Electronic device for generating drawing image using generative artificial intelligence model and operating method therefor

Abstract

According to one embodiment, an electronic device may comprise a display, at least one processor, and a memory for storing instructions. According to one embodiment, the instructions, when collectively or individually executed by the at least one processor, may instruct the electronic device to display, on the display, a first drawing image based on at least one drawing input. According to one embodiment, the instructions, when collectively or individually executed by the at least one processor, may instruct the electronic device to display, on the display, a plurality of objects including guide information for improving the first drawing image on the basis of analyzing the first drawing image. According to one embodiment, the instructions, when collectively or individually executed by the at least one processor, may instruct the electronic device to, on the basis of a first user input for selecting at least one guide object from among the plurality of objects, acquire stroke data for drawing, in a designated order, a second drawing image in which a plurality of strokes are added to the first drawing image on the basis of at least one piece of guide information included in the selected at least one object. According to one embodiment, the instructions, when collectively or individually executed by the at least one processor, may instruct the electronic device to display an image corresponding to the stroke data and the second drawing image together on the display.

Description

Electronic device for generating drawing images using a generative artificial intelligence model and method of operation thereof

[0001] The present disclosure relates to an electronic device that generates a drawing image using a generative artificial intelligence model and a method of operating the same.

[0002] Thanks to the remarkable advancements in information and communication technology and semiconductor technology, the distribution and use of various electronic devices are increasing rapidly. Electronic devices are being developed to allow users to carry them around and communicate. The term "electronic device" may refer to a device that performs specific functions according to an installed program, such as mobile communication terminals, tablet PCs, wearable electronic devices, video / audio devices, desktop / laptop computers, or vehicle navigation systems.

[0003] Electronic devices may utilize artificial intelligence (AI) models to provide services for specific purposes. For example, AI models are used in various fields such as content streaming, translation, photo editing, finance, new drug development, law, and the military. At least some of the various AI models for specific services may be implemented as generative AI models. Depending on the implementation, the AI ​​model may operate in a connected form.

[0004] According to one embodiment, the electronic device may include a display, at least one processor, and a memory for storing instructions. According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause a first drawing image based on at least one drawing input to be displayed on the display. According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause a plurality of objects containing guide information for improving the first drawing image based on analyzing the first drawing image to be displayed on the display. According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause stroke data to be acquired for drawing a second drawing image in a specified order, based on a first user input selecting at least one guide object among the plurality of objects, wherein a plurality of strokes are added to the first drawing image based on at least one guide information included in the selected at least one object. According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the display to display the image corresponding to the stroke data and the second drawing image together.

[0005] According to one embodiment, the method of operating an electronic device may include the operation of displaying a first drawing image based on at least one drawing input on a display included in the electronic device. According to one embodiment, the method of operating the electronic device may include the operation of displaying a plurality of objects on the display that include guide information for improving the first drawing image based on analyzing the first drawing image. According to one embodiment, the method of operating the electronic device may include the operation of acquiring stroke data for drawing a second drawing image in a specified order, based on a first user input selecting at least one object among the plurality of objects, wherein the first drawing image has a plurality of strokes added based on at least one guide information included in the selected at least one object. According to one embodiment, the method of operating the electronic device may include the operation of displaying an image corresponding to the stroke data and the second drawing image together on the display.

[0006] According to one embodiment, in a computer-readable non-transient storage medium for storing instructions, the instructions may cause an electronic device to display a first drawing image based on at least one drawing input on a display included in the electronic device, and based on analyzing the first drawing image, to display a plurality of objects including guide information for improving the first drawing image on the display, and based on a first user input selecting at least one object among the plurality of objects, to obtain stroke data for drawing a second drawing image in which a plurality of strokes are added based on at least one guide information included in the selected at least one object in a specified order, and to display an image corresponding to the stroke data and the second drawing image together on the display.

[0007] FIG. 1 is a block diagram of an electronic device in a network environment according to one embodiment.

[0008] FIG. 2 is a schematic block diagram of an electronic device according to one embodiment.

[0009] FIG. 3 is a block diagram showing a generative artificial intelligence model according to one embodiment.

[0010] FIG. 4 is a flowchart illustrating a method for an electronic device to generate a second drawing image from a first drawing image according to one embodiment.

[0011] FIG. 5 is a flowchart illustrating a method for an electronic device to acquire analysis information and guide information of a first drawing image according to one embodiment.

[0012] FIG. 6 is a diagram illustrating a method for an electronic device to obtain analysis information and guide information of a first drawing image using a first artificial intelligence model according to one embodiment.

[0013] FIG. 7a is a drawing of a first prompt for generating analysis information and guide information of a first drawing image according to one embodiment.

[0014] FIG. 7b is a drawing of analysis information and guide information of a first drawing image according to one embodiment.

[0015] FIG. 8a is a drawing showing a user interface for an electronic device to obtain guide information of a first drawing image according to one embodiment.

[0016] FIG. 8b is a drawing for explaining a method in which an electronic device, according to one embodiment, displays a plurality of texts including guide information of a first drawing image and generates a second drawing image based on at least one guide information selected among the guide information.

[0017] FIG. 9 is a flowchart illustrating a method for an electronic device to acquire stroke data related to a second drawing image according to one embodiment.

[0018] FIG. 10a is a diagram illustrating a method for an electronic device to acquire stroke data for an intermediate drawing image using a second artificial intelligence model according to one embodiment.

[0019] FIG. 10b is a drawing for explaining a method for an electronic device to acquire drawing pattern information according to one embodiment.

[0020] FIG. 11a is a drawing of a second prompt for generating stroke data associated with a second drawing image according to one embodiment.

[0021] FIG. 11b is a drawing of stroke data related to intermediate drawing images in a specified order according to one embodiment.

[0022] FIG. 12 is a flowchart illustrating a method for an electronic device to display a second drawing image according to one embodiment.

[0023] FIG. 13 is a flowchart illustrating a method for an electronic device to edit an intermediate drawing image according to one embodiment.

[0024] FIG. 14a is a drawing for illustrating a method in which an electronic device displays a second drawing image and at least one intermediate drawing image according to one embodiment.

[0025] FIG. 14b is a drawing for explaining a method of editing the stroke properties of at least one intermediate drawing image according to one embodiment.

[0026] FIG. 14c is a drawing for explaining how an electronic device displays a second drawing image according to one embodiment.

[0027] FIG. 14d is a drawing for explaining how an electronic device displays a second drawing image and an intermediate drawing image according to one embodiment.

[0028] FIG. 14e is a drawing for explaining how an electronic device edits a second drawing image according to one embodiment.

[0029] FIG. 15 is a flowchart illustrating a method for an electronic device to display a palette menu related to a first drawing image and a second drawing image, according to one embodiment.

[0030] FIG. 16 is a drawing for explaining how an electronic device displays a palette menu related to a second drawing image according to one embodiment.

[0031] FIG. 17 is a diagram illustrating a generative artificial intelligence system according to one embodiment.

[0032] FIG. 1 is a block diagram of an electronic device in a network environment according to one embodiment.

[0033] Referring to FIG. 1, in a network environment (100), an electronic device (101) may communicate with an electronic device (102) through a first network (198) (e.g., a short-range wireless communication network) or with at least one of an electronic device (104) or a server (108) through a second network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) through a server (108). According to one embodiment, the electronic device (101) may include a processor (120), memory (130), input module (150), sound output module (155), display module (160), audio module (170), sensor module (176), interface (177), connection terminal (178), haptic module (179), camera module (180), power management module (188), battery (189), communication module (190), subscriber identification module (196), or antenna module (197). In some embodiments, at least one of these components (e.g., connection terminal (178)) may be omitted from the electronic device (101), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (176), camera module (180), or antenna module (197)) may be integrated into a single component (e.g., display module (160)).

[0034] The processor (120) can control at least one other component (e.g., hardware or software component) of the electronic device (101) connected to the processor (120) by executing software (e.g., program (140)), for example, and can perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (120) can store commands or data received from other components (e.g., sensor module (176) or communication module (190)) in volatile memory (132), process the commands or data stored in volatile memory (132), and store the resulting data in non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., central processing unit or application processor) or an auxiliary processor (123) that can operate independently or together with it (e.g., graphics processing unit, neural processing unit (NPU), image signal processor, sensor hub processor, or communication processor). For example, if the electronic device (101) includes a main processor (121) and an auxiliary processor (123), the auxiliary processor (123) may be configured to use less power than the main processor (121) or to be specialized for a designated function. The auxiliary processor (123) may be implemented separately from the main processor (121) or as part thereof.

[0035] The auxiliary processor (123) may control at least some of the functions or states associated with at least one component of the electronic device (101) (e.g., display module (160), sensor module (176), or communication module (190)) on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (123) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (180) or communication module (190)). According to one embodiment, the auxiliary processor (123) (e.g., neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (101) itself where the artificial intelligence model is executed, or through a separate server (e.g., server (108)). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model may include a plurality of artificial neural network layers.An artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to the hardware structure, the artificial intelligence model may include a software structure, either additionally or substantially.

[0036] The memory (130) can store various data used by at least one component of the electronic device (101) (e.g., processor (120) or sensor module (176)). The data may include, for example, software (e.g., program (140)) and input data or output data for related commands. The memory (130) may include volatile memory (132) or non-volatile memory (134).

[0037] The program (140) may be stored as software in memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0038] The input module (150) can receive commands or data to be used for a component of the electronic device (101) (e.g., processor (120)) from outside the electronic device (101) (e.g., user). The input module (150) may include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0039] The sound output module (155) can output a sound signal to the outside of the electronic device (101). The sound output module (155) may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as multimedia playback or recording playback. The receiver may be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from the speaker or as part thereof.

[0040] The display module (160) can visually provide information to an external (e.g., user) of the electronic device (101). The display module (160) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling said device. According to one embodiment, the display module (160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of the force generated by said touch.

[0041] The audio module (170) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150) or output sound through the sound output module (155) or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (101).

[0042] The sensor module (176) can detect the operating state of the electronic device (101) (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the detected state. According to one embodiment, the sensor module (176) may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0043] The interface (177) may support one or more specified protocols that can be used for the electronic device (101) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (102)). According to one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0044] The connection terminal (178) may include a connector through which the electronic device (101) can be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0045] The haptic module (179) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that the user can perceive through tactile or kinesthetic senses. According to one embodiment, the haptic module (179) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0046] The camera module (180) can capture still images and video. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0047] The power management module (188) can manage the power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0048] The battery (189) can supply power to at least one component of the electronic device (101). According to one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0049] The communication module (190) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may include one or more communication processors that operate independently of the processor (120) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (194) (e.g., LAN (local area network) communication module, or power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device (104) through a first network (198) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (199) (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (192) can identify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (196).

[0050] The wireless communication module (192) can support 5G networks and next-generation communication technologies following 4G networks, for example, new radio access technology. NR access technology can support high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and connection of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low-latency communications (URLLC)). The wireless communication module (192) can support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (192) can support various technologies for securing performance in the high-frequency band, such as beamforming, massive MIMO (multiple-input and multiple-output), full-dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large-scale antenna. The wireless communication module (192) can support various requirements specified in the electronic device (101), external electronic device (e.g., electronic device (104)), or network system (e.g., second network (199)). According to one embodiment, the wireless communication module (192) can support a Peak data rate (e.g., 20 Gbps or more) for realizing eMBB, loss coverage (e.g., 164 dB or less) for realizing mMTC, or U-plane latency (e.g., downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) for realizing URLLC.

[0051] An antenna module (197) can transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (197) may include an antenna comprising a radiator made of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as a first network (198) or a second network (199), may be selected from the plurality of antennas, for example, by a communication module (190). A signal or power may be transmitted or received between the communication module (190) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as part of the antenna module (197).

[0052] According to various embodiments, the antenna module (197) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., bottom surface) of the printed circuit board and capable of supporting a specified high frequency band (e.g., mmWave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a second surface (e.g., top surface or side surface) of the printed circuit board and capable of transmitting or receiving a signal of the specified high frequency band.

[0053] At least some of the above components can be connected to each other via a communication method between peripheral devices (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and exchange signals (e.g., commands or data) with each other.

[0054] According to one embodiment, commands or data may be transmitted or received between the electronic device (101) and an external electronic device (104) through a server (108) connected to a second network (199). Each of the external electronic devices (102, or 104) may be the same or different type of device as the electronic device (101). According to one embodiment, all or part of the operations performed on the electronic device (101) may be performed on one or more of the external electronic devices (102, 104, or 108). For example, if the electronic device (101) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (101) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least part of the requested function or service, or additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may provide the result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (101) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device (104) or the server (108) may be included within a second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0055] Functions related to artificial intelligence according to the present disclosure are operated through a processor and memory. The processor may be composed of one or more processors. In this case, the one or more processors may be general-purpose processors such as a CPU (central processing unit), AP (application processor), or DSP (digital signal processor), graphics-dedicated processors such as a GPU (graphic processing unit) or VPU (vision processing unit), or artificial intelligence-dedicated processors such as an NPU. The one or more processors control the processing of input data according to predefined operation rules or artificial intelligence models stored in memory. Alternatively, if the one or more processors are artificial intelligence-dedicated processors, the artificial intelligence-dedicated processors may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

[0056] The predefined rules of operation or artificial intelligence models are characterized by being created through learning. Here, being created through learning means that a predefined rules of operation or artificial intelligence models configured to perform a desired characteristic (or objective) are created by a basic artificial intelligence model being trained using multiple learning data by a learning algorithm. Such learning may be performed on the device itself where the artificial intelligence according to the present disclosure is executed, or it may be performed through a separate server and / or system. Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the examples described above.

[0057] An artificial intelligence model may be composed of multiple neural network layers. Each of the multiple neural network layers has multiple weight values ​​and performs neural network operations through operations between the results of previous layers and the multiple weights. The multiple weights possessed by the multiple neural network layers can be optimized based on the learning results of the artificial intelligence model. For example, the multiple weights may be updated so that the loss value or cost value obtained by the artificial intelligence model during the learning process is reduced or minimized. The artificial neural network may include a deep neural network (DNN), and examples include, but are not limited to, convolutional neural networks (CNN), deep neural networks (DNN), recurrent neural networks (RNN), restricted Boltzmann machines (RBM), deep belief networks (DBN), bidirectional recurrent deep neural networks (BRDNN), or deep Q-networks.

[0058] FIG. 2 is a schematic block diagram of an electronic device according to one embodiment.

[0059] Referring to FIG. 2, an electronic device (201) according to one embodiment may include a processor (220), a memory (230), a display (260), and a communication circuit (290). For example, the electronic device (201) may be implemented in the same or similar manner as the electronic device (101) of FIG. 1.

[0060] According to one embodiment, the processor (220) can control the overall operation of the electronic device (201). For example, the processor (220) may be implemented identically or similarly to the processor (120) of FIG. 1. According to one embodiment, the processor (220) can control at least one other component (e.g., hardware or software component) of the electronic device (201) connected to the processor (220) by executing software (e.g., program (140) of FIG. 1), and can perform data processing or operations based on instructions. According to one embodiment, the instructions may include instructions composed of machine language that can be processed by the electronic device (201) or the processor (220). For example, the instructions may include instructions corresponding to operation instructions used in the program.

[0061] Meanwhile, although FIG. 2 illustrates that the electronic device (201) includes one processor (220), this is exemplary and the technical concept of the present invention may not be limited thereto. For example, the electronic device (201) may include at least one processor. For example, the processor (220) may be implemented as at least one processor.

[0062] According to one embodiment, the memory (230) (e.g., the memory (130) of FIG. 1) may store at least one instruction (or instruction) that causes at least one operation of the electronic device (201). When executed by the processor (220), the at least one instruction may cause the electronic device (201) to perform the corresponding operation.

[0063] According to one embodiment, the memory (230) may store data of the electronic device (201). For example, the data may include data about content, and the content may include text, voice, images, and / or video. For example, the content may include an image including strokes drawn by a user (or a stylus pen). Alternatively, the content may include an image received from an external electronic device (e.g., an image including a plurality of strokes).

[0064] According to one embodiment, the generative AI model may be stored in memory (230). Alternatively, the generative AI model may be stored in an external electronic device (e.g., a server). For example, the processor (220) may use the generative AI model to generate or obtain content (e.g., a drawing image) based on a prompt. For example, the prompt may include a command (e.g., text) for generating new content (e.g., a drawing image) or for modifying, changing, editing, and / or adding at least one element or at least one object included in existing content (e.g., a drawing image). For example, the prompt may include text (or a command in the form of text) that the generative AI model can recognize.

[0065] According to one embodiment, the processor (220) may display a first drawing image based on at least one drawing input on the display (260). For example, the processor (220) may execute a drawing application and display the execution screen of the drawing application on the display (260). The processor (220) may verify the drawing input based on user input (e.g., touch by hand or touch by stylus) for the execution screen of the drawing application displayed on the display (260) (or touchscreen). For example, the first drawing image may include strokes corresponding to the drawing input. For example, the strokes may have various attributes (e.g., shape and / or length) depending on the pressure, speed, and / or type of the user input. For example, the first drawing image may include an image drawn by user input. For example, the first drawing image may include an image drawn by a user of the electronic device (201). Alternatively, the first drawing image may include an image received from an external electronic device (e.g., the electronic device (102) of FIG. 1) through a communication circuit (290).

[0066] According to one embodiment, the processor (220) may generate guide information for improving the first drawing image based on user input requesting a guide (or advice, tip) for improving the first drawing image. For example, the processor (220) may analyze the first drawing image in response to the user input. Based on the analysis of the first drawing image, the processor (220) may display a plurality of texts containing guide information for improving the first drawing image on the display (260). Additionally, based on the analysis of the first drawing image, the processor (220) may display analysis information of the first drawing image on the display (260).

[0067] According to one embodiment, the processor (220) can obtain analysis information and guide information of a first drawing image using a first artificial intelligence model. At this time, the processor (220) can generate a prompt for obtaining analysis information and guide information of the first drawing image. The processor (220) can obtain analysis information and guide information of the first drawing image based on providing the prompt to the first artificial intelligence model. For example, the first artificial intelligence model may include a model trained to output analysis information and guide information for improving the drawing image based on analyzing the drawing image.

[0068] According to one embodiment, the processor (220) can confirm a first user input selecting at least one guide information among a plurality of texts (e.g., texts containing guide information) displayed on the display (260). Based on the first user input, the processor (220) can obtain stroke data for drawing a second drawing image in a specified order, wherein the first drawing image is modified based on at least one guide information. For example, the second drawing image may represent an image additionally drawn based on at least one guide information of the first drawing image.

[0069] According to one embodiment, the processor (220) can obtain stroke data for drawing from a first drawing image to a second drawing image in a specified order using a second artificial intelligence model. For example, the processor (220) can obtain stroke data corresponding to each order for drawing the second drawing image using a second artificial intelligence model. At this time, the processor (220) can generate a prompt for obtaining stroke data corresponding to each order. The processor (220) can obtain stroke data corresponding to each order based on providing the prompt to the second artificial intelligence model. For example, the processor (220) can obtain stroke data that reflects the user's drawing pattern information by further providing the user's drawing pattern information to the second artificial intelligence model. For example, the drawing pattern information may include at least one of the user's drawing habit, order, pattern, or stroke attribute (or characteristic). For example, stroke attributes (or characteristics) may include at least one of the input order, type, texture (e.g., brush type), length, color, transparency (or opacity), texture, pen pressure, or number of strokes. For example, the second AI model may include a model trained to output an image that is additionally drawn according to a specified order (or a specified number of steps) of a previously drawn image. For example, the second AI model may learn the user's drawing habits. For example, the second AI model may learn the user's preferred drawing order pattern (e.g., whether to color after completing the sketch, whether to draw objects first or the background first, whether to draw the central object first and then the rest, whether to draw the center part first or the entire part simultaneously), the user's preferred brush type, the user's preferred brightness / saturation / color, the user's preferred opacity, and / or the user's preferred stroke length.Through this, the second artificial intelligence model can be trained to output an image preferred by the user.

[0070] According to one embodiment, the processor (220) may generate an intermediate drawing image corresponding to each sequence based on stroke data for each sequence. Alternatively, the processor (220) may receive or acquire a second drawing image and / or each intermediate drawing image corresponding to each sequence from an external electronic device (e.g., an external server where an artificial intelligence model is stored). In this case, the processor (220) may transmit a prompt for the second drawing image and / or intermediate drawing image to the external electronic device via a communication circuit (290) and receive the second drawing image and / or intermediate drawing image as at least part of the response to the prompt. Depending on the implementation, the processor (220) may receive or acquire an intermediate drawing image corresponding to some sequence from an external electronic device (e.g., an external server where an artificial intelligence model is stored).

[0071] According to one embodiment, the processor (220) may display at least one intermediate drawing image corresponding to a specified order based on stroke data for each order. For example, the processor (220) may arrange at least one intermediate drawing image according to a specified order. The processor (220) may change the order of at least one intermediate drawing image by changing the arrangement of at least one intermediate drawing image. Alternatively, the processor (220) may adjust or edit stroke attributes for each of at least one intermediate drawing image.

[0072] According to one embodiment, the processor (220) can generate a second drawing image based on acquired stroke data. The processor (220) can display the second drawing image on a display (260). The processor (220) can display the second drawing image by sequentially overlapping at least one intermediate drawing image over the first drawing image. Depending on the implementation, the processor (220) may display a screen (e.g., a slideshow screen) that sequentially overlaps at least one intermediate drawing image over the first drawing image.

[0073] FIG. 3 is a block diagram showing a generative artificial intelligence model according to one embodiment.

[0074] Referring to FIG. 3, according to one embodiment, a generative artificial intelligence (AI) model (320) may include a first AI model (330), an image generation model (340), and a palette generation model (370).

[0075] According to one embodiment, the generative AI model (320) may be stored in memory (230). Alternatively, at least a portion of the generative AI model (320) may be stored in an external electronic device (e.g., a server).

[0076] According to one embodiment, the first AI model (330) may include a model trained to generate or output analysis information (or analysis result) of a drawing image and guide information for improving the drawing image based on analyzing a drawing image. For example, a processor (e.g., the processor (220) of FIG. 2) may use the first AI model (330) to obtain at least one of the analysis information (or analysis result) of a first drawing image or guide information including strokes corresponding to a drawing input.

[0077] According to one embodiment, the image generation model (340) may include a model trained to generate or output a second drawing image by additionally drawing a first drawing image in a specified order based on at least one guide information selected by user input.

[0078] According to one embodiment, the image generation model (340) may include a second AI model (350) and a drawing pattern inference model (360).

[0079] According to one embodiment, the second AI model (350) may include a model trained to output data for strokes (hereinafter, stroke data) for additionally drawing a first drawing image including strokes according to a specified order (or a specified number of steps) based on at least one guide information selected by user input. For example, the second AI model (350) may generate or output stroke data corresponding to each order (or each step). For example, the second AI model (350) may determine a specific number of order or steps to additionally draw the first drawing image according to a specified order (or a specified number of steps). The second AI model (350) may generate or output stroke data for strokes drawn at each step.

[0080] According to one embodiment, a drawing pattern inference model (360) can generate or output information about a user's drawing pattern (hereinafter, drawing pattern information). The drawing pattern inference model can analyze drawing images drawn by user input and extract, generate, or output drawing pattern information based on the analysis results. When a drawing image newly drawn through a drawing application is identified, the electronic device (201) can analyze the drawing image to further learn or update the user's drawing pattern information. For example, the drawing pattern information may include at least one of the user's drawing habits, sequence, pattern, or stroke attributes (or characteristics). For example, the stroke attributes may include at least one of the stroke input sequence, type, location (e.g., coordinate information), color, transparency, texture, pen pressure, layer, context, or number. For example, the drawing pattern information may include pattern information regarding the order and texture of strokes used when the user draws an object. Additionally, the drawing pattern information may include pattern information regarding how much pressure and / or length strokes are used to draw a corresponding object when the user draws an object. Based on the method described above, the drawing pattern inference model (360) can be learned or updated as a model personalized to the user of the electronic device (201).

[0081] According to one embodiment, the second AI model (350) may acquire stroke data for each sequence or each step by further considering the user's drawing pattern information output from the drawing pattern inference model (360). For example, when the drawing pattern information includes information for drawing a specific object using a large number of short strokes, the second AI model (350) may output or generate stroke data based on short lengths and a large number of strokes. Additionally, when the drawing pattern information includes information for drawing a specific object from its external shape, the second AI model (350) may output or generate stroke data for drawing from its external shape.

[0082] According to one embodiment, the image generation model (340) can generate a second drawing image based on stroke data for strokes drawn at each step.

[0083] According to one embodiment, the palette generation model (370) may include a model trained to output information (hereinafter, palette menu) about colors added to the second drawing image based on analyzing the second drawing image. For example, a processor (e.g., the processor (220) of FIG. 2) may obtain a palette menu for the second drawing image using the palette generation model (370) based on user input requesting to use the second drawing image as a reference image. The processor (220) may display a palette menu including colors added to the second drawing image so that the user can directly draw the first drawing image as the second drawing image.

[0084] Based on the method described above, the electronic device (201) can provide a second drawing image additionally drawn based on guide information, based on a first drawing image drawn by the user. By providing the second drawing image, the electronic device (201) can enable the user to edit, save, and utilize the second drawing image in various ways.

[0085] For convenience of explanation, the following description will focus on the method by which the electronic device (201) obtains stroke data for drawing a second drawing image based on a first drawing image when the generative AI model is stored in memory (230). However, the technical concept of the present invention is not limited thereto, and the electronic device (201) may perform at least some of the operations of obtaining stroke data through an external electronic device (e.g., a server) according to the same or similar method. For example, when the generative AI model is stored in an external electronic device (e.g., a server), the electronic device (201) may transmit a first prompt through a communication circuit (e.g., the communication circuit (290) of FIG. 2) and receive analysis information and guide information based on the first prompt. Additionally, the electronic device (201) may transmit a second prompt through a communication circuit (e.g., the communication circuit (290) of FIG. 2) and receive stroke data based on the second prompt.

[0086] At least some of the operations of the electronic device (201) described below may be performed by the processor (220). However, for the convenience of explanation, the operations will be described as being performed by the electronic device (201).

[0087] FIG. 4 is a flowchart illustrating a method for an electronic device to generate a second drawing image from a first drawing image according to one embodiment.

[0088] Referring to FIG. 4, according to one embodiment, in operation 401, an electronic device (e.g., the electronic device (201) of FIG. 2) may display a first drawing image based on at least one drawing input. For example, the first drawing image may include a plurality of drawing strokes (or drawing stroke inputs). For example, the electronic device (201) may display the first drawing image on the execution screen of a drawing application.

[0089] According to one embodiment, in operation 403, the electronic device (201) may display a plurality of objects (or texts) containing guide information for improving the first drawing image based on analyzing the first drawing image. For example, the plurality of objects may include at least one of an icon, an image, text, a choice, or a video. Additionally, the electronic device (201) may also display an object (or text) containing analysis information of the first drawing image based on analyzing the first drawing image. For example, the electronic device (201) may display objects (e.g., texts) containing analysis information and guide information using a first artificial intelligence model (e.g., the first AI model (330) of FIG. 3). For example, the electronic device (201) may display objects (or texts) containing analysis information and guide information of the first drawing image on the execution screen of the drawing application based on executing a guide providing function (or tip providing function) provided by the drawing application. For example, the electronic device (201) can generate and display different guide information (or tip information) for each user based on the history of previous drawings (or stroke input history) of the user identified according to the user's identification information (e.g., ID). That is, the electronic device (201) can display a plurality of objects (or texts) including guide information that takes into account the user's drawing habits or patterns, based on analyzing a first drawing image and a user drawing pattern.

[0090] According to one embodiment, in operation 405, the electronic device (201) may acquire stroke data for drawing a second drawing image in a specified order based on at least one guide information included in at least one object among a plurality of objects including guide information, based on a first user input selecting at least one object. The second drawing image may represent a drawing image in which a plurality of strokes are added to the first drawing image based on at least one guide information. For example, the electronic device (201) may acquire stroke data for drawing the second drawing image in a specified order using a second artificial intelligence model (e.g., the second AI model (350) of FIG. 3).

[0091] According to one embodiment, in operation 407, the electronic device (201) may display at least one image (e.g., an intermediate drawing image) corresponding to stroke data and a second drawing image together. For example, the electronic device (201) may display at least one intermediate drawing image and / or a second drawing image based on stroke data. For example, the electronic device (201) may display at least one intermediate drawing image distinct from the second drawing image. For example, at least one intermediate drawing image may be displayed as a thumbnail image. The electronic device (201) may display the second drawing image overlaid on the first drawing image in response to a user input requesting to add the second drawing image over the first drawing image. Alternatively, the electronic device (201) may display the second drawing image while sequentially overlapping at least one intermediate drawing image over the first drawing image in response to the user input. Alternatively, the electronic device (201) may display the first drawing image and the second drawing image together in response to a user input requesting to use the second drawing image as a reference image. At this time, the electronic device (201) may display a palette menu indicating the colors used to draw the second drawing image.

[0092] According to one embodiment, the electronic device (201) may display each intermediate drawing image corresponding to each step of drawing from a first drawing image to a second drawing image based on stroke data for each sequence or each step. At this time, the electronic device (201) may perform an operation of editing each intermediate drawing image corresponding to each step based on user input. For example, the electronic device (201) may perform an operation of editing the sequence of each intermediate drawing image or the attributes of the stroke included in each intermediate drawing image based on user input.

[0093] Based on the method described above, the electronic device (201) can provide a second drawing image additionally drawn based on guide information, based on a first drawing image drawn by the user. By providing the second drawing image, the electronic device (201) can enable the user to edit, save, and utilize the second drawing image in various ways.

[0094] FIG. 5 is a flowchart illustrating a method for an electronic device to acquire analysis information and guide information of a first drawing image according to one embodiment.

[0095] Referring to FIG. 5, according to one embodiment, in operation 501, an electronic device (e.g., the electronic device (201) of FIG. 2) may generate first data for analyzing a first drawing image and generating guide information for the first drawing image based on user input (e.g., user input requesting to execute a guide providing function (or tip providing function)). For example, the first data may include a first prompt requesting (or commanding) the analysis of the first drawing image and the generation of guide information for the first drawing image. For example, the first prompt may be provided to a first artificial intelligence model (330) and may include texts that the first artificial intelligence model (330) can understand.

[0096] According to one embodiment, in operation 503, the electronic device (201) can obtain analysis information and guide information of the first drawing image based on the first data (e.g., the first prompt). For example, the electronic device (201) can obtain analysis information and guide information of the first drawing image based on providing the first drawing image and the first data (e.g., the first prompt) to the first artificial intelligence model (330). For example, the electronic device (201) can display texts including analysis information and guide information of the first drawing image on the execution screen of the drawing application.

[0097] FIG. 6 is a diagram illustrating a method for an electronic device to obtain analysis information and guide information of a first drawing image using a first artificial intelligence model according to one embodiment. FIG. 7a is a diagram of a first prompt for generating analysis information and guide information of a first drawing image according to one embodiment. FIG. 7b is a diagram of analysis information and guide information of a first drawing image according to one embodiment.

[0098] Referring to FIGS. 6 and FIGS. 7a, according to one embodiment, an electronic device (e.g., the electronic device (201) of FIG. 2) may provide a first drawing image and a first prompt (710) to a first AI model (330) based on user input (e.g., user input requesting the execution of a guide providing function (or a tip providing function). For example, the first drawing image may be provided by converting it into a bitmap. For example, referring to FIG. 7a, the first prompt (710) may include texts requesting (or commanding) the analysis of the first drawing image and the generation of guide information for the first drawing image. For example, the first prompt (710) may include content regarding the format of the requested analysis information (e.g., a JSON array). Additionally, the first prompt (710) may include content regarding the content included in the guide information (e.g., elements, colors, shapes, textures, locations, and relationships between objects) and the number (e.g., three pieces of advice).

[0099] Referring to FIGS. 6 and FIGS. 7b, according to one embodiment, an electronic device (201) can obtain analysis information (720) and guide information (730, 740, 750) of a first drawing image using a first AI model (330). For example, the analysis information (720) and guide information (730, 740, 750) may be generated based on attributes (or characteristics) of strokes included in the first drawing image. For example, referring to FIG. 7b, the analysis information (720) may include text describing the analysis results of the first drawing image. For example, the analysis information (720) may include various forms of visual content (e.g., images, videos, icons, and / or options) representing the analysis results of the first drawing image in addition to text. Guide information (730, 740, 750) may include multiple texts describing tips (or advice) for improving the first drawing image. For example, in addition to text, guide information (730, 740, 750) may include various forms of visual objects (e.g., images, videos, icons, and / or options) indicating methods for improving the first drawing image. For example, the number of guide information (730, 740, 750) may correspond to the number of tips requested in the first prompt (710). For example, analysis information (720) may include content regarding the results of analyzing the first drawing image (e.g., line details, object shapes, overall atmosphere). Guide information (730, 740, 750) may include guides or advice for different categories (e.g., color diversification, detail addition and texture expression, and detailed detail addition). Depending on the implementation, the electronic device (201) may also display summary information summarizing the guide information (730, 740, 750) together with the guide information (730, 740, 750).

[0100] Meanwhile, the first prompt (710), analysis information (720), and guide information (730, 740, 750) illustrated in FIGS. 7a and 7b are exemplary, and the technical features of the present invention may not be limited thereto.

[0101] FIG. 8a is a drawing showing a user interface for an electronic device to obtain guide information of a first drawing image according to one embodiment. FIG. 8b is a drawing explaining a method for an electronic device according to one embodiment to display a plurality of texts including guide information of a first drawing image and to generate a second drawing image based on at least one guide information selected among the guide information.

[0102] Referring to FIG. 8a, according to one embodiment, an electronic device (e.g., the electronic device (201) of FIG. 2) can display a first drawing image (820) on an execution screen (810) of a drawing application. For example, the first drawing image (820) may include strokes. For example, at least some of the strokes may be generated by a user's drawing input (e.g., touch by the user's hand and / or touch by a stylus pen). For example, the first drawing image (820) may include an image representing the appearance of a puppy.

[0103] According to one embodiment, the electronic device (201) may display a menu window (830) based on user input for an execution screen (810). For example, the menu window (830) may include objects for executing various functions. For example, among the objects, a first object (840) may be an object for a function of obtaining drawing advice. The electronic device (201) may start and perform an operation of analyzing a first drawing image (820) based on confirming a first user input for the first object (840).

[0104] Referring to FIG. 8b, according to one embodiment, an electronic device (201) may display a screen (850) for drawing advice based on analyzing a first drawing image (820). The screen (850) for drawing advice may include analysis information (860) of the first drawing image (820), first guide information (871), second guide information (872), and third guide information (873). Texts included in the analysis information (860), first guide information (871), second guide information (872), and third guide information (873) may be generated based on analyzing the first drawing image (820). For example, the electronic device (201) can obtain texts included in analysis information (860), first guide information (871), second guide information (872), and third guide information (873) by using a first artificial intelligence model (e.g., the first AI model (330) of FIG. 3). For example, the guide information (871, 872, 873) may include various forms of visual content (e.g., images, videos, icons, and / or options) indicating methods for improving the first drawing image in addition to text.

[0105] According to one embodiment, the guide information (871, 872, and 873) may each include objects (876, 877, and 888) that allow for a schematic view of the result according to the corresponding advice. When user input (e.g., touch input) for the object (876, 877, or 888) is detected, the electronic device (201) may acquire and display a drawing image (or a drawing image in which a drawing corresponding to the advice is added to a pre-specified sample image) in which a drawing corresponding to the advice is added to a first drawing image (820). By doing so, the electronic device (201) may provide a function that allows the user to intuitively view a schematic drawing image reflecting the corresponding advice.

[0106] According to one embodiment, the electronic device (201) can detect user input selecting at least one guide information (871 and / or 872) among the first guide information (871), the second guide information (872), and the third guide information (873). The electronic device (201) can display the selected at least one guide information (871 and / or 872) so as to be visually distinguishable (e.g., by color). When at least one guide information (871 and / or 872) is selected, the electronic device (201) can activate a second object (880) for generating a new drawing image.

[0107] According to one embodiment, the electronic device (201) may initiate an operation to generate a second drawing image (890) by additionally drawing the first drawing image (820) based on at least one guide information (871 and / or 872) in response to confirming user input for the second object (880). To this end, the electronic device (201) may acquire stroke data for drawing the second drawing image (890) based on a specified order. For example, the total stroke data may include each stroke data corresponding to each order or each step. The electronic device (201) may display the second drawing image (890) based on each stroke data corresponding to each order or each step. For example, the second drawing image (890) may include an image in which details (e.g., eyes, nose, mouth, ears, fur, and color) are added to the appearance of the puppy included in the first drawing image (820).

[0108] According to one embodiment, the electronic device (201) may further display, together with the second drawing image (890), an object (891) for adding to a layer, an object (892) for stroke editing, and an object (893) for adding to a reference image.

[0109] According to one embodiment, the electronic device (201) may display a second drawing image (890) on the first drawing image (820) based on confirming user input for an object (891) to be added to the layer. Alternatively, the electronic device (201) may display the second drawing image (890) instead of the first drawing image (820) based on confirming user input for an object (891) to be added to the layer.

[0110] According to one embodiment, the electronic device (201) may display intermediate drawing images based on each stroke data corresponding to each sequence or each step, based on confirming user input for an object (892) for stroke editing. For example, the intermediate drawing images may include images additionally drawn on the first drawing image (820) according to each step. After the intermediate drawing images are displayed, the electronic device (201) may perform an operation to edit the sequence of each intermediate drawing image based on additional user input. Additionally, the electronic device (201) may perform an operation to edit the attributes of the strokes included in each intermediate drawing image based on additional user input.

[0111] According to one embodiment, the electronic device (201) may display a second drawing image (890) together with a first drawing image (820) based on confirming user input for an object (893) to be added to a reference image. At this time, the electronic device (201) may display a palette menu indicating colors added to the second drawing image (890).

[0112] A detailed description of the above-described operation will be explained in more detail in the drawings below.

[0113] FIG. 9 is a flowchart illustrating a method for an electronic device to acquire stroke data related to a second drawing image according to one embodiment.

[0114] Referring to FIG. 9, according to one embodiment, an electronic device (e.g., the electronic device (201) of FIG. 2) may start an operation to acquire stroke data for strokes to be further added to the first drawing image in response to confirming user input to generate a new second drawing image based on the first drawing image.

[0115] According to one embodiment, in operation 901, the electronic device (201) can verify the user's drawing pattern information. For example, the electronic device (201) can obtain the user's drawing pattern information by considering history information regarding the user's drawing image. For example, the electronic device (201) can obtain the user's drawing pattern information by using a pattern information extraction model (e.g., the pattern inference model (360) of FIG. 3).

[0116] According to one embodiment, in operation 903, the electronic device (201) may generate second data related to stroke generation for drawing a second drawing image according to a specified order (or specified steps) based on at least one guide information and drawing pattern information selected by the user. For example, the second data may include a second prompt requesting (or commanding) the generation of strokes for each order (or each step) to draw the second drawing image according to a specified order (or specified steps). For example, the second prompt may be provided to a second artificial intelligence model (350) and may include texts that the second artificial intelligence model (350) can understand.

[0117] According to one embodiment, in operation 905, the electronic device (201) can obtain stroke data for each sequence (or each step) based on the second data.

[0118] FIG. 10a is a diagram illustrating a method for an electronic device to acquire stroke data for an intermediate drawing image using a second artificial intelligence model according to one embodiment. FIG. 10b is a diagram illustrating a method for an electronic device to acquire drawing pattern information according to one embodiment. FIG. 11a is a diagram of a second prompt for generating stroke data related to a second drawing image according to one embodiment. FIG. 11b is a diagram of stroke data related to intermediate drawing images according to a specified order according to one embodiment.

[0119] Referring to FIGS. 10a and FIGS. 11a, according to one embodiment, an electronic device (e.g., the electronic device (201) of FIG. 2) may provide a first drawing image and a second prompt (1101) to a second AI model (350) based on user input (e.g., user input requesting the creation of a second drawing image). For example, the first drawing image may be provided by converting it into a bitmap. For example, referring to FIG. 11a, the second prompt (1101) may include text requesting (or commanding) the creation of strokes for each step to draw the second drawing image. For example, the second prompt (1101) may include text that considers the type of strokes for each step (e.g., line, curve, fill), the position, color, opacity, texture, pressure, the number of the corresponding step (or sequence), and the degree of relevance related to applied guide information (or tips). Additionally, the second prompt (1101) may include at least one guide information (or information about tips) selected by the user in a designated space (1105).

[0120] According to one embodiment, the electronic device (201) may further provide user drawing pattern information to the second AI model (350). Through this, the electronic device (201) may obtain stroke data capable of generating a stroke that takes into account the user's drawing pattern. For example, referring to FIG. 10b, the electronic device (201) may obtain the first drawing pattern as drawing pattern information when the user draws a picture as in the first image (1030). For example, the electronic device (201) may obtain the second image (1040) based on providing the first drawing pattern to the second AI model (350). For example, the second image (1040) may include an image drawn based on a pattern of drawing short strokes with many strokes. For example, the second image (1040) may include an image with complex texture and rich color based on a pattern of drawing short strokes with many strokes. Additionally, the electronic device (201) can acquire a second drawing pattern as drawing pattern information when the user draws a picture as in the third image (1050). For example, the electronic device (201) can acquire a fourth image (1060) based on providing the second drawing pattern to the second artificial intelligence model (350). For example, the fourth image (1060) may include an image drawn based on a pattern of drawing long strokes with a small number of strokes. For example, the fourth image (1060) may include an image with a soft and concise texture and bright and transparent colors based on a pattern of drawing long strokes with a small number of strokes. For example, the electronic device (201) can extract a first drawing pattern or a second drawing pattern using a drawing pattern inference model (e.g., the drawing pattern inference model of FIG. 3).

[0121] According to one embodiment, the drawing pattern information may include various information regarding the user's drawing habits in addition to the drawing pattern information described above. For example, when the drawing order preferred by the user is to color in after the sketch, such information may also be included in the drawing pattern information. By providing the drawing pattern information including the above drawing order to the second AI model (350), the electronic device (201) can obtain stroke data that takes into account the user's drawing order.

[0122] Referring to FIG. 10a and FIG. 11b, according to one embodiment, an electronic device (201) can acquire stroke data (e.g., 1115, 1125, 1135) for step-by-step intermediate drawing images using a second AI model (350). For example, the electronic device (201) can specify (or determine) the number of steps based on the complexity of the drawing (e.g., complexity is determined based on the number of strokes and / or detail information). For example, each step can be divided into appropriate points based on the total drawing time. Or, each step can be specified (or determined) based on the key frame (or main object) being drawn.

[0123] According to one embodiment, the electronic device (201) can acquire stroke data corresponding to designated sequences or designated steps (e.g., sequence 1, sequence 2, sequence 3, sequence 4, sequence 5, and sequence 6). For example, the electronic device (201) can acquire stroke data separated by each step. For example, the electronic device (201) can acquire first stroke data (1115) corresponding to sequence 1. The first stroke data (1115) may be data for strokes for drawing a first intermediate drawing image (1110). For example, the electronic device (201) can acquire second stroke data (1125) corresponding to sequence 2. The second stroke data (1125) may be data for strokes for drawing a second intermediate drawing image (1120). For example, the electronic device (201) can acquire third stroke data (1135) corresponding to sequence 3. The third stroke data (1135) may be data for strokes for drawing a third intermediate drawing image (1113). Likewise, the electronic device (201) can acquire stroke data for intermediate drawing images (1140, 1150, 1160) corresponding to intermediate steps until the second drawing image is completed.

[0124] According to one embodiment, the electronic device (201) can acquire stroke data for newly added strokes based on information regarding strokes included in the first drawing image (e.g., outline, color distribution, stroke pattern). The electronic device (201) can determine a starting point based on information regarding strokes included in the first drawing image. Subsequently, the electronic device (201) can extract key features of the first drawing image by considering at least one guide information selected by the user using the second artificial intelligence model (350). The extracted features can be transmitted as parameters for generating stroke data. The electronic device (201) can acquire stroke data for strokes added at each step by providing the parameters to the second artificial intelligence model (350).

[0125] According to one embodiment, the electronic device (201) can generate and display a second drawing image or at least one intermediate drawing image using stroke data for each step.

[0126] According to one embodiment, the electronic device (201) can display each intermediate drawing image on a separate layer. By doing so, the electronic device (201) can display a second drawing image by overlapping the intermediate drawing images displayed on each layer onto the first drawing image.

[0127] Meanwhile, the second prompt (1101) and stroke data (1115, 1125, 1135) illustrated in FIG. 11a and FIG. 11b are exemplary and the technical features of the present invention may not be limited thereto.

[0128] FIG. 12 is a flowchart illustrating a method for an electronic device to display a second drawing image according to one embodiment. FIG. 14c is a diagram illustrating a method for an electronic device to display a second drawing image according to one embodiment.

[0129] Referring to FIG. 12, according to one embodiment, in operation 1201, an electronic device (e.g., the electronic device (201) of FIG. 2) can detect user input to add a second drawing image to a layer for a first drawing image.

[0130] According to one embodiment, in operation 1203, the electronic device (201) may sequentially overlap at least one intermediate drawing image on the first drawing image in a specified order. In operation 1205, the second drawing image may be displayed by overlapping at least one intermediate drawing image on the first drawing image. Additionally, the electronic device (201) may further display a first thumbnail image representing the existing first drawing image and a second thumbnail image representing the second drawing image. At this time, the electronic device (201) may display the first thumbnail image and the second thumbnail image smaller than the second drawing image.

[0131] According to one embodiment, the electronic device (201) can display identification information on the second drawing image indicating that the second drawing image is an image automatically drawn using an artificial intelligence model.

[0132] According to one embodiment, the electronic device (201) may display a screen in which at least one intermediate drawing image is sequentially overlapped over a first drawing image in a specified order. For example, referring to FIG. 14c, the electronic device (201) may display images (1471, 1472, 1473, 1474, 1475, 1476) in which intermediate drawing images corresponding to each step are sequentially overlapped over the first drawing image. Depending on the implementation, the electronic device (201) may display images (1471, 1472, 1473, 1474, 1475, 1476) in which intermediate drawing images corresponding to each step are sequentially overlapped over the first drawing image through a video. Through this, the electronic device (201) may visually inform the user of the changes in drawing steps from the first drawing image to the second drawing image (1476).

[0133] FIG. 13 is a flowchart illustrating a method for an electronic device to edit an intermediate drawing image according to one embodiment.

[0134] Referring to FIG. 13, an electronic device (e.g., the electronic device (201) of FIG. 2) can display at least one intermediate drawing image based on stroke data.

[0135] According to one embodiment, in operation 1301, user input for at least one intermediate drawing image can be verified. For example, the user input may be an input selecting any one of at least one intermediate drawing image.

[0136] According to one embodiment, in operation 1303, the electronic device (201) can check an intermediate drawing image corresponding to user input and display a stroke editing screen for editing strokes included in the corresponding intermediate drawing image.

[0137] According to one embodiment, in operation 1305, the electronic device (201) can adjust the order of the corresponding intermediate drawing images and / or the attributes of the strokes included in the corresponding intermediate drawing images through a stroke editing screen. For example, the attributes of the strokes may include the size, length, number, pressure intensity, opacity, and / or color of the strokes.

[0138] Below, the operation of the electronic device (201) editing the stroke of the intermediate drawing image will be described in more detail.

[0139] FIG. 14a is a drawing for explaining how an electronic device displays a second drawing image and at least one intermediate drawing image according to one embodiment. FIG. 14b is a drawing for explaining how to edit the stroke properties of at least one intermediate drawing image according to one embodiment. FIG. 14d is a drawing for explaining how an electronic device displays a second drawing image and an intermediate drawing image according to one embodiment. FIG. 14e is a drawing for explaining how an electronic device edits a second drawing image according to one embodiment.

[0140] Referring to FIG. 14a, according to one embodiment, an electronic device (e.g., the electronic device (201) of FIG. 2) can display an execution screen (1401) of a drawing application. The electronic device (201) can display a second drawing image (1410) in which a first drawing image is additionally drawn based on at least one guide information in response to a user input requesting the creation of a new drawing image. For example, the electronic device (201) can acquire stroke data corresponding to intermediate steps for additionally drawing the first drawing image and use the acquired stroke data to display the second drawing image (1410).

[0141] According to one embodiment, the electronic device (201) may display a menu window (1405) including a second drawing image (1410), an object (1411) for adding to a layer, an object (1412) for stroke editing, and an object (1413) for adding to a reference image.

[0142] According to one embodiment, the electronic device (201) may display the second drawing image (1410) by overlapping it on top of the existing first drawing image based on confirming user input for an object (1411) for adding the second drawing image (1410) to a layer. For example, the electronic device (201) may display a first thumbnail image (1430) representing the existing first drawing image and a second thumbnail image (1440) representing the second drawing image. At this time, the electronic device (201) may display the first thumbnail image (1430) and the second thumbnail image (1440) smaller than the second drawing image (1410). For example, if user input for the first thumbnail image (1430) is confirmed, the electronic device (201) may display the existing first drawing image instead of the second drawing image.

[0143] According to one embodiment, the electronic device (201) may display a menu window (1420) containing intermediate drawing images (1421, 1422, 1423, 1424, 1425, 1426) corresponding to intermediate steps, based on confirming user input for an object (1412) for stroke editing. For example, the intermediate drawing images (1421, 1422, 1423, 1424, 1425, 1426) may include images added in intermediate steps before the second drawing image (1410) is completed. For example, the intermediate drawing images (1421, 1422, 1423, 1424, 1425, 1426) may be arranged according to the order in which they were drawn (or a specified order).

[0144] According to one embodiment, the electronic device (201) can determine or adjust the number of intermediate drawing images (1421, 1422, 1423, 1424, 1425, 1426). For example, the electronic device (201) can automatically determine or adjust the number of appropriate intermediate drawing images (or intermediate steps) by analyzing the complexity of the image (or picture) (e.g., determined based on the number of strokes and / or the degree of detail). For example, the electronic device (201) can determine the intermediate steps based on a time series (e.g., a timestep-based adjustment method) or determine the intermediate steps based on keyframes where major changes occur (e.g., a keyframe-based adjustment method). The electronic device (201) can acquire each intermediate image corresponding to each determined intermediate step over the entire time. For example, when determining an intermediate stage based on a time series, the electronic device (201) can divide the entire time interval into multiple stages (e.g., in the case of 5 stages, intervals corresponding to 20%, 40%, 60%, 80%, and 100% of the total time) and can acquire an intermediate image corresponding to each stage. For example, when determining an intermediate stage based on a keyframe, the electronic device (201) can divide the interval where a major change occurs into multiple stages and can acquire an intermediate image corresponding to each stage. To this end, the second artificial intelligence model can be trained to determine an intermediate stage based on a time series or to determine an intermediate stage based on a keyframe. Additionally, the second artificial intelligence model can be trained to generate an intermediate image corresponding to the determined intermediate stage.

[0145] According to one embodiment, the electronic device (201) may change the order of the corresponding intermediate drawing images based on user input (e.g., long press or touch-and-drag input) for any one of the intermediate drawing images (1421, 1422, 1423, 1424, 1425, 1426). For example, the electronic device (201) may change the order of the first intermediate drawing image (1421) from the first to the third based on the user input.

[0146] Referring to FIG. 14b, the electronic device (201) may display an editing window (1450) for editing the attributes of strokes included in the corresponding intermediate drawing image based on user input (e.g., tab input) for any one of the intermediate drawing images (1421, 1422, 1423, 1424, 1425, 1426) (e.g., the first intermediate drawing image (1421)). The electronic device (201) may perform an operation to edit the attributes of strokes included in the corresponding intermediate drawing image (1421) based on user input to the editing window (1450). For example, the electronic device (201) may change the size, length, number, pressure intensity, opacity, and / or color of the strokes included in the corresponding intermediate drawing image (1421) based on user input to the editing window (1450).

[0147] According to one embodiment, the electronic device (201) may display a palette menu associated with a second drawing image (1410) based on confirming user input for an object (1413) to be added to a reference image. An operation related to this will be described in more detail in FIGS. 15 and 16 below.

[0148] According to one embodiment of FIG. 14d, the electronic device (201) may display the second drawing image (1410) and intermediate drawing images (e.g., thumbnail images (1482, 1483, 1484, 1485) in which the intermediate drawing images are sequentially reflected). For example, the electronic device (201) may also display a thumbnail image (1481) corresponding to the first drawing image and a thumbnail image (1486) corresponding to the second drawing image (1410). That is, the electronic device (201) may display intermediate drawing images (e.g., thumbnail images (1482, 1483, 1484, 1485) in which the intermediate drawing images are sequentially reflected) corresponding to intermediate processes for generating the second drawing image together with the second drawing image (1410). For example, the electronic device (201) may display the second drawing image (1410) and the intermediate drawing images so as to be visually distinguishable (e.g., by display position and / or size). For example, thumbnail images (1481, 1482, 1483, 1484, 1485, 1486) corresponding to the intermediate drawing images may each correspond to images (1471, 1472, 1473, 1474, 1475, 1476) in which the intermediate drawing images corresponding to each step shown in FIG. 14c are sequentially overlaid on the first drawing image.

[0149] According to one embodiment, the electronic device (201) can determine the location where intermediate drawing images (or thumbnail images (1481, 1482, 1483, 1484, 1485, 1486)) are displayed based on the chronological order of intermediate drawing images (or thumbnail images (1481, 1482, 1483, 1484, 1485, 1486)) corresponding to the intermediate drawing images. For example, the electronic device (201) can arrange the first intermediate drawing image (1481) to the sixth intermediate drawing image (1486) sequentially (e.g., from bottom to top) based on the chronological order. However, this is an exemplary case, and the direction in which the intermediate drawing images are arranged may not be limited thereto.

[0150] According to one embodiment, the electronic device (201) can change the position or arrangement of intermediate drawing images based on user input (e.g., long press input or drag input). For example, the electronic device (201) can change the position or arrangement of a thumbnail image to the position or arrangement intended by the user input based on user input for any one of the thumbnail images (1481, 1482, 1483, 1484, 1485, 1486). For example, the electronic device (201) can change the position or arrangement of the thumbnail image to a position corresponding to the area where the user input is released. The electronic device (201) can draw (or create) the first drawing image into the second drawing image in order corresponding to the changed position.

[0151] According to one embodiment, the electronic device (201) may delete or remove at least some of the intermediate drawing images based on user input (e.g., touch input for an object for removing an intermediate step). Alternatively, the electronic device (201) may add new intermediate drawing images based on user input (e.g., touch input for an object for adding an intermediate step). The electronic device (201) may draw (or create) the first drawing image into the second drawing image by taking into further consideration the removed or added intermediate drawing images.

[0152] Referring to FIG. 14e, according to one embodiment, an electronic device (201) may display a second drawing image (1410) and intermediate drawing images. For example, intermediate drawing images may be displayed as thumbnail images. The electronic device (201) may display the second drawing image (1410) overlaid on an existing first drawing image based on confirming user input for an object (1411) for adding the second drawing image (1410) to a layer. The electronic device (201) may perform an operation to edit the second drawing image (1410) based on user input. For example, when user input for an object (1490) indicating restoration is confirmed, the electronic device (201) may delete the part or object (e.g., the nose of a dog) drawn last in the second drawing image (1410) based on a specified order. The electronic device (201) can display a drawing image (1495) in which the part drawn in the last sequence has been deleted. Additionally, the electronic device (201) may delete or edit only the intermediate drawing image corresponding to the step selected by user input.

[0153] Based on the method described above, the electronic device (201) can easily edit a desired part of the second drawing image (1410) based on a specified order.

[0154] FIG. 15 is a flowchart illustrating a method for an electronic device to display a palette menu related to a first drawing image and a second drawing image, according to one embodiment.

[0155] Referring to FIG. 15, according to one embodiment, in operation 1501, an electronic device (e.g., the electronic device (201) of FIG. 2) can receive user input selecting a second drawing image as a reference image. For example, the electronic device (201) can receive user input for an object (1413) to be added to the reference image of FIG. 14a.

[0156] According to one embodiment, in operation 1503, the electronic device (201) can generate a palette menu for the second drawing image. For example, the electronic device (201) can generate a palette menu for the second drawing image using a model for generating a palette menu (e.g., the palette generation model (370) of FIG. 3). For example, the palette menu may include information indicating newly added colors in completing the second drawing image.

[0157] According to one embodiment, in operation 1505, the electronic device (201) may display a palette menu together with a first drawing image. For example, the electronic device (201) may display a separate window including a second drawing image and a palette menu together with the first drawing image.

[0158] FIG. 16 is a drawing for explaining how an electronic device displays a palette menu related to a second drawing image according to one embodiment.

[0159] Referring to FIG. 14a and FIG. 16, an electronic device (e.g., the electronic device (201) of FIG. 2) can detect user input for an object (1413) for adding a second drawing image as a reference image. In response to the user input for the object (1413), the electronic device can display a palette window (1620) along with a first drawing image (1610) on the execution screen (1601) of the drawing application. For example, the palette window may include a second drawing image (1630) and a palette menu (1640). For example, the palette menu (1640) may include objects representing colors newly added to the first drawing image (1610) when drawing the second drawing image (1630). Additionally, the palette menu (1640) may include objects representing colors recommended for new addition to the first drawing image (1610), for example. The electronic device (201) can determine the color of the stroke that is subsequently entered as the corresponding color in response to user input selecting one of the objects of the palette menu (1640).

[0160] Based on the method described above, the electronic device (201) can provide a user interface that allows the user to directly make additional drawings on the first drawing image (1610) by referring to the second drawing image (1630) and the palette menu (1640).

[0161] Meanwhile, the generative artificial intelligence model described above can be implemented in the same or similar way as the generative artificial intelligence model of FIG. 17 described below.

[0162] FIG. 17 is a diagram illustrating a generative artificial intelligence system according to one embodiment.

[0163] According to one embodiment, the user query / response interface (1710) may receive user input. The user input may be in the form of natural language, images, and / or videos, but is not limited thereto. Additionally, context information may be transmitted along with the user input. The context information may include various additional information at the time of user input. For example, the additional information may include information about the application currently being used by the user or the user's location information. Additionally, the user input may be in a mixed form of the aforementioned natural language, images, sounds, and context information. Furthermore, the user input may be in a non-natural language form, such as selecting a menu. The user query / response interface (1710) may output results from a generative artificial intelligence system to the user. The output may be in the form of natural language or specific content, and may also be provided in the form of actions requested by the user. The user query / response interface (1710) may output results from a generative artificial intelligence system to the user. The output can be in the form of natural language or specific content, and it may also be provided in the form of actions requested by the user.

[0164] The AI ​​framework (1740) can receive input from the user and coordinate and control each component necessary to perform the user's intent based on the user's query.

[0165] User input received from the user query / response interface (1710) can be transmitted to a prompt design component (1741). The prompt design component (1741) can be used to generate prompts suitable for inputting user input into a large language model (LLM) or a large multimodal model (LMM). The prompt design component (1741) may be an AI component that uses machine learning algorithms or neural networks to develop better prompts over time. The prompt design component (1741) can generate prompts by accessing a knowledge component containing user preference data, a prompt library, and prompt examples based on user input, and can transmit the generated prompts to the LLM or LMM.

[0166] The API / Plug-in management component (1742) can perform the role of communicating with external information when there is a request for additional information when user input is passed as input to a generative model. The API / Plug-in management component (1742) establishes a channel to communicate with the outside of the AI ​​Interface via the API, and through the established channel, it can enable access to various data sources (e.g., knowledge repository (1720)). Additionally, the API / Plug-in management component (1742) can request the application / service component (1730) via the API to perform an action that ultimately executes the user input, rather than an intermediate result, in cases where the application or service needs to perform such action. The information obtained from the outside can be used to generate a prompt in the prompt design component (1741) along with the user input, or it can be passed as input to the generative model.

[0167] The output modification component (or refiner component) (1743) can fine-tune the output of the generative model. For example, the output modification component (1743) can verify whether the content generated through LLM and / or LMM is irrelevant, contains biased content, or contains harmful content. Additionally, the output modification component (1743) can determine the extent to which the output matches the user's desired result and, if additional processing is required, proceed with that process. Furthermore, the output modification component (1743) can configure and provide hints to the user to avoid unwanted output.

[0168] A generative AI model (1760) generally refers to an artificial intelligence neural network that generates new forms of data based on user input information. A generative AI model (1760) may include models that generate images and / or models that generate language. Models that generate images include, but are not limited to, GANs (generative adversarial networks) and VAEs (variational autoencoders), and examples include Diffusion-based generative models that use VAEs and Transformer structures. Models that generate language are models trained to output the most statistically appropriate output value based on input values, and examples include models such as CHAT-GPT 3 and CHAT-GPT 4. There are also LMMs (large multimodal models) that can recognize various forms of data input, such as text, images, and voice, and generate new data corresponding to them.

[0169] According to one embodiment, the electronic device (201) may include a display (260), at least one processor (220), and a memory (230) for storing instructions. According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause a first drawing image based on at least one drawing input to be displayed on the display. According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause a plurality of objects including guide information for improving the first drawing image based on analyzing the first drawing image to be displayed on the display. According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the first drawing image to acquire stroke data for drawing a second drawing image in a specified order, wherein the first drawing image has a plurality of strokes added based on at least one guide information included in the selected at least one object, based on a first user input selecting at least one guide object among the plurality of objects. According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the display to display the image corresponding to the stroke data and the second drawing image together.

[0170] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may be caused to obtain analysis information by analyzing the guide information and the first drawing image using a first artificial intelligence model stored in the memory.

[0171] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the electronic device to generate a prompt for acquiring the stroke data corresponding to the specified order based on the at least one guide information.

[0172] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause stroke data corresponding to each step to be acquired based on providing the first drawing image and the at least one guide information to a second artificial intelligence model stored in the memory. According to one embodiment, the second artificial intelligence model may be trained to generate a drawing image based on the specified order.

[0173] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the second artificial intelligence model to acquire stroke data corresponding to a sequence based on the drawing pattern information, based on providing the second artificial intelligence model with drawing pattern information including at least one of the user's drawing habit, drawing sequence, drawing pattern, or stroke attribute.

[0174] According to one embodiment, the stroke attribute may include at least one of the input order, type, texture, length, color, transparency, texture, pressure, or number of strokes drawn by the user.

[0175] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause identification information indicating that the second drawing image was generated using the second artificial intelligence model to be displayed on the second drawing image.

[0176] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the second drawing image to be displayed on the display over the first drawing image based on user input requesting the second drawing image to be overlapped over the first drawing image.

[0177] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the at least one intermediate drawing image to sequentially overlap the first drawing image in the specified order.

[0178] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the display to show a palette menu associated with the second drawing image based on user input requesting the second drawing image to be used as a reference image.

[0179] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the at least one intermediate drawing image to be placed based on the specified order.

[0180] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the at least one intermediate drawing image to be displayed smaller than the second drawing image.

[0181] According to one embodiment, the method of operation of the electronic device (201) may include the operation of displaying a first drawing image based on at least one drawing input on a display (260) included in the electronic device. According to one embodiment, the method of operation of the electronic device may include the operation of displaying a plurality of objects on the display that include guide information for improving the first drawing image based on analyzing the first drawing image. According to one embodiment, the method of operation of the electronic device may include the operation of obtaining stroke data for drawing a second drawing image in a specified order, based on a first user input selecting at least one object among the plurality of objects, wherein the first drawing image has a plurality of strokes added based on at least one guide information included in the selected at least one object. According to one embodiment, the method of operation of the electronic device may include the operation of displaying an image corresponding to the stroke data and the second drawing image together on the display.

[0182] According to one embodiment, the operation of obtaining the guide information may include the operation of obtaining analysis information by analyzing the guide information and the first drawing image using a first artificial intelligence model stored in the memory.

[0183] According to one embodiment, the method of operating the electronic device may further include the operation of generating a prompt for acquiring the stroke data corresponding to the specified order based on the at least one guide information.

[0184] According to one embodiment, the method of operation of the electronic device may further include an operation of acquiring stroke data corresponding to each step based on providing the first drawing image and the at least one guide information to a second artificial intelligence model stored in the memory. According to one embodiment, the second artificial intelligence model may include a model trained to generate a drawing image based on the specified order.

[0185] According to one embodiment, the operation of acquiring the stroke data may include the operation of acquiring stroke data corresponding to the order based on the drawing pattern information, based on providing the second artificial intelligence model with drawing pattern information including at least one of the user's drawing habit, drawing order, drawing pattern, or stroke attribute.

[0186] According to one embodiment, the operation of displaying the second drawing image may include the operation of displaying the second drawing image on the first drawing image on the display based on user input requesting to overlap the second drawing image on the first drawing image.

[0187] According to one embodiment, the method of operation of the electronic device may further include the operation of displaying a palette menu related to the second drawing image on the display based on a user input requesting to use the second drawing image as a reference image.

[0188] According to one embodiment, in a computer-readable non-transient storage medium (130, 230) that stores instructions, when the instructions are executed collectively or individually by at least one processor (220), the electronic device (201) may display a first drawing image based on at least one drawing input on a display (260) included in the electronic device, display a plurality of objects including guide information for improving the first drawing image based on analyzing the first drawing image, acquire stroke data for drawing a second drawing image in a specified order based on a first user input selecting at least one object among the plurality of objects, and add a plurality of strokes based on at least one guide information included in the selected at least one object.

[0189] According to one embodiment, the electronic device (201) may include a display (260), at least one processor (220), and a memory (230) for storing instructions. According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may display an input image including different first drawing stroke inputs and second drawing stroke inputs through the display, display one or more drawing tips generated based on at least part of the input image through the display, confirm a selection of at least one drawing tip among the one or more drawing tips displayed through the display, and cause the electronic device to display an output image corresponding to the result of applying the drawing tip to the input image based on at least part of the selection of the at least one drawing tip through the display, and the output image may be generated based on at least part of first drawing stroke data corresponding to the first drawing stroke input and second drawing stroke data corresponding to the second drawing stroke input.

[0190] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the at least one drawing tip to be generated based on the first characteristic of the first drawing stroke data or the second characteristic of the second drawing stroke data.

[0191] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause a detailed improvement guide for the input image and a summary of the detailed improvement guide to be displayed simultaneously as at least part of the at least one drawing tip.

[0192] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may provide the input image to an image generation model and, as at least part of the response to the provision of the input image, obtain the at least one drawing tip from the image generation model.

[0193] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may provide the input image and the at least one drawing tip to an image generation model and obtain the output image from the image generation model as at least part of the response to said provision.

[0194] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the first drawing stroke data and the second drawing stroke data to be provided to the image generation model.

[0195] According to one embodiment, the image generation model may be configured to perform learning to generate the output image based on at least a portion of the first drawing stroke data and the second drawing stroke data.

[0196] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause at least one data among the sequence, type, coordinate, color, transparency, texture, pressure, layer, or context of the corresponding drawing stroke input to be identified as at least a part of each of the first drawing stroke data and the second drawing stroke data.

[0197] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may be caused to receive a plurality of drawing stroke inputs, including the first drawing stroke input and the second drawing stroke input, through a designated graphical user interface (GUI) as at least part of the operation of displaying the input image through the display.

[0198] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause a first reference image and a second reference image corresponding to an intermediate process for generating the output image from the input image to be displayed together with the output image.

[0199] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause data corresponding to the first reference image or the second reference image to be received from an external server through the communication circuit.

[0200] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may generate a prompt based on at least part of the at least one drawing tip and the input image, transmit the prompt to the external server using the communication circuit, and receive the first reference image and the second reference image from the external server as at least part of the response to the prompt.

[0201] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the first reference image and the second reference image to determine a first position and a second position, respectively, that are displayed on the display, based at least partially on a first time sequence corresponding to the first reference image and a second time sequence corresponding to the second reference image.

[0202] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the first location or the second location to change based at least partially on user input regarding the first reference image or the second reference image.

[0203] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may be caused to identify the identity of a user providing the input image, and if the user is a first user, to display a first drawing tip or a second drawing tip as at least part of the one or more drawing tips, and if the user is a second user different from the first user, to display a third drawing tip or a fourth drawing tip different from the first drawing tip and the second drawing tip as at least part of the one or more drawing tips.

[0204] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may be caused to identify the identity of a user providing the input image, and if the user is a first user, to display a first output image as the output image, and if the user is a second user different from the first user, to display a second output image that is at least partially different from the first output image as the output image.

[0205] According to one embodiment, the first drawing stroke input or the second drawing stroke input may be configured to be selected from a plurality of drawing stroke inputs forming the input image, based at least partially on corresponding to a part of the drawing stroke history of one or more users.

[0206] According to one embodiment, when the user is a first user, a first set of one or more drawing stroke inputs from the plurality of drawing stroke inputs is selected as the first drawing stroke input or the second drawing stroke input based at least partially on the drawing stroke history, and when the user is a second user different from the first user, a second set of one or more drawing stroke inputs from the plurality of drawing stroke inputs that is at least partially different from the first set may be selected as the first drawing stroke input or the second drawing stroke input based at least partially on the drawing stroke history.

[0207] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause a plurality of drawing strokes previously identified as associated with the one or more users through one or more other input images or corresponding output images other than the input image to be stored in the memory as at least part of the drawing stroke history.

[0208] According to one embodiment, the electronic device (201) may include a display (260), at least one processor (220), and a memory (230) for storing instructions. According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the device to display an input image generated based on one or more drawing stroke inputs through the display, display one or more drawing tips generated based on at least part of the input image through the display, confirm a selection of at least one drawing tip among the one or more drawing tips displayed through the display, display an output image corresponding to the input image through the display based on at least part of the selection of the at least one drawing tip, and display a first reference image and a second reference image corresponding to at least part of an intermediate process for generating the output image from the input image together with the output image.

[0209] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the input image and the at least one drawing tip to be provided to an image generation model, and, as at least part of the response to the provision of the input image and the at least one drawing tip, to obtain the output image from the image generation model.

[0210] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may be caused to acquire corresponding first drawing stroke data and second drawing stroke data for the first reference image and the second reference image, respectively, from the image generation model as at least part of the response to the provision of the input image and the at least one drawing tip.

[0211] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the first reference image and the second reference image to be displayed respectively, based on at least one data among the sequence, type, coordinate, color, transparency, texture, pressure, layer, or context of the corresponding drawing stroke input, as at least part of each of the first drawing stroke data and the second drawing stroke data.

[0212] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may generate a prompt based on at least part of the at least one drawing tip and the input image, transmit the prompt to the external server using the communication circuit, and receive data corresponding to the first reference image or the second reference image from the external server as at least part of the response to the prompt.

[0213] According to one embodiment, when the instructions are executed collectively or individually by the at least one processor, the electronic device may cause the first reference image and the second reference image to determine a first position and a second position, respectively, that are displayed on the display, based at least partially on a first time sequence corresponding to the first reference image and a second time sequence corresponding to the second reference image.

[0214] The embodiment(s) and the terms used in this document are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, phrases such as "A or B," "at least one of A and B," "at least one of A or B," "A, B or C," "at least one of A, B and C," and "at least one of A, B, or C" may each include any one of the items listed together in the corresponding phrase, or any combination thereof. Terms such as "first," "second," or "first" or "second" may be used simply to distinguish said components from other said components and do not limit said components in any other aspect (e.g., importance or order). Where any (e.g., 1st) component is referred to as "coupled" or "connected" to another (e.g., 2nd) component, with or without the terms "functionally" or "communicationly," it means that said any component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component.

[0215] The term “module” as used in the various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0216] Various embodiments of this document may be implemented as software (e.g., a program) comprising one or more instructions stored in a storage medium (e.g., internal memory or external memory) readable by a machine (e.g., an electronic device). For example, a processor (e.g., a processor) of the machine (e.g., an electronic device) may call at least one of the one or more instructions stored from the storage medium and execute it. This enables the machine to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. The storage medium readable by the machine may be provided in the form of a non-transitory storage medium. Here, "non-transitory" simply means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and this term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily in the storage medium.

[0217] According to one embodiment, the method according to various embodiments of the present disclosure may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or an application store (e.g., Play Store). TM It can be distributed online (e.g., downloaded or uploaded) through ) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0218] According to the embodiments, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to the embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to the integration. According to the embodiments, operations performed by the module, program, or other components may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. In an electronic device (201), Display (260); At least one processor (220); and The electronic device includes a memory (230) for storing instructions, and when the instructions are executed collectively or individually by the at least one processor, the electronic device, A first drawing image based on at least one drawing input is displayed on the display, and Based on analyzing the first drawing image, a plurality of objects including guide information for improving the first drawing image are displayed on the display, and Based on a first user input selecting at least one object among the plurality of objects, stroke data is obtained for drawing a second drawing image in a specified order, wherein the first drawing image has a plurality of strokes added based on at least one guide information included in the selected at least one object, and An electronic device that causes an image corresponding to the stroke data and a second drawing image to be displayed together on the above display.

2. In paragraph 1, when the instructions are executed collectively or individually by the at least one processor, the electronic device, An electronic device that causes to obtain analysis information by analyzing the guide information and the first drawing image using the first artificial intelligence model stored in the memory.

3. In any one of paragraphs 1 to 2, when the instructions are executed collectively or individually by the at least one processor, the electronic device, An electronic device that causes a prompt to acquire stroke data corresponding to the specified order based on at least one guide information.

4. In any one of paragraphs 1 to 3, when the instructions are executed collectively or individually by the at least one processor, the electronic device, Based on providing the first drawing image and the at least one guide information to the second artificial intelligence model stored in the memory, the acquisition of stroke data corresponding to each step is induced, and The above second artificial intelligence model is an electronic device trained to generate a drawing image based on the above specified order.

5. In any one of claims 1 to 4, when the instructions are executed collectively or individually by the at least one processor, the electronic device, An electronic device that causes to acquire stroke data corresponding to a sequence based on the drawing pattern information, based on providing the second artificial intelligence model with drawing pattern information including at least one of the user's drawing habit, drawing sequence, drawing pattern, or stroke attribute.

6. In any one of paragraphs 1 through 5, The above stroke attribute is an electronic device comprising at least one of the input order, type, texture, length, color, transparency, texture, pressure, or number of strokes drawn by the user.

7. In any one of claims 1 to 6, when the instructions are executed collectively or individually by the at least one processor, the electronic device, An electronic device that causes identification information indicating that the second drawing image was generated using the second artificial intelligence model to be displayed on the second drawing image.

8. In any one of claims 1 to 7, when the instructions are executed collectively or individually by the at least one processor, the electronic device, An electronic device that causes the second drawing image to be displayed on the display over the first drawing image based on user input requesting the second drawing image to be overlapped over the first drawing image.

9. In any one of claims 1 through 8, when the instructions are executed collectively or individually by the at least one processor, the electronic device, An electronic device that causes at least one intermediate drawing image to be sequentially overlapped over the first drawing image according to the specified order.

10. In any one of claims 1 to 9, when the instructions are executed collectively or individually by the at least one processor, the electronic device, An electronic device that causes a palette menu related to the second drawing image to be displayed on the display based on user input requesting the use of the second drawing image as a reference image.

11. In any one of claims 1 to 10, when the instructions are executed collectively or individually by the at least one processor, the electronic device, An electronic device that causes the placement of at least one intermediate drawing image based on the above-specified order.

12. In any one of claims 1 to 11, when the instructions are executed collectively or individually by the at least one processor, the electronic device, An electronic device that causes at least one intermediate drawing image to be displayed smaller than the second drawing image.

13. In the method of operating the electronic device (201), The operation of displaying a first drawing image based on at least one drawing input on a display (260) included in the electronic device; An operation of displaying a plurality of objects on the display that include guide information for improving the first drawing image based on the analysis of the first drawing image; An operation to obtain stroke data for drawing a second drawing image in a specified order, wherein the first drawing image is based on at least one guide information included in the selected at least one object, based on a first user input selecting at least one object among the plurality of objects; and A method of operation of an electronic device comprising the operation of displaying together an image corresponding to the stroke data and the second drawing image on the above display.

14. In Paragraph 13, the operation of obtaining the above guide information is, A method of operation of an electronic device comprising the operation of obtaining analysis information by analyzing the guide information and the first drawing image using the first artificial intelligence model stored in the memory.

15. In any one of paragraphs 13 to 14, A method of operating an electronic device further comprising the operation of generating a prompt for acquiring stroke data corresponding to the specified order based on at least one guide information.

Images