AIは手が苦手過ぎる～！のでControlNetとデプスライブラリで修正してみよう！使用方法解説！【Stable Diffusion】
TLDRAIが手の描き方を苦手としている問題を解決するために、ControlNetとDepth Map Library & Poserを利用する方法を紹介します。ControlNetを更新し、DepthMapライブラリをインストールして、手の形状を正確に修復する方法を学びます。T2iでは手の修正には限界があるため、既に生成された画像をI2iで修正する方法も提案します。HiRes.fixを使用して、高解像度の画像を生成しながら手の部分を修正する方法も紹介します。
Takeaways
- 😀 AIは手の形成が苦手であることから、ControlNetとDepthMapライブラリを使用して修正する方法を解説。
- 👍 ControlNetをアップデートしてからDepthMapライブラリをインストールする手順が説明されています。
- 📚「Depth Map Library & Poser」を用いて、手のディテクトマップを読み込み、AIの苦手な部分を修正します。
- 🔧 手の修正には限界があるため、生成された画像を直接修正する方法（I2i）が効果的です。
- 🔄 HiRes.fix機能を使用して、生成した画像をアップスケールし、プロンプトに応じて画像を調整します。
- ✨ T2i（テキストから画像へ）とI2i（画像から画像へ）のプロセスを同時に実行する方法が提案されています。
- 🖌 手のポーズをDepthライブラリから選択し、適切な位置やサイズに調整する方法が解説されています。
- 🔄 生成した画像に手の修正を加えた後、Control Netを介して再度画像生成を行うプロセスが説明されています。
- 🎨 AIはベースノイズから不要なノイズを取り除くことで画像を生成するため、同じシード値を使っても異なる結果が得られる可能性があります。
- 👀 最終的な画像の品質向上のためには、Control Netの影響を調整することが重要です。
Q & A
What is the main issue the video addresses with AI-generated images?
-The main issue the video addresses is the difficulty AI has in accurately generating precise and well-formed hands in images.
What is Control-Net and how does it help with the hand issue?
-Control-Net is an extension that extracts outlines, referred to as DetectMaps, to specialize in certain aspects of image generation. It helps with the hand issue by allowing users to adjust and correct the hands in AI-generated images using these specialized maps.
How does the Depth Map Library & Poser function in fixing hands?
-The Depth Map Library & Poser function by reading hand-shaped detect maps in ControlNet and using them to fix hands that AI is not good at. It allows users to add, adjust, and save hand shapes to improve the accuracy of hand depictions in images.
What is the process of updating Control-Net?
-To update Control-Net, users need to launch WebUI, open the extension tab, press the Check for Update button, apply and restart the browser and CMD after the update is complete.
How is the DepthMap library installed?
-To install the DepthMap library, users access the 'SD-WebUI-Depth-Lib' page on GitHub, copy the URL, and paste it into the Install From URL tab in the extension tab of WebUI. After pressing the install button and restarting the browser, the DepthLibrary tab will appear for use.
What is the limitation of fixing hands in T2i?
-The limitation of fixing hands in T2i is that it is generated from noise, and the result can change significantly due to the interference of Control-Net, making it difficult to achieve a perfect hand shape.
How can an image that has already been generated be modified effectively?
-An already generated image can be modified effectively by using the image to image function, saving the hand in the Depth library, and loading the saved hand from the I2i Control Net.
What is InPaint and how is it used to fix hands?
-InPaint is a feature that performs I2i locally. It is used by opening the original image in the InPaint tab and filling in the parts that need fixing. The trick is to fill in a little wider, upscale the resolution, and adjust the settings to achieve the desired result.
How does HiResfix function and how can it be used to fix hands?
-HiResfix is a function for advanced users that upscales an image created with T2i while taking into account the prompts. It can be used to find a favorite image, turn off HiResfix, recreate it, and then fix the hand with the I2i part before going back to the main process.
What are the recommended settings for HiResfix?
-Recommended settings for HiResfix include choosing a high-quality upscaler like Real-ESRGAN or SwinIR, setting the HiRes-step to about one-third to half of the T2i sampling step, and adjusting the denoising strength to a safe range of 0.5 to 0.7.
What is the significance of the hand in human expression and how does it affect AI-generated art?
-Hands are organs that express 'thoughts' in humans. However, current AI-generated art struggles to accurately depict and express these 'thoughts' through hands, often resulting in less accurate or messy hand depictions.
Outlines
🖌️ Introduction to Depth Map Library & Poser for AI-generated Art
This paragraph introduces the challenges of creating precise hand details in AI-generated art, as experienced in the previous video. The speaker, Robin, along with Teruru, tackles this issue by utilizing the 'Depth Map Library & Poser' extension, which was previously installed with the 'Control-Net' extension for outline extraction. The segment covers the process of updating ControlNet, installing the DepthMap library from GitHub, and using it to correct hand details that AI often struggles with. It explains the concept of a DetectMap and how it serves as a specialized catalog for hand shapes. The paragraph concludes with a practical demonstration of using the DepthMap Library to fix the hands of a generated figure in T2i, while also discussing the limitations of hand modification within T2i due to the nature of noise-based generation and the influence of ControlNet on the final output.
🔄 Effective Hand Modification Techniques in AI Art
The second paragraph delves into the limitations of directly modifying hands in T2i, given the噪 (noise) from which AI generates images. It suggests an alternative approach of modifying pre-existing images for better hand details. The process of using image-to-image translation (I2i) is explained, where the original image is sent from PNG info to I2i, and the hand is saved and loaded from the I2i Control Net. The paragraph discusses the upscaling process, the impact of denoising strength, and the potential need for adjustments in hand position in the Depth library. It also introduces the InPaint feature for local image editing and compares the results of upscaling in both I2i and InPaint. The section concludes with a suggestion to change one's perspective on the image, considering the overall atmosphere and focusing on the image after I2i processing rather than before.
🤖 Combining T2i and I2i with HiRes.fix for Enhanced AI Art
The final paragraph discusses the use of HiRes.fix, a feature designed for advanced users that combines the capabilities of T2i and I2i. HiRes.fix is presented as a function that upscales images created with T2i while considering the prompts, and it performs I2i after T2i. The paragraph provides a step-by-step guide on using HiRes.fix to find a favorite image, recreate it without HiRes.fix, and then use I2i to fix parts like hands. It explains the settings for HiRes.fix, including the upscaler, the number of steps in I2i, denoising strength, and the importance of adjusting these settings according to the desired output. The paragraph concludes with a practical example of fixing a hand using HiRes.fix, I2i, and the Depth library, highlighting the improved results and the importance of considering the overall image composition and model limitations when working with AI-generated art.
Mindmap
Keywords
💡AI
💡ControlNet
💡Depth Map Library & Poser
💡T2i
💡手の修正
💡Depth Library
💡I2i
💡HiRes.fix
💡Seed Value
💡Noise
💡Control Net Weight
Highlights
AIは手の表現が難しい問題に取り組む
ControlNetとDepth Mapライブラリを使って手を修正する方法を紹介
ControlNetの更新方法と手順説明
DepthMapライブラリのインストールと使い方
手のDetectMapを使った手の修正方法
T2iでの手の修正には限界がある
DepthLibraryを使って手の形を正確に表現する方法
I2iでの手の修正とアップスケールのテクニック
InPaintを使った手の修正方法と注意点
HiRes.fix機能を使った高解像度な画像の生成と手の修正
AIが生成する画像は「描く」のではなく「生成する」
ControlNetの介入によって生成結果が変化する理由
手の修正が難しい理由とその対策
I2iとInPaintの比較とどちらが適しているか
HiResfixを使ったT2iとI2iの同時処理方法
手の修正にあくまでも一つの方法であること
AIが手をどのように表現するかの限界と今後の可能性