Our Discord : https://discord.gg/HbqgGaZVmr. In this video, You will see the new amazing Stable Diffusion technology – #ControlNet. 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 ðĨ° https://www.patreon.com/SECourses
Playlist of #StableDiffusion Tutorials, Automatic1111 and Google Colab Guides, DreamBooth, Textual Inversion / Embedding, LoRA, AI Upscaling, Pix2Pix, Img2Img:
https://www.youtube.com/playlist?list=PL_pbwdIyffsmclLl0O144nQRnezKlNdx3
ControlNet GitHub repo : https://github.com/lllyasviel/ControlNet
Paper Adding #Conditional Control to Text-to-Image Diffusion Models :
https://github.com/lllyasviel/ControlNet/raw/main/github_page/control.pdf
Anaconda download link : https://www.anaconda.com/products/distribution
GitBash download link : https://git-scm.com/downloads
Pre-trained models repo link : https://huggingface.co/lllyasviel/ControlNet
0:00 What is revolutionary new Stable Diffusion AI technology ControlNet
0:36 What is ControlNet with Canny Edge
0:49 What is ControlNet with M-LSD Lines
1:17 What is ControlNet with HED Boundary
1:41 What is ControlNet with User Scribbles
1:58 What is ControlNet Interactive Interface
2:08 What is ControlNet with Fake Scribbles
2:28 What is ControlNet with Human Pose
2:45 What is ControlNet with Semantic Segmentation
3:02 What is ControlNet with Depth
3:15 What is ControlNet with Normal Map
3:35 How to download and install Anaconda
4:33 How to download / git clone ControlNet
5:25 How to download ControlNet models from Hugging Face repo
6:37 Which folder is the correct folder to put ControlNet models
7:03 How to install ControlNet to generate virtual environment with correct dependencies
8:53 How to start run first app Canny Edge
9:59 Correct local URL of the app
10:11 Testing first test image bird with Canny Edge
11:42 How to start M-LSD lines ControlNet app
12:10 How to set low VRAM option in configuration
13:20 Start again M-LSD lines ControlNet app
13:37 Running Hough Line Maps app example
14:28 Example of Control Stable Diffusion with HED Maps
14:45 Testing ControlNet with User Scribbles
Used lineart source :
https://www.deviantart.com/basiliskzero/art/Free-Dragon-Lineart-285772092
From official paper of Adding Conditional Control to Text-to-Image Diffusion Models
We present a neural network structure, ControlNet, to control pretrained large
diffusion models to support additional input conditions. The ControlNet learns
task-specific conditions in an end-to-end way, and the learning is robust even when
the training dataset is small ( 50k). Moreover, training a ControlNet is as fast as
fine-tuning a diffusion model, and the model can be trained on a personal devices.
Alternatively, if powerful computation clusters are available, the model can scale to
large amounts (millions to billions) of data. We report that large diffusion models
like Stable Diffusion can be augmented with ControlNets to enable conditional
inputs like edge maps, segmentation maps, keypoints, etc. This may enrich the
methods to control large diffusion models and further facilitate related applications.
1 Introduction
With the presence of large text-to-image models, generating a visually appealing image may require only a short descriptive prompt entered by users. After typing some texts and getting the images, we may naturally come up with several questions: does this prompt-based control satisfy our needs? For example in image processing, considering many long-standing tasks with clear problem formulations, can these large models be applied to facilitate these specific tasks? What kind of framework should we build to handle the wide range of problem conditions and user controls? In specific tasks, can large models preserve the advantages and capabilities obtained from billions of images? To answer these questions, we investigate various image processing applications and have three findings. First, the available data scale in a task-specific domain is not always as large as that in the general image-text domain. The largest dataset size of many specific problems (e.g., object shape/normal, pose understanding, etc.) is often under 100k, i.e., 5 Ã 104 times smaller than LAION5B. This would require robust neural network training method to avoid overfitting and to preserve generalization ability when the large models are trained for specific problems. Second, when image processing tasks are handled with data-driven solutions, large computation clusters are not always available. This makes fast training methods important for optimizing large models to specific tasks within an acceptable amount of time and memory space (e.g., on personal devices).
Chat GPT āļāļ·āļ? Chat GPT āđāļāđāļāļēāļāđāļāļ·āđāļāļāļāđāļāļĒāļąāļāđāļ āļŠāļāļāđāļŦāđāđāļāļāļĨāļīāļāļāļĩāđ
- Chat GPT āļāļ·āļ? Chat GPT āđāļāđāļāļēāļāđāļāļ·āđāļāļāļāđāļāļĒāļąāļāđāļ āļŠāļāļāđāļŦāđāđāļāļāļĨāļīāļāļāļĩāđ
- āđāļĄāļ·āđāļ AI āļāļ·āđāļāļāļ·āļāļāļĩāļ āļāļļāļāļāļĨāļāļĢāļāļāļīāļāļāļīāļāļĨāļāļāļāđāļĨāļāļĄāļēāļāļēāļāļāļ§āļēāļĄāļāļēāļĒ #shorts #midjourney
- āļŠāļĢāđāļēāļāļ āļēāļ AI āļŠāļēāļĒāļāļĢāļĩ āļāđāļ§āļĒāļāļēāļĢāļāļāļĄāđāļĢāļāđāļāļ Google Colab
- āđāļāļāļŠāļāļĢāļīāļāļāļĩāļāļēāļĒāļĨāđāļāļāļŦāļąāļ§90%ðĨ āđāļĨāđāļāđāļāļĩāļĒāļāđ āļāļąāļāđāļāļ+āļāļąāļāļāļąāļāļāļĩāļāļģðŊ
- Chat GPT Explained in 5 Minutes | What Is Chat GPT ? | Introduction To Chat GPT | Simplilearn
- Fooocus Stable Diffusion Web UI – Use SDXL Like You Are Using Midjourney – Easy To Use High Quality
- āđāļāđāļāđ 5 āļāļīāļāļŠāđ āđāļāđ ChatGPT āļāđāļ§āļĒāļāļģāļāļēāļāļĒāļąāļāđāļāđāļŦāđāđāļāļĩāļĒāļ ! | beartai āđāļāđāļāđ
- ChatGPT āđāļāļāļāļāļāļāļąāļāļāļĢāļīāļĒāļ° āļāļāļāļāļģāļāļēāļĄāļāļĨāđāļāļ āđāļāļĩāļĒāļāļŦāļāļąāļāļŠāļ·āļāđāļāđāļ āļĄāļēāļāđāļ§āļĒāļŦāļĢāļ·āļāđāļĒāđāļāļāļēāļāļĄāļāļļāļĐāļĒāđ? | KEY MESSAGES #57 | THE STANDARD
- ChatGPT āļāļ·āļāļāļ°āđāļĢ ChatGPT āļāļģāļāļ°āđāļĢāđāļāđāļāđāļēāļ? AI āļāļ°āđāļĒāđāļāļāļēāļāļāļāđāļŦāļĄ? l iT24Hrs | iT24Hrs
- Transform Your Sketches into Masterpieces with Stable Diffusion ControlNet AI – How To Use Tutorial
- āļāļąāļāļāļēāļāļĢāļ°āļāļīāļĐāļāđ 2023 ChatGPT āđāļāļĨāļĩāđāļĒāļāđāļĨāļ? | Executive Espresso EP.414 | THE SECRET SAUCE
- āđāļāđāļāļēāļ MidJourney AI āļŠāļĢāđāļēāļāļāļĨāļāļēāļ : āļŠāļĢāđāļēāļāļāļēāļāļĻāļīāļĨāļāđāļāđāļ§āļĒāļāļģ āļāļąāļ midjourney | Right CG
- āļŠāļĄāļąāļāļĢāđāļāđāļāļēāļ MidJourney āđāļāļāļĢāļēāļĒāđāļāļ·āļāļ $30 : āļ§āļīāļāļĩāđāļāđāļāļēāļ settings āļŠāļĢāđāļēāļāļŠāļĢāļĢāļāđāļāļĨāļāļēāļ | Right CG
Chat GPT āļāļ·āļāļāļ°āđāļĢ āđāļĨāđāļ§ Chat GPT āđāļāđāļāļēāļāļĒāļąāļāđāļ āļŦāļĨāļēāļĒāļāļāļāļēāļāļāļ°āļŠāļāļŠāļąāļĒ āļāļĄāļāļāļāļāļīāļāļēāļĒāđāļŦāđāļāļąāļāļāđāļēāļĒ āđ āļāļ°āļāļĢāļąāļ Chat GPT āļāļ·āļāđāļāļāļāļāļāļāļĩāđāđāļāđāļĢāļ°āļāļ algorithm āļāļāļāļāļĢāļīāļĐāļąāļ openai āđāļāļāļēāļĢāļāļāļāļāļģāļāļēāļĄ āļŠāļ·āđāļāļŠāļēāļĢāļāļąāļāļĄāļāļļāļĐāļĒāđ āļāļēāļĄāļāļģāļŠāļąāđāļ āļŦāļĢāļ·āļāļāļģāļāļēāļĄāļāļĩāđāđāļĢāļēāļāļīāļĄāļāđāļĨāļāđāļ āđāļāļāļąāļāļāļļāļāļąāļ Chat GPT āđāļāļīāđāļāđāļāļīāļāļāļąāļ§āļĢāļļāđāļāļāļĩāđ 4 āļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļāļŠāļđāļāļĄāļēāļ āđ āļāļļāļāļāļ°āļŠāļēāļĄāļēāļĢāļāļŠāļ·āđāļāļŠāļēāļĢāļāļąāļ Chat GPT āđāļāđāđāļŦāļĄāļ·āļāļāļāļļāļĒāļāļąāļāļĄāļāļļāļĐāļĒāđ . āđāļāļāļĨāļīāļāļ§āļīāļāļĩāđāļāļāļĩāđ āđāļāđāđāļāđāļāļĢāļēāļĒāļĨāļ°āđāļāļĩāļĒāļāđāļāļ·āđāļāļŦāļēāļāļēāļĄāļāļĩāđ 0:00 āđāļāļ°āļāļģ Chat GPT 2:56 āļĢāļđāđāļāļąāļāļāļąāļāļŦāļāđāļēāļāļē Chat GPT āđāļāļ·āđāļāļāļāđāļ 4:25 āļŠāļāļāļāļēāļĢāļāđāļāļāļāļģāļŠāļąāđāļāđāļāļāļāđāļāļāļ§āđāļēāļāđāļāļĄāļđāļĨāļāđāļāđāļāđāļāļāļĢāļīāļ 7:40 āļŠāļāļāļāļēāļĢāļāđāļāļāļāļģāļŠāļąāđāļ āđāļŦāđ Chat GPT āļāđāļ§āļĒāļāļīāļāļāļāļāđāļāļāļāđ āļĨāļāļāđāļāđ Chat GPT […]
āđāļĄāļ·āđāļ AI āļāļ·āđāļāļāļ·āļāļāļĩāļ āļāļļāļāļāļĨāļāļĢāļāļāļīāļāļāļīāļāļĨāļāļāļāđāļĨāļāļĄāļēāļāļēāļāļāļ§āļēāļĄāļāļēāļĒ #shorts #midjourney
āđāļĄāļ·āđāļ AI āļāļ·āđāļāļāļ·āļāļāļĩāļ āļāļļāļāļāļĨāļāļĢāļāļāļīāļāļāļīāļāļĨāļāļāļāđāļĨāļāļĄāļēāļāļēāļāļāļ§āļēāļĄāļāļēāļĒ #shorts #midjourney  āļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ Why Ask Why āļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ Why Ask WhyāđāļĄāļ·āđāļ AI āļāļ·āđāļāļāļ·āļāļāļĩāļ āļāļļāļāļāļĨāļāļĢāļāļāļīāļāļāļīāļāļĨāļāļāļāđāļĨāļāļĄāļēāļāļēāļāļāļ§āļēāļĄāļāļēāļĒ #shorts #midjourneyāļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ Why Ask Why  Â
āļŠāļĢāđāļēāļāļ āļēāļ AI āļŠāļēāļĒāļāļĢāļĩ āļāđāļ§āļĒāļāļēāļĢāļāļāļĄāđāļĢāļāđāļāļ Google Colab
āļ§āļīāļāļĩāļāļēāļĢāđāļāđāļāļēāļ AUTOMATIC1111 āļāļ Google Colab āđāļāđāļāļēāļ GPU āđāļāļāļāļĢāļĩāđ āđāļāļāļēāļĢāļĢāļąāļ AUTOMATIC1111 āđāļāļ·āđāļāļŠāļĢāđāļēāļāļ āļēāļ AI āđāļ§āđāļāđāļ§āļĒ Google Colab #googlecolab #automatic1111 #aiart AUTOMATIC1111 Notebooks āļŠāļģāļŦāļĢāļąāļ Google Colab https://github.com/TheLastBen/fast-stable-diffusion CivitAI https://civitai.com/  āļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ lnw’s Idle Days āļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ lnw’s Idle DaysāļŠāļĢāđāļēāļāļ āļēāļ AI āļŠāļēāļĒāļāļĢāļĩ āļāđāļ§āļĒāļāļēāļĢāļāļāļĄāđāļĢāļāđāļāļ Google Colabāļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ lnw’s Idle Days  Â
Playlist of #StableDiffusion Tutorials, Automatic1111 and Google Colab Guides, DreamBooth, Textual Inversion / Embedding, LoRA, AI Upscaling, Pix2Pix, Img2Img:
https://www.youtube.com/playlist?list=PL_pbwdIyffsmclLl0O144nQRnezKlNdx3
ControlNet GitHub repo : https://github.com/lllyasviel/ControlNet
Paper Adding #Conditional Control to Text-to-Image Diffusion Models :
https://github.com/lllyasviel/ControlNet/raw/main/github_page/control.pdf
Anaconda download link : https://www.anaconda.com/products/distribution
GitBash download link : https://git-scm.com/downloads
Pre-trained models repo link : https://huggingface.co/lllyasviel/ControlNet
0:00 What is revolutionary new Stable Diffusion AI technology ControlNet
0:36 What is ControlNet with Canny Edge
0:49 What is ControlNet with M-LSD Lines
1:17 What is ControlNet with HED Boundary
1:41 What is ControlNet with User Scribbles
1:58 What is ControlNet Interactive Interface
2:08 What is ControlNet with Fake Scribbles
2:28 What is ControlNet with Human Pose
2:45 What is ControlNet with Semantic Segmentation
3:02 What is ControlNet with Depth
3:15 What is ControlNet with Normal Map
3:35 How to download and install Anaconda
4:33 How to download / git clone ControlNet
5:25 How to download ControlNet models from Hugging Face repo
6:37 Which folder is the correct folder to put ControlNet models
7:03 How to install ControlNet to generate virtual environment with correct dependencies
8:53 How to start run first app Canny Edge
9:59 Correct local URL of the app
10:11 Testing first test image bird with Canny Edge
11:42 How to start M-LSD lines ControlNet app
12:10 How to set low VRAM option in configuration
13:20 Start again M-LSD lines ControlNet app
13:37 Running Hough Line Maps app example
14:28 Example of Control Stable Diffusion with HED Maps
14:45 Testing ControlNet with User Scribbles
Used lineart source :
https://www.deviantart.com/basiliskzero/art/Free-Dragon-Lineart-285772092
From official paper of Adding Conditional Control to Text-to-Image Diffusion Models
We present a neural network structure, ControlNet, to control pretrained large
diffusion models to support additional input conditions. The ControlNet learns
task-specific conditions in an end-to-end way, and the learning is robust even when
the training dataset is small ( 50k). Moreover, training a ControlNet is as fast as
fine-tuning a diffusion model, and the model can be trained on a personal devices.
Alternatively, if powerful computation clusters are available, the model can scale to
large amounts (millions to billions) of data. We report that large diffusion models
like Stable Diffusion can be augmented with ControlNets to enable conditional
inputs like edge maps, segmentation maps, keypoints, etc. This may enrich the
methods to control large diffusion models and further facilitate related applications.
1 Introduction
With the presence of large text-to-image models, generating a visually appealing image may require only a short descriptive prompt entered by users. After typing some texts and getting the images, we may naturally come up with several questions: does this prompt-based control satisfy our needs? For example in image processing, considering many long-standing tasks with clear problem formulations, can these large models be applied to facilitate these specific tasks? What kind of framework should we build to handle the wide range of problem conditions and user controls? In specific tasks, can large models preserve the advantages and capabilities obtained from billions of images? To answer these questions, we investigate various image processing applications and have three findings. First, the available data scale in a task-specific domain is not always as large as that in the general image-text domain. The largest dataset size of many specific problems (e.g., object shape/normal, pose understanding, etc.) is often under 100k, i.e., 5 Ã 104 times smaller than LAION5B. This would require robust neural network training method to avoid overfitting and to preserve generalization ability when the large models are trained for specific problems. Second, when image processing tasks are handled with data-driven solutions, large computation clusters are not always available. This makes fast training methods important for optimizing large models to specific tasks within an acceptable amount of time and memory space (e.g., on personal devices).
Â
āļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ SECourses
Â
āđāļāļāļŠāļāļĢāļīāļāļāļĩāļāļēāļĒāļĨāđāļāļāļŦāļąāļ§90%ðĨ āđāļĨāđāļāđāļāļĩāļĒāļāđ āļāļąāļāđāļāļ+āļāļąāļāļāļąāļāļāļĩāļāļģðŊ
āļĨāļīāđāļāļāļĒāļđāđāđāļāļāļāļĄāđāļĄāđāļ++ āļāļģāđāļāļ·āļāļðĨ āđāļāļĨāđāļāļļāļāđāļāļĨāđāļĄāļĩāđāļāļāļēāļŠāđāļāļāđāļāļ+āđāļāļāļāļģ āđāļĄāđāļāļ§āļĢāđāļĨāđāļāđāļāļŦāļĨāļąāļ Â āļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ Hades FF āļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ Hades FFāđāļāļāļŠāļāļĢāļīāļāļāļĩāļāļēāļĒāļĨāđāļāļāļŦāļąāļ§90%ðĨ āđāļĨāđāļāđāļāļĩāļĒāļāđ āļāļąāļāđāļāļ+āļāļąāļāļāļąāļāļāļĩāļāļģðŊāļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ Hades FF Â Â
Chat GPT Explained in 5 Minutes | What Is Chat GPT ? | Introduction To Chat GPT | Simplilearn
ðĨ Become An AI & ML Expert Today: 0 – 3 Year Experience: https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=AIMLVideosTapLink&utm_medium=Descriptionff&utm_source=youtube 3 – 8 Year Experience: https://l.linklyhq.com/l/1tx6v 8+ Year Experience: https://l.linklyhq.com/l/1tx6z In today’s video on ChatGPT explained, we will understand what is chatGPT and how OpenAI was able to create this revolutionary chatbot. This introduction to ChatGPT video will teach you about […]
Fooocus Stable Diffusion Web UI – Use SDXL Like You Are Using Midjourney – Easy To Use High Quality
Welcome to an exciting journey into the world of AI creativity! In this tutorial video, we are about to dive deep into the fantastic realm of Fooocus, a remarkable Web UI for Stable Diffusion based models. With over 14,000 stars and a plethora of features, this tool is set to revolutionize your creative endeavors. #StableDiffusion […]
āļāļĢāļļāļāļē āļāļāļāļīāļāļāļēāļĄ >> channel SECourses
Â
āđāļāđāļāđ 5 āļāļīāļāļŠāđ āđāļāđ ChatGPT āļāđāļ§āļĒāļāļģāļāļēāļāļĒāļąāļāđāļāđāļŦāđāđāļāļĩāļĒāļ ! | beartai āđāļāđāļāđ
āđāļāđāļāđ 5 āļāļīāļāļŠāđ āđāļāđ ChatGPT āļāđāļ§āļĒāļāļģāļāļēāļāļĒāļąāļāđāļāđāļŦāđāđāļāļĩāļĒāļ !āđāļāđāļāđ 5 āļāļīāļāļŠāđ āđāļāđ ChatGPT āļāđāļ§āļĒāļāļģāļāļēāļāļĒāļąāļāđāļāđāļŦāđāđāļāļĩāļĒāļ !āļāļāļāļāļāļāļļāļ āļāđāļāļ beartai āđāļāđāļāđāļāļĢāļļāļāļē āļāļāļāļīāļāļāļēāļĄ āļāļĩāđurl video āļāļīāļāļāļēāļĄāđāļāđāļāđ āļāļāđāļĨāļĒ! https://cutt.ly/YTbeartai āđāļāđāļ§āļĨāļēāļāļĩāđ #AI āļāļĒāđāļēāļ #ChatGPT āđāļāđāļēāļĄāļēāļĄāļĩāļāļāļāļēāļāđāļāļāļĩāļ§āļīāļāļāļāļāđāļĢāļēāđāļāļīāđāļĄāļĄāļēāļāļāļķāđāļ āļāļķāļāđāļ§āļĨāļēāđāļĨāđāļ§āļāļĩāđāđāļĢāļēāļāļ°āļāđāļāļāļāļģāđāļāļē AI āļāļąāļ§āļāļĩāđāļĄāļēāļāļĢāļ°āļĒāļļāļāļāđāđāļāđ #beartaiOriginals āļāļĨāļīāļāļāļĩāđāļāļķāļāļāļĒāļēāļāļāļēāļāļļāļāļāļāđāļāļĨāļāļāļŠāļąāļĄāļāļąāļŠ ChatGPT āļāļĩāđ āļāļĢāđāļāļĄāđāļāļ°āļāļģāļāļīāļāļŠāđāđāļĨāđāļāļāđāļāļĒāļŠāļģāļŦāļĢāļąāļāļāļāļāļĩāđāđāļāļīāđāļāļāļ°āđāļāđāļĨāļāļāđāļāđ ChatGPT āļ§āđāļēāđāļĢāļēāļāļ°āđāļāđ ChatGPT āļĒāļąāļāđāļāđāļŦāđāđāļ§āļīāļĢāđāļ āļāļąāļāļāļāļĄ – āļŠāļļāļāļāļē ! ================ āļāļīāļāļāđāļāļāļēāļāđāļāļĐāļāļē āļŦāļĢāļ·āļ Production āđāļāđāļāļĩāđ ð[email protected] ðą To. 085-848-2253 āļāļīāļāļāļēāļĄāļāđāļēāļ§āļŠāļēāļĢāļāđāļēāļāđāļāļāļĩ āđāļĨāļ°āđāļĨāļāđāļŠāđāļāļĨāđāđāļāļ āđ […]
ChatGPT āđāļāļāļāļāļāļāļąāļāļāļĢāļīāļĒāļ° āļāļāļāļāļģāļāļēāļĄāļāļĨāđāļāļ āđāļāļĩāļĒāļāļŦāļāļąāļāļŠāļ·āļāđāļāđāļ āļĄāļēāļāđāļ§āļĒāļŦāļĢāļ·āļāđāļĒāđāļāļāļēāļāļĄāļāļļāļĐāļĒāđ? | KEY MESSAGES #57 | THE STANDARD
ChatGPT āđāļāļāļāļāļāļāļąāļāļāļĢāļīāļĒāļ° āļāļāļāļāļģāļāļēāļĄāļāļĨāđāļāļ āđāļāļĩāļĒāļāļŦāļāļąāļāļŠāļ·āļāđāļāđāļ āļĄāļēāļāđāļ§āļĒāļŦāļĢāļ·āļāđāļĒāđāļāļāļēāļāļĄāļāļļāļĐāļĒāđ? | KEY MESSAGES #57ChatGPT āđāļāļāļāļāļāļāļąāļāļāļĢāļīāļĒāļ° āļāļāļāļāļģāļāļēāļĄāļāļĨāđāļāļ āđāļāļĩāļĒāļāļŦāļāļąāļāļŠāļ·āļāđāļāđāļ āļĄāļēāļāđāļ§āļĒāļŦāļĢāļ·āļāđāļĒāđāļāļāļēāļāļĄāļāļļāļĐāļĒāđ? | KEY MESSAGES #57āļāļāļāļāļāļāļļāļ āļāđāļāļ THE STANDARDāļāļĢāļļāļāļē āļāļāļāļīāļāļāļēāļĄ āļāļĩāđurl video āđāļĄāđāļāļĩāđāļŠāļąāļāļāļēāļŦāđāļāļĩāđāļāđāļēāļāļĄāļē āļāļđāđāļāļāļāļąāđāļ§āđāļĨāļāļāđāļēāļāļŪāļ·āļāļŪāļēāļāļąāļ âChatGPTâ āđāļāļāļāļāļ AI āļŠāļļāļāļāļąāļāļāļĢāļīāļĒāļ°āļāļĩāđāđāļāļīāđāļāđāļāļīāļāļāļąāļ§āđāļŦāđāļāļāļāļąāđāļ§āđāļāļāļāļĨāļāļāđāļāđ āļāđāļāļāļāļ°āļāļĨāļēāļĒāđāļāđāļāđāļ§āļĢāļąāļĨāļāļāđāļĨāļāļāļīāļāđāļāļāļĢāđāđāļāđāļāđāļāđāļ§āļĨāļēāļāļąāļāļĢāļ§āļāđāļĢāđāļ§ āļāļ§āļēāļĄāļāļīāđāļĻāļĐāļāļāļ ChatGPT āļāļąāđāļ āđāļĄāđāļ§āđāļēāļāļ°āļŠāļāļŠāļąāļĒāđāļĢāļ·āđāļāļāļāļ°āđāļĢāļāđāļŠāļēāļĄāļēāļĢāļāļŦāļēāļāļģāļāļāļāđāļāđāļŦāļĄāļ āđāļāļĒāļāļ°āđāļāđāļĢāļ°āļāļ âAIâ āđāļāļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļāļēāļāļāļļāļāļāļĩāđāđāļāđāļĨāļāļĄāļēāļāļĢāļ°āļĄāļ§āļĨāļāļĨāđāļāđāļāļāļģāļāļāļāđāļŦāđāļāļąāļāđāļĢāļē āđāļĨāļ°āļāļģāđāļāđāđāļĄāđāļāļĢāļ°āļāļąāđāļāļāļēāļĢāđāļāļĩāļĒāļāļŠāļāļĢāļīāļāļāđāļāļēāļĢāđāļĢāļĩāļĒāļāļāļēāļĢāļŠāļāļ āđāļāļĩāļĒāļāļāļāļāļ§āļĩ āđāļāđāļāđāļāļĨāļ āļŦāļĢāļ·āļāđāļāļĩāļĒāļāļāđāļēāļ§āļāđāđāļāđ āļāļąāđāļāļĒāļąāļāđāļāđāļāļāļāļŠāļāļāļāļēāļāļąāļāđāļĢāļēāđāļāđāļāļĒāđāļēāļāđāļāđāļāļāļĢāļĢāļĄāļāļēāļāļīāļĢāļēāļ§āļāļąāļāđāļāđāļāļĄāļāļļāļĐāļĒāđ āļāļđāđāļāļĩāđāđāļāđāļāļāļĨāļāļāđāļāđāļāļēāļāļāļāļāļķāļāļāļąāļāđāļāđāļĒāļāļēāļāļ§āđāļē âGoogle āļāļēāļĒāđāļĨāđāļ§â āļāđāļēāļāļāđāļāļāļāļ§āđāļēāļĄāļāļļāļĐāļĒāđāļāļģāļĨāļąāļāļāļ°āđāļāļ AI āđāļĒāđāļāļāļēāļ ChatGPT āļāļ·āļāļāļ°āđāļĢ āļāļĢāļīāļāļŦāļĢāļ·āļāļāļĩāđāļāļ§āļāđāļĢāļēāļāļ°āļāļāļāļēāļāđāļāļĢāļēāļ°āđāļāļāļāļāļāļāļĩāđ āļāļīāļāļāļēāļĄāđāļāđāđāļāļĢāļēāļĒāļāļēāļĢ KEY MESSAGES āđāļĢāļ·āđāļāļ: […]
ChatGPT āļāļ·āļāļāļ°āđāļĢ ChatGPT āļāļģāļāļ°āđāļĢāđāļāđāļāđāļēāļ? AI āļāļ°āđāļĒāđāļāļāļēāļāļāļāđāļŦāļĄ? l iT24Hrs | iT24Hrs
ChatGPT āļāļ·āļāļāļ°āđāļĢ ChatGPT āļāļģāļāļ°āđāļĢāđāļāđāļāđāļēāļ? AI āļāļ°āđāļĒāđāļāļāļēāļāļāļāđāļŦāļĄ? l iT24HrsChatGPT āļāļ·āļāļāļ°āđāļĢ ChatGPT āļāļģāļāļ°āđāļĢāđāļāđāļāđāļēāļ? AI āļāļ°āđāļĒāđāļāļāļēāļāļāļāđāļŦāļĄ? l iT24Hrsāļāļāļāļāļāļāļļāļ āļāđāļāļ iT24HrsāļāļĢāļļāļāļē āļāļāļāļīāļāļāļēāļĄ āļāļĩāđurl video ChatGPT āļāļ·āļāļāļ°āđāļĢ ChatGPT āļāļģāļāļ°āđāļĢāđāļāđāļāđāļēāļ? AI āļāļ°āđāļĒāđāļāļāļēāļāļāļāđāļŦāļĄ? āļāļāļāļāļĩāđāļāļģāļĨāļąāļāļĄāļĩ AI āļĒāđāļāļĄāļēāļāļēāļ Artificial Intelligence ( āļāļąāļāļāļēāļāļĢāļ°āļāļīāļĐāļāđ ) āļāļģāļĨāļąāļāļŠāļĢāđāļēāļāļāļ§āļēāļĄāļŪāļ·āļāļŪāļē āđāļāļēāļāļ·āđāļāļ§āđāļē ChatGPT āļāļģāļĨāļąāļāļĄāļĩāļāļāļāļđāļāļāļķāļāđāļĒāļāļ°āđāļĨāļĒ āļāļķāđāļāļāļđāļāļāļąāļāļāļēāđāļāļĒ OpenAI āđāļāđāļēāđāļāļĩāļĒāļ§āļāļąāļāļāļđāđāđāļāļĒāļāļąāļāļāļē Dall-E 2 āļāļīāļāļĢāļāļĢ AI āļāļĩāđāļŠāļĢāđāļēāļāđāļŠāļĩāļĒāļāļŪāļ·āļāļŪāļēāđāļĄāļ·āđāļāļāļĨāļēāļāļāļĩ 2022 āđāļĨāđāļ§ Chat GPT āļāđāļāļķāđāļāđāļāļīāļāļāļąāļ§āđāļĄāļ·āđāļāļāđāļ§āļāđāļāļ·āļāļāļāļĪāļĻāļāļīāļāļēāļĒāļ 2022 . āļĄāļēāļāļđ AI […]
Â
āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ SECourses
https://www.youtube.com/watch?v=YJebdQ30UZQ
āļāļĢāļļāļāļē āļāļāļāļīāļāļāļēāļĄ >> channel SECourses
āļāļĢāļļāļāļēāļāļĢāļ§āļāļŠāļāļ āļāđāļāļĄāļđāļĨ āļāļĩāļāļāļĢāļąāđāļ āđāļāļ·āđāļ āļāļ§āļēāļĄāļāļđāļāļāđāļāļ
āļāļēāļāđāļ§āļāđāļāļāđ āđāļĄāđāļĄāļĩāđāļāļāļāļē āđāļŦāđāļāđāļāļĄāļđāļĨāļāļĩāđāļāļīāļāļāļĨāļēāļ āļŦāļēāļāļāļāļāļ§āļēāļĄāļāļīāļāļāļĨāļēāļ āļāļāļāļāđāļāļĄāļđāļĨ āļāļĢāļļāļāļēāđāļāđāļ
[email protected]Â āļāļēāļāđāļ§āļāđāļāļāđāļāļ°āļĢāļĩāļāđāļāđāđāļāļāļĒāđāļēāļāđāļĢāđāļ§āļāļĩāđāļŠāļļāļ
āļāļĢāļļāļāļē āļāļāļāļīāļāļāļēāļĄ >> channel SECourses
Transform Your Sketches into Masterpieces with Stable Diffusion ControlNet AI – How To Use Tutorial
āļāļāļāļāļāļāļļāļ āļāđāļāļĄāļđāļĨāļāļēāļ Youtube āļāđāļāļ SECourses
āļāļąāļāļāļēāļāļĢāļ°āļāļīāļĐāļāđ 2023 ChatGPT āđāļāļĨāļĩāđāļĒāļāđāļĨāļ? | Executive Espresso EP.414 | THE SECRET SAUCE
āļāļąāļāļāļēāļāļĢāļ°āļāļīāļĐāļāđ 2023 ChatGPT āđāļāļĨāļĩāđāļĒāļāđāļĨāļ? | Executive Espresso EP.414āļāļąāļāļāļēāļāļĢāļ°āļāļīāļĐāļāđ 2023 ChatGPT āđāļāļĨāļĩāđāļĒāļāđāļĨāļ? | Executive Espresso EP.414āļāļāļāļāļāļāļļāļ āļāđāļāļ THE SECRET SAUCEāļāļĢāļļāļāļē āļāļāļāļīāļāļāļēāļĄ āļāļĩāđurl video āđāļāļāļĩ 2023 āļāļĢāļ°āđāļŠ AI āđāļāļāļāļāļāļāļģāļĨāļąāļāļĄāļēāđāļĢāļāļāļĒāđāļēāļāļāđāļāđāļāļ·āđāļāļ āđāļāļĒāļĄāļĩāļāļļāļāđāļĢāļīāđāļĄāļāđāļāļāļēāļ ChatGPT āļāļģāđāļŦāđāļāļĢāļīāļĐāļąāļāļĒāļąāļāļĐāđāđāļŦāļāđāđāļĨāļ°āļŠāļāļēāļĢāđāļāļāļąāļāļāđāļēāļāđāļāļīāļāļāļąāļ§ AI āđāļāļ·āđāļāđāļāđāļāļāļąāļāļāļąāļāļāļģāļāļ§āļāļĄāļēāļ āļĻāļķāļ AI āļāļĢāļąāđāļāļāļĩāđāļāļģāđāļŦāđāļāļāļāļąāđāļāļāļģāļāļēāļĄāđāļĄāđāđāļāđāļ§āđāļē āļāļāļēāļāļāļāļāļāļāļąāļāļāļēāļāļĢāļ°āļāļīāļĐāļāđāļāļ°āđāļāđāļāđāļāđāļāļāļīāļĻāļāļēāļāđāļ Exclusive Espresso āđāļāļāļīāđāļŠāļāļāļĩāđ āļāļ°āļĄāļēāļŠāļĢāļļāļāļāļāļāļ§āļēāļĄāļāļēāļ MIT āđāļāļŦāļąāļ§āļāđāļ âāļāđāļēāļ§āļāļąāļāđāļāļāļāļāļāļąāļāļāļēāļāļĢāļ°āļāļīāļĐāļāđâ āđāļĨāļ°āļāļĩāđāđāļŦāđāđāļŦāđāļāļāļķāļāļāļēāļĢāđāļāđāļāļāļąāļāļāļāļāļāļąāļāļāļēāļāļĢāļ°āļāļīāļĐāļāđāđāļāļāļĨāļēāļāđāļĨāļāļāļĩ 2023 āļāļĩāđāļāļģāļĨāļąāļāđāļāđāļāđāļāļāļĒāđāļēāļāļāļļāđāļāļ·āļāļ āļāļąāđāļāđāļāļāđāļēāļāļāļāļŦāļĄāļēāļĒ āļāļēāļĢāļŠāļđāļāđāļŠāļĩāļĒāļāļģāļāļēāļāļāļāļāļāļĢāļīāļĐāļąāļāđāļāļ āđāļāļāļāļāļķāļāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄāļĒāļēāđāļāļāļāļēāļāļ āļĢāļ§āļĄāļāļķāļāļāļēāļĒāļ āļēāļāļāļāļēāļāļāļāļāļāđāļāļāļāļāļāļāļĩāđāļāļ°āļāļāļīāļ§āļąāļāļīāļ§āļāļāļēāļĢ Search Engine āđāļāļāļĨāļāļāļāļēāļĨ 00:00 āđāļĢāļīāđāļĄāļĢāļēāļĒāļāļēāļĢ […]
āđāļāđāļāļēāļ MidJourney AI āļŠāļĢāđāļēāļāļāļĨāļāļēāļ : āļŠāļĢāđāļēāļāļāļēāļāļĻāļīāļĨāļāđāļāđāļ§āļĒāļāļģ āļāļąāļ midjourney | Right CG
āđāļāđāļāļēāļ MidJourney AI āļŠāļĢāđāļēāļāļāļĨāļāļēāļ : āļŠāļĢāđāļēāļāļāļēāļāļĻāļīāļĨāļāđāļāđāļ§āļĒāļāļģ āļāļąāļ midjourneyāđāļāđāļāļēāļ MidJourney AI āļŠāļĢāđāļēāļāļāļĨāļāļēāļ : āļŠāļĢāđāļēāļāļāļēāļāļĻāļīāļĨāļāđāļāđāļ§āļĒāļāļģ āļāļąāļ midjourneyāļāļāļāļāļāļāļļāļ āļāđāļāļ Right CGāļāļĢāļļāļāļē āļāļāļāļīāļāļāļēāļĄ āļāļĩāđurl video āđāļĢāļīāđāļĄāļāđāļāđāļāđāļāļēāļ midjourney āļŠāļĢāđāļēāļāļāļĨāļāļēāļāļĻāļīāļĨāļāļ°āļāđāļ§āļĒ AI āļāļĢāļļāļāļēāļāļĢāļ§āļāļŠāļāļ āļāđāļāļĄāļđāļĨ āļāļĩāļāļāļĢāļąāđāļ āđāļāļ·āđāļ āļāļ§āļēāļĄāļāļđāļāļāđāļāļ āļāļēāļāđāļ§āļāđāļāļāđ āđāļĄāđāļĄāļĩāđāļāļāļāļē āđāļŦāđāļāđāļāļĄāļđāļĨāļāļĩāđāļāļīāļāļāļĨāļēāļ āļŦāļēāļāļāļāļāļ§āļēāļĄāļāļīāļāļāļĨāļēāļ āļāļāļāļāđāļāļĄāļđāļĨ āļāļĢāļļāļāļēāđāļāđāļ [email protected] āļāļēāļāđāļ§āļāđāļāļāđāļāļ°āļĢāļĩāļāđāļāđāđāļāļāļĒāđāļēāļāđāļĢāđāļ§āļāļĩāđāļŠāļļāļ āļāļāļāļāļāļāļļāļ āļāđāļāļ Right CG āļāļĢāļļāļāļē āļāļāļāļīāļāļāļēāļĄ āļāļĩāđ youtube channel Right CG […]
āļŠāļĄāļąāļāļĢāđāļāđāļāļēāļ MidJourney āđāļāļāļĢāļēāļĒāđāļāļ·āļāļ $30 : āļ§āļīāļāļĩāđāļāđāļāļēāļ settings āļŠāļĢāđāļēāļāļŠāļĢāļĢāļāđāļāļĨāļāļēāļ | Right CG
āļŠāļĄāļąāļāļĢāđāļāđāļāļēāļ MidJourney āđāļāļāļĢāļēāļĒāđāļāļ·āļāļ $30 : āļ§āļīāļāļĩāđāļāđāļāļēāļ settings āļŠāļĢāđāļēāļāļŠāļĢāļĢāļāđāļāļĨāļāļēāļāļŠāļĄāļąāļāļĢāđāļāđāļāļēāļ MidJourney āđāļāļāļĢāļēāļĒāđāļāļ·āļāļ $30 : āļ§āļīāļāļĩāđāļāđāļāļēāļ settings āļŠāļĢāđāļēāļāļŠāļĢāļĢāļāđāļāļĨāļāļēāļāļāļāļāļāļāļāļļāļ āļāđāļāļ Right CGāļāļĢāļļāļāļē āļāļāļāļīāļāļāļēāļĄ āļāļĩāđurl video āļāļēāļĢāļŠāļĄāļąāļāļĢ midjourney āđāļāļāļĢāļēāļĒāđāļāļ·āļāļ $30 āļĨāļāļāđāļāđāļāļēāļ AI āđāļĨāļ° āđāļāđāļēāđāļāļāļ§āļēāļĄāļāļīāļāļāļāļ midjourney āļāļĢāļąāļāđāļāđāļāļāđāļē /settings āđāļāļ·āđāļāļāļēāļĢāļŠāļĢāđāļēāļāļŠāļĢāļĢāļāđāļ āļēāļ āļāļĢāļļāļāļēāļāļĢāļ§āļāļŠāļāļ āļāđāļāļĄāļđāļĨ āļāļĩāļāļāļĢāļąāđāļ āđāļāļ·āđāļ āļāļ§āļēāļĄāļāļđāļāļāđāļāļ āļāļēāļāđāļ§āļāđāļāļāđ āđāļĄāđāļĄāļĩāđāļāļāļāļē āđāļŦāđāļāđāļāļĄāļđāļĨāļāļĩāđāļāļīāļāļāļĨāļēāļ āļŦāļēāļāļāļāļāļ§āļēāļĄāļāļīāļāļāļĨāļēāļ āļāļāļāļāđāļāļĄāļđāļĨ āļāļĢāļļāļāļēāđāļāđāļ [email protected] āļāļēāļāđāļ§āļāđāļāļāđāļāļ°āļĢāļĩāļāđāļāđāđāļāļāļĒāđāļēāļāđāļĢāđāļ§āļāļĩāđāļŠāļļāļ āļāļāļāļāļāļāļļāļ āļāđāļāļ Right […]
āļāļģāđāļāļ·āļāļ !! āđāļ§āļāļāļĩāđāđāļĄāđāđāļāđāđāļ§āļāļāļĒāđāļēāļāđāļāđāļāļāļēāļāļāļēāļĢ āļāļāļ āļāļĨāļīāļāļ āļąāļāļāđ āļŠāļīāļāļāđāļē āļŦāļĢāļ·āļ āļāļđāđāđāļŦāđāļāļĢāļīāļāļēāļĢ āļāļĩāđ !!!
Discord : https://discord.gg/HbqgGaZVmr – Patreon : https://www.patreon.com/SECourses
Stable Diffusion Playlist (16+ Tutorial / Guide Videos) : https://www.youtube.com/playlist?list=PL_pbwdIyffsmclLl0O144nQRnezKlNdx3
Please join discord, mention me and ask me any questions. Thank you for like, subscribe, share and Patreon support. I am open to private consulting with Patreon subscription.
Now ControlNet extension for Automatic1111 is available : https://youtu.be/vhqqmkTBMlU
Thanks for the great tutorial! However, I'm having problem using the ControlNet after successfully installed. When I run it, it shows: RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument index in method wrapper__index_select). Has anyone seen the same error?
I have a "ControlNet" folder with "model" folder inside with pixar, monaliza, etc in pt. files how use it ?please
Hello! I keep getting the error: "FileNotFound [Errno2] No such file or directory" when trying to input each of the models. Solution? Thanks!
when I put a black and white drawing, it generates another black and white drawing, not colored, how do I solve it?
HI
I followed all the steps of the tutorial.
But when executing the command: python gradio_canny2image.py
I get this error: (My PC Intel(R) Core(TM) i7-6700 CPU. NO GPU,)
raise RuntimeError('Attempting to deserialize object on a CUDA '
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.
Hi, I am a macOS user. When I run conda env create -f environment.yaml, I get an error ResolvePackageNotFound: – cudatoolkit=11.3. How can I solve this problem?ðĨē
Hocam canny modelini yÞkledikten sonra direkt 127.0.0.1'e geçtin. Ãķncesinde bir bat dosyasÄą çalÄąÅtÄąrmamÄąz gerekmiyor mu? ÃķrneÄin scribble2image çalÄąÅmÄąyor. no module xformer ve RuntimeError Cuda hatalarÄą geliyor.
I was a virgin when I saw the stable diffusion group on reddit, and it so hard to learn, because of you now I am deflowered and have experience. Thank you for your guides!
Help w/ setting up on Colab would be greatly appreciated. Ur vids are great btw.
This is amazing, thank you!
I just can't get the code repository updated by the git pull repo_URL command, i got this error :
"fatal: 'repo_URL' does not appear to be a git repository
fatal: Could not read from remote repository.
Please make sure you have the correct access rights
and the repository exists."
Any idea how to fix this?
Thank you !!
incredible ! thank you so much for this step by step tutorial ! I'm wondering how to run it using my second graphic cards (i have a SLI) because now it uses only the first GTX 1080, but my second is idle. But maybe GTX 1080 is too old now for that ? I tried to install tensorflow-gpu on anaconda but it fail installing it
Hi, Is there a colab using it?
and you can vice versa a picture in a sketch drawing?
Jesus 88GB of models. I wonder if you were having trouble with 3060 12GB, would I have a problem with 3080 10GB.
wow amazing
someone already made an extension to implement it to automatic1111. Could you make a tutorial on its usage?
These are awesome! So many applications: better, style transfer, coloring, … Thanks for help! Waiting for Automatic1111 version…
works but really, really bad memory optimization
Fantastic content my friend, I think you have lately become the most valuable yt channel on SD. Sadly even with his low vRAM commit I cant get this going on my 6gb 1660ti. Hope very much to see native support in 1111 soon.
I couldn't get pix2pix going even in 1111 with extention, but when they added native support it suddenly worked. Meanwhile I hope someone makes a Colab notebook.
Can this be added to 1111?
sÞper anlatÄąm saÄ ol hocam
It would be great if it was available as a plugin for automatic 1111
Hi @SECourses, thank you very much for this video, kkkkkk. I have a daughter who is an architect and this week I told her that someone would show up soon showing how to use these tools. Ahh today I also saw ChatGPT application creating codes in Python for map designs. The world we are living in is fantastic.
Is this better than pix2pix? Cna you compare the last control net with the same prompt to pix2pix?
It works fine! Thank you so much for showing step-by-step how to install it properly. Downloading the ControlNet models takes a long time, but it's definitely worth the trouble. I have just one question: the created images are not automatically saved, are they?
how about google colab ?