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645b596eb0 Revert "Frontend of the batch merger" 2023-01-25 19:45:52 +05:30
86 changed files with 14820 additions and 19308 deletions

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.gitignore vendored
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@ -3,4 +3,3 @@ installer
installer.tar
dist
.idea/*
node_modules/*

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@ -1,9 +0,0 @@
*.min.*
*.py
*.json
*.html
/*
!/ui
/ui/easydiffusion
!/ui/plugins
!/ui/media

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@ -1,7 +0,0 @@
{
"printWidth": 120,
"tabWidth": 4,
"semi": false,
"arrowParens": "always",
"trailingComma": "es5"
}

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@ -4,711 +4,24 @@ 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.
The MIT License (MIT)
Copyright (c) 2019 Boniface Pereira
jszip
=====
https://stuk.github.io/jszip/
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:
JSZip is dual licensed. At your choice you may use it under the MIT license *or* the GPLv3
license.
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
The MIT License
===============
Copyright (c) 2009-2016 Stuart Knightley, David Duponchel, Franz Buchinger, António Afonso
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GPL version 3
=============
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USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
SUCH DAMAGES.
17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided
above cannot be given local legal effect according to their terms,
reviewing courts shall apply local law that most closely approximates
an absolute waiver of all civil liability in connection with the
Program, unless a warranty or assumption of liability accompanies a
copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
FileSaver.js
============
https://github.com/eligrey/FileSaver.js
FileSaver.js is licensed under the MIT license:
The MIT License
Copyright © 2016 [Eli Grey][1].
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.
[1]: http://eligrey.com
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.

View File

@ -2,102 +2,23 @@
## v2.5
### Major Changes
- **Nearly twice as fast** - significantly faster speed of image generation. Code contributions are welcome to make our project even faster: https://github.com/easydiffusion/sdkit/#is-it-fast
- **Mac M1/M2 support** - Experimental support for Mac M1/M2. Thanks @michaelgallacher, @JeLuf and vishae.
- **AMD support for Linux** - Experimental support for AMD GPUs on Linux. Thanks @DianaNites and @JeLuf.
- **Nearly twice as fast** - significantly faster speed of image generation. We're now pretty close to automatic1111's speed. Code contributions are welcome to make our project even faster: https://github.com/easydiffusion/sdkit/#is-it-fast
- **Full support for Stable Diffusion 2.1 (including CPU)** - supports loading v1.4 or v2.0 or v2.1 models seamlessly. No need to enable "Test SD2", and no need to add `sd2_` to your SD 2.0 model file names. Works on CPU as well.
- **Memory optimized Stable Diffusion 2.1** - you can now use Stable Diffusion 2.1 models, with the same low VRAM optimizations that we've always had for SD 1.4. Please note, the SD 2.0 and 2.1 models require more GPU and System RAM, as compared to the SD 1.4 and 1.5 models.
- **11 new samplers!** - explore the new samplers, some of which can generate great images in less than 10 inference steps! We've added the Karras and UniPC samplers. Thanks @Schorny for the UniPC samplers.
- **Model Merging** - You can now merge two models (`.ckpt` or `.safetensors`) and output `.ckpt` or `.safetensors` models, optionally in `fp16` precision. Details: https://github.com/cmdr2/stable-diffusion-ui/wiki/Model-Merging . Thanks @JeLuf.
- **Memory optimized Stable Diffusion 2.1** - you can now use 768x768 models for SD 2.1, with the same low VRAM optimizations that we've always had for SD 1.4. Please note, 4 GB graphics cards can still only support images upto 512x512 resolution.
- **6 new samplers!** - explore the new samplers, some of which can generate great images in less than 10 inference steps!
- **Model Merging** - You can now merge two models (`.ckpt` or `.safetensors`) and output `.ckpt` or `.safetensors` models, optionally in `fp16` precision. Details: https://github.com/cmdr2/stable-diffusion-ui/wiki/Model-Merging
- **Fast loading/unloading of VAEs** - No longer needs to reload the entire Stable Diffusion model, each time you change the VAE
- **Database of known models** - automatically picks the right configuration for known models. E.g. we automatically detect and apply "v" parameterization (required for some SD 2.0 models), and "fp32" attention precision (required for some SD 2.1 models).
- **Color correction for img2img** - an option to preserve the color profile (histogram) of the initial image. This is especially useful if you're getting red-tinted images after inpainting/masking.
- **Three GPU Memory Usage Settings** - `High` (fastest, maximum VRAM usage), `Balanced` (default - almost as fast, significantly lower VRAM usage), `Low` (slowest, very low VRAM usage). The `Low` setting is applied automatically for GPUs with less than 4 GB of VRAM.
- **Find models in sub-folders** - This allows you to organize your models into sub-folders inside `models/stable-diffusion`, instead of keeping them all in a single folder. Thanks @patriceac and @ogmaresca.
- **Custom Modifier Categories** - Ability to create custom modifiers with thumbnails, and custom categories (and hierarchy of categories). Details: https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Modifiers . Thanks @ogmaresca.
- **Embed metadata, or save as TXT/JSON** - You can now embed the metadata directly into the images, or save them as text or json files (choose in the Settings tab). Thanks @patriceac.
- **Find models in sub-folders** - This allows you to organize your models into sub-folders inside `models/stable-diffusion`, instead of keeping them all in a single folder.
- **Save metadata as JSON** - You can now save the metadata files as either text or json files (choose in the Settings tab).
- **Major rewrite of the code** - Most of the codebase has been reorganized and rewritten, to make it more manageable and easier for new developers to contribute features. We've separated our core engine into a new project called `sdkit`, which allows anyone to easily integrate Stable Diffusion (and related modules like GFPGAN etc) into their programming projects (via a simple `pip install sdkit`): https://github.com/easydiffusion/sdkit/
- **Name change** - Last, and probably the least, the UI is now called "Easy Diffusion". It indicates the focus of this project - an easy way for people to play with Stable Diffusion.
Our focus continues to remain on an easy installation experience, and an easy user-interface. While still remaining pretty powerful, in terms of features and speed.
### Detailed changelog
* 2.5.41 - 24 Jun 2023 - (beta-only) Fix broken inpainting in low VRAM usage mode.
* 2.5.41 - 24 Jun 2023 - (beta-only) Fix a recent regression where the LoRA would not get applied when changing SD models.
* 2.5.41 - 23 Jun 2023 - Fix a regression where latent upscaler stopped working on PCs without a graphics card.
* 2.5.41 - 20 Jun 2023 - Automatically fix black images if fp32 attention precision is required in diffusers.
* 2.5.41 - 19 Jun 2023 - Another fix for multi-gpu rendering (in all VRAM usage modes).
* 2.5.41 - 13 Jun 2023 - Fix multi-gpu bug with "low" VRAM usage mode while generating images.
* 2.5.41 - 12 Jun 2023 - Fix multi-gpu bug with CodeFormer.
* 2.5.41 - 6 Jun 2023 - Allow changing the strength of CodeFormer, and slightly improved styling of the CodeFormer options.
* 2.5.41 - 5 Jun 2023 - Allow sharing an Easy Diffusion instance via https://try.cloudflare.com/ . You can find this option at the bottom of the Settings tab. Thanks @JeLuf.
* 2.5.41 - 5 Jun 2023 - Show an option to download for tiled images. Shows a button on the generated image. Creates larger images by tiling them with the image generated by Easy Diffusion. Thanks @JeLuf.
* 2.5.41 - 5 Jun 2023 - (beta-only) Allow LoRA strengths between -2 and 2. Thanks @ogmaresca.
* 2.5.40 - 5 Jun 2023 - Reduce the VRAM usage of Latent Upscaling when using "balanced" VRAM usage mode.
* 2.5.40 - 5 Jun 2023 - Fix the "realesrgan" key error when using CodeFormer with more than 1 image in a batch.
* 2.5.40 - 3 Jun 2023 - Added CodeFormer as another option for fixing faces and eyes. CodeFormer tends to perform better than GFPGAN for many images. Thanks @patriceac for the implementation, and for contacting the CodeFormer team (who were supportive of it being integrated into Easy Diffusion).
* 2.5.39 - 25 May 2023 - (beta-only) Seamless Tiling - make seamlessly tiled images, e.g. rock and grass textures. Thanks @JeLuf.
* 2.5.38 - 24 May 2023 - Better reporting of errors, and show an explanation if the user cannot disable the "Use CPU" setting.
* 2.5.38 - 23 May 2023 - Add Latent Upscaler as another option for upscaling images. Thanks @JeLuf for the implementation of the Latent Upscaler model.
* 2.5.37 - 19 May 2023 - (beta-only) Two more samplers: DDPM and DEIS. Also disables the samplers that aren't working yet in the Diffusers version. Thanks @ogmaresca.
* 2.5.37 - 19 May 2023 - (beta-only) Support CLIP-Skip. You can set this option under the models dropdown. Thanks @JeLuf.
* 2.5.37 - 19 May 2023 - (beta-only) More VRAM optimizations for all modes in diffusers. The VRAM usage for diffusers in "low" and "balanced" should now be equal or less than the non-diffusers version. Performs softmax in half precision, like sdkit does.
* 2.5.36 - 16 May 2023 - (beta-only) More VRAM optimizations for "balanced" VRAM usage mode.
* 2.5.36 - 11 May 2023 - (beta-only) More VRAM optimizations for "low" VRAM usage mode.
* 2.5.36 - 10 May 2023 - (beta-only) Bug fix for "meta" error when using a LoRA in 'low' VRAM usage mode.
* 2.5.35 - 8 May 2023 - Allow dragging a zoomed-in image (after opening an image with the "expand" button). Thanks @ogmaresca.
* 2.5.35 - 3 May 2023 - (beta-only) First round of VRAM Optimizations for the "Test Diffusers" version. This change significantly reduces the amount of VRAM used by the diffusers version during image generation. The VRAM usage is still not equal to the "non-diffusers" version, but more optimizations are coming soon.
* 2.5.34 - 22 Apr 2023 - Don't start the browser in an incognito new profile (on Windows). Thanks @JeLuf.
* 2.5.33 - 21 Apr 2023 - Install PyTorch 2.0 on new installations (on Windows and Linux).
* 2.5.32 - 19 Apr 2023 - Automatically check for black images, and set full-precision if necessary (for attn). This means custom models based on Stable Diffusion v2.1 will just work, without needing special command-line arguments or editing of yaml config files.
* 2.5.32 - 18 Apr 2023 - Automatic support for AMD graphics cards on Linux. Thanks @DianaNites and @JeLuf.
* 2.5.31 - 10 Apr 2023 - Reduce VRAM usage while upscaling.
* 2.5.31 - 6 Apr 2023 - Allow seeds upto `4,294,967,295`. Thanks @ogmaresca.
* 2.5.31 - 6 Apr 2023 - Buttons to show the previous/next image in the image popup. Thanks @ogmaresca.
* 2.5.30 - 5 Apr 2023 - Fix a bug where the JPEG image quality wasn't being respected when embedding the metadata into it. Thanks @JeLuf.
* 2.5.30 - 1 Apr 2023 - (beta-only) Slider to control the strength of the LoRA model.
* 2.5.30 - 28 Mar 2023 - Refactor task entry config to use a generating method. Added ability for plugins to easily add to this. Removed confusing sentence from `contributing.md`
* 2.5.30 - 28 Mar 2023 - Allow the user to undo the deletion of tasks or images, instead of showing a pop-up each time. The new `Undo` button will be present at the top of the UI. Thanks @JeLuf.
* 2.5.30 - 28 Mar 2023 - Support saving lossless WEBP images. Thanks @ogmaresca.
* 2.5.30 - 28 Mar 2023 - Lots of bug fixes for the UI (Read LoRA flag in metadata files, new prompt weight format with scrollwheel, fix overflow with lots of tabs, clear button in image editor, shorter filenames in download). Thanks @patriceac, @JeLuf and @ogmaresca.
* 2.5.29 - 27 Mar 2023 - (beta-only) Fix a bug where some non-square images would fail while inpainting with a `The size of tensor a must match size of tensor b` error.
* 2.5.29 - 27 Mar 2023 - (beta-only) Fix the `incorrect number of channels` error, when given a PNG image with an alpha channel in `Test Diffusers`.
* 2.5.29 - 27 Mar 2023 - (beta-only) Fix broken inpainting in `Test Diffusers`.
* 2.5.28 - 24 Mar 2023 - (beta-only) Support for weighted prompts and long prompt lengths (not limited to 77 tokens). This change requires enabling the `Test Diffusers` setting in beta (in the Settings tab), and restarting the program.
* 2.5.27 - 21 Mar 2023 - (beta-only) LoRA support, accessible by enabling the `Test Diffusers` setting (in the Settings tab in the UI). This change switches the internal engine to diffusers (if the `Test Diffusers` setting is enabled). If the `Test Diffusers` flag is disabled, it'll have no impact for the user.
* 2.5.26 - 15 Mar 2023 - Allow styling the buttons displayed on an image. Update the API to allow multiple buttons and text labels in a single row. Thanks @ogmaresca.
* 2.5.26 - 15 Mar 2023 - View images in full-screen, by either clicking on the image, or clicking the "Full screen" icon next to the Seed number on the image. Thanks @ogmaresca for the internal API.
* 2.5.25 - 14 Mar 2023 - Button to download all the images, and all the metadata as a zip file. This is available at the top of the UI, as well as on each image. Thanks @JeLuf.
* 2.5.25 - 14 Mar 2023 - Lots of UI tweaks and bug fixes. Thanks @patriceac and @JeLuf.
* 2.5.24 - 11 Mar 2023 - Button to load an image mask from a file.
* 2.5.24 - 10 Mar 2023 - Logo change. Image credit: @lazlo_vii.
* 2.5.23 - 8 Mar 2023 - Experimental support for Mac M1/M2. Thanks @michaelgallacher, @JeLuf and vishae!
* 2.5.23 - 8 Mar 2023 - Ability to create custom modifiers with thumbnails, and custom categories (and hierarchy of categories). More details - https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Modifiers . Thanks @ogmaresca.
* 2.5.22 - 28 Feb 2023 - Minor styling changes to UI buttons, and the models dropdown.
* 2.5.22 - 28 Feb 2023 - Lots of UI-related bug fixes. Thanks @patriceac.
* 2.5.21 - 22 Feb 2023 - An option to control the size of the image thumbnails. You can use the `Display options` in the top-right corner to change this. Thanks @JeLuf.
* 2.5.20 - 20 Feb 2023 - Support saving images in WEBP format (which consumes less disk space, with similar quality). Thanks @ogmaresca.
* 2.5.20 - 18 Feb 2023 - A setting to block NSFW images from being generated. You can enable this setting in the Settings tab.
* 2.5.19 - 17 Feb 2023 - Initial support for server-side plugins. Currently supports overriding the `get_cond_and_uncond()` function.
* 2.5.18 - 17 Feb 2023 - 5 new samplers! UniPC samplers, some of which produce images in less than 15 steps. Thanks @Schorny.
* 2.5.16 - 13 Feb 2023 - Searchable dropdown for models. This is useful if you have a LOT of models. You can type part of the model name, to auto-search through your models. Thanks @patriceac for the feature, and @AssassinJN for help in UI tweaks!
* 2.5.16 - 13 Feb 2023 - Lots of fixes and improvements to the installer. First round of changes to add Mac support. Thanks @JeLuf.
* 2.5.16 - 13 Feb 2023 - UI bug fixes for the inpainter editor. Thanks @patriceac.
* 2.5.16 - 13 Feb 2023 - Fix broken task reorder. Thanks @JeLuf.
* 2.5.16 - 13 Feb 2023 - Remove a task if all the images inside it have been removed. Thanks @AssassinJN.
* 2.5.16 - 10 Feb 2023 - Embed metadata into the JPG/PNG images, if selected in the "Settings" tab (under "Metadata format"). Thanks @patriceac.
* 2.5.16 - 10 Feb 2023 - Sort models alphabetically in the models dropdown. Thanks @ogmaresca.
* 2.5.16 - 10 Feb 2023 - Support multiple GFPGAN models. Download new GFPGAN models into the `models/gfpgan` folder, and refresh the UI to use it. Thanks @JeLuf.
* 2.5.16 - 10 Feb 2023 - Allow a server to enforce a fixed directory path to save images. This is useful if the server is exposed to a lot of users. This can be set in the `config.json` file as `force_save_path: "/path/to/fixed/save/dir"`. E.g. `force_save_path: "D:/user_images"`. Thanks @JeLuf.
* 2.5.16 - 10 Feb 2023 - The "Make Images" button now shows the correct amount of images it'll create when using operators like `{}` or `|`. For e.g. if the prompt is `Photo of a {woman, man}`, then the button will say `Make 2 Images`. Thanks @JeLuf.
* 2.5.16 - 10 Feb 2023 - A bunch of UI-related bug fixes. Thanks @patriceac.
* 2.5.15 - 8 Feb 2023 - Allow using 'balanced' VRAM usage mode on GPUs with 4 GB or less of VRAM. This mode used to be called 'Turbo' in the previous version.
* 2.5.14 - 8 Feb 2023 - Fix broken auto-save settings. We renamed `sampler` to `sampler_name`, which caused old settings to fail.
* 2.5.14 - 6 Feb 2023 - Simplify the UI for merging models, and some other minor UI tweaks. Better error reporting if a model failed to load.
* 2.5.14 - 3 Feb 2023 - Fix the 'Make Similar Images' button, which was producing incorrect images (weren't very similar).
* 2.5.13 - 1 Feb 2023 - Fix the remaining GPU memory leaks, including a better fix (more comprehensive) for the change in 2.5.12 (27 Jan).
* 2.5.12 - 27 Jan 2023 - Fix a memory leak, which made the UI unresponsive after an out-of-memory error. The allocated memory is now freed-up after an error.
* 2.5.11 - 25 Jan 2023 - UI for Merging Models. Thanks @JeLuf. More info: https://github.com/cmdr2/stable-diffusion-ui/wiki/Model-Merging
* 2.5.10 - 24 Jan 2023 - Reduce the VRAM usage for img2img in 'balanced' mode (without reducing the rendering speed), to make it similar to v2.4 of this UI.
* 2.5.9 - 23 Jan 2023 - Fix a bug where img2img would produce poorer-quality images for the same settings, as compared to version 2.4 of this UI.
* 2.5.9 - 23 Jan 2023 - Reduce the VRAM usage for 'balanced' mode (without reducing the rendering speed), to make it similar to v2.4 of the UI.

View File

@ -42,6 +42,8 @@ or for Windows
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.

View File

@ -5,10 +5,10 @@ If you haven't downloaded Stable Diffusion UI yet, please download from https://
After downloading, to install please follow these instructions:
For Windows:
- Please double-click the "Easy-Diffusion-Windows.exe" file and follow the instructions.
- Please double-click the "Start Stable Diffusion UI.cmd" file inside the "stable-diffusion-ui" folder.
For Linux:
- Please open a terminal, unzip the Easy-Diffusion-Linux.zip file and go to the "easy-diffusion" directory. Then run ./start.sh
- Please open a terminal, and go to the "stable-diffusion-ui" directory. Then run ./start.sh
That file will automatically install everything. After that it will start the Stable Diffusion interface in a web browser.
@ -21,4 +21,4 @@ If you have any problems, please:
3. Or, file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues
Thanks
cmdr2 (and contributors to the project)
cmdr2 (and contributors to the project)

1
NSIS/.gitignore vendored
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@ -1 +0,0 @@
*.exe

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@ -1 +0,0 @@
!define EXISTING_INSTALLATION_DIR "D:\path\to\installed\easy-diffusion"

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@ -1,24 +1,20 @@
; Script generated by the HM NIS Edit Script Wizard.
Target amd64-unicode
Target x86-unicode
Unicode True
SetCompressor /FINAL lzma
RequestExecutionLevel user
!AddPluginDir /amd64-unicode "."
!AddPluginDir /x86-unicode "."
; HM NIS Edit Wizard helper defines
!define PRODUCT_NAME "Easy Diffusion"
!define PRODUCT_VERSION "2.5"
!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\Easy Diffusion\App Paths\installer.exe"
!define PRODUCT_DIR_REGKEY "Software\Microsoft\Cmdr2\App Paths\installer.exe"
; MUI 1.67 compatible ------
!include "MUI.nsh"
!include "LogicLib.nsh"
!include "nsDialogs.nsh"
!include "nsisconf.nsh"
Var Dialog
Var Label
Var Button
@ -110,7 +106,7 @@ Function DirectoryLeave
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"
${AndIf} $1 == "NTFS"
MessageBox mb_ok "$5 has filesystem type '$1'.$\nOnly NTFS filesystems are supported.$\nPlease choose a different drive."
Abort
${EndIf}
@ -144,7 +140,7 @@ Function MediaPackDialog
Abort
${EndIf}
${NSD_CreateLabel} 0 0 100% 48u "The Windows Media Feature Pack is missing on this computer. It is required for Easy Diffusion.$\nYou can continue the installation after installing the Windows Media Feature Pack."
${NSD_CreateLabel} 0 0 100% 48u "The Windows Media Feature Pack is missing on this computer. It is required for the Stable Diffusion UI.$\nYou can continue the installation after installing the Windows Media Feature Pack."
Pop $Label
${NSD_CreateButton} 10% 49u 80% 12u "Download Meda Feature Pack from Microsoft"
@ -157,20 +153,16 @@ Function MediaPackDialog
nsDialogs::Show
FunctionEnd
Function FinishPageAction
CreateShortCut "$DESKTOP\Easy Diffusion.lnk" "$INSTDIR\Start Stable Diffusion UI.cmd" "" "$INSTDIR\installer_files\cyborg_flower_girl.ico"
FunctionEnd
;---------------------------------------------------------------------------------------------------------
; MUI Settings
;---------------------------------------------------------------------------------------------------------
!define MUI_ABORTWARNING
!define MUI_ICON "cyborg_flower_girl.ico"
!define MUI_ICON "sd.ico"
!define MUI_WELCOMEFINISHPAGE_BITMAP "cyborg_flower_girl.bmp"
!define MUI_WELCOMEFINISHPAGE_BITMAP "astro.bmp"
; Welcome page
!define MUI_WELCOMEPAGE_TEXT "This installer will guide you through the installation of Easy Diffusion.$\n$\n\
!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
@ -186,11 +178,6 @@ Page custom MediaPackDialog
!insertmacro MUI_PAGE_INSTFILES
; Finish page
!define MUI_FINISHPAGE_SHOWREADME ""
!define MUI_FINISHPAGE_SHOWREADME_NOTCHECKED
!define MUI_FINISHPAGE_SHOWREADME_TEXT "Create Desktop Shortcut"
!define MUI_FINISHPAGE_SHOWREADME_FUNCTION FinishPageAction
!define MUI_FINISHPAGE_RUN "$INSTDIR\Start Stable Diffusion UI.cmd"
!insertmacro MUI_PAGE_FINISH
@ -201,8 +188,8 @@ Page custom MediaPackDialog
;---------------------------------------------------------------------------------------------------------
Name "${PRODUCT_NAME} ${PRODUCT_VERSION}"
OutFile "Install Easy Diffusion.exe"
InstallDir "C:\EasyDiffusion\"
OutFile "Install Stable Diffusion UI.exe"
InstallDir "C:\Stable-Diffusion-UI\"
InstallDirRegKey HKLM "${PRODUCT_DIR_REGKEY}" ""
ShowInstDetails show
@ -213,42 +200,15 @@ Section "MainSection" SEC01
File "..\CreativeML Open RAIL-M License"
File "..\How to install and run.txt"
File "..\LICENSE"
File "..\scripts\Start Stable Diffusion UI.cmd"
File /r "${EXISTING_INSTALLATION_DIR}\installer_files"
File /r "${EXISTING_INSTALLATION_DIR}\profile"
File /r "${EXISTING_INSTALLATION_DIR}\sd-ui-files"
SetOutPath "$INSTDIR\installer_files"
File "cyborg_flower_girl.ico"
File "..\Start Stable Diffusion UI.cmd"
SetOutPath "$INSTDIR\scripts"
File "${EXISTING_INSTALLATION_DIR}\scripts\install_status.txt"
File "..\scripts\bootstrap.bat"
File "..\scripts\install_status.txt"
File "..\scripts\on_env_start.bat"
File "C:\windows\system32\curl.exe"
CreateDirectory "$INSTDIR\models"
CreateDirectory "$INSTDIR\models\stable-diffusion"
CreateDirectory "$INSTDIR\models\gfpgan"
CreateDirectory "$INSTDIR\models\realesrgan"
CreateDirectory "$INSTDIR\models\vae"
CreateDirectory "$SMPROGRAMS\Easy Diffusion"
CreateShortCut "$SMPROGRAMS\Easy Diffusion\Easy Diffusion.lnk" "$INSTDIR\Start Stable Diffusion UI.cmd" "" "$INSTDIR\installer_files\cyborg_flower_girl.ico"
DetailPrint 'Downloading the Stable Diffusion 1.4 model...'
NScurl::http get "https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt" "$INSTDIR\models\stable-diffusion\sd-v1-4.ckpt" /CANCEL /INSIST /END
DetailPrint 'Downloading the GFPGAN model...'
NScurl::http get "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth" "$INSTDIR\models\gfpgan\GFPGANv1.4.pth" /CANCEL /INSIST /END
DetailPrint 'Downloading the RealESRGAN_x4plus model...'
NScurl::http get "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth" "$INSTDIR\models\realesrgan\RealESRGAN_x4plus.pth" /CANCEL /INSIST /END
DetailPrint 'Downloading the RealESRGAN_x4plus_anime model...'
NScurl::http get "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth" "$INSTDIR\models\realesrgan\RealESRGAN_x4plus_anime_6B.pth" /CANCEL /INSIST /END
DetailPrint 'Downloading the default VAE (sd-vae-ft-mse-original) model...'
NScurl::http get "https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt" "$INSTDIR\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" /CANCEL /INSIST /END
DetailPrint 'Downloading the CLIP model (clip-vit-large-patch14)...'
NScurl::http get "https://huggingface.co/openai/clip-vit-large-patch14/resolve/8d052a0f05efbaefbc9e8786ba291cfdf93e5bff/pytorch_model.bin" "$INSTDIR\profile\.cache\huggingface\hub\models--openai--clip-vit-large-patch14\snapshots\8d052a0f05efbaefbc9e8786ba291cfdf93e5bff\pytorch_model.bin" /CANCEL /INSIST /END
CreateDirectory "$INSTDIR\profile"
CreateDirectory "$SMPROGRAMS\Stable Diffusion UI"
CreateShortCut "$SMPROGRAMS\Stable Diffusion UI\Start Stable Diffusion UI.lnk" "$INSTDIR\Start Stable Diffusion UI.cmd"
SectionEnd
;---------------------------------------------------------------------------------------------------------
@ -294,7 +254,7 @@ Function .onInit
${If} $4 < "8000"
MessageBox MB_OK|MB_ICONEXCLAMATION "Warning!$\n$\nYour system has less than 8GB of memory (RAM).$\n$\n\
You can still try to install Easy Diffusion,$\nbut it might have problems to start, or run$\nvery slowly."
You can still try to install Stable Diffusion UI,$\nbut it might have problems to start, or run$\nvery slowly."
${EndIf}
FunctionEnd

View File

@ -1,9 +0,0 @@
// placeholder until a more formal and legal-sounding privacy policy document is written. but the information below is true.
This is a summary of whether Easy Diffusion uses your data or tracks you:
* The short answer is - Easy Diffusion does *not* use your data, and does *not* track you.
* Easy Diffusion does not send your prompts or usage or analytics to anyone. There is no tracking. We don't even know how many people use Easy Diffusion, let alone their prompts.
* Easy Diffusion fetches updates to the code whenever it starts up. It does this by contacting GitHub directly, via SSL (secure connection). Only your computer and GitHub and [this repository](https://github.com/cmdr2/stable-diffusion-ui) are involved, and no third party is involved. Some countries intercepts SSL connections, that's not something we can do much about. GitHub does *not* share statistics (even with me) about how many people fetched code updates.
* Easy Diffusion fetches the models from huggingface.co and github.com, if they don't exist on your PC. For e.g. if the safety checker (NSFW) model doesn't exist, it'll try to download it.
* Easy Diffusion fetches code packages from pypi.org, which is the standard hosting service for all Python projects. That's where packages installed via `pip install` are stored.
* Occasionally, antivirus software are known to *incorrectly* flag and delete some model files, which will result in Easy Diffusion re-downloading `pytorch_model.bin`. This *incorrect deletion* affects other Stable Diffusion UIs as well, like Invoke AI - https://itch.io/post/7509488

View File

@ -1,46 +1,40 @@
# Easy Diffusion 2.5
### The easiest way to install and use [Stable Diffusion](https://github.com/CompVis/stable-diffusion) on your computer.
# 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.
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)
[Installation guide](#installation) | [Troubleshooting guide](https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting) | <sub>[![Discord Server](https://img.shields.io/discord/1014774730907209781?label=Discord)](https://discord.com/invite/u9yhsFmEkB)</sub> <sup>(for support queries, and development discussions)</sup>
### New:
Experimental support for Stable Diffusion 2.0 is available in beta!
![t2i](https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/assets/stable-samples/txt2img/768/merged-0006.png)
----
# Installation
# Step 1: Download and prepare the installer
Click the download button for your operating system:
<p float="left">
<a href="https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.5.24/Easy-Diffusion-Windows.exe"><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/releases/download/v2.5.24/Easy-Diffusion-Linux.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-linux.png" width="200" /></a>
<a href="https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.5.24/Easy-Diffusion-Mac.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-mac.png" width="200" /></a>
<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/releases/download/v2.4.13/stable-diffusion-ui-linux.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-linux.png" width="200" /></a>
</p>
**Hardware requirements:**
- **Windows:** NVIDIA graphics card (minimum 2 GB RAM), or run on your CPU.
- **Linux:** NVIDIA or AMD graphics card (minimum 2 GB RAM), or run on your CPU.
- **Mac:** M1 or M2, or run on your CPU.
- Minimum 8 GB of system RAM.
- Atleast 25 GB of space on the hard disk.
## 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.
# 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.
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.
## On Windows:
1. Run the downloaded `Easy-Diffusion-Windows.exe` file.
2. Run `Easy Diffusion` once the installation finishes. You can also start from your Start Menu, or from your desktop (if you created a shortcut).
# Step 3: There is no Step 3. It's that simple!
If Windows SmartScreen prevents you from running the program click `More info` and then `Run anyway`.
**Tip:** On Windows 10, please install at the top level in your drive, e.g. `C:\EasyDiffusion` or `D:\EasyDiffusion`. This will avoid a common problem with Windows 10 (file path length limits).
## On Linux/Mac:
1. Unzip/extract the folder `easy-diffusion` which should be in your downloads folder, unless you changed your default downloads destination.
2. Open a terminal window, and navigate to the `easy-diffusion` directory.
3. Run `./start.sh` (or `bash start.sh`) in a terminal.
# To remove/uninstall:
Just delete the `EasyDiffusion` folder to uninstall all the downloaded packages.
**To Uninstall:** Just delete the `stable-diffusion-ui` folder to uninstall all the downloaded packages.
----
@ -50,18 +44,9 @@ Just delete the `EasyDiffusion` folder to uninstall all the downloaded packages.
### 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.
- **Task Queue**: Queue up all your ideas, without waiting for the current task to finish.
- **Intelligent Model Detection**: Automatically figures out the YAML config file to use for the chosen model (via a models database).
- **Live Preview**: See the image as the AI is drawing it.
- **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.
- **Searchable models dropdown**: organize your models into sub-folders, and search through them in the UI.
### Image generation
- **Supports**: "*Text to Image*" and "*Image to Image*".
- **21 Samplers**: `ddim`, `plms`, `heun`, `euler`, `euler_a`, `dpm2`, `dpm2_a`, `lms`, `dpm_solver_stability`, `dpmpp_2s_a`, `dpmpp_2m`, `dpmpp_sde`, `dpm_fast`, `dpm_adaptive`, `ddpm`, `deis`, `unipc_snr`, `unipc_tu`, `unipc_tq`, `unipc_snr_2`, `unipc_tu_2`.
- **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)**
@ -71,23 +56,21 @@ Just delete the `EasyDiffusion` folder to uninstall all the downloaded packages.
- **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/WEBP output**: Multiple file formats.
- **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 2.1 support**
- **Merge Models**
- **Stable Diffusion 2.0 support (experimental)**: available in beta channel.
- **Use custom VAE models**
- **Use pre-trained Hypernetworks**
- **Use custom GFPGAN models**
- **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
- **Fast**: Creates a 512x512 image with euler_a in 5 seconds, on an NVIDIA 3060 12GB.
- **Low Memory Usage**: Create 512x512 images with less than 2 GB of GPU RAM, and 768x768 images with less than 3 GB of GPU RAM!
- **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.
@ -95,17 +78,23 @@ Just delete the `EasyDiffusion` folder to uninstall all the downloaded packages.
- **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.
- **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.
**(and a lot more)**
----
## Easy for new users:
![Screenshot of the initial UI](https://user-images.githubusercontent.com/844287/217043152-29454d15-0387-4228-b70d-9a4b84aeb8ba.png)
![Screenshot of the initial UI](media/shot-v10-simple.jpg?raw=true)
## Powerful features for advanced users:
![Screenshot of advanced settings](https://user-images.githubusercontent.com/844287/217042588-fc53c975-bacd-4a9c-af88-37408734ade3.png)
![Screenshot of advanced settings](media/shot-v10.jpg?raw=true)
## Live Preview
Useful for judging (and stopping) an image quickly, without waiting for it to finish rendering.
@ -113,8 +102,14 @@ Useful for judging (and stopping) an image quickly, without waiting for it to fi
![live-512](https://user-images.githubusercontent.com/844287/192097249-729a0a1e-a677-485e-9ccc-16a9e848fabe.gif)
## Task Queue
![Screenshot of task queue](https://user-images.githubusercontent.com/844287/217043984-0b35f73b-1318-47cb-9eed-a2a91b430490.png)
![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.
You don't need to install or struggle with Python, Anaconda, Docker etc. The installer will take care of whatever is needed.
----

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@ -1,9 +0,0 @@
{
"scripts": {
"prettier-fix": "npx prettier --write \"./**/*.js\"",
"prettier-check": "npx prettier --check \"./**/*.js\""
},
"devDependencies": {
"prettier": "^1.19.1"
}
}

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@ -1,36 +1,20 @@
@echo off
cd /d %~dp0
echo Install dir: %~dp0
set PATH=C:\Windows\System32;%PATH%
if exist "on_sd_start.bat" (
echo ================================================================================
echo.
echo !!!! WARNING !!!!
echo.
echo It looks like you're trying to run the installation script from a source code
echo download. This will not work.
echo.
echo Recommended: Please close this window and download the installer from
echo https://stable-diffusion-ui.github.io/docs/installation/
echo.
echo ================================================================================
echo.
pause
exit /b
)
@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%
@rem Setup the packages required for the installer
call scripts\bootstrap.bat
@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%
set PYTHONPATH=%cd%\installer;%cd%\installer_files\env
@rem Test the core requirements
@rem Test the bootstrap
call where git
call git --version

View File

@ -1,5 +1,4 @@
@echo off
setlocal enabledelayedexpansion
@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).
@ -29,10 +28,10 @@ if not exist "%LEGACY_INSTALL_ENV_DIR%\etc\profile.d\conda.sh" (
)
call git --version >.tmp1 2>.tmp2
if "!ERRORLEVEL!" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% git
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
if "%ERRORLEVEL%" EQU "0" set umamba_exists=T
@rem (if necessary) install git and conda into a contained environment
if "%PACKAGES_TO_INSTALL%" NEQ "" (
@ -43,7 +42,7 @@ if "%PACKAGES_TO_INSTALL%" NEQ "" (
mkdir "%MAMBA_ROOT_PREFIX%"
call curl -Lk "%MICROMAMBA_DOWNLOAD_URL%" > "%MAMBA_ROOT_PREFIX%\micromamba.exe"
if "!ERRORLEVEL!" NEQ "0" (
if "%ERRORLEVEL%" NEQ "0" (
echo "There was a problem downloading micromamba. Cannot continue."
pause
exit /b

View File

@ -21,16 +21,9 @@ OS_ARCH=$(uname -m)
case "${OS_ARCH}" in
x86_64*) OS_ARCH="64";;
arm64*) OS_ARCH="arm64";;
aarch64*) OS_ARCH="arm64";;
*) echo "Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64" && exit
esac
if ! which curl; then fail "'curl' not found. Please install curl."; fi
if ! which tar; then fail "'tar' not found. Please install tar."; fi
if ! which bzip2; then fail "'bzip2' not found. Please install bzip2."; fi
if pwd | grep ' '; then fail "The installation directory's path contains a space character. Conda will fail to install. Please change the directory."; fi
# https://mamba.readthedocs.io/en/latest/installation.html
if [ "$OS_NAME" == "linux" ] && [ "$OS_ARCH" == "arm64" ]; then OS_ARCH="aarch64"; fi
@ -58,7 +51,7 @@ if [ "$PACKAGES_TO_INSTALL" != "" ]; then
echo "Downloading micromamba from $MICROMAMBA_DOWNLOAD_URL to $MAMBA_ROOT_PREFIX/micromamba"
mkdir -p "$MAMBA_ROOT_PREFIX"
curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvj -O bin/micromamba > "$MAMBA_ROOT_PREFIX/micromamba"
curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvj bin/micromamba -O > "$MAMBA_ROOT_PREFIX/micromamba"
if [ "$?" != "0" ]; then
echo

View File

@ -1,161 +1,13 @@
"""
This script checks and installs the required modules.
'''
This script checks if the given modules exist
'''
This script runs inside the legacy "stable-diffusion" folder
import sys
import pkgutil
TODO - Maybe replace the bulk of this script with a call to `pip install -f requirements.txt`, with
a custom index URL depending on the platform.
"""
import os
from importlib.metadata import version as pkg_version
import platform
import traceback
os_name = platform.system()
modules_to_check = {
"torch": ("1.11.0", "1.13.1", "2.0.0"),
"torchvision": ("0.12.0", "0.14.1", "0.15.1"),
"sdkit": "1.0.112",
"stable-diffusion-sdkit": "2.1.4",
"rich": "12.6.0",
"uvicorn": "0.19.0",
"fastapi": "0.85.1",
"pycloudflared": "0.2.0",
# "xformers": "0.0.16",
}
modules_to_log = ["torch", "torchvision", "sdkit", "stable-diffusion-sdkit"]
def version(module_name: str) -> str:
try:
return pkg_version(module_name)
except:
return None
def install(module_name: str, module_version: str):
if module_name == "xformers" and (os_name == "Darwin" or is_amd_on_linux()):
return
index_url = None
if module_name in ("torch", "torchvision"):
module_version, index_url = apply_torch_install_overrides(module_version)
if is_amd_on_linux(): # hack until AMD works properly on torch 2.0 (avoids black images on some cards)
if module_name == "torch":
module_version = "1.13.1+rocm5.2"
elif module_name == "torchvision":
module_version = "0.14.1+rocm5.2"
elif os_name == "Darwin":
if module_name == "torch":
module_version = "1.13.1"
elif module_name == "torchvision":
module_version = "0.14.1"
install_cmd = f"python -m pip install --upgrade {module_name}=={module_version}"
if index_url:
install_cmd += f" --index-url {index_url}"
if module_name == "sdkit" and version("sdkit") is not None:
install_cmd += " -q"
print(">", install_cmd)
os.system(install_cmd)
def init():
for module_name, allowed_versions in modules_to_check.items():
if os.path.exists(f"../src/{module_name}"):
print(f"Skipping {module_name} update, since it's in developer/editable mode")
continue
allowed_versions, latest_version = get_allowed_versions(module_name, allowed_versions)
requires_install = False
if module_name in ("torch", "torchvision"):
if version(module_name) is None: # allow any torch version
requires_install = True
elif os_name == "Darwin" and ( # force mac to downgrade from torch 2.0
version("torch").startswith("2.") or version("torchvision").startswith("0.15.")
):
requires_install = True
elif version(module_name) not in allowed_versions:
requires_install = True
if requires_install:
try:
install(module_name, latest_version)
except:
traceback.print_exc()
fail(module_name)
if module_name in modules_to_log:
print(f"{module_name}: {version(module_name)}")
### utilities
def get_allowed_versions(module_name: str, allowed_versions: tuple):
allowed_versions = (allowed_versions,) if isinstance(allowed_versions, str) else allowed_versions
latest_version = allowed_versions[-1]
if module_name in ("torch", "torchvision"):
allowed_versions = include_cuda_versions(allowed_versions)
return allowed_versions, latest_version
def apply_torch_install_overrides(module_version: str):
index_url = None
if os_name == "Windows":
module_version += "+cu117"
index_url = "https://download.pytorch.org/whl/cu117"
elif is_amd_on_linux():
index_url = "https://download.pytorch.org/whl/rocm5.2"
return module_version, index_url
def include_cuda_versions(module_versions: tuple) -> tuple:
"Adds CUDA-specific versions to the list of allowed version numbers"
allowed_versions = tuple(module_versions)
allowed_versions += tuple(f"{v}+cu116" for v in module_versions)
allowed_versions += tuple(f"{v}+cu117" for v in module_versions)
allowed_versions += tuple(f"{v}+rocm5.2" for v in module_versions)
allowed_versions += tuple(f"{v}+rocm5.4.2" for v in module_versions)
return allowed_versions
def is_amd_on_linux():
if os_name == "Linux":
try:
with open("/proc/bus/pci/devices", "r") as f:
device_info = f.read()
if "amdgpu" in device_info and "nvidia" not in device_info:
return True
except:
return False
return False
def fail(module_name):
print(
f"""Error installing {module_name}. 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!"""
)
exit(1)
### start
init()
modules = sys.argv[1:]
missing_modules = []
for m in modules:
if pkgutil.find_loader(m) is None:
print('module', m, 'not found')
exit(1)

View File

@ -39,8 +39,6 @@ if [ "$0" == "bash" ]; then
export PYTHONPATH="$(pwd)/stable-diffusion/env/lib/python3.8/site-packages"
fi
export PYTHONNOUSERSITE=y
which python
python --version

View File

@ -28,12 +28,5 @@ EOF
}
filesize() {
case "$(uname -s)" in
Linux*) stat -c "%s" $1;;
Darwin*) /usr/bin/stat -f "%z" $1;;
*) echo "Unknown OS: $OS_NAME! This script runs only on Linux or Mac" && exit
esac
}

View File

@ -1,46 +0,0 @@
import os
import argparse
import sys
# The config file is in the same directory as this script
config_directory = os.path.dirname(__file__)
config_yaml = os.path.join(config_directory, "config.yaml")
config_json = os.path.join(config_directory, "config.json")
parser = argparse.ArgumentParser(description='Get values from config file')
parser.add_argument('--default', dest='default', action='store',
help='default value, to be used if the setting is not defined in the config file')
parser.add_argument('key', metavar='key', nargs='+',
help='config key to return')
args = parser.parse_args()
if os.path.isfile(config_yaml):
import yaml
with open(config_yaml, 'r') as configfile:
try:
config = yaml.safe_load(configfile)
except Exception as e:
print(e, file=sys.stderr)
config = {}
elif os.path.isfile(config_json):
import json
with open(config_json, 'r') as configfile:
try:
config = json.load(configfile)
except Exception as e:
print(e, file=sys.stderr)
config = {}
else:
config = {}
for k in args.key:
if k in config:
config = config[k]
else:
if args.default != None:
print(args.default)
exit()
print(config)

View File

@ -1,6 +1,6 @@
@echo off
@echo. & echo "Easy Diffusion - v2" & echo.
@echo. & echo "Stable Diffusion UI - v2" & echo.
set PATH=C:\Windows\System32;%PATH%
@ -8,20 +8,6 @@ if exist "scripts\config.bat" (
@call scripts\config.bat
)
if exist "scripts\user_config.bat" (
@call scripts\user_config.bat
)
if exist "stable-diffusion\env" (
@set PYTHONPATH=%PYTHONPATH%;%cd%\stable-diffusion\env\lib\site-packages
)
if exist "scripts\get_config.py" (
@FOR /F "tokens=* USEBACKQ" %%F IN (`python scripts\get_config.py --default=main update_branch`) DO (
@SET update_branch=%%F
)
)
if "%update_branch%"=="" (
set update_branch=main
)
@ -42,7 +28,7 @@ if "%update_branch%"=="" (
@>nul findstr /m "sd_ui_git_cloned" scripts\install_status.txt
@if "%ERRORLEVEL%" EQU "0" (
@echo "Easy Diffusion's git repository was already installed. Updating from %update_branch%.."
@echo "Stable Diffusion UI's git repository was already installed. Updating from %update_branch%.."
@cd sd-ui-files
@ -52,13 +38,13 @@ if "%update_branch%"=="" (
@cd ..
) else (
@echo. & echo "Downloading Easy Diffusion..." & echo.
@echo. & echo "Downloading Stable Diffusion UI.." & echo.
@echo "Using the %update_branch% channel" & echo.
@call git clone -b "%update_branch%" https://github.com/cmdr2/stable-diffusion-ui.git sd-ui-files && (
@echo sd_ui_git_cloned >> scripts\install_status.txt
) || (
@echo "Error downloading Easy 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 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
)
@ -66,8 +52,8 @@ if "%update_branch%"=="" (
@xcopy sd-ui-files\ui ui /s /i /Y /q
@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\check_modules.py scripts\ /Y
@copy sd-ui-files\scripts\get_config.py scripts\ /Y
@copy "sd-ui-files\scripts\Start Stable Diffusion UI.cmd" . /Y
@copy "sd-ui-files\scripts\Developer Console.cmd" . /Y

View File

@ -2,30 +2,18 @@
source ./scripts/functions.sh
printf "\n\nEasy Diffusion\n\n"
export PYTHONNOUSERSITE=y
printf "\n\nStable Diffusion UI\n\n"
if [ -f "scripts/config.sh" ]; then
source scripts/config.sh
fi
if [ -f "scripts/user_config.sh" ]; then
source scripts/user_config.sh
fi
export PYTHONPATH=$(pwd)/installer_files/env/lib/python3.8/site-packages:$(pwd)/stable-diffusion/env/lib/python3.8/site-packages
if [ -f "scripts/get_config.py" ]; then
export update_branch="$( python scripts/get_config.py --default=main update_branch )"
fi
if [ "$update_branch" == "" ]; then
export update_branch="main"
fi
if [ -f "scripts/install_status.txt" ] && [ `grep -c sd_ui_git_cloned scripts/install_status.txt` -gt "0" ]; then
echo "Easy Diffusion's git repository was already installed. Updating from $update_branch.."
echo "Stable Diffusion UI's git repository was already installed. Updating from $update_branch.."
cd sd-ui-files
@ -35,7 +23,7 @@ if [ -f "scripts/install_status.txt" ] && [ `grep -c sd_ui_git_cloned scripts/in
cd ..
else
printf "\n\nDownloading Easy Diffusion..\n\n"
printf "\n\nDownloading Stable Diffusion UI..\n\n"
printf "Using the $update_branch channel\n\n"
if git clone -b "$update_branch" https://github.com/cmdr2/stable-diffusion-ui.git sd-ui-files ; then
@ -50,9 +38,9 @@ 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/check_modules.py scripts/
cp sd-ui-files/scripts/get_config.py scripts/
cp sd-ui-files/scripts/start.sh .
cp sd-ui-files/scripts/developer_console.sh .
cp sd-ui-files/scripts/functions.sh scripts/
exec ./scripts/on_sd_start.sh
./scripts/on_sd_start.sh
read -p "Press any key to continue"

View File

@ -4,11 +4,11 @@
@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
@copy sd-ui-files\scripts\check_modules.py scripts\ /Y
@copy sd-ui-files\scripts\get_config.py scripts\ /Y
if exist "%cd%\profile" (
set HF_HOME=%cd%\profile\.cache\huggingface
set USERPROFILE=%cd%\profile
)
@rem set the correct installer path (current vs legacy)
@ -26,7 +26,7 @@ if exist "%cd%\stable-diffusion\env" (
@rem activate the installer env
call conda activate
@if "%ERRORLEVEL%" NEQ "0" (
@echo. & echo "Error activating conda for Easy 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 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
)
@ -34,6 +34,8 @@ call conda activate
@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');"
@rem create the stable-diffusion folder, to work with legacy installations
if not exist "stable-diffusion" mkdir stable-diffusion
cd stable-diffusion
@ -47,22 +49,106 @@ if exist "env" (
if exist src rename src src-old
if exist ldm rename ldm ldm-old
if not exist "..\models\stable-diffusion" mkdir "..\models\stable-diffusion"
if not exist "..\models\gfpgan" mkdir "..\models\gfpgan"
if not exist "..\models\realesrgan" mkdir "..\models\realesrgan"
if not exist "..\models\vae" mkdir "..\models\vae"
if not exist "%INSTALL_ENV_DIR%\DLLs\libssl-1_1-x64.dll" copy "%INSTALL_ENV_DIR%\Library\bin\libssl-1_1-x64.dll" "%INSTALL_ENV_DIR%\DLLs\"
if not exist "%INSTALL_ENV_DIR%\DLLs\libcrypto-1_1-x64.dll" copy "%INSTALL_ENV_DIR%\Library\bin\libcrypto-1_1-x64.dll" "%INSTALL_ENV_DIR%\DLLs\"
@rem migrate the legacy models to the correct path (if already downloaded)
if exist "sd-v1-4.ckpt" move sd-v1-4.ckpt ..\models\stable-diffusion\
if exist "custom-model.ckpt" move custom-model.ckpt ..\models\stable-diffusion\
if exist "GFPGANv1.3.pth" move GFPGANv1.3.pth ..\models\gfpgan\
if exist "RealESRGAN_x4plus.pth" move RealESRGAN_x4plus.pth ..\models\realesrgan\
if exist "RealESRGAN_x4plus_anime_6B.pth" move RealESRGAN_x4plus_anime_6B.pth ..\models\realesrgan\
@rem install torch and torchvision
call python ..\scripts\check_modules.py torch torchvision
if "%ERRORLEVEL%" EQU "0" (
echo "torch and torchvision have already been installed."
) else (
echo "Installing torch and torchvision.."
@REM prevent from using packages from the user's home directory, to avoid conflicts
set PYTHONNOUSERSITE=1
set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
call pip install --upgrade torch torchvision --extra-index-url https://download.pytorch.org/whl/cu116 || (
echo "Error installing torch. 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
)
)
@rem install/upgrade sdkit
call python ..\scripts\check_modules.py sdkit sdkit.models ldm transformers numpy antlr4 gfpgan realesrgan
if "%ERRORLEVEL%" EQU "0" (
echo "sdkit is already installed."
@rem skip sdkit upgrade if in developer-mode
if not exist "..\src\sdkit" (
@REM prevent from using packages from the user's home directory, to avoid conflicts
set PYTHONNOUSERSITE=1
set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
call pip install --upgrade sdkit -q || (
echo "Error updating sdkit"
)
)
) else (
echo "Installing sdkit: https://pypi.org/project/sdkit/"
@REM prevent from using packages from the user's home directory, to avoid conflicts
set PYTHONNOUSERSITE=1
set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
call pip install sdkit || (
echo "Error installing sdkit. 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
)
)
call python -c "from importlib.metadata import version; print('sdkit version:', version('sdkit'))"
@rem upgrade stable-diffusion-sdkit
call pip install --upgrade stable-diffusion-sdkit -q || (
echo "Error updating stable-diffusion-sdkit"
)
call python -c "from importlib.metadata import version; print('stable-diffusion version:', version('stable-diffusion-sdkit'))"
@rem install rich
call python ..\scripts\check_modules.py rich
if "%ERRORLEVEL%" EQU "0" (
echo "rich has already been installed."
) else (
echo "Installing rich.."
set PYTHONNOUSERSITE=1
set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
call pip install rich || (
echo "Error installing rich. 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
)
)
@rem install or upgrade the required modules
set PATH=C:\Windows\System32;%PATH%
@REM prevent from using packages from the user's home directory, to avoid conflicts
set PYTHONNOUSERSITE=1
set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
call python ..\scripts\check_modules.py uvicorn fastapi
@if "%ERRORLEVEL%" EQU "0" (
echo "Packages necessary for Stable Diffusion UI were already installed"
) else (
@echo. & echo "Downloading packages necessary for Stable Diffusion UI.." & echo.
@rem Download the required packages
call python ..\scripts\check_modules.py
if "%ERRORLEVEL%" NEQ "0" (
pause
exit /b
set PYTHONNOUSERSITE=1
set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
@call conda install -c conda-forge -y 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!"
pause
exit /b
)
)
call WHERE uvicorn > .tmp
@ -78,13 +164,169 @@ call WHERE uvicorn > .tmp
@echo conda_sd_ui_deps_installed >> ..\scripts\install_status.txt
)
@if exist "..\models\stable-diffusion\sd-v1-4.ckpt" (
for %%I in ("..\models\stable-diffusion\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."
) else (
for %%J in ("..\models\stable-diffusion\sd-v1-4.ckpt") do if "%%~zJ" EQU "7703807346" (
echo "Data files (weights) necessary for Stable Diffusion were already downloaded. Using the HuggingFace 7 GB Model."
) else (
for %%K in ("..\models\stable-diffusion\sd-v1-4.ckpt") do if "%%~zK" EQU "7703810927" (
echo "Data files (weights) necessary for Stable Diffusion were already downloaded. Using the Waifu Model."
) else (
echo. & echo "The model file present at models\stable-diffusion\sd-v1-4.ckpt is invalid. It is only %%~zK bytes in size. Re-downloading.." & echo.
del "..\models\stable-diffusion\sd-v1-4.ckpt"
)
)
)
)
@if not exist "..\models\stable-diffusion\sd-v1-4.ckpt" (
@echo. & echo "Downloading data files (weights) for Stable Diffusion.." & echo.
@call curl -L -k https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt > ..\models\stable-diffusion\sd-v1-4.ckpt
@if exist "..\models\stable-diffusion\sd-v1-4.ckpt" (
for %%I in ("..\models\stable-diffusion\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.
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.
pause
exit /b
)
)
@if exist "..\models\gfpgan\GFPGANv1.3.pth" (
for %%I in ("..\models\gfpgan\GFPGANv1.3.pth") do if "%%~zI" EQU "348632874" (
echo "Data files (weights) necessary for GFPGAN (Face Correction) were already downloaded"
) else (
echo. & echo "The GFPGAN model file present at models\gfpgan\GFPGANv1.3.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
del "..\models\gfpgan\GFPGANv1.3.pth"
)
)
@if not exist "..\models\gfpgan\GFPGANv1.3.pth" (
@echo. & echo "Downloading data files (weights) for GFPGAN (Face Correction).." & echo.
@call curl -L -k https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth > ..\models\gfpgan\GFPGANv1.3.pth
@if exist "..\models\gfpgan\GFPGANv1.3.pth" (
for %%I in ("..\models\gfpgan\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.
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.
pause
exit /b
)
)
@if exist "..\models\realesrgan\RealESRGAN_x4plus.pth" (
for %%I in ("..\models\realesrgan\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 models\realesrgan\RealESRGAN_x4plus.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
del "..\models\realesrgan\RealESRGAN_x4plus.pth"
)
)
@if not exist "..\models\realesrgan\RealESRGAN_x4plus.pth" (
@echo. & echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.." & echo.
@call curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth > ..\models\realesrgan\RealESRGAN_x4plus.pth
@if exist "..\models\realesrgan\RealESRGAN_x4plus.pth" (
for %%I in ("..\models\realesrgan\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.
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.
pause
exit /b
)
)
@if exist "..\models\realesrgan\RealESRGAN_x4plus_anime_6B.pth" (
for %%I in ("..\models\realesrgan\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 models\realesrgan\RealESRGAN_x4plus_anime_6B.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
del "..\models\realesrgan\RealESRGAN_x4plus_anime_6B.pth"
)
)
@if not exist "..\models\realesrgan\RealESRGAN_x4plus_anime_6B.pth" (
@echo. & echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.." & echo.
@call curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth > ..\models\realesrgan\RealESRGAN_x4plus_anime_6B.pth
@if exist "..\models\realesrgan\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.
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.
pause
exit /b
)
)
@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
)
)
@>nul findstr /m "sd_install_complete" ..\scripts\install_status.txt
@if "%ERRORLEVEL%" NEQ "0" (
@echo sd_weights_downloaded >> ..\scripts\install_status.txt
@echo sd_install_complete >> ..\scripts\install_status.txt
)
@echo. & echo "Easy Diffusion installation complete! Starting the server!" & echo.
@echo. & echo "Stable Diffusion is ready!" & echo.
@set SD_DIR=%cd%
@ -96,25 +338,14 @@ call python --version
@cd ..
@set SD_UI_PATH=%cd%\ui
@FOR /F "tokens=* USEBACKQ" %%F IN (`python scripts\get_config.py --default=9000 net listen_port`) DO (
@SET ED_BIND_PORT=%%F
)
@FOR /F "tokens=* USEBACKQ" %%F IN (`python scripts\get_config.py --default=False net listen_to_network`) DO (
if "%%F" EQU "True" (
@SET ED_BIND_IP=0.0.0.0
) else (
@SET ED_BIND_IP=127.0.0.1
)
)
@cd stable-diffusion
@rem set any overrides
set HF_HUB_DISABLE_SYMLINKS_WARNING=true
@uvicorn main:server_api --app-dir "%SD_UI_PATH%" --port %ED_BIND_PORT% --host %ED_BIND_IP% --log-level error
@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 main:server_api --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP% --log-level error
@pause

View File

@ -1,12 +1,10 @@
#!/bin/bash
cp sd-ui-files/scripts/functions.sh scripts/
source ./scripts/functions.sh
cp sd-ui-files/scripts/on_env_start.sh scripts/
cp sd-ui-files/scripts/bootstrap.sh scripts/
cp sd-ui-files/scripts/check_modules.py scripts/
cp sd-ui-files/scripts/get_config.py scripts/
source ./scripts/functions.sh
# activate the installer env
CONDA_BASEPATH=$(conda info --base)
@ -19,6 +17,11 @@ if [ -e "open_dev_console.sh" ]; then
rm "open_dev_console.sh"
fi
python -c "import os; import shutil; frm = 'sd-ui-files/ui/hotfix/9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'; dst = os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'transformers', '9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'); shutil.copyfile(frm, dst) if os.path.exists(dst) else print(''); print('Hotfixed broken JSON file from OpenAI');"
# Caution, this file will make your eyes and brain bleed. It's such an unholy mess.
# Note to self: Please rewrite this in Python. For the sake of your own sanity.
# set the correct installer path (current vs legacy)
if [ -e "installer_files/env" ]; then
export INSTALL_ENV_DIR="$(pwd)/installer_files/env"
@ -40,14 +43,236 @@ fi
if [ -e "src" ]; then mv src src-old; fi
if [ -e "ldm" ]; then mv ldm ldm-old; fi
# Download the required packages
if ! python ../scripts/check_modules.py; then
read -p "Press any key to continue"
exit 1
mkdir -p "../models/stable-diffusion"
mkdir -p "../models/gfpgan"
mkdir -p "../models/realesrgan"
mkdir -p "../models/vae"
# migrate the legacy models to the correct path (if already downloaded)
if [ -e "sd-v1-4.ckpt" ]; then mv sd-v1-4.ckpt ../models/stable-diffusion/; fi
if [ -e "custom-model.ckpt" ]; then mv custom-model.ckpt ../models/stable-diffusion/; fi
if [ -e "GFPGANv1.3.pth" ]; then mv GFPGANv1.3.pth ../models/gfpgan/; fi
if [ -e "RealESRGAN_x4plus.pth" ]; then mv RealESRGAN_x4plus.pth ../models/realesrgan/; fi
if [ -e "RealESRGAN_x4plus_anime_6B.pth" ]; then mv RealESRGAN_x4plus_anime_6B.pth ../models/realesrgan/; fi
# install torch and torchvision
if python ../scripts/check_modules.py torch torchvision; then
echo "torch and torchvision have already been installed."
else
echo "Installing torch and torchvision.."
export PYTHONNOUSERSITE=1
export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
if pip install --upgrade torch torchvision --extra-index-url https://download.pytorch.org/whl/cu116 ; then
echo "Installed."
else
fail "torch install failed"
fi
fi
if ! command -v uvicorn &> /dev/null; then
fail "UI packages not found!"
# install/upgrade sdkit
if python ../scripts/check_modules.py sdkit sdkit.models ldm transformers numpy antlr4 gfpgan realesrgan ; then
echo "sdkit is already installed."
# skip sdkit upgrade if in developer-mode
if [ ! -e "../src/sdkit" ]; then
export PYTHONNOUSERSITE=1
export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
pip install --upgrade sdkit -q
fi
else
echo "Installing sdkit: https://pypi.org/project/sdkit/"
export PYTHONNOUSERSITE=1
export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
if pip install sdkit ; then
echo "Installed."
else
fail "sdkit install failed"
fi
fi
python -c "from importlib.metadata import version; print('sdkit version:', version('sdkit'))"
# upgrade stable-diffusion-sdkit
pip install --upgrade stable-diffusion-sdkit -q
python -c "from importlib.metadata import version; print('stable-diffusion version:', version('stable-diffusion-sdkit'))"
# install rich
if python ../scripts/check_modules.py rich; then
echo "rich has already been installed."
else
echo "Installing rich.."
export PYTHONNOUSERSITE=1
export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
if pip install rich ; then
echo "Installed."
else
fail "Install failed for rich"
fi
fi
if python ../scripts/check_modules.py uvicorn fastapi ; then
echo "Packages necessary for Stable Diffusion UI were already installed"
else
printf "\n\nDownloading packages necessary for Stable Diffusion UI..\n\n"
export PYTHONNOUSERSITE=1
export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
if conda install -c conda-forge -y uvicorn fastapi ; then
echo "Installed. Testing.."
else
fail "'conda install uvicorn' failed"
fi
if ! command -v uvicorn &> /dev/null; then
fail "UI packages not found!"
fi
fi
if [ -f "../models/stable-diffusion/sd-v1-4.ckpt" ]; then
model_size=`find "../models/stable-diffusion/sd-v1-4.ckpt" -printf "%s"`
if [ "$model_size" -eq "4265380512" ] || [ "$model_size" -eq "7703807346" ] || [ "$model_size" -eq "7703810927" ]; then
echo "Data files (weights) necessary for Stable Diffusion were already downloaded"
else
printf "\n\nThe model file present at models/stable-diffusion/sd-v1-4.ckpt is invalid. It is only $model_size bytes in size. Re-downloading.."
rm ../models/stable-diffusion/sd-v1-4.ckpt
fi
fi
if [ ! -f "../models/stable-diffusion/sd-v1-4.ckpt" ]; then
echo "Downloading data files (weights) for Stable Diffusion.."
curl -L -k https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt > ../models/stable-diffusion/sd-v1-4.ckpt
if [ -f "../models/stable-diffusion/sd-v1-4.ckpt" ]; then
model_size=`find "../models/stable-diffusion/sd-v1-4.ckpt" -printf "%s"`
if [ ! "$model_size" == "4265380512" ]; then
fail "The downloaded model file was invalid! Bytes downloaded: $model_size"
fi
else
fail "Error downloading the data files (weights) for Stable Diffusion"
fi
fi
if [ -f "../models/gfpgan/GFPGANv1.3.pth" ]; then
model_size=`find "../models/gfpgan/GFPGANv1.3.pth" -printf "%s"`
if [ "$model_size" -eq "348632874" ]; then
echo "Data files (weights) necessary for GFPGAN (Face Correction) were already downloaded"
else
printf "\n\nThe model file present at models/gfpgan/GFPGANv1.3.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
rm ../models/gfpgan/GFPGANv1.3.pth
fi
fi
if [ ! -f "../models/gfpgan/GFPGANv1.3.pth" ]; then
echo "Downloading data files (weights) for GFPGAN (Face Correction).."
curl -L -k https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth > ../models/gfpgan/GFPGANv1.3.pth
if [ -f "../models/gfpgan/GFPGANv1.3.pth" ]; then
model_size=`find "../models/gfpgan/GFPGANv1.3.pth" -printf "%s"`
if [ ! "$model_size" -eq "348632874" ]; then
fail "The downloaded GFPGAN model file was invalid! Bytes downloaded: $model_size"
fi
else
fail "Error downloading the data files (weights) for GFPGAN (Face Correction)."
fi
fi
if [ -f "../models/realesrgan/RealESRGAN_x4plus.pth" ]; then
model_size=`find "../models/realesrgan/RealESRGAN_x4plus.pth" -printf "%s"`
if [ "$model_size" -eq "67040989" ]; then
echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus were already downloaded"
else
printf "\n\nThe model file present at models/realesrgan/RealESRGAN_x4plus.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
rm ../models/realesrgan/RealESRGAN_x4plus.pth
fi
fi
if [ ! -f "../models/realesrgan/RealESRGAN_x4plus.pth" ]; then
echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.."
curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth > ../models/realesrgan/RealESRGAN_x4plus.pth
if [ -f "../models/realesrgan/RealESRGAN_x4plus.pth" ]; then
model_size=`find "../models/realesrgan/RealESRGAN_x4plus.pth" -printf "%s"`
if [ ! "$model_size" -eq "67040989" ]; then
fail "The downloaded ESRGAN x4plus model file was invalid! Bytes downloaded: $model_size"
fi
else
fail "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus"
fi
fi
if [ -f "../models/realesrgan/RealESRGAN_x4plus_anime_6B.pth" ]; then
model_size=`find "../models/realesrgan/RealESRGAN_x4plus_anime_6B.pth" -printf "%s"`
if [ "$model_size" -eq "17938799" ]; then
echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus_anime were already downloaded"
else
printf "\n\nThe model file present at models/realesrgan/RealESRGAN_x4plus_anime_6B.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
rm ../models/realesrgan/RealESRGAN_x4plus_anime_6B.pth
fi
fi
if [ ! -f "../models/realesrgan/RealESRGAN_x4plus_anime_6B.pth" ]; then
echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.."
curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth > ../models/realesrgan/RealESRGAN_x4plus_anime_6B.pth
if [ -f "../models/realesrgan/RealESRGAN_x4plus_anime_6B.pth" ]; then
model_size=`find "../models/realesrgan/RealESRGAN_x4plus_anime_6B.pth" -printf "%s"`
if [ ! "$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: $model_size\n\n"
printf "\n\nError downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
else
printf "\n\nError downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
fi
if [ `grep -c sd_install_complete ../scripts/install_status.txt` -gt "0" ]; then
@ -55,11 +280,10 @@ if [ `grep -c sd_install_complete ../scripts/install_status.txt` -gt "0" ]; then
echo sd_install_complete >> ../scripts/install_status.txt
fi
printf "\n\nEasy Diffusion installation complete, starting the server!\n\n"
printf "\n\nStable Diffusion is ready!\n\n"
SD_PATH=`pwd`
export PYTORCH_ENABLE_MPS_FALLBACK=1
export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
echo "PYTHONPATH=$PYTHONPATH"
@ -68,17 +292,8 @@ python --version
cd ..
export SD_UI_PATH=`pwd`/ui
export ED_BIND_PORT="$( python scripts/get_config.py --default=9000 net listen_port )"
case "$( python scripts/get_config.py --default=False net listen_to_network )" in
"True")
export ED_BIND_IP=0.0.0.0
;;
"False")
export ED_BIND_IP=127.0.0.1
;;
esac
cd stable-diffusion
uvicorn main:server_api --app-dir "$SD_UI_PATH" --port "$ED_BIND_PORT" --host "$ED_BIND_IP" --log-level error
uvicorn main:server_api --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0} --log-level error
read -p "Press any key to continue"

View File

@ -2,24 +2,6 @@
cd "$(dirname "${BASH_SOURCE[0]}")"
if [ -f "on_sd_start.bat" ]; then
echo ================================================================================
echo
echo !!!! WARNING !!!!
echo
echo It looks like you\'re trying to run the installation script from a source code
echo download. This will not work.
echo
echo Recommended: Please close this window and download the installer from
echo https://stable-diffusion-ui.github.io/docs/installation/
echo
echo ================================================================================
echo
read
exit 1
fi
# set legacy installer's PATH, if it exists
if [ -e "installer" ]; then export PATH="$(pwd)/installer/bin:$PATH"; fi

View File

@ -1,205 +1,152 @@
import json
import logging
import os
import socket
import sys
import json
import traceback
import urllib
import warnings
import logging
from rich.logging import RichHandler
from sdkit.utils import log as sdkit_log # hack, so we can overwrite the log config
from easydiffusion import task_manager
from easydiffusion.utils import log
from rich.logging import RichHandler
from rich.console import Console
from rich.panel import Panel
from sdkit.utils import log as sdkit_log # hack, so we can overwrite the log config
# Remove all handlers associated with the root logger object.
for handler in logging.root.handlers[:]:
logging.root.removeHandler(handler)
LOG_FORMAT = "%(asctime)s.%(msecs)03d %(levelname)s %(threadName)s %(message)s"
LOG_FORMAT = '%(asctime)s.%(msecs)03d %(levelname)s %(threadName)s %(message)s'
logging.basicConfig(
level=logging.INFO,
format=LOG_FORMAT,
datefmt="%X",
handlers=[RichHandler(markup=True, rich_tracebacks=False, show_time=False, show_level=False)],
level=logging.INFO,
format=LOG_FORMAT,
datefmt="%X",
handlers=[RichHandler(markup=True, rich_tracebacks=True, show_time=False, show_level=False)]
)
SD_DIR = os.getcwd()
SD_UI_DIR = os.getenv("SD_UI_PATH", None)
CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, "..", "scripts"))
MODELS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "models"))
USER_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "plugins"))
CORE_PLUGINS_DIR = os.path.abspath(os.path.join(SD_UI_DIR, "plugins"))
USER_UI_PLUGINS_DIR = os.path.join(USER_PLUGINS_DIR, "ui")
CORE_UI_PLUGINS_DIR = os.path.join(CORE_PLUGINS_DIR, "ui")
USER_SERVER_PLUGINS_DIR = os.path.join(USER_PLUGINS_DIR, "server")
UI_PLUGINS_SOURCES = ((CORE_UI_PLUGINS_DIR, "core"), (USER_UI_PLUGINS_DIR, "user"))
SD_UI_DIR = os.getenv('SD_UI_PATH', None)
sys.path.append(os.path.dirname(SD_UI_DIR))
sys.path.append(USER_SERVER_PLUGINS_DIR)
OUTPUT_DIRNAME = "Stable Diffusion UI" # in the user's home folder
PRESERVE_CONFIG_VARS = ["FORCE_FULL_PRECISION"]
TASK_TTL = 15 * 60 # Discard last session's task timeout
CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, '..', 'scripts'))
MODELS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'models'))
USER_UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'plugins', 'ui'))
CORE_UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_UI_DIR, 'plugins', 'ui'))
UI_PLUGINS_SOURCES = ((CORE_UI_PLUGINS_DIR, 'core'), (USER_UI_PLUGINS_DIR, 'user'))
OUTPUT_DIRNAME = "Stable Diffusion UI" # in the user's home folder
TASK_TTL = 15 * 60 # Discard last session's task timeout
APP_CONFIG_DEFAULTS = {
# auto: selects the cuda device with the most free memory, cuda: use the currently active cuda device.
"render_devices": "auto", # valid entries: 'auto', 'cpu' or 'cuda:N' (where N is a GPU index)
"update_branch": "main",
"ui": {
"open_browser_on_start": True,
'render_devices': 'auto', # valid entries: 'auto', 'cpu' or 'cuda:N' (where N is a GPU index)
'update_branch': 'main',
'ui': {
'open_browser_on_start': True,
},
}
IMAGE_EXTENSIONS = [
".png",
".apng",
".jpg",
".jpeg",
".jfif",
".pjpeg",
".pjp",
".jxl",
".gif",
".webp",
".avif",
".svg",
]
CUSTOM_MODIFIERS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "modifiers"))
CUSTOM_MODIFIERS_PORTRAIT_EXTENSIONS = [
".portrait",
"_portrait",
" portrait",
"-portrait",
]
CUSTOM_MODIFIERS_LANDSCAPE_EXTENSIONS = [
".landscape",
"_landscape",
" landscape",
"-landscape",
]
def init():
os.makedirs(USER_UI_PLUGINS_DIR, exist_ok=True)
os.makedirs(USER_SERVER_PLUGINS_DIR, exist_ok=True)
# https://pytorch.org/docs/stable/storage.html
warnings.filterwarnings("ignore", category=UserWarning, message="TypedStorage is deprecated")
load_server_plugins()
update_render_threads()
def getConfig(default_val=APP_CONFIG_DEFAULTS):
try:
config_json_path = os.path.join(CONFIG_DIR, "config.json")
config_json_path = os.path.join(CONFIG_DIR, 'config.json')
if not os.path.exists(config_json_path):
config = default_val
else:
with open(config_json_path, "r", encoding="utf-8") as f:
config = json.load(f)
if "net" not in config:
config["net"] = {}
if os.getenv("SD_UI_BIND_PORT") is not None:
config["net"]["listen_port"] = int(os.getenv("SD_UI_BIND_PORT"))
if os.getenv("SD_UI_BIND_IP") is not None:
config["net"]["listen_to_network"] = os.getenv("SD_UI_BIND_IP") == "0.0.0.0"
return config
except Exception:
return default_val
with open(config_json_path, 'r', encoding='utf-8') as f:
config = json.load(f)
if 'net' not in config:
config['net'] = {}
if os.getenv('SD_UI_BIND_PORT') is not None:
config['net']['listen_port'] = int(os.getenv('SD_UI_BIND_PORT'))
if os.getenv('SD_UI_BIND_IP') is not None:
config['net']['listen_to_network'] = (os.getenv('SD_UI_BIND_IP') == '0.0.0.0')
return config
except Exception as e:
log.warn(traceback.format_exc())
return default_val
def setConfig(config):
try: # config.json
config_json_path = os.path.join(CONFIG_DIR, "config.json")
with open(config_json_path, "w", encoding="utf-8") as f:
try: # config.json
config_json_path = os.path.join(CONFIG_DIR, 'config.json')
with open(config_json_path, 'w', encoding='utf-8') as f:
json.dump(config, f)
except:
log.error(traceback.format_exc())
try: # config.bat
config_bat_path = os.path.join(CONFIG_DIR, 'config.bat')
config_bat = []
if 'update_branch' in config:
config_bat.append(f"@set update_branch={config['update_branch']}")
config_bat.append(f"@set SD_UI_BIND_PORT={config['net']['listen_port']}")
bind_ip = '0.0.0.0' if config['net']['listen_to_network'] else '127.0.0.1'
config_bat.append(f"@set SD_UI_BIND_IP={bind_ip}")
if len(config_bat) > 0:
with open(config_bat_path, 'w', encoding='utf-8') as f:
f.write('\r\n'.join(config_bat))
except:
log.error(traceback.format_exc())
try: # config.sh
config_sh_path = os.path.join(CONFIG_DIR, 'config.sh')
config_sh = ['#!/bin/bash']
if 'update_branch' in config:
config_sh.append(f"export update_branch={config['update_branch']}")
config_sh.append(f"export SD_UI_BIND_PORT={config['net']['listen_port']}")
bind_ip = '0.0.0.0' if config['net']['listen_to_network'] else '127.0.0.1'
config_sh.append(f"export SD_UI_BIND_IP={bind_ip}")
if len(config_sh) > 1:
with open(config_sh_path, 'w', encoding='utf-8') as f:
f.write('\n'.join(config_sh))
except:
log.error(traceback.format_exc())
def save_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name, vram_usage_level):
config = getConfig()
if "model" not in config:
config["model"] = {}
if 'model' not in config:
config['model'] = {}
config["model"]["stable-diffusion"] = ckpt_model_name
config["model"]["vae"] = vae_model_name
config["model"]["hypernetwork"] = hypernetwork_model_name
config['model']['stable-diffusion'] = ckpt_model_name
config['model']['vae'] = vae_model_name
config['model']['hypernetwork'] = hypernetwork_model_name
if vae_model_name is None or vae_model_name == "":
del config["model"]["vae"]
del config['model']['vae']
if hypernetwork_model_name is None or hypernetwork_model_name == "":
del config["model"]["hypernetwork"]
del config['model']['hypernetwork']
config["vram_usage_level"] = vram_usage_level
config['vram_usage_level'] = vram_usage_level
setConfig(config)
def update_render_threads():
config = getConfig()
render_devices = config.get("render_devices", "auto")
active_devices = task_manager.get_devices()["active"].keys()
render_devices = config.get('render_devices', 'auto')
active_devices = task_manager.get_devices()['active'].keys()
log.debug(f"requesting for render_devices: {render_devices}")
log.debug(f'requesting for render_devices: {render_devices}')
task_manager.update_render_threads(render_devices, active_devices)
def getUIPlugins():
plugins = []
for plugins_dir, dir_prefix in UI_PLUGINS_SOURCES:
for file in os.listdir(plugins_dir):
if file.endswith(".plugin.js"):
plugins.append(f"/plugins/{dir_prefix}/{file}")
if file.endswith('.plugin.js'):
plugins.append(f'/plugins/{dir_prefix}/{file}')
return plugins
def load_server_plugins():
if not os.path.exists(USER_SERVER_PLUGINS_DIR):
return
import importlib
def load_plugin(file):
mod_path = file.replace(".py", "")
return importlib.import_module(mod_path)
def apply_plugin(file, plugin):
if hasattr(plugin, "get_cond_and_uncond"):
import sdkit.generate.image_generator
sdkit.generate.image_generator.get_cond_and_uncond = plugin.get_cond_and_uncond
log.info(f"Overridden get_cond_and_uncond with the one in the server plugin: {file}")
for file in os.listdir(USER_SERVER_PLUGINS_DIR):
file_path = os.path.join(USER_SERVER_PLUGINS_DIR, file)
if (not os.path.isdir(file_path) and not file_path.endswith("_plugin.py")) or (
os.path.isdir(file_path) and not file_path.endswith("_plugin")
):
continue
try:
log.info(f"Loading server plugin: {file}")
mod = load_plugin(file)
log.info(f"Applying server plugin: {file}")
apply_plugin(file, mod)
except:
log.warn(f"Error while loading a server plugin")
log.warn(traceback.format_exc())
def getIPConfig():
try:
ips = socket.gethostbyname_ex(socket.gethostname())
@ -209,153 +156,10 @@ def getIPConfig():
log.exception(e)
return []
def open_browser():
config = getConfig()
ui = config.get("ui", {})
net = config.get("net", {})
port = net.get("listen_port", 9000)
if ui.get("open_browser_on_start", True):
import webbrowser
webbrowser.open(f"http://localhost:{port}")
Console().print(
Panel(
"\n"
+ "[white]Easy Diffusion is ready to serve requests.\n\n"
+ "A new browser tab should have been opened by now.\n"
+ f"If not, please open your web browser and navigate to [bold yellow underline]http://localhost:{port}/\n",
title="Easy Diffusion is ready",
style="bold yellow on blue",
)
)
def fail_and_die(fail_type: str, data: str):
suggestions = [
"Run this installer again.",
"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",
"If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues",
]
if fail_type == "model_download":
fail_label = f"Error downloading the {data} model"
suggestions.insert(
1,
"If that doesn't fix it, please try to download the file manually. The address to download from, and the destination to save to are printed above this message.",
)
else:
fail_label = "Error while installing Easy Diffusion"
msg = [f"{fail_label}. Sorry about that, please try to:"]
for i, suggestion in enumerate(suggestions):
msg.append(f"{i+1}. {suggestion}")
msg.append("Thanks!")
print("\n".join(msg))
exit(1)
def get_image_modifiers():
modifiers_json_path = os.path.join(SD_UI_DIR, "modifiers.json")
modifier_categories = {}
original_category_order = []
with open(modifiers_json_path, "r", encoding="utf-8") as f:
modifiers_file = json.load(f)
# The trailing slash is needed to support symlinks
if not os.path.isdir(f"{CUSTOM_MODIFIERS_DIR}/"):
return modifiers_file
# convert modifiers from a list of objects to a dict of dicts
for category_item in modifiers_file:
category_name = category_item["category"]
original_category_order.append(category_name)
category = {}
for modifier_item in category_item["modifiers"]:
modifier = {}
for preview_item in modifier_item["previews"]:
modifier[preview_item["name"]] = preview_item["path"]
category[modifier_item["modifier"]] = modifier
modifier_categories[category_name] = category
def scan_directory(directory_path: str, category_name="Modifiers"):
for entry in os.scandir(directory_path):
if entry.is_file():
file_extension = list(filter(lambda e: entry.name.endswith(e), IMAGE_EXTENSIONS))
if len(file_extension) == 0:
continue
modifier_name = entry.name[: -len(file_extension[0])]
modifier_path = f"custom/{entry.path[len(CUSTOM_MODIFIERS_DIR) + 1:]}"
# URL encode path segments
modifier_path = "/".join(
map(
lambda segment: urllib.parse.quote(segment),
modifier_path.split("/"),
)
)
is_portrait = True
is_landscape = True
portrait_extension = list(
filter(
lambda e: modifier_name.lower().endswith(e),
CUSTOM_MODIFIERS_PORTRAIT_EXTENSIONS,
)
)
landscape_extension = list(
filter(
lambda e: modifier_name.lower().endswith(e),
CUSTOM_MODIFIERS_LANDSCAPE_EXTENSIONS,
)
)
if len(portrait_extension) > 0:
is_landscape = False
modifier_name = modifier_name[: -len(portrait_extension[0])]
elif len(landscape_extension) > 0:
is_portrait = False
modifier_name = modifier_name[: -len(landscape_extension[0])]
if category_name not in modifier_categories:
modifier_categories[category_name] = {}
category = modifier_categories[category_name]
if modifier_name not in category:
category[modifier_name] = {}
if is_portrait or "portrait" not in category[modifier_name]:
category[modifier_name]["portrait"] = modifier_path
if is_landscape or "landscape" not in category[modifier_name]:
category[modifier_name]["landscape"] = modifier_path
elif entry.is_dir():
scan_directory(
entry.path,
entry.name if directory_path == CUSTOM_MODIFIERS_DIR else f"{category_name}/{entry.name}",
)
scan_directory(CUSTOM_MODIFIERS_DIR)
custom_categories = sorted(
[cn for cn in modifier_categories.keys() if cn not in original_category_order],
key=str.casefold,
)
# convert the modifiers back into a list of objects
modifier_categories_list = []
for category_name in [*original_category_order, *custom_categories]:
category = {"category": category_name, "modifiers": []}
for modifier_name in sorted(modifier_categories[category_name].keys(), key=str.casefold):
modifier = {"modifier": modifier_name, "previews": []}
for preview_name, preview_path in modifier_categories[category_name][modifier_name].items():
modifier["previews"].append({"name": preview_name, "path": preview_path})
category["modifiers"].append(modifier)
modifier_categories_list.append(category)
return modifier_categories_list
ui = config.get('ui', {})
net = config.get('net', {'listen_port':9000})
port = net.get('listen_port', 9000)
if ui.get('open_browser_on_start', True):
import webbrowser; webbrowser.open(f"http://localhost:{port}")

View File

@ -1,59 +1,49 @@
import os
import platform
import re
import traceback
import torch
import traceback
import re
from easydiffusion.utils import log
"""
'''
Set `FORCE_FULL_PRECISION` in the environment variables, or in `config.bat`/`config.sh` to set full precision (i.e. float32).
Otherwise the models will load at half-precision (i.e. float16).
Half-precision is fine most of the time. Full precision is only needed for working around GPU bugs (like NVIDIA 16xx GPUs).
"""
'''
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
)
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 'mps' or ['cuda:N'...]
active_devices: ['cpu', 'mps', 'cuda:N'...]
"""
'''
render_devices: 'cpu', or 'auto' or ['cuda:N'...]
active_devices: ['cpu', 'cuda:N'...]
'''
if render_devices in ("cpu", "auto", "mps"):
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:") or x == "mps", render_devices))
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": "mps"} or {"render_devices": "auto"}'
)
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"
)
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"}'
)
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"]
render_devices = ['auto']
if "auto" in render_devices:
if 'auto' in render_devices:
render_devices = auto_pick_devices(active_devices)
if "cpu" in render_devices:
log.warn("WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!")
if 'cpu' in render_devices:
log.warn('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)
@ -63,37 +53,19 @@ def get_device_delta(render_devices, active_devices):
return devices_to_start, devices_to_stop
def is_mps_available():
return (
platform.system() == "Darwin"
and hasattr(torch.backends, "mps")
and torch.backends.mps.is_available()
and torch.backends.mps.is_built()
)
def is_cuda_available():
return torch.cuda.is_available()
def auto_pick_devices(currently_active_devices):
global mem_free_threshold
if is_mps_available():
return ["mps"]
if not is_cuda_available():
return ["cpu"]
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"]
return ['cuda:0'] if is_device_compatible('cuda:0') else ['cpu']
log.debug("Autoselecting GPU. Using most free memory.")
log.debug('Autoselecting GPU. Using most free memory.')
devices = []
for device in range(device_count):
device = f"cuda:{device}"
device = f'cuda:{device}'
if not is_device_compatible(device):
continue
@ -101,13 +73,11 @@ def auto_pick_devices(currently_active_devices):
mem_free /= float(10**9)
mem_total /= float(10**9)
device_name = torch.cuda.get_device_name(device)
log.debug(
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})
log.debug(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"]
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)
@ -117,29 +87,23 @@ def auto_pick_devices(currently_active_devices):
# 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))
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(context, 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")
validate_device_id(device, log_prefix='device_init')
if "cuda" not in device:
context.device = device
if device == 'cpu':
context.device = 'cpu'
context.device_name = get_processor_name()
context.half_precision = False
log.debug(f"Render device available as {context.device_name}")
log.debug(f'Render device CPU available as {context.device_name}')
return
context.device_name = torch.cuda.get_device_name(device)
@ -147,105 +111,83 @@ def device_init(context, device):
# Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
if needs_to_force_full_precision(context):
log.warn(f"forcing full precision on this GPU, to avoid green images. GPU detected: {context.device_name}")
log.warn(f'forcing full precision on this GPU, to avoid green images. GPU detected: {context.device_name}')
# Apply force_full_precision now before models are loaded.
context.half_precision = False
log.info(f'Setting {device} as active, with precision: {"half" if context.half_precision else "full"}')
torch.cuda.device(device)
return
def needs_to_force_full_precision(context):
if "FORCE_FULL_PRECISION" in os.environ:
if 'FORCE_FULL_PRECISION' in os.environ:
return True
device_name = context.device_name.lower()
return (
("nvidia" in device_name or "geforce" in device_name or "quadro" in device_name)
and (
" 1660" in device_name
or " 1650" in device_name
or " 1630" in device_name
or " t400" in device_name
or " t550" in device_name
or " t600" in device_name
or " t1000" in device_name
or " t1200" in device_name
or " t2000" in device_name
)
) or ("tesla k40m" in device_name)
return (('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name or ' t400' in device_name or ' t550' in device_name or ' t1200' in device_name)) or ('Quadro T2000' in device_name)
def get_max_vram_usage_level(device):
if "cuda" in device:
if device != 'cpu':
_, mem_total = torch.cuda.mem_get_info(device)
else:
return "high"
mem_total /= float(10**9)
mem_total /= float(10**9)
if mem_total < 4.5:
return "low"
elif mem_total < 6.5:
return "balanced"
if mem_total < 4.5:
return 'low'
elif mem_total < 6.5:
return 'balanced'
return "high"
return 'high'
def validate_device_id(device, log_prefix=""):
def validate_device_id(device, log_prefix=''):
def is_valid():
if not isinstance(device, str):
return False
if device == "cpu" or device == "mps":
if device == 'cpu':
return True
if not device.startswith("cuda:") or not device[5:].isnumeric():
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', 'mps', or 'cuda:N' (where N is an integer index for the GPU). Got: {device}"
)
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
"""
# static variable "history".
is_device_compatible.history = getattr(is_device_compatible, "history", {})
'''
# static variable "history".
is_device_compatible.history = getattr(is_device_compatible, 'history', {})
try:
validate_device_id(device, log_prefix="is_device_compatible")
validate_device_id(device, log_prefix='is_device_compatible')
except:
log.error(str(e))
return False
if device in ("cpu", "mps"):
return True
if device == 'cpu': return True
# Memory check
try:
_, mem_total = torch.cuda.mem_get_info(device)
mem_total /= float(10**9)
if mem_total < 1.9:
if mem_total < 3.0:
if is_device_compatible.history.get(device) == None:
log.warn(f"GPU {device} with less than 2 GB of VRAM is not compatible with Stable Diffusion")
is_device_compatible.history[device] = 1
log.warn(f'GPU {device} with less than 3 GB of VRAM is not compatible with Stable Diffusion')
is_device_compatible.history[device] = 1
return False
except RuntimeError as e:
log.error(str(e))
return False
return True
def get_processor_name():
try:
import subprocess
import platform, subprocess
if platform.system() == "Windows":
return platform.processor()
elif platform.system() == "Darwin":
os.environ["PATH"] = os.environ["PATH"] + os.pathsep + "/usr/sbin"
os.environ['PATH'] = os.environ['PATH'] + os.pathsep + '/usr/sbin'
command = "sysctl -n machdep.cpu.brand_string"
return subprocess.check_output(command, shell=True).decode().strip()
return subprocess.check_output(command).strip()
elif platform.system() == "Linux":
command = "cat /proc/cpuinfo"
all_info = subprocess.check_output(command, shell=True).decode().strip()

View File

@ -1,232 +1,132 @@
import os
import shutil
from glob import glob
import traceback
from easydiffusion import app
from easydiffusion import app, device_manager
from easydiffusion.types import TaskData
from easydiffusion.utils import log
from sdkit import Context
from sdkit.models import load_model, scan_model, unload_model, download_model, get_model_info_from_db
from sdkit.models import load_model, unload_model, get_model_info_from_db, scan_model
from sdkit.utils import hash_file_quick
KNOWN_MODEL_TYPES = [
"stable-diffusion",
"vae",
"hypernetwork",
"gfpgan",
"realesrgan",
"lora",
"codeformer",
]
KNOWN_MODEL_TYPES = ['stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan']
MODEL_EXTENSIONS = {
"stable-diffusion": [".ckpt", ".safetensors"],
"vae": [".vae.pt", ".ckpt", ".safetensors"],
"hypernetwork": [".pt", ".safetensors"],
"gfpgan": [".pth"],
"realesrgan": [".pth"],
"lora": [".ckpt", ".safetensors"],
"codeformer": [".pth"],
'stable-diffusion': ['.ckpt', '.safetensors'],
'vae': ['.vae.pt', '.ckpt', '.safetensors'],
'hypernetwork': ['.pt', '.safetensors'],
'gfpgan': ['.pth'],
'realesrgan': ['.pth'],
}
DEFAULT_MODELS = {
"stable-diffusion": [
{"file_name": "sd-v1-4.ckpt", "model_id": "1.4"},
],
"gfpgan": [
{"file_name": "GFPGANv1.4.pth", "model_id": "1.4"},
],
"realesrgan": [
{"file_name": "RealESRGAN_x4plus.pth", "model_id": "x4plus"},
{"file_name": "RealESRGAN_x4plus_anime_6B.pth", "model_id": "x4plus_anime_6"},
],
"vae": [
{"file_name": "vae-ft-mse-840000-ema-pruned.ckpt", "model_id": "vae-ft-mse-840000-ema-pruned"},
'stable-diffusion': [ # needed to support the legacy installations
'custom-model', # only one custom model file was supported initially, creatively named 'custom-model'
'sd-v1-4', # Default fallback.
],
'gfpgan': ['GFPGANv1.3'],
'realesrgan': ['RealESRGAN_x4plus'],
}
MODELS_TO_LOAD_ON_START = ["stable-diffusion", "vae", "hypernetwork", "lora"]
MODELS_TO_LOAD_ON_START = ['stable-diffusion', 'vae', 'hypernetwork']
known_models = {}
def init():
make_model_folders()
migrate_legacy_model_location() # if necessary
download_default_models_if_necessary()
getModels() # run this once, to cache the picklescan results
getModels() # run this once, to cache the picklescan results
def load_default_models(context: Context):
set_vram_optimizations(context)
# init default model paths
for model_type in MODELS_TO_LOAD_ON_START:
context.model_paths[model_type] = resolve_model_to_use(model_type=model_type, fail_if_not_found=False)
context.model_paths[model_type] = resolve_model_to_use(model_type=model_type)
try:
load_model(
context,
model_type,
scan_model=context.model_paths[model_type] != None
and not context.model_paths[model_type].endswith(".safetensors"),
)
if model_type in context.model_load_errors:
del context.model_load_errors[model_type]
load_model(context, model_type)
except Exception as e:
log.error(f"[red]Error while loading {model_type} model: {context.model_paths[model_type]}[/red]")
if "DefaultCPUAllocator: not enough memory" in str(e):
log.error(
f"[red]Your PC is low on system RAM. Please add some virtual memory (or swap space) by following the instructions at this link: https://www.ibm.com/docs/en/opw/8.2.0?topic=tuning-optional-increasing-paging-file-size-windows-computers[/red]"
)
else:
log.exception(e)
del context.model_paths[model_type]
context.model_load_errors[model_type] = str(e) # storing the entire Exception can lead to memory leaks
log.error(f'[red]Error while loading {model_type} model: {context.model_paths[model_type]}[/red]')
log.error(f'[red]Error: {e}[/red]')
log.error(f'[red]Consider to remove the model from the model folder.[red]')
def unload_all(context: Context):
for model_type in KNOWN_MODEL_TYPES:
unload_model(context, model_type)
if model_type in context.model_load_errors:
del context.model_load_errors[model_type]
def resolve_model_to_use(model_name: str = None, model_type: str = None, fail_if_not_found: bool = True):
def resolve_model_to_use(model_name:str=None, model_type:str=None):
model_extensions = MODEL_EXTENSIONS.get(model_type, [])
default_models = DEFAULT_MODELS.get(model_type, [])
config = app.getConfig()
model_dir = os.path.join(app.MODELS_DIR, model_type)
if not model_name: # When None try user configured model.
model_dirs = [os.path.join(app.MODELS_DIR, model_type), app.SD_DIR]
if not model_name: # When None try user configured model.
# config = getConfig()
if "model" in config and model_type in config["model"]:
model_name = config["model"][model_type]
if 'model' in config and model_type in config['model']:
model_name = config['model'][model_type]
if model_name:
# Check models directory
model_path = os.path.join(model_dir, model_name)
if os.path.exists(model_path):
return model_path
models_dir_path = os.path.join(app.MODELS_DIR, model_type, model_name)
for model_extension in model_extensions:
if os.path.exists(model_path + model_extension):
return model_path + model_extension
if os.path.exists(models_dir_path + model_extension):
return models_dir_path + model_extension
if os.path.exists(model_name + model_extension):
return os.path.abspath(model_name + model_extension)
# Default locations
if model_name in default_models:
default_model_path = os.path.join(app.SD_DIR, model_name)
for model_extension in model_extensions:
if os.path.exists(default_model_path + model_extension):
return default_model_path + model_extension
# Can't find requested model, check the default paths.
if model_type == "stable-diffusion" and not fail_if_not_found:
for default_model in default_models:
default_model_path = os.path.join(model_dir, default_model["file_name"])
if os.path.exists(default_model_path):
if model_name is not None:
log.warn(
f"Could not find the configured custom model {model_name}. Using the default one: {default_model_path}"
)
return default_model_path
if model_name and fail_if_not_found:
raise Exception(f"Could not find the desired model {model_name}! Is it present in the {model_dir} folder?")
for default_model in default_models:
for model_dir in model_dirs:
default_model_path = os.path.join(model_dir, default_model)
for model_extension in model_extensions:
if os.path.exists(default_model_path + model_extension):
if model_name is not None:
log.warn(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
return default_model_path + model_extension
return None
def reload_models_if_necessary(context: Context, task_data: TaskData):
face_fix_lower = task_data.use_face_correction.lower() if task_data.use_face_correction else ""
upscale_lower = task_data.use_upscale.lower() if task_data.use_upscale else ""
model_paths_in_req = {
"stable-diffusion": task_data.use_stable_diffusion_model,
"vae": task_data.use_vae_model,
"hypernetwork": task_data.use_hypernetwork_model,
"codeformer": task_data.use_face_correction if "codeformer" in face_fix_lower else None,
"gfpgan": task_data.use_face_correction if "gfpgan" in face_fix_lower else None,
"realesrgan": task_data.use_upscale if "realesrgan" in upscale_lower else None,
"latent_upscaler": True if "latent_upscaler" in upscale_lower else None,
"nsfw_checker": True if task_data.block_nsfw else None,
"lora": task_data.use_lora_model,
}
models_to_reload = {
model_type: path
for model_type, path in model_paths_in_req.items()
if context.model_paths.get(model_type) != path
'stable-diffusion': task_data.use_stable_diffusion_model,
'vae': task_data.use_vae_model,
'hypernetwork': task_data.use_hypernetwork_model,
'gfpgan': task_data.use_face_correction,
'realesrgan': task_data.use_upscale,
}
models_to_reload = {model_type: path for model_type, path in model_paths_in_req.items() if context.model_paths.get(model_type) != path}
if task_data.codeformer_upscale_faces:
if "realesrgan" not in models_to_reload and "realesrgan" not in context.models:
default_realesrgan = DEFAULT_MODELS["realesrgan"][0]["file_name"]
models_to_reload["realesrgan"] = resolve_model_to_use(default_realesrgan, "realesrgan")
elif "realesrgan" in models_to_reload and models_to_reload["realesrgan"] is None:
del models_to_reload["realesrgan"] # don't unload realesrgan
if set_vram_optimizations(context) or set_clip_skip(context, task_data): # reload SD
models_to_reload["stable-diffusion"] = model_paths_in_req["stable-diffusion"]
if set_vram_optimizations(context): # reload SD
models_to_reload['stable-diffusion'] = model_paths_in_req['stable-diffusion']
for model_type, model_path_in_req in models_to_reload.items():
context.model_paths[model_type] = model_path_in_req
action_fn = unload_model if context.model_paths[model_type] is None else load_model
try:
action_fn(context, model_type, scan_model=False) # we've scanned them already
if model_type in context.model_load_errors:
del context.model_load_errors[model_type]
except Exception as e:
log.exception(e)
if action_fn == load_model:
context.model_load_errors[model_type] = str(e) # storing the entire Exception can lead to memory leaks
action_fn(context, model_type, scan_model=False) # we've scanned them already
def resolve_model_paths(task_data: TaskData):
task_data.use_stable_diffusion_model = resolve_model_to_use(
task_data.use_stable_diffusion_model, model_type="stable-diffusion"
)
task_data.use_vae_model = resolve_model_to_use(task_data.use_vae_model, model_type="vae")
task_data.use_hypernetwork_model = resolve_model_to_use(task_data.use_hypernetwork_model, model_type="hypernetwork")
task_data.use_lora_model = resolve_model_to_use(task_data.use_lora_model, model_type="lora")
if task_data.use_face_correction:
if "gfpgan" in task_data.use_face_correction.lower():
model_type = "gfpgan"
elif "codeformer" in task_data.use_face_correction.lower():
model_type = "codeformer"
download_if_necessary("codeformer", "codeformer.pth", "codeformer-0.1.0")
task_data.use_face_correction = resolve_model_to_use(task_data.use_face_correction, model_type)
if task_data.use_upscale and "realesrgan" in task_data.use_upscale.lower():
task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, "realesrgan")
def fail_if_models_did_not_load(context: Context):
for model_type in KNOWN_MODEL_TYPES:
if model_type in context.model_load_errors:
e = context.model_load_errors[model_type]
raise Exception(f"Could not load the {model_type} model! Reason: " + e)
def download_default_models_if_necessary():
for model_type, models in DEFAULT_MODELS.items():
for model in models:
try:
download_if_necessary(model_type, model["file_name"], model["model_id"])
except:
traceback.print_exc()
app.fail_and_die(fail_type="model_download", data=model_type)
print(model_type, "model(s) found.")
def download_if_necessary(model_type: str, file_name: str, model_id: str):
model_path = os.path.join(app.MODELS_DIR, model_type, file_name)
expected_hash = get_model_info_from_db(model_type=model_type, model_id=model_id)["quick_hash"]
other_models_exist = any_model_exists(model_type)
known_model_exists = os.path.exists(model_path)
known_model_is_corrupt = known_model_exists and hash_file_quick(model_path) != expected_hash
if known_model_is_corrupt or (not other_models_exist and not known_model_exists):
print("> download", model_type, model_id)
download_model(model_type, model_id, download_base_dir=app.MODELS_DIR)
task_data.use_stable_diffusion_model = resolve_model_to_use(task_data.use_stable_diffusion_model, model_type='stable-diffusion')
task_data.use_vae_model = resolve_model_to_use(task_data.use_vae_model, model_type='vae')
task_data.use_hypernetwork_model = resolve_model_to_use(task_data.use_hypernetwork_model, model_type='hypernetwork')
if task_data.use_face_correction: task_data.use_face_correction = resolve_model_to_use(task_data.use_face_correction, 'gfpgan')
if task_data.use_upscale: task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, 'realesrgan')
def set_vram_optimizations(context: Context):
config = app.getConfig()
vram_usage_level = config.get("vram_usage_level", "balanced")
max_usage_level = device_manager.get_max_vram_usage_level(context.device)
vram_usage_level = config.get('vram_usage_level', 'balanced')
v = {'low': 0, 'balanced': 1, 'high': 2}
if v[vram_usage_level] > v[max_usage_level]:
log.error(f'Requested GPU Memory Usage level ({vram_usage_level}) is higher than what is ' + \
f'possible ({max_usage_level}) on this device ({context.device}). Using "{max_usage_level}" instead')
vram_usage_level = max_usage_level
if vram_usage_level != context.vram_usage_level:
context.vram_usage_level = vram_usage_level
@ -234,90 +134,42 @@ def set_vram_optimizations(context: Context):
return False
def migrate_legacy_model_location():
'Move the models inside the legacy "stable-diffusion" folder, to their respective folders'
for model_type, models in DEFAULT_MODELS.items():
for model in models:
file_name = model["file_name"]
legacy_path = os.path.join(app.SD_DIR, file_name)
if os.path.exists(legacy_path):
shutil.move(legacy_path, os.path.join(app.MODELS_DIR, model_type, file_name))
def any_model_exists(model_type: str) -> bool:
extensions = MODEL_EXTENSIONS.get(model_type, [])
for ext in extensions:
if any(glob(f"{app.MODELS_DIR}/{model_type}/**/*{ext}", recursive=True)):
return True
return False
def set_clip_skip(context: Context, task_data: TaskData):
clip_skip = task_data.clip_skip
if clip_skip != context.clip_skip:
context.clip_skip = clip_skip
return True
return False
def make_model_folders():
for model_type in KNOWN_MODEL_TYPES:
model_dir_path = os.path.join(app.MODELS_DIR, model_type)
os.makedirs(model_dir_path, exist_ok=True)
help_file_name = f"Place your {model_type} model files here.txt"
help_file_name = f'Place your {model_type} model files here.txt'
help_file_contents = f'Supported extensions: {" or ".join(MODEL_EXTENSIONS.get(model_type))}'
with open(os.path.join(model_dir_path, help_file_name), "w", encoding="utf-8") as f:
with open(os.path.join(model_dir_path, help_file_name), 'w', encoding='utf-8') as f:
f.write(help_file_contents)
def is_malicious_model(file_path):
try:
if file_path.endswith(".safetensors"):
return False
scan_result = scan_model(file_path)
if scan_result.issues_count > 0 or scan_result.infected_files > 0:
log.warn(
":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]"
% (
file_path,
scan_result.scanned_files,
scan_result.issues_count,
scan_result.infected_files,
)
)
log.warn(":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
return True
else:
log.debug(
"Scan %s: [green]%d scanned, %d issue, %d infected.[/green]"
% (
file_path,
scan_result.scanned_files,
scan_result.issues_count,
scan_result.infected_files,
)
)
log.debug("Scan %s: [green]%d scanned, %d issue, %d infected.[/green]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
return False
except Exception as e:
log.error(f"error while scanning: {file_path}, error: {e}")
log.error(f'error while scanning: {file_path}, error: {e}')
return False
def getModels():
models = {
"options": {
"stable-diffusion": ["sd-v1-4"],
"vae": [],
"hypernetwork": [],
"lora": [],
"codeformer": ["codeformer"],
'active': {
'stable-diffusion': 'sd-v1-4',
'vae': '',
'hypernetwork': '',
},
'options': {
'stable-diffusion': ['sd-v1-4'],
'vae': [],
'hypernetwork': [],
},
}
@ -325,18 +177,15 @@ def getModels():
class MaliciousModelException(Exception):
"Raised when picklescan reports a problem with a model"
pass
def scan_directory(directory, suffixes, directoriesFirst: bool = True):
def scan_directory(directory, suffixes):
nonlocal models_scanned
tree = []
for entry in sorted(
os.scandir(directory),
key=lambda entry: (entry.is_file() == directoriesFirst, entry.name.lower()),
):
for entry in os.scandir(directory):
if entry.is_file():
matching_suffix = list(filter(lambda s: entry.name.endswith(s), suffixes))
if len(matching_suffix) == 0:
continue
if len(matching_suffix) == 0: continue
matching_suffix = matching_suffix[0]
mtime = entry.stat().st_mtime
@ -346,12 +195,11 @@ def getModels():
if is_malicious_model(entry.path):
raise MaliciousModelException(entry.path)
known_models[entry.path] = mtime
tree.append(entry.name[: -len(matching_suffix)])
tree.append(entry.name[:-len(matching_suffix)])
elif entry.is_dir():
scan = scan_directory(entry.path, suffixes, directoriesFirst=False)
scan=scan_directory(entry.path, suffixes)
if len(scan) != 0:
tree.append((entry.name, scan))
tree.append( (entry.name, scan ) )
return tree
def listModels(model_type):
@ -363,19 +211,20 @@ def getModels():
os.makedirs(models_dir)
try:
models["options"][model_type] = scan_directory(models_dir, model_extensions)
models['options'][model_type] = scan_directory(models_dir, model_extensions)
except MaliciousModelException as e:
models["scan-error"] = e
models['scan-error'] = e
log.info(f"[green]Scanning all model folders for models...[/]")
# custom models
listModels(model_type="stable-diffusion")
listModels(model_type="vae")
listModels(model_type="hypernetwork")
listModels(model_type="gfpgan")
listModels(model_type="lora")
listModels(model_type='stable-diffusion')
listModels(model_type='vae')
listModels(model_type='hypernetwork')
if models_scanned > 0:
log.info(f"[green]Scanned {models_scanned} models. Nothing infected[/]")
if models_scanned > 0: log.info(f'[green]Scanned {models_scanned} models. Nothing infected[/]')
# legacy
custom_weight_path = os.path.join(app.SD_DIR, 'custom-model.ckpt')
if os.path.exists(custom_weight_path):
models['options']['stable-diffusion'].append('custom-model')
return models

View File

@ -1,105 +1,54 @@
import json
import pprint
import queue
import time
import json
import pprint
from easydiffusion import device_manager
from easydiffusion.types import GenerateImageRequest
from easydiffusion.types import Image as ResponseImage
from easydiffusion.types import Response, TaskData, UserInitiatedStop
from easydiffusion.model_manager import DEFAULT_MODELS, resolve_model_to_use
from easydiffusion.utils import get_printable_request, log, save_images_to_disk
from easydiffusion.types import TaskData, Response, Image as ResponseImage, UserInitiatedStop, GenerateImageRequest
from easydiffusion.utils import get_printable_request, save_images_to_disk, log
from sdkit import Context
from sdkit.filter import apply_filters
from sdkit.generate import generate_images
from sdkit.models import load_model
from sdkit.utils import (
diffusers_latent_samples_to_images,
gc,
img_to_base64_str,
img_to_buffer,
latent_samples_to_images,
get_device_usage,
)
from sdkit.filter import apply_filters
from sdkit.utils import img_to_buffer, img_to_base64_str, latent_samples_to_images, gc
context = Context() # thread-local
"""
context = Context() # thread-local
'''
runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
"""
'''
def init(device):
"""
'''
Initializes the fields that will be bound to this runtime's context, and sets the current torch device
"""
'''
context.stop_processing = False
context.temp_images = {}
context.partial_x_samples = None
context.model_load_errors = {}
context.enable_codeformer = True
from easydiffusion import app
app_config = app.getConfig()
context.test_diffusers = (
app_config.get("test_diffusers", False) and app_config.get("update_branch", "main") != "main"
)
log.info("Device usage during initialization:")
get_device_usage(device, log_info=True, process_usage_only=False)
device_manager.device_init(context, device)
def make_images(
req: GenerateImageRequest,
task_data: TaskData,
data_queue: queue.Queue,
task_temp_images: list,
step_callback,
):
def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
context.stop_processing = False
print_task_info(req, task_data)
images, seeds = make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
res = Response(
req,
task_data,
images=construct_response(images, seeds, task_data, base_seed=req.seed),
)
res = Response(req, task_data, images=construct_response(images, seeds, task_data, base_seed=req.seed))
res = res.json()
data_queue.put(json.dumps(res))
log.info("Task completed")
log.info('Task completed')
return res
def print_task_info(req: GenerateImageRequest, task_data: TaskData):
req_str = pprint.pformat(get_printable_request(req, task_data)).replace("[", "\[")
task_str = pprint.pformat(task_data.dict()).replace("[", "\[")
log.info(f"request: {req_str}")
log.info(f"task data: {task_str}")
req_str = pprint.pformat(get_printable_request(req)).replace("[","\[")
task_str = pprint.pformat(task_data.dict()).replace("[","\[")
log.info(f'request: {req_str}')
log.info(f'task data: {task_str}')
def make_images_internal(
req: GenerateImageRequest,
task_data: TaskData,
data_queue: queue.Queue,
task_temp_images: list,
step_callback,
):
images, user_stopped = generate_images_internal(
req,
task_data,
data_queue,
task_temp_images,
step_callback,
task_data.stream_image_progress,
task_data.stream_image_progress_interval,
)
gc(context)
filtered_images = filter_images(req, task_data, images, user_stopped)
def make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
images, user_stopped = generate_images_internal(req, task_data, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)
filtered_images = filter_images(task_data, images, user_stopped)
if task_data.save_to_disk_path is not None:
save_images_to_disk(images, filtered_images, req, task_data)
@ -110,164 +59,70 @@ def make_images_internal(
else:
return images + filtered_images, seeds + seeds
def generate_images_internal(
req: GenerateImageRequest,
task_data: TaskData,
data_queue: queue.Queue,
task_temp_images: list,
step_callback,
stream_image_progress: bool,
stream_image_progress_interval: int,
):
def generate_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
context.temp_images.clear()
callback = make_step_callback(
req,
task_data,
data_queue,
task_temp_images,
step_callback,
stream_image_progress,
stream_image_progress_interval,
)
callback = make_step_callback(req, task_data, data_queue, task_temp_images, step_callback, stream_image_progress)
try:
if req.init_image is not None and not context.test_diffusers:
req.sampler_name = "ddim"
images = generate_images(context, callback=callback, **req.dict())
user_stopped = False
except UserInitiatedStop:
images = []
user_stopped = True
if context.partial_x_samples is not None:
if context.test_diffusers:
images = diffusers_latent_samples_to_images(context, context.partial_x_samples)
else:
images = latent_samples_to_images(context, context.partial_x_samples)
finally:
if hasattr(context, "partial_x_samples") and context.partial_x_samples is not None:
if not context.test_diffusers:
del context.partial_x_samples
images = latent_samples_to_images(context, context.partial_x_samples)
context.partial_x_samples = None
finally:
gc(context)
return images, user_stopped
def filter_images(req: GenerateImageRequest, task_data: TaskData, images: list, user_stopped):
if user_stopped:
def filter_images(task_data: TaskData, images: list, user_stopped):
if user_stopped or (task_data.use_face_correction is None and task_data.use_upscale is None):
return images
if task_data.block_nsfw:
images = apply_filters(context, "nsfw_checker", images)
if task_data.use_face_correction and "codeformer" in task_data.use_face_correction.lower():
default_realesrgan = DEFAULT_MODELS["realesrgan"][0]["file_name"]
prev_realesrgan_path = None
if task_data.codeformer_upscale_faces and default_realesrgan not in context.model_paths["realesrgan"]:
prev_realesrgan_path = context.model_paths["realesrgan"]
context.model_paths["realesrgan"] = resolve_model_to_use(default_realesrgan, "realesrgan")
load_model(context, "realesrgan")
try:
images = apply_filters(
context,
"codeformer",
images,
upscale_faces=task_data.codeformer_upscale_faces,
codeformer_fidelity=task_data.codeformer_fidelity,
)
finally:
if prev_realesrgan_path:
context.model_paths["realesrgan"] = prev_realesrgan_path
load_model(context, "realesrgan")
elif task_data.use_face_correction and "gfpgan" in task_data.use_face_correction.lower():
images = apply_filters(context, "gfpgan", images)
if task_data.use_upscale:
if "realesrgan" in task_data.use_upscale.lower():
images = apply_filters(context, "realesrgan", images, scale=task_data.upscale_amount)
elif task_data.use_upscale == "latent_upscaler":
images = apply_filters(
context,
"latent_upscaler",
images,
scale=task_data.upscale_amount,
latent_upscaler_options={
"prompt": req.prompt,
"negative_prompt": req.negative_prompt,
"seed": req.seed,
"num_inference_steps": task_data.latent_upscaler_steps,
"guidance_scale": 0,
},
)
return images
filters_to_apply = []
if task_data.use_face_correction and 'gfpgan' in task_data.use_face_correction.lower(): filters_to_apply.append('gfpgan')
if task_data.use_upscale and 'realesrgan' in task_data.use_upscale.lower(): filters_to_apply.append('realesrgan')
return apply_filters(context, filters_to_apply, images, scale=task_data.upscale_amount)
def construct_response(images: list, seeds: list, task_data: TaskData, base_seed: int):
return [
ResponseImage(
data=img_to_base64_str(
img,
task_data.output_format,
task_data.output_quality,
task_data.output_lossless,
),
data=img_to_base64_str(img, task_data.output_format, task_data.output_quality),
seed=seed,
)
for img, seed in zip(images, seeds)
) for img, seed in zip(images, seeds)
]
def make_step_callback(
req: GenerateImageRequest,
task_data: TaskData,
data_queue: queue.Queue,
task_temp_images: list,
step_callback,
stream_image_progress: bool,
stream_image_progress_interval: int,
):
def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
n_steps = req.num_inference_steps if req.init_image is None else int(req.num_inference_steps * req.prompt_strength)
last_callback_time = -1
def update_temp_img(x_samples, task_temp_images: list):
partial_images = []
if context.test_diffusers:
images = diffusers_latent_samples_to_images(context, x_samples)
else:
images = latent_samples_to_images(context, x_samples)
if task_data.block_nsfw:
images = apply_filters(context, "nsfw_checker", images)
images = latent_samples_to_images(context, x_samples)
for i, img in enumerate(images):
buf = img_to_buffer(img, output_format="JPEG")
buf = img_to_buffer(img, output_format='JPEG')
context.temp_images[f"{task_data.request_id}/{i}"] = buf
task_temp_images[i] = buf
partial_images.append({"path": f"/image/tmp/{task_data.request_id}/{i}"})
partial_images.append({'path': f"/image/tmp/{task_data.request_id}/{i}"})
del images
return partial_images
def on_image_step(x_samples, i, *args):
def on_image_step(x_samples, i):
nonlocal last_callback_time
if context.test_diffusers:
context.partial_x_samples = (x_samples, args[0])
else:
context.partial_x_samples = x_samples
context.partial_x_samples = x_samples
step_time = time.time() - last_callback_time if last_callback_time != -1 else -1
last_callback_time = time.time()
progress = {"step": i, "step_time": step_time, "total_steps": n_steps}
if stream_image_progress and stream_image_progress_interval > 0 and i % stream_image_progress_interval == 0:
progress["output"] = update_temp_img(context.partial_x_samples, task_temp_images)
if stream_image_progress and i % 5 == 0:
progress['output'] = update_temp_img(x_samples, task_temp_images)
data_queue.put(json.dumps(progress))

View File

@ -2,378 +2,240 @@
Notes:
async endpoints always run on the main thread. Without they run on the thread pool.
"""
import datetime
import mimetypes
import os
import traceback
import datetime
from typing import List, Union
from easydiffusion import app, model_manager, task_manager
from easydiffusion.types import GenerateImageRequest, MergeRequest, TaskData
from easydiffusion.utils import log
from fastapi import FastAPI, HTTPException
from fastapi.staticfiles import StaticFiles
from pydantic import BaseModel, Extra
from starlette.responses import FileResponse, JSONResponse, StreamingResponse
from pycloudflared import try_cloudflare
from pydantic import BaseModel
log.info(f"started in {app.SD_DIR}")
log.info(f"started at {datetime.datetime.now():%x %X}")
from easydiffusion import app, model_manager, task_manager
from easydiffusion.types import TaskData, GenerateImageRequest, MergeRequest
from easydiffusion.utils import log
log.info(f'started in {app.SD_DIR}')
log.info(f'started at {datetime.datetime.now():%x %X}')
server_api = FastAPI()
NOCACHE_HEADERS = {
"Cache-Control": "no-cache, no-store, must-revalidate",
"Pragma": "no-cache",
"Expires": "0",
}
NOCACHE_HEADERS={"Cache-Control": "no-cache, no-store, must-revalidate", "Pragma": "no-cache", "Expires": "0"}
class NoCacheStaticFiles(StaticFiles):
def __init__(self, directory: str):
# follow_symlink is only available on fastapi >= 0.92.0
if os.path.islink(directory):
super().__init__(directory=os.path.realpath(directory))
else:
super().__init__(directory=directory)
def is_not_modified(self, response_headers, request_headers) -> bool:
if "content-type" in response_headers and (
"javascript" in response_headers["content-type"] or "css" in response_headers["content-type"]
):
if 'content-type' in response_headers and ('javascript' in response_headers['content-type'] or 'css' in response_headers['content-type']):
response_headers.update(NOCACHE_HEADERS)
return False
return super().is_not_modified(response_headers, request_headers)
class SetAppConfigRequest(BaseModel, extra=Extra.allow):
class SetAppConfigRequest(BaseModel):
update_branch: str = None
render_devices: Union[List[str], List[int], str, int] = None
model_vae: str = None
ui_open_browser_on_start: bool = None
listen_to_network: bool = None
listen_port: int = None
test_diffusers: bool = False
def init():
mimetypes.init()
mimetypes.add_type("text/css", ".css")
if os.path.isdir(app.CUSTOM_MODIFIERS_DIR):
server_api.mount(
"/media/modifier-thumbnails/custom",
NoCacheStaticFiles(directory=app.CUSTOM_MODIFIERS_DIR),
name="custom-thumbnails",
)
server_api.mount(
"/media",
NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, "media")),
name="media",
)
server_api.mount('/media', NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, 'media')), name="media")
for plugins_dir, dir_prefix in app.UI_PLUGINS_SOURCES:
server_api.mount(
f"/plugins/{dir_prefix}",
NoCacheStaticFiles(directory=plugins_dir),
name=f"plugins-{dir_prefix}",
)
server_api.mount(f'/plugins/{dir_prefix}', NoCacheStaticFiles(directory=plugins_dir), name=f"plugins-{dir_prefix}")
@server_api.post("/app_config")
async def set_app_config(req: SetAppConfigRequest):
@server_api.post('/app_config')
async def set_app_config(req : SetAppConfigRequest):
return set_app_config_internal(req)
@server_api.get("/get/{key:path}")
def read_web_data(key: str = None):
@server_api.get('/get/{key:path}')
def read_web_data(key:str=None):
return read_web_data_internal(key)
@server_api.get("/ping") # Get server and optionally session status.
def ping(session_id: str = None):
@server_api.get('/ping') # Get server and optionally session status.
def ping(session_id:str=None):
return ping_internal(session_id)
@server_api.post("/render")
@server_api.post('/render')
def render(req: dict):
return render_internal(req)
@server_api.post("/model/merge")
@server_api.post('/model/merge')
def model_merge(req: dict):
print(req)
return model_merge_internal(req)
@server_api.get("/image/stream/{task_id:int}")
def stream(task_id: int):
@server_api.get('/image/stream/{task_id:int}')
def stream(task_id:int):
return stream_internal(task_id)
@server_api.get("/image/stop")
@server_api.get('/image/stop')
def stop(task: int):
return stop_internal(task)
@server_api.get("/image/tmp/{task_id:int}/{img_id:int}")
@server_api.get('/image/tmp/{task_id:int}/{img_id:int}')
def get_image(task_id: int, img_id: int):
return get_image_internal(task_id, img_id)
@server_api.post("/tunnel/cloudflare/start")
def start_cloudflare_tunnel(req: dict):
return start_cloudflare_tunnel_internal(req)
@server_api.post("/tunnel/cloudflare/stop")
def stop_cloudflare_tunnel(req: dict):
return stop_cloudflare_tunnel_internal(req)
@server_api.get("/")
@server_api.get('/')
def read_root():
return FileResponse(os.path.join(app.SD_UI_DIR, "index.html"), headers=NOCACHE_HEADERS)
return FileResponse(os.path.join(app.SD_UI_DIR, 'index.html'), headers=NOCACHE_HEADERS)
@server_api.on_event("shutdown")
def shutdown_event(): # Signal render thread to close on shutdown
task_manager.current_state_error = SystemExit("Application shutting down.")
def shutdown_event(): # Signal render thread to close on shutdown
task_manager.current_state_error = SystemExit('Application shutting down.')
# API implementations
def set_app_config_internal(req: SetAppConfigRequest):
def set_app_config_internal(req : SetAppConfigRequest):
config = app.getConfig()
if req.update_branch is not None:
config["update_branch"] = req.update_branch
config['update_branch'] = req.update_branch
if req.render_devices is not None:
update_render_devices_in_config(config, req.render_devices)
if req.ui_open_browser_on_start is not None:
if "ui" not in config:
config["ui"] = {}
config["ui"]["open_browser_on_start"] = req.ui_open_browser_on_start
if 'ui' not in config:
config['ui'] = {}
config['ui']['open_browser_on_start'] = req.ui_open_browser_on_start
if req.listen_to_network is not None:
if "net" not in config:
config["net"] = {}
config["net"]["listen_to_network"] = bool(req.listen_to_network)
if 'net' not in config:
config['net'] = {}
config['net']['listen_to_network'] = bool(req.listen_to_network)
if req.listen_port is not None:
if "net" not in config:
config["net"] = {}
config["net"]["listen_port"] = int(req.listen_port)
config["test_diffusers"] = req.test_diffusers
for property, property_value in req.dict().items():
if property_value is not None and property not in req.__fields__:
config[property] = property_value
if 'net' not in config:
config['net'] = {}
config['net']['listen_port'] = int(req.listen_port)
try:
app.setConfig(config)
if req.render_devices:
app.update_render_threads()
return JSONResponse({"status": "OK"}, headers=NOCACHE_HEADERS)
return JSONResponse({'status': 'OK'}, headers=NOCACHE_HEADERS)
except Exception as e:
log.error(traceback.format_exc())
raise HTTPException(status_code=500, detail=str(e))
def update_render_devices_in_config(config, render_devices):
if render_devices not in ("cpu", "auto") and not render_devices.startswith("cuda:"):
raise HTTPException(status_code=400, detail=f"Invalid render device requested: {render_devices}")
if render_devices not in ('cpu', 'auto') and not render_devices.startswith('cuda:'):
raise HTTPException(status_code=400, detail=f'Invalid render device requested: {render_devices}')
if render_devices.startswith("cuda:"):
render_devices = render_devices.split(",")
if render_devices.startswith('cuda:'):
render_devices = render_devices.split(',')
config["render_devices"] = render_devices
config['render_devices'] = render_devices
def read_web_data_internal(key: str = None):
if not key: # /get without parameters, stable-diffusion easter egg.
raise HTTPException(status_code=418, detail="StableDiffusion is drawing a teapot!") # HTTP418 I'm a teapot
elif key == "app_config":
def read_web_data_internal(key:str=None):
if not key: # /get without parameters, stable-diffusion easter egg.
raise HTTPException(status_code=418, detail="StableDiffusion is drawing a teapot!") # HTTP418 I'm a teapot
elif key == 'app_config':
return JSONResponse(app.getConfig(), headers=NOCACHE_HEADERS)
elif key == "system_info":
elif key == 'system_info':
config = app.getConfig()
output_dir = config.get("force_save_path", os.path.join(os.path.expanduser("~"), app.OUTPUT_DIRNAME))
system_info = {
"devices": task_manager.get_devices(),
"hosts": app.getIPConfig(),
"default_output_dir": output_dir,
"enforce_output_dir": ("force_save_path" in config),
'devices': task_manager.get_devices(),
'hosts': app.getIPConfig(),
'default_output_dir': os.path.join(os.path.expanduser("~"), app.OUTPUT_DIRNAME),
}
system_info["devices"]["config"] = config.get("render_devices", "auto")
system_info['devices']['config'] = config.get('render_devices', "auto")
return JSONResponse(system_info, headers=NOCACHE_HEADERS)
elif key == "models":
elif key == 'models':
return JSONResponse(model_manager.getModels(), headers=NOCACHE_HEADERS)
elif key == "modifiers":
return JSONResponse(app.get_image_modifiers(), headers=NOCACHE_HEADERS)
elif key == "ui_plugins":
return JSONResponse(app.getUIPlugins(), headers=NOCACHE_HEADERS)
elif key == 'modifiers': return FileResponse(os.path.join(app.SD_UI_DIR, 'modifiers.json'), headers=NOCACHE_HEADERS)
elif key == 'ui_plugins': return JSONResponse(app.getUIPlugins(), headers=NOCACHE_HEADERS)
else:
raise HTTPException(status_code=404, detail=f"Request for unknown {key}") # HTTP404 Not Found
raise HTTPException(status_code=404, detail=f'Request for unknown {key}') # HTTP404 Not Found
def ping_internal(session_id: str = None):
if task_manager.is_alive() <= 0: # Check that render threads are alive.
if task_manager.current_state_error:
raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
raise HTTPException(status_code=500, detail="Render thread is dead.")
if task_manager.current_state_error and not isinstance(task_manager.current_state_error, StopAsyncIteration):
raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
def ping_internal(session_id:str=None):
if task_manager.is_alive() <= 0: # Check that render threads are alive.
if task_manager.current_state_error: raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
raise HTTPException(status_code=500, detail='Render thread is dead.')
if task_manager.current_state_error and not isinstance(task_manager.current_state_error, StopAsyncIteration): raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
# Alive
response = {"status": str(task_manager.current_state)}
response = {'status': str(task_manager.current_state)}
if session_id:
session = task_manager.get_cached_session(session_id, update_ttl=True)
response["tasks"] = {id(t): t.status for t in session.tasks}
response["devices"] = task_manager.get_devices()
if cloudflare.address != None:
response["cloudflare"] = cloudflare.address
response['tasks'] = {id(t): t.status for t in session.tasks}
response['devices'] = task_manager.get_devices()
return JSONResponse(response, headers=NOCACHE_HEADERS)
def render_internal(req: dict):
try:
# separate out the request data into rendering and task-specific data
render_req: GenerateImageRequest = GenerateImageRequest.parse_obj(req)
task_data: TaskData = TaskData.parse_obj(req)
# Overwrite user specified save path
config = app.getConfig()
if "force_save_path" in config:
task_data.save_to_disk_path = config["force_save_path"]
render_req.init_image_mask = req.get('mask') # hack: will rename this in the HTTP API in a future revision
render_req.init_image_mask = req.get("mask") # hack: will rename this in the HTTP API in a future revision
app.save_to_config(
task_data.use_stable_diffusion_model,
task_data.use_vae_model,
task_data.use_hypernetwork_model,
task_data.vram_usage_level,
)
app.save_to_config(task_data.use_stable_diffusion_model, task_data.use_vae_model, task_data.use_hypernetwork_model, task_data.vram_usage_level)
# enqueue the task
new_task = task_manager.render(render_req, task_data)
response = {
"status": str(task_manager.current_state),
"queue": len(task_manager.tasks_queue),
"stream": f"/image/stream/{id(new_task)}",
"task": id(new_task),
'status': str(task_manager.current_state),
'queue': len(task_manager.tasks_queue),
'stream': f'/image/stream/{id(new_task)}',
'task': id(new_task)
}
return JSONResponse(response, headers=NOCACHE_HEADERS)
except ChildProcessError as e: # Render thread is dead
raise HTTPException(status_code=500, detail=f"Rendering thread has died.") # HTTP500 Internal Server Error
except ConnectionRefusedError as e: # Unstarted task pending limit reached, deny queueing too many.
raise HTTPException(status_code=503, detail=str(e)) # HTTP503 Service Unavailable
except ChildProcessError as e: # Render thread is dead
raise HTTPException(status_code=500, detail=f'Rendering thread has died.') # HTTP500 Internal Server Error
except ConnectionRefusedError as e: # Unstarted task pending limit reached, deny queueing too many.
raise HTTPException(status_code=503, detail=str(e)) # HTTP503 Service Unavailable
except Exception as e:
log.error(traceback.format_exc())
raise HTTPException(status_code=500, detail=str(e))
def model_merge_internal(req: dict):
try:
from easydiffusion.utils.save_utils import filename_regex
from sdkit.train import merge_models
from easydiffusion.utils.save_utils import filename_regex
mergeReq: MergeRequest = MergeRequest.parse_obj(req)
merge_models(
model_manager.resolve_model_to_use(mergeReq.model0, "stable-diffusion"),
model_manager.resolve_model_to_use(mergeReq.model1, "stable-diffusion"),
mergeReq.ratio,
os.path.join(
app.MODELS_DIR,
"stable-diffusion",
filename_regex.sub("_", mergeReq.out_path),
),
mergeReq.use_fp16,
merge_models(model_manager.resolve_model_to_use(mergeReq.model0,'stable-diffusion'),
model_manager.resolve_model_to_use(mergeReq.model1,'stable-diffusion'),
mergeReq.ratio,
os.path.join(app.MODELS_DIR, 'stable-diffusion', filename_regex.sub('_', mergeReq.out_path)),
mergeReq.use_fp16
)
return JSONResponse({"status": "OK"}, headers=NOCACHE_HEADERS)
return JSONResponse({'status':'OK'}, headers=NOCACHE_HEADERS)
except Exception as e:
log.error(traceback.format_exc())
raise HTTPException(status_code=500, detail=str(e))
def stream_internal(task_id: int):
# TODO Move to WebSockets ??
def stream_internal(task_id:int):
#TODO Move to WebSockets ??
task = task_manager.get_cached_task(task_id, update_ttl=True)
if not task:
raise HTTPException(status_code=404, detail=f"Request {task_id} not found.") # HTTP404 NotFound
# if (id(task) != task_id): raise HTTPException(status_code=409, detail=f'Wrong task id received. Expected:{id(task)}, Received:{task_id}') # HTTP409 Conflict
if not task: raise HTTPException(status_code=404, detail=f'Request {task_id} not found.') # HTTP404 NotFound
#if (id(task) != task_id): raise HTTPException(status_code=409, detail=f'Wrong task id received. Expected:{id(task)}, Received:{task_id}') # HTTP409 Conflict
if task.buffer_queue.empty() and not task.lock.locked():
if task.response:
# log.info(f'Session {session_id} sending cached response')
#log.info(f'Session {session_id} sending cached response')
return JSONResponse(task.response, headers=NOCACHE_HEADERS)
raise HTTPException(status_code=425, detail="Too Early, task not started yet.") # HTTP425 Too Early
# log.info(f'Session {session_id} opened live render stream {id(task.buffer_queue)}')
return StreamingResponse(task.read_buffer_generator(), media_type="application/json")
raise HTTPException(status_code=425, detail='Too Early, task not started yet.') # HTTP425 Too Early
#log.info(f'Session {session_id} opened live render stream {id(task.buffer_queue)}')
return StreamingResponse(task.read_buffer_generator(), media_type='application/json')
def stop_internal(task: int):
if not task:
if (
task_manager.current_state == task_manager.ServerStates.Online
or task_manager.current_state == task_manager.ServerStates.Unavailable
):
raise HTTPException(status_code=409, detail="Not currently running any tasks.") # HTTP409 Conflict
task_manager.current_state_error = StopAsyncIteration("")
return {"OK"}
if task_manager.current_state == task_manager.ServerStates.Online or task_manager.current_state == task_manager.ServerStates.Unavailable:
raise HTTPException(status_code=409, detail='Not currently running any tasks.') # HTTP409 Conflict
task_manager.current_state_error = StopAsyncIteration('')
return {'OK'}
task_id = task
task = task_manager.get_cached_task(task_id, update_ttl=False)
if not task:
raise HTTPException(status_code=404, detail=f"Task {task_id} was not found.") # HTTP404 Not Found
if isinstance(task.error, StopAsyncIteration):
raise HTTPException(status_code=409, detail=f"Task {task_id} is already stopped.") # HTTP409 Conflict
task.error = StopAsyncIteration(f"Task {task_id} stop requested.")
return {"OK"}
if not task: raise HTTPException(status_code=404, detail=f'Task {task_id} was not found.') # HTTP404 Not Found
if isinstance(task.error, StopAsyncIteration): raise HTTPException(status_code=409, detail=f'Task {task_id} is already stopped.') # HTTP409 Conflict
task.error = StopAsyncIteration(f'Task {task_id} stop requested.')
return {'OK'}
def get_image_internal(task_id: int, img_id: int):
task = task_manager.get_cached_task(task_id, update_ttl=True)
if not task:
raise HTTPException(status_code=410, detail=f"Task {task_id} could not be found.") # HTTP404 NotFound
if not task.temp_images[img_id]:
raise HTTPException(status_code=425, detail="Too Early, task data is not available yet.") # HTTP425 Too Early
if not task: raise HTTPException(status_code=410, detail=f'Task {task_id} could not be found.') # HTTP404 NotFound
if not task.temp_images[img_id]: raise HTTPException(status_code=425, detail='Too Early, task data is not available yet.') # HTTP425 Too Early
try:
img_data = task.temp_images[img_id]
img_data.seek(0)
return StreamingResponse(img_data, media_type="image/jpeg")
return StreamingResponse(img_data, media_type='image/jpeg')
except KeyError as e:
raise HTTPException(status_code=500, detail=str(e))
#---- Cloudflare Tunnel ----
class CloudflareTunnel:
def __init__(self):
config = app.getConfig()
self.urls = None
self.port = config.get("net", {}).get("listen_port")
def start(self):
if self.port:
self.urls = try_cloudflare(self.port)
def stop(self):
if self.urls:
try_cloudflare.terminate(self.port)
self.urls = None
@property
def address(self):
if self.urls:
return self.urls.tunnel
else:
return None
cloudflare = CloudflareTunnel()
def start_cloudflare_tunnel_internal(req: dict):
try:
cloudflare.start()
log.info(f"- Started cloudflare tunnel. Using address: {cloudflare.address}")
return JSONResponse({"address":cloudflare.address})
except Exception as e:
log.error(str(e))
log.error(traceback.format_exc())
return HTTPException(status_code=500, detail=str(e))
def stop_cloudflare_tunnel_internal(req: dict):
try:
cloudflare.stop()
except Exception as e:
log.error(str(e))
log.error(traceback.format_exc())
return HTTPException(status_code=500, detail=str(e))

View File

@ -7,112 +7,81 @@ Notes:
import json
import traceback
TASK_TTL = 30 * 60 # seconds, Discard last session's task timeout
import queue
import threading
import time
import weakref
from typing import Any, Hashable
TASK_TTL = 15 * 60 # seconds, Discard last session's task timeout
import torch
from easydiffusion import device_manager
from easydiffusion.types import GenerateImageRequest, TaskData
from easydiffusion.utils import log
from sdkit.utils import gc
import queue, threading, time, weakref
from typing import Any, Hashable
THREAD_NAME_PREFIX = ""
ERR_LOCK_FAILED = " failed to acquire lock within timeout."
LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
from easydiffusion import device_manager
from easydiffusion.types import TaskData, GenerateImageRequest
from easydiffusion.utils import log
THREAD_NAME_PREFIX = ''
ERR_LOCK_FAILED = ' failed to acquire lock within timeout.'
LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
# It's better to get an exception than a deadlock... ALWAYS use timeout in critical paths.
DEVICE_START_TIMEOUT = 60 # seconds - Maximum time to wait for a render device to init.
class SymbolClass(type): # Print nicely formatted Symbol names.
def __repr__(self):
return self.__qualname__
def __str__(self):
return self.__name__
class Symbol(metaclass=SymbolClass):
pass
DEVICE_START_TIMEOUT = 60 # seconds - Maximum time to wait for a render device to init.
class SymbolClass(type): # Print nicely formatted Symbol names.
def __repr__(self): return self.__qualname__
def __str__(self): return self.__name__
class Symbol(metaclass=SymbolClass): pass
class ServerStates:
class Init(Symbol):
pass
class Init(Symbol): pass
class LoadingModel(Symbol): pass
class Online(Symbol): pass
class Rendering(Symbol): pass
class Unavailable(Symbol): pass
class LoadingModel(Symbol):
pass
class Online(Symbol):
pass
class Rendering(Symbol):
pass
class Unavailable(Symbol):
pass
class RenderTask: # Task with output queue and completion lock.
class RenderTask(): # Task with output queue and completion lock.
def __init__(self, req: GenerateImageRequest, task_data: TaskData):
task_data.request_id = id(self)
self.render_request: GenerateImageRequest = req # Initial Request
self.task_data: TaskData = task_data
self.response: Any = None # Copy of the last reponse
self.render_device = None # Select the task affinity. (Not used to change active devices).
self.temp_images: list = [None] * req.num_outputs * (1 if task_data.show_only_filtered_image else 2)
self.response: Any = None # Copy of the last reponse
self.render_device = None # Select the task affinity. (Not used to change active devices).
self.temp_images:list = [None] * req.num_outputs * (1 if task_data.show_only_filtered_image else 2)
self.error: Exception = None
self.lock: threading.Lock = threading.Lock() # Locks at task start and unlocks when task is completed
self.buffer_queue: queue.Queue = queue.Queue() # Queue of JSON string segments
self.lock: threading.Lock = threading.Lock() # Locks at task start and unlocks when task is completed
self.buffer_queue: queue.Queue = queue.Queue() # Queue of JSON string segments
async def read_buffer_generator(self):
try:
while not self.buffer_queue.empty():
res = self.buffer_queue.get(block=False)
self.buffer_queue.task_done()
yield res
except queue.Empty as e:
yield
except queue.Empty as e: yield
@property
def status(self):
if self.lock.locked():
return "running"
return 'running'
if isinstance(self.error, StopAsyncIteration):
return "stopped"
return 'stopped'
if self.error:
return "error"
return 'error'
if not self.buffer_queue.empty():
return "buffer"
return 'buffer'
if self.response:
return "completed"
return "pending"
return 'completed'
return 'pending'
@property
def is_pending(self):
return bool(not self.response and not self.error)
# Temporary cache to allow to query tasks results for a short time after they are completed.
class DataCache:
class DataCache():
def __init__(self):
self._base = dict()
self._lock: threading.Lock = threading.Lock()
def _get_ttl_time(self, ttl: int) -> int:
return int(time.time()) + ttl
def _is_expired(self, timestamp: int) -> bool:
return int(time.time()) >= timestamp
def clean(self) -> None:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.clean" + ERR_LOCK_FAILED)
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.clean' + ERR_LOCK_FAILED)
try:
# Create a list of expired keys to delete
to_delete = []
@ -124,26 +93,20 @@ class DataCache:
for key in to_delete:
(_, val) = self._base[key]
if isinstance(val, RenderTask):
log.debug(f"RenderTask {key} expired. Data removed.")
log.debug(f'RenderTask {key} expired. Data removed.')
elif isinstance(val, SessionState):
log.debug(f"Session {key} expired. Data removed.")
log.debug(f'Session {key} expired. Data removed.')
else:
log.debug(f"Key {key} expired. Data removed.")
log.debug(f'Key {key} expired. Data removed.')
del self._base[key]
finally:
self._lock.release()
def clear(self) -> None:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.clear" + ERR_LOCK_FAILED)
try:
self._base.clear()
finally:
self._lock.release()
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.clear' + ERR_LOCK_FAILED)
try: self._base.clear()
finally: self._lock.release()
def delete(self, key: Hashable) -> bool:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.delete" + ERR_LOCK_FAILED)
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.delete' + ERR_LOCK_FAILED)
try:
if key not in self._base:
return False
@ -151,10 +114,8 @@ class DataCache:
return True
finally:
self._lock.release()
def keep(self, key: Hashable, ttl: int) -> bool:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.keep" + ERR_LOCK_FAILED)
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.keep' + ERR_LOCK_FAILED)
try:
if key in self._base:
_, value = self._base.get(key)
@ -163,54 +124,48 @@ class DataCache:
return False
finally:
self._lock.release()
def put(self, key: Hashable, value: Any, ttl: int) -> bool:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.put" + ERR_LOCK_FAILED)
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.put' + ERR_LOCK_FAILED)
try:
self._base[key] = (self._get_ttl_time(ttl), value)
except Exception:
self._base[key] = (
self._get_ttl_time(ttl), value
)
except Exception as e:
log.error(traceback.format_exc())
return False
else:
return True
finally:
self._lock.release()
def tryGet(self, key: Hashable) -> Any:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.tryGet" + ERR_LOCK_FAILED)
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.tryGet' + ERR_LOCK_FAILED)
try:
ttl, value = self._base.get(key, (None, None))
if ttl is not None and self._is_expired(ttl):
log.debug(f"Session {key} expired. Discarding data.")
log.debug(f'Session {key} expired. Discarding data.')
del self._base[key]
return None
return value
finally:
self._lock.release()
manager_lock = threading.RLock()
render_threads = []
current_state = ServerStates.Init
current_state_error: Exception = None
current_state_error:Exception = None
tasks_queue = []
session_cache = DataCache()
task_cache = DataCache()
weak_thread_data = weakref.WeakKeyDictionary()
idle_event: threading.Event = threading.Event()
class SessionState:
class SessionState():
def __init__(self, id: str):
self._id = id
self._tasks_ids = []
@property
def id(self):
return self._id
@property
def tasks(self):
tasks = []
@ -219,7 +174,6 @@ class SessionState:
if task:
tasks.append(task)
return tasks
def put(self, task, ttl=TASK_TTL):
task_id = id(task)
self._tasks_ids.append(task_id)
@ -229,12 +183,10 @@ class SessionState:
self._tasks_ids.pop(0)
return True
def thread_get_next_task():
from easydiffusion import renderer
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
log.warn(f"Render thread on device: {renderer.context.device} failed to acquire manager lock.")
log.warn(f'Render thread on device: {renderer.context.device} failed to acquire manager lock.')
return None
if len(tasks_queue) <= 0:
manager_lock.release()
@ -248,10 +200,10 @@ def thread_get_next_task():
continue # requested device alive, skip current one.
else:
# Requested device is not active, return error to UI.
queued_task.error = Exception(queued_task.render_device + " is not currently active.")
queued_task.error = Exception(queued_task.render_device + ' is not currently active.')
task = queued_task
break
if not queued_task.render_device and renderer.context.device == "cpu" and is_alive() > 1:
if not queued_task.render_device and renderer.context.device == 'cpu' and is_alive() > 1:
# not asking for any specific devices, cpu want to grab task but other render devices are alive.
continue # Skip Tasks, don't run on CPU unless there is nothing else or user asked for it.
task = queued_task
@ -262,19 +214,17 @@ def thread_get_next_task():
finally:
manager_lock.release()
def thread_render(device):
global current_state, current_state_error
from easydiffusion import model_manager, renderer
from easydiffusion import renderer, model_manager
try:
renderer.init(device)
weak_thread_data[threading.current_thread()] = {
"device": renderer.context.device,
"device_name": renderer.context.device_name,
"alive": True,
'device': renderer.context.device,
'device_name': renderer.context.device_name,
'alive': True
}
current_state = ServerStates.LoadingModel
@ -283,14 +233,17 @@ def thread_render(device):
current_state = ServerStates.Online
except Exception as e:
log.error(traceback.format_exc())
weak_thread_data[threading.current_thread()] = {"error": e, "alive": False}
weak_thread_data[threading.current_thread()] = {
'error': e,
'alive': False
}
return
while True:
session_cache.clean()
task_cache.clean()
if not weak_thread_data[threading.current_thread()]["alive"]:
log.info(f"Shutting down thread for device {renderer.context.device}")
if not weak_thread_data[threading.current_thread()]['alive']:
log.info(f'Shutting down thread for device {renderer.context.device}')
model_manager.unload_all(renderer.context)
return
if isinstance(current_state_error, SystemExit):
@ -303,82 +256,63 @@ def thread_render(device):
continue
if task.error is not None:
log.error(task.error)
task.response = {"status": "failed", "detail": str(task.error)}
task.response = {"status": 'failed', "detail": str(task.error)}
task.buffer_queue.put(json.dumps(task.response))
continue
if current_state_error:
task.error = current_state_error
task.response = {"status": "failed", "detail": str(task.error)}
task.response = {"status": 'failed', "detail": str(task.error)}
task.buffer_queue.put(json.dumps(task.response))
continue
log.info(f"Session {task.task_data.session_id} starting task {id(task)} on {renderer.context.device_name}")
if not task.lock.acquire(blocking=False):
raise Exception("Got locked task from queue.")
log.info(f'Session {task.task_data.session_id} starting task {id(task)} on {renderer.context.device_name}')
if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
try:
def step_callback():
global current_state_error
task_cache.keep(id(task), TASK_TTL)
session_cache.keep(task.task_data.session_id, TASK_TTL)
if (
isinstance(current_state_error, SystemExit)
or isinstance(current_state_error, StopAsyncIteration)
or isinstance(task.error, StopAsyncIteration)
):
if isinstance(current_state_error, SystemExit) or isinstance(current_state_error, StopAsyncIteration) or isinstance(task.error, StopAsyncIteration):
renderer.context.stop_processing = True
if isinstance(current_state_error, StopAsyncIteration):
task.error = current_state_error
current_state_error = None
log.info(f"Session {task.task_data.session_id} sent cancel signal for task {id(task)}")
log.info(f'Session {task.task_data.session_id} sent cancel signal for task {id(task)}')
current_state = ServerStates.LoadingModel
model_manager.resolve_model_paths(task.task_data)
model_manager.reload_models_if_necessary(renderer.context, task.task_data)
model_manager.fail_if_models_did_not_load(renderer.context)
current_state = ServerStates.Rendering
task.response = renderer.make_images(
task.render_request,
task.task_data,
task.buffer_queue,
task.temp_images,
step_callback,
)
task.response = renderer.make_images(task.render_request, task.task_data, task.buffer_queue, task.temp_images, step_callback)
# Before looping back to the generator, mark cache as still alive.
task_cache.keep(id(task), TASK_TTL)
session_cache.keep(task.task_data.session_id, TASK_TTL)
except Exception as e:
task.error = str(e)
task.response = {"status": "failed", "detail": str(task.error)}
task.error = e
task.response = {"status": 'failed', "detail": str(task.error)}
task.buffer_queue.put(json.dumps(task.response))
log.error(traceback.format_exc())
continue
finally:
gc(renderer.context)
# Task completed
task.lock.release()
task_cache.keep(id(task), TASK_TTL)
session_cache.keep(task.task_data.session_id, TASK_TTL)
if isinstance(task.error, StopAsyncIteration):
log.info(f"Session {task.task_data.session_id} task {id(task)} cancelled!")
log.info(f'Session {task.task_data.session_id} task {id(task)} cancelled!')
elif task.error is not None:
log.info(f"Session {task.task_data.session_id} task {id(task)} failed!")
log.info(f'Session {task.task_data.session_id} task {id(task)} failed!')
else:
log.info(
f"Session {task.task_data.session_id} task {id(task)} completed by {renderer.context.device_name}."
)
log.info(f'Session {task.task_data.session_id} task {id(task)} completed by {renderer.context.device_name}.')
current_state = ServerStates.Online
def get_cached_task(task_id: str, update_ttl: bool = False):
def get_cached_task(task_id:str, update_ttl:bool=False):
# By calling keep before tryGet, wont discard if was expired.
if update_ttl and not task_cache.keep(task_id, TASK_TTL):
# Failed to keep task, already gone.
return None
return task_cache.tryGet(task_id)
def get_cached_session(session_id: str, update_ttl: bool = False):
def get_cached_session(session_id:str, update_ttl:bool=False):
if update_ttl:
session_cache.keep(session_id, TASK_TTL)
session = session_cache.tryGet(session_id)
@ -387,71 +321,64 @@ def get_cached_session(session_id: str, update_ttl: bool = False):
session_cache.put(session_id, session, TASK_TTL)
return session
def get_devices():
devices = {
"all": {},
"active": {},
'all': {},
'active': {},
}
def get_device_info(device):
if device in ("cpu", "mps"):
return {"name": device_manager.get_processor_name()}
if device == 'cpu':
return {'name': device_manager.get_processor_name()}
mem_free, mem_total = torch.cuda.mem_get_info(device)
mem_free /= float(10**9)
mem_total /= float(10**9)
return {
"name": torch.cuda.get_device_name(device),
"mem_free": mem_free,
"mem_total": mem_total,
"max_vram_usage_level": device_manager.get_max_vram_usage_level(device),
'name': torch.cuda.get_device_name(device),
'mem_free': mem_free,
'mem_total': mem_total,
'max_vram_usage_level': device_manager.get_max_vram_usage_level(device),
}
# list the compatible devices
cuda_count = torch.cuda.device_count()
for device in range(cuda_count):
device = f"cuda:{device}"
gpu_count = torch.cuda.device_count()
for device in range(gpu_count):
device = f'cuda:{device}'
if not device_manager.is_device_compatible(device):
continue
devices["all"].update({device: get_device_info(device)})
devices['all'].update({device: get_device_info(device)})
if device_manager.is_mps_available():
devices["all"].update({"mps": get_device_info("mps")})
devices["all"].update({"cpu": get_device_info("cpu")})
devices['all'].update({'cpu': get_device_info('cpu')})
# list the activated devices
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("get_devices" + ERR_LOCK_FAILED)
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('get_devices' + ERR_LOCK_FAILED)
try:
for rthread in render_threads:
if not rthread.is_alive():
continue
weak_data = weak_thread_data.get(rthread)
if not weak_data or not "device" in weak_data or not "device_name" in weak_data:
if not weak_data or not 'device' in weak_data or not 'device_name' in weak_data:
continue
device = weak_data["device"]
devices["active"].update({device: get_device_info(device)})
device = weak_data['device']
devices['active'].update({device: get_device_info(device)})
finally:
manager_lock.release()
return devices
def is_alive(device=None):
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("is_alive" + ERR_LOCK_FAILED)
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('is_alive' + ERR_LOCK_FAILED)
nbr_alive = 0
try:
for rthread in render_threads:
if device is not None:
weak_data = weak_thread_data.get(rthread)
if weak_data is None or not "device" in weak_data or weak_data["device"] is None:
if weak_data is None or not 'device' in weak_data or weak_data['device'] is None:
continue
thread_device = weak_data["device"]
thread_device = weak_data['device']
if thread_device != device:
continue
if rthread.is_alive():
@ -460,13 +387,11 @@ def is_alive(device=None):
finally:
manager_lock.release()
def start_render_thread(device):
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("start_render_thread" + ERR_LOCK_FAILED)
log.info(f"Start new Rendering Thread on device: {device}")
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('start_render_thread' + ERR_LOCK_FAILED)
log.info(f'Start new Rendering Thread on device: {device}')
try:
rthread = threading.Thread(target=thread_render, kwargs={"device": device})
rthread = threading.Thread(target=thread_render, kwargs={'device': device})
rthread.daemon = True
rthread.name = THREAD_NAME_PREFIX + device
rthread.start()
@ -474,8 +399,8 @@ def start_render_thread(device):
finally:
manager_lock.release()
timeout = DEVICE_START_TIMEOUT
while not rthread.is_alive() or not rthread in weak_thread_data or not "device" in weak_thread_data[rthread]:
if rthread in weak_thread_data and "error" in weak_thread_data[rthread]:
while not rthread.is_alive() or not rthread in weak_thread_data or not 'device' in weak_thread_data[rthread]:
if rthread in weak_thread_data and 'error' in weak_thread_data[rthread]:
log.error(f"{rthread}, {device}, error: {weak_thread_data[rthread]['error']}")
return False
if timeout <= 0:
@ -484,27 +409,25 @@ def start_render_thread(device):
time.sleep(1)
return True
def stop_render_thread(device):
try:
device_manager.validate_device_id(device, log_prefix="stop_render_thread")
device_manager.validate_device_id(device, log_prefix='stop_render_thread')
except:
log.error(traceback.format_exc())
return False
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("stop_render_thread" + ERR_LOCK_FAILED)
log.info(f"Stopping Rendering Thread on device: {device}")
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('stop_render_thread' + ERR_LOCK_FAILED)
log.info(f'Stopping Rendering Thread on device: {device}')
try:
thread_to_remove = None
for rthread in render_threads:
weak_data = weak_thread_data.get(rthread)
if weak_data is None or not "device" in weak_data or weak_data["device"] is None:
if weak_data is None or not 'device' in weak_data or weak_data['device'] is None:
continue
thread_device = weak_data["device"]
thread_device = weak_data['device']
if thread_device == device:
weak_data["alive"] = False
weak_data['alive'] = False
thread_to_remove = rthread
break
if thread_to_remove is not None:
@ -515,51 +438,44 @@ def stop_render_thread(device):
return False
def update_render_threads(render_devices, active_devices):
devices_to_start, devices_to_stop = device_manager.get_device_delta(render_devices, active_devices)
log.debug(f"devices_to_start: {devices_to_start}")
log.debug(f"devices_to_stop: {devices_to_stop}")
log.debug(f'devices_to_start: {devices_to_start}')
log.debug(f'devices_to_stop: {devices_to_stop}')
for device in devices_to_stop:
if is_alive(device) <= 0:
log.debug(f"{device} is not alive")
log.debug(f'{device} is not alive')
continue
if not stop_render_thread(device):
log.warn(f"{device} could not stop render thread")
log.warn(f'{device} could not stop render thread')
for device in devices_to_start:
if is_alive(device) >= 1:
log.debug(f"{device} already registered.")
log.debug(f'{device} already registered.')
continue
if not start_render_thread(device):
log.warn(f"{device} failed to start.")
log.warn(f'{device} failed to start.')
if is_alive() <= 0: # No running devices, probably invalid user config.
raise EnvironmentError(
'ERROR: No active render devices! Please verify the "render_devices" value in config.json'
)
if is_alive() <= 0: # No running devices, probably invalid user config.
raise EnvironmentError('ERROR: No active render devices! Please verify the "render_devices" value in config.json')
log.debug(f"active devices: {get_devices()['active']}")
def shutdown_event(): # Signal render thread to close on shutdown
def shutdown_event(): # Signal render thread to close on shutdown
global current_state_error
current_state_error = SystemExit("Application shutting down.")
current_state_error = SystemExit('Application shutting down.')
def render(render_req: GenerateImageRequest, task_data: TaskData):
current_thread_count = is_alive()
if current_thread_count <= 0: # Render thread is dead
raise ChildProcessError("Rendering thread has died.")
raise ChildProcessError('Rendering thread has died.')
# Alive, check if task in cache
session = get_cached_session(task_data.session_id, update_ttl=True)
pending_tasks = list(filter(lambda t: t.is_pending, session.tasks))
if current_thread_count < len(pending_tasks):
raise ConnectionRefusedError(
f"Session {task_data.session_id} already has {len(pending_tasks)} pending tasks out of {current_thread_count}."
)
raise ConnectionRefusedError(f'Session {task_data.session_id} already has {len(pending_tasks)} pending tasks out of {current_thread_count}.')
new_task = RenderTask(render_req, task_data)
if session.put(new_task, TASK_TTL):
@ -572,4 +488,4 @@ def render(render_req: GenerateImageRequest, task_data: TaskData):
return new_task
finally:
manager_lock.release()
raise RuntimeError("Failed to add task to cache.")
raise RuntimeError('Failed to add task to cache.')

View File

@ -1,7 +1,5 @@
from typing import Any
from pydantic import BaseModel
from typing import Any
class GenerateImageRequest(BaseModel):
prompt: str = ""
@ -20,40 +18,28 @@ class GenerateImageRequest(BaseModel):
prompt_strength: float = 0.8
preserve_init_image_color_profile = False
sampler_name: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
sampler_name: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
hypernetwork_strength: float = 0
lora_alpha: float = 0
tiling: str = "none" # "none", "x", "y", "xy"
class TaskData(BaseModel):
request_id: str = None
session_id: str = "session"
save_to_disk_path: str = None
vram_usage_level: str = "balanced" # or "low" or "medium"
vram_usage_level: str = "balanced" # or "low" or "medium"
use_face_correction: str = None # or "GFPGANv1.3"
use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B" or "latent_upscaler"
upscale_amount: int = 4 # or 2
latent_upscaler_steps: int = 10
use_face_correction: str = None # or "GFPGANv1.3"
use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
upscale_amount: int = 4 # or 2
use_stable_diffusion_model: str = "sd-v1-4"
# use_stable_diffusion_config: str = "v1-inference"
use_vae_model: str = None
use_hypernetwork_model: str = None
use_lora_model: str = None
show_only_filtered_image: bool = False
block_nsfw: bool = False
output_format: str = "jpeg" # or "png" or "webp"
output_format: str = "jpeg" # or "png"
output_quality: int = 75
output_lossless: bool = False
metadata_output_format: str = "txt" # or "json"
metadata_output_format: str = "txt" # or "json"
stream_image_progress: bool = False
stream_image_progress_interval: int = 5
clip_skip: bool = False
codeformer_upscale_faces: bool = False
codeformer_fidelity: float = 0.5
class MergeRequest(BaseModel):
model0: str = None
@ -62,9 +48,8 @@ class MergeRequest(BaseModel):
out_path: str = "mix"
use_fp16 = True
class Image:
data: str # base64
data: str # base64
seed: int
is_nsfw: bool
path_abs: str = None
@ -80,7 +65,6 @@ class Image:
"path_abs": self.path_abs,
}
class Response:
render_request: GenerateImageRequest
task_data: TaskData
@ -96,7 +80,7 @@ class Response:
del self.render_request.init_image_mask
res = {
"status": "succeeded",
"status": 'succeeded',
"render_request": self.render_request.dict(),
"task_data": self.task_data.dict(),
"output": [],
@ -107,6 +91,5 @@ class Response:
return res
class UserInitiatedStop(Exception):
pass

View File

@ -1,8 +1,8 @@
import logging
log = logging.getLogger("easydiffusion")
log = logging.getLogger('easydiffusion')
from .save_utils import (
save_images_to_disk,
get_printable_request,
)
)

View File

@ -1,298 +1,88 @@
import os
import re
import time
from datetime import datetime
from functools import reduce
import base64
import re
from easydiffusion import app
from easydiffusion.types import GenerateImageRequest, TaskData
from numpy import base_repr
from sdkit.utils import save_dicts, save_images
from easydiffusion.types import TaskData, GenerateImageRequest
filename_regex = re.compile("[^a-zA-Z0-9._-]")
img_number_regex = re.compile("([0-9]{5,})")
from sdkit.utils import save_images, save_dicts
filename_regex = re.compile('[^a-zA-Z0-9._-]')
# keep in sync with `ui/media/js/dnd.js`
TASK_TEXT_MAPPING = {
"prompt": "Prompt",
"negative_prompt": "Negative Prompt",
"seed": "Seed",
"use_stable_diffusion_model": "Stable Diffusion model",
"clip_skip": "Clip Skip",
"use_vae_model": "VAE model",
"sampler_name": "Sampler",
"width": "Width",
"height": "Height",
"num_inference_steps": "Steps",
"guidance_scale": "Guidance Scale",
"prompt_strength": "Prompt Strength",
"use_lora_model": "LoRA model",
"lora_alpha": "LoRA Strength",
"use_hypernetwork_model": "Hypernetwork model",
"hypernetwork_strength": "Hypernetwork Strength",
"tiling": "Seamless Tiling",
"use_face_correction": "Use Face Correction",
"use_upscale": "Use Upscaling",
"upscale_amount": "Upscale By",
"latent_upscaler_steps": "Latent Upscaler Steps"
'prompt': 'Prompt',
'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',
'upscale_amount': 'Upscale By',
'sampler_name': 'Sampler',
'negative_prompt': 'Negative Prompt',
'use_stable_diffusion_model': 'Stable Diffusion model',
'use_hypernetwork_model': 'Hypernetwork model',
'hypernetwork_strength': 'Hypernetwork Strength'
}
time_placeholders = {
"$yyyy": "%Y",
"$MM": "%m",
"$dd": "%d",
"$HH": "%H",
"$mm": "%M",
"$ss": "%S",
}
other_placeholders = {
"$id": lambda req, task_data: filename_regex.sub("_", task_data.session_id),
"$p": lambda req, task_data: filename_regex.sub("_", req.prompt)[:50],
"$s": lambda req, task_data: str(req.seed),
}
class ImageNumber:
_factory = None
_evaluated = False
def __init__(self, factory):
self._factory = factory
self._evaluated = None
def __call__(self) -> int:
if self._evaluated is None:
self._evaluated = self._factory()
return self._evaluated
def format_placeholders(format: str, req: GenerateImageRequest, task_data: TaskData, now=None):
if now is None:
now = time.time()
for placeholder, time_format in time_placeholders.items():
if placeholder in format:
format = format.replace(placeholder, datetime.fromtimestamp(now).strftime(time_format))
for placeholder, replace_func in other_placeholders.items():
if placeholder in format:
format = format.replace(placeholder, replace_func(req, task_data))
return format
def format_folder_name(format: str, req: GenerateImageRequest, task_data: TaskData):
format = format_placeholders(format, req, task_data)
return filename_regex.sub("_", format)
def format_file_name(
format: str,
req: GenerateImageRequest,
task_data: TaskData,
now: float,
batch_file_number: int,
folder_img_number: ImageNumber,
):
format = format_placeholders(format, req, task_data, now)
if "$n" in format:
format = format.replace("$n", f"{folder_img_number():05}")
if "$tsb64" in format:
img_id = base_repr(int(now * 10000), 36)[-7:] + base_repr(
int(batch_file_number), 36
) # Base 36 conversion, 0-9, A-Z
format = format.replace("$tsb64", img_id)
if "$ts" in format:
format = format.replace("$ts", str(int(now * 1000) + batch_file_number))
return filename_regex.sub("_", format)
def save_images_to_disk(images: list, filtered_images: list, req: GenerateImageRequest, task_data: TaskData):
now = time.time()
app_config = app.getConfig()
folder_format = app_config.get("folder_format", "$id")
save_dir_path = os.path.join(task_data.save_to_disk_path, format_folder_name(folder_format, req, task_data))
save_dir_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
metadata_entries = get_metadata_entries_for_request(req, task_data)
file_number = calculate_img_number(save_dir_path, task_data)
make_filename = make_filename_callback(
app_config.get("filename_format", "$p_$tsb64"),
req,
task_data,
file_number,
now=now,
)
make_filename = make_filename_callback(req, now=now)
if task_data.show_only_filtered_image or filtered_images is images:
save_images(
filtered_images,
save_dir_path,
file_name=make_filename,
output_format=task_data.output_format,
output_quality=task_data.output_quality,
output_lossless=task_data.output_lossless,
)
if task_data.metadata_output_format:
for metadata_output_format in task_data.metadata_output_format.split(","):
if metadata_output_format.lower() in ["json", "txt", "embed"]:
save_dicts(
metadata_entries,
save_dir_path,
file_name=make_filename,
output_format=metadata_output_format,
file_format=task_data.output_format,
)
save_images(filtered_images, save_dir_path, file_name=make_filename, output_format=task_data.output_format, output_quality=task_data.output_quality)
save_dicts(metadata_entries, save_dir_path, file_name=make_filename, output_format=task_data.metadata_output_format)
else:
make_filter_filename = make_filename_callback(
app_config.get("filename_format", "$p_$tsb64"),
req,
task_data,
file_number,
now=now,
suffix="filtered",
)
save_images(
images,
save_dir_path,
file_name=make_filename,
output_format=task_data.output_format,
output_quality=task_data.output_quality,
output_lossless=task_data.output_lossless,
)
save_images(
filtered_images,
save_dir_path,
file_name=make_filter_filename,
output_format=task_data.output_format,
output_quality=task_data.output_quality,
output_lossless=task_data.output_lossless,
)
if task_data.metadata_output_format:
for metadata_output_format in task_data.metadata_output_format.split(","):
if metadata_output_format.lower() in ["json", "txt", "embed"]:
save_dicts(
metadata_entries,
save_dir_path,
file_name=make_filter_filename,
output_format=task_data.metadata_output_format,
file_format=task_data.output_format,
)
make_filter_filename = make_filename_callback(req, now=now, suffix='filtered')
save_images(images, save_dir_path, file_name=make_filename, output_format=task_data.output_format, output_quality=task_data.output_quality)
save_images(filtered_images, save_dir_path, file_name=make_filter_filename, output_format=task_data.output_format, output_quality=task_data.output_quality)
save_dicts(metadata_entries, save_dir_path, file_name=make_filter_filename, output_format=task_data.metadata_output_format)
def get_metadata_entries_for_request(req: GenerateImageRequest, task_data: TaskData):
metadata = get_printable_request(req, task_data)
metadata = get_printable_request(req)
metadata.update({
'use_stable_diffusion_model': task_data.use_stable_diffusion_model,
'use_vae_model': task_data.use_vae_model,
'use_hypernetwork_model': task_data.use_hypernetwork_model,
'use_face_correction': task_data.use_face_correction,
'use_upscale': task_data.use_upscale,
})
if metadata['use_upscale'] is not None:
metadata['upscale_amount'] = task_data.upscale_amount
# if text, format it in the text format expected by the UI
is_txt_format = task_data.metadata_output_format and "txt" in task_data.metadata_output_format.lower().split(",")
is_txt_format = (task_data.metadata_output_format.lower() == 'txt')
if is_txt_format:
metadata = {TASK_TEXT_MAPPING[key]: val for key, val in metadata.items() if key in TASK_TEXT_MAPPING}
entries = [metadata.copy() for _ in range(req.num_outputs)]
for i, entry in enumerate(entries):
entry["Seed" if is_txt_format else "seed"] = req.seed + i
entry['Seed' if is_txt_format else 'seed'] = req.seed + i
return entries
def get_printable_request(req: GenerateImageRequest, task_data: TaskData):
req_metadata = req.dict()
task_data_metadata = task_data.dict()
# Save the metadata in the order defined in TASK_TEXT_MAPPING
metadata = {}
for key in TASK_TEXT_MAPPING.keys():
if key in req_metadata:
metadata[key] = req_metadata[key]
elif key in task_data_metadata:
metadata[key] = task_data_metadata[key]
# Clean up the metadata
if req.init_image is None and "prompt_strength" in metadata:
del metadata["prompt_strength"]
if task_data.use_upscale is None and "upscale_amount" in metadata:
del metadata["upscale_amount"]
if task_data.use_hypernetwork_model is None and "hypernetwork_strength" in metadata:
del metadata["hypernetwork_strength"]
if task_data.use_lora_model is None and "lora_alpha" in metadata:
del metadata["lora_alpha"]
if task_data.use_upscale != "latent_upscaler" and "latent_upscaler_steps" in metadata:
del metadata["latent_upscaler_steps"]
app_config = app.getConfig()
if not app_config.get("test_diffusers", False):
for key in (x for x in ["use_lora_model", "lora_alpha", "clip_skip", "tiling", "latent_upscaler_steps"] if x in metadata):
del metadata[key]
def get_printable_request(req: GenerateImageRequest):
metadata = req.dict()
del metadata['init_image']
del metadata['init_image_mask']
return metadata
def make_filename_callback(
filename_format: str,
req: GenerateImageRequest,
task_data: TaskData,
folder_img_number: int,
suffix=None,
now=None,
):
def make_filename_callback(req: GenerateImageRequest, suffix=None, now=None):
if now is None:
now = time.time()
def make_filename(i):
name = format_file_name(filename_format, req, task_data, now, i, folder_img_number)
name = name if suffix is None else f"{name}_{suffix}"
img_id = base64.b64encode(int(now+i).to_bytes(8, 'big')).decode() # Generate unique ID based on time.
img_id = img_id.translate({43:None, 47:None, 61:None})[-8:] # Remove + / = and keep last 8 chars.
prompt_flattened = filename_regex.sub('_', req.prompt)[:50]
name = f"{prompt_flattened}_{img_id}"
name = name if suffix is None else f'{name}_{suffix}'
return name
return make_filename
def _calculate_img_number(save_dir_path: str, task_data: TaskData):
def get_highest_img_number(accumulator: int, file: os.DirEntry) -> int:
if not file.is_file:
return accumulator
if len(list(filter(lambda e: file.name.endswith(e), app.IMAGE_EXTENSIONS))) == 0:
return accumulator
get_highest_img_number.number_of_images = get_highest_img_number.number_of_images + 1
number_match = img_number_regex.match(file.name)
if not number_match:
return accumulator
file_number = number_match.group().lstrip("0")
# Handle 00000
return int(file_number) if file_number else 0
get_highest_img_number.number_of_images = 0
highest_file_number = -1
if os.path.isdir(save_dir_path):
existing_files = list(os.scandir(save_dir_path))
highest_file_number = reduce(get_highest_img_number, existing_files, -1)
calculated_img_number = max(highest_file_number, get_highest_img_number.number_of_images - 1)
if task_data.session_id in _calculate_img_number.session_img_numbers:
calculated_img_number = max(
_calculate_img_number.session_img_numbers[task_data.session_id],
calculated_img_number,
)
calculated_img_number = calculated_img_number + 1
_calculate_img_number.session_img_numbers[task_data.session_id] = calculated_img_number
return calculated_img_number
_calculate_img_number.session_img_numbers = {}
def calculate_img_number(save_dir_path: str, task_data: TaskData):
return ImageNumber(lambda: _calculate_img_number(save_dir_path, task_data))

View File

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

View File

@ -6,7 +6,6 @@
<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/jquery-confirm.min.css">
<link rel="stylesheet" href="/media/css/fonts.css">
<link rel="stylesheet" href="/media/css/themes.css">
<link rel="stylesheet" href="/media/css/main.css">
@ -14,13 +13,10 @@
<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/searchable-models.css">
<link rel="stylesheet" href="/media/css/image-modal.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/jszip.min.js"></script>
<script src="/media/js/FileSaver.min.js"></script>
<script src="/media/js/marked.min.js"></script>
</head>
<body>
@ -28,16 +24,15 @@
<div id="top-nav">
<div id="logo">
<h1>
<img id="logo_img" src="/media/images/icon-512x512.png" >
Easy Diffusion
<small>v2.5.41 <span id="updateBranchLabel"></span></small>
<small>v2.5.10 <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" class="tab-container">
<div id="tab-container">
<span id="tab-main" class="tab active">
<span><i class="fa fa-image icon"></i> Generate</span>
</span>
@ -55,7 +50,7 @@
<div id="editor">
<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" class="tertiaryButton">Load from a file</button>
<label for="prompt"><b>Enter Prompt</b></label> <small>or</small> <button id="promptsFromFileBtn">Load from a file</button>
<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">
@ -74,7 +69,7 @@
<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" class="img_bottom_label"></span>
<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">
@ -102,7 +97,7 @@
</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 right">click an Image Modifier to remove it, right-click to temporarily disable it, use Ctrl+Mouse Wheel to adjust its weight</span></i></label>
<label>Image Modifiers <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">click an Image Modifier to remove it, right-click to temporarily disable it, use Ctrl+Mouse Wheel to adjust its weight</span></i>:</label>
<div id="editor-inputs-tags-list"></div>
</div>
@ -130,20 +125,20 @@
<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 class="model-input">
<input id="stable_diffusion_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<button id="reload-models" class="secondaryButton reloadModels"><i class='fa-solid fa-rotate'></i></button>
<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 displayNone" id="clip_skip_config">
<td><label for="clip_skip">Clip Skip:</label></td>
<td>
<input id="clip_skip" name="clip_skip" type="checkbox">
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Clip-Skip" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about Clip Skip</span></i></a>
</td>
</tr>
<tr class="pl-5"><td><label for="vae_model">Custom VAE:</label></td><td>
<input id="vae_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<!-- <tr id="modelConfigSelection" class="pl-5"><td><label for="model_config">Model Config:</i></label></td><td>
<select id="model_config" name="model_config">
</select>
</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_name">Sampler:</label></td><td>
@ -157,18 +152,11 @@
<option value="dpm2_a">DPM2 Ancestral</option>
<option value="lms">LMS</option>
<option value="dpm_solver_stability">DPM Solver (Stability AI)</option>
<option value="dpmpp_2s_a" class="k_diffusion-only">DPM++ 2s Ancestral (Karras)</option>
<option value="dpmpp_2m">DPM++ 2m (Karras)</option>
<option value="dpmpp_sde" class="k_diffusion-only">DPM++ SDE (Karras)</option>
<option value="dpm_fast" class="k_diffusion-only">DPM Fast (Karras)</option>
<option value="dpm_adaptive" class="k_diffusion-only">DPM Adaptive (Karras)</option>
<option value="ddpm" class="diffusers-only">DDPM</option>
<option value="deis" class="diffusers-only">DEIS</option>
<option value="unipc_snr" class="k_diffusion-only">UniPC SNR</option>
<option value="unipc_tu">UniPC TU</option>
<option value="unipc_snr_2" class="k_diffusion-only">UniPC SNR 2</option>
<option value="unipc_tu_2" class="k_diffusion-only">UniPC TU 2</option>
<option value="unipc_tq" class="k_diffusion-only">UniPC TQ</option>
<option value="dpmpp_2s_a">DPM++ 2s Ancestral</option>
<option value="dpmpp_2m">DPM++ 2m</option>
<option value="dpmpp_sde">DPM++ SDE</option>
<option value="dpm_fast">DPM Fast</option>
<option value="dpm_adaptive">DPM Adaptive</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>
@ -217,48 +205,26 @@
<option value="2048">2048</option>
</select>
<label for="height"><small>(height)</small></label>
<div id="small_image_warning" class="displayNone">Small image sizes can cause bad image quality</div>
</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="11" 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 id="lora_model_container" class="pl-5"><td><label for="lora_model">LoRA:</label></td><td>
<input id="lora_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
</td></tr>
<tr id="lora_alpha_container" class="pl-5">
<td><label for="lora_alpha_slider">LoRA Strength:</label></td>
<td>
<small>-2</small> <input id="lora_alpha_slider" name="lora_alpha_slider" class="editor-slider" value="50" type="range" min="-200" max="200"> <small>2</small> &nbsp;
<input id="lora_alpha" name="lora_alpha" size="4" pattern="^-?[0-9]*\.?[0-9]*$" onkeypress="preventNonNumericalInput(event)"><br/>
</td>
</tr>
<tr class="pl-5"><td><label for="hypernetwork_model">Hypernetwork:</label></td><td>
<input id="hypernetwork_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<tr class="pl-5"><td><label for="hypernetwork_model">Hypernetwork:</i></label></td><td>
<select id="hypernetwork_model" name="hypernetwork_model">
<!-- <option value="" selected>None</option> -->
</select>
</td></tr>
<tr id="hypernetwork_strength_container" class="pl-5">
<td><label for="hypernetwork_strength_slider">Hypernetwork Strength:</label></td>
<td> <input id="hypernetwork_strength_slider" name="hypernetwork_strength_slider" class="editor-slider" value="100" type="range" min="0" max="100"> <input id="hypernetwork_strength" name="hypernetwork_strength" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"><br/></td>
</tr>
<tr id="tiling_container" class="pl-5"><td><label for="tiling">Seamless Tiling:</label></td><td>
<select id="tiling" name="tiling">
<option value="none" selected>None</option>
<option value="x">Horizontal</option>
<option value="y">Vertical</option>
<option value="xy">Both</option>
</select>
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Seamless-Tiling" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about Seamless Tiling</span></i></a>
</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>
<option value="webp">webp</option>
</select>
<span id="output_lossless_container" class="displayNone">
<input id="output_lossless" name="output_lossless" type="checkbox"><label for="output_lossless">Lossless</label>
</span>
</td></tr>
<tr class="pl-5" id="output_quality_row"><td><label for="output_quality">Image Quality:</label></td><td>
<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\.]+$" onkeypress="preventNonNumericalInput(event)">
</td></tr>
</table></div>
@ -266,28 +232,18 @@
<div><ul>
<li><b class="settings-subheader">Render Settings</b></li>
<li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview <small>(uses more VRAM, slower images)</small></label></li>
<li class="pl-5" id="use_face_correction_container">
<input id="use_face_correction" name="use_face_correction" type="checkbox"> <label for="use_face_correction">Fix incorrect faces and eyes</label> <div style="display:inline-block;"><input id="gfpgan_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" /></div>
<table id="codeformer_settings" class="displayNone sub-settings">
<tr class="pl-5"><td><label for="codeformer_fidelity_slider">Strength:</label></td><td><input id="codeformer_fidelity_slider" name="codeformer_fidelity_slider" class="editor-slider" value="5" type="range" min="0" max="10"> <input id="codeformer_fidelity" name="codeformer_fidelity" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"></td></tr>
<tr class="pl-5"><td><label for="codeformer_upscale_faces">Upscale Faces:</label></td><td><input id="codeformer_upscale_faces" name="codeformer_upscale_faces" type="checkbox" checked> <label><small>(improves the resolution of faces)</small></label></td></tr>
</table>
</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="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Scale up by</label>
<select id="upscale_amount" name="upscale_amount">
<option id="upscale_amount_2x" value="2">2x</option>
<option id="upscale_amount_4x" value="4" selected>4x</option>
<option value="2">2x</option>
<option value="4" selected>4x</option>
</select>
with
<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>
<option value="latent_upscaler">Latent Upscaler 2x</option>
</select>
<table id="latent_upscaler_settings" class="displayNone sub-settings">
<tr class="pl-5"><td><label for="latent_upscaler_steps_slider">Upscaling Steps:</label></td><td><input id="latent_upscaler_steps_slider" name="latent_upscaler_steps_slider" class="editor-slider" value="10" type="range" min="1" max="50"> <input id="latent_upscaler_steps" name="latent_upscaler_steps" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"></td></tr>
</table>
</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>
@ -319,45 +275,14 @@
</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! :)
</div>
<div id="preview-content">
<div id="preview-tools" class="displayNone">
<button id="clear-all-previews" class="secondaryButton"><i class="fa-solid fa-trash-can icon"></i> Clear All</button>
<button class="tertiaryButton" id="show-download-popup"><i class="fa-solid fa-download"></i> Download images</button>
<div class="display-settings">
<button id="undo" class="displayNone primaryButton">
Undo <i class="fa-solid fa-rotate-left icon"></i>
<span class="simple-tooltip left">Undo last remove</span>
</button>
<span class="auto-scroll"></span> <!-- hack for Rabbit Hole update -->
<button id="auto_scroll_btn" class="tertiaryButton">
<i class="fa-solid fa-arrows-up-to-line icon"></i>
<input id="auto_scroll" name="auto_scroll" type="checkbox" style="display: none">
<span class="simple-tooltip left">
Scroll to generated image (<span class="state">OFF</span>)
</span>
</button>
<button class="dropdown tertiaryButton">
<i class="fa-solid fa-magnifying-glass-plus icon dropbtn"></i>
<span class="simple-tooltip left">
Image Size
</span>
</button>
<div class="dropdown-content">
<div class="dropdown-item">
<input id="thumbnail_size" name="thumbnail_size" class="editor-slider" type="range" value="70" min="5" max="200" oninput="sliderUpdate(event)">
<input id="thumbnail_size-input" name="thumbnail_size-input" size="3" value="70" pattern="^[0-9.]+$" onkeypress="preventNonNumericalInput(event)" oninput="sliderUpdate(event)">&nbsp;%
</div>
</div>
</div>
<div class="clearfix" style="clear: both;"></div>
</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>
@ -365,16 +290,10 @@
<div id="tab-content-settings" class="tab-content">
<div id="system-settings" class="tab-content-inner">
<h1>System Settings</h1>
<div class="parameters-table" id="system-settings-table"></div>
<div class="parameters-table"></div>
<br/>
<button id="save-system-settings-btn" class="primaryButton">Save</button>
<br/><br/>
<div id="share-easy-diffusion">
<h3><i class="fa fa-user-group"></i> Share Easy Diffusion</h3>
<div class="parameters-table" id="system-settings-network-table">
</div>
</div>
<br/><br/>
<div>
<h3><i class="fa fa-microchip icon"></i> System Info</h3>
<div id="system-info">
@ -433,31 +352,6 @@
</div>
<div class="popup" id="download-images-popup">
<div>
<i class="close-button fa-solid fa-xmark"></i>
<h1>Download all images</h1>
<div class="parameters-table">
<div>
<div><i class="fa fa-file-zipper"></i></div>
<div><label for="theme">Download as a ZIP file</label><small>Instead of downloading individual files, generate one zip file with all images</small></div>
<div><div class="input-toggle"><input id="zip_toggle" name="zip_toggle" checked="" type="checkbox"><label for="zip_toggle"></label></div></div>
</div>
<div id="download-add-folders">
<div><i class="fa fa-folder-tree"></i></div>
<div><label for="theme">Add per-job folders</label><small>Place images into job folders</small></div>
<div><div class="input-toggle"><input id="tree_toggle" name="tree_toggle" checked="" type="checkbox"><label for="tree_toggle"></label></div></div>
</div>
<div>
<div><i class="fa fa-sliders"></i></div>
<div><label for="theme">Add metadata files</label><small>For each image, also download a JSON file with all the settings used to generate the image</small></div>
<div><div class="input-toggle"><input id="json_toggle" name="json_toggle" checked="" type="checkbox"><label for="json_toggle"></label></div></div>
</div>
</div>
<br/>
<button id="save-all-images" class="primaryButton"><i class="fa-solid fa-images"></i> Start download</button>
</div>
</div>
<div id="save-settings-config" class="popup">
<div>
<i class="close-button fa-solid fa-xmark"></i>
@ -468,12 +362,12 @@
</div>
</div>
<div id="modifier-settings-config" class="popup" tabindex="0">
<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" spellcheck="false"></textarea>
<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>
@ -531,12 +425,10 @@
<script src="media/js/image-modifiers.js"></script>
<script src="media/js/auto-save.js"></script>
<script src="media/js/searchable-models.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/js/image-modal.js"></script>
<script>
async function init() {
await initSettings()
@ -548,13 +440,12 @@ async function init() {
SD.init({
events: {
statusChange: setServerStatus,
idle: onIdle,
ping: tunnelUpdate
statusChange: setServerStatus
, idle: onIdle
}
})
// playSound()
playSound()
}
init()

View File

@ -69,15 +69,13 @@
}
.parameters-table > div:first-child {
border-top-left-radius: 12px;
border-top-right-radius: 12px;
border-radius: 12px 12px 0px 0px;
}
.parameters-table > div:last-child {
border-bottom-left-radius: 12px;
border-bottom-right-radius: 12px;
border-radius: 0px 0px 12px 12px;
}
.parameters-table .fa-fire {
color: #F7630C;
}
}

View File

@ -3,7 +3,7 @@
font-family: 'Work Sans';
font-style: normal;
font-weight: 400;
src: local('Work Sans'),
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+ */
}
@ -13,7 +13,7 @@
font-family: 'Work Sans';
font-style: normal;
font-weight: 600;
src: local('Work Sans'),
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+ */
}
@ -23,7 +23,7 @@
font-family: 'Work Sans';
font-style: normal;
font-weight: 700;
src: local('Work Sans'),
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+ */
}
@ -33,8 +33,8 @@
font-family: 'Work Sans';
font-style: normal;
font-weight: 800;
src: local('Work Sans'),
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+ */
}

View File

@ -31,7 +31,7 @@
}
.editor-options-container > * > *.active {
border: 1px solid #3584e4;
border: 2px solid #3584e4;
}
.image_editor_opacity .editor-options-container > * > *:not(.active) {
@ -96,7 +96,7 @@
.editor-controls-center {
/* background: var(--background-color2); */
flex: 0;
flex: 1;
display: flex;
justify-content: center;
align-items: center;
@ -105,8 +105,6 @@
.editor-controls-center > div {
position: relative;
background: black;
margin: 20pt;
margin-top: 40pt;
}
.editor-controls-center canvas {
@ -151,25 +149,17 @@
pointer-events: none;
}
.image-editor-popup {
--popup-margin: 16px;
--popup-padding: 24px;
}
@media screen and (min-width: 700px) {
.image-editor-popup {
overflow-y: auto;
}
}
.image-editor-popup > div {
margin: var(--popup-margin);
padding: var(--popup-padding);
min-height: calc(99h - (2 * var(--popup-margin)));
max-width: fit-content;
min-width: fit-content;
margin-left: auto;
margin-right: auto;
min-height: calc(100vh - (2 * var(--popup-margin)));
max-width: none;
}
.image-editor-popup h1 {
@ -195,7 +185,7 @@
.image-editor-popup > div > div {
min-height: calc(99vh - (2 * var(--popup-margin)) - (2 * var(--popup-padding)));
min-height: calc(100vh - (2 * var(--popup-margin)) - (2 * var(--popup-padding)));
}
.inpainter .image_editor_color {
@ -223,10 +213,3 @@
.image-editor-popup h4 {
text-align: left;
}
.image-editor-popup .load_mask {
display: none;
}
.inpainter .load_mask {
display: flex;
}

View File

@ -1,96 +0,0 @@
#viewFullSizeImgModal {
--popup-padding: 24px;
position: sticky;
padding: var(--popup-padding);
pointer-events: none;
width: 100vw;
height: 100vh;
box-sizing: border-box;
display: flex;
justify-content: center;
align-items: center;
overflow: hidden;
z-index: 1001;
}
#viewFullSizeImgModal:not(.active) {
display: none;
}
#viewFullSizeImgModal > * {
pointer-events: auto;
margin: 0;
padding: 0;
box-sizing: border-box;
}
#viewFullSizeImgModal .backdrop {
max-width: unset;
width: 100%;
max-height: unset;
height: 100%;
inset: 0;
position: absolute;
top: 0;
left: 0;
z-index: 1001;
opacity: .5;
border: none;
box-shadow: none;
overflow: hidden;
}
#viewFullSizeImgModal .content {
min-height: initial;
max-height: calc(100vh - (var(--popup-padding) * 2));
height: fit-content;
min-width: initial;
max-width: calc(100vw - (var(--popup-padding) * 2));
width: fit-content;
z-index: 1003;
overflow: visible;
}
#viewFullSizeImgModal .image-wrapper {
min-height: initial;
max-height: calc(100vh - (var(--popup-padding) * 2));
height: fit-content;
min-width: initial;
max-width: calc(100vw - (var(--popup-padding) * 2));
width: fit-content;
box-sizing: border-box;
pointer-events: auto;
margin: 0;
padding: 0;
overflow: auto;
}
#viewFullSizeImgModal img.natural-zoom {
max-width: calc(100vh - (var(--popup-padding) * 2) - 4px);
max-height: calc(100vh - (var(--popup-padding) * 2) - 4px);
}
#viewFullSizeImgModal img:not(.natural-zoom) {
cursor: grab;
}
#viewFullSizeImgModal .grabbing img:not(.natural-zoom) {
cursor: grabbing;
}
#viewFullSizeImgModal .content > div::-webkit-scrollbar-track, #viewFullSizeImgModal .content > div::-webkit-scrollbar-corner {
background: rgba(0, 0, 0, .5)
}
#viewFullSizeImgModal .menu-bar {
position: absolute;
top: 0;
right: 0;
padding-right: var(--scrollbar-width);
}
#viewFullSizeImgModal .menu-bar .tertiaryButton {
font-size: 1.2em;
margin: 12px 12px 0 0;
cursor: pointer;
}

View File

@ -27,11 +27,6 @@ code {
padding: 2px 4px;
border-radius: 4px;
}
#logo_img {
width: 32px;
height: 32px;
transform: translateY(4px);
}
#prompt {
width: 100%;
height: 65pt;
@ -98,23 +93,11 @@ code {
#footer-spacer {
flex: 0.7
}
.imgInfoLabel {
.imgSeedLabel {
font-size: 0.8em;
background-color: var(--background-color2);
}
.imgSeedLabel {
border-radius: 3px;
padding: 5px;
border-radius: 0px 3px 3px 0px;
}
.imgExpandBtn {
border-radius: 3px 0px 0px 3px;
border-right: 1px solid var(--tertiary-border-color);
padding: 5px 5px 5px;
padding-left: 7px;
cursor: pointer;
}
.imgExpandBtn:hover {
background-color: var(--accent-color);
}
.imgItem {
display: inline-block;
@ -124,7 +107,6 @@ code {
.imgContainer {
display: flex;
justify-content: flex-end;
position: relative;
}
.imgItemInfo {
padding-bottom: 0.5em;
@ -132,38 +114,16 @@ code {
align-items: flex-end;
flex-direction: column;
position: absolute;
padding-right: 5pt;
padding-top: 6pt;
padding: 5px;
opacity: 0;
transition: 0.1s all;
}
.imgPreviewItemClearBtn {
opacity: 0;
}
.imgContainer .img_bottom_label {
opacity: 0;
}
.imgPreviewItemClearBtn:hover {
background: rgb(177, 27, 0);
}
.imgContainer:hover > .imgItemInfo {
opacity: 1;
}
.imgContainer:hover > .imgPreviewItemClearBtn {
opacity: 1;
}
.imgContainer:hover > .img_bottom_label {
opacity: 60%;
}
.imgItemInfo > * {
.imgItemInfo * {
margin-bottom: 7px;
}
.imgItemInfo .tasksBtns {
margin-left: 5pt;
}
.imgItem .image_clear_btn {
transform: translate(40%, -50%);
}
#container {
min-height: 100vh;
width: 100%;
@ -219,7 +179,7 @@ code {
flex: 0 0 70px;
background: var(--accent-color);
border: var(--primary-button-border);
color: var(--accent-text-color);
color: rgb(255, 221, 255);
width: 100%;
height: 30pt;
}
@ -238,10 +198,6 @@ code {
#stopImage:hover {
background: rgb(177, 27, 0);
}
#undo {
float: right;
margin-left: 5px;
}
div#render-buttons {
gap: 3px;
@ -299,7 +255,6 @@ div.img-preview img {
width:100%;
height: 100%;
max-height: 70vh;
cursor: pointer;
}
.line-separator {
background: var(--background-color3);
@ -313,7 +268,8 @@ div.img-preview img {
#server-status {
position: absolute;
right: 16px;
top: 4px;
top: 50%;
transform: translateY(-50%);
text-align: right;
}
#server-status-color {
@ -339,7 +295,6 @@ div.img-preview img {
position: relative;
background: var(--background-color4);
display: flex;
padding: 12px 0 0;
}
.tab .icon {
padding-right: 4pt;
@ -348,7 +303,7 @@ div.img-preview img {
}
#logo {
display: inline;
padding: 0 12px 12px;
padding: 12px;
white-space: nowrap;
}
#logo h1 {
@ -433,44 +388,17 @@ div.img-preview img {
display: none;
position: absolute;
z-index: 2;
background: var(--background-color4);
border: 2px solid var(--background-color2);
border-radius: 7px;
padding: 0px;
padding: 5px;
margin-bottom: 15px;
box-shadow: 0 20px 28px 0 rgba(0, 0, 0, 0.75), 0 6px 20px 0 rgba(0, 0, 0, 0.75);
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;
}
.dropdown:hover + .dropdown-content {
display: block;
}
.dropdown-content:hover {
display: block;
}
.display-settings {
float: right;
position: relative;
}
.display-settings .dropdown-content {
right: 0px;
top: 12pt;
}
.dropdown-item {
padding: 4px;
background: var(--background-color1);
border: 2px solid var(--background-color4);
}
.dropdown-item:first-child {
border-radius: 7px 7px 0px 0px;
}
.dropdown-item:last-child {
border-radius: 0px 0px 7px 7px;
}
.imageTaskContainer {
border: 1px solid var(--background-color2);
@ -526,7 +454,6 @@ div.img-preview img {
background: var(--accent-color);
border: var(--primary-button-border);
color: rgb(255, 221, 255);
padding: 3pt 6pt;
}
.secondaryButton {
background: rgb(132, 8, 0);
@ -538,49 +465,30 @@ div.img-preview img {
.secondaryButton:hover {
background: rgb(177, 27, 0);
}
.tertiaryButton {
background: var(--tertiary-background-color);
color: var(--tertiary-color);
border: 1px solid var(--tertiary-border-color);
padding: 3pt 6pt;
border-radius: 5px;
}
.tertiaryButton:hover {
background: hsl(var(--accent-hue), 100%, calc(var(--accent-lightness) + 6%));
color: var(--accent-text-color);
}
.tertiaryButton.pressed {
border-style: inset;
background: hsl(var(--accent-hue), 100%, calc(var(--accent-lightness) + 6%));
color: var(--accent-text-color);
}
.useSettings {
background: var(--accent-color);
border: 1px solid var(--accent-color);
color: rgb(255, 221, 255);
padding: 3pt 6pt;
margin-right: 6pt;
float: right;
}
.useSettings:hover {
background: hsl(var(--accent-hue), 100%, calc(var(--accent-lightness) + 6%));
}
.stopTask {
float: right;
}
#preview-tools {
display: none;
padding: 4pt;
}
#preview-tools .display-settings .dropdown-content {
right: -6px;
top: 20px;
box-shadow: none;
width: max-content;
}
.taskConfig {
font-size: 10pt;
color: #aaa;
margin-bottom: 5pt;
margin-top: 5pt;
}
.taskConfigContainer {
display: inline;
}
.img-batch {
display: inline;
}
@ -655,9 +563,6 @@ div.img-preview img {
} */
#init_image_size_box {
border-radius: 6px 0px;
}
.img_bottom_label {
position: absolute;
right: 0px;
bottom: 0px;
@ -667,6 +572,7 @@ div.img-preview img {
text-shadow: 0px 0px 4px black;
opacity: 60%;
font-size: 12px;
border-radius: 6px 0px;
}
#editor-settings {
@ -683,6 +589,7 @@ div.img-preview img {
}
#editor-settings-entries ul {
margin: 0px;
padding: 0px;
}
@ -829,16 +736,9 @@ input::file-selector-button {
right: calc(var(--input-border-size) + var(--input-switch-padding));
opacity: 1;
}
.model-filter {
width: 90%;
padding-right: 20px;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
}
/* Small screens */
@media screen and (max-width: 1365px) {
@media screen and (max-width: 1265px) {
#top-nav {
flex-direction: column;
}
@ -873,6 +773,12 @@ input::file-selector-button {
width: 100%;
object-fit: contain;
}
.dropdown-content {
width: auto !important;
transform: none !important;
left: 0px;
right: 0px;
}
#editor {
padding: 16px 8px;
}
@ -888,6 +794,9 @@ input::file-selector-button {
.tab .icon {
padding-right: 0px;
}
#server-status {
top: 75%;
}
.popup > div {
padding-left: 5px !important;
padding-right: 5px !important;
@ -902,12 +811,6 @@ input::file-selector-button {
.simple-tooltip {
display: none;
}
#preview-tools button {
font-size: 0px;
}
#preview-tools button .icon {
font-size: 12pt;
}
}
@media screen and (max-width: 500px) {
@ -940,7 +843,7 @@ input::file-selector-button {
#promptsFromFileBtn {
font-size: 9pt;
display: inline;
padding: 2pt;
background-color: var(--accent-color);
}
.section-button {
@ -973,19 +876,18 @@ input::file-selector-button {
/* SIMPLE TOOTIP */
.simple-tooltip {
border-radius: 3px;
font-weight: bold;
font-size: 12px;
border-radius: 3px;
font-weight: bold;
font-size: 12px;
background-color: var(--background-color3);
visibility: hidden;
opacity: 0;
position: absolute;
width: max-content;
max-width: 300px;
padding: 8px 12px;
transition: 0.3s all;
z-index: 1000;
opacity: 0;
position: absolute;
width: max-content;
max-width: 300px;
padding: 8px 12px;
transition: 0.3s all;
pointer-events: none;
}
@ -1127,11 +1029,9 @@ input::file-selector-button {
}
/* TABS */
.tab-container {
#tab-container {
display: flex;
align-items: flex-end;
overflow-x: auto;
overflow-y: hidden;
}
.tab {
@ -1226,11 +1126,6 @@ div.top-right {
right: 8px;
}
#small_image_warning {
font-size: smaller;
color: var(--status-orange);
}
button#save-system-settings-btn {
padding: 4pt 8pt;
}
@ -1241,10 +1136,6 @@ button#save-system-settings-btn {
line-height: 200%;
}
#download-images-popup .parameters-table > div {
background: var(--background-color1);
}
/* SCROLLBARS */
:root {
--scrollbar-width: 14px;
@ -1291,94 +1182,3 @@ body.wait-pause {
50% { border: solid 12px var(--background-color1); }
100% { border: solid 12px var(--accent-color); }
}
.jconfirm.jconfirm-modern .jconfirm-box div.jconfirm-title-c {
color: var(--button-text-color);
}
.jconfirm.jconfirm-modern .jconfirm-box {
background-color: var(--background-color1);
}
.displayNone {
display:none !important;
}
.sub-settings {
padding-top: 3pt;
padding-bottom: 3pt;
padding-left: 5pt;
}
#cloudflare-address {
background-color: var(--background-color3);
padding: 6px;
border-radius: var(--input-border-radius);
border: var(--input-border-size) solid var(--input-border-color);
margin-top: 0.2em;
margin-bottom: 0.2em;
display: inline-block;
}
#copy-cloudflare-address {
padding: 4px 8px;
margin-left: 0.5em;
}
.expandedSettingRow {
background: var(--background-color1);
width: 95%;
border-radius: 4pt;
margin-top: 5pt;
margin-bottom: 3pt;
}
/* TOAST NOTIFICATIONS */
.toast-notification {
position: fixed;
bottom: 10px;
right: -300px;
width: 300px;
background-color: #333;
color: #fff;
padding: 10px 20px;
border-radius: 5px;
box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
z-index: 9999;
animation: slideInRight 0.5s ease forwards;
transition: bottom 0.5s ease; /* Add a transition to smoothly reposition the toasts */
}
.toast-notification-error {
color: red;
}
@keyframes slideInRight {
from {
right: -300px;
}
to {
right: 10px;
}
}
.toast-notification.hide {
animation: slideOutRight 0.5s ease forwards;
}
@keyframes slideOutRight {
from {
right: 10px;
}
to {
right: -300px;
}
}
@keyframes slideDown {
from {
bottom: 10px;
}
to {
bottom: 0;
}
}

View File

@ -153,10 +153,6 @@
position: absolute;
z-index: 3;
}
.modifier-card-overlay:hover ~ .modifier-card-container .modifier-card-label.tooltip .tooltip-text {
visibility: visible;
opacity: 1;
}
.modifier-card:hover > .modifier-card-image-container .modifier-card-image-overlay {
opacity: 1;
}
@ -224,4 +220,4 @@
#modifier-settings-config textarea {
width: 90%;
height: 150px;
}
}

View File

@ -1,99 +0,0 @@
.model-list {
position: absolute;
margin-block-start: 2px;
display: none;
padding-inline-start: 0;
max-height: 200px;
overflow: auto;
background: var(--input-background-color);
border: var(--input-border-size) solid var(--input-border-color);
border-radius: var(--input-border-radius);
color: var(--input-text-color);
z-index: 1;
line-height: normal;
}
.model-list ul {
padding-right: 20px;
padding-inline-start: 0;
margin-top: 3pt;
}
.model-list li {
padding-top: 3px;
padding-bottom: 3px;
}
.model-list .icon {
padding-right: 3pt;
}
.model-result {
list-style: none;
}
.model-no-result {
color: var(--text-color);
list-style: none;
padding: 3px 6px 3px 6px;
font-size: 9pt;
font-style: italic;
display: none;
}
.model-list li.model-folder {
color: var(--text-color);
list-style: none;
padding: 6px 6px 6px 6px;
font-size: 9pt;
font-weight: bold;
border-top: 1px solid var(--background-color1);
}
.model-list li.model-file {
color: var(--input-text-color);
list-style: none;
padding-left: 12px;
padding-right:20px;
font-size: 10pt;
font-weight: normal;
transition: none;
transition-property: none;
cursor: default;
}
.model-list li.model-file.in-root-folder {
padding-left: 6px;
}
.model-list li.model-file.selected {
background: grey;
}
.model-selector {
cursor: pointer;
}
.model-selector-arrow {
position: absolute;
width: 17px;
margin: 5px -17px;
padding-top: 3px;
cursor: pointer;
font-size: 8pt;
transition: none;
}
.model-input {
white-space: nowrap;
}
.reloadModels {
background: var(--background-color2);
border: none;
padding: 0px 0px;
}
#reload-models.secondaryButton:hover {
background: var(--background-color2);
}

View File

@ -27,19 +27,12 @@
--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));
--accent-text-color: rgb(255, 221, 255);
--primary-button-border: none;
--input-switch-padding: 1px;
--input-height: 18px;
--tertiary-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (2 * var(--value-step))));
--tertiary-border-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (3 * var(--value-step))));
--tertiary-color: var(--input-text-color);
/* Main theme color, hex color fallback. */
--theme-color-fallback: #673AB6;
--status-orange: rgb(200, 139, 0);
--status-green: green;
--status-red: red;
}
.theme-light {
@ -55,11 +48,6 @@
--input-border-color: grey;
--theme-color-fallback: #aaaaaa;
--tertiary-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (16.8 * var(--value-step))));
--tertiary-border-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (12 * var(--value-step))));
--accent-text-color: white;
}
.theme-discord {
@ -76,10 +64,6 @@
--input-border-color: var(--input-background-color);
--theme-color-fallback: #202225;
--tertiary-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (3.5 * var(--value-step))));
--tertiary-border-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (4.5 * var(--value-step))));
--accent-text-color: white;
}
.theme-cool-blue {
@ -97,10 +81,6 @@
--accent-hue: 212;
--theme-color-fallback: #0056b8;
--tertiary-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (3.5 * var(--value-step))));
--tertiary-border-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (4.5 * var(--value-step))));
--accent-text-color: #f7fbff;
}
@ -117,9 +97,6 @@
--input-background-color: var(--background-color3);
--theme-color-fallback: #5300b8;
--tertiary-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (3.5 * var(--value-step))));
--tertiary-border-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (4.5 * var(--value-step))));
}
.theme-super-dark {
@ -154,9 +131,6 @@
--input-background-color: hsl(222, var(--main-saturation), calc(var(--value-base) - (2 * var(--value-step))));
--input-text-color: #FF0000;
--input-border-color: #005E05;
--tertiary-color: white;
--accent-text-color: #f7fbff;
}
@ -183,4 +157,4 @@
border: none;
box-shadow: 0px 1px 2px rgba(0, 0, 0, 0.25);
border-radius: 10px;
}
}

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@ -1,2 +0,0 @@
(function(a,b){if("function"==typeof define&&define.amd)define([],b);else if("undefined"!=typeof exports)b();else{b(),a.FileSaver={exports:{}}.exports}})(this,function(){"use strict";function b(a,b){return"undefined"==typeof b?b={autoBom:!1}:"object"!=typeof b&&(console.warn("Deprecated: Expected third argument to be a object"),b={autoBom:!b}),b.autoBom&&/^\s*(?:text\/\S*|application\/xml|\S*\/\S*\+xml)\s*;.*charset\s*=\s*utf-8/i.test(a.type)?new Blob(["\uFEFF",a],{type:a.type}):a}function c(a,b,c){var d=new XMLHttpRequest;d.open("GET",a),d.responseType="blob",d.onload=function(){g(d.response,b,c)},d.onerror=function(){console.error("could not download file")},d.send()}function d(a){var b=new XMLHttpRequest;b.open("HEAD",a,!1);try{b.send()}catch(a){}return 200<=b.status&&299>=b.status}function e(a){try{a.dispatchEvent(new MouseEvent("click"))}catch(c){var b=document.createEvent("MouseEvents");b.initMouseEvent("click",!0,!0,window,0,0,0,80,20,!1,!1,!1,!1,0,null),a.dispatchEvent(b)}}var f="object"==typeof window&&window.window===window?window:"object"==typeof self&&self.self===self?self:"object"==typeof global&&global.global===global?global:void 0,a=/Macintosh/.test(navigator.userAgent)&&/AppleWebKit/.test(navigator.userAgent)&&!/Safari/.test(navigator.userAgent),g=f.saveAs||("object"!=typeof window||window!==f?function(){}:"download"in HTMLAnchorElement.prototype&&!a?function(b,g,h){var i=f.URL||f.webkitURL,j=document.createElement("a");g=g||b.name||"download",j.download=g,j.rel="noopener","string"==typeof b?(j.href=b,j.origin===location.origin?e(j):d(j.href)?c(b,g,h):e(j,j.target="_blank")):(j.href=i.createObjectURL(b),setTimeout(function(){i.revokeObjectURL(j.href)},4E4),setTimeout(function(){e(j)},0))}:"msSaveOrOpenBlob"in navigator?function(f,g,h){if(g=g||f.name||"download","string"!=typeof f)navigator.msSaveOrOpenBlob(b(f,h),g);else if(d(f))c(f,g,h);else{var i=document.createElement("a");i.href=f,i.target="_blank",setTimeout(function(){e(i)})}}:function(b,d,e,g){if(g=g||open("","_blank"),g&&(g.document.title=g.document.body.innerText="downloading..."),"string"==typeof b)return c(b,d,e);var h="application/octet-stream"===b.type,i=/constructor/i.test(f.HTMLElement)||f.safari,j=/CriOS\/[\d]+/.test(navigator.userAgent);if((j||h&&i||a)&&"undefined"!=typeof FileReader){var k=new FileReader;k.onloadend=function(){var a=k.result;a=j?a:a.replace(/^data:[^;]*;/,"data:attachment/file;"),g?g.location.href=a:location=a,g=null},k.readAsDataURL(b)}else{var l=f.URL||f.webkitURL,m=l.createObjectURL(b);g?g.location=m:location.href=m,g=null,setTimeout(function(){l.revokeObjectURL(m)},4E4)}});f.saveAs=g.saveAs=g,"undefined"!=typeof module&&(module.exports=g)});

View File

@ -13,10 +13,8 @@ const SETTINGS_IDS_LIST = [
"num_outputs_total",
"num_outputs_parallel",
"stable_diffusion_model",
"clip_skip",
"vae_model",
"hypernetwork_model",
"lora_model",
"sampler_name",
"width",
"height",
@ -24,19 +22,13 @@ const SETTINGS_IDS_LIST = [
"guidance_scale",
"prompt_strength",
"hypernetwork_strength",
"lora_alpha",
"tiling",
"output_format",
"output_quality",
"output_lossless",
"negative_prompt",
"stream_image_progress",
"use_face_correction",
"gfpgan_model",
"use_upscale",
"upscale_amount",
"latent_upscaler_steps",
"block_nsfw",
"show_only_filtered_image",
"upscale_model",
"preview-image",
@ -50,32 +42,27 @@ const SETTINGS_IDS_LIST = [
"metadata_output_format",
"auto_save_settings",
"apply_color_correction",
"process_order_toggle",
"thumbnail_size",
"auto_scroll",
"zip_toggle",
"tree_toggle",
"json_toggle",
"process_order_toggle"
]
const IGNORE_BY_DEFAULT = ["prompt"]
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" },
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" },
{ id: "container", name: "Other" }
]
async function initSettings() {
SETTINGS_IDS_LIST.forEach((id) => {
SETTINGS_IDS_LIST.forEach(id => {
var element = document.getElementById(id)
if (!element) {
console.error(`Missing settings element ${id}`)
}
if (id in SETTINGS) {
// don't create it again
if (id in SETTINGS) { // don't create it again
return
}
SETTINGS[id] = {
@ -84,30 +71,27 @@ async function initSettings() {
label: getSettingLabel(element),
default: getSetting(element),
value: getSetting(element),
ignore: IGNORE_BY_DEFAULT.includes(id),
ignore: IGNORE_BY_DEFAULT.includes(id)
}
element.addEventListener("input", settingChangeHandler)
element.addEventListener("change", settingChangeHandler)
})
var unsorted_settings_ids = [...SETTINGS_IDS_LIST]
SETTINGS_SECTIONS.forEach((section) => {
SETTINGS_SECTIONS.forEach(section => {
var name = section.name
var element = document.getElementById(section.id)
var unsorted_ids = unsorted_settings_ids.map((id) => `#${id}`).join(",")
var children = unsorted_ids == "" ? [] : Array.from(element.querySelectorAll(unsorted_ids))
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) => {
children.forEach(e => {
section.keys.push(e.id)
})
unsorted_settings_ids = unsorted_settings_ids.filter((id) => children.find((e) => e.id == id) == undefined)
unsorted_settings_ids = unsorted_settings_ids.filter(id => children.find(e => e.id == id) == undefined)
})
loadSettings()
}
function getSetting(element) {
if (element.dataset && "path" in element.dataset) {
return element.dataset.path
}
if (typeof element === "string" || element instanceof String) {
element = SETTINGS[element].element
}
@ -117,10 +101,6 @@ function getSetting(element) {
return element.value
}
function setSetting(element, value) {
if (element.dataset && "path" in element.dataset) {
element.dataset.path = value
return // no need to dispatch any event here because the models are not loaded yet
}
if (typeof element === "string" || element instanceof String) {
element = SETTINGS[element].element
}
@ -130,7 +110,8 @@ function setSetting(element, value) {
}
if (element.type == "checkbox") {
element.checked = value
} else {
}
else {
element.value = value
}
element.dispatchEvent(new Event("input"))
@ -138,11 +119,11 @@ function setSetting(element, value) {
}
function saveSettings() {
var saved_settings = Object.values(SETTINGS).map((setting) => {
var saved_settings = Object.values(SETTINGS).map(setting => {
return {
key: setting.key,
value: setting.value,
ignore: setting.ignore,
ignore: setting.ignore
}
})
localStorage.setItem(SETTINGS_KEY, JSON.stringify(saved_settings))
@ -153,16 +134,16 @@ 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) {
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) => {
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
console.warn(`Attempted to load setting ${saved_setting.key}, but no setting found`);
return null;
}
setting.ignore = saved_setting.ignore
if (!setting.ignore) {
@ -171,25 +152,10 @@ function loadSettings() {
}
})
CURRENTLY_LOADING_SETTINGS = false
} else if (localStorage.length < 2) {
// localStorage is too short for OldSettings
// So this is likely the first time Easy Diffusion is running.
// Initialize vram_usage_level based on the available VRAM
function initGPUProfile(event) {
if ( "detail" in event
&& "active" in event.detail
&& "cuda:0" in event.detail.active
&& event.detail.active["cuda:0"].mem_total <4.5 )
{
vramUsageLevelField.value = "low"
vramUsageLevelField.dispatchEvent(new Event("change"))
}
document.removeEventListener("system_info_update", initGPUProfile)
}
document.addEventListener("system_info_update", initGPUProfile)
} else {
}
else {
CURRENTLY_LOADING_SETTINGS = true
tryLoadOldSettings()
tryLoadOldSettings();
CURRENTLY_LOADING_SETTINGS = false
saveSettings()
}
@ -197,9 +163,9 @@ function loadSettings() {
function loadDefaultSettingsSection(section_id) {
CURRENTLY_LOADING_SETTINGS = true
var section = SETTINGS_SECTIONS.find((s) => s.id == section_id)
section.keys.forEach((key) => {
var setting = SETTINGS[key]
var section = SETTINGS_SECTIONS.find(s => s.id == section_id);
section.keys.forEach(key => {
var setting = SETTINGS[key];
setting.value = setting.default
setSetting(setting.element, setting.value)
})
@ -235,10 +201,10 @@ function getSettingLabel(element) {
function fillSaveSettingsConfigTable() {
saveSettingsConfigTable.textContent = ""
SETTINGS_SECTIONS.forEach((section) => {
SETTINGS_SECTIONS.forEach(section => {
var section_row = `<tr><th>${section.name}</th><td></td></tr>`
saveSettingsConfigTable.insertAdjacentHTML("beforeend", section_row)
section.keys.forEach((key) => {
section.keys.forEach(key => {
var setting = SETTINGS[key]
var element = setting.element
var checkbox_id = `shouldsave_${element.id}`
@ -251,7 +217,7 @@ function fillSaveSettingsConfigTable() {
var newrow = `<tr><td><label for="${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) => {
checkbox.addEventListener("input", event => {
setting.ignore = !checkbox.checked
saveSettings()
})
@ -262,6 +228,9 @@ function fillSaveSettingsConfigTable() {
// configureSettingsSaveBtn
var autoSaveSettings = document.getElementById("auto_save_settings")
var configSettingsButton = document.createElement("button")
configSettingsButton.textContent = "Configure"
@ -270,75 +239,70 @@ autoSaveSettings.insertAdjacentElement("beforebegin", configSettingsButton)
autoSaveSettings.addEventListener("change", () => {
configSettingsButton.style.display = autoSaveSettings.checked ? "block" : "none"
})
configSettingsButton.addEventListener("click", () => {
configSettingsButton.addEventListener('click', () => {
fillSaveSettingsConfigTable()
saveSettingsConfigOverlay.classList.add("active")
})
resetImageSettingsButton.addEventListener("click", (event) => {
loadDefaultSettingsSection("editor-settings")
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",
"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) => {
Object.keys(saved_settings.should_save).forEach(key => {
key = key in old_map ? old_map[key] : key
if (!(key in SETTINGS)) return
SETTINGS[key].ignore = !saved_settings.should_save[key]
})
Object.keys(saved_settings.values).forEach((key) => {
});
Object.keys(saved_settings.values).forEach(key => {
key = key in old_map ? old_map[key] : key
if (!(key in SETTINGS)) return
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",
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)
var individual_settings_map = { // maps old localStorage-key to new SETTINGS-key
"soundEnabled": "sound_toggle",
"saveToDisk": "save_to_disk",
"useCPU": "use_cpu",
"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
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)
) {
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)
localStorage.removeItem(localStorageKey);
}
})
}

View File

@ -1,25 +1,25 @@
"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", "webp"]
const TEXT_EXTENSIONS = ['txt', 'json']
const IMAGE_EXTENSIONS = ['jpg', 'jpeg', 'png', 'bmp', 'tiff', 'tif', 'tga']
function parseBoolean(stringValue) {
if (typeof stringValue === "boolean") {
if (typeof stringValue === 'boolean') {
return stringValue
}
if (typeof stringValue === "number") {
if (typeof stringValue === 'number') {
return stringValue !== 0
}
if (typeof stringValue !== "string") {
if (typeof stringValue !== 'string') {
return false
}
switch (stringValue?.toLowerCase()?.trim()) {
switch(stringValue?.toLowerCase()?.trim()) {
case "true":
case "yes":
case "on":
case "1":
return true
return true;
case "false":
case "no":
@ -28,77 +28,67 @@ function parseBoolean(stringValue) {
case "none":
case null:
case undefined:
return false
return false;
}
try {
return Boolean(JSON.parse(stringValue))
return Boolean(JSON.parse(stringValue));
} catch {
return Boolean(stringValue)
}
}
// keep in sync with `ui/easydiffusion/utils/save_utils.py`
const TASK_MAPPING = {
prompt: {
name: "Prompt",
prompt: { name: 'Prompt',
setUI: (prompt) => {
promptField.value = prompt
},
readUI: () => promptField.value,
parse: (val) => val,
parse: (val) => val
},
negative_prompt: {
name: "Negative Prompt",
negative_prompt: { name: 'Negative Prompt',
setUI: (negative_prompt) => {
negativePromptField.value = negative_prompt
},
readUI: () => negativePromptField.value,
parse: (val) => val,
parse: (val) => val
},
active_tags: {
name: "Image Modifiers",
active_tags: { name: "Image Modifiers",
setUI: (active_tags) => {
refreshModifiersState(active_tags)
},
readUI: () => activeTags.map((x) => x.name),
parse: (val) => val,
readUI: () => activeTags.map(x => x.name),
parse: (val) => val
},
inactive_tags: {
name: "Inactive Image Modifiers",
inactive_tags: { name: "Inactive Image Modifiers",
setUI: (inactive_tags) => {
refreshInactiveTags(inactive_tags)
},
readUI: () => activeTags.filter((tag) => tag.inactive === true).map((x) => x.name),
parse: (val) => val,
readUI: () => activeTags.filter(tag => tag.inactive === true).map(x => x.name),
parse: (val) => val
},
width: {
name: "Width",
width: { name: 'Width',
setUI: (width) => {
const oldVal = widthField.value
widthField.value = width
if (!widthField.value) {
widthField.value = oldVal
}
widthField.dispatchEvent(new Event("change"))
},
readUI: () => parseInt(widthField.value),
parse: (val) => parseInt(val),
parse: (val) => parseInt(val)
},
height: {
name: "Height",
height: { name: 'Height',
setUI: (height) => {
const oldVal = heightField.value
heightField.value = height
if (!heightField.value) {
heightField.value = oldVal
}
heightField.dispatchEvent(new Event("change"))
},
readUI: () => parseInt(heightField.value),
parse: (val) => parseInt(val),
parse: (val) => parseInt(val)
},
seed: {
name: "Seed",
seed: { name: 'Seed',
setUI: (seed) => {
if (!seed) {
randomSeedField.checked = true
@ -107,108 +97,77 @@ const TASK_MAPPING = {
return
}
randomSeedField.checked = false
randomSeedField.dispatchEvent(new Event("change")) // let plugins know that the state of the random seed toggle changed
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),
parse: (val) => parseInt(val)
},
num_inference_steps: {
name: "Steps",
num_inference_steps: { name: 'Steps',
setUI: (num_inference_steps) => {
numInferenceStepsField.value = num_inference_steps
},
readUI: () => parseInt(numInferenceStepsField.value),
parse: (val) => parseInt(val),
parse: (val) => parseInt(val)
},
guidance_scale: {
name: "Guidance Scale",
guidance_scale: { name: 'Guidance Scale',
setUI: (guidance_scale) => {
guidanceScaleField.value = guidance_scale
updateGuidanceScaleSlider()
},
readUI: () => parseFloat(guidanceScaleField.value),
parse: (val) => parseFloat(val),
parse: (val) => parseFloat(val)
},
prompt_strength: {
name: "Prompt Strength",
prompt_strength: { name: 'Prompt Strength',
setUI: (prompt_strength) => {
promptStrengthField.value = prompt_strength
updatePromptStrengthSlider()
},
readUI: () => parseFloat(promptStrengthField.value),
parse: (val) => parseFloat(val),
parse: (val) => parseFloat(val)
},
init_image: {
name: "Initial Image",
init_image: { name: 'Initial Image',
setUI: (init_image) => {
initImagePreview.src = init_image
},
readUI: () => initImagePreview.src,
parse: (val) => val,
parse: (val) => val
},
mask: {
name: "Mask",
mask: { name: 'Mask',
setUI: (mask) => {
setTimeout(() => {
// add a delay to insure this happens AFTER the main image loads (which reloads the inpainter)
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,
parse: (val) => val
},
preserve_init_image_color_profile: {
name: "Preserve Color Profile",
preserve_init_image_color_profile: { name: 'Preserve Color Profile',
setUI: (preserve_init_image_color_profile) => {
applyColorCorrectionField.checked = parseBoolean(preserve_init_image_color_profile)
},
readUI: () => applyColorCorrectionField.checked,
parse: (val) => parseBoolean(val),
parse: (val) => parseBoolean(val)
},
use_face_correction: {
name: "Use Face Correction",
use_face_correction: { name: 'Use Face Correction',
setUI: (use_face_correction) => {
const oldVal = gfpganModelField.value
console.log("use face correction", use_face_correction)
if (use_face_correction == null || use_face_correction == "None") {
gfpganModelField.disabled = true
useFaceCorrectionField.checked = false
} else {
gfpganModelField.value = getModelPath(use_face_correction, [".pth"])
if (gfpganModelField.value) {
// Is a valid value for the field.
useFaceCorrectionField.checked = true
gfpganModelField.disabled = false
} else {
// Not a valid value, restore the old value and disable the filter.
gfpganModelField.disabled = true
gfpganModelField.value = oldVal
useFaceCorrectionField.checked = false
}
}
//useFaceCorrectionField.checked = parseBoolean(use_face_correction)
useFaceCorrectionField.checked = parseBoolean(use_face_correction)
},
readUI: () => (useFaceCorrectionField.checked ? gfpganModelField.value : undefined),
parse: (val) => val,
readUI: () => useFaceCorrectionField.checked,
parse: (val) => parseBoolean(val)
},
use_upscale: {
name: "Use Upscaling",
use_upscale: { name: 'Use Upscaling',
setUI: (use_upscale) => {
const oldVal = upscaleModelField.value
upscaleModelField.value = getModelPath(use_upscale, [".pth"])
if (upscaleModelField.value) {
// Is a valid value for the field.
upscaleModelField.value = getModelPath(use_upscale, ['.pth'])
if (upscaleModelField.value) { // Is a valid value for the field.
useUpscalingField.checked = true
upscaleModelField.disabled = false
upscaleAmountField.disabled = false
} else {
// Not a valid value, restore the old value and disable the filter.
} else { // Not a valid value, restore the old value and disable the filter.
upscaleModelField.disabled = true
upscaleAmountField.disabled = true
upscaleModelField.value = oldVal
@ -216,38 +175,27 @@ const TASK_MAPPING = {
}
},
readUI: () => (useUpscalingField.checked ? upscaleModelField.value : undefined),
parse: (val) => val,
parse: (val) => val
},
upscale_amount: {
name: "Upscale By",
upscale_amount: { name: 'Upscale By',
setUI: (upscale_amount) => {
upscaleAmountField.value = upscale_amount
},
readUI: () => upscaleAmountField.value,
parse: (val) => val,
parse: (val) => val
},
latent_upscaler_steps: {
name: "Latent Upscaler Steps",
setUI: (latent_upscaler_steps) => {
latentUpscalerStepsField.value = latent_upscaler_steps
},
readUI: () => latentUpscalerStepsField.value,
parse: (val) => val,
},
sampler_name: {
name: "Sampler",
sampler_name: { name: 'Sampler',
setUI: (sampler_name) => {
samplerField.value = sampler_name
},
readUI: () => samplerField.value,
parse: (val) => val,
parse: (val) => val
},
use_stable_diffusion_model: {
name: "Stable Diffusion model",
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", ".safetensors"])
use_stable_diffusion_model = getModelPath(use_stable_diffusion_model, ['.ckpt', '.safetensors'])
stableDiffusionModelField.value = use_stable_diffusion_model
if (!stableDiffusionModelField.value) {
@ -255,162 +203,104 @@ const TASK_MAPPING = {
}
},
readUI: () => stableDiffusionModelField.value,
parse: (val) => val,
parse: (val) => val
},
clip_skip: {
name: "Clip Skip",
setUI: (value) => {
clip_skip.checked = value
},
readUI: () => clip_skip.checked,
parse: (val) => Boolean(val),
},
tiling: {
name: "Tiling",
setUI: (val) => {
tilingField.value = val
},
readUI: () => tilingField.value,
parse: (val) => val,
},
use_vae_model: {
name: "VAE model",
use_vae_model: { name: 'VAE model',
setUI: (use_vae_model) => {
const oldVal = vaeModelField.value
use_vae_model =
use_vae_model === undefined || use_vae_model === null || use_vae_model === "None" ? "" : use_vae_model
use_vae_model = (use_vae_model === undefined || use_vae_model === null || use_vae_model === 'None' ? '' : use_vae_model)
if (use_vae_model !== "") {
use_vae_model = getModelPath(use_vae_model, [".vae.pt", ".ckpt"])
use_vae_model = use_vae_model !== "" ? use_vae_model : oldVal
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,
parse: (val) => val
},
use_lora_model: {
name: "LoRA model",
setUI: (use_lora_model) => {
const oldVal = loraModelField.value
use_lora_model =
use_lora_model === undefined || use_lora_model === null || use_lora_model === "None"
? ""
: use_lora_model
if (use_lora_model !== "") {
use_lora_model = getModelPath(use_lora_model, [".ckpt", ".safetensors"])
use_lora_model = use_lora_model !== "" ? use_lora_model : oldVal
}
loraModelField.value = use_lora_model
},
readUI: () => loraModelField.value,
parse: (val) => val,
},
lora_alpha: {
name: "LoRA Strength",
setUI: (lora_alpha) => {
loraAlphaField.value = lora_alpha
updateLoraAlphaSlider()
},
readUI: () => parseFloat(loraAlphaField.value),
parse: (val) => parseFloat(val),
},
use_hypernetwork_model: {
name: "Hypernetwork model",
use_hypernetwork_model: { name: 'Hypernetwork model',
setUI: (use_hypernetwork_model) => {
const oldVal = hypernetworkModelField.value
use_hypernetwork_model =
use_hypernetwork_model === undefined ||
use_hypernetwork_model === null ||
use_hypernetwork_model === "None"
? ""
: use_hypernetwork_model
use_hypernetwork_model = (use_hypernetwork_model === undefined || use_hypernetwork_model === null || use_hypernetwork_model === 'None' ? '' : use_hypernetwork_model)
if (use_hypernetwork_model !== "") {
use_hypernetwork_model = getModelPath(use_hypernetwork_model, [".pt"])
use_hypernetwork_model = use_hypernetwork_model !== "" ? use_hypernetwork_model : oldVal
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"))
hypernetworkModelField.dispatchEvent(new Event('change'))
},
readUI: () => hypernetworkModelField.value,
parse: (val) => val,
parse: (val) => val
},
hypernetwork_strength: {
name: "Hypernetwork Strength",
hypernetwork_strength: { name: 'Hypernetwork Strength',
setUI: (hypernetwork_strength) => {
hypernetworkStrengthField.value = hypernetwork_strength
updateHypernetworkStrengthSlider()
},
readUI: () => parseFloat(hypernetworkStrengthField.value),
parse: (val) => parseFloat(val),
parse: (val) => parseFloat(val)
},
num_outputs: {
name: "Parallel Images",
num_outputs: { name: 'Parallel Images',
setUI: (num_outputs) => {
numOutputsParallelField.value = num_outputs
},
readUI: () => parseInt(numOutputsParallelField.value),
parse: (val) => val,
parse: (val) => val
},
use_cpu: {
name: "Use CPU",
use_cpu: { name: 'Use CPU',
setUI: (use_cpu) => {
useCPUField.checked = use_cpu
},
readUI: () => useCPUField.checked,
parse: (val) => val,
parse: (val) => val
},
stream_image_progress: {
name: "Stream Image Progress",
stream_image_progress: { name: 'Stream Image Progress',
setUI: (stream_image_progress) => {
streamImageProgressField.checked = parseInt(numOutputsTotalField.value) > 50 ? false : stream_image_progress
streamImageProgressField.checked = (parseInt(numOutputsTotalField.value) > 50 ? false : stream_image_progress)
},
readUI: () => streamImageProgressField.checked,
parse: (val) => Boolean(val),
parse: (val) => Boolean(val)
},
show_only_filtered_image: {
name: "Show only the corrected/upscaled image",
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),
parse: (val) => Boolean(val)
},
output_format: {
name: "Output Format",
output_format: { name: 'Output Format',
setUI: (output_format) => {
outputFormatField.value = output_format
},
readUI: () => outputFormatField.value,
parse: (val) => val,
parse: (val) => val
},
save_to_disk_path: {
name: "Save to disk path",
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,
},
parse: (val) => val
}
}
function restoreTaskToUI(task, fieldsToSkip) {
fieldsToSkip = fieldsToSkip || []
if ("numOutputsTotal" in task) {
if ('numOutputsTotal' in task) {
numOutputsTotalField.value = task.numOutputsTotal
}
if ("seed" in task) {
if ('seed' in task) {
randomSeedField.checked = false
seedField.value = task.seed
}
if (!("reqBody" in task)) {
if (!('reqBody' in task)) {
return
}
for (const key in TASK_MAPPING) {
@ -420,32 +310,25 @@ function restoreTaskToUI(task, fieldsToSkip) {
}
// properly reset fields not present in the task
if (!("use_hypernetwork_model" in task.reqBody)) {
if (!('use_hypernetwork_model' in task.reqBody)) {
hypernetworkModelField.value = ""
hypernetworkModelField.dispatchEvent(new Event("change"))
}
if (!("use_lora_model" in task.reqBody)) {
loraModelField.value = ""
loraModelField.dispatchEvent(new Event("change"))
}
// restore the original prompt if provided (e.g. use settings), fallback to prompt as needed (e.g. copy/paste or d&d)
promptField.value = task.reqBody.original_prompt
if (!("original_prompt" in task.reqBody)) {
if (!('original_prompt' in task.reqBody)) {
promptField.value = task.reqBody.prompt
}
promptField.dispatchEvent(new Event("input"))
// properly reset checkboxes
if (!("use_face_correction" in task.reqBody)) {
if (!('use_face_correction' in task.reqBody)) {
useFaceCorrectionField.checked = false
gfpganModelField.disabled = true
}
if (!("use_upscale" in task.reqBody)) {
if (!('use_upscale' in task.reqBody)) {
useUpscalingField.checked = false
}
if (!("mask" in task.reqBody) && maskSetting.checked) {
if (!('mask' in task.reqBody) && maskSetting.checked) {
maskSetting.checked = false
maskSetting.dispatchEvent(new Event("click"))
}
@ -456,18 +339,14 @@ function restoreTaskToUI(task, fieldsToSkip) {
if (IMAGE_REGEX.test(initImagePreview.src) && task.reqBody.init_image == undefined) {
// hide source image
initImageClearBtn.dispatchEvent(new Event("click"))
} else if (task.reqBody.init_image !== undefined) {
}
else if (task.reqBody.init_image !== undefined) {
// listen for inpainter loading event, which happens AFTER the main image loads (which reloads the inpainter)
initImagePreview.addEventListener(
"load",
function() {
if (Boolean(task.reqBody.mask)) {
imageInpainter.setImg(task.reqBody.mask)
maskSetting.checked = true
}
},
{ once: true }
)
initImagePreview.addEventListener('load', function() {
if (Boolean(task.reqBody.mask)) {
imageInpainter.setImg(task.reqBody.mask)
}
}, { once: true })
initImagePreview.src = task.reqBody.init_image
}
}
@ -477,26 +356,21 @@ function readUI() {
reqBody[key] = TASK_MAPPING[key].readUI()
}
return {
numOutputsTotal: parseInt(numOutputsTotalField.value),
seed: TASK_MAPPING["seed"].readUI(),
reqBody: reqBody,
'numOutputsTotal': parseInt(numOutputsTotalField.value),
'seed': TASK_MAPPING['seed'].readUI(),
'reqBody': reqBody
}
}
function getModelPath(filename, extensions) {
if (typeof filename !== "string") {
return
}
let pathIdx
if (filename.includes("/models/stable-diffusion/")) {
pathIdx = filename.indexOf("/models/stable-diffusion/") + 25 // Linux, Mac paths
} else if (filename.includes("\\models\\stable-diffusion\\")) {
pathIdx = filename.indexOf("\\models\\stable-diffusion\\") + 25 // Linux, Mac paths
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)
filename = filename.slice(pathIdx + 1)
}
extensions.forEach((ext) => {
extensions.forEach(ext => {
if (filename.endsWith(ext)) {
filename = filename.slice(0, filename.length - ext.length)
}
@ -505,26 +379,26 @@ function getModelPath(filename, extensions) {
}
const TASK_TEXT_MAPPING = {
prompt: "Prompt",
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",
upscale_amount: "Upscale By",
sampler_name: "Sampler",
negative_prompt: "Negative Prompt",
use_stable_diffusion_model: "Stable Diffusion model",
use_hypernetwork_model: "Hypernetwork model",
hypernetwork_strength: "Hypernetwork Strength",
prompt: 'Prompt',
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',
upscale_amount: 'Upscale By',
sampler_name: 'Sampler',
negative_prompt: 'Negative Prompt',
use_stable_diffusion_model: 'Stable Diffusion model',
use_hypernetwork_model: 'Hypernetwork model',
hypernetwork_strength: 'Hypernetwork Strength'
}
function parseTaskFromText(str) {
const taskReqBody = {}
const lines = str.split("\n")
const lines = str.split('\n')
if (lines.length === 0) {
return
}
@ -532,14 +406,14 @@ function parseTaskFromText(str) {
// Prompt
let knownKeyOnFirstLine = false
for (let key in TASK_TEXT_MAPPING) {
if (lines[0].startsWith(TASK_TEXT_MAPPING[key] + ":")) {
if (lines[0].startsWith(TASK_TEXT_MAPPING[key] + ':')) {
knownKeyOnFirstLine = true
break
}
}
if (!knownKeyOnFirstLine) {
taskReqBody.prompt = lines[0]
console.log("Prompt:", taskReqBody.prompt)
console.log('Prompt:', taskReqBody.prompt)
}
for (const key in TASK_TEXT_MAPPING) {
@ -547,18 +421,18 @@ function parseTaskFromText(str) {
continue
}
const name = TASK_TEXT_MAPPING[key]
const name = TASK_TEXT_MAPPING[key];
let val = undefined
const reName = new RegExp(`${name}\\ *:\\ *(.*)(?:\\r\\n|\\r|\\n)*`, "igm")
const match = reName.exec(str)
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])
console.log(TASK_MAPPING[key].name + ':', taskReqBody[key])
if (!str) {
break
}
@ -568,19 +442,18 @@ function parseTaskFromText(str) {
return undefined
}
const task = { reqBody: taskReqBody }
if ("seed" in taskReqBody) {
if ('seed' in taskReqBody) {
task.seed = taskReqBody.seed
}
return task
}
async function parseContent(text) {
text = text.trim()
if (text.startsWith("{") && text.endsWith("}")) {
text = text.trim();
if (text.startsWith('{') && text.endsWith('}')) {
try {
const task = JSON.parse(text)
if (!("reqBody" in task)) {
// support the format saved to the disk, by the UI
if (!('reqBody' in task)) { // support the format saved to the disk, by the UI
task.reqBody = Object.assign({}, task)
}
restoreTaskToUI(task)
@ -592,13 +465,11 @@ async function parseContent(text) {
}
// Normal txt file.
const task = parseTaskFromText(text)
if (text.toLowerCase().includes("seed:") && task) {
// only parse valid task content
if (text.toLowerCase().includes('seed:') && task) { // only parse valid task content
restoreTaskToUI(task)
return true
} else {
console.warn(`Raw text content couldn't be parsed.`)
promptField.value = text
return false
}
}
@ -610,25 +481,21 @@ async function readFile(file, i) {
}
function dropHandler(ev) {
console.log("Content dropped...")
console.log('Content dropped...')
let items = []
if (ev?.dataTransfer?.items) {
// Use DataTransferItemList interface
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 = 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]
})
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))
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
@ -638,7 +505,7 @@ function dropHandler(ev) {
text_items.forEach(readFile)
}
function dragOverHandler(ev) {
console.log("Content in drop zone")
console.log('Content in drop zone')
// Prevent default behavior (Prevent file/content from being opened)
ev.preventDefault()
@ -646,72 +513,73 @@ function dragOverHandler(ev) {
ev.dataTransfer.dropEffect = "copy"
let img = new Image()
img.src = "//" + location.host + "/media/images/favicon-32x32.png"
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", "save_to_disk_path"]
const resetSettings = document.getElementById("reset-image-settings")
const TASK_REQ_NO_EXPORT = [
"use_cpu",
"save_to_disk_path"
]
const resetSettings = document.getElementById('reset-image-settings')
function checkReadTextClipboardPermission(result) {
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"
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) => {
pasteIcon.addEventListener('click', async (event) => {
event.stopPropagation()
// Add css class 'active'
pasteIcon.classList.add("active")
pasteIcon.classList.add('active')
// In 350 ms remove the 'active' class
asyncDelay(350).then(() => pasteIcon.classList.remove("active"))
asyncDelay(350).then(() => pasteIcon.classList.remove('active'))
// Retrieve clipboard content and try to parse it
const text = await navigator.clipboard.readText()
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))
navigator.permissions.query({ name: "clipboard-read" }).then(checkReadTextClipboardPermission, (reason) => console.log('clipboard-read is not available. %o', reason))
document.addEventListener("paste", async (event) => {
document.addEventListener('paste', async (event) => {
if (event.target) {
const targetTag = event.target.tagName.toLowerCase()
// Disable when targeting input elements.
if (targetTag === "input" || targetTag === "textarea") {
if (targetTag === 'input' || targetTag === 'textarea') {
return
}
}
const paste = (event.clipboardData || window.clipboardData).getData("text")
const paste = (event.clipboardData || window.clipboardData).getData('text')
const selection = window.getSelection()
if (paste != "" && selection.toString().trim().length <= 0 && (await parseContent(paste))) {
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) {
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"
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) => {
copyIcon.addEventListener('click', (event) => {
event.stopPropagation()
// Add css class 'active'
copyIcon.classList.add("active")
copyIcon.classList.add('active')
// In 350 ms remove the 'active' class
asyncDelay(350).then(() => copyIcon.classList.remove("active"))
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)) {
@ -724,8 +592,8 @@ function checkWriteToClipboardPermission(result) {
}
// 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") {
if (e instanceof TypeError && typeof navigator?.clipboard?.writeText === 'function') {
// Fix for firefox https://bugzilla.mozilla.org/show_bug.cgi?id=1560373
checkWriteToClipboardPermission({ state: "granted" })
checkWriteToClipboardPermission({state:"granted"})
}
})

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View File

@ -1,228 +0,0 @@
"use strict"
/**
* @typedef {object} ImageModalRequest
* @property {string} src
* @property {ImageModalRequest | () => ImageModalRequest | undefined} previous
* @property {ImageModalRequest | () => ImageModalRequest | undefined} next
*/
/**
* @type {(() => (string | ImageModalRequest) | string | ImageModalRequest) => {}}
*/
const imageModal = (function() {
const backElem = createElement("i", undefined, ["fa-solid", "fa-arrow-left", "tertiaryButton"])
const forwardElem = createElement("i", undefined, ["fa-solid", "fa-arrow-right", "tertiaryButton"])
const zoomElem = createElement("i", undefined, ["fa-solid", "tertiaryButton"])
const closeElem = createElement("i", undefined, ["fa-solid", "fa-xmark", "tertiaryButton"])
const menuBarElem = createElement("div", undefined, "menu-bar", [backElem, forwardElem, zoomElem, closeElem])
const imageContainer = createElement("div", undefined, "image-wrapper")
const backdrop = createElement("div", undefined, "backdrop")
const modalContainer = createElement("div", undefined, "content", [menuBarElem, imageContainer])
const modalElem = createElement("div", { id: "viewFullSizeImgModal" }, ["popup"], [backdrop, modalContainer])
document.body.appendChild(modalElem)
const setZoomLevel = (value) => {
const img = imageContainer.querySelector("img")
if (value) {
zoomElem.classList.remove("fa-magnifying-glass-plus")
zoomElem.classList.add("fa-magnifying-glass-minus")
if (img) {
img.classList.remove("natural-zoom")
let zoomLevel = typeof value === "number" ? value : img.dataset.zoomLevel
if (!zoomLevel) {
zoomLevel = 100
}
img.dataset.zoomLevel = zoomLevel
img.width = img.naturalWidth * (+zoomLevel / 100)
img.height = img.naturalHeight * (+zoomLevel / 100)
}
} else {
zoomElem.classList.remove("fa-magnifying-glass-minus")
zoomElem.classList.add("fa-magnifying-glass-plus")
if (img) {
img.classList.add("natural-zoom")
img.removeAttribute("width")
img.removeAttribute("height")
}
}
}
zoomElem.addEventListener("click", () =>
setZoomLevel(imageContainer.querySelector("img")?.classList?.contains("natural-zoom"))
)
const initialState = () => ({
previous: undefined,
next: undefined,
start: {
x: 0,
y: 0,
},
scroll: {
x: 0,
y: 0,
},
})
const state = initialState()
// Allow grabbing the image to scroll
const stopGrabbing = (e) => {
if(imageContainer.classList.contains("grabbing")) {
imageContainer.classList.remove("grabbing")
e?.preventDefault()
console.log(`stopGrabbing()`, e)
}
}
const addImageGrabbing = (image) => {
image?.addEventListener('mousedown', (e) => {
if (!image.classList.contains("natural-zoom")) {
e.stopPropagation()
e.stopImmediatePropagation()
e.preventDefault()
imageContainer.classList.add("grabbing")
state.start.x = e.pageX - imageContainer.offsetLeft
state.scroll.x = imageContainer.scrollLeft
state.start.y = e.pageY - imageContainer.offsetTop
state.scroll.y = imageContainer.scrollTop
}
})
image?.addEventListener('mouseup', stopGrabbing)
image?.addEventListener('mouseleave', stopGrabbing)
image?.addEventListener('mousemove', (e) => {
if(imageContainer.classList.contains("grabbing")) {
e.stopPropagation()
e.stopImmediatePropagation()
e.preventDefault()
// Might need to increase this multiplier based on the image size to window size ratio
// The default 1:1 is pretty slow
const multiplier = 1.0
const deltaX = e.pageX - imageContainer.offsetLeft - state.start.x
imageContainer.scrollLeft = state.scroll.x - (deltaX * multiplier)
const deltaY = e.pageY - imageContainer.offsetTop - state.start.y
imageContainer.scrollTop = state.scroll.y - (deltaY * multiplier)
}
})
}
const clear = () => {
imageContainer.innerHTML = ""
Object.entries(initialState()).forEach(([key, value]) => state[key] = value)
stopGrabbing()
}
const close = () => {
clear()
modalElem.classList.remove("active")
document.body.style.overflow = "initial"
}
/**
* @param {() => (string | ImageModalRequest) | string | ImageModalRequest} optionsFactory
*/
function init(optionsFactory) {
if (!optionsFactory) {
close()
return
}
clear()
const options = typeof optionsFactory === "function" ? optionsFactory() : optionsFactory
const src = typeof options === "string" ? options : options.src
const imgElem = createElement("img", { src }, "natural-zoom")
addImageGrabbing(imgElem)
imageContainer.appendChild(imgElem)
modalElem.classList.add("active")
document.body.style.overflow = "hidden"
setZoomLevel(false)
if (typeof options === "object" && options.previous) {
state.previous = options.previous
backElem.style.display = "unset"
} else {
backElem.style.display = "none"
}
if (typeof options === "object" && options.next) {
state.next = options.next
forwardElem.style.display = "unset"
} else {
forwardElem.style.display = "none"
}
}
const back = () => {
if (state.previous) {
init(state.previous)
} else {
backElem.style.display = "none"
}
}
const forward = () => {
if (state.next) {
init(state.next)
} else {
forwardElem.style.display = "none"
}
}
window.addEventListener("keydown", (e) => {
if (modalElem.classList.contains("active")) {
switch (e.key) {
case "Escape":
close()
break
case "ArrowLeft":
back()
break
case "ArrowRight":
forward()
break
}
}
})
window.addEventListener("click", (e) => {
if (modalElem.classList.contains("active")) {
if (e.target === backdrop || e.target === closeElem) {
close()
}
e.stopPropagation()
e.stopImmediatePropagation()
e.preventDefault()
}
})
backElem.addEventListener("click", back)
forwardElem.addEventListener("click", forward)
/**
* @param {() => (string | ImageModalRequest) | string | ImageModalRequest} optionsFactory
*/
return (optionsFactory) => init(optionsFactory)
})()

View File

@ -1,28 +1,24 @@
let activeTags = []
let modifiers = []
let customModifiersGroupElement = undefined
let customModifiersInitialContent
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")
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 modifierThumbnailPath = 'media/modifier-thumbnails'
const activeCardClass = 'modifier-card-active'
const CUSTOM_MODIFIERS_KEY = "customModifiers"
function createModifierCard(name, previews, removeBy) {
const modifierCard = document.createElement("div")
let style = previewImageField.value
let styleIndex = style == "portrait" ? 0 : 1
modifierCard.className = "modifier-card"
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">
@ -34,95 +30,90 @@ function createModifierCard(name, previews, removeBy) {
<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")
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"
errorText.innerText = 'No Image'
if (typeof previews == "object") {
image.src = previews[styleIndex] // portrait
image.setAttribute("preview-type", style)
if (typeof previews == 'object') {
image.src = previews[0]; // portrait
image.setAttribute('preview-type', 'portrait')
} else {
image.remove()
}
const maxLabelLength = 30
const cardLabel = removeBy ? name.replace("by ", "") : name
const nameWithoutBy = name.replace('by ', '')
if (cardLabel.length <= maxLabelLength) {
label.querySelector("p").innerText = cardLabel
if(nameWithoutBy.length <= maxLabelLength) {
label.querySelector('p').innerText = nameWithoutBy
} else {
const tooltipText = document.createElement("span")
tooltipText.className = "tooltip-text"
const tooltipText = document.createElement('span')
tooltipText.className = 'tooltip-text'
tooltipText.innerText = name
label.classList.add("tooltip")
label.classList.add('tooltip')
label.appendChild(tooltipText)
label.querySelector("p").innerText = cardLabel.substring(0, maxLabelLength) + "..."
label.querySelector('p').innerText = nameWithoutBy.substring(0, maxLabelLength) + '...'
}
label.querySelector("p").dataset.fullName = name // preserve the full name
return modifierCard
}
function createModifierGroup(modifierGroup, initiallyExpanded, removeBy) {
function createModifierGroup(modifierGroup, initiallyExpanded) {
const title = modifierGroup.category
const modifiers = modifierGroup.modifiers
const titleEl = document.createElement("h5")
titleEl.className = "collapsible"
const titleEl = document.createElement('h5')
titleEl.className = 'collapsible'
titleEl.innerText = title
const modifiersEl = document.createElement("div")
modifiersEl.classList.add("collapsible-content", "editor-modifiers-leaf")
const modifiersEl = document.createElement('div')
modifiersEl.classList.add('collapsible-content', 'editor-modifiers-leaf')
if (initiallyExpanded === true) {
titleEl.className += " active"
titleEl.className += ' active'
}
modifiers.forEach((modObj) => {
modifiers.forEach(modObj => {
const modifierName = modObj.modifier
const modifierPreviews = modObj?.previews?.map(
(preview) =>
`${IMAGE_REGEX.test(preview.image) ? preview.image : modifierThumbnailPath + "/" + preview.path}`
)
const modifierPreviews = modObj?.previews?.map(preview => `${modifierThumbnailPath}/${preview.path}`)
const modifierCard = createModifierCard(modifierName, modifierPreviews, removeBy)
const modifierCard = createModifierCard(modifierName, modifierPreviews)
if (typeof modifierCard == "object") {
if(typeof modifierCard == 'object') {
modifiersEl.appendChild(modifierCard)
const trimmedName = trimModifiers(modifierName)
modifierCard.addEventListener("click", () => {
if (activeTags.map((x) => trimModifiers(x.name)).includes(trimmedName)) {
modifierCard.addEventListener('click', () => {
if (activeTags.map(x => trimModifiers(x.name)).includes(trimmedName)) {
// remove modifier from active array
activeTags = activeTags.filter((x) => trimModifiers(x.name) != trimmedName)
activeTags = activeTags.filter(x => trimModifiers(x.name) != trimmedName)
toggleCardState(trimmedName, false)
} else {
// add modifier to active array
activeTags.push({
name: modifierName,
element: modifierCard.cloneNode(true),
originElement: modifierCard,
previews: modifierPreviews,
'name': modifierName,
'element': modifierCard.cloneNode(true),
'originElement': modifierCard,
'previews': modifierPreviews
})
toggleCardState(trimmedName, true)
}
refreshTagsList()
document.dispatchEvent(new Event("refreshImageModifiers"))
document.dispatchEvent(new Event('refreshImageModifiers'))
})
}
})
let brk = document.createElement("br")
brk.style.clear = "both"
let brk = document.createElement('br')
brk.style.clear = 'both'
modifiersEl.appendChild(brk)
let e = document.createElement("div")
e.className = "modifier-category"
let e = document.createElement('div')
e.appendChild(titleEl)
e.appendChild(modifiersEl)
@ -132,146 +123,125 @@ function createModifierGroup(modifierGroup, initiallyExpanded, removeBy) {
}
function trimModifiers(tag) {
// Remove trailing '-' and/or '+'
tag = tag.replace(/[-+]+$/, "")
// Remove parentheses at beginning and end
return tag.replace(/^[(]+|[\s)]+$/g, "")
return tag.replace(/^\(+|\)+$/g, '').replace(/^\[+|\]+$/g, '')
}
async function loadModifiers() {
try {
let res = await fetch("/get/modifiers")
let res = await fetch('/get/modifiers')
if (res.status === 200) {
res = await res.json()
modifiers = res // update global variable
modifiers = res; // update global variable
res.reverse()
res.forEach((modifierGroup, idx) => {
createModifierGroup(modifierGroup, idx === res.length - 1, modifierGroup === "Artist" ? true : false) // only remove "By " for artists
createModifierGroup(modifierGroup, idx === res.length - 1)
})
createCollapsibles(editorModifierEntries)
}
} catch (e) {
console.error("error fetching modifiers", e)
console.log('error fetching modifiers', e)
}
loadCustomModifiers()
resizeModifierCards(modifierCardSizeSlider.value)
document.dispatchEvent(new Event("loadImageModifiers"))
document.dispatchEvent(new Event('loadImageModifiers'))
}
function refreshModifiersState(newTags, inactiveTags) {
function refreshModifiersState(newTags) {
// clear existing modifiers
document
.querySelector("#editor-modifiers")
.querySelectorAll(".modifier-card")
.forEach((modifierCard) => {
const modifierName = modifierCard.querySelector(".modifier-card-label p").dataset.fullName // pick the full modifier name
if (activeTags.map((x) => x.name).includes(modifierName)) {
modifierCard.classList.remove(activeCardClass)
modifierCard.querySelector(".modifier-card-image-overlay").innerText = "+"
}
})
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) => {
newTags.forEach(tag => {
let found = false
document
.querySelector("#editor-modifiers")
.querySelectorAll(".modifier-card")
.forEach((modifierCard) => {
const modifierName = modifierCard.querySelector(".modifier-card-label p").dataset.fullName
const shortModifierName = modifierCard.querySelector(".modifier-card-label p").innerText
if (trimModifiers(tag) == trimModifiers(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
const imageModifierCard = modifierCard.cloneNode(true)
imageModifierCard.querySelector(".modifier-card-label p").innerText = tag.replace(
modifierName,
shortModifierName
)
activeTags.push({
name: tag,
element: imageModifierCard,
originElement: modifierCard,
})
}
modifierCard.classList.add(activeCardClass)
modifierCard.querySelector(".modifier-card-image-overlay").innerText = "-"
found = true
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
})
}
})
if (found == false) {
// custom tag went missing, create one here
let modifierCard = createModifierCard(tag, undefined, false) // create a modifier card for the missing tag, no image
modifierCard.addEventListener("click", () => {
if (activeTags.map((x) => x.name).includes(tag)) {
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)
activeTags = activeTags.filter(x => x.name != tag)
modifierCard.classList.remove(activeCardClass)
modifierCard.querySelector(".modifier-card-image-overlay").innerText = "+"
modifierCard.querySelector('.modifier-card-image-overlay').innerText = '+'
}
refreshTagsList()
})
activeTags.push({
name: tag,
element: modifierCard,
originElement: undefined, // no origin element for missing tags
'name': tag,
'element': modifierCard,
'originElement': undefined // no origin element for missing tags
})
}
})
refreshTagsList(inactiveTags)
refreshTagsList()
}
function refreshInactiveTags(inactiveTags) {
// update inactive tags
if (inactiveTags !== undefined && inactiveTags.length > 0) {
activeTags.forEach((tag) => {
if (inactiveTags.find((element) => element === tag.name) !== undefined) {
activeTags.forEach (tag => {
if (inactiveTags.find(element => element === tag.name) !== undefined) {
tag.inactive = true
}
})
}
// update cards
let overlays = document.querySelector("#editor-inputs-tags-list").querySelectorAll(".modifier-card-overlay")
overlays.forEach((i) => {
let modifierName = i.parentElement.getElementsByClassName("modifier-card-label")[0].getElementsByTagName("p")[0]
.dataset.fullName
if (inactiveTags?.find((element) => trimModifiers(element) === modifierName) !== undefined) {
i.parentElement.classList.add("modifier-toggle-inactive")
let overlays = document.querySelector('#editor-inputs-tags-list').querySelectorAll('.modifier-card-overlay')
overlays.forEach (i => {
let modifierName = i.parentElement.getElementsByClassName('modifier-card-label')[0].getElementsByTagName("p")[0].innerText
if (inactiveTags.find(element => element === modifierName) !== undefined) {
i.parentElement.classList.add('modifier-toggle-inactive')
}
})
}
function refreshTagsList(inactiveTags) {
editorModifierTagsList.innerHTML = ""
function refreshTagsList() {
editorModifierTagsList.innerHTML = ''
if (activeTags.length == 0) {
editorTagsContainer.style.display = "none"
editorTagsContainer.style.display = 'none'
return
} else {
editorTagsContainer.style.display = "block"
editorTagsContainer.style.display = 'block'
}
activeTags.forEach((tag, index) => {
tag.element.querySelector(".modifier-card-image-overlay").innerText = "-"
tag.element.classList.add("modifier-card-tiny")
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
})
tag.element.addEventListener('click', () => {
let idx = activeTags.findIndex(o => { return o.name === tag.name })
if (idx !== -1) {
toggleCardState(activeTags[idx].name, false)
@ -279,91 +249,86 @@ function refreshTagsList(inactiveTags) {
activeTags.splice(idx, 1)
refreshTagsList()
}
document.dispatchEvent(new Event("refreshImageModifiers"))
document.dispatchEvent(new Event('refreshImageModifiers'))
})
})
let brk = document.createElement("br")
brk.style.clear = "both"
let brk = document.createElement('br')
brk.style.clear = 'both'
editorModifierTagsList.appendChild(brk)
refreshInactiveTags(inactiveTags)
document.dispatchEvent(new Event("refreshImageModifiers")) // notify plugins that the image tags have been refreshed
}
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 = "+"
}
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")
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) => {
modifiers.map(x => x.modifiers).forEach(x => previewArr.push(...x.map(m => m.previews)))
previewArr = previewArr.map(x => {
let obj = {}
x.forEach((preview) => {
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()
previewImages.forEach(previewImage => {
const currentPreviewType = previewImage.getAttribute('preview-type')
const relativePreviewPath = previewImage.src.split(modifierThumbnailPath + '/').pop()
const previews = previewArr.find((preview) => relativePreviewPath == preview[currentPreviewType])
const previews = previewArr.find(preview => relativePreviewPath == preview[currentPreviewType])
if (typeof previews == "object") {
if(typeof previews == 'object') {
let preview = null
if (val == "portrait") {
if (val == 'portrait') {
preview = previews.portrait
} else if (val == "landscape") {
}
else if (val == 'landscape') {
preview = previews.landscape
}
if (preview != null) {
if(preview != null) {
previewImage.src = `${modifierThumbnailPath}/${preview}`
previewImage.setAttribute("preview-type", val)
previewImage.setAttribute('preview-type', val)
}
}
})
}
function resizeModifierCards(val) {
const cardSizePrefix = "modifier-card-size_"
const modifierCardClass = "modifier-card"
const cardSizePrefix = 'modifier-card-size_'
const modifierCardClass = 'modifier-card'
const modifierCards = document.querySelectorAll(`.${modifierCardClass}`)
const cardSize = (n) => `${cardSizePrefix}${n}`
const cardSize = n => `${cardSizePrefix}${n}`
modifierCards.forEach((card) => {
modifierCards.forEach(card => {
// remove existing size classes
const classes = card.className.split(" ").filter((c) => !c.startsWith(cardSizePrefix))
card.className = classes.join(" ").trim()
const classes = card.className.split(' ').filter(c => !c.startsWith(cardSizePrefix))
card.className = classes.join(' ').trim()
if (val != 0) {
if(val != 0) {
card.classList.add(cardSize(val))
}
})
@ -372,31 +337,11 @@ function resizeModifierCards(val) {
modifierCardSizeSlider.onchange = () => resizeModifierCards(modifierCardSizeSlider.value)
previewImageField.onchange = () => changePreviewImages(previewImageField.value)
modifierSettingsBtn.addEventListener("click", function(e) {
modifierSettingsBtn.addEventListener('click', function(e) {
modifierSettingsOverlay.classList.add("active")
customModifiersTextBox.setSelectionRange(0, 0)
customModifiersTextBox.focus()
customModifiersInitialContent = customModifiersTextBox.value // preserve the initial content
e.stopPropagation()
})
modifierSettingsOverlay.addEventListener("keydown", function(e) {
switch (e.key) {
case "Escape": // Escape to cancel
customModifiersTextBox.value = customModifiersInitialContent // undo the changes
modifierSettingsOverlay.classList.remove("active")
e.stopPropagation()
break
case "Enter":
if (e.ctrlKey) {
// Ctrl+Enter to confirm
modifierSettingsOverlay.classList.remove("active")
e.stopPropagation()
break
}
}
})
function saveCustomModifiers() {
localStorage.setItem(CUSTOM_MODIFIERS_KEY, customModifiersTextBox.value.trim())
@ -404,7 +349,7 @@ function saveCustomModifiers() {
}
function loadCustomModifiers() {
PLUGINS["MODIFIERS_LOAD"].forEach((fn) => fn.loader.call())
PLUGINS['MODIFIERS_LOAD'].forEach(fn=>fn.loader.call())
}
customModifiersTextBox.addEventListener("change", saveCustomModifiers)
customModifiersTextBox.addEventListener('change', saveCustomModifiers)

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@ -3,33 +3,24 @@
* @readonly
* @enum {string}
*/
var ParameterType = {
var ParameterType = {
checkbox: "checkbox",
select: "select",
select_multiple: "select_multiple",
slider: "slider",
custom: "custom",
}
/**
* Element shortcuts
*/
let parametersTable = document.querySelector("#system-settings-table")
let networkParametersTable = document.querySelector("#system-settings-network-table")
};
/**
* JSDoc style
* @typedef {object} Parameter
* @property {string} id
* @property {keyof ParameterType} type
* @property {string | (parameter: Parameter) => (HTMLElement | string)} label
* @property {string | (parameter: Parameter) => (HTMLElement | string) | undefined} note
* @property {(parameter: Parameter) => (HTMLElement | string) | undefined} render
* @property {string | undefined} icon
* @property {ParameterType} type
* @property {string} label
* @property {?string} note
* @property {number|boolean|string} default
* @property {boolean?} saveInAppConfig
*/
/** @type {Array.<Parameter>} */
var PARAMETERS = [
{
@ -38,14 +29,13 @@ var PARAMETERS = [
label: "Theme",
default: "theme-default",
note: "customize the look and feel of the ui",
options: [
// Note: options expanded dynamically
options: [ // Note: options expanded dynamically
{
value: "theme-default",
label: "Default",
},
label: "Default"
}
],
icon: "fa-palette",
icon: "fa-palette"
},
{
id: "save_to_disk",
@ -61,7 +51,7 @@ var PARAMETERS = [
label: "Save Location",
render: (parameter) => {
return `<input id="${parameter.id}" name="${parameter.id}" size="30" disabled>`
},
}
},
{
id: "metadata_output_format",
@ -70,40 +60,16 @@ var PARAMETERS = [
note: "will be saved to disk in this format",
default: "txt",
options: [
{
value: "none",
label: "none",
},
{
value: "txt",
label: "txt",
label: "txt"
},
{
value: "json",
label: "json",
},
{
value: "embed",
label: "embed",
},
{
value: "embed,txt",
label: "embed & txt",
},
{
value: "embed,json",
label: "embed & json",
},
label: "json"
}
],
},
{
id: "block_nsfw",
type: ParameterType.checkbox,
label: "Block NSFW images",
note: "blurs out NSFW images",
icon: "fa-land-mine-on",
default: false,
},
{
id: "sound_toggle",
type: ParameterType.checkbox,
@ -127,23 +93,21 @@ var PARAMETERS = [
note: "starts the default browser on startup",
icon: "fa-window-restore",
default: true,
saveInAppConfig: true,
},
{
id: "vram_usage_level",
type: ParameterType.select,
label: "GPU Memory Usage",
note:
"Faster performance requires more GPU memory (VRAM)<br/><br/>" +
"<b>Balanced:</b> nearly as fast as High, much lower VRAM usage<br/>" +
"<b>High:</b> fastest, maximum GPU memory usage</br>" +
"<b>Low:</b> slowest, recommended for GPUs with 3 to 4 GB memory",
note: "Faster performance requires more GPU memory (VRAM)<br/><br/>" +
"<b>Balanced:</b> nearly as fast as High, much lower VRAM usage<br/>" +
"<b>High:</b> fastest, maximum GPU memory usage</br>" +
"<b>Low:</b> slowest, force-used for GPUs with 3 to 4 GB memory",
icon: "fa-forward",
default: "balanced",
options: [
{ value: "balanced", label: "Balanced" },
{ value: "high", label: "High" },
{ value: "low", label: "Low" },
{value: "balanced", label: "Balanced"},
{value: "high", label: "High"},
{value: "low", label: "Low"}
],
},
{
@ -179,8 +143,7 @@ var PARAMETERS = [
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",
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,
},
@ -188,228 +151,115 @@ var PARAMETERS = [
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. Please restart the program after changing this.",
note: "Other devices on your network can access this web page",
icon: "fa-network-wired",
default: true,
saveInAppConfig: true,
table: networkParametersTable,
},
{
id: "listen_port",
type: ParameterType.custom,
label: "Network port",
note:
"Port that this server listens to. The '9000' part in 'http://localhost:9000'. Please restart the program after changing this.",
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)">`
},
saveInAppConfig: true,
table: networkParametersTable,
}
},
{
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.",
note: "Get the latest features immediately (but could be less stable). Please restart the program after changing this.",
icon: "fa-fire",
default: false,
},
{
id: "test_diffusers",
type: ParameterType.checkbox,
label: "Test Diffusers",
note:
"<b>Experimental! Can have bugs!</b> Use upcoming features (like LoRA) in our new engine. Please press Save, then restart the program after changing this.",
icon: "fa-bolt",
default: false,
saveInAppConfig: true,
},
{
id: "cloudflare",
type: ParameterType.custom,
label: "Cloudflare tunnel",
note: `<span id="cloudflare-off">Create a VPN tunnel to share your Easy Diffusion instance with your friends. This will
generate a web server address on the public Internet for your Easy Diffusion instance. </span>
<div id="cloudflare-on" class="displayNone"><div>This Easy Diffusion server is available on the Internet using the
address:</div><div><div id="cloudflare-address"></div><button id="copy-cloudflare-address">Copy</button></div></div>
<b>Anyone knowing this address can access your server.</b> The address of your server will change each time
you share a session.<br>
Uses <a href="https://try.cloudflare.com/" target="_blank">Cloudflare services</a>.`,
icon: ["fa-brands", "fa-cloudflare"],
render: () => '<button id="toggle-cloudflare-tunnel" class="primaryButton">Start</button>',
table: networkParametersTable,
}
]
];
function getParameterSettingsEntry(id) {
let parameter = PARAMETERS.filter((p) => p.id === id)
let parameter = PARAMETERS.filter(p => p.id === id)
if (parameter.length === 0) {
return
}
return parameter[0].settingsEntry
}
function sliderUpdate(event) {
if (event.srcElement.id.endsWith("-input")) {
let slider = document.getElementById(event.srcElement.id.slice(0, -6))
slider.value = event.srcElement.value
slider.dispatchEvent(new Event("change"))
} else {
let field = document.getElementById(event.srcElement.id + "-input")
field.value = event.srcElement.value
field.dispatchEvent(new Event("change"))
}
}
/**
* @param {Parameter} parameter
* @returns {string | HTMLElement}
*/
function getParameterElement(parameter) {
switch (parameter.type) {
case ParameterType.checkbox:
var is_checked = parameter.default ? " checked" : ""
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}">${option.label}</option>`)
.join("")
var multiple = parameter.type == ParameterType.select_multiple ? "multiple" : ""
var options = (parameter.options || []).map(option => `<option value="${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.slider:
return `<input id="${parameter.id}" name="${parameter.id}" class="editor-slider" type="range" value="${parameter.default}" min="${parameter.slider_min}" max="${parameter.slider_max}" oninput="sliderUpdate(event)"> <input id="${parameter.id}-input" name="${parameter.id}-input" size="4" value="${parameter.default}" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)" oninput="sliderUpdate(event)">&nbsp;${parameter.slider_unit}`
case ParameterType.custom:
return parameter.render(parameter)
default:
console.error(`Invalid type ${parameter.type} for parameter ${parameter.id}`)
console.error(`Invalid type for parameter ${parameter.id}`);
return "ERROR: Invalid Type"
}
}
/**
* fill in the system settings popup table
* @param {Array<Parameter> | undefined} parameters
* */
function initParameters(parameters) {
parameters.forEach((parameter) => {
const element = getParameterElement(parameter)
const elementWrapper = createElement("div")
if (element instanceof Node) {
elementWrapper.appendChild(element)
} else {
elementWrapper.innerHTML = element
}
const note = typeof parameter.note === "function" ? parameter.note(parameter) : parameter.note
const noteElements = []
if (note) {
const noteElement = createElement("small")
if (note instanceof Node) {
noteElement.appendChild(note)
} else {
noteElement.innerHTML = note || ""
}
noteElements.push(noteElement)
}
if (typeof(parameter.icon) == "string") {
parameter.icon = [parameter.icon]
}
const icon = parameter.icon ? [createElement("i", undefined, ["fa", ...parameter.icon])] : []
const label = typeof parameter.label === "function" ? parameter.label(parameter) : parameter.label
const labelElement = createElement("label", { for: parameter.id })
if (label instanceof Node) {
labelElement.appendChild(label)
} else {
labelElement.innerHTML = label
}
const newrow = createElement(
"div",
{ "data-setting-id": parameter.id, "data-save-in-app-config": parameter.saveInAppConfig },
undefined,
[
createElement("div", undefined, undefined, icon),
createElement("div", undefined, undefined, [labelElement, ...noteElements]),
elementWrapper,
]
)
let p = parametersTable
if (parameter.table) {
p = parameter.table
}
p.appendChild(newrow)
let parametersTable = document.querySelector("#system-settings .parameters-table")
/* fill in the system settings popup table */
function initParameters() {
PARAMETERS.forEach(parameter => {
var element = getParameterElement(parameter)
var note = parameter.note ? `<small>${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(PARAMETERS)
initParameters()
// listen to parameters from plugins
PARAMETERS.addEventListener("push", (...items) => {
initParameters(items)
if (items.find((item) => item.saveInAppConfig)) {
console.log(
"Reloading app config for new parameters",
items.map((p) => p.id)
)
getAppConfig()
}
})
let vramUsageLevelField = document.querySelector("#vram_usage_level")
let useCPUField = document.querySelector("#use_cpu")
let autoPickGPUsField = document.querySelector("#auto_pick_gpus")
let useGPUsField = document.querySelector("#use_gpus")
let saveToDiskField = document.querySelector("#save_to_disk")
let diskPathField = document.querySelector("#diskPath")
let metadataOutputFormatField = document.querySelector("#metadata_output_format")
let vramUsageLevelField = document.querySelector('#vram_usage_level')
let useCPUField = document.querySelector('#use_cpu')
let autoPickGPUsField = document.querySelector('#auto_pick_gpus')
let useGPUsField = document.querySelector('#use_gpus')
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 useBetaChannelField = document.querySelector("#use_beta_channel")
let uiOpenBrowserOnStartField = document.querySelector("#ui_open_browser_on_start")
let confirmDangerousActionsField = document.querySelector("#confirm_dangerous_actions")
let testDiffusers = document.querySelector("#test_diffusers")
let saveSettingsBtn = document.querySelector("#save-system-settings-btn")
let saveSettingsBtn = document.querySelector('#save-system-settings-btn')
async function changeAppConfig(configDelta) {
try {
let res = await fetch("/app_config", {
method: "POST",
let res = await fetch('/app_config', {
method: 'POST',
headers: {
"Content-Type": "application/json",
'Content-Type': 'application/json'
},
body: JSON.stringify(configDelta),
body: JSON.stringify(configDelta)
})
res = await res.json()
console.log("set config status response", res)
console.log('set config status response', res)
} catch (e) {
console.log("set config status error", e)
console.log('set config status error', e)
}
}
async function getAppConfig() {
try {
let res = await fetch("/get/app_config")
let res = await fetch('/get/app_config')
const config = await res.json()
applySettingsFromConfig(config)
// custom overrides
if (config.update_branch === "beta") {
if (config.update_branch === 'beta') {
useBetaChannelField.checked = true
document.querySelector("#updateBranchLabel").innerText = "(beta)"
} else {
getParameterSettingsEntry("test_diffusers").style.display = "none"
}
if (config.ui && config.ui.open_browser_on_start === false) {
uiOpenBrowserOnStartField.checked = false
@ -421,145 +271,80 @@ async function getAppConfig() {
listenPortField.value = config.net.listen_port
}
const testDiffusersEnabled = config.test_diffusers && config.update_branch !== "main"
testDiffusers.checked = testDiffusersEnabled
if (!testDiffusersEnabled) {
document.querySelector("#lora_model_container").style.display = "none"
document.querySelector("#lora_alpha_container").style.display = "none"
document.querySelector("#tiling_container").style.display = "none"
document.querySelectorAll("#sampler_name option.diffusers-only").forEach((option) => {
option.style.display = "none"
})
} else {
document.querySelector("#lora_model_container").style.display = ""
document.querySelector("#lora_alpha_container").style.display = loraModelField.value ? "" : "none"
document.querySelector("#tiling_container").style.display = ""
document.querySelectorAll("#sampler_name option.k_diffusion-only").forEach((option) => {
option.disabled = true
})
document.querySelector("#clip_skip_config").classList.remove("displayNone")
}
console.log("get config status response", config)
return config
console.log('get config status response', config)
} catch (e) {
console.log("get config status error", e)
return {}
console.log('get config status error', e)
}
}
function applySettingsFromConfig(config) {
Array.from(parametersTable.children).forEach((parameterRow) => {
if (parameterRow.dataset.settingId in config && parameterRow.dataset.saveInAppConfig === "true") {
const configValue = config[parameterRow.dataset.settingId]
const parameterElement =
document.getElementById(parameterRow.dataset.settingId) ||
parameterRow.querySelector("input") ||
parameterRow.querySelector("select")
switch (parameterElement?.tagName) {
case "INPUT":
if (parameterElement.type === "checkbox") {
parameterElement.checked = configValue
} else {
parameterElement.value = configValue
}
parameterElement.dispatchEvent(new Event("change"))
break
case "SELECT":
if (Array.isArray(configValue)) {
Array.from(parameterElement.options).forEach((option) => {
if (configValue.includes(option.value || option.text)) {
option.selected = true
}
})
} else {
parameterElement.value = configValue
}
parameterElement.dispatchEvent(new Event("change"))
break
}
}
})
}
saveToDiskField.addEventListener("change", function(e) {
saveToDiskField.addEventListener('change', function(e) {
diskPathField.disabled = !this.checked
metadataOutputFormatField.disabled = !this.checked
})
function getCurrentRenderDeviceSelection() {
let selectedGPUs = $("#use_gpus").val()
let selectedGPUs = $('#use_gpus').val()
if (useCPUField.checked && !autoPickGPUsField.checked) {
return "cpu"
return 'cpu'
}
if (autoPickGPUsField.checked || selectedGPUs.length == 0) {
return "auto"
return 'auto'
}
return selectedGPUs.join(",")
return selectedGPUs.join(',')
}
useCPUField.addEventListener("click", function() {
let gpuSettingEntry = getParameterSettingsEntry("use_gpus")
let autoPickGPUSettingEntry = getParameterSettingsEntry("auto_pick_gpus")
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)
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
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"
autoPickGPUsField.checked = (oldVal === 'true')
}
gpuSettingEntry.style.display = autoPickGPUsField.checked ? "none" : ""
gpuSettingEntry.style.display = (autoPickGPUsField.checked ? 'none' : '')
}
})
useGPUsField.addEventListener("click", function() {
let selectedGPUs = $("#use_gpus").val()
autoPickGPUsField.checked = selectedGPUs.length === 0
useGPUsField.addEventListener('click', function() {
let selectedGPUs = $('#use_gpus').val()
autoPickGPUsField.checked = (selectedGPUs.length === 0)
})
autoPickGPUsField.addEventListener("click", function() {
autoPickGPUsField.addEventListener('click', function() {
if (this.checked) {
$("#use_gpus").val([])
$('#use_gpus').val([])
}
let gpuSettingEntry = getParameterSettingsEntry("use_gpus")
gpuSettingEntry.style.display = this.checked ? "none" : ""
let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
gpuSettingEntry.style.display = (this.checked ? 'none' : '')
})
async function setDiskPath(defaultDiskPath, force = false) {
async function setDiskPath(defaultDiskPath) {
var diskPath = getSetting("diskPath")
if (force || diskPath == "" || diskPath == undefined || diskPath == "undefined") {
if (diskPath == '' || diskPath == undefined || diskPath == "undefined") {
setSetting("diskPath", defaultDiskPath)
}
}
function setDeviceInfo(devices) {
let cpu = devices.all.cpu.name
let allGPUs = Object.keys(devices.all).filter((d) => d != "cpu")
let allGPUs = Object.keys(devices.all).filter(d => d != 'cpu')
let activeGPUs = Object.keys(devices.active)
function ID_TO_TEXT(d) {
let info = devices.all[d]
if ("mem_free" in info && "mem_total" in info) {
return `${info.name} <small>(${d}) (${info.mem_free.toFixed(1)}Gb free / ${info.mem_total.toFixed(
1
)} Gb total)</small>`
return `${info.name} <small>(${d}) (${info.mem_free.toFixed(1)}Gb free / ${info.mem_total.toFixed(1)} Gb total)</small>`
} else {
return `${info.name} <small>(${d}) (no memory info)</small>`
}
@ -568,155 +353,83 @@ function setDeviceInfo(devices) {
allGPUs = allGPUs.map(ID_TO_TEXT)
activeGPUs = activeGPUs.map(ID_TO_TEXT)
let systemInfoEl = document.querySelector("#system-info")
systemInfoEl.querySelector("#system-info-cpu").innerText = cpu
systemInfoEl.querySelector("#system-info-gpus-all").innerHTML = allGPUs.join("</br>")
systemInfoEl.querySelector("#system-info-rendering-devices").innerHTML = activeGPUs.join("</br>")
let systemInfoEl = document.querySelector('#system-info')
systemInfoEl.querySelector('#system-info-cpu').innerText = cpu
systemInfoEl.querySelector('#system-info-gpus-all').innerHTML = allGPUs.join('</br>')
systemInfoEl.querySelector('#system-info-rendering-devices').innerHTML = activeGPUs.join('</br>')
}
function setHostInfo(hosts) {
let port = listenPortField.value
hosts = hosts.map((addr) => `http://${addr}:${port}/`).map((url) => `<div><a href="${url}">${url}</a></div>`)
document.querySelector("#system-info-server-hosts").innerHTML = hosts.join("")
hosts = hosts.map(addr => `http://${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 devices = res['devices']
let allDeviceIds = Object.keys(devices["all"]).filter((d) => d !== "cpu")
let activeDeviceIds = Object.keys(devices["active"]).filter((d) => d !== "cpu")
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"
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
getParameterSettingsEntry("use_cpu").addEventListener("click", function() {
alert(
"Sorry, we could not find a compatible graphics card! Easy Diffusion supports graphics cards with minimum 2 GB of RAM. " +
"Only NVIDIA cards are supported on Windows. NVIDIA and AMD cards are supported on Linux.<br/><br/>" +
"If you have a compatible graphics card, please try updating to the latest drivers.<br/><br/>" +
"Only the CPU can be used for generating images, without a compatible graphics card.",
"No compatible graphics card found!"
)
})
}
autoPickGPUsField.checked = devices["config"] === "auto"
autoPickGPUsField.checked = (devices['config'] === 'auto')
useGPUsField.innerHTML = ""
allDeviceIds.forEach((device) => {
let deviceName = devices["all"][device]["name"]
useGPUsField.innerHTML = ''
allDeviceIds.forEach(device => {
let deviceName = devices['all'][device]['name']
let deviceOption = `<option value="${device}">${deviceName} (${device})</option>`
useGPUsField.insertAdjacentHTML("beforeend", deviceOption)
useGPUsField.insertAdjacentHTML('beforeend', deviceOption)
})
if (autoPickGPUsField.checked) {
let gpuSettingEntry = getParameterSettingsEntry("use_gpus")
gpuSettingEntry.style.display = "none"
let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
gpuSettingEntry.style.display = 'none'
} else {
$("#use_gpus").val(activeDeviceIds)
$('#use_gpus').val(activeDeviceIds)
}
document.dispatchEvent(new CustomEvent("system_info_update", { detail: devices }))
setHostInfo(res["hosts"])
let force = false
if (res["enforce_output_dir"] !== undefined) {
force = res["enforce_output_dir"]
if (force == true) {
saveToDiskField.checked = true
metadataOutputFormatField.disabled = false
}
saveToDiskField.disabled = force
diskPathField.disabled = force
}
setDiskPath(res["default_output_dir"], force)
setDeviceInfo(devices)
setHostInfo(res['hosts'])
setDiskPath(res['default_output_dir'])
} catch (e) {
console.log("error fetching devices", e)
console.log('error fetching devices', e)
}
}
saveSettingsBtn.addEventListener("click", function() {
if (listenPortField.value == "") {
alert("The network port field must not be empty.")
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")
alert('The network port must be a number from 1 to 65535')
return
}
const updateBranch = useBetaChannelField.checked ? "beta" : "main"
const updateAppConfigRequest = {
render_devices: getCurrentRenderDeviceSelection(),
update_branch: updateBranch,
}
document.querySelectorAll('#system-settings [data-setting-id]').forEach((parameterRow) => {
if (parameterRow.dataset.saveInAppConfig === "true") {
const parameterElement =
document.getElementById(parameterRow.dataset.settingId) ||
parameterRow.querySelector("input") ||
parameterRow.querySelector("select")
switch (parameterElement?.tagName) {
case "INPUT":
if (parameterElement.type === "checkbox") {
updateAppConfigRequest[parameterRow.dataset.settingId] = parameterElement.checked
} else {
updateAppConfigRequest[parameterRow.dataset.settingId] = parameterElement.value
}
break
case "SELECT":
if (parameterElement.multiple) {
updateAppConfigRequest[parameterRow.dataset.settingId] = Array.from(parameterElement.options)
.filter((option) => option.selected)
.map((option) => option.value || option.text)
} else {
updateAppConfigRequest[parameterRow.dataset.settingId] = parameterElement.value
}
break
default:
console.error(
`Setting parameter ${parameterRow.dataset.settingId} couldn't be saved to app.config - element #${parameter.id} is a <${parameterElement?.tagName} /> instead of a <input /> or a <select />!`
)
break
}
}
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
})
const savePromise = changeAppConfig(updateAppConfigRequest)
showToast("Settings saved")
saveSettingsBtn.classList.add("active")
Promise.all([savePromise, asyncDelay(300)]).then(() => saveSettingsBtn.classList.remove("active"))
saveSettingsBtn.classList.add('active')
asyncDelay(300).then(() => saveSettingsBtn.classList.remove('active'))
})
listenToNetworkField.addEventListener("change", debounce( ()=>{
saveSettingsBtn.click()
}, 1000))
listenPortField.addEventListener("change", debounce( ()=>{
saveSettingsBtn.click()
}, 1000))
let copyCloudflareAddressBtn = document.querySelector("#copy-cloudflare-address")
let cloudflareAddressField = document.getElementById("cloudflare-address")
copyCloudflareAddressBtn.addEventListener("click", (e) => {
navigator.clipboard.writeText(cloudflareAddressField.innerHTML)
showToast("Copied server address to clipboard")
})
document.addEventListener("system_info_update", (e) => setDeviceInfo(e.detail))

View File

@ -3,7 +3,7 @@ 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',
@ -25,24 +25,16 @@ const PLUGINS = {
* })
*/
IMAGE_INFO_BUTTONS: [],
GET_PROMPTS_HOOK: [],
MODIFIERS_LOAD: [],
TASK_CREATE: [],
OUTPUTS_FORMATS: new ServiceContainer(
function png() {
return (reqBody) => new SD.RenderTask(reqBody)
},
function jpeg() {
return (reqBody) => new SD.RenderTask(reqBody)
},
function webp() {
return (reqBody) => new SD.RenderTask(reqBody)
}
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") {
if (typeof outputFormatField !== 'undefined') {
const newOption = document.createElement("option")
newOption.setAttribute("value", service.name)
newOption.innerText = service.name
@ -52,13 +44,13 @@ PLUGINS.OUTPUTS_FORMATS.register = function(...args) {
}
function loadScript(url) {
const script = document.createElement("script")
const script = document.createElement('script')
const promiseSrc = new PromiseSource()
script.addEventListener("error", () => promiseSrc.reject(new Error(`Script "${url}" couldn't be loaded.`)))
script.addEventListener("load", () => promiseSrc.resolve(url))
script.src = url + "?t=" + Date.now()
script.addEventListener('error', () => promiseSrc.reject(new Error(`Script "${url}" couldn't be loaded.`)))
script.addEventListener('load', () => promiseSrc.resolve(url))
script.src = url + '?t=' + Date.now()
console.log("loading script", url)
console.log('loading script', url)
document.head.appendChild(script)
return promiseSrc.promise
@ -66,7 +58,7 @@ function loadScript(url) {
async function loadUIPlugins() {
try {
const res = await fetch("/get/ui_plugins")
const res = await fetch('/get/ui_plugins')
if (!res.ok) {
console.error(`Error HTTP${res.status} while loading plugins list. - ${res.statusText}`)
return
@ -75,6 +67,6 @@ async function loadUIPlugins() {
const loadingPromises = plugins.map(loadScript)
return await Promise.allSettled(loadingPromises)
} catch (e) {
console.log("error fetching plugin paths", e)
console.log('error fetching plugin paths', e)
}
}

View File

@ -1,670 +0,0 @@
"use strict"
let modelsCache
let modelsOptions
/*
*** SEARCHABLE MODELS ***
Creates searchable dropdowns for SD, VAE, or HN models.
Also adds a reload models button (placed next to SD models, reloads everything including VAE and HN models).
More reload buttons may be added at strategic UI locations as needed.
Merely calling getModels() makes all the magic happen behind the scene to refresh the dropdowns.
HOW TO CREATE A MODEL DROPDOWN:
1) Create an input element. Make sure to add a data-path property, as this is how model dropdowns are identified in auto-save.js.
<input id="stable_diffusion_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
2) Just declare one of these for your own dropdown (remember to change the element id, e.g. #stable_diffusion_models to your own input's id).
let stableDiffusionModelField = new ModelDropdown(document.querySelector('#stable_diffusion_model'), 'stable-diffusion')
let vaeModelField = new ModelDropdown(document.querySelector('#vae_model'), 'vae', 'None')
let hypernetworkModelField = new ModelDropdown(document.querySelector('#hypernetwork_model'), 'hypernetwork', 'None')
3) Model dropdowns will be refreshed automatically when the reload models button is invoked.
*/
class ModelDropdown {
modelFilter //= document.querySelector("#model-filter")
modelFilterArrow //= document.querySelector("#model-filter-arrow")
modelList //= document.querySelector("#model-list")
modelResult //= document.querySelector("#model-result")
modelNoResult //= document.querySelector("#model-no-result")
currentSelection //= { elem: undefined, value: '', path: ''}
highlightedModelEntry //= undefined
activeModel //= undefined
inputModels //= undefined
modelKey //= undefined
flatModelList //= []
noneEntry //= ''
modelFilterInitialized //= undefined
sorted //= true
/* MIMIC A REGULAR INPUT FIELD */
get parentElement() {
return this.modelFilter.parentElement
}
get parentNode() {
return this.modelFilter.parentNode
}
get value() {
return this.modelFilter.dataset.path
}
set value(path) {
this.modelFilter.dataset.path = path
this.selectEntry(path)
}
get disabled() {
return this.modelFilter.disabled
}
set disabled(state) {
this.modelFilter.disabled = state
if (this.modelFilterArrow) {
this.modelFilterArrow.style.color = state ? "dimgray" : ""
}
}
get modelElements() {
return this.modelList.querySelectorAll(".model-file")
}
addEventListener(type, listener, options) {
return this.modelFilter.addEventListener(type, listener, options)
}
dispatchEvent(event) {
return this.modelFilter.dispatchEvent(event)
}
appendChild(option) {
// do nothing
}
// remember 'this' - http://blog.niftysnippets.org/2008/04/you-must-remember-this.html
bind(f, obj) {
return function() {
return f.apply(obj, arguments)
}
}
/* SEARCHABLE INPUT */
constructor(input, modelKey, noneEntry = "", sorted = true) {
this.modelFilter = input
this.noneEntry = noneEntry
this.modelKey = modelKey
this.sorted = sorted
if (modelsOptions !== undefined) {
// reuse models from cache (only useful for plugins, which are loaded after models)
this.inputModels = []
let modelKeys = Array.isArray(this.modelKey) ? this.modelKey : [this.modelKey]
for (let i = 0; i < modelKeys.length; i++) {
let key = modelKeys[i]
let k = Array.isArray(modelsOptions[key]) ? modelsOptions[key] : [modelsOptions[key]]
this.inputModels.push(...k)
}
this.populateModels()
}
document.addEventListener(
"refreshModels",
this.bind(function(e) {
// reload the models
this.inputModels = []
let modelKeys = Array.isArray(this.modelKey) ? this.modelKey : [this.modelKey]
for (let i = 0; i < modelKeys.length; i++) {
let key = modelKeys[i]
let k = Array.isArray(modelsOptions[key]) ? modelsOptions[key] : [modelsOptions[key]]
this.inputModels.push(...k)
}
this.populateModels()
}, this)
)
}
saveCurrentSelection(elem, value, path) {
this.currentSelection.elem = elem
this.currentSelection.value = value
this.currentSelection.path = path
this.modelFilter.dataset.path = path
this.modelFilter.value = value
this.modelFilter.dispatchEvent(new Event("change"))
}
processClick(e) {
e.preventDefault()
if (e.srcElement.classList.contains("model-file") || e.srcElement.classList.contains("fa-file")) {
const elem = e.srcElement.classList.contains("model-file") ? e.srcElement : e.srcElement.parentElement
this.saveCurrentSelection(elem, elem.innerText, elem.dataset.path)
this.hideModelList()
this.modelFilter.focus()
this.modelFilter.select()
}
}
getPreviousVisibleSibling(elem) {
const modelElements = Array.from(this.modelElements)
const index = modelElements.indexOf(elem)
if (index <= 0) {
return undefined
}
return modelElements
.slice(0, index)
.reverse()
.find((e) => e.style.display === "list-item")
}
getLastVisibleChild(elem) {
let lastElementChild = elem.lastElementChild
if (lastElementChild.style.display == "list-item") return lastElementChild
return this.getPreviousVisibleSibling(lastElementChild)
}
getNextVisibleSibling(elem) {
const modelElements = Array.from(this.modelElements)
const index = modelElements.indexOf(elem)
return modelElements.slice(index + 1).find((e) => e.style.display === "list-item")
}
getFirstVisibleChild(elem) {
let firstElementChild = elem.firstElementChild
if (firstElementChild.style.display == "list-item") return firstElementChild
return this.getNextVisibleSibling(firstElementChild)
}
selectModelEntry(elem) {
if (elem) {
if (this.highlightedModelEntry !== undefined) {
this.highlightedModelEntry.classList.remove("selected")
}
this.saveCurrentSelection(elem, elem.innerText, elem.dataset.path)
elem.classList.add("selected")
elem.scrollIntoView({ block: "nearest" })
this.highlightedModelEntry = elem
}
}
selectPreviousFile() {
const elem = this.getPreviousVisibleSibling(this.highlightedModelEntry)
if (elem) {
this.selectModelEntry(elem)
} else {
//this.highlightedModelEntry.parentElement.parentElement.scrollIntoView({block: 'nearest'})
this.highlightedModelEntry.closest(".model-list").scrollTop = 0
}
this.modelFilter.select()
}
selectNextFile() {
this.selectModelEntry(this.getNextVisibleSibling(this.highlightedModelEntry))
this.modelFilter.select()
}
selectFirstFile() {
this.selectModelEntry(this.modelList.querySelector(".model-file"))
this.highlightedModelEntry.scrollIntoView({ block: "nearest" })
this.modelFilter.select()
}
selectLastFile() {
const elems = this.modelList.querySelectorAll(".model-file:last-child")
this.selectModelEntry(elems[elems.length - 1])
this.modelFilter.select()
}
resetSelection() {
this.hideModelList()
this.showAllEntries()
this.modelFilter.value = this.currentSelection.value
this.modelFilter.focus()
this.modelFilter.select()
}
validEntrySelected() {
return this.modelNoResult.style.display === "none"
}
processKey(e) {
switch (e.key) {
case "Escape":
e.preventDefault()
this.resetSelection()
break
case "Enter":
e.preventDefault()
if (this.validEntrySelected()) {
if (this.modelList.style.display != "block") {
this.showModelList()
} else {
this.saveCurrentSelection(
this.highlightedModelEntry,
this.highlightedModelEntry.innerText,
this.highlightedModelEntry.dataset.path
)
this.hideModelList()
this.showAllEntries()
}
this.modelFilter.focus()
} else {
this.resetSelection()
}
break
case "ArrowUp":
e.preventDefault()
if (this.validEntrySelected()) {
this.selectPreviousFile()
}
break
case "ArrowDown":
e.preventDefault()
if (this.validEntrySelected()) {
this.selectNextFile()
}
break
case "ArrowLeft":
if (this.modelList.style.display != "block") {
e.preventDefault()
}
break
case "ArrowRight":
if (this.modelList.style.display != "block") {
e.preventDefault()
}
break
case "PageUp":
e.preventDefault()
if (this.validEntrySelected()) {
this.selectPreviousFile()
this.selectPreviousFile()
this.selectPreviousFile()
this.selectPreviousFile()
this.selectPreviousFile()
this.selectPreviousFile()
this.selectPreviousFile()
this.selectPreviousFile()
}
break
case "PageDown":
e.preventDefault()
if (this.validEntrySelected()) {
this.selectNextFile()
this.selectNextFile()
this.selectNextFile()
this.selectNextFile()
this.selectNextFile()
this.selectNextFile()
this.selectNextFile()
this.selectNextFile()
}
break
case "Home":
//if (this.modelList.style.display != 'block') {
e.preventDefault()
if (this.validEntrySelected()) {
this.selectFirstFile()
}
//}
break
case "End":
//if (this.modelList.style.display != 'block') {
e.preventDefault()
if (this.validEntrySelected()) {
this.selectLastFile()
}
//}
break
default:
//console.log(e.key)
}
}
modelListFocus() {
this.selectEntry()
this.showAllEntries()
}
showModelList() {
this.modelList.style.display = "block"
this.selectEntry()
this.showAllEntries()
//this.modelFilter.value = ''
this.modelFilter.select() // preselect the entire string so user can just start typing.
this.modelFilter.focus()
this.modelFilter.style.cursor = "auto"
}
hideModelList() {
this.modelList.style.display = "none"
this.modelFilter.value = this.currentSelection.value
this.modelFilter.style.cursor = ""
}
toggleModelList(e) {
e.preventDefault()
if (!this.modelFilter.disabled) {
if (this.modelList.style.display != "block") {
this.showModelList()
} else {
this.hideModelList()
this.modelFilter.select()
}
}
}
selectEntry(path) {
if (path !== undefined) {
const entries = this.modelElements
for (const elem of entries) {
if (elem.dataset.path == path) {
this.saveCurrentSelection(elem, elem.innerText, elem.dataset.path)
this.highlightedModelEntry = elem
elem.scrollIntoView({ block: "nearest" })
break
}
}
}
if (this.currentSelection.elem !== undefined) {
// select the previous element
if (this.highlightedModelEntry !== undefined && this.highlightedModelEntry != this.currentSelection.elem) {
this.highlightedModelEntry.classList.remove("selected")
}
this.currentSelection.elem.classList.add("selected")
this.highlightedModelEntry = this.currentSelection.elem
this.currentSelection.elem.scrollIntoView({ block: "nearest" })
} else {
this.selectFirstFile()
}
}
highlightModelAtPosition(e) {
let elem = document.elementFromPoint(e.clientX, e.clientY)
if (elem.classList.contains("model-file")) {
this.highlightModel(elem)
}
}
highlightModel(elem) {
if (elem.classList.contains("model-file")) {
if (this.highlightedModelEntry !== undefined && this.highlightedModelEntry != elem) {
this.highlightedModelEntry.classList.remove("selected")
}
elem.classList.add("selected")
this.highlightedModelEntry = elem
}
}
showAllEntries() {
this.modelList.querySelectorAll("li").forEach(function(li) {
if (li.id !== "model-no-result") {
li.style.display = "list-item"
}
})
this.modelNoResult.style.display = "none"
}
filterList(e) {
const filter = this.modelFilter.value.toLowerCase()
let found = false
let showAllChildren = false
this.modelList.querySelectorAll("li").forEach(function(li) {
if (li.classList.contains("model-folder")) {
showAllChildren = false
}
if (filter == "") {
li.style.display = "list-item"
found = true
} else if (showAllChildren || li.textContent.toLowerCase().match(filter)) {
li.style.display = "list-item"
if (li.classList.contains("model-folder") && li.firstChild.textContent.toLowerCase().match(filter)) {
showAllChildren = true
}
found = true
} else {
li.style.display = "none"
}
})
if (found) {
this.modelResult.style.display = "list-item"
this.modelNoResult.style.display = "none"
const elem = this.getNextVisibleSibling(this.modelList.querySelector(".model-file"))
this.highlightModel(elem)
elem.scrollIntoView({ block: "nearest" })
} else {
this.modelResult.style.display = "none"
this.modelNoResult.style.display = "list-item"
}
this.modelList.style.display = "block"
}
/* MODEL LOADER */
getElementDimensions(element) {
// Clone the element
const clone = element.cloneNode(true)
// Copy the styles of the original element to the cloned element
const originalStyles = window.getComputedStyle(element)
for (let i = 0; i < originalStyles.length; i++) {
const property = originalStyles[i]
clone.style[property] = originalStyles.getPropertyValue(property)
}
// Set its visibility to hidden and display to inline-block
clone.style.visibility = "hidden"
clone.style.display = "inline-block"
// Put the cloned element next to the original element
element.parentNode.insertBefore(clone, element.nextSibling)
// Get its width and height
const width = clone.offsetWidth
const height = clone.offsetHeight
// Remove it from the DOM
clone.remove()
// Return its width and height
return { width, height }
}
/**
* @param {Array<string>} models
*/
sortStringArray(models) {
models.sort((a, b) => a.localeCompare(b, undefined, { sensitivity: "base" }))
}
populateModels() {
this.activeModel = this.modelFilter.dataset.path
this.currentSelection = { elem: undefined, value: "", path: "" }
this.highlightedModelEntry = undefined
this.flatModelList = []
if (this.modelList !== undefined) {
this.modelList.remove()
this.modelFilterArrow.remove()
}
this.createDropdown()
}
createDropdown() {
// create dropdown entries
let rootModelList = this.createRootModelList(this.inputModels)
this.modelFilter.insertAdjacentElement("afterend", rootModelList)
this.modelFilter.insertAdjacentElement(
"afterend",
createElement("i", { id: `${this.modelFilter.id}-model-filter-arrow` }, [
"model-selector-arrow",
"fa-solid",
"fa-angle-down",
])
)
this.modelFilter.classList.add("model-selector")
this.modelFilterArrow = document.querySelector(`#${this.modelFilter.id}-model-filter-arrow`)
if (this.modelFilterArrow) {
this.modelFilterArrow.style.color = this.modelFilter.disabled ? "dimgray" : ""
}
this.modelList = document.querySelector(`#${this.modelFilter.id}-model-list`)
this.modelResult = document.querySelector(`#${this.modelFilter.id}-model-result`)
this.modelNoResult = document.querySelector(`#${this.modelFilter.id}-model-no-result`)
if (this.modelFilterInitialized !== true) {
this.modelFilter.addEventListener("input", this.bind(this.filterList, this))
this.modelFilter.addEventListener("focus", this.bind(this.modelListFocus, this))
this.modelFilter.addEventListener("blur", this.bind(this.hideModelList, this))
this.modelFilter.addEventListener("click", this.bind(this.showModelList, this))
this.modelFilter.addEventListener("keydown", this.bind(this.processKey, this))
this.modelFilterInitialized = true
}
this.modelFilterArrow.addEventListener("mousedown", this.bind(this.toggleModelList, this))
this.modelList.addEventListener("mousemove", this.bind(this.highlightModelAtPosition, this))
this.modelList.addEventListener("mousedown", this.bind(this.processClick, this))
let mf = this.modelFilter
this.modelFilter.addEventListener("focus", function() {
let modelFilterStyle = window.getComputedStyle(mf)
rootModelList.style.minWidth = modelFilterStyle.width
})
this.selectEntry(this.activeModel)
}
/**
* @param {Array<string | object} modelTree
* @param {string} folderName
* @param {boolean} isRootFolder
* @returns {HTMLElement}
*/
createModelNodeList(folderName, modelTree, isRootFolder) {
const listElement = createElement("ul")
const foldersMap = new Map()
const modelsMap = new Map()
modelTree.forEach((model) => {
if (Array.isArray(model)) {
const [childFolderName, childModels] = model
foldersMap.set(
childFolderName,
this.createModelNodeList(`${folderName || ""}/${childFolderName}`, childModels, false)
)
} else {
const classes = ["model-file"]
if (isRootFolder) {
classes.push("in-root-folder")
}
// Remove the leading slash from the model path
const fullPath = folderName ? `${folderName.substring(1)}/${model}` : model
modelsMap.set(
model,
createElement("li", { "data-path": fullPath }, classes, [
createElement("i", undefined, ["fa-regular", "fa-file", "icon"]),
model,
])
)
}
})
const childFolderNames = Array.from(foldersMap.keys())
if (this.sorted) {
this.sortStringArray(childFolderNames)
}
const folderElements = childFolderNames.map((name) => foldersMap.get(name))
const modelNames = Array.from(modelsMap.keys())
if (this.sorted) {
this.sortStringArray(modelNames)
}
const modelElements = modelNames.map((name) => modelsMap.get(name))
if (modelElements.length && folderName) {
listElement.appendChild(
createElement(
"li",
undefined,
["model-folder"],
[createElement("i", undefined, ["fa-regular", "fa-folder-open", "icon"]), folderName.substring(1)]
)
)
}
// const allModelElements = isRootFolder ? [...folderElements, ...modelElements] : [...modelElements, ...folderElements]
const allModelElements = [...modelElements, ...folderElements]
allModelElements.forEach((e) => listElement.appendChild(e))
return listElement
}
/**
* @param {object} modelTree
* @returns {HTMLElement}
*/
createRootModelList(modelTree) {
const rootList = createElement("ul", { id: `${this.modelFilter.id}-model-list` }, ["model-list"])
rootList.appendChild(
createElement("li", { id: `${this.modelFilter.id}-model-no-result` }, ["model-no-result"], "No result")
)
if (this.noneEntry) {
rootList.appendChild(
createElement("li", { "data-path": "" }, ["model-file", "in-root-folder"], this.noneEntry)
)
}
if (modelTree.length > 0) {
const containerListItem = createElement("li", { id: `${this.modelFilter.id}-model-result` }, [
"model-result",
])
//console.log(containerListItem)
containerListItem.appendChild(this.createModelNodeList(undefined, modelTree, true))
rootList.appendChild(containerListItem)
}
return rootList
}
}
/* (RE)LOAD THE MODELS */
async function getModels() {
try {
modelsCache = await SD.getModels()
modelsOptions = modelsCache["options"]
if ("scan-error" in modelsCache) {
// let previewPane = document.getElementById('tab-content-wrapper')
let previewPane = document.getElementById("preview")
previewPane.style.background = "red"
previewPane.style.textAlign = "center"
previewPane.innerHTML =
"<H1>🔥Malware alert!🔥</H1><h2>The file <i>" +
modelsCache["scan-error"] +
'</i> in your <tt>models/stable-diffusion</tt> folder is probably malware infected.</h2><h2>Please delete this file from the folder before proceeding!</h2>After deleting the file, reload this page.<br><br><button onClick="window.location.reload();">Reload Page</button>'
makeImageBtn.disabled = true
}
/* This code should no longer be needed. Commenting out for now, will cleanup later.
const sd_model_setting_key = "stable_diffusion_model"
const vae_model_setting_key = "vae_model"
const hypernetwork_model_key = "hypernetwork_model"
const stableDiffusionOptions = modelsOptions['stable-diffusion']
const vaeOptions = modelsOptions['vae']
const hypernetworkOptions = modelsOptions['hypernetwork']
// TODO: set default for model here too
SETTINGS[sd_model_setting_key].default = stableDiffusionOptions[0]
if (getSetting(sd_model_setting_key) == '' || SETTINGS[sd_model_setting_key].value == '') {
setSetting(sd_model_setting_key, stableDiffusionOptions[0])
}
*/
// notify ModelDropdown objects to refresh
document.dispatchEvent(new Event("refreshModels"))
} catch (e) {
console.log("get models error", e)
}
}
// reload models button
document.querySelector("#reload-models").addEventListener("click", getModels)

View File

@ -1,85 +1,82 @@
const themeField = document.getElementById("theme")
var DEFAULT_THEME = {}
var THEMES = [] // initialized in initTheme from data in css
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
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
.filter(sheet => sheet.href?.startsWith(window.location.origin))
.flatMap(sheet => Array.from(sheet.cssRules))
.forEach(rule => {
var selector = rule.selectorText;
if (selector && selector.startsWith(".theme-") && !selector.includes(" ")) {
if (DEFAULT_THEME) {
// re-add props that dont change (css needs this so they update correctly)
if (DEFAULT_THEME) { // re-add props that dont change (css needs this so they update correctly)
Array.from(DEFAULT_THEME.rule.style)
.filter((cssVariable) => !Array.from(rule.style).includes(cssVariable))
.forEach((cssVariable) => {
rule.style.setProperty(cssVariable, DEFAULT_THEME.rule.style.getPropertyValue(cssVariable))
})
.filter(cssVariable => !Array.from(rule.style).includes(cssVariable))
.forEach(cssVariable => {
rule.style.setProperty(cssVariable, DEFAULT_THEME.rule.style.getPropertyValue(cssVariable));
});
}
var theme_key = selector.substring(1)
var theme_key = selector.substring(1);
THEMES.push({
key: theme_key,
name: getThemeName(theme_key),
rule: rule,
rule: rule
})
}
if (selector && selector == ":root") {
DEFAULT_THEME = {
key: "theme-default",
name: "Default",
rule: rule,
}
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)
})
});
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)
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()
initTheme();
function themeFieldChanged() {
var theme_key = themeField.value
var theme_key = themeField.value;
var body = document.querySelector("body")
body.classList.remove(...THEMES.map((theme) => theme.key))
body.classList.add(theme_key)
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)
body.style = "";
var theme = THEMES.find(t => t.key == theme_key);
let borderColor = undefined
if (theme) {
borderColor = theme.rule.style.getPropertyValue("--input-border-color").trim()
if (!borderColor.startsWith("#")) {
borderColor = theme.rule.style.getPropertyValue("--theme-color-fallback")
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")
borderColor = DEFAULT_THEME.rule.style.getPropertyValue('--theme-color-fallback')
}
document.querySelector('meta[name="theme-color"]').setAttribute("content", borderColor)
}
themeField.addEventListener("change", themeFieldChanged)
themeField.addEventListener('change', themeFieldChanged);

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@ -2428,19 +2428,6 @@
"path": "artist/by_yoshitaka_amano/landscape-0.jpg"
}
]
},
{
"modifier": "by Zdzislaw Beksinski",
"previews": [
{
"name": "portrait",
"path": "artist/by_zdzislaw_beksinski/portrait-0.jpg"
},
{
"name": "landscape",
"path": "artist/by_zdzislaw_beksinski/landscape-0.jpg"
}
]
}
]
},

View File

@ -1,32 +1,45 @@
;(function() {
(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") {
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,
observer.observe(document.getElementById('preview'), {
childList: true,
subtree: true
})
function Autoscroll(target) {
if (autoScroll.checked && target !== null) {
const img = target.querySelector("img")
img.addEventListener(
"load",
function() {
img?.closest(".imageTaskContainer").scrollIntoView()
},
{ once: true }
)
target.parentElement.parentElement.parentElement.scrollIntoView();
}
}
})()

View File

@ -1,116 +1,93 @@
;(function() {
"use strict"
if (typeof editorModifierTagsList !== "object") {
console.error("editorModifierTagsList missing...")
(function () { "use strict"
if (typeof editorModifierTagsList !== 'object') {
console.error('editorModifierTagsList missing...')
return
}
const styleSheet = document.createElement("style")
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)
`;
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)
}
// })
const observer = new MutationObserver(function (mutations) {
// mutations.forEach(function (mutation) {
if (editorModifierTagsList.childNodes.length > 0) {
ModifierDragAndDrop(editorModifierTagsList)
}
// })
})
observer.observe(editorModifierTagsList, {
childList: true,
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
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.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"
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.parentElement.parentElement.style.transform = 'none'
item.parentElement.parentElement.style.boxShadow = 'none'
}
item.innerText = ""
item.innerText = ''
}
}
i.ondragenter = (e) => {
e.preventDefault()
if (i != current) {
let currentPos = 0,
droppedPos = 0
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 (current == overlays[it]) { currentPos = it; }
if (i == overlays[it]) { droppedPos = it; }
}
if (i.parentElement != current.parentElement) {
let currentPos = 0,
droppedPos = 0
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 (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]
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]
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])
document.dispatchEvent(new Event("refreshImageModifiers"))
document.dispatchEvent(new Event('refreshImageModifiers'))
}
}
}
};
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 = "-"
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 = '-'
}
}
})

View File

@ -1,87 +1,64 @@
;(function() {
"use strict"
const MAX_WEIGHT = 5
if (typeof editorModifierTagsList !== "object") {
console.error("editorModifierTagsList missing...")
(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)
}
// })
const observer = new MutationObserver(function (mutations) {
// mutations.forEach(function (mutation) {
if (editorModifierTagsList.childNodes.length > 0) {
ModifierMouseWheel(editorModifierTagsList)
}
// })
})
observer.observe(editorModifierTagsList, {
childList: true,
childList: true
})
function ModifierMouseWheel(target) {
let overlays = document.querySelector("#editor-inputs-tags-list").querySelectorAll(".modifier-card-overlay")
overlays.forEach((i) => {
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
let t
// find the corresponding tag
for (let it = 0; it < overlays.length; it++) {
if (i == overlays[it]) {
t = activeTags[it].name
break
}
}
if (s.charAt(0) !== "(" && s.charAt(s.length - 1) !== ")" && s.trim().includes(" ")) {
s = "(" + s + ")"
t = "(" + t + ")"
}
let s = i.parentElement.getElementsByClassName('modifier-card-label')[0].getElementsByTagName("p")[0].innerText
if (delta < 0) {
// wheel scrolling up
if (s.substring(s.length - 1) == "-") {
s = s.substring(0, s.length - 1)
t = t.substring(0, t.length - 1)
} else {
if (s.substring(s.length - MAX_WEIGHT) !== "+".repeat(MAX_WEIGHT)) {
s = s + "+"
t = t + "+"
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 {
}
else{
// wheel scrolling down
if (s.substring(s.length - 1) == "+") {
s = s.substring(0, s.length - 1)
t = t.substring(0, t.length - 1)
} else {
if (s.substring(s.length - MAX_WEIGHT) !== "-".repeat(MAX_WEIGHT)) {
s = s + "-"
t = t + "-"
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 + ']'
}
}
}
if (s.charAt(0) === "(" && s.charAt(s.length - 1) === ")") {
s = s.substring(1, s.length - 1)
t = t.substring(1, t.length - 1)
}
i.parentElement
.getElementsByClassName("modifier-card-label")[0]
.getElementsByTagName("p")[0].innerText = 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 = t
activeTags[it].name = s
break
}
}
document.dispatchEvent(new Event("refreshImageModifiers"))
document.dispatchEvent(new Event('refreshImageModifiers'))
}
}
})

View File

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

View File

@ -26,39 +26,39 @@ WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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")
(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
/**
* ## 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)
/**
* 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()
/**
* 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)
/**
* ## 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]
}
})()
/**
* 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];
}
})();

View File

@ -33,98 +33,100 @@ WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
after `boot0.js` is loaded and before this file is loaded.
*/
;(function() {
const env = jasmine.getEnv()
(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.
*/
/**
* ## 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 queryString = new jasmine.QueryString({
getWindowLocation: function() {
return window.location;
}
});
const random = queryString.getParam("random")
const filterSpecs = !!queryString.getParam('spec');
if (random !== undefined && random !== "") {
config.random = random
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');
}
});
const seed = queryString.getParam("seed")
if (seed) {
config.seed = seed
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();
}
/**
* ## 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()
}
})()
htmlReporter.initialize();
env.execute();
};
})();

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File diff suppressed because it is too large Load Diff

View File

@ -2,34 +2,34 @@
const JASMINE_SESSION_ID = `jasmine-${String(Date.now()).slice(8)}`
beforeEach(function() {
beforeEach(function () {
jasmine.DEFAULT_TIMEOUT_INTERVAL = 15 * 60 * 1000 // Test timeout after 15 minutes
jasmine.addMatchers({
toBeOneOf: function() {
toBeOneOf: function () {
return {
compare: function(actual, expected) {
compare: function (actual, expected) {
return {
pass: expected.includes(actual),
pass: expected.includes(actual)
}
},
}
}
},
}
})
})
describe("stable-diffusion-ui", function() {
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")
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() {
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() {
it('enfore the current task state', function() {
const task = new SD.Task()
expect(task.status).toBe(SD.TaskStatus.init)
expect(task.isPending).toBeTrue()
@ -65,161 +65,149 @@ describe("stable-diffusion-ui", function() {
task._setStatus(SD.TaskStatus.completed)
}).toThrowError()
})
it("should be able to run tasks", async function() {
expect(typeof SD.Task.run).toBe("function")
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(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 }
})('start')
const callback = function({value, done}) {
return {value: 2 * value, done}
}
expect(await SD.Task.run(promiseGenerator, { callback })).toBe(32)
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")
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(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 }
})('start')
const callback = function({value, done}) {
return {value: 2 * value, done}
}
const gen = SD.Task.asGenerator({ generator: promiseGenerator, callback })
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")
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(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" })
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() {
describe('ServiceContainer', function() {
it('should be able to register providers', function() {
const cont = new ServiceContainer(
function foo() {
this.bar = ""
this.bar = ''
},
function bar() {
return () => 0
},
{ name: "zero", definition: 0 },
{ name: "ctx", definition: () => Object.create(null), singleton: true },
{
name: "test",
{ 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(ctx).toEqual({ran: true})
expect(one).toBe(1)
expect(typeof foo).toBe("object")
expect(typeof foo).toBe('object')
expect(foo.bar).toBeDefined()
expect(typeof missing).toBe("undefined")
return { foo: "bar" }
},
dependencies: ["ctx", "missing", "one", "foo"],
expect(typeof missing).toBe('undefined')
return {foo: 'bar'}
}, dependencies: ['ctx', 'missing', 'one', 'foo']
}
)
const fooObj = cont.get("foo")
expect(typeof fooObj).toBe("object")
const fooObj = cont.get('foo')
expect(typeof fooObj).toBe('object')
fooObj.ran = true
const ctx = cont.get("ctx")
const ctx = cont.get('ctx')
expect(ctx).toEqual({})
ctx.ran = true
const bar = cont.get("bar")
expect(typeof bar).toBe("function")
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")
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() {
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",
let res = await fetch('/render', {
method: 'POST',
headers: {
"Content-Type": "application/json",
'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),
"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,
"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",
"numOutputsParallel": 1,
"stream_image_progress": true,
"show_only_filtered_image": true,
"output_format": "jpeg",
session_id: JASMINE_SESSION_ID,
"session_id": JASMINE_SESSION_ID,
}),
})
expect(res.ok).toBeTruthy()
const renderRequest = await res.json()
expect(typeof renderRequest.stream).toBe("string")
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
)
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"
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)
@ -229,24 +217,24 @@ describe("stable-diffusion-ui", function() {
if (!value || value.length <= 0) {
return
}
return reader.readStreamAsJSON(value.join(""))
return reader.readStreamAsJSON(value.join(''))
}
reader.onNext = function({ done, value }) {
reader.onNext = function({done, value}) {
console.log(value)
if (typeof value === "object" && "status" in value) {
if (typeof value === 'object' && 'status' in value) {
done = true
}
return { done, value }
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)
console.log('ChunkedStreamReader received ', stepUpdate)
lastUpdate = stepUpdate
if (complete) {
expect(stepUpdate.status).toBe("succeeded")
expect(stepUpdate.status).toBe('succeeded')
expect(stepUpdate.output).toHaveSize(1)
} else {
expect(stepUpdate.total_steps).toBe(nbr_steps)
@ -258,76 +246,70 @@ describe("stable-diffusion-ui", function() {
}
}
}
for (let i = 1; i <= 5; ++i) {
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)
console.log('Cache test %s received %o', i, cachedResponse)
expect(lastUpdate).toEqual(cachedResponse)
}
})
describe("should be able to make renders", function() {
describe('should be able to make renders', function() {
beforeEach(function() {
expect(SD.isServerAvailable()).toBeTrue()
})
it("basic inline request", async function() {
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)
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 {
expect(stepUpdate.step).toBe(stepCount)
if (stepUpdate.step === stepUpdate.total_steps) {
complete = true
} else {
stepCount++
}
stepCount++
}
}
}
)
})
console.log(result)
expect(result.status).toBe("succeeded")
expect(result.status).toBe('succeeded')
expect(result.output).toHaveSize(2)
})
it("post and reader request", async function() {
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,
"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(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..."),
})
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
@ -336,7 +318,7 @@ describe("stable-diffusion-ui", function() {
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.status).toBe('succeeded')
expect(stepUpdate.output).toHaveSize(1)
} else {
expect(stepUpdate.step).toBe(stepCount)
@ -348,28 +330,28 @@ describe("stable-diffusion-ui", function() {
}
}
expect(renderTask.status).toBe(SD.TaskStatus.completed)
expect(renderTask.result.status).toBe("succeeded")
expect(renderTask.result.status).toBe('succeeded')
expect(renderTask.result.output).toHaveSize(1)
})
it("queued request", async function() {
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,
"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,
"use_upscale": "RealESRGAN_x4plus",
"session_id": JASMINE_SESSION_ID,
})
await renderTask.enqueue(function(event) {
console.log(this, event)
if ("update" in 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.status).toBe('succeeded')
expect(stepUpdate.output).toHaveSize(2)
} else {
expect(stepUpdate.step).toBe(stepCount)
@ -382,12 +364,12 @@ describe("stable-diffusion-ui", function() {
}
})
console.log(renderTask.result)
expect(renderTask.result.status).toBe("succeeded")
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() {
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.")
@ -404,17 +386,16 @@ 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")
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.
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() {
it('but nothing loaded...', function() {
expect(true).toBeTruthy()
})
return

View File

@ -1,454 +0,0 @@
;(function() {
"use strict"
///////////////////// Function section
function smoothstep(x) {
return x * x * (3 - 2 * x)
}
function smootherstep(x) {
return x * x * x * (x * (x * 6 - 15) + 10)
}
function smootheststep(x) {
let y = -20 * Math.pow(x, 7)
y += 70 * Math.pow(x, 6)
y -= 84 * Math.pow(x, 5)
y += 35 * Math.pow(x, 4)
return y
}
function getCurrentTime() {
const now = new Date()
let hours = now.getHours()
let minutes = now.getMinutes()
let seconds = now.getSeconds()
hours = hours < 10 ? `0${hours}` : hours
minutes = minutes < 10 ? `0${minutes}` : minutes
seconds = seconds < 10 ? `0${seconds}` : seconds
return `${hours}:${minutes}:${seconds}`
}
function addLogMessage(message) {
const logContainer = document.getElementById("merge-log")
logContainer.innerHTML += `<i>${getCurrentTime()}</i> ${message}<br>`
// Scroll to the bottom of the log
logContainer.scrollTop = logContainer.scrollHeight
document.querySelector("#merge-log-container").style.display = "block"
}
function addLogSeparator() {
const logContainer = document.getElementById("merge-log")
logContainer.innerHTML += "<hr>"
logContainer.scrollTop = logContainer.scrollHeight
}
function drawDiagram(fn) {
const SIZE = 300
const canvas = document.getElementById("merge-canvas")
canvas.height = canvas.width = SIZE
const ctx = canvas.getContext("2d")
// Draw coordinate system
ctx.scale(1, -1)
ctx.translate(0, -canvas.height)
ctx.lineWidth = 1
ctx.beginPath()
ctx.strokeStyle = "white"
ctx.moveTo(0, 0)
ctx.lineTo(0, SIZE)
ctx.lineTo(SIZE, SIZE)
ctx.lineTo(SIZE, 0)
ctx.lineTo(0, 0)
ctx.lineTo(SIZE, SIZE)
ctx.stroke()
ctx.beginPath()
ctx.setLineDash([1, 2])
const n = SIZE / 10
for (let i = n; i < SIZE; i += n) {
ctx.moveTo(0, i)
ctx.lineTo(SIZE, i)
ctx.moveTo(i, 0)
ctx.lineTo(i, SIZE)
}
ctx.stroke()
ctx.beginPath()
ctx.setLineDash([])
ctx.beginPath()
ctx.strokeStyle = "black"
ctx.lineWidth = 3
// Plot function
const numSamples = 20
for (let i = 0; i <= numSamples; i++) {
const x = i / numSamples
const y = fn(x)
const canvasX = x * SIZE
const canvasY = y * SIZE
if (i === 0) {
ctx.moveTo(canvasX, canvasY)
} else {
ctx.lineTo(canvasX, canvasY)
}
}
ctx.stroke()
// Plot alpha values (yellow boxes)
let start = parseFloat(document.querySelector("#merge-start").value)
let step = parseFloat(document.querySelector("#merge-step").value)
let iterations = document.querySelector("#merge-count").value >> 0
ctx.beginPath()
ctx.fillStyle = "yellow"
for (let i = 0; i < iterations; i++) {
const alpha = (start + i * step) / 100
const x = alpha * SIZE
const y = fn(alpha) * SIZE
if (x <= SIZE) {
ctx.rect(x - 3, y - 3, 6, 6)
ctx.fill()
} else {
ctx.strokeStyle = "red"
ctx.moveTo(0, 0)
ctx.lineTo(0, SIZE)
ctx.lineTo(SIZE, SIZE)
ctx.lineTo(SIZE, 0)
ctx.lineTo(0, 0)
ctx.lineTo(SIZE, SIZE)
ctx.stroke()
addLogMessage("<i>Warning: maximum ratio is &#8805; 100%</i>")
}
}
}
function updateChart() {
let fn = (x) => x
switch (document.querySelector("#merge-interpolation").value) {
case "SmoothStep":
fn = smoothstep
break
case "SmootherStep":
fn = smootherstep
break
case "SmoothestStep":
fn = smootheststep
break
}
drawDiagram(fn)
}
createTab({
id: "merge",
icon: "fa-code-merge",
label: "Merge models",
css: `
#tab-content-merge .tab-content-inner {
max-width: 100%;
padding: 10pt;
}
.merge-container {
margin-left: 15%;
margin-right: 15%;
text-align: left;
display: inline-grid;
grid-template-columns: 1fr 1fr;
grid-template-rows: auto auto auto;
gap: 0px 0px;
grid-auto-flow: row;
grid-template-areas:
"merge-input merge-config"
"merge-buttons merge-buttons";
}
.merge-container p {
margin-top: 3pt;
margin-bottom: 3pt;
}
.merge-config .tab-content {
background: var(--background-color1);
border-radius: 3pt;
}
.merge-config .tab-content-inner {
text-align: left;
}
.merge-input {
grid-area: merge-input;
padding-left:1em;
}
.merge-config {
grid-area: merge-config;
padding:1em;
}
.merge-config input {
margin-bottom: 3px;
}
.merge-config select {
margin-bottom: 3px;
}
.merge-buttons {
grid-area: merge-buttons;
padding:1em;
text-align: center;
}
#merge-button {
padding: 8px;
width:20em;
}
div#merge-log {
height:150px;
overflow-x:hidden;
overflow-y:scroll;
background:var(--background-color1);
border-radius: 3pt;
}
div#merge-log i {
color: hsl(var(--accent-hue), 100%, calc(2*var(--accent-lightness)));
font-family: monospace;
}
.disabled {
background: var(--background-color4);
color: var(--text-color);
}
#merge-type-tabs {
border-bottom: 1px solid black;
}
#merge-log-container {
display: none;
}
.merge-container #merge-warning {
color: rgb(153, 153, 153);
}`,
content: `
<div class="merge-container panel-box">
<div class="merge-input">
<p><label for="#mergeModelA">Select Model A:</label></p>
<input id="mergeModelA" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<p><label for="#mergeModelB">Select Model B:</label></p>
<input id="mergeModelB" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<br/><br/>
<p id="merge-warning"><small><b>Important:</b> Please merge models of similar type.<br/>For e.g. <code>SD 1.4</code> models with only <code>SD 1.4/1.5</code> models,<br/><code>SD 2.0</code> with <code>SD 2.0</code>-type, and <code>SD 2.1</code> with <code>SD 2.1</code>-type models.</small></p>
<br/>
<table>
<tr>
<td><label for="#merge-filename">Output file name:</label></td>
<td><input id="merge-filename" size=24> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Base name of the output file.<br>Mix ratio and file suffix will be appended to this.</span></i></td>
</tr>
<tr>
<td><label for="#merge-fp">Output precision:</label></td>
<td><select id="merge-fp">
<option value="fp16">fp16 (smaller file size)</option>
<option value="fp32">fp32 (larger file size)</option>
</select>
<i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Image generation uses fp16, so it's a good choice.<br>Use fp32 if you want to use the result models for more mixes</span></i>
</td>
</tr>
<tr>
<td><label for="#merge-format">Output file format:</label></td>
<td><select id="merge-format">
<option value="safetensors">Safetensors (recommended)</option>
<option value="ckpt">CKPT/Pickle (legacy format)</option>
</select>
</td>
</tr>
</table>
<br/>
<div id="merge-log-container">
<p><label for="#merge-log">Log messages:</label></p>
<div id="merge-log"></div>
</div>
</div>
<div class="merge-config">
<div class="tab-container">
<span id="tab-merge-opts-single" class="tab active">
<span>Make a single file</small></span>
</span>
<span id="tab-merge-opts-batch" class="tab">
<span>Make multiple variations</small></span>
</span>
</div>
<div>
<div id="tab-content-merge-opts-single" class="tab-content active">
<div class="tab-content-inner">
<small>Saves a single merged model file, at the specified merge ratio.</small><br/><br/>
<label for="#single-merge-ratio-slider">Merge ratio:</label>
<input id="single-merge-ratio-slider" name="single-merge-ratio-slider" class="editor-slider" value="50" type="range" min="1" max="1000">
<input id="single-merge-ratio" size=2 value="5">%
<i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Model A's contribution to the mix. The rest will be from Model B.</span></i>
</div>
</div>
<div id="tab-content-merge-opts-batch" class="tab-content">
<div class="tab-content-inner">
<small>Saves multiple variations of the model, at different merge ratios.<br/>Each variation will be saved as a separate file.</small><br/><br/>
<table>
<tr><td><label for="#merge-count">Number of variations:</label></td>
<td> <input id="merge-count" size=2 value="5"></td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Number of models to create</span></i></td></tr>
<tr><td><label for="#merge-start">Starting merge ratio:</label></td>
<td> <input id="merge-start" size=2 value="5">%</td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Smallest share of model A in the mix</span></i></td></tr>
<tr><td><label for="#merge-step">Increment each step:</label></td>
<td> <input id="merge-step" size=2 value="10">%</td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Share of model A added into the mix per step</span></i></td></tr>
<tr><td><label for="#merge-interpolation">Interpolation model:</label></td>
<td> <select id="merge-interpolation">
<option>Exact</option>
<option>SmoothStep</option>
<option>SmootherStep</option>
<option>SmoothestStep</option>
</select></td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Sigmoid function to be applied to the model share before mixing</span></i></td></tr>
</table>
<br/>
<small>Preview of variation ratios:</small><br/>
<canvas id="merge-canvas" width="400" height="400"></canvas>
</div>
</div>
</div>
</div>
<div class="merge-buttons">
<button id="merge-button" class="primaryButton">Merge models</button>
</div>
</div>`,
onOpen: ({ firstOpen }) => {
if (!firstOpen) {
return
}
const tabSettingsSingle = document.querySelector("#tab-merge-opts-single")
const tabSettingsBatch = document.querySelector("#tab-merge-opts-batch")
linkTabContents(tabSettingsSingle)
linkTabContents(tabSettingsBatch)
console.log("Activate")
let mergeModelAField = new ModelDropdown(document.querySelector("#mergeModelA"), "stable-diffusion")
let mergeModelBField = new ModelDropdown(document.querySelector("#mergeModelB"), "stable-diffusion")
updateChart()
// slider
const singleMergeRatioField = document.querySelector("#single-merge-ratio")
const singleMergeRatioSlider = document.querySelector("#single-merge-ratio-slider")
function updateSingleMergeRatio() {
singleMergeRatioField.value = singleMergeRatioSlider.value / 10
singleMergeRatioField.dispatchEvent(new Event("change"))
}
function updateSingleMergeRatioSlider() {
if (singleMergeRatioField.value < 0) {
singleMergeRatioField.value = 0
} else if (singleMergeRatioField.value > 100) {
singleMergeRatioField.value = 100
}
singleMergeRatioSlider.value = singleMergeRatioField.value * 10
singleMergeRatioSlider.dispatchEvent(new Event("change"))
}
singleMergeRatioSlider.addEventListener("input", updateSingleMergeRatio)
singleMergeRatioField.addEventListener("input", updateSingleMergeRatioSlider)
updateSingleMergeRatio()
document.querySelector(".merge-config").addEventListener("change", updateChart)
document.querySelector("#merge-button").addEventListener("click", async function(e) {
// Build request template
let model0 = mergeModelAField.value
let model1 = mergeModelBField.value
let request = { model0: model0, model1: model1 }
request["use_fp16"] = document.querySelector("#merge-fp").value == "fp16"
let iterations = document.querySelector("#merge-count").value >> 0
let start = parseFloat(document.querySelector("#merge-start").value)
let step = parseFloat(document.querySelector("#merge-step").value)
if (isTabActive(tabSettingsSingle)) {
start = parseFloat(singleMergeRatioField.value)
step = 0
iterations = 1
addLogMessage(`merge ratio = ${start}%`)
} else {
addLogMessage(`start = ${start}%`)
addLogMessage(`step = ${step}%`)
}
if (start + (iterations - 1) * step >= 100) {
addLogMessage("<i>Aborting: maximum ratio is &#8805; 100%</i>")
addLogMessage("Reduce the number of variations or the step size")
addLogSeparator()
document.querySelector("#merge-count").focus()
return
}
if (document.querySelector("#merge-filename").value == "") {
addLogMessage("<i>Aborting: No output file name specified</i>")
addLogSeparator()
document.querySelector("#merge-filename").focus()
return
}
// Disable merge button
e.target.disabled = true
e.target.classList.add("disabled")
let cursor = $("body").css("cursor")
let label = document.querySelector("#merge-button").innerHTML
$("body").css("cursor", "progress")
document.querySelector("#merge-button").innerHTML = "Merging models ..."
addLogMessage("Merging models")
addLogMessage("Model A: " + model0)
addLogMessage("Model B: " + model1)
// Batch main loop
for (let i = 0; i < iterations; i++) {
let alpha = (start + i * step) / 100
if (isTabActive(tabSettingsBatch)) {
switch (document.querySelector("#merge-interpolation").value) {
case "SmoothStep":
alpha = smoothstep(alpha)
break
case "SmootherStep":
alpha = smootherstep(alpha)
break
case "SmoothestStep":
alpha = smootheststep(alpha)
break
}
}
addLogMessage(`merging batch job ${i + 1}/${iterations}, alpha = ${alpha.toFixed(5)}...`)
request["out_path"] = document.querySelector("#merge-filename").value
request["out_path"] += "-" + alpha.toFixed(5) + "." + document.querySelector("#merge-format").value
addLogMessage(`&nbsp;&nbsp;filename: ${request["out_path"]}`)
// sdkit documentation: "ratio - the ratio of the second model. 1 means only the second model will be used."
request["ratio"] = 1-alpha
let res = await fetch("/model/merge", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(request),
})
const data = await res.json()
addLogMessage(JSON.stringify(data))
}
addLogMessage(
"<b>Done.</b> The models have been saved to your <tt>models/stable-diffusion</tt> folder."
)
addLogSeparator()
// Re-enable merge button
$("body").css("cursor", cursor)
document.querySelector("#merge-button").innerHTML = label
e.target.disabled = false
e.target.classList.remove("disabled")
// Update model list
stableDiffusionModelField.innerHTML = ""
vaeModelField.innerHTML = ""
hypernetworkModelField.innerHTML = ""
await getModels()
})
},
})
})()

View File

@ -1,52 +1,52 @@
;(function() {
(function () {
"use strict"
var styleSheet = document.createElement("style")
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)
`;
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()
}
// })
var observer = new MutationObserver(function (mutations) {
// mutations.forEach(function (mutation) {
if (editorModifierTagsList.childNodes.length > 0) {
ModifierToggle()
}
// })
})
observer.observe(editorModifierTagsList, {
childList: true,
childList: true
})
function ModifierToggle() {
let overlays = document.querySelector("#editor-inputs-tags-list").querySelectorAll(".modifier-card-overlay")
overlays.forEach((i) => {
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")
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].dataset.fullName
activeTags = activeTags.map((obj) => {
if (trimModifiers(obj.name) === trimModifiers(modifierName)) {
return { ...obj, inactive: obj.element.classList.contains("modifier-toggle-inactive") }
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
})
document.dispatchEvent(new Event("refreshImageModifiers"))
return obj;
});
document.dispatchEvent(new Event('refreshImageModifiers'))
}
})
}

View File

@ -1,53 +1,64 @@
;(function() {
(function() {
// Register selftests when loaded by jasmine.
if (typeof PLUGINS?.SELFTEST === "object") {
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`
)
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)
})
}
}
createTab({
id: "news",
icon: "fa-bolt",
label: "What's new",
css: `
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;
}
`,
onOpen: async ({ firstOpen }) => {
if (firstOpen) {
const loadMarkedScriptPromise = loadScript("/media/js/marked.min.js")
</style>
`)
let appConfig = await fetch("/get/app_config")
if (!appConfig.ok) {
console.error("[release-notes] Failed to get app_config.")
return
}
appConfig = await appConfig.json()
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"
const updateBranch = appConfig.update_branch || 'main'
let releaseNotes = await fetch(
`https://raw.githubusercontent.com/cmdr2/stable-diffusion-ui/${updateBranch}/CHANGES.md`
)
if (!releaseNotes.ok) {
console.error("[release-notes] Failed to get CHANGES.md.")
return
}
releaseNotes = await releaseNotes.text()
await loadMarkedScriptPromise
return marked.parse(releaseNotes)
}
},
let releaseNotes = await fetch(`https://raw.githubusercontent.com/cmdr2/stable-diffusion-ui/${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

@ -1,7 +1,6 @@
/* SD-UI Selftest Plugin.js
*/
;(function() {
"use strict"
(function() { "use strict"
const ID_PREFIX = "selftest-plugin"
const links = document.getElementById("community-links")
@ -11,18 +10,16 @@
}
// Add link to Jasmine SpecRunner
const pluginLink = document.createElement("li")
const pluginLink = document.createElement('li')
const options = {
stopSpecOnExpectationFailure: "true",
stopOnSpecFailure: "false",
random: "false",
hideDisabled: "false",
'stopSpecOnExpectationFailure': "true",
'stopOnSpecFailure': 'false',
'random': 'false',
'hideDisabled': 'false'
}
const optStr = Object.entries(options)
.map(([key, val]) => `${key}=${val}`)
.join("&")
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)
console.log('%s loaded!', ID_PREFIX)
})()

View File

@ -1,326 +0,0 @@
;(function(){
"use strict";
const PAPERSIZE = [
{id: "a3p", width: 297, height: 420, unit: "mm"},
{id: "a3l", width: 420, height: 297, unit: "mm"},
{id: "a4p", width: 210, height: 297, unit: "mm"},
{id: "a4l", width: 297, height: 210, unit: "mm"},
{id: "ll", width: 279, height: 216, unit: "mm"},
{id: "lp", width: 216, height: 279, unit: "mm"},
{id: "hd", width: 1920, height: 1080, unit: "pixels"},
{id: "4k", width: 3840, height: 2160, unit: "pixels"},
]
// ---- Register plugin
PLUGINS['IMAGE_INFO_BUTTONS'].push({
html: '<i class="fa-solid fa-table-cells-large"></i> Download tiled image',
on_click: onDownloadTiledImage,
filter: (req, img) => req.tiling != "none",
})
var thisImage
function onDownloadTiledImage(req, img) {
document.getElementById("download-tiled-image-dialog").showModal()
thisImage = new Image()
thisImage.src = img.src
thisImage.dataset["prompt"] = img.dataset["prompt"]
}
// ---- Add HTML
document.getElementById('container').lastElementChild.insertAdjacentHTML("afterend",
`<dialog id="download-tiled-image-dialog">
<h1>Download tiled image</h1>
<div class="download-tiled-image dtim-container">
<div class="download-tiled-image-top">
<div class="tab-container">
<span id="tab-image-tiles" class="tab active">
<span>Number of tiles</small></span>
</span>
<span id="tab-image-size" class="tab">
<span>Image dimensions</span>
</span>
</div>
<div>
<div id="tab-content-image-tiles" class="tab-content active">
<div class="tab-content-inner">
<label for="dtim1-width">Width:</label> <input id="dtim1-width" min="1" max="99" type="number" value="2">
<label for="dtim1-height">Height:</label> <input id="dtim1-height" min="1" max="99" type="number" value="2">
</div>
</div>
<div id="tab-content-image-size" class="tab-content">
<div class="tab-content-inner">
<div class="method-2-options">
<label for="dtim2-width">Width:</label> <input id="dtim2-width" size="3" value="1920">
<label for="dtim2-height">Height:</label> <input id="dtim2-height" size="3" value="1080">
<select id="dtim2-unit">
<option>pixels</option>
<option>mm</option>
<option>inches</option>
</select>
</div>
<div class="method-2-dpi">
<label for="dtim2-dpi">DPI:</label> <input id="dtim2-dpi" size="3" value="72">
</div>
<div class="method-2-paper">
<i>Some standard sizes:</i><br>
<button id="dtim2-a3p">A3 portrait</button><button id="dtim2-a3l">A3 landscape</button><br>
<button id="dtim2-a4p">A4 portrait</button><button id="dtim2-a4l">A4 landscape</button><br>
<button id="dtim2-lp">Letter portrait</button><button id="dtim2-ll">Letter landscape</button><br>
<button id="dtim2-hd">Full HD</button><button id="dtim2-4k">4K</button>
</div>
</div>
</div>
</div>
</div>
<div class="download-tiled-image-placement">
<div class="tab-container">
<span id="tab-image-placement" class="tab active">
<span>Tile placement</span>
</span>
</div>
<div>
<div id="tab-content-image-placement" class="tab-content active">
<div class="tab-content-inner">
<img id="dtim-1tl" class="active" src="data:image/png;base64,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" />
<img id="dtim-1tr" src="data:image/png;base64,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" /><br>
<img id="dtim-1bl" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADwAAAA3BAMAAACiFTSCAAAAMFBMVEUCAgKIhobRz89vMJ7s6uo9PDx4d3ewra0bHR1dXV19NrLa2Nj+/f29u7uWlJQuLi7ws27qAAAACXBIWXMAAAsTAAALEwEAmpwYAAABjElEQVQ4y7WUsU7DMBCG/5GVoUiMMLC4ZcmWrVXVDq7yDiyRuvIEjGyIpS/graMVKYMBqVUkhoYOUTc2Bp6BEd+5qdI2SasGLpE/KZc/d76LD/i6JrvFPfMKGfMGDOCTGUMwA/SYA8yL7iEM8w2yzH1AHderh9D1alGuXmmtBaVGchFgQe8J69bOHZnIyCHsYu8AUkZRZLpYSClf0dAm4zCchGOEOWkNW7ggAO0+2QcY/SUS5ozZ+6uqNVHHR9Q8q1Bnm9+B1B17HdGxbDe1zn7sA1V7DskucbfmObOFb0LThrZTsjlGzHcw0iXcU6woQxFv9i3rah5UdSxvSa/+EMn6hp6iroy9+s/YL2mSjlxRE1fUkX2wZNqiPjrDTwmfDnbsjNeH0q9Y9ZRN2diJjeliJ+ksj+2v3W5j3d2N+R5b4T/fcjuvqppMvqfsdbqaxF7VCc3Vho9eUd0pZi6q1cpThemwdYB9NVVK2cy1NsLYmaqNNmZgZ6sQa7VPmWuavQG9ZkkjV+u42QH8BWe+iD71TSARAAAAAElFTkSuQmCC" />
<img id="dtim-1br" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADwAAAA3BAMAAACiFTSCAAAAMFBMVEUCAgKIhobRz89vMJ7s6uo9PDx4d3ewra0bHR1dXV19NrLa2Nj+/f29u7uWlJQuLi7ws27qAAAACXBIWXMAAAsTAAALEwEAmpwYAAABkklEQVQ4y7VULU/DUBQ9EgtZSEimliWIt2Lmnq5rJ/gJkKXJDGquCGQdwewPzE2+PPeGWeaomgVF6tgPmOTe2zWkox8LC6dLT/ZuTs9957UXPQbuhTxcCF/jU/gGYBpgLH/7yIQNYuHXctniS9hhWlU+Wh03qVX1wwt1+eGKyoZXl8iYFbdmlFIj4N1au0THBUFgLTLrAvphSjcXUPk0RLNocodbpiiC3GcFT4C+7/shur4vvBX28SG0+o/UTHNqrZnXe3uVrW3oKtScuVeUvZYTK3lvyq21pBYRHihzxjlehC/3fHXqgQ5SArapAI9C63w1XR3GUuw75neuN6otV++78SOyza9Dv/lAj1Yf5T061XsQrjnUdSpMoYZ5qLSQvgG7JEmekQgOOWk9sV2l6kxqT4V3Nw1zb7IMyVsvBIcb6+w3lpfn1V+Jw1Awr5tMOq/XqzVdf1Mr9tZ7701JzZ+ia1ab352z6mc6cGO52hiapWPnlFM0U51ximbqUGu90KSOabTyyCWi5UyYO5/n6pPwDYr8fwvXgN7jAAAAAElFTkSuQmCC" /> <br>
<img id="dtim-1center" src="data:image/png;base64,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" />
<img id="dtim-4center" src="data:image/png;base64,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" /> <br>
</div>
</div>
</div>
</div>
<div class="dtim-ok">
<button class="primaryButton" id="dti-ok">Download</button>
</div>
<div class="dtim-newtab">
<button class="primaryButton" id="dti-newtab">Open in new tab</button>
</div>
<div class="dtim-cancel">
<button class="primaryButton" id="dti-cancel">Cancel</button>
</div>
</div>
</dialog>`)
let downloadTiledImageDialog = document.getElementById("download-tiled-image-dialog")
let dtim1_width = document.getElementById("dtim1-width")
let dtim1_height = document.getElementById("dtim1-height")
let dtim2_width = document.getElementById("dtim2-width")
let dtim2_height = document.getElementById("dtim2-height")
let dtim2_unit = document.getElementById("dtim2-unit")
let dtim2_dpi = document.getElementById("dtim2-dpi")
let tabTiledTilesOptions = document.getElementById("tab-image-tiles")
let tabTiledSizeOptions = document.getElementById("tab-image-size")
linkTabContents(tabTiledTilesOptions)
linkTabContents(tabTiledSizeOptions)
prettifyInputs(downloadTiledImageDialog)
// ---- Predefined image dimensions
PAPERSIZE.forEach( function(p) {
document.getElementById("dtim2-" + p.id).addEventListener("click", (e) => {
dtim2_unit.value = p.unit
dtim2_width.value = p.width
dtim2_height.value = p.height
})
})
// ---- Close popup
document.getElementById("dti-cancel").addEventListener("click", (e) => downloadTiledImageDialog.close())
downloadTiledImageDialog.addEventListener('click', function (event) {
var rect = downloadTiledImageDialog.getBoundingClientRect();
var isInDialog=(rect.top <= event.clientY && event.clientY <= rect.top + rect.height
&& rect.left <= event.clientX && event.clientX <= rect.left + rect.width);
if (!isInDialog) {
downloadTiledImageDialog.close();
}
});
// ---- Stylesheet
const styleSheet = document.createElement("style")
styleSheet.textContent = `
dialog {
background: var(--background-color2);
color: var(--text-color);
border-radius: 7px;
border: 1px solid var(--background-color3);
}
dialog::backdrop {
background: rgba(0, 0, 0, 0.5);
}
button[disabled] {
opacity: 0.5;
}
.method-2-dpi {
margin-top: 1em;
margin-bottom: 1em;
}
.method-2-paper button {
width: 10em;
padding: 4px;
margin: 4px;
}
.download-tiled-image .tab-content {
background: var(--background-color1);
border-radius: 3pt;
}
.dtim-container { display: grid;
grid-template-columns: auto auto;
grid-template-rows: auto auto;
gap: 1em 0px;
grid-auto-flow: row;
grid-template-areas:
"dtim-tab dtim-tab dtim-plc"
"dtim-ok dtim-newtab dtim-cancel";
}
.download-tiled-image-top {
justify-self: center;
grid-area: dtim-tab;
}
.download-tiled-image-placement {
justify-self: center;
grid-area: dtim-plc;
margin-left: 1em;
}
.dtim-ok {
justify-self: center;
align-self: start;
grid-area: dtim-ok;
}
.dtim-newtab {
justify-self: center;
align-self: start;
grid-area: dtim-newtab;
}
.dtim-cancel {
justify-self: center;
align-self: start;
grid-area: dtim-cancel;
}
#tab-content-image-placement img {
margin: 4px;
opacity: 0.3;
border: solid 2px var(--background-color1);
}
#tab-content-image-placement img:hover {
margin: 4px;
opacity: 1;
border: solid 2px var(--accent-color);
filter: brightness(2);
}
#tab-content-image-placement img.active {
margin: 4px;
opacity: 1;
border: solid 2px var(--background-color1);
}
`
document.head.appendChild(styleSheet)
// ---- Placement widget
function updatePlacementWidget(event) {
document.querySelector("#tab-content-image-placement img.active").classList.remove("active")
event.target.classList.add("active")
}
document.querySelectorAll("#tab-content-image-placement img").forEach(
(i) => i.addEventListener("click", updatePlacementWidget)
)
function getPlacement() {
return document.querySelector("#tab-content-image-placement img.active").id.substr(5)
}
// ---- Make the image
function downloadTiledImage(image, width, height, offsetX=0, offsetY=0, new_tab=false) {
const canvas = document.createElement('canvas')
canvas.width = width
canvas.height = height
const context = canvas.getContext('2d')
const w = image.width
const h = image.height
for (var x = offsetX; x < width; x += w) {
for (var y = offsetY; y < height; y += h) {
context.drawImage(image, x, y, w, h)
}
}
if (new_tab) {
var newTab = window.open("")
newTab.document.write(`<html><head><title>${width}×${height}, "${image.dataset["prompt"]}"</title></head><body><img src="${canvas.toDataURL()}"></body></html>`)
} else {
const link = document.createElement('a')
link.href = canvas.toDataURL()
link.download = image.dataset["prompt"].replace(/[^a-zA-Z0-9]+/g, "-").substr(0,22)+crypto.randomUUID()+".png"
link.click()
}
}
function onDownloadTiledImageClick(e, newtab=false) {
var width, height, offsetX, offsetY
if (isTabActive(tabTiledTilesOptions)) {
width = thisImage.width * dtim1_width.value
height = thisImage.height * dtim1_height.value
} else {
if ( dtim2_unit.value == "pixels" ) {
width = dtim2_width.value
height= dtim2_height.value
} else if ( dtim2_unit.value == "mm" ) {
width = Math.floor( dtim2_width.value * dtim2_dpi.value / 25.4 )
height = Math.floor( dtim2_height.value * dtim2_dpi.value / 25.4 )
} else { // inch
width = Math.floor( dtim2_width.value * dtim2_dpi.value )
height = Math.floor( dtim2_height.value * dtim2_dpi.value )
}
}
var placement = getPlacement()
if (placement == "1tl") {
offsetX = 0
offsetY = 0
} else if (placement == "1tr") {
offsetX = width - thisImage.width * Math.ceil( width / thisImage.width )
offsetY = 0
} else if (placement == "1bl") {
offsetX = 0
offsetY = height - thisImage.height * Math.ceil( height / thisImage.height )
} else if (placement == "1br") {
offsetX = width - thisImage.width * Math.ceil( width / thisImage.width )
offsetY = height - thisImage.height * Math.ceil( height / thisImage.height )
} else if (placement == "4center") {
offsetX = width/2 - thisImage.width * Math.ceil( width/2 / thisImage.width )
offsetY = height/2 - thisImage.height * Math.ceil( height/2 / thisImage.height )
} else if (placement == "1center") {
offsetX = width/2 - thisImage.width/2 - thisImage.width * Math.ceil( (width/2 - thisImage.width/2) / thisImage.width )
offsetY = height/2 - thisImage.height/2 - thisImage.height * Math.ceil( (height/2 - thisImage.height/2) / thisImage.height )
}
downloadTiledImage(thisImage, width, height, offsetX, offsetY, newtab)
downloadTiledImageDialog.close()
}
document.getElementById("dti-ok").addEventListener("click", onDownloadTiledImageClick)
document.getElementById("dti-newtab").addEventListener("click", (e) => onDownloadTiledImageClick(e,true))
})()