After Detailer Extension In 9 Minutes – Stable Diffusion Tutorial (Automatic1111)
TLDRThis tutorial introduces 'After Detailer,' an extension for Automatic1111 that enhances character details like faces, hands, and bodies post-image generation. It explores various settings, including model selection and prompt customization, to achieve precise results. The video compares different models' effectiveness, discusses advanced options like mask manipulation and denoising strength, and suggests techniques for refining image details. It's a comprehensive guide for users looking to optimize their workflow with After Detailer.
Takeaways
- 😀 After Detailer is an extension for Automatic1111 that enhances image details like faces, hands, and bodies post-generation.
- 🛠️ It offers two tabs, 'First' and 'Second', for different model settings that operate independently and can be used simultaneously.
- 📝 There are prompt and negative prompt boxes for specifying additional changes to the impainted regions.
- 🎭 The models correspond to different body parts, with options like YOLO for faces and various models for hands and full body.
- 🤖 YOLO models show a difference in facial impainting, with YOLOv5 being more effective.
- 👁️ 'Eyes Only' is a specialized model that focuses solely on enhancing the eyes.
- 🤲 Hand models require additional techniques for better results, as After Detailer alone may not suffice.
- 🔍 The 'Detection' tab includes options like confidence threshold and mask settings to control the impainting process.
- 🖼️ 'Mask only' and 'Mask padding pixels' settings help to define the area of impainting and provide context for generation.
- 🔄 The 'Mask merge mode' offers different approaches to merging masks before impainting, affecting the final output quality.
- 🔄 'In-paint denoising strength' adjusts how much the new impainted area should match the original, with higher values leading to more significant changes.
Q & A
What is After Detailer and what does it do?
-After Detailer is an extension for Automatic1111, which can automatically impaint the face, hands, and body of a character after the image generation process, helping to save time and achieve more accurate results.
How does After Detailer work with the main prompt box?
-If the prompt and negative prompt boxes in After Detailer are left blank, it will use the content from the main prompt box above by default.
What are the different tabs available in After Detailer and what do they control?
-There are two tabs called 'First' and 'Second' which contain settings for the corresponding model selected. These tabs operate independently, allowing the use of up to two models simultaneously.
How do the YOLO models in After Detailer affect the impainting process?
-The YOLO models are used for impainting the face, with noticeable differences between the two models. YOLO van is found to provide better results compared to the standard YOLO model.
What is the role of the Media Pipe models in After Detailer?
-Media Pipe models are also used for impainting the face, with varying degrees of quality. Face short seems to provide the best results among them.
What is the purpose of the 'Eyes Only' model in After Detailer?
-The 'Eyes Only' model is used to impaint only the eyes, which can be useful if the rest of the image is fine and only the eyes need adjustments.
How can After Detailer be used to improve the accuracy of hands in an image?
-After Detailer alone may not be sufficient to correct hand details, and additional techniques like negative prompts, embeddings, and control net might be necessary for more accurate hands.
What is the function of the 'Detection Model Confidence Threshold' setting in After Detailer?
-The 'Detection Model Confidence Threshold' ensures that only objects with a detection model confidence above this threshold are used for inpainting, which can help reduce the number of background characters whose faces are painted.
What does the 'Mask only the top K largest' setting do in After Detailer?
-The 'Mask only the top K largest' setting determines how many masks should be applied to the image based on the largest objects detected, where 'K' represents the number of masks to apply.
How does the 'Mask X and Y offset' setting affect the inpainting process in After Detailer?
-The 'Mask X and Y offset' moves the mask in the x or y direction, leaving the unmasked portions of the image unaffected by the inpainting.
What is the significance of the 'In-paint denoising strength' setting in After Detailer?
-The 'In-paint denoising strength' determines how strongly the new inpainted area should match the original image. A lower value keeps the inpainted face closer to the generated image, while a higher value can significantly change the face.
Outlines
🖼️ Introduction to After Detailer Extension
The video script introduces the After Detailer extension, an automatic tool designed to enhance the image generation process by refining the face, hands, and body of characters. It aims to save time and improve accuracy. The script explains the extension's features, including enabling the tool, using two independent tabs for different models, and prompt boxes for additional image adjustments. It also discusses various body part models available for impainting, such as YOLO, Media Pipe, and others, each with their own outcomes. The video promises to demonstrate the extension's capabilities through examples and encourages viewers to engage with the content.
🔍 Exploring After Detailer Settings and Options
This paragraph delves into the detailed settings and options available within the After Detailer extension. It covers the detection tab's functionalities, such as the detection model confidence threshold, which filters objects based on confidence levels, and the 'top K largest' setting, which controls the number of masks applied based on object size. The paragraph also discusses mask area ratios, offsets, erosion/dilation, and merge modes, which influence how the mask is applied and how it interacts with the image. Additionally, it touches on settings like mask blur, in-paint only mask, and padding pixels, which affect the mask's precision and context. The script concludes with a mention of standard image modification settings and the in-paint denoising strength, which determines the match between the impainted area and the original image. It also briefly mentions the noise multiplier for image-to-image and the restore faces after impainting option, suggesting that the extension offers a comprehensive set of tools for fine-tuning image details.
Mindmap
Keywords
💡After Detailer
💡Impainting
💡Models
💡Prompts
💡Detection Model Confidence Threshold
💡Mask
💡Inpaint Denoise Strength
💡Control Net
💡Resolution
💡Noise Multiplier
Highlights
After Detailer is an extension for Automatic1111 that automatically impaints faces, hands, and bodies in images.
The extension saves time and improves accuracy in image generation.
Each option in After Detailer is demonstrated with examples for workflow building.
Enabling After Detailer allows for influence from two independent tabs.
Models correspond to different body parts for targeted impainting.
YOLO models are effective for face impainting, with YOLOv5 being superior.
Mediapipe models vary in quality, with Face Short providing the best results.
Phase 4 and Eyes Only models are useful for specific impainting tasks.
Hand impainting requires additional techniques for better accuracy.
Detection Tab options impact subject and background elements in images.
Detection model confidence threshold filters objects for impainting.
Mask only the top K largest setting prioritizes significant objects in images.
Mask minimum and maximum ratio controls the size of detected masks.
Mask X and Y offset moves the mask for localized impainting.
Mask erosion/dilation adjusts the mask size for impainting.
Mask merge mode offers options for merging masks before impainting.
Inpaint mask blur determines the sharpness of mask edges.
Inpaint only mask ensures impainting affects only the masked area.
Inpaint mask padding pixels provides context for the masked area.
Use separate settings allow independent configuration for masked areas.
In-paint denoising strength controls the match between impainted and original areas.
Inpaint width and height set the resolution for the impainting mask.
Noise multiplier for image to image adds variability to the impainted result.
Restore faces after impainting ensures faces are accurately restored post-process.
Control net integration allows for additional model influence on the image.