【最新版】fast DreamBoothでオリジナルモデルを作る方法。Stable Diffusion v2.1対応です。

Shinano Matsumoto・晴れ時々ガジェット
7 Jan 202311:57

TLDRThe video script introduces a method for creating an AI-based portrait model using 30 original images. It guides viewers through the process of using FastStableTableDiffusion and DreamBooth, including setting up access to Google Drive, selecting the appropriate version of the model, and uploading images. The script emphasizes the importance of diverse image selection to avoid bias in the output and provides tips on model training, including the use of free and premium plans, as well as the significance of learning rates and checkpoint saves. The goal is to achieve a satisfactory result with the given steps and resources.

Takeaways

  • 🎨 The script discusses creating an AI-based drawing model using a service called FastStableTableDiffusion.
  • 🖼️ Users are instructed to prepare 30 original images for the model to learn from.
  • 🔗 The process involves using a link in the video description to access a GitHub page with detailed instructions.
  • 💾 It is recommended to have at least 15GB of Google Drive storage to accommodate the model and its files.
  • 📋 The script provides a step-by-step guide on how to set up and use the service, including granting access to Google Drive.
  • 🎨 Users can choose between different versions of the Stable Diffusion model, with 1.5 being more user-friendly.
  • 🖼️ The images used for training should be diverse, including different poses, backgrounds, and outfits to avoid bias in the AI's output.
  • 📂 The script explains how to upload the images to the service and set up the training environment.
  • 📈 The training process can be monitored and adjusted, with options to add more steps if the initial results are not satisfactory.
  • 🚀 The free plan allows for up to 1500 steps of training, while a paid plan offers more steps and a stress-free experience.
  • 🔄 The script emphasizes the importance of following the instructions carefully to achieve the best results from the AI drawing model.

Q & A

  • What is the main topic of the video script?

    -The main topic of the video script is about creating an AI-based drawing model using one's original images with the Fast Stable Diffusion model.

  • How many original images are needed to create the AI drawing model?

    -To create the AI drawing model, one needs to prepare 30 original images.

  • What is the recommended Google Drive storage capacity for this process?

    -It is recommended to have around half of the 15GB Google Drive capacity free, which is at least 7.5GB, but 3GB is the minimum requirement.

  • What are the differences between the Stable Diffusion 1.5 and 2.1 versions?

    -The 1.5 version is more user-friendly and does not have strong adult filters, while the 2.1 version has a higher quality but may include more mature content. The 1.5 version is recommended for general use.

  • How does one access the Google Drive for this process?

    -Access to Google Drive is granted by clicking the folder icon and allowing the necessary permissions. The process is completed once the user grants access.

  • What is the role of the 'Hanging Face' talk in the process?

    -The 'Hanging Face' talk is a step in the process where the user agrees to the terms and conditions to proceed with the AI model creation.

  • How can one obtain the model token for the process?

    -The model token can be obtained from the user's account settings and then pasted into the designated field in the process.

  • What should be considered when selecting the images for the AI model?

    -The images should be diverse, showing different variations of the subject, such as different poses, backgrounds, and outfits. It is important to avoid having a consistent background or element, like Tokyo Tower, as it may become part of the output.

  • What happens if the learning rate is set too high?

    -If the learning rate is set too high, the training process will complete in fewer steps, but the learning will be less precise, potentially leading to less satisfactory results.

  • How long does it take to train the model with 3000 steps?

    -It takes approximately 50 minutes to train the model with 3000 steps.

  • What should one do if the output is not satisfactory after the initial training?

    -If the output is not satisfactory, one can add more training steps by using the 'Add Training' button, setting the Text Encoder Training to 0, and executing the additional training steps.

Outlines

00:00

🎨 Introduction to AI Art Generation with Stable Diffusion

The paragraph introduces the concept of using AI for art generation, specifically with the Stable Diffusion model. It discusses the creation of an AI art model using 30 original images and the importance of updates to the model. The process involves accessing Google Drive, selecting the Stable Diffusion model version, and setting up the model with the provided images. The paragraph emphasizes the need for sufficient Google Drive storage and the basic steps to get started with the AI art generation process.

05:01

📸 Preparing Images and Understanding Prompts

This paragraph delves into the specifics of preparing images for the AI model, emphasizing the need for variety in the images to avoid learning unwanted elements like backgrounds. It explains how to label the images with prompts and the potential consequences of not doing so, such as the AI learning to include background elements in the generated art. The paragraph also touches on the importance of diverse images to ensure a broad range of outputs and the process of uploading and selecting images for the AI to learn from.

10:01

🛠️ Training the AI Model and Adjusting Settings

The focus of this paragraph is on the training process of the AI model. It outlines the steps to train the model, including adjusting settings such as the learning rate and the number of training steps. The paragraph provides guidance on how to navigate the interface, select the appropriate model version, and save checkpoints at specific intervals. It also discusses the option to add more training steps if the initial results are not satisfactory and the importance of using a paid plan for a smoother and more extensive training process.

Mindmap

Keywords

💡FastStableTableDiffusion

FastStableTableDiffusion is a term that likely refers to a specific model or version of a diffusion-based AI system used for image generation. In the context of the video, it is an essential tool for creating AI-generated art. The script mentions different versions such as 1.5 and 2.1, indicating updates and improvements to the model over time. The choice between these versions affects the style and quality of the generated images.

💡DreamBooth

DreamBooth is a concept that seems to be related to a feature or process within the AI system for creating personalized art. It is likely a method for training the AI with specific images to generate art that reflects certain themes or subjects. The video script suggests that DreamBooth allows users to tailor the AI's output to their preferences by providing it with a set of images to learn from.

💡AI Art Generation

AI Art Generation is the process of using artificial intelligence to create visual art. This technology has advanced to the point where it can produce high-quality images based on user input, such as original images or concepts. In the video, the focus is on using AI models like FastStableTableDiffusion and DreamBooth to generate customized artwork, demonstrating the intersection of technology and creativity.

💡Google Drive

Google Drive is a cloud storage service that allows users to store and share files online. In the context of the video, it is used as a platform to store and access the images and AI models required for the image generation process. The script emphasizes the importance of having sufficient storage capacity on Google Drive to accommodate the files associated with the AI art generation process.

💡Collaboration Plan

The Collaboration Plan refers to a tier or subscription level within the AI art generation platform that offers additional features and capabilities beyond the free plan. It allows for more in-depth and extensive use of the AI system, such as running more steps for image generation and accessing a stress-free experience. The video script suggests that those who wish to delve deeper into AI art generation might consider subscribing to the Collaboration Plan for a better and more extensive experience.

💡Training Steps

Training Steps refers to the number of iterations or cycles the AI model undergoes during the learning process. In AI art generation, more training steps often result in more refined and accurate outputs as the model learns from the provided images. The video script discusses the importance of selecting the right number of training steps to achieve satisfactory results, with options to increase the steps for better quality.

💡Image Upload

Image Upload is the process of transferring image files from a local storage device to a cloud service or an AI platform. In the context of the video, uploading images is a crucial step in preparing the AI model for generating art, as the AI learns from these images to produce new content. The script provides instructions on how to upload images to Google Drive and use them for training the AI in creating art.

💡Token

In the context of the video, a Token is a unique string or key that grants access to certain features or services within the AI platform. It is used to authenticate and authorize users to utilize the system's functionalities. The script mentions obtaining a token from settings and粘贴 it into the platform, which is necessary for the AI art generation process to proceed.

💡Model Download

Model Download refers to the process of obtaining the AI model files from a platform or service, typically for use in generating images or other outputs. In the video, downloading the appropriate model, such as FastStableTableDiffusion 1.5 or 2.1, is a key step in setting up the AI art generation environment. The choice of model affects the style and quality of the generated images.

💡Prompt

In the context of AI art generation, a Prompt is a term or phrase that guides the AI in creating a specific image. It serves as a description of the desired output and is used by the AI model to understand what kind of image to generate. The video script discusses the importance of preparing prompts carefully to ensure the AI generates the desired artwork.

💡Learning Rate

The Learning Rate is a hyperparameter in machine learning models that determines how much the model adjusts its internal parameters based on the data it learns from. A higher learning rate means the model will make larger adjustments during training, potentially leading to faster learning but also a higher risk of not converging to the optimal solution. In the video, adjusting the learning rate is part of fine-tuning the AI art generation process to achieve better results.

💡Save Checkpoint

Save Checkpoint refers to the practice of periodically saving the state of a machine learning model during the training process. This allows the training to be resumed from that point if needed, without losing progress. In the context of the video, saving checkpoints is a feature that can be configured to automatically save the model at specific intervals, ensuring that progress is not lost if the training process is interrupted.

Highlights

The introduction of creating an AI-based drawing model using one's own original images.

The detailed process of using Google Drive for storing and accessing the required data for the AI model.

The importance of having a minimum of 3GB of free space on Google Drive for the AI model to function effectively.

Accessing and utilizing the DreamBooth model for personalized AI drawing.

The explanation of the differences between Stable Diffusion 1.5 and 2.1, and their respective suitability for different users.

The process of downloading the Stable Diffusion model and setting up the necessary tokens and paths for the AI drawing process.

The significance of preparing 30 images for training the AI model, with considerations for variations and consistency in prompts.

The caution against including background elements in training images to prevent unwanted outputs in the AI-generated drawings.

The step-by-step guidance on how to upload and select the images for training the AI model.

The explanation of the training process, including the selection of steps and the impact on the quality and output of the AI model.

The option to save checkpoints during the training process and the recommendation on how often to save based on the available storage.

The provision of a test run of the AI model after the initial training to evaluate its effectiveness and make necessary adjustments.

The suggestion to use the paid plan for a stress-free and more in-depth training experience with the AI model.

The guidance on how to access and download the trained AI model for future use.

The note on the potential for significant time investment in the training process, emphasizing the value of patience and iterative learning.

The mention of the possibility to continue training with additional steps if the initial results are not satisfactory.

The final reminder to monitor the training process and make adjustments as needed to achieve the desired outcome with the AI model.

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