[SD 06] Stable Diffusion 설치부터 응용 시리즈 - img2img 사용법

조피디 연구소 JoPD LAB
28 Jan 202407:31

TLDRIn this video, the host, JopD, continues the series on Stable Diffusion A, focusing on mastering image-to-image (Img2Img) transformations after covering text-to-image in previous chapters. JopD explains how Img2Img can transform an existing image into another through various options and features, including the inpainting technique. The video also introduces ways to retrieve prompts for previously generated images and explores different settings like resizing modes and denoising strength. Furthermore, practical tips on improving image modifications, such as changing dresses or removing cars from a scene, are provided. This episode promises to elevate viewers from beginners to proficient users of image-to-image AI tools.

Takeaways

  • 📚 The session continues with a Stable Diffusion course, building on the previous chapters that covered text and image mastery.
  • 🎨 Today's focus is on 'Image-to-Image', a technique that generates new images using existing ones as a basis.
  • 🔍 To find the prompt used for an image created by Stable Diffusion, drag the image into the input area, which will display all the information including settings.
  • 🚫 The prompt analysis feature is exclusive to images generated by Stable Diffusion Pro and cannot be used for images created with other AI tools or downloaded from the internet.
  • 🌟 Two types of generators are introduced: 'Interrogator Clip' for sentence prompts and 'Interrogator Back' for word prompts, with the latter being preferred for its conciseness.
  • 🎨 The session demonstrates transforming an image into a cartoon style by changing the model settings and using the 'Generate' button to create the new image.
  • 📏 The 'Resize' options are explained, including 'Just Resize', 'Crop and Resize', 'Resize and Fill', and 'Latent Upscale', each with its own use case and considerations.
  • 🎭 The importance of 'Denoising Stress' is highlighted, which adjusts the degree of deviation from the reference image based on the set value.
  • 🖌️ 'Inpaint' is a feature that allows selective editing of an image using a mask to refine specific parts while keeping the surrounding context intact.
  • 🎨 The script showcases the versatility of the 'Inpaint' tool by changing the dress of a person in the image and explaining the different mask modes and their applications.
  • 🚗 A practical example is given on how to remove unwanted elements, such as cars, from an image using the 'Masked Content' option with 'Latent Noise' selected.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is about learning to use the image-to-image feature in the Stable Diffusion AI tool.

  • What was covered in the previous chapters?

    -In the previous chapters, the user learned about text and image mastery within the first five chapters of the course.

  • How can you identify the prompt used for an image generated in Stable Diffusion if you don't remember it?

    -You can identify the prompt by dragging the image into the input area of the prompt, and the tool will display all the information, including the prompt and settings.

  • What is the difference between the two options added for image-to-image, the 'Interrogator Clip' and 'Interrogator Back'?

    -The 'Interrogator Clip' generates a sentence-based prompt, while the 'Interrogator Back' creates a word-based prompt. Both analyze the image and provide a text prompt.

  • How does the 'Cartoon Style' transformation work in the video?

    -The 'Cartoon Style' transformation is achieved by changing the check point model to a cartoon model and adjusting the VAE 1 to 'Nimi', which maintains the structure of the image while changing its style to cartoonish.

  • What are the different 'Resize' modes available in the image-to-image tool?

    -The 'Resize' modes include 'Just Resize', 'Crop and Resize', 'Resize and Fill', and 'Latent Upscale'. Each mode offers a different way to adjust the size of the image, taking into account the aspect ratio and additional space.

  • What is 'Denoising Stress' and how does it affect the generated image?

    -Denoising Stress is a setting that determines the influence of the text prompt on the generated image. A lower value results in minimal changes, while a higher value can produce an entirely different image from the reference.

  • How does the 'Inpaint' feature work in the video?

    -The 'Inpaint' feature allows users to modify parts of an image using a mask. Users can paint over the area they want to change, and the AI will fill in the masked area with the desired pattern or content.

  • What are the different 'Mask Blur' settings and their effects?

    -The 'Mask Blur' settings soften the edges of the mask. A lower setting creates a sharp contrast between the mask area and its surroundings, while a higher setting blends the mask more with the surroundings, but too much can result in an unnatural effect.

  • How can you remove unwanted elements from an image using the image-to-image tool?

    -You can remove unwanted elements by painting over them with a brush, selecting the 'Latent Noise' option for the 'Masked Content', and then generating the image to cleanly remove the elements.

  • What are some of the creative applications of the 'Inpaint' feature shown in the video?

    -The 'Inpaint' feature can be used to change the interior design of an image, correct errors like misplaced fingers, add tattoos, or insert sunglasses into a portrait.

Outlines

00:00

📚 Introduction to Image-to-Image Techniques

This paragraph introduces the concept of image-to-image techniques, emphasizing the transition from mastering text and basic images to creating new images using existing ones. It highlights the learning objectives for the session, which include understanding the overall options and features of image-to-image and studying the inpainting function. The paragraph also provides a tip on how to identify the prompts used in previously generated images in Stable Diffusion, explaining the process of dragging an image into the prompt input area to retrieve all its information and display it in the prompt area. Additionally, it clarifies that this feature is exclusive to images created in Stable Diffusion Pro and cannot be applied to images generated with other AI tools or downloaded from the internet.

05:05

🎨 Exploring Image-to-Image Options and Inpainting

This paragraph delves into the various options available in image-to-image, such as resizing modes, and the inpainting function. It explains the differences between 'Just Resize,' 'Crop and Resize,' and 'Resize and Fill,' detailing how each option handles image dimensions and proportions. The paragraph also emphasizes the importance of denoising stress in image-to-image, which affects the degree of change based on the text prompt. It demonstrates how different denoising stress levels result in varying image outcomes, from minimal changes to completely new images unrelated to the reference image. The paragraph then introduces the 'In Paint' function, which allows for selective image editing using masks. It outlines the process of applying the 'In Paint' function, including setting options and using brushes to modify specific areas of the image.

Mindmap

Keywords

💡Stable Diffusion

Stable Diffusion is a term used in the context of AI-generated images. It refers to a specific AI model that can create new images based on given prompts or existing images. In the video, it is the primary tool discussed for image generation and manipulation, showcasing its capabilities in transforming and enhancing images through various settings and options.

💡Image-to-Image

Image-to-Image is a concept that involves using one image to generate another, which is a core focus of the video. It is a feature within AI image generation models like Stable Diffusion, allowing users to transform and create new images based on the input, such as changing styles or adding elements to the original image.

💡Prompt Analysis

Prompt Analysis refers to the process of understanding the prompts used to generate AI images. It is crucial for users who want to recreate or modify images based on previous creations. In the video, the speaker explains how to analyze the prompts by dragging an image into the input area to retrieve the original prompt and settings, which is essential for replicating or refining the image generation process.

💡Interrogator

Interrogator is a feature within AI image generation tools that analyzes images to provide text prompts. It comes in two forms: Interrogator Clip, which provides sentence-based prompts, and Interrogator Behind, which offers word-based prompts. The choice between these two can affect the creativity and direction of the new images generated, allowing users to select the one that best suits their needs.

💡Cartoon Style

Cartoon Style refers to the transformation of an image into a cartoon-like appearance. In the context of the video, this is achieved by applying specific models and settings within the AI tool to alter the image's style, maintaining its structure while giving it a more stylized, animated look.

💡Options and Features

Options and Features refer to the various settings and tools available within AI image generation software that allow users to manipulate and customize their images. These can include resizing, noise reduction, and color adjustments, among others. Understanding and applying these options effectively is key to achieving desired outcomes in image creation and editing.

💡Inpaint

Inpaint is a function that allows users to modify specific parts of an image by painting over certain areas, which are then filled in or altered based on the surrounding content. This feature is useful for making detailed changes, such as fixing errors or adding elements to a photo.

💡Masking

Masking in the context of image editing refers to the process of selecting and isolating specific parts of an image for modification while leaving the rest untouched. It is a crucial technique for targeted image adjustments, such as changing the color or style of a particular element without affecting the rest of the image.

💡Noise Reduction

Noise Reduction is a process that minimizes the graininess or random variations in an image, typically caused by digital zoom or low light conditions. In AI image generation, it can also refer to reducing the noise or randomness in the generated image to make it more coherent and lifelike.

💡Color Adjustment

Color Adjustment involves modifying the hues, saturation, and brightness of an image to achieve a desired aesthetic or to match specific visual requirements. In the context of AI image generation, color adjustments can ensure that the generated images have a consistent and natural look, especially when integrating new elements or changes.

💡Image Upscaling

Image Upscaling is the process of increasing the resolution of an image while maintaining or improving its quality. This is often necessary when working with low-resolution images or when enlarging an image for better visibility or printing purposes. In the video, the speaker explains different methods of upscaling, such as '저스트 리사이즈', '크롭 앤드 리사이즈', and '리사이즈 앤드 필', each serving a different purpose in the image enhancement process.

Highlights

Introduction to the concept of 'Image to Image', a method of generating new images using existing ones.

The ability to analyze previously generated images in Stable Diffusion to retrieve the prompts used for creation.

The exclusive feature of Stable Diffusion Pro for analyzing images and automatically applying options, including seed and settings.

The distinction between 'Image to Image' and 'Text to Image', with the addition of two buttons for 'Interrogator Clip' and 'Interrogator Back'.

The process of transforming an image into a cartoon style by changing the model and VAE settings.

Explaining the 'Resize' options and their impact on image proportions and dimensions.

The importance of 'Denoising Stress' in influencing the degree of change in the generated image based on the text prompt.

The 'In Paint' feature, which allows for selective changes in parts of an image using a mask.

The option to apply color adjustments to the generated image to match the original color scheme for a natural look.

Demonstration of changing a dress pattern in an image using the 'In Paint' function and mask.

Exploring the 'Mask Blur' option for softening the edges of the mask area.

The 'Mask Mode' feature for altering the masked area or the non-masked area of an image.

The various 'Masked Content' options for filling in the masked area with different styles.

Practical application of the 'In Paint' feature to remove unwanted elements, such as cars, from a street image.

The versatility of the 'In Paint' function for changing interiors, correcting errors, adding tattoos, or accessories to images.

A teaser for the next session, promising to explore more diverse applications of the 'In Paint' feature.

The video concludes with a call to action for viewers to subscribe for more advanced content.

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