Sketches into Epic Art with 1 Click: A Guide to Stable Diffusion ControlNet in Automatic1111 Web UI
Our Discord : Discord: discord. In this video, You will learn how to use new amazing Stable Diffusion technology #ControlNet in Automatic1111 Web UI. If I have been of assistance to you and you would like to show your support for my work, please consider becoming a patron on 🥰 Patreon: SECourses
Playlist of #StableDiffusion Tutorials, Automatic1111 and Google Colab Guides, DreamBooth, Textual Inversion / Embedding, LoRA, AI Upscaling, Pix2Pix, Img2Img:
Stable Diffusion Tutorials, Automatic...
ControlNet GitHub repo : https://github.com/lllyasviel/ControlNet
Automatic1111 Web UI Repo Link:
https://github.com/AUTOMATIC1111/stab...
Pre-trained models repo link : https://huggingface.co/lllyasviel/Con...
Paper Adding Conditional Control to Text-to-Image Diffusion Models :
https://github.com/lllyasviel/Control...
GitBash download link : https://git-scm.com/downloads
Native Python App Video Tutorial of ControlNet :
Transform Your Sketches into Masterpi...
Easiest Way to Install & Run StableDiffusion Web UI on PC by Using Open Source Automatic Installer:
Easiest Way to Install & Run Stable D...
How to use Stable Diffusion V2.1 and Different Models in the Web UI - SD 1.5 vs 2.1 vs Anything V3:
How to use Stable Diffusion V2.1 and ...
Stable Diffusion 1.5 Official model repo link:
https://huggingface.co/runwayml/stabl...
ControlNet extension of Automatic1111 Web UI - Mikubill / sd-webui-controlnet:
https://github.com/Mikubill/sd-webui-...
8 GB LoRA Training - Fix CUDA Version For DreamBooth and Textual Inversion Training By Automatic1111:
8 GB LoRA Training - Fix CUDA & xform...
Ultimate SD Upscale extension for AUTOMATIC1111 Stable Diffusion web UI:
https://github.com/Coyote-A/ultimate-...
FAQ:
https://github.com/Coyote-A/ultimate-...
0:00 Introduction to new amazing Stable Diffusion based #AI technology ControlNet
0:18 Canny Edge model of ControlNet
0:29 M-LSD Lines model of ControlNet
0:36 User Scribbles model of ControlNet
1:12 How to install Automatic1111 Web UI
2:54 Where to and how to put Stable Diffusion model inside Automatic1111 web UI
3:30 How to start Automatic1111 Web UI from which URL
3:33 How to install ControlNet extension in Automatic1111 Web UI
4:04 How to downgrade xformers version to be able to do training with Dreambooth or Textual Inversion
4:30 If you encounter any error for ControlNet extension run this pip command too
4:49 How to download ControlNet model files from Hugging Face repo
6:00 Where to put downloaded ControlNet models in the Automatic1111 installation
6:24 How to use ControlNet script / extension to use models
7:00 First image generation with ControlNet
7:30 How to get best results with User Scribbles model - sketch into masterpiece
8:05 Use anything v3 model to generate images when using ControlNet User Scribbles model
9:30 Canny Edge model example
10:09 How to get good results with Canny Edge model
10:48 Example of M-LSD Lines model
11:40 How did I generate the thumbnail used in this video
12:40 How to use ultimate SD upscaler to upscale your image with even adding more details to the image
12:57 How to update installed extensions in Automatic1111 Web UI
13:13 How to setup and use what settings for ultimate SD upscaler
14:30 Ultimate SD Upscaled version of the image
15:00 If you don't know what is Stable Diffusion if you don't know how to install web ui
Eagle image vector source : https://www.freepik.com/free-vector/4...
Dragon like bird image source : https://www.deviantart.com/basiliskze...
Generative image AI models are becoming increasingly popular, as they offer exciting new ways to create digital artwork and visual media. One such model that has gained a lot of attention in recent years is the Stable Diffusion model, which is a free, open-source algorithm for generating high-quality images.
The Stable Diffusion model is based on a technique called diffusion processes, which involve gradually smoothing out noise in an image. This results in a progression of images that become progressively less noisy and more detailed over time. By controlling the speed and direction of the diffusion process, the model can be used to generate a wide variety of images, ranging from abstract art to realistic photos.
Another advantage of the Stable Diffusion model is its versatility. Because it is based on a probabilistic process, it can be used to generate a wide variety of different types of images, from landscapes to portraits to abstract art. This makes it an ideal tool for artists and designers who want to experiment with different styles and techniques.
Playlist of #StableDiffusion Tutorials, Automatic1111 and Google Colab Guides, DreamBooth, Textual Inversion / Embedding, LoRA, AI Upscaling, Pix2Pix, Img2Img:
Stable Diffusion Tutorials, Automatic...
ControlNet GitHub repo : https://github.com/lllyasviel/ControlNet
Automatic1111 Web UI Repo Link:
https://github.com/AUTOMATIC1111/stab...
Pre-trained models repo link : https://huggingface.co/lllyasviel/Con...
Paper Adding Conditional Control to Text-to-Image Diffusion Models :
https://github.com/lllyasviel/Control...
GitBash download link : https://git-scm.com/downloads
Native Python App Video Tutorial of ControlNet :
Transform Your Sketches into Masterpi...
Easiest Way to Install & Run StableDiffusion Web UI on PC by Using Open Source Automatic Installer:
Easiest Way to Install & Run Stable D...
How to use Stable Diffusion V2.1 and Different Models in the Web UI - SD 1.5 vs 2.1 vs Anything V3:
How to use Stable Diffusion V2.1 and ...
Stable Diffusion 1.5 Official model repo link:
https://huggingface.co/runwayml/stabl...
ControlNet extension of Automatic1111 Web UI - Mikubill / sd-webui-controlnet:
https://github.com/Mikubill/sd-webui-...
8 GB LoRA Training - Fix CUDA Version For DreamBooth and Textual Inversion Training By Automatic1111:
8 GB LoRA Training - Fix CUDA & xform...
Ultimate SD Upscale extension for AUTOMATIC1111 Stable Diffusion web UI:
https://github.com/Coyote-A/ultimate-...
FAQ:
https://github.com/Coyote-A/ultimate-...
0:00 Introduction to new amazing Stable Diffusion based #AI technology ControlNet
0:18 Canny Edge model of ControlNet
0:29 M-LSD Lines model of ControlNet
0:36 User Scribbles model of ControlNet
1:12 How to install Automatic1111 Web UI
2:54 Where to and how to put Stable Diffusion model inside Automatic1111 web UI
3:30 How to start Automatic1111 Web UI from which URL
3:33 How to install ControlNet extension in Automatic1111 Web UI
4:04 How to downgrade xformers version to be able to do training with Dreambooth or Textual Inversion
4:30 If you encounter any error for ControlNet extension run this pip command too
4:49 How to download ControlNet model files from Hugging Face repo
6:00 Where to put downloaded ControlNet models in the Automatic1111 installation
6:24 How to use ControlNet script / extension to use models
7:00 First image generation with ControlNet
7:30 How to get best results with User Scribbles model - sketch into masterpiece
8:05 Use anything v3 model to generate images when using ControlNet User Scribbles model
9:30 Canny Edge model example
10:09 How to get good results with Canny Edge model
10:48 Example of M-LSD Lines model
11:40 How did I generate the thumbnail used in this video
12:40 How to use ultimate SD upscaler to upscale your image with even adding more details to the image
12:57 How to update installed extensions in Automatic1111 Web UI
13:13 How to setup and use what settings for ultimate SD upscaler
14:30 Ultimate SD Upscaled version of the image
15:00 If you don't know what is Stable Diffusion if you don't know how to install web ui
Eagle image vector source : https://www.freepik.com/free-vector/4...
Dragon like bird image source : https://www.deviantart.com/basiliskze...
Generative image AI models are becoming increasingly popular, as they offer exciting new ways to create digital artwork and visual media. One such model that has gained a lot of attention in recent years is the Stable Diffusion model, which is a free, open-source algorithm for generating high-quality images.
The Stable Diffusion model is based on a technique called diffusion processes, which involve gradually smoothing out noise in an image. This results in a progression of images that become progressively less noisy and more detailed over time. By controlling the speed and direction of the diffusion process, the model can be used to generate a wide variety of images, ranging from abstract art to realistic photos.
Another advantage of the Stable Diffusion model is its versatility. Because it is based on a probabilistic process, it can be used to generate a wide variety of different types of images, from landscapes to portraits to abstract art. This makes it an ideal tool for artists and designers who want to experiment with different styles and techniques.
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