This new Outpainting Technique is INSANE - ControlNet 1.1.

AIKnowledge2Go
9 Jul 202305:09

TLDRIn this video, the presenter introduces an advanced outpainting technique using ControlNet 1.1 for AI art creation. They challenge themselves to explain the installation process in under 40 seconds and guide viewers through downloading necessary model files. The video demonstrates how to use ControlNet with the 'intent only' plus 'llama' model for cleaner and more concise results. The presenter shares their process of outpainting with a realistic 3.1 model, setting up resolution, denoising strength, and using the 'resize and fill' option for better image quality. They also show how to upscale images and outpaint images not originally created with Stable Diffusion, offering a comprehensive guide to enhancing AI art workflows.

Takeaways

  • 🖥️ The video introduces a new outpainting technique using ControlNet 1.1.
  • ⏱️ The presenter challenges themselves to explain the installation of ControlNet in under 40 seconds.
  • 📂 The installation process involves downloading ControlNet, installing it via the extensions, and restarting the application.
  • 📁 After installation, specific model files (pth and yaml) need to be downloaded and placed in the correct folder.
  • 🖼️ The video uses 'realistic 3.1', a model suitable for creating hyper-realistic art.
  • 🏰 A prompt image with a landmark or central subject is recommended for outpainting.
  • 🛠️ ControlNet is set up with 'impainting only' and 'intent only plus llama' for better results.
  • 🔍 The 'resize and fill' option is chosen over 'resize' or 'crop and resize' to maintain image quality.
  • 🎛️ Denoising strength is set high (between 0.75 and 1) to introduce significant changes.
  • 🔄 The video includes a subscription intermission, emphasizing the importance of audience feedback.
  • 🔍 For upscaling, the video suggests disabling ControlNet and adjusting the denoising strength and sampler settings.
  • 🖌️ The technique can be applied to images not originally created with Stable Diffusion.
  • 📊 The video corrects a previous mistake regarding image downsampling during inpainting.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is a new outpainting technique using ControlNet 1.1 for creating hyper-realistic art.

  • How long does the presenter challenge themselves to explain the installation of ControlNet?

    -The presenter challenges themselves to explain the installation of ControlNet in 40 seconds or less.

  • What are the two files needed to install ControlNet?

    -The two files needed for the installation are the 'pth' file and the 'yaml' file.

  • Where should the downloaded 'pth' and 'yaml' files be placed after downloading?

    -The downloaded 'pth' and 'yaml' files should be placed in the 'stable Fusion folder under model control net'.

  • Which model does the presenter use for outpainting?

    -The presenter uses the 'realistic 3.1' model for outpainting.

  • What is the purpose of using 'impant only' and 'llama' in combination?

    -Using 'impant only' and 'llama' in combination aims to get the best results by combining the strengths of both AI models for inpaintings.

  • What resolution does the presenter set for the image during the outpainting process?

    -The presenter sets the resolution to 1024 by 768 for the image during the outpainting process.

  • What is the recommended denoising strength when using ControlNet for outpainting?

    -The recommended denoising strength is between 0.75 and 1, with 0.9 being used in the example.

  • How does the presenter upscale the image after outpainting?

    -The presenter upscales the image by sending it to 'image to image', setting the resize to 2, and adjusting other settings such as disabling ControlNet and setting the denoising strength to 0.2.

  • What is the presenter's advice for outpainting images not created with Stable Diffusion?

    -The presenter advises using 'inpaint only' and 'resize and refill' options, and knowing the current image resolution to outpaint images not created with Stable Diffusion.

  • What mistake did the presenter make in their last video, as pointed out by the community?

    -The presenter mistakenly stated that the whole image would be down-sampled during inpainting, which is not the case when using a mask.

Outlines

00:00

🎨 'Out Painting' with ControlNet

The video introduces a preferred technique for out painting using ControlNet, a tool that helps in filling in missing or masked parts of an image. The presenter challenges themselves to explain the installation process in under 40 seconds. The steps include installing ControlNet from the extensions menu, downloading the necessary .pth and .yaml files, and placing them in the correct folder. The video then proceeds to demonstrate the use of ControlNet with the 'Intent Only' and 'Llamas' models for inpainting, aiming for hyper-realistic results. The presenter sets up the resolution, denoising strength, and other parameters for optimal results. The final rendered image is showcased as an example of the technique's effectiveness.

05:00

📈 Upscaling and Text-to-Image Techniques

In the second paragraph, the script discusses methods for upscaling images and using text-to-image features with ControlNet. The presenter shares a simple workflow for upscaling using the 'Image to Image' function with specific settings like disabling ControlNet and adjusting the denoising strength. They also demonstrate how to inpainting images not originally created with Stable Diffusion by loading an image and setting the resolution. The results from using 'Inpaint Only' and 'Inpaint Plus Llamas' are compared, with a preference for the latter's cleaner and more realistic output. The video concludes with a prompt example ('girl in medieval city full Moon heavy rain') and acknowledges a mistake from a previous tutorial regarding the resolution of inpainted areas.

Mindmap

Keywords

💡Outpainting

Outpainting is a technique used in digital art and image processing to extend the borders of an image, creating new content beyond the original frame. In the context of the video, outpainting is used to expand the visual canvas of an image, particularly with the help of AI models like ControlNet, to generate seamless and realistic continuations of the artwork.

💡ControlNet

ControlNet is an AI model designed for tasks such as inpainting and outpainting. It is highlighted in the video for its effectiveness in expanding images while maintaining the original style and content coherence. The video demonstrates how to install and use ControlNet for outpainting, emphasizing its importance in achieving high-quality results.

💡Installation

Installation, in the video, refers to the process of setting up the ControlNet AI model for use. The presenter challenges themselves to explain the installation in under 40 seconds, indicating the process involves downloading the necessary files, such as '.pth' and '.yaml', and placing them in the correct directories for the model to function.

💡Stable Diffusion

Stable Diffusion is an AI model mentioned in the video that is used for generating images from textual descriptions. It is part of the workflow for creating new images or expanding existing ones, as showcased when the presenter discusses outpainting images that were not originally created with Stable Diffusion.

💡Inpainting

Inpainting is the process of filling in missing or damaged parts of an image. The video contrasts inpainting with outpainting, noting that while inpainting focuses on restoring areas within an image, outpainting extends the image boundaries. The presenter uses a script called 'Poor Man's outpainting' as a beginner's approach but finds it mediocre, preferring the use of ControlNet.

💡Model

In the context of the video, a 'model' refers to the AI algorithms used for generating images. The presenter mentions downloading specific models, such as 'realistic 3.1', which is used for creating hyper-realistic art. Models are essential for the AI to understand and produce the desired outcomes in image processing tasks.

💡Resolution

Resolution is a term used to describe the number of pixels in an image, dictating its size and detail. The video discusses setting the resolution to '1024 by 768' when using ControlNet for outpainting, indicating that higher resolution can provide more detailed and clearer images.

💡Denoising Strength

Denoising Strength refers to the intensity at which an AI model reduces noise or artifacts in an image. In the video, the presenter sets the denoising strength to 0.9 when using ControlNet, suggesting that a higher value can lead to cleaner and more realistic image outcomes by reducing unwanted visual noise.

💡Sampler

A 'sampler' in AI image generation refers to the algorithm that selects and combines different elements to create a new image. The video mentions setting the sampler to 'DPM plus plus 2m carrots', which is a specific configuration that influences how the AI generates the image, affecting the final output's style and quality.

💡Text-to-Image

Text-to-image is a process where AI models generate images based on textual descriptions. The video demonstrates how to use this process for outpainting by loading an existing image and specifying its resolution, then generating new images based on textual prompts, showcasing the flexibility of AI in creating customized artwork.

💡Mask

A 'mask' in the context of the video is a tool used to define areas of an image that the AI should focus on, particularly when inpainting. The presenter corrects a previous mistake by clarifying that when using a mask, the inpainted area retains the resolution set by the user, allowing for increased detail in that specific area.

Highlights

Outpainting technique using ControlNet 1.1

Installation challenge in under 40 seconds

How to install ControlNet with step-by-step instructions

Downloading and applying the necessary model files

Using realistic 3.1 model for hyper-realistic art creation

Setting up ControlNet for outpainting

Using 'Poor Man's outpainting' script for beginners

Combining inpainting and llama models for better results

Choosing 'ControlNet' and 'resize and fill' options

Setting denoising strength for quality output

Loading the same image in Image-to-Image for rendering

Result showcase of the outpainting technique

Importance of subscribing for content creators

Upscaling method to be shown in the next video

Simple workflow from the last video

Disabling ControlNet and adjusting settings for upscaling

Comparing results of inpainting only and inpainting plus llama

Outpainting images not created with Stable Diffusion

Using inpainting only without a prompt

Winner selection based on subjective perception

Correction of a mistake from the last tutorial

Details within painting increase when using a mask

Suggestion to watch the basic workflow tutorial for struggling artists