temporarily stores the received image file in storage and provides it to the generative AI model. The generative AI model analyzes the image file's characteristics and applies customization elements (such as changing the background or adding a message) to generate an original design. This original design is returned to the server and then sent to the device.

[0240] The device displays the received original design to the user. If the user is not satisfied with the design, the device accepts a revision request. The accepted revision request is sent again to the server, and the server communicates the revision request to the generative AI model. The generative AI model generates a new design based on the revision request, and that design is sent again to the user's device via the server.

[0241] Finally, if the user is satisfied with the design, it is saved to the user's account and the original design is applied to custom merchandise (e.g., t-shirts, mugs, phone cases, etc.). At this stage, the user can order the product through the e-commerce site.

[0242] The system uses the following hardware and software:

[0243] Hardware: User devices (smartphones, tablets, PCs, etc.), servers

[0244] Software: Generative AI models, HTTP request processing, storage systems, e-commerce sites

[0245] For example:

[0246] When a user selects a photo of their dog using their device, the photo is sent to the server. The server provides the photo to a generative AI model, which then generates an original design with a park background and the message "Pochi" added. This design is then sent to the user for confirmation. If the user requests a change to the design, such as "I want the colors to be brighter," the generative AI model generates a new design and sends it back to the user. Finally, if the user is satisfied with the design, they can order products such as T-shirts and mugs using that design.

[0247] An example of a real prompt is:

[0248] "Please create the design shown on this T-shirt using a photo of your dog. Please use a park as the background and add the dog's name, 'Pochi.'"

[0249] This allows users to easily and quickly create custom designs and order custom products based on those designs.

[0250] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0251] Step 1:

[0252] The user selects an image file from their device. The user opens the image gallery on their smartphone, tablet, or computer and selects the image file they want to use for the customized design. The input is the image file selected by the user, and the output is that the image file is saved on the device.

[0253] Step 2:

[0254] The device sends the selected image file to the server. The device uploads the selected image file to the server using an HTTP request. The input is the selected image file, and the output is the image file sent to the server.

[0255] Step 3:

[0256] The server receives the image file. The server temporarily stores the uploaded image file in its storage area. The input is the image file sent from the device, and the output is the image file stored on the server.

[0257] Step 4:

[0258] The server provides the received image file to the generative AI model, which applies customization elements to generate an original design. The generative AI model analyzes the image file and applies the specified customization elements (for example, changing the background or adding a message). The input is the saved image file and the specified customization elements, and the output is the generated original design.

[0259] Step 5:

[0260] The server sends the generated original design to the terminal. The server sends the generated original design to the user's terminal as an HTTP response. The input is the generated original design, and the output is the original design provided to the terminal.

[0261] Step 6:

[0262] The terminal displays the original design sent to the user and accepts any modification requests. The user checks the displayed original design and inputs modification requests as necessary. The input is the original design displayed to the user and the user's modification requests, and the output is the modified design request.

[0263] Step 7:

[0264] The server sends the modification request back to the generative AI model, which generates a modified original design. The generative AI model accepts the modification request and generates a new design based on the specified changes. The inputs are the modification request and the existing original design, and the output is the modified original design.

[0265] Step 8:

[0266] The server stores the final generated original design in the user's account and applies it to the product. The server associates the final original design with the user's account and stores it, then applies the design to the specified product template. The input is the modified original design and the user's account information, and the output is the customized product.

[0267] Step 9:

[0268] The terminal displays the final saved original design and allows the user to place an order within the e-commerce site. The user checks the displayed custom product and confirms the order through the e-commerce site. The input is the product with the final original design applied, and the output is the order confirmed by the user.

[0269] 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.

[0270] This invention is a system that allows a user to select an image file from a device and generates original LINE stamps using a generative AI model and an emotion engine. Specific embodiments of the invention are described in detail below.

[0271] System configuration

[0272] The system mainly consists of the following components:

[0273] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[0274] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[0275] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[0276] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[0277] Processing flow

[0278] The following shows the process from when the user selects an image file to when an original stamp is generated using the emotion engine.

[0279] 1. User selects an image file

[0280] The user opens the device's gallery and selects the image file they want to use as an original stamp.

[0281] 2. The device sends the image file to the server

[0282] The terminal transmits the selected image file to the server.

[0283] The transmitted image file is temporarily stored in the device's storage and then uploaded to the server via an HTTP request.

[0284] 3. The server receives and analyzes the image file.

[0285] The server receives the image file and temporarily stores it in storage.

[0286] Set the parameters for the server to call the API for the generated AI model.

[0287] 4. The server analyzes the user's emotions

[0288] The server calls the emotion engine and analyzes multiple input data, including the user's voice, facial expressions, and text input.

[0289] The emotion engine detects the user's emotions (e.g., joy, sadness, surprise, etc.).

[0290] 5. Generative AI model generates stamps

[0291] The generative AI model analyzes the characteristics of the image file and, based on the analysis results of the emotion engine, applies customization elements (such as changing the background or adding an appropriate message) to generate original stamps.

[0292] The generated stamp image is returned to the server.

[0293] 6. The server sends the generated stamp to the device.

[0294] The server transmits the generated original stamp to the terminal.

[0295] The device receives the stamp image and displays it to the user.

[0296] 7. The user checks the stamp and requests corrections

[0297] The user checks the generated stamp image and specifies correction requests as necessary.

[0298] The revision requests include specific changes to the message or background.

[0299] 8. The server generates the stamp again

[0300] The server sends the correction request again to the API of the generation AI model, which generates the corrected stamp.

[0301] 9. The server saves the final stamp and notifies the device.

[0302] The server then stores the final generated stamp in the user's account.

[0303] A notification will be sent to the device when the save is complete, making the stamp immediately available to the user as a LINE stamp.

[0304] Specific examples

[0305] For example, a user can create original LINE stickers using a photo of their pet dog, leveraging the emotion engine.

[0306] 1. User selects a photo

[0307] Select a photo of your dog from your smartphone gallery.

[0308] 2. The device sends the photo

[0309] The selected photo is sent to the server.

[0310] 3. The server receives the photo and analyzes it with the generative AI model

[0311] The server receives the photo and provides it to the generative AI model to begin analysis.

[0312] 4. The server analyzes the user's emotions using an emotion engine

[0313] The emotion engine analyzes the user's facial expressions and voice data to detect "joy."

[0314] 5. Generative AI model generates stickers based on emotions

[0315] Based on the emotion analysis result of "joy," a stamp was generated with the background changed to a sunny park and the message "I'm happy!" added.

[0316] 6. The server sends the stamp to the device

[0317] The generated stamp is sent to the terminal and displayed to the user.

[0318] 7. The user checks the stamp and requests corrections

[0319] The user requests that the message be changed to "Let's play!"

[0320] 8. The server generates the stamp again

[0321] The server then has the AI ​​model generate stamps again based on the correction request.

[0322] 9. The server saves the final stamp and notifies the device.

[0323] The modified stamps will be saved to the user's LINE account and made available for use.

[0324] In this way, a system that utilizes an emotion engine can quickly create original stamps that reflect the user's emotions, enabling more personalized communication.

[0325] The processing flow will be explained below.

[0326] Step 1:

[0327] The user opens the device's gallery.

[0328] The user selects the image file they want to use as an original stamp.

[0329] The device temporarily saves the selected image file.

[0330] Step 2:

[0331] The terminal creates a request to notify the server that the image file selection has been completed.

[0332] The terminal sends the selected image file to the server in the form of an HTTP request.

[0333] Verify that the server received the request.

[0334] Step 3:

[0335] The server temporarily stores the received image file in storage.

[0336] Set the parameters for the server to call the API for the generated AI model.

[0337] The server provides the image file to the generative AI model and begins analysis.

[0338] Step 4:

[0339] The server calls the emotion engine and prepares to analyze the user's emotions.

[0340] The user provides data such as voice, facial expressions, and text input through the device.

[0341] The device collects this data and sends it to the server.

[0342] Step 5:

[0343] The server provides the data sent to the emotion engine and analyzes the user's emotions.

[0344] The emotion engine detects the user's emotions (e.g., "happiness," "sadness," "surprise," etc.).

[0345] Step 6:

[0346] Based on the image features analyzed by the generative AI model and the analysis results of the emotion engine, customization elements (such as changing the background or adding an appropriate message) are applied to generate original stamps.

[0347] The generated stamp image is returned to the server.

[0348] Step 7:

[0349] The server temporarily stores the generated original stamp.

[0350] The server creates a request to send the stamp image to the terminal.

[0351] Step 8:

[0352] The terminal displays the stamp image received from the server to the user.

[0353] The user checks the stamp and specifies correction requests as necessary.

[0354] Step 9:

[0355] The terminal receives the user's modification request and creates a request to send to the server.

[0356] The terminal sends a modification request to the server.

[0357] Step 10:

[0358] The server receives the correction request and sets the parameters to call the API for the generated AI model again.

[0359] Based on the modification request, the server sends the image file and customization elements to the generative AI model.

[0360] Step 11:

[0361] The generative AI model recreates the original stamp reflecting the requested modifications.

[0362] The generative AI model returns the corrected stamp image to the server.

[0363] Step 12:

[0364] The server temporarily stores the returned corrected stamp image.

[0365] The server starts the process of saving the final generated original stamp to the user's account.

[0366] Step 13:

[0367] The server creates a request to notify the terminal that the stamp saving process has been completed.

[0368] The device receives a notification from the server and displays to the user that the final stamp has been saved.

[0369] Step 14:

[0370] The user opens the LINE app on their device and confirms that the generated original stamps are available.

[0371] The user sends an original stamp in a LINE chat and checks that it displays as intended.

[0372] The above are the specific processing steps that allow users to select an image file, and then use the emotion engine and generative AI model to generate, modify, save, and ultimately use original LINE stamps.

[0373] Example 2

[0374] 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."

[0375] Conventional stamp generation systems have had difficulty in quickly and efficiently generating personalized stamps that reflect the user's emotions. Furthermore, they lacked the means to flexibly accommodate requests for corrections to generated stamps. This has led to the problem that it is difficult for users to create original stamps that satisfy them.

[0376] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a transmitted image file and temporarily storing it in storage, means for analyzing the user's emotions using an emotion engine, and means for providing the received image file to a generative AI model and applying customization elements based on the emotion analysis result to generate an original stamp. This makes it possible to quickly generate a personalized original stamp that reflects the user's emotions.

[0377] "User" refers to a general user who operates a terminal to select an image file or request a stamp modification.

[0378] "Terminal" refers to a device operated by a user, such as a smartphone, tablet, or PC.

[0379] "Image file" refers to the digital image data that the user selects from the device and that is the basis for generating the stamp.

[0380] The term "server" refers to a computer system that receives data sent from a terminal via a network and performs image processing and stamp generation.

[0381] "Generative AI model" refers to the algorithms and programs used to generate original stamps based on received image files.

[0382] "Emotion engine" refers to algorithms and programs for analyzing user emotions.

[0383] "Customization Elements" refers to customization elements applied to a sticker by a generative AI model, such as changing the background or adding a text message.

[0384] "Original stamp" refers to a stamp image to which customization elements have been applied by a generative AI model.

[0385] "Modification Request" means a request for change submitted by a User to a Generated Stamp.

[0386] "Communication platform" refers to applications and services that allow users to communicate with other users using original stamps.

[0387] This invention is a system in which a user selects an image file from a terminal and generates an original stamp image using a generative AI model and an emotion engine. Specific embodiments for implementing this invention are described below.

[0388] The system mainly consists of the following components:

[0389] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[0390] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[0391] 3. Generative AI Model - Algorithms and programs for generating stamp images based on received images.

[0392] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[0393] System Operation Overview

[0394] The user selects an image file on the device

[0395] The user selects the image they want to use as the original stamp from the image gallery or file manager on their device. For example, the user opens the gallery app on their smartphone and selects a photo of their pet dog.

[0396] The device sends the image file to the server

[0397] The device sends the selected image file to the server using an HTTP request. At this time, the image file is temporarily stored in the device's storage. Specifically, the device uploads the selected photo of the pet dog to the server using an HTTP POST request.

[0398] The server receives and analyzes the image file.

[0399] The server receives the image file and temporarily stores it in storage. Then, the server sets parameters to call the API of the generative AI model. For example, the server stores a photo of your dog in the image_input variable and prepares it for analysis.

[0400] The server analyzes the user's emotions

[0401] The server calls the emotion engine and analyzes the user's facial expressions, voice, text input, etc. The emotion engine detects the user's emotions and identifies emotion categories such as "happiness," "sadness," and "surprise." As a specific example, the emotion engine analyzes the user's happy facial expression and detects the emotion "happiness."

[0402] Generative AI model generates stamps

[0403] The generative AI model analyzes the characteristics of an image file and applies customization elements such as changing the background and adding a text message based on the results of the emotion analysis to generate original stamps. For example, the generative AI model analyzes a photo of a pet dog, changes the background to a sunny park, and creates a stamp with the message "I'm happy!"

[0404] The server sends the generated stamp to the terminal.

[0405] The server sends the generated original stamp to the device. The device receives the stamp image and displays it to the user. Specifically, the server sends the generated stamp to the device via an HTTP response, and it is displayed in the gallery or within the app on the user's device.

[0406] The user checks the stamp and requests corrections.

[0407] The user checks the generated stamp image and requests corrections if necessary. This correction request includes specific changes. For example, the user requests that the message "I'm happy!" be changed to "Let's play!"

[0408] The server generates the stamp again

[0409] The server sends the correction request again to the generative AI model to generate the corrected stamp. The server sends a new prompt containing the corrections to the generative AI model to obtain a new stamp.

[0410] The server saves the final stamp and notifies the device

[0411] The server saves the final generated stickers to the user's account, then sends a save completion notification to the device, allowing the user to immediately use the stickers within communication platforms such as the LINE app. For example, by saving new stickers to a database and sending a save completion notification to the device, the user can use the new stickers on LINE.

[0412] Specific examples

[0413] The process for users to create original LINE stickers using photos of their pet dogs is as follows:

[0414] 1. The user opens the gallery app on their smartphone and selects a photo of their dog.

[0415] 2. The device sends the selected photo of the dog to the server via an HTTP request.

[0416] 3. The server receives the photo and provides it to the generative AI model to begin analysis.

[0417] 4. Use an emotion engine to analyze the user's facial expression data and detect "happiness."

[0418] 5. Based on the emotion analysis result of "joy," the generative AI model changes the background to a sunny park and generates a stamp with the message "I'm so happy!" added.

[0419] 6. The server sends the generated stamp to the device and displays it to the user.

[0420] 7. The user requests that the "Happy!" message be changed to "Let's play!"

[0421] 8. The server sends the correction request to the generative AI model to generate the corrected stamp.

[0422] 9. The modified stamps are saved to the user's LINE account and made available for use.

[0423] Prompt Sentence Examples

[0424] Create an original stamp based on the user's emotion "joy" using a photo of your dog. Change the background to a sunny park and add the message "I'm so happy!"

[0425] In this way, it becomes possible to quickly generate personalized original stamps that reflect the user's emotions.

[0426] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0427] Step 1:

[0428] The user selects an image file on the device.

[0429] Input: The user operates the image gallery or file manager on the device and specifies the image file they want to use as a stamp.

[0430] What happens: The user opens the gallery app on their smartphone and selects a photo of their dog.

[0431] Output: The path or URL of the selected image file is retrieved.

[0432] Step 2:

[0433] The device sends the image file to the server.

[0434] Input: The path or URL of the image file obtained in step 1.

[0435] Specific operation: The device uploads the selected image file to the server using an HTTP POST request.

[0436] Output: The server receives the image file and it is temporarily saved in storage.

[0437] Step 3:

[0438] The server receives the image file and prepares it for analysis.

[0439] Input: The image file uploaded in step 2.

[0440] Specific operation: The server temporarily saves the image file in storage and sets parameters for analysis. For example, it saves the image file in the image_input variable.

[0441] Output: Image data ready for analysis.

[0442] Step 4:

[0443] The server analyzes the user's emotions.

[0444] Input: Emotional data such as user facial expressions, voice, and text input.

[0445] Specific operation: This data is sent to the emotion engine to perform emotion analysis. For example, the emotion engine analyzes the user's facial expression data and detects the emotion "joy."

[0446] Output: Sentiment analysis result (e.g. "Happy", "Sad", "Surprise", etc.).

[0447] Step 5:

[0448] The server generates stamps using a generative AI model.

[0449] Input: The image data prepared in step 3 and the sentiment analysis results obtained in step 4.

[0450] How it works: The generative AI model analyzes the characteristics of an image file and applies customization elements such as changing the background or adding a message based on the results of emotion analysis. For example, based on the emotion of "joy," the generative AI model generates a stamp that changes the background to a sunny park and adds the message "I'm so happy!"

[0451] Output: Customized original stamp image.

[0452] Step 6:

[0453] The server sends the generated stamp to the terminal.

[0454] Input: The original stamp image generated in step 5.

[0455] Specific operation: The server sends the generated stamp to the terminal in an HTTP response.

[0456] Output: The device receives the stamp image and displays it to the user.

[0457] Step 7:

[0458] The user checks the stamp and requests corrections.

[0459] Input: The original stamp image shown to the user in step 6.

[0460] Specific behavior: The user checks the stamp and, if necessary, requests corrections through the application interface. For example, the user requests that the message "I'm happy!" be changed to "Let's play!"

[0461] Output: User requested corrections.

[0462] Step 8:

[0463] The server generates the stamp again.

[0464] Input: The correction request provided by the user in step 7.

[0465] Specific operation: The server sends a correction request to the generative AI model again, and sends a new prompt sentence to the generative AI model to generate a corrected stamp.

[0466] Output: The original stamp image after modification.

[0467] Step 9:

[0468] The server saves the final stamp and notifies the terminal.

[0469] Input: The modified original stamp image generated in step 8.

[0470] Specific operation: The server saves the modified stamp in the database and sends a save completion notification to the terminal.

[0471] Output: The modified stickers are saved to the user's LINE account, and a notification is sent to the user's device. The user can then use the stickers in the LINE app.

[0472] (Application example 2)

[0473] 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."

[0474] In the conventional LINE sticker generation system, the process for users to generate sticker images was limited, making it difficult to generate stickers in real time or use them in stores. Furthermore, stickers were not generated to reflect the user's emotions, making it difficult to realize personalized communication. Furthermore, the process of generating and modifying stickers was complicated, resulting in a poor user experience.

[0475] 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.

[0476] In this invention, the server includes means for receiving an image file selected by a user and providing it to a generative AI model to generate an original stamp, means for sending the generated original stamp to a terminal, means including an emotion engine that analyzes the user's emotions and reflects them in the stamp generation, and means for generating the stamp again using the generative AI model based on a correction request. This enables users to generate original stamps in real time at physical stores and share them on social media on the spot.

[0477] A "terminal" is a device operated by a user, such as a smartphone, tablet, or personal computer.

[0478] A "server" is a computer system that receives and processes data sent from a terminal via a network.

[0479] A "generative AI model" is a collection of algorithms and programs for generating customized stamp images based on image files and other data received from users.

[0480] "Customization elements" are additional elements or modifications that are applied to the generated stamp image, such as changing the background or adding a message.

[0481] An "emotion engine" is a collection of algorithms and programs that analyze a user's voice, facial expressions, text input, etc. to detect the user's emotions.

[0482] "Original Stamps" are individually customized stamp images created by a generative AI model that users can use on communication platforms.

[0483] A "communication platform" is an online service that enables users to send and receive messages using stamps, such as LINE or other SNS.

[0484] A "physical store" is a physical location, such as a commercial facility or retail outlet, that a user can visit.

[0485] "Real time" is a time characteristic that refers to immediate results being obtained the moment an operation or event occurs.

[0486] A "modification request" is a request made by a user to make changes or improvements to a generated stamp.

[0487] This invention provides a system that allows users to create original LINE stamps in real time in physical stores. The system consists of elements such as a smartphone, a server, a generative AI model, and an emotion engine.

[0488] System configuration

[0489] The system consists of the following components:

[0490] 1. Terminal - A device operated by a user, such as a smartphone or tablet.

[0491] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[0492] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[0493] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[0494] Explanation of program processing

[0495] 1. Select and send image files:

[0496] The user operates the smartphone application and selects an image file from the gallery, and the selected image is sent to the server via an HTTP request.

[0497] 2. Data Receipt and Analysis:

[0498] The server receives the image file and temporarily stores it in storage, then calls the API of the generative AI model to begin analyzing the image.

[0499] 3. Emotion Analysis:

[0500] The server uses an emotion engine to analyze the user's emotions, using data such as facial expressions, voice, and text input. For example, emotions such as "happiness" or "surprise" can be detected.

[0501] 4. Stamp generation:

[0502] The generative AI model analyzes the image features and applies customization elements (such as changing the background or adding a message) based on the detected emotion to generate an original stamp. The generated stamp image is then returned to the server.

[0503] 5. Sending and viewing stamps:

[0504] The server sends the generated original stamp to the smartphone and displays it to the user, who can then check the stamp and make correction requests.

[0505] 6. Processing Amendment Requests:

[0506] If the user makes a correction request, the request is sent again to the generative AI model, and a new stamp is generated.

[0507] 7. Save and share your final stamp:

[0508] The server then saves the final stamps to the user's account, allowing the user to instantly share them on social media and other communication platforms.

[0509] Specific examples

[0510] The video shows a user visiting a physical store creating original LINE stamps using photos taken with their smartphone.

[0511] 1. User selects a photo:

[0512] Select a photo taken at a photo spot within the store from your smartphone gallery.

[0513] 2. The device sends the photo:

[0514] The selected photo is sent to the server.

[0515] 3. The server analyzes the photo:

[0516] The server receives the photo and begins analyzing it using the generative AI model.

[0517] 4. Emotion Analysis:

[0518] The emotion engine detects the user's "joy" from the photo.

[0519] 5. Stamp generation:

[0520] Based on the emotion of "joy," a stamp was generated with the background changed to a sunny park and the message "I'm so happy!" added.

[0521] 6. Viewing and Modifying Stamps:

[0522] The generated stamp is displayed on the smartphone. The user requests to change the message to "Let's play!"

[0523] 7. Generate and display correction stamps:

[0524] The message is then regenerated by the AI ​​model and the revised stamp is displayed.

[0525] 8. Save and share your final stamp:

[0526] The final stamp will be saved in the user's account and can be shared on LINE and other platforms.

[0527] Prompt Sentence Examples

[0528] "Please create LINE stamps that express joy using photos of smiling customers visiting your store with their friends."

[0529] The system will improve the customer experience in physical stores and enable personalized communication.

[0530] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0531] Step 1:

[0532] A user operates a smartphone application and selects an image file from the gallery. The input here is the image file selected by the user, and the output is the data of the selected image file.

[0533] Step 2:

[0534] The terminal sends the data of the selected image file to the server via an HTTP request. The input is the image file data obtained in step 1, and the output is the image file data sent to the server.

[0535] Step 3:

[0536] The server receives the image file and temporarily stores it in storage. The image file data stored in the server's storage is input data, and the output is temporary data stored on the server.

[0537] Step 4:

[0538] The server calls the API of the generative AI model and analyzes the data of the saved image file. The input is the data of the saved image file, and the output is data that analyzes the image features. In this step, the server extracts the features of the image file.

[0539] Step 5:

[0540] The server analyzes the user's emotions using an emotion engine. The input is the image file and additional user data (e.g., voice, facial expressions, etc.), and the output is the analyzed emotion data. In this step, the server classifies the user's emotions into categories such as "happiness" or "surprise."

[0541] Step 6:

[0542] The server uses a generative AI model to apply customization elements based on the analyzed emotion data and the features of the image file, generating an original stamp. The input is the image feature data and emotion data, and the output is the generated original stamp image. In this step, processing such as changing the background and adding text is performed.

[0543] Step 7:

[0544] The server sends the generated original stamp to the terminal. The input is the image of the generated original stamp, and the output is the stamp image sent to the terminal.

[0545] Step 8:

[0546] The terminal displays the generated original stamp to the user and accepts modification requests. The input is the stamp image sent from the server, and the output is the stamp image that the user sees on the screen and modification request data. The user can request changes to the stamp content.

[0547] Step 9:

[0548] The server sends the correction request to the generative AI model again to generate a corrected original stamp. The input is the correction request data, and the output is the corrected stamp image. The server again instructs the generative AI model to generate a new stamp image.

[0549] Step 10:

[0550] The server saves the final generated stamp in the user's account. The input is the modified original stamp image, and the output is the stamp image saved in the user's account.

[0551] Step 11:

[0552] The device finally displays the saved original stamp and makes it available to the user within the communication platform. The input is the saved stamp image, and the output is the stamp image displayed on the user's device. The user can share this image on LINE or other SNS.

[0553] 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.

[0554] 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.

[0555] 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.

[0556] [Second embodiment]

[0557] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0558] 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.

[0559] 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).

[0560] 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.

[0561] 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.

[0562] 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).

[0563] 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.

[0564] 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.

[0565] 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.

[0566] 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.

[0567] 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.

[0568] 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."

[0569] This invention is a system that allows users to select image files from their devices and generate original LINE stamps using a generative AI model. Specific embodiments of the invention are described in detail below.

[0570] System configuration

[0571] The system mainly consists of the following components:

[0572] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[0573] 2. Server - Receives data sent from the device via the network and processes the images using generative AI models.

[0574] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[0575] Processing flow

[0576] The following shows the process from when the user selects an image file to when an original stamp is generated.

[0577] 1. User selects an image file

[0578] The user opens the device's gallery and selects the image they want to use as an original stamp.

[0579] 2. The device sends the image file to the server

[0580] The terminal transmits the selected image file to the server.

[0581] The transmitted image file is temporarily stored in the device's storage and then uploaded to the server via an HTTP request.

[0582] 3. The server receives and analyzes the image file.

[0583] The server receives the image file and temporarily stores it in storage.

[0584] The server calls the generated AI model and begins image analysis.

[0585] 4. Generative AI model generates stamps

[0586] The generative AI model analyzes the characteristics of the image file and applies the customization elements you set (changing the background, adding a message, etc.) to generate an original stamp.

[0587] The generated stamp image is returned to the server.

[0588] 5. The server sends the generated stamp to the device.

[0589] The server transmits the generated original stamp to the terminal.

[0590] The device receives the stamp image and displays it to the user.

[0591] 6. The user checks the stamp and requests corrections

[0592] The user checks the generated stamp image and specifies correction requests as necessary.

[0593] The revision requests include specific changes to the message or background.

[0594] 7. The server generates the stamp again

[0595] The server sends the correction request again to the generation AI model, which generates the corrected stamp.

[0596] 8. The server saves the final stamp and notifies the device.

[0597] The server then stores the final generated stamp in the user's account.

[0598] A notification will be sent to the device when the save is complete, making the stamp immediately available to the user as a LINE stamp.

[0599] Specific examples

[0600] For example, let's say a user creates an original LINE stamp using a photo of their beloved dog.

[0601] 1. User selects a photo

[0602] Select a photo of your dog from your smartphone gallery.

[0603] 2. The device sends the photo

[0604] The selected photo is sent to the server.

[0605] 3. The server receives the photo and analyzes it with the generative AI model

[0606] The server receives the photo and provides it to the generative AI model to begin analysis.

[0607] 4. Generative AI model generates stamps

[0608] After analyzing the photo, a stamp was generated with the background changed to a park and the message "Let's go for a walk" added.

[0609] 5. The server sends the stamp to the device.

[0610] The generated stamp is sent to the terminal and displayed to the user.

[0611] 6. The user checks the stamp and requests corrections

[0612] The user requests that the message be changed to "Let's play!"

[0613] 7. The server generates the stamp again

[0614] The server then has the AI ​​model generate stamps again based on the correction request.

[0615] 8. The server saves the final stamp and notifies the device.

[0616] The modified stamps will be saved to the user's LINE account and made available for use.

[0617] In this way, users can quickly create original LINE stamps using images stored on their smartphones and use them instantly, significantly reducing the time and effort required for creating stamps and increasing the number of ways stamps can be used.

[0618] The processing flow will be explained below.

[0619] Step 1:

[0620] The user opens the device's gallery.

[0621] The user selects the image file they want to use as an original stamp.

[0622] The device temporarily saves the selected image file.

[0623] Step 2:

[0624] The terminal creates a request to notify the server that the image file selection has been completed.

[0625] The terminal sends the selected image file to the server in the form of an HTTP request.

[0626] Verify that the server received the request.

[0627] Step 3:

[0628] The server temporarily stores the received image file in storage.

[0629] Set the parameters for the server to call the API for the generated AI model.

[0630] Step 4:

[0631] The server sends the image file as input data to the generative AI model.

[0632] A generative AI model analyzes image files and extracts features.

[0633] Step 5:

[0634] The generative AI model applies the specified customization elements (changing the background, adding a message, etc.) to generate original stamps.

[0635] The stamp image generated by the generative AI model is returned to the server.

[0636] Step 6:

[0637] The server receives the returned stamp image and temporarily stores it.

[0638] The server creates a request to send the generated original stamp to the terminal.

[0639] Step 7:

[0640] The terminal displays the stamp image received from the server to the user.

[0641] The user reviews the stamp and requests corrections if necessary.

[0642] Step 8:

[0643] The device receives the user's modification request and creates a request to send to the server.

[0644] The terminal sends a modification request to the server.

[0645] Step 9:

[0646] The server receives the correction request and sets the parameters to call the API for the generated AI model again.

[0647] Based on the modification request, the server sends the image file and customization elements to the generative AI model.

[0648] Step 10:

[0649] The generative AI model recreates the original stamp reflecting the requested modifications.

[0650] The generative AI model returns the corrected stamp image to the server.

[0651] Step 11:

[0652] The server receives the corrected stamp image and temporarily stores it again.

[0653] The server initiates the process to store the final generated original stamp in the user's account.

[0654] Step 12:

[0655] The server creates a request to notify the terminal that the stamp saving process has been completed.

[0656] The device receives a notification from the server and displays to the user that the final stamp has been saved.

[0657] Step 13:

[0658] The user opens the LINE app on their device and confirms that the generated original stamps are available.

[0659] The user sends an original stamp in a LINE chat and checks that it displays as intended.

[0660] The above are the specific processing steps for a user to select an image file, generate, modify, save, and finally use an original LINE stamp using the generative AI model.

[0661] Example 1

[0662] 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."

[0663] Conventional stamp generation systems require users to manually design stamps, which is time-consuming and labor-intensive. Furthermore, the quality of the generated stamps is inconsistent, and any corrections required can require additional work. Furthermore, applying user-specified customization elements is difficult, resulting in a lack of flexibility.

[0664] 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.

[0665] In this invention, the server includes: means for a user to select an image file from the device; means for the device to transmit the selected image file to a network server; means for the network server to receive the transmitted image file; means for the network server to provide the received image file to an image generation model and apply customization elements to generate an original stamp; means for the network server to transmit the generated original stamp to the device; means for the device to display the transmitted original stamp to the user and accept a modification request; means for the network server to transmit the modification request again to the image generation model and generate a modified original stamp; means for the network server to save the finally generated original stamp in the user's account; and means for the device to display the finally saved original stamp and make it available to the user within the communication platform. This enables users to easily generate and customize high-quality original stamps.

[0666] "User" refers to the entity that uses the system, an individual or organization that selects image files and gives instructions for customization.

[0667] "Device" refers to equipment operated by a user, such as a smartphone, tablet, or computer.

[0668] "Network Server" refers to a centralized management system for receiving and processing data sent from devices.

[0669] "Image File" refers to digital image data selected by a User and provided to the System.

[0670] "Image generation model" refers to algorithms and programs for generating new images based on input images.

[0671] "Customization Elements" refers to modifications or additions (e.g., changing the background, adding text) that are applied to the generated image based on the user's specifications.

[0672] "Custom Stamp" refers to a unique image generated based on the image and customization elements provided by the user.

[0673] "Communication platform" refers to a place where users can exchange messages with other users using original stamps they have created, and generally refers to a messaging application.

[0674] A "modification request" refers to an instruction from a user requesting changes or additions to an already generated original stamp.

[0675] "Account" means the ID and related information that enables a User to access the System and manage their personal data and settings.

[0676] The system of this invention allows users to select an image file from their device and then executes a series of processes to generate original stamps using a generative AI model. The elements of the system are as follows:

[0677] Hardware and Software

[0678] The system mainly consists of the following hardware and software:

[0679] 1. Device:

[0680] Smartphones, tablets, computers, etc. operated by users.

[0681] It has the function of sending image files to a network server.

[0682] 2. Network Server:

[0683] It receives and processes data sent from the device and sends the generated stamp back to the device.

[0684] It uses a generative AI model to analyze images and generate stamps.

[0685] 3. Generative AI Model:

[0686] Algorithms and programs for image generation, such as OpenAI's DALL-E and Stable Diffusion.

[0687] Operation of each element

[0688] This section explains how each element operates and what data processing and calculations are performed.

[0689] device

[0690] The user selects an image file using the device. The selected image file is sent to the network server using an HTTP request. The device has a storage device that temporarily stores data, and the data is temporarily saved before being sent.

[0691] Network Server

[0692] The network server receives the image file sent from the device and temporarily stores it in storage. It then calls the generative AI model to analyze the image. The analyzed data is used to generate a stamp by applying customization elements (changing the background, adding a message, etc.). The generated stamp image is then sent back to the device. If the user makes a modification request, the network server sends this modification request again to the generative AI model, which then generates a new stamp.

[0693] Specific examples

[0694] For example, below is a scenario in which a user creates original LINE stamps using a photo of their beloved dog.

[0695] 1. User selects a photo:

[0696] The user opens the gallery on their smartphone and selects a photo of their dog.

[0697] 2. The device sends the photo:

[0698] The user selects a photo of their dog and sends it to the server using an HTTP POST request.

[0699] 3. The network server analyzes the photo using the generated AI model:

[0700] The photos received by the server are temporarily saved in the " / tmp" directory, and a generative AI model (e.g., DALL-E) is called to analyze them.

[0701] 4. Generative AI model generates stamps:

[0702] For the analyzed photo, a stamp is generated by changing the background to a park and adding the message "Let's go for a walk."

[0703] 5. The network server sends the generated stamp to the device:

[0704] The generated stamp image is sent back to the device as an HTTP response.

[0705] 6. User checks stamp and requests correction:

[0706] The user checks the generated stamp and operates the device to request that the message be changed to "Let's play!"

[0707] 7. The network server generates the stamp again:

[0708] The server sends the correction request again to the image generation model to generate the corrected stamp.

[0709] Prompt Sentence Examples

[0710] Here are some examples of prompts based on user input:

[0711] Photo Analysis: Photos of your beloved dog

[0712] Change background: Park

[0713] Added message: "Let's go for a walk?"

[0714] By passing this prompt text to a generative AI model, an original stamp is generated based on the specified elements.

[0715] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0716] Step 1:

[0717] The user opens the device's gallery and selects the image file they want to use as an original stamp. When the user taps on the image in the smartphone's photo app to select it, the selected image file is saved in temporary storage on the device.

[0718] Input: An image file selected by the user from the gallery

[0719] Output: Image file saved to temporary storage on device

[0720] Step 2:

[0721] The device sends the selected image file to the network server using an HTTP POST request. The device uploads the selected image file to the server.

[0722] Input: Image file saved on device

[0723] Output: Image file sent to network server

[0724] Step 3:

[0725] The server receives the image file and temporarily stores it in storage. The server receives the HTTP request and stores the received image file in the " / tmp" directory.

[0726] Input: Image file sent from device to server

[0727] Output: Image file saved in temporary storage on the server

[0728] Step 4:

[0729] The server invokes the generative AI model and begins analyzing the received image file. The server uses a Python script to pass the image file to the generative AI model (e.g., DALL-E) for analysis.

[0730] Input: Image file saved in the " / tmp" directory

[0731] Output: Analysis results returned from the generative AI model

[0732] Step 5:

[0733] The generative AI model analyzes the characteristics of the image file and applies customization elements to generate original stamps. The generative AI model generates stamp images based on prompts such as "change the background to a park" and "add the text 'Let's go for a walk.'"

[0734] Input: Image file to be analyzed and prompt text containing customization elements

[0735] Output: Stamp image generated by the generative AI model

[0736] Step 6:

[0737] The server sends the generated original stamp to the device. The server returns the generated stamp image as an HTTP response, which is received by the device.

[0738] Input: Stamp image received from the generative AI model

[0739] Output: Stamp image sent to device

[0740] Step 7:

[0741] The user checks the generated original stamp and requests a correction. The user operates the device to request a correction to the stamp content (for example, to change the text to "Let's play!").

[0742] Input: Stamp image displayed on device

[0743] Output: Correction request entered by the user

[0744] Step 8:

[0745] The server sends the correction request to the image generation model again, and generates the corrected original stamp. Based on the correction request, the server passes the necessary parameters to the generation AI model again, and generates the corrected stamp.

[0746] Input: Correction request submitted by the user

[0747] Output: Stamp image generated after correction by the generative AI model

[0748] Step 9:

[0749] The server saves the final generated original stamp to the user's account. The server saves the modified stamp image to the database and assigns it to the user's account.

[0750] Input: Modified stamp image

[0751] Output: Final stamp image saved in the user's account

[0752] Step 10:

[0753] The device will then display the original stamps and make them available to the user within their communication platform. The device will then receive the final stamps and import them into messaging apps such as LINE, making them available for use.

[0754] Input: The final stamp image saved in the user's account

[0755] Output: Stamp image available within the communication platform

[0756] (Application example 1)

[0757] 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."

[0758] Conventional stamp generation systems allow users to easily create custom designs using their image files, but lack the functionality to apply the created designs to products and order them through e-commerce sites, making it difficult to quickly provide products with original designs.

[0759] 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.

[0760] In this invention, the server includes means for providing the received image file to a generative AI model and applying customization elements to generate an original design, means for sending the generated original design to the terminal, means for sending a modification request to the generative AI model again to generate a modified original design, and means for saving the final generated original design to the user's account and applying it to a product, thereby enabling users to easily generate custom designs using their own image files and order products based on those designs.

[0761] "User" means a person who uses the System to select image files, generate customized designs, and order products.

[0762] "Terminal" refers to a device operated by a user, such as a smartphone, tablet, or PC.

[0763] An "image file" is image data such as a photograph or illustration that is selected by the user from the terminal and sent to the server.

[0764] A "server" is a computer system that receives image files sent from a terminal via a network, processes the images using a generative AI model, and provides the final generated design to the user.

[0765] A "generative AI model" is an algorithm and program that analyzes the characteristics of a received image file and applies customization elements to generate an original design.

[0766] "Customization elements" are design items, such as changing the background or adding a message, that the generative AI model applies to the image file.

[0767] An "original design" is a design image with customization elements applied, generated by a generative AI model.

[0768] A "modification request" is a request for changes made by a user to the generated original design.

[0769] "Products" are items such as t-shirts, mugs, and phone cases with custom designs applied.

[0770] "E-commerce Site" means an online platform through which users can order products using the final generated Original Design.

[0771] This invention relates to an e-commerce system that allows users to create original designs using images uploaded by users and order them as custom products. Specifically, the system is implemented as follows using a server, a terminal, and a generative AI model.

[0772] First, the user selects an image file using their device. The selected image file is sent to the server via an HTTP request. The server temporarily stores the received image file in storage and provides it to the generative AI model. The generative AI model analyzes the image file's characteristics and applies customization elements (such as changing the background or adding a message) to generate an original design. This original design is returned to the server and then sent to the device.

[0773] The device displays the received original design to the user. If the user is not satisfied with the design, the device accepts a revision request. The accepted revision request is sent again to the server, and the server communicates the revision request to the generative AI model. The generative AI model generates a new design based on the revision request, and that design is sent again to the user's device via the server.

[0774] Finally, if the user is satisfied with the design, it is saved to the user's account and the original design is applied to custom merchandise (e.g., t-shirts, mugs, phone cases, etc.). At this stage, the user can order the product through the e-commerce site.

[0775] The system uses the following hardware and software:

[0776] Hardware: User devices (smartphones, tablets, PCs, etc.), servers

[0777] Software: Generative AI models, HTTP request processing, storage systems, e-commerce sites

[0778] For example:

[0779] When a user selects a photo of their dog using their device, the photo is sent to the server. The server provides the photo to a generative AI model, which then generates an original design with a park background and the message "Pochi" added. This design is then sent to the user for confirmation. If the user requests a change to the design, such as "I want the colors to be brighter," the generative AI model generates a new design and sends it back to the user. Finally, if the user is satisfied with the design, they can order products such as T-shirts and mugs using that design.

[0780] An example of a real prompt is:

[0781] "Please create the design shown on this T-shirt using a photo of your dog. Please use a park as the background and add the dog's name, 'Pochi.'"

[0782] This allows users to easily and quickly create custom designs and order custom products based on those designs.

[0783] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0784] Step 1:

[0785] The user selects an image file from their device. The user opens the image gallery on their smartphone, tablet, or computer and selects the image file they want to use for the customized design. The input is the image file selected by the user, and the output is that the image file is saved on the device.

[0786] Step 2:

[0787] The device sends the selected image file to the server. The device uploads the selected image file to the server using an HTTP request. The input is the selected image file, and the output is the image file sent to the server.

[0788] Step 3:

[0789] The server receives the image file. The server temporarily stores the uploaded image file in its storage area. The input is the image file sent from the device, and the output is the image file stored on the server.

[0790] Step 4:

[0791] The server provides the received image file to the generative AI model, which applies customization elements to generate an original design. The generative AI model analyzes the image file and applies the specified customization elements (for example, changing the background or adding a message). The input is the saved image file and the specified customization elements, and the output is the generated original design.

[0792] Step 5:

[0793] The server sends the generated original design to the terminal. The server sends the generated original design to the user's terminal as an HTTP response. The input is the generated original design, and the output is the original design provided to the terminal.

[0794] Step 6:

[0795] The terminal displays the original design sent to the user and accepts any modification requests. The user checks the displayed original design and inputs modification requests as necessary. The input is the original design displayed to the user and the user's modification requests, and the output is the modified design request.

[0796] Step 7:

[0797] The server sends the modification request back to the generative AI model, which generates a modified original design. The generative AI model accepts the modification request and generates a new design based on the specified changes. The inputs are the modification request and the existing original design, and the output is the modified original design.

[0798] Step 8:

[0799] The server stores the final generated original design in the user's account and applies it to the product. The server associates the final original design with the user's account and stores it, then applies the design to the specified product template. The input is the modified original design and the user's account information, and the output is the customized product.

[0800] Step 9:

[0801] The terminal displays the final saved original design and allows the user to place an order within the e-commerce site. The user checks the displayed custom product and confirms the order through the e-commerce site. The input is the product with the final original design applied, and the output is the order confirmed by the user.

[0802] 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.

[0803] This invention is a system that allows a user to select an image file from a device and generates original LINE stamps using a generative AI model and an emotion engine. Specific embodiments of the invention are described in detail below.

[0804] System configuration

[0805] The system mainly consists of the following components:

[0806] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[0807] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[0808] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[0809] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[0810] Processing flow

[0811] The following shows the process from when the user selects an image file to when an original stamp is generated using the emotion engine.

[0812] 1. User selects an image file

[0813] The user opens the device's gallery and selects the image file they want to use as an original stamp.

[0814] 2. The device sends the image file to the server

[0815] The terminal transmits the selected image file to the server.

[0816] The transmitted image file is temporarily stored in the device's storage and then uploaded to the server via an HTTP request.

[0817] 3. The server receives and analyzes the image file.

[0818] The server receives the image file and temporarily stores it in storage.

[0819] Set the parameters for the server to call the API for the generated AI model.

[0820] 4. The server analyzes the user's emotions

[0821] The server calls the emotion engine and analyzes multiple input data, including the user's voice, facial expressions, and text input.

[0822] The emotion engine detects the user's emotions (e.g., joy, sadness, surprise, etc.).

[0823] 5. Generative AI model generates stamps

[0824] The generative AI model analyzes the characteristics of the image file and, based on the analysis results of the emotion engine, applies customization elements (such as changing the background or adding an appropriate message) to generate original stamps.

[0825] The generated stamp image is returned to the server.

[0826] 6. The server sends the generated stamp to the device.

[0827] The server transmits the generated original stamp to the terminal.

[0828] The device receives the stamp image and displays it to the user.

[0829] 7. The user checks the stamp and requests corrections

[0830] The user checks the generated stamp image and specifies correction requests as necessary.

[0831] The revision requests include specific changes to the message or background.

[0832] 8. The server generates the stamp again

[0833] The server sends the correction request again to the API of the generation AI model, which generates the corrected stamp.

[0834] 9. The server saves the final stamp and notifies the device.

[0835] The server then stores the final generated stamp in the user's account.

[0836] A notification will be sent to the device when the save is complete, making the stamp immediately available to the user as a LINE stamp.

[0837] Specific examples

[0838] For example, a user can create original LINE stickers using a photo of their pet dog, leveraging the emotion engine.

[0839] 1. User selects a photo

[0840] Select a photo of your dog from your smartphone gallery.

[0841] 2. The device sends the photo

[0842] The selected photo is sent to the server.

[0843] 3. The server receives the photo and analyzes it with the generative AI model

[0844] The server receives the photo and provides it to the generative AI model to begin analysis.

[0845] 4. The server analyzes the user's emotions using an emotion engine

[0846] The emotion engine analyzes the user's facial expressions and voice data to detect "joy."

[0847] 5. Generative AI model generates stickers based on emotions

[0848] Based on the emotion analysis result of "joy," a stamp was generated with the background changed to a sunny park and the message "I'm happy!" added.

[0849] 6. The server sends the stamp to the device

[0850] The generated stamp is sent to the terminal and displayed to the user.

[0851] 7. The user checks the stamp and requests corrections

[0852] The user requests that the message be changed to "Let's play!"

[0853] 8. The server generates the stamp again

[0854] The server then has the AI ​​model generate stamps again based on the correction request.

[0855] 9. The server saves the final stamp and notifies the device.

[0856] The modified stamps will be saved to the user's LINE account and made available for use.

[0857] In this way, a system that utilizes an emotion engine can quickly create original stamps that reflect the user's emotions, enabling more personalized communication.

[0858] The processing flow will be explained below.

[0859] Step 1:

[0860] The user opens the device's gallery.

[0861] The user selects the image file they want to use as an original stamp.

[0862] The device temporarily saves the selected image file.

[0863] Step 2:

[0864] The terminal creates a request to notify the server that the image file selection has been completed.

[0865] The terminal sends the selected image file to the server in the form of an HTTP request.

[0866] Verify that the server received the request.

[0867] Step 3:

[0868] The server temporarily stores the received image file in storage.

[0869] Set the parameters for the server to call the API for the generated AI model.

[0870] The server provides the image file to the generative AI model and begins analysis.

[0871] Step 4:

[0872] The server calls the emotion engine and prepares to analyze the user's emotions.

[0873] The user provides data such as voice, facial expressions, and text input through the device.

[0874] The device collects this data and sends it to the server.

[0875] Step 5:

[0876] The server provides the data sent to the emotion engine and analyzes the user's emotions.

[0877] The emotion engine detects the user's emotions (e.g., "happiness," "sadness," "surprise," etc.).

[0878] Step 6:

[0879] Based on the image features analyzed by the generative AI model and the analysis results of the emotion engine, customization elements (such as changing the background or adding an appropriate message) are applied to generate original stamps.

[0880] The generated stamp image is returned to the server.

[0881] Step 7:

[0882] The server temporarily stores the generated original stamp.

[0883] The server creates a request to send the stamp image to the terminal.

[0884] Step 8:

[0885] The terminal displays the stamp image received from the server to the user.

[0886] The user checks the stamp and specifies correction requests as necessary.

[0887] Step 9:

[0888] The terminal receives the user's modification request and creates a request to send to the server.

[0889] The terminal sends a modification request to the server.

[0890] Step 10:

[0891] The server receives the correction request and sets the parameters to call the API for the generated AI model again.

[0892] Based on the modification request, the server sends the image file and customization elements to the generative AI model.

[0893] Step 11:

[0894] The generative AI model recreates the original stamp reflecting the requested modifications.

[0895] The generative AI model returns the corrected stamp image to the server.

[0896] Step 12:

[0897] The server temporarily stores the returned corrected stamp image.

[0898] The server starts the process of saving the final generated original stamp to the user's account.

[0899] Step 13:

[0900] The server creates a request to notify the terminal that the stamp saving process has been completed.

[0901] The device receives a notification from the server and displays to the user that the final stamp has been saved.

[0902] Step 14:

[0903] The user opens the LINE app on their device and confirms that the generated original stamps are available.

[0904] The user sends an original stamp in a LINE chat and checks that it displays as intended.

[0905] The above are the specific processing steps that allow users to select an image file, and then use the emotion engine and generative AI model to generate, modify, save, and ultimately use original LINE stamps.

[0906] Example 2

[0907] 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."

[0908] Conventional stamp generation systems have had difficulty in quickly and efficiently generating personalized stamps that reflect the user's emotions. Furthermore, they lacked the means to flexibly accommodate requests for corrections to generated stamps. This has led to the problem that it is difficult for users to create original stamps that satisfy them.

[0909] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a transmitted image file and temporarily storing it in storage, means for analyzing the user's emotions using an emotion engine, and means for providing the received image file to a generative AI model and applying customization elements based on the emotion analysis result to generate an original stamp. This makes it possible to quickly generate a personalized original stamp that reflects the user's emotions.

[0910] "User" refers to a general user who operates a terminal to select an image file or request a stamp modification.

[0911] "Terminal" refers to a device operated by a user, such as a smartphone, tablet, or PC.

[0912] "Image file" refers to the digital image data that the user selects from the device and that is the basis for generating the stamp.

[0913] The term "server" refers to a computer system that receives data sent from a terminal via a network and performs image processing and stamp generation.

[0914] "Generative AI model" refers to the algorithms and programs used to generate original stamps based on received image files.

[0915] "Emotion engine" refers to algorithms and programs for analyzing user emotions.

[0916] "Customization Elements" refers to customization elements applied to a sticker by a generative AI model, such as changing the background or adding a text message.

[0917] "Original stamp" refers to a stamp image to which customization elements have been applied by a generative AI model.

[0918] "Modification Request" means a request for change submitted by a User to a Generated Stamp.

[0919] "Communication platform" refers to applications and services that allow users to communicate with other users using original stamps.

[0920] This invention is a system in which a user selects an image file from a terminal and generates an original stamp image using a generative AI model and an emotion engine. Specific embodiments for implementing this invention are described below.

[0921] The system mainly consists of the following components:

[0922] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[0923] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[0924] 3. Generative AI Model - Algorithms and programs for generating stamp images based on received images.

[0925] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[0926] System Operation Overview

[0927] The user selects an image file on the device

[0928] The user selects the image they want to use as the original stamp from the image gallery or file manager on their device. For example, the user opens the gallery app on their smartphone and selects a photo of their pet dog.

[0929] The device sends the image file to the server

[0930] The device sends the selected image file to the server using an HTTP request. At this time, the image file is temporarily stored in the device's storage. Specifically, the device uploads the selected photo of the pet dog to the server using an HTTP POST request.

[0931] The server receives and analyzes the image file.

[0932] The server receives the image file and temporarily stores it in storage. Then, the server sets parameters to call the API of the generative AI model. For example, the server stores a photo of your dog in the image_input variable and prepares it for analysis.

[0933] The server analyzes the user's emotions

[0934] The server calls the emotion engine and analyzes the user's facial expressions, voice, text input, etc. The emotion engine detects the user's emotions and identifies emotion categories such as "happiness," "sadness," and "surprise." As a specific example, the emotion engine analyzes the user's happy facial expression and detects the emotion "happiness."

[0935] Generative AI model generates stamps

[0936] The generative AI model analyzes the characteristics of an image file and applies customization elements such as changing the background and adding a text message based on the results of the emotion analysis to generate original stamps. For example, the generative AI model analyzes a photo of a pet dog, changes the background to a sunny park, and creates a stamp with the message "I'm happy!"

[0937] The server sends the generated stamp to the terminal.

[0938] The server sends the generated original stamp to the device. The device receives the stamp image and displays it to the user. Specifically, the server sends the generated stamp to the device via an HTTP response, and it is displayed in the gallery or within the app on the user's device.

[0939] The user checks the stamp and requests corrections.

[0940] The user checks the generated stamp image and requests corrections if necessary. This correction request includes specific changes. For example, the user requests that the message "I'm happy!" be changed to "Let's play!"

[0941] The server generates the stamp again

[0942] The server sends the correction request again to the generative AI model to generate the corrected stamp. The server sends a new prompt containing the corrections to the generative AI model to obtain a new stamp.

[0943] The server saves the final stamp and notifies the device

[0944] The server saves the final generated stickers to the user's account, then sends a save completion notification to the device, allowing the user to immediately use the stickers within communication platforms such as the LINE app. For example, by saving new stickers to a database and sending a save completion notification to the device, the user can use the new stickers on LINE.

[0945] Specific examples

[0946] The process for users to create original LINE stickers using photos of their pet dogs is as follows:

[0947] 1. The user opens the gallery app on their smartphone and selects a photo of their dog.

[0948] 2. The device sends the selected photo of the dog to the server via an HTTP request.

[0949] 3. The server receives the photo and provides it to the generative AI model to begin analysis.

[0950] 4. Use an emotion engine to analyze the user's facial expression data and detect "happiness."

[0951] 5. Based on the emotion analysis result of "joy," the generative AI model changes the background to a sunny park and generates a stamp with the message "I'm so happy!" added.

[0952] 6. The server sends the generated stamp to the device and displays it to the user.

[0953] 7. The user requests that the "Happy!" message be changed to "Let's play!"

[0954] 8. The server sends the correction request to the generative AI model to generate the corrected stamp.

[0955] 9. The modified stamps are saved to the user's LINE account and made available for use.

[0956] Prompt Sentence Examples

[0957] Create an original stamp based on the user's emotion "joy" using a photo of your dog. Change the background to a sunny park and add the message "I'm so happy!"

[0958] In this way, it becomes possible to quickly generate personalized original stamps that reflect the user's emotions.

[0959] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0960] Step 1:

[0961] The user selects an image file on the device.

[0962] Input: The user operates the image gallery or file manager on the device and specifies the image file they want to use as a stamp.

[0963] What happens: The user opens the gallery app on their smartphone and selects a photo of their dog.

[0964] Output: The path or URL of the selected image file is retrieved.

[0965] Step 2:

[0966] The device sends the image file to the server.

[0967] Input: The path or URL of the image file obtained in step 1.

[0968] Specific operation: The device uploads the selected image file to the server using an HTTP POST request.

[0969] Output: The server receives the image file and it is temporarily saved in storage.

[0970] Step 3:

[0971] The server receives the image file and prepares it for analysis.

[0972] Input: The image file uploaded in step 2.

[0973] Specific operation: The server temporarily saves the image file in storage and sets parameters for analysis. For example, it saves the image file in the image_input variable.

[0974] Output: Image data ready for analysis.

[0975] Step 4:

[0976] The server analyzes the user's emotions.

[0977] Input: Emotional data such as user facial expressions, voice, and text input.

[0978] Specific operation: This data is sent to the emotion engine to perform emotion analysis. For example, the emotion engine analyzes the user's facial expression data and detects the emotion "joy."

[0979] Output: Sentiment analysis result (e.g. "Happy", "Sad", "Surprise", etc.).

[0980] Step 5:

[0981] The server generates stamps using a generative AI model.

[0982] Input: The image data prepared in step 3 and the sentiment analysis results obtained in step 4.

[0983] How it works: The generative AI model analyzes the characteristics of an image file and applies customization elements such as changing the background or adding a message based on the results of emotion analysis. For example, based on the emotion of "joy," the generative AI model generates a stamp that changes the background to a sunny park and adds the message "I'm so happy!"

[0984] Output: Customized original stamp image.

[0985] Step 6:

[0986] The server sends the generated stamp to the terminal.

[0987] Input: The original stamp image generated in step 5.

[0988] Specific operation: The server sends the generated stamp to the terminal in an HTTP response.

[0989] Output: The device receives the stamp image and displays it to the user.

[0990] Step 7:

[0991] The user checks the stamp and requests corrections.

[0992] Input: The original stamp image shown to the user in step 6.

[0993] Specific behavior: The user checks the stamp and, if necessary, requests corrections through the application interface. For example, the user requests that the message "I'm happy!" be changed to "Let's play!"

[0994] Output: User requested corrections.

[0995] Step 8:

[0996] The server generates the stamp again.

[0997] Input: The correction request provided by the user in step 7.

[0998] Specific operation: The server sends a correction request to the generative AI model again, and sends a new prompt sentence to the generative AI model to generate a corrected stamp.

[0999] Output: The original stamp image after modification.

[1000] Step 9:

[1001] The server saves the final stamp and notifies the terminal.

[1002] Input: The modified original stamp image generated in step 8.

[1003] Specific operation: The server saves the modified stamp in the database and sends a save completion notification to the terminal.

[1004] Output: The modified stickers are saved to the user's LINE account, and a notification is sent to the user's device. The user can then use the stickers in the LINE app.

[1005] (Application example 2)

[1006] 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."

[1007] In the conventional LINE sticker generation system, the process for users to generate sticker images was limited, making it difficult to generate stickers in real time or use them in stores. Furthermore, stickers were not generated to reflect the user's emotions, making it difficult to realize personalized communication. Furthermore, the process of generating and modifying stickers was complicated, resulting in a poor user experience.

[1008] 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.

[1009] In this invention, the server includes means for receiving an image file selected by a user and providing it to a generative AI model to generate an original stamp, means for sending the generated original stamp to a terminal, means including an emotion engine that analyzes the user's emotions and reflects them in the stamp generation, and means for generating the stamp again using the generative AI model based on a correction request. This enables users to generate original stamps in real time at physical stores and share them on social media on the spot.

[1010] A "terminal" is a device operated by a user, such as a smartphone, tablet, or personal computer.

[1011] A "server" is a computer system that receives and processes data sent from a terminal via a network.

[1012] A "generative AI model" is a collection of algorithms and programs for generating customized stamp images based on image files and other data received from users.

[1013] "Customization elements" are additional elements or modifications that are applied to the generated stamp image, such as changing the background or adding a message.

[1014] An "emotion engine" is a collection of algorithms and programs that analyze a user's voice, facial expressions, text input, etc. to detect the user's emotions.

[1015] "Original Stamps" are individually customized stamp images created by a generative AI model that users can use on communication platforms.

[1016] A "communication platform" is an online service that enables users to send and receive messages using stamps, such as LINE or other SNS.

[1017] A "physical store" is a physical location, such as a commercial facility or retail outlet, that a user can visit.

[1018] "Real time" is a time characteristic that refers to immediate results being obtained the moment an operation or event occurs.

[1019] A "modification request" is a request made by a user to make changes or improvements to a generated stamp.

[1020] This invention provides a system that allows users to create original LINE stamps in real time in physical stores. The system consists of elements such as a smartphone, a server, a generative AI model, and an emotion engine.

[1021] System configuration

[1022] The system consists of the following components:

[1023] 1. Terminal - A device operated by a user, such as a smartphone or tablet.

[1024] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[1025] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[1026] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[1027] Explanation of program processing

[1028] 1. Select and send image files:

[1029] The user operates the smartphone application and selects an image file from the gallery, and the selected image is sent to the server via an HTTP request.

[1030] 2. Data Receipt and Analysis:

[1031] The server receives the image file and temporarily stores it in storage, then calls the API of the generative AI model to begin analyzing the image.

[1032] 3. Emotion Analysis:

[1033] The server uses an emotion engine to analyze the user's emotions, using data such as facial expressions, voice, and text input. For example, emotions such as "happiness" or "surprise" can be detected.

[1034] 4. Stamp generation:

[1035] The generative AI model analyzes the image features and applies customization elements (such as changing the background or adding a message) based on the detected emotion to generate an original stamp. The generated stamp image is then returned to the server.

[1036] 5. Sending and viewing stamps:

[1037] The server sends the generated original stamp to the smartphone and displays it to the user, who can then check the stamp and make correction requests.

[1038] 6. Processing Amendment Requests:

[1039] If the user makes a correction request, the request is sent again to the generative AI model, and a new stamp is generated.

[1040] 7. Save and share your final stamp:

[1041] The server then saves the final stamps to the user's account, allowing the user to instantly share them on social media and other communication platforms.

[1042] Specific examples

[1043] The video shows a user visiting a physical store creating original LINE stamps using photos taken with their smartphone.

[1044] 1. User selects a photo:

[1045] Select a photo taken at a photo spot within the store from your smartphone gallery.

[1046] 2. The device sends the photo:

[1047] The selected photo is sent to the server.

[1048] 3. The server analyzes the photo:

[1049] The server receives the photo and begins analyzing it using the generative AI model.

[1050] 4. Emotion Analysis:

[1051] The emotion engine detects the user's "joy" from the photo.

[1052] 5. Stamp generation:

[1053] Based on the emotion of "joy," a stamp was generated with the background changed to a sunny park and the message "I'm so happy!" added.

[1054] 6. Viewing and Modifying Stamps:

[1055] The generated stamp is displayed on the smartphone. The user requests to change the message to "Let's play!"

[1056] 7. Generate and display correction stamps:

[1057] The message is then regenerated by the AI ​​model and the revised stamp is displayed.

[1058] 8. Save and share your final stamp:

[1059] The final stamp will be saved in the user's account and can be shared on LINE and other platforms.

[1060] Prompt Sentence Examples

[1061] "Please create LINE stamps that express joy using photos of smiling customers visiting your store with their friends."

[1062] The system will improve the customer experience in physical stores and enable personalized communication.

[1063] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1064] Step 1:

[1065] A user operates a smartphone application and selects an image file from the gallery. The input here is the image file selected by the user, and the output is the data of the selected image file.

[1066] Step 2:

[1067] The terminal sends the data of the selected image file to the server via an HTTP request. The input is the image file data obtained in step 1, and the output is the image file data sent to the server.

[1068] Step 3:

[1069] The server receives the image file and temporarily stores it in storage. The image file data stored in the server's storage is input data, and the output is temporary data stored on the server.

[1070] Step 4:

[1071] The server calls the API of the generative AI model and analyzes the data of the saved image file. The input is the data of the saved image file, and the output is data that analyzes the image features. In this step, the server extracts the features of the image file.

[1072] Step 5:

[1073] The server analyzes the user's emotions using an emotion engine. The input is the image file and additional user data (e.g., voice, facial expressions, etc.), and the output is the analyzed emotion data. In this step, the server classifies the user's emotions into categories such as "happiness" or "surprise."

[1074] Step 6:

[1075] The server uses a generative AI model to apply customization elements based on the analyzed emotion data and the features of the image file, generating an original stamp. The input is the image feature data and emotion data, and the output is the generated original stamp image. In this step, processing such as changing the background and adding text is performed.

[1076] Step 7:

[1077] The server sends the generated original stamp to the terminal. The input is the image of the generated original stamp, and the output is the stamp image sent to the terminal.

[1078] Step 8:

[1079] The terminal displays the generated original stamp to the user and accepts modification requests. The input is the stamp image sent from the server, and the output is the stamp image that the user sees on the screen and modification request data. The user can request changes to the stamp content.

[1080] Step 9:

[1081] The server sends the correction request to the generative AI model again to generate a corrected original stamp. The input is the correction request data, and the output is the corrected stamp image. The server again instructs the generative AI model to generate a new stamp image.

[1082] Step 10:

[1083] The server saves the final generated stamp in the user's account. The input is the modified original stamp image, and the output is the stamp image saved in the user's account.

[1084] Step 11:

[1085] The device finally displays the saved original stamp and makes it available to the user within the communication platform. The input is the saved stamp image, and the output is the stamp image displayed on the user's device. The user can share this image on LINE or other SNS.

[1086] 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.

[1087] 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.

[1088] 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.

[1089] [Third embodiment]

[1090] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1091] 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.

[1092] 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).

[1093] 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.

[1094] 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.

[1095] 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).

[1096] 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.

[1097] 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.

[1098] 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.

[1099] 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.

[1100] 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.

[1101] 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."

[1102] This invention is a system that allows users to select image files from their devices and generate original LINE stamps using a generative AI model. Specific embodiments of the invention are described in detail below.

[1103] System configuration

[1104] The system mainly consists of the following components:

[1105] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[1106] 2. Server - Receives data sent from the device via the network and processes the images using generative AI models.

[1107] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[1108] Processing flow

[1109] The following shows the process from when the user selects an image file to when an original stamp is generated.

[1110] 1. User selects an image file

[1111] The user opens the device's gallery and selects the image they want to use as an original stamp.

[1112] 2. The device sends the image file to the server

[1113] The terminal transmits the selected image file to the server.

[1114] The transmitted image file is temporarily stored in the device's storage and then uploaded to the server via an HTTP request.

[1115] 3. The server receives and analyzes the image file.

[1116] The server receives the image file and temporarily stores it in storage.

[1117] The server calls the generated AI model and begins image analysis.

[1118] 4. Generative AI model generates stamps

[1119] The generative AI model analyzes the characteristics of the image file and applies the customization elements you set (changing the background, adding a message, etc.) to generate an original stamp.

[1120] The generated stamp image is returned to the server.

[1121] 5. The server sends the generated stamp to the device.

[1122] The server transmits the generated original stamp to the terminal.

[1123] The device receives the stamp image and displays it to the user.

[1124] 6. The user checks the stamp and requests corrections

[1125] The user checks the generated stamp image and specifies correction requests as necessary.

[1126] The revision requests include specific changes to the message or background.

[1127] 7. The server generates the stamp again

[1128] The server sends the correction request again to the generation AI model, which generates the corrected stamp.

[1129] 8. The server saves the final stamp and notifies the device.

[1130] The server then stores the final generated stamp in the user's account.

[1131] A notification will be sent to the device when the save is complete, making the stamp immediately available to the user as a LINE stamp.

[1132] Specific examples

[1133] For example, let's say a user creates an original LINE stamp using a photo of their beloved dog.

[1134] 1. User selects a photo

[1135] Select a photo of your dog from your smartphone gallery.

[1136] 2. The device sends the photo

[1137] The selected photo is sent to the server.

[1138] 3. The server receives the photo and analyzes it with the generative AI model

[1139] The server receives the photo and provides it to the generative AI model to begin analysis.

[1140] 4. Generative AI model generates stamps

[1141] After analyzing the photo, a stamp was generated with the background changed to a park and the message "Let's go for a walk" added.

[1142] 5. The server sends the stamp to the device.

[1143] The generated stamp is sent to the terminal and displayed to the user.

[1144] 6. The user checks the stamp and requests corrections

[1145] The user requests that the message be changed to "Let's play!"

[1146] 7. The server generates the stamp again

[1147] The server then has the AI ​​model generate stamps again based on the correction request.

[1148] 8. The server saves the final stamp and notifies the device.

[1149] The modified stamps will be saved to the user's LINE account and made available for use.

[1150] In this way, users can quickly create original LINE stamps using images stored on their smartphones and use them instantly, significantly reducing the time and effort required for creating stamps and increasing the number of ways stamps can be used.

[1151] The processing flow will be explained below.

[1152] Step 1:

[1153] The user opens the device's gallery.

[1154] The user selects the image file they want to use as an original stamp.

[1155] The device temporarily saves the selected image file.

[1156] Step 2:

[1157] The terminal creates a request to notify the server that the image file selection has been completed.

[1158] The terminal sends the selected image file to the server in the form of an HTTP request.

[1159] Verify that the server received the request.

[1160] Step 3:

[1161] The server temporarily stores the received image file in storage.

[1162] Set the parameters for the server to call the API for the generated AI model.

[1163] Step 4:

[1164] The server sends the image file as input data to the generative AI model.

[1165] A generative AI model analyzes image files and extracts features.

[1166] Step 5:

[1167] The generative AI model applies the specified customization elements (changing the background, adding a message, etc.) to generate original stamps.

[1168] The stamp image generated by the generative AI model is returned to the server.

[1169] Step 6:

[1170] The server receives the returned stamp image and temporarily stores it.

[1171] The server creates a request to send the generated original stamp to the terminal.

[1172] Step 7:

[1173] The terminal displays the stamp image received from the server to the user.

[1174] The user reviews the stamp and requests corrections if necessary.

[1175] Step 8:

[1176] The device receives the user's modification request and creates a request to send to the server.

[1177] The terminal sends a modification request to the server.

[1178] Step 9:

[1179] The server receives the correction request and sets the parameters to call the API for the generated AI model again.

[1180] Based on the modification request, the server sends the image file and customization elements to the generative AI model.

[1181] Step 10:

[1182] The generative AI model recreates the original stamp reflecting the requested modifications.

[1183] The generative AI model returns the corrected stamp image to the server.

[1184] Step 11:

[1185] The server receives the corrected stamp image and temporarily stores it again.

[1186] The server initiates the process to store the final generated original stamp in the user's account.

[1187] Step 12:

[1188] The server creates a request to notify the terminal that the stamp saving process has been completed.

[1189] The device receives a notification from the server and displays to the user that the final stamp has been saved.

[1190] Step 13:

[1191] The user opens the LINE app on their device and confirms that the generated original stamps are available.

[1192] The user sends an original stamp in a LINE chat and checks that it displays as intended.

[1193] The above are the specific processing steps for a user to select an image file, generate, modify, save, and finally use an original LINE stamp using the generative AI model.

[1194] Example 1

[1195] 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."

[1196] Conventional stamp generation systems require users to manually design stamps, which is time-consuming and labor-intensive. Furthermore, the quality of the generated stamps is inconsistent, and any corrections required can require additional work. Furthermore, applying user-specified customization elements is difficult, resulting in a lack of flexibility.

[1197] 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.

[1198] In this invention, the server includes: means for a user to select an image file from the device; means for the device to transmit the selected image file to a network server; means for the network server to receive the transmitted image file; means for the network server to provide the received image file to an image generation model and apply customization elements to generate an original stamp; means for the network server to transmit the generated original stamp to the device; means for the device to display the transmitted original stamp to the user and accept a modification request; means for the network server to transmit the modification request again to the image generation model and generate a modified original stamp; means for the network server to save the finally generated original stamp in the user's account; and means for the device to display the finally saved original stamp and make it available to the user within the communication platform. This enables users to easily generate and customize high-quality original stamps.

[1199] "User" refers to the entity that uses the system, an individual or organization that selects image files and gives instructions for customization.

[1200] "Device" refers to equipment operated by a user, such as a smartphone, tablet, or computer.

[1201] "Network Server" refers to a centralized management system for receiving and processing data sent from devices.

[1202] "Image File" refers to digital image data selected by a User and provided to the System.

[1203] "Image generation model" refers to algorithms and programs for generating new images based on input images.

[1204] "Customization Elements" refers to modifications or additions (e.g., changing the background, adding text) that are applied to the generated image based on the user's specifications.

[1205] "Custom Stamp" refers to a unique image generated based on the image and customization elements provided by the user.

[1206] "Communication platform" refers to a place where users can exchange messages with other users using original stamps they have created, and generally refers to a messaging application.

[1207] A "modification request" refers to an instruction from a user requesting changes or additions to an already generated original stamp.

[1208] "Account" means the ID and related information that enables a User to access the System and manage their personal data and settings.

[1209] The system of this invention allows users to select an image file from their device and then executes a series of processes to generate original stamps using a generative AI model. The elements of the system are as follows:

[1210] Hardware and Software

[1211] The system mainly consists of the following hardware and software:

[1212] 1. Device:

[1213] Smartphones, tablets, computers, etc. operated by users.

[1214] It has the function of sending image files to a network server.

[1215] 2. Network Server:

[1216] It receives and processes data sent from the device and sends the generated stamp back to the device.

[1217] It uses a generative AI model to analyze images and generate stamps.

[1218] 3. Generative AI Model:

[1219] Algorithms and programs for image generation, such as OpenAI's DALL-E and Stable Diffusion.

[1220] Operation of each element

[1221] This section explains how each element operates and what data processing and calculations are performed.

[1222] device

[1223] The user selects an image file using the device. The selected image file is sent to the network server using an HTTP request. The device has a storage device that temporarily stores data, and the data is temporarily saved before being sent.

[1224] Network Server

[1225] The network server receives the image file sent from the device and temporarily stores it in storage. It then calls the generative AI model to analyze the image. The analyzed data is used to generate a stamp by applying customization elements (changing the background, adding a message, etc.). The generated stamp image is then sent back to the device. If the user makes a modification request, the network server sends this modification request again to the generative AI model, which then generates a new stamp.

[1226] Specific examples

[1227] For example, below is a scenario in which a user creates original LINE stamps using a photo of their beloved dog.

[1228] 1. User selects a photo:

[1229] The user opens the gallery on their smartphone and selects a photo of their dog.

[1230] 2. The device sends the photo:

[1231] The user selects a photo of their dog and sends it to the server using an HTTP POST request.

[1232] 3. The network server analyzes the photo using the generated AI model:

[1233] The photos received by the server are temporarily saved in the " / tmp" directory, and a generative AI model (e.g., DALL-E) is called to analyze them.

[1234] 4. Generative AI model generates stamps:

[1235] For the analyzed photo, a stamp is generated by changing the background to a park and adding the message "Let's go for a walk."

[1236] 5. The network server sends the generated stamp to the device:

[1237] The generated stamp image is sent back to the device as an HTTP response.

[1238] 6. User checks stamp and requests correction:

[1239] The user checks the generated stamp and operates the device to request that the message be changed to "Let's play!"

[1240] 7. The network server generates the stamp again:

[1241] The server sends the correction request again to the image generation model to generate the corrected stamp.

[1242] Prompt Sentence Examples

[1243] Here are some examples of prompts based on user input:

[1244] Photo Analysis: Photos of your beloved dog

[1245] Change background: Park

[1246] Added message: "Let's go for a walk?"

[1247] By passing this prompt text to a generative AI model, an original stamp is generated based on the specified elements.

[1248] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1249] Step 1:

[1250] The user opens the device's gallery and selects the image file they want to use as an original stamp. When the user taps on the image in the smartphone's photo app to select it, the selected image file is saved in temporary storage on the device.

[1251] Input: An image file selected by the user from the gallery

[1252] Output: Image file saved to temporary storage on device

[1253] Step 2:

[1254] The device sends the selected image file to the network server using an HTTP POST request. The device uploads the selected image file to the server.

[1255] Input: Image file saved on device

[1256] Output: Image file sent to network server

[1257] Step 3:

[1258] The server receives the image file and temporarily stores it in storage. The server receives the HTTP request and stores the received image file in the " / tmp" directory.

[1259] Input: Image file sent from device to server

[1260] Output: Image file saved in temporary storage on the server

[1261] Step 4:

[1262] The server invokes the generative AI model and begins analyzing the received image file. The server uses a Python script to pass the image file to the generative AI model (e.g., DALL-E) for analysis.

[1263] Input: Image file saved in the " / tmp" directory

[1264] Output: Analysis results returned from the generative AI model

[1265] Step 5:

[1266] The generative AI model analyzes the characteristics of the image file and applies customization elements to generate original stamps. The generative AI model generates stamp images based on prompts such as "change the background to a park" and "add the text 'Let's go for a walk.'"

[1267] Input: Image file to be analyzed and prompt text containing customization elements

[1268] Output: Stamp image generated by the generative AI model

[1269] Step 6:

[1270] The server sends the generated original stamp to the device. The server returns the generated stamp image as an HTTP response, which is received by the device.

[1271] Input: Stamp image received from the generative AI model

[1272] Output: Stamp image sent to device

[1273] Step 7:

[1274] The user checks the generated original stamp and requests a correction. The user operates the device to request a correction to the stamp content (for example, to change the text to "Let's play!").

[1275] Input: Stamp image displayed on device

[1276] Output: Correction request entered by the user

[1277] Step 8:

[1278] The server sends the correction request to the image generation model again, and generates the corrected original stamp. Based on the correction request, the server passes the necessary parameters to the generation AI model again, and generates the corrected stamp.

[1279] Input: Correction request submitted by the user

[1280] Output: Stamp image generated after correction by the generative AI model

[1281] Step 9:

[1282] The server saves the final generated original stamp to the user's account. The server saves the modified stamp image to the database and assigns it to the user's account.

[1283] Input: Modified stamp image

[1284] Output: Final stamp image saved in the user's account

[1285] Step 10:

[1286] The device will then display the original stamps and make them available to the user within their communication platform. The device will then receive the final stamps and import them into messaging apps such as LINE, making them available for use.

[1287] Input: The final stamp image saved in the user's account

[1288] Output: Stamp image available within the communication platform

[1289] (Application example 1)

[1290] 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."

[1291] Conventional stamp generation systems allow users to easily create custom designs using their image files, but lack the functionality to apply the created designs to products and order them through e-commerce sites, making it difficult to quickly provide products with original designs.

[1292] 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.

[1293] In this invention, the server includes means for providing the received image file to a generative AI model and applying customization elements to generate an original design, means for sending the generated original design to the terminal, means for sending a modification request to the generative AI model again to generate a modified original design, and means for saving the final generated original design to the user's account and applying it to a product, thereby enabling users to easily generate custom designs using their own image files and order products based on those designs.

[1294] "User" means a person who uses the System to select image files, generate customized designs, and order products.

[1295] "Terminal" refers to a device operated by a user, such as a smartphone, tablet, or PC.

[1296] An "image file" is image data such as a photograph or illustration that is selected by the user from the terminal and sent to the server.

[1297] A "server" is a computer system that receives image files sent from a terminal via a network, processes the images using a generative AI model, and provides the final generated design to the user.

[1298] A "generative AI model" is an algorithm and program that analyzes the characteristics of a received image file and applies customization elements to generate an original design.

[1299] "Customization elements" are design items, such as changing the background or adding a message, that the generative AI model applies to the image file.

[1300] An "original design" is a design image with customization elements applied, generated by a generative AI model.

[1301] A "modification request" is a request for changes made by a user to the generated original design.

[1302] "Products" are items such as t-shirts, mugs, and phone cases with custom designs applied.

[1303] "E-commerce Site" means an online platform through which users can order products using the final generated Original Design.

[1304] This invention relates to an e-commerce system that allows users to create original designs using images uploaded by users and order them as custom products. Specifically, the system is implemented as follows using a server, a terminal, and a generative AI model.

[1305] First, the user selects an image file using their device. The selected image file is sent to the server via an HTTP request. The server temporarily stores the received image file in storage and provides it to the generative AI model. The generative AI model analyzes the image file's characteristics and applies customization elements (such as changing the background or adding a message) to generate an original design. This original design is returned to the server and then sent to the device.

[1306] The device displays the received original design to the user. If the user is not satisfied with the design, the device accepts a revision request. The accepted revision request is sent again to the server, and the server communicates the revision request to the generative AI model. The generative AI model generates a new design based on the revision request, and that design is sent again to the user's device via the server.

[1307] Finally, if the user is satisfied with the design, it is saved to the user's account and the original design is applied to custom merchandise (e.g., t-shirts, mugs, phone cases, etc.). At this stage, the user can order the product through the e-commerce site.

[1308] The system uses the following hardware and software:

[1309] Hardware: User devices (smartphones, tablets, PCs, etc.), servers

[1310] Software: Generative AI models, HTTP request processing, storage systems, e-commerce sites

[1311] For example:

[1312] When a user selects a photo of their dog using their device, the photo is sent to the server. The server provides the photo to a generative AI model, which then generates an original design with a park background and the message "Pochi" added. This design is then sent to the user for confirmation. If the user requests a change to the design, such as "I want the colors to be brighter," the generative AI model generates a new design and sends it back to the user. Finally, if the user is satisfied with the design, they can order products such as T-shirts and mugs using that design.

[1313] An example of a real prompt is:

[1314] "Please create the design shown on this T-shirt using a photo of your dog. Please use a park as the background and add the dog's name, 'Pochi.'"

[1315] This allows users to easily and quickly create custom designs and order custom products based on those designs.

[1316] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1317] Step 1:

[1318] The user selects an image file from their device. The user opens the image gallery on their smartphone, tablet, or computer and selects the image file they want to use for the customized design. The input is the image file selected by the user, and the output is that the image file is saved on the device.

[1319] Step 2:

[1320] The device sends the selected image file to the server. The device uploads the selected image file to the server using an HTTP request. The input is the selected image file, and the output is the image file sent to the server.

[1321] Step 3:

[1322] The server receives the image file. The server temporarily stores the uploaded image file in its storage area. The input is the image file sent from the device, and the output is the image file stored on the server.

[1323] Step 4:

[1324] The server provides the received image file to the generative AI model, which applies customization elements to generate an original design. The generative AI model analyzes the image file and applies the specified customization elements (for example, changing the background or adding a message). The input is the saved image file and the specified customization elements, and the output is the generated original design.

[1325] Step 5:

[1326] The server sends the generated original design to the terminal. The server sends the generated original design to the user's terminal as an HTTP response. The input is the generated original design, and the output is the original design provided to the terminal.

[1327] Step 6:

[1328] The terminal displays the original design sent to the user and accepts any modification requests. The user checks the displayed original design and inputs modification requests as necessary. The input is the original design displayed to the user and the user's modification requests, and the output is the modified design request.

[1329] Step 7:

[1330] The server sends the modification request back to the generative AI model, which generates a modified original design. The generative AI model accepts the modification request and generates a new design based on the specified changes. The inputs are the modification request and the existing original design, and the output is the modified original design.

[1331] Step 8:

[1332] The server stores the final generated original design in the user's account and applies it to the product. The server associates the final original design with the user's account and stores it, then applies the design to the specified product template. The input is the modified original design and the user's account information, and the output is the customized product.

[1333] Step 9:

[1334] The terminal displays the final saved original design and allows the user to place an order within the e-commerce site. The user checks the displayed custom product and confirms the order through the e-commerce site. The input is the product with the final original design applied, and the output is the order confirmed by the user.

[1335] 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.

[1336] This invention is a system that allows a user to select an image file from a device and generates original LINE stamps using a generative AI model and an emotion engine. Specific embodiments of the invention are described in detail below.

[1337] System configuration

[1338] The system mainly consists of the following components:

[1339] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[1340] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[1341] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[1342] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[1343] Processing flow

[1344] The following shows the process from when the user selects an image file to when an original stamp is generated using the emotion engine.

[1345] 1. User selects an image file

[1346] The user opens the device's gallery and selects the image file they want to use as an original stamp.

[1347] 2. The device sends the image file to the server

[1348] The terminal transmits the selected image file to the server.

[1349] The transmitted image file is temporarily stored in the device's storage and then uploaded to the server via an HTTP request.

[1350] 3. The server receives and analyzes the image file.

[1351] The server receives the image file and temporarily stores it in storage.

[1352] Set the parameters for the server to call the API for the generated AI model.

[1353] 4. The server analyzes the user's emotions

[1354] The server calls the emotion engine and analyzes multiple input data, including the user's voice, facial expressions, and text input.

[1355] The emotion engine detects the user's emotions (e.g., joy, sadness, surprise, etc.).

[1356] 5. Generative AI model generates stamps

[1357] The generative AI model analyzes the characteristics of the image file and, based on the analysis results of the emotion engine, applies customization elements (such as changing the background or adding an appropriate message) to generate original stamps.

[1358] The generated stamp image is returned to the server.

[1359] 6. The server sends the generated stamp to the device.

[1360] The server transmits the generated original stamp to the terminal.

[1361] The device receives the stamp image and displays it to the user.

[1362] 7. The user checks the stamp and requests corrections

[1363] The user checks the generated stamp image and specifies correction requests as necessary.

[1364] The revision requests include specific changes to the message or background.

[1365] 8. The server generates the stamp again

[1366] The server sends the correction request again to the API of the generation AI model, which generates the corrected stamp.

[1367] 9. The server saves the final stamp and notifies the device.

[1368] The server then stores the final generated stamp in the user's account.

[1369] A notification will be sent to the device when the save is complete, making the stamp immediately available to the user as a LINE stamp.

[1370] Specific examples

[1371] For example, a user can create original LINE stickers using a photo of their pet dog, leveraging the emotion engine.

[1372] 1. User selects a photo

[1373] Select a photo of your dog from your smartphone gallery.

[1374] 2. The device sends the photo

[1375] The selected photo is sent to the server.

[1376] 3. The server receives the photo and analyzes it with the generative AI model

[1377] The server receives the photo and provides it to the generative AI model to begin analysis.

[1378] 4. The server analyzes the user's emotions using an emotion engine

[1379] The emotion engine analyzes the user's facial expressions and voice data to detect "joy."

[1380] 5. Generative AI model generates stickers based on emotions

[1381] Based on the emotion analysis result of "joy," a stamp was generated with the background changed to a sunny park and the message "I'm happy!" added.

[1382] 6. The server sends the stamp to the device

[1383] The generated stamp is sent to the terminal and displayed to the user.

[1384] 7. The user checks the stamp and requests corrections

[1385] The user requests that the message be changed to "Let's play!"

[1386] 8. The server generates the stamp again

[1387] The server then has the AI ​​model generate stamps again based on the correction request.

[1388] 9. The server saves the final stamp and notifies the device.

[1389] The modified stamps will be saved to the user's LINE account and made available for use.

[1390] In this way, a system that utilizes an emotion engine can quickly create original stamps that reflect the user's emotions, enabling more personalized communication.

[1391] The processing flow will be explained below.

[1392] Step 1:

[1393] The user opens the device's gallery.

[1394] The user selects the image file they want to use as an original stamp.

[1395] The device temporarily saves the selected image file.

[1396] Step 2:

[1397] The terminal creates a request to notify the server that the image file selection has been completed.

[1398] The terminal sends the selected image file to the server in the form of an HTTP request.

[1399] Verify that the server received the request.

[1400] Step 3:

[1401] The server temporarily stores the received image file in storage.

[1402] Set the parameters for the server to call the API for the generated AI model.

[1403] The server provides the image file to the generative AI model and begins analysis.

[1404] Step 4:

[1405] The server calls the emotion engine and prepares to analyze the user's emotions.

[1406] The user provides data such as voice, facial expressions, and text input through the device.

[1407] The device collects this data and sends it to the server.

[1408] Step 5:

[1409] The server provides the data sent to the emotion engine and analyzes the user's emotions.

[1410] The emotion engine detects the user's emotions (e.g., "happiness," "sadness," "surprise," etc.).

[1411] Step 6:

[1412] Based on the image features analyzed by the generative AI model and the analysis results of the emotion engine, customization elements (such as changing the background or adding an appropriate message) are applied to generate original stamps.

[1413] The generated stamp image is returned to the server.

[1414] Step 7:

[1415] The server temporarily stores the generated original stamp.

[1416] The server creates a request to send the stamp image to the terminal.

[1417] Step 8:

[1418] The terminal displays the stamp image received from the server to the user.

[1419] The user checks the stamp and specifies correction requests as necessary.

[1420] Step 9:

[1421] The terminal receives the user's modification request and creates a request to send to the server.

[1422] The terminal sends a modification request to the server.

[1423] Step 10:

[1424] The server receives the correction request and sets the parameters to call the API for the generated AI model again.

[1425] Based on the modification request, the server sends the image file and customization elements to the generative AI model.

[1426] Step 11:

[1427] The generative AI model recreates the original stamp reflecting the requested modifications.

[1428] The generative AI model returns the corrected stamp image to the server.

[1429] Step 12:

[1430] The server temporarily stores the returned corrected stamp image.

[1431] The server starts the process of saving the final generated original stamp to the user's account.

[1432] Step 13:

[1433] The server creates a request to notify the terminal that the stamp saving process has been completed.

[1434] The device receives a notification from the server and displays to the user that the final stamp has been saved.

[1435] Step 14:

[1436] The user opens the LINE app on their device and confirms that the generated original stamps are available.

[1437] The user sends an original stamp in a LINE chat and checks that it displays as intended.

[1438] The above are the specific processing steps that allow users to select an image file, and then use the emotion engine and generative AI model to generate, modify, save, and ultimately use original LINE stamps.

[1439] Example 2

[1440] 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."

[1441] Conventional stamp generation systems have had difficulty in quickly and efficiently generating personalized stamps that reflect the user's emotions. Furthermore, they lacked the means to flexibly accommodate requests for corrections to generated stamps. This has led to the problem that it is difficult for users to create original stamps that satisfy them.

[1442] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a transmitted image file and temporarily storing it in storage, means for analyzing the user's emotions using an emotion engine, and means for providing the received image file to a generative AI model and applying customization elements based on the emotion analysis result to generate an original stamp. This makes it possible to quickly generate a personalized original stamp that reflects the user's emotions.

[1443] "User" refers to a general user who operates a terminal to select an image file or request a stamp modification.

[1444] "Terminal" refers to a device operated by a user, such as a smartphone, tablet, or PC.

[1445] "Image file" refers to the digital image data that the user selects from the device and that is the basis for generating the stamp.

[1446] The term "server" refers to a computer system that receives data sent from a terminal via a network and performs image processing and stamp generation.

[1447] "Generative AI model" refers to the algorithms and programs used to generate original stamps based on received image files.

[1448] "Emotion engine" refers to algorithms and programs for analyzing user emotions.

[1449] "Customization Elements" refers to customization elements applied to a sticker by a generative AI model, such as changing the background or adding a text message.

[1450] "Original stamp" refers to a stamp image to which customization elements have been applied by a generative AI model.

[1451] "Modification Request" means a request for change submitted by a User to a Generated Stamp.

[1452] "Communication platform" refers to applications and services that allow users to communicate with other users using original stamps.

[1453] This invention is a system in which a user selects an image file from a terminal and generates an original stamp image using a generative AI model and an emotion engine. Specific embodiments for implementing this invention are described below.

[1454] The system mainly consists of the following components:

[1455] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[1456] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[1457] 3. Generative AI Model - Algorithms and programs for generating stamp images based on received images.

[1458] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[1459] System Operation Overview

[1460] The user selects an image file on the device

[1461] The user selects the image they want to use as the original stamp from the image gallery or file manager on their device. For example, the user opens the gallery app on their smartphone and selects a photo of their pet dog.

[1462] The device sends the image file to the server

[1463] The device sends the selected image file to the server using an HTTP request. At this time, the image file is temporarily stored in the device's storage. Specifically, the device uploads the selected photo of the pet dog to the server using an HTTP POST request.

[1464] The server receives and analyzes the image file.

[1465] The server receives the image file and temporarily stores it in storage. Then, the server sets parameters to call the API of the generative AI model. For example, the server stores a photo of your dog in the image_input variable and prepares it for analysis.

[1466] The server analyzes the user's emotions

[1467] The server calls the emotion engine and analyzes the user's facial expressions, voice, text input, etc. The emotion engine detects the user's emotions and identifies emotion categories such as "happiness," "sadness," and "surprise." As a specific example, the emotion engine analyzes the user's happy facial expression and detects the emotion "happiness."

[1468] Generative AI model generates stamps

[1469] The generative AI model analyzes the characteristics of an image file and applies customization elements such as changing the background and adding a text message based on the results of the emotion analysis to generate original stamps. For example, the generative AI model analyzes a photo of a pet dog, changes the background to a sunny park, and creates a stamp with the message "I'm happy!"

[1470] The server sends the generated stamp to the terminal.

[1471] The server sends the generated original stamp to the device. The device receives the stamp image and displays it to the user. Specifically, the server sends the generated stamp to the device via an HTTP response, and it is displayed in the gallery or within the app on the user's device.

[1472] The user checks the stamp and requests corrections.

[1473] The user checks the generated stamp image and requests corrections if necessary. This correction request includes specific changes. For example, the user requests that the message "I'm happy!" be changed to "Let's play!"

[1474] The server generates the stamp again

[1475] The server sends the correction request again to the generative AI model to generate the corrected stamp. The server sends a new prompt containing the corrections to the generative AI model to obtain a new stamp.

[1476] The server saves the final stamp and notifies the device

[1477] The server saves the final generated stickers to the user's account, then sends a save completion notification to the device, allowing the user to immediately use the stickers within communication platforms such as the LINE app. For example, by saving new stickers to a database and sending a save completion notification to the device, the user can use the new stickers on LINE.

[1478] Specific examples

[1479] The process for users to create original LINE stickers using photos of their pet dogs is as follows:

[1480] 1. The user opens the gallery app on their smartphone and selects a photo of their dog.

[1481] 2. The device sends the selected photo of the dog to the server via an HTTP request.

[1482] 3. The server receives the photo and provides it to the generative AI model to begin analysis.

[1483] 4. Use an emotion engine to analyze the user's facial expression data and detect "happiness."

[1484] 5. Based on the emotion analysis result of "joy," the generative AI model changes the background to a sunny park and generates a stamp with the message "I'm so happy!" added.

[1485] 6. The server sends the generated stamp to the device and displays it to the user.

[1486] 7. The user requests that the "Happy!" message be changed to "Let's play!"

[1487] 8. The server sends the correction request to the generative AI model to generate the corrected stamp.

[1488] 9. The modified stamps are saved to the user's LINE account and made available for use.

[1489] Prompt Sentence Examples

[1490] Create an original stamp based on the user's emotion "joy" using a photo of your dog. Change the background to a sunny park and add the message "I'm so happy!"

[1491] In this way, it becomes possible to quickly generate personalized original stamps that reflect the user's emotions.

[1492] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1493] Step 1:

[1494] The user selects an image file on the device.

[1495] Input: The user operates the image gallery or file manager on the device and specifies the image file they want to use as a stamp.

[1496] What happens: The user opens the gallery app on their smartphone and selects a photo of their dog.

[1497] Output: The path or URL of the selected image file is retrieved.

[1498] Step 2:

[1499] The device sends the image file to the server.

[1500] Input: The path or URL of the image file obtained in step 1.

[1501] Specific operation: The device uploads the selected image file to the server using an HTTP POST request.

[1502] Output: The server receives the image file and it is temporarily saved in storage.

[1503] Step 3:

[1504] The server receives the image file and prepares it for analysis.

[1505] Input: The image file uploaded in step 2.

[1506] Specific operation: The server temporarily saves the image file in storage and sets parameters for analysis. For example, it saves the image file in the image_input variable.

[1507] Output: Image data ready for analysis.

[1508] Step 4:

[1509] The server analyzes the user's emotions.

[1510] Input: Emotional data such as user facial expressions, voice, and text input.

[1511] Specific operation: This data is sent to the emotion engine to perform emotion analysis. For example, the emotion engine analyzes the user's facial expression data and detects the emotion "joy."

[1512] Output: Sentiment analysis result (e.g. "Happy", "Sad", "Surprise", etc.).

[1513] Step 5:

[1514] The server generates stamps using a generative AI model.

[1515] Input: The image data prepared in step 3 and the sentiment analysis results obtained in step 4.

[1516] How it works: The generative AI model analyzes the characteristics of an image file and applies customization elements such as changing the background or adding a message based on the results of emotion analysis. For example, based on the emotion of "joy," the generative AI model generates a stamp that changes the background to a sunny park and adds the message "I'm so happy!"

[1517] Output: Customized original stamp image.

[1518] Step 6:

[1519] The server sends the generated stamp to the terminal.

[1520] Input: The original stamp image generated in step 5.

[1521] Specific operation: The server sends the generated stamp to the terminal in an HTTP response.

[1522] Output: The device receives the stamp image and displays it to the user.

[1523] Step 7:

[1524] The user checks the stamp and requests corrections.

[1525] Input: The original stamp image shown to the user in step 6.

[1526] Specific behavior: The user checks the stamp and, if necessary, requests corrections through the application interface. For example, the user requests that the message "I'm happy!" be changed to "Let's play!"

[1527] Output: User requested corrections.

[1528] Step 8:

[1529] The server generates the stamp again.

[1530] Input: The correction request provided by the user in step 7.

[1531] Specific operation: The server sends a correction request to the generative AI model again, and sends a new prompt sentence to the generative AI model to generate a corrected stamp.

[1532] Output: The original stamp image after modification.

[1533] Step 9:

[1534] The server saves the final stamp and notifies the terminal.

[1535] Input: The modified original stamp image generated in step 8.

[1536] Specific operation: The server saves the modified stamp in the database and sends a save completion notification to the terminal.

[1537] Output: The modified stickers are saved to the user's LINE account, and a notification is sent to the user's device. The user can then use the stickers in the LINE app.

[1538] (Application example 2)

[1539] 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."

[1540] In the conventional LINE sticker generation system, the process for users to generate sticker images was limited, making it difficult to generate stickers in real time or use them in stores. Furthermore, stickers were not generated to reflect the user's emotions, making it difficult to realize personalized communication. Furthermore, the process of generating and modifying stickers was complicated, resulting in a poor user experience.

[1541] 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.

[1542] In this invention, the server includes means for receiving an image file selected by a user and providing it to a generative AI model to generate an original stamp, means for sending the generated original stamp to a terminal, means including an emotion engine that analyzes the user's emotions and reflects them in the stamp generation, and means for generating the stamp again using the generative AI model based on a correction request. This enables users to generate original stamps in real time at physical stores and share them on social media on the spot.

[1543] A "terminal" is a device operated by a user, such as a smartphone, tablet, or personal computer.

[1544] A "server" is a computer system that receives and processes data sent from a terminal via a network.

[1545] A "generative AI model" is a collection of algorithms and programs for generating customized stamp images based on image files and other data received from users.

[1546] "Customization elements" are additional elements or modifications that are applied to the generated stamp image, such as changing the background or adding a message.

[1547] An "emotion engine" is a collection of algorithms and programs that analyze a user's voice, facial expressions, text input, etc. to detect the user's emotions.

[1548] "Original Stamps" are individually customized stamp images created by a generative AI model that users can use on communication platforms.

[1549] A "communication platform" is an online service that enables users to send and receive messages using stamps, such as LINE or other SNS.

[1550] A "physical store" is a physical location, such as a commercial facility or retail outlet, that a user can visit.

[1551] "Real time" is a time characteristic that refers to immediate results being obtained the moment an operation or event occurs.

[1552] A "modification request" is a request made by a user to make changes or improvements to a generated stamp.

[1553] This invention provides a system that allows users to create original LINE stamps in real time in physical stores. The system consists of elements such as a smartphone, a server, a generative AI model, and an emotion engine.

[1554] System configuration

[1555] The system consists of the following components:

[1556] 1. Terminal - A device operated by a user, such as a smartphone or tablet.

[1557] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[1558] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[1559] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[1560] Explanation of program processing

[1561] 1. Select and send image files:

[1562] The user operates the smartphone application and selects an image file from the gallery, and the selected image is sent to the server via an HTTP request.

[1563] 2. Data Receipt and Analysis:

[1564] The server receives the image file and temporarily stores it in storage, then calls the API of the generative AI model to begin analyzing the image.

[1565] 3. Emotion Analysis:

[1566] The server uses an emotion engine to analyze the user's emotions, using data such as facial expressions, voice, and text input. For example, emotions such as "happiness" or "surprise" can be detected.

[1567] 4. Stamp generation:

[1568] The generative AI model analyzes the image features and applies customization elements (such as changing the background or adding a message) based on the detected emotion to generate an original stamp. The generated stamp image is then returned to the server.

[1569] 5. Sending and viewing stamps:

[1570] The server sends the generated original stamp to the smartphone and displays it to the user, who can then check the stamp and make correction requests.

[1571] 6. Processing Amendment Requests:

[1572] If the user makes a correction request, the request is sent again to the generative AI model, and a new stamp is generated.

[1573] 7. Save and share your final stamp:

[1574] The server then saves the final stamps to the user's account, allowing the user to instantly share them on social media and other communication platforms.

[1575] Specific examples

[1576] The video shows a user visiting a physical store creating original LINE stamps using photos taken with their smartphone.

[1577] 1. User selects a photo:

[1578] Select a photo taken at a photo spot within the store from your smartphone gallery.

[1579] 2. The device sends the photo:

[1580] The selected photo is sent to the server.

[1581] 3. The server analyzes the photo:

[1582] The server receives the photo and begins analyzing it using the generative AI model.

[1583] 4. Emotion Analysis:

[1584] The emotion engine detects the user's "joy" from the photo.

[1585] 5. Stamp generation:

[1586] Based on the emotion of "joy," a stamp was generated with the background changed to a sunny park and the message "I'm so happy!" added.

[1587] 6. Viewing and Modifying Stamps:

[1588] The generated stamp is displayed on the smartphone. The user requests to change the message to "Let's play!"

[1589] 7. Generate and display correction stamps:

[1590] The message is then regenerated by the AI ​​model and the revised stamp is displayed.

[1591] 8. Save and share your final stamp:

[1592] The final stamp will be saved in the user's account and can be shared on LINE and other platforms.

[1593] Prompt Sentence Examples

[1594] "Please create LINE stamps that express joy using photos of smiling customers visiting your store with their friends."

[1595] The system will improve the customer experience in physical stores and enable personalized communication.

[1596] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1597] Step 1:

[1598] A user operates a smartphone application and selects an image file from the gallery. The input here is the image file selected by the user, and the output is the data of the selected image file.

[1599] Step 2:

[1600] The terminal sends the data of the selected image file to the server via an HTTP request. The input is the image file data obtained in step 1, and the output is the image file data sent to the server.

[1601] Step 3:

[1602] The server receives the image file and temporarily stores it in storage. The image file data stored in the server's storage is input data, and the output is temporary data stored on the server.

[1603] Step 4:

[1604] The server calls the API of the generative AI model and analyzes the data of the saved image file. The input is the data of the saved image file, and the output is data that analyzes the image features. In this step, the server extracts the features of the image file.

[1605] Step 5:

[1606] The server analyzes the user's emotions using an emotion engine. The input is the image file and additional user data (e.g., voice, facial expressions, etc.), and the output is the analyzed emotion data. In this step, the server classifies the user's emotions into categories such as "happiness" or "surprise."

[1607] Step 6:

[1608] The server uses a generative AI model to apply customization elements based on the analyzed emotion data and the features of the image file, generating an original stamp. The input is the image feature data and emotion data, and the output is the generated original stamp image. In this step, processing such as changing the background and adding text is performed.

[1609] Step 7:

[1610] The server sends the generated original stamp to the terminal. The input is the image of the generated original stamp, and the output is the stamp image sent to the terminal.

[1611] Step 8:

[1612] The terminal displays the generated original stamp to the user and accepts modification requests. The input is the stamp image sent from the server, and the output is the stamp image that the user sees on the screen and modification request data. The user can request changes to the stamp content.

[1613] Step 9:

[1614] The server sends the correction request to the generative AI model again to generate a corrected original stamp. The input is the correction request data, and the output is the corrected stamp image. The server again instructs the generative AI model to generate a new stamp image.

[1615] Step 10:

[1616] The server saves the final generated stamp in the user's account. The input is the modified original stamp image, and the output is the stamp image saved in the user's account.

[1617] Step 11:

[1618] The device finally displays the saved original stamp and makes it available to the user within the communication platform. The input is the saved stamp image, and the output is the stamp image displayed on the user's device. The user can share this image on LINE or other SNS.

[1619] 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.

[1620] 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.

[1621] 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.

[1622] [Fourth embodiment]

[1623] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1624] 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.

[1625] 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).

[1626] 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.

[1627] 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.

[1628] 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).

[1629] 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.

[1630] 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.

[1631] 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.

[1632] 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.

[1633] 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.

[1634] 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.

[1635] 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."

[1636] This invention is a system that allows users to select image files from their devices and generate original LINE stamps using a generative AI model. Specific embodiments of the invention are described in detail below.

[1637] System configuration

[1638] The system mainly consists of the following components:

[1639] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[1640] 2. Server - Receives data sent from the device via the network and processes the images using generative AI models.

[1641] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[1642] Processing flow

[1643] The following shows the process from when the user selects an image file to when an original stamp is generated.

[1644] 1. User selects an image file

[1645] The user opens the device's gallery and selects the image they want to use as an original stamp.

[1646] 2. The device sends the image file to the server

[1647] The terminal transmits the selected image file to the server.

[1648] The transmitted image file is temporarily stored in the device's storage and then uploaded to the server via an HTTP request.

[1649] 3. The server receives and analyzes the image file.

[1650] The server receives the image file and temporarily stores it in storage.

[1651] The server calls the generated AI model and begins image analysis.

[1652] 4. Generative AI model generates stamps

[1653] The generative AI model analyzes the characteristics of the image file and applies the customization elements you set (changing the background, adding a message, etc.) to generate an original stamp.

[1654] The generated stamp image is returned to the server.

[1655] 5. The server sends the generated stamp to the device.

[1656] The server transmits the generated original stamp to the terminal.

[1657] The device receives the stamp image and displays it to the user.

[1658] 6. The user checks the stamp and requests corrections

[1659] The user checks the generated stamp image and specifies correction requests as necessary.

[1660] The revision requests include specific changes to the message or background.

[1661] 7. The server generates the stamp again

[1662] The server sends the correction request again to the generation AI model, which generates the corrected stamp.

[1663] 8. The server saves the final stamp and notifies the device.

[1664] The server then stores the final generated stamp in the user's account.

[1665] A notification will be sent to the device when the save is complete, making the stamp immediately available to the user as a LINE stamp.

[1666] Specific examples

[1667] For example, let's say a user creates an original LINE stamp using a photo of their beloved dog.

[1668] 1. User selects a photo

[1669] Select a photo of your dog from your smartphone gallery.

[1670] 2. The device sends the photo

[1671] The selected photo is sent to the server.

[1672] 3. The server receives the photo and analyzes it with the generative AI model

[1673] The server receives the photo and provides it to the generative AI model to begin analysis.

[1674] 4. Generative AI model generates stamps

[1675] After analyzing the photo, a stamp was generated with the background changed to a park and the message "Let's go for a walk" added.

[1676] 5. The server sends the stamp to the device.

[1677] The generated stamp is sent to the terminal and displayed to the user.

[1678] 6. The user checks the stamp and requests corrections

[1679] The user requests that the message be changed to "Let's play!"

[1680] 7. The server generates the stamp again

[1681] The server then has the AI ​​model generate stamps again based on the correction request.

[1682] 8. The server saves the final stamp and notifies the device.

[1683] The modified stamps will be saved to the user's LINE account and made available for use.

[1684] In this way, users can quickly create original LINE stamps using images stored on their smartphones and use them instantly, significantly reducing the time and effort required for creating stamps and increasing the number of ways stamps can be used.

[1685] The processing flow will be explained below.

[1686] Step 1:

[1687] The user opens the device's gallery.

[1688] The user selects the image file they want to use as an original stamp.

[1689] The device temporarily saves the selected image file.

[1690] Step 2:

[1691] The terminal creates a request to notify the server that the image file selection has been completed.

[1692] The terminal sends the selected image file to the server in the form of an HTTP request.

[1693] Verify that the server received the request.

[1694] Step 3:

[1695] The server temporarily stores the received image file in storage.

[1696] Set the parameters for the server to call the API for the generated AI model.

[1697] Step 4:

[1698] The server sends the image file as input data to the generative AI model.

[1699] A generative AI model analyzes image files and extracts features.

[1700] Step 5:

[1701] The generative AI model applies the specified customization elements (changing the background, adding a message, etc.) to generate original stamps.

[1702] The stamp image generated by the generative AI model is returned to the server.

[1703] Step 6:

[1704] The server receives the returned stamp image and temporarily stores it.

[1705] The server creates a request to send the generated original stamp to the terminal.

[1706] Step 7:

[1707] The terminal displays the stamp image received from the server to the user.

[1708] The user reviews the stamp and requests corrections if necessary.

[1709] Step 8:

[1710] The device receives the user's modification request and creates a request to send to the server.

[1711] The terminal sends a modification request to the server.

[1712] Step 9:

[1713] The server receives the correction request and sets the parameters to call the API for the generated AI model again.

[1714] Based on the modification request, the server sends the image file and customization elements to the generative AI model.

[1715] Step 10:

[1716] The generative AI model recreates the original stamp reflecting the requested modifications.

[1717] The generative AI model returns the corrected stamp image to the server.

[1718] Step 11:

[1719] The server receives the corrected stamp image and temporarily stores it again.

[1720] The server initiates the process to store the final generated original stamp in the user's account.

[1721] Step 12:

[1722] The server creates a request to notify the terminal that the stamp saving process has been completed.

[1723] The device receives a notification from the server and displays to the user that the final stamp has been saved.

[1724] Step 13:

[1725] The user opens the LINE app on their device and confirms that the generated original stamps are available.

[1726] The user sends an original stamp in a LINE chat and checks that it displays as intended.

[1727] The above are the specific processing steps for a user to select an image file, generate, modify, save, and finally use an original LINE stamp using the generative AI model.

[1728] Example 1

[1729] 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."

[1730] Conventional stamp generation systems require users to manually design stamps, which is time-consuming and labor-intensive. Furthermore, the quality of the generated stamps is inconsistent, and any corrections required can require additional work. Furthermore, applying user-specified customization elements is difficult, resulting in a lack of flexibility.

[1731] 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.

[1732] In this invention, the server includes: means for a user to select an image file from the device; means for the device to transmit the selected image file to a network server; means for the network server to receive the transmitted image file; means for the network server to provide the received image file to an image generation model and apply customization elements to generate an original stamp; means for the network server to transmit the generated original stamp to the device; means for the device to display the transmitted original stamp to the user and accept a modification request; means for the network server to transmit the modification request again to the image generation model and generate a modified original stamp; means for the network server to save the finally generated original stamp in the user's account; and means for the device to display the finally saved original stamp and make it available to the user within the communication platform. This enables users to easily generate and customize high-quality original stamps.

[1733] "User" refers to the entity that uses the system, an individual or organization that selects image files and gives instructions for customization.

[1734] "Device" refers to equipment operated by a user, such as a smartphone, tablet, or computer.

[1735] "Network Server" refers to a centralized management system for receiving and processing data sent from devices.

[1736] "Image File" refers to digital image data selected by a User and provided to the System.

[1737] "Image generation model" refers to algorithms and programs for generating new images based on input images.

[1738] "Customization Elements" refers to modifications or additions (e.g., changing the background, adding text) that are applied to the generated image based on the user's specifications.

[1739] "Custom Stamp" refers to a unique image generated based on the image and customization elements provided by the user.

[1740] "Communication platform" refers to a place where users can exchange messages with other users using original stamps they have created, and generally refers to a messaging application.

[1741] A "modification request" refers to an instruction from a user requesting changes or additions to an already generated original stamp.

[1742] "Account" means the ID and related information that enables a User to access the System and manage their personal data and settings.

[1743] The system of this invention allows users to select an image file from their device and then executes a series of processes to generate original stamps using a generative AI model. The elements of the system are as follows:

[1744] Hardware and Software

[1745] The system mainly consists of the following hardware and software:

[1746] 1. Device:

[1747] Smartphones, tablets, computers, etc. operated by users.

[1748] It has the function of sending image files to a network server.

[1749] 2. Network Server:

[1750] It receives and processes data sent from the device and sends the generated stamp back to the device.

[1751] It uses a generative AI model to analyze images and generate stamps.

[1752] 3. Generative AI Model:

[1753] Algorithms and programs for image generation, such as OpenAI's DALL-E and Stable Diffusion.

[1754] Operation of each element

[1755] This section explains how each element operates and what data processing and calculations are performed.

[1756] device

[1757] The user selects an image file using the device. The selected image file is sent to the network server using an HTTP request. The device has a storage device that temporarily stores data, and the data is temporarily saved before being sent.

[1758] Network Server

[1759] The network server receives the image file sent from the device and temporarily stores it in storage. It then calls the generative AI model to analyze the image. The analyzed data is used to generate a stamp by applying customization elements (changing the background, adding a message, etc.). The generated stamp image is then sent back to the device. If the user makes a modification request, the network server sends this modification request again to the generative AI model, which then generates a new stamp.

[1760] Specific examples

[1761] For example, below is a scenario in which a user creates original LINE stamps using a photo of their beloved dog.

[1762] 1. User selects a photo:

[1763] The user opens the gallery on their smartphone and selects a photo of their dog.

[1764] 2. The device sends the photo:

[1765] The user selects a photo of their dog and sends it to the server using an HTTP POST request.

[1766] 3. The network server analyzes the photo using the generated AI model:

[1767] The photos received by the server are temporarily saved in the " / tmp" directory, and a generative AI model (e.g., DALL-E) is called to analyze them.

[1768] 4. Generative AI model generates stamps:

[1769] For the analyzed photo, a stamp is generated by changing the background to a park and adding the message "Let's go for a walk."

[1770] 5. The network server sends the generated stamp to the device:

[1771] The generated stamp image is sent back to the device as an HTTP response.

[1772] 6. User checks stamp and requests correction:

[1773] The user checks the generated stamp and operates the device to request that the message be changed to "Let's play!"

[1774] 7. The network server generates the stamp again:

[1775] The server sends the correction request again to the image generation model to generate the corrected stamp.

[1776] Prompt Sentence Examples

[1777] Here are some examples of prompts based on user input:

[1778] Photo Analysis: Photos of your beloved dog

[1779] Change background: Park

[1780] Added message: "Let's go for a walk?"

[1781] By passing this prompt text to a generative AI model, an original stamp is generated based on the specified elements.

[1782] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1783] Step 1:

[1784] The user opens the device's gallery and selects the image file they want to use as an original stamp. When the user taps on the image in the smartphone's photo app to select it, the selected image file is saved in temporary storage on the device.

[1785] Input: An image file selected by the user from the gallery

[1786] Output: Image file saved to temporary storage on device

[1787] Step 2:

[1788] The device sends the selected image file to the network server using an HTTP POST request. The device uploads the selected image file to the server.

[1789] Input: Image file saved on device

[1790] Output: Image file sent to network server

[1791] Step 3:

[1792] The server receives the image file and temporarily stores it in storage. The server receives the HTTP request and stores the received image file in the " / tmp" directory.

[1793] Input: Image file sent from device to server

[1794] Output: Image file saved in temporary storage on the server

[1795] Step 4:

[1796] The server invokes the generative AI model and begins analyzing the received image file. The server uses a Python script to pass the image file to the generative AI model (e.g., DALL-E) for analysis.

[1797] Input: Image file saved in the " / tmp" directory

[1798] Output: Analysis results returned from the generative AI model

[1799] Step 5:

[1800] The generative AI model analyzes the characteristics of the image file and applies customization elements to generate original stamps. The generative AI model generates stamp images based on prompts such as "change the background to a park" and "add the text 'Let's go for a walk.'"

[1801] Input: Image file to be analyzed and prompt text containing customization elements

[1802] Output: Stamp image generated by the generative AI model

[1803] Step 6:

[1804] The server sends the generated original stamp to the device. The server returns the generated stamp image as an HTTP response, which is received by the device.

[1805] Input: Stamp image received from the generative AI model

[1806] Output: Stamp image sent to device

[1807] Step 7:

[1808] The user checks the generated original stamp and requests a correction. The user operates the device to request a correction to the stamp content (for example, to change the text to "Let's play!").

[1809] Input: Stamp image displayed on device

[1810] Output: Correction request entered by the user

[1811] Step 8:

[1812] The server sends the correction request to the image generation model again, and generates the corrected original stamp. Based on the correction request, the server passes the necessary parameters to the generation AI model again, and generates the corrected stamp.

[1813] Input: Correction request submitted by the user

[1814] Output: Stamp image generated after correction by the generative AI model

[1815] Step 9:

[1816] The server saves the final generated original stamp to the user's account. The server saves the modified stamp image to the database and assigns it to the user's account.

[1817] Input: Modified stamp image

[1818] Output: Final stamp image saved in the user's account

[1819] Step 10:

[1820] The device will then display the original stamps and make them available to the user within their communication platform. The device will then receive the final stamps and import them into messaging apps such as LINE, making them available for use.

[1821] Input: The final stamp image saved in the user's account

[1822] Output: Stamp image available within the communication platform

[1823] (Application example 1)

[1824] 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."

[1825] Conventional stamp generation systems allow users to easily create custom designs using their image files, but lack the functionality to apply the created designs to products and order them through e-commerce sites, making it difficult to quickly provide products with original designs.

[1826] 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.

[1827] In this invention, the server includes means for providing the received image file to a generative AI model and applying customization elements to generate an original design, means for sending the generated original design to the terminal, means for sending a modification request to the generative AI model again to generate a modified original design, and means for saving the final generated original design to the user's account and applying it to a product, thereby enabling users to easily generate custom designs using their own image files and order products based on those designs.

[1828] "User" means a person who uses the System to select image files, generate customized designs, and order products.

[1829] "Terminal" refers to a device operated by a user, such as a smartphone, tablet, or PC.

[1830] An "image file" is image data such as a photograph or illustration that is selected by the user from the terminal and sent to the server.

[1831] A "server" is a computer system that receives image files sent from a terminal via a network, processes the images using a generative AI model, and provides the final generated design to the user.

[1832] A "generative AI model" is an algorithm and program that analyzes the characteristics of a received image file and applies customization elements to generate an original design.

[1833] "Customization elements" are design items, such as changing the background or adding a message, that the generative AI model applies to the image file.

[1834] An "original design" is a design image with customization elements applied, generated by a generative AI model.

[1835] A "modification request" is a request for changes made by a user to the generated original design.

[1836] "Products" are items such as t-shirts, mugs, and phone cases with custom designs applied.

[1837] "E-commerce Site" means an online platform through which users can order products using the final generated Original Design.

[1838] This invention relates to an e-commerce system that allows users to create original designs using images uploaded by users and order them as custom products. Specifically, the system is implemented as follows using a server, a terminal, and a generative AI model.

[1839] First, the user selects an image file using their device. The selected image file is sent to the server via an HTTP request. The server temporarily stores the received image file in storage and provides it to the generative AI model. The generative AI model analyzes the image file's characteristics and applies customization elements (such as changing the background or adding a message) to generate an original design. This original design is returned to the server and then sent to the device.

[1840] The device displays the received original design to the user. If the user is not satisfied with the design, the device accepts a revision request. The accepted revision request is sent again to the server, and the server communicates the revision request to the generative AI model. The generative AI model generates a new design based on the revision request, and that design is sent again to the user's device via the server.

[1841] Finally, if the user is satisfied with the design, it is saved to the user's account and the original design is applied to custom merchandise (e.g., t-shirts, mugs, phone cases, etc.). At this stage, the user can order the product through the e-commerce site.

[1842] The system uses the following hardware and software:

[1843] Hardware: User devices (smartphones, tablets, PCs, etc.), servers

[1844] Software: Generative AI models, HTTP request processing, storage systems, e-commerce sites

[1845] For example:

[1846] When a user selects a photo of their dog using their device, the photo is sent to the server. The server provides the photo to a generative AI model, which then generates an original design with a park background and the message "Pochi" added. This design is then sent to the user for confirmation. If the user requests a change to the design, such as "I want the colors to be brighter," the generative AI model generates a new design and sends it back to the user. Finally, if the user is satisfied with the design, they can order products such as T-shirts and mugs using that design.

[1847] An example of a real prompt is:

[1848] "Please create the design shown on this T-shirt using a photo of your dog. Please use a park as the background and add the dog's name, 'Pochi.'"

[1849] This allows users to easily and quickly create custom designs and order custom products based on those designs.

[1850] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1851] Step 1:

[1852] The user selects an image file from their device. The user opens the image gallery on their smartphone, tablet, or computer and selects the image file they want to use for the customized design. The input is the image file selected by the user, and the output is that the image file is saved on the device.

[1853] Step 2:

[1854] The device sends the selected image file to the server. The device uploads the selected image file to the server using an HTTP request. The input is the selected image file, and the output is the image file sent to the server.

[1855] Step 3:

[1856] The server receives the image file. The server temporarily stores the uploaded image file in its storage area. The input is the image file sent from the device, and the output is the image file stored on the server.

[1857] Step 4:

[1858] The server provides the received image file to the generative AI model, which applies customization elements to generate an original design. The generative AI model analyzes the image file and applies the specified customization elements (for example, changing the background or adding a message). The input is the saved image file and the specified customization elements, and the output is the generated original design.

[1859] Step 5:

[1860] The server sends the generated original design to the terminal. The server sends the generated original design to the user's terminal as an HTTP response. The input is the generated original design, and the output is the original design provided to the terminal.

[1861] Step 6:

[1862] The terminal displays the original design sent to the user and accepts any modification requests. The user checks the displayed original design and inputs modification requests as necessary. The input is the original design displayed to the user and the user's modification requests, and the output is the modified design request.

[1863] Step 7:

[1864] The server sends the modification request back to the generative AI model, which generates a modified original design. The generative AI model accepts the modification request and generates a new design based on the specified changes. The inputs are the modification request and the existing original design, and the output is the modified original design.

[1865] Step 8:

[1866] The server stores the final generated original design in the user's account and applies it to the product. The server associates the final original design with the user's account and stores it, then applies the design to the specified product template. The input is the modified original design and the user's account information, and the output is the customized product.

[1867] Step 9:

[1868] The terminal displays the final saved original design and allows the user to place an order within the e-commerce site. The user checks the displayed custom product and confirms the order through the e-commerce site. The input is the product with the final original design applied, and the output is the order confirmed by the user.

[1869] 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.

[1870] This invention is a system that allows a user to select an image file from a device and generates original LINE stamps using a generative AI model and an emotion engine. Specific embodiments of the invention are described in detail below.

[1871] System configuration

[1872] The system mainly consists of the following components:

[1873] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[1874] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[1875] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[1876] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[1877] Processing flow

[1878] The following shows the process from when the user selects an image file to when an original stamp is generated using the emotion engine.

[1879] 1. User selects an image file

[1880] The user opens the device's gallery and selects the image file they want to use as an original stamp.

[1881] 2. The device sends the image file to the server

[1882] The terminal transmits the selected image file to the server.

[1883] The transmitted image file is temporarily stored in the device's storage and then uploaded to the server via an HTTP request.

[1884] 3. The server receives and analyzes the image file.

[1885] The server receives the image file and temporarily stores it in storage.

[1886] Set the parameters for the server to call the API for the generated AI model.

[1887] 4. The server analyzes the user's emotions

[1888] The server calls the emotion engine and analyzes multiple input data, including the user's voice, facial expressions, and text input.

[1889] The emotion engine detects the user's emotions (e.g., joy, sadness, surprise, etc.).

[1890] 5. Generative AI model generates stamps

[1891] The generative AI model analyzes the characteristics of the image file and, based on the analysis results of the emotion engine, applies customization elements (such as changing the background or adding an appropriate message) to generate original stamps.

[1892] The generated stamp image is returned to the server.

[1893] 6. The server sends the generated stamp to the device.

[1894] The server transmits the generated original stamp to the terminal.

[1895] The device receives the stamp image and displays it to the user.

[1896] 7. The user checks the stamp and requests corrections

[1897] The user checks the generated stamp image and specifies correction requests as necessary.

[1898] The revision requests include specific changes to the message or background.

[1899] 8. The server generates the stamp again

[1900] The server sends the correction request again to the API of the generation AI model, which generates the corrected stamp.

[1901] 9. The server saves the final stamp and notifies the device.

[1902] The server then stores the final generated stamp in the user's account.

[1903] A notification will be sent to the device when the save is complete, making the stamp immediately available to the user as a LINE stamp.

[1904] Specific examples

[1905] For example, a user can create original LINE stickers using a photo of their pet dog, leveraging the emotion engine.

[1906] 1. User selects a photo

[1907] Select a photo of your dog from your smartphone gallery.

[1908] 2. The device sends the photo

[1909] The selected photo is sent to the server.

[1910] 3. The server receives the photo and analyzes it with the generative AI model

[1911] The server receives the photo and provides it to the generative AI model to begin analysis.

[1912] 4. The server analyzes the user's emotions using an emotion engine

[1913] The emotion engine analyzes the user's facial expressions and voice data to detect "joy."

[1914] 5. Generative AI model generates stickers based on emotions

[1915] Based on the emotion analysis result of "joy," a stamp was generated with the background changed to a sunny park and the message "I'm happy!" added.

[1916] 6. The server sends the stamp to the device

[1917] The generated stamp is sent to the terminal and displayed to the user.

[1918] 7. The user checks the stamp and requests corrections

[1919] The user requests that the message be changed to "Let's play!"

[1920] 8. The server generates the stamp again

[1921] The server then has the AI ​​model generate stamps again based on the correction request.

[1922] 9. The server saves the final stamp and notifies the device.

[1923] The modified stamps will be saved to the user's LINE account and made available for use.

[1924] In this way, a system that utilizes an emotion engine can quickly create original stamps that reflect the user's emotions, enabling more personalized communication.

[1925] The processing flow will be explained below.

[1926] Step 1:

[1927] The user opens the device's gallery.

[1928] The user selects the image file they want to use as an original stamp.

[1929] The device temporarily saves the selected image file.

[1930] Step 2:

[1931] The terminal creates a request to notify the server that the image file selection has been completed.

[1932] The terminal sends the selected image file to the server in the form of an HTTP request.

[1933] Verify that the server received the request.

[1934] Step 3:

[1935] The server temporarily stores the received image file in storage.

[1936] Set the parameters for the server to call the API for the generated AI model.

[1937] The server provides the image file to the generative AI model and begins analysis.

[1938] Step 4:

[1939] The server calls the emotion engine and prepares to analyze the user's emotions.

[1940] The user provides data such as voice, facial expressions, and text input through the device.

[1941] The device collects this data and sends it to the server.

[1942] Step 5:

[1943] The server provides the data sent to the emotion engine and analyzes the user's emotions.

[1944] The emotion engine detects the user's emotions (e.g., "happiness," "sadness," "surprise," etc.).

[1945] Step 6:

[1946] Based on the image features analyzed by the generative AI model and the analysis results of the emotion engine, customization elements (such as changing the background or adding an appropriate message) are applied to generate original stamps.

[1947] The generated stamp image is returned to the server.

[1948] Step 7:

[1949] The server temporarily stores the generated original stamp.

[1950] The server creates a request to send the stamp image to the terminal.

[1951] Step 8:

[1952] The terminal displays the stamp image received from the server to the user.

[1953] The user checks the stamp and specifies correction requests as necessary.

[1954] Step 9:

[1955] The terminal receives the user's modification request and creates a request to send to the server.

[1956] The terminal sends a modification request to the server.

[1957] Step 10:

[1958] The server receives the correction request and sets the parameters to call the API for the generated AI model again.

[1959] Based on the modification request, the server sends the image file and customization elements to the generative AI model.

[1960] Step 11:

[1961] The generative AI model recreates the original stamp reflecting the requested modifications.

[1962] The generative AI model returns the corrected stamp image to the server.

[1963] Step 12:

[1964] The server temporarily stores the returned corrected stamp image.

[1965] The server starts the process of saving the final generated original stamp to the user's account.

[1966] Step 13:

[1967] The server creates a request to notify the terminal that the stamp saving process has been completed.

[1968] The device receives a notification from the server and displays to the user that the final stamp has been saved.

[1969] Step 14:

[1970] The user opens the LINE app on their device and confirms that the generated original stamps are available.

[1971] The user sends an original stamp in a LINE chat and checks that it displays as intended.

[1972] The above are the specific processing steps that allow users to select an image file, and then use the emotion engine and generative AI model to generate, modify, save, and ultimately use original LINE stamps.

[1973] Example 2

[1974] 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."

[1975] Conventional stamp generation systems have had difficulty in quickly and efficiently generating personalized stamps that reflect the user's emotions. Furthermore, they lacked the means to flexibly accommodate requests for corrections to generated stamps. This has led to the problem that it is difficult for users to create original stamps that satisfy them.

[1976] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a transmitted image file and temporarily storing it in storage, means for analyzing the user's emotions using an emotion engine, and means for providing the received image file to a generative AI model and applying customization elements based on the emotion analysis result to generate an original stamp. This makes it possible to quickly generate a personalized original stamp that reflects the user's emotions.

[1977] "User" refers to a general user who operates a terminal to select an image file or request a stamp modification.

[1978] "Terminal" refers to a device operated by a user, such as a smartphone, tablet, or PC.

[1979] "Image file" refers to the digital image data that the user selects from the device and that is the basis for generating the stamp.

[1980] The term "server" refers to a computer system that receives data sent from a terminal via a network and performs image processing and stamp generation.

[1981] "Generative AI model" refers to the algorithms and programs used to generate original stamps based on received image files.

[1982] "Emotion engine" refers to algorithms and programs for analyzing user emotions.

[1983] "Customization Elements" refers to customization elements applied to a sticker by a generative AI model, such as changing the background or adding a text message.

[1984] "Original stamp" refers to a stamp image to which customization elements have been applied by a generative AI model.

[1985] "Modification Request" means a request for change submitted by a User to a Generated Stamp.

[1986] "Communication platform" refers to applications and services that allow users to communicate with other users using original stamps.

[1987] This invention is a system in which a user selects an image file from a terminal and generates an original stamp image using a generative AI model and an emotion engine. Specific embodiments for implementing this invention are described below.

[1988] The system mainly consists of the following components:

[1989] 1. Device - A device operated by a user, including a smartphone, tablet, or computer.

[1990] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[1991] 3. Generative AI Model - Algorithms and programs for generating stamp images based on received images.

[1992] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[1993] System Operation Overview

[1994] The user selects an image file on the device

[1995] The user selects the image they want to use as the original stamp from the image gallery or file manager on their device. For example, the user opens the gallery app on their smartphone and selects a photo of their pet dog.

[1996] The device sends the image file to the server

[1997] The device sends the selected image file to the server using an HTTP request. At this time, the image file is temporarily stored in the device's storage. Specifically, the device uploads the selected photo of the pet dog to the server using an HTTP POST request.

[1998] The server receives and analyzes the image file.

[1999] The server receives the image file and temporarily stores it in storage. Then, the server sets parameters to call the API of the generative AI model. For example, the server stores a photo of your dog in the image_input variable and prepares it for analysis.

[2000] The server analyzes the user's emotions

[2001] The server calls the emotion engine and analyzes the user's facial expressions, voice, text input, etc. The emotion engine detects the user's emotions and identifies emotion categories such as "happiness," "sadness," and "surprise." As a specific example, the emotion engine analyzes the user's happy facial expression and detects the emotion "happiness."

[2002] Generative AI model generates stamps

[2003] The generative AI model analyzes the characteristics of an image file and applies customization elements such as changing the background and adding a text message based on the results of the emotion analysis to generate original stamps. For example, the generative AI model analyzes a photo of a pet dog, changes the background to a sunny park, and creates a stamp with the message "I'm happy!"

[2004] The server sends the generated stamp to the terminal.

[2005] The server sends the generated original stamp to the device. The device receives the stamp image and displays it to the user. Specifically, the server sends the generated stamp to the device via an HTTP response, and it is displayed in the gallery or within the app on the user's device.

[2006] The user checks the stamp and requests corrections.

[2007] The user checks the generated stamp image and requests corrections if necessary. This correction request includes specific changes. For example, the user requests that the message "I'm happy!" be changed to "Let's play!"

[2008] The server generates the stamp again

[2009] The server sends the correction request again to the generative AI model to generate the corrected stamp. The server sends a new prompt containing the corrections to the generative AI model to obtain a new stamp.

[2010] The server saves the final stamp and notifies the device

[2011] The server saves the final generated stickers to the user's account, then sends a save completion notification to the device, allowing the user to immediately use the stickers within communication platforms such as the LINE app. For example, by saving new stickers to a database and sending a save completion notification to the device, the user can use the new stickers on LINE.

[2012] Specific examples

[2013] The process for users to create original LINE stickers using photos of their pet dogs is as follows:

[2014] 1. The user opens the gallery app on their smartphone and selects a photo of their dog.

[2015] 2. The device sends the selected photo of the dog to the server via an HTTP request.

[2016] 3. The server receives the photo and provides it to the generative AI model to begin analysis.

[2017] 4. Use an emotion engine to analyze the user's facial expression data and detect "happiness."

[2018] 5. Based on the emotion analysis result of "joy," the generative AI model changes the background to a sunny park and generates a stamp with the message "I'm so happy!" added.

[2019] 6. The server sends the generated stamp to the device and displays it to the user.

[2020] 7. The user requests that the "Happy!" message be changed to "Let's play!"

[2021] 8. The server sends the correction request to the generative AI model to generate the corrected stamp.

[2022] 9. The modified stamps are saved to the user's LINE account and made available for use.

[2023] Prompt Sentence Examples

[2024] Create an original stamp based on the user's emotion "joy" using a photo of your dog. Change the background to a sunny park and add the message "I'm so happy!"

[2025] In this way, it becomes possible to quickly generate personalized original stamps that reflect the user's emotions.

[2026] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2027] Step 1:

[2028] The user selects an image file on the device.

[2029] Input: The user operates the image gallery or file manager on the device and specifies the image file they want to use as a stamp.

[2030] What happens: The user opens the gallery app on their smartphone and selects a photo of their dog.

[2031] Output: The path or URL of the selected image file is retrieved.

[2032] Step 2:

[2033] The device sends the image file to the server.

[2034] Input: The path or URL of the image file obtained in step 1.

[2035] Specific operation: The device uploads the selected image file to the server using an HTTP POST request.

[2036] Output: The server receives the image file and it is temporarily saved in storage.

[2037] Step 3:

[2038] The server receives the image file and prepares it for analysis.

[2039] Input: The image file uploaded in step 2.

[2040] Specific operation: The server temporarily saves the image file in storage and sets parameters for analysis. For example, it saves the image file in the image_input variable.

[2041] Output: Image data ready for analysis.

[2042] Step 4:

[2043] The server analyzes the user's emotions.

[2044] Input: Emotional data such as user facial expressions, voice, and text input.

[2045] Specific operation: This data is sent to the emotion engine to perform emotion analysis. For example, the emotion engine analyzes the user's facial expression data and detects the emotion "joy."

[2046] Output: Sentiment analysis result (e.g. "Happy", "Sad", "Surprise", etc.).

[2047] Step 5:

[2048] The server generates stamps using a generative AI model.

[2049] Input: The image data prepared in step 3 and the sentiment analysis results obtained in step 4.

[2050] How it works: The generative AI model analyzes the characteristics of an image file and applies customization elements such as changing the background or adding a message based on the results of emotion analysis. For example, based on the emotion of "joy," the generative AI model generates a stamp that changes the background to a sunny park and adds the message "I'm so happy!"

[2051] Output: Customized original stamp image.

[2052] Step 6:

[2053] The server sends the generated stamp to the terminal.

[2054] Input: The original stamp image generated in step 5.

[2055] Specific operation: The server sends the generated stamp to the terminal in an HTTP response.

[2056] Output: The device receives the stamp image and displays it to the user.

[2057] Step 7:

[2058] The user checks the stamp and requests corrections.

[2059] Input: The original stamp image shown to the user in step 6.

[2060] Specific behavior: The user checks the stamp and, if necessary, requests corrections through the application interface. For example, the user requests that the message "I'm happy!" be changed to "Let's play!"

[2061] Output: User requested corrections.

[2062] Step 8:

[2063] The server generates the stamp again.

[2064] Input: The correction request provided by the user in step 7.

[2065] Specific operation: The server sends a correction request to the generative AI model again, and sends a new prompt sentence to the generative AI model to generate a corrected stamp.

[2066] Output: The original stamp image after modification.

[2067] Step 9:

[2068] The server saves the final stamp and notifies the terminal.

[2069] Input: The modified original stamp image generated in step 8.

[2070] Specific operation: The server saves the modified stamp in the database and sends a save completion notification to the terminal.

[2071] Output: The modified stickers are saved to the user's LINE account, and a notification is sent to the user's device. The user can then use the stickers in the LINE app.

[2072] (Application example 2)

[2073] 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."

[2074] In the conventional LINE sticker generation system, the process for users to generate sticker images was limited, making it difficult to generate stickers in real time or use them in stores. Furthermore, stickers were not generated to reflect the user's emotions, making it difficult to realize personalized communication. Furthermore, the process of generating and modifying stickers was complicated, resulting in a poor user experience.

[2075] 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.

[2076] In this invention, the server includes means for receiving an image file selected by a user and providing it to a generative AI model to generate an original stamp, means for sending the generated original stamp to a terminal, means including an emotion engine that analyzes the user's emotions and reflects them in the stamp generation, and means for generating the stamp again using the generative AI model based on a correction request. This enables users to generate original stamps in real time at physical stores and share them on social media on the spot.

[2077] A "terminal" is a device operated by a user, such as a smartphone, tablet, or personal computer.

[2078] A "server" is a computer system that receives and processes data sent from a terminal via a network.

[2079] A "generative AI model" is a collection of algorithms and programs for generating customized stamp images based on image files and other data received from users.

[2080] "Customization elements" are additional elements or modifications that are applied to the generated stamp image, such as changing the background or adding a message.

[2081] An "emotion engine" is a collection of algorithms and programs that analyze a user's voice, facial expressions, text input, etc. to detect the user's emotions.

[2082] "Original Stamps" are individually customized stamp images created by a generative AI model that users can use on communication platforms.

[2083] A "communication platform" is an online service that enables users to send and receive messages using stamps, such as LINE or other SNS.

[2084] A "physical store" is a physical location, such as a commercial facility or retail outlet, that a user can visit.

[2085] "Real time" is a time characteristic that refers to immediate results being obtained the moment an operation or event occurs.

[2086] A "modification request" is a request made by a user to make changes or improvements to a generated stamp.

[2087] This invention provides a system that allows users to create original LINE stamps in real time in physical stores. The system consists of elements such as a smartphone, a server, a generative AI model, and an emotion engine.

[2088] System configuration

[2089] The system consists of the following components:

[2090] 1. Terminal - A device operated by a user, such as a smartphone or tablet.

[2091] 2. Server - Receives data sent from devices via the network and performs image processing and emotion analysis using generative AI models and emotion engines.

[2092] 3. Generative AI model - Algorithms and programs for generating stamp images based on received images.

[2093] 4. Emotion Engine - Algorithms and programs for analyzing user emotions.

[2094] Explanation of program processing

[2095] 1. Select and send image files:

[2096] The user operates the smartphone application and selects an image file from the gallery, and the selected image is sent to the server via an HTTP request.

[2097] 2. Data Receipt and Analysis:

[2098] The server receives the image file and temporarily stores it in storage, then calls the API of the generative AI model to begin analyzing the image.

[2099] 3. Emotion Analysis:

[2100] The server uses an emotion engine to analyze the user's emotions, using data such as facial expressions, voice, and text input. For example, emotions such as "happiness" or "surprise" can be detected.

[2101] 4. Stamp generation:

[2102] The generative AI model analyzes the image features and applies customization elements (such as changing the background or adding a message) based on the detected emotion to generate an original stamp. The generated stamp image is then returned to the server.

[2103] 5. Sending and viewing stamps:

[2104] The server sends the generated original stamp to the smartphone and displays it to the user, who can then check the stamp and make correction requests.

[2105] 6. Processing Amendment Requests:

[2106] If the user makes a correction request, the request is sent again to the generative AI model, and a new stamp is generated.

[2107] 7. Save and share your final stamp:

[2108] The server then saves the final stamps to the user's account, allowing the user to instantly share them on social media and other communication platforms.

[2109] Specific examples

[2110] The video shows a user visiting a physical store creating original LINE stamps using photos taken with their smartphone.

[2111] 1. User selects a photo:

[2112] Select a photo taken at a photo spot within the store from your smartphone gallery.

[2113] 2. The device sends the photo:

[2114] The selected photo is sent to the server.

[2115] 3. The server analyzes the photo:

[2116] The server receives the photo and begins analyzing it using the generative AI model.

[2117] 4. Emotion Analysis:

[2118] The emotion engine detects the user's "joy" from the photo.

[2119] 5. Stamp generation:

[2120] Based on the emotion of "joy," a stamp was generated with the background changed to a sunny park and the message "I'm so happy!" added.

[2121] 6. Viewing and Modifying Stamps:

[2122] The generated stamp is displayed on the smartphone. The user requests to change the message to "Let's play!"

[2123] 7. Generate and display correction stamps:

[2124] The message is then regenerated by the AI ​​model and the revised stamp is displayed.

[2125] 8. Save and share your final stamp:

[2126] The final stamp will be saved in the user's account and can be shared on LINE and other platforms.

[2127] Prompt Sentence Examples

[2128] "Please create LINE stamps that express joy using photos of smiling customers visiting your store with their friends."

[2129] The system will improve the customer experience in physical stores and enable personalized communication.

[2130] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2131] Step 1:

[2132] A user operates a smartphone application and selects an image file from the gallery. The input here is the image file selected by the user, and the output is the data of the selected image file.

[2133] Step 2:

[2134] The terminal sends the data of the selected image file to the server via an HTTP request. The input is the image file data obtained in step 1, and the output is the image file data sent to the server.

[2135] Step 3:

[2136] The server receives the image file and temporarily stores it in storage. The image file data stored in the server's storage is input data, and the output is temporary data stored on the server.

[2137] Step 4:

[2138] The server calls the API of the generative AI model and analyzes the data of the saved image file. The input is the data of the saved image file, and the output is data that analyzes the image features. In this step, the server extracts the features of the image file.

[2139] Step 5:

[2140] The server analyzes the user's emotions using an emotion engine. The input is the image file and additional user data (e.g., voice, facial expressions, etc.), and the output is the analyzed emotion data. In this step, the server classifies the user's emotions into categories such as "happiness" or "surprise."

[2141] Step 6:

[2142] The server uses a generative AI model to apply customization elements based on the analyzed emotion data and the features of the image file, generating an original stamp. The input is the image feature data and emotion data, and the output is the generated original stamp image. In this step, processing such as changing the background and adding text is performed.

[2143] Step 7:

[2144] The server sends the generated original stamp to the terminal. The input is the image of the generated original stamp, and the output is the stamp image sent to the terminal.

[2145] Step 8:

[2146] The terminal displays the generated original stamp to the user and accepts modification requests. The input is the stamp image sent from the server, and the output is the stamp image that the user sees on the screen and modification request data. The user can request changes to the stamp content.

[2147] Step 9:

[2148] The server sends the correction request to the generative AI model again to generate a corrected original stamp. The input is the correction request data, and the output is the corrected stamp image. The server again instructs the generative AI model to generate a new stamp image.

[2149] Step 10:

[2150] The server saves the final generated stamp in the user's account. The input is the modified original stamp image, and the output is the stamp image saved in the user's account.

[2151] Step 11:

[2152] The device finally displays the saved original stamp and makes it available to the user within the communication platform. The input is the saved stamp image, and the output is the stamp image displayed on the user's device. The user can share this image on LINE or other SNS.

[2153] 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.

[2154] 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.

[2155] 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.

[2156] 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.

[2157] 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.

[2158] 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.

[2159] 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).

[2160] 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.

[2161] 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."

[2162] 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.

[2163] 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).

[2164] 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.

[2165] 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.

[2166] 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.

[2167] 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.

[2168] 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.

[2169] 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.

[2170] 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.

[2171] 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.

[2172] 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.

[2173] 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.

[2174] The following is further disclosed regarding the above embodiment.

[2175] (Claim 1)

[2176] A means for the user to select an image file from their device;

[2177] means for the terminal to transmit the selected image file to a server;

[2178] A means for the server to receive the transmitted image file;

[2179] A means for providing the image file received by the server to a generative AI model and applying customization elements to generate an original stamp;

[2180] A means for the server to transmit the generated original stamp to the terminal;

[2181] a means for displaying the original stamp sent by the terminal to the user and accepting a request for modification;

[2182] A means for the server to send the modification request to the generation AI model again to generate a modified original stamp;

[2183] A means for the server to store the final generated original stamp in the user's account;

[2184] The terminal finally displays the saved original stamp and makes it available to the user within the communication platform;

[2185] A system including:

[2186] (Claim 2)

[2187] 10. The system of claim 1, wherein the generative AI model includes means for analyzing characteristics of the image file and means for applying customization elements thereon.

[2188] (Claim 3)

[2189] 10. The system of claim 1, further comprising means for the generative AI model to generate the stamp image again based on a modification request provided by the user.

[2190] "Example 1"

[2191] (Claim 1)

[2192] A means for the user to select an image file from their device;

[2193] means for the device to transmit the selected image file to a network server;

[2194] a means for the network server to receive the transmitted image file;

[2195] A means for providing the image file received by the network server to an image generation model and applying customization elements to generate an original stamp;

[2196] a means for the network server to transmit the generated original stamp to the device;

[2197] means for the device to display the original stamp to the user and accept requests for modification;

[2198] a means for the network server to send the modification request again to the image generation model to generate a modified original stamp;

[2199] A means for the network server to store the final generated original stamp in the user's account;

[2200] The device ultimately displays the saved original stamp and makes it available to the user within the communication platform; and

[2201] A system including:

[2202] (Claim 2)

[2203] 10. The system of claim 1, wherein the image generation model comprises means for analyzing characteristics of the image file and means for applying customization elements thereon.

[2204] (Claim 3)

[2205] 10. The system of claim 1, further comprising means for the image generation model to generate the stamp image again based on a modification request provided by the user.

[2206] "Application Example 1"

[2207] (Claim 1)

[2208] A means for the user to select an image file from their device;

[2209] means for the terminal to transmit the selected image file to a server;

[2210] A means for the server to receive the transmitted image file;

[2211] A means for providing the image file received by the server to a generative AI model and applying customization elements to generate an original design;

[2212] A means for the server to transmit the generated original design to the terminal;

[2213] a means for the terminal to display the transmitted original design to the user and accept requests for modifications;

[2214] a means for the server to send the modification request to the generating AI model again to generate a modified original design;

[2215] The server stores the final generated original design in the user's account and applies it to the product;

[2216] and a means for the device to finally display the saved original design and enable the user to place an order within the e-commerce site.

[2217] A system including:

[2218] (Claim 2)

[2219] The system of claim 1, further comprising: a means for the generative AI model to analyze characteristics of the image file and then apply customization elements thereto; and a means for reflecting the generated design in a product template.

[2220] (Claim 3)

[2221] 10. The system of claim 1, further comprising means for the generative AI model to generate the design image again based on a modification request provided by the user.

[2222] "Example 2: Combining Emotion Engines"

[2223] (Claim 1)

[2224] A means for the user to select an image file from their device;

[2225] means for the terminal to transmit the selected image file to a server;

[2226] A means for the server to receive the transmitted image file and temporarily store it in storage;

[2227] A means for the server to analyze the user's emotions using an emotion engine;

[2228] A means for providing the image file received by the server to a generation AI model and applying customization elements based on the emotion analysis results to generate original stamps;

[2229] A means for the server to transmit the generated original stamp to the terminal;

[2230] a means for displaying the original stamp sent by the terminal to the user and accepting a request for modification;

[2231] A means for the server to send the modification request to the generation AI model again to generate a modified original stamp;

[2232] A means for the server to store the final generated original stamp in the user's account;

[2233] The terminal finally displays the saved original stamp and makes it available to the user within the communication platform;

[2234] A system including:

[2235] (Claim 2)

[2236] 10. The system of claim 1, further comprising: means for the generative AI model to analyze characteristics of the image file and then apply customization elements based on the sentiment analysis results.

[2237] (Claim 3)

[2238] 10. The system of claim 1, further comprising means for the generative AI model to generate the stamp image again based on a modification request provided by the user.

[2239] "Application example 2 when combining emotion engines"

[2240] (Claim 1)

[2241] A means for the user to select an image file from their device;

[2242] means for the terminal to transmit the selected image file to a server;

[2243] A means for the server to receive the transmitted image file;

[2244] A means for providing the image file received by the server to a generative AI model and applying customization elements to generate an original stamp;

[2245] A means for the server to transmit the generated original stamp to the terminal;

[2246] a means for displaying the original stamp sent by the terminal to the user and accepting a request for modification;

[2247] A means for the server to send the modification request again to the generation AI model to generate a modified original stamp;

[2248] A means for the server to store the final generated original stamp in the user's account;

[2249] The terminal finally displays the saved original stamp and makes it available to the user within the communication platform;

[2250] A means for a user to operate a dedicated application for a physical store to generate images in the physical store;

[2251] A means for customers in physical stores to generate original stamps in real time using their smartphones and share them on the spot based on the generated AI model, and

[2252] A system including:

[2253] (Claim 2)

[2254] 10. The system of claim 1, wherein the generative AI model comprises means for analyzing characteristics of the image file and means for applying customization elements thereon, and an emotion engine for analyzing user emotions.

[2255] (Claim 3)

[2256] The system of claim 1, further comprising: means for the generative AI model to regenerate the stamp image based on a correction request provided by the user; and means for displaying and making the generated stamp shareable in real time on a smartphone. [Explanation of symbols]

[2257] 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. A means for the user to select an image file from their device; means for the terminal to transmit the selected image file to a server; A means for the server to receive the transmitted image file; A means for providing the image file received by the server to a generative AI model and applying customization elements to generate an original stamp; A means for the server to transmit the generated original stamp to the terminal; a means for displaying the original stamp sent by the terminal to the user and accepting a request for modification; A means for the server to send the modification request to the generation AI model again to generate a modified original stamp; A means for the server to store the final generated original stamp in the user's account; The terminal finally displays the saved original stamp and makes it available to the user within the communication platform; A system including:

2. 10. The system of claim 1, wherein the generative AI model comprises means for analyzing characteristics of the image file and means for applying customization elements thereon.

3. 10. The system of claim 1, further comprising means for the generative AI model to generate the stamp image again based on a modification request provided by the user.

Images