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jquery-confirm
==============
https://craftpip.github.io/jquery-confirm/
jquery-confirm is licensed under the MIT license:
The MIT License (MIT)
Copyright (c) 2019 Boniface Pereira
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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# What's new?
## v2.4
### Major Changes
- **Allow reordering the task queue** (by dragging and dropping tasks). Thanks @madrang
- **Automatic scanning for malicious model files** - using `picklescan`, and support for `safetensor` model format. Thanks @JeLuf
- **Image Editor** - for drawing simple images for guiding the AI. Thanks @mdiller
- **Use pre-trained hypernetworks** - for improving the quality of images. Thanks @C0bra5
- **Support for custom VAE models**. You can place your VAE files in the `models/vae` folder, and refresh the browser page to use them. More info: https://github.com/cmdr2/stable-diffusion-ui/wiki/VAE-Variational-Auto-Encoder
- **Experimental support for multiple GPUs!** It should work automatically. Just open one browser tab per GPU, and spread your tasks across your GPUs. For e.g. open our UI in two browser tabs if you have two GPUs. You can customize which GPUs it should use in the "Settings" tab, otherwise let it automatically pick the best GPUs. Thanks @madrang . More info: https://github.com/cmdr2/stable-diffusion-ui/wiki/Run-on-Multiple-GPUs
- **Cleaner UI design** - Show settings and help in new tabs, instead of dropdown popups (which were buggy). Thanks @mdiller
- **Progress bar.** Thanks @mdiller
- **Custom Image Modifiers** - You can now save your custom image modifiers! Your saved modifiers can include special characters like `{}, (), [], |`
- Drag and Drop **text files generated from previously saved images**, and copy settings to clipboard. Thanks @madrang
- Paste settings from clipboard. Thanks @JeLuf
- Bug fixes to reduce the chances of tasks crashing during long multi-hour runs (chrome can put long-running background tabs to sleep). Thanks @JeLuf and @madrang
- **Improved documentation.** Thanks @JeLuf and @jsuelwald
- Improved the codebase for dealing with system settings and UI settings. Thanks @mdiller
- Help instructions next to some setttings, and in the tab
- Show system info in the settings tab
- Keyboard shortcut: Ctrl+Enter to start a task
- Configuration to prevent the browser from opening on startup
- Lots of minor bug fixes
- A `What's New?` tab in the UI
- Ask for a confimation before clearing the results pane or stopping a render task. The dialog can be skipped by holding down the shift key while clicking on the button.
- Show the network addresses of the server in the systems setting dialog
- Support loading models in the safetensor format, for improved safety
### Detailed changelog
* 2.4.20 - 22 Dec 2022 - `Pause All` button to pause all the pending tasks. Thanks @JeLuf
* 2.4.20 - 22 Dec 2022 - `Undo`/`Redo` buttons in the image editor. Thanks @JeLuf
* 2.4.20 - 22 Dec 2022 - Drag handle to reorder the tasks. This fixed a bug where the metadata was no longer selectable (for copying). Thanks @JeLuf
* 2.4.19 - 17 Dec 2022 - Add Undo/Redo buttons in the Image Editor. Thanks @JeLuf
* 2.4.19 - 10 Dec 2022 - Show init img in task list
* 2.4.19 - 7 Dec 2022 - Use pre-trained hypernetworks while generating images. Thanks @C0bra5
* 2.4.19 - 6 Dec 2022 - Allow processing new tasks first. Thanks @madrang
* 2.4.19 - 6 Dec 2022 - Allow reordering the task queue (by dragging tasks). Thanks @madrang
* 2.4.19 - 6 Dec 2022 - Re-organize the code, to make it easier to write user plugins. Thanks @madrang
* 2.4.18 - 5 Dec 2022 - Make JPEG Output quality user controllable. Thanks @JeLuf
* 2.4.18 - 5 Dec 2022 - Support loading models in the safetensor format, for improved safety. Thanks @JeLuf
* 2.4.18 - 1 Dec 2022 - Image Editor, for drawing simple images for guiding the AI. Thanks @mdiller
* 2.4.18 - 1 Dec 2022 - Disable an image modifier temporarily by right-clicking it. Thanks @patriceac
* 2.4.17 - 30 Nov 2022 - Scroll to generated image. Thanks @patriceac
* 2.4.17 - 30 Nov 2022 - Show the network addresses of the server in the systems setting dialog. Thanks @JeLuf
* 2.4.17 - 30 Nov 2022 - Fix a bug where GFPGAN wouldn't work properly when multiple GPUs tried to run it at the same time. Thanks @madrang
* 2.4.17 - 30 Nov 2022 - Confirm before stopping or clearing all the tasks. Thanks @JeLuf
* 2.4.16 - 29 Nov 2022 - Bug fixes for SD 2.0 - remove the need for patching, default to SD 1.4 model if trying to load an SD2 model in SD1.4.
* 2.4.15 - 25 Nov 2022 - Experimental support for SD 2.0. Uses lots of memory, not optimized, probably GPU-only.
* 2.4.14 - 22 Nov 2022 - Change the backend to a custom fork of Stable Diffusion
* 2.4.13 - 21 Nov 2022 - Change the modifier weight via mouse wheel, drag to reorder selected modifiers, and some more modifier-related fixes. Thanks @patriceac
* 2.4.12 - 21 Nov 2022 - Another fix for improving how long images take to generate. Reduces the time taken for an enqueued task to start processing.
* 2.4.11 - 21 Nov 2022 - Installer improvements: avoid crashing if the username contains a space or special characters, allow moving/renaming the folder after installation on Windows, whitespace fix on git apply
* 2.4.11 - 21 Nov 2022 - Validate inputs before submitting the Image request
* 2.4.11 - 19 Nov 2022 - New system settings to manage the network config (port number and whether to only listen on localhost)
* 2.4.11 - 19 Nov 2022 - Address a regression in how long images take to generate. Use the previous code for moving a model to CPU. This improves things by a second or two per image, but we still have a regression (investigating).
* 2.4.10 - 18 Nov 2022 - Textarea for negative prompts. Thanks @JeLuf
* 2.4.10 - 18 Nov 2022 - Improved design for Settings, and rounded toggle buttons instead of checkboxes for a more modern look. Thanks @mdiller
* 2.4.9 - 18 Nov 2022 - Add Picklescan - a scanner for malicious model files. If it finds a malicious file, it will halt the web application and alert the user. Thanks @JeLuf
* 2.4.8 - 18 Nov 2022 - A `Use these settings` button to use the settings from a previously generated image task. Thanks @patriceac
* 2.4.7 - 18 Nov 2022 - Don't crash if a VAE file fails to load
* 2.4.7 - 17 Nov 2022 - Fix a bug where Face Correction (GFPGAN) would fail on cuda:N (i.e. GPUs other than cuda:0), as well as fail on CPU if the system had an incompatible GPU.
* 2.4.6 - 16 Nov 2022 - Fix a regression in VRAM usage during startup, which caused 'Out of Memory' errors when starting on GPUs with 4gb (or less) VRAM
* 2.4.5 - 16 Nov 2022 - Add checkbox for "Open browser on startup".
* 2.4.5 - 16 Nov 2022 - Add a directory for core plugins that ship with Stable Diffusion UI by default.
* 2.4.5 - 16 Nov 2022 - Add a "What's New?" tab as a core plugin, which fetches the contents of CHANGES.md from the app's release branch.

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# For developers:
If you would like to contribute to this project, there is a discord for discussion:
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) Install the project to a new location using the [usual installation process](https://github.com/cmdr2/stable-diffusion-ui#installation), e.g. to `/projects/stable-diffusion-ui-archive`
2) Start the newly installed project, and check that you can view and generate images on `localhost:9000`
3) Next, please clone the project repository using `git clone` (e.g. to `/projects/stable-diffusion-ui-repo`)
4) Close the server (started in step 2), and edit `/projects/stable-diffusion-ui-archive/scripts/on_env_start.sh` (or `on_env_start.bat`)
5) Comment out the lines near the bottom that copies the `files/ui` folder, e.g:
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`
```
@ -32,20 +33,23 @@ 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
```
6) Next, comment out the line at the top of `/projects/stable-diffusion-ui-archive/scripts/on_sd_start.sh` (or `on_sd_start.bat`) that copies `on_env_start`. For e.g. `@rem @copy sd-ui-files\scripts\on_env_start.bat scripts\ /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 /J \projects\stable-diffusion-ui-archive\ui \projects\stable-diffusion-ui-repo\ui` (link name first, source repo dir second)
9) Run the project again (like in step 2) and ensure you can still use the UI.
`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.
11) Please update CHANGES.md in your pull requests.
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. Run `build.bat` or `./build.sh` depending on whether you're in Windows or Linux.
2. Make a new GitHub release and upload the Windows and Linux installer builds created inside the `dist` folder.
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.

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Scripts to be used with the Nullsoft Scriptable Installation System

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; Script generated by the HM NIS Edit Script Wizard.
Target x86-unicode
Unicode True
!AddPluginDir /x86-unicode "."
; HM NIS Edit Wizard helper defines
!define PRODUCT_NAME "Stable Diffusion UI"
!define PRODUCT_VERSION "Installer 2.35"
!define PRODUCT_PUBLISHER "cmdr2 and contributors"
!define PRODUCT_WEB_SITE "https://stable-diffusion-ui.github.io"
!define PRODUCT_DIR_REGKEY "Software\Microsoft\Cmdr2\App Paths\installer.exe"
; MUI 1.67 compatible ------
!include "MUI.nsh"
!include "LogicLib.nsh"
!include "nsDialogs.nsh"
Var Dialog
Var Label
Var Button
Var InstDirLen
Var LongPathsEnabled
Var AccountType
;---------------------------------------------------------------------------------------------------------
; This function returns the number of spaces in a string.
; The string is passed on the stack (using Push $STRING)
; The result is also returned on the stack and can be consumed with Pop $var
; https://nsis.sourceforge.io/Check_for_spaces_in_a_directory_path
Function CheckForSpaces
Exch $R0
Push $R1
Push $R2
Push $R3
StrCpy $R1 -1
StrCpy $R3 $R0
StrCpy $R0 0
loop:
StrCpy $R2 $R3 1 $R1
IntOp $R1 $R1 - 1
StrCmp $R2 "" done
StrCmp $R2 " " 0 loop
IntOp $R0 $R0 + 1
Goto loop
done:
Pop $R3
Pop $R2
Pop $R1
Exch $R0
FunctionEnd
;---------------------------------------------------------------------------------------------------------
; The function DirectoryLeave is called after the user chose the installation directory.
; If it calls "abort", the user is sent back to choose a different directory.
Function DirectoryLeave
; check whether the installation directory path is longer than 30 characters.
; If yes, we suggest to the user to enable long filename support
;----------------------------------------------------------------------------
StrLen $InstDirLen "$INSTDIR"
; Check whether the registry key that allows for >260 characters in a path name is set
ReadRegStr $LongPathsEnabled HKLM "SYSTEM\CurrentControlSet\Control\FileSystem" "LongPathsEnabled"
${If} $InstDirLen > 30
${AndIf} $LongPathsEnabled == "0"
; Check whether we're in the Admin group
UserInfo::GetAccountType
Pop $AccountType
${If} $AccountType == "Admin"
${AndIf} ${Cmd} `MessageBox MB_YESNO|MB_ICONQUESTION 'The path name is too long. $\n$\nYou can either enable long file name support in Windows,$\nor you can go back and choose a different path.$\n$\nFor details see: shorturl.at/auBD1$\n$\nEnable long path name support in Windows?' IDYES`
; Enable long path names
WriteRegDWORD HKLM "SYSTEM\CurrentControlSet\Control\FileSystem" "LongPathsEnabled" 1
${Else}
MessageBox MB_OK|MB_ICONEXCLAMATION "Installation path name too long. The installation path must not have more than 30 characters."
abort
${EndIf}
${EndIf}
; Check for spaces in the installation directory path.
; ----------------------------------------------------
; $R0 = CheckForSpaces( $INSTDIR )
Push $INSTDIR # Input string (install path).
Call CheckForSpaces
Pop $R0 # The function returns the number of spaces found in the input string.
; Check if any spaces exist in $INSTDIR.
${If} $R0 != 0
; Plural if more than 1 space in $INSTDIR.
; If $R0 == 1: $R1 = ""; else: $R1 = "s"
StrCmp $R0 1 0 +3
StrCpy $R1 ""
Goto +2
StrCpy $R1 "s"
; Show message box then take the user back to the Directory page.
MessageBox MB_OK|MB_ICONEXCLAMATION "Error: The Installaton directory \
has $R0 space character$R1.$\nPlease choose an installation directory without space characters."
Abort
${EndIf}
; Check for NTFS filesystem. Installations on FAT fail.
; -----------------------------------------------------
StrCpy $5 $INSTDIR 3
System::Call 'Kernel32::GetVolumeInformation(t "$5",t,i ${NSIS_MAX_STRLEN},*i,*i,*i,t.r1,i ${NSIS_MAX_STRLEN})i.r0'
${If} $0 <> 0
${AndIf} $1 == "NTFS"
MessageBox mb_ok "$5 has filesystem type '$1'.$\nOnly NTFS filesystems are supported.$\nPlease choose a different drive."
Abort
${EndIf}
FunctionEnd
;---------------------------------------------------------------------------------------------------------
; Open the MS download page in a browser and enable the [Next] button
Function MSMediaFeaturepack
ExecShell "open" "https://www.microsoft.com/en-us/software-download/mediafeaturepack"
GetDlgItem $0 $HWNDPARENT 1
EnableWindow $0 1
FunctionEnd
;---------------------------------------------------------------------------------------------------------
; Install the MS Media Feature Pack, if it is missing (e.g. on Windows 10 N)
Function MediaPackDialog
!insertmacro MUI_HEADER_TEXT "Windows Media Feature Pack" "Required software module is missing"
; Skip this dialog if mf.dll is installed
${If} ${FileExists} "$WINDIR\system32\mf.dll"
Abort
${EndIf}
nsDialogs::Create 1018
Pop $Dialog
${If} $Dialog == error
Abort
${EndIf}
${NSD_CreateLabel} 0 0 100% 48u "The Windows Media Feature Pack is missing on this computer. It is required for the Stable Diffusion UI.$\nYou can continue the installation after installing the Windows Media Feature Pack."
Pop $Label
${NSD_CreateButton} 10% 49u 80% 12u "Download Meda Feature Pack from Microsoft"
Pop $Button
GetFunctionAddress $0 MSMediaFeaturePack
nsDialogs::OnClick $Button $0
GetDlgItem $0 $HWNDPARENT 1
EnableWindow $0 0
nsDialogs::Show
FunctionEnd
;---------------------------------------------------------------------------------------------------------
; MUI Settings
;---------------------------------------------------------------------------------------------------------
!define MUI_ABORTWARNING
!define MUI_ICON "sd.ico"
!define MUI_WELCOMEFINISHPAGE_BITMAP "astro.bmp"
; Welcome page
!define MUI_WELCOMEPAGE_TEXT "This installer will guide you through the installation of Stable Diffusion UI.$\n$\n\
Click Next to continue."
!insertmacro MUI_PAGE_WELCOME
Page custom MediaPackDialog
; License page
!insertmacro MUI_PAGE_LICENSE "..\LICENSE"
!insertmacro MUI_PAGE_LICENSE "..\CreativeML Open RAIL-M License"
; Directory page
!define MUI_PAGE_CUSTOMFUNCTION_LEAVE "DirectoryLeave"
!insertmacro MUI_PAGE_DIRECTORY
; Instfiles page
!insertmacro MUI_PAGE_INSTFILES
; Finish page
!define MUI_FINISHPAGE_RUN "$INSTDIR\Start Stable Diffusion UI.cmd"
!insertmacro MUI_PAGE_FINISH
; Language files
!insertmacro MUI_LANGUAGE "English"
;---------------------------------------------------------------------------------------------------------
; MUI end
;---------------------------------------------------------------------------------------------------------
Name "${PRODUCT_NAME} ${PRODUCT_VERSION}"
OutFile "Install Stable Diffusion UI.exe"
InstallDir "C:\Stable-Diffusion-UI\"
InstallDirRegKey HKLM "${PRODUCT_DIR_REGKEY}" ""
ShowInstDetails show
;---------------------------------------------------------------------------------------------------------
; List of files to be installed
Section "MainSection" SEC01
SetOutPath "$INSTDIR"
File "..\CreativeML Open RAIL-M License"
File "..\How to install and run.txt"
File "..\LICENSE"
File "..\Start Stable Diffusion UI.cmd"
SetOutPath "$INSTDIR\scripts"
File "..\scripts\bootstrap.bat"
File "..\scripts\install_status.txt"
File "..\scripts\on_env_start.bat"
File "C:\windows\system32\curl.exe"
CreateDirectory "$INSTDIR\profile"
CreateDirectory "$SMPROGRAMS\Stable Diffusion UI"
CreateShortCut "$SMPROGRAMS\Stable Diffusion UI\Start Stable Diffusion UI.lnk" "$INSTDIR\Start Stable Diffusion UI.cmd"
SectionEnd
;---------------------------------------------------------------------------------------------------------
; Our installer only needs 25 KB, but once it has run, we need 25 GB
; So we need to overwrite the automatically detected space requirements.
; https://nsis.sourceforge.io/Docs/Chapter4.html#4.9.13.7
; The example in section 4.9.13.7 seems to be wrong: the number
; needs to be provided in Kilobytes.
Function .onInit
; Set required size of section 'SEC01' to 25 Gigabytes
SectionSetSize ${SEC01} 26214400
; Check system meory size. We need at least 8GB
; ----------------------------------------------------
; allocate a few bytes of memory
System::Alloc 64
Pop $1
; Retrieve HW info from the Windows Kernel
System::Call "*$1(i64)"
System::Call "Kernel32::GlobalMemoryStatusEx(i r1)"
; unpack the data into $R2 - $R10
System::Call "*$1(i.r2, i.r3, l.r4, l.r5, l.r6, l.r7, l.r8, l.r9, l.r10)"
# free up the memory
System::Free $1
; Result mapping:
; "Structure size: $2 bytes"
; "Memory load: $3%"
; "Total physical memory: $4 bytes"
; "Free physical memory: $5 bytes"
; "Total page file: $6 bytes"
; "Free page file: $7 bytes"
; "Total virtual: $8 bytes"
; "Free virtual: $9 bytes"
; Mem size in MB
System::Int64Op $4 / 1048576
Pop $4
${If} $4 < "8000"
MessageBox MB_OK|MB_ICONEXCLAMATION "Warning!$\n$\nYour system has less than 8GB of memory (RAM).$\n$\n\
You can still try to install Stable Diffusion UI,$\nbut it might have problems to start, or run$\nvery slowly."
${EndIf}
FunctionEnd
;Section -Post
; WriteRegStr HKLM "${PRODUCT_DIR_REGKEY}" "" "$INSTDIR\installer.exe"
;SectionEnd

190
README.md
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# Stable Diffusion UI
### The easiest way to install and use [Stable Diffusion](https://github.com/CompVis/stable-diffusion) on your own computer. Does not require technical knowledge, does not require pre-installed software. 1-click install, powerful features, friendly community.
[![Discord Server](https://img.shields.io/discord/1014774730907209781?label=Discord)](https://discord.com/invite/u9yhsFmEkB) (for support, and development discussion) | [Troubleshooting guide for common problems](https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting)
### New:
Experimental support for Stable Diffusion 2.0 is available in beta!
----
# Step 1: Download and prepare the installer
Click the download button for your operating system:
# 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="https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.4.13/stable-diffusion-ui-windows.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-win.png" width="200" /></a>
<a href="https://github.com/cmdr2/stable-diffusion-ui#installation"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-linux.png" width="200" /></a>
<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>
## On Windows:
1. Unzip/extract the folder `stable-diffusion-ui` which should be in your downloads folder, unless you changed your default downloads destination.
2. Move the `stable-diffusion-ui` folder to your `C:` drive (or any other drive like `D:`, at the top root level). `C:\stable-diffusion-ui` or `D:\stable-diffusion-ui` as examples. This will avoid a common problem with Windows (file path length limits).
## On Linux:
1. Unzip/extract the folder `stable-diffusion-ui` which should be in your downloads folder, unless you changed your default downloads destination.
2. Open a terminal window, and navigate to the `stable-diffusion-ui` directory.
[![Discord Server](https://img.shields.io/discord/1014774730907209781?label=Discord)](https://discord.com/invite/u9yhsFmEkB) (for support, and development discussion) | [Troubleshooting guide for common problems](Troubleshooting.md)
# Step 2: Run the program
## On Windows:
Double-click `Start Stable Diffusion UI.cmd`.
If Windows SmartScreen prevents you from running the program click `More info` and then `Run anyway`.
## On Linux:
Run `./start.sh` (or `bash start.sh`) in a terminal.
️‍🔥🎉 **New!** Live Preview, More Samplers, In-Painting, Face Correction (GFPGAN) and Upscaling (RealESRGAN) have been added!
The installer will take care of whatever is needed. If you face any problems, you can join the friendly [Discord community](https://discord.com/invite/u9yhsFmEkB) and ask for assistance.
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.
# Step 3: There is no Step 3. It's that simple!
**To Uninstall:** Just delete the `stable-diffusion-ui` folder to uninstall all the downloaded packages.
----
# Easy for new users, powerful features for advanced users
## Features:
### User experience
- **Hassle-free installation**: Does not require technical knowledge, does not require pre-installed software. Just download and run!
- **Clutter-free UI**: A friendly and simple UI, while providing a lot of powerful features.
### Image generation
- **Supports**: "*Text to Image*" and "*Image to Image*".
- **In-Painting**: Specify areas of your image to paint into.
- **Simple Drawing Tool**: Draw basic images to guide the AI, without needing an external drawing program.
- **Face Correction (GFPGAN)**
- **Upscaling (RealESRGAN)**
- **Loopback**: Use the output image as the input image for the next img2img task.
- **Negative Prompt**: Specify aspects of the image to *remove*.
- **Attention/Emphasis**: () in the prompt increases the model's attention to enclosed words, and [] decreases it.
- **Weighted Prompts**: Use weights for specific words in your prompt to change their importance, e.g. `red:2.4 dragon:1.2`.
- **Prompt Matrix**: Quickly create multiple variations of your prompt, e.g. `a photograph of an astronaut riding a horse | illustration | cinematic lighting`.
- **Lots of Samplers**: ddim, plms, heun, euler, euler_a, dpm2, dpm2_a, lms.
- **1-click Upscale/Face Correction**: Upscale or correct an image after it has been generated.
- **Make Similar Images**: Click to generate multiple variations of a generated image.
- **NSFW Setting**: A setting in the UI to control *NSFW content*.
- **JPEG/PNG output**: Multiple file formats.
### Advanced features
- **Custom Models**: Use your own `.ckpt` or `.safetensors` file, by placing it inside the `models/stable-diffusion` folder!
- **Stable Diffusion 2.0 support (experimental)**: available in beta channel.
- **Use custom VAE models**
- **Use pre-trained Hypernetworks**
- **UI Plugins**: Choose from a growing list of [community-generated UI plugins](https://github.com/cmdr2/stable-diffusion-ui/wiki/UI-Plugins), or write your own plugin to add features to the project!
### Performance and security
- **Low Memory Usage**: Creates 512x512 images with less than 4GB of GPU RAM!
- **Use CPU setting**: If you don't have a compatible graphics card, but still want to run it on your CPU.
- **Multi-GPU support**: Automatically spreads your tasks across multiple GPUs (if available), for faster performance!
- **Auto scan for malicious models**: Uses picklescan to prevent malicious models.
- **Safetensors support**: Support loading models in the safetensor format, for improved safety.
- **Auto-updater**: Gets you the latest improvements and bug-fixes to a rapidly evolving project.
- **Developer Console**: A developer-mode for those who want to modify their Stable Diffusion code, and edit the conda environment.
### Usability:
- **Live Preview**: See the image as the AI is drawing it.
- **Task Queue**: Queue up all your ideas, without waiting for the current task to finish.
# 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:** ddim, plms, heun, euler, euler_a, dpm2, dpm2_a, lms
- **Image Modifiers**: A library of *modifier tags* like *"Realistic"*, *"Pencil Sketch"*, *"ArtStation"* etc. Experiment with various styles quickly.
- **Multiple Prompts File**: Queue multiple prompts by entering one prompt per line, or by running a text file.
- **Save generated images to disk**: Save your images to your PC!
- **UI Themes**: Customize the program to your liking.
- **New UI**: with cleaner design
- **Waifu Model Support**: Just replace the `stable-diffusion\sd-v1-4.ckpt` file after installation with the Waifu model
- 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!
**(and a lot more)**
----
## Easy for new users:
![Screenshot of the initial UI](media/shot-v10-simple.jpg?raw=true)
## Powerful features for advanced users:
![Screenshot of advanced settings](media/shot-v10.jpg?raw=true)
![Screenshot of advanced settings](media/shot-v9.jpg?raw=true)
## Live Preview
Useful for judging (and stopping) an image quickly, without waiting for it to finish rendering.
![live-512](https://user-images.githubusercontent.com/844287/192097249-729a0a1e-a677-485e-9ccc-16a9e848fabe.gif)
## Task Queue
![Screenshot of task queue](media/task-queue-v1.jpg?raw=true)
# System Requirements
1. Windows 10/11, or Linux. Experimental support for Mac is coming soon.
2. An NVIDIA graphics card, preferably with 4GB or more of VRAM. If you don't have a compatible graphics card, it'll automatically run in the slower "CPU Mode".
3. Minimum 8 GB of RAM and 25GB of disk space.
2. An NVIDIA graphics card, preferably with 4GB 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.
You don't need to install or struggle with Python, Anaconda, Docker etc. The installer will take care of whatever is needed.
You do not need anything else. You do not need WSL, Docker or Conda. The installer will take care of it.
----
# Installation
1. **Download** [for Windows](https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.16/stable-diffusion-ui-win64.zip) or [for Linux](https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.16/stable-diffusion-ui-linux.tar.xz).
# How to use?
Please refer to our [guide](https://github.com/cmdr2/stable-diffusion-ui/wiki/How-to-Use) to understand how to use the features in this UI.
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.
# Usage
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.
2. Press `Make Image`. This will take some time, depending on your system's processing power.
3. See the image generated using your prompt.
## With an image
1. Click `Browse..` next to `Initial Image`. Select your desired image.
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 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? 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).
# Image 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 'Image 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-v6.jpg?raw=true)
# System Settings
The system settings are reachable via the cogwheel symbol on the top right. It can be used to configure whether all generated images should
saved be automically, or to tune the Stable Diffusion image generation.
![Screenshot of advanced settings](media/system-settings-v2.jpg?raw=true)
# Image Modifiers
![Screenshot of advanced settings](media/modifiers-v1.jpg?raw=true)
# Bugs reports and code contributions welcome
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).
We could really use help on these aspects (click to view tasks that need your help):
* [User Interface](https://github.com/users/cmdr2/projects/1/views/1)
* [Engine](https://github.com/users/cmdr2/projects/3/views/1)
* [Installer](https://github.com/users/cmdr2/projects/4/views/1)
* [Documentation](https://github.com/users/cmdr2/projects/5/views/1)
If you have any code contributions in mind, please feel free to say Hi to us on the [discord server](https://discord.com/invite/u9yhsFmEkB). We use the Discord server for development-related discussions, and for helping users.
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.
The license of this software forbids you from sharing any content that:
- Violates any laws.
- Produces any harm to a person or persons.
- Disseminates (spreads) any personal information that would be meant for harm.
- Spreads misinformation.
- Target vulnerable groups.
For the full list of restrictions please read [the License](LICENSE). You agree to these terms by using this software.
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.

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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))

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@ -8,40 +8,40 @@
set /p answer=Are you a developer of this project (Y/N)?
if /i "%answer:~,1%" NEQ "Y" exit /b
mkdir dist\win\stable-diffusion-ui\scripts
@REM mkdir dist\linux-mac\stable-diffusion-ui\scripts
@set PYTHONNOUSERSITE=1
@rem copy the installer files for Windows
@mkdir dist\stable-diffusion-ui
copy scripts\on_env_start.bat dist\win\stable-diffusion-ui\scripts\
copy scripts\bootstrap.bat dist\win\stable-diffusion-ui\scripts\
copy "scripts\Start Stable Diffusion UI.cmd" dist\win\stable-diffusion-ui\
copy LICENSE dist\win\stable-diffusion-ui\
copy "CreativeML Open RAIL-M License" dist\win\stable-diffusion-ui\
copy "How to install and run.txt" dist\win\stable-diffusion-ui\
echo. > dist\win\stable-diffusion-ui\scripts\install_status.txt
@echo "Downloading components for the installer.."
@rem copy the installer files for Linux and Mac
@call conda env create --prefix installer -f environment.yaml
@call conda activate .\installer
@REM copy scripts\on_env_start.sh dist\linux-mac\stable-diffusion-ui\scripts\
@REM copy scripts\bootstrap.sh dist\linux-mac\stable-diffusion-ui\scripts\
@REM copy scripts\start.sh dist\linux-mac\stable-diffusion-ui\
@REM copy LICENSE dist\linux-mac\stable-diffusion-ui\
@REM copy "CreativeML Open RAIL-M License" dist\linux-mac\stable-diffusion-ui\
@REM copy "How to install and run.txt" dist\linux-mac\stable-diffusion-ui\
@REM echo. > dist\linux-mac\stable-diffusion-ui\scripts\install_status.txt
@echo "Creating a distributable package.."
@rem make the zip
@call conda install -c conda-forge -y conda-pack
@call conda pack --n-threads -1 --prefix installer --format tar
cd dist\win
call powershell Compress-Archive -Path stable-diffusion-ui -DestinationPath ..\stable-diffusion-ui-windows.zip
cd ..\..
@cd dist\stable-diffusion-ui
@mkdir installer
@REM cd dist\linux-mac
@REM call powershell Compress-Archive -Path stable-diffusion-ui -DestinationPath ..\stable-diffusion-ui-linux.zip
@REM call powershell Compress-Archive -Path stable-diffusion-ui -DestinationPath ..\stable-diffusion-ui-mac.zip
@REM cd ..\..
@call tar -xf ..\..\installer.tar -C installer
echo "Build ready. Upload the zip files inside the 'dist' folder."
@mkdir scripts
pause
@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. > scripts\install_status.txt
@echo "Build ready. Zip the 'dist\stable-diffusion-ui' folder."
@echo "Cleaning up.."
@cd ..\..
@rmdir /s /q installer
@del installer.tar

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@ -11,39 +11,45 @@ case $yn in
* ) exit;;
esac
# mkdir -p dist/win/stable-diffusion-ui/scripts
mkdir -p dist/linux-mac/stable-diffusion-ui/scripts
export PYTHONNOUSERSITE=1
# copy the installer files for Windows
mkdir -p dist/stable-diffusion-ui
# cp scripts/on_env_start.bat dist/win/stable-diffusion-ui/scripts/
# cp scripts/bootstrap.bat dist/win/stable-diffusion-ui/scripts/
# cp "scripts/Start Stable Diffusion UI.cmd" dist/win/stable-diffusion-ui/
# cp LICENSE dist/win/stable-diffusion-ui/
# cp "CreativeML Open RAIL-M License" dist/win/stable-diffusion-ui/
# cp "How to install and run.txt" dist/win/stable-diffusion-ui/
# echo "" > dist/win/stable-diffusion-ui/scripts/install_status.txt
echo "Downloading components for the installer.."
# copy the installer files for Linux and Mac
source ~/miniconda3/etc/profile.d/conda.sh
cp scripts/on_env_start.sh dist/linux-mac/stable-diffusion-ui/scripts/
cp scripts/bootstrap.sh dist/linux-mac/stable-diffusion-ui/scripts/
cp scripts/functions.sh dist/linux-mac/stable-diffusion-ui/scripts/
cp scripts/start.sh dist/linux-mac/stable-diffusion-ui/
cp LICENSE dist/linux-mac/stable-diffusion-ui/
cp "CreativeML Open RAIL-M License" dist/linux-mac/stable-diffusion-ui/
cp "How to install and run.txt" dist/linux-mac/stable-diffusion-ui/
echo "" > dist/linux-mac/stable-diffusion-ui/scripts/install_status.txt
conda install -c conda-forge -y conda-pack
# make the zip
conda env create --prefix installer -f environment.yaml
conda activate ./installer
# cd dist/win
# zip -r ../stable-diffusion-ui-windows.zip stable-diffusion-ui
# cd ../..
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" .
echo "" > scripts/install_status.txt
chmod u+x start.sh
echo "Build ready. Zip the 'dist/stable-diffusion-ui' folder."
echo "Cleaning up.."
cd dist/linux-mac
zip -r ../stable-diffusion-ui-linux.zip stable-diffusion-ui
zip -r ../stable-diffusion-ui-mac.zip stable-diffusion-ui
cd ../..
echo "Build ready. Upload the zip files inside the 'dist' folder."
rm -rf installer
rm installer.tar

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@echo off
echo "Opening Stable Diffusion UI - Developer Console.." & echo.
set PATH=C:\Windows\System32;%PATH%
@rem set legacy and new installer's PATH, if they exist
if exist "installer" set PATH=%cd%\installer;%cd%\installer\Library\bin;%cd%\installer\Scripts;%cd%\installer\Library\usr\bin;%PATH%
if exist "installer_files\env" set PATH=%cd%\installer_files\env;%cd%\installer_files\env\Library\bin;%cd%\installer_files\env\Scripts;%cd%\installer_files\Library\usr\bin;%PATH%
set PYTHONPATH=%cd%\installer;%cd%\installer_files\env
@rem activate the installer env
call conda activate
@rem Test the environment
echo "Environment Info:"
call where git
call git --version
call where conda
call conda --version
echo.
@rem activate the environment
call conda activate .\stable-diffusion\env
call where python
call python --version
@rem set the PYTHONPATH
cd stable-diffusion
set SD_DIR=%cd%
cd env\lib\site-packages
set PYTHONPATH=%SD_DIR%;%cd%
cd ..\..\..
echo PYTHONPATH=%PYTHONPATH%
cd ..
@rem done
echo.
cmd /k

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@ -1,27 +1,19 @@
@echo off
cd /d %~dp0
set PATH=C:\Windows\System32;%PATH%
@REM Delete the post-activate hook from the old installer
if exist "installer\etc\conda\activate.d\post_activate.bat" (
echo. > installer\etc\conda\activate.d\post_activate.bat
)
@rem set legacy installer's PATH, if it exists
if exist "installer" set PATH=%cd%\installer;%cd%\installer\Library\bin;%cd%\installer\Scripts;%cd%\installer\Library\usr\bin;%PATH%
@call installer\Scripts\activate.bat
@rem Setup the packages required for the installer
call scripts\bootstrap.bat
@call conda-unpack
@rem set new installer's PATH, if it downloaded any packages
if exist "installer_files\env" set PATH=%cd%\installer_files\env;%cd%\installer_files\env\Library\bin;%cd%\installer_files\env\Scripts;%cd%\installer_files\Library\usr\bin;%PATH%
@call conda --version
@call git --version
set PYTHONPATH=%cd%\installer;%cd%\installer_files\env
@cd installer
@rem Test the bootstrap
call where git
call git --version
call where conda
call conda --version
@rem Download the rest of the installer and UI
call scripts\on_env_start.bat
@call ..\scripts\on_env_start.bat
@pause

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@ -1,77 +0,0 @@
@echo off
@rem This script will install git and conda (if not found on the PATH variable)
@rem using micromamba (an 8mb static-linked single-file binary, conda replacement).
@rem For users who already have git and conda, this step will be skipped.
@rem This enables a user to install this project without manually installing conda and git.
@rem config
set MAMBA_ROOT_PREFIX=%cd%\installer_files\mamba
set INSTALL_ENV_DIR=%cd%\installer_files\env
set LEGACY_INSTALL_ENV_DIR=%cd%\installer
set MICROMAMBA_DOWNLOAD_URL=https://github.com/cmdr2/stable-diffusion-ui/releases/download/v1.1/micromamba.exe
set umamba_exists=F
set OLD_APPDATA=%APPDATA%
set OLD_USERPROFILE=%USERPROFILE%
set APPDATA=%cd%\installer_files\appdata
set USERPROFILE=%cd%\profile
@rem figure out whether git and conda needs to be installed
if exist "%INSTALL_ENV_DIR%" set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Library\bin;%INSTALL_ENV_DIR%\Scripts;%INSTALL_ENV_DIR%\Library\usr\bin;%PATH%
set PACKAGES_TO_INSTALL=
if not exist "%LEGACY_INSTALL_ENV_DIR%\etc\profile.d\conda.sh" (
if not exist "%INSTALL_ENV_DIR%\etc\profile.d\conda.sh" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% conda
)
call git --version >.tmp1 2>.tmp2
if "%ERRORLEVEL%" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% git
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version >.tmp1 2>.tmp2
if "%ERRORLEVEL%" EQU "0" set umamba_exists=T
@rem (if necessary) install git and conda into a contained environment
if "%PACKAGES_TO_INSTALL%" NEQ "" (
@rem download micromamba
if "%umamba_exists%" == "F" (
echo "Downloading micromamba from %MICROMAMBA_DOWNLOAD_URL% to %MAMBA_ROOT_PREFIX%\micromamba.exe"
mkdir "%MAMBA_ROOT_PREFIX%"
call curl -Lk "%MICROMAMBA_DOWNLOAD_URL%" > "%MAMBA_ROOT_PREFIX%\micromamba.exe"
if "%ERRORLEVEL%" NEQ "0" (
echo "There was a problem downloading micromamba. Cannot continue."
pause
exit /b
)
mkdir "%APPDATA%"
mkdir "%USERPROFILE%"
@rem test the mamba binary
echo Micromamba version:
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version
)
@rem create the installer env
if not exist "%INSTALL_ENV_DIR%" (
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" create -y --prefix "%INSTALL_ENV_DIR%"
)
echo "Packages to install:%PACKAGES_TO_INSTALL%"
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" install -y --prefix "%INSTALL_ENV_DIR%" -c conda-forge %PACKAGES_TO_INSTALL%
if not exist "%INSTALL_ENV_DIR%" (
echo "There was a problem while installing%PACKAGES_TO_INSTALL% using micromamba. Cannot continue."
pause
exit /b
)
)
@rem revert to the old APPDATA. only needed it for bypassing a bug in micromamba (with special characters)
set APPDATA=%OLD_APPDATA%
set USERPROFILE=%OLD_USERPROFILE%

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#!/bin/bash
# This script will install git and conda (if not found on the PATH variable)
# using micromamba (an 8mb static-linked single-file binary, conda replacement).
# For users who already have git and conda, this step will be skipped.
# This enables a user to install this project without manually installing conda and git.
source ./scripts/functions.sh
set -o pipefail
OS_NAME=$(uname -s)
case "${OS_NAME}" in
Linux*) OS_NAME="linux";;
Darwin*) OS_NAME="osx";;
*) echo "Unknown OS: $OS_NAME! This script runs only on Linux or Mac" && exit
esac
OS_ARCH=$(uname -m)
case "${OS_ARCH}" in
x86_64*) OS_ARCH="64";;
arm64*) OS_ARCH="arm64";;
*) echo "Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64" && exit
esac
# https://mamba.readthedocs.io/en/latest/installation.html
if [ "$OS_NAME" == "linux" ] && [ "$OS_ARCH" == "arm64" ]; then OS_ARCH="aarch64"; fi
# config
export MAMBA_ROOT_PREFIX="$(pwd)/installer_files/mamba"
INSTALL_ENV_DIR="$(pwd)/installer_files/env"
LEGACY_INSTALL_ENV_DIR="$(pwd)/installer"
MICROMAMBA_DOWNLOAD_URL="https://micro.mamba.pm/api/micromamba/${OS_NAME}-${OS_ARCH}/latest"
umamba_exists="F"
# figure out whether git and conda needs to be installed
if [ -e "$INSTALL_ENV_DIR" ]; then export PATH="$INSTALL_ENV_DIR/bin:$PATH"; fi
PACKAGES_TO_INSTALL=""
if [ ! -e "$LEGACY_INSTALL_ENV_DIR/etc/profile.d/conda.sh" ] && [ ! -e "$INSTALL_ENV_DIR/etc/profile.d/conda.sh" ]; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL conda"; fi
if ! hash "git" &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL git"; fi
if "$MAMBA_ROOT_PREFIX/micromamba" --version &>/dev/null; then umamba_exists="T"; fi
# (if necessary) install git and conda into a contained environment
if [ "$PACKAGES_TO_INSTALL" != "" ]; then
# download micromamba
if [ "$umamba_exists" == "F" ]; then
echo "Downloading micromamba from $MICROMAMBA_DOWNLOAD_URL to $MAMBA_ROOT_PREFIX/micromamba"
mkdir -p "$MAMBA_ROOT_PREFIX"
curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvj bin/micromamba -O > "$MAMBA_ROOT_PREFIX/micromamba"
if [ "$?" != "0" ]; then
echo
echo "EE micromamba download failed"
echo "EE If the lines above contain 'bzip2: Cannot exec', your system doesn't have bzip2 installed"
echo "EE If there are network errors, please check your internet setup"
fail "micromamba download failed"
fi
chmod u+x "$MAMBA_ROOT_PREFIX/micromamba"
# test the mamba binary
echo "Micromamba version:"
"$MAMBA_ROOT_PREFIX/micromamba" --version
fi
# create the installer env
if [ ! -e "$INSTALL_ENV_DIR" ]; then
"$MAMBA_ROOT_PREFIX/micromamba" create -y --prefix "$INSTALL_ENV_DIR" || fail "unable to create the install environment"
fi
if [ ! -e "$INSTALL_ENV_DIR" ]; then
fail "There was a problem while installing$PACKAGES_TO_INSTALL using micromamba. Cannot continue."
fi
echo "Packages to install:$PACKAGES_TO_INSTALL"
"$MAMBA_ROOT_PREFIX/micromamba" install -y --prefix "$INSTALL_ENV_DIR" -c conda-forge $PACKAGES_TO_INSTALL
if [ "$?" != "0" ]; then
fail "Installation of the packages '$PACKAGES_TO_INSTALL' failed."
fi
fi

View File

@ -1,51 +0,0 @@
#!/bin/bash
cd "$(dirname "${BASH_SOURCE[0]}")"
if [ "$0" == "bash" ]; then
echo "Opening Stable Diffusion UI - Developer Console.."
echo ""
# set legacy and new installer's PATH, if they exist
if [ -e "installer" ]; then export PATH="$(pwd)/installer/bin:$PATH"; fi
if [ -e "installer_files/env" ]; then export PATH="$(pwd)/installer_files/env/bin:$PATH"; fi
# activate the installer env
CONDA_BASEPATH=$(conda info --base)
source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # avoids the 'shell not initialized' error
conda activate
# test the environment
echo "Environment Info:"
which git
git --version
which conda
conda --version
echo ""
# activate the environment
CONDA_BASEPATH=$(conda info --base)
source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains about 'shell not initialized' (needed when running in a script)
conda activate ./stable-diffusion/env
which python
python --version
# set the PYTHONPATH
cd stable-diffusion
SD_PATH=`pwd`
export PYTHONPATH="$SD_PATH:$SD_PATH/env/lib/python3.8/site-packages"
echo "PYTHONPATH=$PYTHONPATH"
cd ..
# done
echo ""
else
file_name=$(basename "${BASH_SOURCE[0]}")
bash --init-file "$file_name"
fi

View File

@ -1,32 +0,0 @@
#
# utility functions for all scripts
#
fail() {
echo
echo "EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE"
echo
if [ "$1" != "" ]; then
echo ERROR: $1
else
echo An error occurred.
fi
cat <<EOF
Error downloading Stable Diffusion UI. Sorry about that, please try to:
1. Run this installer again.
2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting
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
4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues
Thanks!
EOF
read -p "Press any key to continue"
exit 1
}

View File

@ -4,6 +4,8 @@
set PATH=C:\Windows\System32;%PATH%
@cd ..
if exist "scripts\config.bat" (
@call scripts\config.bat
)
@ -12,7 +14,7 @@ if "%update_branch%"=="" (
set update_branch=main
)
@>nul findstr /m "conda_sd_ui_deps_installed" scripts\install_status.txt
@>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.
@ -26,14 +28,14 @@ if "%update_branch%"=="" (
)
)
@>nul findstr /m "sd_ui_git_cloned" scripts\install_status.txt
@>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 -c advice.detachedHead=false checkout "%update_branch%"
@call git checkout "%update_branch%"
@call git pull
@cd ..
@ -44,18 +46,16 @@ if "%update_branch%"=="" (
@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/wiki/Troubleshooting" & 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 "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 /q
@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\bootstrap.bat scripts\ /Y
@copy "sd-ui-files\scripts\Start Stable Diffusion UI.cmd" . /Y
@copy "sd-ui-files\scripts\Developer Console.cmd" . /Y
@call scripts\on_sd_start.bat
@pause
@pause

View File

@ -1,7 +1,5 @@
#!/bin/bash
source ./scripts/functions.sh
printf "\n\nStable Diffusion UI\n\n"
if [ -f "scripts/config.sh" ]; then
@ -18,7 +16,7 @@ if [ -f "scripts/install_status.txt" ] && [ `grep -c sd_ui_git_cloned scripts/in
cd sd-ui-files
git reset --hard
git -c advice.detachedHead=false checkout "$update_branch"
git checkout "$update_branch"
git pull
cd ..
@ -29,16 +27,16 @@ else
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
fail "git clone failed"
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/bootstrap.sh scripts/
cp sd-ui-files/scripts/start.sh .
cp sd-ui-files/scripts/developer_console.sh .
./scripts/on_sd_start.sh

View File

@ -1,73 +1,51 @@
@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.
@copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y
@copy sd-ui-files\scripts\bootstrap.bat scripts\ /Y
if exist "%cd%\profile" (
set USERPROFILE=%cd%\profile
)
@mkdir tmp
@set TMP=%cd%\tmp
@set TEMP=%cd%\tmp
@rem activate the installer env
call conda activate
@if "%ERRORLEVEL%" NEQ "0" (
@echo. & echo "Error activating conda 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/wiki/Troubleshooting" & 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
)
@REM remove the old version of the dev console script, if it's still present
if exist "Open Developer Console.cmd" del "Open Developer Console.cmd"
@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');"
if NOT DEFINED test_sd2 set test_sd2=N
@>nul findstr /m "sd_git_cloned" scripts\install_status.txt
@>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 remote set-url origin https://github.com/easydiffusion/diffusion-kit.git
@call git reset --hard
@call git pull
@call git checkout d87bd29a6862996d8a0980c1343b6f0d4eb718b4
if "%test_sd2%" == "N" (
@call git -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
)
if "%test_sd2%" == "Y" (
@call git -c advice.detachedHead=false checkout 733a1f6f9cae9b9a9b83294bf3281b123378cb1f
)
@REM @call git apply ..\ui\sd_internal\ddim_callback.patch
@REM @call git apply ..\ui\sd_internal\env_yaml.patch
@call git apply ..\ui\sd_internal\custom_sd.patch
@cd ..
) else (
@echo. & echo "Downloading Stable Diffusion.." & echo.
@call git clone https://github.com/easydiffusion/diffusion-kit.git stable-diffusion && (
@call git clone https://github.com/invoke-ai/InvokeAI.git stable-diffusion && (
@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/wiki/Troubleshooting" & 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 "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 -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
@call git checkout d87bd29a6862996d8a0980c1343b6f0d4eb718b4
@REM @call git apply ..\ui\sd_internal\ddim_callback.patch
@REM @call git apply ..\ui\sd_internal\env_yaml.patch
@call git apply ..\ui\sd_internal\custom_sd.patch
@cd ..
)
@cd stable-diffusion
@>nul findstr /m "conda_sd_env_created" ..\scripts\install_status.txt
@>nul grep -c "conda_sd_env_created" ..\scripts\install_status.txt
@if "%ERRORLEVEL%" EQU "0" (
@echo "Packages necessary for Stable Diffusion were already installed"
@ -80,20 +58,22 @@ if NOT DEFINED test_sd2 set test_sd2=N
@REM prevent conda from using packages from the user's home directory, to avoid conflicts
@set PYTHONNOUSERSITE=1
set USERPROFILE=%cd%\profile
set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
@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/wiki/Troubleshooting" & 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.
@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/wiki/Troubleshooting" & 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.
@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
)
@ -103,49 +83,7 @@ if NOT DEFINED test_sd2 set test_sd2=N
set PATH=C:\Windows\System32;%PATH%
@>nul findstr /m "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
set USERPROFILE=%cd%\profile
set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
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/wiki/Troubleshooting" & 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 findstr /m "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
set USERPROFILE=%cd%\profile
set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
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/wiki/Troubleshooting" & 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 findstr /m "conda_sd_ui_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 (
@ -153,59 +91,28 @@ set PATH=C:\Windows\System32;%PATH%
@set PYTHONNOUSERSITE=1
set USERPROFILE=%cd%\profile
set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
@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/wiki/Troubleshooting" & 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 "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 findstr /m "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/wiki/Troubleshooting" & 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.
@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 2>nul call python -m picklescan --help
@if "%ERRORLEVEL%" NEQ "0" (
@echo. & echo Picklescan not found. Installing
@call pip install picklescan || (
echo "Error installing the picklescan package 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/wiki/Troubleshooting" & 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
)
)
@>nul 2>nul call python -c "import safetensors"
@if "%ERRORLEVEL%" NEQ "0" (
@echo. & echo SafeTensors not found. Installing
@call pip install safetensors || (
echo "Error installing the safetensors package 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/wiki/Troubleshooting" & 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
)
)
@>nul findstr /m "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
@>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 not exist "..\models\stable-diffusion" mkdir "..\models\stable-diffusion"
if not exist "..\models\vae" mkdir "..\models\vae"
if not exist "..\models\hypernetwork" mkdir "..\models\hypernetwork"
echo. > "..\models\stable-diffusion\Put your custom ckpt files here.txt"
echo. > "..\models\vae\Put your VAE files here.txt"
echo. > "..\models\hypernetwork\Put your hypernetwork files here.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. Using the HuggingFace 4 GB Model."
@ -231,12 +138,12 @@ echo. > "..\models\hypernetwork\Put your hypernetwork files here.txt"
@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/wiki/Troubleshooting" & 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.
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/wiki/Troubleshooting" & 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.
@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
)
@ -261,12 +168,12 @@ echo. > "..\models\hypernetwork\Put your hypernetwork files here.txt"
@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/wiki/Troubleshooting" & 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.
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/wiki/Troubleshooting" & 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.
@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
)
@ -278,7 +185,7 @@ echo. > "..\models\hypernetwork\Put your hypernetwork files here.txt"
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 RealESRGAN model file present at %cd%\RealESRGAN_x4plus.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
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"
)
)
@ -291,12 +198,12 @@ echo. > "..\models\hypernetwork\Put your hypernetwork files here.txt"
@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/wiki/Troubleshooting" & 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.
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/wiki/Troubleshooting" & 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.
@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
)
@ -308,7 +215,7 @@ echo. > "..\models\hypernetwork\Put your hypernetwork files here.txt"
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 RealESRGAN model file present at %cd%\RealESRGAN_x4plus_anime_6B.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
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"
)
)
@ -321,12 +228,12 @@ echo. > "..\models\hypernetwork\Put your hypernetwork files here.txt"
@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/wiki/Troubleshooting" & 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.
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/wiki/Troubleshooting" & 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.
@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
)
@ -334,39 +241,7 @@ echo. > "..\models\hypernetwork\Put your hypernetwork files here.txt"
@if exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
for %%I in ("..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt") do if "%%~zI" EQU "334695179" (
echo "Data files (weights) necessary for the default VAE (sd-vae-ft-mse-original) were already downloaded"
) else (
echo. & echo "The default VAE (sd-vae-ft-mse-original) file present at models\vae\vae-ft-mse-840000-ema-pruned.ckpt is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
del "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt"
)
)
@if not exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
@echo. & echo "Downloading data files (weights) for the default VAE (sd-vae-ft-mse-original).." & echo.
@call curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt
@if exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
for %%I in ("..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt") do if "%%~zI" NEQ "334695179" (
echo. & echo "Error: The downloaded default VAE (sd-vae-ft-mse-original) file was invalid! Bytes downloaded: %%~zI" & echo.
echo. & echo "Error downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). 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/wiki/Troubleshooting" & 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 the default VAE (sd-vae-ft-mse-original). 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/wiki/Troubleshooting" & 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 "%test_sd2%" == "Y" (
@call pip install open_clip_torch==2.0.2
)
@>nul findstr /m "sd_install_complete" ..\scripts\install_status.txt
@>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
@ -381,24 +256,12 @@ if "%test_sd2%" == "Y" (
@cd ..\..\..
@echo PYTHONPATH=%PYTHONPATH%
call where python
call python --version
@cd ..
@set SD_UI_PATH=%cd%\ui
@cd stable-diffusion
@rem
@rem Rewrite easy-install.pth. This fixes the installation if the user has relocated the SDUI installation
@rem
>env\Lib\site-packages\easy-install.pth echo %cd%\src\taming-transformers
>>env\Lib\site-packages\easy-install.pth echo %cd%\src\clip
>>env\Lib\site-packages\easy-install.pth echo %cd%\src\gfpgan
>>env\Lib\site-packages\easy-install.pth echo %cd%\src\realesrgan
@call python --version
@if NOT DEFINED SD_UI_BIND_PORT set SD_UI_BIND_PORT=9000
@if NOT DEFINED SD_UI_BIND_IP set SD_UI_BIND_IP=0.0.0.0
@uvicorn server:app --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP%
@uvicorn server:app --app-dir "%SD_UI_PATH%" --port 9000 --host 0.0.0.0
@pause
@pause

View File

@ -1,58 +1,43 @@
#!/bin/bash
source ./scripts/functions.sh
cp sd-ui-files/scripts/on_env_start.sh scripts/
cp sd-ui-files/scripts/bootstrap.sh scripts/
# activate the installer env
CONDA_BASEPATH=$(conda info --base)
source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # avoids the 'shell not initialized' error
source installer/etc/profile.d/conda.sh
conda activate || fail "Failed to activate conda"
# remove the old version of the dev console script, if it's still present
if [ -e "open_dev_console.sh" ]; then
rm "open_dev_console.sh"
fi
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');"
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 [ "$test_sd2" == "" ]; then
export test_sd2="N"
fi
if [ -e "scripts/install_status.txt" ] && [ `grep -c sd_git_cloned scripts/install_status.txt` -gt "0" ]; then
echo "Stable Diffusion's git repository was already installed. Updating.."
cd stable-diffusion
git remote set-url origin https://github.com/easydiffusion/diffusion-kit.git
git reset --hard
git pull
git checkout f6cfebffa752ee11a7b07497b8529d5971de916c
if [ "$test_sd2" == "N" ]; then
git -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
elif [ "$test_sd2" == "Y" ]; then
git -c advice.detachedHead=false checkout 733a1f6f9cae9b9a9b83294bf3281b123378cb1f
fi
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/easydiffusion/diffusion-kit.git stable-diffusion ; then
if git clone https://github.com/basujindal/stable-diffusion.git ; then
echo sd_git_cloned >> scripts/install_status.txt
else
fail "git clone of basujindal/stable-diffusion.git failed"
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 -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
git checkout f6cfebffa752ee11a7b07497b8529d5971de916c
git apply ../ui/sd_internal/ddim_callback.patch
git apply ../ui/sd_internal/env_yaml.patch
cd ..
fi
@ -62,26 +47,37 @@ 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 || fail "conda activate failed"
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
export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
if conda env create --prefix env --force -f environment.yaml ; then
echo "Installed. Testing.."
else
fail "'conda env create' failed"
printf "\n\nError installing the packages necessary for Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
conda activate ./env || fail "conda activate failed"
conda activate ./env
if conda install -c conda-forge --prefix ./env -y antlr4-python3-runtime=4.8 ; then
echo "Installed. Testing.."
else
printf "\n\nError installing antlr4-python3-runtime for Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
out_test=`python -c "import torch; import ldm; import transformers; import numpy; import antlr4; print(42)"`
if [ "$out_test" != "42" ]; then
fail "Dependency test failed"
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
@ -93,14 +89,20 @@ else
printf "\n\nDownloading packages necessary for GFPGAN (Face Correction)..\n"
export PYTHONNOUSERSITE=1
export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
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 [ "$out_test" != "42" ]; then
echo "EE The dependency check has failed. This usually means that some system libraries are missing."
echo "EE On Debian/Ubuntu systems, this are often these packages: libsm6 libxext6 libxrender-dev"
echo "EE Other Linux distributions might have different package names for these libraries."
fail "GFPGAN dependency test failed"
printf "\n\nDependency test failed! Error installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
echo conda_sd_gfpgan_deps_installed >> ../scripts/install_status.txt
@ -112,11 +114,20 @@ else
printf "\n\nDownloading packages necessary for ESRGAN (Resolution Upscaling)..\n"
export PYTHONNOUSERSITE=1
export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
if pip install -e git+https://github.com/xinntao/Real-ESRGAN#egg=realesrgan ; then
echo "Installed. Testing.."
else
printf "\n\nError installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
out_test=`python -c "from basicsr.archs.rrdbnet_arch import RRDBNet; from realesrgan import RealESRGANer; print(42)"`
if [ "$out_test" != "42" ]; then
fail "ESRGAN dependency test failed"
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
@ -128,46 +139,28 @@ else
printf "\n\nDownloading packages necessary for Stable Diffusion UI..\n\n"
export PYTHONNOUSERSITE=1
export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
if conda install -c conda-forge --prefix ./env -y uvicorn fastapi ; then
echo "Installed. Testing.."
else
fail "'conda install uvicorn' failed"
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
fail "UI packages not found!"
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 python -m picklescan --help >/dev/null 2>&1; then
echo "Picklescan is already installed."
else
echo "Picklescan not found, installing."
pip install picklescan || fail "Picklescan installation failed."
fi
if python -c "import safetensors" --help >/dev/null 2>&1; then
echo "SafeTensors is already installed."
else
echo "SafeTensors not found, installing."
pip install safetensors || fail "SafeTensors installation failed."
fi
mkdir -p "../models/stable-diffusion"
mkdir -p "../models/vae"
mkdir -p "../models/hypernetwork"
echo "" > "../models/stable-diffusion/Put your custom ckpt files here.txt"
echo "" > "../models/vae/Put your VAE files here.txt"
echo "" > "../models/hypernetwork/Put your hypernetwork files here.txt"
if [ -f "sd-v1-4.ckpt" ]; then
model_size=`find "sd-v1-4.ckpt" -printf "%s"`
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"
@ -183,18 +176,23 @@ if [ ! -f "sd-v1-4.ckpt" ]; then
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=`find "sd-v1-4.ckpt" -printf "%s"`
model_size=`ls -l sd-v1-4.ckpt | awk '{print $5}'`
if [ ! "$model_size" == "4265380512" ]; then
fail "The downloaded model file was invalid! Bytes downloaded: $model_size"
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
fail "Error downloading the data files (weights) for Stable Diffusion"
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=`find "GFPGANv1.3.pth" -printf "%s"`
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"
@ -210,18 +208,23 @@ if [ ! -f "GFPGANv1.3.pth" ]; then
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=`find "GFPGANv1.3.pth" -printf "%s"`
model_size=`ls -l GFPGANv1.3.pth | awk '{print $5}'`
if [ ! "$model_size" -eq "348632874" ]; then
fail "The downloaded GFPGAN model file was invalid! Bytes downloaded: $model_size"
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
fail "Error downloading the data files (weights) for GFPGAN (Face Correction)."
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=`find "RealESRGAN_x4plus.pth" -printf "%s"`
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"
@ -237,18 +240,23 @@ if [ ! -f "RealESRGAN_x4plus.pth" ]; then
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=`find "RealESRGAN_x4plus.pth" -printf "%s"`
model_size=`ls -l RealESRGAN_x4plus.pth | awk '{print $5}'`
if [ ! "$model_size" -eq "67040989" ]; then
fail "The downloaded ESRGAN x4plus model file was invalid! Bytes downloaded: $model_size"
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
fail "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus"
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=`find "RealESRGAN_x4plus_anime_6B.pth" -printf "%s"`
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"
@ -264,50 +272,20 @@ if [ ! -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
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=`find "RealESRGAN_x4plus_anime_6B.pth" -printf "%s"`
model_size=`ls -l RealESRGAN_x4plus_anime_6B.pth | awk '{print $5}'`
if [ ! "$model_size" -eq "17938799" ]; then
fail "The downloaded ESRGAN x4plus_anime model file was invalid! Bytes downloaded: $model_size"
fi
else
fail "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime."
fi
fi
if [ -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
model_size=`find ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt -printf "%s"`
if [ "$model_size" -eq "334695179" ]; then
echo "Data files (weights) necessary for the default VAE (sd-vae-ft-mse-original) were already downloaded"
else
printf "\n\nThe model file present at models/vae/vae-ft-mse-840000-ema-pruned.ckpt is invalid. It is only $model_size bytes in size. Re-downloading.."
rm ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt
fi
fi
if [ ! -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
echo "Downloading data files (weights) for the default VAE (sd-vae-ft-mse-original).."
curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt
if [ -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
model_size=`find ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt -printf "%s"`
if [ ! "$model_size" -eq "334695179" ]; then
printf "\n\nError: The downloaded default VAE (sd-vae-ft-mse-original) file was invalid! Bytes downloaded: $model_size\n\n"
printf "\n\nError downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). 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/wiki/Troubleshooting\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"
printf "\n\nError: The downloaded ESRGAN x4plus_anime model file was invalid! Bytes downloaded: $model_size\n\n"
printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
else
printf "\n\nError downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
fi
if [ "$test_sd2" == "Y" ]; then
pip install open_clip_torch==2.0.2
fi
if [ `grep -c sd_install_complete ../scripts/install_status.txt` -gt "0" ]; then
echo sd_weights_downloaded >> ../scripts/install_status.txt
@ -317,16 +295,15 @@ fi
printf "\n\nStable Diffusion is ready!\n\n"
SD_PATH=`pwd`
export PYTHONPATH="$SD_PATH:$SD_PATH/env/lib/python3.8/site-packages"
export PYTHONPATH="$SD_PATH;$SD_PATH/env/lib/python3.8/site-packages"
echo "PYTHONPATH=$PYTHONPATH"
which python
python --version
cd ..
export SD_UI_PATH=`pwd`/ui
cd stable-diffusion
uvicorn server:app --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0}
python --version
uvicorn server:app --app-dir "$SD_UI_PATH" --port 9000 --host 0.0.0.0
read -p "Press any key to continue"

View File

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

12
scripts/post_activate.sh Executable file
View File

@ -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

20
scripts/start.sh Executable file → Normal file
View File

@ -1,22 +1,10 @@
#!/bin/bash
cd "$(dirname "${BASH_SOURCE[0]}")"
source installer/bin/activate
# set legacy installer's PATH, if it exists
if [ -e "installer" ]; then export PATH="$(pwd)/installer/bin:$PATH"; fi
conda-unpack
# Setup the packages required for the installer
scripts/bootstrap.sh || exit 1
conda --version
git --version
# set new installer's PATH, if it downloaded any packages
if [ -e "installer_files/env" ]; then export PATH="$(pwd)/installer_files/env/bin:$PATH"; fi
# Test the bootstrap
which git
git --version || exit 1
which conda
conda --version || exit 1
# Download the rest of the installer and UI
scripts/on_env_start.sh

View File

@ -1,154 +1,107 @@
<!DOCTYPE html>
<html>
<head>
<title>Stable Diffusion UI</title>
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="theme-color" content="#673AB6">
<link rel="icon" type="image/png" href="/media/images/favicon-16x16.png" sizes="16x16">
<link rel="icon" type="image/png" href="/media/images/favicon-32x32.png" sizes="32x32">
<link rel="stylesheet" href="/media/css/fonts.css">
<link rel="stylesheet" href="/media/css/themes.css">
<link rel="stylesheet" href="/media/css/main.css">
<link rel="stylesheet" href="/media/css/auto-save.css">
<link rel="stylesheet" href="/media/css/modifier-thumbnails.css">
<link rel="stylesheet" href="/media/css/fontawesome-all.min.css">
<link rel="stylesheet" href="/media/css/image-editor.css">
<link rel="stylesheet" href="/media/css/jquery-confirm.min.css">
<link rel="manifest" href="/media/manifest.webmanifest">
<script src="/media/js/jquery-3.6.1.min.js"></script>
<script src="/media/js/jquery-confirm.min.js"></script>
<script src="/media/js/marked.min.js"></script>
<link rel="icon" type="image/png" href="/media/favicon-16x16.png" sizes="16x16">
<link rel="icon" type="image/png" href="/media/favicon-32x32.png" sizes="32x32">
<link rel="stylesheet" href="/media/main.css?v=21">
<link rel="stylesheet" href="/media/modifier-thumbnails.css?v=1">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.2.0/css/all.min.css">
<link rel="stylesheet" href="/media/drawingboard.min.css">
<script src="/media/jquery-3.6.1.min.js"></script>
<script src="/media/drawingboard.min.js"></script>
</head>
<body>
<div id="container">
<div id="top-nav">
<div id="logo">
<h1>
Stable Diffusion UI
<small>v2.4.20 <span id="updateBranchLabel"></span></small>
</h1>
<h1>Stable Diffusion UI <small>v2.2 <span id="updateBranchLabel"></span></small></h1>
</div>
<div id="server-status">
<div id="server-status-color"></div>
<span id="server-status-msg">Stable Diffusion is starting..</span>
</div>
<div id="tab-container">
<span id="tab-main" class="tab active">
<span><i class="fa fa-image icon"></i> Generate</span>
</span>
<span id="tab-settings" class="tab">
<span><i class="fa fa-gear icon"></i> Settings</span>
</span>
<span id="tab-about" class="tab">
<ul id="top-nav-items">
<li class="dropdown">
<span><i class="fa fa-comments icon"></i> Help & Community</span>
</span>
</div>
<ul id="community-links" class="dropdown-content">
<li><a href="https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" target="_blank"><i class="fa-solid fa-circle-question fa-fw"></i> Usual problems and solutions</a></li>
<li><a href="https://discord.com/invite/u9yhsFmEkB" target="_blank"><i class="fa-brands fa-discord fa-fw"></i> Discord user community</a></li>
<li><a href="https://www.reddit.com/r/StableDiffusionUI/" target="_blank"><i class="fa-brands fa-reddit fa-fw"></i> Reddit community</a></li>
<li><a href="https://github.com/cmdr2/stable-diffusion-ui" target="_blank"><i class="fa-brands fa-github fa-fw"></i> Source code on GitHub</a></li>
</ul>
</li>
<li class="dropdown">
<span><i class="fa fa-gear icon"></i> Settings</span>
<div id="system-settings" class="panel-box settings-box dropdown-content">
<ul id="system-settings-entries">
<li><b class="settings-subheader">System Settings</b></li>
<br/>
<li><input id="save_to_disk" name="save_to_disk" type="checkbox"> <label for="save_to_disk">Automatically save to <input id="diskPath" name="diskPath" size="40" disabled></label></li>
<li><input id="sound_toggle" name="sound_toggle" type="checkbox" checked> <label for="sound_toggle">Play sound on task completion</label></li>
<li><input id="turbo" name="turbo" type="checkbox" checked> <label for="turbo">Turbo mode <small>(generates images faster, but uses an additional 1 GB of GPU memory)</small></label></li>
<li><input id="use_cpu" name="use_cpu" type="checkbox"> <label for="use_cpu">Use CPU instead of GPU <small>(warning: this will be *very* slow)</small></label></li>
<li><input id="use_full_precision" name="use_full_precision" type="checkbox"> <label for="use_full_precision">Use full precision <small>(for GPU-only. warning: this will consume more VRAM)</small></label></li>
<!-- <li><input id="allow_nsfw" name="allow_nsfw" type="checkbox"> <label for="allow_nsfw">Allow NSFW Content (You confirm you are above 18 years of age)</label></li> -->
<br/>
<li><input id="use_beta_channel" name="use_beta_channel" type="checkbox"> <label for="use_beta_channel">🔥Beta channel. Get the latest features immediately (but could be less stable). Please restart the program after changing this.</label></li>
</ul>
</div>
</li>
</ul>
</div>
<div id="tab-content-wrapper">
<div id="tab-content-main" class="tab-content active flex-container">
<div id="editor">
<div class="flex-container">
<div id="editor" class="col-fixed-10">
<div id="server-status">
<div id="server-status-color"></div>
<span id="server-status-msg">Stable Diffusion is starting..</span>
</div>
<div id="editor-inputs">
<div id="editor-inputs-prompt" class="row">
<label for="prompt"><b>Enter Prompt</b></label> <small>or</small> <button id="promptsFromFileBtn">Load from a file</button>
<label for="prompt">Prompt</label>
<textarea id="prompt" class="col-free">a photograph of an astronaut riding a horse</textarea>
<input id="prompt_from_file" name="prompt_from_file" type="file" /> <!-- hidden -->
<label for="negative_prompt" class="collapsible" id="negative_prompt_handle">
Negative Prompt
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Writing-prompts#negative-prompts" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about Negative Prompts</span></i></a>
<small>(optional)</small>
</label>
<div class="collapsible-content">
<textarea id="negative_prompt" name="negative_prompt" placeholder="list the things to remove from the image (e.g. fog, green)"></textarea>
</div>
</div>
<div id="editor-inputs-init-image" class="row">
<label for="init_image">Initial Image (img2img) <small>(optional)</small> </label>
<label for="init_image"><b>Initial Image:</b> (optional) </label> <input id="init_image" name="init_image" type="file" /><br/>
<div id="init_image_preview_container" class="image_preview_container">
<div id="init_image_wrapper">
<img id="init_image_preview" src="" />
<span id="init_image_size_box"></span>
<button class="init_image_clear image_clear_btn"><i class="fa-solid fa-xmark"></i></button>
</div>
<div id="init_image_buttons">
<div class="button">
<i class="fa-regular fa-folder-open"></i>
Browse
<input id="init_image" name="init_image" type="file" />
</div>
<div id="init_image_button_draw" class="button">
<i class="fa-solid fa-pencil"></i>
Draw
</div>
<div id="inpaint_button_container">
<div id="init_image_button_inpaint" class="button">
<i class="fa-solid fa-paintbrush"></i>
Inpaint
</div>
<input id="enable_mask" name="enable_mask" type="checkbox">
</div>
</div>
</div>
<img id="init_image_preview" src="" width="100" height="100" />
<button class="init_image_clear image_clear_btn">X</button>
<br/>
<input id="enable_mask" name="enable_mask" type="checkbox"> <label for="enable_mask">In-Painting (beta) <small>(select the area which the AI will paint into)</small></label>
<div id="inpaintingEditor"></div>
</div>
</div>
<div id="editor-inputs-tags-container" class="row">
<label>Image Modifiers <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">click an Image Modifier to remove it, use Ctrl+Mouse Wheel to adjust its weight</span></i>:</label>
<label>Image Modifiers: <small>(click an Image Modifier to remove it)</small></label>
<div id="editor-inputs-tags-list"></div>
</div>
<button id="makeImage" class="primaryButton">Make Image</button>
<div id="render-buttons">
<button id="stopImage" class="secondaryButton">Stop All</button>
<button id="pause"><i class="fa-solid fa-pause"></i> Pause All</button>
<button id="resume"><i class="fa-solid fa-play"></i> Resume</button>
</div>
<button id="makeImage">Make Image</button>
<button id="stopImage" class="secondaryButton">Stop All</button>
</div>
<span class="line-separator"></span>
<div class="line-separator">&nbsp;</div>
<div id="editor-settings" class="settings-box panel-box">
<h4 class="collapsible">
Image Settings
<i id="reset-image-settings" class="fa-solid fa-arrow-rotate-left section-button">
<span class="simple-tooltip top-left">
Reset Image Settings
</span>
</i>
</h4>
<div id="editor-settings-entries" class="collapsible-content">
<div><table>
<tr><b class="settings-subheader">Image Settings</b></tr>
<tr class="pl-5"><td><label for="seed">Seed:</label></td><td><input id="seed" name="seed" size="10" value="0" onkeypress="preventNonNumericalInput(event)"> <input id="random_seed" name="random_seed" type="checkbox" checked><label for="random_seed">Random</label></td></tr>
<tr class="pl-5"><td><label for="num_outputs_total">Number of Images:</label></td><td><input id="num_outputs_total" name="num_outputs_total" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label><small>(total)</small></label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label for="num_outputs_parallel"><small>(in parallel)</small></label></td></tr>
<tr class="pl-5"><td><label for="stable_diffusion_model">Model:</label></td><td>
<select id="stable_diffusion_model" name="stable_diffusion_model">
<!-- <option value="sd-v1-4" selected>sd-v1-4</option> -->
</select>
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Models" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about custom models</span></i></a>
</td></tr>
<tr class="pl-5"><td><label for="vae_model">Custom VAE:</i></label></td><td>
<select id="vae_model" name="vae_model">
<!-- <option value="" selected>None</option> -->
</select>
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/VAE-Variational-Auto-Encoder" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about VAEs</span></i></a>
</td></tr>
<tr id="samplerSelection" class="pl-5"><td><label for="sampler">Sampler:</label></td><td>
<div id="editor-settings" class="panel-box settings-box">
<h4 class="collapsible">Image Settings</h4>
<ul id="editor-settings-entries" class="collapsible-content">
<li><b class="settings-subheader">Image Settings</b></li>
<li class="pl-5"><label for="seed">Seed:</label> <input id="seed" name="seed" size="10" value="30000"> <input id="random_seed" name="random_seed" type="checkbox" checked> <label for="random_seed">Random Image</label></li>
<li class="pl-5"><label for="num_outputs_total">Number of images to make:</label> <input id="num_outputs_total" name="num_outputs_total" value="1" size="1"> <label for="num_outputs_parallel">Generate in parallel:</label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1"> (images at once)</li>
<li id="samplerSelection" class="pl-5"><label for="sampler">Sampler:</label>
<select id="sampler" name="sampler">
<option value="plms">plms</option>
<option value="plms" selected>plms</option>
<option value="ddim">ddim</option>
<option value="heun">heun</option>
<option value="euler">euler</option>
<option value="euler_a" selected>euler_a</option>
<option value="euler_a">euler_a</option>
<option value="dpm2">dpm2</option>
<option value="dpm2_a">dpm2_a</option>
<option value="lms">lms</option>
</select>
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/How-to-Use#samplers" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about samplers</span></i></a>
</td></tr>
<tr class="pl-5"><td><label>Image Size: </label></td><td>
</li>
<li class="pl-5"><label>Image Size: </label>
<select id="width" name="width" value="512">
<option value="128">128 (*)</option>
<option value="192">192</option>
@ -193,204 +146,63 @@
<option value="2048">2048</option>
</select>
<label for="height"><small>(height)</small></label>
</td></tr>
<tr class="pl-5"><td><label for="num_inference_steps">Inference Steps:</label></td><td> <input id="num_inference_steps" name="num_inference_steps" size="4" value="25" onkeypress="preventNonNumericalInput(event)"></td></tr>
<tr class="pl-5"><td><label for="guidance_scale_slider">Guidance Scale:</label></td><td> <input id="guidance_scale_slider" name="guidance_scale_slider" class="editor-slider" value="75" type="range" min="10" max="500"> <input id="guidance_scale" name="guidance_scale" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"></td></tr>
<tr id="prompt_strength_container" class="pl-5"><td><label for="prompt_strength_slider">Prompt Strength:</label></td><td> <input id="prompt_strength_slider" name="prompt_strength_slider" class="editor-slider" value="80" type="range" min="0" max="99"> <input id="prompt_strength" name="prompt_strength" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"><br/></td></tr>
<tr class="pl-5"><td><label for="hypernetwork_model">Hypernetwork:</i></label></td><td>
<select id="hypernetwork_model" name="hypernetwork_model">
<!-- <option value="" selected>None</option> -->
</select>
</td></tr>
<tr id="hypernetwork_strength_container" class="pl-5">
<td><label for="hypernetwork_strength_slider">Hypernetwork Strength:</label></td>
<td> <input id="hypernetwork_strength_slider" name="hypernetwork_strength_slider" class="editor-slider" value="100" type="range" min="0" max="100"> <input id="hypernetwork_strength" name="hypernetwork_strength" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"><br/></td>
</tr>
<tr class="pl-5"><td><label for="output_format">Output Format:</label></td><td>
<select id="output_format" name="output_format">
<option value="jpeg" selected>jpeg</option>
<option value="png">png</option>
</select>
</td></tr>
<tr class="pl-5" id="output_quality_row"><td><label for="output_quality">JPEG Quality:</label></td><td>
<input id="output_quality_slider" name="output_quality" class="editor-slider" value="75" type="range" min="10" max="95"> <input id="output_quality" name="output_quality" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)">
</td></tr>
</table></div>
</li>
<li class="pl-5"><label for="num_inference_steps">Number of inference steps:</label> <input id="num_inference_steps" name="num_inference_steps" size="4" value="50"></li>
<li class="pl-5"><label for="guidance_scale_slider">Guidance Scale:</label> <input id="guidance_scale_slider" name="guidance_scale_slider" class="editor-slider" value="75" type="range" min="10" max="500"> <input id="guidance_scale" name="guidance_scale" size="4"></li>
<li class="pl-5"><span id="prompt_strength_container"><label for="prompt_strength_slider">Prompt Strength:</label> <input id="prompt_strength_slider" name="prompt_strength_slider" class="editor-slider" value="80" type="range" min="0" max="99"> <input id="prompt_strength" name="prompt_strength" size="4"><br/></span></li>
<br/>
<li><b class="settings-subheader">Prompt Settings</b></li>
<li class="pl-5"><label for="negative_prompt">Negative Prompt:</label> <input id="negative_prompt" name="negative_prompt" size="55"></li>
<br/>
<div><ul>
<li><b class="settings-subheader">Render Settings</b></li>
<li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview <small>(uses more VRAM, slower images)</small></label></li>
<li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox"> <label for="use_face_correction">Fix incorrect faces and eyes <small>(uses GFPGAN)</small></label></li>
<li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview of the image <small>(uses more VRAM, slightly slower image creation)</small></label></li>
<li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox" checked> <label for="use_face_correction">Fix incorrect faces and eyes <small>(uses GFPGAN)</small></label></li>
<li class="pl-5">
<input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Upscale image by 4x with </label>
<input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Upscale the image to 4x resolution using </label>
<select id="upscale_model" name="upscale_model">
<option value="RealESRGAN_x4plus" selected>RealESRGAN_x4plus</option>
<option value="RealESRGAN_x4plus_anime_6B">RealESRGAN_x4plus_anime_6B</option>
</select>
</li>
<li class="pl-5"><input id="show_only_filtered_image" name="show_only_filtered_image" type="checkbox" checked> <label for="show_only_filtered_image">Show only the corrected/upscaled image</label></li>
</ul></div>
</div>
<br/>
<li><small>The system-related settings have been moved to the top-right corner.</small></li>
</ul>
</div>
<div id="editor-modifiers" class="panel-box">
<h4 class="collapsible">
Image Modifiers (art styles, tags etc)
<i id="modifier-settings-btn" class="fa-solid fa-gear section-button">
<span class="simple-tooltip left">
Add Custom Modifiers
</span>
</i>
</h4>
<h4 class="collapsible">Image Modifiers (art styles, tags etc)</h4>
<div id="editor-modifiers-entries" class="collapsible-content">
<div id="editor-modifiers-entries-toolbar">
<label for="preview-image">Image Style:</label>
<select id="preview-image" name="preview-image" value="portrait">
<option value="portrait" selected="">Face</option>
<option value="landscape">Landscape</option>
</select>
&nbsp;
<label for="modifier-card-size-slider">Thumbnail Size:</label>
<input id="modifier-card-size-slider" name="modifier-card-size-slider" value="0" type="range" min="-3" max="5">
</div>
<label for="preview-image">Image Style:</label>
<select id="preview-image" name="preview-image" value="portrait">
<option value="portrait" selected="">Face</option>
<option value="landscape">Landscape</option>
</select>
&nbsp;
<label for="modifier-card-size-slider">Thumbnail Size:</label>
<input id="modifier-card-size-slider" name="modifier-card-size-slider" value="0" type="range" min="-3" max="5">
</div>
</div>
</div>
<div id="preview" class="col-free">
<div id="initial-text">
Type a prompt and press the "Make Image" button.<br/><br/>You can set an "Initial Image" if you want to guide the AI.<br/><br/>
You can also add modifiers like "Realistic", "Pencil Sketch", "ArtStation" etc by browsing through the "Image Modifiers" section
and selecting the desired modifiers.<br/><br/>
Click "Image Settings" for additional settings like seed, image size, number of images to generate etc.<br/><br/>Enjoy! :)
Type a prompt and press the "Make Image" button.<br/><br/>You can set an "Initial Image" if you want to guide the AI.<br/><br/>You can also add modifiers like "Realistic", "Pencil Sketch", "ArtStation" etc by browsing through the "Image Modifiers" section and selecting the desired modifiers.<br/><br/>Click "Advanced Settings" for additional settings like seed, image size, number of images to generate etc.<br/><br/>Enjoy! :)
</div>
<div id="preview-tools">
<button id="clear-all-previews" class="secondaryButton"><i class="fa-solid fa-trash-can"></i> Clear All</button>
</div>
</div>
</div>
<div id="tab-content-settings" class="tab-content">
<div id="system-settings" class="tab-content-inner">
<h1>System Settings</h1>
<div class="parameters-table"></div>
<br/>
<button id="save-system-settings-btn" class="primaryButton">Save</button>
<br/><br/>
<div>
<h3><i class="fa fa-microchip icon"></i> System Info</h3>
<div id="system-info">
<table>
<tr><td><label>Processor:</label></td><td id="system-info-cpu" class="value"></td></tr>
<tr><td><label>Compatible Graphics Cards (all):</label></td><td id="system-info-gpus-all" class="value"></td></tr>
<tr><td></td><td>&nbsp;</td></tr>
<tr><td><label>Used for rendering 🔥:</label></td><td id="system-info-rendering-devices" class="value"></td></tr>
<tr><td><label>Server Addresses <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">You can access Stable Diffusion UI from other devices using these addresses</span></i> :</label></td><td id="system-info-server-hosts" class="value"></td></tr>
</table>
</div>
</div>
</div>
</div>
<div id="tab-content-about" class="tab-content">
<div class="tab-content-inner">
<div class="float-container">
<div class="float-child">
<h1>Help</h1>
<ul id="help-links">
<li><span class="help-section">Using the software</span>
<ul>
<li> <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/How-To-Use" target="_blank"><i class="fa-solid fa-book fa-fw"></i> How to use</a>
<li> <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/UI-Overview" target="_blank"><i class="fa-solid fa-list fa-fw"></i> UI Overview</a>
<li> <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Writing-Prompts" target="_blank"><i class="fa-solid fa-pen-to-square fa-fw"></i> Writing prompts</a>
<li> <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Inpainting" target="_blank"><i class="fa-solid fa-paintbrush fa-fw"></i> Inpainting</a>
<li> <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Run-on-Multiple-GPUs" target="_blank"><i class="fa-solid fa-paintbrush fa-fw"></i> Run on Multiple GPUs</a>
</ul>
<li><span class="help-section">Installation</span>
<ul>
<li> <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" target="_blank"><i class="fa-solid fa-circle-question fa-fw"></i> Troubleshooting</a>
</ul>
<li><span class="help-section">Downloadable Content</span>
<ul>
<li> <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Models" target="_blank"><i class="fa-solid fa-images fa-fw"></i> Custom Models</a>
<li> <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/UI-Plugins" target="_blank"><i class="fa-solid fa-puzzle-piece fa-fw"></i> UI Plugins</a>
<li> <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/VAE-Variational-Auto-Encoder" target="_blank"><i class="fa-solid fa-hand-sparkles fa-fw"></i> VAE Variational Auto Encoder</a>
</ul>
</ul>
</div>
<div class="float-child">
<h1>Community</h1>
<ul id="community-links">
<li><a href="https://discord.com/invite/u9yhsFmEkB" target="_blank"><i class="fa-brands fa-discord fa-fw"></i> Discord user community</a></li>
<li><a href="https://www.reddit.com/r/StableDiffusionUI/" target="_blank"><i class="fa-brands fa-reddit fa-fw"></i> Reddit community</a></li>
<li><a href="https://github.com/cmdr2/stable-diffusion-ui" target="_blank"><i class="fa-brands fa-github fa-fw"></i> Source code on GitHub</a></li>
</ul>
</div>
</div>
</div>
</div>
</div>
<div id="save-settings-config" class="popup">
<div>
<i class="close-button fa-solid fa-xmark"></i>
<h1>Save Settings Configuration</h1>
<p>Select which settings should be remembered when restarting the browser</p>
<table id="save-settings-config-table" class="form-table">
</table>
</div>
</div>
<div id="modifier-settings-config" class="popup">
<div>
<i class="close-button fa-solid fa-xmark"></i>
<h1>Modifier Settings</h1>
<p>Set your custom modifiers (one per line)</p>
<textarea id="custom-modifiers-input" placeholder="Enter your custom modifiers, one-per-line"></textarea>
<p><small><b>Tip:</b> You can include special characters like {} () [] and |. You can also put multiple comma-separated phrases in a single line, to make a single modifier that combines all of those.</small></p>
</div>
</div>
<div class="line-separator">&nbsp;</div>
<div id="image-editor" class="popup image-editor-popup">
<div>
<i class="close-button fa-solid fa-xmark"></i>
<h1>Image Editor</h1>
<div class="flex-container">
<div class="editor-controls-left"></div>
<div class="editor-controls-center">
<div></div>
</div>
<div class="editor-controls-right">
<div></div>
</div>
</div>
</div>
</div>
<div id="image-inpainter" class="popup image-editor-popup">
<div>
<i class="close-button fa-solid fa-xmark"></i>
<h1>Inpainter</h1>
<div class="flex-container">
<div class="editor-controls-left"></div>
<div class="editor-controls-center">
<div></div>
</div>
<div class="editor-controls-right">
<div></div>
</div>
</div>
</div>
</div>
<div id="footer-spacer"></div>
<div id="footer">
<div class="line-separator">&nbsp;</div>
<p>If you found this project useful and want to help keep it alive, please <a href="https://ko-fi.com/cmdr2_stablediffusion_ui" target="_blank"><img src="/media/images/kofi.png" id="coffeeButton"></a> to help cover the cost of development and maintenance! Thank you for your support!</p>
<div id="footer" class="panel-box">
<p>If you found this project useful and want to help keep it alive, please <a href="https://ko-fi.com/cmdr2_stablediffusion_ui" target="_blank"><img src="media/kofi.png" id="coffeeButton"></a> to help cover the cost of development and maintenance! Thank you for your support!</p>
<p>Please feel free to join the <a href="https://discord.com/invite/u9yhsFmEkB" target="_blank">discord community</a> or <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>
<div id="footer-legal">
<p><b>Disclaimer:</b> The authors of this project are not responsible for any content generated using this interface.</p>
@ -400,34 +212,16 @@
</div>
</div>
</body>
<script src="media/js/utils.js"></script>
<script src="media/js/engine.js"></script>
<script src="media/js/parameters.js"></script>
<script src="media/js/plugins.js"></script>
<script src="media/js/image-modifiers.js"></script>
<script src="media/js/auto-save.js"></script>
<script src="media/js/main.js"></script>
<script src="media/js/themes.js"></script>
<script src="media/js/dnd.js"></script>
<script src="media/js/image-editor.js"></script>
<script src="media/main.js?v=21"></script>
<script>
async function init() {
await initSettings()
await getModels()
await loadModifiers()
await getDiskPath()
await getAppConfig()
await loadUIPlugins()
await loadModifiers()
await getSystemInfo()
SD.init({
events: {
statusChange: setServerStatus
, idle: onIdle
}
})
setInterval(healthCheck, HEALTH_PING_INTERVAL * 1000)
healthCheck()
playSound()
}

View File

@ -1,81 +0,0 @@
/* Auto-Settings Styling */
#auto_save_settings ~ button {
margin: 5px;
}
#auto_save_settings:not(:checked) ~ button {
display: none;
}
.form-table {
margin: auto;
}
.form-table th {
padding-top: 15px;
padding-bottom: 5px;
}
.form-table td:first-child > *,
.form-table th:first-child > * {
float: right;
white-space: nowrap;
}
.form-table td:last-child > *,
.form-table th:last-child > * {
float: left;
}
.parameters-table {
display: flex;
flex-direction: column;
gap: 1px;
}
.parameters-table > div {
background: var(--background-color2);
display: flex;
padding: 0px 4px;
}
.parameters-table > div > div {
padding: 10px;
display: flex;
align-items: center;
justify-content: center;
}
.parameters-table small {
color: rgb(153, 153, 153);
}
.parameters-table > div > div:nth-child(1) {
font-size: 20px;
width: 45px;
}
.parameters-table > div > div:nth-child(2) {
flex: 1;
flex-direction: column;
text-align: left;
justify-content: center;
align-items: start;
gap: 4px;
}
.parameters-table > div > div:nth-child(3) {
text-align: right;
}
.parameters-table > div:first-child {
border-radius: 12px 12px 0px 0px;
}
.parameters-table > div:last-child {
border-radius: 0px 0px 12px 12px;
}
.parameters-table .fa-fire {
color: #F7630C;
}

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/* work-sans-regular - latin */
@font-face {
font-family: 'Work Sans';
font-style: normal;
font-weight: 400;
src: local(''),
url('/media/fonts/work-sans-v18-latin-regular.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
url('/media/fonts/work-sans-v18-latin-regular.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
}
/* work-sans-600 - latin */
@font-face {
font-family: 'Work Sans';
font-style: normal;
font-weight: 600;
src: local(''),
url('/media/fonts/work-sans-v18-latin-600.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
url('/media/fonts/work-sans-v18-latin-600.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
}
/* work-sans-700 - latin */
@font-face {
font-family: 'Work Sans';
font-style: normal;
font-weight: 700;
src: local(''),
url('/media/fonts/work-sans-v18-latin-700.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
url('/media/fonts/work-sans-v18-latin-700.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
}
/* work-sans-800 - latin */
@font-face {
font-family: 'Work Sans';
font-style: normal;
font-weight: 800;
src: local(''),
url('/media/fonts/work-sans-v18-latin-800.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
url('/media/fonts/work-sans-v18-latin-800.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
}

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.editor-controls-left {
padding-left: 32px;
text-align: left;
padding-bottom: 20px;
}
.editor-options-container {
display: flex;
row-gap: 10px;
max-width: 210px;
}
.editor-options-container > * {
flex: 1;
display: flex;
justify-content: center;
align-items: center;
}
.editor-options-container > * > * {
position: inherit;
width: 32px;
height: 32px;
border-radius: 16px;
background: var(--background-color3);
cursor: pointer;
transition: opacity 0.25s;
}
.editor-options-container > * > *:hover {
opacity: 0.75;
}
.editor-options-container > * > *.active {
border: 2px solid #3584e4;
}
.image_editor_opacity .editor-options-container > * > *:not(.active) {
border: 1px solid var(--background-color3);
}
.image_editor_color .editor-options-container {
flex-wrap: wrap;
}
.image_editor_color .editor-options-container > * {
flex: 20%;
}
.image_editor_color .editor-options-container > * > * {
position: relative;
}
.image_editor_color .editor-options-container > * > *.active::before {
content: "\f00c";
display: var(--fa-display,inline-block);
font-style: normal;
font-variant: normal;
line-height: 1;
text-rendering: auto;
font-family: var(--fa-style-family, "Font Awesome 6 Free");
font-weight: var(--fa-style, 900);
position: absolute;
left: 50%;
top: 50%;
transform: translate(-50%, -50%) scale(125%);
color: black;
}
.image_editor_color .editor-options-container > *:first-child {
flex: 100%;
}
.image_editor_color .editor-options-container > *:first-child > * {
width: 100%;
}
.image_editor_color .editor-options-container > *:first-child > * > input {
width: 100%;
height: 100%;
opacity: 0;
cursor: pointer;
}
.image_editor_color .editor-options-container > *:first-child > * > span {
position: absolute;
left: 50%;
top: 50%;
transform: translate(-50%, -50%);
opacity: 0.5;
}
.image_editor_color .editor-options-container > *:first-child > *.active > span {
opacity: 0;
}
.image_editor_tool .editor-options-container {
flex-wrap: wrap;
}
.image_editor_tool .editor-options-container > * {
padding: 2px;
flex: 50%;
}
.editor-controls-center {
/* background: var(--background-color2); */
flex: 1;
display: flex;
justify-content: center;
align-items: center;
}
.editor-controls-center > div {
position: relative;
background: black;
}
.editor-controls-center canvas {
position: absolute;
left: 0;
top: 0;
}
.editor-controls-right {
padding: 32px;
display: flex;
flex-direction: column;
}
.editor-controls-right > div:last-child {
flex: 1;
display: flex;
flex-direction: column;
min-width: 200px;
gap: 5px;
justify-content: end;
}
.image-editor-button {
width: 100%;
height: 32px;
border-radius: 16px;
background: var(--background-color3);
}
.editor-controls-right .image-editor-button {
margin-bottom: 4px;
}
#init_image_button_inpaint .input-toggle {
position: absolute;
left: 16px;
}
#init_image_button_inpaint .input-toggle input:not(:checked) ~ label {
pointer-events: none;
}
.image-editor-popup {
--popup-margin: 16px;
--popup-padding: 24px;
}
.image-editor-popup > div {
margin: var(--popup-margin);
padding: var(--popup-padding);
min-height: calc(100vh - (2 * var(--popup-margin)));
max-width: none;
}
.image-editor-popup h1 {
position: absolute;
top: 32px;
left: 50%;
transform: translateX(-50%);
}
@media screen and (max-width: 700px) {
.image-editor-popup > div {
margin: 0px;
padding: 0px;
}
.image-editor-popup h1 {
position: relative;
transform: none;
left: auto;
}
}
.image-editor-popup > div > div {
min-height: calc(100vh - (2 * var(--popup-margin)) - (2 * var(--popup-padding)));
}
.inpainter .image_editor_color {
display: none;
}
.inpainter .editor-canvas-background {
opacity: 0.75;
}
#init_image_preview_container .button {
display: flex;
padding: 6px;
height: 24px;
box-shadow: 2px 2px 1px 1px #00000088;
}
#init_image_preview_container .button:hover {
background: var(--background-color4)
}
.image-editor-popup .button {
display: flex;
}
.image-editor-popup h4 {
text-align: left;
}

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:root {
--main-hue: 222;
--main-saturation: 4%;
--value-base: 13%;
--value-step: 5%;
--background-color1: hsl(var(--main-hue), var(--main-saturation), var(--value-base));
--background-color2: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (1 * var(--value-step))));
--background-color3: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (0.5 * var(--value-step))));
--background-color4: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (1.5 * var(--value-step))));
--accent-hue: 267;
--accent-lightness: 36%;
--accent-lightness-hover: 40%;
--text-color: #eee;
--input-text-color: #eee;
--input-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (0.7 * var(--value-step))));
--input-border-color: var(--background-color4);
--button-text-color: var(--input-text-color);
--button-color: var(--input-background-color);
--button-border: none;
/* other */
--input-border-radius: 4px;
--input-border-size: 1px;
--accent-color: hsl(var(--accent-hue), 100%, var(--accent-lightness));
--accent-color-hover: hsl(var(--accent-hue), 100%, var(--accent-lightness-hover));
--primary-button-border: none;
--input-switch-padding: 1px;
--input-height: 18px;
/* Main theme color, hex color fallback. */
--theme-color-fallback: #673AB6;
}
.theme-light {
--background-color1: white;
--background-color2: #ececec;
--background-color3: #e7e9eb;
--background-color4: #cccccc;
--text-color: black;
--input-text-color: black;
--input-background-color: #f8f9fa;
--input-border-color: grey;
--theme-color-fallback: #aaaaaa;
}
.theme-discord {
--background-color1: #36393f;
--background-color2: #2f3136;
--background-color3: #292b2f;
--background-color4: #202225;
--accent-hue: 235;
--accent-lightness: 65%;
--input-border-size: 2px;
--input-background-color: #202225;
--input-border-color: var(--input-background-color);
--theme-color-fallback: #202225;
}
.theme-cool-blue {
--main-hue: 222;
--main-saturation: 18%;
--value-base: 18%;
--value-step: 3%;
--background-color1: hsl(var(--main-hue), var(--main-saturation), var(--value-base));
--background-color2: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (1 * var(--value-step))));
--background-color3: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (2 * var(--value-step))));
--background-color4: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (3 * var(--value-step))));
--input-background-color: var(--background-color3);
--accent-hue: 212;
--theme-color-fallback: #0056b8;
}
.theme-blurple {
--main-hue: 235;
--main-saturation: 18%;
--value-base: 16%;
--value-step: 3%;
--background-color1: hsl(var(--main-hue), var(--main-saturation), var(--value-base));
--background-color2: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (1 * var(--value-step))));
--background-color3: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (2 * var(--value-step))));
--background-color4: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (3 * var(--value-step))));
--input-background-color: var(--background-color3);
--theme-color-fallback: #5300b8;
}
.theme-super-dark {
--main-hue: 222;
--main-saturation: 18%;
--value-base: 5%;
--value-step: 5%;
--background-color1: hsl(var(--main-hue), var(--main-saturation), var(--value-base));
--background-color2: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (1 * var(--value-step))));
--background-color3: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (2 * var(--value-step))));
--background-color4: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (1.4 * var(--value-step))));
--input-background-color: var(--background-color3);
--input-border-size: 0px;
--theme-color-fallback: #000000;
}
.theme-wild {
--main-hue: 128;
--main-saturation: 18%;
--value-base: 20%;
--value-step: 5%;
--background-color1: hsl(var(--main-hue), var(--main-saturation), var(--value-base));
--background-color2: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (1 * var(--value-step))));
--background-color3: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (2 * var(--value-step))));
--background-color4: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (3 * var(--value-step))));
--accent-hue: 212;
--input-border-size: 1px;
--input-background-color: hsl(222, var(--main-saturation), calc(var(--value-base) - (2 * var(--value-step))));
--input-text-color: #FF0000;
--input-border-color: #005E05;
}
.theme-gnomie {
--background-color1: #242424;
--background-color2: #353535;
--background-color3: #494949;
--background-color4: #000000;
--accent-hue: 213;
--accent-lightness: 55%;
--accent-color: #2168bf;
--input-border-radius: 6px;
--input-text-color: #ffffff;
--input-background-color: #2a2a2a;
--input-border-size: 0px;
--input-border-color: var(--input-background-color);
--theme-color-fallback: #2168bf;
}
.theme-gnomie .panel-box {
border: none;
box-shadow: 0px 1px 2px rgba(0, 0, 0, 0.25);
border-radius: 10px;
}

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// Saving settings
let saveSettingsConfigTable = document.getElementById("save-settings-config-table")
let saveSettingsConfigOverlay = document.getElementById("save-settings-config")
let resetImageSettingsButton = document.getElementById("reset-image-settings")
const SETTINGS_KEY = "user_settings_v2"
const SETTINGS = {} // key=id. dict initialized in initSettings. { element, default, value, ignore }
const SETTINGS_IDS_LIST = [
"prompt",
"seed",
"random_seed",
"num_outputs_total",
"num_outputs_parallel",
"stable_diffusion_model",
"vae_model",
"hypernetwork_model",
"sampler",
"width",
"height",
"num_inference_steps",
"guidance_scale",
"prompt_strength",
"hypernetwork_strength",
"output_format",
"output_quality",
"negative_prompt",
"stream_image_progress",
"use_face_correction",
"use_upscale",
"show_only_filtered_image",
"upscale_model",
"preview-image",
"modifier-card-size-slider",
"theme",
"save_to_disk",
"diskPath",
"sound_toggle",
"turbo",
"use_full_precision",
"confirm_dangerous_actions",
"auto_save_settings"
]
const IGNORE_BY_DEFAULT = [
"prompt"
]
const SETTINGS_SECTIONS = [ // gets the "keys" property filled in with an ordered list of settings in this section via initSettings
{ id: "editor-inputs", name: "Prompt" },
{ id: "editor-settings", name: "Image Settings" },
{ id: "system-settings", name: "System Settings" },
{ id: "container", name: "Other" }
]
async function initSettings() {
SETTINGS_IDS_LIST.forEach(id => {
var element = document.getElementById(id)
if (!element) {
console.error(`Missing settings element ${id}`)
}
if (id in SETTINGS) { // don't create it again
return
}
SETTINGS[id] = {
key: id,
element: element,
label: getSettingLabel(element),
default: getSetting(element),
value: getSetting(element),
ignore: IGNORE_BY_DEFAULT.includes(id)
}
element.addEventListener("input", settingChangeHandler)
element.addEventListener("change", settingChangeHandler)
})
var unsorted_settings_ids = [...SETTINGS_IDS_LIST]
SETTINGS_SECTIONS.forEach(section => {
var name = section.name
var element = document.getElementById(section.id)
var unsorted_ids = unsorted_settings_ids.map(id => `#${id}`).join(",")
var children = unsorted_ids == "" ? [] : Array.from(element.querySelectorAll(unsorted_ids));
section.keys = []
children.forEach(e => {
section.keys.push(e.id)
})
unsorted_settings_ids = unsorted_settings_ids.filter(id => children.find(e => e.id == id) == undefined)
})
loadSettings()
}
function getSetting(element) {
if (typeof element === "string" || element instanceof String) {
element = SETTINGS[element].element
}
if (element.type == "checkbox") {
return element.checked
}
return element.value
}
function setSetting(element, value) {
if (typeof element === "string" || element instanceof String) {
element = SETTINGS[element].element
}
SETTINGS[element.id].value = value
if (getSetting(element) == value) {
return // no setting necessary
}
if (element.type == "checkbox") {
element.checked = value
}
else {
element.value = value
}
element.dispatchEvent(new Event("input"))
element.dispatchEvent(new Event("change"))
}
function saveSettings() {
var saved_settings = Object.values(SETTINGS).map(setting => {
return {
key: setting.key,
value: setting.value,
ignore: setting.ignore
}
})
localStorage.setItem(SETTINGS_KEY, JSON.stringify(saved_settings))
}
var CURRENTLY_LOADING_SETTINGS = false
function loadSettings() {
var saved_settings_text = localStorage.getItem(SETTINGS_KEY)
if (saved_settings_text) {
var saved_settings = JSON.parse(saved_settings_text)
if (saved_settings.find(s => s.key == "auto_save_settings")?.value == false) {
setSetting("auto_save_settings", false)
return
}
CURRENTLY_LOADING_SETTINGS = true
saved_settings.forEach(saved_setting => {
var setting = SETTINGS[saved_setting.key]
if (!setting) {
console.warn(`Attempted to load setting ${saved_setting.key}, but no setting found`);
return null;
}
setting.ignore = saved_setting.ignore
if (!setting.ignore) {
setting.value = saved_setting.value
setSetting(setting.element, setting.value)
}
})
CURRENTLY_LOADING_SETTINGS = false
}
else {
CURRENTLY_LOADING_SETTINGS = true
tryLoadOldSettings();
CURRENTLY_LOADING_SETTINGS = false
saveSettings()
}
}
function loadDefaultSettingsSection(section_id) {
CURRENTLY_LOADING_SETTINGS = true
var section = SETTINGS_SECTIONS.find(s => s.id == section_id);
section.keys.forEach(key => {
var setting = SETTINGS[key];
setting.value = setting.default
setSetting(setting.element, setting.value)
})
CURRENTLY_LOADING_SETTINGS = false
saveSettings()
}
function settingChangeHandler(event) {
if (!CURRENTLY_LOADING_SETTINGS) {
var element = event.target
var value = getSetting(element)
if (value != SETTINGS[element.id].value) {
SETTINGS[element.id].value = value
saveSettings()
}
}
}
function getSettingLabel(element) {
var labelElement = document.querySelector(`label[for='${element.id}']`)
var label = labelElement?.innerText || element.id
var truncate_length = 30
if (label.includes(" (")) {
label = label.substring(0, label.indexOf(" ("))
}
if (label.length > truncate_length) {
label = label.substring(0, truncate_length - 3) + "..."
}
label = label.replace("", "")
label = label.replace("", "")
return label
}
function fillSaveSettingsConfigTable() {
saveSettingsConfigTable.textContent = ""
SETTINGS_SECTIONS.forEach(section => {
var section_row = `<tr><th>${section.name}</th><td></td></tr>`
saveSettingsConfigTable.insertAdjacentHTML("beforeend", section_row)
section.keys.forEach(key => {
var setting = SETTINGS[key]
var element = setting.element
var checkbox_id = `shouldsave_${element.id}`
var is_checked = setting.ignore ? "" : "checked"
var value = setting.value
var value_truncate_length = 30
if ((typeof value === "string" || value instanceof String) && value.length > value_truncate_length) {
value = value.substring(0, value_truncate_length - 3) + "..."
}
var newrow = `<tr><td><label for="${checkbox_id}">${setting.label}</label></td><td><input id="${checkbox_id}" name="${checkbox_id}" ${is_checked} type="checkbox" ></td><td><small>(${value})</small></td></tr>`
saveSettingsConfigTable.insertAdjacentHTML("beforeend", newrow)
var checkbox = document.getElementById(checkbox_id)
checkbox.addEventListener("input", event => {
setting.ignore = !checkbox.checked
saveSettings()
})
})
})
prettifyInputs(saveSettingsConfigTable)
}
// configureSettingsSaveBtn
var autoSaveSettings = document.getElementById("auto_save_settings")
var configSettingsButton = document.createElement("button")
configSettingsButton.textContent = "Configure"
configSettingsButton.style.margin = "0px 5px"
autoSaveSettings.insertAdjacentElement("beforebegin", configSettingsButton)
autoSaveSettings.addEventListener("change", () => {
configSettingsButton.style.display = autoSaveSettings.checked ? "block" : "none"
})
configSettingsButton.addEventListener('click', () => {
fillSaveSettingsConfigTable()
saveSettingsConfigOverlay.classList.add("active")
})
resetImageSettingsButton.addEventListener('click', event => {
loadDefaultSettingsSection("editor-settings");
event.stopPropagation()
})
function tryLoadOldSettings() {
console.log("Loading old user settings")
// load v1 auto-save.js settings
var old_map = {
"guidance_scale_slider": "guidance_scale",
"prompt_strength_slider": "prompt_strength"
}
var settings_key_v1 = "user_settings"
var saved_settings_text = localStorage.getItem(settings_key_v1)
if (saved_settings_text) {
var saved_settings = JSON.parse(saved_settings_text)
Object.keys(saved_settings.should_save).forEach(key => {
key = key in old_map ? old_map[key] : key
SETTINGS[key].ignore = !saved_settings.should_save[key]
});
Object.keys(saved_settings.values).forEach(key => {
key = key in old_map ? old_map[key] : key
var setting = SETTINGS[key]
if (!setting.ignore) {
setting.value = saved_settings.values[key]
setSetting(setting.element, setting.value)
}
});
localStorage.removeItem(settings_key_v1)
}
// load old individually stored items
var individual_settings_map = { // maps old localStorage-key to new SETTINGS-key
"soundEnabled": "sound_toggle",
"saveToDisk": "save_to_disk",
"useCPU": "use_cpu",
"useFullPrecision": "use_full_precision",
"useTurboMode": "turbo",
"diskPath": "diskPath",
"useFaceCorrection": "use_face_correction",
"useUpscaling": "use_upscale",
"showOnlyFilteredImage": "show_only_filtered_image",
"streamImageProgress": "stream_image_progress",
"outputFormat": "output_format",
"autoSaveSettings": "auto_save_settings",
};
Object.keys(individual_settings_map).forEach(localStorageKey => {
var localStorageValue = localStorage.getItem(localStorageKey);
if (localStorageValue !== null) {
let key = individual_settings_map[localStorageKey]
var setting = SETTINGS[key]
if (!setting) {
console.warn(`Attempted to map old setting ${key}, but no setting found`);
return null;
}
if (setting.element.type == "checkbox" && (typeof localStorageValue === "string" || localStorageValue instanceof String)) {
localStorageValue = localStorageValue == "true"
}
setting.value = localStorageValue
setSetting(setting.element, setting.value)
localStorage.removeItem(localStorageKey);
}
})
}

View File

@ -1,555 +0,0 @@
"use strict" // Opt in to a restricted variant of JavaScript
const EXT_REGEX = /(?:\.([^.]+))?$/
const TEXT_EXTENSIONS = ['txt', 'json']
const IMAGE_EXTENSIONS = ['jpg', 'jpeg', 'png', 'bmp', 'tiff', 'tif', 'tga']
function parseBoolean(stringValue) {
if (typeof stringValue === 'boolean') {
return stringValue
}
if (typeof stringValue === 'number') {
return stringValue !== 0
}
if (typeof stringValue !== 'string') {
return false
}
switch(stringValue?.toLowerCase()?.trim()) {
case "true":
case "yes":
case "on":
case "1":
return true;
case "false":
case "no":
case "off":
case "0":
case null:
case undefined:
return false;
}
try {
return Boolean(JSON.parse(stringValue));
} catch {
return Boolean(stringValue)
}
}
const TASK_MAPPING = {
prompt: { name: 'Prompt',
setUI: (prompt) => {
promptField.value = prompt
},
readUI: () => promptField.value,
parse: (val) => val
},
negative_prompt: { name: 'Negative Prompt',
setUI: (negative_prompt) => {
negativePromptField.value = negative_prompt
},
readUI: () => negativePromptField.value,
parse: (val) => val
},
active_tags: { name: "Image Modifiers",
setUI: (active_tags) => {
refreshModifiersState(active_tags)
},
readUI: () => activeTags.map(x => x.name),
parse: (val) => val
},
width: { name: 'Width',
setUI: (width) => {
const oldVal = widthField.value
widthField.value = width
if (!widthField.value) {
widthField.value = oldVal
}
},
readUI: () => parseInt(widthField.value),
parse: (val) => parseInt(val)
},
height: { name: 'Height',
setUI: (height) => {
const oldVal = heightField.value
heightField.value = height
if (!heightField.value) {
heightField.value = oldVal
}
},
readUI: () => parseInt(heightField.value),
parse: (val) => parseInt(val)
},
seed: { name: 'Seed',
setUI: (seed) => {
if (!seed) {
randomSeedField.checked = true
seedField.disabled = true
seedField.value = 0
return
}
randomSeedField.checked = false
seedField.disabled = false
seedField.value = seed
},
readUI: () => parseInt(seedField.value), // just return the value the user is seeing in the UI
parse: (val) => parseInt(val)
},
num_inference_steps: { name: 'Steps',
setUI: (num_inference_steps) => {
numInferenceStepsField.value = num_inference_steps
},
readUI: () => parseInt(numInferenceStepsField.value),
parse: (val) => parseInt(val)
},
guidance_scale: { name: 'Guidance Scale',
setUI: (guidance_scale) => {
guidanceScaleField.value = guidance_scale
updateGuidanceScaleSlider()
},
readUI: () => parseFloat(guidanceScaleField.value),
parse: (val) => parseFloat(val)
},
prompt_strength: { name: 'Prompt Strength',
setUI: (prompt_strength) => {
promptStrengthField.value = prompt_strength
updatePromptStrengthSlider()
},
readUI: () => parseFloat(promptStrengthField.value),
parse: (val) => parseFloat(val)
},
init_image: { name: 'Initial Image',
setUI: (init_image) => {
initImagePreview.src = init_image
},
readUI: () => initImagePreview.src,
parse: (val) => val
},
mask: { name: 'Mask',
setUI: (mask) => {
setTimeout(() => { // add a delay to insure this happens AFTER the main image loads (which reloads the inpainter)
imageInpainter.setImg(mask)
}, 250)
maskSetting.checked = Boolean(mask)
},
readUI: () => (maskSetting.checked ? imageInpainter.getImg() : undefined),
parse: (val) => val
},
use_face_correction: { name: 'Use Face Correction',
setUI: (use_face_correction) => {
useFaceCorrectionField.checked = parseBoolean(use_face_correction)
},
readUI: () => useFaceCorrectionField.checked,
parse: (val) => parseBoolean(val)
},
use_upscale: { name: 'Use Upscaling',
setUI: (use_upscale) => {
const oldVal = upscaleModelField.value
upscaleModelField.value = use_upscale
if (upscaleModelField.value) { // Is a valid value for the field.
useUpscalingField.checked = true
upscaleModelField.disabled = false
} else { // Not a valid value, restore the old value and disable the filter.
upscaleModelField.disabled = true
upscaleModelField.value = oldVal
useUpscalingField.checked = false
}
},
readUI: () => (useUpscalingField.checked ? upscaleModelField.value : undefined),
parse: (val) => val
},
sampler: { name: 'Sampler',
setUI: (sampler) => {
samplerField.value = sampler
},
readUI: () => samplerField.value,
parse: (val) => val
},
use_stable_diffusion_model: { name: 'Stable Diffusion model',
setUI: (use_stable_diffusion_model) => {
const oldVal = stableDiffusionModelField.value
use_stable_diffusion_model = getModelPath(use_stable_diffusion_model, ['.ckpt'])
stableDiffusionModelField.value = use_stable_diffusion_model
if (!stableDiffusionModelField.value) {
stableDiffusionModelField.value = oldVal
}
},
readUI: () => stableDiffusionModelField.value,
parse: (val) => val
},
use_vae_model: { name: 'VAE model',
setUI: (use_vae_model) => {
const oldVal = vaeModelField.value
if (use_vae_model !== '') {
use_vae_model = getModelPath(use_vae_model, ['.vae.pt', '.ckpt'])
use_vae_model = use_vae_model !== '' ? use_vae_model : oldVal
}
vaeModelField.value = use_vae_model
},
readUI: () => vaeModelField.value,
parse: (val) => val
},
use_hypernetwork_model: { name: 'Hypernetwork model',
setUI: (use_hypernetwork_model) => {
const oldVal = hypernetworkModelField.value
if (use_hypernetwork_model !== '') {
use_hypernetwork_model = getModelPath(use_hypernetwork_model, ['.pt'])
use_hypernetwork_model = use_hypernetwork_model !== '' ? use_hypernetwork_model : oldVal
}
hypernetworkModelField.value = use_hypernetwork_model
hypernetworkModelField.dispatchEvent(new Event('change'))
},
readUI: () => hypernetworkModelField.value,
parse: (val) => val
},
hypernetwork_strength: { name: 'Hypernetwork Strength',
setUI: (hypernetwork_strength) => {
hypernetworkStrengthField.value = hypernetwork_strength
updateHypernetworkStrengthSlider()
},
readUI: () => parseFloat(hypernetworkStrengthField.value),
parse: (val) => parseFloat(val)
},
num_outputs: { name: 'Parallel Images',
setUI: (num_outputs) => {
numOutputsParallelField.value = num_outputs
},
readUI: () => parseInt(numOutputsParallelField.value),
parse: (val) => val
},
use_cpu: { name: 'Use CPU',
setUI: (use_cpu) => {
useCPUField.checked = use_cpu
},
readUI: () => useCPUField.checked,
parse: (val) => val
},
turbo: { name: 'Turbo',
setUI: (turbo) => {
turboField.checked = turbo
},
readUI: () => turboField.checked,
parse: (val) => Boolean(val)
},
use_full_precision: { name: 'Use Full Precision',
setUI: (use_full_precision) => {
useFullPrecisionField.checked = use_full_precision
},
readUI: () => useFullPrecisionField.checked,
parse: (val) => Boolean(val)
},
stream_image_progress: { name: 'Stream Image Progress',
setUI: (stream_image_progress) => {
streamImageProgressField.checked = (parseInt(numOutputsTotalField.value) > 50 ? false : stream_image_progress)
},
readUI: () => streamImageProgressField.checked,
parse: (val) => Boolean(val)
},
show_only_filtered_image: { name: 'Show only the corrected/upscaled image',
setUI: (show_only_filtered_image) => {
showOnlyFilteredImageField.checked = show_only_filtered_image
},
readUI: () => showOnlyFilteredImageField.checked,
parse: (val) => Boolean(val)
},
output_format: { name: 'Output Format',
setUI: (output_format) => {
outputFormatField.value = output_format
},
readUI: () => outputFormatField.value,
parse: (val) => val
},
save_to_disk_path: { name: 'Save to disk path',
setUI: (save_to_disk_path) => {
saveToDiskField.checked = Boolean(save_to_disk_path)
diskPathField.value = save_to_disk_path
},
readUI: () => diskPathField.value,
parse: (val) => val
}
}
function restoreTaskToUI(task, fieldsToSkip) {
fieldsToSkip = fieldsToSkip || []
if ('numOutputsTotal' in task) {
numOutputsTotalField.value = task.numOutputsTotal
}
if ('seed' in task) {
randomSeedField.checked = false
seedField.value = task.seed
}
if (!('reqBody' in task)) {
return
}
for (const key in TASK_MAPPING) {
if (key in task.reqBody && !fieldsToSkip.includes(key)) {
TASK_MAPPING[key].setUI(task.reqBody[key])
}
}
// restore the original tag
promptField.value = task.reqBody.original_prompt || task.reqBody.prompt
// properly reset checkboxes
if (!('use_face_correction' in task.reqBody)) {
useFaceCorrectionField.checked = false
}
if (!('use_upscale' in task.reqBody)) {
useUpscalingField.checked = false
}
if (!('mask' in task.reqBody)) {
maskSetting.checked = false
}
upscaleModelField.disabled = !useUpscalingField.checked
// Show the source picture if present
initImagePreview.src = (task.reqBody.init_image == undefined ? '' : task.reqBody.init_image)
if (IMAGE_REGEX.test(initImagePreview.src)) {
if (Boolean(task.reqBody.mask)) {
setTimeout(() => { // add a delay to insure this happens AFTER the main image loads (which reloads the inpainter)
imageInpainter.setImg(task.reqBody.mask)
}, 250)
}
}
}
function readUI() {
const reqBody = {}
for (const key in TASK_MAPPING) {
reqBody[key] = TASK_MAPPING[key].readUI()
}
return {
'numOutputsTotal': parseInt(numOutputsTotalField.value),
'seed': TASK_MAPPING['seed'].readUI(),
'reqBody': reqBody
}
}
function getModelPath(filename, extensions)
{
let pathIdx = filename.lastIndexOf('/') // Linux, Mac paths
if (pathIdx < 0) {
pathIdx = filename.lastIndexOf('\\') // Windows paths.
}
if (pathIdx >= 0) {
filename = filename.slice(pathIdx + 1)
}
extensions.forEach(ext => {
if (filename.endsWith(ext)) {
filename = filename.slice(0, filename.length - ext.length)
}
})
return filename
}
const TASK_TEXT_MAPPING = {
width: 'Width',
height: 'Height',
seed: 'Seed',
num_inference_steps: 'Steps',
guidance_scale: 'Guidance Scale',
prompt_strength: 'Prompt Strength',
use_face_correction: 'Use Face Correction',
use_upscale: 'Use Upscaling',
sampler: 'Sampler',
negative_prompt: 'Negative Prompt',
use_stable_diffusion_model: 'Stable Diffusion model',
use_hypernetwork_model: 'Hypernetwork model',
hypernetwork_strength: 'Hypernetwork Strength'
}
const afterPromptRe = /^\s*Width\s*:\s*\d+\s*(?:\r\n|\r|\n)+\s*Height\s*:\s*\d+\s*(\r\n|\r|\n)+Seed\s*:\s*\d+\s*$/igm
function parseTaskFromText(str) {
const taskReqBody = {}
// Prompt
afterPromptRe.lastIndex = 0
const match = afterPromptRe.exec(str)
if (match) {
let prompt = str.slice(0, match.index)
str = str.slice(prompt.length)
taskReqBody.prompt = prompt.trim()
console.log('Prompt:', taskReqBody.prompt)
}
for (const key in TASK_TEXT_MAPPING) {
const name = TASK_TEXT_MAPPING[key];
let val = undefined
const reName = new RegExp(`${name}\\ *:\\ *(.*)(?:\\r\\n|\\r|\\n)*`, 'igm')
const match = reName.exec(str);
if (match) {
str = str.slice(0, match.index) + str.slice(match.index + match[0].length)
val = match[1]
}
if (val !== undefined) {
taskReqBody[key] = TASK_MAPPING[key].parse(val.trim())
console.log(TASK_MAPPING[key].name + ':', taskReqBody[key])
if (!str) {
break
}
}
}
if (Object.keys(taskReqBody).length <= 0) {
return undefined
}
const task = { reqBody: taskReqBody }
if ('seed' in taskReqBody) {
task.seed = taskReqBody.seed
}
return task
}
async function parseContent(text) {
text = text.trim();
if (text.startsWith('{') && text.endsWith('}')) {
try {
const task = JSON.parse(text)
restoreTaskToUI(task)
return true
} catch (e) {
console.warn(`JSON text content couldn't be parsed.`, e)
}
return false
}
// Normal txt file.
const task = parseTaskFromText(text)
if (task) {
restoreTaskToUI(task)
return true
} else {
console.warn(`Raw text content couldn't be parsed.`)
return false
}
}
async function readFile(file, i) {
console.log(`Event %o reading file[${i}]:${file.name}...`)
const fileContent = (await file.text()).trim()
return await parseContent(fileContent)
}
function dropHandler(ev) {
console.log('Content dropped...')
let items = []
if (ev?.dataTransfer?.items) { // Use DataTransferItemList interface
items = Array.from(ev.dataTransfer.items)
items = items.filter(item => item.kind === 'file')
items = items.map(item => item.getAsFile())
} else if (ev?.dataTransfer?.files) { // Use DataTransfer interface
items = Array.from(ev.dataTransfer.files)
}
items.forEach(item => {item.file_ext = EXT_REGEX.exec(item.name.toLowerCase())[1]})
let text_items = items.filter(item => TEXT_EXTENSIONS.includes(item.file_ext))
let image_items = items.filter(item => IMAGE_EXTENSIONS.includes(item.file_ext))
if (image_items.length > 0 && ev.target == initImageSelector) {
return // let the event bubble up, so that the Init Image filepicker can receive this
}
ev.preventDefault() // Prevent default behavior (Prevent file/content from being opened)
text_items.forEach(readFile)
}
function dragOverHandler(ev) {
console.log('Content in drop zone')
// Prevent default behavior (Prevent file/content from being opened)
ev.preventDefault()
ev.dataTransfer.dropEffect = "copy"
let img = new Image()
img.src = location.host + '/media/images/favicon-32x32.png'
ev.dataTransfer.setDragImage(img, 16, 16)
}
document.addEventListener("drop", dropHandler)
document.addEventListener("dragover", dragOverHandler)
const TASK_REQ_NO_EXPORT = [
"use_cpu",
"turbo",
"use_full_precision",
"save_to_disk_path"
]
const resetSettings = document.getElementById('reset-image-settings')
function checkReadTextClipboardPermission (result) {
if (result.state != "granted" && result.state != "prompt") {
return
}
// PASTE ICON
const pasteIcon = document.createElement('i')
pasteIcon.className = 'fa-solid fa-paste section-button'
pasteIcon.innerHTML = `<span class="simple-tooltip top-left">Paste Image Settings</span>`
pasteIcon.addEventListener('click', async (event) => {
event.stopPropagation()
// Add css class 'active'
pasteIcon.classList.add('active')
// In 350 ms remove the 'active' class
asyncDelay(350).then(() => pasteIcon.classList.remove('active'))
// Retrieve clipboard content and try to parse it
const text = await navigator.clipboard.readText();
await parseContent(text)
})
resetSettings.parentNode.insertBefore(pasteIcon, resetSettings)
}
navigator.permissions.query({ name: "clipboard-read" }).then(checkReadTextClipboardPermission, (reason) => console.log('clipboard-read is not available. %o', reason))
document.addEventListener('paste', async (event) => {
if (event.target) {
const targetTag = event.target.tagName.toLowerCase()
// Disable when targeting input elements.
if (targetTag === 'input' || targetTag === 'textarea') {
return
}
}
const paste = (event.clipboardData || window.clipboardData).getData('text')
const selection = window.getSelection()
if (selection.toString().trim().length <= 0 && await parseContent(paste)) {
event.preventDefault()
return
}
})
// Adds a copy and a paste icon if the browser grants permission to write to clipboard.
function checkWriteToClipboardPermission (result) {
if (result.state != "granted" && result.state != "prompt") {
return
}
// COPY ICON
const copyIcon = document.createElement('i')
copyIcon.className = 'fa-solid fa-clipboard section-button'
copyIcon.innerHTML = `<span class="simple-tooltip top-left">Copy Image Settings</span>`
copyIcon.addEventListener('click', (event) => {
event.stopPropagation()
// Add css class 'active'
copyIcon.classList.add('active')
// In 350 ms remove the 'active' class
asyncDelay(350).then(() => copyIcon.classList.remove('active'))
const uiState = readUI()
TASK_REQ_NO_EXPORT.forEach((key) => delete uiState.reqBody[key])
if (uiState.reqBody.init_image && !IMAGE_REGEX.test(uiState.reqBody.init_image)) {
delete uiState.reqBody.init_image
delete uiState.reqBody.prompt_strength
}
navigator.clipboard.writeText(JSON.stringify(uiState, undefined, 4))
})
resetSettings.parentNode.insertBefore(copyIcon, resetSettings)
}
// Determine which access we have to the clipboard. Clipboard access is only available on localhost or via TLS.
navigator.permissions.query({ name: "clipboard-write" }).then(checkWriteToClipboardPermission, (e) => {
if (e instanceof TypeError && typeof navigator?.clipboard?.writeText === 'function') {
// Fix for firefox https://bugzilla.mozilla.org/show_bug.cgi?id=1560373
checkWriteToClipboardPermission({state:"granted"})
}
})

File diff suppressed because it is too large Load Diff

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@ -1,706 +0,0 @@
var editorControlsLeft = document.getElementById("image-editor-controls-left")
const IMAGE_EDITOR_MAX_SIZE = 800
const IMAGE_EDITOR_BUTTONS = [
{
name: "Cancel",
icon: "fa-regular fa-circle-xmark",
handler: editor => {
editor.hide()
}
},
{
name: "Save",
icon: "fa-solid fa-floppy-disk",
handler: editor => {
editor.saveImage()
}
}
]
const defaultToolBegin = (editor, ctx, x, y, is_overlay = false) => {
ctx.beginPath()
ctx.moveTo(x, y)
}
const defaultToolMove = (editor, ctx, x, y, is_overlay = false) => {
ctx.lineTo(x, y)
if (is_overlay) {
ctx.clearRect(0, 0, editor.width, editor.height)
ctx.stroke()
}
}
const defaultToolEnd = (editor, ctx, x, y, is_overlay = false) => {
ctx.stroke()
if (is_overlay) {
ctx.clearRect(0, 0, editor.width, editor.height)
}
}
const IMAGE_EDITOR_TOOLS = [
{
id: "draw",
name: "Draw",
icon: "fa-solid fa-pencil",
cursor: "url(/media/images/fa-pencil.png) 0 24, pointer",
begin: defaultToolBegin,
move: defaultToolMove,
end: defaultToolEnd
},
{
id: "erase",
name: "Erase",
icon: "fa-solid fa-eraser",
cursor: "url(/media/images/fa-eraser.png) 0 18, pointer",
begin: defaultToolBegin,
move: (editor, ctx, x, y, is_overlay = false) => {
ctx.lineTo(x, y)
if (is_overlay) {
ctx.clearRect(0, 0, editor.width, editor.height)
ctx.globalCompositeOperation = "source-over"
ctx.globalAlpha = 1
ctx.filter = "none"
ctx.drawImage(editor.canvas_current, 0, 0)
editor.setBrush(editor.layers.overlay)
ctx.stroke()
editor.canvas_current.style.opacity = 0
}
},
end: (editor, ctx, x, y, is_overlay = false) => {
ctx.stroke()
if (is_overlay) {
ctx.clearRect(0, 0, editor.width, editor.height)
editor.canvas_current.style.opacity = ""
}
},
setBrush: (editor, layer) => {
layer.ctx.globalCompositeOperation = "destination-out"
}
},
{
id: "colorpicker",
name: "Color Picker",
icon: "fa-solid fa-eye-dropper",
cursor: "url(/media/images/fa-eye-dropper.png) 0 24, pointer",
begin: (editor, ctx, x, y, is_overlay = false) => {
var img_rgb = editor.layers.background.ctx.getImageData(x, y, 1, 1).data
var drawn_rgb = editor.ctx_current.getImageData(x, y, 1, 1).data
var drawn_opacity = drawn_rgb[3] / 255
editor.custom_color_input.value = rgbToHex({
r: (drawn_rgb[0] * drawn_opacity) + (img_rgb[0] * (1 - drawn_opacity)),
g: (drawn_rgb[1] * drawn_opacity) + (img_rgb[1] * (1 - drawn_opacity)),
b: (drawn_rgb[2] * drawn_opacity) + (img_rgb[2] * (1 - drawn_opacity)),
})
editor.custom_color_input.dispatchEvent(new Event("change"))
},
move: (editor, ctx, x, y, is_overlay = false) => {},
end: (editor, ctx, x, y, is_overlay = false) => {}
}
]
const IMAGE_EDITOR_ACTIONS = [
{
id: "clear",
name: "Clear",
icon: "fa-solid fa-xmark",
handler: (editor) => {
editor.ctx_current.clearRect(0, 0, editor.width, editor.height)
},
trackHistory: true
},
{
id: "undo",
name: "Undo",
icon: "fa-solid fa-rotate-left",
handler: (editor) => {
editor.history.undo()
},
trackHistory: false
},
{
id: "redo",
name: "Redo",
icon: "fa-solid fa-rotate-right",
handler: (editor) => {
editor.history.redo()
},
trackHistory: false
}
]
var IMAGE_EDITOR_SECTIONS = [
{
name: "tool",
title: "Tool",
default: "draw",
options: Array.from(IMAGE_EDITOR_TOOLS.map(t => t.id)),
initElement: (element, option) => {
var tool_info = IMAGE_EDITOR_TOOLS.find(t => t.id == option)
element.className = "image-editor-button button"
var sub_element = document.createElement("div")
var icon = document.createElement("i")
tool_info.icon.split(" ").forEach(c => icon.classList.add(c))
sub_element.appendChild(icon)
sub_element.append(tool_info.name)
element.appendChild(sub_element)
}
},
{
name: "color",
title: "Color",
default: "#f1c232",
options: [
"custom",
"#ea9999", "#e06666", "#cc0000", "#990000", "#660000",
"#f9cb9c", "#f6b26b", "#e69138", "#b45f06", "#783f04",
"#ffe599", "#ffd966", "#f1c232", "#bf9000", "#7f6000",
"#b6d7a8", "#93c47d", "#6aa84f", "#38761d", "#274e13",
"#a4c2f4", "#6d9eeb", "#3c78d8", "#1155cc", "#1c4587",
"#b4a7d6", "#8e7cc3", "#674ea7", "#351c75", "#20124d",
"#d5a6bd", "#c27ba0", "#a64d79", "#741b47", "#4c1130",
"#ffffff", "#c0c0c0", "#838383", "#525252", "#000000",
],
initElement: (element, option) => {
if (option == "custom") {
var input = document.createElement("input")
input.type = "color"
element.appendChild(input)
var span = document.createElement("span")
span.textContent = "Custom"
span.onclick = function(e) {
input.click()
}
element.appendChild(span)
}
else {
element.style.background = option
}
},
getCustom: editor => {
var input = editor.popup.querySelector(".image_editor_color input")
return input.value
}
},
{
name: "brush_size",
title: "Brush Size",
default: 48,
options: [ 6, 12, 16, 24, 30, 40, 48, 64 ],
initElement: (element, option) => {
element.parentElement.style.flex = option
element.style.width = option + "px"
element.style.height = option + "px"
element.style['margin-right'] = '2px'
element.style["border-radius"] = (option / 2).toFixed() + "px"
}
},
{
name: "opacity",
title: "Opacity",
default: 0,
options: [ 0, 0.2, 0.4, 0.6, 0.8 ],
initElement: (element, option) => {
element.style.background = `repeating-conic-gradient(rgba(0, 0, 0, ${option}) 0% 25%, rgba(255, 255, 255, ${option}) 0% 50%) 50% / 10px 10px`
}
},
{
name: "sharpness",
title: "Sharpness",
default: 0,
options: [ 0, 0.05, 0.1, 0.2, 0.3 ],
initElement: (element, option) => {
var size = 32
var blur_amount = parseInt(option * size)
var sub_element = document.createElement("div")
sub_element.style.background = `var(--background-color3)`
sub_element.style.filter = `blur(${blur_amount}px)`
sub_element.style.width = `${size - 4}px`
sub_element.style.height = `${size - 4}px`
sub_element.style['border-radius'] = `${size}px`
element.style.background = "none"
element.appendChild(sub_element)
}
}
]
class EditorHistory {
constructor(editor) {
this.editor = editor
this.events = [] // stack of all events (actions/edits)
this.current_edit = null
this.rewind_index = 0 // how many events back into the history we've rewound to. (current state is just after event at index 'length - this.rewind_index - 1')
}
push(event) {
// probably add something here eventually to save state every x events
if (this.rewind_index != 0) {
this.events = this.events.slice(0, 0 - this.rewind_index)
this.rewind_index = 0
}
var snapshot_frequency = 20 // (every x edits, take a snapshot of the current drawing state, for faster rewinding)
if (this.events.length > 0 && this.events.length % snapshot_frequency == 0) {
event.snapshot = this.editor.layers.drawing.ctx.getImageData(0, 0, this.editor.width, this.editor.height)
}
this.events.push(event)
}
pushAction(action) {
this.push({
type: "action",
id: action
});
}
editBegin(x, y) {
this.current_edit = {
type: "edit",
id: this.editor.getOptionValue("tool"),
options: Object.assign({}, this.editor.options),
points: [ { x: x, y: y } ]
}
}
editMove(x, y) {
if (this.current_edit) {
this.current_edit.points.push({ x: x, y: y })
}
}
editEnd(x, y) {
if (this.current_edit) {
this.push(this.current_edit)
this.current_edit = null
}
}
clear() {
this.events = []
}
undo() {
this.rewindTo(this.rewind_index + 1)
}
redo() {
this.rewindTo(this.rewind_index - 1)
}
rewindTo(new_rewind_index) {
if (new_rewind_index < 0 || new_rewind_index > this.events.length) {
return; // do nothing if target index is out of bounds
}
var ctx = this.editor.layers.drawing.ctx
ctx.clearRect(0, 0, this.editor.width, this.editor.height)
var target_index = this.events.length - 1 - new_rewind_index
var snapshot_index = target_index
while (snapshot_index > -1) {
if (this.events[snapshot_index].snapshot) {
break
}
snapshot_index--
}
if (snapshot_index != -1) {
ctx.putImageData(this.events[snapshot_index].snapshot, 0, 0);
}
for (var i = (snapshot_index + 1); i <= target_index; i++) {
var event = this.events[i]
if (event.type == "action") {
var action = IMAGE_EDITOR_ACTIONS.find(a => a.id == event.id)
action.handler(this.editor)
}
else if (event.type == "edit") {
var tool = IMAGE_EDITOR_TOOLS.find(t => t.id == event.id)
this.editor.setBrush(this.editor.layers.drawing, event.options)
var first_point = event.points[0]
tool.begin(this.editor, ctx, first_point.x, first_point.y)
for (var point_i = 1; point_i < event.points.length; point_i++) {
tool.move(this.editor, ctx, event.points[point_i].x, event.points[point_i].y)
}
var last_point = event.points[event.points.length - 1]
tool.end(this.editor, ctx, last_point.x, last_point.y)
}
}
// re-set brush to current settings
this.editor.setBrush(this.editor.layers.drawing)
this.rewind_index = new_rewind_index
}
}
class ImageEditor {
constructor(popup, inpainter = false) {
this.inpainter = inpainter
this.popup = popup
this.history = new EditorHistory(this)
if (inpainter) {
this.popup.classList.add("inpainter")
}
this.drawing = false
this.temp_previous_tool = null // used for the ctrl-colorpicker functionality
this.container = popup.querySelector(".editor-controls-center > div")
this.layers = {}
var layer_names = [
"background",
"drawing",
"overlay"
]
layer_names.forEach(name => {
let canvas = document.createElement("canvas")
canvas.className = `editor-canvas-${name}`
this.container.appendChild(canvas)
this.layers[name] = {
name: name,
canvas: canvas,
ctx: canvas.getContext("2d")
}
})
// add mouse handlers
this.container.addEventListener("mousedown", this.mouseHandler.bind(this))
this.container.addEventListener("mouseup", this.mouseHandler.bind(this))
this.container.addEventListener("mousemove", this.mouseHandler.bind(this))
this.container.addEventListener("mouseout", this.mouseHandler.bind(this))
this.container.addEventListener("mouseenter", this.mouseHandler.bind(this))
this.container.addEventListener("touchstart", this.mouseHandler.bind(this))
this.container.addEventListener("touchmove", this.mouseHandler.bind(this))
this.container.addEventListener("touchcancel", this.mouseHandler.bind(this))
this.container.addEventListener("touchend", this.mouseHandler.bind(this))
// initialize editor controls
this.options = {}
this.optionElements = {}
IMAGE_EDITOR_SECTIONS.forEach(section => {
section.id = `image_editor_${section.name}`
var sectionElement = document.createElement("div")
sectionElement.className = section.id
var title = document.createElement("h4")
title.innerText = section.title
sectionElement.appendChild(title)
var optionsContainer = document.createElement("div")
optionsContainer.classList.add("editor-options-container")
this.optionElements[section.name] = []
section.options.forEach((option, index) => {
var optionHolder = document.createElement("div")
var optionElement = document.createElement("div")
optionHolder.appendChild(optionElement)
section.initElement(optionElement, option)
optionElement.addEventListener("click", target => this.selectOption(section.name, index))
optionsContainer.appendChild(optionHolder)
this.optionElements[section.name].push(optionElement)
})
this.selectOption(section.name, section.options.indexOf(section.default))
sectionElement.appendChild(optionsContainer)
this.popup.querySelector(".editor-controls-left").appendChild(sectionElement)
})
this.custom_color_input = this.popup.querySelector(`input[type="color"]`)
this.custom_color_input.addEventListener("change", () => {
this.custom_color_input.parentElement.style.background = this.custom_color_input.value
this.selectOption("color", 0)
})
if (this.inpainter) {
this.selectOption("color", IMAGE_EDITOR_SECTIONS.find(s => s.name == "color").options.indexOf("#ffffff"))
this.selectOption("opacity", IMAGE_EDITOR_SECTIONS.find(s => s.name == "opacity").options.indexOf(0.4))
}
// initialize the right-side controls
var buttonContainer = document.createElement("div")
IMAGE_EDITOR_BUTTONS.forEach(button => {
var element = document.createElement("div")
var icon = document.createElement("i")
element.className = "image-editor-button button"
icon.className = button.icon
element.appendChild(icon)
element.append(button.name)
buttonContainer.appendChild(element)
element.addEventListener("click", event => button.handler(this))
})
var actionsContainer = document.createElement("div")
var actionsTitle = document.createElement("h4")
actionsTitle.textContent = "Actions"
actionsContainer.appendChild(actionsTitle);
IMAGE_EDITOR_ACTIONS.forEach(action => {
var element = document.createElement("div")
var icon = document.createElement("i")
element.className = "image-editor-button button"
icon.className = action.icon
element.appendChild(icon)
element.append(action.name)
actionsContainer.appendChild(element)
element.addEventListener("click", event => this.runAction(action.id))
})
this.popup.querySelector(".editor-controls-right").appendChild(actionsContainer)
this.popup.querySelector(".editor-controls-right").appendChild(buttonContainer)
this.keyHandlerBound = this.keyHandler.bind(this)
this.setSize(512, 512)
}
show() {
this.popup.classList.add("active")
document.addEventListener("keydown", this.keyHandlerBound)
document.addEventListener("keyup", this.keyHandlerBound)
}
hide() {
this.popup.classList.remove("active")
document.removeEventListener("keydown", this.keyHandlerBound)
document.removeEventListener("keyup", this.keyHandlerBound)
}
setSize(width, height) {
if (width == this.width && height == this.height) {
return
}
if (width > height) {
var max_size = Math.min(parseInt(window.innerWidth * 0.9), width, 768)
var multiplier = max_size / width
width = (multiplier * width).toFixed()
height = (multiplier * height).toFixed()
}
else {
var max_size = Math.min(parseInt(window.innerHeight * 0.9), height, 768)
var multiplier = max_size / height
width = (multiplier * width).toFixed()
height = (multiplier * height).toFixed()
}
this.width = width
this.height = height
this.container.style.width = width + "px"
this.container.style.height = height + "px"
Object.values(this.layers).forEach(layer => {
layer.canvas.width = width
layer.canvas.height = height
})
if (this.inpainter) {
this.saveImage() // We've reset the size of the image so inpainting is different
}
this.setBrush()
this.history.clear()
}
get tool() {
var tool_id = this.getOptionValue("tool")
return IMAGE_EDITOR_TOOLS.find(t => t.id == tool_id);
}
loadTool() {
this.drawing = false
this.container.style.cursor = this.tool.cursor;
}
setImage(url, width, height) {
this.setSize(width, height)
this.layers.drawing.ctx.clearRect(0, 0, this.width, this.height)
this.layers.background.ctx.clearRect(0, 0, this.width, this.height)
if (url) {
var image = new Image()
image.onload = () => {
this.layers.background.ctx.drawImage(image, 0, 0, this.width, this.height)
}
image.src = url
}
else {
this.layers.background.ctx.fillStyle = "#ffffff"
this.layers.background.ctx.beginPath()
this.layers.background.ctx.rect(0, 0, this.width, this.height)
this.layers.background.ctx.fill()
}
this.history.clear()
}
saveImage() {
if (!this.inpainter) {
// This is not an inpainter, so save the image as the new img2img input
this.layers.background.ctx.drawImage(this.layers.drawing.canvas, 0, 0, this.width, this.height)
var base64 = this.layers.background.canvas.toDataURL()
initImagePreview.src = base64 // this will trigger the rest of the app to use it
}
else {
// This is an inpainter, so make sure the toggle is set accordingly
var is_blank = !this.layers.drawing.ctx
.getImageData(0, 0, this.width, this.height).data
.some(channel => channel !== 0)
maskSetting.checked = !is_blank
}
this.hide()
}
getImg() { // a drop-in replacement of the drawingboard version
return this.layers.drawing.canvas.toDataURL()
}
setImg(dataUrl) { // a drop-in replacement of the drawingboard version
var image = new Image()
image.onload = () => {
var ctx = this.layers.drawing.ctx;
ctx.clearRect(0, 0, this.width, this.height)
ctx.globalCompositeOperation = "source-over"
ctx.globalAlpha = 1
ctx.filter = "none"
ctx.drawImage(image, 0, 0, this.width, this.height)
this.setBrush(this.layers.drawing)
}
image.src = dataUrl
}
runAction(action_id) {
var action = IMAGE_EDITOR_ACTIONS.find(a => a.id == action_id)
if (action.trackHistory) {
this.history.pushAction(action_id)
}
action.handler(this)
}
setBrush(layer = null, options = null) {
if (options == null) {
options = this.options
}
if (layer) {
layer.ctx.lineCap = "round"
layer.ctx.lineJoin = "round"
layer.ctx.lineWidth = options.brush_size
layer.ctx.fillStyle = options.color
layer.ctx.strokeStyle = options.color
var sharpness = parseInt(options.sharpness * options.brush_size)
layer.ctx.filter = sharpness == 0 ? `none` : `blur(${sharpness}px)`
layer.ctx.globalAlpha = (1 - options.opacity)
layer.ctx.globalCompositeOperation = "source-over"
var tool = IMAGE_EDITOR_TOOLS.find(t => t.id == options.tool)
if (tool && tool.setBrush) {
tool.setBrush(editor, layer)
}
}
else {
Object.values([ "drawing", "overlay" ]).map(name => this.layers[name]).forEach(l => {
this.setBrush(l)
})
}
}
get ctx_overlay() {
return this.layers.overlay.ctx
}
get ctx_current() { // the idea is this will help support having custom layers and editing each one
return this.layers.drawing.ctx
}
get canvas_current() {
return this.layers.drawing.canvas
}
keyHandler(event) { // handles keybinds like ctrl+z, ctrl+y
if (!this.popup.classList.contains("active")) {
document.removeEventListener("keydown", this.keyHandlerBound)
document.removeEventListener("keyup", this.keyHandlerBound)
return // this catches if something else closes the window but doesnt properly unbind the key handler
}
// keybindings
if (event.type == "keydown") {
if ((event.key == "z" || event.key == "Z") && event.ctrlKey) {
if (!event.shiftKey) {
this.history.undo()
}
else {
this.history.redo()
}
}
if (event.key == "y" && event.ctrlKey) {
this.history.redo()
}
}
// dropper ctrl holding handler stuff
var dropper_active = this.temp_previous_tool != null;
if (dropper_active && !event.ctrlKey) {
this.selectOption("tool", IMAGE_EDITOR_TOOLS.findIndex(t => t.id == this.temp_previous_tool))
this.temp_previous_tool = null
}
else if (!dropper_active && event.ctrlKey) {
this.temp_previous_tool = this.getOptionValue("tool")
this.selectOption("tool", IMAGE_EDITOR_TOOLS.findIndex(t => t.id == "colorpicker"))
}
}
mouseHandler(event) {
var bbox = this.layers.overlay.canvas.getBoundingClientRect()
var x = (event.clientX || 0) - bbox.left
var y = (event.clientY || 0) - bbox.top
var type = event.type;
var touchmap = {
touchstart: "mousedown",
touchmove: "mousemove",
touchend: "mouseup",
touchcancel: "mouseup"
}
if (type in touchmap) {
type = touchmap[type]
if (event.touches && event.touches[0]) {
var touch = event.touches[0]
var x = (touch.clientX || 0) - bbox.left
var y = (touch.clientY || 0) - bbox.top
}
}
event.preventDefault()
// do drawing-related stuff
if (type == "mousedown" || (type == "mouseenter" && event.buttons == 1)) {
this.drawing = true
this.tool.begin(this, this.ctx_current, x, y)
this.tool.begin(this, this.ctx_overlay, x, y, true)
this.history.editBegin(x, y)
}
if (type == "mouseup" || type == "mousemove") {
if (this.drawing) {
if (x > 0 && y > 0) {
this.tool.move(this, this.ctx_current, x, y)
this.tool.move(this, this.ctx_overlay, x, y, true)
this.history.editMove(x, y)
}
}
}
if (type == "mouseup" || type == "mouseout") {
if (this.drawing) {
this.drawing = false
this.tool.end(this, this.ctx_current, x, y)
this.tool.end(this, this.ctx_overlay, x, y, true)
this.history.editEnd(x, y)
}
}
}
getOptionValue(section_name) {
var section = IMAGE_EDITOR_SECTIONS.find(s => s.name == section_name)
return this.options && section_name in this.options ? this.options[section_name] : section.default
}
selectOption(section_name, option_index) {
var section = IMAGE_EDITOR_SECTIONS.find(s => s.name == section_name)
var value = section.options[option_index]
this.options[section_name] = value == "custom" ? section.getCustom(this) : value
this.optionElements[section_name].forEach(element => element.classList.remove("active"))
this.optionElements[section_name][option_index].classList.add("active")
// change the editor
this.setBrush()
if (section.name == "tool") {
this.loadTool()
}
}
}
function rgbToHex(rgb) {
function componentToHex(c) {
var hex = parseInt(c).toString(16)
return hex.length == 1 ? "0" + hex : hex
}
return "#" + componentToHex(rgb.r) + componentToHex(rgb.g) + componentToHex(rgb.b)
}
const imageEditor = new ImageEditor(document.getElementById("image-editor"))
const imageInpainter = new ImageEditor(document.getElementById("image-inpainter"), true)
imageEditor.setImage(null, 512, 512)
imageInpainter.setImage(null, 512, 512)
document.getElementById("init_image_button_draw").addEventListener("click", () => {
imageEditor.show()
})
document.getElementById("init_image_button_inpaint").addEventListener("click", () => {
imageInpainter.show()
})
img2imgUnload() // no init image when the app starts

View File

@ -1,332 +0,0 @@
let activeTags = []
let modifiers = []
let customModifiersGroupElement = undefined
let editorModifierEntries = document.querySelector('#editor-modifiers-entries')
let editorModifierTagsList = document.querySelector('#editor-inputs-tags-list')
let editorTagsContainer = document.querySelector('#editor-inputs-tags-container')
let modifierCardSizeSlider = document.querySelector('#modifier-card-size-slider')
let previewImageField = document.querySelector('#preview-image')
let modifierSettingsBtn = document.querySelector('#modifier-settings-btn')
let modifierSettingsOverlay = document.querySelector('#modifier-settings-config')
let customModifiersTextBox = document.querySelector('#custom-modifiers-input')
let customModifierEntriesToolbar = document.querySelector('#editor-modifiers-entries-toolbar')
const modifierThumbnailPath = 'media/modifier-thumbnails'
const activeCardClass = 'modifier-card-active'
const CUSTOM_MODIFIERS_KEY = "customModifiers"
function createModifierCard(name, previews) {
const modifierCard = document.createElement('div')
modifierCard.className = 'modifier-card'
modifierCard.innerHTML = `
<div class="modifier-card-overlay"></div>
<div class="modifier-card-image-container">
<div class="modifier-card-image-overlay">+</div>
<p class="modifier-card-error-label"></p>
<img onerror="this.remove()" alt="Modifier Image" class="modifier-card-image">
</div>
<div class="modifier-card-container">
<div class="modifier-card-label"><p></p></div>
</div>`
const image = modifierCard.querySelector('.modifier-card-image')
const errorText = modifierCard.querySelector('.modifier-card-error-label')
const label = modifierCard.querySelector('.modifier-card-label')
errorText.innerText = 'No Image'
if (typeof previews == 'object') {
image.src = previews[0]; // portrait
image.setAttribute('preview-type', 'portrait')
} else {
image.remove()
}
const maxLabelLength = 30
const nameWithoutBy = name.replace('by ', '')
if(nameWithoutBy.length <= maxLabelLength) {
label.querySelector('p').innerText = nameWithoutBy
} else {
const tooltipText = document.createElement('span')
tooltipText.className = 'tooltip-text'
tooltipText.innerText = name
label.classList.add('tooltip')
label.appendChild(tooltipText)
label.querySelector('p').innerText = nameWithoutBy.substring(0, maxLabelLength) + '...'
}
return modifierCard
}
function createModifierGroup(modifierGroup, initiallyExpanded) {
const title = modifierGroup.category
const modifiers = modifierGroup.modifiers
const titleEl = document.createElement('h5')
titleEl.className = 'collapsible'
titleEl.innerText = title
const modifiersEl = document.createElement('div')
modifiersEl.classList.add('collapsible-content', 'editor-modifiers-leaf')
if (initiallyExpanded === true) {
titleEl.className += ' active'
}
modifiers.forEach(modObj => {
const modifierName = modObj.modifier
const modifierPreviews = modObj?.previews?.map(preview => `${modifierThumbnailPath}/${preview.path}`)
const modifierCard = createModifierCard(modifierName, modifierPreviews)
if(typeof modifierCard == 'object') {
modifiersEl.appendChild(modifierCard)
const trimmedName = trimModifiers(modifierName)
modifierCard.addEventListener('click', () => {
if (activeTags.map(x => trimModifiers(x.name)).includes(trimmedName)) {
// remove modifier from active array
activeTags = activeTags.filter(x => trimModifiers(x.name) != trimmedName)
toggleCardState(trimmedName, false)
} else {
// add modifier to active array
activeTags.push({
'name': modifierName,
'element': modifierCard.cloneNode(true),
'originElement': modifierCard,
'previews': modifierPreviews
})
toggleCardState(trimmedName, true)
}
refreshTagsList()
})
}
})
let brk = document.createElement('br')
brk.style.clear = 'both'
modifiersEl.appendChild(brk)
let e = document.createElement('div')
e.appendChild(titleEl)
e.appendChild(modifiersEl)
editorModifierEntries.insertBefore(e, customModifierEntriesToolbar.nextSibling)
return e
}
function trimModifiers(tag) {
return tag.replace(/^\(+|\)+$/g, '').replace(/^\[+|\]+$/g, '')
}
async function loadModifiers() {
try {
let res = await fetch('/get/modifiers')
if (res.status === 200) {
res = await res.json()
modifiers = res; // update global variable
res.reverse()
res.forEach((modifierGroup, idx) => {
createModifierGroup(modifierGroup, idx === res.length - 1)
})
createCollapsibles(editorModifierEntries)
}
} catch (e) {
console.log('error fetching modifiers', e)
}
loadCustomModifiers()
}
function refreshModifiersState(newTags) {
// clear existing modifiers
document.querySelector('#editor-modifiers').querySelectorAll('.modifier-card').forEach(modifierCard => {
const modifierName = modifierCard.querySelector('.modifier-card-label').innerText
if (activeTags.map(x => x.name).includes(modifierName)) {
modifierCard.classList.remove(activeCardClass)
modifierCard.querySelector('.modifier-card-image-overlay').innerText = '+'
}
})
activeTags = []
// set new modifiers
newTags.forEach(tag => {
let found = false
document.querySelector('#editor-modifiers').querySelectorAll('.modifier-card').forEach(modifierCard => {
const modifierName = modifierCard.querySelector('.modifier-card-label').innerText
if (tag == modifierName) {
// add modifier to active array
if (!activeTags.map(x => x.name).includes(tag)) { // only add each tag once even if several custom modifier cards share the same tag
activeTags.push({
'name': modifierName,
'element': modifierCard.cloneNode(true),
'originElement': modifierCard
})
}
modifierCard.classList.add(activeCardClass)
modifierCard.querySelector('.modifier-card-image-overlay').innerText = '-'
found = true
}
})
if (found == false) { // custom tag went missing, create one here
let modifierCard = createModifierCard(tag, undefined) // create a modifier card for the missing tag, no image
modifierCard.addEventListener('click', () => {
if (activeTags.map(x => x.name).includes(tag)) {
// remove modifier from active array
activeTags = activeTags.filter(x => x.name != tag)
modifierCard.classList.remove(activeCardClass)
modifierCard.querySelector('.modifier-card-image-overlay').innerText = '+'
}
refreshTagsList()
})
activeTags.push({
'name': tag,
'element': modifierCard,
'originElement': undefined // no origin element for missing tags
})
}
})
refreshTagsList()
}
function refreshTagsList() {
editorModifierTagsList.innerHTML = ''
if (activeTags.length == 0) {
editorTagsContainer.style.display = 'none'
return
} else {
editorTagsContainer.style.display = 'block'
}
activeTags.forEach((tag, index) => {
tag.element.querySelector('.modifier-card-image-overlay').innerText = '-'
tag.element.classList.add('modifier-card-tiny')
editorModifierTagsList.appendChild(tag.element)
tag.element.addEventListener('click', () => {
let idx = activeTags.findIndex(o => { return o.name === tag.name })
if (idx !== -1) {
toggleCardState(activeTags[idx].name, false)
activeTags.splice(idx, 1)
refreshTagsList()
}
})
})
let brk = document.createElement('br')
brk.style.clear = 'both'
editorModifierTagsList.appendChild(brk)
}
function toggleCardState(modifierName, makeActive) {
document.querySelector('#editor-modifiers').querySelectorAll('.modifier-card').forEach(card => {
const name = card.querySelector('.modifier-card-label').innerText
if ( trimModifiers(modifierName) == trimModifiers(name)
|| trimModifiers(modifierName) == 'by ' + trimModifiers(name)) {
if(makeActive) {
card.classList.add(activeCardClass)
card.querySelector('.modifier-card-image-overlay').innerText = '-'
}
else{
card.classList.remove(activeCardClass)
card.querySelector('.modifier-card-image-overlay').innerText = '+'
}
}
})
}
function changePreviewImages(val) {
const previewImages = document.querySelectorAll('.modifier-card-image-container img')
let previewArr = []
modifiers.map(x => x.modifiers).forEach(x => previewArr.push(...x.map(m => m.previews)))
previewArr = previewArr.map(x => {
let obj = {}
x.forEach(preview => {
obj[preview.name] = preview.path
})
return obj
})
previewImages.forEach(previewImage => {
const currentPreviewType = previewImage.getAttribute('preview-type')
const relativePreviewPath = previewImage.src.split(modifierThumbnailPath + '/').pop()
const previews = previewArr.find(preview => relativePreviewPath == preview[currentPreviewType])
if(typeof previews == 'object') {
let preview = null
if (val == 'portrait') {
preview = previews.portrait
}
else if (val == 'landscape') {
preview = previews.landscape
}
if(preview != null) {
previewImage.src = `${modifierThumbnailPath}/${preview}`
previewImage.setAttribute('preview-type', val)
}
}
})
}
function resizeModifierCards(val) {
const cardSizePrefix = 'modifier-card-size_'
const modifierCardClass = 'modifier-card'
const modifierCards = document.querySelectorAll(`.${modifierCardClass}`)
const cardSize = n => `${cardSizePrefix}${n}`
modifierCards.forEach(card => {
// remove existing size classes
const classes = card.className.split(' ').filter(c => !c.startsWith(cardSizePrefix))
card.className = classes.join(' ').trim()
if(val != 0) {
card.classList.add(cardSize(val))
}
})
}
modifierCardSizeSlider.onchange = () => resizeModifierCards(modifierCardSizeSlider.value)
previewImageField.onchange = () => changePreviewImages(previewImageField.value)
modifierSettingsBtn.addEventListener('click', function(e) {
modifierSettingsOverlay.classList.add("active")
e.stopPropagation()
})
function saveCustomModifiers() {
localStorage.setItem(CUSTOM_MODIFIERS_KEY, customModifiersTextBox.value.trim())
loadCustomModifiers()
}
function loadCustomModifiers() {
PLUGINS['MODIFIERS_LOAD'].forEach(fn=>fn.loader.call())
}
customModifiersTextBox.addEventListener('change', saveCustomModifiers)

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/**
* Enum of parameter types
* @readonly
* @enum {string}
*/
var ParameterType = {
checkbox: "checkbox",
select: "select",
select_multiple: "select_multiple",
custom: "custom",
};
/**
* JSDoc style
* @typedef {object} Parameter
* @property {string} id
* @property {ParameterType} type
* @property {string} label
* @property {?string} note
* @property {number|boolean|string} default
*/
/** @type {Array.<Parameter>} */
var PARAMETERS = [
{
id: "theme",
type: ParameterType.select,
label: "Theme",
default: "theme-default",
note: "customize the look and feel of the ui",
options: [ // Note: options expanded dynamically
{
value: "theme-default",
label: "Default"
}
],
icon: "fa-palette"
},
{
id: "save_to_disk",
type: ParameterType.checkbox,
label: "Auto-Save Images",
note: "automatically saves images to the specified location",
icon: "fa-download",
default: false,
},
{
id: "diskPath",
type: ParameterType.custom,
label: "Save Location",
render: (parameter) => {
return `<input id="${parameter.id}" name="${parameter.id}" size="30" disabled>`
}
},
{
id: "sound_toggle",
type: ParameterType.checkbox,
label: "Enable Sound",
note: "plays a sound on task completion",
icon: "fa-volume-low",
default: true,
},
{
id: "process_order_toggle",
type: ParameterType.checkbox,
label: "Process newest jobs first",
note: "reverse the normal processing order",
default: false,
},
{
id: "ui_open_browser_on_start",
type: ParameterType.checkbox,
label: "Open browser on startup",
note: "starts the default browser on startup",
icon: "fa-window-restore",
default: true,
},
{
id: "turbo",
type: ParameterType.checkbox,
label: "Turbo Mode",
note: "generates images faster, but uses an additional 1 GB of GPU memory",
icon: "fa-forward",
default: true,
},
{
id: "use_cpu",
type: ParameterType.checkbox,
label: "Use CPU (not GPU)",
note: "warning: this will be *very* slow",
icon: "fa-microchip",
default: false,
},
{
id: "auto_pick_gpus",
type: ParameterType.checkbox,
label: "Automatically pick the GPUs (experimental)",
default: false,
},
{
id: "use_gpus",
type: ParameterType.select_multiple,
label: "GPUs to use (experimental)",
note: "to process in parallel",
default: false,
},
{
id: "use_full_precision",
type: ParameterType.checkbox,
label: "Use Full Precision",
note: "for GPU-only. warning: this will consume more VRAM",
icon: "fa-crosshairs",
default: false,
},
{
id: "auto_save_settings",
type: ParameterType.checkbox,
label: "Auto-Save Settings",
note: "restores settings on browser load",
icon: "fa-gear",
default: true,
},
{
id: "confirm_dangerous_actions",
type: ParameterType.checkbox,
label: "Confirm dangerous actions",
note: "Actions that might lead to data loss must either be clicked with the shift key pressed, or confirmed in an 'Are you sure?' dialog",
icon: "fa-check-double",
default: true,
},
{
id: "listen_to_network",
type: ParameterType.checkbox,
label: "Make Stable Diffusion available on your network",
note: "Other devices on your network can access this web page",
icon: "fa-network-wired",
default: true,
},
{
id: "listen_port",
type: ParameterType.custom,
label: "Network port",
note: "Port that this server listens to. The '9000' part in 'http://localhost:9000'",
icon: "fa-anchor",
render: (parameter) => {
return `<input id="${parameter.id}" name="${parameter.id}" size="6" value="9000" onkeypress="preventNonNumericalInput(event)">`
}
},
{
id: "test_sd2",
type: ParameterType.checkbox,
label: "Test SD 2.0",
note: "Experimental! High memory usage! GPU-only! Not the final version! Please restart the program after changing this.",
icon: "fa-fire",
default: false,
},
{
id: "use_beta_channel",
type: ParameterType.checkbox,
label: "Beta channel",
note: "Get the latest features immediately (but could be less stable). Please restart the program after changing this.",
icon: "fa-fire",
default: false,
},
];
function getParameterSettingsEntry(id) {
let parameter = PARAMETERS.filter(p => p.id === id)
if (parameter.length === 0) {
return
}
return parameter[0].settingsEntry
}
function getParameterElement(parameter) {
switch (parameter.type) {
case ParameterType.checkbox:
var is_checked = parameter.default ? " checked" : "";
return `<input id="${parameter.id}" name="${parameter.id}"${is_checked} type="checkbox">`
case ParameterType.select:
case ParameterType.select_multiple:
var options = (parameter.options || []).map(option => `<option value="${option.value}">${option.label}</option>`).join("")
var multiple = (parameter.type == ParameterType.select_multiple ? 'multiple' : '')
return `<select id="${parameter.id}" name="${parameter.id}" ${multiple}>${options}</select>`
case ParameterType.custom:
return parameter.render(parameter)
default:
console.error(`Invalid type for parameter ${parameter.id}`);
return "ERROR: Invalid Type"
}
}
let parametersTable = document.querySelector("#system-settings .parameters-table")
/* fill in the system settings popup table */
function initParameters() {
PARAMETERS.forEach(parameter => {
var element = getParameterElement(parameter)
var note = parameter.note ? `<small>${parameter.note}</small>` : "";
var icon = parameter.icon ? `<i class="fa ${parameter.icon}"></i>` : "";
var newrow = document.createElement('div')
newrow.innerHTML = `
<div>${icon}</div>
<div><label for="${parameter.id}">${parameter.label}</label>${note}</div>
<div>${element}</div>`
parametersTable.appendChild(newrow)
parameter.settingsEntry = newrow
})
}
initParameters()
let turboField = document.querySelector('#turbo')
let useCPUField = document.querySelector('#use_cpu')
let autoPickGPUsField = document.querySelector('#auto_pick_gpus')
let useGPUsField = document.querySelector('#use_gpus')
let useFullPrecisionField = document.querySelector('#use_full_precision')
let saveToDiskField = document.querySelector('#save_to_disk')
let diskPathField = document.querySelector('#diskPath')
let listenToNetworkField = document.querySelector("#listen_to_network")
let listenPortField = document.querySelector("#listen_port")
let testSD2Field = document.querySelector("#test_sd2")
let useBetaChannelField = document.querySelector("#use_beta_channel")
let uiOpenBrowserOnStartField = document.querySelector("#ui_open_browser_on_start")
let confirmDangerousActionsField = document.querySelector("#confirm_dangerous_actions")
let saveSettingsBtn = document.querySelector('#save-system-settings-btn')
async function changeAppConfig(configDelta) {
try {
let res = await fetch('/app_config', {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify(configDelta)
})
res = await res.json()
console.log('set config status response', res)
} catch (e) {
console.log('set config status error', e)
}
}
async function getAppConfig() {
try {
let res = await fetch('/get/app_config')
const config = await res.json()
if (config.update_branch === 'beta') {
useBetaChannelField.checked = true
document.querySelector("#updateBranchLabel").innerText = "(beta)"
}
if (config.ui && config.ui.open_browser_on_start === false) {
uiOpenBrowserOnStartField.checked = false
}
if ('test_sd2' in config) {
testSD2Field.checked = config['test_sd2']
}
let testSD2SettingEntry = getParameterSettingsEntry('test_sd2')
testSD2SettingEntry.style.display = (config.update_branch === 'beta' ? '' : 'none')
if (config.net && config.net.listen_to_network === false) {
listenToNetworkField.checked = false
}
if (config.net && config.net.listen_port !== undefined) {
listenPortField.value = config.net.listen_port
}
console.log('get config status response', config)
} catch (e) {
console.log('get config status error', e)
}
}
saveToDiskField.addEventListener('change', function(e) {
diskPathField.disabled = !this.checked
})
function getCurrentRenderDeviceSelection() {
let selectedGPUs = $('#use_gpus').val()
if (useCPUField.checked && !autoPickGPUsField.checked) {
return 'cpu'
}
if (autoPickGPUsField.checked || selectedGPUs.length == 0) {
return 'auto'
}
return selectedGPUs.join(',')
}
useCPUField.addEventListener('click', function() {
let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
let autoPickGPUSettingEntry = getParameterSettingsEntry('auto_pick_gpus')
if (this.checked) {
gpuSettingEntry.style.display = 'none'
autoPickGPUSettingEntry.style.display = 'none'
autoPickGPUsField.setAttribute('data-old-value', autoPickGPUsField.checked)
autoPickGPUsField.checked = false
} else if (useGPUsField.options.length >= MIN_GPUS_TO_SHOW_SELECTION) {
gpuSettingEntry.style.display = ''
autoPickGPUSettingEntry.style.display = ''
let oldVal = autoPickGPUsField.getAttribute('data-old-value')
if (oldVal === null || oldVal === undefined) { // the UI started with CPU selected by default
autoPickGPUsField.checked = true
} else {
autoPickGPUsField.checked = (oldVal === 'true')
}
gpuSettingEntry.style.display = (autoPickGPUsField.checked ? 'none' : '')
}
})
useGPUsField.addEventListener('click', function() {
let selectedGPUs = $('#use_gpus').val()
autoPickGPUsField.checked = (selectedGPUs.length === 0)
})
autoPickGPUsField.addEventListener('click', function() {
if (this.checked) {
$('#use_gpus').val([])
}
let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
gpuSettingEntry.style.display = (this.checked ? 'none' : '')
})
async function getDiskPath() {
try {
var diskPath = getSetting("diskPath")
if (diskPath == '' || diskPath == undefined || diskPath == "undefined") {
let res = await fetch('/get/output_dir')
if (res.status === 200) {
res = await res.json()
res = res.output_dir
setSetting("diskPath", res)
}
}
} catch (e) {
console.log('error fetching output dir path', e)
}
}
function setDeviceInfo(devices) {
let cpu = devices.all.cpu.name
let allGPUs = Object.keys(devices.all).filter(d => d != 'cpu')
let activeGPUs = Object.keys(devices.active)
function ID_TO_TEXT(d) {
let info = devices.all[d]
if ("mem_free" in info && "mem_total" in info) {
return `${info.name} <small>(${d}) (${info.mem_free.toFixed(1)}Gb free / ${info.mem_total.toFixed(1)} Gb total)</small>`
} else {
return `${info.name} <small>(${d}) (no memory info)</small>`
}
}
allGPUs = allGPUs.map(ID_TO_TEXT)
activeGPUs = activeGPUs.map(ID_TO_TEXT)
let systemInfoEl = document.querySelector('#system-info')
systemInfoEl.querySelector('#system-info-cpu').innerText = cpu
systemInfoEl.querySelector('#system-info-gpus-all').innerHTML = allGPUs.join('</br>')
systemInfoEl.querySelector('#system-info-rendering-devices').innerHTML = activeGPUs.join('</br>')
}
function setHostInfo(hosts) {
let port = listenPortField.value
hosts = hosts.map(addr => `http://${addr}:${port}/`).map(url => `<div><a href="${url}">${url}</a></div>`)
document.querySelector('#system-info-server-hosts').innerHTML = hosts.join('')
}
async function getSystemInfo() {
try {
const res = await SD.getSystemInfo()
let devices = res['devices']
let allDeviceIds = Object.keys(devices['all']).filter(d => d !== 'cpu')
let activeDeviceIds = Object.keys(devices['active']).filter(d => d !== 'cpu')
if (activeDeviceIds.length === 0) {
useCPUField.checked = true
}
if (allDeviceIds.length < MIN_GPUS_TO_SHOW_SELECTION || useCPUField.checked) {
let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
gpuSettingEntry.style.display = 'none'
let autoPickGPUSettingEntry = getParameterSettingsEntry('auto_pick_gpus')
autoPickGPUSettingEntry.style.display = 'none'
}
if (allDeviceIds.length === 0) {
useCPUField.checked = true
useCPUField.disabled = true // no compatible GPUs, so make the CPU mandatory
}
autoPickGPUsField.checked = (devices['config'] === 'auto')
useGPUsField.innerHTML = ''
allDeviceIds.forEach(device => {
let deviceName = devices['all'][device]['name']
let deviceOption = `<option value="${device}">${deviceName} (${device})</option>`
useGPUsField.insertAdjacentHTML('beforeend', deviceOption)
})
if (autoPickGPUsField.checked) {
let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
gpuSettingEntry.style.display = 'none'
} else {
$('#use_gpus').val(activeDeviceIds)
}
setDeviceInfo(devices)
setHostInfo(res['hosts'])
} catch (e) {
console.log('error fetching devices', e)
}
}
saveSettingsBtn.addEventListener('click', function() {
if (listenPortField.value == '') {
alert('The network port field must not be empty.')
return
}
if (listenPortField.value < 1 || listenPortField.value > 65535) {
alert('The network port must be a number from 1 to 65535')
return
}
let updateBranch = (useBetaChannelField.checked ? 'beta' : 'main')
changeAppConfig({
'render_devices': getCurrentRenderDeviceSelection(),
'update_branch': updateBranch,
'ui_open_browser_on_start': uiOpenBrowserOnStartField.checked,
'listen_to_network': listenToNetworkField.checked,
'listen_port': listenPortField.value,
'test_sd2': testSD2Field.checked
})
saveSettingsBtn.classList.add('active')
asyncDelay(300).then(() => saveSettingsBtn.classList.remove('active'))
})

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@ -1,72 +0,0 @@
const PLUGIN_API_VERSION = "1.0"
const PLUGINS = {
/**
* Register new buttons to show on each output image.
*
* Example:
* PLUGINS['IMAGE_INFO_BUTTONS'].push({
* text: 'Make a Similar Image',
* on_click: function(origRequest, image) {
* let newTaskRequest = getCurrentUserRequest()
* newTaskRequest.reqBody = Object.assign({}, origRequest, {
* init_image: image.src,
* prompt_strength: 0.7,
* seed: Math.floor(Math.random() * 10000000)
* })
* newTaskRequest.seed = newTaskRequest.reqBody.seed
* createTask(newTaskRequest)
* },
* filter: function(origRequest, image) {
* // this is an optional function. return true/false to show/hide the button
* // if this function isn't set, the button will always be visible
* return true
* }
* })
*/
IMAGE_INFO_BUTTONS: [],
MODIFIERS_LOAD: [],
TASK_CREATE: [],
OUTPUTS_FORMATS: new ServiceContainer(
function png() { return (reqBody) => new SD.RenderTask(reqBody) }
, function jpeg() { return (reqBody) => new SD.RenderTask(reqBody) }
),
}
PLUGINS.OUTPUTS_FORMATS.register = function(...args) {
const service = ServiceContainer.prototype.register.apply(this, args)
if (typeof outputFormatField !== 'undefined') {
const newOption = document.createElement("option")
newOption.setAttribute("value", service.name)
newOption.innerText = service.name
outputFormatField.appendChild(newOption)
}
return service
}
function loadScript(url) {
const script = document.createElement('script')
const promiseSrc = new PromiseSource()
script.addEventListener('error', () => promiseSrc.reject(new Error(`Script "${url}" couldn't be loaded.`)))
script.addEventListener('load', () => promiseSrc.resolve(url))
script.src = url + '?t=' + Date.now()
console.log('loading script', url)
document.head.appendChild(script)
return promiseSrc.promise
}
async function loadUIPlugins() {
try {
const res = await fetch('/get/ui_plugins')
if (!res.ok) {
console.error(`Error HTTP${res.status} while loading plugins list. - ${res.statusText}`)
return
}
const plugins = await res.json()
const loadingPromises = plugins.map(loadScript)
return await Promise.allSettled(loadingPromises)
} catch (e) {
console.log('error fetching plugin paths', e)
}
}

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const themeField = document.getElementById("theme");
var DEFAULT_THEME = {};
var THEMES = []; // initialized in initTheme from data in css
function getThemeName(theme) {
theme = theme.replace("theme-", "");
theme = theme.split("-").map(word => word.charAt(0).toUpperCase() + word.slice(1)).join(" ");
return theme;
}
// init themefield
function initTheme() {
Array.from(document.styleSheets)
.filter(sheet => sheet.href?.startsWith(window.location.origin))
.flatMap(sheet => Array.from(sheet.cssRules))
.forEach(rule => {
var selector = rule.selectorText; // TODO: also do selector == ":root", re-run un-set props
if (selector && selector.startsWith(".theme-") && !selector.includes(" ")) {
var theme_key = selector.substring(1);
THEMES.push({
key: theme_key,
name: getThemeName(theme_key),
rule: rule
})
}
if (selector && selector == ":root") {
DEFAULT_THEME = {
key: "theme-default",
name: "Default",
rule: rule
};
}
});
THEMES.forEach(theme => {
var new_option = document.createElement("option");
new_option.setAttribute("value", theme.key);
new_option.innerText = theme.name;
themeField.appendChild(new_option);
});
// setup the style transitions a second after app initializes, so initial style is instant
setTimeout(() => {
var body = document.querySelector("body");
var style = document.createElement('style');
style.innerHTML = "* { transition: background 0.5s, color 0.5s, background-color 0.5s; }";
body.appendChild(style);
}, 1000);
}
initTheme();
function themeFieldChanged() {
var theme_key = themeField.value;
var body = document.querySelector("body");
body.classList.remove(...THEMES.map(theme => theme.key));
body.classList.add(theme_key);
//
body.style = "";
var theme = THEMES.find(t => t.key == theme_key);
let borderColor = undefined
if (theme) {
// refresh variables incase they are back referencing
Array.from(DEFAULT_THEME.rule.style)
.filter(cssVariable => !Array.from(theme.rule.style).includes(cssVariable))
.forEach(cssVariable => {
body.style.setProperty(cssVariable, DEFAULT_THEME.rule.style.getPropertyValue(cssVariable));
});
borderColor = theme.rule.style.getPropertyValue('--input-border-color').trim()
if (!borderColor.startsWith('#')) {
borderColor = theme.rule.style.getPropertyValue('--theme-color-fallback')
}
} else {
borderColor = DEFAULT_THEME.rule.style.getPropertyValue('--theme-color-fallback')
}
document.querySelector('meta[name="theme-color"]').setAttribute("content", borderColor)
}
themeField.addEventListener('change', themeFieldChanged);

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"use strict";
// https://gomakethings.com/finding-the-next-and-previous-sibling-elements-that-match-a-selector-with-vanilla-js/
function getNextSibling(elem, selector) {
// Get the next sibling element
let sibling = elem.nextElementSibling
// If there's no selector, return the first sibling
if (!selector) {
return sibling
}
// If the sibling matches our selector, use it
// If not, jump to the next sibling and continue the loop
while (sibling) {
if (sibling.matches(selector)) {
return sibling
}
sibling = sibling.nextElementSibling
}
}
/* Panel Stuff */
// true = open
let COLLAPSIBLES_INITIALIZED = false;
const COLLAPSIBLES_KEY = "collapsibles";
const COLLAPSIBLE_PANELS = []; // filled in by createCollapsibles with all the elements matching .collapsible
// on-init call this for any panels that are marked open
function toggleCollapsible(element) {
const collapsibleHeader = element.querySelector(".collapsible");
const handle = element.querySelector(".collapsible-handle");
collapsibleHeader.classList.toggle("active")
let content = getNextSibling(collapsibleHeader, '.collapsible-content')
if (!collapsibleHeader.classList.contains("active")) {
content.style.display = "none"
if (handle != null) { // render results don't have a handle
handle.innerHTML = '&#x2795;' // plus
}
} else {
content.style.display = "block"
if (handle != null) { // render results don't have a handle
handle.innerHTML = '&#x2796;' // minus
}
}
document.dispatchEvent(new CustomEvent('collapsibleClick', { detail: collapsibleHeader }))
if (COLLAPSIBLES_INITIALIZED && COLLAPSIBLE_PANELS.includes(element)) {
saveCollapsibles()
}
}
function saveCollapsibles() {
let values = {}
COLLAPSIBLE_PANELS.forEach(element => {
let value = element.querySelector(".collapsible").className.indexOf("active") !== -1
values[element.id] = value
})
localStorage.setItem(COLLAPSIBLES_KEY, JSON.stringify(values))
}
function createCollapsibles(node) {
let save = false
if (!node) {
node = document
save = true
}
let collapsibles = node.querySelectorAll(".collapsible")
collapsibles.forEach(function(c) {
if (save && c.parentElement.id) {
COLLAPSIBLE_PANELS.push(c.parentElement)
}
let handle = document.createElement('span')
handle.className = 'collapsible-handle'
if (c.classList.contains("active")) {
handle.innerHTML = '&#x2796;' // minus
} else {
handle.innerHTML = '&#x2795;' // plus
}
c.insertBefore(handle, c.firstChild)
c.addEventListener('click', function() {
toggleCollapsible(c.parentElement)
})
})
if (save) {
let saved = localStorage.getItem(COLLAPSIBLES_KEY)
if (!saved) {
saved = tryLoadOldCollapsibles();
}
if (!saved) {
saveCollapsibles()
saved = localStorage.getItem(COLLAPSIBLES_KEY)
}
let values = JSON.parse(saved)
COLLAPSIBLE_PANELS.forEach(element => {
let value = element.querySelector(".collapsible").className.indexOf("active") !== -1
if (values[element.id] != value) {
toggleCollapsible(element)
}
})
COLLAPSIBLES_INITIALIZED = true
}
}
function tryLoadOldCollapsibles() {
const old_map = {
"advancedPanelOpen": "editor-settings",
"modifiersPanelOpen": "editor-modifiers",
"negativePromptPanelOpen": "editor-inputs-prompt"
};
if (localStorage.getItem(Object.keys(old_map)[0])) {
let result = {};
Object.keys(old_map).forEach(key => {
const value = localStorage.getItem(key);
if (value !== null) {
result[old_map[key]] = (value == true || value == "true")
localStorage.removeItem(key)
}
});
result = JSON.stringify(result)
localStorage.setItem(COLLAPSIBLES_KEY, result)
return result
}
return null;
}
function permute(arr) {
let permutations = []
let n = arr.length
let n_permutations = Math.pow(2, n)
for (let i = 0; i < n_permutations; i++) {
let perm = []
let mask = Number(i).toString(2).padStart(n, '0')
for (let idx = 0; idx < mask.length; idx++) {
if (mask[idx] === '1' && arr[idx].trim() !== '') {
perm.push(arr[idx])
}
}
if (perm.length > 0) {
permutations.push(perm)
}
}
return permutations
}
// https://stackoverflow.com/a/8212878
function millisecondsToStr(milliseconds) {
function numberEnding (number) {
return (number > 1) ? 's' : ''
}
let temp = Math.floor(milliseconds / 1000)
let hours = Math.floor((temp %= 86400) / 3600)
let s = ''
if (hours) {
s += hours + ' hour' + numberEnding(hours) + ' '
}
let minutes = Math.floor((temp %= 3600) / 60)
if (minutes) {
s += minutes + ' minute' + numberEnding(minutes) + ' '
}
let seconds = temp % 60
if (!hours && minutes < 4 && seconds) {
s += seconds + ' second' + numberEnding(seconds)
}
return s
}
// https://rosettacode.org/wiki/Brace_expansion#JavaScript
function BraceExpander() {
'use strict'
// Index of any closing brace matching the opening
// brace at iPosn,
// with the indices of any immediately-enclosed commas.
function bracePair(tkns, iPosn, iNest, lstCommas) {
if (iPosn >= tkns.length || iPosn < 0) return null;
let t = tkns[iPosn],
n = (t === '{') ? (
iNest + 1
) : (t === '}' ? (
iNest - 1
) : iNest),
lst = (t === ',' && iNest === 1) ? (
lstCommas.concat(iPosn)
) : lstCommas;
return n ? bracePair(tkns, iPosn + 1, n, lst) : {
close: iPosn,
commas: lst
};
}
// Parse of a SYNTAGM subtree
function andTree(dctSofar, tkns) {
if (!tkns.length) return [dctSofar, []];
let dctParse = dctSofar ? dctSofar : {
fn: and,
args: []
},
head = tkns[0],
tail = head ? tkns.slice(1) : [],
dctBrace = head === '{' ? bracePair(
tkns, 0, 0, []
) : null,
lstOR = dctBrace && (
dctBrace.close
) && dctBrace.commas.length ? (
splitAt(dctBrace.close + 1, tkns)
) : null;
return andTree({
fn: and,
args: dctParse.args.concat(
lstOR ? (
orTree(dctParse, lstOR[0], dctBrace.commas)
) : head
)
}, lstOR ? (
lstOR[1]
) : tail);
}
// Parse of a PARADIGM subtree
function orTree(dctSofar, tkns, lstCommas) {
if (!tkns.length) return [dctSofar, []];
let iLast = lstCommas.length;
return {
fn: or,
args: splitsAt(
lstCommas, tkns
).map(function (x, i) {
let ts = x.slice(
1, i === iLast ? (
-1
) : void 0
);
return ts.length ? ts : [''];
}).map(function (ts) {
return ts.length > 1 ? (
andTree(null, ts)[0]
) : ts[0];
})
};
}
// List of unescaped braces and commas, and remaining strings
function tokens(str) {
// Filter function excludes empty splitting artefacts
let toS = function (x) {
return x.toString();
};
return str.split(/(\\\\)/).filter(toS).reduce(function (a, s) {
return a.concat(s.charAt(0) === '\\' ? s : s.split(
/(\\*[{,}])/
).filter(toS));
}, []);
}
// PARSE TREE OPERATOR (1 of 2)
// Each possible head * each possible tail
function and(args) {
let lng = args.length,
head = lng ? args[0] : null,
lstHead = "string" === typeof head ? (
[head]
) : head;
return lng ? (
1 < lng ? lstHead.reduce(function (a, h) {
return a.concat(
and(args.slice(1)).map(function (t) {
return h + t;
})
);
}, []) : lstHead
) : [];
}
// PARSE TREE OPERATOR (2 of 2)
// Each option flattened
function or(args) {
return args.reduce(function (a, b) {
return a.concat(b);
}, []);
}
// One list split into two (first sublist length n)
function splitAt(n, lst) {
return n < lst.length + 1 ? [
lst.slice(0, n), lst.slice(n)
] : [lst, []];
}
// One list split into several (sublist lengths [n])
function splitsAt(lstN, lst) {
return lstN.reduceRight(function (a, x) {
return splitAt(x, a[0]).concat(a.slice(1));
}, [lst]);
}
// Value of the parse tree
function evaluated(e) {
return typeof e === 'string' ? e :
e.fn(e.args.map(evaluated));
}
// JSON prettyprint (for parse tree, token list etc)
function pp(e) {
return JSON.stringify(e, function (k, v) {
return typeof v === 'function' ? (
'[function ' + v.name + ']'
) : v;
}, 2)
}
// ----------------------- MAIN ------------------------
// s -> [s]
this.expand = function(s) {
// BRACE EXPRESSION PARSED
let dctParse = andTree(null, tokens(s))[0];
// ABSTRACT SYNTAX TREE LOGGED
// console.log(pp(dctParse));
// AST EVALUATED TO LIST OF STRINGS
return evaluated(dctParse);
}
}
/** Pause the execution of an async function until timer elapse.
* @Returns a promise that will resolve after the specified timeout.
*/
function asyncDelay(timeout) {
return new Promise(function(resolve, reject) {
setTimeout(resolve, timeout, true)
})
}
function PromiseSource() {
const srcPromise = new Promise((resolve, reject) => {
Object.defineProperties(this, {
resolve: { value: resolve, writable: false }
, reject: { value: reject, writable: false }
})
})
Object.defineProperties(this, {
promise: {value: makeQuerablePromise(srcPromise), writable: false}
})
}
/** A debounce is a higher-order function, which is a function that returns another function
* that, as long as it continues to be invoked, will not be triggered.
* The function will be called after it stops being called for N milliseconds.
* If `immediate` is passed, trigger the function on the leading edge, instead of the trailing.
* @Returns a promise that will resolve to func return value.
*/
function debounce (func, wait, immediate) {
if (typeof wait === "undefined") {
wait = 40
}
if (typeof wait !== "number") {
throw new Error("wait is not an number.")
}
let timeout = null
let lastPromiseSrc = new PromiseSource()
const applyFn = function(context, args) {
let result = undefined
try {
result = func.apply(context, args)
} catch (err) {
lastPromiseSrc.reject(err)
}
if (result instanceof Promise) {
result.then(lastPromiseSrc.resolve, lastPromiseSrc.reject)
} else {
lastPromiseSrc.resolve(result)
}
}
return function(...args) {
const callNow = Boolean(immediate && !timeout)
const context = this;
if (timeout) {
clearTimeout(timeout)
}
timeout = setTimeout(function () {
if (!immediate) {
applyFn(context, args)
}
lastPromiseSrc = new PromiseSource()
timeout = null
}, wait)
if (callNow) {
applyFn(context, args)
}
return lastPromiseSrc.promise
}
}
function preventNonNumericalInput(e) {
e = e || window.event;
let charCode = (typeof e.which == "undefined") ? e.keyCode : e.which;
let charStr = String.fromCharCode(charCode);
let re = e.target.getAttribute('pattern') || '^[0-9]+$'
re = new RegExp(re)
if (!charStr.match(re)) {
e.preventDefault();
}
}
/** Returns the global object for the current execution environement.
* @Returns window in a browser, global in node and self in a ServiceWorker.
* @Notes Allows unit testing and use of the engine outside of a browser.
*/
function getGlobal() {
if (typeof globalThis === 'object') {
return globalThis
} else if (typeof global === 'object') {
return global
} else if (typeof self === 'object') {
return self
}
try {
return Function('return this')()
} catch {
// If the Function constructor fails, we're in a browser with eval disabled by CSP headers.
return window
} // Returns undefined if global can't be found.
}
/** Check if x is an Array or a TypedArray.
* @Returns true if x is an Array or a TypedArray, false otherwise.
*/
function isArrayOrTypedArray(x) {
return Boolean(typeof x === 'object' && (Array.isArray(x) || (ArrayBuffer.isView(x) && !(x instanceof DataView))))
}
function makeQuerablePromise(promise) {
if (typeof promise !== 'object') {
throw new Error('promise is not an object.')
}
if (!(promise instanceof Promise)) {
throw new Error('Argument is not a promise.')
}
// Don't modify a promise that's been already modified.
if ('isResolved' in promise || 'isRejected' in promise || 'isPending' in promise) {
return promise
}
let isPending = true
let isRejected = false
let rejectReason = undefined
let isResolved = false
let resolvedValue = undefined
const qurPro = promise.then(
function(val){
isResolved = true
isPending = false
resolvedValue = val
return val
}
, function(reason) {
rejectReason = reason
isRejected = true
isPending = false
throw reason
}
)
Object.defineProperties(qurPro, {
'isResolved': {
get: () => isResolved
}
, 'resolvedValue': {
get: () => resolvedValue
}
, 'isPending': {
get: () => isPending
}
, 'isRejected': {
get: () => isRejected
}
, 'rejectReason': {
get: () => rejectReason
}
})
return qurPro
}
/* inserts custom html to allow prettifying of inputs */
function prettifyInputs(root_element) {
root_element.querySelectorAll(`input[type="checkbox"]`).forEach(element => {
var parent = element.parentNode;
if (!parent.classList.contains("input-toggle")) {
var wrapper = document.createElement("div");
wrapper.classList.add("input-toggle");
parent.replaceChild(wrapper, element);
wrapper.appendChild(element);
var label = document.createElement("label");
label.htmlFor = element.id;
wrapper.appendChild(label);
}
})
}
class GenericEventSource {
#events = {};
#types = []
constructor(...eventsTypes) {
if (Array.isArray(eventsTypes) && eventsTypes.length === 1 && Array.isArray(eventsTypes[0])) {
eventsTypes = eventsTypes[0]
}
this.#types.push(...eventsTypes)
}
get eventTypes() {
return this.#types
}
/** Add a new event listener
*/
addEventListener(name, handler) {
if (!this.#types.includes(name)) {
throw new Error('Invalid event name.')
}
if (this.#events.hasOwnProperty(name)) {
this.#events[name].push(handler)
} else {
this.#events[name] = [handler]
}
}
/** Remove the event listener
*/
removeEventListener(name, handler) {
if (!this.#events.hasOwnProperty(name)) {
return
}
const index = this.#events[name].indexOf(handler)
if (index != -1) {
this.#events[name].splice(index, 1)
}
}
fireEvent(name, ...args) {
if (!this.#types.includes(name)) {
throw new Error(`Event ${String(name)} missing from Events.types`)
}
if (!this.#events.hasOwnProperty(name)) {
return Promise.resolve()
}
if (!args || !args.length) {
args = []
}
const evs = this.#events[name]
if (evs.length <= 0) {
return Promise.resolve()
}
return Promise.allSettled(evs.map((callback) => {
try {
return Promise.resolve(callback.apply(SD, args))
} catch (ex) {
return Promise.reject(ex)
}
}))
}
}
class ServiceContainer {
#services = new Map()
#singletons = new Map()
constructor(...servicesParams) {
servicesParams.forEach(this.register.bind(this))
}
get services () {
return this.#services
}
get singletons() {
return this.#singletons
}
register(params) {
if (ServiceContainer.isConstructor(params)) {
if (typeof params.name !== 'string') {
throw new Error('params.name is not a string.')
}
params = {name:params.name, definition:params}
}
if (typeof params !== 'object') {
throw new Error('params is not an object.')
}
[ 'name',
'definition',
].forEach((key) => {
if (!(key in params)) {
console.error('Invalid service %o registration.', params)
throw new Error(`params.${key} is not defined.`)
}
})
const opts = {definition: params.definition}
if ('dependencies' in params) {
if (Array.isArray(params.dependencies)) {
params.dependencies.forEach((dep) => {
if (typeof dep !== 'string') {
throw new Error('dependency name is not a string.')
}
})
opts.dependencies = params.dependencies
} else {
throw new Error('params.dependencies is not an array.')
}
}
if (params.singleton) {
opts.singleton = true
}
this.#services.set(params.name, opts)
return Object.assign({name: params.name}, opts)
}
get(name) {
const ctorInfos = this.#services.get(name)
if (!ctorInfos) {
return
}
if(!ServiceContainer.isConstructor(ctorInfos.definition)) {
return ctorInfos.definition
}
if(!ctorInfos.singleton) {
return this._createInstance(ctorInfos)
}
const singletonInstance = this.#singletons.get(name)
if(singletonInstance) {
return singletonInstance
}
const newSingletonInstance = this._createInstance(ctorInfos)
this.#singletons.set(name, newSingletonInstance)
return newSingletonInstance
}
_getResolvedDependencies(service) {
let classDependencies = []
if(service.dependencies) {
classDependencies = service.dependencies.map(this.get.bind(this))
}
return classDependencies
}
_createInstance(service) {
if (!ServiceContainer.isClass(service.definition)) {
// Call as normal function.
return service.definition(...this._getResolvedDependencies(service))
}
// Use new
return new service.definition(...this._getResolvedDependencies(service))
}
static isClass(definition) {
return typeof definition === 'function' && Boolean(definition.prototype) && definition.prototype.constructor === definition
}
static isConstructor(definition) {
return typeof definition === 'function'
}
}

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413
ui/media/main.css Normal file
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@ -0,0 +1,413 @@
body {
font-family: Arial, Helvetica, sans-serif;
font-size: 11pt;
background-color: rgb(32, 33, 36);
color: #eee;
}
a {
color: rgb(0, 102, 204);
}
a:visited {
color: rgb(0, 102, 204);
}
label {
font-size: 10pt;
}
#prompt {
width: 100%;
height: 65pt;
box-sizing: border-box;
}
@media screen and (max-width: 600px) {
#prompt {
width: 95%;
}
}
.image_preview_container {
/* display: none; */
margin-top: 10pt;
}
.image_clear_btn {
position: absolute;
transform: translateX(-50%) translateY(-35%);
background: black;
color: white;
border: 2pt solid #ccc;
padding: 0;
cursor: pointer;
outline: inherit;
border-radius: 8pt;
width: 16pt;
height: 16pt;
font-family: Verdana;
font-size: 8pt;
}
.settings-box ul {
font-size: 9pt;
margin-bottom: 5px;
padding-left: 10px;
list-style-type: none;
}
.settings-box li {
padding-bottom: 4pt;
}
.editor-slider {
vertical-align: middle;
}
.outputMsg {
font-size: small;
padding-bottom: 3pt;
}
#progressBar {
font-size: small;
}
#footer {
font-size: small;
padding-left: 10pt;
background: none;
}
#footer-legal {
font-size: 8pt;
}
.imgSeedLabel {
font-size: 0.8em;
background-color: rgb(44, 45, 48);
border-radius: 3px;
padding: 5px;
}
.imgItem {
display: inline-block;
margin-top: 1em;
margin-right: 1em;
}
.imgContainer {
display: flex;
justify-content: flex-end;
}
.imgItemInfo {
padding-bottom: 0.5em;
display: flex;
align-items: flex-end;
flex-direction: column;
position: absolute;
padding: 5px;
opacity: 0;
transition: 0.1s all;
}
.imgContainer:hover > .imgItemInfo {
opacity: 1;
}
.imgItemInfo * {
margin-bottom: 7px;
}
#container {
width: 90%;
margin-left: auto;
margin-right: auto;
}
@media screen and (max-width: 1800px) {
#container {
width: 100%;
}
}
#logo small {
font-size: 11pt;
}
#editor {
padding: 5px;
}
#editor label {
font-weight: normal;
}
.settings-box label small {
color: rgb(153, 153, 153);
}
#preview {
padding: 5px;
}
#editor-inputs {
margin-bottom: 20px;
}
#editor-inputs-prompt {
flex: 1;
}
#editor-inputs .row {
padding-bottom: 10px;
}
#makeImage {
border-radius: 6px;
}
#editor-modifiers h5 {
padding: 5pt 0;
margin: 0;
}
#makeImage {
flex: 0 0 70px;
background: rgb(80, 0, 185);
border: 2px solid rgb(40, 0, 78);
color: rgb(255, 221, 255);
width: 100%;
height: 30pt;
}
#makeImage:hover {
background: rgb(93, 0, 214);
}
#stopImage {
flex: 0 0 70px;
background: rgb(132, 8, 0);
border: 2px solid rgb(122, 29, 0);
color: rgb(255, 221, 255);
width: 100%;
height: 30pt;
border-radius: 6px;
display: none;
}
#stopImage:hover {
background: rgb(177, 27, 0);
}
.flex-container {
display: flex;
}
.col-50 {
flex: 50%;
}
.col-fixed-10 {
flex: 0 0 380pt;
}
.col-free {
flex: 1;
}
.collapsible {
cursor: pointer;
}
.collapsible-content {
display: none;
padding-left: 15px;
}
.collapsible-content h5 {
padding: 5pt 0pt;
margin: 0;
font-size: 10pt;
}
.collapsible-handle {
color: white;
padding-right: 5px;
}
.panel-box {
background: rgb(44, 45, 48);
border: 1px solid rgb(47, 49, 53);
border-radius: 7px;
padding: 5px;
margin-bottom: 15px;
box-shadow: 0 4px 8px 0 rgba(0, 0, 0, 0.15), 0 6px 20px 0 rgba(0, 0, 0, 0.15);
}
.panel-box h4 {
margin: 0;
padding: 2px 0;
}
#editor-modifiers .editor-modifiers-leaf {
padding-top: 10pt;
padding-bottom: 10pt;
}
#preview {
margin-left: 10pt;
}
img {
box-shadow: 0 4px 8px 0 rgba(0, 0, 0, 0.15), 0 6px 20px 0 rgba(0, 0, 0, 0.15);
}
.line-separator {
background: rgb(56, 56, 56);
height: 1pt;
margin: 15pt 0;
}
#editor-inputs-tags-container {
margin-top: 5pt;
display: none;
}
#server-status {
display: inline;
float: right;
transform: translateY(-5pt);
}
#server-status-color {
/* width: 8pt;
height: 8pt;
border-radius: 4pt; */
font-size: 14pt;
color: rgb(128, 87, 0);
/* background-color: rgb(197, 1, 1); */
/* transform: translateY(15%); */
display: inline;
}
#server-status-msg {
color: rgb(128, 87, 0);
padding-left: 2pt;
font-size: 10pt;
}
.preview-prompt {
font-size: 16pt;
margin-bottom: 10pt;
}
#coffeeButton {
height: 23px;
transform: translateY(25%);
}
#inpaintingEditor {
width: 300pt;
height: 300pt;
margin-top: 5pt;
}
.drawing-board-canvas-wrapper {
background-size: 100% 100%;
}
.drawing-board-control > button {
background-color: #eee;
border-radius: 3pt;
}
.drawing-board-control-inner {
background-color: #eee;
border-radius: 3pt;
}
#inpaintingEditor canvas {
opacity: 0.6;
}
#enable_mask {
margin-top: 8pt;
}
#top-nav {
padding-top: 3pt;
padding-bottom: 15pt;
}
#top-nav .icon {
padding-right: 4pt;
font-size: 14pt;
transform: translateY(1pt);
}
#logo {
display: inline;
}
#logo h1 {
display: inline;
}
#top-nav-items {
list-style-type: none;
display: inline;
float: right;
}
#top-nav-items > li {
float: left;
display: inline;
padding-left: 20pt;
cursor: default;
}
#initial-text {
padding-top: 15pt;
padding-left: 4pt;
}
.settings-subheader {
font-size: 10pt;
font-weight: bold;
}
.pl-5 {
padding-left: 5pt;
}
#system-settings {
width: 360pt;
transform: translateX(-100%) translateX(70pt);
padding-top: 10pt;
padding-bottom: 10pt;
}
#system-settings ul {
margin: 0;
padding: 0;
}
#system-settings li {
padding-left: 5pt;
}
#community-links {
list-style-type: none;
margin: 0;
padding: 12pt;
padding-bottom: 0pt;
transform: translateX(-15%);
}
#community-links li {
padding-bottom: 12pt;
display: block;
font-size: 10pt;
}
#community-links li .fa-fw {
padding-right: 2pt;
}
#community-links li a {
color: white;
text-decoration: none;
}
.dropdown {
overflow: hidden;
}
.dropdown-content {
display: none;
position: absolute;
z-index: 2;
background: rgb(18, 18, 19);
border: 2px solid rgb(37, 38, 41);
border-radius: 7px;
padding: 5px;
margin-bottom: 15px;
box-shadow: 0 20px 28px 0 rgba(0, 0, 0, 0.15), 0 6px 20px 0 rgba(0, 0, 0, 0.15);
}
.dropdown:hover .dropdown-content {
display: block;
}
.imageTaskContainer {
border: 1px solid #333;
margin-bottom: 10pt;
padding: 5pt;
border-radius: 5pt;
box-shadow: 0 20px 28px 0 rgba(0, 0, 0, 0.15), 0 6px 20px 0 rgba(0, 0, 0, 0.15);
}
.taskStatusLabel {
float: left;
font-size: 8pt;
background:rgb(44, 45, 48);
border: 1px solid rgb(61, 62, 66);
padding: 2pt 4pt;
border-radius: 2pt;
margin-right: 5pt;
}
.activeTaskLabel {
background:rgb(0, 90, 30);
border: 1px solid rgb(0, 75, 19);
color:rgb(204, 255, 217)
}
.secondaryButton {
background: rgb(132, 8, 0);
border: 1px solid rgb(122, 29, 0);
color: rgb(255, 221, 255);
padding: 3pt 6pt;
border-radius: 5px;
}
.secondaryButton:hover {
background: rgb(177, 27, 0);
}
.stopTask {
float: right;
}
#preview-tools {
display: none;
padding: 4pt;
}
.taskConfig {
font-size: 10pt;
color: #aaa;
margin-bottom: 5pt;
}
.img-batch {
display: inline;
}

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ui/media/main.js Normal file

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{
"name": "Stable Diffusion UI",
"display": "standalone",
"display_override": [
"window-controls-overlay"
],
"theme_color": "#000000"
}

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@ -214,10 +214,3 @@
margin-bottom: 0.5em;
vertical-align: middle;
}
#modifier-settings-btn {
float: right;
}
#modifier-settings-config textarea {
width: 90%;
height: 150px;
}

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(function () {
"use strict"
var styleSheet = document.createElement("style");
styleSheet.textContent = `
.auto-scroll {
float: right;
}
`;
document.head.appendChild(styleSheet);
const autoScrollControl = document.createElement('div');
autoScrollControl.innerHTML = `<input id="auto_scroll" name="auto_scroll" type="checkbox">
<label for="auto_scroll">Scroll to generated image</label>`
autoScrollControl.className = "auto-scroll"
clearAllPreviewsBtn.parentNode.insertBefore(autoScrollControl, clearAllPreviewsBtn.nextSibling)
prettifyInputs(document);
let autoScroll = document.querySelector("#auto_scroll")
// save/restore the toggle state
autoScroll.addEventListener('click', (e) => {
localStorage.setItem('auto_scroll', autoScroll.checked)
})
autoScroll.checked = localStorage.getItem('auto_scroll') == "true"
// observe for changes in the preview pane
var observer = new MutationObserver(function (mutations) {
mutations.forEach(function (mutation) {
if (mutation.target.className == 'img-batch') {
Autoscroll(mutation.target)
}
})
})
observer.observe(document.getElementById('preview'), {
childList: true,
subtree: true
})
function Autoscroll(target) {
if (autoScroll.checked && target !== null) {
target.parentElement.parentElement.parentElement.scrollIntoView();
}
}
})()

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@ -1,94 +0,0 @@
(function () { "use strict"
if (typeof editorModifierTagsList !== 'object') {
console.error('editorModifierTagsList missing...')
return
}
const styleSheet = document.createElement("style");
styleSheet.textContent = `
.modifier-card-tiny.drag-sort-active {
background: transparent;
border: 2px dashed white;
opacity:0.2;
}
`;
document.head.appendChild(styleSheet);
// observe for changes in tag list
const observer = new MutationObserver(function (mutations) {
// mutations.forEach(function (mutation) {
if (editorModifierTagsList.childNodes.length > 0) {
ModifierDragAndDrop(editorModifierTagsList)
}
// })
})
observer.observe(editorModifierTagsList, {
childList: true
})
let current
function ModifierDragAndDrop(target) {
let overlays = document.querySelector('#editor-inputs-tags-list').querySelectorAll('.modifier-card-overlay')
overlays.forEach (i => {
i.parentElement.draggable = true;
i.parentElement.ondragstart = (e) => {
current = i
i.parentElement.getElementsByClassName('modifier-card-image-overlay')[0].innerText = ''
i.parentElement.draggable = true
i.parentElement.classList.add('drag-sort-active')
for(let item of document.querySelector('#editor-inputs-tags-list').getElementsByClassName('modifier-card-image-overlay')) {
if (item.parentElement.parentElement.getElementsByClassName('modifier-card-overlay')[0] != current) {
item.parentElement.parentElement.getElementsByClassName('modifier-card-image-overlay')[0].style.opacity = 0
if(item.parentElement.getElementsByClassName('modifier-card-image').length > 0) {
item.parentElement.getElementsByClassName('modifier-card-image')[0].style.filter = 'none'
}
item.parentElement.parentElement.style.transform = 'none'
item.parentElement.parentElement.style.boxShadow = 'none'
}
item.innerText = ''
}
}
i.ondragenter = (e) => {
e.preventDefault()
if (i != current) {
let currentPos = 0, droppedPos = 0;
for (let it = 0; it < overlays.length; it++) {
if (current == overlays[it]) { currentPos = it; }
if (i == overlays[it]) { droppedPos = it; }
}
if (i.parentElement != current.parentElement) {
let currentPos = 0, droppedPos = 0
for (let it = 0; it < overlays.length; it++) {
if (current == overlays[it]) { currentPos = it }
if (i == overlays[it]) { droppedPos = it }
}
if (currentPos < droppedPos) {
current = i.parentElement.parentNode.insertBefore(current.parentElement, i.parentElement.nextSibling).getElementsByClassName('modifier-card-overlay')[0]
} else {
current = i.parentElement.parentNode.insertBefore(current.parentElement, i.parentElement).getElementsByClassName('modifier-card-overlay')[0]
}
// update activeTags
const tag = activeTags.splice(currentPos, 1)
activeTags.splice(droppedPos, 0, tag[0])
}
}
};
i.ondragover = (e) => {
e.preventDefault()
}
i.parentElement.ondragend = (e) => {
i.parentElement.classList.remove('drag-sort-active')
for(let item of document.querySelector('#editor-inputs-tags-list').getElementsByClassName('modifier-card-image-overlay')) {
item.style.opacity = ''
item.innerText = '-'
}
}
})
}
})()

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@ -1,65 +0,0 @@
(function () { "use strict"
if (typeof editorModifierTagsList !== 'object') {
console.error('editorModifierTagsList missing...')
return
}
// observe for changes in tag list
const observer = new MutationObserver(function (mutations) {
// mutations.forEach(function (mutation) {
if (editorModifierTagsList.childNodes.length > 0) {
ModifierMouseWheel(editorModifierTagsList)
}
// })
})
observer.observe(editorModifierTagsList, {
childList: true
})
function ModifierMouseWheel(target) {
let overlays = document.querySelector('#editor-inputs-tags-list').querySelectorAll('.modifier-card-overlay')
overlays.forEach (i => {
i.onwheel = (e) => {
if (e.ctrlKey == true) {
e.preventDefault()
const delta = Math.sign(event.deltaY)
let s = i.parentElement.getElementsByClassName('modifier-card-label')[0].getElementsByTagName("p")[0].innerText
if (delta < 0) {
// wheel scrolling up
if (s.substring(0, 1) == '[' && s.substring(s.length-1) == ']') {
s = s.substring(1, s.length - 1)
}
else
{
if (s.substring(0, 10) !== '('.repeat(10) && s.substring(s.length-10) !== ')'.repeat(10)) {
s = '(' + s + ')'
}
}
}
else{
// wheel scrolling down
if (s.substring(0, 1) == '(' && s.substring(s.length-1) == ')') {
s = s.substring(1, s.length - 1)
}
else
{
if (s.substring(0, 10) !== '['.repeat(10) && s.substring(s.length-10) !== ']'.repeat(10)) {
s = '[' + s + ']'
}
}
}
i.parentElement.getElementsByClassName('modifier-card-label')[0].getElementsByTagName("p")[0].innerText = s
// update activeTags
for (let it = 0; it < overlays.length; it++) {
if (i == overlays[it]) {
activeTags[it].name = s
break
}
}
}
}
})
}
})()

View File

@ -1,3 +0,0 @@
Custom plugins in this folder will be shipped to all the users by default.
This allows UI features to be built as plugins (testing our Plugins API, and keeping our core lean and modular).

View File

@ -1,29 +0,0 @@
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>Jasmine Spec Runner v4.5.0</title>
<link rel="shortcut icon" type="image/png" href="./jasmine/jasmine_favicon.png">
<link rel="stylesheet" href="./jasmine/jasmine.css">
<script src="./jasmine/jasmine.js"></script>
<script src="./jasmine/jasmine-html.js"></script>
<script src="./jasmine/boot0.js"></script>
<!-- optional: include a file here that configures the Jasmine env -->
<script src="./jasmine/boot1.js"></script>
<!-- include source files here... -->
<script src="/media/js/utils.js?v=4"></script>
<script src="/media/js/engine.js?v=1"></script>
<!-- <script src="./engine.js?v=1"></script> -->
<script src="/media/js/plugins.js?v=1"></script>
<!-- include spec files here... -->
<script src="./jasmineSpec.js"></script>
</head>
<body>
</body>
</html>

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@ -1,31 +0,0 @@
(function() {
PLUGINS['MODIFIERS_LOAD'].push({
loader: function() {
let customModifiers = localStorage.getItem(CUSTOM_MODIFIERS_KEY, '')
customModifiersTextBox.value = customModifiers
if (customModifiersGroupElement !== undefined) {
customModifiersGroupElement.remove()
}
if (customModifiers && customModifiers.trim() !== '') {
customModifiers = customModifiers.split('\n')
customModifiers = customModifiers.filter(m => m.trim() !== '')
customModifiers = customModifiers.map(function(m) {
return {
"modifier": m
}
})
let customGroup = {
'category': 'Custom Modifiers',
'modifiers': customModifiers
}
customModifiersGroupElement = createModifierGroup(customGroup, true)
createCollapsibles(customModifiersGroupElement)
}
}
})
})()

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@ -1,64 +0,0 @@
/*
Copyright (c) 2008-2022 Pivotal Labs
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*/
/**
This file starts the process of "booting" Jasmine. It initializes Jasmine,
makes its globals available, and creates the env. This file should be loaded
after `jasmine.js` and `jasmine_html.js`, but before `boot1.js` or any project
source files or spec files are loaded.
*/
(function() {
const jasmineRequire = window.jasmineRequire || require('./jasmine.js');
/**
* ## Require &amp; Instantiate
*
* Require Jasmine's core files. Specifically, this requires and attaches all of Jasmine's code to the `jasmine` reference.
*/
const jasmine = jasmineRequire.core(jasmineRequire),
global = jasmine.getGlobal();
global.jasmine = jasmine;
/**
* Since this is being run in a browser and the results should populate to an HTML page, require the HTML-specific Jasmine code, injecting the same reference.
*/
jasmineRequire.html(jasmine);
/**
* Create the Jasmine environment. This is used to run all specs in a project.
*/
const env = jasmine.getEnv();
/**
* ## The Global Interface
*
* Build up the functions that will be exposed as the Jasmine public interface. A project can customize, rename or alias any of these functions as desired, provided the implementation remains unchanged.
*/
const jasmineInterface = jasmineRequire.interface(jasmine, env);
/**
* Add all of the Jasmine global/public interface to the global scope, so a project can use the public interface directly. For example, calling `describe` in specs instead of `jasmine.getEnv().describe`.
*/
for (const property in jasmineInterface) {
global[property] = jasmineInterface[property];
}
})();

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@ -1,132 +0,0 @@
/*
Copyright (c) 2008-2022 Pivotal Labs
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*/
/**
This file finishes 'booting' Jasmine, performing all of the necessary
initialization before executing the loaded environment and all of a project's
specs. This file should be loaded after `boot0.js` but before any project
source files or spec files are loaded. Thus this file can also be used to
customize Jasmine for a project.
If a project is using Jasmine via the standalone distribution, this file can
be customized directly. If you only wish to configure the Jasmine env, you
can load another file that calls `jasmine.getEnv().configure({...})`
after `boot0.js` is loaded and before this file is loaded.
*/
(function() {
const env = jasmine.getEnv();
/**
* ## Runner Parameters
*
* More browser specific code - wrap the query string in an object and to allow for getting/setting parameters from the runner user interface.
*/
const queryString = new jasmine.QueryString({
getWindowLocation: function() {
return window.location;
}
});
const filterSpecs = !!queryString.getParam('spec');
const config = {
stopOnSpecFailure: queryString.getParam('stopOnSpecFailure'),
stopSpecOnExpectationFailure: queryString.getParam(
'stopSpecOnExpectationFailure'
),
hideDisabled: queryString.getParam('hideDisabled')
};
const random = queryString.getParam('random');
if (random !== undefined && random !== '') {
config.random = random;
}
const seed = queryString.getParam('seed');
if (seed) {
config.seed = seed;
}
/**
* ## Reporters
* The `HtmlReporter` builds all of the HTML UI for the runner page. This reporter paints the dots, stars, and x's for specs, as well as all spec names and all failures (if any).
*/
const htmlReporter = new jasmine.HtmlReporter({
env: env,
navigateWithNewParam: function(key, value) {
return queryString.navigateWithNewParam(key, value);
},
addToExistingQueryString: function(key, value) {
return queryString.fullStringWithNewParam(key, value);
},
getContainer: function() {
return document.body;
},
createElement: function() {
return document.createElement.apply(document, arguments);
},
createTextNode: function() {
return document.createTextNode.apply(document, arguments);
},
timer: new jasmine.Timer(),
filterSpecs: filterSpecs
});
/**
* The `jsApiReporter` also receives spec results, and is used by any environment that needs to extract the results from JavaScript.
*/
env.addReporter(jsApiReporter);
env.addReporter(htmlReporter);
/**
* Filter which specs will be run by matching the start of the full name against the `spec` query param.
*/
const specFilter = new jasmine.HtmlSpecFilter({
filterString: function() {
return queryString.getParam('spec');
}
});
config.specFilter = function(spec) {
return specFilter.matches(spec.getFullName());
};
env.configure(config);
/**
* ## Execution
*
* Replace the browser window's `onload`, ensure it's called, and then run all of the loaded specs. This includes initializing the `HtmlReporter` instance and then executing the loaded Jasmine environment. All of this will happen after all of the specs are loaded.
*/
const currentWindowOnload = window.onload;
window.onload = function() {
if (currentWindowOnload) {
currentWindowOnload();
}
htmlReporter.initialize();
env.execute();
};
})();

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@ -1,964 +0,0 @@
/*
Copyright (c) 2008-2022 Pivotal Labs
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*/
// eslint-disable-next-line no-var
var jasmineRequire = window.jasmineRequire || require('./jasmine.js');
jasmineRequire.html = function(j$) {
j$.ResultsNode = jasmineRequire.ResultsNode();
j$.HtmlReporter = jasmineRequire.HtmlReporter(j$);
j$.QueryString = jasmineRequire.QueryString();
j$.HtmlSpecFilter = jasmineRequire.HtmlSpecFilter();
};
jasmineRequire.HtmlReporter = function(j$) {
function ResultsStateBuilder() {
this.topResults = new j$.ResultsNode({}, '', null);
this.currentParent = this.topResults;
this.specsExecuted = 0;
this.failureCount = 0;
this.pendingSpecCount = 0;
}
ResultsStateBuilder.prototype.suiteStarted = function(result) {
this.currentParent.addChild(result, 'suite');
this.currentParent = this.currentParent.last();
};
ResultsStateBuilder.prototype.suiteDone = function(result) {
this.currentParent.updateResult(result);
if (this.currentParent !== this.topResults) {
this.currentParent = this.currentParent.parent;
}
if (result.status === 'failed') {
this.failureCount++;
}
};
ResultsStateBuilder.prototype.specStarted = function(result) {};
ResultsStateBuilder.prototype.specDone = function(result) {
this.currentParent.addChild(result, 'spec');
if (result.status !== 'excluded') {
this.specsExecuted++;
}
if (result.status === 'failed') {
this.failureCount++;
}
if (result.status == 'pending') {
this.pendingSpecCount++;
}
};
ResultsStateBuilder.prototype.jasmineDone = function(result) {
if (result.failedExpectations) {
this.failureCount += result.failedExpectations.length;
}
};
function HtmlReporter(options) {
function config() {
return (options.env && options.env.configuration()) || {};
}
const getContainer = options.getContainer;
const createElement = options.createElement;
const createTextNode = options.createTextNode;
const navigateWithNewParam = options.navigateWithNewParam || function() {};
const addToExistingQueryString =
options.addToExistingQueryString || defaultQueryString;
const filterSpecs = options.filterSpecs;
let htmlReporterMain;
let symbols;
const deprecationWarnings = [];
const failures = [];
this.initialize = function() {
clearPrior();
htmlReporterMain = createDom(
'div',
{ className: 'jasmine_html-reporter' },
createDom(
'div',
{ className: 'jasmine-banner' },
createDom('a', {
className: 'jasmine-title',
href: 'http://jasmine.github.io/',
target: '_blank'
}),
createDom('span', { className: 'jasmine-version' }, j$.version)
),
createDom('ul', { className: 'jasmine-symbol-summary' }),
createDom('div', { className: 'jasmine-alert' }),
createDom(
'div',
{ className: 'jasmine-results' },
createDom('div', { className: 'jasmine-failures' })
)
);
getContainer().appendChild(htmlReporterMain);
};
let totalSpecsDefined;
this.jasmineStarted = function(options) {
totalSpecsDefined = options.totalSpecsDefined || 0;
};
const summary = createDom('div', { className: 'jasmine-summary' });
const stateBuilder = new ResultsStateBuilder();
this.suiteStarted = function(result) {
stateBuilder.suiteStarted(result);
};
this.suiteDone = function(result) {
stateBuilder.suiteDone(result);
if (result.status === 'failed') {
failures.push(failureDom(result));
}
addDeprecationWarnings(result, 'suite');
};
this.specStarted = function(result) {
stateBuilder.specStarted(result);
};
this.specDone = function(result) {
stateBuilder.specDone(result);
if (noExpectations(result)) {
const noSpecMsg = "Spec '" + result.fullName + "' has no expectations.";
if (result.status === 'failed') {
console.error(noSpecMsg);
} else {
console.warn(noSpecMsg);
}
}
if (!symbols) {
symbols = find('.jasmine-symbol-summary');
}
symbols.appendChild(
createDom('li', {
className: this.displaySpecInCorrectFormat(result),
id: 'spec_' + result.id,
title: result.fullName
})
);
if (result.status === 'failed') {
failures.push(failureDom(result));
}
addDeprecationWarnings(result, 'spec');
};
this.displaySpecInCorrectFormat = function(result) {
return noExpectations(result) && result.status === 'passed'
? 'jasmine-empty'
: this.resultStatus(result.status);
};
this.resultStatus = function(status) {
if (status === 'excluded') {
return config().hideDisabled
? 'jasmine-excluded-no-display'
: 'jasmine-excluded';
}
return 'jasmine-' + status;
};
this.jasmineDone = function(doneResult) {
stateBuilder.jasmineDone(doneResult);
const banner = find('.jasmine-banner');
const alert = find('.jasmine-alert');
const order = doneResult && doneResult.order;
alert.appendChild(
createDom(
'span',
{ className: 'jasmine-duration' },
'finished in ' + doneResult.totalTime / 1000 + 's'
)
);
banner.appendChild(optionsMenu(config()));
if (stateBuilder.specsExecuted < totalSpecsDefined) {
const skippedMessage =
'Ran ' +
stateBuilder.specsExecuted +
' of ' +
totalSpecsDefined +
' specs - run all';
// include window.location.pathname to fix issue with karma-jasmine-html-reporter in angular: see https://github.com/jasmine/jasmine/issues/1906
const skippedLink =
(window.location.pathname || '') +
addToExistingQueryString('spec', '');
alert.appendChild(
createDom(
'span',
{ className: 'jasmine-bar jasmine-skipped' },
createDom(
'a',
{ href: skippedLink, title: 'Run all specs' },
skippedMessage
)
)
);
}
let statusBarMessage = '';
let statusBarClassName = 'jasmine-overall-result jasmine-bar ';
const globalFailures =
(doneResult && doneResult.failedExpectations) || [];
const failed = stateBuilder.failureCount + globalFailures.length > 0;
if (totalSpecsDefined > 0 || failed) {
statusBarMessage +=
pluralize('spec', stateBuilder.specsExecuted) +
', ' +
pluralize('failure', stateBuilder.failureCount);
if (stateBuilder.pendingSpecCount) {
statusBarMessage +=
', ' + pluralize('pending spec', stateBuilder.pendingSpecCount);
}
}
if (doneResult.overallStatus === 'passed') {
statusBarClassName += ' jasmine-passed ';
} else if (doneResult.overallStatus === 'incomplete') {
statusBarClassName += ' jasmine-incomplete ';
statusBarMessage =
'Incomplete: ' +
doneResult.incompleteReason +
', ' +
statusBarMessage;
} else {
statusBarClassName += ' jasmine-failed ';
}
let seedBar;
if (order && order.random) {
seedBar = createDom(
'span',
{ className: 'jasmine-seed-bar' },
', randomized with seed ',
createDom(
'a',
{
title: 'randomized with seed ' + order.seed,
href: seedHref(order.seed)
},
order.seed
)
);
}
alert.appendChild(
createDom(
'span',
{ className: statusBarClassName },
statusBarMessage,
seedBar
)
);
const errorBarClassName = 'jasmine-bar jasmine-errored';
const afterAllMessagePrefix = 'AfterAll ';
for (let i = 0; i < globalFailures.length; i++) {
alert.appendChild(
createDom(
'span',
{ className: errorBarClassName },
globalFailureMessage(globalFailures[i])
)
);
}
function globalFailureMessage(failure) {
if (failure.globalErrorType === 'load') {
const prefix = 'Error during loading: ' + failure.message;
if (failure.filename) {
return (
prefix + ' in ' + failure.filename + ' line ' + failure.lineno
);
} else {
return prefix;
}
} else if (failure.globalErrorType === 'afterAll') {
return afterAllMessagePrefix + failure.message;
} else {
return failure.message;
}
}
addDeprecationWarnings(doneResult);
for (let i = 0; i < deprecationWarnings.length; i++) {
const children = [];
let context;
switch (deprecationWarnings[i].runnableType) {
case 'spec':
context = '(in spec: ' + deprecationWarnings[i].runnableName + ')';
break;
case 'suite':
context = '(in suite: ' + deprecationWarnings[i].runnableName + ')';
break;
default:
context = '';
}
deprecationWarnings[i].message.split('\n').forEach(function(line) {
children.push(line);
children.push(createDom('br'));
});
children[0] = 'DEPRECATION: ' + children[0];
children.push(context);
if (deprecationWarnings[i].stack) {
children.push(createExpander(deprecationWarnings[i].stack));
}
alert.appendChild(
createDom(
'span',
{ className: 'jasmine-bar jasmine-warning' },
children
)
);
}
const results = find('.jasmine-results');
results.appendChild(summary);
summaryList(stateBuilder.topResults, summary);
if (failures.length) {
alert.appendChild(
createDom(
'span',
{ className: 'jasmine-menu jasmine-bar jasmine-spec-list' },
createDom('span', {}, 'Spec List | '),
createDom(
'a',
{ className: 'jasmine-failures-menu', href: '#' },
'Failures'
)
)
);
alert.appendChild(
createDom(
'span',
{ className: 'jasmine-menu jasmine-bar jasmine-failure-list' },
createDom(
'a',
{ className: 'jasmine-spec-list-menu', href: '#' },
'Spec List'
),
createDom('span', {}, ' | Failures ')
)
);
find('.jasmine-failures-menu').onclick = function() {
setMenuModeTo('jasmine-failure-list');
return false;
};
find('.jasmine-spec-list-menu').onclick = function() {
setMenuModeTo('jasmine-spec-list');
return false;
};
setMenuModeTo('jasmine-failure-list');
const failureNode = find('.jasmine-failures');
for (let i = 0; i < failures.length; i++) {
failureNode.appendChild(failures[i]);
}
}
};
return this;
function failureDom(result) {
const failure = createDom(
'div',
{ className: 'jasmine-spec-detail jasmine-failed' },
failureDescription(result, stateBuilder.currentParent),
createDom('div', { className: 'jasmine-messages' })
);
const messages = failure.childNodes[1];
for (let i = 0; i < result.failedExpectations.length; i++) {
const expectation = result.failedExpectations[i];
messages.appendChild(
createDom(
'div',
{ className: 'jasmine-result-message' },
expectation.message
)
);
messages.appendChild(
createDom(
'div',
{ className: 'jasmine-stack-trace' },
expectation.stack
)
);
}
if (result.failedExpectations.length === 0) {
messages.appendChild(
createDom(
'div',
{ className: 'jasmine-result-message' },
'Spec has no expectations'
)
);
}
if (result.debugLogs) {
messages.appendChild(debugLogTable(result.debugLogs));
}
return failure;
}
function debugLogTable(debugLogs) {
const tbody = createDom('tbody');
debugLogs.forEach(function(entry) {
tbody.appendChild(
createDom(
'tr',
{},
createDom('td', {}, entry.timestamp.toString()),
createDom('td', {}, entry.message)
)
);
});
return createDom(
'div',
{ className: 'jasmine-debug-log' },
createDom(
'div',
{ className: 'jasmine-debug-log-header' },
'Debug logs'
),
createDom(
'table',
{},
createDom(
'thead',
{},
createDom(
'tr',
{},
createDom('th', {}, 'Time (ms)'),
createDom('th', {}, 'Message')
)
),
tbody
)
);
}
function summaryList(resultsTree, domParent) {
let specListNode;
for (let i = 0; i < resultsTree.children.length; i++) {
const resultNode = resultsTree.children[i];
if (filterSpecs && !hasActiveSpec(resultNode)) {
continue;
}
if (resultNode.type === 'suite') {
const suiteListNode = createDom(
'ul',
{ className: 'jasmine-suite', id: 'suite-' + resultNode.result.id },
createDom(
'li',
{
className:
'jasmine-suite-detail jasmine-' + resultNode.result.status
},
createDom(
'a',
{ href: specHref(resultNode.result) },
resultNode.result.description
)
)
);
summaryList(resultNode, suiteListNode);
domParent.appendChild(suiteListNode);
}
if (resultNode.type === 'spec') {
if (domParent.getAttribute('class') !== 'jasmine-specs') {
specListNode = createDom('ul', { className: 'jasmine-specs' });
domParent.appendChild(specListNode);
}
let specDescription = resultNode.result.description;
if (noExpectations(resultNode.result)) {
specDescription = 'SPEC HAS NO EXPECTATIONS ' + specDescription;
}
if (
resultNode.result.status === 'pending' &&
resultNode.result.pendingReason !== ''
) {
specDescription =
specDescription +
' PENDING WITH MESSAGE: ' +
resultNode.result.pendingReason;
}
specListNode.appendChild(
createDom(
'li',
{
className: 'jasmine-' + resultNode.result.status,
id: 'spec-' + resultNode.result.id
},
createDom(
'a',
{ href: specHref(resultNode.result) },
specDescription
)
)
);
}
}
}
function optionsMenu(config) {
const optionsMenuDom = createDom(
'div',
{ className: 'jasmine-run-options' },
createDom('span', { className: 'jasmine-trigger' }, 'Options'),
createDom(
'div',
{ className: 'jasmine-payload' },
createDom(
'div',
{ className: 'jasmine-stop-on-failure' },
createDom('input', {
className: 'jasmine-fail-fast',
id: 'jasmine-fail-fast',
type: 'checkbox'
}),
createDom(
'label',
{ className: 'jasmine-label', for: 'jasmine-fail-fast' },
'stop execution on spec failure'
)
),
createDom(
'div',
{ className: 'jasmine-throw-failures' },
createDom('input', {
className: 'jasmine-throw',
id: 'jasmine-throw-failures',
type: 'checkbox'
}),
createDom(
'label',
{ className: 'jasmine-label', for: 'jasmine-throw-failures' },
'stop spec on expectation failure'
)
),
createDom(
'div',
{ className: 'jasmine-random-order' },
createDom('input', {
className: 'jasmine-random',
id: 'jasmine-random-order',
type: 'checkbox'
}),
createDom(
'label',
{ className: 'jasmine-label', for: 'jasmine-random-order' },
'run tests in random order'
)
),
createDom(
'div',
{ className: 'jasmine-hide-disabled' },
createDom('input', {
className: 'jasmine-disabled',
id: 'jasmine-hide-disabled',
type: 'checkbox'
}),
createDom(
'label',
{ className: 'jasmine-label', for: 'jasmine-hide-disabled' },
'hide disabled tests'
)
)
)
);
const failFastCheckbox = optionsMenuDom.querySelector(
'#jasmine-fail-fast'
);
failFastCheckbox.checked = config.stopOnSpecFailure;
failFastCheckbox.onclick = function() {
navigateWithNewParam('stopOnSpecFailure', !config.stopOnSpecFailure);
};
const throwCheckbox = optionsMenuDom.querySelector(
'#jasmine-throw-failures'
);
throwCheckbox.checked = config.stopSpecOnExpectationFailure;
throwCheckbox.onclick = function() {
navigateWithNewParam(
'stopSpecOnExpectationFailure',
!config.stopSpecOnExpectationFailure
);
};
const randomCheckbox = optionsMenuDom.querySelector(
'#jasmine-random-order'
);
randomCheckbox.checked = config.random;
randomCheckbox.onclick = function() {
navigateWithNewParam('random', !config.random);
};
const hideDisabled = optionsMenuDom.querySelector(
'#jasmine-hide-disabled'
);
hideDisabled.checked = config.hideDisabled;
hideDisabled.onclick = function() {
navigateWithNewParam('hideDisabled', !config.hideDisabled);
};
const optionsTrigger = optionsMenuDom.querySelector('.jasmine-trigger'),
optionsPayload = optionsMenuDom.querySelector('.jasmine-payload'),
isOpen = /\bjasmine-open\b/;
optionsTrigger.onclick = function() {
if (isOpen.test(optionsPayload.className)) {
optionsPayload.className = optionsPayload.className.replace(
isOpen,
''
);
} else {
optionsPayload.className += ' jasmine-open';
}
};
return optionsMenuDom;
}
function failureDescription(result, suite) {
const wrapper = createDom(
'div',
{ className: 'jasmine-description' },
createDom(
'a',
{ title: result.description, href: specHref(result) },
result.description
)
);
let suiteLink;
while (suite && suite.parent) {
wrapper.insertBefore(createTextNode(' > '), wrapper.firstChild);
suiteLink = createDom(
'a',
{ href: suiteHref(suite) },
suite.result.description
);
wrapper.insertBefore(suiteLink, wrapper.firstChild);
suite = suite.parent;
}
return wrapper;
}
function suiteHref(suite) {
const els = [];
while (suite && suite.parent) {
els.unshift(suite.result.description);
suite = suite.parent;
}
// include window.location.pathname to fix issue with karma-jasmine-html-reporter in angular: see https://github.com/jasmine/jasmine/issues/1906
return (
(window.location.pathname || '') +
addToExistingQueryString('spec', els.join(' '))
);
}
function addDeprecationWarnings(result, runnableType) {
if (result && result.deprecationWarnings) {
for (let i = 0; i < result.deprecationWarnings.length; i++) {
const warning = result.deprecationWarnings[i].message;
deprecationWarnings.push({
message: warning,
stack: result.deprecationWarnings[i].stack,
runnableName: result.fullName,
runnableType: runnableType
});
}
}
}
function createExpander(stackTrace) {
const expandLink = createDom('a', { href: '#' }, 'Show stack trace');
const root = createDom(
'div',
{ className: 'jasmine-expander' },
expandLink,
createDom(
'div',
{ className: 'jasmine-expander-contents jasmine-stack-trace' },
stackTrace
)
);
expandLink.addEventListener('click', function(e) {
e.preventDefault();
if (root.classList.contains('jasmine-expanded')) {
root.classList.remove('jasmine-expanded');
expandLink.textContent = 'Show stack trace';
} else {
root.classList.add('jasmine-expanded');
expandLink.textContent = 'Hide stack trace';
}
});
return root;
}
function find(selector) {
return getContainer().querySelector('.jasmine_html-reporter ' + selector);
}
function clearPrior() {
const oldReporter = find('');
if (oldReporter) {
getContainer().removeChild(oldReporter);
}
}
function createDom(type, attrs, childrenArrayOrVarArgs) {
const el = createElement(type);
let children;
if (j$.isArray_(childrenArrayOrVarArgs)) {
children = childrenArrayOrVarArgs;
} else {
children = [];
for (let i = 2; i < arguments.length; i++) {
children.push(arguments[i]);
}
}
for (let i = 0; i < children.length; i++) {
const child = children[i];
if (typeof child === 'string') {
el.appendChild(createTextNode(child));
} else {
if (child) {
el.appendChild(child);
}
}
}
for (const attr in attrs) {
if (attr == 'className') {
el[attr] = attrs[attr];
} else {
el.setAttribute(attr, attrs[attr]);
}
}
return el;
}
function pluralize(singular, count) {
const word = count == 1 ? singular : singular + 's';
return '' + count + ' ' + word;
}
function specHref(result) {
// include window.location.pathname to fix issue with karma-jasmine-html-reporter in angular: see https://github.com/jasmine/jasmine/issues/1906
return (
(window.location.pathname || '') +
addToExistingQueryString('spec', result.fullName)
);
}
function seedHref(seed) {
// include window.location.pathname to fix issue with karma-jasmine-html-reporter in angular: see https://github.com/jasmine/jasmine/issues/1906
return (
(window.location.pathname || '') +
addToExistingQueryString('seed', seed)
);
}
function defaultQueryString(key, value) {
return '?' + key + '=' + value;
}
function setMenuModeTo(mode) {
htmlReporterMain.setAttribute('class', 'jasmine_html-reporter ' + mode);
}
function noExpectations(result) {
const allExpectations =
result.failedExpectations.length + result.passedExpectations.length;
return (
allExpectations === 0 &&
(result.status === 'passed' || result.status === 'failed')
);
}
function hasActiveSpec(resultNode) {
if (resultNode.type == 'spec' && resultNode.result.status != 'excluded') {
return true;
}
if (resultNode.type == 'suite') {
for (let i = 0, j = resultNode.children.length; i < j; i++) {
if (hasActiveSpec(resultNode.children[i])) {
return true;
}
}
}
}
}
return HtmlReporter;
};
jasmineRequire.HtmlSpecFilter = function() {
function HtmlSpecFilter(options) {
const filterString =
options &&
options.filterString() &&
options.filterString().replace(/[-[\]{}()*+?.,\\^$|#\s]/g, '\\$&');
const filterPattern = new RegExp(filterString);
this.matches = function(specName) {
return filterPattern.test(specName);
};
}
return HtmlSpecFilter;
};
jasmineRequire.ResultsNode = function() {
function ResultsNode(result, type, parent) {
this.result = result;
this.type = type;
this.parent = parent;
this.children = [];
this.addChild = function(result, type) {
this.children.push(new ResultsNode(result, type, this));
};
this.last = function() {
return this.children[this.children.length - 1];
};
this.updateResult = function(result) {
this.result = result;
};
}
return ResultsNode;
};
jasmineRequire.QueryString = function() {
function QueryString(options) {
this.navigateWithNewParam = function(key, value) {
options.getWindowLocation().search = this.fullStringWithNewParam(
key,
value
);
};
this.fullStringWithNewParam = function(key, value) {
const paramMap = queryStringToParamMap();
paramMap[key] = value;
return toQueryString(paramMap);
};
this.getParam = function(key) {
return queryStringToParamMap()[key];
};
return this;
function toQueryString(paramMap) {
const qStrPairs = [];
for (const prop in paramMap) {
qStrPairs.push(
encodeURIComponent(prop) + '=' + encodeURIComponent(paramMap[prop])
);
}
return '?' + qStrPairs.join('&');
}
function queryStringToParamMap() {
const paramStr = options.getWindowLocation().search.substring(1);
let params = [];
const paramMap = {};
if (paramStr.length > 0) {
params = paramStr.split('&');
for (let i = 0; i < params.length; i++) {
const p = params[i].split('=');
let value = decodeURIComponent(p[1]);
if (value === 'true' || value === 'false') {
value = JSON.parse(value);
}
paramMap[decodeURIComponent(p[0])] = value;
}
}
return paramMap;
}
}
return QueryString;
};

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"use strict"
const JASMINE_SESSION_ID = `jasmine-${String(Date.now()).slice(8)}`
beforeEach(function () {
jasmine.DEFAULT_TIMEOUT_INTERVAL = 15 * 60 * 1000 // Test timeout after 15 minutes
jasmine.addMatchers({
toBeOneOf: function () {
return {
compare: function (actual, expected) {
return {
pass: expected.includes(actual)
}
}
}
}
})
})
describe('stable-diffusion-ui', function() {
beforeEach(function() {
expect(typeof SD).toBe('object')
expect(typeof SD.serverState).toBe('object')
expect(typeof SD.serverState.status).toBe('string')
})
it('should be able to reach the backend', async function() {
expect(SD.serverState.status).toBe(SD.ServerStates.unavailable)
SD.sessionId = JASMINE_SESSION_ID
await SD.init()
expect(SD.isServerAvailable()).toBeTrue()
})
it('enfore the current task state', function() {
const task = new SD.Task()
expect(task.status).toBe(SD.TaskStatus.init)
expect(task.isPending).toBeTrue()
task._setStatus(SD.TaskStatus.pending)
expect(task.status).toBe(SD.TaskStatus.pending)
expect(task.isPending).toBeTrue()
expect(function() {
task._setStatus(SD.TaskStatus.init)
}).toThrowError()
task._setStatus(SD.TaskStatus.waiting)
expect(task.status).toBe(SD.TaskStatus.waiting)
expect(task.isPending).toBeTrue()
expect(function() {
task._setStatus(SD.TaskStatus.pending)
}).toThrowError()
task._setStatus(SD.TaskStatus.processing)
expect(task.status).toBe(SD.TaskStatus.processing)
expect(task.isPending).toBeTrue()
expect(function() {
task._setStatus(SD.TaskStatus.pending)
}).toThrowError()
task._setStatus(SD.TaskStatus.failed)
expect(task.status).toBe(SD.TaskStatus.failed)
expect(task.isPending).toBeFalse()
expect(function() {
task._setStatus(SD.TaskStatus.processing)
}).toThrowError()
expect(function() {
task._setStatus(SD.TaskStatus.completed)
}).toThrowError()
})
it('should be able to run tasks', async function() {
expect(typeof SD.Task.run).toBe('function')
const promiseGenerator = (function*(val) {
expect(val).toBe('start')
expect(yield 1 + 1).toBe(4)
expect(yield 2 + 2).toBe(8)
yield asyncDelay(500)
expect(yield 3 + 3).toBe(12)
expect(yield 4 + 4).toBe(16)
return 8 + 8
})('start')
const callback = function({value, done}) {
return {value: 2 * value, done}
}
expect(await SD.Task.run(promiseGenerator, {callback})).toBe(32)
})
it('should be able to queue tasks', async function() {
expect(typeof SD.Task.enqueue).toBe('function')
const promiseGenerator = (function*(val) {
expect(val).toBe('start')
expect(yield 1 + 1).toBe(4)
expect(yield 2 + 2).toBe(8)
yield asyncDelay(500)
expect(yield 3 + 3).toBe(12)
expect(yield 4 + 4).toBe(16)
return 8 + 8
})('start')
const callback = function({value, done}) {
return {value: 2 * value, done}
}
const gen = SD.Task.asGenerator({generator: promiseGenerator, callback})
expect(await SD.Task.enqueue(gen)).toBe(32)
})
it('should be able to chain handlers', async function() {
expect(typeof SD.Task.enqueue).toBe('function')
const promiseGenerator = (function*(val) {
expect(val).toBe('start')
expect(yield {test: '1'}).toEqual({test: '1', foo: 'bar'})
expect(yield 2 + 2).toEqual(8)
yield asyncDelay(500)
expect(yield 3 + 3).toEqual(12)
expect(yield {test: 4}).toEqual({test: 8, foo: 'bar'})
return {test: 8}
})('start')
const gen1 = SD.Task.asGenerator({generator: promiseGenerator, callback: function({value, done}) {
if (typeof value === "object") {
value['foo'] = 'bar'
}
return {value, done}
}})
const gen2 = SD.Task.asGenerator({generator: gen1, callback: function({value, done}) {
if (typeof value === 'number') {
value = 2 * value
}
if (typeof value === 'object' && typeof value.test === 'number') {
value.test = 2 * value.test
}
return {value, done}
}})
expect(await SD.Task.enqueue(gen2)).toEqual({test:32, foo: 'bar'})
})
describe('ServiceContainer', function() {
it('should be able to register providers', function() {
const cont = new ServiceContainer(
function foo() {
this.bar = ''
},
function bar() {
return () => 0
},
{ name: 'zero', definition: 0 },
{ name: 'ctx', definition: () => Object.create(null), singleton: true },
{ name: 'test',
definition: (ctx, missing, one, foo) => {
expect(ctx).toEqual({ran: true})
expect(one).toBe(1)
expect(typeof foo).toBe('object')
expect(foo.bar).toBeDefined()
expect(typeof missing).toBe('undefined')
return {foo: 'bar'}
}, dependencies: ['ctx', 'missing', 'one', 'foo']
}
)
const fooObj = cont.get('foo')
expect(typeof fooObj).toBe('object')
fooObj.ran = true
const ctx = cont.get('ctx')
expect(ctx).toEqual({})
ctx.ran = true
const bar = cont.get('bar')
expect(typeof bar).toBe('function')
expect(bar()).toBe(0)
cont.register({name: 'one', definition: 1})
const test = cont.get('test')
expect(typeof test).toBe('object')
expect(test.foo).toBe('bar')
})
})
it('should be able to stream data in chunks', async function() {
expect(SD.isServerAvailable()).toBeTrue()
const nbr_steps = 15
let res = await fetch('/render', {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify({
"prompt": "a photograph of an astronaut riding a horse",
"negative_prompt": "",
"width": 128,
"height": 128,
"seed": Math.floor(Math.random() * 10000000),
"sampler": "plms",
"use_stable_diffusion_model": "sd-v1-4",
"num_inference_steps": nbr_steps,
"guidance_scale": 7.5,
"numOutputsParallel": 1,
"stream_image_progress": true,
"show_only_filtered_image": true,
"output_format": "jpeg",
"session_id": JASMINE_SESSION_ID,
}),
})
expect(res.ok).toBeTruthy()
const renderRequest = await res.json()
expect(typeof renderRequest.stream).toBe('string')
expect(renderRequest.task).toBeDefined()
// Wait for server status to update.
await SD.waitUntil(() => {
console.log('Waiting for %s to be received...', renderRequest.task)
return (!SD.serverState.tasks || SD.serverState.tasks[String(renderRequest.task)])
}, 250, 10 * 60 * 1000)
// Wait for task to start on server.
await SD.waitUntil(() => {
console.log('Waiting for %s to start...', renderRequest.task)
return !SD.serverState.tasks || SD.serverState.tasks[String(renderRequest.task)] !== 'pending'
}, 250)
const reader = new SD.ChunkedStreamReader(renderRequest.stream)
const parseToString = reader.parse
reader.parse = function(value) {
value = parseToString.call(this, value)
if (!value || value.length <= 0) {
return
}
return reader.readStreamAsJSON(value.join(''))
}
reader.onNext = function({done, value}) {
console.log(value)
if (typeof value === 'object' && 'status' in value) {
done = true
}
return {done, value}
}
let lastUpdate = undefined
let stepCount = 0
let complete = false
//for await (const stepUpdate of reader) {
for await (const stepUpdate of reader.open()) {
console.log('ChunkedStreamReader received ', stepUpdate)
lastUpdate = stepUpdate
if (complete) {
expect(stepUpdate.status).toBe('succeeded')
expect(stepUpdate.output).toHaveSize(1)
} else {
expect(stepUpdate.total_steps).toBe(nbr_steps)
expect(stepUpdate.step).toBe(stepCount)
if (stepUpdate.step === stepUpdate.total_steps) {
complete = true
} else {
stepCount++
}
}
}
for(let i=1; i <= 5; ++i) {
res = await fetch(renderRequest.stream)
expect(res.ok).toBeTruthy()
const cachedResponse = await res.json()
console.log('Cache test %s received %o', i, cachedResponse)
expect(lastUpdate).toEqual(cachedResponse)
}
})
describe('should be able to make renders', function() {
beforeEach(function() {
expect(SD.isServerAvailable()).toBeTrue()
})
it('basic inline request', async function() {
let stepCount = 0
let complete = false
const result = await SD.render({
"prompt": "a photograph of an astronaut riding a horse",
"width": 128,
"height": 128,
"num_inference_steps": 10,
"show_only_filtered_image": false,
//"use_face_correction": 'GFPGANv1.3',
"use_upscale": "RealESRGAN_x4plus",
"session_id": JASMINE_SESSION_ID,
}, function(event) {
console.log(this, event)
if ('update' in event) {
const stepUpdate = event.update
if (complete || (stepUpdate.status && stepUpdate.step === stepUpdate.total_steps)) {
expect(stepUpdate.status).toBe('succeeded')
expect(stepUpdate.output).toHaveSize(2)
} else {
expect(stepUpdate.step).toBe(stepCount)
if (stepUpdate.step === stepUpdate.total_steps) {
complete = true
} else {
stepCount++
}
}
}
})
console.log(result)
expect(result.status).toBe('succeeded')
expect(result.output).toHaveSize(2)
})
it('post and reader request', async function() {
const renderTask = new SD.RenderTask({
"prompt": "a photograph of an astronaut riding a horse",
"width": 128,
"height": 128,
"seed": SD.MAX_SEED_VALUE,
"num_inference_steps": 10,
"session_id": JASMINE_SESSION_ID,
})
expect(renderTask.status).toBe(SD.TaskStatus.init)
const timeout = -1
const renderRequest = await renderTask.post(timeout)
expect(typeof renderRequest.stream).toBe('string')
expect(renderTask.status).toBe(SD.TaskStatus.waiting)
expect(renderTask.streamUrl).toBe(renderRequest.stream)
await renderTask.waitUntil({state: SD.TaskStatus.processing, callback: () => console.log('Waiting for render task to start...') })
expect(renderTask.status).toBe(SD.TaskStatus.processing)
let stepCount = 0
let complete = false
//for await (const stepUpdate of renderTask.reader) {
for await (const stepUpdate of renderTask.reader.open()) {
console.log(stepUpdate)
if (complete || (stepUpdate.status && stepUpdate.step === stepUpdate.total_steps)) {
expect(stepUpdate.status).toBe('succeeded')
expect(stepUpdate.output).toHaveSize(1)
} else {
expect(stepUpdate.step).toBe(stepCount)
if (stepUpdate.step === stepUpdate.total_steps) {
complete = true
} else {
stepCount++
}
}
}
expect(renderTask.status).toBe(SD.TaskStatus.completed)
expect(renderTask.result.status).toBe('succeeded')
expect(renderTask.result.output).toHaveSize(1)
})
it('queued request', async function() {
let stepCount = 0
let complete = false
const renderTask = new SD.RenderTask({
"prompt": "a photograph of an astronaut riding a horse",
"width": 128,
"height": 128,
"num_inference_steps": 10,
"show_only_filtered_image": false,
//"use_face_correction": 'GFPGANv1.3',
"use_upscale": "RealESRGAN_x4plus",
"session_id": JASMINE_SESSION_ID,
})
await renderTask.enqueue(function(event) {
console.log(this, event)
if ('update' in event) {
const stepUpdate = event.update
if (complete || (stepUpdate.status && stepUpdate.step === stepUpdate.total_steps)) {
expect(stepUpdate.status).toBe('succeeded')
expect(stepUpdate.output).toHaveSize(2)
} else {
expect(stepUpdate.step).toBe(stepCount)
if (stepUpdate.step === stepUpdate.total_steps) {
complete = true
} else {
stepCount++
}
}
}
})
console.log(renderTask.result)
expect(renderTask.result.status).toBe('succeeded')
expect(renderTask.result.output).toHaveSize(2)
})
})
describe('# Special cases', function() {
it('should throw an exception on set for invalid sessionId', function() {
expect(function() {
SD.sessionId = undefined
}).toThrowError("Can't set sessionId to undefined.")
})
})
})
const loadCompleted = window.onload
let loadEvent = undefined
window.onload = function(evt) {
loadEvent = evt
}
if (!PLUGINS.SELFTEST) {
PLUGINS.SELFTEST = {}
}
loadUIPlugins().then(function() {
console.log('loadCompleted', loadEvent)
describe('@Plugins', function() {
it('exposes hooks to overide', function() {
expect(typeof PLUGINS.IMAGE_INFO_BUTTONS).toBe('object')
expect(typeof PLUGINS.TASK_CREATE).toBe('object')
})
describe('supports selftests', function() { // Hook to allow plugins to define tests.
const pluginsTests = Object.keys(PLUGINS.SELFTEST).filter((key) => PLUGINS.SELFTEST.hasOwnProperty(key))
if (!pluginsTests || pluginsTests.length <= 0) {
it('but nothing loaded...', function() {
expect(true).toBeTruthy()
})
return
}
for (const pTest of pluginsTests) {
describe(pTest, function() {
const testFn = PLUGINS.SELFTEST[pTest]
return Promise.resolve(testFn.call(jasmine, pTest))
})
}
})
})
loadCompleted.call(window, loadEvent)
})

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(function () {
"use strict"
var styleSheet = document.createElement("style");
styleSheet.textContent = `
.modifier-card-tiny.modifier-toggle-inactive {
background: transparent;
border: 2px dashed red;
opacity:0.2;
}
`;
document.head.appendChild(styleSheet);
// observe for changes in tag list
var observer = new MutationObserver(function (mutations) {
// mutations.forEach(function (mutation) {
if (editorModifierTagsList.childNodes.length > 0) {
ModifierToggle()
}
// })
})
observer.observe(editorModifierTagsList, {
childList: true
})
function ModifierToggle() {
let overlays = document.querySelector('#editor-inputs-tags-list').querySelectorAll('.modifier-card-overlay')
overlays.forEach (i => {
i.oncontextmenu = (e) => {
e.preventDefault()
if (i.parentElement.classList.contains('modifier-toggle-inactive')) {
i.parentElement.classList.remove('modifier-toggle-inactive')
}
else
{
i.parentElement.classList.add('modifier-toggle-inactive')
}
// refresh activeTags
let modifierName = i.parentElement.getElementsByClassName('modifier-card-label')[0].getElementsByTagName("p")[0].innerText
activeTags = activeTags.map(obj => {
if (obj.name === modifierName) {
return {...obj, inactive: (obj.element.classList.contains('modifier-toggle-inactive'))};
}
return obj;
});
console.log(activeTags)
}
})
}
})()

View File

@ -1,64 +0,0 @@
(function() {
// Register selftests when loaded by jasmine.
if (typeof PLUGINS?.SELFTEST === 'object') {
PLUGINS.SELFTEST["release-notes"] = function() {
it('should be able to fetch CHANGES.md', async function() {
let releaseNotes = await fetch(`https://raw.githubusercontent.com/cmdr2/stable-diffusion-ui/main/CHANGES.md`)
expect(releaseNotes.status).toBe(200)
})
}
}
document.querySelector('#tab-container')?.insertAdjacentHTML('beforeend', `
<span id="tab-news" class="tab">
<span><i class="fa fa-bolt icon"></i> What's new?</span>
</span>
`)
document.querySelector('#tab-content-wrapper')?.insertAdjacentHTML('beforeend', `
<div id="tab-content-news" class="tab-content">
<div id="news" class="tab-content-inner">
Loading..
</div>
</div>
`)
const tabNews = document.querySelector('#tab-news')
if (tabNews) {
linkTabContents(tabNews)
}
const news = document.querySelector('#news')
if (!news) {
// news tab not found, dont exec plugin code.
return
}
document.querySelector('body').insertAdjacentHTML('beforeend', `
<style>
#tab-content-news .tab-content-inner {
max-width: 100%;
text-align: left;
padding: 10pt;
}
</style>
`)
loadScript('/media/js/marked.min.js').then(async function() {
let appConfig = await fetch('/get/app_config')
if (!appConfig.ok) {
console.error('[release-notes] Failed to get app_config.')
return
}
appConfig = await appConfig.json()
const updateBranch = appConfig.update_branch || 'main'
let releaseNotes = await fetch(`https://raw.githubusercontent.com/cmdr2/stable-diffusion-ui/${updateBranch}/CHANGES.md`)
if (!releaseNotes.ok) {
console.error('[release-notes] Failed to get CHANGES.md.')
return
}
releaseNotes = await releaseNotes.text()
news.innerHTML = marked.parse(releaseNotes)
})
})()

View File

@ -1,25 +0,0 @@
/* SD-UI Selftest Plugin.js
*/
(function() { "use strict"
const ID_PREFIX = "selftest-plugin"
const links = document.getElementById("community-links")
if (!links) {
console.error('%s the ID "community-links" cannot be found.', ID_PREFIX)
return
}
// Add link to Jasmine SpecRunner
const pluginLink = document.createElement('li')
const options = {
'stopSpecOnExpectationFailure': "true",
'stopOnSpecFailure': 'false',
'random': 'false',
'hideDisabled': 'false'
}
const optStr = Object.entries(options).map(([key, val]) => `${key}=${val}`).join('&')
pluginLink.innerHTML = `<a id="${ID_PREFIX}-starttest" href="${location.protocol}/plugins/core/SpecRunner.html?${optStr}" target="_blank"><i class="fa-solid fa-vial-circle-check"></i> Start SelfTest</a>`
links.appendChild(pluginLink)
console.log('%s loaded!', ID_PREFIX)
})()

View File

@ -1,7 +1,6 @@
import json
class Request:
request_id: str = None
session_id: str = "session"
prompt: str = ""
negative_prompt: str = ""
@ -19,16 +18,12 @@ class Request:
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"
use_stable_diffusion_model: str = "sd-v1-4"
use_vae_model: str = None
use_hypernetwork_model: str = None
hypernetwork_strength: float = 1
show_only_filtered_image: bool = False
output_format: str = "jpeg" # or "png"
output_quality: int = 75
output_format: str = "jpeg" # "png", "jpeg"
stream_progress_updates: bool = False
stream_image_progress: bool = False
@ -41,7 +36,6 @@ class Request:
"num_outputs": self.num_outputs,
"num_inference_steps": self.num_inference_steps,
"guidance_scale": self.guidance_scale,
"hypernetwork_strengtgh": self.guidance_scale,
"width": self.width,
"height": self.height,
"seed": self.seed,
@ -49,15 +43,10 @@ class Request:
"sampler": self.sampler,
"use_face_correction": self.use_face_correction,
"use_upscale": self.use_upscale,
"use_stable_diffusion_model": self.use_stable_diffusion_model,
"use_vae_model": self.use_vae_model,
"use_hypernetwork_model": self.use_hypernetwork_model,
"hypernetwork_strength": self.hypernetwork_strength,
"output_format": self.output_format,
"output_quality": self.output_quality,
}
def __str__(self):
def to_string(self):
return f'''
session_id: {self.session_id}
prompt: {self.prompt}
@ -71,16 +60,12 @@ class Request:
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}
use_stable_diffusion_model: {self.use_stable_diffusion_model}
use_vae_model: {self.use_vae_model}
use_hypernetwork_model: {self.use_hypernetwork_model}
hypernetwork_strength: {self.hypernetwork_strength}
show_only_filtered_image: {self.show_only_filtered_image}
output_format: {self.output_format}
output_quality: {self.output_quality}
stream_progress_updates: {self.stream_progress_updates}
stream_image_progress: {self.stream_image_progress}'''

View File

@ -0,0 +1,46 @@
diff --git a/ldm/dream/conditioning.py b/ldm/dream/conditioning.py
index dfa1089..e4908ad 100644
--- a/ldm/dream/conditioning.py
+++ b/ldm/dream/conditioning.py
@@ -12,8 +12,8 @@ log_tokenization() print out colour-coded tokens and warn if trunca
import re
import torch
-def get_uc_and_c(prompt, model, log_tokens=False, skip_normalize=False):
- uc = model.get_learned_conditioning([''])
+def get_uc_and_c(prompt, model, log_tokens=False, skip_normalize=False, negative_prompt=''):
+ uc = model.get_learned_conditioning([negative_prompt])
# get weighted sub-prompts
weighted_subprompts = split_weighted_subprompts(
diff --git a/ldm/generate.py b/ldm/generate.py
index 8f67403..d88ce2d 100644
--- a/ldm/generate.py
+++ b/ldm/generate.py
@@ -205,6 +205,7 @@ class Generate:
init_mask = None,
fit = False,
strength = None,
+ init_img_is_path = True,
# these are specific to GFPGAN/ESRGAN
gfpgan_strength= 0,
save_original = False,
@@ -303,11 +304,15 @@ class Generate:
uc, c = get_uc_and_c(
prompt, model=self.model,
skip_normalize=skip_normalize,
- log_tokens=self.log_tokenization
+ log_tokens=self.log_tokenization,
+ negative_prompt=(args['negative_prompt'] if 'negative_prompt' in args else '')
)
- (init_image,mask_image) = self._make_images(init_img,init_mask, width, height, fit)
-
+ if init_img_is_path:
+ (init_image,mask_image) = self._make_images(init_img,init_mask, width, height, fit)
+ else:
+ (init_image,mask_image) = (init_img, init_mask)
+
if (init_image is not None) and (mask_image is not None):
generator = self._make_inpaint()
elif init_image is not None:

View File

@ -1,13 +1,72 @@
diff --git a/optimizedSD/ddpm.py b/optimizedSD/ddpm.py
index 79058bc..a473411 100644
index b967b55..35ef520 100644
--- a/optimizedSD/ddpm.py
+++ b/optimizedSD/ddpm.py
@@ -564,12 +564,12 @@ class UNet(DDPM):
unconditional_guidance_scale=unconditional_guidance_scale,
callback=callback, img_callback=img_callback)
@@ -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
+ yield from samples
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")
@ -17,7 +76,7 @@ index 79058bc..a473411 100644
@torch.no_grad()
def plms_sampling(self, cond,b, img,
ddim_use_original_steps=False,
@@ -608,10 +608,10 @@ class UNet(DDPM):
@@ -599,10 +608,10 @@ class UNet(DDPM):
old_eps.append(e_t)
if len(old_eps) >= 4:
old_eps.pop(0)
@ -31,15 +90,23 @@ index 79058bc..a473411 100644
@torch.no_grad()
def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
@@ -740,13 +740,13 @@ class UNet(DDPM):
@@ -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: callback(i)
- if img_callback: img_callback(x_dec, i)
+ 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
@ -49,114 +116,217 @@ index 79058bc..a473411 100644
@torch.no_grad()
@@ -820,12 +820,12 @@ class UNet(DDPM):
@@ -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: callback(i)
- if img_callback: img_callback(x, i)
+ if callback: yield from callback(i)
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, img_callback=None):
@@ -852,14 +852,14 @@ class UNet(DDPM):
denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
- 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: callback(i)
- if img_callback: img_callback(x, i)
+ if callback: yield from callback(i)
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)
@@ -892,8 +892,8 @@ class UNet(DDPM):
denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
@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: callback(i)
- if img_callback: img_callback(x, i)
+ if callback: yield from callback(i)
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
@@ -913,7 +913,7 @@ class UNet(DDPM):
@@ -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()
@@ -944,8 +944,8 @@ class UNet(DDPM):
- 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 callback: callback(i)
- if img_callback: img_callback(x, i)
+ if callback: yield from callback(i)
-
+ 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
@@ -966,7 +966,7 @@ class UNet(DDPM):
@@ -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()
@@ -994,8 +994,8 @@ class UNet(DDPM):
- 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: callback(i)
- if img_callback: img_callback(x, i)
+ if callback: yield from callback(i)
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
@@ -1016,7 +1016,7 @@ class UNet(DDPM):
@@ -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()
@@ -1042,8 +1042,8 @@ class UNet(DDPM):
- 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 callback: callback(i)
- if img_callback: img_callback(x, i)
+ if callback: yield from callback(i)
+ if img_callback: yield from img_callback(x, i)
d = to_d(x, sigmas[i], denoised)
ds.append(d)
@@ -1054,4 +1054,4 @@ class UNet(DDPM):
@@ -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):

View File

@ -1,84 +0,0 @@
diff --git a/ldm/models/diffusion/ddim.py b/ldm/models/diffusion/ddim.py
index 27ead0e..6215939 100644
--- a/ldm/models/diffusion/ddim.py
+++ b/ldm/models/diffusion/ddim.py
@@ -100,7 +100,7 @@ class DDIMSampler(object):
size = (batch_size, C, H, W)
print(f'Data shape for DDIM sampling is {size}, eta {eta}')
- samples, intermediates = self.ddim_sampling(conditioning, size,
+ samples = self.ddim_sampling(conditioning, size,
callback=callback,
img_callback=img_callback,
quantize_denoised=quantize_x0,
@@ -117,7 +117,8 @@ class DDIMSampler(object):
dynamic_threshold=dynamic_threshold,
ucg_schedule=ucg_schedule
)
- return samples, intermediates
+ # return samples, intermediates
+ yield from samples
@torch.no_grad()
def ddim_sampling(self, cond, shape,
@@ -168,14 +169,15 @@ class DDIMSampler(object):
unconditional_conditioning=unconditional_conditioning,
dynamic_threshold=dynamic_threshold)
img, pred_x0 = outs
- 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)
if index % log_every_t == 0 or index == total_steps - 1:
intermediates['x_inter'].append(img)
intermediates['pred_x0'].append(pred_x0)
- return img, intermediates
+ # return img, intermediates
+ yield from img_callback(pred_x0, len(iterator)-1)
@torch.no_grad()
def p_sample_ddim(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
diff --git a/ldm/models/diffusion/plms.py b/ldm/models/diffusion/plms.py
index 7002a36..0951f39 100644
--- a/ldm/models/diffusion/plms.py
+++ b/ldm/models/diffusion/plms.py
@@ -96,7 +96,7 @@ class PLMSSampler(object):
size = (batch_size, C, H, W)
print(f'Data shape for PLMS sampling is {size}')
- samples, intermediates = self.plms_sampling(conditioning, size,
+ samples = self.plms_sampling(conditioning, size,
callback=callback,
img_callback=img_callback,
quantize_denoised=quantize_x0,
@@ -112,7 +112,8 @@ class PLMSSampler(object):
unconditional_conditioning=unconditional_conditioning,
dynamic_threshold=dynamic_threshold,
)
- return samples, intermediates
+ #return samples, intermediates
+ yield from samples
@torch.no_grad()
def plms_sampling(self, cond, shape,
@@ -165,14 +166,15 @@ class PLMSSampler(object):
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)
if index % log_every_t == 0 or index == total_steps - 1:
intermediates['x_inter'].append(img)
intermediates['pred_x0'].append(pred_x0)
- return img, intermediates
+ # return img, intermediates
+ yield from img_callback(pred_x0, 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,

View File

@ -1,168 +0,0 @@
import os
import torch
import traceback
import re
COMPARABLE_GPU_PERCENTILE = 0.65 # if a GPU's free_mem is within this % of the GPU with the most free_mem, it will be picked
mem_free_threshold = 0
def get_device_delta(render_devices, active_devices):
'''
render_devices: 'cpu', or 'auto' or ['cuda:N'...]
active_devices: ['cpu', 'cuda:N'...]
'''
if render_devices in ('cpu', 'auto'):
render_devices = [render_devices]
elif render_devices is not None:
if isinstance(render_devices, str):
render_devices = [render_devices]
if isinstance(render_devices, list) and len(render_devices) > 0:
render_devices = list(filter(lambda x: x.startswith('cuda:'), render_devices))
if len(render_devices) == 0:
raise Exception('Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "auto"}')
render_devices = list(filter(lambda x: is_device_compatible(x), render_devices))
if len(render_devices) == 0:
raise Exception('Sorry, none of the render_devices configured in config.json are compatible with Stable Diffusion')
else:
raise Exception('Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "auto"}')
else:
render_devices = ['auto']
if 'auto' in render_devices:
render_devices = auto_pick_devices(active_devices)
if 'cpu' in render_devices:
print('WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!')
active_devices = set(active_devices)
render_devices = set(render_devices)
devices_to_start = render_devices - active_devices
devices_to_stop = active_devices - render_devices
return devices_to_start, devices_to_stop
def auto_pick_devices(currently_active_devices):
global mem_free_threshold
if not torch.cuda.is_available(): return ['cpu']
device_count = torch.cuda.device_count()
if device_count == 1:
return ['cuda:0'] if is_device_compatible('cuda:0') else ['cpu']
print('Autoselecting GPU. Using most free memory.')
devices = []
for device in range(device_count):
device = f'cuda:{device}'
if not is_device_compatible(device):
continue
mem_free, mem_total = torch.cuda.mem_get_info(device)
mem_free /= float(10**9)
mem_total /= float(10**9)
device_name = torch.cuda.get_device_name(device)
print(f'{device} detected: {device_name} - Memory (free/total): {round(mem_free, 2)}Gb / {round(mem_total, 2)}Gb')
devices.append({'device': device, 'device_name': device_name, 'mem_free': mem_free})
devices.sort(key=lambda x:x['mem_free'], reverse=True)
max_mem_free = devices[0]['mem_free']
curr_mem_free_threshold = COMPARABLE_GPU_PERCENTILE * max_mem_free
mem_free_threshold = max(curr_mem_free_threshold, mem_free_threshold)
# Auto-pick algorithm:
# 1. Pick the top 75 percentile of the GPUs, sorted by free_mem.
# 2. Also include already-running devices (GPU-only), otherwise their free_mem will
# always be very low (since their VRAM contains the model).
# These already-running devices probably aren't terrible, since they were picked in the past.
# Worst case, the user can restart the program and that'll get rid of them.
devices = list(filter((lambda x: x['mem_free'] > mem_free_threshold or x['device'] in currently_active_devices), devices))
devices = list(map(lambda x: x['device'], devices))
return devices
def device_init(thread_data, device):
'''
This function assumes the 'device' has already been verified to be compatible.
`get_device_delta()` has already filtered out incompatible devices.
'''
validate_device_id(device, log_prefix='device_init')
if device == 'cpu':
thread_data.device = 'cpu'
thread_data.device_name = get_processor_name()
print('Render device CPU available as', thread_data.device_name)
return
thread_data.device_name = torch.cuda.get_device_name(device)
thread_data.device = device
# Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
device_name = thread_data.device_name.lower()
thread_data.force_full_precision = (('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)) or ('Quadro T2000' in device_name)
if thread_data.force_full_precision:
print('forcing full precision on NVIDIA 16xx cards, to avoid green images. GPU detected: ', thread_data.device_name)
# Apply force_full_precision now before models are loaded.
thread_data.precision = 'full'
print(f'Setting {device} as active')
torch.cuda.device(device)
return
def validate_device_id(device, log_prefix=''):
def is_valid():
if not isinstance(device, str):
return False
if device == 'cpu':
return True
if not device.startswith('cuda:') or not device[5:].isnumeric():
return False
return True
if not is_valid():
raise EnvironmentError(f"{log_prefix}: device id should be 'cpu', or 'cuda:N' (where N is an integer index for the GPU). Got: {device}")
def is_device_compatible(device):
'''
Returns True/False, and prints any compatibility errors
'''
try:
validate_device_id(device, log_prefix='is_device_compatible')
except:
print(str(e))
return False
if device == 'cpu': return True
# Memory check
try:
_, mem_total = torch.cuda.mem_get_info(device)
mem_total /= float(10**9)
if mem_total < 3.0:
print(f'GPU {device} with less than 3 GB of VRAM is not compatible with Stable Diffusion')
return False
except RuntimeError as e:
print(str(e))
return False
return True
def get_processor_name():
try:
import platform, subprocess
if platform.system() == "Windows":
return platform.processor()
elif platform.system() == "Darwin":
os.environ['PATH'] = os.environ['PATH'] + os.pathsep + '/usr/sbin'
command = "sysctl -n machdep.cpu.brand_string"
return subprocess.check_output(command).strip()
elif platform.system() == "Linux":
command = "cat /proc/cpuinfo"
all_info = subprocess.check_output(command, shell=True).decode().strip()
for line in all_info.split("\n"):
if "model name" in line:
return re.sub(".*model name.*:", "", line, 1).strip()
except:
print(traceback.format_exc())
return "cpu"

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