System

Abstract

A system is provided.SOLUTION: A system, comprising: means for receiving input information specified by a user; means for sending the input information to a server; means for generating a logo based on the input information by the server; and means for providing the generated logo to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] For small businesses and personal brands, hiring a professional designer or using expensive design software can be difficult. There are also many situations where a logo is needed quickly for events such as generative AI contests and hackathons. These users face financial and time constraints that make it difficult to obtain a high-quality, unique logo. This invention solves these problems, enabling anyone to easily create a high-quality logo. [Means for solving the problem]

[0005] The system includes a means for receiving user input information, a means for transmitting the input information to a server, a means for generating a logo in the server based on the input information, and a means for providing the generated logo to the user. Specifically, the server has a means for generating a logo based on the colors, concept, and motif specified by the user and providing multiple logo designs. The server also has a means for transmitting the input information to an AI model, which then generates a logo and returns it to the server. This allows users to quickly and easily obtain a high-quality logo without having to hire a professional designer.

[0006] "User-entered information" refers to information including colors, concepts, and motifs specified by the user.

[0007] A "server" is a computer system that receives input information sent by a user, generates a logo using an AI model based on that information, and provides the generated logo to the user.

[0008] "Color" is information that indicates the specific color used in the logo and is specified by the user.

[0009] "Concept" is information that indicates the overall design and theme of the logo and is specified by the user.

[0010] "Motif" refers to information that refers to specific shapes or symbols used as the main design elements of the logo and is specified by the user.

[0011] An "AI model" is an algorithm that uses artificial intelligence and has the ability to generate a logo based on specified input information.

[0012] A "logo" is a designed device that visually represents your brand or service.

[0013] "Logo ideas" are multiple logo design candidates generated by an AI model.

[0014] "Generative means" refers to the process and techniques used to create a logo using an AI model based on user input.

[0015] The "means of delivery" refers to the process and technology used to display and make the generated logo available to users for download. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This system uses AI to quickly generate a logo based on the colors, concept, and motif specified by the user. The detailed implementation method is explained below.

[0038] overview

[0039] The system works through a series of processes: receiving user input, sending it to the server, generating a logo using an AI model, and providing the generated logo, allowing users to easily obtain a high-quality logo.

[0040] Program processing

[0041] Receiving user input information

[0042] The user uses a terminal to input information about the color, concept, and motif into an input form. For example, the user inputs "blue" as the color, "futuristic" as the concept, and "rocket" as the motif.

[0043] The device receives this input information, stores it in a variable, and converts it to JSON format, ready to be sent to the server.

[0044] Sending input information

[0045] The device converts the information entered by the user into JSON format and sends the information to the server as an HTTP POST request.

[0046] json

[0047] {

[0048] "color": "blue",

[0049] "concept": "futuristic",

[0050] "motif": "rocket"

[0051] }

[0052] Processing on the server

[0053] The server receives and analyzes the JSON data sent from the device, extracting information on color, concept, and motif, and storing it in the respective variables.

[0054] The server then calls the interface with the AI ​​model and requests logo generation based on the received input information. The server then passes parameters to the AI ​​model's API endpoint to start the logo generation process.

[0055] json

[0056] POST / generate_logo

[0057] {

[0058] "color": "blue",

[0059] "concept": "futuristic",

[0060] "motif": "rocket"

[0061] }

[0062] AI-powered logo generation

[0063] The AI ​​model generates multiple logo designs based on the specified color, concept, and motif, for example, generating three blue-based, futuristic rocket-themed logos.

[0064] The generated logo designs are sent back to the server as a response including their respective file paths and related information.

[0065] json

[0066] {

[0067] "logos": [

[0068] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0069] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0070] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0071] ]

[0072] }

[0073] Sending the generated results

[0074] The server analyzes the logo design data received from the AI ​​model, converts it back into JSON format, and sends it back to the device.

[0075] json

[0076] {

[0077] "logos": [

[0078] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0079] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0080] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0081] ]

[0082] }

[0083] Display and provide logo proposals

[0084] The device analyzes the logo proposal data received from the server and displays it on the user interface, showing the user thumbnail images of each logo so they can check the details.

[0085] User Selection and Download

[0086] The user selects the logo they like best from multiple logo designs and clicks the download button to download the logo. At this time, the device retrieves the image file of the selected logo from the download link and saves it locally.

[0087] Through this series of processes, users can easily generate and obtain high-quality and unique logos. This system is very useful for helping small businesses and personal brands quickly create logos.

[0088] The processing flow will be explained below.

[0089] Step 1: Receiving user input

[0090] The user inputs the color, concept, and motif into the input form on the terminal. For example, "Color: Blue," "Concept: Futuristic," and "Motif: Rocket" are input.

[0091] The terminal receives the input information and stores it in variables. The input information is divided into fields called "color", "concept", and "motif" and prepared for the next process.

[0092] Step 2: Submit your input

[0093] The terminal converts the input information into JSON format.

[0094] json

[0095] {

[0096] "color": "blue",

[0097] "concept": "futuristic",

[0098] "motif": "rocket"

[0099] }

[0100] The device sends JSON data to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[0101] Step 3: Processing on the Server

[0102] The server receives the JSON data sent from the device.

[0103] The server analyzes the received data, extracts the "color," "concept," and "motif," and stores them in variables.

[0104] Step 4: Processing the logo generation request

[0105] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo.

[0106] The server sends an HTTP POST request to the AI ​​model's API endpoint.

[0107] json

[0108] POST / generate_logo

[0109] {

[0110] "color": "blue",

[0111] "concept": "futuristic",

[0112] "motif": "rocket"

[0113] }

[0114] Step 5: AI-powered logo generation

[0115] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified features.

[0116] The AI ​​model sends a response back to the server, including the file path and data of the generated logo design.

[0117] json

[0118] {

[0119] "logos": [

[0120] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0121] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0122] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0123] ]

[0124] }

[0125] Step 6: Sending the generated results

[0126] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[0127] json

[0128] {

[0129] "logos": [

[0130] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0131] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0132] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0133] ]

[0134] }

[0135] Step 7: View and submit logo ideas

[0136] The terminal analyzes the logo proposal data received from the server.

[0137] The device displays a thumbnail image of the proposed logo and a description in the user interface.

[0138] Step 8: User Selection and Download

[0139] The user selects the logo they like best from multiple designs.

[0140] The user selects a specific logo design and clicks the download button.

[0141] The device retrieves the image file of the selected logo from the download link and saves it locally.

[0142] Through this series of steps, users can quickly get a high-quality logo without having to hire a professional designer.

[0143] Example 1

[0144] 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."

[0145] Conventional logo generation systems often fail to respond quickly and accurately to user requests, making it difficult to provide high-quality logos based on specific colors, concepts, and motifs. Furthermore, they provide insufficient support for users in selecting the most suitable logo from numerous logo designs, creating a need for an improved user experience.

[0146] 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.

[0147] In this invention, the server includes means for receiving input information specified by a user, means for converting the input information into a data format and sending it to the server, means for the server to request a logo generation from an AI model based on the input information, and means for providing the generated logo to the user. This makes it possible to quickly generate a high-quality logo based on the user's specific requirements and provide multiple logo designs to allow the user to select the most suitable logo.

[0148] A "user" is an entity that provides input information such as colors, concepts, and motifs to generate a logo using the system.

[0149] "Input information" refers to information such as colors, concepts, and motifs that a user provides to the system for logo generation.

[0150] A "data format" is the structured format into which input information is converted for transmission to the server, typically in a format such as JSON or XML.

[0151] A "server" is a computer system that has the ability to analyze received input information and request logo generation from an AI model.

[0152] "AI Model" refers to an artificial intelligence algorithm and its implementation for generating a logo based on specified parameters.

[0153] A "logo" is an image or design created to visually represent a company or brand.

[0154] "Logo ideas" refers to multiple logo variations generated by the AI ​​model and are options offered to users.

[0155] This invention is a system that uses AI to quickly generate a logo from the colors, concept, and motif specified by the user. A specific embodiment of this system will be described below.

[0156] Hardware and software used

[0157] Device: The device (e.g., computer, tablet, smartphone) on which the user enters information and on which the generated logo is displayed and downloaded.

[0158] Server: A back-end system that receives and analyzes input information and generates logos using AI models.

[0159] AI Model: An artificial intelligence model (e.g. TensorFlow, PyTorch) trained for logo generation.

[0160] API: An interface that mediates communication between the server and the AI ​​model.

[0161] System Features

[0162] Receiving user input information

[0163] The user uses the terminal to input color, concept, and motif information into the system's input form. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The terminal receives this input information and stores it in variables. Next, it converts this input information into JSON format and prepares it to be sent to the server.

[0164] Sending input information

[0165] The device sends the information entered by the user to the server as an HTTP POST request, which contains data in JSON format and is structured so that the server can parse it properly.

[0166] Processing on the server

[0167] The server analyzes the JSON data received from the device and extracts information on color, concept, and motif.The server then calls the interface with the AI ​​model and requests the AI ​​model to generate a logo based on the analyzed input information.

[0168] AI-powered logo generation

[0169] The AI ​​model generates multiple logo designs based on the specified color, concept, and motif. For example, it generates three futuristic rocket logo designs based on blue. The generated logo designs are then sent back to the server as data, including their file paths and descriptions.

[0170] Sending the generated results

[0171] The server then converts the logo design data received from the AI ​​model back into JSON format and sends it back to the device, including the file path and description of the logo design.

[0172] Display and provide logo proposals

[0173] The device analyzes the logo design data received from the server and displays it on the user interface. The user can view multiple logo designs in thumbnail format and check the details of each one.

[0174] User Selection and Download

[0175] The user selects the logo they like best from multiple logo designs and clicks the download button to download the logo. At this time, the device retrieves the image file of the selected logo from the download link and saves it locally.

[0176] Specific operation example

[0177] For example, if the user enters the following prompt sentence:

[0178] Example prompt: "Generate a blue logo featuring a futuristic rocket design."

[0179] Through this series of processes, users can easily and quickly generate and obtain high-quality logos, which is especially useful for small businesses and personal brands to quickly create logos.

[0180] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0181] Step 1:

[0182] The user uses the terminal to input color, concept, and motif information into the input form. At this time, the user enters specific information such as "blue," "futuristic," and "rocket." The input is text information entered by the user. The terminal receives this information and stores it in variables.

[0183] Step 2:

[0184] The terminal converts the received input information into JSON format. During this conversion process, the text information is structured into a JSON object like the following:

[0185] json

[0186] {

[0187] "color": "blue",

[0188] "concept": "futuristic",

[0189] "motif": "rocket"

[0190] }

[0191] The input is the user's text input information, and the output is JSON formatted data that the device prepares to send to the server as an HTTP POST request.

[0192] Step 3:

[0193] The terminal sends the generated JSON data to the server using an HTTP POST request. The input is the user's input information converted to JSON format, and the output is the HTTP request sent to the server.

[0194] Step 4:

[0195] The server receives the HTTP POST request from the device and parses the JSON data. During this parsing process, information on color, concept, and motif is extracted and stored in the corresponding variables. The input is the JSON data sent to the server, and the output is the parsed information.

[0196] Step 5:

[0197] The server requests the AI ​​model to generate a logo based on the analyzed input information. The server sends the following request to the AI ​​model's API endpoint:

[0198] json

[0199] {

[0200] "color": "blue",

[0201] "concept": "futuristic",

[0202] "motif": "rocket"

[0203] }

[0204] The input is the analyzed color, concept, and motif information, and the output is a request to the AI ​​model.

[0205] Step 6:

[0206] The AI ​​model begins generating logos based on the received parameters. For example, it generates multiple futuristic rocket logos with a blue base. The input is a logo generation request from the server, and the output is multiple generated logo designs. The generated logo designs are sent back to the server as JSON data, including each file path and description.

[0207] Step 7:

[0208] The server receives the logo proposal data returned by the AI ​​model and restructures it into JSON format. The data is formatted as follows:

[0209] json

[0210] {

[0211] "logos": [

[0212] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0213] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0214] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0215] ]

[0216] }

[0217] The input is the data returned from the AI ​​model, and the output is JSON formatted data sent to the device.

[0218] Step 8:

[0219] The server returns the formatted logo design data to the device. The data to be displayed in the user interface is sent as an HTTP response. The input is JSON data formatted on the server side, and the output is the HTTP response sent to the device.

[0220] Step 9:

[0221] The terminal analyzes the logo proposal data received from the server and displays it in the user interface. A thumbnail image of each logo is displayed, and the user can check the details of each logo. The input is the JSON data received from the server, and the output is the logo proposal displayed in the user interface.

[0222] Step 10:

[0223] The user selects the logo they like best from multiple logo designs and clicks the download button. The input is the user's selection information, and the output is a download link for the logo. The device retrieves the image file of the selected logo from the download link and saves it locally. The input is the download link for the selected logo, and the output is the locally saved logo file.

[0224] (Application example 1)

[0225] 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."

[0226] Conventional logo generation systems allow users to generate logos based on the colors, concept, and motif specified by the user. However, there is no mechanism for easily setting the generated logo in an electronic payment service account. This makes it difficult for users to instantly reflect the custom logo they created in their payment account. Therefore, it is necessary to provide a series of processes that allow users to intuitively generate a logo and apply it to their electronic payment account.

[0227] 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.

[0228] In this invention, the server includes means for receiving input information specified by a user, means for transmitting the input information to the server, means for the server to generate a logo based on the input information, means for providing the generated logo to the user, and means for the user to select the generated logo and set it as a custom logo for an account of an electronic payment service, thereby enabling the user to quickly apply the generated logo to their electronic payment account and perform advanced customization.

[0229] "User" refers to an individual or legal entity that uses the System to generate and configure a logo.

[0230] "Input Information" refers to information related to logo generation, such as colors, concepts, and motifs, that a user provides to the system.

[0231] "Server" refers to a computing device that processes input information received from a user and generates and serves a logo.

[0232] A "logo" refers to a symbol or design that is generated based on user-specified conditions.

[0233] "Providing" means providing the generated logo to the user in a displayable or downloadable form.

[0234] "Electronic payment service" refers to a system that processes payments electronically in online or offline commercial transactions.

[0235] "Custom Logo" means a unique logo generated based on User-specified criteria and applied to User's Electronic Payment Account.

[0236] "AI Model" refers to the artificial intelligence algorithm used to generate a logo based on input information.

[0237] "Selection" refers to the act of the user choosing one logo from multiple generated designs.

[0238] "Setting" refers to applying the selected logo to an electronic payment service account.

[0239] This invention is a system that uses an AI model to quickly generate a logo based on the user's specified colors, concept, and motif, and then sets it in an electronic payment service account. The system is configured to enable users to easily generate high-quality custom logos and instantly update them in their electronic payment accounts.

[0240] Hardware and software used

[0241] Hardware

[0242] Smartphone (iOS or Android)

[0243] software

[0244] Python 3.x

[0245] 'requests' library (for sending HTTP requests)

[0246] Data processing and calculation flow

[0247] 1. Receiving user-entered information:

[0248] Users input colors, concepts, and motifs via their smartphones, such as "blue," "futuristic," and "rocket." This information is then stored as variables on the device.

[0249] 2. Submitting input information:

[0250] The smartphone converts the information entered by the user into JSON format and sends it to the server as an HTTP POST request. The HTTP request is made using the "requests" library.

[0251] 3. On the server:

[0252] The server receives and analyzes the JSON data sent from the smartphone. The server then sends the analyzed data to the API endpoint of the AI ​​model, requesting logo generation. The AI ​​model generates a logo based on the specified colors, concept, and motif.

[0253] 4. AI Logo Generation:

[0254] The AI ​​model generates multiple logo designs and sends them back to the server, such as multiple futuristic rocket logos with a blue base.

[0255] 5. Sending the generated results:

[0256] The server then sends the logo ideas received from the AI ​​model back to the smartphone, where they are offered to the user as options.

[0257] 6. User Choices and Applications:

[0258] Users can choose the logo they like best from multiple options, download it, and apply it to their electronic payment service account. The smartphone retrieves the selected logo from the download link and saves it locally.

[0259] Specific examples

[0260] For example, if a user inputs "blue" (color), "modern" (concept), and "card" (motif), the AI ​​will generate a "card logo with a modern design based on blue" based on this information. The user can select one of the multiple logo designs generated and set it for their QR code payment account.

[0261] Prompt Sentence Examples

[0262] Enter logo color: Blue

[0263] Enter your logo concept: Modern

[0264] Enter your logo motif: Card

[0265] Please select the logo number you would like to download: 1

[0266] The system aims to use an AI model to generate a logo based on specific criteria entered by the user and then quickly apply that logo to electronic payment accounts, enabling a high level of customization for small businesses and personal brands quickly and easily.

[0267] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0268] Step 1:

[0269] Receiving user input information

[0270] The user uses a smartphone to input the colors, concept, and motif required for logo generation, and this information is stored in variables on the smartphone.

[0271] Input: Color, Concept, Motif

[0272] Data processing / calculation: Store specified information in variables

[0273] Output: Input information stored in variables on the smartphone

[0274] Step 2:

[0275] Sending input information

[0276] The device converts the information entered by the user into JSON format and sends the data to the server as an HTTP POST request.

[0277] Input: Input information in JSON format

[0278] Data processing / calculation: Data converted to JSON format is sent via HTTP request

[0279] Output: If the HTTP POST request is successful, the data arrives at the server.

[0280] Step 3:

[0281] Processing on the server

[0282] The server receives and analyzes the JSON data sent from the device, extracts color, concept, and motif information, and stores them in variables. It then sends this information to the API endpoint of the AI ​​model to request logo generation.

[0283] Input: JSON data sent from the terminal

[0284] Data processing / calculation: Parse JSON data and extract information, store it in variables, and send it to an AI model

[0285] Output: Information sent to the AI ​​model

[0286] Step 4:

[0287] AI-powered logo generation

[0288] The AI ​​model generates multiple logo designs based on the provided colors, concept, and motif, and sends the resulting logo designs back to the server as a response containing file paths and related information.

[0289] Input: Color, concept, and motif information

[0290] Data processing / calculation: Creating designs using logo generation algorithms

[0291] Output: File paths and descriptions of multiple logo designs

[0292] Step 5:

[0293] Sending the generated results

[0294] The server analyzes the logo design data received from the AI ​​model, converts it back into JSON format, and sends it back to the device.

[0295] Input: Logo design data returned by the AI ​​model

[0296] Data processing / calculation: Data analysis and conversion to JSON format

[0297] Output: JSON data sent to the device

[0298] Step 6:

[0299] Display and provide logo proposals

[0300] The device analyzes the logo proposal data received from the server and displays it on the user interface, showing the user thumbnail images of each logo so they can check the details.

[0301] Input: Logo design data in JSON format

[0302] Data processing / calculation: Data analysis and display on the interface

[0303] Output: Logo proposal displayed in the user interface

[0304] Step 7:

[0305] User selection and application

[0306] Users can choose the logo they like best from several options, download the image file of the selected logo, and set it in their electronic payment account.

[0307] Input: User selected logo design

[0308] Data processing / calculation: Download logo image file and apply it to your account

[0309] Output: Custom logo set for electronic payment account

[0310] The system allows users to select the best logo from multiple options and instantly apply it to their electronic payment account.

[0311] 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.

[0312] This invention combines a system that uses AI to generate logos based on user-specified colors, concepts, and motifs with an emotion engine that recognizes the user's emotions. The following describes specific embodiments based on the scope of this patent claim.

[0313] overview

[0314] The system involves a series of processes: receiving user input information, sending it to a server, generating a logo using an AI model, customizing it based on emotion information, and providing the generated logo, allowing users to obtain a high-quality logo that matches their emotions.

[0315] Program processing

[0316] Receiving user input information and emotion recognition

[0317] The user inputs the color, concept, and motif into the input form on the terminal. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket."

[0318] The device receives this input information and stores it in variables. The device's built-in emotion engine then recognizes the user's emotions. The emotion engine extracts emotional information from the user's facial expressions, voice, text, etc. For example, it recognizes "emotion: excitement."

[0319] Sending input information and emotional information

[0320] The device converts the user's input information and emotional information into JSON format.

[0321] json

[0322] {

[0323] "color": "blue",

[0324] "concept": "futuristic",

[0325] "motif": "rocket",

[0326] "emotion": "excitement"

[0327] }

[0328] The device sends JSON data to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[0329] Processing on the server

[0330] The server receives and analyzes the JSON data sent from the device, extracting color, concept, motif, and emotion information and storing them in variables.

[0331] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[0332] Processing logo generation requests

[0333] The server sends an HTTP POST request to the AI ​​model's API endpoint.

[0334] json

[0335] POST / generate_logo

[0336] {

[0337] "color": "blue",

[0338] "concept": "futuristic",

[0339] "motif": "rocket",

[0340] "emotion": "excitement"

[0341] }

[0342] AI-powered logo generation

[0343] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos that express the emotion "excitement" using a blue, futuristic rocket motif.

[0344] The generated logo designs are sent back to the server as a response including their respective file paths and related information.

[0345] json

[0346] {

[0347] "logos": [

[0348] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0349] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0350] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0351] ]

[0352] }

[0353] Sending the generated results

[0354] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[0355] json

[0356] {

[0357] "logos": [

[0358] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0359] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0360] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0361] ]

[0362] }

[0363] Display and provide logo proposals

[0364] The device analyzes the logo proposal data received from the server, and displays a thumbnail image and description of the logo proposal on the user interface, allowing the user to confirm the details.

[0365] User Selection and Download

[0366] The user can choose the logo design they like best from multiple options. The user selects a specific logo design and clicks the download button.

[0367] The device will retrieve the image file of the selected logo from the download link and save it locally, allowing the user to get a logo that matches their emotions.

[0368] This invention allows users to quickly and easily generate high-quality logos that match emotions. The introduction of an emotion engine makes it possible to provide more personalized logos.

[0369] The processing flow will be explained below.

[0370] Step 1: Receiving user input and recognizing emotions

[0371] The user inputs the color, concept, and motif into the input form on the terminal. For example, "Color: Blue," "Concept: Futuristic," and "Motif: Rocket" are input.

[0372] The terminal receives the input information and stores it in variables. The input information is divided into fields called "color", "concept", and "motif".

[0373] The device also uses a built-in emotion engine to recognize the user's emotions. This emotion engine extracts emotional information using techniques such as facial expression recognition, voice analysis, and text analysis. For example, it recognizes "emotion: excitement."

[0374] Step 2: Sending input and emotion information

[0375] The device converts the user's input information and emotional information into JSON format.

[0376] json

[0377] {

[0378] "color": "blue",

[0379] "concept": "futuristic",

[0380] "motif": "rocket",

[0381] "emotion": "excitement"

[0382] }

[0383] The device sends this JSON data to the server as an HTTP POST request, and the destination endpoint is the API for logo generation.

[0384] Step 3: Receiving and analyzing data on the server

[0385] The server receives the JSON data sent from the terminal.

[0386] The server analyzes the JSON data and stores the "color," "concept," "motif," and "emotional information" in the respective variables.

[0387] Step 4: Prepare your logo generation request

[0388] The server uses the extracted information (color, concept, motif, and emotional information) to prepare parameters for requesting the AI ​​model to generate a logo.

[0389] The server makes an HTTP POST request with these parameters to the AI ​​model's API endpoint.

[0390] json

[0391] POST / generate_logo

[0392] {

[0393] "color": "blue",

[0394] "concept": "futuristic",

[0395] "motif": "rocket",

[0396] "emotion": "excitement"

[0397] }

[0398] Step 5: AI-powered logo generation

[0399] Based on the parameters received, the AI ​​model generates multiple logos that match the specified colors, concepts, motifs, and emotional information.

[0400] For example, the AI ​​model generates three logos with a futuristic blue design, a rocket motif, and the emotion "excitement."

[0401] Step 6: Sending the generated results

[0402] The file path and related information of the logo design generated by the AI ​​model are sent back to the server as a response from the AI ​​model.

[0403] json

[0404] {

[0405] "logos": [

[0406] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0407] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0408] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0409] ]

[0410] }

[0411] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[0412] json

[0413] {

[0414] "logos": [

[0415] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0416] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0417] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0418] ]

[0419] }

[0420] Step 7: View logo ideas

[0421] The terminal analyzes the logo proposal data received from the server and displays it on the user interface.

[0422] The device will show the user a thumbnail image and description of each logo, allowing them to view more details.

[0423] Step 8: User Selection and Download

[0424] The user selects the logo they like best from multiple designs.

[0425] The user selects a specific logo design and clicks the download button.

[0426] The device retrieves the image file of the selected logo from the download link and saves it locally.

[0427] This allows users to quickly and easily create and obtain a personalized, high-quality logo that matches their personal style.

[0428] Example 2

[0429] 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."

[0430] Conventional logo generation systems can generate a certain logo based on the color, concept, and motif specified by the user, but they are unable to generate a logo that reflects the user's emotions. This makes it difficult to obtain a logo that reflects the user's emotions and personality. Generation results that ignore emotions result in low user satisfaction, which in turn reduces the effectiveness of the logo.

[0431] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0432] In this invention, the server includes means for receiving input information and emotion information specified by a user, means for transmitting the input information and emotion information to the server, means for generating a logo based on the input information and emotion information, and means for providing the generated logo to the user, thereby enabling the generation of a high-quality logo personalized based on the user's emotion.

[0433] "User" refers to a person who uses the System to generate a logo.

[0434] "Input information" refers to information such as colors, concepts, and motifs that the user specifies to the system.

[0435] "Emotional information" refers to information that expresses a user's emotions extracted from the user's facial expressions, voice, text, etc.

[0436] "Terminal" refers to the device used by a user to input and transmit input information and emotional information.

[0437] "Server" refers to a computer system that has the ability to receive input information and emotion information and generate a logo using an AI model.

[0438] "Logo" refers to a visual design generated based on user-specified input and emotional information.

[0439] "AI model" refers to an artificial intelligence algorithm that uses input information and emotional information to automatically generate a logo.

[0440] "Generated logo" refers to a logo design generated by an AI model based on user input and emotional information.

[0441] This invention provides a system that combines a system that generates a logo based on the color, concept, and motif specified by the user with an emotion engine that recognizes the user's emotions. Here, an embodiment of this system will be described in detail.

[0442] System Overview

[0443] The system operates through a series of processes: receiving user-input information, sending it to a server, generating a logo using an AI model, customizing it based on emotional information, and providing the generated logo.

[0444] Hardware and software used

[0445] The device receives input information from the user and recognizes emotions. The device is equipped with a camera and microphone, and these devices are used to obtain the user's emotional information. The emotion engine is software that analyzes the user's facial expressions, voice, and text to extract emotions.

[0446] The server receives and analyzes the input and emotion information sent from the device. The server is equipped with an AI model, which generates a logo based on the input and emotion information.

[0447] System Operation

[0448] Receiving user input information and emotion recognition

[0449] The user inputs the color, concept, and motif into the input form on the terminal. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket."

[0450] The device receives this input information and stores it in variables. The device's built-in emotion engine analyzes the user's facial expressions, voice, and text to extract emotional information. For example, the emotion engine recognizes "excitement."

[0451] Sending input information and emotional information

[0452] The device converts the user's input information and emotion information into JSON format and sends it to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[0453] Processing on the server

[0454] The server receives the JSON data sent from the device, analyzes the content, and stores the color, concept, motif, and emotion information in the corresponding variables. This information is used to prepare parameters for requesting the AI ​​model to generate a logo.

[0455] Processing logo generation requests

[0456] The server sends an HTTP POST request to the AI ​​model's API endpoint, including the user-specified color, concept, motif, and emotion information.

[0457] AI-powered logo generation

[0458] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos expressing "excitement" using a blue-based, futuristic rocket motif. The generated logo proposals are sent back to the server as a response, including their respective file paths and related information.

[0459] Sending and displaying the generated results

[0460] The server analyzes the logo design data it receives, converts it back to JSON format, and sends it back to the device. The device analyzes the logo design data it receives from the server and displays it on the user interface.

[0461] User Selection and Download

[0462] The user selects the logo they like best from multiple logo designs and clicks the download button. The device retrieves the image file of the selected logo from the download link and saves it locally. This allows the user to obtain a logo that matches their own emotions.

[0463] Specific examples

[0464] An example prompt might be "Generate a blue, futuristic rocket logo that reflects the emotion of excitement."

[0465] This invention allows users to quickly and easily generate high-quality logos that match emotions, and the introduction of an emotion engine makes it possible to provide more personalized logos.

[0466] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0467] Step 1:

[0468] The user inputs the color, concept, and motif into the input form on the device. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The input information is saved in the device's internal memory. The input is as follows:

[0469] json

[0470] {

[0471] "color": "blue",

[0472] "concept": "futuristic",

[0473] "motif": "rocket"

[0474] }

[0475] Step 2:

[0476] The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by the emotion engine to extract emotional information. For example, the emotion "excitement" is recognized. The recognized emotional information is stored in the device's internal memory in the following format:

[0477] json

[0478] {

[0479] "emotion": "excitement"

[0480] }

[0481] Step 3:

[0482] The device converts the user's input and emotion information into JSON format, resulting in the data in the following format:

[0483] json

[0484] {

[0485] "color": "blue",

[0486] "concept": "futuristic",

[0487] "motif": "rocket",

[0488] "emotion": "excitement"

[0489] }

[0490] Step 4:

[0491] The device sends the converted JSON data to the server as an HTTP POST request. The destination is the API endpoint for logo generation. The input of this step is the converted JSON data, and the output is the HTTP request.

[0492] Step 5:

[0493] The server receives the JSON data sent from the device and analyzes its contents. The analyzed data is stored in the server's internal memory as color, concept, motif, and emotion information. It is divided as follows:

[0494] json

[0495] {

[0496] "color": "blue",

[0497] "concept": "futuristic",

[0498] "motif": "rocket",

[0499] "emotion": "excitement"

[0500] }

[0501] Step 6:

[0502] Based on this information, the server prepares the parameters to request the AI ​​model to generate a logo. This creates the following parameters:

[0503] json

[0504] {

[0505] "color": "blue",

[0506] "concept": "futuristic",

[0507] "motif": "rocket",

[0508] "emotion": "excitement"

[0509] }

[0510] Step 7:

[0511] The server uses the prepared parameters to send an HTTP POST request to the AI ​​model's API endpoint. The input of this step is the prepared parameters, and the output is the HTTP request sent.

[0512] Step 8:

[0513] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, a logo with a blue base, a futuristic rocket motif, and the emotion "excitement" may be generated. Multiple logo designs are generated, as shown below.

[0514] json

[0515] {

[0516] "logos": [

[0517] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0518] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0519] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0520] ]

[0521] }

[0522] Step 9:

[0523] The server analyzes the received logo design data, converts it back to JSON format, and sends it back to the device. The input to this step is the logo design data returned by the AI ​​model, and the output is an HTTP response in JSON format.

[0524] Step 10:

[0525] The device analyzes the logo proposal data received from the server and displays it on the user interface, which displays a thumbnail image of the logo proposal and a description. The interface looks like this:

[0526] html

[0527]

[0528]

[0529] Futuristic Rocket 1

[0530]

[0531]

[0532]

[0533] Futuristic Rocket 2

[0534]

[0535]

[0536]

[0537] Futuristic Rocket 3

[0538]

[0539] Step 11:

[0540] The user selects the logo they like best from the displayed options and clicks the download button. For example, they can select "Futuristic Rocket 2."

[0541] Step 12:

[0542] The device retrieves the image file of the selected logo from the server and saves it to the local disk, allowing the user to download the logo that best suits their emotions.

[0543] The above are the specific processing steps of the program of this system.

[0544] (Application example 2)

[0545] 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."

[0546] Conventional logo generation systems simply generate logos based on the colors, concept, and motif specified by the user, without personalizing them to reflect the user's personal feelings or the situation. As a result, the generated logos often do not fully meet the user's expectations and needs. Furthermore, in the advertising industry, designs that appeal to emotions are in demand, so technology is needed that can generate logos that incorporate the user's emotional information. To solve this problem, a logo generation system that takes the user's emotional information into account is needed.

[0547] 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.

[0548] In this invention, the server includes means for receiving input information specified by a user, means for recognizing the user's emotional information using an emotion recognition engine and transmitting it to the server together with the input information, and means for incorporating the emotional information into an AI model to generate a logo and providing the generated logo to the user. This makes it possible to generate and provide a customized, high-quality logo that includes the user's emotional information.

[0549] "User-input information" refers to information that a user inputs by specifying a color, concept, motif, etc.

[0550] An "emotion recognition engine" is an engine that extracts emotional information from a user's facial expressions, voice, text, etc.

[0551] "Server" means a device or system that receives user input information and emotion information and generates a logo based on an AI model.

[0552] An "AI model" is a model that uses artificial intelligence technology to generate a logo based on input information and emotional information.

[0553] A "logo" is a graphic design that represents a particular brand or concept.

[0554] A "generated logo" is a logo created by an AI model based on user input and emotional information.

[0555] The "multiple logo designs" are multiple different logo designs generated based on the user's input information and emotional information.

[0556] The "means for providing" is a method or device for providing the generated logo or logo proposal to the user.

[0557] This invention combines a system that uses AI to generate logos based on user-specified colors, concepts, and motifs with an emotion engine that recognizes the user's emotions. The following describes specific embodiments based on the scope of this patent claim.

[0558] Receiving user input information and emotion recognition

[0559] The device provides an input form for users to specify the color, concept, and motif. For example, the user can input "blue" as the color, "futuristic" as the concept, and "rocket" as the motif.

[0560] The device is equipped with an emotion recognition engine that extracts emotional information in real time from the user's facial expressions, voice, text, etc. For example, the emotion is recognized as "excitement."

[0561] Sending input information and emotional information

[0562] The device converts the user's input information and emotion information into JSON format and sends it to the server as an HTTP POST request. The server receives and analyzes this information, extracting color, concept, motif, and emotion information.

[0563] Processing on the server

[0564] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[0565] The server sends an HTTP POST request to the AI ​​model's API endpoint, and the AI ​​model generates multiple logos incorporating the specified features and emotion information based on the received parameters. For example, it generates three logos that express the emotion "excitement" using a blue base and a futuristic rocket motif.

[0566] Sending and receiving logo generation results

[0567] The generated logo designs are sent back to the server as a response containing their respective file paths and related information. The server analyzes the received logo design data, converts it back into JSON format, and sends it back to the device. The device then analyzes the logo design data received from the server and displays thumbnail images and descriptions of the logo designs in the user interface. The user can then select the logo design they like best from the multiple designs and download it.

[0568] Hardware and software used

[0569] Hardware: Webcam, device (smartphone, tablet, etc.)

[0570] Software: Emotion Recognition Model, AI model, JSON format, HTTP protocol

[0571] Specific examples

[0572] For example, if a user inputs the color "red," the concept "passionate," and the motif "heart," and the emotion is recognized as "happiness," the server will send the following prompt to the AI ​​model based on this data.

[0573] Example prompt sentence:

[0574] Color: Red

[0575] Concept: Passionate

[0576] Motif: Heart

[0577] Emotion: Happiness

[0578] This makes it possible to generate and provide a customized logo that includes the user's emotional information.

[0579] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0580] Step 1:

[0581] The user inputs a color, concept, and motif into the input form on the device. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The device then stores the user's input information in variables.

[0582] Step 2:

[0583] The device's built-in emotion recognition engine uses the webcam and microphone to recognize the user's emotions. It extracts emotional information from the user's facial expressions, voice, and text, and recognizes "Emotion: Excitement." It stores the recognized emotional information in a variable.

[0584] Step 3:

[0585] The device converts the user's input information, including color, concept, motif, and emotion information, into JSON format. The converted JSON data looks like this:

[0586] json

[0587] {

[0588] "color": "blue",

[0589] "concept": "futuristic",

[0590] "motif": "rocket",

[0591] "emotion": "excitement"

[0592] }

[0593] Step 4:

[0594] The device sends the converted JSON data to the server as an HTTP POST request. The endpoint the server receives is the logo generation API.

[0595] Step 5:

[0596] The server receives and analyzes the JSON data sent from the device. Through the analysis, color, concept, motif, and emotion information are extracted and stored in variables.

[0597] Step 6:

[0598] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[0599] Step 7:

[0600] The server sends an HTTP POST request to the AI ​​model's API endpoint, which includes the following data:

[0601] json

[0602] POST / generate_logo

[0603] {

[0604] "color": "blue",

[0605] "concept": "futuristic",

[0606] "motif": "rocket",

[0607] "emotion": "excitement"

[0608] }

[0609] Step 8:

[0610] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos that express the emotion "excitement" using a futuristic rocket motif with a blue base. The generated logo proposals are sent back to the server as a response, including each file path and related information.

[0611] Step 9:

[0612] The server analyzes the received logo design data, converts it back to JSON format, and sends it back to the device. The returned data looks like this:

[0613] json

[0614] {

[0615] "logos": [

[0616] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0617] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0618] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0619] ]

[0620] }

[0621] Step 10:

[0622] The device analyzes the logo design data received from the server and displays thumbnail images and descriptions of the logo designs on the user interface. The user can then select the logo design they like best.

[0623] Step 11:

[0624] The user selects a specific logo design and clicks the download button. The device retrieves the image file of the selected logo from the download link and saves it locally. This allows the user to obtain a logo that matches their own emotions.

[0625] 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.

[0626] 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.

[0627] 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.

[0628] [Second embodiment]

[0629] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0630] 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.

[0631] 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).

[0632] 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.

[0633] 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.

[0634] 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).

[0635] 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.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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.

[0640] 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."

[0641] This system uses AI to quickly generate a logo based on the colors, concept, and motif specified by the user. The detailed implementation method is explained below.

[0642] overview

[0643] The system works through a series of processes: receiving user input, sending it to the server, generating a logo using an AI model, and providing the generated logo, allowing users to easily obtain a high-quality logo.

[0644] Program processing

[0645] Receiving user input information

[0646] The user uses a terminal to input information about the color, concept, and motif into an input form. For example, the user inputs "blue" as the color, "futuristic" as the concept, and "rocket" as the motif.

[0647] The device receives this input information, stores it in a variable, and converts it to JSON format, ready to be sent to the server.

[0648] Sending input information

[0649] The device converts the information entered by the user into JSON format and sends the information to the server as an HTTP POST request.

[0650] json

[0651] {

[0652] "color": "blue",

[0653] "concept": "futuristic",

[0654] "motif": "rocket"

[0655] }

[0656] Processing on the server

[0657] The server receives and analyzes the JSON data sent from the device, extracting information on color, concept, and motif, and storing it in the respective variables.

[0658] The server then calls the interface with the AI ​​model and requests logo generation based on the received input information. The server then passes parameters to the AI ​​model's API endpoint to start the logo generation process.

[0659] json

[0660] POST / generate_logo

[0661] {

[0662] "color": "blue",

[0663] "concept": "futuristic",

[0664] "motif": "rocket"

[0665] }

[0666] AI-powered logo generation

[0667] The AI ​​model generates multiple logo designs based on the specified color, concept, and motif, for example, generating three blue-based, futuristic rocket-themed logos.

[0668] The generated logo designs are sent back to the server as a response including their respective file paths and related information.

[0669] json

[0670] {

[0671] "logos": [

[0672] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0673] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0674] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0675] ]

[0676] }

[0677] Sending the generated results

[0678] The server analyzes the logo design data received from the AI ​​model, converts it back into JSON format, and sends it back to the device.

[0679] json

[0680] {

[0681] "logos": [

[0682] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0683] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0684] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0685] ]

[0686] }

[0687] Display and provide logo proposals

[0688] The device analyzes the logo proposal data received from the server and displays it on the user interface, showing the user thumbnail images of each logo so they can check the details.

[0689] User Selection and Download

[0690] The user selects the logo they like best from multiple logo designs and clicks the download button to download the logo. At this time, the device retrieves the image file of the selected logo from the download link and saves it locally.

[0691] Through this series of processes, users can easily generate and obtain high-quality and unique logos. This system is very useful for helping small businesses and personal brands quickly create logos.

[0692] The processing flow will be explained below.

[0693] Step 1: Receiving user input

[0694] The user inputs the color, concept, and motif into the input form on the terminal. For example, "Color: Blue," "Concept: Futuristic," and "Motif: Rocket" are input.

[0695] The terminal receives the input information and stores it in variables. The input information is divided into fields called "color", "concept", and "motif" and prepared for the next process.

[0696] Step 2: Submit your input

[0697] The terminal converts the input information into JSON format.

[0698] json

[0699] {

[0700] "color": "blue",

[0701] "concept": "futuristic",

[0702] "motif": "rocket"

[0703] }

[0704] The device sends JSON data to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[0705] Step 3: Processing on the Server

[0706] The server receives the JSON data sent from the device.

[0707] The server analyzes the received data, extracts the "color," "concept," and "motif," and stores them in variables.

[0708] Step 4: Processing the logo generation request

[0709] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo.

[0710] The server sends an HTTP POST request to the AI ​​model's API endpoint.

[0711] json

[0712] POST / generate_logo

[0713] {

[0714] "color": "blue",

[0715] "concept": "futuristic",

[0716] "motif": "rocket"

[0717] }

[0718] Step 5: AI-powered logo generation

[0719] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified features.

[0720] The AI ​​model sends a response back to the server, including the file path and data of the generated logo design.

[0721] json

[0722] {

[0723] "logos": [

[0724] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0725] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0726] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0727] ]

[0728] }

[0729] Step 6: Sending the generated results

[0730] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[0731] json

[0732] {

[0733] "logos": [

[0734] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0735] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0736] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0737] ]

[0738] }

[0739] Step 7: View and submit logo ideas

[0740] The terminal analyzes the logo proposal data received from the server.

[0741] The device displays a thumbnail image of the proposed logo and a description in the user interface.

[0742] Step 8: User Selection and Download

[0743] The user selects the logo they like best from multiple designs.

[0744] The user selects a specific logo design and clicks the download button.

[0745] The device retrieves the image file of the selected logo from the download link and saves it locally.

[0746] Through this series of steps, users can quickly get a high-quality logo without having to hire a professional designer.

[0747] Example 1

[0748] 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."

[0749] Conventional logo generation systems often fail to respond quickly and accurately to user requests, making it difficult to provide high-quality logos based on specific colors, concepts, and motifs. Furthermore, they provide insufficient support for users in selecting the most suitable logo from numerous logo designs, creating a need for an improved user experience.

[0750] 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.

[0751] In this invention, the server includes means for receiving input information specified by a user, means for converting the input information into a data format and sending it to the server, means for the server to request a logo generation from an AI model based on the input information, and means for providing the generated logo to the user. This makes it possible to quickly generate a high-quality logo based on the user's specific requirements and provide multiple logo designs to allow the user to select the most suitable logo.

[0752] A "user" is an entity that provides input information such as colors, concepts, and motifs to generate a logo using the system.

[0753] "Input information" refers to information such as colors, concepts, and motifs that a user provides to the system for logo generation.

[0754] A "data format" is the structured format into which input information is converted for transmission to the server, typically in a format such as JSON or XML.

[0755] A "server" is a computer system that has the ability to analyze received input information and request logo generation from an AI model.

[0756] "AI Model" refers to an artificial intelligence algorithm and its implementation for generating a logo based on specified parameters.

[0757] A "logo" is an image or design created to visually represent a company or brand.

[0758] "Logo ideas" refers to multiple logo variations generated by the AI ​​model and are options offered to users.

[0759] This invention is a system that uses AI to quickly generate a logo from the colors, concept, and motif specified by the user. A specific embodiment of this system will be described below.

[0760] Hardware and software used

[0761] Device: The device (e.g., computer, tablet, smartphone) on which the user enters information and on which the generated logo is displayed and downloaded.

[0762] Server: A back-end system that receives and analyzes input information and generates logos using AI models.

[0763] AI Model: An artificial intelligence model (e.g. TensorFlow, PyTorch) trained for logo generation.

[0764] API: An interface that mediates communication between the server and the AI ​​model.

[0765] System Features

[0766] Receiving user input information

[0767] The user uses the terminal to input color, concept, and motif information into the system's input form. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The terminal receives this input information and stores it in variables. Next, it converts this input information into JSON format and prepares it to be sent to the server.

[0768] Sending input information

[0769] The device sends the information entered by the user to the server as an HTTP POST request, which contains data in JSON format and is structured so that the server can parse it properly.

[0770] Processing on the server

[0771] The server analyzes the JSON data received from the device and extracts information on color, concept, and motif.The server then calls the interface with the AI ​​model and requests the AI ​​model to generate a logo based on the analyzed input information.

[0772] AI-powered logo generation

[0773] The AI ​​model generates multiple logo designs based on the specified color, concept, and motif. For example, it generates three futuristic rocket logo designs based on blue. The generated logo designs are then sent back to the server as data, including their file paths and descriptions.

[0774] Sending the generated results

[0775] The server then converts the logo design data received from the AI ​​model back into JSON format and sends it back to the device, including the file path and description of the logo design.

[0776] Display and provide logo proposals

[0777] The device analyzes the logo design data received from the server and displays it on the user interface. The user can view multiple logo designs in thumbnail format and check the details of each one.

[0778] User Selection and Download

[0779] The user selects the logo they like best from multiple logo designs and clicks the download button to download the logo. At this time, the device retrieves the image file of the selected logo from the download link and saves it locally.

[0780] Specific operation example

[0781] For example, if the user enters the following prompt sentence:

[0782] Example prompt: "Generate a blue logo featuring a futuristic rocket design."

[0783] Through this series of processes, users can easily and quickly generate and obtain high-quality logos, which is especially useful for small businesses and personal brands to quickly create logos.

[0784] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0785] Step 1:

[0786] The user uses the terminal to input color, concept, and motif information into the input form. At this time, the user enters specific information such as "blue," "futuristic," and "rocket." The input is text information entered by the user. The terminal receives this information and stores it in variables.

[0787] Step 2:

[0788] The terminal converts the received input information into JSON format. During this conversion process, the text information is structured into a JSON object like the following:

[0789] json

[0790] {

[0791] "color": "blue",

[0792] "concept": "futuristic",

[0793] "motif": "rocket"

[0794] }

[0795] The input is the user's text input information, and the output is JSON formatted data that the device prepares to send to the server as an HTTP POST request.

[0796] Step 3:

[0797] The terminal sends the generated JSON data to the server using an HTTP POST request. The input is the user's input information converted to JSON format, and the output is the HTTP request sent to the server.

[0798] Step 4:

[0799] The server receives the HTTP POST request from the device and parses the JSON data. During this parsing process, information on color, concept, and motif is extracted and stored in the corresponding variables. The input is the JSON data sent to the server, and the output is the parsed information.

[0800] Step 5:

[0801] The server requests the AI ​​model to generate a logo based on the analyzed input information. The server sends the following request to the AI ​​model's API endpoint:

[0802] json

[0803] {

[0804] "color": "blue",

[0805] "concept": "futuristic",

[0806] "motif": "rocket"

[0807] }

[0808] The input is the analyzed color, concept, and motif information, and the output is a request to the AI ​​model.

[0809] Step 6:

[0810] The AI ​​model begins generating logos based on the received parameters. For example, it generates multiple futuristic rocket logos with a blue base. The input is a logo generation request from the server, and the output is multiple generated logo designs. The generated logo designs are sent back to the server as JSON data, including each file path and description.

[0811] Step 7:

[0812] The server receives the logo proposal data returned by the AI ​​model and restructures it into JSON format. The data is formatted as follows:

[0813] json

[0814] {

[0815] "logos": [

[0816] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0817] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0818] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0819] ]

[0820] }

[0821] The input is the data returned from the AI ​​model, and the output is JSON formatted data sent to the device.

[0822] Step 8:

[0823] The server returns the formatted logo design data to the device. The data to be displayed in the user interface is sent as an HTTP response. The input is JSON data formatted on the server side, and the output is the HTTP response sent to the device.

[0824] Step 9:

[0825] The terminal analyzes the logo proposal data received from the server and displays it in the user interface. A thumbnail image of each logo is displayed, and the user can check the details of each logo. The input is the JSON data received from the server, and the output is the logo proposal displayed in the user interface.

[0826] Step 10:

[0827] The user selects the logo they like best from multiple logo designs and clicks the download button. The input is the user's selection information, and the output is a download link for the logo. The device retrieves the image file of the selected logo from the download link and saves it locally. The input is the download link for the selected logo, and the output is the locally saved logo file.

[0828] (Application example 1)

[0829] 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."

[0830] Conventional logo generation systems allow users to generate logos based on the colors, concept, and motif specified by the user. However, there is no mechanism for easily setting the generated logo in an electronic payment service account. This makes it difficult for users to instantly reflect the custom logo they created in their payment account. Therefore, it is necessary to provide a series of processes that allow users to intuitively generate a logo and apply it to their electronic payment account.

[0831] 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.

[0832] In this invention, the server includes means for receiving input information specified by a user, means for transmitting the input information to the server, means for the server to generate a logo based on the input information, means for providing the generated logo to the user, and means for the user to select the generated logo and set it as a custom logo for an account of an electronic payment service, thereby enabling the user to quickly apply the generated logo to their electronic payment account and perform advanced customization.

[0833] "User" refers to an individual or legal entity that uses the System to generate and configure a logo.

[0834] "Input Information" refers to information related to logo generation, such as colors, concepts, and motifs, that a user provides to the system.

[0835] "Server" refers to a computing device that processes input information received from a user and generates and serves a logo.

[0836] A "logo" refers to a symbol or design that is generated based on user-specified conditions.

[0837] "Providing" means providing the generated logo to the user in a displayable or downloadable form.

[0838] "Electronic payment service" refers to a system that processes payments electronically in online or offline commercial transactions.

[0839] "Custom Logo" means a unique logo generated based on User-specified criteria and applied to User's Electronic Payment Account.

[0840] "AI Model" refers to the artificial intelligence algorithm used to generate a logo based on input information.

[0841] "Selection" refers to the act of the user choosing one logo from multiple generated designs.

[0842] "Setting" refers to applying the selected logo to an electronic payment service account.

[0843] This invention is a system that uses an AI model to quickly generate a logo based on the user's specified colors, concept, and motif, and then sets it in an electronic payment service account. The system is configured to enable users to easily generate high-quality custom logos and instantly update them in their electronic payment accounts.

[0844] Hardware and software used

[0845] Hardware

[0846] Smartphone (iOS or Android)

[0847] software

[0848] Python 3.x

[0849] 'requests' library (for sending HTTP requests)

[0850] Data processing and calculation flow

[0851] 1. Receiving user-entered information:

[0852] Users input colors, concepts, and motifs via their smartphones, such as "blue," "futuristic," and "rocket." This information is then stored as variables on the device.

[0853] 2. Submitting input information:

[0854] The smartphone converts the information entered by the user into JSON format and sends it to the server as an HTTP POST request. The HTTP request is made using the "requests" library.

[0855] 3. On the server:

[0856] The server receives and analyzes the JSON data sent from the smartphone. The server then sends the analyzed data to the API endpoint of the AI ​​model, requesting logo generation. The AI ​​model generates a logo based on the specified colors, concept, and motif.

[0857] 4. AI Logo Generation:

[0858] The AI ​​model generates multiple logo designs and sends them back to the server, such as multiple futuristic rocket logos with a blue base.

[0859] 5. Sending the generated results:

[0860] The server then sends the logo ideas received from the AI ​​model back to the smartphone, where they are offered to the user as options.

[0861] 6. User Choices and Applications:

[0862] Users can choose the logo they like best from multiple options, download it, and apply it to their electronic payment service account. The smartphone retrieves the selected logo from the download link and saves it locally.

[0863] Specific examples

[0864] For example, if a user inputs "blue" (color), "modern" (concept), and "card" (motif), the AI ​​will generate a "card logo with a modern design based on blue" based on this information. The user can select one of the multiple logo designs generated and set it for their QR code payment account.

[0865] Prompt Sentence Examples

[0866] Enter logo color: Blue

[0867] Enter your logo concept: Modern

[0868] Enter your logo motif: Card

[0869] Please select the logo number you would like to download: 1

[0870] The system aims to use an AI model to generate a logo based on specific criteria entered by the user and then quickly apply that logo to electronic payment accounts, enabling a high level of customization for small businesses and personal brands quickly and easily.

[0871] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0872] Step 1:

[0873] Receiving user input information

[0874] The user uses a smartphone to input the colors, concept, and motif required for logo generation, and this information is stored in variables on the smartphone.

[0875] Input: Color, Concept, Motif

[0876] Data processing / calculation: Store specified information in variables

[0877] Output: Input information stored in variables on the smartphone

[0878] Step 2:

[0879] Sending input information

[0880] The device converts the information entered by the user into JSON format and sends the data to the server as an HTTP POST request.

[0881] Input: Input information in JSON format

[0882] Data processing / calculation: Data converted to JSON format is sent via HTTP request

[0883] Output: If the HTTP POST request is successful, the data arrives at the server.

[0884] Step 3:

[0885] Processing on the server

[0886] The server receives and analyzes the JSON data sent from the device, extracts color, concept, and motif information, and stores them in variables. It then sends this information to the API endpoint of the AI ​​model to request logo generation.

[0887] Input: JSON data sent from the terminal

[0888] Data processing / calculation: Parse JSON data and extract information, store it in variables, and send it to an AI model

[0889] Output: Information sent to the AI ​​model

[0890] Step 4:

[0891] AI-powered logo generation

[0892] The AI ​​model generates multiple logo designs based on the provided colors, concept, and motif, and sends the resulting logo designs back to the server as a response containing file paths and related information.

[0893] Input: Color, concept, and motif information

[0894] Data processing / calculation: Creating designs using logo generation algorithms

[0895] Output: File paths and descriptions of multiple logo designs

[0896] Step 5:

[0897] Sending the generated results

[0898] The server analyzes the logo design data received from the AI ​​model, converts it back into JSON format, and sends it back to the device.

[0899] Input: Logo design data returned by the AI ​​model

[0900] Data processing / calculation: Data analysis and conversion to JSON format

[0901] Output: JSON data sent to the device

[0902] Step 6:

[0903] Display and provide logo proposals

[0904] The device analyzes the logo proposal data received from the server and displays it on the user interface, showing the user thumbnail images of each logo so they can check the details.

[0905] Input: Logo design data in JSON format

[0906] Data processing / calculation: Data analysis and display on the interface

[0907] Output: Logo proposal displayed in the user interface

[0908] Step 7:

[0909] User selection and application

[0910] Users can choose the logo they like best from several options, download the image file of the selected logo, and set it in their electronic payment account.

[0911] Input: User selected logo design

[0912] Data processing / calculation: Download logo image file and apply it to your account

[0913] Output: Custom logo set for electronic payment account

[0914] The system allows users to select the best logo from multiple options and instantly apply it to their electronic payment account.

[0915] 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.

[0916] This invention combines a system that uses AI to generate logos based on user-specified colors, concepts, and motifs with an emotion engine that recognizes the user's emotions. The following describes specific embodiments based on the scope of this patent claim.

[0917] overview

[0918] The system involves a series of processes: receiving user input information, sending it to a server, generating a logo using an AI model, customizing it based on emotion information, and providing the generated logo, allowing users to obtain a high-quality logo that matches their emotions.

[0919] Program processing

[0920] Receiving user input information and emotion recognition

[0921] The user inputs the color, concept, and motif into the input form on the terminal. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket."

[0922] The device receives this input information and stores it in variables. The device's built-in emotion engine then recognizes the user's emotions. The emotion engine extracts emotional information from the user's facial expressions, voice, text, etc. For example, it recognizes "emotion: excitement."

[0923] Sending input information and emotional information

[0924] The device converts the user's input information and emotional information into JSON format.

[0925] json

[0926] {

[0927] "color": "blue",

[0928] "concept": "futuristic",

[0929] "motif": "rocket",

[0930] "emotion": "excitement"

[0931] }

[0932] The device sends JSON data to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[0933] Processing on the server

[0934] The server receives and analyzes the JSON data sent from the device, extracting color, concept, motif, and emotion information and storing them in variables.

[0935] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[0936] Processing logo generation requests

[0937] The server sends an HTTP POST request to the AI ​​model's API endpoint.

[0938] json

[0939] POST / generate_logo

[0940] {

[0941] "color": "blue",

[0942] "concept": "futuristic",

[0943] "motif": "rocket",

[0944] "emotion": "excitement"

[0945] }

[0946] AI-powered logo generation

[0947] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos that express the emotion "excitement" using a blue, futuristic rocket motif.

[0948] The generated logo designs are sent back to the server as a response including their respective file paths and related information.

[0949] json

[0950] {

[0951] "logos": [

[0952] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0953] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0954] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0955] ]

[0956] }

[0957] Sending the generated results

[0958] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[0959] json

[0960] {

[0961] "logos": [

[0962] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[0963] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[0964] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[0965] ]

[0966] }

[0967] Display and provide logo proposals

[0968] The device analyzes the logo proposal data received from the server, and displays a thumbnail image and description of the logo proposal on the user interface, allowing the user to confirm the details.

[0969] User Selection and Download

[0970] The user can choose the logo design they like best from multiple options. The user selects a specific logo design and clicks the download button.

[0971] The device will retrieve the image file of the selected logo from the download link and save it locally, allowing the user to get a logo that matches their emotions.

[0972] This invention allows users to quickly and easily generate high-quality logos that match emotions. The introduction of an emotion engine makes it possible to provide more personalized logos.

[0973] The processing flow will be explained below.

[0974] Step 1: Receiving user input and recognizing emotions

[0975] The user inputs the color, concept, and motif into the input form on the terminal. For example, "Color: Blue," "Concept: Futuristic," and "Motif: Rocket" are input.

[0976] The terminal receives the input information and stores it in variables. The input information is divided into fields called "color", "concept", and "motif".

[0977] The device also uses a built-in emotion engine to recognize the user's emotions. This emotion engine extracts emotional information using techniques such as facial expression recognition, voice analysis, and text analysis. For example, it recognizes "emotion: excitement."

[0978] Step 2: Sending input and emotion information

[0979] The device converts the user's input information and emotional information into JSON format.

[0980] json

[0981] {

[0982] "color": "blue",

[0983] "concept": "futuristic",

[0984] "motif": "rocket",

[0985] "emotion": "excitement"

[0986] }

[0987] The device sends this JSON data to the server as an HTTP POST request, and the destination endpoint is the API for logo generation.

[0988] Step 3: Receiving and analyzing data on the server

[0989] The server receives the JSON data sent from the terminal.

[0990] The server analyzes the JSON data and stores the "color," "concept," "motif," and "emotional information" in the respective variables.

[0991] Step 4: Prepare your logo generation request

[0992] The server uses the extracted information (color, concept, motif, and emotional information) to prepare parameters for requesting the AI ​​model to generate a logo.

[0993] The server makes an HTTP POST request with these parameters to the AI ​​model's API endpoint.

[0994] json

[0995] POST / generate_logo

[0996] {

[0997] "color": "blue",

[0998] "concept": "futuristic",

[0999] "motif": "rocket",

[1000] "emotion": "excitement"

[1001] }

[1002] Step 5: AI-powered logo generation

[1003] Based on the parameters received, the AI ​​model generates multiple logos that match the specified colors, concepts, motifs, and emotional information.

[1004] For example, the AI ​​model generates three logos with a futuristic blue design, a rocket motif, and the emotion "excitement."

[1005] Step 6: Sending the generated results

[1006] The file path and related information of the logo design generated by the AI ​​model are sent back to the server as a response from the AI ​​model.

[1007] json

[1008] {

[1009] "logos": [

[1010] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1011] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1012] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1013] ]

[1014] }

[1015] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[1016] json

[1017] {

[1018] "logos": [

[1019] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1020] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1021] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1022] ]

[1023] }

[1024] Step 7: View logo ideas

[1025] The terminal analyzes the logo proposal data received from the server and displays it on the user interface.

[1026] The device will show the user a thumbnail image and description of each logo, allowing them to view more details.

[1027] Step 8: User Selection and Download

[1028] The user selects the logo they like best from multiple designs.

[1029] The user selects a specific logo design and clicks the download button.

[1030] The device retrieves the image file of the selected logo from the download link and saves it locally.

[1031] This allows users to quickly and easily create and obtain a personalized, high-quality logo that matches their personal style.

[1032] Example 2

[1033] 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."

[1034] Conventional logo generation systems can generate a certain logo based on the color, concept, and motif specified by the user, but they are unable to generate a logo that reflects the user's emotions. This makes it difficult to obtain a logo that reflects the user's emotions and personality. Generation results that ignore emotions result in low user satisfaction, which in turn reduces the effectiveness of the logo.

[1035] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1036] In this invention, the server includes means for receiving input information and emotion information specified by a user, means for transmitting the input information and emotion information to the server, means for generating a logo based on the input information and emotion information, and means for providing the generated logo to the user, thereby enabling the generation of a high-quality logo personalized based on the user's emotion.

[1037] "User" refers to a person who uses the System to generate a logo.

[1038] "Input information" refers to information such as colors, concepts, and motifs that the user specifies to the system.

[1039] "Emotional information" refers to information that expresses a user's emotions extracted from the user's facial expressions, voice, text, etc.

[1040] "Terminal" refers to the device used by a user to input and transmit input information and emotional information.

[1041] "Server" refers to a computer system that has the ability to receive input information and emotion information and generate a logo using an AI model.

[1042] "Logo" refers to a visual design generated based on user-specified input and emotional information.

[1043] "AI model" refers to an artificial intelligence algorithm that uses input information and emotional information to automatically generate a logo.

[1044] "Generated logo" refers to a logo design generated by an AI model based on user input and emotional information.

[1045] This invention provides a system that combines a system that generates a logo based on the color, concept, and motif specified by the user with an emotion engine that recognizes the user's emotions. Here, an embodiment of this system will be described in detail.

[1046] System Overview

[1047] The system operates through a series of processes: receiving user-input information, sending it to a server, generating a logo using an AI model, customizing it based on emotional information, and providing the generated logo.

[1048] Hardware and software used

[1049] The device receives input information from the user and recognizes emotions. The device is equipped with a camera and microphone, and these devices are used to obtain the user's emotional information. The emotion engine is software that analyzes the user's facial expressions, voice, and text to extract emotions.

[1050] The server receives and analyzes the input and emotion information sent from the device. The server is equipped with an AI model, which generates a logo based on the input and emotion information.

[1051] System Operation

[1052] Receiving user input information and emotion recognition

[1053] The user inputs the color, concept, and motif into the input form on the terminal. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket."

[1054] The device receives this input information and stores it in variables. The device's built-in emotion engine analyzes the user's facial expressions, voice, and text to extract emotional information. For example, the emotion engine recognizes "excitement."

[1055] Sending input information and emotional information

[1056] The device converts the user's input information and emotion information into JSON format and sends it to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[1057] Processing on the server

[1058] The server receives the JSON data sent from the device, analyzes the content, and stores the color, concept, motif, and emotion information in the corresponding variables. This information is used to prepare parameters for requesting the AI ​​model to generate a logo.

[1059] Processing logo generation requests

[1060] The server sends an HTTP POST request to the AI ​​model's API endpoint, including the user-specified color, concept, motif, and emotion information.

[1061] AI-powered logo generation

[1062] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos expressing "excitement" using a blue-based, futuristic rocket motif. The generated logo proposals are sent back to the server as a response, including their respective file paths and related information.

[1063] Sending and displaying the generated results

[1064] The server analyzes the logo design data it receives, converts it back to JSON format, and sends it back to the device. The device analyzes the logo design data it receives from the server and displays it on the user interface.

[1065] User Selection and Download

[1066] The user selects the logo they like best from multiple logo designs and clicks the download button. The device retrieves the image file of the selected logo from the download link and saves it locally. This allows the user to obtain a logo that matches their own emotions.

[1067] Specific examples

[1068] An example prompt might be "Generate a blue, futuristic rocket logo that reflects the emotion of excitement."

[1069] This invention allows users to quickly and easily generate high-quality logos that match emotions, and the introduction of an emotion engine makes it possible to provide more personalized logos.

[1070] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1071] Step 1:

[1072] The user inputs the color, concept, and motif into the input form on the device. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The input information is saved in the device's internal memory. The input is as follows:

[1073] json

[1074] {

[1075] "color": "blue",

[1076] "concept": "futuristic",

[1077] "motif": "rocket"

[1078] }

[1079] Step 2:

[1080] The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by the emotion engine to extract emotional information. For example, the emotion "excitement" is recognized. The recognized emotional information is stored in the device's internal memory in the following format:

[1081] json

[1082] {

[1083] "emotion": "excitement"

[1084] }

[1085] Step 3:

[1086] The device converts the user's input and emotion information into JSON format, resulting in the data in the following format:

[1087] json

[1088] {

[1089] "color": "blue",

[1090] "concept": "futuristic",

[1091] "motif": "rocket",

[1092] "emotion": "excitement"

[1093] }

[1094] Step 4:

[1095] The device sends the converted JSON data to the server as an HTTP POST request. The destination is the API endpoint for logo generation. The input of this step is the converted JSON data, and the output is the HTTP request.

[1096] Step 5:

[1097] The server receives the JSON data sent from the device and analyzes its contents. The analyzed data is stored in the server's internal memory as color, concept, motif, and emotion information. It is divided as follows:

[1098] json

[1099] {

[1100] "color": "blue",

[1101] "concept": "futuristic",

[1102] "motif": "rocket",

[1103] "emotion": "excitement"

[1104] }

[1105] Step 6:

[1106] Based on this information, the server prepares the parameters to request the AI ​​model to generate a logo. This creates the following parameters:

[1107] json

[1108] {

[1109] "color": "blue",

[1110] "concept": "futuristic",

[1111] "motif": "rocket",

[1112] "emotion": "excitement"

[1113] }

[1114] Step 7:

[1115] The server uses the prepared parameters to send an HTTP POST request to the AI ​​model's API endpoint. The input of this step is the prepared parameters, and the output is the HTTP request sent.

[1116] Step 8:

[1117] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, a logo with a blue base, a futuristic rocket motif, and the emotion "excitement" may be generated. Multiple logo designs are generated, as shown below.

[1118] json

[1119] {

[1120] "logos": [

[1121] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1122] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1123] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1124] ]

[1125] }

[1126] Step 9:

[1127] The server analyzes the received logo design data, converts it back to JSON format, and sends it back to the device. The input to this step is the logo design data returned by the AI ​​model, and the output is an HTTP response in JSON format.

[1128] Step 10:

[1129] The device analyzes the logo proposal data received from the server and displays it on the user interface, which displays a thumbnail image of the logo proposal and a description. The interface looks like this:

[1130] html

[1131]

[1132]

[1133] Futuristic Rocket 1

[1134]

[1135]

[1136]

[1137] Futuristic Rocket 2

[1138]

[1139]

[1140]

[1141] Futuristic Rocket 3

[1142]

[1143] Step 11:

[1144] The user selects the logo they like best from the displayed options and clicks the download button. For example, they can select "Futuristic Rocket 2."

[1145] Step 12:

[1146] The device retrieves the image file of the selected logo from the server and saves it to the local disk, allowing the user to download the logo that best suits their emotions.

[1147] The above are the specific processing steps of the program of this system.

[1148] (Application example 2)

[1149] 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."

[1150] Conventional logo generation systems simply generate logos based on the colors, concept, and motif specified by the user, without personalizing them to reflect the user's personal feelings or the situation. As a result, the generated logos often do not fully meet the user's expectations and needs. Furthermore, in the advertising industry, designs that appeal to emotions are in demand, so technology is needed that can generate logos that incorporate the user's emotional information. To solve this problem, a logo generation system that takes the user's emotional information into account is needed.

[1151] 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.

[1152] In this invention, the server includes means for receiving input information specified by a user, means for recognizing the user's emotional information using an emotion recognition engine and transmitting it to the server together with the input information, and means for incorporating the emotional information into an AI model to generate a logo and providing the generated logo to the user. This makes it possible to generate and provide a customized, high-quality logo that includes the user's emotional information.

[1153] "User-input information" refers to information that a user inputs by specifying a color, concept, motif, etc.

[1154] An "emotion recognition engine" is an engine that extracts emotional information from a user's facial expressions, voice, text, etc.

[1155] "Server" means a device or system that receives user input information and emotion information and generates a logo based on an AI model.

[1156] An "AI model" is a model that uses artificial intelligence technology to generate a logo based on input information and emotional information.

[1157] A "logo" is a graphic design that represents a particular brand or concept.

[1158] A "generated logo" is a logo created by an AI model based on user input and emotional information.

[1159] The "multiple logo designs" are multiple different logo designs generated based on the user's input information and emotional information.

[1160] The "means for providing" is a method or device for providing the generated logo or logo proposal to the user.

[1161] This invention combines a system that uses AI to generate logos based on user-specified colors, concepts, and motifs with an emotion engine that recognizes the user's emotions. The following describes specific embodiments based on the scope of this patent claim.

[1162] Receiving user input information and emotion recognition

[1163] The device provides an input form for users to specify the color, concept, and motif. For example, the user can input "blue" as the color, "futuristic" as the concept, and "rocket" as the motif.

[1164] The device is equipped with an emotion recognition engine that extracts emotional information in real time from the user's facial expressions, voice, text, etc. For example, the emotion is recognized as "excitement."

[1165] Sending input information and emotional information

[1166] The device converts the user's input information and emotion information into JSON format and sends it to the server as an HTTP POST request. The server receives and analyzes this information, extracting color, concept, motif, and emotion information.

[1167] Processing on the server

[1168] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[1169] The server sends an HTTP POST request to the AI ​​model's API endpoint, and the AI ​​model generates multiple logos incorporating the specified features and emotion information based on the received parameters. For example, it generates three logos that express the emotion "excitement" using a blue base and a futuristic rocket motif.

[1170] Sending and receiving logo generation results

[1171] The generated logo designs are sent back to the server as a response containing their respective file paths and related information. The server analyzes the received logo design data, converts it back into JSON format, and sends it back to the device. The device then analyzes the logo design data received from the server and displays thumbnail images and descriptions of the logo designs in the user interface. The user can then select the logo design they like best from the multiple designs and download it.

[1172] Hardware and software used

[1173] Hardware: Webcam, device (smartphone, tablet, etc.)

[1174] Software: Emotion Recognition Model, AI model, JSON format, HTTP protocol

[1175] Specific examples

[1176] For example, if a user inputs the color "red," the concept "passionate," and the motif "heart," and the emotion is recognized as "happiness," the server will send the following prompt to the AI ​​model based on this data.

[1177] Example prompt sentence:

[1178] Color: Red

[1179] Concept: Passionate

[1180] Motif: Heart

[1181] Emotion: Happiness

[1182] This makes it possible to generate and provide a customized logo that includes the user's emotional information.

[1183] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1184] Step 1:

[1185] The user inputs a color, concept, and motif into the input form on the device. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The device then stores the user's input information in variables.

[1186] Step 2:

[1187] The device's built-in emotion recognition engine uses the webcam and microphone to recognize the user's emotions. It extracts emotional information from the user's facial expressions, voice, and text, and recognizes "Emotion: Excitement." It stores the recognized emotional information in a variable.

[1188] Step 3:

[1189] The device converts the user's input information, including color, concept, motif, and emotion information, into JSON format. The converted JSON data looks like this:

[1190] json

[1191] {

[1192] "color": "blue",

[1193] "concept": "futuristic",

[1194] "motif": "rocket",

[1195] "emotion": "excitement"

[1196] }

[1197] Step 4:

[1198] The device sends the converted JSON data to the server as an HTTP POST request. The endpoint the server receives is the logo generation API.

[1199] Step 5:

[1200] The server receives and analyzes the JSON data sent from the device. Through the analysis, color, concept, motif, and emotion information are extracted and stored in variables.

[1201] Step 6:

[1202] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[1203] Step 7:

[1204] The server sends an HTTP POST request to the AI ​​model's API endpoint, which includes the following data:

[1205] json

[1206] POST / generate_logo

[1207] {

[1208] "color": "blue",

[1209] "concept": "futuristic",

[1210] "motif": "rocket",

[1211] "emotion": "excitement"

[1212] }

[1213] Step 8:

[1214] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos that express the emotion "excitement" using a futuristic rocket motif with a blue base. The generated logo proposals are sent back to the server as a response, including each file path and related information.

[1215] Step 9:

[1216] The server analyzes the received logo design data, converts it back to JSON format, and sends it back to the device. The returned data looks like this:

[1217] json

[1218] {

[1219] "logos": [

[1220] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1221] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1222] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1223] ]

[1224] }

[1225] Step 10:

[1226] The device analyzes the logo design data received from the server and displays thumbnail images and descriptions of the logo designs on the user interface. The user can then select the logo design they like best.

[1227] Step 11:

[1228] The user selects a specific logo design and clicks the download button. The device retrieves the image file of the selected logo from the download link and saves it locally. This allows the user to obtain a logo that matches their own emotions.

[1229] 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.

[1230] 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.

[1231] 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.

[1232] [Third embodiment]

[1233] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1234] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1235] 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).

[1236] 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.

[1237] 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.

[1238] 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).

[1239] 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.

[1240] 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.

[1241] 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.

[1242] 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.

[1243] 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.

[1244] 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."

[1245] This system uses AI to quickly generate a logo based on the colors, concept, and motif specified by the user. The detailed implementation method is explained below.

[1246] overview

[1247] The system works through a series of processes: receiving user input, sending it to the server, generating a logo using an AI model, and providing the generated logo, allowing users to easily obtain a high-quality logo.

[1248] Program processing

[1249] Receiving user input information

[1250] The user uses a terminal to input information about the color, concept, and motif into an input form. For example, the user inputs "blue" as the color, "futuristic" as the concept, and "rocket" as the motif.

[1251] The device receives this input information, stores it in a variable, and converts it to JSON format, ready to be sent to the server.

[1252] Sending input information

[1253] The device converts the information entered by the user into JSON format and sends the information to the server as an HTTP POST request.

[1254] json

[1255] {

[1256] "color": "blue",

[1257] "concept": "futuristic",

[1258] "motif": "rocket"

[1259] }

[1260] Processing on the server

[1261] The server receives and analyzes the JSON data sent from the device, extracting information on color, concept, and motif, and storing it in the respective variables.

[1262] The server then calls the interface with the AI ​​model and requests logo generation based on the received input information. The server then passes parameters to the AI ​​model's API endpoint to start the logo generation process.

[1263] json

[1264] POST / generate_logo

[1265] {

[1266] "color": "blue",

[1267] "concept": "futuristic",

[1268] "motif": "rocket"

[1269] }

[1270] AI-powered logo generation

[1271] The AI ​​model generates multiple logo designs based on the specified color, concept, and motif, for example, generating three blue-based, futuristic rocket-themed logos.

[1272] The generated logo designs are sent back to the server as a response including their respective file paths and related information.

[1273] json

[1274] {

[1275] "logos": [

[1276] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1277] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1278] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1279] ]

[1280] }

[1281] Sending the generated results

[1282] The server analyzes the logo design data received from the AI ​​model, converts it back into JSON format, and sends it back to the device.

[1283] json

[1284] {

[1285] "logos": [

[1286] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1287] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1288] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1289] ]

[1290] }

[1291] Display and provide logo proposals

[1292] The device analyzes the logo proposal data received from the server and displays it on the user interface, showing the user thumbnail images of each logo so they can check the details.

[1293] User Selection and Download

[1294] The user selects the logo they like best from multiple logo designs and clicks the download button to download the logo. At this time, the device retrieves the image file of the selected logo from the download link and saves it locally.

[1295] Through this series of processes, users can easily generate and obtain high-quality and unique logos. This system is very useful for helping small businesses and personal brands quickly create logos.

[1296] The processing flow will be explained below.

[1297] Step 1: Receiving user input

[1298] The user inputs the color, concept, and motif into the input form on the terminal. For example, "Color: Blue," "Concept: Futuristic," and "Motif: Rocket" are input.

[1299] The terminal receives the input information and stores it in variables. The input information is divided into fields called "color", "concept", and "motif" and prepared for the next process.

[1300] Step 2: Submit your input

[1301] The terminal converts the input information into JSON format.

[1302] json

[1303] {

[1304] "color": "blue",

[1305] "concept": "futuristic",

[1306] "motif": "rocket"

[1307] }

[1308] The device sends JSON data to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[1309] Step 3: Processing on the Server

[1310] The server receives the JSON data sent from the device.

[1311] The server analyzes the received data, extracts the "color," "concept," and "motif," and stores them in variables.

[1312] Step 4: Processing the logo generation request

[1313] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo.

[1314] The server sends an HTTP POST request to the AI ​​model's API endpoint.

[1315] json

[1316] POST / generate_logo

[1317] {

[1318] "color": "blue",

[1319] "concept": "futuristic",

[1320] "motif": "rocket"

[1321] }

[1322] Step 5: AI-powered logo generation

[1323] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified features.

[1324] The AI ​​model sends a response back to the server, including the file path and data of the generated logo design.

[1325] json

[1326] {

[1327] "logos": [

[1328] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1329] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1330] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1331] ]

[1332] }

[1333] Step 6: Sending the generated results

[1334] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[1335] json

[1336] {

[1337] "logos": [

[1338] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1339] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1340] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1341] ]

[1342] }

[1343] Step 7: View and submit logo ideas

[1344] The terminal analyzes the logo proposal data received from the server.

[1345] The device displays a thumbnail image of the proposed logo and a description in the user interface.

[1346] Step 8: User Selection and Download

[1347] The user selects the logo they like best from multiple designs.

[1348] The user selects a specific logo design and clicks the download button.

[1349] The device retrieves the image file of the selected logo from the download link and saves it locally.

[1350] Through this series of steps, users can quickly get a high-quality logo without having to hire a professional designer.

[1351] Example 1

[1352] 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."

[1353] Conventional logo generation systems often fail to respond quickly and accurately to user requests, making it difficult to provide high-quality logos based on specific colors, concepts, and motifs. Furthermore, they provide insufficient support for users in selecting the most suitable logo from numerous logo designs, creating a need for an improved user experience.

[1354] 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.

[1355] In this invention, the server includes means for receiving input information specified by a user, means for converting the input information into a data format and sending it to the server, means for the server to request a logo generation from an AI model based on the input information, and means for providing the generated logo to the user. This makes it possible to quickly generate a high-quality logo based on the user's specific requirements and provide multiple logo designs to allow the user to select the most suitable logo.

[1356] A "user" is an entity that provides input information such as colors, concepts, and motifs to generate a logo using the system.

[1357] "Input information" refers to information such as colors, concepts, and motifs that a user provides to the system for logo generation.

[1358] A "data format" is the structured format into which input information is converted for transmission to the server, typically in a format such as JSON or XML.

[1359] A "server" is a computer system that has the ability to analyze received input information and request logo generation from an AI model.

[1360] "AI Model" refers to an artificial intelligence algorithm and its implementation for generating a logo based on specified parameters.

[1361] A "logo" is an image or design created to visually represent a company or brand.

[1362] "Logo ideas" refers to multiple logo variations generated by the AI ​​model and are options offered to users.

[1363] This invention is a system that uses AI to quickly generate a logo from the colors, concept, and motif specified by the user. A specific embodiment of this system will be described below.

[1364] Hardware and software used

[1365] Device: The device (e.g., computer, tablet, smartphone) on which the user enters information and on which the generated logo is displayed and downloaded.

[1366] Server: A back-end system that receives and analyzes input information and generates logos using AI models.

[1367] AI Model: An artificial intelligence model (e.g. TensorFlow, PyTorch) trained for logo generation.

[1368] API: An interface that mediates communication between the server and the AI ​​model.

[1369] System Features

[1370] Receiving user input information

[1371] The user uses the terminal to input color, concept, and motif information into the system's input form. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The terminal receives this input information and stores it in variables. Next, it converts this input information into JSON format and prepares it to be sent to the server.

[1372] Sending input information

[1373] The device sends the information entered by the user to the server as an HTTP POST request, which contains data in JSON format and is structured so that the server can parse it properly.

[1374] Processing on the server

[1375] The server analyzes the JSON data received from the device and extracts information on color, concept, and motif.The server then calls the interface with the AI ​​model and requests the AI ​​model to generate a logo based on the analyzed input information.

[1376] AI-powered logo generation

[1377] The AI ​​model generates multiple logo designs based on the specified color, concept, and motif. For example, it generates three futuristic rocket logo designs based on blue. The generated logo designs are then sent back to the server as data, including their file paths and descriptions.

[1378] Sending the generated results

[1379] The server then converts the logo design data received from the AI ​​model back into JSON format and sends it back to the device, including the file path and description of the logo design.

[1380] Display and provide logo proposals

[1381] The device analyzes the logo design data received from the server and displays it on the user interface. The user can view multiple logo designs in thumbnail format and check the details of each one.

[1382] User Selection and Download

[1383] The user selects the logo they like best from multiple logo designs and clicks the download button to download the logo. At this time, the device retrieves the image file of the selected logo from the download link and saves it locally.

[1384] Specific operation example

[1385] For example, if the user enters the following prompt sentence:

[1386] Example prompt: "Generate a blue logo featuring a futuristic rocket design."

[1387] Through this series of processes, users can easily and quickly generate and obtain high-quality logos, which is especially useful for small businesses and personal brands to quickly create logos.

[1388] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1389] Step 1:

[1390] The user uses the terminal to input color, concept, and motif information into the input form. At this time, the user enters specific information such as "blue," "futuristic," and "rocket." The input is text information entered by the user. The terminal receives this information and stores it in variables.

[1391] Step 2:

[1392] The terminal converts the received input information into JSON format. During this conversion process, the text information is structured into a JSON object like the following:

[1393] json

[1394] {

[1395] "color": "blue",

[1396] "concept": "futuristic",

[1397] "motif": "rocket"

[1398] }

[1399] The input is the user's text input information, and the output is JSON formatted data that the device prepares to send to the server as an HTTP POST request.

[1400] Step 3:

[1401] The terminal sends the generated JSON data to the server using an HTTP POST request. The input is the user's input information converted to JSON format, and the output is the HTTP request sent to the server.

[1402] Step 4:

[1403] The server receives the HTTP POST request from the device and parses the JSON data. During this parsing process, information on color, concept, and motif is extracted and stored in the corresponding variables. The input is the JSON data sent to the server, and the output is the parsed information.

[1404] Step 5:

[1405] The server requests the AI ​​model to generate a logo based on the analyzed input information. The server sends the following request to the AI ​​model's API endpoint:

[1406] json

[1407] {

[1408] "color": "blue",

[1409] "concept": "futuristic",

[1410] "motif": "rocket"

[1411] }

[1412] The input is the analyzed color, concept, and motif information, and the output is a request to the AI ​​model.

[1413] Step 6:

[1414] The AI ​​model begins generating logos based on the received parameters. For example, it generates multiple futuristic rocket logos with a blue base. The input is a logo generation request from the server, and the output is multiple generated logo designs. The generated logo designs are sent back to the server as JSON data, including each file path and description.

[1415] Step 7:

[1416] The server receives the logo proposal data returned by the AI ​​model and restructures it into JSON format. The data is formatted as follows:

[1417] json

[1418] {

[1419] "logos": [

[1420] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1421] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1422] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1423] ]

[1424] }

[1425] The input is the data returned from the AI ​​model, and the output is JSON formatted data sent to the device.

[1426] Step 8:

[1427] The server returns the formatted logo design data to the device. The data to be displayed in the user interface is sent as an HTTP response. The input is JSON data formatted on the server side, and the output is the HTTP response sent to the device.

[1428] Step 9:

[1429] The terminal analyzes the logo proposal data received from the server and displays it in the user interface. A thumbnail image of each logo is displayed, and the user can check the details of each logo. The input is the JSON data received from the server, and the output is the logo proposal displayed in the user interface.

[1430] Step 10:

[1431] The user selects the logo they like best from multiple logo designs and clicks the download button. The input is the user's selection information, and the output is a download link for the logo. The device retrieves the image file of the selected logo from the download link and saves it locally. The input is the download link for the selected logo, and the output is the locally saved logo file.

[1432] (Application example 1)

[1433] 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."

[1434] Conventional logo generation systems allow users to generate logos based on the colors, concept, and motif specified by the user. However, there is no mechanism for easily setting the generated logo in an electronic payment service account. This makes it difficult for users to instantly reflect the custom logo they created in their payment account. Therefore, it is necessary to provide a series of processes that allow users to intuitively generate a logo and apply it to their electronic payment account.

[1435] 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.

[1436] In this invention, the server includes means for receiving input information specified by a user, means for transmitting the input information to the server, means for the server to generate a logo based on the input information, means for providing the generated logo to the user, and means for the user to select the generated logo and set it as a custom logo for an account of an electronic payment service, thereby enabling the user to quickly apply the generated logo to their electronic payment account and perform advanced customization.

[1437] "User" refers to an individual or legal entity that uses the System to generate and configure a logo.

[1438] "Input Information" refers to information related to logo generation, such as colors, concepts, and motifs, that a user provides to the system.

[1439] "Server" refers to a computing device that processes input information received from a user and generates and serves a logo.

[1440] A "logo" refers to a symbol or design that is generated based on user-specified conditions.

[1441] "Providing" means providing the generated logo to the user in a displayable or downloadable form.

[1442] "Electronic payment service" refers to a system that processes payments electronically in online or offline commercial transactions.

[1443] "Custom Logo" means a unique logo generated based on User-specified criteria and applied to User's Electronic Payment Account.

[1444] "AI Model" refers to the artificial intelligence algorithm used to generate a logo based on input information.

[1445] "Selection" refers to the act of the user choosing one logo from multiple generated designs.

[1446] "Setting" refers to applying the selected logo to an electronic payment service account.

[1447] This invention is a system that uses an AI model to quickly generate a logo based on the user's specified colors, concept, and motif, and then sets it in an electronic payment service account. The system is configured to enable users to easily generate high-quality custom logos and instantly update them in their electronic payment accounts.

[1448] Hardware and software used

[1449] Hardware

[1450] Smartphone (iOS or Android)

[1451] software

[1452] Python 3.x

[1453] 'requests' library (for sending HTTP requests)

[1454] Data processing and calculation flow

[1455] 1. Receiving user-entered information:

[1456] Users input colors, concepts, and motifs via their smartphones, such as "blue," "futuristic," and "rocket." This information is then stored as variables on the device.

[1457] 2. Submitting input information:

[1458] The smartphone converts the information entered by the user into JSON format and sends it to the server as an HTTP POST request. The HTTP request is made using the "requests" library.

[1459] 3. On the server:

[1460] The server receives and analyzes the JSON data sent from the smartphone. The server then sends the analyzed data to the API endpoint of the AI ​​model, requesting logo generation. The AI ​​model generates a logo based on the specified colors, concept, and motif.

[1461] 4. AI Logo Generation:

[1462] The AI ​​model generates multiple logo designs and sends them back to the server, such as multiple futuristic rocket logos with a blue base.

[1463] 5. Sending the generated results:

[1464] The server then sends the logo ideas received from the AI ​​model back to the smartphone, where they are offered to the user as options.

[1465] 6. User Choices and Applications:

[1466] Users can choose the logo they like best from multiple options, download it, and apply it to their electronic payment service account. The smartphone retrieves the selected logo from the download link and saves it locally.

[1467] Specific examples

[1468] For example, if a user inputs "blue" (color), "modern" (concept), and "card" (motif), the AI ​​will generate a "card logo with a modern design based on blue" based on this information. The user can select one of the multiple logo designs generated and set it for their QR code payment account.

[1469] Prompt Sentence Examples

[1470] Enter logo color: Blue

[1471] Enter your logo concept: Modern

[1472] Enter your logo motif: Card

[1473] Please select the logo number you would like to download: 1

[1474] The system aims to use an AI model to generate a logo based on specific criteria entered by the user and then quickly apply that logo to electronic payment accounts, enabling a high level of customization for small businesses and personal brands quickly and easily.

[1475] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1476] Step 1:

[1477] Receiving user input information

[1478] The user uses a smartphone to input the colors, concept, and motif required for logo generation, and this information is stored in variables on the smartphone.

[1479] Input: Color, Concept, Motif

[1480] Data processing / calculation: Store specified information in variables

[1481] Output: Input information stored in variables on the smartphone

[1482] Step 2:

[1483] Sending input information

[1484] The device converts the information entered by the user into JSON format and sends the data to the server as an HTTP POST request.

[1485] Input: Input information in JSON format

[1486] Data processing / calculation: Data converted to JSON format is sent via HTTP request

[1487] Output: If the HTTP POST request is successful, the data arrives at the server.

[1488] Step 3:

[1489] Processing on the server

[1490] The server receives and analyzes the JSON data sent from the device, extracts color, concept, and motif information, and stores them in variables. It then sends this information to the API endpoint of the AI ​​model to request logo generation.

[1491] Input: JSON data sent from the terminal

[1492] Data processing / calculation: Parse JSON data and extract information, store it in variables, and send it to an AI model

[1493] Output: Information sent to the AI ​​model

[1494] Step 4:

[1495] AI-powered logo generation

[1496] The AI ​​model generates multiple logo designs based on the provided colors, concept, and motif, and sends the resulting logo designs back to the server as a response containing file paths and related information.

[1497] Input: Color, concept, and motif information

[1498] Data processing / calculation: Creating designs using logo generation algorithms

[1499] Output: File paths and descriptions of multiple logo designs

[1500] Step 5:

[1501] Sending the generated results

[1502] The server analyzes the logo design data received from the AI ​​model, converts it back into JSON format, and sends it back to the device.

[1503] Input: Logo design data returned by the AI ​​model

[1504] Data processing / calculation: Data analysis and conversion to JSON format

[1505] Output: JSON data sent to the device

[1506] Step 6:

[1507] Display and provide logo proposals

[1508] The device analyzes the logo proposal data received from the server and displays it on the user interface, showing the user thumbnail images of each logo so they can check the details.

[1509] Input: Logo design data in JSON format

[1510] Data processing / calculation: Data analysis and display on the interface

[1511] Output: Logo proposal displayed in the user interface

[1512] Step 7:

[1513] User selection and application

[1514] Users can choose the logo they like best from several options, download the image file of the selected logo, and set it in their electronic payment account.

[1515] Input: User selected logo design

[1516] Data processing / calculation: Download logo image file and apply it to your account

[1517] Output: Custom logo set for electronic payment account

[1518] The system allows users to select the best logo from multiple options and instantly apply it to their electronic payment account.

[1519] 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.

[1520] This invention combines a system that uses AI to generate logos based on user-specified colors, concepts, and motifs with an emotion engine that recognizes the user's emotions. The following describes specific embodiments based on the scope of this patent claim.

[1521] overview

[1522] The system involves a series of processes: receiving user input information, sending it to a server, generating a logo using an AI model, customizing it based on emotion information, and providing the generated logo, allowing users to obtain a high-quality logo that matches their emotions.

[1523] Program processing

[1524] Receiving user input information and emotion recognition

[1525] The user inputs the color, concept, and motif into the input form on the terminal. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket."

[1526] The device receives this input information and stores it in variables. The device's built-in emotion engine then recognizes the user's emotions. The emotion engine extracts emotional information from the user's facial expressions, voice, text, etc. For example, it recognizes "emotion: excitement."

[1527] Sending input information and emotional information

[1528] The device converts the user's input information and emotional information into JSON format.

[1529] json

[1530] {

[1531] "color": "blue",

[1532] "concept": "futuristic",

[1533] "motif": "rocket",

[1534] "emotion": "excitement"

[1535] }

[1536] The device sends JSON data to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[1537] Processing on the server

[1538] The server receives and analyzes the JSON data sent from the device, extracting color, concept, motif, and emotion information and storing them in variables.

[1539] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[1540] Processing logo generation requests

[1541] The server sends an HTTP POST request to the AI ​​model's API endpoint.

[1542] json

[1543] POST / generate_logo

[1544] {

[1545] "color": "blue",

[1546] "concept": "futuristic",

[1547] "motif": "rocket",

[1548] "emotion": "excitement"

[1549] }

[1550] AI-powered logo generation

[1551] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos that express the emotion "excitement" using a blue, futuristic rocket motif.

[1552] The generated logo designs are sent back to the server as a response including their respective file paths and related information.

[1553] json

[1554] {

[1555] "logos": [

[1556] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1557] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1558] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1559] ]

[1560] }

[1561] Sending the generated results

[1562] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[1563] json

[1564] {

[1565] "logos": [

[1566] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1567] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1568] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1569] ]

[1570] }

[1571] Display and provide logo proposals

[1572] The device analyzes the logo proposal data received from the server, and displays a thumbnail image and description of the logo proposal on the user interface, allowing the user to confirm the details.

[1573] User Selection and Download

[1574] The user can choose the logo design they like best from multiple options. The user selects a specific logo design and clicks the download button.

[1575] The device will retrieve the image file of the selected logo from the download link and save it locally, allowing the user to get a logo that matches their emotions.

[1576] This invention allows users to quickly and easily generate high-quality logos that match emotions. The introduction of an emotion engine makes it possible to provide more personalized logos.

[1577] The processing flow will be explained below.

[1578] Step 1: Receiving user input and recognizing emotions

[1579] The user inputs the color, concept, and motif into the input form on the terminal. For example, "Color: Blue," "Concept: Futuristic," and "Motif: Rocket" are input.

[1580] The terminal receives the input information and stores it in variables. The input information is divided into fields called "color", "concept", and "motif".

[1581] The device also uses a built-in emotion engine to recognize the user's emotions. This emotion engine extracts emotional information using techniques such as facial expression recognition, voice analysis, and text analysis. For example, it recognizes "emotion: excitement."

[1582] Step 2: Sending input and emotion information

[1583] The device converts the user's input information and emotional information into JSON format.

[1584] json

[1585] {

[1586] "color": "blue",

[1587] "concept": "futuristic",

[1588] "motif": "rocket",

[1589] "emotion": "excitement"

[1590] }

[1591] The device sends this JSON data to the server as an HTTP POST request, and the destination endpoint is the API for logo generation.

[1592] Step 3: Receiving and analyzing data on the server

[1593] The server receives the JSON data sent from the terminal.

[1594] The server analyzes the JSON data and stores the "color," "concept," "motif," and "emotional information" in the respective variables.

[1595] Step 4: Prepare your logo generation request

[1596] The server uses the extracted information (color, concept, motif, and emotional information) to prepare parameters for requesting the AI ​​model to generate a logo.

[1597] The server makes an HTTP POST request with these parameters to the AI ​​model's API endpoint.

[1598] json

[1599] POST / generate_logo

[1600] {

[1601] "color": "blue",

[1602] "concept": "futuristic",

[1603] "motif": "rocket",

[1604] "emotion": "excitement"

[1605] }

[1606] Step 5: AI-powered logo generation

[1607] Based on the parameters received, the AI ​​model generates multiple logos that match the specified colors, concepts, motifs, and emotional information.

[1608] For example, the AI ​​model generates three logos with a futuristic blue design, a rocket motif, and the emotion "excitement."

[1609] Step 6: Sending the generated results

[1610] The file path and related information of the logo design generated by the AI ​​model are sent back to the server as a response from the AI ​​model.

[1611] json

[1612] {

[1613] "logos": [

[1614] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1615] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1616] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1617] ]

[1618] }

[1619] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[1620] json

[1621] {

[1622] "logos": [

[1623] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1624] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1625] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1626] ]

[1627] }

[1628] Step 7: View logo ideas

[1629] The terminal analyzes the logo proposal data received from the server and displays it on the user interface.

[1630] The device will show the user a thumbnail image and description of each logo, allowing them to view more details.

[1631] Step 8: User Selection and Download

[1632] The user selects the logo they like best from multiple designs.

[1633] The user selects a specific logo design and clicks the download button.

[1634] The device retrieves the image file of the selected logo from the download link and saves it locally.

[1635] This allows users to quickly and easily create and obtain a personalized, high-quality logo that matches their personal style.

[1636] Example 2

[1637] 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."

[1638] Conventional logo generation systems can generate a certain logo based on the color, concept, and motif specified by the user, but they are unable to generate a logo that reflects the user's emotions. This makes it difficult to obtain a logo that reflects the user's emotions and personality. Generation results that ignore emotions result in low user satisfaction, which in turn reduces the effectiveness of the logo.

[1639] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1640] In this invention, the server includes means for receiving input information and emotion information specified by a user, means for transmitting the input information and emotion information to the server, means for generating a logo based on the input information and emotion information, and means for providing the generated logo to the user, thereby enabling the generation of a high-quality logo personalized based on the user's emotion.

[1641] "User" refers to a person who uses the System to generate a logo.

[1642] "Input information" refers to information such as colors, concepts, and motifs that the user specifies to the system.

[1643] "Emotional information" refers to information that expresses a user's emotions extracted from the user's facial expressions, voice, text, etc.

[1644] "Terminal" refers to the device used by a user to input and transmit input information and emotional information.

[1645] "Server" refers to a computer system that has the ability to receive input information and emotion information and generate a logo using an AI model.

[1646] "Logo" refers to a visual design generated based on user-specified input and emotional information.

[1647] "AI model" refers to an artificial intelligence algorithm that uses input information and emotional information to automatically generate a logo.

[1648] "Generated logo" refers to a logo design generated by an AI model based on user input and emotional information.

[1649] This invention provides a system that combines a system that generates a logo based on the color, concept, and motif specified by the user with an emotion engine that recognizes the user's emotions. Here, an embodiment of this system will be described in detail.

[1650] System Overview

[1651] The system operates through a series of processes: receiving user-input information, sending it to a server, generating a logo using an AI model, customizing it based on emotional information, and providing the generated logo.

[1652] Hardware and software used

[1653] The device receives input information from the user and recognizes emotions. The device is equipped with a camera and microphone, and these devices are used to obtain the user's emotional information. The emotion engine is software that analyzes the user's facial expressions, voice, and text to extract emotions.

[1654] The server receives and analyzes the input and emotion information sent from the device. The server is equipped with an AI model, which generates a logo based on the input and emotion information.

[1655] System Operation

[1656] Receiving user input information and emotion recognition

[1657] The user inputs the color, concept, and motif into the input form on the terminal. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket."

[1658] The device receives this input information and stores it in variables. The device's built-in emotion engine analyzes the user's facial expressions, voice, and text to extract emotional information. For example, the emotion engine recognizes "excitement."

[1659] Sending input information and emotional information

[1660] The device converts the user's input information and emotion information into JSON format and sends it to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[1661] Processing on the server

[1662] The server receives the JSON data sent from the device, analyzes the content, and stores the color, concept, motif, and emotion information in the corresponding variables. This information is used to prepare parameters for requesting the AI ​​model to generate a logo.

[1663] Processing logo generation requests

[1664] The server sends an HTTP POST request to the AI ​​model's API endpoint, including the user-specified color, concept, motif, and emotion information.

[1665] AI-powered logo generation

[1666] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos expressing "excitement" using a blue-based, futuristic rocket motif. The generated logo proposals are sent back to the server as a response, including their respective file paths and related information.

[1667] Sending and displaying the generated results

[1668] The server analyzes the logo design data it receives, converts it back to JSON format, and sends it back to the device. The device analyzes the logo design data it receives from the server and displays it on the user interface.

[1669] User Selection and Download

[1670] The user selects the logo they like best from multiple logo designs and clicks the download button. The device retrieves the image file of the selected logo from the download link and saves it locally. This allows the user to obtain a logo that matches their own emotions.

[1671] Specific examples

[1672] An example prompt might be "Generate a blue, futuristic rocket logo that reflects the emotion of excitement."

[1673] This invention allows users to quickly and easily generate high-quality logos that match emotions, and the introduction of an emotion engine makes it possible to provide more personalized logos.

[1674] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1675] Step 1:

[1676] The user inputs the color, concept, and motif into the input form on the device. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The input information is saved in the device's internal memory. The input is as follows:

[1677] json

[1678] {

[1679] "color": "blue",

[1680] "concept": "futuristic",

[1681] "motif": "rocket"

[1682] }

[1683] Step 2:

[1684] The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by the emotion engine to extract emotional information. For example, the emotion "excitement" is recognized. The recognized emotional information is stored in the device's internal memory in the following format:

[1685] json

[1686] {

[1687] "emotion": "excitement"

[1688] }

[1689] Step 3:

[1690] The device converts the user's input and emotion information into JSON format, resulting in the data in the following format:

[1691] json

[1692] {

[1693] "color": "blue",

[1694] "concept": "futuristic",

[1695] "motif": "rocket",

[1696] "emotion": "excitement"

[1697] }

[1698] Step 4:

[1699] The device sends the converted JSON data to the server as an HTTP POST request. The destination is the API endpoint for logo generation. The input of this step is the converted JSON data, and the output is the HTTP request.

[1700] Step 5:

[1701] The server receives the JSON data sent from the device and analyzes its contents. The analyzed data is stored in the server's internal memory as color, concept, motif, and emotion information. It is divided as follows:

[1702] json

[1703] {

[1704] "color": "blue",

[1705] "concept": "futuristic",

[1706] "motif": "rocket",

[1707] "emotion": "excitement"

[1708] }

[1709] Step 6:

[1710] Based on this information, the server prepares the parameters to request the AI ​​model to generate a logo. This creates the following parameters:

[1711] json

[1712] {

[1713] "color": "blue",

[1714] "concept": "futuristic",

[1715] "motif": "rocket",

[1716] "emotion": "excitement"

[1717] }

[1718] Step 7:

[1719] The server uses the prepared parameters to send an HTTP POST request to the AI ​​model's API endpoint. The input of this step is the prepared parameters, and the output is the HTTP request sent.

[1720] Step 8:

[1721] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, a logo with a blue base, a futuristic rocket motif, and the emotion "excitement" may be generated. Multiple logo designs are generated, as shown below.

[1722] json

[1723] {

[1724] "logos": [

[1725] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1726] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1727] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1728] ]

[1729] }

[1730] Step 9:

[1731] The server analyzes the received logo design data, converts it back to JSON format, and sends it back to the device. The input to this step is the logo design data returned by the AI ​​model, and the output is an HTTP response in JSON format.

[1732] Step 10:

[1733] The device analyzes the logo proposal data received from the server and displays it on the user interface, which displays a thumbnail image of the logo proposal and a description. The interface looks like this:

[1734] html

[1735]

[1736]

[1737] Futuristic Rocket 1

[1738]

[1739]

[1740]

[1741] Futuristic Rocket 2

[1742]

[1743]

[1744]

[1745] Futuristic Rocket 3

[1746]

[1747] Step 11:

[1748] The user selects the logo they like best from the displayed options and clicks the download button. For example, they can select "Futuristic Rocket 2."

[1749] Step 12:

[1750] The device retrieves the image file of the selected logo from the server and saves it to the local disk, allowing the user to download the logo that best suits their emotions.

[1751] The above are the specific processing steps of the program of this system.

[1752] (Application example 2)

[1753] 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."

[1754] Conventional logo generation systems simply generate logos based on the colors, concept, and motif specified by the user, without personalizing them to reflect the user's personal feelings or the situation. As a result, the generated logos often do not fully meet the user's expectations and needs. Furthermore, in the advertising industry, designs that appeal to emotions are in demand, so technology is needed that can generate logos that incorporate the user's emotional information. To solve this problem, a logo generation system that takes the user's emotional information into account is needed.

[1755] 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.

[1756] In this invention, the server includes means for receiving input information specified by a user, means for recognizing the user's emotional information using an emotion recognition engine and transmitting it to the server together with the input information, and means for incorporating the emotional information into an AI model to generate a logo and providing the generated logo to the user. This makes it possible to generate and provide a customized, high-quality logo that includes the user's emotional information.

[1757] "User-input information" refers to information that a user inputs by specifying a color, concept, motif, etc.

[1758] An "emotion recognition engine" is an engine that extracts emotional information from a user's facial expressions, voice, text, etc.

[1759] "Server" means a device or system that receives user input information and emotion information and generates a logo based on an AI model.

[1760] An "AI model" is a model that uses artificial intelligence technology to generate a logo based on input information and emotional information.

[1761] A "logo" is a graphic design that represents a particular brand or concept.

[1762] A "generated logo" is a logo created by an AI model based on user input and emotional information.

[1763] The "multiple logo designs" are multiple different logo designs generated based on the user's input information and emotional information.

[1764] The "means for providing" is a method or device for providing the generated logo or logo proposal to the user.

[1765] This invention combines a system that uses AI to generate logos based on user-specified colors, concepts, and motifs with an emotion engine that recognizes the user's emotions. The following describes specific embodiments based on the scope of this patent claim.

[1766] Receiving user input information and emotion recognition

[1767] The device provides an input form for users to specify the color, concept, and motif. For example, the user can input "blue" as the color, "futuristic" as the concept, and "rocket" as the motif.

[1768] The device is equipped with an emotion recognition engine that extracts emotional information in real time from the user's facial expressions, voice, text, etc. For example, the emotion is recognized as "excitement."

[1769] Sending input information and emotional information

[1770] The device converts the user's input information and emotion information into JSON format and sends it to the server as an HTTP POST request. The server receives and analyzes this information, extracting color, concept, motif, and emotion information.

[1771] Processing on the server

[1772] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[1773] The server sends an HTTP POST request to the AI ​​model's API endpoint, and the AI ​​model generates multiple logos incorporating the specified features and emotion information based on the received parameters. For example, it generates three logos that express the emotion "excitement" using a blue base and a futuristic rocket motif.

[1774] Sending and receiving logo generation results

[1775] The generated logo designs are sent back to the server as a response containing their respective file paths and related information. The server analyzes the received logo design data, converts it back into JSON format, and sends it back to the device. The device then analyzes the logo design data received from the server and displays thumbnail images and descriptions of the logo designs in the user interface. The user can then select the logo design they like best from the multiple designs and download it.

[1776] Hardware and software used

[1777] Hardware: Webcam, device (smartphone, tablet, etc.)

[1778] Software: Emotion Recognition Model, AI model, JSON format, HTTP protocol

[1779] Specific examples

[1780] For example, if a user inputs the color "red," the concept "passionate," and the motif "heart," and the emotion is recognized as "happiness," the server will send the following prompt to the AI ​​model based on this data.

[1781] Example prompt sentence:

[1782] Color: Red

[1783] Concept: Passionate

[1784] Motif: Heart

[1785] Emotion: Happiness

[1786] This makes it possible to generate and provide a customized logo that includes the user's emotional information.

[1787] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1788] Step 1:

[1789] The user inputs a color, concept, and motif into the input form on the device. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The device then stores the user's input information in variables.

[1790] Step 2:

[1791] The device's built-in emotion recognition engine uses the webcam and microphone to recognize the user's emotions. It extracts emotional information from the user's facial expressions, voice, and text, and recognizes "Emotion: Excitement." It stores the recognized emotional information in a variable.

[1792] Step 3:

[1793] The device converts the user's input information, including color, concept, motif, and emotion information, into JSON format. The converted JSON data looks like this:

[1794] json

[1795] {

[1796] "color": "blue",

[1797] "concept": "futuristic",

[1798] "motif": "rocket",

[1799] "emotion": "excitement"

[1800] }

[1801] Step 4:

[1802] The device sends the converted JSON data to the server as an HTTP POST request. The endpoint the server receives is the logo generation API.

[1803] Step 5:

[1804] The server receives and analyzes the JSON data sent from the device. Through the analysis, color, concept, motif, and emotion information are extracted and stored in variables.

[1805] Step 6:

[1806] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[1807] Step 7:

[1808] The server sends an HTTP POST request to the AI ​​model's API endpoint, which includes the following data:

[1809] json

[1810] POST / generate_logo

[1811] {

[1812] "color": "blue",

[1813] "concept": "futuristic",

[1814] "motif": "rocket",

[1815] "emotion": "excitement"

[1816] }

[1817] Step 8:

[1818] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos that express the emotion "excitement" using a futuristic rocket motif with a blue base. The generated logo proposals are sent back to the server as a response, including each file path and related information.

[1819] Step 9:

[1820] The server analyzes the received logo design data, converts it back to JSON format, and sends it back to the device. The returned data looks like this:

[1821] json

[1822] {

[1823] "logos": [

[1824] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1825] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1826] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1827] ]

[1828] }

[1829] Step 10:

[1830] The device analyzes the logo design data received from the server and displays thumbnail images and descriptions of the logo designs on the user interface. The user can then select the logo design they like best.

[1831] Step 11:

[1832] The user selects a specific logo design and clicks the download button. The device retrieves the image file of the selected logo from the download link and saves it locally. This allows the user to obtain a logo that matches their own emotions.

[1833] 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.

[1834] 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.

[1835] 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.

[1836] [Fourth embodiment]

[1837] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1838] 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.

[1839] 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).

[1840] 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.

[1841] 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.

[1842] 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).

[1843] 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.

[1844] 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.

[1845] 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.

[1846] 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.

[1847] 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.

[1848] 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.

[1849] 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."

[1850] This system uses AI to quickly generate a logo based on the colors, concept, and motif specified by the user. The detailed implementation method is explained below.

[1851] overview

[1852] The system works through a series of processes: receiving user input, sending it to the server, generating a logo using an AI model, and providing the generated logo, allowing users to easily obtain a high-quality logo.

[1853] Program processing

[1854] Receiving user input information

[1855] The user uses a terminal to input information about the color, concept, and motif into an input form. For example, the user inputs "blue" as the color, "futuristic" as the concept, and "rocket" as the motif.

[1856] The device receives this input information, stores it in a variable, and converts it to JSON format, ready to be sent to the server.

[1857] Sending input information

[1858] The device converts the information entered by the user into JSON format and sends the information to the server as an HTTP POST request.

[1859] json

[1860] {

[1861] "color": "blue",

[1862] "concept": "futuristic",

[1863] "motif": "rocket"

[1864] }

[1865] Processing on the server

[1866] The server receives and analyzes the JSON data sent from the device, extracting information on color, concept, and motif, and storing it in the respective variables.

[1867] The server then calls the interface with the AI ​​model and requests logo generation based on the received input information. The server then passes parameters to the AI ​​model's API endpoint to start the logo generation process.

[1868] json

[1869] POST / generate_logo

[1870] {

[1871] "color": "blue",

[1872] "concept": "futuristic",

[1873] "motif": "rocket"

[1874] }

[1875] AI-powered logo generation

[1876] The AI ​​model generates multiple logo designs based on the specified color, concept, and motif, for example, generating three blue-based, futuristic rocket-themed logos.

[1877] The generated logo designs are sent back to the server as a response including their respective file paths and related information.

[1878] json

[1879] {

[1880] "logos": [

[1881] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1882] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1883] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1884] ]

[1885] }

[1886] Sending the generated results

[1887] The server analyzes the logo design data received from the AI ​​model, converts it back into JSON format, and sends it back to the device.

[1888] json

[1889] {

[1890] "logos": [

[1891] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1892] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1893] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1894] ]

[1895] }

[1896] Display and provide logo proposals

[1897] The device analyzes the logo proposal data received from the server and displays it on the user interface, showing the user thumbnail images of each logo so they can check the details.

[1898] User Selection and Download

[1899] The user selects the logo they like best from multiple logo designs and clicks the download button to download the logo. At this time, the device retrieves the image file of the selected logo from the download link and saves it locally.

[1900] Through this series of processes, users can easily generate and obtain high-quality and unique logos. This system is very useful for helping small businesses and personal brands quickly create logos.

[1901] The processing flow will be explained below.

[1902] Step 1: Receiving user input

[1903] The user inputs the color, concept, and motif into the input form on the terminal. For example, "Color: Blue," "Concept: Futuristic," and "Motif: Rocket" are input.

[1904] The terminal receives the input information and stores it in variables. The input information is divided into fields called "color", "concept", and "motif" and prepared for the next process.

[1905] Step 2: Submit your input

[1906] The terminal converts the input information into JSON format.

[1907] json

[1908] {

[1909] "color": "blue",

[1910] "concept": "futuristic",

[1911] "motif": "rocket"

[1912] }

[1913] The device sends JSON data to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[1914] Step 3: Processing on the Server

[1915] The server receives the JSON data sent from the device.

[1916] The server analyzes the received data, extracts the "color," "concept," and "motif," and stores them in variables.

[1917] Step 4: Processing the logo generation request

[1918] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo.

[1919] The server sends an HTTP POST request to the AI ​​model's API endpoint.

[1920] json

[1921] POST / generate_logo

[1922] {

[1923] "color": "blue",

[1924] "concept": "futuristic",

[1925] "motif": "rocket"

[1926] }

[1927] Step 5: AI-powered logo generation

[1928] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified features.

[1929] The AI ​​model sends a response back to the server, including the file path and data of the generated logo design.

[1930] json

[1931] {

[1932] "logos": [

[1933] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1934] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1935] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1936] ]

[1937] }

[1938] Step 6: Sending the generated results

[1939] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[1940] json

[1941] {

[1942] "logos": [

[1943] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[1944] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[1945] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[1946] ]

[1947] }

[1948] Step 7: View and submit logo ideas

[1949] The terminal analyzes the logo proposal data received from the server.

[1950] The device displays a thumbnail image of the proposed logo and a description in the user interface.

[1951] Step 8: User Selection and Download

[1952] The user selects the logo they like best from multiple designs.

[1953] The user selects a specific logo design and clicks the download button.

[1954] The device retrieves the image file of the selected logo from the download link and saves it locally.

[1955] Through this series of steps, users can quickly get a high-quality logo without having to hire a professional designer.

[1956] Example 1

[1957] 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."

[1958] Conventional logo generation systems often fail to respond quickly and accurately to user requests, making it difficult to provide high-quality logos based on specific colors, concepts, and motifs. Furthermore, they provide insufficient support for users in selecting the most suitable logo from numerous logo designs, creating a need for an improved user experience.

[1959] 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.

[1960] In this invention, the server includes means for receiving input information specified by a user, means for converting the input information into a data format and sending it to the server, means for the server to request a logo generation from an AI model based on the input information, and means for providing the generated logo to the user. This makes it possible to quickly generate a high-quality logo based on the user's specific requirements and provide multiple logo designs to allow the user to select the most suitable logo.

[1961] A "user" is an entity that provides input information such as colors, concepts, and motifs to generate a logo using the system.

[1962] "Input information" refers to information such as colors, concepts, and motifs that a user provides to the system for logo generation.

[1963] A "data format" is the structured format into which input information is converted for transmission to the server, typically in a format such as JSON or XML.

[1964] A "server" is a computer system that has the ability to analyze received input information and request logo generation from an AI model.

[1965] "AI Model" refers to an artificial intelligence algorithm and its implementation for generating a logo based on specified parameters.

[1966] A "logo" is an image or design created to visually represent a company or brand.

[1967] "Logo ideas" refers to multiple logo variations generated by the AI ​​model and are options offered to users.

[1968] This invention is a system that uses AI to quickly generate a logo from the colors, concept, and motif specified by the user. A specific embodiment of this system will be described below.

[1969] Hardware and software used

[1970] Device: The device (e.g., computer, tablet, smartphone) on which the user enters information and on which the generated logo is displayed and downloaded.

[1971] Server: A back-end system that receives and analyzes input information and generates logos using AI models.

[1972] AI Model: An artificial intelligence model (e.g. TensorFlow, PyTorch) trained for logo generation.

[1973] API: An interface that mediates communication between the server and the AI ​​model.

[1974] System Features

[1975] Receiving user input information

[1976] The user uses the terminal to input color, concept, and motif information into the system's input form. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The terminal receives this input information and stores it in variables. Next, it converts this input information into JSON format and prepares it to be sent to the server.

[1977] Sending input information

[1978] The device sends the information entered by the user to the server as an HTTP POST request, which contains data in JSON format and is structured so that the server can parse it properly.

[1979] Processing on the server

[1980] The server analyzes the JSON data received from the device and extracts information on color, concept, and motif.The server then calls the interface with the AI ​​model and requests the AI ​​model to generate a logo based on the analyzed input information.

[1981] AI-powered logo generation

[1982] The AI ​​model generates multiple logo designs based on the specified color, concept, and motif. For example, it generates three futuristic rocket logo designs based on blue. The generated logo designs are then sent back to the server as data, including their file paths and descriptions.

[1983] Sending the generated results

[1984] The server then converts the logo design data received from the AI ​​model back into JSON format and sends it back to the device, including the file path and description of the logo design.

[1985] Display and provide logo proposals

[1986] The device analyzes the logo design data received from the server and displays it on the user interface. The user can view multiple logo designs in thumbnail format and check the details of each one.

[1987] User Selection and Download

[1988] The user selects the logo they like best from multiple logo designs and clicks the download button to download the logo. At this time, the device retrieves the image file of the selected logo from the download link and saves it locally.

[1989] Specific operation example

[1990] For example, if the user enters the following prompt sentence:

[1991] Example prompt: "Generate a blue logo featuring a futuristic rocket design."

[1992] Through this series of processes, users can easily and quickly generate and obtain high-quality logos, which is especially useful for small businesses and personal brands to quickly create logos.

[1993] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1994] Step 1:

[1995] The user uses the terminal to input color, concept, and motif information into the input form. At this time, the user enters specific information such as "blue," "futuristic," and "rocket." The input is text information entered by the user. The terminal receives this information and stores it in variables.

[1996] Step 2:

[1997] The terminal converts the received input information into JSON format. During this conversion process, the text information is structured into a JSON object like the following:

[1998] json

[1999] {

[2000] "color": "blue",

[2001] "concept": "futuristic",

[2002] "motif": "rocket"

[2003] }

[2004] The input is the user's text input information, and the output is JSON formatted data that the device prepares to send to the server as an HTTP POST request.

[2005] Step 3:

[2006] The terminal sends the generated JSON data to the server using an HTTP POST request. The input is the user's input information converted to JSON format, and the output is the HTTP request sent to the server.

[2007] Step 4:

[2008] The server receives the HTTP POST request from the device and parses the JSON data. During this parsing process, information on color, concept, and motif is extracted and stored in the corresponding variables. The input is the JSON data sent to the server, and the output is the parsed information.

[2009] Step 5:

[2010] The server requests the AI ​​model to generate a logo based on the analyzed input information. The server sends the following request to the AI ​​model's API endpoint:

[2011] json

[2012] {

[2013] "color": "blue",

[2014] "concept": "futuristic",

[2015] "motif": "rocket"

[2016] }

[2017] The input is the analyzed color, concept, and motif information, and the output is a request to the AI ​​model.

[2018] Step 6:

[2019] The AI ​​model begins generating logos based on the received parameters. For example, it generates multiple futuristic rocket logos with a blue base. The input is a logo generation request from the server, and the output is multiple generated logo designs. The generated logo designs are sent back to the server as JSON data, including each file path and description.

[2020] Step 7:

[2021] The server receives the logo proposal data returned by the AI ​​model and restructures it into JSON format. The data is formatted as follows:

[2022] json

[2023] {

[2024] "logos": [

[2025] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[2026] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[2027] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[2028] ]

[2029] }

[2030] The input is the data returned from the AI ​​model, and the output is JSON formatted data sent to the device.

[2031] Step 8:

[2032] The server returns the formatted logo design data to the device. The data to be displayed in the user interface is sent as an HTTP response. The input is JSON data formatted on the server side, and the output is the HTTP response sent to the device.

[2033] Step 9:

[2034] The terminal analyzes the logo proposal data received from the server and displays it in the user interface. A thumbnail image of each logo is displayed, and the user can check the details of each logo. The input is the JSON data received from the server, and the output is the logo proposal displayed in the user interface.

[2035] Step 10:

[2036] The user selects the logo they like best from multiple logo designs and clicks the download button. The input is the user's selection information, and the output is a download link for the logo. The device retrieves the image file of the selected logo from the download link and saves it locally. The input is the download link for the selected logo, and the output is the locally saved logo file.

[2037] (Application example 1)

[2038] 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."

[2039] Conventional logo generation systems allow users to generate logos based on the colors, concept, and motif specified by the user. However, there is no mechanism for easily setting the generated logo in an electronic payment service account. This makes it difficult for users to instantly reflect the custom logo they created in their payment account. Therefore, it is necessary to provide a series of processes that allow users to intuitively generate a logo and apply it to their electronic payment account.

[2040] 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.

[2041] In this invention, the server includes means for receiving input information specified by a user, means for transmitting the input information to the server, means for the server to generate a logo based on the input information, means for providing the generated logo to the user, and means for the user to select the generated logo and set it as a custom logo for an account of an electronic payment service, thereby enabling the user to quickly apply the generated logo to their electronic payment account and perform advanced customization.

[2042] "User" refers to an individual or legal entity that uses the System to generate and configure a logo.

[2043] "Input Information" refers to information related to logo generation, such as colors, concepts, and motifs, that a user provides to the system.

[2044] "Server" refers to a computing device that processes input information received from a user and generates and serves a logo.

[2045] A "logo" refers to a symbol or design that is generated based on user-specified conditions.

[2046] "Providing" means providing the generated logo to the user in a displayable or downloadable form.

[2047] "Electronic payment service" refers to a system that processes payments electronically in online or offline commercial transactions.

[2048] "Custom Logo" means a unique logo generated based on User-specified criteria and applied to User's Electronic Payment Account.

[2049] "AI Model" refers to the artificial intelligence algorithm used to generate a logo based on input information.

[2050] "Selection" refers to the act of the user choosing one logo from multiple generated designs.

[2051] "Setting" refers to applying the selected logo to an electronic payment service account.

[2052] This invention is a system that uses an AI model to quickly generate a logo based on the user's specified colors, concept, and motif, and then sets it in an electronic payment service account. The system is configured to enable users to easily generate high-quality custom logos and instantly update them in their electronic payment accounts.

[2053] Hardware and software used

[2054] Hardware

[2055] Smartphone (iOS or Android)

[2056] software

[2057] Python 3.x

[2058] 'requests' library (for sending HTTP requests)

[2059] Data processing and calculation flow

[2060] 1. Receiving user-entered information:

[2061] Users input colors, concepts, and motifs via their smartphones, such as "blue," "futuristic," and "rocket." This information is then stored as variables on the device.

[2062] 2. Submitting input information:

[2063] The smartphone converts the information entered by the user into JSON format and sends it to the server as an HTTP POST request. The HTTP request is made using the "requests" library.

[2064] 3. On the server:

[2065] The server receives and analyzes the JSON data sent from the smartphone. The server then sends the analyzed data to the API endpoint of the AI ​​model, requesting logo generation. The AI ​​model generates a logo based on the specified colors, concept, and motif.

[2066] 4. AI Logo Generation:

[2067] The AI ​​model generates multiple logo designs and sends them back to the server, such as multiple futuristic rocket logos with a blue base.

[2068] 5. Sending the generated results:

[2069] The server then sends the logo ideas received from the AI ​​model back to the smartphone, where they are offered to the user as options.

[2070] 6. User Choices and Applications:

[2071] Users can choose the logo they like best from multiple options, download it, and apply it to their electronic payment service account. The smartphone retrieves the selected logo from the download link and saves it locally.

[2072] Specific examples

[2073] For example, if a user inputs "blue" (color), "modern" (concept), and "card" (motif), the AI ​​will generate a "card logo with a modern design based on blue" based on this information. The user can select one of the multiple logo designs generated and set it for their QR code payment account.

[2074] Prompt Sentence Examples

[2075] Enter logo color: Blue

[2076] Enter your logo concept: Modern

[2077] Enter your logo motif: Card

[2078] Please select the logo number you would like to download: 1

[2079] The system aims to use an AI model to generate a logo based on specific criteria entered by the user and then quickly apply that logo to electronic payment accounts, enabling a high level of customization for small businesses and personal brands quickly and easily.

[2080] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2081] Step 1:

[2082] Receiving user input information

[2083] The user uses a smartphone to input the colors, concept, and motif required for logo generation, and this information is stored in variables on the smartphone.

[2084] Input: Color, Concept, Motif

[2085] Data processing / calculation: Store specified information in variables

[2086] Output: Input information stored in variables on the smartphone

[2087] Step 2:

[2088] Sending input information

[2089] The device converts the information entered by the user into JSON format and sends the data to the server as an HTTP POST request.

[2090] Input: Input information in JSON format

[2091] Data processing / calculation: Data converted to JSON format is sent via HTTP request

[2092] Output: If the HTTP POST request is successful, the data arrives at the server.

[2093] Step 3:

[2094] Processing on the server

[2095] The server receives and analyzes the JSON data sent from the device, extracts color, concept, and motif information, and stores them in variables. It then sends this information to the API endpoint of the AI ​​model to request logo generation.

[2096] Input: JSON data sent from the terminal

[2097] Data processing / calculation: Parse JSON data and extract information, store it in variables, and send it to an AI model

[2098] Output: Information sent to the AI ​​model

[2099] Step 4:

[2100] AI-powered logo generation

[2101] The AI ​​model generates multiple logo designs based on the provided colors, concept, and motif, and sends the resulting logo designs back to the server as a response containing file paths and related information.

[2102] Input: Color, concept, and motif information

[2103] Data processing / calculation: Creating designs using logo generation algorithms

[2104] Output: File paths and descriptions of multiple logo designs

[2105] Step 5:

[2106] Sending the generated results

[2107] The server analyzes the logo design data received from the AI ​​model, converts it back into JSON format, and sends it back to the device.

[2108] Input: Logo design data returned by the AI ​​model

[2109] Data processing / calculation: Data analysis and conversion to JSON format

[2110] Output: JSON data sent to the device

[2111] Step 6:

[2112] Display and provide logo proposals

[2113] The device analyzes the logo proposal data received from the server and displays it on the user interface, showing the user thumbnail images of each logo so they can check the details.

[2114] Input: Logo design data in JSON format

[2115] Data processing / calculation: Data analysis and display on the interface

[2116] Output: Logo proposal displayed in the user interface

[2117] Step 7:

[2118] User selection and application

[2119] Users can choose the logo they like best from several options, download the image file of the selected logo, and set it in their electronic payment account.

[2120] Input: User selected logo design

[2121] Data processing / calculation: Download logo image file and apply it to your account

[2122] Output: Custom logo set for electronic payment account

[2123] The system allows users to select the best logo from multiple options and instantly apply it to their electronic payment account.

[2124] 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.

[2125] This invention combines a system that uses AI to generate logos based on user-specified colors, concepts, and motifs with an emotion engine that recognizes the user's emotions. The following describes specific embodiments based on the scope of this patent claim.

[2126] overview

[2127] The system involves a series of processes: receiving user input information, sending it to a server, generating a logo using an AI model, customizing it based on emotion information, and providing the generated logo, allowing users to obtain a high-quality logo that matches their emotions.

[2128] Program processing

[2129] Receiving user input information and emotion recognition

[2130] The user inputs the color, concept, and motif into the input form on the terminal. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket."

[2131] The device receives this input information and stores it in variables. The device's built-in emotion engine then recognizes the user's emotions. The emotion engine extracts emotional information from the user's facial expressions, voice, text, etc. For example, it recognizes "emotion: excitement."

[2132] Sending input information and emotional information

[2133] The device converts the user's input information and emotional information into JSON format.

[2134] json

[2135] {

[2136] "color": "blue",

[2137] "concept": "futuristic",

[2138] "motif": "rocket",

[2139] "emotion": "excitement"

[2140] }

[2141] The device sends JSON data to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[2142] Processing on the server

[2143] The server receives and analyzes the JSON data sent from the device, extracting color, concept, motif, and emotion information and storing them in variables.

[2144] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[2145] Processing logo generation requests

[2146] The server sends an HTTP POST request to the AI ​​model's API endpoint.

[2147] json

[2148] POST / generate_logo

[2149] {

[2150] "color": "blue",

[2151] "concept": "futuristic",

[2152] "motif": "rocket",

[2153] "emotion": "excitement"

[2154] }

[2155] AI-powered logo generation

[2156] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos that express the emotion "excitement" using a blue, futuristic rocket motif.

[2157] The generated logo designs are sent back to the server as a response including their respective file paths and related information.

[2158] json

[2159] {

[2160] "logos": [

[2161] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[2162] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[2163] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[2164] ]

[2165] }

[2166] Sending the generated results

[2167] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[2168] json

[2169] {

[2170] "logos": [

[2171] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[2172] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[2173] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[2174] ]

[2175] }

[2176] Display and provide logo proposals

[2177] The device analyzes the logo proposal data received from the server, and displays a thumbnail image and description of the logo proposal on the user interface, allowing the user to confirm the details.

[2178] User Selection and Download

[2179] The user can choose the logo design they like best from multiple options. The user selects a specific logo design and clicks the download button.

[2180] The device will retrieve the image file of the selected logo from the download link and save it locally, allowing the user to get a logo that matches their emotions.

[2181] This invention allows users to quickly and easily generate high-quality logos that match emotions. The introduction of an emotion engine makes it possible to provide more personalized logos.

[2182] The processing flow will be explained below.

[2183] Step 1: Receiving user input and recognizing emotions

[2184] The user inputs the color, concept, and motif into the input form on the terminal. For example, "Color: Blue," "Concept: Futuristic," and "Motif: Rocket" are input.

[2185] The terminal receives the input information and stores it in variables. The input information is divided into fields called "color", "concept", and "motif".

[2186] The device also uses a built-in emotion engine to recognize the user's emotions. This emotion engine extracts emotional information using techniques such as facial expression recognition, voice analysis, and text analysis. For example, it recognizes "emotion: excitement."

[2187] Step 2: Sending input and emotion information

[2188] The device converts the user's input information and emotional information into JSON format.

[2189] json

[2190] {

[2191] "color": "blue",

[2192] "concept": "futuristic",

[2193] "motif": "rocket",

[2194] "emotion": "excitement"

[2195] }

[2196] The device sends this JSON data to the server as an HTTP POST request, and the destination endpoint is the API for logo generation.

[2197] Step 3: Receiving and analyzing data on the server

[2198] The server receives the JSON data sent from the terminal.

[2199] The server analyzes the JSON data and stores the "color," "concept," "motif," and "emotional information" in the respective variables.

[2200] Step 4: Prepare your logo generation request

[2201] The server uses the extracted information (color, concept, motif, and emotional information) to prepare parameters for requesting the AI ​​model to generate a logo.

[2202] The server makes an HTTP POST request with these parameters to the AI ​​model's API endpoint.

[2203] json

[2204] POST / generate_logo

[2205] {

[2206] "color": "blue",

[2207] "concept": "futuristic",

[2208] "motif": "rocket",

[2209] "emotion": "excitement"

[2210] }

[2211] Step 5: AI-powered logo generation

[2212] Based on the parameters received, the AI ​​model generates multiple logos that match the specified colors, concepts, motifs, and emotional information.

[2213] For example, the AI ​​model generates three logos with a futuristic blue design, a rocket motif, and the emotion "excitement."

[2214] Step 6: Sending the generated results

[2215] The file path and related information of the logo design generated by the AI ​​model are sent back to the server as a response from the AI ​​model.

[2216] json

[2217] {

[2218] "logos": [

[2219] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[2220] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[2221] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[2222] ]

[2223] }

[2224] The server analyzes the logo design data it receives, converts it back into JSON format, and sends it back to the device.

[2225] json

[2226] {

[2227] "logos": [

[2228] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[2229] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[2230] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[2231] ]

[2232] }

[2233] Step 7: View logo ideas

[2234] The terminal analyzes the logo proposal data received from the server and displays it on the user interface.

[2235] The device will show the user a thumbnail image and description of each logo, allowing them to view more details.

[2236] Step 8: User Selection and Download

[2237] The user selects the logo they like best from multiple designs.

[2238] The user selects a specific logo design and clicks the download button.

[2239] The device retrieves the image file of the selected logo from the download link and saves it locally.

[2240] This allows users to quickly and easily create and obtain a personalized, high-quality logo that matches their personal style.

[2241] Example 2

[2242] 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."

[2243] Conventional logo generation systems can generate a certain logo based on the color, concept, and motif specified by the user, but they are unable to generate a logo that reflects the user's emotions. This makes it difficult to obtain a logo that reflects the user's emotions and personality. Generation results that ignore emotions result in low user satisfaction, which in turn reduces the effectiveness of the logo.

[2244] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2245] In this invention, the server includes means for receiving input information and emotion information specified by a user, means for transmitting the input information and emotion information to the server, means for generating a logo based on the input information and emotion information, and means for providing the generated logo to the user, thereby enabling the generation of a high-quality logo personalized based on the user's emotion.

[2246] "User" refers to a person who uses the System to generate a logo.

[2247] "Input information" refers to information such as colors, concepts, and motifs that the user specifies to the system.

[2248] "Emotional information" refers to information that expresses a user's emotions extracted from the user's facial expressions, voice, text, etc.

[2249] "Terminal" refers to the device used by a user to input and transmit input information and emotional information.

[2250] "Server" refers to a computer system that has the ability to receive input information and emotion information and generate a logo using an AI model.

[2251] "Logo" refers to a visual design generated based on user-specified input and emotional information.

[2252] "AI model" refers to an artificial intelligence algorithm that uses input information and emotional information to automatically generate a logo.

[2253] "Generated logo" refers to a logo design generated by an AI model based on user input and emotional information.

[2254] This invention provides a system that combines a system that generates a logo based on the color, concept, and motif specified by the user with an emotion engine that recognizes the user's emotions. Here, an embodiment of this system will be described in detail.

[2255] System Overview

[2256] The system operates through a series of processes: receiving user-input information, sending it to a server, generating a logo using an AI model, customizing it based on emotional information, and providing the generated logo.

[2257] Hardware and software used

[2258] The device receives input information from the user and recognizes emotions. The device is equipped with a camera and microphone, and these devices are used to obtain the user's emotional information. The emotion engine is software that analyzes the user's facial expressions, voice, and text to extract emotions.

[2259] The server receives and analyzes the input and emotion information sent from the device. The server is equipped with an AI model, which generates a logo based on the input and emotion information.

[2260] System Operation

[2261] Receiving user input information and emotion recognition

[2262] The user inputs the color, concept, and motif into the input form on the terminal. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket."

[2263] The device receives this input information and stores it in variables. The device's built-in emotion engine analyzes the user's facial expressions, voice, and text to extract emotional information. For example, the emotion engine recognizes "excitement."

[2264] Sending input information and emotional information

[2265] The device converts the user's input information and emotion information into JSON format and sends it to the server as an HTTP POST request. The destination endpoint is the API for logo generation.

[2266] Processing on the server

[2267] The server receives the JSON data sent from the device, analyzes the content, and stores the color, concept, motif, and emotion information in the corresponding variables. This information is used to prepare parameters for requesting the AI ​​model to generate a logo.

[2268] Processing logo generation requests

[2269] The server sends an HTTP POST request to the AI ​​model's API endpoint, including the user-specified color, concept, motif, and emotion information.

[2270] AI-powered logo generation

[2271] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos expressing "excitement" using a blue-based, futuristic rocket motif. The generated logo proposals are sent back to the server as a response, including their respective file paths and related information.

[2272] Sending and displaying the generated results

[2273] The server analyzes the logo design data it receives, converts it back to JSON format, and sends it back to the device. The device analyzes the logo design data it receives from the server and displays it on the user interface.

[2274] User Selection and Download

[2275] The user selects the logo they like best from multiple logo designs and clicks the download button. The device retrieves the image file of the selected logo from the download link and saves it locally. This allows the user to obtain a logo that matches their own emotions.

[2276] Specific examples

[2277] An example prompt might be "Generate a blue, futuristic rocket logo that reflects the emotion of excitement."

[2278] This invention allows users to quickly and easily generate high-quality logos that match emotions, and the introduction of an emotion engine makes it possible to provide more personalized logos.

[2279] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2280] Step 1:

[2281] The user inputs the color, concept, and motif into the input form on the device. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The input information is saved in the device's internal memory. The input is as follows:

[2282] json

[2283] {

[2284] "color": "blue",

[2285] "concept": "futuristic",

[2286] "motif": "rocket"

[2287] }

[2288] Step 2:

[2289] The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by the emotion engine to extract emotional information. For example, the emotion "excitement" is recognized. The recognized emotional information is stored in the device's internal memory in the following format:

[2290] json

[2291] {

[2292] "emotion": "excitement"

[2293] }

[2294] Step 3:

[2295] The device converts the user's input and emotion information into JSON format, resulting in the data in the following format:

[2296] json

[2297] {

[2298] "color": "blue",

[2299] "concept": "futuristic",

[2300] "motif": "rocket",

[2301] "emotion": "excitement"

[2302] }

[2303] Step 4:

[2304] The device sends the converted JSON data to the server as an HTTP POST request. The destination is the API endpoint for logo generation. The input of this step is the converted JSON data, and the output is the HTTP request.

[2305] Step 5:

[2306] The server receives the JSON data sent from the device and analyzes its contents. The analyzed data is stored in the server's internal memory as color, concept, motif, and emotion information. It is divided as follows:

[2307] json

[2308] {

[2309] "color": "blue",

[2310] "concept": "futuristic",

[2311] "motif": "rocket",

[2312] "emotion": "excitement"

[2313] }

[2314] Step 6:

[2315] Based on this information, the server prepares the parameters to request the AI ​​model to generate a logo. This creates the following parameters:

[2316] json

[2317] {

[2318] "color": "blue",

[2319] "concept": "futuristic",

[2320] "motif": "rocket",

[2321] "emotion": "excitement"

[2322] }

[2323] Step 7:

[2324] The server uses the prepared parameters to send an HTTP POST request to the AI ​​model's API endpoint. The input of this step is the prepared parameters, and the output is the HTTP request sent.

[2325] Step 8:

[2326] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, a logo with a blue base, a futuristic rocket motif, and the emotion "excitement" may be generated. Multiple logo designs are generated, as shown below.

[2327] json

[2328] {

[2329] "logos": [

[2330] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[2331] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[2332] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[2333] ]

[2334] }

[2335] Step 9:

[2336] The server analyzes the received logo design data, converts it back to JSON format, and sends it back to the device. The input to this step is the logo design data returned by the AI ​​model, and the output is an HTTP response in JSON format.

[2337] Step 10:

[2338] The device analyzes the logo proposal data received from the server and displays it on the user interface, which displays a thumbnail image of the logo proposal and a description. The interface looks like this:

[2339] html

[2340]

[2341]

[2342] Futuristic Rocket 1

[2343]

[2344]

[2345]

[2346] Futuristic Rocket 2

[2347]

[2348]

[2349]

[2350] Futuristic Rocket 3

[2351]

[2352] Step 11:

[2353] The user selects the logo they like best from the displayed options and clicks the download button. For example, they can select "Futuristic Rocket 2."

[2354] Step 12:

[2355] The device retrieves the image file of the selected logo from the server and saves it to the local disk, allowing the user to download the logo that best suits their emotions.

[2356] The above are the specific processing steps of the program of this system.

[2357] (Application example 2)

[2358] 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."

[2359] Conventional logo generation systems simply generate logos based on the colors, concept, and motif specified by the user, without personalizing them to reflect the user's personal feelings or the situation. As a result, the generated logos often do not fully meet the user's expectations and needs. Furthermore, in the advertising industry, designs that appeal to emotions are in demand, so technology is needed that can generate logos that incorporate the user's emotional information. To solve this problem, a logo generation system that takes the user's emotional information into account is needed.

[2360] 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.

[2361] In this invention, the server includes means for receiving input information specified by a user, means for recognizing the user's emotional information using an emotion recognition engine and transmitting it to the server together with the input information, and means for incorporating the emotional information into an AI model to generate a logo and providing the generated logo to the user. This makes it possible to generate and provide a customized, high-quality logo that includes the user's emotional information.

[2362] "User-input information" refers to information that a user inputs by specifying a color, concept, motif, etc.

[2363] An "emotion recognition engine" is an engine that extracts emotional information from a user's facial expressions, voice, text, etc.

[2364] "Server" means a device or system that receives user input information and emotion information and generates a logo based on an AI model.

[2365] An "AI model" is a model that uses artificial intelligence technology to generate a logo based on input information and emotional information.

[2366] A "logo" is a graphic design that represents a particular brand or concept.

[2367] A "generated logo" is a logo created by an AI model based on user input and emotional information.

[2368] The "multiple logo designs" are multiple different logo designs generated based on the user's input information and emotional information.

[2369] The "means for providing" is a method or device for providing the generated logo or logo proposal to the user.

[2370] This invention combines a system that uses AI to generate logos based on user-specified colors, concepts, and motifs with an emotion engine that recognizes the user's emotions. The following describes specific embodiments based on the scope of this patent claim.

[2371] Receiving user input information and emotion recognition

[2372] The device provides an input form for users to specify the color, concept, and motif. For example, the user can input "blue" as the color, "futuristic" as the concept, and "rocket" as the motif.

[2373] The device is equipped with an emotion recognition engine that extracts emotional information in real time from the user's facial expressions, voice, text, etc. For example, the emotion is recognized as "excitement."

[2374] Sending input information and emotional information

[2375] The device converts the user's input information and emotion information into JSON format and sends it to the server as an HTTP POST request. The server receives and analyzes this information, extracting color, concept, motif, and emotion information.

[2376] Processing on the server

[2377] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[2378] The server sends an HTTP POST request to the AI ​​model's API endpoint, and the AI ​​model generates multiple logos incorporating the specified features and emotion information based on the received parameters. For example, it generates three logos that express the emotion "excitement" using a blue base and a futuristic rocket motif.

[2379] Sending and receiving logo generation results

[2380] The generated logo designs are sent back to the server as a response containing their respective file paths and related information. The server analyzes the received logo design data, converts it back into JSON format, and sends it back to the device. The device then analyzes the logo design data received from the server and displays thumbnail images and descriptions of the logo designs in the user interface. The user can then select the logo design they like best from the multiple designs and download it.

[2381] Hardware and software used

[2382] Hardware: Webcam, device (smartphone, tablet, etc.)

[2383] Software: Emotion Recognition Model, AI model, JSON format, HTTP protocol

[2384] Specific examples

[2385] For example, if a user inputs the color "red," the concept "passionate," and the motif "heart," and the emotion is recognized as "happiness," the server will send the following prompt to the AI ​​model based on this data.

[2386] Example prompt sentence:

[2387] Color: Red

[2388] Concept: Passionate

[2389] Motif: Heart

[2390] Emotion: Happiness

[2391] This makes it possible to generate and provide a customized logo that includes the user's emotional information.

[2392] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2393] Step 1:

[2394] The user inputs a color, concept, and motif into the input form on the device. For example, the color is "blue," the concept is "futuristic," and the motif is "rocket." The device then stores the user's input information in variables.

[2395] Step 2:

[2396] The device's built-in emotion recognition engine uses the webcam and microphone to recognize the user's emotions. It extracts emotional information from the user's facial expressions, voice, and text, and recognizes "Emotion: Excitement." It stores the recognized emotional information in a variable.

[2397] Step 3:

[2398] The device converts the user's input information, including color, concept, motif, and emotion information, into JSON format. The converted JSON data looks like this:

[2399] json

[2400] {

[2401] "color": "blue",

[2402] "concept": "futuristic",

[2403] "motif": "rocket",

[2404] "emotion": "excitement"

[2405] }

[2406] Step 4:

[2407] The device sends the converted JSON data to the server as an HTTP POST request. The endpoint the server receives is the logo generation API.

[2408] Step 5:

[2409] The server receives and analyzes the JSON data sent from the device. Through the analysis, color, concept, motif, and emotion information are extracted and stored in variables.

[2410] Step 6:

[2411] The server uses the extracted information to prepare parameters for requesting the AI ​​model to generate a logo, including emotional information.

[2412] Step 7:

[2413] The server sends an HTTP POST request to the AI ​​model's API endpoint, which includes the following data:

[2414] json

[2415] POST / generate_logo

[2416] {

[2417] "color": "blue",

[2418] "concept": "futuristic",

[2419] "motif": "rocket",

[2420] "emotion": "excitement"

[2421] }

[2422] Step 8:

[2423] Based on the parameters received, the AI ​​model generates multiple logos incorporating the specified characteristics and emotional information. For example, it generates three logos that express the emotion "excitement" using a futuristic rocket motif with a blue base. The generated logo proposals are sent back to the server as a response, including each file path and related information.

[2424] Step 9:

[2425] The server analyzes the received logo design data, converts it back to JSON format, and sends it back to the device. The returned data looks like this:

[2426] json

[2427] {

[2428] "logos": [

[2429] {"path": " / logos / logo1.png", "description": "Futuristic Rocket 1"},

[2430] {"path": " / logos / logo2.png", "description": "Futuristic Rocket 2"},

[2431] {"path": " / logos / logo3.png", "description": "Futuristic Rocket 3"}

[2432] ]

[2433] }

[2434] Step 10:

[2435] The device analyzes the logo design data received from the server and displays thumbnail images and descriptions of the logo designs on the user interface. The user can then select the logo design they like best.

[2436] Step 11:

[2437] The user selects a specific logo design and clicks the download button. The device retrieves the image file of the selected logo from the download link and saves it locally. This allows the user to obtain a logo that matches their own emotions.

[2438] 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.

[2439] 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.

[2440] 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.

[2441] 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.

[2442] 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.

[2443] 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.

[2444] 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).

[2445] 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.

[2446] 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."

[2447] 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.

[2448] 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).

[2449] 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.

[2450] 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.

[2451] 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.

[2452] 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.

[2453] 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.

[2454] 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.

[2455] 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.

[2456] 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.

[2457] 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.

[2458] 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.

[2459] The following is further disclosed regarding the above embodiment.

[2460] (Claim 1)

[2461] means for receiving input information specified by a user;

[2462] means for transmitting the input information to a server;

[2463] means for generating a logo based on the input information by the server;

[2464] means for providing the generated logo to the user;

[2465] A system including:

[2466] (Claim 2)

[2467] 2. The system according to claim 1, wherein the server has means for generating a logo based on colors, concepts, and motifs specified by a user, and providing a plurality of logo designs.

[2468] (Claim 3)

[2469] 2. The system of claim 1, wherein the server has means for transmitting the input information to an AI model, and the AI ​​model generates the logo and transmits it back to the server.

[2470] "Example 1"

[2471] (Claim 1)

[2472] means for receiving input information specified by a user;

[2473] means for converting the input information into a data format and transmitting the converted data to a server;

[2474] a means for requesting a logo generation from an AI model based on the input information by the server;

[2475] means for providing the generated logo to the user;

[2476] A system including:

[2477] (Claim 2)

[2478] 2. The system according to claim 1, wherein the server has means for generating a logo based on colors, concepts, and motifs specified by a user, and providing a plurality of logo designs.

[2479] (Claim 3)

[2480] 2. The system of claim 1, wherein the server has means for transmitting the input information to an AI model, and the AI ​​model generates the logo and transmits it back to the server.

[2481] "Application Example 1"

[2482] New Claims

[2483] (Claim 1)

[2484] means for receiving input information specified by a user;

[2485] means for transmitting the input information to a server;

[2486] means for generating a logo based on the input information by the server;

[2487] means for providing the generated logo to the user;

[2488] A means for a user to select the generated logo and set it as a custom logo for an account of an electronic payment service;

[2489] A system including:

[2490] (Claim 2)

[2491] 2. The system according to claim 1, wherein the server has means for generating a logo based on colors, concepts, and motifs specified by a user, and providing a plurality of logo designs.

[2492] (Claim 3)

[2493] 2. The system of claim 1, wherein the server has means for transmitting the input information to an AI model, and the AI ​​model generates the logo and transmits it back to the server.

[2494] "Example 2: Combining Emotion Engines"

[2495] (Claim 1)

[2496] means for receiving input information specified by a user;

[2497] means for transmitting the input information and user emotion information to a server;

[2498] means for generating a logo based on the input information and emotion information by the server;

[2499] means for providing the generated logo to the user;

[2500] A system including:

[2501] (Claim 2)

[2502] 2. The system according to claim 1, wherein the server has means for generating a logo based on color, concept, motif and emotional information specified by a user, and providing a plurality of logo designs.

[2503] (Claim 3)

[2504] 2. The system of claim 1, wherein the server has means for transmitting the input information and emotion information to an AI model, and the AI ​​model generates the logo and transmits it back to the server.

[2505] "Application example 2 when combining emotion engines"

[2506] (Claim 1)

[2507] means for receiving input information specified by a user;

[2508] means for transmitting the input information to a server;

[2509] means for generating a logo based on the input information by the server;

[2510] means for recognizing user emotion information by an emotion recognition engine and transmitting the information together with the input information to a server;

[2511] means for incorporating the emotion information into an AI model to generate a logo and providing the generated logo to the user;

[2512] A system including:

[2513] (Claim 2)

[2514] The system according to claim 1, characterized in that the server has a means for generating a logo based on the user's emotional information in addition to the color, concept, and motif specified by the user, and for providing multiple logo proposals.

[2515] (Claim 3)

[2516] 2. The system according to claim 1, further comprising means for transmitting the input information and the user's emotional information to an AI model, and for the AI ​​model to generate the logo and return it to the server. [Explanation of symbols]

[2517] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving input information specified by a user; means for transmitting the input information to a server; means for generating a logo based on the input information by the server; means for providing the generated logo to the user; A system including:

2. 2. The system according to claim 1, wherein the server has means for generating a logo based on colors, concepts, and motifs specified by a user, and providing a plurality of logo designs.

3. 2. The system of claim 1, wherein the server has means for transmitting the input information to an AI model, and the AI ​​model generates the logo and transmits it back to the server.

Images