[SD 06] Stable Diffusion 설치부터 응용 시리즈 - img2img 사용법
TLDRThe video script discusses the process of using Stable Diffusion to create and modify images. It introduces the concept of 'image-to-image' generation, where one image is used to generate another. The script explains various features and options, such as the 'Inpaint' function for detailed modifications, and the 'Mask' feature for selective editing. It also touches on the importance of the 'Denoising Stress' setting and its impact on the final image. The video concludes by encouraging viewers to explore the diverse applications of the 'Inpaint' function and promises to cover more advanced techniques in future content.
Takeaways
- 📚 The session continues with a Stable Diffusion course, building on the knowledge from previous chapters which covered text and image generation.
- 🎨 Today's focus is on 'image-to-image' functionality, which involves creating new images based on existing ones, allowing users to escape beginner status.
- 🔍 To identify the prompt used for an image created by Stable Diffusion, drag the image into the prompt input area, which will display all the image information and settings.
- 🚀 The 'image-to-image' feature is exclusive to images generated with Stable Diffusion Pro and cannot be applied to images created with other AI tools or downloaded from the internet.
- 🌟 Two types of 'interrogators' are introduced: Clip and DeepBlue, which analyze images and generate text prompts, with Clip providing sentence-based prompts and DeepBlue offering word-based prompts.
- 🎨 The session demonstrates transforming an image into a cartoon style by changing the model settings and applying transformations.
- 📏 The 'Resize' option is crucial when dealing with different image sizes, offering several modes: Just Resize, Crop and Resize, Resize and Fill, and Latent Upscale.
- 🎭 The 'Inpaint' feature is highlighted, which uses a mask to modify parts of an image, allowing for detailed adjustments and natural-looking results.
- 🖌️ Mask settings such as 'Mask Blur' and 'Mask Mode' are discussed, emphasizing their importance in achieving a harmonious blend between the edited and unedited parts of an image.
- 🚗 A practical example is given, showing how to remove unwanted elements (like cars) from an image using the 'Masked Content' option with 'Latent Noise' selected.
- 🌈 The versatility of the 'Inpaint' function is emphasized, mentioning its potential for changing interiors, correcting errors, adding tattoos, or inserting sunglasses into images.
Q & A
What is the main topic of the video?
-The main topic of the video is about learning and understanding the features and functionalities of image-to-image generation in Stable Diffusion, including the use of various options and the inpainting feature.
How can you identify the prompt used for an image generated in a previous chapter?
-To identify the prompt used for a previously generated image, you can drag the image into the prompt input area in Stable Diffusion, and the system will display all the information related to that image, including the prompt and settings.
What is the difference between 'Interrogator Clip' and 'Interrogator Background'?
-Interrogator Clip generates a sentence-based prompt, while Interrogator Background creates a word-based prompt. Both analyze the image to produce a text prompt, but the format of the prompt differs.
How does the 'Cartoon Style' transformation work?
-The 'Cartoon Style' transformation works by changing the check point model to a cartoon model and adjusting the VAE to 'nimi', which maintains the structure of the image while changing its style to a cartoonish appearance.
What are the different 'Resize' options available in the image-to-image feature?
-The 'Resize' options include 'Just Resize', 'Crop and Resize', 'Resize and Fill', 'Latent Upscale', and 'Latent Resizing'. Each option handles the resizing of the image differently, considering aspects like maintaining aspect ratio, cropping, filling in the background, and upscaling using a latent space approach.
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 a completely different image from the reference image.
How does the 'Inpaint' feature work in Stable Diffusion?
-The 'Inpaint' feature allows users to modify parts of an image by applying a mask. Users can select the area to be modified, choose a brush size, and input a new prompt to generate the desired change in the image.
What is the purpose of 'Mask Blur' and 'Mask Mode' options in the 'Inpaint' feature?
-Mask Blur softens the edges of the mask area, while Mask Mode determines whether the changes are applied within the masked area or outside of it. These options help in creating a more natural-looking edited image.
What are the different 'Masked Content' options and when would you use them?
-The 'Masked Content' options include 'Fill', 'Original', 'Latent Noise', and 'Latent Rashing'. 'Fill' is used to match the masked area with surrounding colors, 'Original' is for working with areas that fit the surroundings, 'Latent Noise' is for creatively filling the mask area, and 'Latent Rashing' is used to remove unwanted elements.
How can you remove elements from an image using the 'Inpaint' feature?
-To remove elements from an image, you can first mask the area containing the unwanted elements, adjust the size to fit, and then select 'Latent Rashing' from the 'Masked Content' options. After clearing the prompt and clicking the 'Generate' button, the unwanted elements will be removed from the image.
What are some potential applications of the 'Inpaint' feature?
-The 'Inpaint' feature can be used to change interior designs, correct errors in images, add tattoos, or add accessories like glasses or watches to a person in a photo. It offers a wide range of possibilities for image modification.
Outlines
📚 Introduction to Image-to-Image Techniques
This paragraph introduces the concept of image-to-image techniques, emphasizing the transition from mastering text and images to creating new images using existing ones. It discusses the capabilities of Stable Diffusion, a tool for generating images, and provides tips on identifying prompts used in previously created images. The speaker explains how to analyze images to recreate prompts and differentiates between two methods of text generation: sentence-based and word-based, with a preference for the latter.
🎨 Exploring Image-to-Image Options and Features
This section delves into the various options and features of image-to-image technology, focusing on the practical application of image manipulation. It covers resizing modes, such as Just Resize, Crop and Resize, and Resize and Fill, each with its own approach to maintaining or adjusting image proportions. The importance of denoising stress is highlighted, which affects the degree of change in the generated image based on the set value. The paragraph also introduces the Paint feature, which allows for selective image editing using masks and various mask modes to refine the final output.
Mindmap
Keywords
💡Stable Diffusion
💡Image-to-Image
💡Prompt
💡Interrogator
💡Cartoon Style
💡Options and Features
💡Inpaint
💡Masking
💡Denoising Stress
💡Latent Upscale
💡Image Editing
Highlights
The lecture continues with an introduction to Image-to-Image techniques, building upon the previously mastered Text and Image chapters.
The concept of Image-to-Image is explained as a method to generate new images using existing ones, marking an advancement from beginner level.
A tip is provided on how to identify the prompt used for an image generated in Stable Diffusion if forgotten, by dragging the image into the prompt input area.
The Image-to-Image 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.
Two buttons are introduced for Image-to-Image, the Interrogate Clip and Interrogate Background, both analyzing the image to create a text prompt.
The Interrogate Clip generates sentence-based prompts, while the Interrogate Background creates word-based prompts, with a preference for the latter for its conciseness.
The process of transforming an image into a cartoon style is demonstrated, using Checkpoint models and VAE 1.
Options for Image-to-Image are discussed, including Resize mode, which deals with the handling of image size discrepancies.
The Denoising Stress option is highlighted as a crucial setting in Image-to-Image, affecting the degree of change in the generated image based on the reference image.
Inpainting is introduced as a feature that allows selective modification of an image using masks, with a focus on blending with the surrounding colors.
The Apply Color Collection option is explained, ensuring the inpainted image parts match the original color scheme for a natural look.
Mask Blur and Mask Mode are detailed, discussing their impact on the smoothness and focus of the masked areas.
Masked Content, Fill, and Original options are described, each offering different ways to handle the color filling in the masked areas.
The use of Inpainting and Masked Mask for changing specific parts of an image, such as clothing or accessories, is demonstrated.
The video concludes with a mention of future lessons covering more advanced uses of the Inpainting feature.
The presenter encourages viewers to subscribe for more advanced content and thanks them for their interest in the topic.