Lecture 1: How To Install Python, Setup Virtual Environment VENV, Set Default Python System Path & Install Git 0:00 Very comprehensive guide to Python installation on Windows 1:11 What is CMD - Command Prompt 1:56 How to open a cmd window and use it 2:04 How to run cmd as administrator 2:17 What is Git and why do we need Git 2:35 How to download and install Git 3:30 Why do we need Git large and how to download and install Git large 3:50 Why do we need specific Python versions 4:03 How to download and install any Python version 4:32 How to verify if Python installed or not 4:55 How to customize Python installation 5:17 Python add path checkbox during installation 6:20 How to verify your Python installed version 6:35 How to change or set system environment variables path of Python 7:15 How to install another Python version - multiple Python installations 8:30 How to change default Python version when having multiple Python installations 9:30 How to use specific Python installation when having multiple Python 9:35 What is Python venv and why do we need it 10:40 How to start cmd inside certain directory 10:55 How to compose a Python venv 11:19 How to activate Python venv 11:58 How to compose a venv from different Python version 13:39 Demo of installed package separation from other Python installations inside venv 14:17 Where to find installed packages in Python installation folder 14:50 How to write a bash script to automatically activate Python venv and start a cmd 15:24 How to view extensions of files in Windows 15:43 The script itself to activate venv and start cmd 17:11 How to install Stable Diffusion Automatic1111 web UI 17:30 How to use Git clone to download entire project from GitHub repo Lecture 2: Zero to Hero ControlNet Tutorial: Stable Diffusion Web UI Extension | Complete Feature Guide 0:00 Introduction to most advanced zero to hero ControlNet tutorial 2:55 How to install Stable Diffusion Automatic1111 Web UI from scratch 5:05 How to see extensions of files like .bat 6:15 Where to find command line arguments of Automatic1111 and what are they 6:46 How to run Stable Diffusion and ControlNet on a weak GPU 7:37 Where to put downloaded Stable Diffusion model files 8:29 How to give different folder path as the model path - you can store models on another drive 9:15 How to start using Stable Diffusion via Automatic1111 Web UI 10:00 Command line interface freezing behaviour 10:13 How to improve image generation of Stable Diffusion with better VAE file 11:39 Default VAE vs best VAE comparison 11:50 How to set quick shortcuts for VAE and Clip Skip for Automatic1111 Web UI 12:30 How to upgrade xFormers to the latest version in Automatic1111 13:40 What is xFormers and other optimizers 14:26 How to install ControlNet extension of Automatic1111 Web UI 18:00 How to download ControlNet models 19:40 How to use custom Stable Diffusion models with Automatic1111 Web UI 21:24 How to update ControlNet extension to the latest version 22:53 Set this true, allow other scripts to control ControlNet extension 24:37 How to make amazing QR code images with ControlNet 30:59 Best settings for QR code image generation 31:44 What is Depth ControlNet option and how to use it 33:28 Depth_leres++ of ControlNet 34:15 Depth_zoe of ControlNet 34:22 Official information of Depth maps 34:49 ControlNet Normal map 35:34 Normal Midas map 36:05 Official information of Normal maps 34:49 ControlNet Canny model 37:42 Official information of Canny 37:55 ControlNet MLSD straight lines model 39:08 Official information of MLSD straight lines 39:18 ControlNet Scribble model 40:28 How to use your own scribble images and turn them into amazing artworks 40:45 When to select none in pre-processor section 41:20 My prompt is more important 41:36 ControlNet is more important 42:01 Official information of Scribble 42:11 ControlNet Softedge model 43:12 Official information of SoftEdge 43:22 ControlNet Segmentation (Seg) model 43:55 How to modify your prompt to properly utilize segmentation 44:10 Association of prompt with segments the ControlNet finds 44:41 How to turn your wall into a painting with ControlNet 45:33 Why I selected none preprocessor 43:06 Official information of segmentation (Seg) 46:16 Open pose module of ControlNet 46:40 How to install and use OpenPose editor 50:58 Official information of OpenPose 51:08 ControlNet Lineart model 51:36 Preprocessor preview bug 54:21 Real lineart into amazing art example 56:34 How to generate amazing logo images by using Lineart of ControlNet 58:16 Difference between just resize, crop and resize, and resize and fill 59:02 ControlNet Shuffle model 1:00:50 Official information of Shuffle 1:02:36 What is multi-ControlNet and how to use it 1:04:05 Instruct pix2pix of ControlNet 1:06:00 Inpainting feature of ControlNet 1:07:49 ControlNet inpainting vs Automatic1111 inpainting 1:07:59 How to get true power of inpainting of ControlNet (hint: with tiling) 1:09:00 How to upscale and add details to the images with inpainting + tiling 1:09:30 The tile color fix + sharp to obtain even better results 1:10:35 Tile color fix + sharp vs old tile resample result comparison 1:11:20 How to use generative fill feature of Photoshop in ControlNet to remove objects 1:12:58 How to outpaint (zoom out feature of midjourney 5.2) image with ControlNet 1:14:17 The logic of outpainting 1:14:40 How to continue outpainting easily 1:16:06 Tiling of ControlNet - ultimate game changer for upscaling 1:17:19 How to turn your image into a fully stylized image with tiling without training 1:20:57 Reference only feature of ControlNet 1:22:29 Official information of Reference mode 1:22:39 Style Transfer (T2IA) of ControlNet 1:26:54 How to install and use ControlNet on RunPod Lecture 3: How To Find Best Stable Diffusion Generated Images By Using DeepFace AI - DreamBooth / LoRA Training 0:00 Introduction to what DeepFace does and how we are going to utilize it 0:58 Let's say you have generated 2000 images how to get good ones 1:17 This approach can be used for professional business purposes 1:32 If you are new to Stable Diffusion or image generation 2:17 Beginning with composing venv to install DeepFace 3:18 The training dataset images I have used for this tutorial 3:57 I have generated over 3000 images 4:06 The prompts I have used to generate images - how to use PNG info to find used prompts 5:23 How to write and use DeepFace best images finding script 9:18 How to use the script demonstration after you written and set it 11:20 Explanation of the values displayed during the script runtime 12:18 Sorted images from best to worst Lecture 4: Generate Studio Quality Realistic Photos By Kohya LoRA Stable Diffusion Training - Full Tutorial 0:00 Introduction to Kohya LoRA Training and Studio Quality Realistic AI Photo Generation 2:40 How to download and install Kohya’s GUI to do Stable Diffusion training 5:04 How to install newer cuDNN dll files to increase training speed 6:43 How to upgrade to the latest version previously installed Kohya GUI 7:02 How to start Kohya GUI via cmd 8:00 How to set DreamBooth LoRA training parameters correctly 8:10 How to use previously downloaded models to do Kohya LoRA training 8:35 How to download Realistic Vision V2 model 8:49 How to do training with Stable Diffusion 2.1 512px and 768px versions 9:44 Instance / activation and class prompt settings 10:18 What kind of training dataset you should use 11:46 Explanation of number of repeats in Kohya DreamBooth LoRA training 13:34 How to set best VAE file for better image generation quality 13:52 How to generate classification / regularization images via Automatic1111 Web UI 16:53 How to prepare captions to images and when you do need image captions 17:48 What kind of regularization images I have used 18:04 How to set training folders 18:57 Best LoRA Training settings for minimum amount of VRAM having GPUs 21:47 How to save state of training and continue later 22:44 How to save and load Kohya Training settings 23:31 How to calculate 1 epoch step count when considering repeating count 24:41 How to decide how many epochs when repeating count considered 26:00 Explanation of command line parameters displayed during training 28:19 Caption extension changing 29:24 After when we will get a checkpoint and checkpoints will be saved where 29:57 How to use generated LoRA safetensors files in SD Automatic1111 Web UI 30:45 How to activate LoRA in Stable Diffusion web UI 31:30 How to do x/y/z checkpoint comparison of LoRA checkpoints to find best model 33:29 How to improve face quality of generated images with high res fix 36:00 18 Different training parameters experiments I have made and their results comparison 36:42 How to test 18 different LoRA checkpoints with x/y/z plot 39:18 How to properly set number of epochs and save checkpoints when reducing repeating count 40:36 How to use checkpoints of Kohya DyLora, LoCon, LyCORIS/LoCon, LoHa in Automatic1111 Web UI 42:12 How to install Torch 1.13 instead of 1.12 and newer xFormers compatible with this version 43:06 How to make Kohya scripts to use your second GPU instead of your primary GPU Lecture 5: The END of Photography - Use AI to Make Your Own Studio Photos, FREE Via DreamBooth Training 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
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