Include C:\Windows\System32 in the path anyway, to avoid the errors some users have

Live Preview, In-Painting Editor, New Sampler Options, VRAM (Memory) Usage Improvements, Progress Bar, Re-organized UI with more space for images, Update to the latest fork version

.github/FUNDING.yml

@@ -0,0 +1,3 @@
+# These are supported funding model platforms
+
+ko_fi: cmdr2_stablediffusion_ui

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,38 @@
+---
+name: Bug report
+about: Create a report to help us improve
+title: ''
+labels: bug
+assignees: ''
+
+---
+
+**Describe the bug**
+A clear and concise description of what the bug is.
+
+**To Reproduce**
+Steps to reproduce the behavior:
+1. Go to '...'
+2. Click on '....'
+3. Scroll down to '....'
+4. See error
+
+**Expected behavior**
+A clear and concise description of what you expected to happen.
+
+**Screenshots**
+If applicable, add screenshots to help explain your problem.
+
+**Desktop (please complete the following information):**
+ - OS: 
+ - Browser:
+ - Version:
+
+**Smartphone (please complete the following information):**
+ - Device: 
+ - OS: 
+ - Browser 
+ - Version 
+
+**Additional context**
+Add any other context about the problem here.

.github/ISSUE_TEMPLATE/feature_request.md

@@ -0,0 +1,20 @@
+---
+name: Feature request
+about: Suggest an idea for this project
+title: ''
+labels: enhancement
+assignees: ''
+
+---
+
+**Is your feature request related to a problem? Please describe.**
+A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
+
+**Describe the solution you'd like**
+A clear and concise description of what you want to happen.
+
+**Describe alternatives you've considered**
+A clear and concise description of any alternative solutions or features you've considered.
+
+**Additional context**
+Add any other context or screenshots about the feature request here.

.gitignore

@@ -1 +1,5 @@
 __pycache__
+installer
+installer.tar
+dist
+.idea/*

CONTRIBUTING.md

@@ -0,0 +1,55 @@
+Hi there, these instructions are meant for the developers of this project.
+
+If you only want to use the Stable Diffusion UI, you've downloaded the wrong file. In that case, please download and follow the instructions at https://github.com/cmdr2/stable-diffusion-ui#installation
+
+Thanks
+
+# For developers:
+
+If you would like to contribute to this project, there is a discord for dicussion:
+[![Discord Server](https://badgen.net/badge/icon/discord?icon=discord&label)](https://discord.com/invite/u9yhsFmEkB)
+
+## Development environment for UI (frontend and server) changes
+This is in-flux, but one way to get a development environment running for editing the UI of this project is:
+(swap `.sh` or `.bat` in instructions depending on your environment, and be sure to adjust any paths to match where you're working)
+
+1) `git clone` the repository, e.g. to `/projects/stable-diffusion-ui-repo`
+2) Download the pre-built end user archive from the link on github, and extract it, e.g. to `/projects/stable-diffusion-ui-archive`
+3) `cd /projects/stable-diffusion-ui-archive` and run the script to set up and start the project, e.g. `start.sh`
+4) Check you can view and generate images on `localhost:9000`
+5) Close the server, and edit `/projects/stable-diffusion-ui-archive/scripts/on_env_start.sh`
+6) Comment out the lines near the bottom that copies the `files/ui` folder, e.g:
+  
+  for `.sh`
+```
+# rm -rf ui
+# cp -Rf sd-ui-files/ui .
+# cp sd-ui-files/scripts/on_sd_start.sh scripts/
+# cp sd-ui-files/scripts/start.sh .
+``` 
+for `.bat`
+```
+REM @xcopy sd-ui-files\ui ui /s /i /Y
+REM @copy sd-ui-files\scripts\on_sd_start.bat scripts\ /Y
+REM @copy "sd-ui-files\scripts\Start Stable Diffusion UI.cmd" . /Y
+``` 
+7) Comment out the line at the top of `/projects/stable-diffusion-ui-archive/scripts/on_sd_start.sh` that copies `on_env_start`. For e.g. `@copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y`
+8) Delete the current `ui` folder at `/projects/stable-diffusion-ui-archive/ui`
+9) Now make a symlink between the repository clone (where you will be making changes) and this archive (where you will be running stable diffusion):
+`ln -s /projects/stable-diffusion-ui-repo/ui /projects/stable-diffusion-ui-archive/ui`
+or for Windows
+`mklink /D \projects\stable-diffusion-ui-archive\ui \projects\stable-diffusion-ui-repo\ui` (link name first, source repo dir second)
+9) Run the archive again `start.sh` and ensure you can still use the UI.
+10) Congrats, now any changes you make in your repo `ui` folder are linked to this running archive of the app and can be previewed in the browser.
+
+Check the `ui/frontend/build/README.md` for instructions on running and building the React code.
+
+## Development environment for Installer changes
+Build the Windows installer using Windows, and the Linux installer using Linux. Don't mix the two, and don't use WSL. An Ubuntu VM is fine for building the Linux installer on a Windows host.
+
+1. Install Miniconda 3 or Anaconda.
+2. Install `conda install -c conda-forge -y conda-pack`
+3. Open the Anaconda Prompt. Do not use WSL if you're building for Windows.
+4. Run `build.bat` or `./build.sh` depending on whether you're in Windows or Linux.
+5. Compress the `stable-diffusion-ui` folder created inside the `dist` folder. Make a `zip` for Windows, and `tar.xz` for Linux (smaller files, and Linux users already have tar).
+6. Make a new GitHub release and upload the Windows and Linux installer builds.

Dockerfile

@@ -1,15 +0,0 @@
-FROM python:3.9
-
-RUN mkdir /app
-WORKDIR /app
-
-RUN apt update
-
-COPY requirements.txt ./
-RUN pip install --no-cache-dir -r requirements.txt
-
-COPY . .
-
-EXPOSE 8000
-
-ENTRYPOINT ["uvicorn", "main:app", "--reload", "--host", "0.0.0.0"]

How to install and run.txt

@@ -0,0 +1,24 @@
+Congrats on downloading Stable Diffusion UI, version 2!
+
+If you haven't downloaded Stable Diffusion UI yet, please download from https://github.com/cmdr2/stable-diffusion-ui#installation
+
+After downloading, to install please follow these instructions:
+
+For Windows:
+- Please double-click the "Start Stable Diffusion UI.cmd" file inside the "stable-diffusion-ui" folder.
+
+For Linux:
+- Please open a terminal, and go to the "stable-diffusion-ui" directory. Then run ./start.sh
+
+That file will automatically install everything. After that it will start the Stable Diffusion interface in a web browser.
+
+To start the UI in the future, please run the same command mentioned above.
+
+
+If you have any problems, please:
+1. Try the troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting
+2. Or, seek help from the community at https://discord.com/invite/u9yhsFmEkB
+3. Or, file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues
+
+Thanks
+cmdr2 (and contributors to the project)

README BEFORE YOU RUN THIS.txt

@@ -0,0 +1,8 @@
+Hi there,
+
+What you have downloaded is meant for the developers of this project, not for users.
+
+If you only want to use the Stable Diffusion UI, you've downloaded the wrong file.
+Please download and follow the instructions at https://github.com/cmdr2/stable-diffusion-ui#installation
+
+Thanks

README.md

@@ -1,37 +1,57 @@
-# Stable Diffusion UI
-### A simple way to install and use [Stable Diffusion](https://replicate.com/stability-ai/stable-diffusion) on your own computer
+# Stable Diffusion UI v2
+### A simple 1-click way to install and use [Stable Diffusion](https://github.com/CompVis/stable-diffusion) on your own computer. No dependencies or technical knowledge required.
 
----
+<p float="left">
+  <a href="#installation"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/develop/media/download-win.png" width="200" /></a>
+  <a href="#installation"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/develop/media/download-linux.png" width="200" /></a>
+</p>
 
-🎉 **New!** `img2img` and `inpaint` (masking) are now supported! You can provide an image to generate new images based on it (and an optional text prompt). You can also use the generated image as the new input image in 1-click, to refine it further. (Thanks [Andreas](https://github.com/andreasjansson)!)
+[![Discord Server](https://badgen.net/badge/icon/discord?icon=discord&label)](https://discord.com/invite/u9yhsFmEkB) (for support, and development discussion) | [Troubleshooting guide for common problems](Troubleshooting.md)
 
-# What does this do?
-Two things:
-1. Automatically downloads and installs Stable Diffusion on your own computer (no need to mess with conda or environments)
-2. Gives you a simple browser-based UI to talk to your local Stable Diffusion. Enter text prompts and view the generated image. No API keys required.
+️‍🔥🎉 **New!** Live Preview, More Samplers, In-Painting, Face Correction (GFPGAN) and Upscaling (RealESRGAN) have been added!
 
-All the processing will happen on your computer locally, it does not transmit your prompts or process on any remote server.
+This distribution currently uses Stable Diffusion 1.4. Once the model for 1.5 becomes publicly available, the model in this distribution will be updated.
 
-<img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/shot-v4.jpg" height="500" alt="Screenshot of tool">
+# Features in the new v2 Version:
+- **No Dependencies or Technical Knowledge Required**: 1-click install for Windows 10/11 and Linux. *No dependencies*, no need for WSL or Docker or Conda or technical setup. Just download and run!
+- **Face Correction (GFPGAN) and Upscaling (RealESRGAN)**
+- **In-Painting**
+- **Live Preview**: See the image as the AI is drawing it
+- **Lots of Samplers**
+- **Image Modifiers**: A library of *modifier tags* like *"Realistic"*, *"Pencil Sketch"*, *"ArtStation"* etc. Experiment with various styles quickly.
+- **New UI**: with cleaner design
+- Supports "*Text to Image*" and "*Image to Image*"
+- **NSFW Setting**: A setting in the UI to control *NSFW content*
+- **Use CPU setting**: If you don't have a compatible graphics card, but still want to run it on your CPU.
+- **Auto-updater**: Gets you the latest improvements and bug-fixes to a rapidly evolving project.
+- **Low Memory Usage**: Creates 512x512 images with less than 4GB of VRAM!
+
+![Screenshot](media/shot-v8.jpg?raw=true)
 
 # System Requirements
-1. Computer capable of running Stable Diffusion.
-2. Linux or Windows 11 (with [WSL](https://docs.microsoft.com/en-us/windows/wsl/install)) or Windows 10 v2004+ (Build 19041+) with [WSL](https://docs.microsoft.com/en-us/windows/wsl/install).
-3. Requires (a) [Docker](https://docs.docker.com/engine/install/), (b) [docker-compose v1.29](https://docs.docker.com/compose/install/), and (c) [nvidia-container-toolkit](https://stackoverflow.com/a/58432877).
+1. Windows 10/11, or Linux. Experimental support for Mac is coming soon.
+2. An NVIDIA graphics card, preferably with 6GB or more of VRAM. But if you don't have a compatible graphics card, you can still use it with a "Use CPU" setting. It'll be very slow, but it should still work.
 
-**Important:** If you're using Windows, please install docker inside your [WSL](https://docs.microsoft.com/en-us/windows/wsl/install)'s Linux. Install docker for the Linux distro in your WSL. **Don't install Docker for Windows.**
+You do not need anything else. You do not need WSL, Docker or Conda. The installer will take care of it.
 
 # Installation
-1. Clone this repository: `git clone https://github.com/cmdr2/stable-diffusion-ui.git` or [download the zip file](https://github.com/cmdr2/stable-diffusion-ui/archive/refs/heads/main.zip) and unzip.
-2. Open your terminal, and in the project directory run: `./server` (warning: this will take some time during the first run, since it'll download Stable Diffusion's [docker image](https://replicate.com/stability-ai/stable-diffusion), nearly 17 GiB)
-3. Open http://localhost:8000 in your browser. That's it!
+1. **Download** [for Windows](https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.05/stable-diffusion-ui-win64.zip) or [for Linux](https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.05/stable-diffusion-ui-linux.tar.xz).
 
-If you're getting errors, please check the [Troubleshooting](#troubleshooting) section below.
+2. **Extract**:
+  - For Windows: After unzipping the file, please move the `stable-diffusion-ui` folder to your `C:` (or any drive like D:, at the top root level), e.g. `C:\stable-diffusion-ui`. This will avoid a common problem with Windows (file path length limits).
+  - For Linux: After extracting the .tar.xz file, please open a terminal, and go to the `stable-diffusion-ui` directory.
+
+3. **Run**:
+  - For Windows: `Start Stable Diffusion UI.cmd` by double-clicking it.
+  - For Linux: In the terminal, run `./start.sh` (or `bash start.sh`)
+
+This will automatically install Stable Diffusion, set it up, and start the interface. No additional steps are needed.
+
+**To Uninstall:** Just delete the `stable-diffusion-ui` folder to uninstall all the downloaded packages.
 
-To stop the server, please run `./server stop`
 
 # Usage
-Open http://localhost:8000 in your browser (after running `./server` from step 2 previously).
+Open http://localhost:9000 in your browser (after running step 3 previously). It may take a few moments for the back-end to be ready.
 
 ## With a text description
 1. Enter a text prompt, like `a photograph of an astronaut riding a horse` in the textbox.
@@ -43,50 +63,35 @@ Open http://localhost:8000 in your browser (after running `./server` from step 2
 2. An optional text prompt can help you further describe the kind of image you want to generate.
 3. Press `Make Image`. See the image generated using your prompt.
 
-You can also set an `Image Mask` for telling Stable Diffusion to draw in only the black areas in your image mask. White areas in your mask will be ignored.
+You can use Face Correction or Upscaling to improve the image further.
 
 **Pro tip:** You can also click `Use as Input` on a generated image, to use it as the input image for your next generation. This can be useful for sequentially refining the generated image with a single click.
 
 **Another tip:** Images with the same aspect ratio of your generated image work best. E.g. 1:1 if you're generating images sized 512x512.
 
-## Problems?
-Please [file an issue](https://github.com/cmdr2/stable-diffusion-ui/issues) if this did not work for you (after trying the common [troubleshooting](#troubleshooting) steps)!
+## Problems? Troubleshooting
+Please try the common [troubleshooting](Troubleshooting.md) steps. If that doesn't fix it, please ask on the [discord server](https://discord.com/invite/u9yhsFmEkB), or [file an issue](https://github.com/cmdr2/stable-diffusion-ui/issues).
 
 # Advanced Settings
 You can also set the configuration like `seed`, `width`, `height`, `num_outputs`, `num_inference_steps` and `guidance_scale` using the 'show' button next to 'Advanced settings'.
 
 Use the same `seed` number to get the same image for a certain prompt. This is useful for refining a prompt without losing the basic image design. Enable the `random images` checkbox to get random images.
 
-![Screenshot of advanced settings](media/config-v2.jpg?raw=true)
+![Screenshot of advanced settings](media/config-v6.png?raw=true)
 
-# Troubleshooting
-## './docker-compose.yml' is invalid:
-> ERROR: The Compose file './docker-compose.yml' is invalid because:
-> services.stability-ai.deploy.resources.reservations value Additional properties are not allowed ('devices' was unexpected)
+# What is this? Why no Docker?
+This version is a 1-click installer. You don't need WSL or Docker or anything beyond a working NVIDIA GPU with an updated driver. You don't need to use the command-line at all. Even if you don't have a compatible GPU, you can run it on your CPU (albeit very slowly).
 
-Please ensure you have `docker-compose` version 1.29 or higher. Check `docker-compose --version`, and if required [update it to 1.29](https://docs.docker.com/compose/install/). (Thanks [HVRyan](https://github.com/HVRyan))
+It'll download the necessary files from the original [Stable Diffusion](https://github.com/CompVis/stable-diffusion) git repository, and set it up. It'll then start the browser-based interface like before.
 
-## RuntimeError: Found no NVIDIA driver on your system:
-If you have an NVIDIA GPU and the latest [NVIDIA driver](http://www.nvidia.com/Download/index.aspx), please ensure that you've installed [nvidia-container-toolkit](https://stackoverflow.com/a/58432877). (Thanks [u/exintrovert420](https://www.reddit.com/user/exintrovert420/))
-
-## Some other process is already running at port 8000 / port 8000 could not be bound
-You can override the port used. Please change `docker-compose.yml` inside the project directory, and update the line `8000:8000` to `1337:8000` (or where 1337 is whichever port number you want).
-
-After doing this, please restart your server, by running `./server restart`.
-
-After this, you can access the server at `http://localhost:1337` (where 1337 is the new port you specified earlier).
-
-# Behind the scenes
-This project is a quick way to get started with Stable Diffusion. You do not need to have Stable Diffusion already installed, and do not need any API keys. This project will automatically download Stable Diffusion's docker image, the first time it is run.
-
-This project runs Stable Diffusion in a docker container behind the scenes, using Stable Diffusion's [Docker image](https://replicate.com/stability-ai/stable-diffusion) on replicate.com.
+The NSFW option is currently off (temporarily), so it'll allow NSFW images, for those people who are unable to run their prompts without hitting the NSFW filter incorrectly.
 
 # Bugs reports and code contributions welcome
-If there are any problems or suggestions, please feel free to [file an issue](https://github.com/cmdr2/stable-diffusion-ui/issues).
+If there are any problems or suggestions, please feel free to ask on the [discord server](https://discord.com/invite/u9yhsFmEkB) or [file an issue](https://github.com/cmdr2/stable-diffusion-ui/issues).
 
-Also, please feel free to submit a pull request, if you have any code contributions in mind.
+Also, please feel free to submit a pull request, if you have any code contributions in mind. Join the [discord server](https://discord.com/invite/u9yhsFmEkB) for development-related discussions, and for helping other users.
 
 # Disclaimer
 The authors of this project are not responsible for any content generated using this interface.
 
-This license of this software forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, spread misinformation and target vulnerable groups. For the full list of restrictions please read [the license](LICENSE).
+The license of this software forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, spread misinformation, or target vulnerable groups. For the full list of restrictions please read [the license](LICENSE). You agree to these terms by using this software.

Troubleshooting.md

@@ -0,0 +1,46 @@
+Common issues and their solutions. If these solutions don't work, please feel free to ask at the [discord server](https://discord.com/invite/u9yhsFmEkB) or [file an issue](https://github.com/cmdr2/stable-diffusion-ui/issues).
+
+## RuntimeError: CUDA out of memory
+This can happen if your PC has less than 6GB of VRAM.
+
+Try disabling the "Turbo mode" setting under "Advanced Settings", since that takes an additional 1 GB of VRAM (to increase the speed).
+
+Additionally, a common reason for this error is that you're using an initial image larger than 768x768 pixels. Try using a smaller initial image.
+
+Also try generating smaller sized images.
+
+## No ldm found, or antlr4 or any other missing module, or ClobberError: This transaction has incompatible packages due to a shared path
+On Windows, please ensure that you had placed the `stable-diffusion-ui` folder after unzipping to the root of C: or D: (or any drive). For e.g. `C:\stable-diffusion-ui`. **Note:** This has to be done **before** you start the installation process. If you have already installed (and are facing this error), please delete the installed folder, and start fresh by unzipping and placing the folder at the top of your drive.
+
+This error can also be caused if you already have conda/miniconda/anaconda installed, due to package conflicts. Please open your Anaconda Prompt, and run `conda clean --all` to clean up unused packages.
+
+If nothing works, this could be due to a corrupted installation. Please try reinstalling this, by deleting the installed folder, and unzipping from the downloaded zip file.
+
+## Killed uvicorn server:app --app-dir ... --port 9000 --host 0.0.0.0
+This happens if your PC ran out of RAM. Stable Diffusion requires a lot of RAM, and requires atleast 10 GB of RAM to work well. You can also try closing all other applications before running Stable Diffusion UI.
+
+## Green image generated
+This usually happens if you're running NVIDIA 1650 or 1660 Super. To solve this, please close and run the Stable Diffusion command on your computer. If you're using the older Docker-based solution (v1), please upgrade to v2: https://github.com/cmdr2/stable-diffusion-ui/tree/v2#installation
+
+If you're still seeing this error, please try enabling "Full Precision" under "Advanced Settings" in the Stable Diffusion UI.
+
+## './docker-compose.yml' is invalid:
+> ERROR: The Compose file './docker-compose.yml' is invalid because:
+> services.stability-ai.deploy.resources.reservations value Additional properties are not allowed ('devices' was unexpected)
+
+Please ensure you have `docker-compose` version 1.29 or higher. Check `docker-compose --version`, and if required [update it to 1.29](https://docs.docker.com/compose/install/). (Thanks [HVRyan](https://github.com/HVRyan))
+
+## RuntimeError: Found no NVIDIA driver on your system:
+If you have an NVIDIA GPU and the latest [NVIDIA driver](http://www.nvidia.com/Download/index.aspx), please ensure that you've installed [nvidia-container-toolkit](https://stackoverflow.com/a/58432877). (Thanks [u/exintrovert420](https://www.reddit.com/user/exintrovert420/))
+
+## Some other process is already running at port 9000 / port 9000 could not be bound
+You can override the port used. Please change `docker-compose.yml` inside the project directory, and update the line `9000:9000` to `1337:9000` (where 1337 is whichever port number you want).
+
+After doing this, please restart your server, by running `./server restart`.
+
+After this, you can access the server at `http://localhost:1337` (where 1337 is the new port you specified earlier).
+
+## RuntimeError: CUDA error: unknown error
+Please ensure that you have an NVIDIA GPU and the latest [NVIDIA driver](http://www.nvidia.com/Download/index.aspx), and that you've installed [nvidia-container-toolkit](https://stackoverflow.com/a/58432877).
+
+Also, if you are using WSL (Windows), please ensure you have the latest WSL kernel by running `wsl --shutdown` and then `wsl --update`. (Thanks [AndrWeisR](https://github.com/AndrWeisR))

build.bat

@@ -0,0 +1,49 @@
+@echo off
+
+@echo "Hi there, what you are running is meant for the developers of this project, not for users." & echo.
+@echo "If you only want to use the Stable Diffusion UI, you've downloaded the wrong file."
+@echo "Please download and follow the instructions at https://github.com/cmdr2/stable-diffusion-ui#installation" & echo.
+@echo "If you are actually a developer of this project, please type Y and press enter" & echo.
+
+set /p answer=Are you a developer of this project (Y/N)?
+if /i "%answer:~,1%" NEQ "Y" exit /b
+
+@mkdir dist\stable-diffusion-ui
+
+@echo "Downloading components for the installer.."
+
+@call conda env create --prefix installer -f environment.yaml
+@call conda activate .\installer
+
+@echo "Setting up startup scripts.."
+
+@mkdir installer\etc\conda\activate.d
+@copy scripts\post_activate.bat installer\etc\conda\activate.d\
+
+@echo "Creating a distributable package.."
+
+@call conda install -c conda-forge -y conda-pack
+@call conda pack --n-threads -1 --prefix installer --format tar
+
+@cd dist\stable-diffusion-ui
+@mkdir installer
+
+@call tar -xf ..\..\installer.tar -C installer
+
+@mkdir scripts
+
+@copy ..\..\scripts\on_env_start.bat scripts\
+@copy "..\..\scripts\Start Stable Diffusion UI.cmd" .
+@copy ..\..\LICENSE .
+@copy "..\..\CreativeML Open RAIL-M License" .
+@copy "..\..\How to install and run.txt" .
+
+@echo "Build ready. Zip the 'dist\stable-diffusion-ui' folder."
+
+@echo "Cleaning up.."
+
+@cd ..\..
+
+@rmdir /s /q installer
+
+@del installer.tar

build.sh

@@ -0,0 +1,52 @@
+#!/bin/bash
+
+printf "Hi there, what you are running is meant for the developers of this project, not for users.\n\n"
+printf "If you only want to use the Stable Diffusion UI, you've downloaded the wrong file.\n"
+printf "Please download and follow the instructions at https://github.com/cmdr2/stable-diffusion-ui#installation\n\n"
+printf "If you are actually a developer of this project, please type Y and press enter\n\n"
+
+read -p "Are you a developer of this project (Y/N) " yn
+case $yn in
+    [Yy]* ) ;;
+    * ) exit;;
+esac
+
+mkdir -p dist/stable-diffusion-ui
+
+echo "Downloading components for the installer.."
+
+source ~/miniconda3/etc/profile.d/conda.sh
+
+conda install -c conda-forge -y conda-pack
+
+conda env create --prefix installer -f environment.yaml
+conda activate ./installer
+
+echo "Creating a distributable package.."
+
+conda pack --n-threads -1 --prefix installer --format tar
+
+cd dist/stable-diffusion-ui
+mkdir installer
+
+tar -xf ../../installer.tar -C installer
+
+mkdir scripts
+
+cp ../../scripts/on_env_start.sh scripts/
+cp ../../scripts/start.sh .
+cp ../../LICENSE .
+cp "../../CreativeML Open RAIL-M License" .
+cp "../../How to install and run.txt" .
+
+chmod u+x start.sh
+
+echo "Build ready. Zip the 'dist/stable-diffusion-ui' folder."
+
+echo "Cleaning up.."
+
+cd ../..
+
+rm -rf installer
+
+rm installer.tar

docker-compose.yml

@@ -1,28 +0,0 @@
-version: '3.3'
-
-services:
-  stability-ai:
-    container_name: sd
-    ports:
-      - '5000:5000'
-    image: 'r8.im/stability-ai/stable-diffusion@sha256:3080f37ef32771c9984d65033cbe71caa96c69680008bae64cf691724a6df04c'
-    deploy:
-      resources:
-        reservations:
-          devices:
-            - capabilities: [gpu]
-
-  stable-diffusion-ui:
-    container_name: sd-ui
-    ports:
-      - '8000:8000'
-    build:
-      context: .
-      dockerfile: Dockerfile
-    volumes:
-      - .:/app
-    depends_on:
-      - stability-ai
-
-networks:
-  default:

environment.yaml

@@ -0,0 +1,7 @@
+name: stable-diffusion-ui-installer
+channels:
+  - defaults
+  - conda-forge
+dependencies:
+  - conda
+  - git

index.html

@@ -1,471 +0,0 @@
-<!DOCTYPE html>
-<html>
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <style>
-    body {
-        font-family: Arial, Helvetica, sans-serif;
-        font-size: 11pt;
-    }
-    a {
-        color: rgb(0, 102, 204);
-    }
-    a:visited {
-        color: rgb(0, 102, 204);
-    }
-    @media (prefers-color-scheme: dark) {
-        body {
-            background-color: rgb(32, 33, 36);
-            color: #eee;
-        }
-    }
-    label {
-        font-size: 10pt;
-    }
-    #prompt {
-        width: 50vw;
-        height: 50pt;
-    }
-    @media screen and (max-width: 600px) {
-        #prompt {
-            width: 95%;
-        }
-    }
-    .image_preview_container {
-        display: none;
-    }
-    .image_clear_btn {
-        position: absolute;
-        transform: translateX(-50%);
-        background: black;
-        color: white;
-        border: 2pt solid #ccc;
-        padding: 0;
-        cursor: pointer;
-        outline: inherit;
-        border-radius: 8pt;
-        width: 16pt;
-        height: 16pt;
-        font-size: 10pt;
-    }
-    #configHeader {
-        margin-top: 5px;
-        margin-bottom: 5px;
-        font-size: 10pt;
-    }
-    #config {
-        font-size: 9pt;
-        margin-bottom: 5px;
-        padding-left: 10px;
-    }
-    #outputMsg {
-        font-size: small;
-    }
-    #footer {
-        border-top: 1px solid #999;
-        margin-top: 10px;
-        padding-top: 10px;
-        font-size: small;
-    }
-    .imgUseBtn {
-        position: absolute;
-        transform: translateX(-100%);
-        margin-top: 5pt;
-        margin-left: -5pt;
-    }
-    .imgItem {
-        display: inline;
-        padding-right: 10px;
-    }
-    </style>
-</html>
-<body>
-    <div id="status">Server status: <span id="serverStatus">checking..</span> | Request status: <span id="reqStatus">n/a</span></div>
-
-    <br/>
-
-    <b>Prompt:</b><br/>
-    <textarea id="prompt">a photograph of an astronaut riding a horse</textarea><br/>
-
-    <label for="init_image"><b>Initial Image:</b> (optional) </label> <input id="init_image" name="init_image" type="file" /> </button><br/>
-    <div id="init_image_preview_container" class="image_preview_container">
-        <img id="init_image_preview" src="" width="100" height="100" />
-        <button id="init_image_clear" class="image_clear_btn">X</button>
-    </div><br/>
-
-    <div id="mask_setting">
-        <label for="mask"><b>Image Mask:</b> (optional) </label> <input id="mask" name="mask" type="file" /> </button><br/>
-        <div id="mask_preview_container" class="image_preview_container">
-            <img id="mask_preview" src="" width="100" height="100" />
-            <button id="mask_clear" class="image_clear_btn">X</button>
-        </div>
-    </div>
-
-    <div id="configHeader"><b>Advanced settings:</b> [<a id="configToggleBtn" href="#">show</a>]</div>
-    <div id="config">
-        <label for="seed">Seed:</label> <input id="seed" name="seed" value="30000"> <input id="random_seed" name="random_seed" type="checkbox" checked> <label for="random_seed">Random Image</label> <br/>
-        <label for="num_outputs">Number of outputs:</label> <select id="num_outputs" name="num_outputs" value="1"><option value="1" selected>1</option><option value="4">4</option></select><br/>
-        <label for="width">Width:</label> <select id="width" name="width" value="512"><option value="128">128</option><option value="256">256</option><option value="512" selected>512</option><option value="768">768</option><option value="1024">1024</option></select><br/>
-        <label for="height">Height:</label> <select id="height" name="height" value="512"><option value="128">128</option><option value="256">256</option><option value="512" selected>512</option><option value="768">768</option></select><br/>
-        <label for="num_inference_steps">Number of inference steps:</label> <input id="num_inference_steps" name="num_inference_steps" value="50"><br/>
-        <label for="guidance_scale">Guidance Scale:</label> <input id="guidance_scale" name="guidance_scale" value="75" type="range" min="10" max="200"> <span id="guidance_scale_value"></span><br/>
-        <span id="prompt_strength_container"><label for="prompt_strength">Prompt Strength:</label> <input id="prompt_strength" name="prompt_strength" value="8" type="range" min="0" max="10"> <span id="prompt_strength_value"></span><br/></span><br/>
-        <input id="sound_toggle" name="sound_toggle" type="checkbox" checked> <label for="sound_toggle">Play sound on task completion</label><br/>
-    </div>
-
-    <button id="makeImage">Make Image</button> <br/><br/>
-
-    <div id="outputMsg"></div>
-
-    <div id="images"></div>
-
-    <div id="footer">
-        <p>Please feel free to <a href="https://github.com/cmdr2/stable-diffusion-ui/issues" target="_blank">file an issue</a> if you have any problems or suggestions in using this interface.</p>
-        <p><b>Disclaimer:</b> The authors of this project are not responsible for any content generated using this interface.</p>
-        <p>This license of this software forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, <br/>spread misinformation and target vulnerable groups. For the full list of restrictions please read <a href="https://github.com/cmdr2/stable-diffusion-ui/blob/main/LICENSE" target="_blank">the license</a>.</p>
-        <p>By using this software, you consent to the terms and conditions of the license.</p>
-    </div>
-</body>
-
-<script>
-const SOUND_ENABLED_KEY = "soundEnabled"
-const HEALTH_PING_INTERVAL = 5 // seconds
-
-let promptField = document.querySelector('#prompt')
-let numOutputsField = document.querySelector('#num_outputs')
-let numInferenceStepsField = document.querySelector('#num_inference_steps')
-let guidanceScaleField = document.querySelector('#guidance_scale')
-let guidanceScaleValueLabel = document.querySelector('#guidance_scale_value')
-let randomSeedField = document.querySelector("#random_seed")
-let seedField = document.querySelector('#seed')
-let widthField = document.querySelector('#width')
-let heightField = document.querySelector('#height')
-let initImageSelector = document.querySelector("#init_image")
-let initImagePreview = document.querySelector("#init_image_preview")
-let maskImageSelector = document.querySelector("#mask")
-let maskImagePreview = document.querySelector("#mask_preview")
-let promptStrengthField = document.querySelector('#prompt_strength')
-let promptStrengthValueLabel = document.querySelector('#prompt_strength_value')
-
-let makeImageBtn = document.querySelector('#makeImage')
-
-let imagesContainer = document.querySelector('#images')
-let initImagePreviewContainer = document.querySelector('#init_image_preview_container')
-let initImageClearBtn = document.querySelector('#init_image_clear')
-let promptStrengthContainer = document.querySelector('#prompt_strength_container')
-
-let maskSetting = document.querySelector('#mask_setting')
-let maskImagePreviewContainer = document.querySelector('#mask_preview_container')
-let maskImageClearBtn = document.querySelector('#mask_clear')
-
-let showConfigToggle = document.querySelector('#configToggleBtn')
-let configBox = document.querySelector('#config')
-let outputMsg = document.querySelector('#outputMsg')
-
-let soundToggle = document.querySelector('#sound_toggle')
-
-let serverStatus = 'offline'
-
-function isSoundEnabled() {
-    if (localStorage.getItem(SOUND_ENABLED_KEY) === 'false') {
-        return false
-    }
-    return true
-}
-
-function setStatus(statusType, msg, msgType) {
-    let el = ''
-
-    if (statusType === 'server') {
-        el = '#serverStatus'
-        serverStatus = msg
-    } else if (statusType === 'request') {
-        el = '#reqStatus'
-    }
-
-    if (msgType == 'error') {
-        msg = '<span style="color: red">' + msg + '<span>'
-    } else if (msgType == 'success') {
-        msg = '<span style="color: green">' + msg + '<span>'
-    }
-
-    if (el) {
-        document.querySelector(el).innerHTML = msg
-    }
-}
-
-function playSound() {
-    const audio = new Audio('/media/ding.mp3')
-    audio.volume = 0.2
-    audio.play()
-}
-
-async function healthCheck() {
-    try {
-        let res = await fetch('/ping')
-        res = await res.json()
-
-        if (res[0] == 'OK') {
-            setStatus('server', 'online', 'success')
-        } else {
-            setStatus('server', 'offline', 'error')
-        }
-    } catch (e) {
-        setStatus('server', 'offline', 'error')
-    }
-}
-
-async function makeImage() {
-    setStatus('request', 'fetching..')
-
-    makeImageBtn.innerHTML = 'Processing..'
-    makeImageBtn.disabled = true
-
-    outputMsg.innerHTML = 'Fetching..'
-
-    function logError(msg, res) {
-        outputMsg.innerHTML = '<span style="color: red">Error: ' + msg + '</span>'
-        console.log('request error', res)
-        setStatus('request', 'error', 'error')
-    }
-
-    let seed = (randomSeedField.checked ? Math.floor(Math.random() * 10000) : seedField.value)
-
-    let reqBody = {
-        prompt: promptField.value,
-        num_outputs: numOutputsField.value,
-        num_inference_steps: numInferenceStepsField.value,
-        guidance_scale: guidanceScaleField.value / 10,
-        width: widthField.value,
-        height: heightField.value,
-        seed: seed,
-    }
-
-    if (initImagePreview.src.indexOf('data:image/png;base64') !== -1) {
-        reqBody['init_image'] = initImagePreview.src
-        reqBody['prompt_strength'] = promptStrengthField.value / 10
-
-        if (maskImagePreview.src.indexOf('data:image/png;base64') !== -1) {
-            reqBody['mask'] = maskImagePreview.src
-        }
-    }
-
-    let res = ''
-    let time = new Date().getTime()
-
-    try {
-        res = await fetch('/image', {
-            method: 'POST',
-            headers: {
-                'Content-Type': 'application/json'
-            },
-            body: JSON.stringify(reqBody)
-        })
-
-        if (res.status != 200) {
-            if (serverStatus === 'online') {
-                logError('Stable Diffusion had an error: ' + await res.text() + '. This happens sometimes. Maybe modify the prompt or seed a little bit?', res)
-            } else {
-                logError("Stable Diffusion is still starting up, please wait. If this goes on beyond a few minutes, Stable Diffusion has probably crashed.", res)
-            }
-            res = undefined
-        } else {
-            res = await res.json()
-
-            if (res.status !== 'succeeded') {
-                let msg = ''
-                if (res.detail !== undefined) {
-                    msg = res.detail[0].msg + " in " + JSON.stringify(res.detail[0].loc)
-                } else {
-                    msg = res
-                }
-                logError(msg, res)
-                res = undefined
-            }
-        }
-    } catch (e) {
-        console.log('request error', e)
-        setStatus('request', 'error', 'error')
-    }
-
-    makeImageBtn.innerHTML = 'Make Image'
-    makeImageBtn.disabled = false
-
-    if (isSoundEnabled()) {
-        playSound()
-    }
-
-    if (!res) {
-        return
-    }
-
-    time = new Date().getTime() - time
-    time /= 1000
-
-    outputMsg.innerHTML = 'Processed in ' + time + ' seconds. Seed: ' + seed
-
-    imagesContainer.innerHTML = ''
-
-    for (let idx in res.output) {
-        let imgBody = ''
-
-        try {
-            imgBody = res.output[idx]
-        } catch (e) {
-            console.log(imgBody)
-            setStatus('request', 'invalid image', 'error')
-            return
-        }
-
-        let imgItem = document.createElement('div')
-        imgItem.className = 'imgItem'
-
-        let img = document.createElement('img')
-        img.width = parseInt(reqBody.width)
-        img.height = parseInt(reqBody.height)
-        img.src = imgBody
-
-        let imgUseBtn = document.createElement('button')
-        imgUseBtn.className = 'imgUseBtn'
-        imgUseBtn.innerHTML = 'Use as Input'
-
-        imgItem.appendChild(img)
-        imgItem.appendChild(imgUseBtn)
-        imagesContainer.appendChild(imgItem)
-
-        imgUseBtn.addEventListener('click', function() {
-            initImageSelector.value = null
-            initImagePreview.src = imgBody
-
-            initImagePreviewContainer.style.display = 'block'
-            promptStrengthContainer.style.display = 'block'
-
-            maskSetting.style.display = 'block'
-
-            randomSeedField.checked = false
-            seedField.value = seed
-            seedField.disabled = false
-        })
-    }
-
-    setStatus('request', 'done', 'success')
-
-    if (randomSeedField.checked) {
-        seedField.value = seed
-    }
-}
-
-function handleAudioEnabledChange(e) {
-    localStorage.setItem(SOUND_ENABLED_KEY, e.target.checked.toString())
-}
-
-soundToggle.addEventListener('click', handleAudioEnabledChange)
-soundToggle.checked = isSoundEnabled();
-
-makeImageBtn.addEventListener('click', makeImage)
-
-configBox.style.display = 'none'
-
-showConfigToggle.addEventListener('click', function() {
-    configBox.style.display = (configBox.style.display === 'none' ? 'block' : 'none')
-    showConfigToggle.innerHTML = (configBox.style.display === 'none' ? 'show' : 'hide')
-    return false
-})
-
-function updateGuidanceScale() {
-    guidanceScaleValueLabel.innerHTML = guidanceScaleField.value / 10
-}
-
-guidanceScaleField.addEventListener('input', updateGuidanceScale)
-updateGuidanceScale()
-
-function updatePromptStrength() {
-    promptStrengthValueLabel.innerHTML = promptStrengthField.value / 10
-}
-
-promptStrengthField.addEventListener('input', updatePromptStrength)
-updatePromptStrength()
-
-function checkRandomSeed() {
-    if (randomSeedField.checked) {
-        seedField.disabled = true
-        seedField.value = "random"
-    } else {
-        seedField.disabled = false
-    }
-}
-randomSeedField.addEventListener('input', checkRandomSeed)
-checkRandomSeed()
-
-function showInitImagePreview() {
-    if (initImageSelector.files.length === 0) {
-        initImagePreviewContainer.style.display = 'none'
-        promptStrengthContainer.style.display = 'none'
-        maskSetting.style.display = 'none'
-        return
-    }
-
-    let reader = new FileReader()
-    let file = initImageSelector.files[0]
-
-    reader.addEventListener('load', function() {
-        // console.log(file.name, reader.result)
-        initImagePreview.src = reader.result
-        initImagePreviewContainer.style.display = 'block'
-        promptStrengthContainer.style.display = 'block'
-
-        maskSetting.style.display = 'block'
-    })
-
-    if (file) {
-        reader.readAsDataURL(file)
-    }
-}
-initImageSelector.addEventListener('change', showInitImagePreview)
-showInitImagePreview()
-
-initImageClearBtn.addEventListener('click', function() {
-    initImageSelector.value = null
-    maskImageSelector.value = null
-
-    initImagePreview.src = ''
-    maskImagePreview.src = ''
-
-    initImagePreviewContainer.style.display = 'none'
-    maskImagePreviewContainer.style.display = 'none'
-
-    maskSetting.style.display = 'none'
-
-    promptStrengthContainer.style.display = 'none'
-})
-
-function showMaskImagePreview() {
-    if (maskImageSelector.files.length === 0) {
-        maskImagePreviewContainer.style.display = 'none'
-        return
-    }
-
-    let reader = new FileReader()
-    let file = maskImageSelector.files[0]
-
-    reader.addEventListener('load', function() {
-        maskImagePreview.src = reader.result
-        maskImagePreviewContainer.style.display = 'block'
-    })
-
-    if (file) {
-        reader.readAsDataURL(file)
-    }
-}
-maskImageSelector.addEventListener('change', showMaskImagePreview)
-showMaskImagePreview()
-
-maskImageClearBtn.addEventListener('click', function() {
-    maskImageSelector.value = null
-    maskImagePreview.src = ''
-    maskImagePreviewContainer.style.display = 'none'
-})
-
-setInterval(healthCheck, HEALTH_PING_INTERVAL * 1000)
-</script>
-
-</html>

main.py

@@ -1,69 +0,0 @@
-from fastapi import FastAPI, HTTPException
-from starlette.responses import FileResponse
-from pydantic import BaseModel
-
-import requests
-
-LOCAL_SERVER_URL = 'http://stability-ai:5000'
-PREDICT_URL = LOCAL_SERVER_URL + '/predictions'
-
-app = FastAPI()
-
-# defaults from https://huggingface.co/blog/stable_diffusion
-class ImageRequest(BaseModel):
-    prompt: str
-    init_image: str = None # base64
-    mask: str = None # base64
-    num_outputs: str = "1"
-    num_inference_steps: str = "50"
-    guidance_scale: str = "7.5"
-    width: str = "512"
-    height: str = "512"
-    seed: str = "30000"
-    prompt_strength: str = "0.8"
-
-@app.get('/')
-def read_root():
-    return FileResponse('index.html')
-
-@app.get('/ping')
-async def ping():
-    try:
-        requests.get(LOCAL_SERVER_URL)
-        return {'OK'}
-    except:
-        return {'ERROR'}
-
-@app.post('/image')
-async def image(req : ImageRequest):
-    data = {
-        "input": {
-            "prompt": req.prompt,
-            "num_outputs": req.num_outputs,
-            "num_inference_steps": req.num_inference_steps,
-            "width": req.width,
-            "height": req.height,
-            "seed": req.seed,
-            "guidance_scale": req.guidance_scale,
-        }
-    }
-
-    if req.init_image is not None:
-        data['input']['init_image'] = req.init_image
-        data['input']['prompt_strength'] = req.prompt_strength
-
-        if req.mask is not None:
-            data['input']['mask'] = req.mask
-
-    if req.seed == "-1":
-        del data['input']['seed']
-
-    res = requests.post(PREDICT_URL, json=data)
-    if res.status_code != 200:
-        raise HTTPException(status_code=500, detail=res.text)
-
-    return res.json()
-
-@app.get('/media/ding.mp3')
-def read_root():
-    return FileResponse('media/ding.mp3')

requirements.txt

@@ -1,3 +0,0 @@
-requests
-fastapi==0.80.0
-uvicorn==0.18.2

scripts/Start Stable Diffusion UI.cmd

@@ -0,0 +1 @@
+installer\Scripts\activate.bat

scripts/on_env_start.bat

@@ -0,0 +1,61 @@
+@echo off
+
+@echo. & echo "Stable Diffusion UI - v2" & echo.
+
+set PATH=C:\Windows\System32;%PATH%
+
+@cd ..
+
+if exist "scripts\config.bat" (
+    @call scripts\config.bat
+)
+
+if "%update_branch%"=="" (
+    set update_branch=main
+)
+
+@>nul grep -c "conda_sd_ui_deps_installed" scripts\install_status.txt
+@if "%ERRORLEVEL%" NEQ "0" (
+    for /f "tokens=*" %%a in ('python -c "import os; parts = os.getcwd().split(os.path.sep); print(len(parts))"') do if "%%a" NEQ "2" (
+        echo. & echo "!!!! WARNING !!!!" & echo.
+        echo "Your 'stable-diffusion-ui' folder is at %cd%" & echo.
+        echo "The 'stable-diffusion-ui' folder needs to be at the top of your drive, for e.g. 'C:\stable-diffusion-ui' or 'D:\stable-diffusion-ui' etc."
+        echo "Not placing this folder at the top of a drive can cause errors on some computers."
+        echo. & echo "Recommended: Please close this window and move the 'stable-diffusion-ui' folder to the top of a drive. For e.g. 'C:\stable-diffusion-ui'. Then run the installer again." & echo.
+        echo "Not Recommended: If you're sure that you want to install at the current location, please press any key to continue." & echo.
+
+        pause
+    )
+)
+
+@>nul grep -c "sd_ui_git_cloned" scripts\install_status.txt
+@if "%ERRORLEVEL%" EQU "0" (
+    @echo "Stable Diffusion UI's git repository was already installed. Updating from %update_branch%.."
+
+    @cd sd-ui-files
+
+    @call git reset --hard
+    @call git checkout "%update_branch%"
+    @call git pull
+
+    @cd ..
+) else (
+    @echo. & echo "Downloading Stable Diffusion UI.." & echo.
+    @echo "Using the %update_branch% channel" & echo.
+
+    @call git clone -b "%update_branch%" https://github.com/cmdr2/stable-diffusion-ui.git sd-ui-files && (
+        @echo sd_ui_git_cloned >> scripts\install_status.txt
+    ) || (
+        @echo "Error downloading Stable Diffusion UI. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
+        pause
+        @exit /b
+    )
+)
+
+@xcopy sd-ui-files\ui ui /s /i /Y
+@copy sd-ui-files\scripts\on_sd_start.bat scripts\ /Y
+@copy "sd-ui-files\scripts\Start Stable Diffusion UI.cmd" . /Y
+
+@call scripts\on_sd_start.bat
+
+@pause

scripts/on_env_start.sh

@@ -0,0 +1,43 @@
+#!/bin/bash
+
+printf "\n\nStable Diffusion UI\n\n"
+
+if [ -f "scripts/config.sh" ]; then
+    source scripts/config.sh
+fi
+
+if [ "$update_branch" == "" ]; then
+    export update_branch="main"
+fi
+
+if [ -f "scripts/install_status.txt" ] && [ `grep -c sd_ui_git_cloned scripts/install_status.txt` -gt "0" ]; then
+    echo "Stable Diffusion UI's git repository was already installed. Updating from $update_branch.."
+
+    cd sd-ui-files
+
+    git reset --hard
+    git checkout "$update_branch"
+    git pull
+
+    cd ..
+else
+    printf "\n\nDownloading Stable Diffusion UI..\n\n"
+    printf "Using the $update_branch channel\n\n"
+
+    if git clone -b "$update_branch" https://github.com/cmdr2/stable-diffusion-ui.git sd-ui-files ; then
+        echo sd_ui_git_cloned >> scripts/install_status.txt
+    else
+        printf "\n\nError downloading Stable Diffusion UI. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+fi
+
+rm -rf ui
+cp -Rf sd-ui-files/ui .
+cp sd-ui-files/scripts/on_sd_start.sh scripts/
+cp sd-ui-files/scripts/start.sh .
+
+./scripts/on_sd_start.sh
+
+read -p "Press any key to continue"

scripts/on_sd_start.bat

@@ -0,0 +1,317 @@
+@echo off
+
+@copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y
+
+@REM Caution, this file will make your eyes and brain bleed. It's such an unholy mess.
+@REM Note to self: Please rewrite this in Python. For the sake of your own sanity.
+
+@call python -c "import os; import shutil; frm = 'sd-ui-files\\ui\\hotfix\\9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'; dst = os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'transformers', '9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'); shutil.copyfile(frm, dst) if os.path.exists(dst) else print(''); print('Hotfixed broken JSON file from OpenAI');"
+
+@>nul grep -c "sd_git_cloned" scripts\install_status.txt
+@if "%ERRORLEVEL%" EQU "0" (
+    @echo "Stable Diffusion's git repository was already installed. Updating.."
+
+    @cd stable-diffusion
+
+    @call git reset --hard
+    @call git pull
+    @call git checkout f6cfebffa752ee11a7b07497b8529d5971de916c
+
+    @call git apply ..\ui\sd_internal\ddim_callback.patch
+    @call git apply ..\ui\sd_internal\env_yaml.patch
+
+    @cd ..
+) else (
+    @echo. & echo "Downloading Stable Diffusion.." & echo.
+
+    @call git clone https://github.com/basujindal/stable-diffusion.git && (
+        @echo sd_git_cloned >> scripts\install_status.txt
+    ) || (
+        @echo "Error downloading Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
+        pause
+        @exit /b
+    )
+
+    @cd stable-diffusion
+    @call git checkout f6cfebffa752ee11a7b07497b8529d5971de916c
+
+    @call git apply ..\ui\sd_internal\ddim_callback.patch
+    @call git apply ..\ui\sd_internal\env_yaml.patch
+
+    @cd ..
+)
+
+@cd stable-diffusion
+
+@>nul grep -c "conda_sd_env_created" ..\scripts\install_status.txt
+@if "%ERRORLEVEL%" EQU "0" (
+    @echo "Packages necessary for Stable Diffusion were already installed"
+
+    @call conda activate .\env
+) else (
+    @echo. & echo "Downloading packages necessary for Stable Diffusion.." & echo. & echo "***** This will take some time (depending on the speed of the Internet connection) and may appear to be stuck, but please be patient ***** .." & echo.
+
+    @rmdir /s /q .\env
+
+    @REM prevent conda from using packages from the user's home directory, to avoid conflicts
+    @set PYTHONNOUSERSITE=1
+
+    @call conda env create --prefix env -f environment.yaml || (
+        @echo. & echo "Error installing the packages necessary for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+
+    @call conda activate .\env
+
+    @call conda install -c conda-forge -y --prefix env antlr4-python3-runtime=4.8 || (
+        @echo. & echo "Error installing antlr4-python3-runtime for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+
+    for /f "tokens=*" %%a in ('python -c "import torch; import ldm; import transformers; import numpy; import antlr4; print(42)"') do if "%%a" NEQ "42" (
+        @echo. & echo "Dependency test failed! Error installing the packages necessary for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+
+    @echo conda_sd_env_created >> ..\scripts\install_status.txt
+)
+
+set PATH=C:\Windows\System32;%PATH%
+
+@>nul grep -c "conda_sd_gfpgan_deps_installed" ..\scripts\install_status.txt
+@if "%ERRORLEVEL%" EQU "0" (
+    @echo "Packages necessary for GFPGAN (Face Correction) were already installed"
+) else (
+    @echo. & echo "Downloading packages necessary for GFPGAN (Face Correction).." & echo.
+
+    @set PYTHONNOUSERSITE=1
+
+    @call pip install -e git+https://github.com/TencentARC/GFPGAN#egg=GFPGAN || (
+        @echo. & echo "Error installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+
+    @call pip install basicsr==1.4.2 || (
+        @echo. & echo "Error installing the basicsr package necessary for GFPGAN (Face Correction). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+
+    for /f "tokens=*" %%a in ('python -c "from gfpgan import GFPGANer; print(42)"') do if "%%a" NEQ "42" (
+        @echo. & echo "Dependency test failed! Error installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+
+    @echo conda_sd_gfpgan_deps_installed >> ..\scripts\install_status.txt
+)
+
+@>nul grep -c "conda_sd_esrgan_deps_installed" ..\scripts\install_status.txt
+@if "%ERRORLEVEL%" EQU "0" (
+    @echo "Packages necessary for ESRGAN (Resolution Upscaling) were already installed"
+) else (
+    @echo. & echo "Downloading packages necessary for ESRGAN (Resolution Upscaling).." & echo.
+
+    @set PYTHONNOUSERSITE=1
+
+    @call pip install -e git+https://github.com/xinntao/Real-ESRGAN#egg=realesrgan || (
+        @echo. & echo "Error installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+
+    for /f "tokens=*" %%a in ('python -c "from basicsr.archs.rrdbnet_arch import RRDBNet; from realesrgan import RealESRGANer; print(42)"') do if "%%a" NEQ "42" (
+        @echo. & echo "Dependency test failed! Error installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+
+    @echo conda_sd_esrgan_deps_installed >> ..\scripts\install_status.txt
+)
+
+@>nul grep -c "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
+@if "%ERRORLEVEL%" EQU "0" (
+    echo "Packages necessary for Stable Diffusion UI were already installed"
+) else (
+    @echo. & echo "Downloading packages necessary for Stable Diffusion UI.." & echo.
+
+    @set PYTHONNOUSERSITE=1
+
+    @call conda install -c conda-forge -y --prefix env uvicorn fastapi || (
+        echo "Error installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
+        pause
+        exit /b
+    )
+)
+
+call WHERE uvicorn > .tmp
+@>nul grep -c "uvicorn" .tmp
+@if "%ERRORLEVEL%" NEQ "0" (
+    @echo. & echo "UI packages not found! Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+    pause
+    exit /b
+)
+
+@>nul grep -c "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
+@if "%ERRORLEVEL%" NEQ "0" (
+    @echo conda_sd_ui_deps_installed >> ..\scripts\install_status.txt
+)
+
+
+
+@if exist "sd-v1-4.ckpt" (
+    for %%I in ("sd-v1-4.ckpt") do if "%%~zI" EQU "4265380512" (
+        echo "Data files (weights) necessary for Stable Diffusion were already downloaded"
+    ) else (
+        for %%J in ("sd-v1-4.ckpt") do if "%%~zJ" EQU "7703807346" (
+            echo "Data files (weights) necessary for Stable Diffusion were already downloaded"
+        ) else (
+            for %%K in ("sd-v1-4.ckpt") do if "%%~zK" EQU "7703810927" (
+                echo "Data files (weights) necessary for Stable Diffusion were already downloaded"
+            ) else (
+                echo. & echo "The model file present at %cd%\sd-v1-4.ckpt is invalid. It is only %%~zK bytes in size. Re-downloading.." & echo.
+                del "sd-v1-4.ckpt"
+            )
+        )
+    )
+)
+
+@if not exist "sd-v1-4.ckpt" (
+    @echo. & echo "Downloading data files (weights) for Stable Diffusion.." & echo.
+
+    @call curl -L -k https://me.cmdr2.org/stable-diffusion-ui/sd-v1-4.ckpt > sd-v1-4.ckpt
+
+    @if exist "sd-v1-4.ckpt" (
+        for %%I in ("sd-v1-4.ckpt") do if "%%~zI" NEQ "4265380512" (
+            echo. & echo "Error: The downloaded model file was invalid! Bytes downloaded: %%~zI" & echo.
+            echo. & echo "Error downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+            pause
+            exit /b
+        )
+    ) else (
+        @echo. & echo "Error downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+)
+
+
+
+@if exist "GFPGANv1.3.pth" (
+    for %%I in ("GFPGANv1.3.pth") do if "%%~zI" EQU "348632874" (
+        echo "Data files (weights) necessary for GFPGAN (Face Correction) were already downloaded"
+    ) else (
+        echo. & echo "The GFPGAN model file present at %cd%\GFPGANv1.3.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
+        del "GFPGANv1.3.pth"
+    )
+)
+
+@if not exist "GFPGANv1.3.pth" (
+    @echo. & echo "Downloading data files (weights) for GFPGAN (Face Correction).." & echo.
+
+    @call curl -L -k https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth > GFPGANv1.3.pth
+
+    @if exist "GFPGANv1.3.pth" (
+        for %%I in ("GFPGANv1.3.pth") do if "%%~zI" NEQ "348632874" (
+            echo. & echo "Error: The downloaded GFPGAN model file was invalid! Bytes downloaded: %%~zI" & echo.
+            echo. & echo "Error downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+            pause
+            exit /b
+        )
+    ) else (
+        @echo. & echo "Error downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+)
+
+
+
+@if exist "RealESRGAN_x4plus.pth" (
+    for %%I in ("RealESRGAN_x4plus.pth") do if "%%~zI" EQU "67040989" (
+        echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus were already downloaded"
+    ) else (
+        echo. & echo "The GFPGAN model file present at %cd%\RealESRGAN_x4plus.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
+        del "RealESRGAN_x4plus.pth"
+    )
+)
+
+@if not exist "RealESRGAN_x4plus.pth" (
+    @echo. & echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.." & echo.
+
+    @call curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth > RealESRGAN_x4plus.pth
+
+    @if exist "RealESRGAN_x4plus.pth" (
+        for %%I in ("RealESRGAN_x4plus.pth") do if "%%~zI" NEQ "67040989" (
+            echo. & echo "Error: The downloaded ESRGAN x4plus model file was invalid! Bytes downloaded: %%~zI" & echo.
+            echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+            pause
+            exit /b
+        )
+    ) else (
+        @echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+)
+
+
+
+@if exist "RealESRGAN_x4plus_anime_6B.pth" (
+    for %%I in ("RealESRGAN_x4plus_anime_6B.pth") do if "%%~zI" EQU "17938799" (
+        echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus_anime were already downloaded"
+    ) else (
+        echo. & echo "The GFPGAN model file present at %cd%\RealESRGAN_x4plus_anime_6B.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
+        del "RealESRGAN_x4plus_anime_6B.pth"
+    )
+)
+
+@if not exist "RealESRGAN_x4plus_anime_6B.pth" (
+    @echo. & echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.." & echo.
+
+    @call curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth > RealESRGAN_x4plus_anime_6B.pth
+
+    @if exist "RealESRGAN_x4plus_anime_6B.pth" (
+        for %%I in ("RealESRGAN_x4plus_anime_6B.pth") do if "%%~zI" NEQ "17938799" (
+            echo. & echo "Error: The downloaded ESRGAN x4plus_anime model file was invalid! Bytes downloaded: %%~zI" & echo.
+            echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+            pause
+            exit /b
+        )
+    ) else (
+        @echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+        pause
+        exit /b
+    )
+)
+
+
+
+@>nul grep -c "sd_install_complete" ..\scripts\install_status.txt
+@if "%ERRORLEVEL%" NEQ "0" (
+    @echo sd_weights_downloaded >> ..\scripts\install_status.txt
+    @echo sd_install_complete >> ..\scripts\install_status.txt
+)
+
+@echo. & echo "Stable Diffusion is ready!" & echo.
+
+@set SD_DIR=%cd%
+
+@cd env\lib\site-packages
+@set PYTHONPATH=%SD_DIR%;%cd%
+@cd ..\..\..
+@echo PYTHONPATH=%PYTHONPATH%
+
+@cd ..
+@set SD_UI_PATH=%cd%\ui
+@cd stable-diffusion
+
+@call python --version
+
+@uvicorn server:app --app-dir "%SD_UI_PATH%" --port 9000 --host 0.0.0.0
+
+@pause

scripts/on_sd_start.sh

@@ -0,0 +1,309 @@
+#!/bin/bash
+
+cp sd-ui-files/scripts/on_env_start.sh scripts/
+
+source installer/etc/profile.d/conda.sh
+
+python -c "import os; import shutil; frm = 'sd-ui-files/ui/hotfix/9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'; dst = os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'transformers', '9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'); shutil.copyfile(frm, dst) if os.path.exists(dst) else print(''); print('Hotfixed broken JSON file from OpenAI');"
+
+# Caution, this file will make your eyes and brain bleed. It's such an unholy mess.
+# Note to self: Please rewrite this in Python. For the sake of your own sanity.
+
+if [ -e "scripts/install_status.txt" ] && [ `grep -c sd_git_cloned scripts/install_status.txt` -gt "0" ]; then
+    echo "Stable Diffusion's git repository was already installed. Updating.."
+
+    cd stable-diffusion
+
+    git reset --hard
+    git pull
+    git checkout f6cfebffa752ee11a7b07497b8529d5971de916c
+
+    git apply ../ui/sd_internal/ddim_callback.patch
+    git apply ../ui/sd_internal/env_yaml.patch
+
+    cd ..
+else
+    printf "\n\nDownloading Stable Diffusion..\n\n"
+
+    if git clone https://github.com/basujindal/stable-diffusion.git ; then
+        echo sd_git_cloned >> scripts/install_status.txt
+    else
+        printf "\n\nError downloading Stable Diffusion. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+
+    cd stable-diffusion
+    git checkout f6cfebffa752ee11a7b07497b8529d5971de916c
+
+    git apply ../ui/sd_internal/ddim_callback.patch
+    git apply ../ui/sd_internal/env_yaml.patch
+
+    cd ..
+fi
+
+cd stable-diffusion
+
+if [ `grep -c conda_sd_env_created ../scripts/install_status.txt` -gt "0" ]; then
+    echo "Packages necessary for Stable Diffusion were already installed"
+
+    conda activate ./env
+else
+    printf "\n\nDownloading packages necessary for Stable Diffusion..\n"
+    printf "\n\n***** This will take some time (depending on the speed of the Internet connection) and may appear to be stuck, but please be patient ***** ..\n\n"
+
+    # prevent conda from using packages from the user's home directory, to avoid conflicts
+    export PYTHONNOUSERSITE=1
+
+    if conda env create --prefix env --force -f environment.yaml ; then
+        echo "Installed. Testing.."
+    else
+        printf "\n\nError installing the packages necessary for Stable Diffusion. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+
+    conda activate ./env
+
+    if conda install -c conda-forge --prefix ./env -y antlr4-python3-runtime=4.8 ; then
+        echo "Installed. Testing.."
+    else
+        printf "\n\nError installing antlr4-python3-runtime for Stable Diffusion. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+
+    out_test=`python -c "import torch; import ldm; import transformers; import numpy; import antlr4; print(42)"`
+    if [ "$out_test" != "42" ]; then
+        printf "\n\nDependency test failed! Error installing the packages necessary for Stable Diffusion. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+
+    echo conda_sd_env_created >> ../scripts/install_status.txt
+fi
+
+if [ `grep -c conda_sd_gfpgan_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
+    echo "Packages necessary for GFPGAN (Face Correction) were already installed"
+else
+    printf "\n\nDownloading packages necessary for GFPGAN (Face Correction)..\n"
+
+    export PYTHONNOUSERSITE=1
+
+    if pip install -e git+https://github.com/TencentARC/GFPGAN#egg=GFPGAN ; then
+        echo "Installed. Testing.."
+    else
+        printf "\n\nError installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+
+    out_test=`python -c "from gfpgan import GFPGANer; print(42)"`
+    if [ "$out_test" != "42" ]; then
+        printf "\n\nDependency test failed! Error installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+
+    echo conda_sd_gfpgan_deps_installed >> ../scripts/install_status.txt
+fi
+
+if [ `grep -c conda_sd_esrgan_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
+    echo "Packages necessary for ESRGAN (Resolution Upscaling) were already installed"
+else
+    printf "\n\nDownloading packages necessary for ESRGAN (Resolution Upscaling)..\n"
+
+    export PYTHONNOUSERSITE=1
+
+    if pip install -e git+https://github.com/xinntao/Real-ESRGAN#egg=realesrgan ; then
+        echo "Installed. Testing.."
+    else
+        printf "\n\nError installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+
+    out_test=`python -c "from basicsr.archs.rrdbnet_arch import RRDBNet; from realesrgan import RealESRGANer; print(42)"`
+    if [ "$out_test" != "42" ]; then
+        printf "\n\nDependency test failed! Error installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+
+    echo conda_sd_esrgan_deps_installed >> ../scripts/install_status.txt
+fi
+
+if [ `grep -c conda_sd_ui_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
+    echo "Packages necessary for Stable Diffusion UI were already installed"
+else
+    printf "\n\nDownloading packages necessary for Stable Diffusion UI..\n\n"
+
+    export PYTHONNOUSERSITE=1
+
+    if conda install -c conda-forge --prefix ./env -y uvicorn fastapi ; then
+        echo "Installed. Testing.."
+    else
+        printf "\n\nError installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+
+    if ! command -v uvicorn &> /dev/null; then
+        printf "\n\nUI packages not found! Error installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+
+    echo conda_sd_ui_deps_installed >> ../scripts/install_status.txt
+fi
+
+
+
+if [ -f "sd-v1-4.ckpt" ]; then
+    model_size=`ls -l sd-v1-4.ckpt | awk '{print $5}'`
+
+    if [ "$model_size" -eq "4265380512" ] || [ "$model_size" -eq "7703807346" ] || [ "$model_size" -eq "7703810927" ]; then
+        echo "Data files (weights) necessary for Stable Diffusion were already downloaded"
+    else
+        printf "\n\nThe model file present at $PWD/sd-v1-4.ckpt is invalid. It is only $model_size bytes in size. Re-downloading.."
+        rm sd-v1-4.ckpt
+    fi
+fi
+
+if [ ! -f "sd-v1-4.ckpt" ]; then
+    echo "Downloading data files (weights) for Stable Diffusion.."
+
+    curl -L -k https://me.cmdr2.org/stable-diffusion-ui/sd-v1-4.ckpt > sd-v1-4.ckpt
+
+    if [ -f "sd-v1-4.ckpt" ]; then
+        model_size=`ls -l sd-v1-4.ckpt | awk '{print $5}'`
+        if [ ! "$model_size" == "4265380512" ]; then
+            printf "\n\nError: The downloaded model file was invalid! Bytes downloaded: $model_size\n\n"
+            printf "\n\nError downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+            read -p "Press any key to continue"
+            exit
+        fi
+    else
+        printf "\n\nError downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+fi
+
+
+if [ -f "GFPGANv1.3.pth" ]; then
+    model_size=`ls -l GFPGANv1.3.pth | awk '{print $5}'`
+
+    if [ "$model_size" -eq "348632874" ]; then
+        echo "Data files (weights) necessary for GFPGAN (Face Correction) were already downloaded"
+    else
+        printf "\n\nThe model file present at $PWD/GFPGANv1.3.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
+        rm GFPGANv1.3.pth
+    fi
+fi
+
+if [ ! -f "GFPGANv1.3.pth" ]; then
+    echo "Downloading data files (weights) for GFPGAN (Face Correction).."
+
+    curl -L -k https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth > GFPGANv1.3.pth
+
+    if [ -f "GFPGANv1.3.pth" ]; then
+        model_size=`ls -l GFPGANv1.3.pth | awk '{print $5}'`
+        if [ ! "$model_size" -eq "348632874" ]; then
+            printf "\n\nError: The downloaded GFPGAN model file was invalid! Bytes downloaded: $model_size\n\n"
+            printf "\n\nError downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+            read -p "Press any key to continue"
+            exit
+        fi
+    else
+        printf "\n\nError downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+fi
+
+
+if [ -f "RealESRGAN_x4plus.pth" ]; then
+    model_size=`ls -l RealESRGAN_x4plus.pth | awk '{print $5}'`
+
+    if [ "$model_size" -eq "67040989" ]; then
+        echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus were already downloaded"
+    else
+        printf "\n\nThe model file present at $PWD/RealESRGAN_x4plus.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
+        rm RealESRGAN_x4plus.pth
+    fi
+fi
+
+if [ ! -f "RealESRGAN_x4plus.pth" ]; then
+    echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.."
+
+    curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth > RealESRGAN_x4plus.pth
+
+    if [ -f "RealESRGAN_x4plus.pth" ]; then
+        model_size=`ls -l RealESRGAN_x4plus.pth | awk '{print $5}'`
+        if [ ! "$model_size" -eq "67040989" ]; then
+            printf "\n\nError: The downloaded ESRGAN x4plus model file was invalid! Bytes downloaded: $model_size\n\n"
+            printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+            read -p "Press any key to continue"
+            exit
+        fi
+    else
+        printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+fi
+
+
+if [ -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
+    model_size=`ls -l RealESRGAN_x4plus_anime_6B.pth | awk '{print $5}'`
+
+    if [ "$model_size" -eq "17938799" ]; then
+        echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus_anime were already downloaded"
+    else
+        printf "\n\nThe model file present at $PWD/RealESRGAN_x4plus_anime_6B.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
+        rm RealESRGAN_x4plus_anime_6B.pth
+    fi
+fi
+
+if [ ! -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
+    echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.."
+
+    curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth > RealESRGAN_x4plus_anime_6B.pth
+
+    if [ -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
+        model_size=`ls -l RealESRGAN_x4plus_anime_6B.pth | awk '{print $5}'`
+        if [ ! "$model_size" -eq "17938799" ]; then
+            printf "\n\nError: The downloaded ESRGAN x4plus_anime model file was invalid! Bytes downloaded: $model_size\n\n"
+            printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+            read -p "Press any key to continue"
+            exit
+        fi
+    else
+        printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
+        read -p "Press any key to continue"
+        exit
+    fi
+fi
+
+
+if [ `grep -c sd_install_complete ../scripts/install_status.txt` -gt "0" ]; then
+    echo sd_weights_downloaded >> ../scripts/install_status.txt
+    echo sd_install_complete >> ../scripts/install_status.txt
+fi
+
+printf "\n\nStable Diffusion is ready!\n\n"
+
+SD_PATH=`pwd`
+export PYTHONPATH="$SD_PATH;$SD_PATH/env/lib/python3.8/site-packages"
+echo "PYTHONPATH=$PYTHONPATH"
+
+cd ..
+export SD_UI_PATH=`pwd`/ui
+cd stable-diffusion
+
+python --version
+
+uvicorn server:app --app-dir "$SD_UI_PATH" --port 9000 --host 0.0.0.0
+
+read -p "Press any key to continue"

scripts/post_activate.bat

@@ -0,0 +1,6 @@
+@call conda --version
+@call git --version
+
+cd %CONDA_PREFIX%\..\scripts
+
+on_env_start.bat

scripts/post_activate.sh

@@ -0,0 +1,12 @@
+#!/bin/bash
+
+conda-unpack
+
+source $CONDA_PREFIX/etc/profile.d/conda.sh
+
+conda --version
+git --version
+
+cd $CONDA_PREFIX/../scripts
+
+./on_env_start.sh

scripts/start.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+
+source installer/bin/activate
+
+conda-unpack
+
+scripts/on_env_start.sh

scripts/win_enable_long_filepaths.ps1

@@ -0,0 +1,2 @@
+Set-ItemProperty -Path 'HKLM:\SYSTEM\CurrentControlSet\Control\FileSystem' -Name LongPathsEnabled -Type DWord -Value 1
+pause

server

@@ -1,25 +0,0 @@
-#!/bin/bash
-
-CMD="$1"
-if [ -z "$1" ]; then
-  CMD="start"
-fi
-
-start_server() {
-  docker-compose up &
-}
-
-stop_server() {
-  docker-compose down
-}
-
-if [ "$CMD" == "start" ]; then
-  start_server
-elif [ "$CMD" == "stop" ]; then
-  stop_server
-elif [ "$CMD" == "restart" ]; then
-  stop_server
-  start_server
-else
-  echo "Unknown option: $1 (Expected start or stop)"
-fi

ui/hotfix/9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142

@@ -0,0 +1,171 @@
+{
+  "_name_or_path": "clip-vit-large-patch14/",
+  "architectures": [
+    "CLIPModel"
+  ],
+  "initializer_factor": 1.0,
+  "logit_scale_init_value": 2.6592,
+  "model_type": "clip",
+  "projection_dim": 768,
+  "text_config": {
+    "_name_or_path": "",
+    "add_cross_attention": false,
+    "architectures": null,
+    "attention_dropout": 0.0,
+    "bad_words_ids": null,
+    "bos_token_id": 0,
+    "chunk_size_feed_forward": 0,
+    "cross_attention_hidden_size": null,
+    "decoder_start_token_id": null,
+    "diversity_penalty": 0.0,
+    "do_sample": false,
+    "dropout": 0.0,
+    "early_stopping": false,
+    "encoder_no_repeat_ngram_size": 0,
+    "eos_token_id": 2,
+    "finetuning_task": null,
+    "forced_bos_token_id": null,
+    "forced_eos_token_id": null,
+    "hidden_act": "quick_gelu",
+    "hidden_size": 768,
+    "id2label": {
+      "0": "LABEL_0",
+      "1": "LABEL_1"
+    },
+    "initializer_factor": 1.0,
+    "initializer_range": 0.02,
+    "intermediate_size": 3072,
+    "is_decoder": false,
+    "is_encoder_decoder": false,
+    "label2id": {
+      "LABEL_0": 0,
+      "LABEL_1": 1
+    },
+    "layer_norm_eps": 1e-05,
+    "length_penalty": 1.0,
+    "max_length": 20,
+    "max_position_embeddings": 77,
+    "min_length": 0,
+    "model_type": "clip_text_model",
+    "no_repeat_ngram_size": 0,
+    "num_attention_heads": 12,
+    "num_beam_groups": 1,
+    "num_beams": 1,
+    "num_hidden_layers": 12,
+    "num_return_sequences": 1,
+    "output_attentions": false,
+    "output_hidden_states": false,
+    "output_scores": false,
+    "pad_token_id": 1,
+    "prefix": null,
+    "problem_type": null,
+    "projection_dim" : 768,
+    "pruned_heads": {},
+    "remove_invalid_values": false,
+    "repetition_penalty": 1.0,
+    "return_dict": true,
+    "return_dict_in_generate": false,
+    "sep_token_id": null,
+    "task_specific_params": null,
+    "temperature": 1.0,
+    "tie_encoder_decoder": false,
+    "tie_word_embeddings": true,
+    "tokenizer_class": null,
+    "top_k": 50,
+    "top_p": 1.0,
+    "torch_dtype": null,
+    "torchscript": false,
+    "transformers_version": "4.16.0.dev0",
+    "use_bfloat16": false,
+    "vocab_size": 49408
+  },
+  "text_config_dict": {
+    "hidden_size": 768,
+    "intermediate_size": 3072,
+    "num_attention_heads": 12,
+    "num_hidden_layers": 12,
+    "projection_dim": 768
+  },
+  "torch_dtype": "float32",
+  "transformers_version": null,
+  "vision_config": {
+    "_name_or_path": "",
+    "add_cross_attention": false,
+    "architectures": null,
+    "attention_dropout": 0.0,
+    "bad_words_ids": null,
+    "bos_token_id": null,
+    "chunk_size_feed_forward": 0,
+    "cross_attention_hidden_size": null,
+    "decoder_start_token_id": null,
+    "diversity_penalty": 0.0,
+    "do_sample": false,
+    "dropout": 0.0,
+    "early_stopping": false,
+    "encoder_no_repeat_ngram_size": 0,
+    "eos_token_id": null,
+    "finetuning_task": null,
+    "forced_bos_token_id": null,
+    "forced_eos_token_id": null,
+    "hidden_act": "quick_gelu",
+    "hidden_size": 1024,
+    "id2label": {
+      "0": "LABEL_0",
+      "1": "LABEL_1"
+    },
+    "image_size": 224,
+    "initializer_factor": 1.0,
+    "initializer_range": 0.02,
+    "intermediate_size": 4096,
+    "is_decoder": false,
+    "is_encoder_decoder": false,
+    "label2id": {
+      "LABEL_0": 0,
+      "LABEL_1": 1
+    },
+    "layer_norm_eps": 1e-05,
+    "length_penalty": 1.0,
+    "max_length": 20,
+    "min_length": 0,
+    "model_type": "clip_vision_model",
+    "no_repeat_ngram_size": 0,
+    "num_attention_heads": 16,
+    "num_beam_groups": 1,
+    "num_beams": 1,
+    "num_hidden_layers": 24,
+    "num_return_sequences": 1,
+    "output_attentions": false,
+    "output_hidden_states": false,
+    "output_scores": false,
+    "pad_token_id": null,
+    "patch_size": 14,
+    "prefix": null,
+    "problem_type": null,
+    "projection_dim" : 768,
+    "pruned_heads": {},
+    "remove_invalid_values": false,
+    "repetition_penalty": 1.0,
+    "return_dict": true,
+    "return_dict_in_generate": false,
+    "sep_token_id": null,
+    "task_specific_params": null,
+    "temperature": 1.0,
+    "tie_encoder_decoder": false,
+    "tie_word_embeddings": true,
+    "tokenizer_class": null,
+    "top_k": 50,
+    "top_p": 1.0,
+    "torch_dtype": null,
+    "torchscript": false,
+    "transformers_version": "4.16.0.dev0",
+    "use_bfloat16": false
+  },
+  "vision_config_dict": {
+    "hidden_size": 1024,
+    "intermediate_size": 4096,
+    "num_attention_heads": 16,
+    "num_hidden_layers": 24,
+    "patch_size": 14,
+    "projection_dim": 768
+  }
+}

ui/modifiers.json

@@ -0,0 +1,258 @@
+[
+  [
+    "Drawing Style",
+    [
+      "Cel Shading",
+      "Children's Drawing",
+      "Crosshatch",
+      "Detailed and Intricate",
+      "Doodle",
+      "Dot Art",
+      "Line Art",
+      "Sketch"
+    ]
+  ],
+  [
+    "Visual Style",
+    [
+      "2D",
+      "8-bit",
+      "16-bit",
+      "Anaglyph",
+      "Anime",
+      "Art Nouveau",
+      "Bauhaus",
+      "Baroque",
+      "CGI",
+      "Cartoon",
+      "Comic Book",
+      "Concept Art",
+      "Constructivist",
+      "Cubist",
+      "Digital Art",
+      "Dadaist",
+      "Expressionist",
+      "Fantasy",
+      "Fauvist",
+      "Figurative",
+      "Graphic Novel",
+      "Geometric",
+      "Hard Edge Painting",
+      "Hydrodipped",
+      "Impressionistic",
+      "Lithography",
+      "Manga",
+      "Minimalist",
+      "Modern Art",
+      "Mosaic",
+      "Mural",
+      "Naive",
+      "Neoclassical",
+      "Photo",
+      "Realistic",
+      "Rococo",
+      "Romantic",
+      "Street Art",
+      "Symbolist",
+      "Stuckist",
+      "Surrealist",
+      "Visual Novel",
+      "Watercolor"
+    ]
+  ],
+  [
+    "Pen",
+    [
+      "Chalk",
+      "Colored Pencil",
+      "Graphite",
+      "Ink",
+      "Oil Paint",
+      "Pastel Art"
+    ]
+  ],
+  [
+    "Carving and Etching",
+    [
+      "Etching",
+      "Linocut",
+      "Paper Model",
+      "Paper-Mache",
+      "Papercutting",
+      "Pyrography",
+      "Wood-Carving"
+    ]
+  ],
+  [
+    "Camera",
+    [
+      "Aerial View",
+      "Canon50",
+      "Cinematic",
+      "Close-up",
+      "Color Grading",
+      "Dramatic",
+      "Film Grain",
+      "Fisheye Lens",
+      "Glamor Shot",
+      "Golden Hour",
+      "HD",
+      "Landscape",
+      "Lens Flare",
+      "Macro",
+      "Polaroid",
+      "Photoshoot",
+      "Portrait",
+      "Studio Lighting",
+      "Vintage",
+      "War Photography",
+      "White Balance",
+      "Wildlife Photography"
+    ]
+  ],
+  [
+    "Color",
+    [
+      "Beautiful Lighting",
+      "Cold Color Palette",
+      "Colorful",
+      "Dynamic Lighting",
+      "Electric Colors",
+      "Infrared",
+      "Pastel",
+      "Neon",
+      "Synthwave",
+      "Warm Color Palette"
+    ]
+  ],
+  [
+    "Emotions",
+    [
+      "Angry",
+      "Bitter",
+      "Disgusted",
+      "Embarrassed",
+      "Evil",
+      "Excited",
+      "Fear",
+      "Funny",
+      "Happy",
+      "Horrifying",
+      "Lonely",
+      "Sad",
+      "Serene",
+      "Surprised",
+      "Melancholic"
+    ]
+  ],
+  [
+    "Style of an artist or community",
+    [
+      "Artstation",
+      "trending on Artstation",
+      "by Agnes Lawrence Pelton",
+      "by Akihito Yoshida",
+      "by Alex Grey",
+      "by Alexander Jansson",
+      "by Alphonse Mucha",
+      "by Andy Warhol",
+      "by Artgerm",
+      "by Asaf Hanuka",
+      "by Aubrey Beardsley",
+      "by Banksy",
+      "by Beeple",
+      "by Ben Enwonwu",
+      "by Bob Eggleton",
+      "by Caravaggio Michelangelo Merisi",
+      "by Caspar David Friedrich",
+      "by Chris Foss",
+      "by Claude Monet",
+      "by Dan Mumford",
+      "by David Mann",
+      "by Diego Velázquez",
+      "by Disney Animation Studios",
+      "by Édouard Manet",
+      "by Esao Andrews",
+      "by Frida Kahlo",
+      "by Gediminas Pranckevicius",
+      "by Georgia O'Keeffe",
+      "by Greg Rutkowski",
+      "by Gustave Doré",
+      "by Gustave Klimt",
+      "by H.R. Giger",
+      "by Hayao Miyazaki",
+      "by Henri Matisse",
+      "by HP Lovecraft",
+      "by Ivan Shishkin",
+      "by Jack Kirby",
+      "by Jackson Pollock",
+      "by James Jean",
+      "by Jim Burns",
+      "by Johannes Vermeer",
+      "by John William Waterhouse",
+      "by Katsushika Hokusai",
+      "by Kim Tschang Yeul",
+      "by Ko Young Hoon",
+      "by Leonardo da Vinci",
+      "by Lisa Frank",
+      "by M.C. Escher",
+      "by Mahmoud Saïd",
+      "by Makoto Shinkai",
+      "by Marc Simonetti",
+      "by Mark Brooks",
+      "by Michelangelo",
+      "by Pablo Picasso",
+      "by Paul Klee",
+      "by Peter Mohrbacher",
+      "by Pierre-Auguste Renoir",
+      "by Pixar Animation Studios",
+      "by Rembrandt",
+      "by Richard Dadd",
+      "by Rossdraws",
+      "by Salvador Dalí",
+      "by Sam Does Arts",
+      "by Sandro Botticelli",
+      "by Ted Nasmith",
+      "by Ten Hundred",
+      "by Thomas Kinkade",
+      "by Tivadar Csontváry Kosztka",
+      "by Victo Ngai",
+      "by Vincent Di Fate",
+      "by Vincent van Gogh",
+      "by Wes Anderson",
+      "by wlop",
+      "by Yoshitaka Amano"
+    ]
+  ],
+  [
+    "CGI Software",
+    [
+      "3D Model",
+      "3D Sculpt",
+      "3Ds Max Model",
+      "Blender Model",
+      "Cinema4d Model",
+      "Maya Model",
+      "Unreal Engine",
+      "Zbrush Sculpt"
+    ]
+  ],
+  [
+    "CGI Rendering",
+    [
+      "3D Render",
+      "Corona Render",
+      "Creature Design",
+      "Cycles Render",
+      "Detailed Render",
+      "Environment Design",
+      "Intricate Environment",
+      "LSD Render",
+      "Octane Render",
+      "PBR",
+      "Glass Caustics",
+      "Global Illumination",
+      "Subsurface Scattering"
+    ]
+  ]
+]

ui/sd_internal/__init__.py

@@ -0,0 +1,98 @@
+import json
+
+class Request:
+    session_id: str = "session"
+    prompt: str = ""
+    init_image: str = None # base64
+    mask: str = None # base64
+    num_outputs: int = 1
+    num_inference_steps: int = 50
+    guidance_scale: float = 7.5
+    width: int = 512
+    height: int = 512
+    seed: int = 42
+    prompt_strength: float = 0.8
+    sampler: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
+    # allow_nsfw: bool = False
+    precision: str = "autocast" # or "full"
+    save_to_disk_path: str = None
+    turbo: bool = True
+    use_cpu: bool = False
+    use_full_precision: bool = False
+    use_face_correction: str = None # or "GFPGANv1.3"
+    use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
+    show_only_filtered_image: bool = False
+
+    stream_progress_updates: bool = False
+    stream_image_progress: bool = False
+
+    def json(self):
+        return {
+            "session_id": self.session_id,
+            "prompt": self.prompt,
+            "num_outputs": self.num_outputs,
+            "num_inference_steps": self.num_inference_steps,
+            "guidance_scale": self.guidance_scale,
+            "width": self.width,
+            "height": self.height,
+            "seed": self.seed,
+            "prompt_strength": self.prompt_strength,
+            "sampler": self.sampler,
+            "use_face_correction": self.use_face_correction,
+            "use_upscale": self.use_upscale,
+        }
+
+    def to_string(self):
+        return f'''
+    session_id: {self.session_id}
+    prompt: {self.prompt}
+    seed: {self.seed}
+    num_inference_steps: {self.num_inference_steps}
+    sampler: {self.sampler}
+    guidance_scale: {self.guidance_scale}
+    w: {self.width}
+    h: {self.height}
+    precision: {self.precision}
+    save_to_disk_path: {self.save_to_disk_path}
+    turbo: {self.turbo}
+    use_cpu: {self.use_cpu}
+    use_full_precision: {self.use_full_precision}
+    use_face_correction: {self.use_face_correction}
+    use_upscale: {self.use_upscale}
+    show_only_filtered_image: {self.show_only_filtered_image}
+
+    stream_progress_updates: {self.stream_progress_updates}
+    stream_image_progress: {self.stream_image_progress}'''
+
+class Image:
+    data: str # base64
+    seed: int
+    is_nsfw: bool
+    path_abs: str = None
+
+    def __init__(self, data, seed):
+        self.data = data
+        self.seed = seed
+
+    def json(self):
+        return {
+            "data": self.data,
+            "seed": self.seed,
+            "path_abs": self.path_abs,
+        }
+
+class Response:
+    request: Request
+    images: list
+
+    def json(self):
+        res = {
+            "status": 'succeeded',
+            "request": self.request.json(),
+            "output": [],
+        }
+
+        for image in self.images:
+            res["output"].append(image.json())
+
+        return res

ui/sd_internal/ddim_callback.patch

@@ -0,0 +1,332 @@
+diff --git a/optimizedSD/ddpm.py b/optimizedSD/ddpm.py
+index b967b55..35ef520 100644
+--- a/optimizedSD/ddpm.py
++++ b/optimizedSD/ddpm.py
+@@ -22,7 +22,7 @@ from ldm.util import exists, default, instantiate_from_config
+ from ldm.modules.diffusionmodules.util import make_beta_schedule
+ from ldm.modules.diffusionmodules.util import make_ddim_sampling_parameters, make_ddim_timesteps, noise_like
+ from ldm.modules.diffusionmodules.util import make_beta_schedule, extract_into_tensor, noise_like
+-from samplers import CompVisDenoiser, get_ancestral_step, to_d, append_dims,linear_multistep_coeff
++from .samplers import CompVisDenoiser, get_ancestral_step, to_d, append_dims,linear_multistep_coeff
+ 
+ def disabled_train(self):
+     """Overwrite model.train with this function to make sure train/eval mode
+@@ -506,6 +506,8 @@ class UNet(DDPM):
+ 
+         x_latent = noise if x0 is None else x0
+         # sampling
++        if sampler in ('ddim', 'dpm2', 'heun', 'dpm2_a', 'lms') and not hasattr(self, 'ddim_timesteps'):
++            self.make_schedule(ddim_num_steps=S, ddim_eta=eta, verbose=False)
+         
+         if sampler == "plms":
+             self.make_schedule(ddim_num_steps=S, ddim_eta=eta, verbose=False)
+@@ -528,39 +530,46 @@ class UNet(DDPM):
+         elif sampler == "ddim":
+             samples = self.ddim_sampling(x_latent, conditioning, S, unconditional_guidance_scale=unconditional_guidance_scale,
+                                          unconditional_conditioning=unconditional_conditioning,
+-                                         mask = mask,init_latent=x_T,use_original_steps=False)
++                                         mask = mask,init_latent=x_T,use_original_steps=False,
++                                         callback=callback, img_callback=img_callback)
+ 
+         elif sampler == "euler":
+             self.make_schedule(ddim_num_steps=S, ddim_eta=eta, verbose=False)
+             samples = self.euler_sampling(self.alphas_cumprod,x_latent, S, conditioning, unconditional_conditioning=unconditional_conditioning,
+-                                        unconditional_guidance_scale=unconditional_guidance_scale)
++                                        unconditional_guidance_scale=unconditional_guidance_scale,
++                                        img_callback=img_callback)
+         elif sampler == "euler_a":
+             self.make_schedule(ddim_num_steps=S, ddim_eta=eta, verbose=False)
+             samples = self.euler_ancestral_sampling(self.alphas_cumprod,x_latent, S, conditioning, unconditional_conditioning=unconditional_conditioning,
+-                                        unconditional_guidance_scale=unconditional_guidance_scale)
++                                        unconditional_guidance_scale=unconditional_guidance_scale,
++                                        img_callback=img_callback)
+ 
+         elif sampler == "dpm2":
+             samples = self.dpm_2_sampling(self.alphas_cumprod,x_latent, S, conditioning, unconditional_conditioning=unconditional_conditioning,
+-                                        unconditional_guidance_scale=unconditional_guidance_scale)
++                                        unconditional_guidance_scale=unconditional_guidance_scale,
++                                        img_callback=img_callback)
+         elif sampler == "heun":
+             samples = self.heun_sampling(self.alphas_cumprod,x_latent, S, conditioning, unconditional_conditioning=unconditional_conditioning,
+-                                        unconditional_guidance_scale=unconditional_guidance_scale)
++                                        unconditional_guidance_scale=unconditional_guidance_scale,
++                                        img_callback=img_callback)
+ 
+         elif sampler == "dpm2_a":
+             samples = self.dpm_2_ancestral_sampling(self.alphas_cumprod,x_latent, S, conditioning, unconditional_conditioning=unconditional_conditioning,
+-                                        unconditional_guidance_scale=unconditional_guidance_scale)
++                                        unconditional_guidance_scale=unconditional_guidance_scale,
++                                        img_callback=img_callback)
+ 
+ 
+         elif sampler == "lms":
+             samples = self.lms_sampling(self.alphas_cumprod,x_latent, S, conditioning, unconditional_conditioning=unconditional_conditioning,
+-                                        unconditional_guidance_scale=unconditional_guidance_scale)
++                                        unconditional_guidance_scale=unconditional_guidance_scale,
++                                        img_callback=img_callback)
++
++        yield from samples
+ 
+         if(self.turbo):
+             self.model1.to("cpu")
+             self.model2.to("cpu")
+ 
+-        return samples
+-
+     @torch.no_grad()
+     def plms_sampling(self, cond,b, img,
+                       ddim_use_original_steps=False,
+@@ -599,10 +608,10 @@ class UNet(DDPM):
+             old_eps.append(e_t)
+             if len(old_eps) >= 4:
+                 old_eps.pop(0)
+-            if callback: callback(i)
+-            if img_callback: img_callback(pred_x0, i)
++            if callback: yield from callback(i)
++            if img_callback: yield from img_callback(pred_x0, i)
+ 
+-        return img
++        yield from img_callback(img, len(iterator)-1)
+ 
+     @torch.no_grad()
+     def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
+@@ -706,7 +715,8 @@ class UNet(DDPM):
+ 
+     @torch.no_grad()
+     def ddim_sampling(self, x_latent, cond, t_start, unconditional_guidance_scale=1.0, unconditional_conditioning=None,
+-               mask = None,init_latent=None,use_original_steps=False):
++               mask = None,init_latent=None,use_original_steps=False,
++               callback=None, img_callback=None):
+ 
+         timesteps = self.ddim_timesteps
+         timesteps = timesteps[:t_start]
+@@ -730,10 +740,13 @@ class UNet(DDPM):
+                                           unconditional_guidance_scale=unconditional_guidance_scale,
+                                           unconditional_conditioning=unconditional_conditioning)
+         
++            if callback: yield from callback(i)
++            if img_callback: yield from img_callback(x_dec, i)
++
+         if mask is not None:
+-            return x0 * mask + (1. - mask) * x_dec
++            x_dec = x0 * mask + (1. - mask) * x_dec
+ 
+-        return x_dec
++        yield from img_callback(x_dec, len(iterator)-1)
+ 
+ 
+     @torch.no_grad()
+@@ -779,13 +792,16 @@ class UNet(DDPM):
+ 
+ 
+     @torch.no_grad()
+-    def euler_sampling(self, ac, x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1,extra_args=None,callback=None, disable=None, s_churn=0., s_tmin=0., s_tmax=float('inf'), s_noise=1.):
++    def euler_sampling(self, ac, x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1,extra_args=None,callback=None, disable=None, s_churn=0., s_tmin=0., s_tmax=float('inf'), s_noise=1.,
++                        img_callback=None):
+         """Implements Algorithm 2 (Euler steps) from Karras et al. (2022)."""
+         extra_args = {} if extra_args is None else extra_args
+         cvd = CompVisDenoiser(ac)
+         sigmas = cvd.get_sigmas(S)
+         x = x*sigmas[0]
+ 
++        print(f"Running Euler Sampling with {len(sigmas) - 1} timesteps")
++
+         s_in = x.new_ones([x.shape[0]]).half()
+         for i in trange(len(sigmas) - 1, disable=disable):
+             gamma = min(s_churn / (len(sigmas) - 1), 2 ** 0.5 - 1) if s_tmin <= sigmas[i] <= s_tmax else 0.
+@@ -807,13 +823,18 @@ class UNet(DDPM):
+             d = to_d(x, sigma_hat, denoised)
+             if callback is not None:
+                 callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigma_hat, 'denoised': denoised})
++
++            if img_callback: yield from img_callback(x, i)
++
+             dt = sigmas[i + 1] - sigma_hat
+             # Euler method
+             x = x + d * dt
+-        return x
++
++        yield from img_callback(x, len(sigmas)-1)
+ 
+     @torch.no_grad()
+-    def euler_ancestral_sampling(self,ac,x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1,extra_args=None, callback=None, disable=None):
++    def euler_ancestral_sampling(self,ac,x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1,extra_args=None, callback=None, disable=None,
++                        img_callback=None):
+         """Ancestral sampling with Euler method steps."""
+         extra_args = {} if extra_args is None else extra_args
+ 
+@@ -822,6 +843,8 @@ class UNet(DDPM):
+         sigmas = cvd.get_sigmas(S)
+         x = x*sigmas[0]
+ 
++        print(f"Running Euler Ancestral Sampling with {len(sigmas) - 1} timesteps")
++
+         s_in = x.new_ones([x.shape[0]]).half()
+         for i in trange(len(sigmas) - 1, disable=disable):
+ 
+@@ -837,17 +860,22 @@ class UNet(DDPM):
+             sigma_down, sigma_up = get_ancestral_step(sigmas[i], sigmas[i + 1])
+             if callback is not None:
+                 callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigmas[i], 'denoised': denoised})
++
++            if img_callback: yield from img_callback(x, i)
++
+             d = to_d(x, sigmas[i], denoised)
+             # Euler method
+             dt = sigma_down - sigmas[i]
+             x = x + d * dt
+             x = x + torch.randn_like(x) * sigma_up
+-        return x
++
++        yield from img_callback(x, len(sigmas)-1)
+ 
+ 
+ 
+     @torch.no_grad()
+-    def heun_sampling(self, ac, x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1, extra_args=None, callback=None, disable=None, s_churn=0., s_tmin=0., s_tmax=float('inf'), s_noise=1.):
++    def heun_sampling(self, ac, x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1, extra_args=None, callback=None, disable=None, s_churn=0., s_tmin=0., s_tmax=float('inf'), s_noise=1.,
++                        img_callback=None):
+         """Implements Algorithm 2 (Heun steps) from Karras et al. (2022)."""
+         extra_args = {} if extra_args is None else extra_args
+ 
+@@ -855,6 +883,8 @@ class UNet(DDPM):
+         sigmas = cvd.get_sigmas(S)
+         x = x*sigmas[0]
+ 
++        print(f"Running Heun Sampling with {len(sigmas) - 1} timesteps")
++
+ 
+         s_in = x.new_ones([x.shape[0]]).half()
+         for i in trange(len(sigmas) - 1, disable=disable):
+@@ -876,6 +906,9 @@ class UNet(DDPM):
+             d = to_d(x, sigma_hat, denoised)
+             if callback is not None:
+                 callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigma_hat, 'denoised': denoised})
++
++            if img_callback: yield from img_callback(x, i)
++
+             dt = sigmas[i + 1] - sigma_hat
+             if sigmas[i + 1] == 0:
+                 # Euler method
+@@ -895,11 +928,13 @@ class UNet(DDPM):
+                 d_2 = to_d(x_2, sigmas[i + 1], denoised_2)
+                 d_prime = (d + d_2) / 2
+                 x = x + d_prime * dt
+-        return x
++
++        yield from img_callback(x, len(sigmas)-1)
+ 
+ 
+     @torch.no_grad()
+-    def dpm_2_sampling(self,ac,x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1,extra_args=None, callback=None, disable=None, s_churn=0., s_tmin=0., s_tmax=float('inf'), s_noise=1.):
++    def dpm_2_sampling(self,ac,x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1,extra_args=None, callback=None, disable=None, s_churn=0., s_tmin=0., s_tmax=float('inf'), s_noise=1.,
++                        img_callback=None):
+         """A sampler inspired by DPM-Solver-2 and Algorithm 2 from Karras et al. (2022)."""
+         extra_args = {} if extra_args is None else extra_args
+ 
+@@ -907,6 +942,8 @@ class UNet(DDPM):
+         sigmas = cvd.get_sigmas(S)
+         x = x*sigmas[0]
+ 
++        print(f"Running DPM2 Sampling with {len(sigmas) - 1} timesteps")
++
+         s_in = x.new_ones([x.shape[0]]).half()
+         for i in trange(len(sigmas) - 1, disable=disable):
+             gamma = min(s_churn / (len(sigmas) - 1), 2 ** 0.5 - 1) if s_tmin <= sigmas[i] <= s_tmax else 0.
+@@ -924,7 +961,7 @@ class UNet(DDPM):
+             e_t_uncond, e_t = (x_in  + eps * c_out).chunk(2)
+             denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
+ 
+-
++            if img_callback: yield from img_callback(x, i)
+             
+             d = to_d(x, sigma_hat, denoised)
+             # Midpoint method, where the midpoint is chosen according to a rho=3 Karras schedule
+@@ -945,11 +982,13 @@ class UNet(DDPM):
+ 
+             d_2 = to_d(x_2, sigma_mid, denoised_2)
+             x = x + d_2 * dt_2
+-        return x
++
++        yield from img_callback(x, len(sigmas)-1)
+ 
+ 
+     @torch.no_grad()
+-    def dpm_2_ancestral_sampling(self,ac,x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1, extra_args=None, callback=None, disable=None):
++    def dpm_2_ancestral_sampling(self,ac,x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1, extra_args=None, callback=None, disable=None,
++                        img_callback=None):
+         """Ancestral sampling with DPM-Solver inspired second-order steps."""
+         extra_args = {} if extra_args is None else extra_args
+ 
+@@ -957,6 +996,8 @@ class UNet(DDPM):
+         sigmas = cvd.get_sigmas(S)
+         x = x*sigmas[0]
+ 
++        print(f"Running DPM2 Ancestral Sampling with {len(sigmas) - 1} timesteps")
++
+         s_in = x.new_ones([x.shape[0]]).half()
+         for i in trange(len(sigmas) - 1, disable=disable):
+ 
+@@ -973,6 +1014,9 @@ class UNet(DDPM):
+             sigma_down, sigma_up = get_ancestral_step(sigmas[i], sigmas[i + 1])
+             if callback is not None:
+                 callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigmas[i], 'denoised': denoised})
++
++            if img_callback: yield from img_callback(x, i)
++
+             d = to_d(x, sigmas[i], denoised)
+             # Midpoint method, where the midpoint is chosen according to a rho=3 Karras schedule
+             sigma_mid = ((sigmas[i] ** (1 / 3) + sigma_down ** (1 / 3)) / 2) ** 3
+@@ -993,11 +1037,13 @@ class UNet(DDPM):
+             d_2 = to_d(x_2, sigma_mid, denoised_2)
+             x = x + d_2 * dt_2
+             x = x + torch.randn_like(x) * sigma_up
+-        return x
++
++        yield from img_callback(x, len(sigmas)-1)
+ 
+ 
+     @torch.no_grad()
+-    def lms_sampling(self,ac,x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1, extra_args=None, callback=None, disable=None, order=4):
++    def lms_sampling(self,ac,x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1, extra_args=None, callback=None, disable=None, order=4,
++                        img_callback=None):
+         extra_args = {} if extra_args is None else extra_args
+         s_in = x.new_ones([x.shape[0]])
+ 
+@@ -1005,6 +1051,8 @@ class UNet(DDPM):
+         sigmas = cvd.get_sigmas(S)
+         x = x*sigmas[0]
+ 
++        print(f"Running LMS Sampling with {len(sigmas) - 1} timesteps")
++
+         ds = []
+         for i in trange(len(sigmas) - 1, disable=disable):
+ 
+@@ -1017,6 +1065,7 @@ class UNet(DDPM):
+             e_t_uncond, e_t = (x_in  + eps * c_out).chunk(2)
+             denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
+ 
++            if img_callback: yield from img_callback(x, i)
+ 
+             d = to_d(x, sigmas[i], denoised)
+             ds.append(d)
+@@ -1027,4 +1076,5 @@ class UNet(DDPM):
+             cur_order = min(i + 1, order)
+             coeffs = [linear_multistep_coeff(cur_order, sigmas.cpu(), i, j) for j in range(cur_order)]
+             x = x + sum(coeff * d for coeff, d in zip(coeffs, reversed(ds)))
+-        return x
++
++        yield from img_callback(x, len(sigmas)-1)
+diff --git a/optimizedSD/openaimodelSplit.py b/optimizedSD/openaimodelSplit.py
+index abc3098..7a32ffe 100644
+--- a/optimizedSD/openaimodelSplit.py
++++ b/optimizedSD/openaimodelSplit.py
+@@ -13,7 +13,7 @@ from ldm.modules.diffusionmodules.util import (
+     normalization,
+     timestep_embedding,
+ )
+-from splitAttention import SpatialTransformer
++from .splitAttention import SpatialTransformer
+ 
+ 
+ class AttentionPool2d(nn.Module):

ui/sd_internal/env_yaml.patch

@@ -0,0 +1,13 @@
+diff --git a/environment.yaml b/environment.yaml
+index 7f25da8..306750f 100644
+--- a/environment.yaml
++++ b/environment.yaml
+@@ -23,6 +23,8 @@ dependencies:
+     - torch-fidelity==0.3.0
+     - transformers==4.19.2
+     - torchmetrics==0.6.0
++    - pywavelets==1.3.0
++    - pandas==1.4.4
+     - kornia==0.6
+     - -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers
+     - -e git+https://github.com/openai/CLIP.git@main#egg=clip

ui/sd_internal/runtime.py

@@ -0,0 +1,658 @@
+import json
+import os, re
+import traceback
+import torch
+import numpy as np
+from omegaconf import OmegaConf
+from PIL import Image, ImageOps
+from tqdm import tqdm, trange
+from itertools import islice
+from einops import rearrange
+import time
+from pytorch_lightning import seed_everything
+from torch import autocast
+from contextlib import nullcontext
+from einops import rearrange, repeat
+from ldm.util import instantiate_from_config
+from optimizedSD.optimUtils import split_weighted_subprompts
+from transformers import logging
+
+from gfpgan import GFPGANer
+from basicsr.archs.rrdbnet_arch import RRDBNet
+from realesrgan import RealESRGANer
+
+import uuid
+
+logging.set_verbosity_error()
+
+# consts
+config_yaml = "optimizedSD/v1-inference.yaml"
+filename_regex = re.compile('[^a-zA-Z0-9]')
+
+# api stuff
+from . import Request, Response, Image as ResponseImage
+import base64
+from io import BytesIO
+#from colorama import Fore
+
+# local
+stop_processing = False
+temp_images = {}
+
+ckpt_file = None
+gfpgan_file = None
+real_esrgan_file = None
+
+model = None
+modelCS = None
+modelFS = None
+model_gfpgan = None
+model_real_esrgan = None
+
+model_is_half = False
+model_fs_is_half = False
+device = None
+unet_bs = 1
+precision = 'autocast'
+sampler_plms = None
+sampler_ddim = None
+
+has_valid_gpu = False
+force_full_precision = False
+try:
+    gpu = torch.cuda.current_device()
+    gpu_name = torch.cuda.get_device_name(gpu)
+    print('GPU detected: ', gpu_name)
+
+    force_full_precision = ('nvidia' in gpu_name.lower() or 'geforce' in gpu_name.lower()) and (' 1660' in gpu_name or ' 1650' in gpu_name) # otherwise these NVIDIA cards create green images
+    if force_full_precision:
+        print('forcing full precision on NVIDIA 16xx cards, to avoid green images. GPU detected: ', gpu_name)
+
+    mem_free, mem_total = torch.cuda.mem_get_info(gpu)
+    mem_total /= float(10**9)
+    if mem_total < 3.0:
+        print("GPUs with less than 3 GB of VRAM are not compatible with Stable Diffusion")
+        raise Exception()
+
+    has_valid_gpu = True
+except:
+    print('WARNING: No compatible GPU found. Using the CPU, but this will be very slow!')
+    pass
+
+def load_model_ckpt(ckpt_to_use, device_to_use='cuda', turbo=False, unet_bs_to_use=1, precision_to_use='autocast', half_model_fs=False):
+    global ckpt_file, model, modelCS, modelFS, model_is_half, device, unet_bs, precision, model_fs_is_half
+
+    ckpt_file = ckpt_to_use
+    device = device_to_use if has_valid_gpu else 'cpu'
+    precision = precision_to_use if not force_full_precision else 'full'
+    unet_bs = unet_bs_to_use
+
+    if device == 'cpu':
+        precision = 'full'
+
+    sd = load_model_from_config(f"{ckpt_file}.ckpt")
+    li, lo = [], []
+    for key, value in sd.items():
+        sp = key.split(".")
+        if (sp[0]) == "model":
+            if "input_blocks" in sp:
+                li.append(key)
+            elif "middle_block" in sp:
+                li.append(key)
+            elif "time_embed" in sp:
+                li.append(key)
+            else:
+                lo.append(key)
+    for key in li:
+        sd["model1." + key[6:]] = sd.pop(key)
+    for key in lo:
+        sd["model2." + key[6:]] = sd.pop(key)
+
+    config = OmegaConf.load(f"{config_yaml}")
+
+    model = instantiate_from_config(config.modelUNet)
+    _, _ = model.load_state_dict(sd, strict=False)
+    model.eval()
+    model.cdevice = device
+    model.unet_bs = unet_bs
+    model.turbo = turbo
+
+    modelCS = instantiate_from_config(config.modelCondStage)
+    _, _ = modelCS.load_state_dict(sd, strict=False)
+    modelCS.eval()
+    modelCS.cond_stage_model.device = device
+
+    modelFS = instantiate_from_config(config.modelFirstStage)
+    _, _ = modelFS.load_state_dict(sd, strict=False)
+    modelFS.eval()
+    del sd
+
+    if device != "cpu" and precision == "autocast":
+        model.half()
+        modelCS.half()
+        model_is_half = True
+    else:
+        model_is_half = False
+
+    if half_model_fs:
+        modelFS.half()
+        model_fs_is_half = True
+    else:
+        model_fs_is_half = False
+
+    print('loaded ', ckpt_file, 'to', device, 'precision', precision)
+
+def load_model_gfpgan(gfpgan_to_use):
+    global gfpgan_file, model_gfpgan
+
+    if gfpgan_to_use is None:
+        return
+
+    gfpgan_file = gfpgan_to_use
+    model_path = gfpgan_to_use + ".pth"
+
+    if device == 'cpu':
+        model_gfpgan = GFPGANer(model_path=model_path, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None, device=torch.device('cpu'))
+    else:
+        model_gfpgan = GFPGANer(model_path=model_path, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None, device=torch.device('cuda'))
+
+    print('loaded ', gfpgan_to_use, 'to', device, 'precision', precision)
+
+def load_model_real_esrgan(real_esrgan_to_use):
+    global real_esrgan_file, model_real_esrgan
+
+    if real_esrgan_to_use is None:
+        return
+
+    real_esrgan_file = real_esrgan_to_use
+    model_path = real_esrgan_to_use + ".pth"
+
+    RealESRGAN_models = {
+        'RealESRGAN_x4plus': RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4),
+        'RealESRGAN_x4plus_anime_6B': RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
+    }
+
+    model_to_use = RealESRGAN_models[real_esrgan_to_use]
+
+    if device == 'cpu':
+        model_real_esrgan = RealESRGANer(scale=2, model_path=model_path, model=model_to_use, pre_pad=0, half=False) # cpu does not support half
+        model_real_esrgan.device = torch.device('cpu')
+        model_real_esrgan.model.to('cpu')
+    else:
+        model_real_esrgan = RealESRGANer(scale=2, model_path=model_path, model=model_to_use, pre_pad=0, half=model_is_half)
+
+    model_real_esrgan.model.name = real_esrgan_to_use
+
+    print('loaded ', real_esrgan_to_use, 'to', device, 'precision', precision)
+
+def mk_img(req: Request):
+    try:
+        yield from do_mk_img(req)
+    except Exception as e:
+        print(traceback.format_exc())
+
+        gc()
+
+        if device != "cpu":
+            modelFS.to("cpu")
+            modelCS.to("cpu")
+
+            model.model1.to("cpu")
+            model.model2.to("cpu")
+
+        gc()
+
+        yield json.dumps({
+            "status": 'failed',
+            "detail": str(e)
+        })
+
+def do_mk_img(req: Request):
+    global model, modelCS, modelFS, device
+    global model_gfpgan, model_real_esrgan
+    global stop_processing
+
+    stop_processing = False
+
+    res = Response()
+    res.request = req
+    res.images = []
+
+    temp_images.clear()
+
+    model.turbo = req.turbo
+    if req.use_cpu:
+        if device != 'cpu':
+            device = 'cpu'
+
+            if model_is_half:
+                del model, modelCS, modelFS
+                load_model_ckpt(ckpt_file, device)
+
+            load_model_gfpgan(gfpgan_file)
+            load_model_real_esrgan(real_esrgan_file)
+    else:
+        if has_valid_gpu:
+            prev_device = device
+            device = 'cuda'
+
+            if (precision == 'autocast' and (req.use_full_precision or not model_is_half)) or \
+                (precision == 'full' and not req.use_full_precision and not force_full_precision) or \
+                (req.init_image is None and model_fs_is_half) or \
+                (req.init_image is not None and not model_fs_is_half and not force_full_precision):
+
+                del model, modelCS, modelFS
+                load_model_ckpt(ckpt_file, device, req.turbo, unet_bs, ('full' if req.use_full_precision else 'autocast'), half_model_fs=(req.init_image is not None and not req.use_full_precision))
+
+                if prev_device != device:
+                    load_model_gfpgan(gfpgan_file)
+                    load_model_real_esrgan(real_esrgan_file)
+
+    if req.use_face_correction != gfpgan_file:
+        load_model_gfpgan(req.use_face_correction)
+
+    if req.use_upscale != real_esrgan_file:
+        load_model_real_esrgan(req.use_upscale)
+
+    model.cdevice = device
+    modelCS.cond_stage_model.device = device
+
+    opt_prompt = req.prompt
+    opt_seed = req.seed
+    opt_n_samples = req.num_outputs
+    opt_n_iter = 1
+    opt_scale = req.guidance_scale
+    opt_C = 4
+    opt_H = req.height
+    opt_W = req.width
+    opt_f = 8
+    opt_ddim_steps = req.num_inference_steps
+    opt_ddim_eta = 0.0
+    opt_strength = req.prompt_strength
+    opt_save_to_disk_path = req.save_to_disk_path
+    opt_init_img = req.init_image
+    opt_use_face_correction = req.use_face_correction
+    opt_use_upscale = req.use_upscale
+    opt_show_only_filtered = req.show_only_filtered_image
+    opt_format = 'png'
+    opt_sampler_name = req.sampler
+
+    print(req.to_string(), '\n    device', device)
+
+    print('\n\n    Using precision:', precision)
+
+    seed_everything(opt_seed)
+
+    batch_size = opt_n_samples
+    prompt = opt_prompt
+    assert prompt is not None
+    data = [batch_size * [prompt]]
+
+    if precision == "autocast" and device != "cpu":
+        precision_scope = autocast
+    else:
+        precision_scope = nullcontext
+
+    mask = None
+
+    if req.init_image is None:
+        handler = _txt2img
+
+        init_latent = None
+        t_enc = None
+    else:
+        handler = _img2img
+
+        init_image = load_img(req.init_image, opt_W, opt_H)
+        init_image = init_image.to(device)
+
+        if device != "cpu" and precision == "autocast":
+            init_image = init_image.half()
+
+        modelFS.to(device)
+
+        init_image = repeat(init_image, '1 ... -> b ...', b=batch_size)
+        init_latent = modelFS.get_first_stage_encoding(modelFS.encode_first_stage(init_image))  # move to latent space
+
+        if req.mask is not None:
+            mask = load_mask(req.mask, opt_W, opt_H, init_latent.shape[2], init_latent.shape[3], True).to(device)
+            mask = mask[0][0].unsqueeze(0).repeat(4, 1, 1).unsqueeze(0)
+            mask = repeat(mask, '1 ... -> b ...', b=batch_size)
+
+            if device != "cpu" and precision == "autocast":
+                mask = mask.half()
+
+        move_fs_to_cpu()
+
+        assert 0. <= opt_strength <= 1., 'can only work with strength in [0.0, 1.0]'
+        t_enc = int(opt_strength * opt_ddim_steps)
+        print(f"target t_enc is {t_enc} steps")
+
+    if opt_save_to_disk_path is not None:
+        session_out_path = os.path.join(opt_save_to_disk_path, req.session_id)
+        os.makedirs(session_out_path, exist_ok=True)
+    else:
+        session_out_path = None
+
+    seeds = ""
+    with torch.no_grad():
+        for n in trange(opt_n_iter, desc="Sampling"):
+            for prompts in tqdm(data, desc="data"):
+
+                with precision_scope("cuda"):
+                    modelCS.to(device)
+                    uc = None
+                    if opt_scale != 1.0:
+                        uc = modelCS.get_learned_conditioning(batch_size * [""])
+                    if isinstance(prompts, tuple):
+                        prompts = list(prompts)
+
+                    subprompts, weights = split_weighted_subprompts(prompts[0])
+                    if len(subprompts) > 1:
+                        c = torch.zeros_like(uc)
+                        totalWeight = sum(weights)
+                        # normalize each "sub prompt" and add it
+                        for i in range(len(subprompts)):
+                            weight = weights[i]
+                            # if not skip_normalize:
+                            weight = weight / totalWeight
+                            c = torch.add(c, modelCS.get_learned_conditioning(subprompts[i]), alpha=weight)
+                    else:
+                        c = modelCS.get_learned_conditioning(prompts)
+
+                    modelFS.to(device)
+
+                    partial_x_samples = None
+                    def img_callback(x_samples, i):
+                        nonlocal partial_x_samples
+
+                        partial_x_samples = x_samples
+
+                        if req.stream_progress_updates:
+                            n_steps = opt_ddim_steps if req.init_image is None else t_enc
+                            progress = {"step": i, "total_steps": n_steps}
+
+                            if req.stream_image_progress and i % 5 == 0:
+                                partial_images = []
+
+                                for i in range(batch_size):
+                                    x_samples_ddim = modelFS.decode_first_stage(x_samples[i].unsqueeze(0))
+                                    x_sample = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
+                                    x_sample = 255.0 * rearrange(x_sample[0].cpu().numpy(), "c h w -> h w c")
+                                    x_sample = x_sample.astype(np.uint8)
+                                    img = Image.fromarray(x_sample)
+                                    buf = BytesIO()
+                                    img.save(buf, format='JPEG')
+                                    buf.seek(0)
+
+                                    del img, x_sample, x_samples_ddim
+                                    # don't delete x_samples, it is used in the code that called this callback
+
+                                    temp_images[str(req.session_id) + '/' + str(i)] = buf
+                                    partial_images.append({'path': f'/image/tmp/{req.session_id}/{i}'})
+
+                                progress['output'] = partial_images
+
+                            yield json.dumps(progress)
+
+                        if stop_processing:
+                            raise UserInitiatedStop("User requested that we stop processing")
+
+                    # run the handler
+                    try:
+                        if handler == _txt2img:
+                            x_samples = _txt2img(opt_W, opt_H, opt_n_samples, opt_ddim_steps, opt_scale, None, opt_C, opt_f, opt_ddim_eta, c, uc, opt_seed, img_callback, mask, opt_sampler_name)
+                        else:
+                            x_samples = _img2img(init_latent, t_enc, batch_size, opt_scale, c, uc, opt_ddim_steps, opt_ddim_eta, opt_seed, img_callback, mask)
+
+                        yield from x_samples
+
+                        x_samples = partial_x_samples
+                    except UserInitiatedStop:
+                        if partial_x_samples is None:
+                            continue
+
+                        x_samples = partial_x_samples
+
+                    print("saving images")
+                    for i in range(batch_size):
+
+                        x_samples_ddim = modelFS.decode_first_stage(x_samples[i].unsqueeze(0))
+                        x_sample = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
+                        x_sample = 255.0 * rearrange(x_sample[0].cpu().numpy(), "c h w -> h w c")
+                        x_sample = x_sample.astype(np.uint8)
+                        img = Image.fromarray(x_sample)
+
+                        has_filters =   (opt_use_face_correction is not None and opt_use_face_correction.startswith('GFPGAN')) or \
+                                        (opt_use_upscale is not None and opt_use_upscale.startswith('RealESRGAN'))
+
+                        return_orig_img = not has_filters or not opt_show_only_filtered
+
+                        if stop_processing:
+                            return_orig_img = True
+
+                        if opt_save_to_disk_path is not None:
+                            prompt_flattened = filename_regex.sub('_', prompts[0])
+                            prompt_flattened = prompt_flattened[:50]
+
+                            img_id = str(uuid.uuid4())[-8:]
+
+                            file_path = f"{prompt_flattened}_{img_id}"
+                            img_out_path = os.path.join(session_out_path, f"{file_path}.{opt_format}")
+                            meta_out_path = os.path.join(session_out_path, f"{file_path}.txt")
+
+                            if return_orig_img:
+                                save_image(img, img_out_path)
+
+                            save_metadata(meta_out_path, prompts, opt_seed, opt_W, opt_H, opt_ddim_steps, opt_scale, opt_strength, opt_use_face_correction, opt_use_upscale, opt_sampler_name)
+
+                        if return_orig_img:
+                            img_data = img_to_base64_str(img)
+                            res_image_orig = ResponseImage(data=img_data, seed=opt_seed)
+                            res.images.append(res_image_orig)
+
+                            if opt_save_to_disk_path is not None:
+                                res_image_orig.path_abs = img_out_path
+
+                        del img
+
+                        if has_filters and not stop_processing:
+                            print('Applying filters..')
+
+                            gc()
+                            filters_applied = []
+
+                            if opt_use_face_correction:
+                                _, _, output = model_gfpgan.enhance(x_sample[:,:,::-1], has_aligned=False, only_center_face=False, paste_back=True)
+                                x_sample = output[:,:,::-1]
+                                filters_applied.append(opt_use_face_correction)
+
+                            if opt_use_upscale:
+                                output, _ = model_real_esrgan.enhance(x_sample[:,:,::-1])
+                                x_sample = output[:,:,::-1]
+                                filters_applied.append(opt_use_upscale)
+
+                            filtered_image = Image.fromarray(x_sample)
+
+                            filtered_img_data = img_to_base64_str(filtered_image)
+                            res_image_filtered = ResponseImage(data=filtered_img_data, seed=opt_seed)
+                            res.images.append(res_image_filtered)
+
+                            filters_applied = "_".join(filters_applied)
+
+                            if opt_save_to_disk_path is not None:
+                                filtered_img_out_path = os.path.join(session_out_path, f"{file_path}_{filters_applied}.{opt_format}")
+                                save_image(filtered_image, filtered_img_out_path)
+                                res_image_filtered.path_abs = filtered_img_out_path
+
+                            del filtered_image
+
+                        seeds += str(opt_seed) + ","
+                        opt_seed += 1
+
+                    move_fs_to_cpu()
+                    gc()
+                    del x_samples, x_samples_ddim, x_sample
+                    print("memory_final = ", torch.cuda.memory_allocated() / 1e6)
+
+    print('Task completed')
+
+    yield json.dumps(res.json())
+
+def save_image(img, img_out_path):
+    try:
+        img.save(img_out_path)
+    except:
+        print('could not save the file', traceback.format_exc())
+
+def save_metadata(meta_out_path, prompts, opt_seed, opt_W, opt_H, opt_ddim_steps, opt_scale, opt_prompt_strength, opt_correct_face, opt_upscale, sampler_name):
+    metadata = f"{prompts[0]}\nWidth: {opt_W}\nHeight: {opt_H}\nSeed: {opt_seed}\nSteps: {opt_ddim_steps}\nGuidance Scale: {opt_scale}\nPrompt Strength: {opt_prompt_strength}\nUse Face Correction: {opt_correct_face}\nUse Upscaling: {opt_upscale}\nSampler: {sampler_name}"
+
+    try:
+        with open(meta_out_path, 'w') as f:
+            f.write(metadata)
+    except:
+        print('could not save the file', traceback.format_exc())
+
+def _txt2img(opt_W, opt_H, opt_n_samples, opt_ddim_steps, opt_scale, start_code, opt_C, opt_f, opt_ddim_eta, c, uc, opt_seed, img_callback, mask, sampler_name):
+    shape = [opt_n_samples, opt_C, opt_H // opt_f, opt_W // opt_f]
+
+    if device != "cpu":
+        mem = torch.cuda.memory_allocated() / 1e6
+        modelCS.to("cpu")
+        while torch.cuda.memory_allocated() / 1e6 >= mem:
+            time.sleep(1)
+
+    if sampler_name == 'ddim':
+        model.make_schedule(ddim_num_steps=opt_ddim_steps, ddim_eta=opt_ddim_eta, verbose=False)
+
+    samples_ddim = model.sample(
+        S=opt_ddim_steps,
+        conditioning=c,
+        seed=opt_seed,
+        shape=shape,
+        verbose=False,
+        unconditional_guidance_scale=opt_scale,
+        unconditional_conditioning=uc,
+        eta=opt_ddim_eta,
+        x_T=start_code,
+        img_callback=img_callback,
+        mask=mask,
+        sampler = sampler_name,
+    )
+
+    yield from samples_ddim
+
+def _img2img(init_latent, t_enc, batch_size, opt_scale, c, uc, opt_ddim_steps, opt_ddim_eta, opt_seed, img_callback, mask):
+    # encode (scaled latent)
+    z_enc = model.stochastic_encode(
+        init_latent,
+        torch.tensor([t_enc] * batch_size).to(device),
+        opt_seed,
+        opt_ddim_eta,
+        opt_ddim_steps,
+    )
+    x_T = None if mask is None else init_latent
+
+    # decode it
+    samples_ddim = model.sample(
+        t_enc,
+        c,
+        z_enc,
+        unconditional_guidance_scale=opt_scale,
+        unconditional_conditioning=uc,
+        img_callback=img_callback,
+        mask=mask,
+        x_T=x_T,
+        sampler = 'ddim'
+    )
+
+    yield from samples_ddim
+
+def move_fs_to_cpu():
+    if device != "cpu":
+        mem = torch.cuda.memory_allocated() / 1e6
+        modelFS.to("cpu")
+        while torch.cuda.memory_allocated() / 1e6 >= mem:
+            time.sleep(1)
+
+def gc():
+    if device == 'cpu':
+        return
+
+    torch.cuda.empty_cache()
+    torch.cuda.ipc_collect()
+
+# internal
+
+def chunk(it, size):
+    it = iter(it)
+    return iter(lambda: tuple(islice(it, size)), ())
+
+
+def load_model_from_config(ckpt, verbose=False):
+    print(f"Loading model from {ckpt}")
+    pl_sd = torch.load(ckpt, map_location="cpu")
+    if "global_step" in pl_sd:
+        print(f"Global Step: {pl_sd['global_step']}")
+    sd = pl_sd["state_dict"]
+    return sd
+
+# utils
+class UserInitiatedStop(Exception):
+    pass
+
+def load_img(img_str, w0, h0):
+    image = base64_str_to_img(img_str).convert("RGB")
+    w, h = image.size
+    print(f"loaded input image of size ({w}, {h}) from base64")
+    if h0 is not None and w0 is not None:
+        h, w = h0, w0
+
+    w, h = map(lambda x: x - x % 64, (w, h))  # resize to integer multiple of 64
+    image = image.resize((w, h), resample=Image.Resampling.LANCZOS)
+    image = np.array(image).astype(np.float32) / 255.0
+    image = image[None].transpose(0, 3, 1, 2)
+    image = torch.from_numpy(image)
+    return 2.*image - 1.
+
+def load_mask(mask_str, h0, w0, newH, newW, invert=False):
+    image = base64_str_to_img(mask_str).convert("RGB")
+    w, h = image.size
+    print(f"loaded input mask of size ({w}, {h})")
+
+    if invert:
+        print("inverted")
+        image = ImageOps.invert(image)
+        # where_0, where_1 = np.where(image == 0), np.where(image == 255)
+        # image[where_0], image[where_1] = 255, 0
+
+    if h0 is not None and w0 is not None:
+        h, w = h0, w0
+
+    w, h = map(lambda x: x - x % 64, (w, h))  # resize to integer multiple of 64
+
+    print(f"New mask size ({w}, {h})")
+    image = image.resize((newW, newH), resample=Image.Resampling.LANCZOS)
+    image = np.array(image)
+
+    image = image.astype(np.float32) / 255.0
+    image = image[None].transpose(0, 3, 1, 2)
+    image = torch.from_numpy(image)
+    return image
+
+# https://stackoverflow.com/a/61114178
+def img_to_base64_str(img):
+    buffered = BytesIO()
+    img.save(buffered, format="PNG")
+    buffered.seek(0)
+    img_byte = buffered.getvalue()
+    img_str = "data:image/png;base64," + base64.b64encode(img_byte).decode()
+    return img_str
+
+def base64_str_to_img(img_str):
+    img_str = img_str[len("data:image/png;base64,"):]
+    data = base64.b64decode(img_str)
+    buffered = BytesIO(data)
+    img = Image.open(buffered)
+    return img

ui/server.py

@@ -0,0 +1,223 @@
+import json
+import traceback
+
+import sys
+import os
+
+SCRIPT_DIR = os.getcwd()
+print('started in ', SCRIPT_DIR)
+
+SD_UI_DIR = os.getenv('SD_UI_PATH', None)
+sys.path.append(os.path.dirname(SD_UI_DIR))
+
+CONFIG_DIR = os.path.join(SD_UI_DIR, '..', 'scripts')
+
+OUTPUT_DIRNAME = "Stable Diffusion UI" # in the user's home folder
+
+from fastapi import FastAPI, HTTPException
+from fastapi.staticfiles import StaticFiles
+from starlette.responses import FileResponse, StreamingResponse
+from pydantic import BaseModel
+import logging
+
+from sd_internal import Request, Response
+
+app = FastAPI()
+
+model_loaded = False
+model_is_loading = False
+
+modifiers_cache = None
+outpath = os.path.join(os.path.expanduser("~"), OUTPUT_DIRNAME)
+
+# defaults from https://huggingface.co/blog/stable_diffusion
+class ImageRequest(BaseModel):
+    session_id: str = "session"
+    prompt: str = ""
+    init_image: str = None # base64
+    mask: str = None # base64
+    num_outputs: int = 1
+    num_inference_steps: int = 50
+    guidance_scale: float = 7.5
+    width: int = 512
+    height: int = 512
+    seed: int = 42
+    prompt_strength: float = 0.8
+    sampler: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
+    # allow_nsfw: bool = False
+    save_to_disk_path: str = None
+    turbo: bool = True
+    use_cpu: bool = False
+    use_full_precision: bool = False
+    use_face_correction: str = None # or "GFPGANv1.3"
+    use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
+    show_only_filtered_image: bool = False
+
+    stream_progress_updates: bool = False
+    stream_image_progress: bool = False
+
+class SetAppConfigRequest(BaseModel):
+    update_branch: str = "main"
+
+app.mount('/media', StaticFiles(directory=os.path.join(SD_UI_DIR, 'media/')), name="media")
+
+@app.get('/')
+def read_root():
+    headers = {"Cache-Control": "no-cache, no-store, must-revalidate", "Pragma": "no-cache", "Expires": "0"}
+    return FileResponse(os.path.join(SD_UI_DIR, 'index.html'), headers=headers)
+
+@app.get('/ping')
+async def ping():
+    global model_loaded, model_is_loading
+
+    try:
+        if model_loaded:
+            return {'OK'}
+
+        if model_is_loading:
+            return {'ERROR'}
+
+        model_is_loading = True
+
+        from sd_internal import runtime
+        runtime.load_model_ckpt(ckpt_to_use="sd-v1-4")
+
+        model_loaded = True
+        model_is_loading = False
+
+        return {'OK'}
+    except Exception as e:
+        print(traceback.format_exc())
+        return HTTPException(status_code=500, detail=str(e))
+
+@app.post('/image')
+def image(req : ImageRequest):
+    from sd_internal import runtime
+
+    r = Request()
+    r.session_id = req.session_id
+    r.prompt = req.prompt
+    r.init_image = req.init_image
+    r.mask = req.mask
+    r.num_outputs = req.num_outputs
+    r.num_inference_steps = req.num_inference_steps
+    r.guidance_scale = req.guidance_scale
+    r.width = req.width
+    r.height = req.height
+    r.seed = req.seed
+    r.prompt_strength = req.prompt_strength
+    r.sampler = req.sampler
+    # r.allow_nsfw = req.allow_nsfw
+    r.turbo = req.turbo
+    r.use_cpu = req.use_cpu
+    r.use_full_precision = req.use_full_precision
+    r.save_to_disk_path = req.save_to_disk_path
+    r.use_upscale: str = req.use_upscale
+    r.use_face_correction = req.use_face_correction
+    r.show_only_filtered_image = req.show_only_filtered_image
+
+    r.stream_progress_updates = True # the underlying implementation only supports streaming
+    r.stream_image_progress = req.stream_image_progress
+
+    try:
+        if not req.stream_progress_updates:
+            r.stream_image_progress = False
+
+        res = runtime.mk_img(r)
+
+        if req.stream_progress_updates:
+            return StreamingResponse(res, media_type='application/json')
+        else: # compatibility mode: buffer the streaming responses, and return the last one
+            last_result = None
+
+            for result in res:
+                last_result = result
+
+            return json.loads(last_result)
+    except Exception as e:
+        print(traceback.format_exc())
+        return HTTPException(status_code=500, detail=str(e))
+
+@app.get('/image/stop')
+def stop():
+    try:
+        if model_is_loading:
+            return {'ERROR'}
+
+        from sd_internal import runtime
+        runtime.stop_processing = True
+
+        return {'OK'}
+    except Exception as e:
+        print(traceback.format_exc())
+        return HTTPException(status_code=500, detail=str(e))
+
+@app.get('/image/tmp/{session_id}/{img_id}')
+def get_image(session_id, img_id):
+    from sd_internal import runtime
+    buf = runtime.temp_images[session_id + '/' + img_id]
+    buf.seek(0)
+    return StreamingResponse(buf, media_type='image/jpeg')
+
+@app.post('/app_config')
+async def setAppConfig(req : SetAppConfigRequest):
+    try:
+        config = {
+            'update_branch': req.update_branch
+        }
+
+        config_json_str = json.dumps(config)
+        config_bat_str = f'@set update_branch={req.update_branch}'
+        config_sh_str = f'export update_branch={req.update_branch}'
+
+        config_json_path = os.path.join(CONFIG_DIR, 'config.json')
+        config_bat_path = os.path.join(CONFIG_DIR, 'config.bat')
+        config_sh_path = os.path.join(CONFIG_DIR, 'config.sh')
+
+        with open(config_json_path, 'w') as f:
+            f.write(config_json_str)
+
+        with open(config_bat_path, 'w') as f:
+            f.write(config_bat_str)
+
+        with open(config_sh_path, 'w') as f:
+            f.write(config_sh_str)
+
+        return {'OK'}
+    except Exception as e:
+        print(traceback.format_exc())
+        return HTTPException(status_code=500, detail=str(e))
+
+@app.get('/app_config')
+def getAppConfig():
+    try:
+        config_json_path = os.path.join(CONFIG_DIR, 'config.json')
+
+        if not os.path.exists(config_json_path):
+            return HTTPException(status_code=500, detail="No config file")
+
+        with open(config_json_path, 'r') as f:
+            config_json_str = f.read()
+            config = json.loads(config_json_str)
+            return config
+    except Exception as e:
+        print(traceback.format_exc())
+        return HTTPException(status_code=500, detail=str(e))
+
+@app.get('/modifiers.json')
+def read_modifiers():
+    return FileResponse(os.path.join(SD_UI_DIR, 'modifiers.json'))
+
+@app.get('/output_dir')
+def read_home_dir():
+    return {outpath}
+
+# don't log /ping requests
+class HealthCheckLogFilter(logging.Filter):
+    def filter(self, record: logging.LogRecord) -> bool:
+        return record.getMessage().find('/ping') == -1
+
+logging.getLogger('uvicorn.access').addFilter(HealthCheckLogFilter())
+
+# start the browser ui
+import webbrowser; webbrowser.open('http://localhost:9000')