--K-DIFFUSION RETARD GUIDE (GUI)--

(8/22) New 1.4 AI model released! Tested fully functioning, no adjustments needed!
The definitive Stable Diffusion experience ™
(Windows)
Special thanks to all anons who contributed

What does this add?

Gradio GUI: A retard-proof, fully featured frontend for both txt2img and img2img generation
No more manually typing parameters, now all you have to do is write your prompt and adjust sliders
K-sampling: Far greater quality outputs than the default sampler, less distortion and more accurate
Easy Img2Img: Drag and drop img2img with built-in cropping tool
CFG: Classifier free guidance scale, a previously unavailable feature for fine-tuning your output
Lighter on Vram: 512x512 img2img & txt2img tested working on 6gb
Randomized seed: No more getting the same results, seed is randomized by default

Guide

Step 1: Download the NEW 1.4 model from HERE
Torrent magnet: https://rentry.org/sdiffusionmagnet

Step 2: Git clone or download the repo from https://github.com/harubaru/waifu-diffusion/ and extract
(Make sure you have Git beforehand anyway, it will be needed)

Step 3: Go into the repo you downloaded and go to waifu-diffusion-main/models/ldm.
Create a folder called "stable-diffusion-v1". Rename your .ckpt file to "model.ckpt", and put it into that folder you've made

Step 4: Download the Gradio script and rename it to "kdiff.py" (save as all files)
https://pastebin.com/0cFdFC5V
mirror
Put kdiff.py into your /scripts folder

Step 5: Download the new environment.yaml and place it in waifu-diffusion-main, replacing the old one (save as all files)
https://pastebin.com/S9V49mvu
mirror

Step 6: Download Miniconda HERE. Download Miniconda 3

Step 7: Install Miniconda. Install for all users. Uncheck "Register Miniconda as the system Python 3.9" unless you want to

Step 8: Open Anaconda Prompt (miniconda3).
Go to the waifu-diffusion-main folder wherever you downloaded using "cd" to jump folders.
(Or just type "cd" followed by a space and then drag the folder into the Anaconda prompt.)

Step 9: If you have existing folders named "clip" and "taming-transformers" in /src, delete them

Step 10: Run the following command: "conda env create -f environment.yaml" and wait
(Make sure you are in the waifu-diffusion-main folder)

Step 11: Run the following command: "conda activate ldw"
(You will need to type this each time you open Miniconda before running scripts!)

Setup Complete

--USAGE--

Open Miniconda and navigate to waifu-diffusion
Type "conda activate ldw"
Type "python scripts/kdiff.py" and wait while it loads into ram and vram
After finishing, it should give you a LAN ip with a port such as '192.0.1:3288'
Open your browser and enter the address
You should now be in an interface with a txt2img and img2img tab
Have fun

--NOTES AND TIPS--

Build great prompts using the prompt builder
Check out the wiki https://wiki.installgentoo.com/wiki/Stable_Diffusion
Sampling iterations = how many images are made in a batch
Samples per iteration = how many images are rendered simultaneously. It shouldn't be greater than 1 or 2 unless you have very high vram
(img2img) Adjust Denoising Strength accordingly. Higher = more guided toward prompt, Lower = more guided toward image
Anywhere between 0.3 and 0.9 is the sweet spot for prompts
If your output is a jumbled rainbow mess your image resolution is set TOO LOW
Feeding outputs back in using the same prompt with a weak strength multiple times can produce great results
The more keywords, the better. Look up guides for prompt tagging
It's recommended to have your prompts be at least 512 pixels in one dimension, or a 384x384 square at the smallest
Anything smaller will have heavy artifacting
Try Low strength (0.3-0.4) + High CFG in img2img for interesting outputs
The seed for each generated result is in the output filename if you want to revisit it
You can use Japanese Unicode characters in prompts
This guide is designed for NVIDIA GPUs only, as stable diffusion requires cuda cores.
AMD users should try https://rentry.org/kretard
A good tool for upscaling your outputs is Real-ESRGAN: https://github.com/xinntao/Real-ESRGAN
You can prune a v1.3 weight model using "python scripts/prune.py" in waifu-diffusion-main
Pruning shrinks the file size to 2gb instead of 7. Output remains largely equivalent
Comparison- https://i.postimg.cc/ZRKz4tJv/textprune.png
(Prune.py does not work on the new model, and does not matter as v1.4 is less heavy than v1.3 )
If your output is solid green, the half precision optimization may not be working for you:
GREEN SCREEN FIX:
1- change the value of "default" to "full" in line 169 and 343 of kdiff.py
2- delete ".half()" in line 89 of kdiff.py
(Note: this will raise vram usage drastically)

--OLD MODEL--
The original v1.3 leaked model from July can be downloaded here:
https://drinkordiecdn.lol/sd-v1-3-full-ema.ckpt
Backup Download: https://download1980.mediafire.com/3nu6nlhy92ag/wnlyj8vikn2kpzn/sd-v1-3-full-ema.ckpt
Torrent Magnet: https://rentry.co/6gocs

--CHANGELOG--
8/22: renamed "gradio.py" to "kdiff.py"- previous name conflicted with Gradio package causing an AttributeError.
If you are having issues, please rename it

added fix to green screen of death
added official v1.4 model links
8/23: Installation process now simplified vastly using new environment.yaml, original guide available at https://rentry.org/kretardold if problems arise