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Zero To Hero Generative AI - Become A Master

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  1. Lecture 1 : How To Install Python, Setup Virtual Environment VENV, Set Default Python System Path & Install Git
  2. Lecture 3 : Zero to Hero ControlNet Tutorial: Stable Diffusion Web UI Extension | Complete Feature Guide
  3. Lecture 4 : How To Find Best Stable Diffusion Generated Images By Using DeepFace AI - DreamBooth / LoRA Training
  4. Lecture 5 : Generate Studio Quality Realistic Photos By Kohya LoRA Stable Diffusion Training - Full Tutorial
  5. Lecture 6 : The END of Photography - Use AI to Make Your Own Studio Photos, FREE Via DreamBooth Training
  6. Lecture 7 : How To Use Stable Diffusion X-Large (SDXL) On Google Colab For Free
  7. Lecture 8 : Stable Diffusion XL (SDXL) Locally On Your PC - 8GB VRAM - Easy Tutorial With Automatic Installer
  8. Lecture 9 : Ultimate RunPod Tutorial For Stable Diffusion - Automatic1111 - Data Transfers, Extensions, CivitAI
  9. Lecture 10 : How To Use SDXL On RunPod Tutorial. Auto Installer & Refiner & Amazing Native Diffusers Based Gradio
  10. Lecture 11 : ComfyUI Tutorial - How to Install ComfyUI on Windows, RunPod & Google Colab | Stable Diffusion SDXL
  11. Lecture 12 : First Ever SDXL Training With Kohya LoRA - Stable Diffusion XL Training Will Replace Older Models
  12. Lecture 13 : How To Use SDXL in Automatic1111 Web UI - SD Web UI vs ComfyUI - Easy Local Install Tutorial / Guide
  13. Lecture 14 : Mind-Blowing Deepfake Tutorial: Turn Anyone into Your Favorite Movie Star! PC & Google Colab - roop
  14. Lecture 15 : How to use Stable Diffusion X-Large (SDXL) with Automatic1111 Web UI on RunPod - Easy Tutorial
  15. Lecture 16 : Become A Master Of SDXL Training With Kohya SS LoRAs - Combine Power Of Automatic1111 & SDXL LoRAs
  16. Lecture 17 : How To Do SDXL LoRA Training On RunPod With Kohya SS GUI Trainer & Use LoRAs With Automatic1111 UI
  17. Lecture 18 : How to Do SDXL Training For FREE with Kohya LoRA - Kaggle - NO GPU Required - Pwns Google Colab
  18. Lecture 19 : How Use Stable Diffusion, SDXL, ControlNet, LoRAs For FREE Without A GPU On Kaggle Like Google Colab
  19. Lecture 20 : Turn Videos Into Animation With Just 1 Click - ReRender A Video Tutorial
  20. Lecture 21 : Turn Videos Into Animation / 3D Just 1 Click - ReRender A Video Tutorial - Installer For RunPod
  21. Lecture 22 : Double Your Stable Diffusion Inference Speed with RTX Acceleration TensorRT: A Comprehensive Guide
  22. Lecture 23 : How to Install & Run TensorRT on RunPod, Unix, Linux for 2x Faster Stable Diffusion Inference Speed
  23. Lecture 24 : SOTA Image PreProcessing Scripts For Stable Diffusion Training - Auto Subject Crop & Face Focus
  24. Lecture 25 : Fooocus Stable Diffusion Web UI - Use SDXL Like You Are Using Midjourney - Easy To Use High Quality
  25. Lecture 26 : How To Do Stable Diffusion XL (SDXL) DreamBooth Training For Free - Utilizing Kaggle - Easy Tutorial
  26. Lecture 2 : Essential AI Tools and Libraries: A Guide to Python, Git, C++ Compile Tools, FFmpeg, CUDA, PyTorch
  27. Lecture 27 : Essential AI Tools and Libraries: A Guide to Python, Git, C++ Compile Tools, FFmpeg, CUDA, PyTorch
Lesson 5 of 27
In Progress

Lecture 6 : The END of Photography – Use AI to Make Your Own Studio Photos, FREE Via DreamBooth Training

icarus November 10, 2023

Dreambooth is the best training method for Stable Diffusion. In this tutorial, I show how to install the Dreambooth extension of Automatic1111 Web UI from scratch. Additionally, I demonstrate my months of work on the realism workflow, which enables you to produce studio-quality images of yourself through #Dreambooth training. Furthermore, I share my automatic installer script for the DreamBooth extension.

Source GitHub Readme File ⤵️

Automatic Installer Scripts ⤵️

Our Discord server ⤵️

Auto Install Scripts (windows) ⤵️

Auto Install Scripts (runpod) ⤵️

The generative AI along with LLMs are going to cause huge unemployment. Looks like #photography is going to be one of the early goners.

Moreover if you are having hard time to install and use DreamBooth, this tutorial is the best place that will teach you both automatically and manually installing the extension.

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 🥰 ⤵️

Technology & Science: News, Tips, Tutorials, Tricks, Best Applications, Guides, Reviews ⤵️

Playlist of #StableDiffusion Tutorials, Automatic1111 and Google Colab Guides, DreamBooth, Textual Inversion / Embedding, LoRA, AI Upscaling, Pix2Pix, Img2Img ⤵️

0:00 Dreambooth training with Automatic1111 Web UI
1:44 How to install DreamBooth extension of Automatic1111 Web UI
2:37 Automatic installer script for DreamBooth extension
3:20 Manual installation of DreamBooth extension
3:30 How to use older / certain version of Auto1111 or DreamBooth with git checkout
4:30 Main manual installation part of DreamBooth extension
4:57 How to manually update previously installed DreamBooth extension to the latest version
5:44 How to install requirements of DreamBooth extension
7:15 How to use DreamBooth extension
7:25 How to compose your training model in DreamBooth extension
7:35 Best base model and settings for realism training in DreamBooth
7:51 Where to find installed Python ,xFormers, Torch, Auto1111 versions
8:10 How to solve frozen / non-progressing CMD window
8:23 Where the DreamBooth generated training files (native diffusers) are stored
8:37 Where the Stable Diffusion training files are stored
8:57 Select training model and start setting parameters for best realism
9:07 How to continue training later a time
9:38 Which configuration (settings tab) for best realism and best training
12:14 Concept tab settings
12:28 How to prepare your training images dataset with my human cropping script and pre-processing
13:43 What kind of training images you should have for DreamBooth training
14:52 Continue back setting parameters for concepts tab
15:02 Everything about classification / regularization images used during Dreambooth / LoRA training
16:07 Used pre-prepared real images based classification images for this tutorial
16:55 How to generate classification images by using the trained model
17:22 How to generate images with Automatic1111 forever until cancelled
18:09 How to use image captions with DreamBooth extension via [filewords]
18:25 How to automatically generate captions for training or class images
18:35 How to use BLIP or deepbooru for captioning
19:25 What happens when image caption is read, what is the final output of instance prompt
19:59 How to set class images per instance
20:32 What is the benefit of using real photos as classification images
21:42 How to start training after setting all configuration
23:05 Training started, displayed messages on CMD
23:47 When it generates new classification images
25:52 What if if you don’t have such powerful GPU for such quality training
26:55 How to do x/y/z checkpoint comparison to find best checkpoint
28:43 How checkpoints are named when saved – 1 epoch step count
30:05 The best VAE file I use for best quality
30:36 How to open x/y/z plot comparison results and evaluate them
33:20 How sort thousands of generated image with the best similarity thus quality
34:39 How to improve generated image quality via 2 different inpainting methodology
36:56 Improve results with inpainting + ControlNet
38:50 What is important to get good quality images after inpainting