【Stable-Diffusion】🔰ペイントソフト不要！手の修正方法 #stablediffusion #ControlNet #openpose #canny #Lamacleaner
TLDRIn this informative video, the presenter introduces a method for refining hand gestures in 3D models using ControlNet and other advanced features in Stable Diffusion. The tutorial covers the preparation of ControlNet and the registration of hand correction styles, followed by a detailed walkthrough of using OpenPose & Canny techniques for natural-looking hand adjustments. The video also touches on the use of RamaCleaner for minor touch-ups, offering a comprehensive guide to enhance the realism of 3D character animations.
Takeaways
- 🎨 The video discusses a method for refining hand gestures in 3D models using ControlNet and additional features without relying on paint software.
- 📐 ControlNet is a powerful extension for Stable Diffusion that comes with a variety of tools, likened to a toolbox filled with excellent tools.
- 🤲 The video introduces the use of OpenPose and CanvasZoom, which help in extracting poses and refining the hand gestures of the model.
- 🖌️ The process involves three main steps: preparing ControlNet and its extension, registering hand correction style templates, and using OpenPose & Carry methods for refinement.
- 👐 The video emphasizes the importance of having the correct model for the tools used in ControlNet, which need to be downloaded separately.
- 🔍 The video provides a detailed explanation of how to install and use the ControlNet extension and the required model files from Hugging Face.
- 🌟 The presenter demonstrates the process of refining hand gestures by using the OpenPose editor to adjust the pose and structure of the hands.
- 🖱️ CanvasZoom and other extensions like RamaCleaner are introduced as additional tools to enhance the user experience and workflow.
- 🔄 The video highlights the iterative nature of the refinement process, showing multiple attempts to achieve a more natural look for the hands.
- 🎯 The use of negative prompts (e.g., 'Bad Hands', 'Missing Fingers') is suggested to suppress unwanted hand gestures and improve the final result.
- 💡 The video concludes by encouraging viewers to experiment with the techniques presented and to look forward to future tutorials that delve deeper into ControlNet's capabilities.
Q & A
What is the main topic of the video?
-The main topic of the video is about using ControlNet and other extension functions to correct and improve the appearance of hands in 3D models without the need for paint software.
What are the three steps involved in the hand correction process using ControlNet?
-The three steps involved are: 1) Preparing the ControlNet extension and its tools, 2) Registering a hand correction style template, and 3) Utilizing OpenPose & Carrier method for further refinement.
How does the ControlNet extension function within the software?
-ControlNet functions as a toolbox filled with various tools that aid in image generation and manipulation within the software. It is considered a must-have extension for stable diffusion image generation.
What is the purpose of the 'Negative Prompts' in the hand correction process?
-Negative Prompts are used to specify undesired features or elements, such as 'Bad Hands', 'Missing Fingers', or 'Extra Fingers', to guide the AI away from generating such issues in the final output.
What is the role of the 'Lam Cleaner' extension?
-The 'Lam Cleaner' extension is used to clean up unwanted parts of an image. It acts like an eraser, allowing users to remove specific elements from the image by painting over them.
How does the 'Canvas Zoom' extension help in the editing process?
-The 'Canvas Zoom' extension helps users to zoom in and out of the canvas for detailed work. It provides functionalities like maximizing the view, adjusting brush size, and returning to a previous state, which are useful for precise editing tasks.
What is the significance of the 'Inpaint' process in the hand correction?
-The 'Inpaint' process is used to fill in and correct specific areas of the image. It uses the surrounding pixels and the content of the image to regenerate the selected area, which is particularly useful for fixing the shape of hands.
Why is it important to download the JSON data during the editing process?
-Downloading the JSON data is important as it serves as a backup of the progress made during the editing process. It prevents loss of work in case the web UI stops working or encounters errors.
How does the 'Canny' processor help in refining the image?
-The 'Canny' processor is used to extract lines and edges from the image, which can then be used to refine the details and ensure that the hands and other elements of the image blend naturally with the rest of the artwork.
What are some of the positive outcomes of using ControlNet for hand correction?
-Using ControlNet for hand correction allows for more natural and precise adjustments to the hand's shape and position. It also eliminates the need for external paint software, streamlining the editing process within the same platform.
What is the role of 'Prompts' in the context of the video?
-In the context of the video, 'Prompts' are used to guide the AI in generating or modifying specific aspects of the image. For example, 'Positive Prompts' like 'Perfect Hand' or 'Natural Finger Position' can help in achieving the desired outcome for the hand correction.
Outlines
🎨 Introduction to 3D Transformation and Hand Correction Techniques
The video begins with an introduction to the AI channel's host, who has transformed from 2D to 3D. The host discusses the challenges of hand correction in detail, mentioning the use of Depth Library for inpainting and the subtle issues that arise. The host then introduces a method using ControlNet and an extension function for natural hand correction without the need for paint software like Photoshop.
🛠️ Preparing ControlNet and Additional Extensions
The host explains the process of preparing ControlNet and additional extensions, including Canvas Zoom and Cleanup Cleaner. Detailed instructions are provided on installing the extensions from GitHub URLs and downloading the necessary tool models from Hanging Face. The host emphasizes the importance of storing the downloaded models in the correct folders for stability and functionality.
🖌️ Creating and Registering Hand Correction Styles
The host guides the audience through creating and registering hand correction styles, which are similar to the Hins template but focus solely on hand elements. The process involves using the ControlNet's tools to extract poses and refine the hand shapes. The host also discusses the importance of having the right prompt and parameter information for successful inpainting.
📐 OpenPose & Carry Method Explanation
The host delves into the OpenPose & Carry method using ControlNet, explaining the process of extracting poses and refining hand shapes. The host demonstrates how to use the OpenPose Editor to adjust hand positions and correct any issues. The explanation includes the use of various processors and the importance of aligning the pointers correctly to achieve the desired hand shape.
🎨 Inpainting and Final Touches
The host shows the process of inpainting and making final adjustments to the hand shapes using the inpainting function. This includes using the brush tool to paint over specific areas and adjusting the size and position of the hand joints. The host also discusses the use of the Canvas Zoom function for precision and the importance of aligning the hand shape with the desired pose.
🔄 Iterative Adjustments and Positive Prompts
The host explains the iterative process of adjusting the hand shapes using both the OpenPose bone structure and positive prompts to enforce the desired hand shape. The host emphasizes the use of negative prompts to suppress unwanted hand deformations and the importance of using specific hand gestures and poses to improve the accuracy of the final image.
🌟 Finalizing the Image and Backup Recommendations
The host concludes the video by discussing the final steps of the hand correction process, including the use of positive prompts to refine the image further. The host recommends backing up the JSON data to prevent loss of progress and provides tips on how to download and save the data for future use.
🧹 Using the Ramacleaner for Fine-Tuning
The host provides a brief explanation of the Ramacleaner tool, which is used for fine-tuning and removing unwanted elements from the image. The host demonstrates how to use the tool to selectively erase parts of the image and emphasizes its convenience for making precise adjustments without the need for external software like Photoshop.
Mindmap
Keywords
💡ControlNet
Highlights
The video introduces a method for changing a 2D model to 3D, showcasing the process and its results.
The main topic of the video is about fixing hand的姿势 in generated images, which is a common issue in AI-generated art.
The video discusses the use of ControlNet, an extension feature that provides a suite of tools for image generation and manipulation.
ControlNet can be used with various models, such as Canny, Depth, Normal Map, and Open Pose, each serving different functions in image processing.
The video provides a step-by-step guide on how to install and use ControlNet and its associated models and tools.
The video demonstrates the use of Open Pose and Canny methods for hand correction, offering a more natural look without the need for paint software.
The video emphasizes the importance of having the correct prompts and parameters for successful image refinement using ControlNet.
The process involves three main steps: preparing ControlNet and its extension features, registering hand correction styles, and using Open Pose & Canny methods for refinement.
The video provides practical advice on how to adjust hand shapes and positions to better fit the overall image composition.
The video showcases the use of negative prompts to suppress unwanted elements, such as 'Bad Hand' and 'Missing Finger', to improve the final image.
The video explains how to use the Canvas Zoom and Cleaner features for更方便的 image editing and manipulation.
The video demonstrates the iterative process of refining hand positions and shapes, highlighting the importance of patience and attention to detail.
The video concludes by showing the final results of the hand correction process, comparing the before and after images to illustrate the improvements.
The video encourages viewers to experiment with different ControlNet tools and settings to find the best approach for their specific image editing needs.
The video ends with a call to action for viewers to like, subscribe, and comment on the video if they found it helpful or have further questions.