【無料！AIで画像を生成】Stable Diffusion の使い方 〜Pythonプログラミング〜初心者向け【可愛い女の子のイラストを生成したい！】
TLDRIn this video, Python Vtuber Sapu introduces viewers to the use of AI for generating images from sentences and words. The focus is on using Japanese stable diffusion, an open-source model developed by Rinna, which allows for the creation of high-quality images from Japanese text. The tutorial covers setting up an account with Fakingface, using a collaboratory with GPU support, and installing the necessary AI model with pip. Sapu walks through the process of writing code to generate images, explaining the components of the code and how to adjust the input text for different styles, such as watercolor or oil painting. The video also demonstrates generating anime-style faces using the Wife Diffusion model and provides tips for creating detailed and appealing images. Sapu encourages viewers to experiment with the models and search for inspiration on social media platforms like Twitter.
Takeaways
- 🎨 The video introduces how to use AI for generating images from sentences and words using a model called Stable Diffusion.
- 🚀 The AI model Dari2 by OpenAI has significantly improved the quality of image generation, making it possible to create high-quality images.
- 🌐 Services like Mid Journey and open-source models like Stable Diffusion are gaining popularity for image creation.
- 🇯🇵 A Japanese version of Stable Diffusion has been developed by a company called Reina and is available as an open-source model.
- 📚 The video demonstrates using Japanese Stable Diffusion to generate images from Japanese sentences with the help of a collaboratory.
- 💻 To get started, viewers are instructed to create an account on faggingface and share account information for repository access.
- 🔧 The collaboratory's runtime is set to GPU to utilize its processing power for faster image generation.
- 📝 The installation of Japanese Stable Diffusion is done using the pip install command, followed by the login process for faggingface-cli.
- 🌟 The source code for image generation is copied from the Japanese Stable Diffusion page and executed in the collaboratory.
- 🖼️ Customizing the input text allows for generating different styles of images, such as oil paintings or watercolors.
- 🌈 The video shows an example of generating an image of a high-rise building in Tokyo with rain and a rainbow.
- 🎭 For generating anime-style faces, a different model called Wife Diffusion is used, which requires English input text.
Q & A
What is the main topic of the video?
-The main topic of the video is how to use an AI that generates images from sentences and words, specifically using Japanese stable diffusion and Wife Diffusion models.
Who developed the AI model called DALL-E 2?
-The AI model DALL-E 2 was developed by OpenAI, a company that specializes in AI research.
What is the name of the service that generates images through Discord?
-The service that generates images through Discord is called Mid Journey.
How can one create an account on the faggingface platform?
-To create an account on faggingface, one needs to go to the official site, click on the Sign Up button at the top right, enter an email address and password, and follow the instructions. After registration, a confirmation email is sent, and one must click the URL in that email to complete the sign-up process.
What is a 'scheduler' in the context of the video?
-In the context of the video, a scheduler is a pipeline that creates a series of flows to generate images when a text is entered into the system.
How can one use the GPU on the collaboratory?
-To use the GPU on the collaboratory, one needs to click on the runtime in the menu above, change the runtime type, set the hardware accelerator to GPU, and press the Save button.
What is the name of the model used for generating anime-like face illustrations?
-The model used for generating anime-like face illustrations is called Wife Diffusion.
What is the significance of the 'seed' in image generation?
-The 'seed' in image generation is a value that, when fixed, allows the generation of the same image multiple times, ensuring consistency in the output.
How can one find out what kind of text and words can generate specific images with stable diffusion?
-One can search for stable diffusion and wife diffusion on Twitter to find examples of what kind of text and words can generate specific images, as people often share their findings there.
What is the purpose of the 'prompt' variable in the code?
-The 'prompt' variable in the code is used to enter the input text for generating images, which can be descriptive phrases or specific words that guide the AI in creating the desired image.
How does the AI generate different styles of images, such as watercolor or oil paintings?
-The AI generates different styles of images by incorporating descriptive words into the 'prompt' variable that specify the desired style, such as 'watercolor' or 'oil painting'.
What is the difference between Japanese stable diffusion and Wife Diffusion in terms of language usage?
-Japanese stable diffusion is used with Japanese text for generating images, while Wife Diffusion requires the input text to be specified in English.
Outlines
🖼️ Introduction to Image Generation AI
Sapu, a Python Vtuber, introduces the concept of image generation AI, which uses machine learning models to create images from sentences and words. The video focuses on using Japanese stable diffusion to generate images from Japanese sentences. Sapu emphasizes the high quality of recent image generation and mentions the development of the Dari2 model by OpenAI. The video also discusses other services like Mid Journey and StableDiffusion, and the open-source Japanese stable diffusion by Reina. Sapu provides a step-by-step guide on setting up an account with faggingface, accessing the Japanese stable diffusion page, and using a collaboratory with GPU to install and use the Japanese stable diffusion model.
🎨 Generating Images with Japanese Stable Diffusion
The video continues with a detailed explanation of how to generate images using the Japanese stable diffusion model. Sapu outlines the process of creating a pipeline for image generation, specifying the pre-trained model, and configuring the settings. The model used is developed by Rinna and released on faggingface. The video demonstrates how to input text for image generation and how to utilize a GPU for faster processing. Sapu also shows how to modify the input text to generate different styles of images, such as changing a picture to a watercolor painting. The video concludes with an example of generating an image of a high-rise building in Tokyo with a rainbow after rain, showcasing the capabilities of the AI model.
🌟 Using Wife Diffusion for Anime-like Faces
Sapu then explores using the Wife Diffusion model, specialized in drawing anime-like face illustrations, also available on Fagging Face. The video provides instructions on copying and pasting sample code into a collaboratory cell, adjusting the scheduler, pipeline class, and model ID for Wife Diffusion. Unlike the Japanese stable diffusion, input text for Wife Diffusion must be in English. Sapu demonstrates how to create a detailed and appealing illustration of a girl with specific attributes like dark blue hair, a light blue sailor suit, and a soft focus for a beautiful composition. The video also touches on the variability of the generated images and how fixing the seed of the generator can produce the same image consistently. Sapu concludes by encouraging viewers to experiment with both Japanese stable diffusion and Wife Diffusion models to create their own unique images.
Mindmap
Keywords
💡AI image generation
💡Python
💡Stable Diffusion
💡Mid Journey
💡Japanese stable diffusion
💡Collaboratory
💡Faggingface
💡Deep learning
💡Wife Diffusion
💡Pipeline
💡Prompt
Highlights
The video demonstrates using AI to generate images from sentences and words.
Image generation AI is a machine learning model that creates non-existent images from text.
OpenAI's model, DALL-E 2, has significantly improved image generation quality.
Stable Diffusion is an open-source alternative for image generation.
Japanese Stable Diffusion is capable of generating images from Japanese sentences.
The video uses a collaboratory to demonstrate the image generation process.
Filling out an account on Hugging Face is a prerequisite for using Japanese Stable Diffusion.
The collaboratory's runtime type is changed to GPU for enhanced performance.
Japanese Stable Diffusion is installed using the pip install command.
Logging in to Hugging Face CLI is required before generating images.
The source code for image generation is copied from the Japanese Stable Diffusion page.
A scheduler and pipeline are created for the image generation process.
The pre-trained Rinna Japanese Stable Diffusion model is specified for image creation.
Input text for image generation is entered into the 'prompt' variable.
The generated image can be displayed or saved as a file.
Wife Diffusion is a specialized model for drawing anime-like face illustrations.
Different techniques and descriptive words can influence the style and outcome of the generated images.
The seed value of the generator can be fixed to reproduce the same image consistently.
Stable Diffusion and Wife Diffusion models can be used to generate a wide range of imaginative images.
For further inspiration, one can search for examples on Twitter where people share their generated images.