KR102479195B1 - Nft-based digital art self-generating apparatus and methods thereof - Google Patents

Abstract

According to one embodiment of the present invention, an NFT-based digital art self-creation device may comprise: a transmission/reception unit which receives content including one or more image frames and transmits a generated digital art to the outside; a content analysis unit which recognizes and derives content elements including character elements, elements other than characters, and style elements in the one or more image frames; a database which stores data including the received content and derived content elements; a depiction element selection unit which presents a plurality of items for at least one of the character elements, elements other than characters, and style elements based on the data, and performs a selection for each user from among the plurality of depiction elements; and a digital art creation unit which creates a digital art based on the selection. According to the present invention, the NFT-based digital art self-creation device and a method thereof can improve accessibility so that even ordinary users who are not experts in creating digital art can easily self-create new digital art and acquire NFTs, and thus can induce interest and participation in an NFT trading system.

Description

NFT-based digital art self-generation device and method {NFT-BASED DIGITAL ART SELF-GENERATING APPARATUS AND METHODS THEREOF}

The present invention relates to an NFT-based digital art self-generating device and method, and more particularly, to enable general users to easily self-generate new digital art and acquire NFTs, thereby inducing interest and participation in the NFT trading system. It relates to a device and method for self-generating NFT-based digital art.

In blockchain, smart contract is a basic technology that can implement DApp (Decentralized Application) to build a blockchain ecosystem by extending the concept of cryptocurrency issued on the main net. can be issued to build a sub-blockchain network based on the mainnet.

Tokens are largely divided into fungible tokens (FT) and non-fungible tokens (NFT), and fungible tokens have the same value as issued tokens such as cryptocurrencies and can be exchanged with other tokens. Non-Fungible Tokens (NFTs) are mainly used as tokens to record tangible and intangible assets and cannot be exchanged with other tokens. Due to the emergence of such NFTs and the metaverse paradigm of the virtual world, a great shift has been made in the field of digital assets. NFT has been recognized as a technology that can recognize ownership of digital art such as rare characters or items or memes in the game field, such as Crypto Kitty of Cryptopunk, for example, and is fused with the metaverse to create real and virtual It is possible to build a virtual economy by converting the ownership and property rights of existing objects and concepts into digital assets as NFTs. “Meme” refers to a short video, photo, language, or secondary creation using them online, and NFTs are often created and/or sold as digital assets.

Users of the NFT trading system register the digital assets they create or own to create NFTs, and the generated NFTs are traded using coins or currencies of the blockchain network. The NFT value of digital assets is created by trading NFTs between users in the NFT trading system, and the NFT trading system is an important factor in forming the value and ownership of NFTs.

Recently, an emerging issue in the art market is to turn digital art works into NFTs through the Ethereum blockchain, or 'Minting'. In the existing NFT trading system, NFTs are actively being carried out for specific digital assets, such as works of art that require creation, and NFTs are issued and traded for digital art created by a specific user class, such as users who are professional artists. In this regard, Korean Patent No. 10-2343025 discloses that the ownership of digital art can be divided into a desired number and sold according to the creator's choice, and the divided ownership can be safely and freely traded among users in various ways. It discloses a non-fungible token-based digital art trading method.

However, this current method has a problem in that it is not easy for non-professional general users to issue NFTs by creating popular digital art such as memes that are widely popular, limiting the user class who sells digital assets through NFTs. . This makes it difficult for ownership of digital assets to become popular, and furthermore, causes a problem in that the value of ownership is lowered. Therefore, there is a need for a technology that can easily create digital assets for more diverse users and facilitate issuance as NFTs.

Republic of Korea Patent Registration No. 10-2343025

The technical problem to be achieved by the present invention is to provide NFT-based digital art self-creation that can induce interest and participation in the NFT trading system by allowing ordinary users who are not experts in digital art to easily self-create new digital art and acquire NFTs. It is a technical challenge to provide a generating device and method.

In addition, the technical problem to be achieved by the present invention is that general users easily self-generate new digital art based on existing content such as digital art, their own creations, and/or non-owned content through NFT. The technical task is to provide an NFT-based digital art self-generating device and method that can attract interest and participation in the NFT trading system while reducing risk by acquiring NFTs and clarifying the ownership of them.

The technical problem to be achieved by the present invention is not limited to the above-mentioned technical problem, and other technical problems not mentioned can be clearly understood by those skilled in the art from the description below. There will be.

NFT-based digital art self-generating device of an embodiment of the present invention for achieving the above technical problem

a transceiver for receiving content including one or more image frames and transmitting the generated digital art to the outside;

a content analyzer for recognizing and deriving content elements including character elements, non-character elements, and style elements within the one or more image frames;

a database for storing data including the received content and derived content elements;

a depiction element selector configured to present a plurality of items for at least one depiction element among character elements, non-character elements, and style elements based on the content elements and perform selection for each user among the plurality of items; and

A digital art creation unit may be included to generate digital art based on the selection.

According to an embodiment of the present invention, the NFT-based digital art self-generating device determines the at least one description element derived from the description element selection unit. and a user interface unit displaying a plurality of items to each user and receiving a selection input among the plurality of items from each user, wherein the depiction element selection unit selects the plurality of items based on a selection input received from the user interface unit. A selection can be made among the items of

According to an embodiment of the present invention, the NFT-based digital art self-generating device displays a plurality of contents stored in the database to each user, receives a plurality of preferred image inputs from each user, and receives character elements, characters, etc. Further comprising a propensity analyzer for generating propensity data by analyzing each user's preference for at least one or more of depiction elements such as elements and style elements, wherein the preference derived for each user by the propensity analyzer Based on the propensity data, selection of the plurality of items for the at least one or more depiction elements may be performed in the depiction element selector.

According to an embodiment of the present invention, the NFT-based digital art self-generating device performs learning of the artificial intelligence model based on the preference data derived from the propensity analyzer for the user to select the depiction element, A model generator for generating a depiction element selection model is further included, wherein the depiction element selection unit performs selection among the plurality of items for the at least one depiction element through the depiction element selection model learned for each user. can

According to one embodiment of the present invention, the content analysis unit analyzes whether ownership of the received content exists and may tag the received content and related content elements.

According to an embodiment of the present invention, a user displaying a plurality of items for the at least one depiction element derived from the depiction element selector to each user and receiving a selection input from the plurality of items from each user An interface unit may further include an interface unit, and when displaying the plurality of items to each user, each depiction element is tagged with ownership or not, and the depiction element selection unit displays the plurality of depiction elements based on a selection input received from the user interface unit. A selection can be made among the items of

The NFT-based digital art self-generating method performed by a server or client device according to another embodiment of the present invention for achieving the above technical problem is,

a content receiving step of receiving content including one or more image frames;

a content analysis step of recognizing and deriving content elements including character elements, non-character elements, and painting styles within the one or more image frames;

a depiction element selection step of presenting a plurality of items for at least one of a character element, non-character element, and style element based on the content elements and selecting one or more of the plurality of items; and

A digital art generation step of generating digital art based on the selection may be included.

According to one embodiment of the present invention, the selecting of the description elements may include: selecting a plurality of description elements for at least one of a character element, non-character elements, and style elements based on the content elements through the user interface. displaying to each user; receiving a selection input from among the plurality of items for the at least one depiction element from each user; and selecting from among the plurality of items based on a selection input received from the user interface unit.

According to one embodiment of the present invention, the method displays a plurality of contents stored in a database to the user through a user interface, receives a preference image input from each user, and receives at least one of a character element, non-character element, and style element. a propensity analysis step of generating propensity data by analyzing each user's preference for one or more; and a depiction element selection model generating step of generating a depiction element selection model for each user by performing learning of an artificial intelligence model based on the propensity data for each user, wherein the depiction element selection model in the depiction element selection step Selection of at least one depiction element among the plurality of items may be performed based on a depiction element selection model learned for each user.

According to one embodiment of the present invention, the method may further include a non-fungible token generation step of generating a non-fungible token through a smart contract with respect to the generated digital art.

According to an embodiment of the present invention, an NFT-based method that can induce interest and participation in the NFT trading system by improving accessibility so that even general users who are not experts in digital art can easily self-create new digital art and acquire NFTs. A digital art self-generating device and method can be provided.

In addition, according to an embodiment of the present invention, general users can easily self-create new digital art based on existing content such as digital art, their own creations, and/or non-owned content through NFT, NFT-based digital art self-generating device that can induce interest and participation in the NFT trading system while improving accessibility to acquire NFTs, while reducing legal risks related to ownership by clarifying the ownership of existing NFTs, and It is a technical task to provide a method.

The effects of the present invention are not limited to the above effects, and should be understood to include all effects that can be inferred from the detailed description of the present invention or the configuration of the invention described in the claims.

1 is a schematic diagram of an NFT-based digital art self-generating device according to an embodiment of the present invention.
2 is a schematic flowchart of a method for self-generating NFT-based digital art according to an embodiment of the present invention.
3 is a flowchart illustrating an embodiment of detailed steps when selection is performed based on input from each user in the step of selecting a depiction element of the method of self-generating NFT-based digital art according to an embodiment of the present invention.
4 is a flowchart showing an embodiment of detailed steps when selection is performed by artificial intelligence in the description element selection step of the NFT-based digital art self-generating method according to an embodiment of the present invention.
5 is a schematic diagram showing the configuration of an embodiment of an integrated system for generating and distributedly storing NFT-based digital art including an NFT-based digital art self-generating device according to an embodiment of the present invention.
6 is a schematic diagram showing an integrated system for generating, storing, and trading NFT digital assets for memes including an NFT-based meme generating device according to an embodiment of the present invention.

Hereinafter, the present invention will be described with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and, therefore, is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part is said to be "connected (connected, contacted, combined)" with another part, this is not only "directly connected", but also "indirectly connected" with another member in between. "Including cases where In addition, when a part "includes" a certain component, it means that it may further include other components without excluding other components unless otherwise stated.

Terms used in this specification are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as "include" or "have" are intended to indicate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

1 is a schematic diagram of an NFT-based digital art self-generating device 100 according to an embodiment of the present invention. Referring to FIG. 1, the NFT-based digital art self-generating device 100 according to an embodiment of the present invention includes a transceiver 110, a content analyzer 120, a database 130, and a depiction element selector 140. , may include a digital art creation unit 150. The NFT-based digital art self-generating device 100 may further include a user interface unit 160, a tendency analysis unit 170, and a model generation unit 180.

The transceiver 110 can receive content including one or more image frames, and transmits the digital art generated by the digital art generator 150 to the outside for NFT issuance or distributed storage in an external storage. can do. The contents including the one or more image frames may be other digital art contents for which NFTs have been previously issued, or may be each user's own creation or non-owned contents disclosed to the public. The content is any object that can be registered as an NFT, and may be an image or video, a character, or a meme. Digital art for which NFT is issued may be stored in an NFT-based content storage system or a distributed content storage or storage network (eg, a distributed storage network such as IPFS (InterPlanetary File System) or a distributed storage platform such as SWAM). there is.

The content analyzer 120 may recognize and derive content elements constituting an image including a character element, non-character elements, and a painting style within one or more image frames of the received content. The character element refers to a representation of a shape having vitality through its own personality and characteristics in the image of the content through a picture or photograph, and refers to a symbol in which personality is expressed, such as a name, personality, or behavior. Elements other than characters are a generic term for elements expressed in an image other than characters, and mean, for example, a background, props, displayed language, effects, and the like. A painting style refers to a particular tendency or characteristic of expressing a painting or its image. The content analyzer 120 may recognize and derive content elements using a vision recognition model learned based on conventional content data. The content analyzer 120 may verify whether ownership of the received content exists in a self-response manner, and may tag the received content and related content elements.

The database 130 may store data and related metadata including the contents received by the transceiver and/or content elements derived from the content analyzer 120, but the stored data is not limited thereto. no.

Based on the data stored in the database 130, the depiction element selector 140 presents a plurality of items for each of at least one or more of character elements, non-character elements, and style elements, and each of the plurality of items One or more selections may be made for the user. The selection may be made based on an input by each user, or may be automatically made through an artificial intelligence model that has learned prior propensity data for each user's selection, and an artificial intelligence model for each user's input and each user. It may be performed by mixing the depiction element selection model generated through

When one or more selections are made for each user from among the plurality of items based on each user's input, the depiction element selection unit 140 uses the display or user interface unit 160 to character elements based on the data. , displaying a plurality of items for at least one or more of elements other than characters and style elements to each user, receiving an input related to selection among the plurality of items from each user, and the user interface unit ( Based on the selection input received from 160), one or more selections may be performed among the plurality of items.

When one or more selections are made for each user among the plurality of items based on the artificial intelligence model, the character elements, non-character elements, and painting styles are based on the user's previous selection in the propensity analyzer 170. Each user's preference for at least one or more of the elements is analyzed to generate propensity data, and the model generator 180 performs learning of an artificial intelligence model based on the propensity data for each user to generate each of the user's preferences. After creating a description element selection model for the user, the description element selection unit 140 presents a plurality of items for at least one or more of character elements, non-character elements, and style elements based on the data, and One or more of the plurality of items may be selected based on a description element selection model learned for each user. All of these operations may be implemented by one processing device, or may be implemented by combining a plurality of processing devices.

The digital art generation unit 150 may generate digital art based on the selection of one or more for each user among the plurality of depiction elements in the depiction element selection unit 140 . In the digital art, at least one digital art can be created by processing an image by optimally combining selections for each user with respect to at least one of character elements, non-character elements, and style elements. The digital art may be images or videos, characters or memes, but is not limited thereto. Non-fungible tokens (NFTs) can be issued from the one or more generated digital arts through a smart contract later.

The user interface unit 160 may display a plurality of depiction elements derived from the depiction element selection unit 140 to each user and receive a selection input from among the plurality of depiction elements from each user. The user interface unit 150 may further include a display displaying a plurality of items derived from the depiction element selector 140 to each user. When displaying the plurality of items to each user in the user interface unit 160, whether or not ownership of each description element is tagged may also be displayed. The user interface unit 150 displays the plurality of digital arts created for each user in the digital art creation unit 150 to each user and receives a selection input for one or more preferred digital arts from each user. Alternatively, the selected preferred digital art can be transmitted to the outside through the transmission/reception unit 110, and a non-fungible token (NRT) can be generated through a smart contract therefor.

The propensity analysis unit 170 displays a plurality of contents stored in the database to each user, receives a plurality of preferred image inputs from each user, and determines at least one of character elements, non-character elements, and style elements. The preference data of each user may be analyzed to generate propensity data. The analysis of the preference for each user may be performed based on a predetermined set of standard rules or may be performed through a preference analysis model generated through an artificial intelligence model, but is not limited thereto.

The model generating unit 180 selects a learning model for selecting the description element in the description element selection unit 140 and/or a learning model for analysis of propensity in the propensity analyzer 170, and selects each learning model. In relation to this, the artificial intelligence model may be learned with the propensity data derived for the user and/or a plurality of basic data for propensity analysis to generate a depiction element selection model and/or a propensity analysis model.

2 is a schematic flowchart of a method 200 for self-generating NFT-based digital art according to an embodiment of the present invention. This method may be performed by a server and/or a client device. Referring to FIG. 2 , in the NFT-based digital art creation method according to an embodiment of the present invention, first, a content reception step (S210) of receiving content including one or more image frames in a transceiver, A content analysis step (S220) of recognizing and deriving content elements including character elements, non-character elements, and style elements, and a plurality of at least one or more elements among character elements, non-character elements, and style elements based on the data. It may include a description element selection step (S230) of presenting description elements and selecting one or more of the plurality of description elements, and a digital art creation step (S240) of generating digital art based on the selection. It may further include generating the digital art as a non-fungible token (NFT) through a smart contract.

3 is a flowchart illustrating an embodiment of detailed steps when selection is performed based on input from each user in the step of selecting a depiction element of the method of self-generating NFT-based digital art according to an embodiment of the present invention. In the description element selection step (S230) in FIG. 2, when one or more items are selected for each user from among the plurality of items based on each user's input, referring to FIG. 3, the character element is based on the data. Displaying a plurality of depiction elements for at least one or more of elements other than characters and style elements to each user through a user interface (S332), receiving a selection input among the plurality of items from each user (S334), selecting from among the plurality of depiction elements based on the selection input received from the user interface (S336).

4 is a flowchart showing an embodiment of detailed steps when selection is performed by artificial intelligence in the description element selection step of the NFT-based digital art self-generating method according to an embodiment of the present invention. In the selection step (S230) of FIG. 2, when one or more selections for each user are made from among the plurality of depiction elements based on an artificial intelligence model, referring to FIG. 4, a plurality of contents stored in the database. Displayed to the user through a user interface, receiving a preferred image input from each user, analyzing each user's preference for at least one of character elements, non-character elements, and painting style elements to generate propensity data A propensity analysis step (S432), a depiction element selection model creation step (S434) of performing learning of an artificial intelligence model based on the propensity data for each user to generate a depiction element selection model for each user, Based on this, a plurality of depiction elements are presented for at least one of character elements, non-character elements, and style elements, and selection of one or more of the plurality of depiction elements is performed based on the learning descriptive element selection model for each user. A performing step (S436) may be included.

5 is a schematic diagram showing the configuration of an embodiment of an integrated system 500 for generating and distributing and storing NFT-based digital art including an NFT-based digital art self-generating device according to an embodiment of the present invention. Referring to FIG. 5 , in the integrated system 500, the NFT-based digital art generator 520 receives the content including one or more images from the NFT-content storage system 510 and stores the content in the one or more images. Recognizes and derives content elements including character elements, non-character elements, and style elements, and presents a plurality of depiction elements for at least one of the character elements, non-character elements, and style elements based on the data. Then, at least one or more of the plurality of items is selected by the user's selection or by an artificial intelligence (AI) algorithm in which each user's preference is learned, and based on the selection, digital art desired by each user can create

For mounted digital art, digital assetization can be performed by issuing a non-fungible token (NFT) by smart contract through the DApp 540, which is an NFT system, for example. Multiple Memes digital assets created with this technology are minted through DApp, and actual digital assets are stored as an open distributed file storage based on the P2P protocol through the NFT-Contents Storage system. In addition, it is provided to connect with coins of other blockchain networks through interface modules using Cross-Chain or Inter-Chain technology through DApp. For example, the client 550 can deploy a smart contract to the Ethereum main net and share and synchronize a distributed ledger. The Ethereum Virtual Machine (EVM) composed of Ethereum client (550) nodes can form an independent environment for recording blockchains and operating smart contracts in Ethereum, and through the client interface, DApp ( 540) is connected. The Ethereum network 580 includes a public Ethereum mainnet, an Ethereum testnet, and a private Ethereum Ganache. DApp 540 can communicate with other blockchain networks (e.g., Hyperledger, Klaytn, Polygon, Tron, etc.) by including a cross-chain interface.

6 is a schematic diagram showing an integrated system 600 for generating, storing, and trading NFT digital assets for memes including an NFT-based meme generating device according to an embodiment of the present invention.

Referring to FIG. 6, a meme NFT stored in the NFT content storage system 612 as a previously registered NFT digital asset or a user's own creation or published content 614 is received and a character is generated in the NFT-based meme generator 620. can be recognized and extracted, and external elements such as background, language, etc., or characteristic style elements of images can be extracted as description elements. The descriptive elements extracted in this way are combined and reflected into desired images by a machine learning model based on each user's selection or each user's preference data and processed to create one or more new memes, and when a plurality of memes are created In this case, the user can select a preferred meme, transmit and register it to the DApp (630), issue NFT through a smart contract (e.g., ERC-721 based smart contract) and turn it into a digital asset. When selections of preferred memes are accumulated, the performance of the meme generator 620 can be enhanced by learning the description element selection model of the meme generator 620 based on the preference data of each user derived from the selection.

These digital assets may again be stored in the NFT content storage system 612, and some or all of them may be distributed and stored again. The issued NFT information can be distributed and stored in the Ethereum network, and the NFT information for the meme is the NFT ID, the original image of the description element before the meme is created, the created meme image, the owner of the digital asset, the meme storage location, and the order tag It may include at least one or more of information such as (tag), entropy (Cross-Entropy), and the like. In addition, the generated NFTs can be shared with other blockchain networks through a cross-chain interface. The meme NFT generated by the DApp (630) is transmitted to the general NFT trading system (640) to facilitate trading of distributed NFT-based digital assets to users, scoring digital assets based on profile or entropy It can be recommended and listed and provided. Originals of NFT-based digital assets registered in the NFT trading system can be permanently stored as an open distributed file storage through the NFT content storage system 612.

NFT-based digital assets purchased in the existing NFT trading system are linked with coins of other blockchain networks through an interface module using Cross-Chain or Inter-Chain technology in DApp (630). It is possible to maintain the value and ownership of NFT-based digital assets by providing various payment methods.

The above description of the present invention is for illustrative purposes, and those skilled in the art can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, the embodiments described above should be understood as illustrative in all respects and not limiting. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims, and all changes or modifications derived from the meaning and scope of the claims and equivalent concepts should be interpreted as being included in the scope of the present invention.

100: NFT-based digital art self-generating device
110: transmission and reception unit 120: content analysis unit
130: database 140: description element selection unit
150: digital art generation unit 160: user interface unit
170: tendency analysis unit 180: model generation unit
500: An integrated system for generating and distributing storage of NFT-based digital art
510, 612: NFT content storage system
520: NFT-based digital art generator
530: decentralized content storage system
540, 630: DApp (Decentralized Application)
550: Ethereum client (node)
560: Blockchain mainnet integration platform
570: other blockchain networks
580: Ethereum network
600: An integrated system that creates, stores, and trades NFT digital assets for memes
614: User's repository or public repository
620: Meme Generator
640: NFT trading system

Claims (10)

a transceiver for receiving content including one or more image frames and transmitting the generated digital art to the outside;
a content analyzer for recognizing and deriving content elements including character elements, non-character elements, and style elements within the one or more image frames;
a database for storing data including the received content and derived content elements;
a depiction element selector configured to present a plurality of items for at least one depiction element among character elements, non-character elements, and style elements based on the content elements and perform selection for each user among the plurality of items;
a digital art generating unit generating digital art based on the selection; and
a user interface unit displaying a plurality of items for the at least one depiction element derived from the depiction element selection unit to each user and receiving a selection input from among the plurality of items from each user;
The content analyzer analyzes whether ownership of the received content exists and tags the received content and related content elements;
When displaying the plurality of items to each user in the user interface unit, whether each item is tagged with ownership is displayed together, and the depiction element selection unit selects the plurality of items based on a selection input received from the user interface unit. NFT-based digital art self-generating device that allows selection among According to claim 1,
The NFT-based digital art self-generating device, characterized in that the description element selection unit selects among the plurality of items based on the selection input received from the user interface unit. According to claim 1,
A plurality of contents stored in the database are displayed to each user, and a plurality of preferred image inputs are received from each user to analyze the preference of each user for at least one of character elements, non-character elements, and style elements. Further comprising a propensity analyzer for generating propensity data by
NFT-based digital art self-generating device, characterized in that the selection of the plurality of items is performed in the depiction element selection unit based on the preference data derived for each user in the propensity analysis unit. According to claim 3,
A model generating unit that selects a learning model for selecting the depiction elements and performs machine learning of the learning model based on the preference data derived for each user in the propensity analysis unit to generate a depiction element selection model. contain more,
The description element selection unit performs a selection among the plurality of items through the description element selection model learned for each user, NFT-based digital art self-generating device. delete delete As an NFT-based digital art self-generation method performed by a server or client device,
a content receiving step of receiving content including one or more image frames;
a content analysis step of recognizing and deriving content elements including character elements, non-character elements, and painting styles within the one or more image frames;
a depiction element selection step of presenting a plurality of items to each user and selecting one or more of the plurality of items for at least one of a character element, a non-character element, and a style element based on the content elements; and
A digital art creation step of generating digital art based on the selection,
The step of analyzing the content includes tagging the received content and related content elements by analyzing whether ownership of the received content exists,
In the selecting of the depiction elements, when presenting the plurality of items of the at least one or more depiction elements to each user, whether each item is tagged with ownership is displayed, and each user's selection input received from the user interface unit is displayed. Further comprising the step of performing a selection among the plurality of items based on, NFT-based digital art self-generating method. According to claim 7,
The depiction element selection step is:
displaying a plurality of depiction elements for at least one of a character element, a non-character element, and a style element based on the content elements to each user through the user interface unit;
receiving a selection input among the plurality of depiction elements from each user;
Characterized in that it comprises the step of performing a selection among the plurality of depiction elements based on the selection input received from the user interface unit, NFT-based digital art self-generating method. According to claim 7,
Displaying a plurality of contents stored in the database to each user through the user interface unit and receiving a preferred image input from each user to determine the preference of each user for at least one of character elements, non-character elements, and style elements a propensity analysis step of generating propensity data by analyzing; and
Further comprising a depiction element selection model generation step of generating a depiction element selection model for each user by performing learning of an artificial intelligence model based on the propensity data for each user,
The NFT-based digital art self-generating method, characterized in that the selection of the plurality of items in the description element selection step is performed based on a description element selection model learned for each user. According to claim 7,
Characterized in that it further comprises a non-fungible token generating step of generating a non-fungible token through a smart contract for the generated digital art, NFT-based digital art self-generating method.

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