system

Abstract

Provide a system. [Solution] a terminal means for a user to upload a handwritten rough sketch; a server means for receiving the rough image data transmitted from the terminal means and generating an image; In the server means, a generation AI means for analyzing rough sketch data and generating illustrations and images with a unified appearance; data communication means for transmitting the image data generated by the server means to the terminal means; and display means for displaying the transmitted generated image in said terminal means and making it available for download.

Description

[Technical Field]

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

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

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

[0004] In conventional document and website creation, users have had to spend a lot of time and effort creating unified illustrations and images from hand-drawn rough sketches, making it difficult for users without specialized skills. This has led to problems such as a decline in the quality of documents and difficulty in working efficiently. Furthermore, other services on the market are limited to specific touches and styles, which sometimes do not fully meet users' needs. There is a need for a system that can solve these issues, allowing users to efficiently convert hand-drawn rough sketches into digital images and generate unified illustrations in a variety of styles. [Means for solving the problem]

[0005] The present invention provides a system including a terminal means for a user to upload handwritten rough drawings, a server means for receiving the rough drawing data sent from the terminal means and generating images, a generation AI means for analyzing the rough drawing data in the server means and generating unified illustrations and images, a data communication means for transmitting the image data generated from the server means to the terminal means, and a display means for displaying the generated images sent in the terminal means and making them available for download.

[0006] The AI ​​generation means has the ability to generate illustrations in multiple different styles and variations from rough sketches, and further records and saves metadata related to the generated images, allowing users to efficiently obtain illustrations that meet a variety of needs.

[0007] "User" refers to a person who uses this system to upload handwritten rough sketches and obtain the generated illustrations and images.

[0008] "Terminal means" refers to a device (e.g., a smartphone, tablet, PC, etc.) that a user uses to upload handwritten rough sketches and display and download generated images.

[0009] "Rough sketch data" refers to image data of a rough sketch hand-drawn by a user.

[0010] "Server means" refers to a computer system that has the function of receiving rough sketch data sent from terminal means, generating unified illustrations and images using generation AI means, and transmitting the image data to terminal means.

[0011] "Generative AI means" refers to artificial intelligence technology for generating consistent illustrations and images based on received rough sketch data, specifically generative adversarial networks (GANs) and transformation models.

[0012] "Data communication means" refers to a communication technology for transmitting and receiving data between server means and terminal means (for example, HTTP / HTTPS protocol via the Internet).

[0013] The "display means" refers to a user interface in the terminal means that allows the user to check the generated image that has been sent and to download it as necessary.

[0014] "Metadata" refers to additional information associated with a generated image (e.g., generation date and time, user ID, version, etc.).

[0015] "Styles and variations" refers to the variety of illustrations with different designs and expressions that the generative AI means creates based on rough sketches. [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] The present invention relates to a system that enables a user to efficiently digitize rough sketches drawn by hand and generate a variety of illustrations with a unified appearance. Specific embodiments of this system are described below.

[0038] System Overview

[0039] This system includes a terminal means for uploading rough drawings drawn by hand by the user, a server means for receiving rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, and a display means for displaying and downloading the generated images.

[0040] Program processing flow

[0041] 1. Upload a rough sketch

[0042] Users upload handwritten rough sketches using a dedicated app or web app on terminal means such as a smartphone, tablet, or PC. The terminal means has an image preview function, and after the user checks and corrects the rough sketch, they press the send button, which sends the rough sketch data to the server means.

[0043] 2. Receiving and analyzing rough sketch data

[0044] The server receives the rough sketch data sent from the terminal means. The server stores this data appropriately and analyzes the image resolution and format. Based on the analysis results, the server passes the rough sketch data to the generation AI means.

[0045] 3. Generating illustrations using generative AI

[0046] The server-integrated generative AI generates unified illustrations with various styles and variations based on the received rough sketch data. In this process, the generative AI uses, for example, generative adversarial networks (GANs) and transformation models.

[0047] 4. Sending the generated image data to the terminal

[0048] The server transmits the generated illustrations and images to the terminal means via data communication means. At this time, metadata such as the generation date and time and the user ID are also added to the generated image data.

[0049] 5. Viewing and downloading generated images

[0050] The terminal means displays the generated images received and notifies the user, who can then check the displayed images and download any images he or she likes to use in documents or on a website.

[0051] Specific examples

[0052] Case Study: Creating Presentation Materials

[0053] User Tanaka needs a friendly character illustration to insert into a presentation. He draws a rough sketch on paper, takes a photo of it using a dedicated app on his smartphone, and presses the upload button.

[0054] The device sends the rough sketch data to a server. The server receives the data, analyzes the rough sketch using a generation AI, and generates multiple character illustrations according to Tanaka's wishes. The generated illustrations are then sent from the server to Tanaka's smartphone and displayed in the app.

[0055] Tanaka could choose his favorite from the multiple illustrations displayed, download them, and insert them into his presentation materials. Thanks to this system, Tanaka was able to obtain high-quality character illustrations quickly and efficiently.

[0056] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate illustrations that meet a variety of needs.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] The user draws a rough sketch by hand.

[0060] Step 2:

[0061] The user takes a rough sketch using a device (smartphone, tablet, PC, etc.) or selects an existing image.

[0062] Step 3:

[0063] The device displays the selected rough sketch on a preview screen, and the user presses the upload button.

[0064] Step 4:

[0065] The device converts the rough sketch data into an appropriate format (e.g., JPEG, PNG).

[0066] Step 5:

[0067] The device adds metadata (user ID, timestamp, etc.) to the rough sketch data.

[0068] Step 6:

[0069] The device sends the rough sketch data to the server via an HTTP POST request.

[0070] Step 7:

[0071] The server receives the HTTP POST request and receives the rough sketch data.

[0072] Step 8:

[0073] The server stores the rough sketch data in an appropriate storage system.

[0074] Step 9:

[0075] The server analyzes the rough sketch data it receives and converts it into a format that can be used by the generation AI.

[0076] Step 10:

[0077] The server invokes the generative AI method (e.g., GAN, Transformer) and sets the necessary parameters.

[0078] Step 11:

[0079] The server inputs the rough sketch data into the generation AI means and begins generating the illustration.

[0080] Step 12:

[0081] Generative AI generates unified illustrations and images from rough sketch data.

[0082] Step 13:

[0083] If the generating AI generates illustrations in multiple styles or variations, it will generate different versions of the illustration.

[0084] Step 14:

[0085] The server saves the generated illustrations and adds metadata.

[0086] Step 15:

[0087] The server compresses or encodes the generated illustrations and prepares them for data transmission.

[0088] Step 16:

[0089] The server sends the generated illustration data to the terminal as an HTTP response.

[0090] Step 17:

[0091] The terminal displays the generated illustration data received from the server.

[0092] Step 18:

[0093] The user can check the generated illustrations and download them if necessary.

[0094] Example 1

[0095] 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."

[0096] Currently, many users find it difficult to digitize rough sketches and then use them to create consistent illustrations or images. In particular, it is difficult to easily correct or check rough sketches during digitization, and the resulting illustrations often do not match the user's desired style or variation. Furthermore, managing the metadata associated with the resulting images is cumbersome. To address these issues, a system is needed that can efficiently digitize rough sketches, generate a wide variety of illustrations, and properly manage metadata.

[0097] 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.

[0098] In this invention, the server includes terminal means for users to upload handwritten rough drawings, server means for receiving rough drawing data sent from the terminal means and generating images, generation AI means for analyzing the rough drawing data and generating unified illustrations and images, data communication means for transmitting the generated image data from the server means to the terminal means, display means in the terminal means for displaying the transmitted generated images and making them available for download, and a function in the terminal means for previewing the rough drawings and for user correction, and a function for users to send the rough drawings after checking and correcting them. This enables users to easily digitize and correct their handwritten rough drawings and generate, display, and download a variety of illustrations.

[0099] "Terminal means" refers to an electronic device used by a user to upload handwritten rough sketches, and includes smartphones, tablets, PCs, etc.

[0100] The "server means" is a computer system that receives rough sketch data sent from the terminal means, analyzes and stores the data, and generates an image.

[0101] The "generative AI means" is an artificial intelligence model used by the server means to generate unified illustrations and images based on the received rough sketch data, and utilizes a generative adversarial network (GAN) or a transformation model.

[0102] "Data communication means" refers to the communication infrastructure and protocol for transmitting image data generated by the server means to the terminal means.

[0103] "Display Means" means a software function that displays the generated image transmitted by the Terminal Means and enables the user to confirm and download it.

[0104] The "preview function" is a function that allows the user to check and correct the rough sketch that he or she uploads on the terminal means.

[0105] The "correction function" is a function that allows the user to make corrections to the rough image during preview, and is installed in the terminal means.

[0106] "Rough sketch data" is data that digitally represents a rough sketch that a user has hand-drawn.

[0107] "Metadata" refers to accompanying information such as the date and time of generation and user ID that is added to the generated image data.

[0108] The present invention relates to a system that enables a user to efficiently digitize rough sketches drawn by hand and generate a variety of illustrations with a unified appearance. Specific embodiments of this system are described below.

[0109] The system includes a terminal means for users to upload rough drawings drawn by hand, a server means for receiving the rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, and a display means for displaying and downloading the generated images.

[0110] The user uploads rough sketches using a dedicated app or web app using a terminal means such as a smartphone, tablet, or PC. The terminal means is equipped with an image preview function and an editing function, and the user can check and edit the rough sketch and then press the send button, which sends the rough sketch data to the server means.

[0111] The server receives the rough sketch data sent from the terminal means, stores the data appropriately, analyzes the resolution and format of the received rough sketch data, and passes the analyzed metadata to the generation AI means.

[0112] The generative AI method uses generative adversarial networks (GANs) and transformation models to generate unified illustrations with diverse styles and variations based on the received rough sketch data. The generated illustration data is then returned to the server.

[0113] The server adds metadata such as the generation date and time and user ID to the illustration data returned by the generation AI and sends it to the user's terminal means via data communication means. The terminal means displays the generated illustration received from the server and notifies the user. The user can check the displayed illustration and download the image they like.

[0114] Specific examples are shown below.

[0115] Case Study: Creating Presentation Materials

[0116] User Sato needs a friendly character illustration to insert into a presentation. Sato draws a rough sketch on paper, photographs it using a dedicated smartphone app, and presses the upload button. The device sends the rough sketch data to the server. The server receives the data, analyzes the rough sketch using a generation AI, and generates multiple character illustrations that meet Sato's needs. The generated illustrations are sent from the server to Sato's smartphone and displayed in the app. Sato selects his favorite from the displayed illustrations, downloads them, and inserts them into his presentation. Thanks to this system, Sato was able to obtain high-quality character illustrations quickly and efficiently.

[0117] An example prompt is, "Create friendly character illustrations for presentations. Create illustrations in a variety of styles based on the rough sketches below."

[0118] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0119] Step 1: The user photographs or selects a rough sketch using a device and uploads it using a dedicated app or web app. The input is the rough sketch provided by the user on the device, and the output is the rough sketch displayed on the preview screen. Specifically, the user clicks the "Upload" button in the app, and then either photographs a rough sketch using the device's camera function or selects an existing image file. The user then checks and corrects the rough sketch on the preview screen and finally presses the "Send" button.

[0120] Step 2: The terminal means sends the rough sketch data sent by the user to the server. The input is the rough sketch data uploaded by the user to the terminal, and the output is the rough sketch data sent to the server. In concrete terms, when the user presses the "send" button, the terminal prepares the rough sketch data and sends the data to the server via a secure protocol.

[0121] Step 3: The server saves and analyzes the rough sketch data received from the terminal means. The input is the rough sketch data sent from the terminal, and the output is the analyzed metadata passed to the generation AI means. Specifically, the server saves the received data in a database and extracts and analyzes metadata such as resolution, file format, and size.

[0122] Step 4: The server passes the analyzed rough sketch data to a generation AI means, which generates a unified illustration with diverse styles and variations. The input is the analyzed rough sketch data, and the output is the generated illustration data. Specifically, the server inputs the analyzed data into the generation AI, which generates an illustration based on a generative adversarial network (GAN) or a transformation model.

[0123] Step 5: The server receives the illustration data returned from the generation AI, adds metadata, and sends it to the user's terminal. The input is the illustration data returned from the generation AI, and the output is the illustration data with the metadata added. Specifically, the server adds the generation date and time and user ID to the data and sends the illustration data to the user's terminal via a secure protocol.

[0124] Step 6: The terminal displays the received illustration data and notifies the user. The input is the illustration data sent from the server, and the output is the displayed illustration and the notified user. Specifically, the terminal analyzes the illustration data, notifies the user that a new illustration has been generated, and displays a preview of the generated illustration.

[0125] Step 7: The user checks the displayed illustrations and downloads the ones they like. The input is the illustration data displayed on the device, and the output is the illustration data downloaded by the user. Specifically, the user checks the illustrations on the device's display screen, presses the download button, and saves the desired illustration on the device.

[0126] (Application example 1)

[0127] 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."

[0128] The present invention relates to a system for efficiently digitizing handwritten rough sketches to generate high-quality, consistent illustrations. In particular, the objective is to provide a system that can quickly and easily generate illustrations for guidance and sales promotion in brick-and-mortar stores. Conventionally, store staff have had to spend a lot of time and effort creating illustrations, and the quality and consistency of the generated illustrations have been inconsistent.

[0129] 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.

[0130] In this invention, the server includes input means for users to upload handwritten rough drawings, central processing means for receiving the rough drawing data sent from the input means and generating images, automatic generation means in the central processing means for analyzing the rough drawing data and generating unified illustrations and images, data transmission means for transmitting the image data generated by the central processing means to the input means, and display means in the input means for displaying the generated images sent and making them available for download. This makes it possible to quickly digitize handwritten rough drawings into illustrations for physical store guides and promotional purposes and display them as illustrations for electronic displays and posters.

[0131] "Input means" refers to a device or interface that allows a user to upload a rough handwritten sketch.

[0132] The "central processing means" is a computer super or processor that receives the rough sketch data sent from the input means and executes image generation and data analysis.

[0133] The "automatic generation means" is an algorithm or AI model that analyzes rough sketch data in the central processing means and generates unified illustrations and images.

[0134] The "data transmission means" refers to a communication means, network cable, or wireless communication technology for transmitting image data generated by the central processing means to the input means.

[0135] The "display means" is a display or monitor that displays the generated image sent by the input means and allows the user to download it.

[0136] "Attribute data" refers to metadata and additional information associated with the generated image, including the date and time of generation, user ID, and the version of the AI ​​model used.

[0137] "For physical stores" refers to information and materials used in and around physical stores, including store directions, product introductions, and promotional displays.

[0138] The present invention provides a system that allows a user to efficiently digitize rough sketches drawn by hand and generate illustrations with a consistent look. Specific embodiments of this system are described below.

[0139] System Overview

[0140] The system includes the following components:

[0141] 1. Input method:

[0142] A device such as a smartphone, tablet, or PC for users to upload hand-drawn rough sketches.

[0143] The device has the ability to upload rough sketches via a dedicated app or web app.

[0144] 2. Central Processing Means:

[0145] A server that receives and analyzes rough sketch data. Typically, Google (registered trademark) Cloud Functions or AWS (registered trademark) Lambda is used.

[0146] The resolution and format of the rough sketch data are analyzed and passed on to the next step.

[0147] 3. Automatic generation means:

[0148] Image generation AI (e.g., GAN model) is used. The AI ​​model is built using Python's TENSORFLOW (registered trademark) or PyTorch library.

[0149] Based on rough sketch data, a variety of illustrations with a unified look are generated.

[0150] 4. Means of data transmission:

[0151] The internet or a mobile network is used to transmit the generated image data from the central processing means to the input means.

[0152] When data is sent, it also includes metadata such as the date and time of generation and user ID.

[0153] 5. Display means:

[0154] The generated illustrations sent via the input means are displayed on a display that the user can check and download.

[0155] It can be used as an electronic display in a physical store or as a promotional poster.

[0156] How to use

[0157] For example, when promoting a new product in a brick-and-mortar store, store staff can upload hand-drawn rough sketches using a smartphone app. The rough sketch data sent from the device is received by the server, where it is analyzed and generated. The generated illustrations can then be instantly displayed on electronic displays or posters, allowing users to easily obtain high-quality promotional materials.

[0158] A concrete example is a promotional poster for a new product in a supermarket. Store staff use their smartphones to upload a rough sketch they have drawn by hand to a dedicated app. The rough sketch is then received by a server, which analyzes and generates it using generative AI to create a high-quality digital illustration. This illustration is then instantly sent to a smartphone and displayed on an electronic display for promotional purposes.

[0159] Example prompt sentence:

[0160] "Just take a photo of a rough sketch you've created to promote your new product, press the upload button, and we'll deliver a high-quality digital illustration to you within five minutes."

[0161] In this way, the present invention makes it possible to efficiently generate high-quality, consistent illustrations in physical stores and use them for promotions and guidance.

[0162] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0163] Step 1:

[0164] Users use an input method (smartphone, tablet, or PC) to upload handwritten rough sketches. Here, users take a photo of the rough sketch and upload the image data through a dedicated app or web app. Input: Handwritten rough sketch. Output: Base64 encoded rough sketch data.

[0165] Step 2:

[0166] The device sends the uploaded rough sketch data to the server. Here, the device has an image preview function, and the user can check the rough sketch and press the send button to send the data. Input: Base64 encoded rough sketch data. Output: Rough sketch data sent to the server.

[0167] Step 3:

[0168] The server receives the rough sketch data. The server stores the data appropriately and analyzes the image resolution and format. Input: Rough sketch data. Output: Analyzed image data.

[0169] Step 4:

[0170] The server passes the analyzed image data to an automatic generation method (generative AI model). The generative AI model generates unified illustrations with diverse styles and variations based on the received rough sketch data. Input: Analyzed image data. Output: Generated illustration data.

[0171] Step 5:

[0172] The server adds metadata such as the date and time of creation and the user ID to the generated illustration data and transmits it to the terminal via the data transmission means. Input: Generated illustration data. Output: Generated illustration data with metadata.

[0173] Step 6:

[0174] The device receives the generated illustration data sent from the server and notifies the user. The user can check the generated images in the app and download the illustrations they like. Input: Generated illustration data with metadata. Output: Displayed generated illustration, download link.

[0175] Step 7:

[0176] (Example) Store staff upload hand-drawn rough sketches using a dedicated smartphone app. The server receives the rough sketches and uses a generative AI model to generate a consistent illustration. The generated illustrations can be viewed instantly on the smartphone and, if necessary, displayed on electronic displays or promotional posters. This makes it possible to quickly provide high-quality promotional materials within the store.

[0177] 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.

[0178] The present invention relates to a system for efficiently digitizing a user's rough handwritten sketches and generating a variety of illustrations with a consistent feel that reflect the user's emotions. Specific embodiments of this system are described below.

[0179] System Overview

[0180] This system includes a terminal means for uploading rough drawings drawn by hand by the user, a server means for receiving the rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, a display means for displaying and downloading the generated images, and an emotion engine for recognizing the user's emotions.

[0181] Program processing flow

[0182] 1. Upload a rough sketch

[0183] Users upload handwritten rough sketches using a dedicated app or web app on terminal means such as a smartphone, tablet, or PC. The terminal means has an image preview function, and after the user checks and corrects the rough sketch, they press the send button, which sends the rough sketch data to the server means.

[0184] 2. Receiving and analyzing rough sketch data

[0185] The server receives the rough sketch data sent from the terminal means. The server stores this data appropriately and analyzes the image resolution and format. Based on the analysis results, the server passes the rough sketch data to the generation AI means.

[0186] 3. Emotion recognition using the emotion engine

[0187] The emotion engine integrated into the server recognizes the user's emotions by analyzing the rough sketches uploaded by the user and other input data (e.g., text input, voice, facial expressions, etc.). Based on the emotion recognition results, the user's current mood and emotional state are understood.

[0188] 4. Generating illustrations using generative AI

[0189] Based on the rough sketch data received by the generation AI means integrated into the server, it generates illustrations with a unified look and a variety of styles and variations. It reflects the emotion recognition results from the emotion engine and generates illustrations using soft colors if the user is relaxed, or bright colors if the user is energetic.

[0190] 5. Sending the generated image data to the terminal

[0191] The server transmits the generated illustrations and images to the terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added to the generated image data.

[0192] 6. Viewing and downloading generated images

[0193] The terminal means displays the generated images received and notifies the user, who can then check the displayed images and download any images he or she likes to use in documents or on a website.

[0194] Specific examples

[0195] Case Study: Creating an Illustration Blog

[0196] User Sato wants to create an illustration to post on his blog. First, Sato draws a rough sketch on paper, then takes a photo of it using a dedicated smartphone app and presses the upload button. The app also includes a function to input emotional information in the form of simple questions, and Sato enters that he feels "relaxed."

[0197] The device sends rough sketch data and emotion data to the server. The server receives this data and uses generative AI to generate a cohesive illustration. Based on the information from the emotion engine, an illustration with a relaxed atmosphere and soft colors is generated. This generated illustration is sent from the server to Sato's smartphone and displayed in the app.

[0198] Sato chose her favorite illustration from the displayed list, downloaded it, and posted it on her blog. Thanks to this system, Sato was able to quickly and efficiently create a high-quality illustration that reflected her relaxed mood.

[0199] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate a variety of illustrations that reflect their emotions.

[0200] The processing flow will be explained below.

[0201] Step 1:

[0202] The user draws a rough sketch by hand. The user sketches out an idea or concept by hand on paper or a digital device.

[0203] Step 2:

[0204] The user uses a device (smartphone, tablet, PC, etc.) to take a rough sketch or select an existing image. The device displays the rough sketch selected by the user on a preview screen.

[0205] Step 3:

[0206] The user checks the rough sketch on the device's preview screen, makes corrections or retakes the photo as necessary, and when the user is satisfied, presses the upload button.

[0207] Step 4:

[0208] The device converts the selected rough sketch into the appropriate format (e.g., JPEG, PNG) and adds metadata (user ID, timestamp, etc.).

[0209] Step 5:

[0210] The terminal displays rough sketch data and an interface for inputting emotions to the user, who then inputs their current emotional state.

[0211] Step 6:

[0212] The device sends the rough sketch data and emotion data to the server using an HTTP POST request.

[0213] Step 7:

[0214] The server receives the HTTP POST request, receives the rough sketch data and emotion data, and saves them.

[0215] Step 8:

[0216] The server analyzes the received rough sketch data, checks the image resolution and format, and converts the rough sketch data into a format that can be used by the AI ​​generation method.

[0217] Step 9:

[0218] An emotion engine integrated in the server analyzes the received emotion data and recognizes the user's emotional state (e.g., relaxed, energetic, sad, etc.).

[0219] Step 10:

[0220] The server invokes the generative AI means (e.g., GAN, Transformer) and sets the necessary parameters. Based on input from the emotion engine, the parameters of the generative AI means are adjusted.

[0221] Step 11:

[0222] The server inputs the rough sketch data and emotional data into the generation AI means and begins generating the illustration.

[0223] Step 12:

[0224] The generative AI generates unified illustrations and images from rough sketch data, adjusting the style and color tone of the illustrations while taking into account the emotional data from the emotion engine.

[0225] Step 13:

[0226] If the generating AI generates illustrations in multiple styles or variations, it will generate different versions of the illustration.

[0227] Step 14:

[0228] The server saves the generated illustrations and records metadata such as the creation date and time, user ID, and emotional state.

[0229] Step 15:

[0230] The server compresses or encodes the generated illustration data and prepares it for transmission.

[0231] Step 16:

[0232] The server sends the generated illustration data to the terminal as an HTTP response.

[0233] Step 17:

[0234] The terminal displays the generated illustration data received from the server, and the user checks the multiple generated illustrations.

[0235] Step 18:

[0236] Users can select the generated illustration they like, press the download button, and save the image to their device. Users can use it in documents or on their website.

[0237] The above are the specific processing steps for generating a unified illustration from a hand-drawn rough sketch that reflects the user's emotions.

[0238] Example 2

[0239] 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."

[0240] Conventional rough sketch digitization systems simply convert handwritten rough sketches into digital data, making it difficult to generate illustrations that reflect the user's emotions. It is also difficult to create a sense of unity among the generated illustrations or to generate illustrations with multiple styles and variations. As a result, it has not been possible to efficiently generate diverse, high-quality illustrations that match the user's intentions.

[0241] 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.

[0242] In this invention, the server includes a generation AI means for analyzing rough sketch data and generating unified illustrations and images, an emotion recognition means for analyzing the user's emotions and reflecting them in the generated illustrations, and a data communication means, which enables the efficient generation of diverse, high-quality illustrations that reflect the user's emotions.

[0243] "Terminal means" refers to an electronic device that allows a user to upload handwritten rough sketches, and includes smartphones, tablets, PCs, etc.

[0244] The "computer means" is a device having a server or computer function for receiving and analyzing rough sketch data.

[0245] "Generative AI means" is a system that uses artificial intelligence technology to analyze rough sketch data and generate unified illustrations and images.

[0246] "Emotion recognition means" is a system that includes analytical techniques and algorithms for analyzing the user's emotions and reflecting them in the generated illustrations.

[0247] "Data communication means" refers to communication techniques and protocols for transmitting and receiving data between the computer means and the terminal means.

[0248] "Display means" refers to a display or software interface for displaying the transmitted generated image to the user and making it available for download.

[0249] "Rough sketch data" is a digital representation of a rough sketch hand-drawn by a user.

[0250] "Metadata" is additional information related to the generated image, including the date and time of generation, user ID, emotion recognition results, etc.

[0251] The present invention relates to a system for efficiently digitizing rough sketches hand-drawn by a user and generating a variety of illustrations with a consistent feel that reflect the user's emotions. Specific embodiments of this system are described below.

[0252] System Overview

[0253] This system includes terminal means for uploading rough drawings drawn by hand by the user, computer means for receiving the rough drawing data and generating images, generation AI means for generating unified illustrations and images, data communication means for transmitting the generated image data, display means for displaying and downloading the generated images, and emotion recognition means for recognizing the user's emotions.

[0254] Terminal means

[0255] A user launches a dedicated app or web app using a terminal means such as a smartphone, tablet, or PC. Using this terminal means, the user photographs a handwritten rough sketch or selects it using a file selection function. After that, the user checks the rough sketch on the preview screen, makes any necessary corrections, and then presses the send button to send the rough sketch data to the computer means.

[0256] computer means

[0257] The computer means includes a server and other computer devices. The computer means receives the rough sketch data sent from the terminal means and first stores it appropriately in storage. Then, it analyzes the resolution, format, size, etc. of the rough sketch data and converts it into a form suitable for the generating AI means. It also analyzes the user's emotions using the emotion recognition means.

[0258] Generation AI means

[0259] The AI ​​generation means generates unified illustrations with diverse styles and variations based on the received rough sketch data. It reflects the emotion recognition results of the emotion recognition means, generating illustrations with pale colors for a relaxed character, and bright colors for an energetic character.

[0260] Data communication means

[0261] The data communication means includes communication technologies and protocols for transmitting and receiving data between the computer means and the terminal means. The generated illustrations and images are sent to the terminal means along with metadata such as the generation date and time, user ID, and emotion recognition results.

[0262] Display means

[0263] The terminal means includes a display and a software interface for displaying the received generated images to the user and making them available for download, so that the user can check the displayed images and download and use the images they like.

[0264] Specific examples

[0265] Case Study: Creating an Illustration Blog

[0266] A user is thinking about creating an illustration to post on their blog. First, they draw a rough sketch by hand on paper, then use a dedicated smartphone app to take a photo of the rough sketch and press the upload button. The dedicated app also includes a function to input emotional information in the form of a simple question, and the user enters that they are feeling "relaxed."

[0267] The terminal transmits the rough sketch data and emotion data to the computing means. The computing means receives this data and uses the generation AI to generate a unified illustration. Based on the information from the emotion recognition means, an illustration with a relaxed atmosphere and soft colors is generated. This generated illustration is transmitted from the computing means to the user's smartphone and displayed on a dedicated app.

[0268] Users can select their favorite illustrations from the displayed list, download them, and post them to their blogs. In this way, users can quickly and efficiently create high-quality illustrations that reflect their emotions.

[0269] Prompt Sentence Examples

[0270] "Please turn the rough sketches that users have drawn by hand into digital illustrations with a relaxed atmosphere. Please design using soft colors."

[0271] Based on this prompt, the generative AI generates an illustration that reflects the user's emotions.

[0272] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate a variety of illustrations that reflect their emotions.

[0273] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0274] Step 1: User uploads rough sketch

[0275] The user launches a dedicated app or web app using a device such as a smartphone, tablet, or PC. The user then uses the camera or file selection function to take or select a handwritten rough sketch. After checking the rough sketch on the preview screen and making any necessary corrections, the user presses the send button. The data entered by the user at this time is rough sketch image data, which is sent from the device to the server.

[0276] Specific working example:

[0277] The user draws a rough sketch by hand on paper.

[0278] The user takes a rough sketch using the smartphone camera.

[0279] The user taps the "Upload" button on the dedicated app, checks the preview screen, and then presses the "Send" button.

[0280] Input: rough sketch image data

[0281] Output: Send image data to the server

[0282] Step 2: The server receives and analyzes the rough sketch data.

[0283] The server receives the rough sketch data sent from the device. The received data is first stored in the server's storage. The server then analyzes the image data's resolution, format, size, etc., and converts it into a format that can be used by the generation AI. This process performs preprocessing to provide the optimal data to the generation AI.

[0284] Specific working example:

[0285] The server saves the image file in a storage directory.

[0286] The server analyzes the image file's resolution, format, and size, and resizes or converts the format as needed.

[0287] Input: rough sketch image data

[0288] Output: Image data formatted for generative AI

[0289] Step 3: The server's emotion recognition means recognizes the emotion.

[0290] The emotion recognition means integrated into the server analyzes the rough sketches and other input data (e.g., text input, voice, facial expressions, etc.) uploaded by the user to recognize the user's emotions. The emotion engine uses facial expression analysis algorithms and text analysis algorithms to identify the user's emotional state. This recognition result is used as important input data for subsequent illustration generation.

[0291] Specific working example:

[0292] An emotion recognition means of the server analyzes the text comments related to the rough sketch.

[0293] The emotion recognition means of the server analyzes the voice data and identifies the emotion.

[0294] Input: rough sketch, text comments, audio data

[0295] Output: User emotion recognition results

[0296] Step 4: Server generation AI generates illustrations

[0297] The server's generation AI generates a consistent illustration based on the rough sketch data and the emotion recognition results. It reflects the emotion recognition results, generating an illustration with soft colors if the user is relaxed, or bright colors if the user is energetic. This process ensures that the generated illustration reflects the user's emotions.

[0298] Specific working example:

[0299] The server inputs rough sketch data and emotional data into the generation AI.

[0300] The generation AI generates illustrations according to prompts.

[0301] Input: rough sketch data, emotion recognition results

[0302] Output: Generated illustration data

[0303] Step 5: The server sends the generated image data to the terminal.

[0304] The server sends the generated illustrations and images to the terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added to the generated image data. This process allows the user to check the generated illustrations.

[0305] Specific working example:

[0306] The server adds metadata to the generated illustration.

[0307] The illustration data is transmitted to the terminal through the data communication means.

[0308] Input: Generated illustration data

[0309] Output: Illustration data sent to the device

[0310] Step 6: The device displays the generated image and makes it available for download

[0311] The device displays the generated images to the user and makes them available for download. A notification function lets the user know that new illustrations are available. The user can review the displayed images and download the ones they like for use in other materials or on other websites.

[0312] Specific working example:

[0313] The illustrations received by the device will be displayed on the app's gallery screen.

[0314] Use notifications to let users know when new illustrations are available.

[0315] The user selects the illustration they like and clicks the "Download" button.

[0316] Input: Illustration data sent from the server

[0317] Output: The illustration that is displayed to the user and available for download

[0318] (Application example 2)

[0319] 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."

[0320] Conventional systems struggle to efficiently generate consistent designs and styles when digitizing users' handwritten rough sketches. Furthermore, they are unable to generate illustrations that reflect the user's emotional state, making it difficult to create custom designs that satisfy the user. Furthermore, they lack the functionality to manage metadata for the generated illustrations, making subsequent editing and reuse cumbersome.

[0321] 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.

[0322] In this invention, the server includes a terminal means for users to upload handwritten rough sketches; a server means for receiving the rough sketch data sent from the terminal means and generating images; a generation AI means in the server means for analyzing the rough sketch data and generating unified illustrations and images; an emotion recognition means in the server means for adjusting the style and color tone of the generated images based on emotions; a data communication means for transmitting the generated image data from the server means to the terminal means; and a display means in the terminal means for displaying the transmitted generated images and making them available for download. This allows users to easily digitize handwritten rough sketches and generate illustrations that reflect their emotions. This not only enables the rapid creation of custom products with consistent designs, but also simplifies subsequent editing and reuse thanks to the metadata management function.

[0323] "User" means a person who uses the system to upload hand-drawn rough sketches and create digitized illustrations and product designs.

[0324] A "hand-drawn rough sketch" is an early sketch that a user draws on paper or a digital device.

[0325] "Terminal means" refers to a device such as a smartphone, tablet, or PC that a user uses to upload rough sketches.

[0326] "Server means" refers to a server that receives and analyzes rough sketch data and generates illustrations and images using generation AI.

[0327] "Generative AI means" refers to artificial intelligence that analyzes rough sketch data and generates unified illustrations and images.

[0328] The "emotion recognition means" is an engine that analyzes the user's emotional state and adjusts the style and color tone of the generated image.

[0329] The "data communication means" refers to a mechanism for transmitting the generated image data from the server means to the terminal means.

[0330] "Display means" refers to a device or software that has the function of displaying the generated image on a terminal and allowing the user to view and download the image.

[0331] "Metadata" is additional information related to the generated image, including the date and time of generation, user ID, emotion recognition results, etc.

[0332] The present invention relates to a system that digitizes rough sketches handwritten by a user and generates a variety of illustrations that reflect emotion and have a consistent feel. Specific embodiments of this system will be described below.

[0333] The server includes terminal means for users to upload handwritten rough drawings, server means for receiving the rough drawing data sent from the terminal means and generating images, generation AI means for analyzing the rough drawing data and generating unified illustrations and images, emotion recognition means for adjusting the style and color tone of the generated images based on emotions, data communication means for sending the image data generated from the server means to the terminal means, and display means for displaying the sent generated images and making them available for download.

[0334] Hardware and software used

[0335] Terminal means: A device such as a smartphone, tablet, or PC that a user uses to upload handwritten rough sketches.

[0336] Server method: A server running a high-performance CPU / GPU is used to receive and analyze rough sketch data.

[0337] Generative AI methods: Using generative models (e.g., GAN, VAE) trained using deep learning libraries such as TensorFlow or Keras.

[0338] Emotion recognizer: An engine or model for analyzing emotions (e.g., an emotion recognition model trained with TensorFlow or Keras).

[0339] Display: An application that allows the user to view and download the generated images on their device.

[0340] Data processing and calculation

[0341] 1. The user takes a picture of a rough sketch using a terminal and uploads it through a dedicated application. At the same time, the user inputs emotional information in the form of simple questions.

[0342] 2. The terminal means transmits the rough sketch data and emotion data to the server.

[0343] 3. The server analyzes the received rough sketch data and converts it into an appropriate resolution and format. The emotion recognition analyzes the emotion data and recognizes the user's current emotional state.

[0344] 4. The AI ​​generation method generates unified illustrations and product designs based on rough sketch data and emotion recognition results. Color tones and design patterns are adjusted based on the emotion recognition results.

[0345] 5. The generated image data is sent from the server to the device, along with metadata such as the generation date and time, user ID, and emotion recognition results.

[0346] 6. The terminal means displays the generated image, and the user checks the image, downloads it, and uses it.

[0347] Specific examples

[0348] If a user wants to design a custom T-shirt in the virtual store, they first sketch it on paper, then photograph it using a dedicated smartphone app and upload it. During this process, the user inputs their current emotion as "energetic." The server uses an emotion recognition engine to interpret the input emotion data, and the generation AI generates a brightly colored design that matches that emotion. The generated design is sent to the user's smartphone and displayed in the app. The user can then select their favorite design and download it, completing their custom T-shirt.

[0349] Example prompt sentence:

[0350] User: "I'm uploading a rough sketch I did on paper. I'm feeling energetic right now. I'd like to create a custom t-shirt design with a bright color scheme and a cohesive look."

[0351] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0352] Step 1:

[0353] The user prepares a rough sketch by hand and then photographs or scans it using a dedicated application on a device such as a smartphone, tablet, or PC. The user also inputs their current emotional state into the application, using prompts or simple questions. The input data consists of image data of the rough sketch and emotional data.

[0354] Step 2:

[0355] The terminal transmits rough sketch data and emotion data to the server. The transmitted data includes image data of the rough sketch and the user's emotion information. The data calculation in this step is the accurate transfer of image and emotion data. The terminal receives rough sketch data and emotion data as input and transmits them to the server as output.

[0356] Step 3:

[0357] The server receives the rough sketch data sent from the device. The received data includes rough sketch image data and emotion data. The server analyzes this data and converts the image resolution and format to an appropriate format. The input data is the rough sketch data, and the output data is the analyzed rough sketch data.

[0358] Step 4:

[0359] The server uses an emotion recognition means to analyze the user's emotion data. It uses an emotion recognition engine (e.g., a model trained with TensorFlow or Keras) to classify the user's current emotional state. The input data is the emotion data, and the output data is the recognized emotional state (e.g., energetic, relaxed, etc.).

[0360] Step 5:

[0361] The server uses a generative AI to generate illustrations and product designs based on the analyzed rough sketch data and emotion recognition results. The generative AI (e.g., a GAN or VAE model) adjusts color tones and design patterns based on the emotion recognition results. The input data are the rough sketch data and emotion recognition results, and the output data is the generated illustration or design.

[0362] Step 6:

[0363] The server transmits the generated illustrations and designs to the user's terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added. The input data is the generated illustrations and designs and metadata, and the output data is the transmitted illustrations and designs.

[0364] Step 7:

[0365] The terminal means displays the received generated image. The user checks the displayed image and downloads it if necessary. The input data is the received generated image, and the output data is the displayed and downloaded image.

[0366] In this way, specific actions, inputs, and outputs are clarified at each step, realizing the process of digitizing the user's rough handwritten sketch and generating a custom design that reflects their emotions.

[0367] 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.

[0368] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0369] 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.

[0370] [Second embodiment]

[0371] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0372] 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.

[0373] 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).

[0374] 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.

[0375] 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.

[0376] 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).

[0377] 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.

[0378] 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.

[0379] 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.

[0380] 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.

[0381] 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.

[0382] 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."

[0383] The present invention relates to a system that enables a user to efficiently digitize rough sketches drawn by hand and generate a variety of illustrations with a unified appearance. Specific embodiments of this system are described below.

[0384] System Overview

[0385] This system includes a terminal means for uploading rough drawings drawn by hand by the user, a server means for receiving rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, and a display means for displaying and downloading the generated images.

[0386] Program processing flow

[0387] 1. Upload a rough sketch

[0388] Users upload handwritten rough sketches using a dedicated app or web app on terminal means such as a smartphone, tablet, or PC. The terminal means has an image preview function, and after the user checks and corrects the rough sketch, they press the send button, which sends the rough sketch data to the server means.

[0389] 2. Receiving and analyzing rough sketch data

[0390] The server receives the rough sketch data sent from the terminal means. The server stores this data appropriately and analyzes the image resolution and format. Based on the analysis results, the server passes the rough sketch data to the generation AI means.

[0391] 3. Generating illustrations using generative AI

[0392] The server-integrated generative AI generates unified illustrations with various styles and variations based on the received rough sketch data. In this process, the generative AI uses, for example, generative adversarial networks (GANs) and transformation models.

[0393] 4. Sending the generated image data to the terminal

[0394] The server transmits the generated illustrations and images to the terminal means via data communication means. At this time, metadata such as the generation date and time and the user ID are also added to the generated image data.

[0395] 5. Viewing and downloading generated images

[0396] The terminal means displays the generated images received and notifies the user, who can then check the displayed images and download any images he or she likes to use in documents or on a website.

[0397] Specific examples

[0398] Case Study: Creating Presentation Materials

[0399] User Tanaka needs a friendly character illustration to insert into a presentation. He draws a rough sketch on paper, takes a photo of it using a dedicated app on his smartphone, and presses the upload button.

[0400] The device sends the rough sketch data to a server. The server receives the data, analyzes the rough sketch using a generation AI, and generates multiple character illustrations according to Tanaka's wishes. The generated illustrations are then sent from the server to Tanaka's smartphone and displayed in the app.

[0401] Tanaka could choose his favorite from the multiple illustrations displayed, download them, and insert them into his presentation materials. Thanks to this system, Tanaka was able to obtain high-quality character illustrations quickly and efficiently.

[0402] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate illustrations that meet a variety of needs.

[0403] The processing flow will be explained below.

[0404] Step 1:

[0405] The user draws a rough sketch by hand.

[0406] Step 2:

[0407] The user takes a rough sketch using a device (smartphone, tablet, PC, etc.) or selects an existing image.

[0408] Step 3:

[0409] The device displays the selected rough sketch on a preview screen, and the user presses the upload button.

[0410] Step 4:

[0411] The device converts the rough sketch data into an appropriate format (e.g., JPEG, PNG).

[0412] Step 5:

[0413] The device adds metadata (user ID, timestamp, etc.) to the rough sketch data.

[0414] Step 6:

[0415] The device sends the rough sketch data to the server via an HTTP POST request.

[0416] Step 7:

[0417] The server receives the HTTP POST request and receives the rough sketch data.

[0418] Step 8:

[0419] The server stores the rough sketch data in an appropriate storage system.

[0420] Step 9:

[0421] The server analyzes the rough sketch data it receives and converts it into a format that can be used by the generation AI.

[0422] Step 10:

[0423] The server invokes the generative AI method (e.g., GAN, Transformer) and sets the necessary parameters.

[0424] Step 11:

[0425] The server inputs the rough sketch data into the generation AI means and begins generating the illustration.

[0426] Step 12:

[0427] Generative AI generates unified illustrations and images from rough sketch data.

[0428] Step 13:

[0429] If the generating AI generates illustrations in multiple styles or variations, it will generate different versions of the illustration.

[0430] Step 14:

[0431] The server saves the generated illustrations and adds metadata.

[0432] Step 15:

[0433] The server compresses or encodes the generated illustrations and prepares them for data transmission.

[0434] Step 16:

[0435] The server sends the generated illustration data to the terminal as an HTTP response.

[0436] Step 17:

[0437] The terminal displays the generated illustration data received from the server.

[0438] Step 18:

[0439] The user can check the generated illustrations and download them if necessary.

[0440] Example 1

[0441] 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."

[0442] Currently, many users find it difficult to digitize rough sketches and then use them to create consistent illustrations or images. In particular, it is difficult to easily correct or check rough sketches during digitization, and the resulting illustrations often do not match the user's desired style or variation. Furthermore, managing the metadata associated with the resulting images is cumbersome. To address these issues, a system is needed that can efficiently digitize rough sketches, generate a wide variety of illustrations, and properly manage metadata.

[0443] 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.

[0444] In this invention, the server includes terminal means for users to upload handwritten rough drawings, server means for receiving rough drawing data sent from the terminal means and generating images, generation AI means for analyzing the rough drawing data and generating unified illustrations and images, data communication means for transmitting the generated image data from the server means to the terminal means, display means in the terminal means for displaying the transmitted generated images and making them available for download, and a function in the terminal means for previewing the rough drawings and for user correction, and a function for users to send the rough drawings after checking and correcting them. This enables users to easily digitize and correct their handwritten rough drawings and generate, display, and download a variety of illustrations.

[0445] "Terminal means" refers to an electronic device used by a user to upload handwritten rough sketches, and includes smartphones, tablets, PCs, etc.

[0446] The "server means" is a computer system that receives rough sketch data sent from the terminal means, analyzes and stores the data, and generates an image.

[0447] The "generative AI means" is an artificial intelligence model used by the server means to generate unified illustrations and images based on the received rough sketch data, and utilizes a generative adversarial network (GAN) or a transformation model.

[0448] "Data communication means" refers to the communication infrastructure and protocol for transmitting image data generated by the server means to the terminal means.

[0449] "Display Means" means a software function that displays the generated image transmitted by the Terminal Means and enables the user to confirm and download it.

[0450] The "preview function" is a function that allows the user to check and correct the rough sketch that he or she uploads on the terminal means.

[0451] The "correction function" is a function that allows the user to make corrections to the rough image during preview, and is installed in the terminal means.

[0452] "Rough sketch data" is data that digitally represents a rough sketch that a user has hand-drawn.

[0453] "Metadata" refers to accompanying information such as the date and time of generation and user ID that is added to the generated image data.

[0454] The present invention relates to a system that enables a user to efficiently digitize rough sketches drawn by hand and generate a variety of illustrations with a unified appearance. Specific embodiments of this system are described below.

[0455] The system includes a terminal means for users to upload rough drawings drawn by hand, a server means for receiving the rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, and a display means for displaying and downloading the generated images.

[0456] The user uploads rough sketches using a dedicated app or web app using a terminal means such as a smartphone, tablet, or PC. The terminal means is equipped with an image preview function and an editing function, and the user can check and edit the rough sketch and then press the send button, which sends the rough sketch data to the server means.

[0457] The server receives the rough sketch data sent from the terminal means, stores the data appropriately, analyzes the resolution and format of the received rough sketch data, and passes the analyzed metadata to the generation AI means.

[0458] The generative AI method uses generative adversarial networks (GANs) and transformation models to generate unified illustrations with diverse styles and variations based on the received rough sketch data. The generated illustration data is then returned to the server.

[0459] The server adds metadata such as the generation date and time and user ID to the illustration data returned by the generation AI and sends it to the user's terminal means via data communication means. The terminal means displays the generated illustration received from the server and notifies the user. The user can check the displayed illustration and download the image they like.

[0460] Specific examples are shown below.

[0461] Case Study: Creating Presentation Materials

[0462] User Sato needs a friendly character illustration to insert into a presentation. Sato draws a rough sketch on paper, photographs it using a dedicated smartphone app, and presses the upload button. The device sends the rough sketch data to the server. The server receives the data, analyzes the rough sketch using a generation AI, and generates multiple character illustrations that meet Sato's needs. The generated illustrations are sent from the server to Sato's smartphone and displayed in the app. Sato selects his favorite from the displayed illustrations, downloads them, and inserts them into his presentation. Thanks to this system, Sato was able to obtain high-quality character illustrations quickly and efficiently.

[0463] An example prompt is, "Create friendly character illustrations for presentations. Create illustrations in a variety of styles based on the rough sketches below."

[0464] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0465] Step 1: The user photographs or selects a rough sketch using a device and uploads it using a dedicated app or web app. The input is the rough sketch provided by the user on the device, and the output is the rough sketch displayed on the preview screen. Specifically, the user clicks the "Upload" button in the app, and then either photographs a rough sketch using the device's camera function or selects an existing image file. The user then checks and corrects the rough sketch on the preview screen and finally presses the "Send" button.

[0466] Step 2: The terminal means sends the rough sketch data sent by the user to the server. The input is the rough sketch data uploaded by the user to the terminal, and the output is the rough sketch data sent to the server. In concrete terms, when the user presses the "send" button, the terminal prepares the rough sketch data and sends the data to the server via a secure protocol.

[0467] Step 3: The server saves and analyzes the rough sketch data received from the terminal means. The input is the rough sketch data sent from the terminal, and the output is the analyzed metadata passed to the generation AI means. Specifically, the server saves the received data in a database and extracts and analyzes metadata such as resolution, file format, and size.

[0468] Step 4: The server passes the analyzed rough sketch data to a generation AI means, which generates a unified illustration with diverse styles and variations. The input is the analyzed rough sketch data, and the output is the generated illustration data. Specifically, the server inputs the analyzed data into the generation AI, which generates an illustration based on a generative adversarial network (GAN) or a transformation model.

[0469] Step 5: The server receives the illustration data returned from the generation AI, adds metadata, and sends it to the user's terminal. The input is the illustration data returned from the generation AI, and the output is the illustration data with the metadata added. Specifically, the server adds the generation date and time and user ID to the data and sends the illustration data to the user's terminal via a secure protocol.

[0470] Step 6: The terminal displays the received illustration data and notifies the user. The input is the illustration data sent from the server, and the output is the displayed illustration and the notified user. Specifically, the terminal analyzes the illustration data, notifies the user that a new illustration has been generated, and displays a preview of the generated illustration.

[0471] Step 7: The user checks the displayed illustrations and downloads the ones they like. The input is the illustration data displayed on the device, and the output is the illustration data downloaded by the user. Specifically, the user checks the illustrations on the device's display screen, presses the download button, and saves the desired illustration on the device.

[0472] (Application example 1)

[0473] 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."

[0474] The present invention relates to a system for efficiently digitizing handwritten rough sketches to generate high-quality, consistent illustrations. In particular, the objective is to provide a system that can quickly and easily generate illustrations for guidance and sales promotion in brick-and-mortar stores. Conventionally, store staff have had to spend a lot of time and effort creating illustrations, and the quality and consistency of the generated illustrations have been inconsistent.

[0475] 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.

[0476] In this invention, the server includes input means for users to upload handwritten rough drawings, central processing means for receiving the rough drawing data sent from the input means and generating images, automatic generation means in the central processing means for analyzing the rough drawing data and generating unified illustrations and images, data transmission means for transmitting the image data generated by the central processing means to the input means, and display means in the input means for displaying the generated images sent and making them available for download. This makes it possible to quickly digitize handwritten rough drawings into illustrations for physical store guides and promotional purposes and display them as illustrations for electronic displays and posters.

[0477] "Input means" refers to a device or interface that allows a user to upload a rough handwritten sketch.

[0478] The "central processing means" is a computer super or processor that receives the rough sketch data sent from the input means and executes image generation and data analysis.

[0479] The "automatic generation means" is an algorithm or AI model that analyzes rough sketch data in the central processing means and generates unified illustrations and images.

[0480] The "data transmission means" refers to a communication means, network cable, or wireless communication technology for transmitting image data generated by the central processing means to the input means.

[0481] The "display means" is a display or monitor that displays the generated image sent by the input means and allows the user to download it.

[0482] "Attribute data" refers to metadata and additional information associated with the generated image, including the date and time of generation, user ID, and the version of the AI ​​model used.

[0483] "For physical stores" refers to information and materials used in and around physical stores, including store directions, product introductions, and promotional displays.

[0484] The present invention provides a system that allows a user to efficiently digitize rough sketches drawn by hand and generate illustrations with a consistent look. Specific embodiments of this system are described below.

[0485] System Overview

[0486] The system includes the following components:

[0487] 1. Input method:

[0488] A device such as a smartphone, tablet, or PC for users to upload hand-drawn rough sketches.

[0489] The device has the ability to upload rough sketches via a dedicated app or web app.

[0490] 2. Central Processing Means:

[0491] A server that receives and analyzes rough sketch data. Typically, Google Cloud Functions or AWS Lambda is used.

[0492] The resolution and format of the rough sketch data are analyzed and passed on to the next step.

[0493] 3. Automatic generation means:

[0494] Image generation AI (e.g., GAN model) is used. The AI ​​model is built using Python's TensorFlow or PyTorch libraries.

[0495] Based on rough sketch data, a variety of illustrations with a unified look are generated.

[0496] 4. Means of data transmission:

[0497] The internet or a mobile network is used to transmit the generated image data from the central processing means to the input means.

[0498] When data is sent, it also includes metadata such as the date and time of generation and user ID.

[0499] 5. Display means:

[0500] The generated illustrations sent via the input means are displayed on a display that the user can check and download.

[0501] It can be used as an electronic display in a physical store or as a promotional poster.

[0502] How to use

[0503] For example, when promoting a new product in a brick-and-mortar store, store staff can upload hand-drawn rough sketches using a smartphone app. The rough sketch data sent from the device is received by the server, where it is analyzed and generated. The generated illustrations can then be instantly displayed on electronic displays or posters, allowing users to easily obtain high-quality promotional materials.

[0504] A concrete example is a promotional poster for a new product in a supermarket. Store staff use their smartphones to upload a rough sketch they have drawn by hand to a dedicated app. The rough sketch is then received by a server, which analyzes and generates it using generative AI to create a high-quality digital illustration. This illustration is then instantly sent to a smartphone and displayed on an electronic display for promotional purposes.

[0505] Example prompt sentence:

[0506] "Just take a photo of a rough sketch you've created to promote your new product, press the upload button, and we'll deliver a high-quality digital illustration to you within five minutes."

[0507] In this way, the present invention makes it possible to efficiently generate high-quality, consistent illustrations in physical stores and use them for promotions and guidance.

[0508] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0509] Step 1:

[0510] Users use an input method (smartphone, tablet, or PC) to upload handwritten rough sketches. Here, users take a photo of the rough sketch and upload the image data through a dedicated app or web app. Input: Handwritten rough sketch. Output: Base64 encoded rough sketch data.

[0511] Step 2:

[0512] The device sends the uploaded rough sketch data to the server. Here, the device has an image preview function, and the user can check the rough sketch and press the send button to send the data. Input: Base64 encoded rough sketch data. Output: Rough sketch data sent to the server.

[0513] Step 3:

[0514] The server receives the rough sketch data. The server stores the data appropriately and analyzes the image resolution and format. Input: Rough sketch data. Output: Analyzed image data.

[0515] Step 4:

[0516] The server passes the analyzed image data to an automatic generation method (generative AI model). The generative AI model generates unified illustrations with diverse styles and variations based on the received rough sketch data. Input: Analyzed image data. Output: Generated illustration data.

[0517] Step 5:

[0518] The server adds metadata such as the date and time of creation and the user ID to the generated illustration data and transmits it to the terminal via the data transmission means. Input: Generated illustration data. Output: Generated illustration data with metadata.

[0519] Step 6:

[0520] The device receives the generated illustration data sent from the server and notifies the user. The user can check the generated images in the app and download the illustrations they like. Input: Generated illustration data with metadata. Output: Displayed generated illustration, download link.

[0521] Step 7:

[0522] (Example) Store staff upload hand-drawn rough sketches using a dedicated smartphone app. The server receives the rough sketches and uses a generative AI model to generate a consistent illustration. The generated illustrations can be viewed instantly on the smartphone and, if necessary, displayed on electronic displays or promotional posters. This makes it possible to quickly provide high-quality promotional materials within the store.

[0523] 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.

[0524] The present invention relates to a system for efficiently digitizing a user's rough handwritten sketches and generating a variety of illustrations with a consistent feel that reflect the user's emotions. Specific embodiments of this system are described below.

[0525] System Overview

[0526] This system includes a terminal means for uploading rough drawings drawn by hand by the user, a server means for receiving the rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, a display means for displaying and downloading the generated images, and an emotion engine for recognizing the user's emotions.

[0527] Program processing flow

[0528] 1. Upload a rough sketch

[0529] Users upload handwritten rough sketches using a dedicated app or web app on terminal means such as a smartphone, tablet, or PC. The terminal means has an image preview function, and after the user checks and corrects the rough sketch, they press the send button, which sends the rough sketch data to the server means.

[0530] 2. Receiving and analyzing rough sketch data

[0531] The server receives the rough sketch data sent from the terminal means. The server stores this data appropriately and analyzes the image resolution and format. Based on the analysis results, the server passes the rough sketch data to the generation AI means.

[0532] 3. Emotion recognition using the emotion engine

[0533] The emotion engine integrated into the server recognizes the user's emotions by analyzing the rough sketches uploaded by the user and other input data (e.g., text input, voice, facial expressions, etc.). Based on the emotion recognition results, the user's current mood and emotional state are understood.

[0534] 4. Generating illustrations using generative AI

[0535] Based on the rough sketch data received by the generation AI means integrated into the server, it generates illustrations with a unified look and a variety of styles and variations. It reflects the emotion recognition results from the emotion engine and generates illustrations using soft colors if the user is relaxed, or bright colors if the user is energetic.

[0536] 5. Sending the generated image data to the terminal

[0537] The server transmits the generated illustrations and images to the terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added to the generated image data.

[0538] 6. Viewing and downloading generated images

[0539] The terminal means displays the generated images received and notifies the user, who can then check the displayed images and download any images he or she likes to use in documents or on a website.

[0540] Specific examples

[0541] Case Study: Creating an Illustration Blog

[0542] User Sato wants to create an illustration to post on his blog. First, Sato draws a rough sketch on paper, then takes a photo of it using a dedicated smartphone app and presses the upload button. The app also includes a function to input emotional information in the form of simple questions, and Sato enters that he feels "relaxed."

[0543] The device sends rough sketch data and emotion data to the server. The server receives this data and uses generative AI to generate a cohesive illustration. Based on the information from the emotion engine, an illustration with a relaxed atmosphere and soft colors is generated. This generated illustration is sent from the server to Sato's smartphone and displayed in the app.

[0544] Sato chose her favorite illustration from the displayed list, downloaded it, and posted it on her blog. Thanks to this system, Sato was able to quickly and efficiently create a high-quality illustration that reflected her relaxed mood.

[0545] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate a variety of illustrations that reflect their emotions.

[0546] The processing flow will be explained below.

[0547] Step 1:

[0548] The user draws a rough sketch by hand. The user sketches out an idea or concept by hand on paper or a digital device.

[0549] Step 2:

[0550] The user uses a device (smartphone, tablet, PC, etc.) to take a rough sketch or select an existing image. The device displays the rough sketch selected by the user on a preview screen.

[0551] Step 3:

[0552] The user checks the rough sketch on the device's preview screen, makes corrections or retakes the photo as necessary, and when the user is satisfied, presses the upload button.

[0553] Step 4:

[0554] The device converts the selected rough sketch into the appropriate format (e.g., JPEG, PNG) and adds metadata (user ID, timestamp, etc.).

[0555] Step 5:

[0556] The terminal displays rough sketch data and an interface for inputting emotions to the user, who then inputs their current emotional state.

[0557] Step 6:

[0558] The device sends the rough sketch data and emotion data to the server using an HTTP POST request.

[0559] Step 7:

[0560] The server receives the HTTP POST request, receives the rough sketch data and emotion data, and saves them.

[0561] Step 8:

[0562] The server analyzes the received rough sketch data, checks the image resolution and format, and converts the rough sketch data into a format that can be used by the AI ​​generation method.

[0563] Step 9:

[0564] An emotion engine integrated in the server analyzes the received emotion data and recognizes the user's emotional state (e.g., relaxed, energetic, sad, etc.).

[0565] Step 10:

[0566] The server invokes the generative AI means (e.g., GAN, Transformer) and sets the necessary parameters. Based on input from the emotion engine, the parameters of the generative AI means are adjusted.

[0567] Step 11:

[0568] The server inputs the rough sketch data and emotional data into the generation AI means and begins generating the illustration.

[0569] Step 12:

[0570] The generative AI generates unified illustrations and images from rough sketch data, adjusting the style and color tone of the illustrations while taking into account the emotional data from the emotion engine.

[0571] Step 13:

[0572] If the generating AI generates illustrations in multiple styles or variations, it will generate different versions of the illustration.

[0573] Step 14:

[0574] The server saves the generated illustrations and records metadata such as the creation date and time, user ID, and emotional state.

[0575] Step 15:

[0576] The server compresses or encodes the generated illustration data and prepares it for transmission.

[0577] Step 16:

[0578] The server sends the generated illustration data to the terminal as an HTTP response.

[0579] Step 17:

[0580] The terminal displays the generated illustration data received from the server, and the user checks the multiple generated illustrations.

[0581] Step 18:

[0582] Users can select the generated illustration they like, press the download button, and save the image to their device. Users can use it in documents or on their website.

[0583] The above are the specific processing steps for generating a unified illustration from a hand-drawn rough sketch that reflects the user's emotions.

[0584] Example 2

[0585] 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."

[0586] Conventional rough sketch digitization systems simply convert handwritten rough sketches into digital data, making it difficult to generate illustrations that reflect the user's emotions. It is also difficult to create a sense of unity among the generated illustrations or to generate illustrations with multiple styles and variations. As a result, it has not been possible to efficiently generate diverse, high-quality illustrations that match the user's intentions.

[0587] 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.

[0588] In this invention, the server includes a generation AI means for analyzing rough sketch data and generating unified illustrations and images, an emotion recognition means for analyzing the user's emotions and reflecting them in the generated illustrations, and a data communication means, which enables the efficient generation of diverse, high-quality illustrations that reflect the user's emotions.

[0589] "Terminal means" refers to an electronic device that allows a user to upload handwritten rough sketches, and includes smartphones, tablets, PCs, etc.

[0590] The "computer means" is a device having a server or computer function for receiving and analyzing rough sketch data.

[0591] "Generative AI means" is a system that uses artificial intelligence technology to analyze rough sketch data and generate unified illustrations and images.

[0592] "Emotion recognition means" is a system that includes analytical techniques and algorithms for analyzing the user's emotions and reflecting them in the generated illustrations.

[0593] "Data communication means" refers to communication techniques and protocols for transmitting and receiving data between the computer means and the terminal means.

[0594] "Display means" refers to a display or software interface for displaying the transmitted generated image to the user and making it available for download.

[0595] "Rough sketch data" is a digital representation of a rough sketch hand-drawn by a user.

[0596] "Metadata" is additional information related to the generated image, including the date and time of generation, user ID, emotion recognition results, etc.

[0597] The present invention relates to a system for efficiently digitizing rough sketches hand-drawn by a user and generating a variety of illustrations with a consistent feel that reflect the user's emotions. Specific embodiments of this system are described below.

[0598] System Overview

[0599] This system includes terminal means for uploading rough drawings drawn by hand by the user, computer means for receiving the rough drawing data and generating images, generation AI means for generating unified illustrations and images, data communication means for transmitting the generated image data, display means for displaying and downloading the generated images, and emotion recognition means for recognizing the user's emotions.

[0600] Terminal means

[0601] A user launches a dedicated app or web app using a terminal means such as a smartphone, tablet, or PC. Using this terminal means, the user photographs a handwritten rough sketch or selects it using a file selection function. After that, the user checks the rough sketch on the preview screen, makes any necessary corrections, and then presses the send button to send the rough sketch data to the computer means.

[0602] computer means

[0603] The computer means includes a server and other computer devices. The computer means receives the rough sketch data sent from the terminal means and first stores it appropriately in storage. Then, it analyzes the resolution, format, size, etc. of the rough sketch data and converts it into a form suitable for the generating AI means. It also analyzes the user's emotions using the emotion recognition means.

[0604] Generation AI means

[0605] The AI ​​generation means generates unified illustrations with diverse styles and variations based on the received rough sketch data. It reflects the emotion recognition results of the emotion recognition means, generating illustrations with pale colors for a relaxed character, and bright colors for an energetic character.

[0606] Data communication means

[0607] The data communication means includes communication technologies and protocols for transmitting and receiving data between the computer means and the terminal means. The generated illustrations and images are sent to the terminal means along with metadata such as the generation date and time, user ID, and emotion recognition results.

[0608] Display means

[0609] The terminal means includes a display and a software interface for displaying the received generated images to the user and making them available for download, so that the user can check the displayed images and download and use the images they like.

[0610] Specific examples

[0611] Case Study: Creating an Illustration Blog

[0612] A user is thinking about creating an illustration to post on their blog. First, they draw a rough sketch by hand on paper, then use a dedicated smartphone app to take a photo of the rough sketch and press the upload button. The dedicated app also includes a function to input emotional information in the form of a simple question, and the user enters that they are feeling "relaxed."

[0613] The terminal transmits the rough sketch data and emotion data to the computing means. The computing means receives this data and uses the generation AI to generate a unified illustration. Based on the information from the emotion recognition means, an illustration with a relaxed atmosphere and soft colors is generated. This generated illustration is transmitted from the computing means to the user's smartphone and displayed on a dedicated app.

[0614] Users can select their favorite illustrations from the displayed list, download them, and post them to their blogs. In this way, users can quickly and efficiently create high-quality illustrations that reflect their emotions.

[0615] Prompt Sentence Examples

[0616] "Please turn the rough sketches that users have drawn by hand into digital illustrations with a relaxed atmosphere. Please design using soft colors."

[0617] Based on this prompt, the generative AI generates an illustration that reflects the user's emotions.

[0618] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate a variety of illustrations that reflect their emotions.

[0619] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0620] Step 1: User uploads rough sketch

[0621] The user launches a dedicated app or web app using a device such as a smartphone, tablet, or PC. The user then uses the camera or file selection function to take or select a handwritten rough sketch. After checking the rough sketch on the preview screen and making any necessary corrections, the user presses the send button. The data entered by the user at this time is rough sketch image data, which is sent from the device to the server.

[0622] Specific working example:

[0623] The user draws a rough sketch by hand on paper.

[0624] The user takes a rough sketch using the smartphone camera.

[0625] The user taps the "Upload" button on the dedicated app, checks the preview screen, and then presses the "Send" button.

[0626] Input: rough sketch image data

[0627] Output: Send image data to the server

[0628] Step 2: The server receives and analyzes the rough sketch data.

[0629] The server receives the rough sketch data sent from the device. The received data is first stored in the server's storage. The server then analyzes the image data's resolution, format, size, etc., and converts it into a format that can be used by the generation AI. This process performs preprocessing to provide the optimal data to the generation AI.

[0630] Specific working example:

[0631] The server saves the image file in a storage directory.

[0632] The server analyzes the image file's resolution, format, and size, and resizes or converts the format as needed.

[0633] Input: rough sketch image data

[0634] Output: Image data formatted for generative AI

[0635] Step 3: The server's emotion recognition means recognizes the emotion.

[0636] The emotion recognition means integrated into the server analyzes the rough sketches and other input data (e.g., text input, voice, facial expressions, etc.) uploaded by the user to recognize the user's emotions. The emotion engine uses facial expression analysis algorithms and text analysis algorithms to identify the user's emotional state. This recognition result is used as important input data for subsequent illustration generation.

[0637] Specific working example:

[0638] An emotion recognition means of the server analyzes the text comments related to the rough sketch.

[0639] The emotion recognition means of the server analyzes the voice data and identifies the emotion.

[0640] Input: rough sketch, text comments, audio data

[0641] Output: User emotion recognition results

[0642] Step 4: Server generation AI generates illustrations

[0643] The server's generation AI generates a consistent illustration based on the rough sketch data and the emotion recognition results. It reflects the emotion recognition results, generating an illustration with soft colors if the user is relaxed, or bright colors if the user is energetic. This process ensures that the generated illustration reflects the user's emotions.

[0644] Specific working example:

[0645] The server inputs rough sketch data and emotional data into the generation AI.

[0646] The generation AI generates illustrations according to prompts.

[0647] Input: rough sketch data, emotion recognition results

[0648] Output: Generated illustration data

[0649] Step 5: The server sends the generated image data to the terminal.

[0650] The server sends the generated illustrations and images to the terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added to the generated image data. This process allows the user to check the generated illustrations.

[0651] Specific working example:

[0652] The server adds metadata to the generated illustration.

[0653] The illustration data is transmitted to the terminal through the data communication means.

[0654] Input: Generated illustration data

[0655] Output: Illustration data sent to the device

[0656] Step 6: The device displays the generated image and makes it available for download

[0657] The device displays the generated images to the user and makes them available for download. A notification function lets the user know that new illustrations are available. The user can review the displayed images and download the ones they like for use in other materials or on other websites.

[0658] Specific working example:

[0659] The illustrations received by the device will be displayed on the app's gallery screen.

[0660] Use notifications to let users know when new illustrations are available.

[0661] The user selects the illustration they like and clicks the "Download" button.

[0662] Input: Illustration data sent from the server

[0663] Output: The illustration that is displayed to the user and available for download

[0664] (Application example 2)

[0665] 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."

[0666] Conventional systems struggle to efficiently generate consistent designs and styles when digitizing users' handwritten rough sketches. Furthermore, they are unable to generate illustrations that reflect the user's emotional state, making it difficult to create custom designs that satisfy the user. Furthermore, they lack the functionality to manage metadata for the generated illustrations, making subsequent editing and reuse cumbersome.

[0667] 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.

[0668] In this invention, the server includes a terminal means for users to upload handwritten rough sketches; a server means for receiving the rough sketch data sent from the terminal means and generating images; a generation AI means in the server means for analyzing the rough sketch data and generating unified illustrations and images; an emotion recognition means in the server means for adjusting the style and color tone of the generated images based on emotions; a data communication means for transmitting the generated image data from the server means to the terminal means; and a display means in the terminal means for displaying the transmitted generated images and making them available for download. This allows users to easily digitize handwritten rough sketches and generate illustrations that reflect their emotions. This not only enables the rapid creation of custom products with consistent designs, but also simplifies subsequent editing and reuse thanks to the metadata management function.

[0669] "User" means a person who uses the system to upload hand-drawn rough sketches and create digitized illustrations and product designs.

[0670] A "hand-drawn rough sketch" is an early sketch that a user draws on paper or a digital device.

[0671] "Terminal means" refers to a device such as a smartphone, tablet, or PC that a user uses to upload rough sketches.

[0672] "Server means" refers to a server that receives and analyzes rough sketch data and generates illustrations and images using generation AI.

[0673] "Generative AI means" refers to artificial intelligence that analyzes rough sketch data and generates unified illustrations and images.

[0674] The "emotion recognition means" is an engine that analyzes the user's emotional state and adjusts the style and color tone of the generated image.

[0675] The "data communication means" refers to a mechanism for transmitting the generated image data from the server means to the terminal means.

[0676] "Display means" refers to a device or software that has the function of displaying the generated image on a terminal and allowing the user to view and download the image.

[0677] "Metadata" is additional information related to the generated image, including the date and time of generation, user ID, emotion recognition results, etc.

[0678] The present invention relates to a system that digitizes rough sketches handwritten by a user and generates a variety of illustrations that reflect emotion and have a consistent feel. Specific embodiments of this system will be described below.

[0679] The server includes terminal means for users to upload handwritten rough drawings, server means for receiving the rough drawing data sent from the terminal means and generating images, generation AI means for analyzing the rough drawing data and generating unified illustrations and images, emotion recognition means for adjusting the style and color tone of the generated images based on emotions, data communication means for sending the image data generated from the server means to the terminal means, and display means for displaying the sent generated images and making them available for download.

[0680] Hardware and software used

[0681] Terminal means: A device such as a smartphone, tablet, or PC that a user uses to upload handwritten rough sketches.

[0682] Server method: A server running a high-performance CPU / GPU is used to receive and analyze rough sketch data.

[0683] Generative AI methods: Using generative models (e.g., GAN, VAE) trained using deep learning libraries such as TensorFlow or Keras.

[0684] Emotion recognizer: An engine or model for analyzing emotions (e.g., an emotion recognition model trained with TensorFlow or Keras).

[0685] Display: An application that allows the user to view and download the generated images on their device.

[0686] Data processing and calculation

[0687] 1. The user takes a picture of a rough sketch using a terminal and uploads it through a dedicated application. At the same time, the user inputs emotional information in the form of simple questions.

[0688] 2. The terminal means transmits the rough sketch data and emotion data to the server.

[0689] 3. The server analyzes the received rough sketch data and converts it into an appropriate resolution and format. The emotion recognition analyzes the emotion data and recognizes the user's current emotional state.

[0690] 4. The AI ​​generation method generates unified illustrations and product designs based on rough sketch data and emotion recognition results. Color tones and design patterns are adjusted based on the emotion recognition results.

[0691] 5. The generated image data is sent from the server to the device, along with metadata such as the generation date and time, user ID, and emotion recognition results.

[0692] 6. The terminal means displays the generated image, and the user checks the image, downloads it, and uses it.

[0693] Specific examples

[0694] If a user wants to design a custom T-shirt in the virtual store, they first sketch it on paper, then photograph it using a dedicated smartphone app and upload it. During this process, the user inputs their current emotion as "energetic." The server uses an emotion recognition engine to interpret the input emotion data, and the generation AI generates a brightly colored design that matches that emotion. The generated design is sent to the user's smartphone and displayed in the app. The user can then select their favorite design and download it, completing their custom T-shirt.

[0695] Example prompt sentence:

[0696] User: "I'm uploading a rough sketch I did on paper. I'm feeling energetic right now. I'd like to create a custom t-shirt design with a bright color scheme and a cohesive look."

[0697] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0698] Step 1:

[0699] The user prepares a rough sketch by hand and then photographs or scans it using a dedicated application on a device such as a smartphone, tablet, or PC. The user also inputs their current emotional state into the application, using prompts or simple questions. The input data consists of image data of the rough sketch and emotional data.

[0700] Step 2:

[0701] The terminal transmits rough sketch data and emotion data to the server. The transmitted data includes image data of the rough sketch and the user's emotion information. The data calculation in this step is the accurate transfer of image and emotion data. The terminal receives rough sketch data and emotion data as input and transmits them to the server as output.

[0702] Step 3:

[0703] The server receives the rough sketch data sent from the device. The received data includes rough sketch image data and emotion data. The server analyzes this data and converts the image resolution and format to an appropriate format. The input data is the rough sketch data, and the output data is the analyzed rough sketch data.

[0704] Step 4:

[0705] The server uses an emotion recognition means to analyze the user's emotion data. It uses an emotion recognition engine (e.g., a model trained with TensorFlow or Keras) to classify the user's current emotional state. The input data is the emotion data, and the output data is the recognized emotional state (e.g., energetic, relaxed, etc.).

[0706] Step 5:

[0707] The server uses a generative AI to generate illustrations and product designs based on the analyzed rough sketch data and emotion recognition results. The generative AI (e.g., a GAN or VAE model) adjusts color tones and design patterns based on the emotion recognition results. The input data are the rough sketch data and emotion recognition results, and the output data is the generated illustration or design.

[0708] Step 6:

[0709] The server transmits the generated illustrations and designs to the user's terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added. The input data is the generated illustrations and designs and metadata, and the output data is the transmitted illustrations and designs.

[0710] Step 7:

[0711] The terminal means displays the received generated image. The user checks the displayed image and downloads it if necessary. The input data is the received generated image, and the output data is the displayed and downloaded image.

[0712] In this way, specific actions, inputs, and outputs are clarified at each step, realizing the process of digitizing the user's rough handwritten sketch and generating a custom design that reflects their emotions.

[0713] 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.

[0714] 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.

[0715] 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.

[0716] [Third embodiment]

[0717] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0718] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0719] 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).

[0720] 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.

[0721] 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.

[0722] 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).

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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.

[0728] 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."

[0729] The present invention relates to a system that enables a user to efficiently digitize rough sketches drawn by hand and generate a variety of illustrations with a unified appearance. Specific embodiments of this system are described below.

[0730] System Overview

[0731] This system includes a terminal means for uploading rough drawings drawn by hand by the user, a server means for receiving rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, and a display means for displaying and downloading the generated images.

[0732] Program processing flow

[0733] 1. Upload a rough sketch

[0734] Users upload handwritten rough sketches using a dedicated app or web app on terminal means such as a smartphone, tablet, or PC. The terminal means has an image preview function, and after the user checks and corrects the rough sketch, they press the send button, which sends the rough sketch data to the server means.

[0735] 2. Receiving and analyzing rough sketch data

[0736] The server receives the rough sketch data sent from the terminal means. The server stores this data appropriately and analyzes the image resolution and format. Based on the analysis results, the server passes the rough sketch data to the generation AI means.

[0737] 3. Generating illustrations using generative AI

[0738] The server-integrated generative AI generates unified illustrations with various styles and variations based on the received rough sketch data. In this process, the generative AI uses, for example, generative adversarial networks (GANs) and transformation models.

[0739] 4. Sending the generated image data to the terminal

[0740] The server transmits the generated illustrations and images to the terminal means via data communication means. At this time, metadata such as the generation date and time and the user ID are also added to the generated image data.

[0741] 5. Viewing and downloading generated images

[0742] The terminal means displays the generated images received and notifies the user, who can then check the displayed images and download any images he or she likes to use in documents or on a website.

[0743] Specific examples

[0744] Case Study: Creating Presentation Materials

[0745] User Tanaka needs a friendly character illustration to insert into a presentation. He draws a rough sketch on paper, takes a photo of it using a dedicated app on his smartphone, and presses the upload button.

[0746] The device sends the rough sketch data to a server. The server receives the data, analyzes the rough sketch using a generation AI, and generates multiple character illustrations according to Tanaka's wishes. The generated illustrations are then sent from the server to Tanaka's smartphone and displayed in the app.

[0747] Tanaka could choose his favorite from the multiple illustrations displayed, download them, and insert them into his presentation materials. Thanks to this system, Tanaka was able to obtain high-quality character illustrations quickly and efficiently.

[0748] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate illustrations that meet a variety of needs.

[0749] The processing flow will be explained below.

[0750] Step 1:

[0751] The user draws a rough sketch by hand.

[0752] Step 2:

[0753] The user takes a rough sketch using a device (smartphone, tablet, PC, etc.) or selects an existing image.

[0754] Step 3:

[0755] The device displays the selected rough sketch on a preview screen, and the user presses the upload button.

[0756] Step 4:

[0757] The device converts the rough sketch data into an appropriate format (e.g., JPEG, PNG).

[0758] Step 5:

[0759] The device adds metadata (user ID, timestamp, etc.) to the rough sketch data.

[0760] Step 6:

[0761] The device sends the rough sketch data to the server via an HTTP POST request.

[0762] Step 7:

[0763] The server receives the HTTP POST request and receives the rough sketch data.

[0764] Step 8:

[0765] The server stores the rough sketch data in an appropriate storage system.

[0766] Step 9:

[0767] The server analyzes the rough sketch data it receives and converts it into a format that can be used by the generation AI.

[0768] Step 10:

[0769] The server invokes the generative AI method (e.g., GAN, Transformer) and sets the necessary parameters.

[0770] Step 11:

[0771] The server inputs the rough sketch data into the generation AI means and begins generating the illustration.

[0772] Step 12:

[0773] Generative AI generates unified illustrations and images from rough sketch data.

[0774] Step 13:

[0775] If the generating AI generates illustrations in multiple styles or variations, it will generate different versions of the illustration.

[0776] Step 14:

[0777] The server saves the generated illustrations and adds metadata.

[0778] Step 15:

[0779] The server compresses or encodes the generated illustrations and prepares them for data transmission.

[0780] Step 16:

[0781] The server sends the generated illustration data to the terminal as an HTTP response.

[0782] Step 17:

[0783] The terminal displays the generated illustration data received from the server.

[0784] Step 18:

[0785] The user can check the generated illustrations and download them if necessary.

[0786] Example 1

[0787] 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."

[0788] Currently, many users find it difficult to digitize rough sketches and then use them to create consistent illustrations or images. In particular, it is difficult to easily correct or check rough sketches during digitization, and the resulting illustrations often do not match the user's desired style or variation. Furthermore, managing the metadata associated with the resulting images is cumbersome. To address these issues, a system is needed that can efficiently digitize rough sketches, generate a wide variety of illustrations, and properly manage metadata.

[0789] 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.

[0790] In this invention, the server includes terminal means for users to upload handwritten rough drawings, server means for receiving rough drawing data sent from the terminal means and generating images, generation AI means for analyzing the rough drawing data and generating unified illustrations and images, data communication means for transmitting the generated image data from the server means to the terminal means, display means in the terminal means for displaying the transmitted generated images and making them available for download, and a function in the terminal means for previewing the rough drawings and for user correction, and a function for users to send the rough drawings after checking and correcting them. This enables users to easily digitize and correct their handwritten rough drawings and generate, display, and download a variety of illustrations.

[0791] "Terminal means" refers to an electronic device used by a user to upload handwritten rough sketches, and includes smartphones, tablets, PCs, etc.

[0792] The "server means" is a computer system that receives rough sketch data sent from the terminal means, analyzes and stores the data, and generates an image.

[0793] The "generative AI means" is an artificial intelligence model used by the server means to generate unified illustrations and images based on the received rough sketch data, and utilizes a generative adversarial network (GAN) or a transformation model.

[0794] "Data communication means" refers to the communication infrastructure and protocol for transmitting image data generated by the server means to the terminal means.

[0795] "Display Means" means a software function that displays the generated image transmitted by the Terminal Means and enables the user to confirm and download it.

[0796] The "preview function" is a function that allows the user to check and correct the rough sketch that he or she uploads on the terminal means.

[0797] The "correction function" is a function that allows the user to make corrections to the rough image during preview, and is installed in the terminal means.

[0798] "Rough sketch data" is data that digitally represents a rough sketch that a user has hand-drawn.

[0799] "Metadata" refers to accompanying information such as the date and time of generation and user ID that is added to the generated image data.

[0800] The present invention relates to a system that enables a user to efficiently digitize rough sketches drawn by hand and generate a variety of illustrations with a unified appearance. Specific embodiments of this system are described below.

[0801] The system includes a terminal means for users to upload rough drawings drawn by hand, a server means for receiving the rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, and a display means for displaying and downloading the generated images.

[0802] The user uploads rough sketches using a dedicated app or web app using a terminal means such as a smartphone, tablet, or PC. The terminal means is equipped with an image preview function and an editing function, and the user can check and edit the rough sketch and then press the send button, which sends the rough sketch data to the server means.

[0803] The server receives the rough sketch data sent from the terminal means, stores the data appropriately, analyzes the resolution and format of the received rough sketch data, and passes the analyzed metadata to the generation AI means.

[0804] The generative AI method uses generative adversarial networks (GANs) and transformation models to generate unified illustrations with diverse styles and variations based on the received rough sketch data. The generated illustration data is then returned to the server.

[0805] The server adds metadata such as the generation date and time and user ID to the illustration data returned by the generation AI and sends it to the user's terminal means via data communication means. The terminal means displays the generated illustration received from the server and notifies the user. The user can check the displayed illustration and download the image they like.

[0806] Specific examples are shown below.

[0807] Case Study: Creating Presentation Materials

[0808] User Sato needs a friendly character illustration to insert into a presentation. Sato draws a rough sketch on paper, photographs it using a dedicated smartphone app, and presses the upload button. The device sends the rough sketch data to the server. The server receives the data, analyzes the rough sketch using a generation AI, and generates multiple character illustrations that meet Sato's needs. The generated illustrations are sent from the server to Sato's smartphone and displayed in the app. Sato selects his favorite from the displayed illustrations, downloads them, and inserts them into his presentation. Thanks to this system, Sato was able to obtain high-quality character illustrations quickly and efficiently.

[0809] An example prompt is, "Create friendly character illustrations for presentations. Create illustrations in a variety of styles based on the rough sketches below."

[0810] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0811] Step 1: The user photographs or selects a rough sketch using a device and uploads it using a dedicated app or web app. The input is the rough sketch provided by the user on the device, and the output is the rough sketch displayed on the preview screen. Specifically, the user clicks the "Upload" button in the app, and then either photographs a rough sketch using the device's camera function or selects an existing image file. The user then checks and corrects the rough sketch on the preview screen and finally presses the "Send" button.

[0812] Step 2: The terminal means sends the rough sketch data sent by the user to the server. The input is the rough sketch data uploaded by the user to the terminal, and the output is the rough sketch data sent to the server. In concrete terms, when the user presses the "send" button, the terminal prepares the rough sketch data and sends the data to the server via a secure protocol.

[0813] Step 3: The server saves and analyzes the rough sketch data received from the terminal means. The input is the rough sketch data sent from the terminal, and the output is the analyzed metadata passed to the generation AI means. Specifically, the server saves the received data in a database and extracts and analyzes metadata such as resolution, file format, and size.

[0814] Step 4: The server passes the analyzed rough sketch data to a generation AI means, which generates a unified illustration with diverse styles and variations. The input is the analyzed rough sketch data, and the output is the generated illustration data. Specifically, the server inputs the analyzed data into the generation AI, which generates an illustration based on a generative adversarial network (GAN) or a transformation model.

[0815] Step 5: The server receives the illustration data returned from the generation AI, adds metadata, and sends it to the user's terminal. The input is the illustration data returned from the generation AI, and the output is the illustration data with the metadata added. Specifically, the server adds the generation date and time and user ID to the data and sends the illustration data to the user's terminal via a secure protocol.

[0816] Step 6: The terminal displays the received illustration data and notifies the user. The input is the illustration data sent from the server, and the output is the displayed illustration and the notified user. Specifically, the terminal analyzes the illustration data, notifies the user that a new illustration has been generated, and displays a preview of the generated illustration.

[0817] Step 7: The user checks the displayed illustrations and downloads the ones they like. The input is the illustration data displayed on the device, and the output is the illustration data downloaded by the user. Specifically, the user checks the illustrations on the device's display screen, presses the download button, and saves the desired illustration on the device.

[0818] (Application example 1)

[0819] 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."

[0820] The present invention relates to a system for efficiently digitizing handwritten rough sketches to generate high-quality, consistent illustrations. In particular, the objective is to provide a system that can quickly and easily generate illustrations for guidance and sales promotion in brick-and-mortar stores. Conventionally, store staff have had to spend a lot of time and effort creating illustrations, and the quality and consistency of the generated illustrations have been inconsistent.

[0821] 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.

[0822] In this invention, the server includes input means for users to upload handwritten rough drawings, central processing means for receiving the rough drawing data sent from the input means and generating images, automatic generation means in the central processing means for analyzing the rough drawing data and generating unified illustrations and images, data transmission means for transmitting the image data generated by the central processing means to the input means, and display means in the input means for displaying the generated images sent and making them available for download. This makes it possible to quickly digitize handwritten rough drawings into illustrations for physical store guides and promotional purposes and display them as illustrations for electronic displays and posters.

[0823] "Input means" refers to a device or interface that allows a user to upload a rough handwritten sketch.

[0824] The "central processing means" is a computer super or processor that receives the rough sketch data sent from the input means and executes image generation and data analysis.

[0825] The "automatic generation means" is an algorithm or AI model that analyzes rough sketch data in the central processing means and generates unified illustrations and images.

[0826] The "data transmission means" refers to a communication means, network cable, or wireless communication technology for transmitting image data generated by the central processing means to the input means.

[0827] The "display means" is a display or monitor that displays the generated image sent by the input means and allows the user to download it.

[0828] "Attribute data" refers to metadata and additional information associated with the generated image, including the date and time of generation, user ID, and the version of the AI ​​model used.

[0829] "For physical stores" refers to information and materials used in and around physical stores, including store directions, product introductions, and promotional displays.

[0830] The present invention provides a system that allows a user to efficiently digitize rough sketches drawn by hand and generate illustrations with a consistent look. Specific embodiments of this system are described below.

[0831] System Overview

[0832] The system includes the following components:

[0833] 1. Input method:

[0834] A device such as a smartphone, tablet, or PC for users to upload hand-drawn rough sketches.

[0835] The device has the ability to upload rough sketches via a dedicated app or web app.

[0836] 2. Central Processing Means:

[0837] A server that receives and analyzes rough sketch data. Typically, Google Cloud Functions or AWS Lambda is used.

[0838] The resolution and format of the rough sketch data are analyzed and passed on to the next step.

[0839] 3. Automatic generation means:

[0840] Image generation AI (e.g., GAN model) is used. The AI ​​model is built using Python's TensorFlow or PyTorch libraries.

[0841] Based on rough sketch data, a variety of illustrations with a unified look are generated.

[0842] 4. Means of data transmission:

[0843] The internet or a mobile network is used to transmit the generated image data from the central processing means to the input means.

[0844] When data is sent, it also includes metadata such as the date and time of generation and user ID.

[0845] 5. Display means:

[0846] The generated illustrations sent via the input means are displayed on a display that the user can check and download.

[0847] It can be used as an electronic display in a physical store or as a promotional poster.

[0848] How to use

[0849] For example, when promoting a new product in a brick-and-mortar store, store staff can upload hand-drawn rough sketches using a smartphone app. The rough sketch data sent from the device is received by the server, where it is analyzed and generated. The generated illustrations can then be instantly displayed on electronic displays or posters, allowing users to easily obtain high-quality promotional materials.

[0850] A concrete example is a promotional poster for a new product in a supermarket. Store staff use their smartphones to upload a rough sketch they have drawn by hand to a dedicated app. The rough sketch is then received by a server, which analyzes and generates it using generative AI to create a high-quality digital illustration. This illustration is then instantly sent to a smartphone and displayed on an electronic display for promotional purposes.

[0851] Example prompt sentence:

[0852] "Just take a photo of a rough sketch you've created to promote your new product, press the upload button, and we'll deliver a high-quality digital illustration to you within five minutes."

[0853] In this way, the present invention makes it possible to efficiently generate high-quality, consistent illustrations in physical stores and use them for promotions and guidance.

[0854] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0855] Step 1:

[0856] Users use an input method (smartphone, tablet, or PC) to upload handwritten rough sketches. Here, users take a photo of the rough sketch and upload the image data through a dedicated app or web app. Input: Handwritten rough sketch. Output: Base64 encoded rough sketch data.

[0857] Step 2:

[0858] The device sends the uploaded rough sketch data to the server. Here, the device has an image preview function, and the user can check the rough sketch and press the send button to send the data. Input: Base64 encoded rough sketch data. Output: Rough sketch data sent to the server.

[0859] Step 3:

[0860] The server receives the rough sketch data. The server stores the data appropriately and analyzes the image resolution and format. Input: Rough sketch data. Output: Analyzed image data.

[0861] Step 4:

[0862] The server passes the analyzed image data to an automatic generation method (generative AI model). The generative AI model generates unified illustrations with diverse styles and variations based on the received rough sketch data. Input: Analyzed image data. Output: Generated illustration data.

[0863] Step 5:

[0864] The server adds metadata such as the date and time of creation and the user ID to the generated illustration data and transmits it to the terminal via the data transmission means. Input: Generated illustration data. Output: Generated illustration data with metadata.

[0865] Step 6:

[0866] The device receives the generated illustration data sent from the server and notifies the user. The user can check the generated images in the app and download the illustrations they like. Input: Generated illustration data with metadata. Output: Displayed generated illustration, download link.

[0867] Step 7:

[0868] (Example) Store staff upload hand-drawn rough sketches using a dedicated smartphone app. The server receives the rough sketches and uses a generative AI model to generate a consistent illustration. The generated illustrations can be viewed instantly on the smartphone and, if necessary, displayed on electronic displays or promotional posters. This makes it possible to quickly provide high-quality promotional materials within the store.

[0869] 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.

[0870] The present invention relates to a system for efficiently digitizing a user's rough handwritten sketches and generating a variety of illustrations with a consistent feel that reflect the user's emotions. Specific embodiments of this system are described below.

[0871] System Overview

[0872] This system includes a terminal means for uploading rough drawings drawn by hand by the user, a server means for receiving the rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, a display means for displaying and downloading the generated images, and an emotion engine for recognizing the user's emotions.

[0873] Program processing flow

[0874] 1. Upload a rough sketch

[0875] Users upload handwritten rough sketches using a dedicated app or web app on terminal means such as a smartphone, tablet, or PC. The terminal means has an image preview function, and after the user checks and corrects the rough sketch, they press the send button, which sends the rough sketch data to the server means.

[0876] 2. Receiving and analyzing rough sketch data

[0877] The server receives the rough sketch data sent from the terminal means. The server stores this data appropriately and analyzes the image resolution and format. Based on the analysis results, the server passes the rough sketch data to the generation AI means.

[0878] 3. Emotion recognition using the emotion engine

[0879] The emotion engine integrated into the server recognizes the user's emotions by analyzing the rough sketches uploaded by the user and other input data (e.g., text input, voice, facial expressions, etc.). Based on the emotion recognition results, the user's current mood and emotional state are understood.

[0880] 4. Generating illustrations using generative AI

[0881] Based on the rough sketch data received by the generation AI means integrated into the server, it generates illustrations with a unified look and a variety of styles and variations. It reflects the emotion recognition results from the emotion engine and generates illustrations using soft colors if the user is relaxed, or bright colors if the user is energetic.

[0882] 5. Sending the generated image data to the terminal

[0883] The server transmits the generated illustrations and images to the terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added to the generated image data.

[0884] 6. Viewing and downloading generated images

[0885] The terminal means displays the generated images received and notifies the user, who can then check the displayed images and download any images he or she likes to use in documents or on a website.

[0886] Specific examples

[0887] Case Study: Creating an Illustration Blog

[0888] User Sato wants to create an illustration to post on his blog. First, Sato draws a rough sketch on paper, then takes a photo of it using a dedicated smartphone app and presses the upload button. The app also includes a function to input emotional information in the form of simple questions, and Sato enters that he feels "relaxed."

[0889] The device sends rough sketch data and emotion data to the server. The server receives this data and uses generative AI to generate a cohesive illustration. Based on the information from the emotion engine, an illustration with a relaxed atmosphere and soft colors is generated. This generated illustration is sent from the server to Sato's smartphone and displayed in the app.

[0890] Sato chose her favorite illustration from the displayed list, downloaded it, and posted it on her blog. Thanks to this system, Sato was able to quickly and efficiently create a high-quality illustration that reflected her relaxed mood.

[0891] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate a variety of illustrations that reflect their emotions.

[0892] The processing flow will be explained below.

[0893] Step 1:

[0894] The user draws a rough sketch by hand. The user sketches out an idea or concept by hand on paper or a digital device.

[0895] Step 2:

[0896] The user uses a device (smartphone, tablet, PC, etc.) to take a rough sketch or select an existing image. The device displays the rough sketch selected by the user on a preview screen.

[0897] Step 3:

[0898] The user checks the rough sketch on the device's preview screen, makes corrections or retakes the photo as necessary, and when the user is satisfied, presses the upload button.

[0899] Step 4:

[0900] The device converts the selected rough sketch into the appropriate format (e.g., JPEG, PNG) and adds metadata (user ID, timestamp, etc.).

[0901] Step 5:

[0902] The terminal displays rough sketch data and an interface for inputting emotions to the user, who then inputs their current emotional state.

[0903] Step 6:

[0904] The device sends the rough sketch data and emotion data to the server using an HTTP POST request.

[0905] Step 7:

[0906] The server receives the HTTP POST request, receives the rough sketch data and emotion data, and saves them.

[0907] Step 8:

[0908] The server analyzes the received rough sketch data, checks the image resolution and format, and converts the rough sketch data into a format that can be used by the AI ​​generation method.

[0909] Step 9:

[0910] An emotion engine integrated in the server analyzes the received emotion data and recognizes the user's emotional state (e.g., relaxed, energetic, sad, etc.).

[0911] Step 10:

[0912] The server invokes the generative AI means (e.g., GAN, Transformer) and sets the necessary parameters. Based on input from the emotion engine, the parameters of the generative AI means are adjusted.

[0913] Step 11:

[0914] The server inputs the rough sketch data and emotional data into the generation AI means and begins generating the illustration.

[0915] Step 12:

[0916] The generative AI generates unified illustrations and images from rough sketch data, adjusting the style and color tone of the illustrations while taking into account the emotional data from the emotion engine.

[0917] Step 13:

[0918] If the generating AI generates illustrations in multiple styles or variations, it will generate different versions of the illustration.

[0919] Step 14:

[0920] The server saves the generated illustrations and records metadata such as the creation date and time, user ID, and emotional state.

[0921] Step 15:

[0922] The server compresses or encodes the generated illustration data and prepares it for transmission.

[0923] Step 16:

[0924] The server sends the generated illustration data to the terminal as an HTTP response.

[0925] Step 17:

[0926] The terminal displays the generated illustration data received from the server, and the user checks the multiple generated illustrations.

[0927] Step 18:

[0928] Users can select the generated illustration they like, press the download button, and save the image to their device. Users can use it in documents or on their website.

[0929] The above are the specific processing steps for generating a unified illustration from a hand-drawn rough sketch that reflects the user's emotions.

[0930] Example 2

[0931] 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."

[0932] Conventional rough sketch digitization systems simply convert handwritten rough sketches into digital data, making it difficult to generate illustrations that reflect the user's emotions. It is also difficult to create a sense of unity among the generated illustrations or to generate illustrations with multiple styles and variations. As a result, it has not been possible to efficiently generate diverse, high-quality illustrations that match the user's intentions.

[0933] 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.

[0934] In this invention, the server includes a generation AI means for analyzing rough sketch data and generating unified illustrations and images, an emotion recognition means for analyzing the user's emotions and reflecting them in the generated illustrations, and a data communication means, which enables the efficient generation of diverse, high-quality illustrations that reflect the user's emotions.

[0935] "Terminal means" refers to an electronic device that allows a user to upload handwritten rough sketches, and includes smartphones, tablets, PCs, etc.

[0936] The "computer means" is a device having a server or computer function for receiving and analyzing rough sketch data.

[0937] "Generative AI means" is a system that uses artificial intelligence technology to analyze rough sketch data and generate unified illustrations and images.

[0938] "Emotion recognition means" is a system that includes analytical techniques and algorithms for analyzing the user's emotions and reflecting them in the generated illustrations.

[0939] "Data communication means" refers to communication techniques and protocols for transmitting and receiving data between the computer means and the terminal means.

[0940] "Display means" refers to a display or software interface for displaying the transmitted generated image to the user and making it available for download.

[0941] "Rough sketch data" is a digital representation of a rough sketch hand-drawn by a user.

[0942] "Metadata" is additional information related to the generated image, including the date and time of generation, user ID, emotion recognition results, etc.

[0943] The present invention relates to a system for efficiently digitizing rough sketches hand-drawn by a user and generating a variety of illustrations with a consistent feel that reflect the user's emotions. Specific embodiments of this system are described below.

[0944] System Overview

[0945] This system includes terminal means for uploading rough drawings drawn by hand by the user, computer means for receiving the rough drawing data and generating images, generation AI means for generating unified illustrations and images, data communication means for transmitting the generated image data, display means for displaying and downloading the generated images, and emotion recognition means for recognizing the user's emotions.

[0946] Terminal means

[0947] A user launches a dedicated app or web app using a terminal means such as a smartphone, tablet, or PC. Using this terminal means, the user photographs a handwritten rough sketch or selects it using a file selection function. After that, the user checks the rough sketch on the preview screen, makes any necessary corrections, and then presses the send button to send the rough sketch data to the computer means.

[0948] computer means

[0949] The computer means includes a server and other computer devices. The computer means receives the rough sketch data sent from the terminal means and first stores it appropriately in storage. Then, it analyzes the resolution, format, size, etc. of the rough sketch data and converts it into a form suitable for the generating AI means. It also analyzes the user's emotions using the emotion recognition means.

[0950] Generation AI means

[0951] The AI ​​generation means generates unified illustrations with diverse styles and variations based on the received rough sketch data. It reflects the emotion recognition results of the emotion recognition means, generating illustrations with pale colors for a relaxed character, and bright colors for an energetic character.

[0952] Data communication means

[0953] The data communication means includes communication technologies and protocols for transmitting and receiving data between the computer means and the terminal means. The generated illustrations and images are sent to the terminal means along with metadata such as the generation date and time, user ID, and emotion recognition results.

[0954] Display means

[0955] The terminal means includes a display and a software interface for displaying the received generated images to the user and making them available for download, so that the user can check the displayed images and download and use the images they like.

[0956] Specific examples

[0957] Case Study: Creating an Illustration Blog

[0958] A user is thinking about creating an illustration to post on their blog. First, they draw a rough sketch by hand on paper, then use a dedicated smartphone app to take a photo of the rough sketch and press the upload button. The dedicated app also includes a function to input emotional information in the form of a simple question, and the user enters that they are feeling "relaxed."

[0959] The terminal transmits the rough sketch data and emotion data to the computing means. The computing means receives this data and uses the generation AI to generate a unified illustration. Based on the information from the emotion recognition means, an illustration with a relaxed atmosphere and soft colors is generated. This generated illustration is transmitted from the computing means to the user's smartphone and displayed on a dedicated app.

[0960] Users can select their favorite illustrations from the displayed list, download them, and post them to their blogs. In this way, users can quickly and efficiently create high-quality illustrations that reflect their emotions.

[0961] Prompt Sentence Examples

[0962] "Please turn the rough sketches that users have drawn by hand into digital illustrations with a relaxed atmosphere. Please design using soft colors."

[0963] Based on this prompt, the generative AI generates an illustration that reflects the user's emotions.

[0964] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate a variety of illustrations that reflect their emotions.

[0965] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0966] Step 1: User uploads rough sketch

[0967] The user launches a dedicated app or web app using a device such as a smartphone, tablet, or PC. The user then uses the camera or file selection function to take or select a handwritten rough sketch. After checking the rough sketch on the preview screen and making any necessary corrections, the user presses the send button. The data entered by the user at this time is rough sketch image data, which is sent from the device to the server.

[0968] Specific working example:

[0969] The user draws a rough sketch by hand on paper.

[0970] The user takes a rough sketch using the smartphone camera.

[0971] The user taps the "Upload" button on the dedicated app, checks the preview screen, and then presses the "Send" button.

[0972] Input: rough sketch image data

[0973] Output: Send image data to the server

[0974] Step 2: The server receives and analyzes the rough sketch data.

[0975] The server receives the rough sketch data sent from the device. The received data is first stored in the server's storage. The server then analyzes the image data's resolution, format, size, etc., and converts it into a format that can be used by the generation AI. This process performs preprocessing to provide the optimal data to the generation AI.

[0976] Specific working example:

[0977] The server saves the image file in a storage directory.

[0978] The server analyzes the image file's resolution, format, and size, and resizes or converts the format as needed.

[0979] Input: rough sketch image data

[0980] Output: Image data formatted for generative AI

[0981] Step 3: The server's emotion recognition means recognizes the emotion.

[0982] The emotion recognition means integrated into the server analyzes the rough sketches and other input data (e.g., text input, voice, facial expressions, etc.) uploaded by the user to recognize the user's emotions. The emotion engine uses facial expression analysis algorithms and text analysis algorithms to identify the user's emotional state. This recognition result is used as important input data for subsequent illustration generation.

[0983] Specific working example:

[0984] An emotion recognition means of the server analyzes the text comments related to the rough sketch.

[0985] The emotion recognition means of the server analyzes the voice data and identifies the emotion.

[0986] Input: rough sketch, text comments, audio data

[0987] Output: User emotion recognition results

[0988] Step 4: Server generation AI generates illustrations

[0989] The server's generation AI generates a consistent illustration based on the rough sketch data and the emotion recognition results. It reflects the emotion recognition results, generating an illustration with soft colors if the user is relaxed, or bright colors if the user is energetic. This process ensures that the generated illustration reflects the user's emotions.

[0990] Specific working example:

[0991] The server inputs rough sketch data and emotional data into the generation AI.

[0992] The generation AI generates illustrations according to prompts.

[0993] Input: rough sketch data, emotion recognition results

[0994] Output: Generated illustration data

[0995] Step 5: The server sends the generated image data to the terminal.

[0996] The server sends the generated illustrations and images to the terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added to the generated image data. This process allows the user to check the generated illustrations.

[0997] Specific working example:

[0998] The server adds metadata to the generated illustration.

[0999] The illustration data is transmitted to the terminal through the data communication means.

[1000] Input: Generated illustration data

[1001] Output: Illustration data sent to the device

[1002] Step 6: The device displays the generated image and makes it available for download

[1003] The device displays the generated images to the user and makes them available for download. A notification function lets the user know that new illustrations are available. The user can review the displayed images and download the ones they like for use in other materials or on other websites.

[1004] Specific working example:

[1005] The illustrations received by the device will be displayed on the app's gallery screen.

[1006] Use notifications to let users know when new illustrations are available.

[1007] The user selects the illustration they like and clicks the "Download" button.

[1008] Input: Illustration data sent from the server

[1009] Output: The illustration that is displayed to the user and available for download

[1010] (Application example 2)

[1011] 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."

[1012] Conventional systems struggle to efficiently generate consistent designs and styles when digitizing users' handwritten rough sketches. Furthermore, they are unable to generate illustrations that reflect the user's emotional state, making it difficult to create custom designs that satisfy the user. Furthermore, they lack the functionality to manage metadata for the generated illustrations, making subsequent editing and reuse cumbersome.

[1013] 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.

[1014] In this invention, the server includes a terminal means for users to upload handwritten rough sketches; a server means for receiving the rough sketch data sent from the terminal means and generating images; a generation AI means in the server means for analyzing the rough sketch data and generating unified illustrations and images; an emotion recognition means in the server means for adjusting the style and color tone of the generated images based on emotions; a data communication means for transmitting the generated image data from the server means to the terminal means; and a display means in the terminal means for displaying the transmitted generated images and making them available for download. This allows users to easily digitize handwritten rough sketches and generate illustrations that reflect their emotions. This not only enables the rapid creation of custom products with consistent designs, but also simplifies subsequent editing and reuse thanks to the metadata management function.

[1015] "User" means a person who uses the system to upload hand-drawn rough sketches and create digitized illustrations and product designs.

[1016] A "hand-drawn rough sketch" is an early sketch that a user draws on paper or a digital device.

[1017] "Terminal means" refers to a device such as a smartphone, tablet, or PC that a user uses to upload rough sketches.

[1018] "Server means" refers to a server that receives and analyzes rough sketch data and generates illustrations and images using generation AI.

[1019] "Generative AI means" refers to artificial intelligence that analyzes rough sketch data and generates unified illustrations and images.

[1020] The "emotion recognition means" is an engine that analyzes the user's emotional state and adjusts the style and color tone of the generated image.

[1021] The "data communication means" refers to a mechanism for transmitting the generated image data from the server means to the terminal means.

[1022] "Display means" refers to a device or software that has the function of displaying the generated image on a terminal and allowing the user to view and download the image.

[1023] "Metadata" is additional information related to the generated image, including the date and time of generation, user ID, emotion recognition results, etc.

[1024] The present invention relates to a system that digitizes rough sketches handwritten by a user and generates a variety of illustrations that reflect emotion and have a consistent feel. Specific embodiments of this system will be described below.

[1025] The server includes terminal means for users to upload handwritten rough drawings, server means for receiving the rough drawing data sent from the terminal means and generating images, generation AI means for analyzing the rough drawing data and generating unified illustrations and images, emotion recognition means for adjusting the style and color tone of the generated images based on emotions, data communication means for sending the image data generated from the server means to the terminal means, and display means for displaying the sent generated images and making them available for download.

[1026] Hardware and software used

[1027] Terminal means: A device such as a smartphone, tablet, or PC that a user uses to upload handwritten rough sketches.

[1028] Server method: A server running a high-performance CPU / GPU is used to receive and analyze rough sketch data.

[1029] Generative AI methods: Using generative models (e.g., GAN, VAE) trained using deep learning libraries such as TensorFlow or Keras.

[1030] Emotion recognizer: An engine or model for analyzing emotions (e.g., an emotion recognition model trained with TensorFlow or Keras).

[1031] Display: An application that allows the user to view and download the generated images on their device.

[1032] Data processing and calculation

[1033] 1. The user takes a picture of a rough sketch using a terminal and uploads it through a dedicated application. At the same time, the user inputs emotional information in the form of simple questions.

[1034] 2. The terminal means transmits the rough sketch data and emotion data to the server.

[1035] 3. The server analyzes the received rough sketch data and converts it into an appropriate resolution and format. The emotion recognition analyzes the emotion data and recognizes the user's current emotional state.

[1036] 4. The AI ​​generation method generates unified illustrations and product designs based on rough sketch data and emotion recognition results. Color tones and design patterns are adjusted based on the emotion recognition results.

[1037] 5. The generated image data is sent from the server to the device, along with metadata such as the generation date and time, user ID, and emotion recognition results.

[1038] 6. The terminal means displays the generated image, and the user checks the image, downloads it, and uses it.

[1039] Specific examples

[1040] If a user wants to design a custom T-shirt in the virtual store, they first sketch it on paper, then photograph it using a dedicated smartphone app and upload it. During this process, the user inputs their current emotion as "energetic." The server uses an emotion recognition engine to interpret the input emotion data, and the generation AI generates a brightly colored design that matches that emotion. The generated design is sent to the user's smartphone and displayed in the app. The user can then select their favorite design and download it, completing their custom T-shirt.

[1041] Example prompt sentence:

[1042] User: "I'm uploading a rough sketch I did on paper. I'm feeling energetic right now. I'd like to create a custom t-shirt design with a bright color scheme and a cohesive look."

[1043] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1044] Step 1:

[1045] The user prepares a rough sketch by hand and then photographs or scans it using a dedicated application on a device such as a smartphone, tablet, or PC. The user also inputs their current emotional state into the application, using prompts or simple questions. The input data consists of image data of the rough sketch and emotional data.

[1046] Step 2:

[1047] The terminal transmits rough sketch data and emotion data to the server. The transmitted data includes image data of the rough sketch and the user's emotion information. The data calculation in this step is the accurate transfer of image and emotion data. The terminal receives rough sketch data and emotion data as input and transmits them to the server as output.

[1048] Step 3:

[1049] The server receives the rough sketch data sent from the device. The received data includes rough sketch image data and emotion data. The server analyzes this data and converts the image resolution and format to an appropriate format. The input data is the rough sketch data, and the output data is the analyzed rough sketch data.

[1050] Step 4:

[1051] The server uses an emotion recognition means to analyze the user's emotion data. It uses an emotion recognition engine (e.g., a model trained with TensorFlow or Keras) to classify the user's current emotional state. The input data is the emotion data, and the output data is the recognized emotional state (e.g., energetic, relaxed, etc.).

[1052] Step 5:

[1053] The server uses a generative AI to generate illustrations and product designs based on the analyzed rough sketch data and emotion recognition results. The generative AI (e.g., a GAN or VAE model) adjusts color tones and design patterns based on the emotion recognition results. The input data are the rough sketch data and emotion recognition results, and the output data is the generated illustration or design.

[1054] Step 6:

[1055] The server transmits the generated illustrations and designs to the user's terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added. The input data is the generated illustrations and designs and metadata, and the output data is the transmitted illustrations and designs.

[1056] Step 7:

[1057] The terminal means displays the received generated image. The user checks the displayed image and downloads it if necessary. The input data is the received generated image, and the output data is the displayed and downloaded image.

[1058] In this way, specific actions, inputs, and outputs are clarified at each step, realizing the process of digitizing the user's rough handwritten sketch and generating a custom design that reflects their emotions.

[1059] 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.

[1060] 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.

[1061] 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.

[1062] [Fourth embodiment]

[1063] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1064] 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.

[1065] 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).

[1066] 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.

[1067] 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.

[1068] 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).

[1069] 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.

[1070] 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.

[1071] 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.

[1072] 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.

[1073] 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.

[1074] 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.

[1075] 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."

[1076] The present invention relates to a system that enables a user to efficiently digitize rough sketches drawn by hand and generate a variety of illustrations with a unified appearance. Specific embodiments of this system are described below.

[1077] System Overview

[1078] This system includes a terminal means for uploading rough drawings drawn by hand by the user, a server means for receiving rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, and a display means for displaying and downloading the generated images.

[1079] Program processing flow

[1080] 1. Upload a rough sketch

[1081] Users upload handwritten rough sketches using a dedicated app or web app on terminal means such as a smartphone, tablet, or PC. The terminal means has an image preview function, and after the user checks and corrects the rough sketch, they press the send button, which sends the rough sketch data to the server means.

[1082] 2. Receiving and analyzing rough sketch data

[1083] The server receives the rough sketch data sent from the terminal means. The server stores this data appropriately and analyzes the image resolution and format. Based on the analysis results, the server passes the rough sketch data to the generation AI means.

[1084] 3. Generating illustrations using generative AI

[1085] The server-integrated generative AI generates unified illustrations with various styles and variations based on the received rough sketch data. In this process, the generative AI uses, for example, generative adversarial networks (GANs) and transformation models.

[1086] 4. Sending the generated image data to the terminal

[1087] The server transmits the generated illustrations and images to the terminal means via data communication means. At this time, metadata such as the generation date and time and the user ID are also added to the generated image data.

[1088] 5. Viewing and downloading generated images

[1089] The terminal means displays the generated images received and notifies the user, who can then check the displayed images and download any images he or she likes to use in documents or on a website.

[1090] Specific examples

[1091] Case Study: Creating Presentation Materials

[1092] User Tanaka needs a friendly character illustration to insert into a presentation. He draws a rough sketch on paper, takes a photo of it using a dedicated app on his smartphone, and presses the upload button.

[1093] The device sends the rough sketch data to a server. The server receives the data, analyzes the rough sketch using a generation AI, and generates multiple character illustrations according to Tanaka's wishes. The generated illustrations are then sent from the server to Tanaka's smartphone and displayed in the app.

[1094] Tanaka could choose his favorite from the multiple illustrations displayed, download them, and insert them into his presentation materials. Thanks to this system, Tanaka was able to obtain high-quality character illustrations quickly and efficiently.

[1095] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate illustrations that meet a variety of needs.

[1096] The processing flow will be explained below.

[1097] Step 1:

[1098] The user draws a rough sketch by hand.

[1099] Step 2:

[1100] The user takes a rough sketch using a device (smartphone, tablet, PC, etc.) or selects an existing image.

[1101] Step 3:

[1102] The device displays the selected rough sketch on a preview screen, and the user presses the upload button.

[1103] Step 4:

[1104] The device converts the rough sketch data into an appropriate format (e.g., JPEG, PNG).

[1105] Step 5:

[1106] The device adds metadata (user ID, timestamp, etc.) to the rough sketch data.

[1107] Step 6:

[1108] The device sends the rough sketch data to the server via an HTTP POST request.

[1109] Step 7:

[1110] The server receives the HTTP POST request and receives the rough sketch data.

[1111] Step 8:

[1112] The server stores the rough sketch data in an appropriate storage system.

[1113] Step 9:

[1114] The server analyzes the rough sketch data it receives and converts it into a format that can be used by the generation AI.

[1115] Step 10:

[1116] The server invokes the generative AI method (e.g., GAN, Transformer) and sets the necessary parameters.

[1117] Step 11:

[1118] The server inputs the rough sketch data into the generation AI means and begins generating the illustration.

[1119] Step 12:

[1120] Generative AI generates unified illustrations and images from rough sketch data.

[1121] Step 13:

[1122] If the generating AI generates illustrations in multiple styles or variations, it will generate different versions of the illustration.

[1123] Step 14:

[1124] The server saves the generated illustrations and adds metadata.

[1125] Step 15:

[1126] The server compresses or encodes the generated illustrations and prepares them for data transmission.

[1127] Step 16:

[1128] The server sends the generated illustration data to the terminal as an HTTP response.

[1129] Step 17:

[1130] The terminal displays the generated illustration data received from the server.

[1131] Step 18:

[1132] The user can check the generated illustrations and download them if necessary.

[1133] Example 1

[1134] 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."

[1135] Currently, many users find it difficult to digitize rough sketches and then use them to create consistent illustrations or images. In particular, it is difficult to easily correct or check rough sketches during digitization, and the resulting illustrations often do not match the user's desired style or variation. Furthermore, managing the metadata associated with the resulting images is cumbersome. To address these issues, a system is needed that can efficiently digitize rough sketches, generate a wide variety of illustrations, and properly manage metadata.

[1136] 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.

[1137] In this invention, the server includes terminal means for users to upload handwritten rough drawings, server means for receiving rough drawing data sent from the terminal means and generating images, generation AI means for analyzing the rough drawing data and generating unified illustrations and images, data communication means for transmitting the generated image data from the server means to the terminal means, display means in the terminal means for displaying the transmitted generated images and making them available for download, and a function in the terminal means for previewing the rough drawings and for user correction, and a function for users to send the rough drawings after checking and correcting them. This enables users to easily digitize and correct their handwritten rough drawings and generate, display, and download a variety of illustrations.

[1138] "Terminal means" refers to an electronic device used by a user to upload handwritten rough sketches, and includes smartphones, tablets, PCs, etc.

[1139] The "server means" is a computer system that receives rough sketch data sent from the terminal means, analyzes and stores the data, and generates an image.

[1140] The "generative AI means" is an artificial intelligence model used by the server means to generate unified illustrations and images based on the received rough sketch data, and utilizes a generative adversarial network (GAN) or a transformation model.

[1141] "Data communication means" refers to the communication infrastructure and protocol for transmitting image data generated by the server means to the terminal means.

[1142] "Display Means" means a software function that displays the generated image transmitted by the Terminal Means and enables the user to confirm and download it.

[1143] The "preview function" is a function that allows the user to check and correct the rough sketch that he or she uploads on the terminal means.

[1144] The "correction function" is a function that allows the user to make corrections to the rough image during preview, and is installed in the terminal means.

[1145] "Rough sketch data" is data that digitally represents a rough sketch that a user has hand-drawn.

[1146] "Metadata" refers to accompanying information such as the date and time of generation and user ID that is added to the generated image data.

[1147] The present invention relates to a system that enables a user to efficiently digitize rough sketches drawn by hand and generate a variety of illustrations with a unified appearance. Specific embodiments of this system are described below.

[1148] The system includes a terminal means for users to upload rough drawings drawn by hand, a server means for receiving the rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, and a display means for displaying and downloading the generated images.

[1149] The user uploads rough sketches using a dedicated app or web app using a terminal means such as a smartphone, tablet, or PC. The terminal means is equipped with an image preview function and an editing function, and the user can check and edit the rough sketch and then press the send button, which sends the rough sketch data to the server means.

[1150] The server receives the rough sketch data sent from the terminal means, stores the data appropriately, analyzes the resolution and format of the received rough sketch data, and passes the analyzed metadata to the generation AI means.

[1151] The generative AI method uses generative adversarial networks (GANs) and transformation models to generate unified illustrations with diverse styles and variations based on the received rough sketch data. The generated illustration data is then returned to the server.

[1152] The server adds metadata such as the generation date and time and user ID to the illustration data returned by the generation AI and sends it to the user's terminal means via data communication means. The terminal means displays the generated illustration received from the server and notifies the user. The user can check the displayed illustration and download the image they like.

[1153] Specific examples are shown below.

[1154] Case Study: Creating Presentation Materials

[1155] User Sato needs a friendly character illustration to insert into a presentation. Sato draws a rough sketch on paper, photographs it using a dedicated smartphone app, and presses the upload button. The device sends the rough sketch data to the server. The server receives the data, analyzes the rough sketch using a generation AI, and generates multiple character illustrations that meet Sato's needs. The generated illustrations are sent from the server to Sato's smartphone and displayed in the app. Sato selects his favorite from the displayed illustrations, downloads them, and inserts them into his presentation. Thanks to this system, Sato was able to obtain high-quality character illustrations quickly and efficiently.

[1156] An example prompt is, "Create friendly character illustrations for presentations. Create illustrations in a variety of styles based on the rough sketches below."

[1157] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1158] Step 1: The user photographs or selects a rough sketch using a device and uploads it using a dedicated app or web app. The input is the rough sketch provided by the user on the device, and the output is the rough sketch displayed on the preview screen. Specifically, the user clicks the "Upload" button in the app, and then either photographs a rough sketch using the device's camera function or selects an existing image file. The user then checks and corrects the rough sketch on the preview screen and finally presses the "Send" button.

[1159] Step 2: The terminal means sends the rough sketch data sent by the user to the server. The input is the rough sketch data uploaded by the user to the terminal, and the output is the rough sketch data sent to the server. In concrete terms, when the user presses the "send" button, the terminal prepares the rough sketch data and sends the data to the server via a secure protocol.

[1160] Step 3: The server saves and analyzes the rough sketch data received from the terminal means. The input is the rough sketch data sent from the terminal, and the output is the analyzed metadata passed to the generation AI means. Specifically, the server saves the received data in a database and extracts and analyzes metadata such as resolution, file format, and size.

[1161] Step 4: The server passes the analyzed rough sketch data to a generation AI means, which generates a unified illustration with diverse styles and variations. The input is the analyzed rough sketch data, and the output is the generated illustration data. Specifically, the server inputs the analyzed data into the generation AI, which generates an illustration based on a generative adversarial network (GAN) or a transformation model.

[1162] Step 5: The server receives the illustration data returned from the generation AI, adds metadata, and sends it to the user's terminal. The input is the illustration data returned from the generation AI, and the output is the illustration data with the metadata added. Specifically, the server adds the generation date and time and user ID to the data and sends the illustration data to the user's terminal via a secure protocol.

[1163] Step 6: The terminal displays the received illustration data and notifies the user. The input is the illustration data sent from the server, and the output is the displayed illustration and the notified user. Specifically, the terminal analyzes the illustration data, notifies the user that a new illustration has been generated, and displays a preview of the generated illustration.

[1164] Step 7: The user checks the displayed illustrations and downloads the ones they like. The input is the illustration data displayed on the device, and the output is the illustration data downloaded by the user. Specifically, the user checks the illustrations on the device's display screen, presses the download button, and saves the desired illustration on the device.

[1165] (Application example 1)

[1166] 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."

[1167] The present invention relates to a system for efficiently digitizing handwritten rough sketches to generate high-quality, consistent illustrations. In particular, the objective is to provide a system that can quickly and easily generate illustrations for guidance and sales promotion in brick-and-mortar stores. Conventionally, store staff have had to spend a lot of time and effort creating illustrations, and the quality and consistency of the generated illustrations have been inconsistent.

[1168] 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.

[1169] In this invention, the server includes input means for users to upload handwritten rough drawings, central processing means for receiving the rough drawing data sent from the input means and generating images, automatic generation means in the central processing means for analyzing the rough drawing data and generating unified illustrations and images, data transmission means for transmitting the image data generated by the central processing means to the input means, and display means in the input means for displaying the generated images sent and making them available for download. This makes it possible to quickly digitize handwritten rough drawings into illustrations for physical store guides and promotional purposes and display them as illustrations for electronic displays and posters.

[1170] "Input means" refers to a device or interface that allows a user to upload a rough handwritten sketch.

[1171] The "central processing means" is a computer super or processor that receives the rough sketch data sent from the input means and executes image generation and data analysis.

[1172] The "automatic generation means" is an algorithm or AI model that analyzes rough sketch data in the central processing means and generates unified illustrations and images.

[1173] The "data transmission means" refers to a communication means, network cable, or wireless communication technology for transmitting image data generated by the central processing means to the input means.

[1174] The "display means" is a display or monitor that displays the generated image sent by the input means and allows the user to download it.

[1175] "Attribute data" refers to metadata and additional information associated with the generated image, including the date and time of generation, user ID, and the version of the AI ​​model used.

[1176] "For physical stores" refers to information and materials used in and around physical stores, including store directions, product introductions, and promotional displays.

[1177] The present invention provides a system that allows a user to efficiently digitize rough sketches drawn by hand and generate illustrations with a consistent look. Specific embodiments of this system are described below.

[1178] System Overview

[1179] The system includes the following components:

[1180] 1. Input method:

[1181] A device such as a smartphone, tablet, or PC for users to upload hand-drawn rough sketches.

[1182] The device has the ability to upload rough sketches via a dedicated app or web app.

[1183] 2. Central Processing Means:

[1184] A server that receives and analyzes rough sketch data. Typically, Google Cloud Functions or AWS Lambda is used.

[1185] The resolution and format of the rough sketch data are analyzed and passed on to the next step.

[1186] 3. Automatic generation means:

[1187] Image generation AI (e.g., GAN model) is used. The AI ​​model is built using Python's TensorFlow or PyTorch libraries.

[1188] Based on rough sketch data, a variety of illustrations with a unified look are generated.

[1189] 4. Means of data transmission:

[1190] The internet or a mobile network is used to transmit the generated image data from the central processing means to the input means.

[1191] When data is sent, it also includes metadata such as the date and time of generation and user ID.

[1192] 5. Display means:

[1193] The generated illustrations sent via the input means are displayed on a display that the user can check and download.

[1194] It can be used as an electronic display in a physical store or as a promotional poster.

[1195] How to use

[1196] For example, when promoting a new product in a brick-and-mortar store, store staff can upload hand-drawn rough sketches using a smartphone app. The rough sketch data sent from the device is received by the server, where it is analyzed and generated. The generated illustrations can then be instantly displayed on electronic displays or posters, allowing users to easily obtain high-quality promotional materials.

[1197] A concrete example is a promotional poster for a new product in a supermarket. Store staff use their smartphones to upload a rough sketch they have drawn by hand to a dedicated app. The rough sketch is then received by a server, which analyzes and generates it using generative AI to create a high-quality digital illustration. This illustration is then instantly sent to a smartphone and displayed on an electronic display for promotional purposes.

[1198] Example prompt sentence:

[1199] "Just take a photo of a rough sketch you've created to promote your new product, press the upload button, and we'll deliver a high-quality digital illustration to you within five minutes."

[1200] In this way, the present invention makes it possible to efficiently generate high-quality, consistent illustrations in physical stores and use them for promotions and guidance.

[1201] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1202] Step 1:

[1203] Users use an input method (smartphone, tablet, or PC) to upload handwritten rough sketches. Here, users take a photo of the rough sketch and upload the image data through a dedicated app or web app. Input: Handwritten rough sketch. Output: Base64 encoded rough sketch data.

[1204] Step 2:

[1205] The device sends the uploaded rough sketch data to the server. Here, the device has an image preview function, and the user can check the rough sketch and press the send button to send the data. Input: Base64 encoded rough sketch data. Output: Rough sketch data sent to the server.

[1206] Step 3:

[1207] The server receives the rough sketch data. The server stores the data appropriately and analyzes the image resolution and format. Input: Rough sketch data. Output: Analyzed image data.

[1208] Step 4:

[1209] The server passes the analyzed image data to an automatic generation method (generative AI model). The generative AI model generates unified illustrations with diverse styles and variations based on the received rough sketch data. Input: Analyzed image data. Output: Generated illustration data.

[1210] Step 5:

[1211] The server adds metadata such as the date and time of creation and the user ID to the generated illustration data and transmits it to the terminal via the data transmission means. Input: Generated illustration data. Output: Generated illustration data with metadata.

[1212] Step 6:

[1213] The device receives the generated illustration data sent from the server and notifies the user. The user can check the generated images in the app and download the illustrations they like. Input: Generated illustration data with metadata. Output: Displayed generated illustration, download link.

[1214] Step 7:

[1215] (Example) Store staff upload hand-drawn rough sketches using a dedicated smartphone app. The server receives the rough sketches and uses a generative AI model to generate a consistent illustration. The generated illustrations can be viewed instantly on the smartphone and, if necessary, displayed on electronic displays or promotional posters. This makes it possible to quickly provide high-quality promotional materials within the store.

[1216] 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.

[1217] The present invention relates to a system for efficiently digitizing a user's rough handwritten sketches and generating a variety of illustrations with a consistent feel that reflect the user's emotions. Specific embodiments of this system are described below.

[1218] System Overview

[1219] This system includes a terminal means for uploading rough drawings drawn by hand by the user, a server means for receiving the rough drawing data and generating images, a generation AI means for generating unified illustrations and images, a data communication means for transmitting the generated image data, a display means for displaying and downloading the generated images, and an emotion engine for recognizing the user's emotions.

[1220] Program processing flow

[1221] 1. Upload a rough sketch

[1222] Users upload handwritten rough sketches using a dedicated app or web app on terminal means such as a smartphone, tablet, or PC. The terminal means has an image preview function, and after the user checks and corrects the rough sketch, they press the send button, which sends the rough sketch data to the server means.

[1223] 2. Receiving and analyzing rough sketch data

[1224] The server receives the rough sketch data sent from the terminal means. The server stores this data appropriately and analyzes the image resolution and format. Based on the analysis results, the server passes the rough sketch data to the generation AI means.

[1225] 3. Emotion recognition using the emotion engine

[1226] The emotion engine integrated into the server recognizes the user's emotions by analyzing the rough sketches uploaded by the user and other input data (e.g., text input, voice, facial expressions, etc.). Based on the emotion recognition results, the user's current mood and emotional state are understood.

[1227] 4. Generating illustrations using generative AI

[1228] Based on the rough sketch data received by the generation AI means integrated into the server, it generates illustrations with a unified look and a variety of styles and variations. It reflects the emotion recognition results from the emotion engine and generates illustrations using soft colors if the user is relaxed, or bright colors if the user is energetic.

[1229] 5. Sending the generated image data to the terminal

[1230] The server transmits the generated illustrations and images to the terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added to the generated image data.

[1231] 6. Viewing and downloading generated images

[1232] The terminal means displays the generated images received and notifies the user, who can then check the displayed images and download any images he or she likes to use in documents or on a website.

[1233] Specific examples

[1234] Case Study: Creating an Illustration Blog

[1235] User Sato wants to create an illustration to post on his blog. First, Sato draws a rough sketch on paper, then takes a photo of it using a dedicated smartphone app and presses the upload button. The app also includes a function to input emotional information in the form of simple questions, and Sato enters that he feels "relaxed."

[1236] The device sends rough sketch data and emotion data to the server. The server receives this data and uses generative AI to generate a cohesive illustration. Based on the information from the emotion engine, an illustration with a relaxed atmosphere and soft colors is generated. This generated illustration is sent from the server to Sato's smartphone and displayed in the app.

[1237] Sato chose her favorite illustration from the displayed list, downloaded it, and posted it on her blog. Thanks to this system, Sato was able to quickly and efficiently create a high-quality illustration that reflected her relaxed mood.

[1238] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate a variety of illustrations that reflect their emotions.

[1239] The processing flow will be explained below.

[1240] Step 1:

[1241] The user draws a rough sketch by hand. The user sketches out an idea or concept by hand on paper or a digital device.

[1242] Step 2:

[1243] The user uses a device (smartphone, tablet, PC, etc.) to take a rough sketch or select an existing image. The device displays the rough sketch selected by the user on a preview screen.

[1244] Step 3:

[1245] The user checks the rough sketch on the device's preview screen, makes corrections or retakes the photo as necessary, and when the user is satisfied, presses the upload button.

[1246] Step 4:

[1247] The device converts the selected rough sketch into the appropriate format (e.g., JPEG, PNG) and adds metadata (user ID, timestamp, etc.).

[1248] Step 5:

[1249] The terminal displays rough sketch data and an interface for inputting emotions to the user, who then inputs their current emotional state.

[1250] Step 6:

[1251] The device sends the rough sketch data and emotion data to the server using an HTTP POST request.

[1252] Step 7:

[1253] The server receives the HTTP POST request, receives the rough sketch data and emotion data, and saves them.

[1254] Step 8:

[1255] The server analyzes the received rough sketch data, checks the image resolution and format, and converts the rough sketch data into a format that can be used by the AI ​​generation method.

[1256] Step 9:

[1257] An emotion engine integrated in the server analyzes the received emotion data and recognizes the user's emotional state (e.g., relaxed, energetic, sad, etc.).

[1258] Step 10:

[1259] The server invokes the generative AI means (e.g., GAN, Transformer) and sets the necessary parameters. Based on input from the emotion engine, the parameters of the generative AI means are adjusted.

[1260] Step 11:

[1261] The server inputs the rough sketch data and emotional data into the generation AI means and begins generating the illustration.

[1262] Step 12:

[1263] The generative AI generates unified illustrations and images from rough sketch data, adjusting the style and color tone of the illustrations while taking into account the emotional data from the emotion engine.

[1264] Step 13:

[1265] If the generating AI generates illustrations in multiple styles or variations, it will generate different versions of the illustration.

[1266] Step 14:

[1267] The server saves the generated illustrations and records metadata such as the creation date and time, user ID, and emotional state.

[1268] Step 15:

[1269] The server compresses or encodes the generated illustration data and prepares it for transmission.

[1270] Step 16:

[1271] The server sends the generated illustration data to the terminal as an HTTP response.

[1272] Step 17:

[1273] The terminal displays the generated illustration data received from the server, and the user checks the multiple generated illustrations.

[1274] Step 18:

[1275] Users can select the generated illustration they like, press the download button, and save the image to their device. Users can use it in documents or on their website.

[1276] The above are the specific processing steps for generating a unified illustration from a hand-drawn rough sketch that reflects the user's emotions.

[1277] Example 2

[1278] 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."

[1279] Conventional rough sketch digitization systems simply convert handwritten rough sketches into digital data, making it difficult to generate illustrations that reflect the user's emotions. It is also difficult to create a sense of unity among the generated illustrations or to generate illustrations with multiple styles and variations. As a result, it has not been possible to efficiently generate diverse, high-quality illustrations that match the user's intentions.

[1280] 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.

[1281] In this invention, the server includes a generation AI means for analyzing rough sketch data and generating unified illustrations and images, an emotion recognition means for analyzing the user's emotions and reflecting them in the generated illustrations, and a data communication means, which enables the efficient generation of diverse, high-quality illustrations that reflect the user's emotions.

[1282] "Terminal means" refers to an electronic device that allows a user to upload handwritten rough sketches, and includes smartphones, tablets, PCs, etc.

[1283] The "computer means" is a device having a server or computer function for receiving and analyzing rough sketch data.

[1284] "Generative AI means" is a system that uses artificial intelligence technology to analyze rough sketch data and generate unified illustrations and images.

[1285] "Emotion recognition means" is a system that includes analytical techniques and algorithms for analyzing the user's emotions and reflecting them in the generated illustrations.

[1286] "Data communication means" refers to communication techniques and protocols for transmitting and receiving data between the computer means and the terminal means.

[1287] "Display means" refers to a display or software interface for displaying the transmitted generated image to the user and making it available for download.

[1288] "Rough sketch data" is a digital representation of a rough sketch hand-drawn by a user.

[1289] "Metadata" is additional information related to the generated image, including the date and time of generation, user ID, emotion recognition results, etc.

[1290] The present invention relates to a system for efficiently digitizing rough sketches hand-drawn by a user and generating a variety of illustrations with a consistent feel that reflect the user's emotions. Specific embodiments of this system are described below.

[1291] System Overview

[1292] This system includes terminal means for uploading rough drawings drawn by hand by the user, computer means for receiving the rough drawing data and generating images, generation AI means for generating unified illustrations and images, data communication means for transmitting the generated image data, display means for displaying and downloading the generated images, and emotion recognition means for recognizing the user's emotions.

[1293] Terminal means

[1294] A user launches a dedicated app or web app using a terminal means such as a smartphone, tablet, or PC. Using this terminal means, the user photographs a handwritten rough sketch or selects it using a file selection function. After that, the user checks the rough sketch on the preview screen, makes any necessary corrections, and then presses the send button to send the rough sketch data to the computer means.

[1295] computer means

[1296] The computer means includes a server and other computer devices. The computer means receives the rough sketch data sent from the terminal means and first stores it appropriately in storage. Then, it analyzes the resolution, format, size, etc. of the rough sketch data and converts it into a form suitable for the generating AI means. It also analyzes the user's emotions using the emotion recognition means.

[1297] Generation AI means

[1298] The AI ​​generation means generates unified illustrations with diverse styles and variations based on the received rough sketch data. It reflects the emotion recognition results of the emotion recognition means, generating illustrations with pale colors for a relaxed character, and bright colors for an energetic character.

[1299] Data communication means

[1300] The data communication means includes communication technologies and protocols for transmitting and receiving data between the computer means and the terminal means. The generated illustrations and images are sent to the terminal means along with metadata such as the generation date and time, user ID, and emotion recognition results.

[1301] Display means

[1302] The terminal means includes a display and a software interface for displaying the received generated images to the user and making them available for download, so that the user can check the displayed images and download and use the images they like.

[1303] Specific examples

[1304] Case Study: Creating an Illustration Blog

[1305] A user is thinking about creating an illustration to post on their blog. First, they draw a rough sketch by hand on paper, then use a dedicated smartphone app to take a photo of the rough sketch and press the upload button. The dedicated app also includes a function to input emotional information in the form of a simple question, and the user enters that they are feeling "relaxed."

[1306] The terminal transmits the rough sketch data and emotion data to the computing means. The computing means receives this data and uses the generation AI to generate a unified illustration. Based on the information from the emotion recognition means, an illustration with a relaxed atmosphere and soft colors is generated. This generated illustration is transmitted from the computing means to the user's smartphone and displayed on a dedicated app.

[1307] Users can select their favorite illustrations from the displayed list, download them, and post them to their blogs. In this way, users can quickly and efficiently create high-quality illustrations that reflect their emotions.

[1308] Prompt Sentence Examples

[1309] "Please turn the rough sketches that users have drawn by hand into digital illustrations with a relaxed atmosphere. Please design using soft colors."

[1310] Based on this prompt, the generative AI generates an illustration that reflects the user's emotions.

[1311] In this way, the present invention provides a means for users to efficiently digitize rough handwritten drawings and generate a variety of illustrations that reflect their emotions.

[1312] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1313] Step 1: User uploads rough sketch

[1314] The user launches a dedicated app or web app using a device such as a smartphone, tablet, or PC. The user then uses the camera or file selection function to take or select a handwritten rough sketch. After checking the rough sketch on the preview screen and making any necessary corrections, the user presses the send button. The data entered by the user at this time is rough sketch image data, which is sent from the device to the server.

[1315] Specific working example:

[1316] The user draws a rough sketch by hand on paper.

[1317] The user takes a rough sketch using the smartphone camera.

[1318] The user taps the "Upload" button on the dedicated app, checks the preview screen, and then presses the "Send" button.

[1319] Input: rough sketch image data

[1320] Output: Send image data to the server

[1321] Step 2: The server receives and analyzes the rough sketch data.

[1322] The server receives the rough sketch data sent from the device. The received data is first stored in the server's storage. The server then analyzes the image data's resolution, format, size, etc., and converts it into a format that can be used by the generation AI. This process performs preprocessing to provide the optimal data to the generation AI.

[1323] Specific working example:

[1324] The server saves the image file in a storage directory.

[1325] The server analyzes the image file's resolution, format, and size, and resizes or converts the format as needed.

[1326] Input: rough sketch image data

[1327] Output: Image data formatted for generative AI

[1328] Step 3: The server's emotion recognition means recognizes the emotion.

[1329] The emotion recognition means integrated into the server analyzes the rough sketches and other input data (e.g., text input, voice, facial expressions, etc.) uploaded by the user to recognize the user's emotions. The emotion engine uses facial expression analysis algorithms and text analysis algorithms to identify the user's emotional state. This recognition result is used as important input data for subsequent illustration generation.

[1330] Specific working example:

[1331] An emotion recognition means of the server analyzes the text comments related to the rough sketch.

[1332] The emotion recognition means of the server analyzes the voice data and identifies the emotion.

[1333] Input: rough sketch, text comments, audio data

[1334] Output: User emotion recognition results

[1335] Step 4: Server generation AI generates illustrations

[1336] The server's generation AI generates a consistent illustration based on the rough sketch data and the emotion recognition results. It reflects the emotion recognition results, generating an illustration with soft colors if the user is relaxed, or bright colors if the user is energetic. This process ensures that the generated illustration reflects the user's emotions.

[1337] Specific working example:

[1338] The server inputs rough sketch data and emotional data into the generation AI.

[1339] The generation AI generates illustrations according to prompts.

[1340] Input: rough sketch data, emotion recognition results

[1341] Output: Generated illustration data

[1342] Step 5: The server sends the generated image data to the terminal.

[1343] The server sends the generated illustrations and images to the terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added to the generated image data. This process allows the user to check the generated illustrations.

[1344] Specific working example:

[1345] The server adds metadata to the generated illustration.

[1346] The illustration data is transmitted to the terminal through the data communication means.

[1347] Input: Generated illustration data

[1348] Output: Illustration data sent to the device

[1349] Step 6: The device displays the generated image and makes it available for download

[1350] The device displays the generated images to the user and makes them available for download. A notification function lets the user know that new illustrations are available. The user can review the displayed images and download the ones they like for use in other materials or on other websites.

[1351] Specific working example:

[1352] The illustrations received by the device will be displayed on the app's gallery screen.

[1353] Use notifications to let users know when new illustrations are available.

[1354] The user selects the illustration they like and clicks the "Download" button.

[1355] Input: Illustration data sent from the server

[1356] Output: The illustration that is displayed to the user and available for download

[1357] (Application example 2)

[1358] 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."

[1359] Conventional systems struggle to efficiently generate consistent designs and styles when digitizing users' handwritten rough sketches. Furthermore, they are unable to generate illustrations that reflect the user's emotional state, making it difficult to create custom designs that satisfy the user. Furthermore, they lack the functionality to manage metadata for the generated illustrations, making subsequent editing and reuse cumbersome.

[1360] 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.

[1361] In this invention, the server includes a terminal means for users to upload handwritten rough sketches; a server means for receiving the rough sketch data sent from the terminal means and generating images; a generation AI means in the server means for analyzing the rough sketch data and generating unified illustrations and images; an emotion recognition means in the server means for adjusting the style and color tone of the generated images based on emotions; a data communication means for transmitting the generated image data from the server means to the terminal means; and a display means in the terminal means for displaying the transmitted generated images and making them available for download. This allows users to easily digitize handwritten rough sketches and generate illustrations that reflect their emotions. This not only enables the rapid creation of custom products with consistent designs, but also simplifies subsequent editing and reuse thanks to the metadata management function.

[1362] "User" means a person who uses the system to upload hand-drawn rough sketches and create digitized illustrations and product designs.

[1363] A "hand-drawn rough sketch" is an early sketch that a user draws on paper or a digital device.

[1364] "Terminal means" refers to a device such as a smartphone, tablet, or PC that a user uses to upload rough sketches.

[1365] "Server means" refers to a server that receives and analyzes rough sketch data and generates illustrations and images using generation AI.

[1366] "Generative AI means" refers to artificial intelligence that analyzes rough sketch data and generates unified illustrations and images.

[1367] The "emotion recognition means" is an engine that analyzes the user's emotional state and adjusts the style and color tone of the generated image.

[1368] The "data communication means" refers to a mechanism for transmitting the generated image data from the server means to the terminal means.

[1369] "Display means" refers to a device or software that has the function of displaying the generated image on a terminal and allowing the user to view and download the image.

[1370] "Metadata" is additional information related to the generated image, including the date and time of generation, user ID, emotion recognition results, etc.

[1371] The present invention relates to a system that digitizes rough sketches handwritten by a user and generates a variety of illustrations that reflect emotion and have a consistent feel. Specific embodiments of this system will be described below.

[1372] The server includes terminal means for users to upload handwritten rough drawings, server means for receiving the rough drawing data sent from the terminal means and generating images, generation AI means for analyzing the rough drawing data and generating unified illustrations and images, emotion recognition means for adjusting the style and color tone of the generated images based on emotions, data communication means for sending the image data generated from the server means to the terminal means, and display means for displaying the sent generated images and making them available for download.

[1373] Hardware and software used

[1374] Terminal means: A device such as a smartphone, tablet, or PC that a user uses to upload handwritten rough sketches.

[1375] Server method: A server running a high-performance CPU / GPU is used to receive and analyze rough sketch data.

[1376] Generative AI methods: Using generative models (e.g., GAN, VAE) trained using deep learning libraries such as TensorFlow or Keras.

[1377] Emotion recognizer: An engine or model for analyzing emotions (e.g., an emotion recognition model trained with TensorFlow or Keras).

[1378] Display: An application that allows the user to view and download the generated images on their device.

[1379] Data processing and calculation

[1380] 1. The user takes a picture of a rough sketch using a terminal and uploads it through a dedicated application. At the same time, the user inputs emotional information in the form of simple questions.

[1381] 2. The terminal means transmits the rough sketch data and emotion data to the server.

[1382] 3. The server analyzes the received rough sketch data and converts it into an appropriate resolution and format. The emotion recognition analyzes the emotion data and recognizes the user's current emotional state.

[1383] 4. The AI ​​generation method generates unified illustrations and product designs based on rough sketch data and emotion recognition results. Color tones and design patterns are adjusted based on the emotion recognition results.

[1384] 5. The generated image data is sent from the server to the device, along with metadata such as the generation date and time, user ID, and emotion recognition results.

[1385] 6. The terminal means displays the generated image, and the user checks the image, downloads it, and uses it.

[1386] Specific examples

[1387] If a user wants to design a custom T-shirt in the virtual store, they first sketch it on paper, then photograph it using a dedicated smartphone app and upload it. During this process, the user inputs their current emotion as "energetic." The server uses an emotion recognition engine to interpret the input emotion data, and the generation AI generates a brightly colored design that matches that emotion. The generated design is sent to the user's smartphone and displayed in the app. The user can then select their favorite design and download it, completing their custom T-shirt.

[1388] Example prompt sentence:

[1389] User: "I'm uploading a rough sketch I did on paper. I'm feeling energetic right now. I'd like to create a custom t-shirt design with a bright color scheme and a cohesive look."

[1390] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1391] Step 1:

[1392] The user prepares a rough sketch by hand and then photographs or scans it using a dedicated application on a device such as a smartphone, tablet, or PC. The user also inputs their current emotional state into the application, using prompts or simple questions. The input data consists of image data of the rough sketch and emotional data.

[1393] Step 2:

[1394] The terminal transmits rough sketch data and emotion data to the server. The transmitted data includes image data of the rough sketch and the user's emotion information. The data calculation in this step is the accurate transfer of image and emotion data. The terminal receives rough sketch data and emotion data as input and transmits them to the server as output.

[1395] Step 3:

[1396] The server receives the rough sketch data sent from the device. The received data includes rough sketch image data and emotion data. The server analyzes this data and converts the image resolution and format to an appropriate format. The input data is the rough sketch data, and the output data is the analyzed rough sketch data.

[1397] Step 4:

[1398] The server uses an emotion recognition means to analyze the user's emotion data. It uses an emotion recognition engine (e.g., a model trained with TensorFlow or Keras) to classify the user's current emotional state. The input data is the emotion data, and the output data is the recognized emotional state (e.g., energetic, relaxed, etc.).

[1399] Step 5:

[1400] The server uses a generative AI to generate illustrations and product designs based on the analyzed rough sketch data and emotion recognition results. The generative AI (e.g., a GAN or VAE model) adjusts color tones and design patterns based on the emotion recognition results. The input data are the rough sketch data and emotion recognition results, and the output data is the generated illustration or design.

[1401] Step 6:

[1402] The server transmits the generated illustrations and designs to the user's terminal via data communication means. At this time, metadata such as the generation date and time, user ID, and emotion recognition results are also added. The input data is the generated illustrations and designs and metadata, and the output data is the transmitted illustrations and designs.

[1403] Step 7:

[1404] The terminal means displays the received generated image. The user checks the displayed image and downloads it if necessary. The input data is the received generated image, and the output data is the displayed and downloaded image.

[1405] In this way, specific actions, inputs, and outputs are clarified at each step, realizing the process of digitizing the user's rough handwritten sketch and generating a custom design that reflects their emotions.

[1406] 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.

[1407] 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.

[1408] 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.

[1409] 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.

[1410] FIG. 9 illustrates 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 behaviors 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.

[1411] 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.

[1412] 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).

[1413] 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.

[1414] 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."

[1415] 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.

[1416] 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).

[1417] 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.

[1418] 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.

[1419] 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.

[1420] 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.

[1421] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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 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.

[1422] 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.

[1423] 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.

[1424] 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.

[1425] 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.

[1426] 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.

[1427] The following is further disclosed regarding the above embodiment.

[1428] (Claim 1)

[1429] a terminal means for a user to upload a handwritten rough sketch;

[1430] a server means for receiving the rough image data transmitted from the terminal means and generating an image;

[1431] In the server means, a generation AI means for analyzing rough sketch data and generating illustrations and images with a unified appearance;

[1432] data communication means for transmitting the image data generated by the server means to the terminal means;

[1433] The system further includes a display means for displaying the transmitted generated image in the terminal means and making the image available for download.

[1434] (Claim 2)

[1435] The system of claim 1, wherein the generating AI means generates illustrations in a plurality of different styles and variations from rough sketches.

[1436] (Claim 3)

[1437] 10. The system of claim 1, wherein the generating AI means records and stores metadata associated with the generated image.

[1438] "Example 1"

[1439] (Claim 1)

[1440] a terminal means for a user to upload a handwritten rough sketch;

[1441] a server means for receiving the rough image data transmitted from the terminal means and generating an image;

[1442] In the server means, a generation AI means for analyzing rough sketch data and generating illustrations and images with a unified appearance;

[1443] data communication means for transmitting the image data generated by the server means to the terminal means;

[1444] a display means in the terminal means for displaying the transmitted generated image and making it downloadable;

[1445] The terminal means has a rough sketch preview function and a user correction function, and includes a function for the user to send the rough sketch after checking and correcting it.

[1446] (Claim 2)

[1447] The system of claim 1, wherein the generating AI means generates illustrations in a plurality of different styles and variations from rough sketches.

[1448] (Claim 3)

[1449] 10. The system of claim 1, wherein the generating AI means records and stores metadata associated with the generated image.

[1450] "Application Example 1"

[1451] (Claim 1)

[1452] an input means for a user to upload a handwritten rough sketch;

[1453] a central processing means for receiving the rough image data transmitted from the input means and generating an image;

[1454] In the central processing means, an automatic generation means for analyzing the rough sketch data and generating illustrations and images with a unified look;

[1455] data transmission means for transmitting image data generated by said central processing means to said input means;

[1456] The system further includes a display means for displaying the generated image transmitted by the input means and making it available for download.

[1457] (Claim 2)

[1458] 2. The system according to claim 1, wherein the automatic generation means generates illustrations in a plurality of different styles and variations from rough sketches.

[1459] (Claim 3)

[1460] 10. The system of claim 1, wherein the automatic generation means records and stores attribute data associated with the generated images.

[1461] (Claim 4)

[1462] The system of claim 1 is applicable to generating illustrations for physical store guides and promotional materials, and quickly digitizes hand-drawn rough sketches for use in physical stores and displays them as illustrations for electronic displays and posters.

[1463] "Example 2: Combining Emotion Engines"

[1464] (Claim 1)

[1465] a terminal means for a user to upload a handwritten rough sketch;

[1466] computer means for receiving the rough image data transmitted from the terminal means and generating an image;

[1467] In the computer means, a generation AI means for analyzing the rough sketch data and generating illustrations and images with a sense of unity;

[1468] emotion recognition means for analyzing the user's emotion and reflecting it in the generated illustration;

[1469] data communication means for transmitting image data generated by said computer means to said terminal means;

[1470] The system further includes a display means for displaying the transmitted generated image in the terminal means and making the image available for download.

[1471] (Claim 2)

[1472] The system of claim 1, wherein the generating AI means generates illustrations in a plurality of different styles and variations from rough sketches.

[1473] (Claim 3)

[1474] 10. The system of claim 1, wherein the generating AI means records and stores metadata associated with the generated image.

[1475] "Application example 2 when combining emotion engines"

[1476] (Claim 1)

[1477] a terminal means for a user to upload a handwritten rough sketch;

[1478] a server means for receiving the rough image data transmitted from the terminal means and generating an image;

[1479] In the server means, a generation AI means for analyzing rough sketch data and generating illustrations and images with a unified appearance;

[1480] an emotion recognition means for adjusting the style and color tone of the generated image based on the emotion;

[1481] data communication means for transmitting the image data generated by the server means to the terminal means;

[1482] The system further includes a display means for displaying the transmitted generated image in the terminal means and making the image available for download.

[1483] (Claim 2)

[1484] The system of claim 1, wherein the generating AI means generates illustrations in a plurality of different styles and variations from rough sketches.

[1485] (Claim 3)

[1486] 10. The system of claim 1, wherein the generating AI means records and stores metadata associated with the generated image. [Explanation of symbols]

[1487] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a terminal means for a user to upload a handwritten rough sketch; a server means for receiving the rough image data transmitted from the terminal means and generating an image; In the server means, a generation AI means for analyzing rough sketch data and generating illustrations and images with a unified appearance; data communication means for transmitting the image data generated by the server means to the terminal means; and display means for displaying the transmitted generated image in said terminal means and making it available for download.

2. The system according to claim 1 , wherein the generating AI means generates illustrations in a plurality of different styles and variations from rough sketches.

3. 10. The system of claim 1, wherein said generating AI means records and stores metadata associated with the generated images.

Images