Image processing service system, image processing method and program for the image processing service system

Abstract

This invention provides an image processing service system, image processing method, and program that efficiently produce high-quality edited image information through a simple operation of uploading line drawing information. [Solution] An image processing service system that enables communication between a server device 1 that publishes a platform 1A providing a background image generation service to any of the data terminals via a network 21, wherein the server device comprises a first reading unit that reads a learning model stored in a model database, a second reading unit that reads line drawing information acquired from a data terminal, a third reading unit that reads reference image information stored in a model database, a fourth reading unit that reads a prompt acquired from a data terminal, and an AI generation unit that generates a background image to be applied to the line drawing information from composition information and style information acquired from the data terminal.

Description

Technical Field

[0001] The present invention relates to an image processing service system for assisting in the production of background images, an image processing method of the image processing service system, and a program.

Background Art

[0002] Conventionally, the production of background images in commercial anime has been carried out manually on a PC using hand-drawn or painting software (CLIPSTUDIO (registered trademark), Photoshop (registered trademark)). As an alternative, there are image generation AI technologies and services such as Stable Diffusion, and there is a mechanism that can output still images using these technologies.

[0003] Furthermore, in the extension function of Stable Diffusion, images are generated based on text (prompts) input by conventional users. In recent years, in addition to text, images can also be input as instructions, enabling the generation of images that reflect detailed requirements and constraints such as people's poses and object depth information that users cannot verbalize.

[0004] The following Patent Document 1 describes generating a training sample by synthesizing a foreground image and a background image and performing learning of a saliency detection model.

[0005] Also, the following Patent Document 2 discloses that "as a method for generating a background image, the image occupancy rate in the original image of the target subject is determined. When the image occupancy rate is smaller than a predetermined threshold, the image of the subject area corresponding to the target subject is cut out from the original image, a corresponding subject area mask is determined based on the subject area image, and the subject area mask and the subject area image are synthesized to generate a backgroundless image corresponding to the original image, thereby ensuring high matting accuracy even for images with a low subject occupancy rate."

Prior Art Documents

Patent Documents

[0006] [Patent Document 1] Chinese Patent Application Publication No. 109727264 Specification [Patent Document 2] Japanese Patent Publication No. 2021-119457 [Overview of the Initiative] [Problems that the invention aims to solve]

[0007] However, simply applying the conventional techniques described above presented several challenges: the resulting background art was of low quality, it was impossible to reproduce arbitrary compositions or styles according to layout instructions, or the reproduction accuracy was still low, preventing it from reaching a level usable in animation production.

[0008] This invention was made to solve the above problems, and significantly reduces the burden of the process involved in creating edited images by combining line art information drawn at the motif stage of animation creation with background images. Furthermore, by producing background images with various style parameters entrusted to the line art information automatically generated, it is possible to efficiently produce high-quality edited image information with a simple operation of uploading image information. [Means for solving the problem]

[0009] The image processing service system of the present invention, which achieves the above objective, has the following configuration.

[0010] An image processing service system that enables communication between a server device that publishes a platform providing a background image generation service to any of the data terminals via a predetermined communication medium, wherein the server device comprises: a first reading means for reading a learning model stored in a predetermined database; a second reading means for reading line drawing information acquired from the data terminals; a third reading means for reading reference image information stored in the predetermined database; a fourth reading means for reading prompts acquired from the data terminals; and an AI generation means for generating a background image to be applied to the line drawing information from composition information and style information acquired from the data terminals. [Effects of the Invention]

[0011] According to the present invention, high-quality edited image information can be efficiently produced with a simple operation of uploading line drawing information. [Brief explanation of the drawing]

[0012] The drawings illustrate specific embodiments of the present invention, including not only essential components of the invention but also optional and preferred embodiments. [Figure 1] A block diagram illustrating the configuration of the image processing service system shown in this embodiment. [Figure 2] A block diagram illustrating the configuration of the server device shown in Figure 1. [Figure 3] A block diagram illustrating the configuration of the first to fourth data terminals shown in Figure 1. [Figure 4] Figure 1 shows an example of a user interface (UI) screen that the server device presents to a data terminal. [Figure 5] Figure 1 shows an example of a user interface (UI) screen that the server device presents to a data terminal. [Figure 6] Figure 1 shows an example of a user interface (UI) screen that the server device presents to a data terminal. [Figure 7]A diagram showing an example of a user interface screen (UI screen) presented by the server device shown in FIG. 1 to a data terminal. [Figure 8] A diagram showing an example of a user interface screen (UI screen) presented by the server device shown in FIG. 1 to a data terminal. [Figure 9] A flowchart for explaining an image processing method of an image processing service system showing this embodiment.

Mode for Carrying Out the Invention

[0013] Next, the best mode for carrying out the present invention will be described with reference to the drawings.

[0014] <Description of System Configuration> 〔First Embodiment〕 FIG. 1 is a block diagram for explaining the hardware configuration of an image processing system showing this embodiment.

[0015] In FIG. 1, 3-1 to 3-N are data terminals operated by a first animator and are communicably connected to the server device 1 via the network 21.

[0016] 4-1 to 4-N are data terminals operated by a second animator and are communicably connected to the server device 1 via the network 21.

[0017] 5-1 to 5-N are data terminals operated by a third animator and are communicably connected to the server device 1 via the network 21.

[0018] 2-1 to 2-N are data terminals operated by a fourth animator and are communicably connected to the server device 1 via the network 21.

[0019] Hereinafter, in this embodiment, assuming that an animator creates line drawing information and uploads the created line drawing information to the server device 1, since the animator becomes a user of the system, instructions from the data terminal to the server device 1 are described as a user. Furthermore, individuals other than animators (including students and the general public) may also connect to this system and receive similar services, and in such cases, these individuals may be referred to as users.

[0020] Server device 1 provides image editing services to the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, the third data terminals 5-1 to 5-N, and the fourth data terminals 2-1 to 2-N via platform 1A.

[0021] Figure 2 is a block diagram illustrating the configuration of the server device 1 shown in Figure 1. In Figure 2, the AI ​​generation unit 16-5, which functions as a background image processing unit, can also be composed of a processing unit including a DSP (Digital Signal Processor), a CPU (Central Processing Unit) 13, and a GPU (Graphics Processing Unit) as hardware.

[0022] The DSP and GPU operate under the control of the CPU 13 and are responsible for performing image-related processing. Here, a processing unit including a DSP, CPU 13, and GPU is given as an example of a processor, but this is merely an example, and the processor may consist of one or more CPUs and one or more GPUs, one or more CPUs and DSPs with integrated GPU functionality, one or more CPUs and DSPs without integrated GPU functionality, or a TPU (Tensor Processing Unit) may be included.

[0023] RAM16 is memory where information is temporarily stored and is used as work memory by the processor.

[0024] Examples of RAM16 include DRAM (Dynamic Random Access Memory) or SRAM (Static Random Access Memory).

[0025] The communication unit 11 is an interface including a communication processor and an antenna, and is connected to the internal bus 12. The communication unit 11 is responsible for communication between the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, the third data terminals 5-1 to 5-N, and the fourth data terminals 2-1 to 2-N and the server device 1, etc. The communication standard applied to the communication unit 11 may be a wireless communication standard including, for example, 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), or a wired communication standard including Ethernet (registered trademark), Fast Ethernet (registered trademark), or Gigabit Ethernet (registered trademark).

[0026] 18 is external memory, which stores the web pages (HTML files) to be presented by platform 1A.

[0027] 14 is the model database, which functions as an image database that stores large models of background image patterns. 15 is the keyboard, which is used to control icons and dashboards displayed on display 17, and to input text and commands.

[0028] Unit 19 is the AI ​​support unit, which works in conjunction with an AI server (not shown) to synchronize with requests (including prompts) from the AI ​​generation unit 16-5 and supports background image generation and editing image processing.

[0029] Here, we will explain the Stable Diffusion function used by server device 1.

[0030] (Learning model) Transformer models such as GPT-3 and GPT-4 are typically used as large-scale neural network models for image generation.

[0031] (Training data) This corresponds to the dataset used to determine the quality and style of the generated images. This dataset includes a large amount of image and text data.

[0032] (encoder) This function converts input text into a format that the model can understand.

[0033] (Decoder) Supports the ability to convert images generated from a model back to their original text format.

[0034] (Noise level) It supports a setting function to adjust the noise level applied to the generated image. This will change the image quality and style.

[0035] (Hardware) In addition to the CPU13 mentioned above, high-performance hardware resources such as GPUs (Graphics Processing Units) and TPUs (Tensor Processing Units) may be required. This enables the efficient execution of large-scale models.

[0036] The program deployed in RAM16 includes a first reading unit 16-1 that reads a learning model stored in the model database 14, a second reading unit 16-2 that reads line drawing information acquired from a data terminal, a third reading unit 16-3 that reads reference image information stored in the model database 14, a fourth reading unit 16-4 that reads a prompt acquired from the data terminal, an AI generation unit 16-5 that generates a background image to be applied to the line drawing information from composition information and drawing style information acquired from the data terminal, and a delivery unit 16-6 that delivers edited image information, in which the background image generated by the AI ​​generation unit 16-5 is adapted to the line drawing information, to the data terminal.

[0037] Figure 3 is a block diagram illustrating the configuration of the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, the third data terminals 5-1 to 5-N, and the fourth data terminals 2-1 to 2-N shown in Figure 1. In the following embodiments, when the first data terminals 3-1 to 3-N, the second data terminals 4-1 to 4-N, the third data terminals 5-1 to 5-N, and the fourth data terminals 2-1 to 2-N are representative, they will simply be referred to as "data terminals."

[0038] In Figure 3, 301 is the CPU, which starts the BIOS stored in ROM 302 and controls the I / O devices. 303 is RAM, which loads applications stored in external memory (not shown) into RAM 303 and performs various data processing. 304 is the communication unit, which is connected to network 21 and configured to communicate bidirectionally with server device 1. 311 is the display, which displays information entered from keyboard 310.

[0039] Specifically, RAM303 contains a login unit 303-1 that performs login processing to the platform 1A of server device 1, an upload / download unit 303-2 that uploads line drawing information as a background image created by an animator by launching a line drawing processing application (not shown) to server device 1, and downloads generated images with background processing applied by the AI ​​generation unit 16-5 of server device 1 using AI, and a UI control unit 303-3 that controls the browser. Various data processing is performed when a program is launched by CPU301.

[0040] Figures 4 to 8 show examples of user interface screens (UI screens) that the server device 1 shown in Figure 1 presents to a data terminal.

[0041] This screen is displayed when a user operating a data terminal connects to platform 1A via network 21 and uploads line drawing information to server device 1.

[0042] The UI screen shown in Figure 4 corresponds to the screen used by a user to upload line drawing information created by launching a retouching application from a data terminal to server device 1. Here, it is assumed that the user has already registered on platform 1A, and that this screen is displayed on the data terminal after the user has logged in.

[0043] Here, the user selects line drawing information from external memory and then uploads it from the data terminal to server device 1 by pressing the upload button UPLB.

[0044] Note that the diagram shows an example where the selected line drawing information LI is displayed, but it is possible to omit the display as appropriate.

[0045] The UI screen shown in Figure 5 corresponds to the style selection screen presented by Server Device 1, and while TYPE1 to TYPE3 are shown as examples, the repertoire is not limited to these.

[0046] The UI screen shown in Figure 6 corresponds to the scene setting screen presented by Server Device 1, and shows the case where the time parameter TP1 can be selected as "dawn," "morning," "daytime," "evening," "night," or "midnight."

[0047] Furthermore, the weather parameter TP2 is configured to allow selection of "sunny," "cloudy," and "rainy," and the user operating the data terminal can instruct the server device 1 to select a combination of the time parameter TP1 and the weather parameter TP2.

[0048] Furthermore, the COM component is configured to allow the user to control the server device 1 via text input using the keyboard. GEN is a generate button, which is pressed when the user instructs the server device 1 to generate an edited image.

[0049] The UI screen shown in Figure 7 corresponds to the edited image screen, which is generated by the server device 1 through AI image generation processing on line drawing information uploaded from the data terminal, and represents the final image.

[0050] The UI screen shown in Figure 8 corresponds to the screen on which the edited image, created from line drawing information uploaded to the server device 1, can be viewed on the data terminal's display 17, and finally downloaded.

[0051] In this example, after the generated edited images GPIC-1 to GPIC-4 are displayed in a list, the user selects one of the final images, and then the GEN button is pressed to complete the editing instructions for the line drawing information.

[0052] The following explains the image generation process. The image generation process in this embodiment consists of the following five steps. (1) Uploading and selecting line art (2) Selection process of reference images (3) Instruction process for composition content and scene setting (4) Image generation process (5) Saving process of generated images

[0053] Furthermore, the processes shown in (1) to (5) have detailed setting parameters (not shown) pre-registered in the model database 14, and the final image of the edited image information can be freely adjusted by changing the parameter thresholds.

[0054] [(1) Details of the line art upload and selection process] After accessing the website and agreeing to the terms of service, users of the product can either press the upload button UPLB to select and upload line art information (illustrations drawn only with lines, without color) from a folder stored in the external memory of their data terminal, or upload line art information to server device 1 using drag-and-drop. Alternatively, the system may be configured to allow users to select line art information from pre-made samples at the bottom of the screen.

[0055] [(2) Selection process for reference images] Next, the user selects one of the available art styles (see Figure 5) on the left side of the screen. This instructs the server device 1 to apply the art style to the generated result.

[0056] [(3) Instruction process for composition content and scene setting] Next, the user selects the elements depicted in the line drawing and inputs them in text format, which then functions as a prompt. Furthermore, the user can delete elements by hovering the mouse cursor over them and clicking the × button (see Figure 6) that appears. The elements of the image are automatically entered when the server device 1 reads the line drawing information uploaded from the data terminal.

[0057] [(4) Image generation process] Here, users can modify and add to the automatically entered configuration content as needed to further improve the accuracy of the generated results. Furthermore, in the scene settings, users can select the time of day (shown as time parameter TP1 in Figure 6, which includes dawn, morning, daytime, evening, night, and midnight) and the weather (shown as weather parameter TP2 in Figure 6, which includes sunny, cloudy, and rainy). As a result, users operating the data terminal can simply instruct the server device 1 to select a scene with their chosen time of day and weather, and receive an edited image (corresponding to a finished image that is colorized and has a motif applied) as the generated result.

[0058] [(5) Saving process of generated images] First, the user can select one edited image from among those displayed on the data terminal's display 311 and check the finished image on the editing screen. In the UI screen shown in Figure 7, saturation, highlights, and shadows can be adjusted on the right side of the screen.

[0059] Then, after completing the adjustments by instructing the server device 1 with the image adjustment parameters shown in Figure 8, pressing the download button DLB shown in Figure 8 allows the data terminal to import the edited image created by the AI ​​generation process on the server device 1 into external memory.

[0060] In this manner, the system's server device 1 accesses the service page provided by platform 1A via network 21 from a data terminal operated by the user, and uploads line drawings and makes processing requests through a browser controlled by the UI control unit 303-3. Server device 1 has a model database 14, which stores the learning model of the image generation AI, line drawing information uploaded by the user, reference image information for reproducing the drawing style, and the generated edited image.

[0061] In this embodiment, the server device 1 incorporates an image generation AI module (Stable Diffusion) and provides a service that supports the process of generating edited images based on a learning model, uploaded line drawings, reference images, and configuration information entered by the user.

[0062] Figure 9 is a flowchart illustrating the image processing method of the image processing system shown in this embodiment. Steps (1) to (8) represent the respective steps, which are realized by the CPU 13 loading the control program stored in the external memory 18 into the RAM 16 and executing it.

[0063] CPU13 loads the trained model from the model database14 into RAM16 (1). Here, the trained model is a pre-trained dataset that Stable Diffusion references when generating edited images.

[0064] Next, CPU13 executes the process of reading the line drawing information uploaded from the data terminal (2).

[0065] Here, the resolution of line drawing information uploaded from the data terminal, or pre-made line drawing samples (hereinafter referred to as "line drawing information"), is reduced or enlarged so that the longest side is 1920 pixels. In particular, line drawing information with low resolution results in low quality generated images, so it is necessary to ensure a sufficiently high resolution.

[0066] Furthermore, by reading the strength (the intensity with which the lines of the line drawing are reflected) of the line drawing information between, for example, 0.70 and 0.95, the CPU 13 can reproduce the composition of the generated edited image in a way that closely resembles the line drawing.

[0067] Next, the CPU 13 reads reference image information from the model database 14 into the RAM 16 (3).

[0068] Specifically, by reading the strength (the intensity of the image reference) of any reference image selected by the user (hereinafter referred to as "reference image") between, for example, 0.30 and 1.00, the style of the generated image can be reflected in a desirable manner.

[0069] Next, the CPU 13 reads the prompt entered as text by the user operating the data terminal (4).

[0070] Specifically, the system reads text information indicating the weather and time of day as a prompt, based on the configuration entered by the user operating the data terminal (as explained in Figure 6).

[0071] Furthermore, this system has prompts for improving image quality pre-configured in the model database 14. By inputting these prompts along with the user's own input, the generated background image can be customized to the user's specifications.

[0072] Next, CPU 13 generates a background image that reproduces the composition and style shown in Figure 5 (5).

[0073] Specifically, the edited image is generated based on the learning model loaded in step (1) and the various parameter settings in steps (2) to (4). For example, by setting the CFG Scale (Classifier Free Guidance (prompt reference strength)) to a range of, say, 4.5-7.0, and the denoise (the strength of noise removal in image generation) to a range of, say, 0.90-1.00, the content of the generated image can be set to the scene intended by the user.

[0074] Next, the CPU 13 determines whether an instruction has been given from the data terminal to change the parameters that determine the background of the edited image (6). If it determines that an instruction has been given to change the parameters that determine the background, it returns to step (4), reads the newly issued prompt from the data terminal, and repeats the same process.

[0075] Next, the CPU 13 performs image processing to write the edited image to be output to the data terminal onto the RAM 16 according to the parameters for generating the edited image determined by the processing in steps (1) to (5) (7).

[0076] On the other hand, if step (7) determines that no change has been instructed for the parameters that determine the background, the CPU 13 delivers the edited image information to the data terminal (8) and terminates this process.

[0077] Specifically, by upscaling the edited image to twice its resolution (resulting in a longer side of 3840px), it becomes easier to achieve sufficient detail in the generated image.

[0078] Furthermore, the screen is generated based on the learning model from step (1) and the default settings for the image quality improvement prompts.

[0079] Specifically, by generating CFG Scale between 1.0 and 2.0 and denoise between 0.35 and 0.50, it is possible to increase the detail of the edited image while maintaining the composition of the generated image, thereby obtaining the level of detail required in, for example, animation production.

[0080] The following describes the results of our verification of the final output image obtained through the editing image generation process for the submitted line drawing information in this embodiment, focusing on the following items.

[0081] [Verification process] (1) Overview of the verification To determine that it is suitable for use in animation production, it must be confirmed that the generated edited image is faithful to the lines of the input line art information, that the composition is reproduced accurately, that the user's chosen art style is reproduced accurately, and that the user's set scene settings (weather, time of day, etc.) are reflected. In other words, it must meet the quality requirements to be a viable alternative to manual work as a means of creating background art.

[0082] As described above, in this embodiment, we conducted verification on representative scenes that frequently appear in anime production (six scenes: landscape, beach, downtown, residential area, classroom, and corridor) and drawing styles (three types: art style, anime style, and realistic style).

[0083] [Effects of the First Embodiment] According to this embodiment, the burden of the process involved in creating an edited image by combining line art information drawn at the motif stage of animation creation with a background image is greatly reduced. Furthermore, since the background image is produced with various style parameters entrusted to the line art information automatically generated, it is possible to efficiently produce high-quality edited image information.

[0084] [Second Embodiment] In the above embodiment, a system for supporting animation production was described, but the concept of "picture style" can also be applied to other types of videos besides animation, as well as to general painting.

[0085] [Effects of the second embodiment] According to this embodiment, by incorporating image processing by generation AI into the background processing of a video using line drawing information as the original image, the delivery time required for final video production can be significantly shortened. Furthermore, it is possible to support optimal video editing work while maintaining novelty by making full use of the expressive power learned based on the user's intentions.

[0086] The present invention can also be realized by supplying a program (corresponding to each step shown in Figure 9) that implements one or more of the functions of the above-described embodiments to a system or device via a network or storage medium, and by having one or more processors in the computer of that system or device read and execute the program. It can also be realized by a circuit (e.g., an ASIC) that implements one or more functions.

[0087] The present invention is not limited to the embodiments described above, and various modifications (including organic combinations of each embodiment) are possible based on the spirit of the invention, and these are not excluded from the scope of the invention.

[0088] (1) An image processing service system that enables communication between a server device that publishes a platform providing background image generation services to any of the data terminals via a predetermined communication medium, wherein the server device comprises: a first reading means for reading a learning model stored in a predetermined database; a second reading means for reading line drawing information acquired from the data terminals; a third reading means for reading reference image information stored in the predetermined database; a fourth reading means for reading prompts acquired from the data terminals; and an AI generation means for generating a background image to be applied to the line drawing information from composition information and style information acquired from the data terminals.

[0089] (2) The system is characterized by comprising a delivery means for delivering edited image information, which is obtained by adapting the background image generated by the AI ​​generation means to the line drawing information, to the data terminal.

[0090] (3) The delivery means is characterized by delivering the edited image information to the data terminal as original drawing information for animation.

[0091] (4) An image processing method for an image processing service system, wherein a server device that publishes a platform providing a background image generation service to any of the data terminals via a predetermined communication medium can communicate with a plurality of data terminals operated by a user, the server device comprising: a first reading step of reading a learning model stored in a predetermined database; a second reading step of reading line drawing information obtained from the data terminals; a third reading step of reading reference image information stored in the predetermined database; a fourth reading step of reading a prompt obtained from the data terminals; and an AI generation step of generating a background image to be applied to the line drawing information from composition information and style information obtained from the data terminals.

[0092] (5) An image processing service system in which a server computer that publishes a platform providing background image generation services to any of the data terminals on the web is made public via a predetermined communication medium and the server computer is made public via a predetermined communication medium the server computer is made to execute a first read step of reading a learning model stored in a predetermined database, a second read step of reading line drawing information obtained from the data terminals, a third read step of reading reference image information stored in the predetermined database, a fourth read step of reading a prompt obtained from the data terminals, and an AI generation step of generating a background image to be applied to the line drawing information from composition information and drawing style information obtained from the data terminals. [Explanation of Symbols]

[0093] 1 Server device 1A Platform 3-1~3-N First data terminal 4-1~4-N Second data terminal 5-1~5-N Third data terminal 2-1~2-N The fourth data terminal

Claims

1. An image processing service system that enables communication between multiple data terminals operated by users and a server device that publishes a platform providing a background image generation service to any of the data terminals via a predetermined communication medium, The server device is A first loading means for loading a learning model stored in a predetermined database, A second reading means for reading line drawing information acquired from the aforementioned data terminal, A third reading means for reading reference image information stored in the predetermined database, A fourth reading means for reading a prompt obtained from the aforementioned data terminal, AI generation means for generating a background image to be applied to the line drawing information from composition information and drawing style information acquired from the data terminal, An image processing service system characterized by comprising the following features.

2. The image processing service system according to claim 1, further comprising a delivery means for delivering edited image information, in which the background image generated by the AI ​​generation means is adapted to the line drawing information, to the data terminal.

3. The image processing service system according to claim 2, characterized in that the delivery means delivers the edited image information as animation original drawing information to the data terminal.

4. An image processing method for an image processing service system, which enables communication between multiple data terminals operated by a user and a server device that publishes a platform providing a background image generation service to any of the data terminals via a predetermined communication medium, The server device is A first loading step involves loading a learning model stored in a designated database, A second reading step involves reading line drawing information obtained from the aforementioned data terminal, A third reading step involves reading reference image information stored in the predetermined database, A fourth reading step involves reading a prompt obtained from the aforementioned data terminal, An AI generation step that generates a background image to be applied to the line drawing information from composition information and drawing style information acquired from the data terminal, An image processing method for an image processing service system, characterized by comprising:

5. In an image processing service system, the server computer is capable of communicating with multiple data terminals operated by users via a predetermined communication medium, and with a server computer that publishes a platform providing background image generation services to any of the data terminals on the web. A first loading step involves loading a learning model stored in a designated database, A second reading step involves reading line drawing information obtained from the aforementioned data terminal, A third reading step involves reading reference image information stored in the predetermined database, A fourth reading step involves reading a prompt obtained from the aforementioned data terminal, An AI generation step that generates a background image to be applied to the line drawing information from composition information and drawing style information acquired from the data terminal, A program characterized by causing the execution of a specific action.

Images