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installer.tar
dist
.idea/*
node_modules/*

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*.min.*
*.py
*.json
*.html
/*
!/ui
/ui/easydiffusion
!/ui/plugins
!/ui/media

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{
"printWidth": 120,
"tabWidth": 4,
"semi": false,
"arrowParens": "always",
"trailingComma": "es5"
}

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jquery-confirm
==============
https://craftpip.github.io/jquery-confirm/
jquery-confirm is licensed under the MIT license:
The MIT License (MIT)
Copyright (c) 2019 Boniface Pereira
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
jszip
=====
https://stuk.github.io/jszip/
JSZip is dual licensed. At your choice you may use it under the MIT license *or* the GPLv3
license.
The MIT License
===============
Copyright (c) 2009-2016 Stuart Knightley, David Duponchel, Franz Buchinger, António Afonso
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.
GPL version 3
=============
GNU GENERAL PUBLIC LICENSE
Version 3, 29 June 2007
Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
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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

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@ -1,200 +0,0 @@
# What's new?
## 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.
- **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/easydiffusion/easydiffusion/wiki/Model-Merging . Thanks @JeLuf.
- **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/easydiffusion/easydiffusion/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.
- **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
* 2.5.46 - 27 Jul 2023 - (beta-only) Full support for SD-XL models (base and refiner)!
* 2.5.45 - 24 Jul 2023 - (beta-only) Hide the samplers that won't be supported in the new diffusers version.
* 2.5.45 - 22 Jul 2023 - (beta-only) Fix the recently-broken inpainting models.
* 2.5.45 - 16 Jul 2023 - (beta-only) Fix the image quality of LoRAs, which had degraded in v2.5.44.
* 2.5.44 - 15 Jul 2023 - (beta-only) Support for multiple LoRA files.
* 2.5.43 - 9 Jul 2023 - (beta-only) Support for loading Textual Inversion embeddings. You can find the option in the Image Settings panel. Thanks @JeLuf.
* 2.5.43 - 9 Jul 2023 - Improve the startup time of the UI.
* 2.5.42 - 4 Jul 2023 - Keyboard shortcuts for the Image Editor. Thanks @JeLuf.
* 2.5.42 - 28 Jun 2023 - Allow dropping images from folders to use as an Initial Image.
* 2.5.42 - 26 Jun 2023 - Show a popup for Image Modifiers, allowing a larger screen space, better UX on mobile screens, and more room for us to develop and improve the Image Modifiers panel. Thanks @Hakorr.
* 2.5.42 - 26 Jun 2023 - (beta-only) Show a welcome screen for users of the diffusers beta, with instructions on how to use the new prompt syntax, and known bugs. Thanks @JeLuf.
* 2.5.42 - 26 Jun 2023 - Use YAML files for config. You can now edit the `config.yaml` file (using a text editor, like Notepad). This file is present inside the Easy Diffusion folder, and is easier to read and edit (for humans) than JSON. Thanks @JeLuf.
* 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/easydiffusion/easydiffusion/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/easydiffusion/easydiffusion/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.
* 2.5.8 - 17 Jan 2023 - Fix a bug where 'Low' VRAM usage would consume a LOT of VRAM (on higher-end GPUs). Also fixed a bug that caused out-of-memory errors on SD 2.1-768 models, on 'high' VRAM usage setting.
* 2.5.7 - 16 Jan 2023 - Fix a bug where VAE files ending with .vae.pt weren't getting displayed. Thanks Madrang, rbertus2000 and JeLuf.
* 2.5.6 - 10 Jan 2023 - `Fill` tool for the Image Editor, to allow filling areas with color (or the entire image). And some bug fixes to the Image Editor. Thanks @mdiller.
* 2.5.6 - 10 Jan 2023 - Find Stable Diffusion models in sub-folders inside `models/stable-diffusion`. This allows you to organize your models into sub-folders, instead of keeping them all in a single folder. Thanks @JeLuf.
* 2.5.5 - 9 Jan 2023 - Lots of bug fixes. Thanks @patriceac and @JeLuf.
* 2.5.4 - 29 Dec 2022 - Press Esc key on the keyboard to close the Image Editor. Thanks @patriceac.
* 2.5.4 - 29 Dec 2022 - Lots of bug fixes in the UI. Thanks @patriceac.
* 2.5.4 - 28 Dec 2022 - Full support for running tasks in parallel on multiple GPUs. Warning: 'Euler Ancestral', 'DPM2 Ancestral' and 'DPM++ 2s Ancestral' may produce slight variations in the image (if run in parallel), so we recommend using the other samplers.
* 2.5.3 - 27 Dec 2022 - Fix broken drag-and-drop for text metadata files (as well as paste in clipboard).
* 2.5.3 - 27 Dec 2022 - Allow upscaling by 2x as well as 4x.
* 2.5.3 - 27 Dec 2022 - Fix broken renders on a second GPU.
* 2.5.3 - 26 Dec 2022 - Add a `Remove` button on each image. Thanks @JeLuf.
* 2.5.2 - 26 Dec 2022 - Fix broken inpainting if using non-square target images.
* 2.5.2 - 26 Dec 2022 - Fix a bug where an incorrect model config would get used for some SD 2.1 models.
* 2.5.2 - 26 Dec 2022 - Slight performance and memory improvement while rendering using SD 2.1 models.
* 2.5.1 - 25 Dec 2022 - Allow custom config yaml files for models. You can put a config file (`.yaml`) next to the model file, with the same name as the model. For e.g. if you put `robo-diffusion-v2-base.yaml` next to `robo-diffusion-v2-base.ckpt`, it'll automatically use that config file.
* 2.5.1 - 25 Dec 2022 - Fix broken rendering for SD 2.1-768 models. Fix broken rendering SD 2.0 safetensor models.
* 2.5.0 - 25 Dec 2022 - Major new release! Nearly twice as fast, Full support for SD 2.1 (including low GPU RAM optimizations), 6 new samplers, Model Merging, Fast loading/unloading of VAEs, Database of known models, Color correction for img2img, Three GPU Memory Usage Settings, Save metadata as JSON, Major rewrite of the code, Name change.
## v2.4
### Major Changes
- **Allow reordering the task queue** (by dragging and dropping tasks). Thanks @madrang
- **Automatic scanning for malicious model files** - using `picklescan`, and support for `safetensor` model format. Thanks @JeLuf
- **Image Editor** - for drawing simple images for guiding the AI. Thanks @mdiller
- **Use pre-trained hypernetworks** - for improving the quality of images. Thanks @C0bra5
- **Support for custom VAE models**. You can place your VAE files in the `models/vae` folder, and refresh the browser page to use them. More info: https://github.com/easydiffusion/easydiffusion/wiki/VAE-Variational-Auto-Encoder
- **Experimental support for multiple GPUs!** It should work automatically. Just open one browser tab per GPU, and spread your tasks across your GPUs. For e.g. open our UI in two browser tabs if you have two GPUs. You can customize which GPUs it should use in the "Settings" tab, otherwise let it automatically pick the best GPUs. Thanks @madrang . More info: https://github.com/easydiffusion/easydiffusion/wiki/Run-on-Multiple-GPUs
- **Cleaner UI design** - Show settings and help in new tabs, instead of dropdown popups (which were buggy). Thanks @mdiller
- **Progress bar.** Thanks @mdiller
- **Custom Image Modifiers** - You can now save your custom image modifiers! Your saved modifiers can include special characters like `{}, (), [], |`
- Drag and Drop **text files generated from previously saved images**, and copy settings to clipboard. Thanks @madrang
- Paste settings from clipboard. Thanks @JeLuf
- Bug fixes to reduce the chances of tasks crashing during long multi-hour runs (chrome can put long-running background tabs to sleep). Thanks @JeLuf and @madrang
- **Improved documentation.** Thanks @JeLuf and @jsuelwald
- Improved the codebase for dealing with system settings and UI settings. Thanks @mdiller
- Help instructions next to some setttings, and in the tab
- Show system info in the settings tab
- Keyboard shortcut: Ctrl+Enter to start a task
- Configuration to prevent the browser from opening on startup
- Lots of minor bug fixes
- A `What's New?` tab in the UI
- Ask for a confimation before clearing the results pane or stopping a render task. The dialog can be skipped by holding down the shift key while clicking on the button.
- Show the network addresses of the server in the systems setting dialog
- Support loading models in the safetensor format, for improved safety
### Detailed changelog
* 2.4.24 - 9 Jan 2022 - Urgent fix for failures on old/long-term-support browsers. Thanks @JeLuf.
* 2.4.23/22 - 29 Dec 2022 - Allow rolling back from the upcoming v2.5 change (in beta).
* 2.4.21 - 23 Dec 2022 - Speed up image creation, by removing a delay (regression) of 4-5 seconds between clicking the `Make Image` button and calling the server.
* 2.4.20 - 22 Dec 2022 - `Pause All` button to pause all the pending tasks. Thanks @JeLuf
* 2.4.20 - 22 Dec 2022 - `Undo`/`Redo` buttons in the image editor. Thanks @JeLuf
* 2.4.20 - 22 Dec 2022 - Drag handle to reorder the tasks. This fixed a bug where the metadata was no longer selectable (for copying). Thanks @JeLuf
* 2.4.19 - 17 Dec 2022 - Add Undo/Redo buttons in the Image Editor. Thanks @JeLuf
* 2.4.19 - 10 Dec 2022 - Show init img in task list
* 2.4.19 - 7 Dec 2022 - Use pre-trained hypernetworks while generating images. Thanks @C0bra5
* 2.4.19 - 6 Dec 2022 - Allow processing new tasks first. Thanks @madrang
* 2.4.19 - 6 Dec 2022 - Allow reordering the task queue (by dragging tasks). Thanks @madrang
* 2.4.19 - 6 Dec 2022 - Re-organize the code, to make it easier to write user plugins. Thanks @madrang
* 2.4.18 - 5 Dec 2022 - Make JPEG Output quality user controllable. Thanks @JeLuf
* 2.4.18 - 5 Dec 2022 - Support loading models in the safetensor format, for improved safety. Thanks @JeLuf
* 2.4.18 - 1 Dec 2022 - Image Editor, for drawing simple images for guiding the AI. Thanks @mdiller
* 2.4.18 - 1 Dec 2022 - Disable an image modifier temporarily by right-clicking it. Thanks @patriceac
* 2.4.17 - 30 Nov 2022 - Scroll to generated image. Thanks @patriceac
* 2.4.17 - 30 Nov 2022 - Show the network addresses of the server in the systems setting dialog. Thanks @JeLuf
* 2.4.17 - 30 Nov 2022 - Fix a bug where GFPGAN wouldn't work properly when multiple GPUs tried to run it at the same time. Thanks @madrang
* 2.4.17 - 30 Nov 2022 - Confirm before stopping or clearing all the tasks. Thanks @JeLuf
* 2.4.16 - 29 Nov 2022 - Bug fixes for SD 2.0 - remove the need for patching, default to SD 1.4 model if trying to load an SD2 model in SD1.4.
* 2.4.15 - 25 Nov 2022 - Experimental support for SD 2.0. Uses lots of memory, not optimized, probably GPU-only.
* 2.4.14 - 22 Nov 2022 - Change the backend to a custom fork of Stable Diffusion
* 2.4.13 - 21 Nov 2022 - Change the modifier weight via mouse wheel, drag to reorder selected modifiers, and some more modifier-related fixes. Thanks @patriceac
* 2.4.12 - 21 Nov 2022 - Another fix for improving how long images take to generate. Reduces the time taken for an enqueued task to start processing.
* 2.4.11 - 21 Nov 2022 - Installer improvements: avoid crashing if the username contains a space or special characters, allow moving/renaming the folder after installation on Windows, whitespace fix on git apply
* 2.4.11 - 21 Nov 2022 - Validate inputs before submitting the Image request
* 2.4.11 - 19 Nov 2022 - New system settings to manage the network config (port number and whether to only listen on localhost)
* 2.4.11 - 19 Nov 2022 - Address a regression in how long images take to generate. Use the previous code for moving a model to CPU. This improves things by a second or two per image, but we still have a regression (investigating).
* 2.4.10 - 18 Nov 2022 - Textarea for negative prompts. Thanks @JeLuf
* 2.4.10 - 18 Nov 2022 - Improved design for Settings, and rounded toggle buttons instead of checkboxes for a more modern look. Thanks @mdiller
* 2.4.9 - 18 Nov 2022 - Add Picklescan - a scanner for malicious model files. If it finds a malicious file, it will halt the web application and alert the user. Thanks @JeLuf
* 2.4.8 - 18 Nov 2022 - A `Use these settings` button to use the settings from a previously generated image task. Thanks @patriceac
* 2.4.7 - 18 Nov 2022 - Don't crash if a VAE file fails to load
* 2.4.7 - 17 Nov 2022 - Fix a bug where Face Correction (GFPGAN) would fail on cuda:N (i.e. GPUs other than cuda:0), as well as fail on CPU if the system had an incompatible GPU.
* 2.4.6 - 16 Nov 2022 - Fix a regression in VRAM usage during startup, which caused 'Out of Memory' errors when starting on GPUs with 4gb (or less) VRAM
* 2.4.5 - 16 Nov 2022 - Add checkbox for "Open browser on startup".
* 2.4.5 - 16 Nov 2022 - Add a directory for core plugins that ship with Stable Diffusion UI by default.
* 2.4.5 - 16 Nov 2022 - Add a "What's New?" tab as a core plugin, which fetches the contents of CHANGES.md from the app's release branch.

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Hi there, these instructions are meant for the developers of this project.
If you only want to use the Stable Diffusion UI, you've downloaded the wrong file. In that case, please download and follow the instructions at https://github.com/easydiffusion/easydiffusion#installation
If you only want to use the Stable Diffusion UI, you've downloaded the wrong file. In that case, please download and follow the instructions at https://github.com/cmdr2/stable-diffusion-ui#installation
Thanks
# For developers:
If you would like to contribute to this project, there is a discord for discussion:
If you would like to contribute to this project, there is a discord for dicussion:
[![Discord Server](https://badgen.net/badge/icon/discord?icon=discord&label)](https://discord.com/invite/u9yhsFmEkB)
## Development environment for UI (frontend and server) changes
This is in-flux, but one way to get a development environment running for editing the UI of this project is:
(swap `.sh` or `.bat` in instructions depending on your environment, and be sure to adjust any paths to match where you're working)
1) Install the project to a new location using the [usual installation process](https://github.com/easydiffusion/easydiffusion#installation), e.g. to `/projects/stable-diffusion-ui-archive`
2) Start the newly installed project, and check that you can view and generate images on `localhost:9000`
3) Next, please clone the project repository using `git clone` (e.g. to `/projects/stable-diffusion-ui-repo`)
4) Close the server (started in step 2), and edit `/projects/stable-diffusion-ui-archive/scripts/on_env_start.sh` (or `on_env_start.bat`)
5) Comment out the lines near the bottom that copies the `files/ui` folder, e.g:
1) `git clone` the repository, e.g. to `/projects/stable-diffusion-ui-repo`
2) Download the pre-built end user archive from the link on github, and extract it, e.g. to `/projects/stable-diffusion-ui-archive`
3) `cd /projects/stable-diffusion-ui-archive` and run the script to set up and start the project, e.g. `start.sh`
4) Check you can view and generate images on `localhost:9000`
5) Close the server, and edit `/projects/stable-diffusion-ui-archive/scripts/on_env_start.sh`
6) Comment out the lines near the bottom that copies the `files/ui` folder, e.g:
for `.sh`
```
@ -32,18 +33,23 @@ REM @xcopy sd-ui-files\ui ui /s /i /Y
REM @copy sd-ui-files\scripts\on_sd_start.bat scripts\ /Y
REM @copy "sd-ui-files\scripts\Start Stable Diffusion UI.cmd" . /Y
```
6) Next, comment out the line at the top of `/projects/stable-diffusion-ui-archive/scripts/on_sd_start.sh` (or `on_sd_start.bat`) that copies `on_env_start`. For e.g. `@rem @copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y`
7) Comment out the line at the top of `/projects/stable-diffusion-ui-archive/scripts/on_sd_start.sh` that copies `on_env_start`. For e.g. `@copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y`
8) Delete the current `ui` folder at `/projects/stable-diffusion-ui-archive/ui`
9) Now make a symlink between the repository clone (where you will be making changes) and this archive (where you will be running stable diffusion):
`ln -s /projects/stable-diffusion-ui-repo/ui /projects/stable-diffusion-ui-archive/ui`
or for Windows
`mklink /J \projects\stable-diffusion-ui-archive\ui \projects\stable-diffusion-ui-repo\ui` (link name first, source repo dir second)
9) Run the project again (like in step 2) and ensure you can still use the UI.
`mklink /D \projects\stable-diffusion-ui-archive\ui \projects\stable-diffusion-ui-repo\ui` (link name first, source repo dir second)
9) Run the archive again `start.sh` and ensure you can still use the UI.
10) Congrats, now any changes you make in your repo `ui` folder are linked to this running archive of the app and can be previewed in the browser.
11) Please update CHANGES.md in your pull requests.
Check the `ui/frontend/build/README.md` for instructions on running and building the React code.
## Development environment for Installer changes
Build the Windows installer using Windows, and the Linux installer using Linux. Don't mix the two, and don't use WSL. An Ubuntu VM is fine for building the Linux installer on a Windows host.
1. Run `build.bat` or `./build.sh` depending on whether you're in Windows or Linux.
2. Make a new GitHub release and upload the Windows and Linux installer builds created inside the `dist` folder.
1. Install Miniconda 3 or Anaconda.
2. Install `conda install -c conda-forge -y conda-pack`
3. Open the Anaconda Prompt. Do not use WSL if you're building for Windows.
4. Run `build.bat` or `./build.sh` depending on whether you're in Windows or Linux.
5. Compress the `stable-diffusion-ui` folder created inside the `dist` folder. Make a `zip` for Windows, and `tar.xz` for Linux (smaller files, and Linux users already have tar).
6. Make a new GitHub release and upload the Windows and Linux installer builds.

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@ -1,6 +1,6 @@
Congrats on downloading Stable Diffusion UI, version 2!
If you haven't downloaded Stable Diffusion UI yet, please download from https://github.com/easydiffusion/easydiffusion#installation
If you haven't downloaded Stable Diffusion UI yet, please download from https://github.com/cmdr2/stable-diffusion-ui#installation
After downloading, to install please follow these instructions:
@ -16,9 +16,9 @@ To start the UI in the future, please run the same command mentioned above.
If you have any problems, please:
1. Try the troubleshooting steps at https://github.com/easydiffusion/easydiffusion/wiki/Troubleshooting
1. Try the troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting
2. Or, seek help from the community at https://discord.com/invite/u9yhsFmEkB
3. Or, file an issue at https://github.com/easydiffusion/easydiffusion/issues
3. Or, file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues
Thanks
cmdr2 (and contributors to the project)

1
NSIS/.gitignore vendored
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*.exe

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Scripts to be used with the Nullsoft Scriptable Installation System

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!define EXISTING_INSTALLATION_DIR "D:\path\to\installed\easy-diffusion"

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@ -1,305 +0,0 @@
; Script generated by the HM NIS Edit Script Wizard.
Target amd64-unicode
Unicode True
SetCompressor /FINAL lzma
RequestExecutionLevel user
!AddPluginDir /amd64-unicode "."
; HM NIS Edit Wizard helper defines
!define PRODUCT_NAME "Easy Diffusion"
!define PRODUCT_VERSION "2.5"
!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"
; MUI 1.67 compatible ------
!include "MUI.nsh"
!include "LogicLib.nsh"
!include "nsDialogs.nsh"
!include "nsisconf.nsh"
Var Dialog
Var Label
Var Button
Var InstDirLen
Var LongPathsEnabled
Var AccountType
;---------------------------------------------------------------------------------------------------------
; This function returns the number of spaces in a string.
; The string is passed on the stack (using Push $STRING)
; The result is also returned on the stack and can be consumed with Pop $var
; https://nsis.sourceforge.io/Check_for_spaces_in_a_directory_path
Function CheckForSpaces
Exch $R0
Push $R1
Push $R2
Push $R3
StrCpy $R1 -1
StrCpy $R3 $R0
StrCpy $R0 0
loop:
StrCpy $R2 $R3 1 $R1
IntOp $R1 $R1 - 1
StrCmp $R2 "" done
StrCmp $R2 " " 0 loop
IntOp $R0 $R0 + 1
Goto loop
done:
Pop $R3
Pop $R2
Pop $R1
Exch $R0
FunctionEnd
;---------------------------------------------------------------------------------------------------------
; The function DirectoryLeave is called after the user chose the installation directory.
; If it calls "abort", the user is sent back to choose a different directory.
Function DirectoryLeave
; check whether the installation directory path is longer than 30 characters.
; If yes, we suggest to the user to enable long filename support
;----------------------------------------------------------------------------
StrLen $InstDirLen "$INSTDIR"
; Check whether the registry key that allows for >260 characters in a path name is set
ReadRegStr $LongPathsEnabled HKLM "SYSTEM\CurrentControlSet\Control\FileSystem" "LongPathsEnabled"
${If} $InstDirLen > 30
${AndIf} $LongPathsEnabled == "0"
; Check whether we're in the Admin group
UserInfo::GetAccountType
Pop $AccountType
${If} $AccountType == "Admin"
${AndIf} ${Cmd} `MessageBox MB_YESNO|MB_ICONQUESTION 'The path name is too long. $\n$\nYou can either enable long file name support in Windows,$\nor you can go back and choose a different path.$\n$\nFor details see: shorturl.at/auBD1$\n$\nEnable long path name support in Windows?' IDYES`
; Enable long path names
WriteRegDWORD HKLM "SYSTEM\CurrentControlSet\Control\FileSystem" "LongPathsEnabled" 1
${Else}
MessageBox MB_OK|MB_ICONEXCLAMATION "Installation path name too long. The installation path must not have more than 30 characters."
abort
${EndIf}
${EndIf}
; Check for spaces in the installation directory path.
; ----------------------------------------------------
; $R0 = CheckForSpaces( $INSTDIR )
Push $INSTDIR # Input string (install path).
Call CheckForSpaces
Pop $R0 # The function returns the number of spaces found in the input string.
; Check if any spaces exist in $INSTDIR.
${If} $R0 != 0
; Plural if more than 1 space in $INSTDIR.
; If $R0 == 1: $R1 = ""; else: $R1 = "s"
StrCmp $R0 1 0 +3
StrCpy $R1 ""
Goto +2
StrCpy $R1 "s"
; Show message box then take the user back to the Directory page.
MessageBox MB_OK|MB_ICONEXCLAMATION "Error: The Installaton directory \
has $R0 space character$R1.$\nPlease choose an installation directory without space characters."
Abort
${EndIf}
; Check for NTFS filesystem. Installations on FAT fail.
; -----------------------------------------------------
StrCpy $5 $INSTDIR 3
System::Call 'Kernel32::GetVolumeInformation(t "$5",t,i ${NSIS_MAX_STRLEN},*i,*i,*i,t.r1,i ${NSIS_MAX_STRLEN})i.r0'
${If} $0 <> 0
${AndIf} $1 != "NTFS"
MessageBox mb_ok "$5 has filesystem type '$1'.$\nOnly NTFS filesystems are supported.$\nPlease choose a different drive."
Abort
${EndIf}
FunctionEnd
;---------------------------------------------------------------------------------------------------------
; Open the MS download page in a browser and enable the [Next] button
Function MSMediaFeaturepack
ExecShell "open" "https://www.microsoft.com/en-us/software-download/mediafeaturepack"
GetDlgItem $0 $HWNDPARENT 1
EnableWindow $0 1
FunctionEnd
;---------------------------------------------------------------------------------------------------------
; Install the MS Media Feature Pack, if it is missing (e.g. on Windows 10 N)
Function MediaPackDialog
!insertmacro MUI_HEADER_TEXT "Windows Media Feature Pack" "Required software module is missing"
; Skip this dialog if mf.dll is installed
${If} ${FileExists} "$WINDIR\system32\mf.dll"
Abort
${EndIf}
nsDialogs::Create 1018
Pop $Dialog
${If} $Dialog == error
Abort
${EndIf}
${NSD_CreateLabel} 0 0 100% 48u "The Windows Media Feature Pack is missing on this computer. It is required for Easy Diffusion.$\nYou can continue the installation after installing the Windows Media Feature Pack."
Pop $Label
${NSD_CreateButton} 10% 49u 80% 12u "Download Meda Feature Pack from Microsoft"
Pop $Button
GetFunctionAddress $0 MSMediaFeaturePack
nsDialogs::OnClick $Button $0
GetDlgItem $0 $HWNDPARENT 1
EnableWindow $0 0
nsDialogs::Show
FunctionEnd
Function FinishPageAction
CreateShortCut "$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_WELCOMEFINISHPAGE_BITMAP "cyborg_flower_girl.bmp"
; Welcome page
!define MUI_WELCOMEPAGE_TEXT "This installer will guide you through the installation of Easy Diffusion.$\n$\n\
Click Next to continue."
!insertmacro MUI_PAGE_WELCOME
Page custom MediaPackDialog
; License page
!insertmacro MUI_PAGE_LICENSE "..\LICENSE"
!insertmacro MUI_PAGE_LICENSE "..\CreativeML Open RAIL-M License"
; Directory page
!define MUI_PAGE_CUSTOMFUNCTION_LEAVE "DirectoryLeave"
!insertmacro MUI_PAGE_DIRECTORY
; Instfiles page
!insertmacro MUI_PAGE_INSTFILES
; Finish page
!define MUI_FINISHPAGE_SHOWREADME ""
!define MUI_FINISHPAGE_SHOWREADME_NOTCHECKED
!define MUI_FINISHPAGE_SHOWREADME_TEXT "Create Desktop Shortcut"
!define MUI_FINISHPAGE_SHOWREADME_FUNCTION FinishPageAction
!define MUI_FINISHPAGE_RUN "$INSTDIR\Start Stable Diffusion UI.cmd"
!insertmacro MUI_PAGE_FINISH
; Language files
!insertmacro MUI_LANGUAGE "English"
;---------------------------------------------------------------------------------------------------------
; MUI end
;---------------------------------------------------------------------------------------------------------
Name "${PRODUCT_NAME} ${PRODUCT_VERSION}"
OutFile "Install Easy Diffusion.exe"
InstallDir "C:\EasyDiffusion\"
InstallDirRegKey HKLM "${PRODUCT_DIR_REGKEY}" ""
ShowInstDetails show
;---------------------------------------------------------------------------------------------------------
; List of files to be installed
Section "MainSection" SEC01
SetOutPath "$INSTDIR"
File "..\CreativeML Open RAIL-M License"
File "..\How to install and run.txt"
File "..\LICENSE"
File "..\scripts\Start Stable Diffusion UI.cmd"
File /r "${EXISTING_INSTALLATION_DIR}\installer_files"
File /r "${EXISTING_INSTALLATION_DIR}\profile"
File /r "${EXISTING_INSTALLATION_DIR}\sd-ui-files"
SetOutPath "$INSTDIR\installer_files"
File "cyborg_flower_girl.ico"
SetOutPath "$INSTDIR\scripts"
File "${EXISTING_INSTALLATION_DIR}\scripts\install_status.txt"
File "..\scripts\on_env_start.bat"
File "C:\windows\system32\curl.exe"
CreateDirectory "$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
SectionEnd
;---------------------------------------------------------------------------------------------------------
; Our installer only needs 25 KB, but once it has run, we need 25 GB
; So we need to overwrite the automatically detected space requirements.
; https://nsis.sourceforge.io/Docs/Chapter4.html#4.9.13.7
; The example in section 4.9.13.7 seems to be wrong: the number
; needs to be provided in Kilobytes.
Function .onInit
; Set required size of section 'SEC01' to 25 Gigabytes
SectionSetSize ${SEC01} 26214400
; Check system meory size. We need at least 8GB
; ----------------------------------------------------
; allocate a few bytes of memory
System::Alloc 64
Pop $1
; Retrieve HW info from the Windows Kernel
System::Call "*$1(i64)"
System::Call "Kernel32::GlobalMemoryStatusEx(i r1)"
; unpack the data into $R2 - $R10
System::Call "*$1(i.r2, i.r3, l.r4, l.r5, l.r6, l.r7, l.r8, l.r9, l.r10)"
# free up the memory
System::Free $1
; Result mapping:
; "Structure size: $2 bytes"
; "Memory load: $3%"
; "Total physical memory: $4 bytes"
; "Free physical memory: $5 bytes"
; "Total page file: $6 bytes"
; "Free page file: $7 bytes"
; "Total virtual: $8 bytes"
; "Free virtual: $9 bytes"
; Mem size in MB
System::Int64Op $4 / 1048576
Pop $4
${If} $4 < "8000"
MessageBox MB_OK|MB_ICONEXCLAMATION "Warning!$\n$\nYour system has less than 8GB of memory (RAM).$\n$\n\
You can still try to install Easy Diffusion,$\nbut it might have problems to start, or run$\nvery slowly."
${EndIf}
FunctionEnd
;Section -Post
; WriteRegStr HKLM "${PRODUCT_DIR_REGKEY}" "" "$INSTDIR\installer.exe"
;SectionEnd

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@ -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/easydiffusion/easydiffusion) 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

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@ -3,6 +3,6 @@ Hi there,
What you have downloaded is meant for the developers of this project, not for users.
If you only want to use the Stable Diffusion UI, you've downloaded the wrong file.
Please download and follow the instructions at https://github.com/easydiffusion/easydiffusion#installation
Please download and follow the instructions at https://github.com/cmdr2/stable-diffusion-ui#installation
Thanks

199
README.md
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@ -1,145 +1,104 @@
# Easy Diffusion 2.5
### The easiest way to install and use [Stable Diffusion](https://github.com/CompVis/stable-diffusion) on your computer.
Does not require technical knowledge, does not require pre-installed software. 1-click install, powerful features, friendly community.
[Installation guide](#installation) | [Troubleshooting guide](https://github.com/easydiffusion/easydiffusion/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>
![t2i](https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/assets/stable-samples/txt2img/768/merged-0006.png)
# Installation
Click the download button for your operating system:
# Stable Diffusion UI v2
### A simple 1-click way to install and use [Stable Diffusion](https://github.com/CompVis/stable-diffusion) on your own computer. No dependencies or technical knowledge required.
<p float="left">
<a href="https://github.com/easydiffusion/easydiffusion/releases/download/v2.5.24/Easy-Diffusion-Windows.exe"><img src="https://github.com/easydiffusion/easydiffusion/raw/main/media/download-win.png" width="200" /></a>
<a href="https://github.com/easydiffusion/easydiffusion/releases/download/v2.5.24/Easy-Diffusion-Linux.zip"><img src="https://github.com/easydiffusion/easydiffusion/raw/main/media/download-linux.png" width="200" /></a>
<a href="https://github.com/easydiffusion/easydiffusion/releases/download/v2.5.24/Easy-Diffusion-Mac.zip"><img src="https://github.com/easydiffusion/easydiffusion/raw/main/media/download-mac.png" width="200" /></a>
<a href="#installation"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/develop/media/download-win.png" width="200" /></a>
<a href="#installation"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/develop/media/download-linux.png" width="200" /></a>
</p>
**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.
[![Discord Server](https://img.shields.io/discord/1014774730907209781?label=Discord)](https://discord.com/invite/u9yhsFmEkB) (for support, and development discussion) | [Troubleshooting guide for common problems](Troubleshooting.md)
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.
️‍🔥🎉 **New!** Live Preview, More Samplers, In-Painting, Face Correction (GFPGAN) and Upscaling (RealESRGAN) have been added!
## 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).
This distribution currently uses Stable Diffusion 1.4. Once the model for 1.5 becomes publicly available, the model in this distribution will be updated.
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.
----
# Easy for new users, powerful features for advanced users
## Features:
### User experience
- **Hassle-free installation**: Does not require technical knowledge, does not require pre-installed software. Just download and run!
- **Clutter-free UI**: A friendly and simple UI, while providing a lot of powerful features.
- **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.
# Features in the new v2 Version:
- **No Dependencies or Technical Knowledge Required**: 1-click install for Windows 10/11 and Linux. *No dependencies*, no need for WSL or Docker or Conda or technical setup. Just download and run!
- **Face Correction (GFPGAN) and Upscaling (RealESRGAN)**
- **In-Painting**
- **Live Preview**: See the image as the AI is drawing it
- **Lots of Samplers:** ddim, plms, heun, euler, euler_a, dpm2, dpm2_a, lms
- **Image Modifiers**: A library of *modifier tags* like *"Realistic"*, *"Pencil Sketch"*, *"ArtStation"* etc. Experiment with various styles quickly.
- **Multiple Prompts File**: Queue multiple prompts by entering one prompt per line, or by running a text file.
- **Save generated images to disk**: Save your images to your PC!
- **UI Themes**: Customize the program to your liking.
- **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)**
- **Upscaling (RealESRGAN)**
- **Loopback**: Use the output image as the input image for the next img2img task.
- **Negative Prompt**: Specify aspects of the image to *remove*.
- **Attention/Emphasis**: () in the prompt increases the model's attention to enclosed words, and [] decreases it.
- **Weighted Prompts**: Use weights for specific words in your prompt to change their importance, e.g. `red:2.4 dragon:1.2`.
- **Prompt Matrix**: Quickly create multiple variations of your prompt, e.g. `a photograph of an astronaut riding a horse | illustration | cinematic lighting`.
- **Prompt Set**: Quickly create multiple variations of your prompt, e.g. `a photograph of an astronaut on the {moon,earth}`
- **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.
### 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**
- **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/easydiffusion/easydiffusion/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!
- **New UI**: with cleaner design
- **Waifu Model Support**: Just replace the `stable-diffusion\sd-v1-4.ckpt` file after installation with the Waifu model
- Supports "*Text to Image*" and "*Image to Image*"
- **NSFW Setting**: A setting in the UI to control *NSFW content*
- **Use CPU setting**: If you don't have a compatible graphics card, but still want to run it on your CPU.
- **Multi-GPU support**: Automatically spreads your tasks across multiple GPUs (if available), for faster performance!
- **Auto scan for malicious models**: Uses picklescan to prevent malicious models.
- **Safetensors support**: Support loading models in the safetensor format, for improved safety.
- **Auto-updater**: Gets you the latest improvements and bug-fixes to a rapidly evolving project.
- **Developer Console**: A developer-mode for those who want to modify their Stable Diffusion code, and edit the conda environment.
**(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)
## Powerful features for advanced users:
![Screenshot of advanced settings](https://user-images.githubusercontent.com/844287/217042588-fc53c975-bacd-4a9c-af88-37408734ade3.png)
- **Low Memory Usage**: Creates 512x512 images with less than 4GB of VRAM!
![Screenshot of advanced settings](media/shot-v9.jpg?raw=true)
## Live Preview
Useful for judging (and stopping) an image quickly, without waiting for it to finish rendering.
![live-512](https://user-images.githubusercontent.com/844287/192097249-729a0a1e-a677-485e-9ccc-16a9e848fabe.gif)
## Task Queue
![Screenshot of task queue](https://user-images.githubusercontent.com/844287/217043984-0b35f73b-1318-47cb-9eed-a2a91b430490.png)
# 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. But if you don't have a compatible graphics card, you can still use it with a "Use CPU" setting. It'll be very slow, but it should still work.
You do not need anything else. You do not need WSL, Docker or Conda. The installer will take care of it.
# Installation
1. **Download** [for Windows](https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.16/stable-diffusion-ui-win64.zip) or [for Linux](https://github.com/cmdr2/stable-diffusion-ui/releases/download/v2.16/stable-diffusion-ui-linux.tar.xz).
2. **Extract**:
- For Windows: After unzipping the file, please move the `stable-diffusion-ui` folder to your `C:` (or any drive like D:, at the top root level), e.g. `C:\stable-diffusion-ui`. This will avoid a common problem with Windows (file path length limits).
- For Linux: After extracting the .tar.xz file, please open a terminal, and go to the `stable-diffusion-ui` directory.
3. **Run**:
- For Windows: `Start Stable Diffusion UI.cmd` by double-clicking it.
- For Linux: In the terminal, run `./start.sh` (or `bash start.sh`)
This will automatically install Stable Diffusion, set it up, and start the interface. No additional steps are needed.
**To Uninstall:** Just delete the `stable-diffusion-ui` folder to uninstall all the downloaded packages.
----
# Usage
Open http://localhost:9000 in your browser (after running step 3 previously). It may take a few moments for the back-end to be ready.
# How to use?
Please refer to our [guide](https://github.com/easydiffusion/easydiffusion/wiki/How-to-Use) to understand how to use the features in this UI.
## With a text description
1. Enter a text prompt, like `a photograph of an astronaut riding a horse` in the textbox.
2. Press `Make Image`. This will take some time, depending on your system's processing power.
3. See the image generated using your prompt.
## With an image
1. Click `Browse..` next to `Initial Image`. Select your desired image.
2. An optional text prompt can help you further describe the kind of image you want to generate.
3. Press `Make Image`. See the image generated using your prompt.
You can use Face Correction or Upscaling to improve the image further.
**Pro tip:** You can also click `Use as Input` on a generated image, to use it as the input image for your next generation. This can be useful for sequentially refining the generated image with a single click.
**Another tip:** Images with the same aspect ratio of your generated image work best. E.g. 1:1 if you're generating images sized 512x512.
## Problems? Troubleshooting
Please try the common [troubleshooting](Troubleshooting.md) steps. If that doesn't fix it, please ask on the [discord server](https://discord.com/invite/u9yhsFmEkB), or [file an issue](https://github.com/cmdr2/stable-diffusion-ui/issues).
# Image Settings
You can also set the configuration like `seed`, `width`, `height`, `num_outputs`, `num_inference_steps` and `guidance_scale` using the 'show' button next to 'Image settings'.
Use the same `seed` number to get the same image for a certain prompt. This is useful for refining a prompt without losing the basic image design. Enable the `random images` checkbox to get random images.
![Screenshot of advanced settings](media/config-v6.jpg?raw=true)
# System Settings
The system settings are reachable via the cogwheel symbol on the top right. It can be used to configure whether all generated images should
saved be automically, or to tune the Stable Diffusion image generation.
![Screenshot of advanced settings](media/system-settings-v2.jpg?raw=true)
# Image Modifiers
![Screenshot of advanced settings](media/modifiers-v1.jpg?raw=true)
# Bugs reports and code contributions welcome
If there are any problems or suggestions, please feel free to ask on the [discord server](https://discord.com/invite/u9yhsFmEkB) or [file an issue](https://github.com/easydiffusion/easydiffusion/issues).
If there are any problems or suggestions, please feel free to ask on the [discord server](https://discord.com/invite/u9yhsFmEkB) or [file an issue](https://github.com/cmdr2/stable-diffusion-ui/issues).
We could really use help on these aspects (click to view tasks that need your help):
* [User Interface](https://github.com/users/cmdr2/projects/1/views/1)
* [Engine](https://github.com/users/cmdr2/projects/3/views/1)
* [Installer](https://github.com/users/cmdr2/projects/4/views/1)
* [Documentation](https://github.com/users/cmdr2/projects/5/views/1)
If you have any code contributions in mind, please feel free to say Hi to us on the [discord server](https://discord.com/invite/u9yhsFmEkB). We use the Discord server for development-related discussions, and for helping users.
Also, please feel free to submit a pull request, if you have any code contributions in mind. Join the [discord server](https://discord.com/invite/u9yhsFmEkB) for development-related discussions, and for helping other users.
# Disclaimer
The authors of this project are not responsible for any content generated using this interface.
The license of this software forbids you from sharing any content that:
- Violates any laws.
- Produces any harm to a person or persons.
- Disseminates (spreads) any personal information that would be meant for harm.
- Spreads misinformation.
- Target vulnerable groups.
For the full list of restrictions please read [the License](LICENSE). You agree to these terms by using this software.
The license of this software forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, spread misinformation, or target vulnerable groups. For the full list of restrictions please read [the license](LICENSE). You agree to these terms by using this software.

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

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@ -2,47 +2,46 @@
@echo "Hi there, what you are running is meant for the developers of this project, not for users." & echo.
@echo "If you only want to use the Stable Diffusion UI, you've downloaded the wrong file."
@echo "Please download and follow the instructions at https://github.com/easydiffusion/easydiffusion#installation" & echo.
@echo "Please download and follow the instructions at https://github.com/cmdr2/stable-diffusion-ui#installation" & echo.
@echo "If you are actually a developer of this project, please type Y and press enter" & echo.
set /p answer=Are you a developer of this project (Y/N)?
if /i "%answer:~,1%" NEQ "Y" exit /b
mkdir dist\win\stable-diffusion-ui\scripts
@REM mkdir dist\linux-mac\stable-diffusion-ui\scripts
@set PYTHONNOUSERSITE=1
@rem copy the installer files for Windows
@mkdir dist\stable-diffusion-ui
copy scripts\on_env_start.bat dist\win\stable-diffusion-ui\scripts\
copy scripts\bootstrap.bat dist\win\stable-diffusion-ui\scripts\
copy scripts\config.yaml.sample dist\win\stable-diffusion-ui\scripts\config.yaml
copy "scripts\Start Stable Diffusion UI.cmd" dist\win\stable-diffusion-ui\
copy LICENSE dist\win\stable-diffusion-ui\
copy "CreativeML Open RAIL-M License" dist\win\stable-diffusion-ui\
copy "How to install and run.txt" dist\win\stable-diffusion-ui\
echo. > dist\win\stable-diffusion-ui\scripts\install_status.txt
@echo "Downloading components for the installer.."
@rem copy the installer files for Linux and Mac
@call conda env create --prefix installer -f environment.yaml
@call conda activate .\installer
@REM copy scripts\on_env_start.sh dist\linux-mac\stable-diffusion-ui\scripts\
@REM copy scripts\bootstrap.sh dist\linux-mac\stable-diffusion-ui\scripts\
@REM copy scripts\start.sh dist\linux-mac\stable-diffusion-ui\
@REM copy LICENSE dist\linux-mac\stable-diffusion-ui\
@REM copy "CreativeML Open RAIL-M License" dist\linux-mac\stable-diffusion-ui\
@REM copy "How to install and run.txt" dist\linux-mac\stable-diffusion-ui\
@REM echo. > dist\linux-mac\stable-diffusion-ui\scripts\install_status.txt
@echo "Creating a distributable package.."
@rem make the zip
@call conda install -c conda-forge -y conda-pack
@call conda pack --n-threads -1 --prefix installer --format tar
cd dist\win
call powershell Compress-Archive -Path stable-diffusion-ui -DestinationPath ..\stable-diffusion-ui-windows.zip
cd ..\..
@cd dist\stable-diffusion-ui
@mkdir installer
@REM cd dist\linux-mac
@REM call powershell Compress-Archive -Path stable-diffusion-ui -DestinationPath ..\stable-diffusion-ui-linux.zip
@REM call powershell Compress-Archive -Path stable-diffusion-ui -DestinationPath ..\stable-diffusion-ui-mac.zip
@REM cd ..\..
@call tar -xf ..\..\installer.tar -C installer
echo "Build ready. Upload the zip files inside the 'dist' folder."
@mkdir scripts
pause
@copy ..\..\scripts\on_env_start.bat scripts\
@copy "..\..\scripts\Start Stable Diffusion UI.cmd" .
@copy ..\..\LICENSE .
@copy "..\..\CreativeML Open RAIL-M License" .
@copy "..\..\How to install and run.txt" .
@echo. > scripts\install_status.txt
@echo "Build ready. Zip the 'dist\stable-diffusion-ui' folder."
@echo "Cleaning up.."
@cd ..\..
@rmdir /s /q installer
@del installer.tar

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@ -2,7 +2,7 @@
printf "Hi there, what you are running is meant for the developers of this project, not for users.\n\n"
printf "If you only want to use the Stable Diffusion UI, you've downloaded the wrong file.\n"
printf "Please download and follow the instructions at https://github.com/easydiffusion/easydiffusion#installation \n\n"
printf "Please download and follow the instructions at https://github.com/cmdr2/stable-diffusion-ui#installation\n\n"
printf "If you are actually a developer of this project, please type Y and press enter\n\n"
read -p "Are you a developer of this project (Y/N) " yn
@ -11,40 +11,45 @@ case $yn in
* ) exit;;
esac
# mkdir -p dist/win/stable-diffusion-ui/scripts
mkdir -p dist/linux-mac/stable-diffusion-ui/scripts
export PYTHONNOUSERSITE=1
# copy the installer files for Windows
mkdir -p dist/stable-diffusion-ui
# cp scripts/on_env_start.bat dist/win/stable-diffusion-ui/scripts/
# cp scripts/bootstrap.bat dist/win/stable-diffusion-ui/scripts/
# cp "scripts/Start Stable Diffusion UI.cmd" dist/win/stable-diffusion-ui/
# cp LICENSE dist/win/stable-diffusion-ui/
# cp "CreativeML Open RAIL-M License" dist/win/stable-diffusion-ui/
# cp "How to install and run.txt" dist/win/stable-diffusion-ui/
# echo "" > dist/win/stable-diffusion-ui/scripts/install_status.txt
echo "Downloading components for the installer.."
# copy the installer files for Linux and Mac
source ~/miniconda3/etc/profile.d/conda.sh
cp scripts/on_env_start.sh dist/linux-mac/stable-diffusion-ui/scripts/
cp scripts/bootstrap.sh dist/linux-mac/stable-diffusion-ui/scripts/
cp scripts/functions.sh dist/linux-mac/stable-diffusion-ui/scripts/
cp scripts/config.yaml.sample dist/linux-mac/stable-diffusion-ui/scripts/config.yaml
cp scripts/start.sh dist/linux-mac/stable-diffusion-ui/
cp LICENSE dist/linux-mac/stable-diffusion-ui/
cp "CreativeML Open RAIL-M License" dist/linux-mac/stable-diffusion-ui/
cp "How to install and run.txt" dist/linux-mac/stable-diffusion-ui/
echo "" > dist/linux-mac/stable-diffusion-ui/scripts/install_status.txt
conda install -c conda-forge -y conda-pack
# make the zip
conda env create --prefix installer -f environment.yaml
conda activate ./installer
# cd dist/win
# zip -r ../stable-diffusion-ui-windows.zip stable-diffusion-ui
# cd ../..
echo "Creating a distributable package.."
conda pack --n-threads -1 --prefix installer --format tar
cd dist/stable-diffusion-ui
mkdir installer
tar -xf ../../installer.tar -C installer
mkdir scripts
cp ../../scripts/on_env_start.sh scripts/
cp ../../scripts/start.sh .
cp ../../LICENSE .
cp "../../CreativeML Open RAIL-M License" .
cp "../../How to install and run.txt" .
echo "" > scripts/install_status.txt
chmod u+x start.sh
echo "Build ready. Zip the 'dist/stable-diffusion-ui' folder."
echo "Cleaning up.."
cd dist/linux-mac
zip -r ../stable-diffusion-ui-linux.zip stable-diffusion-ui
zip -r ../stable-diffusion-ui-mac.zip stable-diffusion-ui
cd ../..
echo "Build ready. Upload the zip files inside the 'dist' folder."
rm -rf installer
rm installer.tar

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

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@ -1,51 +0,0 @@
@echo off
echo "Opening Stable Diffusion UI - Developer Console.." & echo.
cd /d %~dp0
set PATH=C:\Windows\System32;%PATH%
@rem set legacy and new installer's PATH, if they exist
if exist "installer" set PATH=%cd%\installer;%cd%\installer\Library\bin;%cd%\installer\Scripts;%cd%\installer\Library\usr\bin;%PATH%
if exist "installer_files\env" set PATH=%cd%\installer_files\env;%cd%\installer_files\env\Library\bin;%cd%\installer_files\env\Scripts;%cd%\installer_files\Library\usr\bin;%PATH%
set PYTHONPATH=%cd%\installer;%cd%\installer_files\env
@rem activate the installer env
call conda activate
@rem Test the environment
echo "Environment Info:"
call where git
call git --version
call where conda
call conda --version
echo.
echo COMSPEC=%COMSPEC%
echo.
@rem activate the legacy environment (if present) and set PYTHONPATH
if exist "installer_files\env" (
set PYTHONPATH=%cd%\installer_files\env\lib\site-packages
)
if exist "stable-diffusion\env" (
call conda activate .\stable-diffusion\env
set PYTHONPATH=%cd%\stable-diffusion\env\lib\site-packages
)
call where python
call python --version
echo PYTHONPATH=%PYTHONPATH%
if exist "%cd%\profile" (
set HF_HOME=%cd%\profile\.cache\huggingface
)
@rem done
echo.
cmd /k

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@ -1,44 +1,19 @@
@echo off
cd /d %~dp0
echo Install dir: %~dp0
@REM Delete the post-activate hook from the old installer
if exist "installer\etc\conda\activate.d\post_activate.bat" (
echo. > installer\etc\conda\activate.d\post_activate.bat
)
set PATH=C:\Windows\System32;%PATH%
@call installer\Scripts\activate.bat
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
)
@call conda-unpack
@rem set legacy installer's PATH, if it exists
if exist "installer" set PATH=%cd%\installer;%cd%\installer\Library\bin;%cd%\installer\Scripts;%cd%\installer\Library\usr\bin;%PATH%
@call conda --version
@call git --version
@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%
@cd installer
set PYTHONPATH=%cd%\installer;%cd%\installer_files\env
@call ..\scripts\on_env_start.bat
@rem Test the core requirements
call where git
call git --version
call where conda
call conda --version
echo .
echo COMSPEC=%COMSPEC%
@rem Download the rest of the installer and UI
call scripts\on_env_start.bat
@pause

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@ -1,78 +0,0 @@
@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).
@rem For users who already have git and conda, this step will be skipped.
@rem This enables a user to install this project without manually installing conda and git.
@rem config
set MAMBA_ROOT_PREFIX=%cd%\installer_files\mamba
set INSTALL_ENV_DIR=%cd%\installer_files\env
set LEGACY_INSTALL_ENV_DIR=%cd%\installer
set MICROMAMBA_DOWNLOAD_URL=https://github.com/easydiffusion/easydiffusion/releases/download/v1.1/micromamba.exe
set umamba_exists=F
set OLD_APPDATA=%APPDATA%
set OLD_USERPROFILE=%USERPROFILE%
set APPDATA=%cd%\installer_files\appdata
set USERPROFILE=%cd%\profile
@rem figure out whether git and conda needs to be installed
if exist "%INSTALL_ENV_DIR%" set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Library\bin;%INSTALL_ENV_DIR%\Scripts;%INSTALL_ENV_DIR%\Library\usr\bin;%PATH%
set PACKAGES_TO_INSTALL=
if not exist "%LEGACY_INSTALL_ENV_DIR%\etc\profile.d\conda.sh" (
if not exist "%INSTALL_ENV_DIR%\etc\profile.d\conda.sh" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% conda python=3.8.5
)
call git --version >.tmp1 2>.tmp2
if "!ERRORLEVEL!" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% git
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version >.tmp1 2>.tmp2
if "!ERRORLEVEL!" EQU "0" set umamba_exists=T
@rem (if necessary) install git and conda into a contained environment
if "%PACKAGES_TO_INSTALL%" NEQ "" (
@rem download micromamba
if "%umamba_exists%" == "F" (
echo "Downloading micromamba from %MICROMAMBA_DOWNLOAD_URL% to %MAMBA_ROOT_PREFIX%\micromamba.exe"
mkdir "%MAMBA_ROOT_PREFIX%"
call curl -Lk "%MICROMAMBA_DOWNLOAD_URL%" > "%MAMBA_ROOT_PREFIX%\micromamba.exe"
if "!ERRORLEVEL!" NEQ "0" (
echo "There was a problem downloading micromamba. Cannot continue."
pause
exit /b
)
mkdir "%APPDATA%"
mkdir "%USERPROFILE%"
@rem test the mamba binary
echo Micromamba version:
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version
)
@rem create the installer env
if not exist "%INSTALL_ENV_DIR%" (
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" create -y --prefix "%INSTALL_ENV_DIR%"
)
echo "Packages to install:%PACKAGES_TO_INSTALL%"
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" install -y --prefix "%INSTALL_ENV_DIR%" -c conda-forge %PACKAGES_TO_INSTALL%
if not exist "%INSTALL_ENV_DIR%" (
echo "There was a problem while installing%PACKAGES_TO_INSTALL% using micromamba. Cannot continue."
pause
exit /b
)
)
@rem revert to the old APPDATA. only needed it for bypassing a bug in micromamba (with special characters)
set APPDATA=%OLD_APPDATA%
set USERPROFILE=%OLD_USERPROFILE%

View File

@ -1,93 +0,0 @@
#!/bin/bash
# This script will install git and conda (if not found on the PATH variable)
# using micromamba (an 8mb static-linked single-file binary, conda replacement).
# For users who already have git and conda, this step will be skipped.
# This enables a user to install this project without manually installing conda and git.
source ./scripts/functions.sh
set -o pipefail
OS_NAME=$(uname -s)
case "${OS_NAME}" in
Linux*) OS_NAME="linux";;
Darwin*) OS_NAME="osx";;
*) echo "Unknown OS: $OS_NAME! This script runs only on Linux or Mac" && exit
esac
OS_ARCH=$(uname -m)
case "${OS_ARCH}" in
x86_64*) OS_ARCH="64";;
arm64*) OS_ARCH="arm64";;
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" ] && [ "$OS_ARCH" == "arm64" ]; then OS_ARCH="aarch64"; fi
# config
export MAMBA_ROOT_PREFIX="$(pwd)/installer_files/mamba"
INSTALL_ENV_DIR="$(pwd)/installer_files/env"
LEGACY_INSTALL_ENV_DIR="$(pwd)/installer"
MICROMAMBA_DOWNLOAD_URL="https://micro.mamba.pm/api/micromamba/${OS_NAME}-${OS_ARCH}/latest"
umamba_exists="F"
# figure out whether git and conda needs to be installed
if [ -e "$INSTALL_ENV_DIR" ]; then export PATH="$INSTALL_ENV_DIR/bin:$PATH"; fi
PACKAGES_TO_INSTALL=""
if [ ! -e "$LEGACY_INSTALL_ENV_DIR/etc/profile.d/conda.sh" ] && [ ! -e "$INSTALL_ENV_DIR/etc/profile.d/conda.sh" ]; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL conda python=3.8.5"; fi
if ! hash "git" &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL git"; fi
if "$MAMBA_ROOT_PREFIX/micromamba" --version &>/dev/null; then umamba_exists="T"; fi
# (if necessary) install git and conda into a contained environment
if [ "$PACKAGES_TO_INSTALL" != "" ]; then
# download micromamba
if [ "$umamba_exists" == "F" ]; then
echo "Downloading micromamba from $MICROMAMBA_DOWNLOAD_URL to $MAMBA_ROOT_PREFIX/micromamba"
mkdir -p "$MAMBA_ROOT_PREFIX"
curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvj -O bin/micromamba > "$MAMBA_ROOT_PREFIX/micromamba"
if [ "$?" != "0" ]; then
echo
echo "EE micromamba download failed"
echo "EE If the lines above contain 'bzip2: Cannot exec', your system doesn't have bzip2 installed"
echo "EE If there are network errors, please check your internet setup"
fail "micromamba download failed"
fi
chmod u+x "$MAMBA_ROOT_PREFIX/micromamba"
# test the mamba binary
echo "Micromamba version:"
"$MAMBA_ROOT_PREFIX/micromamba" --version
fi
# create the installer env
if [ ! -e "$INSTALL_ENV_DIR" ]; then
"$MAMBA_ROOT_PREFIX/micromamba" create -y --prefix "$INSTALL_ENV_DIR" || fail "unable to create the install environment"
fi
if [ ! -e "$INSTALL_ENV_DIR" ]; then
fail "There was a problem while installing$PACKAGES_TO_INSTALL using micromamba. Cannot continue."
fi
echo "Packages to install:$PACKAGES_TO_INSTALL"
"$MAMBA_ROOT_PREFIX/micromamba" install -y --prefix "$INSTALL_ENV_DIR" -c conda-forge $PACKAGES_TO_INSTALL
if [ "$?" != "0" ]; then
fail "Installation of the packages '$PACKAGES_TO_INSTALL' failed."
fi
fi

View File

@ -1,162 +0,0 @@
"""
This script checks and installs the required modules.
This script runs inside the legacy "stable-diffusion" folder
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": "1.0.142",
"stable-diffusion-sdkit": "2.1.4",
"rich": "12.6.0",
"uvicorn": "0.19.0",
"fastapi": "0.85.1",
"pycloudflared": "0.2.0",
"ruamel.yaml": "0.17.21",
# "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/easydiffusion/easydiffusion/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/easydiffusion/easydiffusion/issues
Thanks!"""
)
exit(1)
### start
init()

View File

@ -1,24 +0,0 @@
# Change listen_port if port 9000 is already in use on your system
# Set listen_to_network to true to make Easy Diffusion accessibble on your local network
net:
listen_port: 9000
listen_to_network: false
# Multi GPU setup
render_devices: auto
# Set open_browser_on_start to false to disable opening a new browser tab on each restart
ui:
open_browser_on_start: true
# set update_branch to main to use the stable version, or to beta to use the experimental
# beta version.
update_branch: main
# Set force_save_path to enforce an auto save path. Clients will not be able to change or
# disable auto save when this option is set. Please adapt the path in the examples to your
# needs.
# Windows:
# force_save_path: C:\\Easy Diffusion Images\\
# Linux:
# force_save_path: /data/easy-diffusion-images/

View File

@ -1,55 +0,0 @@
#!/bin/bash
cd "$(dirname "${BASH_SOURCE[0]}")"
if [ "$0" == "bash" ]; then
echo "Opening Stable Diffusion UI - Developer Console.."
echo ""
# set legacy and new installer's PATH, if they exist
if [ -e "installer" ]; then export PATH="$(pwd)/installer/bin:$PATH"; fi
if [ -e "installer_files/env" ]; then export PATH="$(pwd)/installer_files/env/bin:$PATH"; fi
# activate the installer env
CONDA_BASEPATH=$(conda info --base)
source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # avoids the 'shell not initialized' error
conda activate
# test the environment
echo "Environment Info:"
which git
git --version
which conda
conda --version
echo ""
# activate the legacy environment (if present) and set PYTHONPATH
if [ -e "installer_files/env" ]; then
export PYTHONPATH="$(pwd)/installer_files/env/lib/python3.8/site-packages"
fi
if [ -e "stable-diffusion/env" ]; then
CONDA_BASEPATH=$(conda info --base)
source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains about 'shell not initialized' (needed when running in a script)
conda activate ./stable-diffusion/env
export PYTHONPATH="$(pwd)/stable-diffusion/env/lib/python3.8/site-packages"
fi
export PYTHONNOUSERSITE=y
which python
python --version
echo "PYTHONPATH=$PYTHONPATH"
# done
echo ""
else
file_name=$(basename "${BASH_SOURCE[0]}")
bash --init-file "$file_name"
fi

View File

@ -1,39 +0,0 @@
#
# utility functions for all scripts
#
fail() {
echo
echo "EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE"
echo
if [ "$1" != "" ]; then
echo ERROR: $1
else
echo An error occurred.
fi
cat <<EOF
Error downloading Stable Diffusion UI. Sorry about that, please try to:
1. Run this installer again.
2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/easydiffusion/easydiffusion/wiki/Troubleshooting
3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB
4. If that doesn't solve the problem, please file an issue at https://github.com/easydiffusion/easydiffusion/issues
Thanks!
EOF
read -p "Press any key to continue"
exit 1
}
filesize() {
case "$(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

@ -1,53 +0,0 @@
import os
import argparse
import sys
import shutil
# 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()
config = None
# migrate the old config yaml location
config_legacy_yaml = os.path.join(config_directory, "config.yaml")
if os.path.isfile(config_legacy_yaml):
shutil.move(config_legacy_yaml, config_yaml)
if os.path.isfile(config_yaml):
from ruamel.yaml import YAML
yaml = YAML(typ='safe')
with open(config_yaml, 'r') as configfile:
try:
config = yaml.load(configfile)
except Exception as e:
print(e, file=sys.stderr)
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)
if config is None:
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

@ -1,32 +1,20 @@
@echo off
@echo. & echo "Easy Diffusion - v2" & echo.
@echo. & echo "Stable Diffusion UI - v2" & echo.
set PATH=C:\Windows\System32;%PATH%
@cd ..
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
)
@>nul findstr /m "conda_sd_ui_deps_installed" scripts\install_status.txt
@>nul grep -c "conda_sd_ui_deps_installed" scripts\install_status.txt
@if "%ERRORLEVEL%" NEQ "0" (
for /f "tokens=*" %%a in ('python -c "import os; parts = os.getcwd().split(os.path.sep); print(len(parts))"') do if "%%a" NEQ "2" (
echo. & echo "!!!! WARNING !!!!" & echo.
@ -40,38 +28,34 @@ if "%update_branch%"=="" (
)
)
@>nul findstr /m "sd_ui_git_cloned" scripts\install_status.txt
@>nul grep -c "sd_ui_git_cloned" scripts\install_status.txt
@if "%ERRORLEVEL%" EQU "0" (
@echo "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
@call git reset --hard
@call git -c advice.detachedHead=false checkout "%update_branch%"
@call git checkout "%update_branch%"
@call git pull
@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/easydiffusion/easydiffusion.git sd-ui-files && (
@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/easydiffusion/easydiffusion/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/easydiffusion/easydiffusion/issues" & echo "Thanks!"
@echo "Error downloading Stable Diffusion UI. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
pause
@exit /b
)
)
@xcopy sd-ui-files\ui ui /s /i /Y /q
@xcopy sd-ui-files\ui ui /s /i /Y
@copy sd-ui-files\scripts\on_sd_start.bat scripts\ /Y
@copy sd-ui-files\scripts\check_modules.py scripts\ /Y
@copy sd-ui-files\scripts\get_config.py scripts\ /Y
@copy sd-ui-files\scripts\config.yaml.sample scripts\ /Y
@copy "sd-ui-files\scripts\Start Stable Diffusion UI.cmd" . /Y
@copy "sd-ui-files\scripts\Developer Console.cmd" . /Y
@call scripts\on_sd_start.bat
@pause
@pause

View File

@ -1,59 +1,43 @@
#!/bin/bash
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 $update_branch.."
cd sd-ui-files
git reset --hard
git -c advice.detachedHead=false checkout "$update_branch"
git checkout "$update_branch"
git pull
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/easydiffusion/easydiffusion.git sd-ui-files ; then
if git clone -b "$update_branch" https://github.com/cmdr2/stable-diffusion-ui.git sd-ui-files ; then
echo sd_ui_git_cloned >> scripts/install_status.txt
else
fail "git clone failed"
printf "\n\nError downloading Stable Diffusion UI. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
fi
rm -rf ui
cp -Rf sd-ui-files/ui .
cp sd-ui-files/scripts/on_sd_start.sh scripts/
cp sd-ui-files/scripts/bootstrap.sh scripts/
cp sd-ui-files/scripts/check_modules.py scripts/
cp sd-ui-files/scripts/get_config.py scripts/
cp sd-ui-files/scripts/config.yaml.sample 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

@ -1,124 +1,267 @@
@echo off
@copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y
@REM Caution, this file will make your eyes and brain bleed. It's such an unholy mess.
@REM Note to self: Please rewrite this in Python. For the sake of your own sanity.
@copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y
@copy sd-ui-files\scripts\check_modules.py scripts\ /Y
@copy sd-ui-files\scripts\get_config.py scripts\ /Y
@copy sd-ui-files\scripts\config.yaml.sample scripts\ /Y
@call python -c "import os; import shutil; frm = 'sd-ui-files\\ui\\hotfix\\9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'; dst = os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'transformers', '9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'); shutil.copyfile(frm, dst) if os.path.exists(dst) else print(''); print('Hotfixed broken JSON file from OpenAI');"
if exist "%cd%\profile" (
set HF_HOME=%cd%\profile\.cache\huggingface
@>nul grep -c "sd_git_cloned" scripts\install_status.txt
@if "%ERRORLEVEL%" EQU "0" (
@echo "Stable Diffusion's git repository was already installed. Updating.."
@cd stable-diffusion
@call git reset --hard
@call git pull
@call git checkout d87bd29a6862996d8a0980c1343b6f0d4eb718b4
@REM @call git apply ..\ui\sd_internal\ddim_callback.patch
@REM @call git apply ..\ui\sd_internal\env_yaml.patch
@call git apply ..\ui\sd_internal\custom_sd.patch
@cd ..
) else (
@echo. & echo "Downloading Stable Diffusion.." & echo.
@call git clone https://github.com/invoke-ai/InvokeAI.git stable-diffusion && (
@echo sd_git_cloned >> scripts\install_status.txt
) || (
@echo "Error downloading Stable Diffusion. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
pause
@exit /b
)
@cd stable-diffusion
@call git checkout d87bd29a6862996d8a0980c1343b6f0d4eb718b4
@REM @call git apply ..\ui\sd_internal\ddim_callback.patch
@REM @call git apply ..\ui\sd_internal\env_yaml.patch
@call git apply ..\ui\sd_internal\custom_sd.patch
@cd ..
)
@rem set the correct installer path (current vs legacy)
if exist "%cd%\installer_files\env" (
set INSTALL_ENV_DIR=%cd%\installer_files\env
)
if exist "%cd%\stable-diffusion\env" (
set INSTALL_ENV_DIR=%cd%\stable-diffusion\env
@cd stable-diffusion
@>nul grep -c "conda_sd_env_created" ..\scripts\install_status.txt
@if "%ERRORLEVEL%" EQU "0" (
@echo "Packages necessary for Stable Diffusion were already installed"
@call conda activate .\env
) else (
@echo. & echo "Downloading packages necessary for Stable Diffusion.." & echo. & echo "***** This will take some time (depending on the speed of the Internet connection) and may appear to be stuck, but please be patient ***** .." & echo.
@rmdir /s /q .\env
@REM prevent conda from using packages from the user's home directory, to avoid conflicts
@set PYTHONNOUSERSITE=1
@call conda env create --prefix env -f environment.yaml || (
@echo. & echo "Error installing the packages necessary for Stable Diffusion. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
@call conda activate .\env
@call conda install -c conda-forge -y --prefix env antlr4-python3-runtime=4.8 || (
@echo. & echo "Error installing antlr4-python3-runtime for Stable Diffusion. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
for /f "tokens=*" %%a in ('python -c "import torch; import ldm; import transformers; import numpy; import antlr4; print(42)"') do if "%%a" NEQ "42" (
@echo. & echo "Dependency test failed! Error installing the packages necessary for Stable Diffusion. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
@echo conda_sd_env_created >> ..\scripts\install_status.txt
)
@mkdir tmp
@set TMP=%cd%\tmp
@set TEMP=%cd%\tmp
@rem activate the installer env
call conda activate
@if "%ERRORLEVEL%" NEQ "0" (
@echo. & echo "Error activating conda for 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/easydiffusion/easydiffusion/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/easydiffusion/easydiffusion/issues" & echo "Thanks!" & echo.
pause
exit /b
)
@REM remove the old version of the dev console script, if it's still present
if exist "Open Developer Console.cmd" del "Open Developer Console.cmd"
@rem create the stable-diffusion folder, to work with legacy installations
if not exist "stable-diffusion" mkdir stable-diffusion
cd stable-diffusion
@rem activate the old stable-diffusion env, if it exists
if exist "env" (
call conda activate .\env
)
@rem disable the legacy src and ldm folder (otherwise this prevents installing gfpgan and realesrgan)
if exist src rename src src-old
if exist ldm rename ldm ldm-old
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 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
@>nul grep -c "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
@if "%ERRORLEVEL%" EQU "0" (
echo "Packages necessary for Stable Diffusion UI were already installed"
) else (
@echo. & echo "Downloading packages necessary for Stable Diffusion UI.." & echo.
@rem Download the required packages
call python ..\scripts\check_modules.py
if "%ERRORLEVEL%" NEQ "0" (
pause
exit /b
@set PYTHONNOUSERSITE=1
@call conda install -c conda-forge -y --prefix env uvicorn fastapi || (
echo "Error installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
pause
exit /b
)
)
call WHERE uvicorn > .tmp
@>nul findstr /m "uvicorn" .tmp
@>nul grep -c "uvicorn" .tmp
@if "%ERRORLEVEL%" NEQ "0" (
@echo. & echo "UI packages not found! Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/easydiffusion/easydiffusion/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/easydiffusion/easydiffusion/issues" & echo "Thanks!" & echo.
@echo. & echo "UI packages not found! Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
@>nul findstr /m "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
@>nul grep -c "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
@if "%ERRORLEVEL%" NEQ "0" (
@echo conda_sd_ui_deps_installed >> ..\scripts\install_status.txt
)
@>nul findstr /m "sd_install_complete" ..\scripts\install_status.txt
@if exist "sd-v1-4.ckpt" (
for %%I in ("sd-v1-4.ckpt") do if "%%~zI" EQU "4265380512" (
echo "Data files (weights) necessary for Stable Diffusion were already downloaded. Using the HuggingFace 4 GB Model."
) else (
for %%J in ("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 ("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 %cd%\sd-v1-4.ckpt is invalid. It is only %%~zK bytes in size. Re-downloading.." & echo.
del "sd-v1-4.ckpt"
)
)
)
)
@if not exist "sd-v1-4.ckpt" (
@echo. & echo "Downloading data files (weights) for Stable Diffusion.." & echo.
@call curl -L -k https://me.cmdr2.org/stable-diffusion-ui/sd-v1-4.ckpt > sd-v1-4.ckpt
@if exist "sd-v1-4.ckpt" (
for %%I in ("sd-v1-4.ckpt") do if "%%~zI" NEQ "4265380512" (
echo. & echo "Error: The downloaded model file was invalid! Bytes downloaded: %%~zI" & echo.
echo. & echo "Error downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
) else (
@echo. & echo "Error downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
)
@if exist "GFPGANv1.3.pth" (
for %%I in ("GFPGANv1.3.pth") do if "%%~zI" EQU "348632874" (
echo "Data files (weights) necessary for GFPGAN (Face Correction) were already downloaded"
) else (
echo. & echo "The GFPGAN model file present at %cd%\GFPGANv1.3.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
del "GFPGANv1.3.pth"
)
)
@if not exist "GFPGANv1.3.pth" (
@echo. & echo "Downloading data files (weights) for GFPGAN (Face Correction).." & echo.
@call curl -L -k https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth > GFPGANv1.3.pth
@if exist "GFPGANv1.3.pth" (
for %%I in ("GFPGANv1.3.pth") do if "%%~zI" NEQ "348632874" (
echo. & echo "Error: The downloaded GFPGAN model file was invalid! Bytes downloaded: %%~zI" & echo.
echo. & echo "Error downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
) else (
@echo. & echo "Error downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
)
@if exist "RealESRGAN_x4plus.pth" (
for %%I in ("RealESRGAN_x4plus.pth") do if "%%~zI" EQU "67040989" (
echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus were already downloaded"
) else (
echo. & echo "The GFPGAN model file present at %cd%\RealESRGAN_x4plus.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
del "RealESRGAN_x4plus.pth"
)
)
@if not exist "RealESRGAN_x4plus.pth" (
@echo. & echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.." & echo.
@call curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth > RealESRGAN_x4plus.pth
@if exist "RealESRGAN_x4plus.pth" (
for %%I in ("RealESRGAN_x4plus.pth") do if "%%~zI" NEQ "67040989" (
echo. & echo "Error: The downloaded ESRGAN x4plus model file was invalid! Bytes downloaded: %%~zI" & echo.
echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
) else (
@echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
)
@if exist "RealESRGAN_x4plus_anime_6B.pth" (
for %%I in ("RealESRGAN_x4plus_anime_6B.pth") do if "%%~zI" EQU "17938799" (
echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus_anime were already downloaded"
) else (
echo. & echo "The GFPGAN model file present at %cd%\RealESRGAN_x4plus_anime_6B.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
del "RealESRGAN_x4plus_anime_6B.pth"
)
)
@if not exist "RealESRGAN_x4plus_anime_6B.pth" (
@echo. & echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.." & echo.
@call curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth > RealESRGAN_x4plus_anime_6B.pth
@if exist "RealESRGAN_x4plus_anime_6B.pth" (
for %%I in ("RealESRGAN_x4plus_anime_6B.pth") do if "%%~zI" NEQ "17938799" (
echo. & echo "Error: The downloaded ESRGAN x4plus_anime model file was invalid! Bytes downloaded: %%~zI" & echo.
echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
) else (
@echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause
exit /b
)
)
@>nul grep -c "sd_install_complete" ..\scripts\install_status.txt
@if "%ERRORLEVEL%" NEQ "0" (
@echo sd_weights_downloaded >> ..\scripts\install_status.txt
@echo sd_install_complete >> ..\scripts\install_status.txt
)
@echo. & echo "Easy Diffusion installation complete! Starting the server!" & echo.
@echo. & echo "Stable Diffusion is ready!" & echo.
@set SD_DIR=%cd%
set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
echo PYTHONPATH=%PYTHONPATH%
call where python
call python --version
@cd env\lib\site-packages
@set PYTHONPATH=%SD_DIR%;%cd%
@cd ..\..\..
@echo PYTHONPATH=%PYTHONPATH%
@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" (
@FOR /F "tokens=* USEBACKQ" %%G IN (`python scripts\get_config.py --default=0.0.0.0 net bind_ip`) DO (
@SET ED_BIND_IP=%%G
)
) else (
@SET ED_BIND_IP=127.0.0.1
)
)
@cd stable-diffusion
@rem set any overrides
set HF_HUB_DISABLE_SYMLINKS_WARNING=true
@call python --version
@python -m uvicorn main:server_api --app-dir "%SD_UI_PATH%" --port %ED_BIND_PORT% --host %ED_BIND_IP% --log-level error
@uvicorn server:app --app-dir "%SD_UI_PATH%" --port 9000 --host 0.0.0.0
@pause
@pause

View File

@ -1,85 +1,309 @@
#!/bin/bash
cp sd-ui-files/scripts/functions.sh scripts/
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/
cp sd-ui-files/scripts/config.yaml.sample scripts/
source ./scripts/functions.sh
source installer/etc/profile.d/conda.sh
# activate the installer env
CONDA_BASEPATH=$(conda info --base)
source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # avoids the 'shell not initialized' error
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');"
conda activate || fail "Failed to activate conda"
# 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.
# remove the old version of the dev console script, if it's still present
if [ -e "open_dev_console.sh" ]; then
rm "open_dev_console.sh"
if [ -e "scripts/install_status.txt" ] && [ `grep -c sd_git_cloned scripts/install_status.txt` -gt "0" ]; then
echo "Stable Diffusion's git repository was already installed. Updating.."
cd stable-diffusion
git reset --hard
git pull
git checkout f6cfebffa752ee11a7b07497b8529d5971de916c
git apply ../ui/sd_internal/ddim_callback.patch
git apply ../ui/sd_internal/env_yaml.patch
cd ..
else
printf "\n\nDownloading Stable Diffusion..\n\n"
if git clone https://github.com/basujindal/stable-diffusion.git ; then
echo sd_git_cloned >> scripts/install_status.txt
else
printf "\n\nError downloading Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
cd stable-diffusion
git checkout f6cfebffa752ee11a7b07497b8529d5971de916c
git apply ../ui/sd_internal/ddim_callback.patch
git apply ../ui/sd_internal/env_yaml.patch
cd ..
fi
# set the correct installer path (current vs legacy)
if [ -e "installer_files/env" ]; then
export INSTALL_ENV_DIR="$(pwd)/installer_files/env"
fi
if [ -e "stable-diffusion/env" ]; then
export INSTALL_ENV_DIR="$(pwd)/stable-diffusion/env"
fi
# create the stable-diffusion folder, to work with legacy installations
if [ ! -e "stable-diffusion" ]; then mkdir stable-diffusion; fi
cd stable-diffusion
# activate the old stable-diffusion env, if it exists
if [ -e "env" ]; then
conda activate ./env || fail "conda activate failed"
if [ `grep -c conda_sd_env_created ../scripts/install_status.txt` -gt "0" ]; then
echo "Packages necessary for Stable Diffusion were already installed"
conda activate ./env
else
printf "\n\nDownloading packages necessary for Stable Diffusion..\n"
printf "\n\n***** This will take some time (depending on the speed of the Internet connection) and may appear to be stuck, but please be patient ***** ..\n\n"
# prevent conda from using packages from the user's home directory, to avoid conflicts
export PYTHONNOUSERSITE=1
if conda env create --prefix env --force -f environment.yaml ; then
echo "Installed. Testing.."
else
printf "\n\nError installing the packages necessary for Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
conda activate ./env
if conda install -c conda-forge --prefix ./env -y antlr4-python3-runtime=4.8 ; then
echo "Installed. Testing.."
else
printf "\n\nError installing antlr4-python3-runtime for Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
out_test=`python -c "import torch; import ldm; import transformers; import numpy; import antlr4; print(42)"`
if [ "$out_test" != "42" ]; then
printf "\n\nDependency test failed! Error installing the packages necessary for Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
echo conda_sd_env_created >> ../scripts/install_status.txt
fi
# disable the legacy src and ldm folder (otherwise this prevents installing gfpgan and realesrgan)
if [ -e "src" ]; then mv src src-old; fi
if [ -e "ldm" ]; then mv ldm ldm-old; fi
if [ `grep -c conda_sd_gfpgan_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
echo "Packages necessary for GFPGAN (Face Correction) were already installed"
else
printf "\n\nDownloading packages necessary for GFPGAN (Face Correction)..\n"
# Download the required packages
if ! python ../scripts/check_modules.py; then
read -p "Press any key to continue"
exit 1
export PYTHONNOUSERSITE=1
if pip install -e git+https://github.com/TencentARC/GFPGAN#egg=GFPGAN ; then
echo "Installed. Testing.."
else
printf "\n\nError installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
out_test=`python -c "from gfpgan import GFPGANer; print(42)"`
if [ "$out_test" != "42" ]; then
printf "\n\nDependency test failed! Error installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
echo conda_sd_gfpgan_deps_installed >> ../scripts/install_status.txt
fi
if ! command -v uvicorn &> /dev/null; then
fail "UI packages not found!"
if [ `grep -c conda_sd_esrgan_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
echo "Packages necessary for ESRGAN (Resolution Upscaling) were already installed"
else
printf "\n\nDownloading packages necessary for ESRGAN (Resolution Upscaling)..\n"
export PYTHONNOUSERSITE=1
if pip install -e git+https://github.com/xinntao/Real-ESRGAN#egg=realesrgan ; then
echo "Installed. Testing.."
else
printf "\n\nError installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
out_test=`python -c "from basicsr.archs.rrdbnet_arch import RRDBNet; from realesrgan import RealESRGANer; print(42)"`
if [ "$out_test" != "42" ]; then
printf "\n\nDependency test failed! Error installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
echo conda_sd_esrgan_deps_installed >> ../scripts/install_status.txt
fi
if [ `grep -c conda_sd_ui_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
echo "Packages necessary for Stable Diffusion UI were already installed"
else
printf "\n\nDownloading packages necessary for Stable Diffusion UI..\n\n"
export PYTHONNOUSERSITE=1
if conda install -c conda-forge --prefix ./env -y uvicorn fastapi ; then
echo "Installed. Testing.."
else
printf "\n\nError installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
if ! command -v uvicorn &> /dev/null; then
printf "\n\nUI packages not found! Error installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
echo conda_sd_ui_deps_installed >> ../scripts/install_status.txt
fi
if [ -f "sd-v1-4.ckpt" ]; then
model_size=`ls -l sd-v1-4.ckpt | awk '{print $5}'`
if [ "$model_size" -eq "4265380512" ] || [ "$model_size" -eq "7703807346" ] || [ "$model_size" -eq "7703810927" ]; then
echo "Data files (weights) necessary for Stable Diffusion were already downloaded"
else
printf "\n\nThe model file present at $PWD/sd-v1-4.ckpt is invalid. It is only $model_size bytes in size. Re-downloading.."
rm sd-v1-4.ckpt
fi
fi
if [ ! -f "sd-v1-4.ckpt" ]; then
echo "Downloading data files (weights) for Stable Diffusion.."
curl -L -k https://me.cmdr2.org/stable-diffusion-ui/sd-v1-4.ckpt > sd-v1-4.ckpt
if [ -f "sd-v1-4.ckpt" ]; then
model_size=`ls -l sd-v1-4.ckpt | awk '{print $5}'`
if [ ! "$model_size" == "4265380512" ]; then
printf "\n\nError: The downloaded model file was invalid! Bytes downloaded: $model_size\n\n"
printf "\n\nError downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
else
printf "\n\nError downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
fi
if [ -f "GFPGANv1.3.pth" ]; then
model_size=`ls -l GFPGANv1.3.pth | awk '{print $5}'`
if [ "$model_size" -eq "348632874" ]; then
echo "Data files (weights) necessary for GFPGAN (Face Correction) were already downloaded"
else
printf "\n\nThe model file present at $PWD/GFPGANv1.3.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
rm GFPGANv1.3.pth
fi
fi
if [ ! -f "GFPGANv1.3.pth" ]; then
echo "Downloading data files (weights) for GFPGAN (Face Correction).."
curl -L -k https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth > GFPGANv1.3.pth
if [ -f "GFPGANv1.3.pth" ]; then
model_size=`ls -l GFPGANv1.3.pth | awk '{print $5}'`
if [ ! "$model_size" -eq "348632874" ]; then
printf "\n\nError: The downloaded GFPGAN model file was invalid! Bytes downloaded: $model_size\n\n"
printf "\n\nError downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
else
printf "\n\nError downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
fi
if [ -f "RealESRGAN_x4plus.pth" ]; then
model_size=`ls -l RealESRGAN_x4plus.pth | awk '{print $5}'`
if [ "$model_size" -eq "67040989" ]; then
echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus were already downloaded"
else
printf "\n\nThe model file present at $PWD/RealESRGAN_x4plus.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
rm RealESRGAN_x4plus.pth
fi
fi
if [ ! -f "RealESRGAN_x4plus.pth" ]; then
echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.."
curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth > RealESRGAN_x4plus.pth
if [ -f "RealESRGAN_x4plus.pth" ]; then
model_size=`ls -l RealESRGAN_x4plus.pth | awk '{print $5}'`
if [ ! "$model_size" -eq "67040989" ]; then
printf "\n\nError: The downloaded ESRGAN x4plus model file was invalid! Bytes downloaded: $model_size\n\n"
printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
else
printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
fi
if [ -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
model_size=`ls -l RealESRGAN_x4plus_anime_6B.pth | awk '{print $5}'`
if [ "$model_size" -eq "17938799" ]; then
echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus_anime were already downloaded"
else
printf "\n\nThe model file present at $PWD/RealESRGAN_x4plus_anime_6B.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
rm RealESRGAN_x4plus_anime_6B.pth
fi
fi
if [ ! -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.."
curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth > RealESRGAN_x4plus_anime_6B.pth
if [ -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
model_size=`ls -l RealESRGAN_x4plus_anime_6B.pth | awk '{print $5}'`
if [ ! "$model_size" -eq "17938799" ]; then
printf "\n\nError: The downloaded ESRGAN x4plus_anime model file was invalid! Bytes downloaded: $model_size\n\n"
printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
else
printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
read -p "Press any key to continue"
exit
fi
fi
if [ `grep -c sd_install_complete ../scripts/install_status.txt` -gt "0" ]; then
echo sd_weights_downloaded >> ../scripts/install_status.txt
echo sd_install_complete >> ../scripts/install_status.txt
fi
printf "\n\nEasy Diffusion installation complete, starting the server!\n\n"
printf "\n\nStable Diffusion is ready!\n\n"
SD_PATH=`pwd`
export PYTORCH_ENABLE_MPS_FALLBACK=1
export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
export PYTHONPATH="$SD_PATH;$SD_PATH/env/lib/python3.8/site-packages"
echo "PYTHONPATH=$PYTHONPATH"
which python
python --version
cd ..
export SD_UI_PATH=`pwd`/ui
export ED_BIND_PORT="$( python scripts/get_config.py --default=9000 net listen_port )"
case "$( python scripts/get_config.py --default=False net listen_to_network )" in
"True")
export ED_BIND_IP=$( python scripts/get_config.py --default=0.0.0.0 net bind_ip)
;;
"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 "$ED_BIND_IP" --log-level error
python --version
uvicorn server:app --app-dir "$SD_UI_PATH" --port 9000 --host 0.0.0.0
read -p "Press any key to continue"

View File

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

12
scripts/post_activate.sh Executable file
View File

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

39
scripts/start.sh Executable file → Normal file
View File

@ -1,41 +1,10 @@
#!/bin/bash
cd "$(dirname "${BASH_SOURCE[0]}")"
source installer/bin/activate
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
conda-unpack
conda --version
git --version
# set legacy installer's PATH, if it exists
if [ -e "installer" ]; then export PATH="$(pwd)/installer/bin:$PATH"; fi
# Setup the packages required for the installer
scripts/bootstrap.sh || exit 1
# set new installer's PATH, if it downloaded any packages
if [ -e "installer_files/env" ]; then export PATH="$(pwd)/installer_files/env/bin:$PATH"; fi
# Test the bootstrap
which git
git --version || exit 1
which conda
conda --version || exit 1
# Download the rest of the installer and UI
chmod +x scripts/*.sh
scripts/on_env_start.sh

View File

@ -1,441 +0,0 @@
import json
import logging
import os
import shutil
import socket
import sys
import traceback
import copy
from ruamel.yaml import YAML
import urllib
import warnings
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"
logging.basicConfig(
level=logging.INFO,
format=LOG_FORMAT,
datefmt="%X",
handlers=[RichHandler(markup=True, rich_tracebacks=False, 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"))
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
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,
},
}
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")
def init_render_threads():
load_server_plugins()
update_render_threads()
def getConfig(default_val=APP_CONFIG_DEFAULTS):
config_yaml_path = os.path.join(CONFIG_DIR, "..", "config.yaml")
# migrate the old config yaml location
config_legacy_yaml = os.path.join(CONFIG_DIR, "config.yaml")
if os.path.isfile(config_legacy_yaml):
shutil.move(config_legacy_yaml, config_yaml_path)
def set_config_on_startup(config: dict):
if getConfig.__test_diffusers_on_startup is None:
getConfig.__test_diffusers_on_startup = config.get("test_diffusers", False)
config["config_on_startup"] = {"test_diffusers": getConfig.__test_diffusers_on_startup}
if os.path.isfile(config_yaml_path):
try:
yaml = YAML()
with open(config_yaml_path, "r", encoding="utf-8") as f:
config = yaml.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"))
else:
config["net"]["listen_port"] = 9000
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"
else:
config["net"]["listen_to_network"] = True
set_config_on_startup(config)
return config
except Exception as e:
log.warn(traceback.format_exc())
set_config_on_startup(default_val)
return default_val
else:
try:
config_json_path = os.path.join(CONFIG_DIR, "config.json")
if not os.path.exists(config_json_path):
return default_val
log.info("Converting old json config file to yaml")
with open(config_json_path, "r", encoding="utf-8") as f:
config = json.load(f)
# Save config in new format
setConfig(config)
with open(config_json_path + ".txt", "w") as f:
f.write("Moved to config.yaml inside the Easy Diffusion folder. You can open it in any text editor.")
os.remove(config_json_path)
return getConfig(default_val)
except Exception as e:
log.warn(traceback.format_exc())
set_config_on_startup(default_val)
return default_val
getConfig.__test_diffusers_on_startup = None
def setConfig(config):
try: # config.yaml
config_yaml_path = os.path.join(CONFIG_DIR, "..", "config.yaml")
yaml = YAML()
if not hasattr(config, "_yaml_comment"):
config_yaml_sample_path = os.path.join(CONFIG_DIR, "config.yaml.sample")
if os.path.exists(config_yaml_sample_path):
with open(config_yaml_sample_path, "r", encoding="utf-8") as f:
commented_config = yaml.load(f)
for k in config:
commented_config[k] = config[k]
config = commented_config
yaml.indent(mapping=2, sequence=4, offset=2)
if "config_on_startup" in config:
del config["config_on_startup"]
try:
f = open(config_yaml_path + ".tmp", "w", encoding="utf-8")
yaml.dump(config, f)
finally:
f.close() # do this explicitly to avoid NUL bytes (possible rare bug when using 'with')
# verify that the new file is valid, and only then overwrite the old config file
# helps prevent the rare NUL bytes error from corrupting the config file
yaml = YAML()
with open(config_yaml_path + ".tmp", "r", encoding="utf-8") as f:
yaml.load(f)
shutil.move(config_yaml_path + ".tmp", config_yaml_path)
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"] = {}
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"]
if hypernetwork_model_name is None or hypernetwork_model_name == "":
del config["model"]["hypernetwork"]
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()
log.debug(f"requesting for render_devices: {render_devices}")
task_manager.update_render_threads(render_devices, active_devices)
def getUIPlugins():
plugins = []
file_names = set()
for plugins_dir, dir_prefix in UI_PLUGINS_SOURCES:
for file in os.listdir(plugins_dir):
if file.endswith(".plugin.js") and file not in file_names:
plugins.append(f"/plugins/{dir_prefix}/{file}")
file_names.add(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())
ips[2].append(ips[0])
return ips[2]
except Exception as e:
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
log.info("Opening browser..")
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/easydiffusion/easydiffusion/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

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@ -1,257 +0,0 @@
import os
import platform
import re
import traceback
import torch
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
)
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'...]
"""
if render_devices in ("cpu", "auto", "mps"):
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))
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"}'
)
render_devices = list(filter(lambda x: is_device_compatible(x), render_devices))
if len(render_devices) == 0:
raise Exception(
"Sorry, none of the render_devices configured in config.json are compatible with Stable Diffusion"
)
else:
raise Exception(
'Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "auto"}'
)
else:
render_devices = ["auto"]
if "auto" in render_devices:
render_devices = auto_pick_devices(active_devices)
if "cpu" in render_devices:
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)
devices_to_start = render_devices - active_devices
devices_to_stop = active_devices - render_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"]
device_count = torch.cuda.device_count()
if device_count == 1:
return ["cuda:0"] if is_device_compatible("cuda:0") else ["cpu"]
log.debug("Autoselecting GPU. Using most free memory.")
devices = []
for device in range(device_count):
device = f"cuda:{device}"
if not is_device_compatible(device):
continue
mem_free, mem_total = torch.cuda.mem_get_info(device)
mem_free /= float(10**9)
mem_total /= float(10**9)
device_name = torch.cuda.get_device_name(device)
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"]
curr_mem_free_threshold = COMPARABLE_GPU_PERCENTILE * max_mem_free
mem_free_threshold = max(curr_mem_free_threshold, mem_free_threshold)
# Auto-pick algorithm:
# 1. Pick the top 75 percentile of the GPUs, sorted by free_mem.
# 2. Also include already-running devices (GPU-only), otherwise their free_mem will
# always be very low (since their VRAM contains the model).
# These already-running devices probably aren't terrible, since they were picked in the past.
# Worst case, the user can restart the program and that'll get rid of them.
devices = list(
filter(
(lambda x: x["mem_free"] > mem_free_threshold or x["device"] in currently_active_devices),
devices,
)
)
devices = list(map(lambda x: x["device"], devices))
return devices
def device_init(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")
if "cuda" not in device:
context.device = device
context.device_name = get_processor_name()
context.half_precision = False
log.debug(f"Render device available as {context.device_name}")
return
context.device_name = torch.cuda.get_device_name(device)
context.device = 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}")
# 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)
def needs_to_force_full_precision(context):
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)
def get_max_vram_usage_level(device):
if "cuda" in device:
_, mem_total = torch.cuda.mem_get_info(device)
else:
return "high"
mem_total /= float(10**9)
if mem_total < 4.5:
return "low"
elif mem_total < 6.5:
return "balanced"
return "high"
def validate_device_id(device, log_prefix=""):
def is_valid():
if not isinstance(device, str):
return False
if device == "cpu" or device == "mps":
return True
if not device.startswith("cuda:") or not device[5:].isnumeric():
return False
return True
if not is_valid():
raise EnvironmentError(
f"{log_prefix}: device id should be 'cpu', 'mps', 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", {})
try:
validate_device_id(device, log_prefix="is_device_compatible")
except:
log.error(str(e))
return False
if device in ("cpu", "mps"):
return True
# Memory check
try:
_, mem_total = torch.cuda.mem_get_info(device)
mem_total /= float(10**9)
if mem_total < 1.9:
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
return False
except RuntimeError as e:
log.error(str(e))
return False
return True
def get_processor_name():
try:
import subprocess
if platform.system() == "Windows":
return platform.processor()
elif platform.system() == "Darwin":
os.environ["PATH"] = os.environ["PATH"] + os.pathsep + "/usr/sbin"
command = "sysctl -n machdep.cpu.brand_string"
return subprocess.check_output(command, shell=True).decode().strip()
elif platform.system() == "Linux":
command = "cat /proc/cpuinfo"
all_info = subprocess.check_output(command, shell=True).decode().strip()
for line in all_info.split("\n"):
if "model name" in line:
return re.sub(".*model name.*:", "", line, 1).strip()
except:
log.error(traceback.format_exc())
return "cpu"

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@ -1,396 +0,0 @@
import os
import shutil
from glob import glob
import traceback
from typing import Union
from easydiffusion import app
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.utils import hash_file_quick
KNOWN_MODEL_TYPES = [
"stable-diffusion",
"vae",
"hypernetwork",
"gfpgan",
"realesrgan",
"lora",
"codeformer",
]
MODEL_EXTENSIONS = {
"stable-diffusion": [".ckpt", ".safetensors"],
"vae": [".vae.pt", ".ckpt", ".safetensors"],
"hypernetwork": [".pt", ".safetensors"],
"gfpgan": [".pth"],
"realesrgan": [".pth"],
"lora": [".ckpt", ".safetensors"],
"codeformer": [".pth"],
"embeddings": [".pt", ".bin", ".safetensors"],
}
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"},
],
}
MODELS_TO_LOAD_ON_START = ["stable-diffusion", "vae", "hypernetwork", "lora"]
known_models = {}
def init():
make_model_folders()
migrate_legacy_model_location() # if necessary
download_default_models_if_necessary()
def load_default_models(context: Context):
set_vram_optimizations(context)
config = app.getConfig()
context.embeddings_path = os.path.join(app.MODELS_DIR, "embeddings")
# 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)
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]
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
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: Union[str, list] = None, model_type: str = None, fail_if_not_found: bool = True):
model_names = model_name if isinstance(model_name, list) else [model_name]
model_paths = [resolve_model_to_use_single(m, model_type, fail_if_not_found) for m in model_names]
return model_paths[0] if len(model_paths) == 1 else model_paths
def resolve_model_to_use_single(model_name: str = None, model_type: str = None, fail_if_not_found: bool = True):
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.
# config = getConfig()
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
for model_extension in model_extensions:
if os.path.exists(model_path + model_extension):
return model_path + model_extension
if os.path.exists(model_name + model_extension):
return os.path.abspath(model_name + 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?")
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
}
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"]
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
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)
def set_vram_optimizations(context: Context):
config = app.getConfig()
vram_usage_level = config.get("vram_usage_level", "balanced")
if vram_usage_level != context.vram_usage_level:
context.vram_usage_level = vram_usage_level
return True
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_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:
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,
)
)
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,
)
)
return False
except Exception as e:
log.error(f"error while scanning: {file_path}, error: {e}")
return False
def getModels(scan_for_malicious: bool = True):
models = {
"options": {
"stable-diffusion": ["sd-v1-4"],
"vae": [],
"hypernetwork": [],
"lora": [],
"codeformer": ["codeformer"],
"embeddings": [],
},
}
models_scanned = 0
class MaliciousModelException(Exception):
"Raised when picklescan reports a problem with a model"
def scan_directory(directory, suffixes, directoriesFirst: bool = True):
nonlocal models_scanned
tree = []
for entry in sorted(
os.scandir(directory),
key=lambda entry: (entry.is_file() == directoriesFirst, entry.name.lower()),
):
if entry.is_file():
matching_suffix = list(filter(lambda s: entry.name.endswith(s), suffixes))
if len(matching_suffix) == 0:
continue
matching_suffix = matching_suffix[0]
mtime = entry.stat().st_mtime
mod_time = known_models[entry.path] if entry.path in known_models else -1
if mod_time != mtime:
models_scanned += 1
if scan_for_malicious and is_malicious_model(entry.path):
raise MaliciousModelException(entry.path)
if scan_for_malicious:
known_models[entry.path] = mtime
tree.append(entry.name[: -len(matching_suffix)])
elif entry.is_dir():
scan = scan_directory(entry.path, suffixes, directoriesFirst=False)
if len(scan) != 0:
tree.append((entry.name, scan))
return tree
def listModels(model_type):
nonlocal models_scanned
model_extensions = MODEL_EXTENSIONS.get(model_type, [])
models_dir = os.path.join(app.MODELS_DIR, model_type)
if not os.path.exists(models_dir):
os.makedirs(models_dir)
try:
models["options"][model_type] = scan_directory(models_dir, model_extensions)
except MaliciousModelException as e:
models["scan-error"] = str(e)
if scan_for_malicious:
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="embeddings")
if scan_for_malicious and models_scanned > 0:
log.info(f"[green]Scanned {models_scanned} models. Nothing infected[/]")
return models

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@ -1,279 +0,0 @@
import json
import pprint
import queue
import time
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 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,
)
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,
):
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 = res.json()
data_queue.put(json.dumps(res))
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}")
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)
if task_data.save_to_disk_path is not None:
save_images_to_disk(images, filtered_images, req, task_data)
seeds = [*range(req.seed, req.seed + len(images))]
if task_data.show_only_filtered_image or filtered_images is images:
return filtered_images, seeds
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,
):
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,
)
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
context.partial_x_samples = None
return images, user_stopped
def filter_images(req: GenerateImageRequest, task_data: TaskData, images: list, user_stopped):
if user_stopped:
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
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,
),
seed=seed,
)
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,
):
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)
for i, img in enumerate(images):
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}"})
del images
return partial_images
def on_image_step(x_samples, i, *args):
nonlocal last_callback_time
if context.test_diffusers:
context.partial_x_samples = (x_samples, args[0])
else:
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)
data_queue.put(json.dumps(progress))
step_callback()
if context.stop_processing:
raise UserInitiatedStop("User requested that we stop processing")
return on_image_step

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@ -1,383 +0,0 @@
"""server.py: FastAPI SD-UI Web Host.
Notes:
async endpoints always run on the main thread. Without they run on the thread pool.
"""
import datetime
import mimetypes
import os
import traceback
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
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",
}
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"]
):
response_headers.update(NOCACHE_HEADERS)
return False
return super().is_not_modified(response_headers, request_headers)
class SetAppConfigRequest(BaseModel, extra=Extra.allow):
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",
)
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.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, scan_for_malicious: bool = True):
return read_web_data_internal(key, scan_for_malicious=scan_for_malicious)
@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")
def render(req: dict):
return render_internal(req)
@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):
return stream_internal(task_id)
@server_api.get("/image/stop")
def stop(task: int):
return stop_internal(task)
@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("/")
def read_root():
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.")
# API implementations
def set_app_config_internal(req: SetAppConfigRequest):
config = app.getConfig()
if req.update_branch is not None:
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 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 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
try:
app.setConfig(config)
if req.render_devices:
app.update_render_threads()
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.startswith("cuda:"):
render_devices = render_devices.split(",")
config["render_devices"] = render_devices
def read_web_data_internal(key: str = None, **kwargs):
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":
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),
}
system_info["devices"]["config"] = config.get("render_devices", "auto")
return JSONResponse(system_info, headers=NOCACHE_HEADERS)
elif key == "models":
scan_for_malicious = kwargs.get("scan_for_malicious", True)
return JSONResponse(model_manager.getModels(scan_for_malicious), 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)
else:
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))
# Alive
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
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
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),
}
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 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
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,
)
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 ??
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 task.buffer_queue.empty() and not task.lock.locked():
if task.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")
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"}
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"}
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
try:
img_data = task.temp_images[img_id]
img_data.seek(0)
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))

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@ -1,575 +0,0 @@
"""task_manager.py: manage tasks dispatching and render threads.
Notes:
render_threads should be the only hard reference held by the manager to the threads.
Use weak_thread_data to store all other data using weak keys.
This will allow for garbage collection after the thread dies.
"""
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
import torch
from easydiffusion import device_manager
from easydiffusion.types import GenerateImageRequest, TaskData
from easydiffusion.utils import log
from sdkit.utils import gc
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
class ServerStates:
class Init(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.
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.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
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
@property
def status(self):
if self.lock.locked():
return "running"
if isinstance(self.error, StopAsyncIteration):
return "stopped"
if self.error:
return "error"
if not self.buffer_queue.empty():
return "buffer"
if self.response:
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:
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)
try:
# Create a list of expired keys to delete
to_delete = []
for key in self._base:
ttl, _ = self._base[key]
if self._is_expired(ttl):
to_delete.append(key)
# Remove Items
for key in to_delete:
(_, val) = self._base[key]
if isinstance(val, RenderTask):
log.debug(f"RenderTask {key} expired. Data removed.")
elif isinstance(val, SessionState):
log.debug(f"Session {key} expired. Data removed.")
else:
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()
def delete(self, key: Hashable) -> bool:
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
del self._base[key]
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)
try:
if key in self._base:
_, value = self._base.get(key)
self._base[key] = (self._get_ttl_time(ttl), value)
return True
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)
try:
self._base[key] = (self._get_ttl_time(ttl), value)
except Exception:
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)
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.")
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
tasks_queue = []
session_cache = DataCache()
task_cache = DataCache()
weak_thread_data = weakref.WeakKeyDictionary()
idle_event: threading.Event = threading.Event()
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 = []
for task_id in self._tasks_ids:
task = task_cache.tryGet(task_id)
if task:
tasks.append(task)
return tasks
def put(self, task, ttl=TASK_TTL):
task_id = id(task)
self._tasks_ids.append(task_id)
if not task_cache.put(task_id, task, ttl):
return False
while len(self._tasks_ids) > len(render_threads) * 2:
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.")
return None
if len(tasks_queue) <= 0:
manager_lock.release()
return None
task = None
try: # Select a render task.
for queued_task in tasks_queue:
if queued_task.render_device and renderer.context.device != queued_task.render_device:
# Is asking for a specific render device.
if is_alive(queued_task.render_device) > 0:
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.")
task = queued_task
break
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
break
if task is not None:
del tasks_queue[tasks_queue.index(task)]
return task
finally:
manager_lock.release()
def thread_render(device):
global current_state, current_state_error
from easydiffusion import model_manager, renderer
try:
renderer.init(device)
weak_thread_data[threading.current_thread()] = {
"device": renderer.context.device,
"device_name": renderer.context.device_name,
"alive": True,
}
current_state = ServerStates.LoadingModel
model_manager.load_default_models(renderer.context)
current_state = ServerStates.Online
except Exception as e:
log.error(traceback.format_exc())
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}")
model_manager.unload_all(renderer.context)
return
if isinstance(current_state_error, SystemExit):
current_state = ServerStates.Unavailable
return
task = thread_get_next_task()
if task is None:
idle_event.clear()
idle_event.wait(timeout=1)
continue
if task.error is not None:
log.error(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.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.")
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)
):
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)}")
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,
)
# 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.buffer_queue.put(json.dumps(task.response))
log.error(traceback.format_exc())
finally:
gc(renderer.context)
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!")
elif task.error is not None:
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}."
)
current_state = ServerStates.Online
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):
if update_ttl:
session_cache.keep(session_id, TASK_TTL)
session = session_cache.tryGet(session_id)
if not session:
session = SessionState(session_id)
session_cache.put(session_id, session, TASK_TTL)
return session
def get_devices():
devices = {
"all": {},
"active": {},
}
def get_device_info(device):
if device in ("cpu", "mps"):
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),
}
# list the compatible devices
cuda_count = torch.cuda.device_count()
for device in range(cuda_count):
device = f"cuda:{device}"
if not device_manager.is_device_compatible(device):
continue
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")})
# list the activated devices
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:
continue
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)
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:
continue
thread_device = weak_data["device"]
if thread_device != device:
continue
if rthread.is_alive():
nbr_alive += 1
return nbr_alive
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}")
try:
rthread = threading.Thread(target=thread_render, kwargs={"device": device})
rthread.daemon = True
rthread.name = THREAD_NAME_PREFIX + device
rthread.start()
render_threads.append(rthread)
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]:
log.error(f"{rthread}, {device}, error: {weak_thread_data[rthread]['error']}")
return False
if timeout <= 0:
return False
timeout -= 1
time.sleep(1)
return True
def stop_render_thread(device):
try:
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}")
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:
continue
thread_device = weak_data["device"]
if thread_device == device:
weak_data["alive"] = False
thread_to_remove = rthread
break
if thread_to_remove is not None:
render_threads.remove(rthread)
return True
finally:
manager_lock.release()
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}")
for device in devices_to_stop:
if is_alive(device) <= 0:
log.debug(f"{device} is not alive")
continue
if not stop_render_thread(device):
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.")
continue
if not start_render_thread(device):
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'
)
log.debug(f"active devices: {get_devices()['active']}")
def shutdown_event(): # Signal render thread to close on shutdown
global current_state_error
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.")
# 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}."
)
new_task = RenderTask(render_req, task_data)
if session.put(new_task, TASK_TTL):
# Use twice the normal timeout for adding user requests.
# Tries to force session.put to fail before tasks_queue.put would.
if manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT * 2):
try:
tasks_queue.append(new_task)
idle_event.set()
return new_task
finally:
manager_lock.release()
raise RuntimeError("Failed to add task to cache.")

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@ -1,111 +0,0 @@
from typing import Any, List, Union
from pydantic import BaseModel
class GenerateImageRequest(BaseModel):
prompt: str = ""
negative_prompt: str = ""
seed: int = 42
width: int = 512
height: int = 512
num_outputs: int = 1
num_inference_steps: int = 50
guidance_scale: float = 7.5
init_image: Any = None
init_image_mask: Any = None
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"
hypernetwork_strength: float = 0
lora_alpha: Union[float, List[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"
use_face_correction: Union[str, List[str]] = None # or "GFPGANv1.3"
use_upscale: Union[str, List[str]] = None
upscale_amount: int = 4 # or 2
latent_upscaler_steps: int = 10
use_stable_diffusion_model: Union[str, List[str]] = "sd-v1-4"
use_vae_model: Union[str, List[str]] = None
use_hypernetwork_model: Union[str, List[str]] = None
use_lora_model: Union[str, List[str]] = None
show_only_filtered_image: bool = False
block_nsfw: bool = False
output_format: str = "jpeg" # or "png" or "webp"
output_quality: int = 75
output_lossless: bool = False
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
model1: str = None
ratio: float = None
out_path: str = "mix"
use_fp16 = True
class Image:
data: str # base64
seed: int
is_nsfw: bool
path_abs: str = None
def __init__(self, data, seed):
self.data = data
self.seed = seed
def json(self):
return {
"data": self.data,
"seed": self.seed,
"path_abs": self.path_abs,
}
class Response:
render_request: GenerateImageRequest
task_data: TaskData
images: list
def __init__(self, render_request: GenerateImageRequest, task_data: TaskData, images: list):
self.render_request = render_request
self.task_data = task_data
self.images = images
def json(self):
del self.render_request.init_image
del self.render_request.init_image_mask
res = {
"status": "succeeded",
"render_request": self.render_request.dict(),
"task_data": self.task_data.dict(),
"output": [],
}
for image in self.images:
res["output"].append(image.json())
return res
class UserInitiatedStop(Exception):
pass

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@ -1,8 +0,0 @@
import logging
log = logging.getLogger("easydiffusion")
from .save_utils import (
save_images_to_disk,
get_printable_request,
)

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@ -1,328 +0,0 @@
import os
import re
import time
import regex
from datetime import datetime
from functools import reduce
from easydiffusion import app
from easydiffusion.types import GenerateImageRequest, TaskData
from numpy import base_repr
from sdkit.utils import save_dicts, save_images
filename_regex = re.compile("[^a-zA-Z0-9._-]")
img_number_regex = re.compile("([0-9]{5,})")
# 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",
"use_embedding_models": "Embedding models",
"tiling": "Seamless Tiling",
"use_face_correction": "Use Face Correction",
"use_upscale": "Use Upscaling",
"upscale_amount": "Upscale By",
"latent_upscaler_steps": "Latent Upscaler Steps",
}
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))
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,
)
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,
)
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,
)
def get_metadata_entries_for_request(req: GenerateImageRequest, task_data: TaskData):
metadata = get_printable_request(req, task_data)
# 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(",")
if is_txt_format:
def format_value(value):
if isinstance(value, list):
return ", ".join([ str(it) for it in value ])
return value
metadata = {
TASK_TEXT_MAPPING[key]: format_value(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
return entries
def get_printable_request(req: GenerateImageRequest, task_data: TaskData):
req_metadata = req.dict()
task_data_metadata = task_data.dict()
app_config = app.getConfig()
using_diffusers = app_config.get("test_diffusers", False)
# 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]
elif key == "use_embedding_models" and using_diffusers:
embeddings_extensions = {".pt", ".bin", ".safetensors"}
def scan_directory(directory_path: str):
used_embeddings = []
for entry in os.scandir(directory_path):
if entry.is_file():
entry_extension = os.path.splitext(entry.name)[1]
if entry_extension not in embeddings_extensions:
continue
embedding_name_regex = regex.compile(r"(^|[\s,])" + regex.escape(os.path.splitext(entry.name)[0]) + r"([+-]*$|[\s,]|[+-]+[\s,])")
if embedding_name_regex.search(req.prompt) or embedding_name_regex.search(req.negative_prompt):
used_embeddings.append(entry.path)
elif entry.is_dir():
used_embeddings.extend(scan_directory(entry.path))
return used_embeddings
used_embeddings = scan_directory(os.path.join(app.MODELS_DIR, "embeddings"))
metadata["use_embedding_models"] = used_embeddings if len(used_embeddings) > 0 else None
# 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"]
if not using_diffusers:
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]
return metadata
def make_filename_callback(
filename_format: str,
req: GenerateImageRequest,
task_data: TaskData,
folder_img_number: int,
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}"
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))

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@ -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
}
}

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@ -1,188 +1,107 @@
<!DOCTYPE html>
<html>
<head>
<title>Easy Diffusion</title>
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="theme-color" content="#673AB6">
<link rel="icon" type="image/png" href="/media/images/favicon-16x16.png" sizes="16x16">
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<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">
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<script src="/media/jquery-3.6.1.min.js"></script>
<script src="/media/drawingboard.min.js"></script>
</head>
<body>
<div id="container">
<div id="top-nav">
<div id="logo">
<h1>
<img id="logo_img" src="/media/images/icon-512x512.png" >
Easy Diffusion
<small><span id="version">v2.5.46</span> <span id="updateBranchLabel"></span></small>
</h1>
<h1>Stable Diffusion UI <small>v2.2 <span id="updateBranchLabel"></span></small></h1>
</div>
<div id="server-status">
<div id="server-status-color"></div>
<span id="server-status-msg">Stable Diffusion is starting..</span>
</div>
<div id="tab-container" class="tab-container">
<span id="tab-main" class="tab active">
<span><i class="fa fa-image icon"></i> Generate</span>
</span>
<span id="tab-settings" class="tab">
<span><i class="fa fa-gear icon"></i> Settings</span>
</span>
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<ul id="top-nav-items">
<li class="dropdown">
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</span>
</div>
<ul id="community-links" class="dropdown-content">
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<li><a href="https://discord.com/invite/u9yhsFmEkB" target="_blank"><i class="fa-brands fa-discord fa-fw"></i> Discord user community</a></li>
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</ul>
</li>
<li class="dropdown">
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<div id="system-settings" class="panel-box settings-box dropdown-content">
<ul id="system-settings-entries">
<li><b class="settings-subheader">System Settings</b></li>
<br/>
<li><input id="save_to_disk" name="save_to_disk" type="checkbox"> <label for="save_to_disk">Automatically save to <input id="diskPath" name="diskPath" size="40" disabled></label></li>
<li><input id="sound_toggle" name="sound_toggle" type="checkbox" checked> <label for="sound_toggle">Play sound on task completion</label></li>
<li><input id="turbo" name="turbo" type="checkbox" checked> <label for="turbo">Turbo mode <small>(generates images faster, but uses an additional 1 GB of GPU memory)</small></label></li>
<li><input id="use_cpu" name="use_cpu" type="checkbox"> <label for="use_cpu">Use CPU instead of GPU <small>(warning: this will be *very* slow)</small></label></li>
<li><input id="use_full_precision" name="use_full_precision" type="checkbox"> <label for="use_full_precision">Use full precision <small>(for GPU-only. warning: this will consume more VRAM)</small></label></li>
<!-- <li><input id="allow_nsfw" name="allow_nsfw" type="checkbox"> <label for="allow_nsfw">Allow NSFW Content (You confirm you are above 18 years of age)</label></li> -->
<br/>
<li><input id="use_beta_channel" name="use_beta_channel" type="checkbox"> <label for="use_beta_channel">🔥Beta channel. Get the latest features immediately (but could be less stable). Please restart the program after changing this.</label></li>
</ul>
</div>
</li>
</ul>
</div>
<div id="tab-content-wrapper">
<div id="tab-content-main" class="tab-content active flex-container">
<div id="editor">
<div class="flex-container">
<div id="editor" class="col-fixed-10">
<div id="server-status">
<div id="server-status-color"></div>
<span id="server-status-msg">Stable Diffusion is starting..</span>
</div>
<div id="editor-inputs">
<div id="editor-inputs-prompt" class="row">
<div id="prompt-toolbar" class="split-toolbar">
<div id="prompt-toolbar-left" class="toolbar-left">
<label for="prompt"><b>Enter Prompt</b></label> <small>or</small> <button id="promptsFromFileBtn" class="tertiaryButton smallButton">Load from a file</button>
</div>
<div id="prompt-toolbar-right" class="toolbar-right">
<button id="image-modifier-dropdown" class="tertiaryButton smallButton">+ Image Modifiers</button>
<button id="embeddings-button" class="tertiaryButton smallButton displayNone">+ Embedding</button>
</div>
</div>
<label for="prompt">Prompt</label>
<textarea id="prompt" class="col-free">a photograph of an astronaut riding a horse</textarea>
<input id="prompt_from_file" name="prompt_from_file" type="file" /> <!-- hidden -->
<label for="negative_prompt" class="collapsible" id="negative_prompt_handle">
Negative Prompt
<a href="https://github.com/easydiffusion/easydiffusion/wiki/Writing-prompts#negative-prompts" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top">Click to learn more about Negative Prompts</span></i></a>
<small>(optional)</small>
</label>
<button id="negative-embeddings-button" class="tertiaryButton smallButton displayNone">+ Embedding</button>
<div class="collapsible-content">
<textarea id="negative_prompt" name="negative_prompt" placeholder="list the things to remove from the image (e.g. fog, green)"></textarea>
</div>
</div>
<div id="editor-inputs-init-image" class="row">
<label for="init_image">Initial Image (img2img) <small>(optional)</small> </label>
<label for="init_image"><b>Initial Image:</b> (optional) </label> <input id="init_image" name="init_image" type="file" /><br/>
<div id="init_image_preview_container" class="image_preview_container">
<div id="init_image_wrapper">
<img id="init_image_preview" src="" crossorigin="anonymous" />
<span id="init_image_size_box" class="img_bottom_label"></span>
<button class="init_image_clear image_clear_btn"><i class="fa-solid fa-xmark"></i></button>
</div>
<div id="init_image_buttons">
<div class="button">
<i class="fa-regular fa-folder-open"></i>
Browse
<input id="init_image" name="init_image" type="file" />
</div>
<div id="init_image_button_draw" class="button">
<i class="fa-solid fa-pencil"></i>
Draw
</div>
<div id="inpaint_button_container">
<div id="init_image_button_inpaint" class="button">
<i class="fa-solid fa-paintbrush"></i>
Inpaint
</div>
<input id="enable_mask" name="enable_mask" type="checkbox">
</div>
</div>
<img id="init_image_preview" src="" width="100" height="100" />
<button class="init_image_clear image_clear_btn">X</button>
<br/>
<input id="enable_mask" name="enable_mask" type="checkbox"> <label for="enable_mask">In-Painting (beta) <small>(select the area which the AI will paint into)</small></label>
<div id="inpaintingEditor"></div>
</div>
<div id="apply_color_correction_setting" class="pl-5"><input id="apply_color_correction" name="apply_color_correction" type="checkbox"> <label for="apply_color_correction">Preserve color profile <small>(helps during inpainting)</small></label></div>
</div>
<div id="editor-inputs-tags-container" class="row">
<label>Image Modifiers <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip 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: <small>(click an Image Modifier to remove it)</small></label>
<div id="editor-inputs-tags-list"></div>
</div>
<button id="makeImage" class="primaryButton">Make Image</button>
<div id="render-buttons">
<button id="stopImage" class="secondaryButton">Stop All</button>
<button id="pause"><i class="fa-solid fa-pause"></i> Pause All</button>
<button id="resume"><i class="fa-solid fa-play"></i> Resume</button>
</div>
<button id="makeImage">Make Image</button>
<button id="stopImage" class="secondaryButton">Stop All</button>
</div>
<span class="line-separator"></span>
<div class="line-separator">&nbsp;</div>
<div id="editor-settings" class="settings-box panel-box">
<h4 class="collapsible">
Image Settings
<i id="reset-image-settings" class="fa-solid fa-arrow-rotate-left section-button">
<span class="simple-tooltip top-left">
Reset Image Settings
</span>
</i>
</h4>
<div id="editor-settings-entries" class="collapsible-content">
<div><table>
<tr><b class="settings-subheader">Image Settings</b></tr>
<tr class="pl-5"><td><label for="seed">Seed:</label></td><td><input id="seed" name="seed" size="10" value="0" onkeypress="preventNonNumericalInput(event)"> <input id="random_seed" name="random_seed" type="checkbox" checked><label for="random_seed">Random</label></td></tr>
<tr class="pl-5"><td><label for="num_outputs_total">Number of Images:</label></td><td><input id="num_outputs_total" name="num_outputs_total" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label><small>(total)</small></label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label for="num_outputs_parallel"><small>(in parallel)</small></label></td></tr>
<tr class="pl-5"><td><label for="stable_diffusion_model">Model:</label></td><td 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>
<a href="https://github.com/easydiffusion/easydiffusion/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 class="diffusers-restart-needed">
<input id="clip_skip" name="clip_skip" type="checkbox">
<a href="https://github.com/easydiffusion/easydiffusion/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="" />
<a href="https://github.com/easydiffusion/easydiffusion/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>
<select id="sampler_name" name="sampler_name">
<option value="plms">PLMS</option>
<option value="ddim">DDIM</option>
<option value="heun">Heun</option>
<option value="euler">Euler</option>
<option value="euler_a" selected>Euler Ancestral</option>
<option value="dpm2">DPM2</option>
<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">DPM++ 2s Ancestral (Karras)</option>
<option value="dpmpp_2m">DPM++ 2m (Karras)</option>
<option value="dpmpp_2m_sde" class="diffusers-only">DPM++ 2m SDE (Karras)</option>
<option value="dpmpp_sde">DPM++ SDE (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>
<div id="editor-settings" class="panel-box settings-box">
<h4 class="collapsible">Image Settings</h4>
<ul id="editor-settings-entries" class="collapsible-content">
<li><b class="settings-subheader">Image Settings</b></li>
<li class="pl-5"><label for="seed">Seed:</label> <input id="seed" name="seed" size="10" value="30000"> <input id="random_seed" name="random_seed" type="checkbox" checked> <label for="random_seed">Random Image</label></li>
<li class="pl-5"><label for="num_outputs_total">Number of images to make:</label> <input id="num_outputs_total" name="num_outputs_total" value="1" size="1"> <label for="num_outputs_parallel">Generate in parallel:</label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1"> (images at once)</li>
<li id="samplerSelection" class="pl-5"><label for="sampler">Sampler:</label>
<select id="sampler" name="sampler">
<option value="plms" selected>plms</option>
<option value="ddim">ddim</option>
<option value="heun">heun</option>
<option value="euler">euler</option>
<option value="euler_a">euler_a</option>
<option value="dpm2">dpm2</option>
<option value="dpm2_a">dpm2_a</option>
<option value="lms">lms</option>
</select>
<a href="https://github.com/easydiffusion/easydiffusion/wiki/How-to-Use#samplers" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about samplers</span></i></a>
</td></tr>
<tr class="pl-5"><td><label>Image Size: </label></td><td>
</li>
<li class="pl-5"><label>Image Size: </label>
<select id="width" name="width" value="512">
<option value="128">128 (*)</option>
<option value="192">192</option>
@ -227,457 +146,84 @@
<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" type="number" min="1" step="1" style="width: 42pt" 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 class="diffusers-restart-needed">
<div class="model_entries"></div>
<button class="add_model_entry"><i class="fa-solid fa-plus"></i> add another LoRA</button>
</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="" />
</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\.]+$" onkeypress="preventNonNumericalInput(event)"><br/></td>
</tr>
<tr id="tiling_container" class="pl-5">
<td><label for="tiling">Seamless Tiling:</label></td>
<td class="diffusers-restart-needed">
<select id="tiling" name="tiling">
<option value="none" selected>None</option>
<option value="x">Horizontal</option>
<option value="y">Vertical</option>
<option value="xy">Both</option>
</select>
<a href="https://github.com/easydiffusion/easydiffusion/wiki/Seamless-Tiling" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about Seamless Tiling</span></i></a>
</td>
</tr>
<tr class="pl-5"><td><label for="output_format">Output Format:</label></td><td>
<select id="output_format" name="output_format">
<option value="jpeg" selected>jpeg</option>
<option value="png">png</option>
<option value="webp">webp</option>
</select>
<span id="output_lossless_container" class="displayNone">
<input id="output_lossless" name="output_lossless" type="checkbox"><label for="output_lossless">Lossless</label>
</span>
</td></tr>
<tr class="pl-5" id="output_quality_row"><td><label for="output_quality">Image Quality:</label></td><td>
<input id="output_quality_slider" name="output_quality" class="editor-slider" value="75" type="range" min="10" max="95"> <input id="output_quality" name="output_quality" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)">
</td></tr>
</table></div>
<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"><label for="num_inference_steps">Number of inference steps:</label> <input id="num_inference_steps" name="num_inference_steps" size="4" value="50"></li>
<li class="pl-5"><label for="guidance_scale_slider">Guidance Scale:</label> <input id="guidance_scale_slider" name="guidance_scale_slider" class="editor-slider" value="75" type="range" min="10" max="500"> <input id="guidance_scale" name="guidance_scale" size="4"></li>
<li class="pl-5"><span id="prompt_strength_container"><label for="prompt_strength_slider">Prompt Strength:</label> <input id="prompt_strength_slider" name="prompt_strength_slider" class="editor-slider" value="80" type="range" min="0" max="99"> <input id="prompt_strength" name="prompt_strength" size="4"><br/></span></li>
<br/>
<li><b class="settings-subheader">Prompt Settings</b></li>
<li class="pl-5"><label for="negative_prompt">Negative Prompt:</label> <input id="negative_prompt" name="negative_prompt" size="55"></li>
<br/>
<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 of the image <small>(uses more VRAM, slightly slower image creation)</small></label></li>
<li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox" checked> <label for="use_face_correction">Fix incorrect faces and eyes <small>(uses GFPGAN)</small></label></li>
<li class="pl-5">
<input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">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>
</select>
with
<input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Upscale the image to 4x resolution using </label>
<select id="upscale_model" name="upscale_model">
<option value="RealESRGAN_x4plus" selected>RealESRGAN_x4plus</option>
<option value="RealESRGAN_x4plus_anime_6B">RealESRGAN_x4plus_anime_6B</option>
<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>
</div>
<br/>
<li><small>The system-related settings have been moved to the top-right corner.</small></li>
</ul>
</div>
<label><small><b>Note:</b> The Image Modifiers section has moved to the <code>+ Image Modifiers</code> button at the top, just below the Prompt textbox.</small></label>
<div id="editor-modifiers" class="panel-box">
<h4 class="collapsible">Image Modifiers (art styles, tags etc)</h4>
<div id="editor-modifiers-entries" class="collapsible-content">
<label for="preview-image">Image Style:</label>
<select id="preview-image" name="preview-image" value="portrait">
<option value="portrait" selected="">Face</option>
<option value="landscape">Landscape</option>
</select>
&nbsp;
<label for="modifier-card-size-slider">Thumbnail Size:</label>
<input id="modifier-card-size-slider" name="modifier-card-size-slider" value="0" type="range" min="-3" max="5">
</div>
</div>
</div>
<div id="preview" class="col-free">
<div id="initial-text">
Type a prompt and press the "Make Image" button.<br/><br/>You can set an "Initial Image" if you want to guide the AI.<br/><br/>
You can also add modifiers like "Realistic", "Pencil Sketch", "ArtStation" etc by browsing through the "Image Modifiers" section
and selecting the desired modifiers.<br/><br/>
Click "Image Settings" for additional settings like seed, image size, number of images to generate etc.<br/><br/>Enjoy! :)
Type a prompt and press the "Make Image" button.<br/><br/>You can set an "Initial Image" if you want to guide the AI.<br/><br/>You can also add modifiers like "Realistic", "Pencil Sketch", "ArtStation" etc by browsing through the "Image Modifiers" section and selecting the desired modifiers.<br/><br/>Click "Advanced Settings" for additional settings like seed, image size, number of images to generate etc.<br/><br/>Enjoy! :)
</div>
<div id="preview-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>
</div>
</div>
<div id="tab-content-settings" class="tab-content">
<div id="system-settings" class="tab-content-inner">
<h1>System Settings</h1>
<div class="parameters-table" id="system-settings-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">
<table>
<tr><td><label>Processor:</label></td><td id="system-info-cpu" class="value"></td></tr>
<tr><td><label>Compatible Graphics Cards (all):</label></td><td id="system-info-gpus-all" class="value"></td></tr>
<tr><td></td><td>&nbsp;</td></tr>
<tr><td><label>Used for rendering 🔥:</label></td><td id="system-info-rendering-devices" class="value"></td></tr>
<tr><td><label>Server Addresses <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">You can access Stable Diffusion UI from other devices using these addresses</span></i> :</label></td><td id="system-info-server-hosts" class="value"></td></tr>
</table>
</div>
</div>
</div>
</div>
<div id="tab-content-about" class="tab-content">
<div class="tab-content-inner">
<div class="float-container">
<div class="float-child">
<h1>Help</h1>
<ul id="help-links">
<li><span class="help-section">Using the software</span>
<ul>
<li> <a href="https://github.com/easydiffusion/easydiffusion/wiki/How-To-Use" target="_blank"><i class="fa-solid fa-book fa-fw"></i> How to use</a>
<li> <a href="https://github.com/easydiffusion/easydiffusion/wiki/UI-Overview" target="_blank"><i class="fa-solid fa-list fa-fw"></i> UI Overview</a>
<li> <a href="https://github.com/easydiffusion/easydiffusion/wiki/Writing-Prompts" target="_blank"><i class="fa-solid fa-pen-to-square fa-fw"></i> Writing prompts</a>
<li> <a href="https://github.com/easydiffusion/easydiffusion/wiki/Inpainting" target="_blank"><i class="fa-solid fa-paintbrush fa-fw"></i> Inpainting</a>
<li> <a href="https://github.com/easydiffusion/easydiffusion/wiki/Run-on-Multiple-GPUs" target="_blank"><i class="fa-solid fa-paintbrush fa-fw"></i> Run on Multiple GPUs</a>
</ul>
<li><span class="help-section">Installation</span>
<ul>
<li> <a href="https://github.com/easydiffusion/easydiffusion/wiki/Troubleshooting" target="_blank"><i class="fa-solid fa-circle-question fa-fw"></i> Troubleshooting</a>
</ul>
<li><span class="help-section">Downloadable Content</span>
<ul>
<li> <a href="https://github.com/easydiffusion/easydiffusion/wiki/Custom-Models" target="_blank"><i class="fa-solid fa-images fa-fw"></i> Custom Models</a>
<li> <a href="https://github.com/easydiffusion/easydiffusion/wiki/UI-Plugins" target="_blank"><i class="fa-solid fa-puzzle-piece fa-fw"></i> UI Plugins</a>
<li> <a href="https://github.com/easydiffusion/easydiffusion/wiki/VAE-Variational-Auto-Encoder" target="_blank"><i class="fa-solid fa-hand-sparkles fa-fw"></i> VAE Variational Auto Encoder</a>
</ul>
</ul>
</div>
<div class="float-child">
<h1>Community</h1>
<ul id="community-links">
<li><a href="https://discord.com/invite/u9yhsFmEkB" target="_blank"><i class="fa-brands fa-discord fa-fw"></i> Discord user community</a></li>
<li><a href="https://www.reddit.com/r/StableDiffusionUI/" target="_blank"><i class="fa-brands fa-reddit fa-fw"></i> Reddit community</a></li>
<li><a href="https://github.com/easydiffusion/easydiffusion" target="_blank"><i class="fa-brands fa-github fa-fw"></i> Source code on GitHub</a></li>
</ul>
</div>
</div>
</div>
</div>
</div>
<div class="popup" id="splash-screen" data-version="1">
<div>
<i class="close-button fa-solid fa-xmark"></i>
<img class="splash-img" src="/media/images/icon-512x512.png" width="128" height="128">
<h1>Diffusers Tech Preview</h1>
<p>The Diffusers Tech Preview allows early access to the new features based on <a href="https://huggingface.co/docs/diffusers/index" target="_blank">Diffusers</a>.</p>
<p>This is under active development, and is missing a few features. It is experimental! Please report any bugs to the #beta channel in our <a href="https://discord.gg/QUcNZufQNZ" target="_blank">Discord</a> server!</p>
<h2>New upcoming features in our new engine</h2>
<ul>
<li><a href="https://huggingface.co/blog/lora" target="_blank">LORA</a> support - Place LORA files in the <tt>models/lora</tt> folder.</li>
<li><a href="https://github.com/damian0815/compel/blob/main/Reference.md" target="_blank">Compel Prompt Parser</a> - New, more powerful parser. In short:
<ul>
<li> no limit to the length of prompts (i.e. long prompts are supported)</li>
<li> Use <tt>+</tt> and <tt>-</tt> to increase/decrease the weight. E.g. <tt>apple</tt>, <tt>apple+</tt>, <tt>apple++</tt>, <tt>apple+++</tt>,
or <tt>apple-</tt>, <tt>apple--</tt> for different weights.</li>
<li> Use exact weights - 0.0 to 1.0 reduces the weight, 1.0 to 2.0 increases the weight.
Think of it like a multiplier, like 1.5x or 0.5x: E.g. <tt>(apple)0.8 falling from a tree</tt>,
<tt>(apple)1.5 falling from a tree</tt>, <tt>(apple falling)1.4 from a tree</tt></li>
<li> You can group tokens together using parentheses/round-brackets. E.g. <tt>(apple falling)++
from a tree</tt>. Nested parentheses are supported.</li>
</ul>
This clarifies a few things:
<ul>
<li> colon (<tt>:</tt>) is NOT used for blending. Neither is it used for weights. It has no impact and
will be considered a part of the prompt.</li>
<li> <tt>(())</tt> and <tt>[]</tt> do not affect the prompt's weights.</li>
</ul>
</li>
<li> More choices for img2img samplers</li>
<li> Support for official inpainting models</li>
<li> Generate images that tile seamlessly</li>
<li> <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Clip-Skip" target="_blank">Clip Skip</a> support allows to skip the last CLIP layer (recommended by some LORA models)</li>
<li> New samplers: DDPM and DEIS</li>
<li> Memory optimizations that allow the use of 2GB GPUs</li>
</ul>
<h2>Known issues</h2>
<ul>
<li> Some LoRA consistently fail to load in EasyDiffusion</li>
<li> Some LoRA are far more sensitive to alpha (compared to a11)</li>
<li> Hangs sometimes on "compel is ready", while making the token.</li>
<li> Some custom inpainting models don't work</li>
<li> These samplers don't work yet: Unipc SNR, Unipc TQ, Unipc SNR2, DPM++ 2s Ancestral, DPM++ SDE, DPM Fast, DPM Adaptive, DPM2</li>
<li> Hypernetwork doesn't work</li>
<li> The time remaining in browser differs from the one in the console</li>
</ul>
</div>
</div>
<dialog id="download-images-dialog">
<div class="dialog-header">
<div class="dialog-header-left">
<h4>Download all images</h4>
<span></span>
</div>
<div>
<i id="download-images-close-button" class="fa-solid fa-xmark fa-lg"></i>
</div>
</div>
<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>
<div class="center">
<button id="save-all-images" class="primaryButton"><i class="fa-solid fa-images"></i> Start download</button>
</div>
</dialog>
<div id="save-settings-config" class="popup">
<div>
<i class="close-button fa-solid fa-xmark"></i>
<h1>Save Settings Configuration</h1>
<p>Select which settings should be remembered when restarting the browser</p>
<table id="save-settings-config-table" class="form-table">
</table>
</div>
</div>
<div id="editor-modifiers">
<div id="editor-modifiers-header" class="dialog-header">
<div id="modifiers-header-left" class="dialog-header-left">
<h4>Image Modifiers</h4>
<span>(drawing style, camera, etc.)</span>
</div>
<div id="modifiers-header-right">
<i id="modifier-settings-btn" class="fa-solid fa-gear section-button">
<span class="simple-tooltip left">
Add Custom Modifiers
</span>
</i>
<i id="modifiers-container-size-btn" class="fa-solid fa-expand"></i>
<i id="modifiers-close-button" class="fa-solid fa-xmark fa-lg"></i>
</div>
</div>
<div id="editor-modifiers-subheader">
<div id="modifiers-action-collapsibles-btn">
<i class="modifiers-action-icon fa-solid fa-square-plus"></i>
<span class="modifiers-action-text">
Expand Categories
</span>
</div>
<div>
<label for="preview-image">Image Style:</label>
<select id="preview-image" name="preview-image" value="portrait">
<option value="portrait" selected="">Face</option>
<option value="landscape">Landscape</option>
</select>
</div>
<div>
<label for="modifier-card-size-slider">Thumbnail Size:</label>
<input id="modifier-card-size-slider" name="modifier-card-size-slider" value="0" type="range" min="-2" max="3">
</div>
</div>
<div id="editor-modifiers-entries" class="collapsible-content"></div>
</div>
<dialog id="modifier-settings-config">
<div id="modifier-settings-header" class="dialog-header">
<div id="modifier-settings-header-left" class="dialog-header-left">
<h4>Custom Modifiers</h4>
<span>Set your custom modifiers (one per line)</span>
</div>
<div id="modifier-settings-header-right">
<i id="modifier-settings-close-button" class="fa-solid fa-xmark fa-lg"></i>
</div>
</div>
<textarea id="custom-modifiers-input" placeholder="Enter your custom modifiers, one-per-line" spellcheck="false"></textarea>
<div>
<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>
</div>
</dialog>
<dialog id="embeddings-dialog">
<div id="embeddings-dialog-header" class="dialog-header">
<div id="embeddings-dialog-header-left" class="dialog-header-left">
<h4>Embeddings</h4>
<span>
<span class="displayNone" id="positive-embedding-text"> Add embeddings to the prompt (click) or negative prompt (shift-click)</span>
<span class="displayNone" id="negative-embedding-text"> Add embeddings to the negative prompt</span>
<span>
</div>
<div id="embeddings-dialog-header-right">
<i id="embeddings-dialog-close-button" class="fa-solid fa-xmark fa-lg"></i>
</div>
</div>
<div>
<button id="embeddings-action-collapsibles-btn" class="tertiaryButton smallButton">
<i class="embeddings-action-icon fa-solid fa-square-plus"></i>
<span class="embeddings-action-text">Expand Categories</span>
</button>
<i class="fa-solid fa-magnifying-glass"></i>
<input id="embeddings-search-box" type="text" spellcheck="false" autocomplete="off" placeholder="Search...">
<span style="float:right;"><label>Mode:</label>&nbsp;<select id="embeddings-mode"><option value="insert">Insert at cursor position</option><option value="append">Append at the end</option></select>
</div>
<div id="embeddings-list">
</div>
</div>
</dialog>
<div id="image-editor" class="popup image-editor-popup">
<div>
<i class="close-button fa-solid fa-xmark"></i>
<h1>Image Editor</h1>
<div class="flex-container">
<div class="editor-controls-left"></div>
<div class="editor-controls-center">
<div></div>
</div>
<div class="editor-controls-right">
<div></div>
</div>
<div id="preview-tools">
<button id="clear-all-previews" class="secondaryButton"><i class="fa-solid fa-trash-can"></i> Clear All</button>
</div>
</div>
</div>
<div id="image-inpainter" class="popup image-editor-popup">
<div>
<i class="close-button fa-solid fa-xmark"></i>
<h1>Inpainter</h1>
<div class="flex-container">
<div class="editor-controls-left"></div>
<div class="editor-controls-center">
<div></div>
</div>
<div class="editor-controls-right">
<div></div>
</div>
</div>
</div>
</div>
<div class="line-separator">&nbsp;</div>
<div id="footer-spacer"></div>
<div id="footer">
<div class="line-separator">&nbsp;</div>
<p>If you found this project useful and want to help keep it alive, please <a href="https://ko-fi.com/cmdr2_stablediffusion_ui" target="_blank"><img src="/media/images/kofi.png" id="coffeeButton"></a> to help cover the cost of development and maintenance! Thank you for your support!</p>
<p>Please feel free to join the <a href="https://discord.com/invite/u9yhsFmEkB" target="_blank">discord community</a> or <a href="https://github.com/easydiffusion/easydiffusion/issues" target="_blank">file an issue</a> if you have any problems or suggestions in using this interface.</p>
<div id="footer" class="panel-box">
<p>If you found this project useful and want to help keep it alive, please <a href="https://ko-fi.com/cmdr2_stablediffusion_ui" target="_blank"><img src="media/kofi.png" id="coffeeButton"></a> to help cover the cost of development and maintenance! Thank you for your support!</p>
<p>Please feel free to join the <a href="https://discord.com/invite/u9yhsFmEkB" target="_blank">discord community</a> or <a href="https://github.com/cmdr2/stable-diffusion-ui/issues" target="_blank">file an issue</a> if you have any problems or suggestions in using this interface.</p>
<div id="footer-legal">
<p><b>Disclaimer:</b> The authors of this project are not responsible for any content generated using this interface.</p>
<p>This license of this software forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, <br/>spread misinformation and target vulnerable groups. For the full list of restrictions please read <a href="https://github.com/easydiffusion/easydiffusion/blob/main/LICENSE" target="_blank">the license</a>.</p>
<p>This license of this software forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, <br/>spread misinformation and target vulnerable groups. For the full list of restrictions please read <a href="https://github.com/cmdr2/stable-diffusion-ui/blob/main/LICENSE" target="_blank">the license</a>.</p>
<p>By using this software, you consent to the terms and conditions of the license.</p>
</div>
</div>
</div>
</body>
<script src="media/js/utils.js"></script>
<script src="media/js/engine.js"></script>
<script src="media/js/parameters.js"></script>
<script src="media/js/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/plugins.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 src="media/main.js?v=21"></script>
<script>
async function init() {
await initSettings()
await getModels(false)
await getAppConfig()
await loadUIPlugins()
await loadModifiers()
await getSystemInfo()
// await initPlugins()
await getDiskPath()
await getAppConfig()
SD.init({
events: {
statusChange: setServerStatus,
idle: onIdle,
ping: tunnelUpdate
}
})
splashScreen()
setInterval(healthCheck, HEALTH_PING_INTERVAL * 1000)
healthCheck()
// load models again, but scan for malicious this time
await getModels(true)
// playSound()
playSound()
}
init()

View File

@ -1,12 +0,0 @@
from easydiffusion import model_manager, app, server
from easydiffusion.server import server_api # required for uvicorn
server.init()
# Init the app
model_manager.init()
app.init()
app.init_render_threads()
# start the browser ui
app.open_browser()

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@ -1,84 +0,0 @@
/* Auto-Settings Styling */
#auto_save_settings ~ button {
margin: 5px;
}
#auto_save_settings:not(:checked) ~ button {
display: none;
}
.form-table {
margin: auto;
}
.form-table th {
padding-top: 15px;
padding-bottom: 5px;
}
.form-table td:first-child > *,
.form-table th:first-child > * {
float: right;
white-space: nowrap;
}
.form-table td:last-child > *,
.form-table th:last-child > * {
float: left;
}
.parameters-table {
display: flex;
flex-direction: column;
gap: 1px;
}
.parameters-table > div {
background: var(--background-color2);
display: flex;
padding: 0px 4px;
}
.parameters-table > div > div {
padding: 10px;
display: flex;
align-items: center;
justify-content: center;
}
.parameters-table small {
color: rgb(153, 153, 153);
}
.parameters-table > div > div:nth-child(1) {
font-size: 20px;
width: 45px;
}
.parameters-table > div > div:nth-child(2) {
flex: 1;
flex-direction: column;
text-align: left;
justify-content: center;
align-items: start;
gap: 4px;
}
.parameters-table > div > div:nth-child(3) {
text-align: right;
}
.parameters-table > div:first-child {
border-top-left-radius: 12px;
border-top-right-radius: 12px;
}
.parameters-table > div:last-child {
border-bottom-left-radius: 12px;
border-bottom-right-radius: 12px;
}
.parameters-table .fa-fire,
.parameters-table .fa-bolt {
color: #F7630C;
}

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@ -1,40 +0,0 @@
/* work-sans-regular - latin */
@font-face {
font-family: 'Work Sans';
font-style: normal;
font-weight: 400;
src: local('Work Sans'),
url('/media/fonts/work-sans-v18-latin-regular.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
url('/media/fonts/work-sans-v18-latin-regular.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
}
/* work-sans-600 - latin */
@font-face {
font-family: 'Work Sans';
font-style: normal;
font-weight: 600;
src: local('Work Sans'),
url('/media/fonts/work-sans-v18-latin-600.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
url('/media/fonts/work-sans-v18-latin-600.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
}
/* work-sans-700 - latin */
@font-face {
font-family: 'Work Sans';
font-style: normal;
font-weight: 700;
src: local('Work Sans'),
url('/media/fonts/work-sans-v18-latin-700.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
url('/media/fonts/work-sans-v18-latin-700.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
}
/* work-sans-800 - latin */
@font-face {
font-family: 'Work Sans';
font-style: normal;
font-weight: 800;
src: local('Work Sans'),
url('/media/fonts/work-sans-v18-latin-800.woff2') format('woff2'), /* Chrome 26+, Opera 23+, Firefox 39+ */
url('/media/fonts/work-sans-v18-latin-800.woff') format('woff'); /* Chrome 6+, Firefox 3.6+, IE 9+, Safari 5.1+ */
}

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@ -1,232 +0,0 @@
.editor-controls-left {
padding-left: 32px;
text-align: left;
padding-bottom: 20px;
max-width: min-content;
}
.editor-options-container {
display: flex;
row-gap: 10px;
}
.editor-options-container > * {
flex: 1;
display: flex;
justify-content: center;
align-items: center;
}
.editor-options-container > * > * {
position: inherit;
width: 32px;
height: 32px;
border-radius: 16px;
background: var(--background-color3);
cursor: pointer;
transition: opacity 0.25s;
}
.editor-options-container > * > *:hover {
opacity: 0.75;
}
.editor-options-container > * > *.active {
border: 1px solid #3584e4;
}
.image_editor_opacity .editor-options-container > * > *:not(.active) {
border: 1px solid var(--background-color3);
}
.image_editor_color .editor-options-container {
flex-wrap: wrap;
}
.image_editor_color .editor-options-container > * {
flex: 20%;
}
.image_editor_color .editor-options-container > * > * {
position: relative;
}
.image_editor_color .editor-options-container > * > *.active::before {
content: "\f00c";
display: var(--fa-display,inline-block);
font-style: normal;
font-variant: normal;
line-height: 1;
text-rendering: auto;
font-family: var(--fa-style-family, "Font Awesome 6 Free");
font-weight: var(--fa-style, 900);
position: absolute;
left: 50%;
top: 50%;
transform: translate(-50%, -50%) scale(125%);
color: black;
}
.image_editor_color .editor-options-container > *:first-child {
flex: 100%;
}
.image_editor_color .editor-options-container > *:first-child > * {
width: 100%;
}
.image_editor_color .editor-options-container > *:first-child > * > input {
width: 100%;
height: 100%;
opacity: 0;
cursor: pointer;
}
.image_editor_color .editor-options-container > *:first-child > * > span {
position: absolute;
left: 50%;
top: 50%;
transform: translate(-50%, -50%);
opacity: 0.5;
}
.image_editor_color .editor-options-container > *:first-child > *.active > span {
opacity: 0;
}
.image_editor_tool .editor-options-container {
flex-wrap: wrap;
}
.image_editor_tool .editor-options-container > * {
padding: 2px;
flex: 50%;
}
.editor-controls-center {
/* background: var(--background-color2); */
flex: 0;
display: flex;
justify-content: center;
align-items: center;
}
.editor-controls-center > div {
position: relative;
background: black;
margin: 20pt;
margin-top: 40pt;
}
.editor-controls-center canvas {
position: absolute;
left: 0;
top: 0;
}
.editor-controls-right {
padding: 32px;
display: flex;
flex-direction: column;
}
.editor-controls-right > div:last-child {
flex: 1;
display: flex;
flex-direction: column;
min-width: 200px;
gap: 5px;
justify-content: end;
}
.image-editor-button {
width: 100%;
height: 32px;
border-radius: 16px;
background: var(--background-color3);
}
.editor-controls-right .image-editor-button {
margin-bottom: 4px;
}
#init_image_button_inpaint .input-toggle {
position: absolute;
left: 16px;
}
#init_image_button_inpaint .input-toggle input:not(:checked) ~ label {
pointer-events: none;
}
.image-editor-popup {
--popup-margin: 16px;
--popup-padding: 24px;
}
@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;
}
.image-editor-popup h1 {
position: absolute;
top: 32px;
left: 50%;
transform: translateX(-50%);
}
@media screen and (max-width: 700px) {
.image-editor-popup > div {
margin: 0px;
padding: 0px;
}
.image-editor-popup h1 {
position: relative;
transform: none;
left: auto;
}
}
.image-editor-popup > div > div {
min-height: calc(99vh - (2 * var(--popup-margin)) - (2 * var(--popup-padding)));
}
.inpainter .image_editor_color {
display: none;
}
.inpainter .editor-canvas-background {
opacity: 0.75;
}
#init_image_preview_container .button {
display: flex;
padding: 6px;
height: 24px;
box-shadow: 2px 2px 1px 1px #00000088;
}
#init_image_preview_container .button:hover {
background: var(--background-color4)
}
.image-editor-popup .button {
display: flex;
}
.image-editor-popup h4 {
text-align: left;
}
.image-editor-popup .load_mask {
display: none;
}
.inpainter .load_mask {
display: flex;
}

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@ -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;
}

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.plugins-table {
display: flex;
flex-direction: column;
gap: 1px;
}
.plugins-table > div {
background: var(--background-color2);
display: flex;
padding: 0px 4px;
}
.plugins-table > div > div {
padding: 10px;
display: flex;
align-items: center;
justify-content: center;
}
.plugins-table small {
color: rgb(153, 153, 153);
}
.plugins-table > div > div:nth-child(1) {
font-size: 20px;
width: 45px;
}
.plugins-table > div > div:nth-child(2) {
flex: 1;
flex-direction: column;
text-align: left;
justify-content: center;
align-items: start;
gap: 4px;
}
.plugins-table > div > div:nth-child(3) {
text-align: right;
}
.plugins-table > div:first-child {
border-radius: 12px 12px 0px 0px;
}
.plugins-table > div:last-child {
border-radius: 0px 0px 12px 12px;
}
.notifications-table {
display: flex;
flex-direction: column;
gap: 1px;
}
.notifications-table > div {
background: var(--background-color2);
display: flex;
padding: 0px 4px;
}
.notifications-table > div > div {
padding: 10px;
display: flex;
align-items: center;
justify-content: center;
}
.notifications-table small {
color: rgb(153, 153, 153);
}
.notifications-table > div > div:nth-child(1) {
flex: 1;
flex-direction: column;
text-align: left;
justify-content: center;
align-items: start;
gap: 4px;
}
.notifications-table > div > div:nth-child(2) {
width: auto;
}
.notifications-table > div:first-child {
border-radius: 12px 12px 0px 0px;
}
.notifications-table > div:last-child {
border-radius: 0px 0px 12px 12px;
}
.notification-error {
color: red;
}
DIV.no-notification {
padding-top: 16px;
font-style: italic;
}
.plugin-manager-intro {
margin: 0 0 16px 0;
}
#plugin-filter {
box-sizing: border-box;
width: 100%;
margin: 4px 0 6px 0;
padding: 10px;
}
#refresh-plugins {
box-sizing: border-box;
width: 100%;
padding: 0px;
}
#refresh-plugins a {
cursor: pointer;
}
#refresh-plugins a:active {
transition-duration: 0.1s;
position: relative;
top: 1px;
left: 1px;
}
.plugin-installed-locally {
font-style: italic;
font-size: small;
}
.plugin-source {
font-size: x-small;
}
.plugin-warning {
color: orange;
font-size: smaller;
}
.plugin-warning.hide {
display: none;
}
.plugin-warning ul {
list-style: square;
margin: 0 0 8px 16px;
padding: 0;
}
.plugin-warning li {
margin-left: 8px;
padding: 0;
}
/* MODAL DIALOG */
#pluginDialog-input-dialog {
position: fixed;
z-index: 1000;
top: 0;
left: 0;
width: 100%;
height: 100%;
display: none;
}
.pluginDialog-dialog-overlay {
position: absolute;
top: 0;
left: 0;
width: 100%;
height: 100%;
background: rgba(32, 33, 36, 50%);
}
.pluginDialog-dialog-box {
position: absolute;
top: 50%;
left: 50%;
transform: translate(-50%, -50%);
width: 80%;
max-width: 600px;
background: var(--background-color2);
border: solid 1px var(--background-color3);
border-radius: 6px;
box-shadow: 0px 0px 30px black;
}
.pluginDialog-dialog-header {
display: flex;
align-items: center;
justify-content: space-between;
padding: 16px;
}
.pluginDialog-dialog-header h2 {
margin: 0;
}
.pluginDialog-dialog-close-button {
font-size: 24px;
font-weight: bold;
line-height: 1;
border: none;
background-color: transparent;
cursor: pointer;
}
.pluginDialog-dialog-close-button:hover {
color: #555;
}
.pluginDialog-dialog-content {
padding: 0 16px 0 16px;
}
.pluginDialog-dialog-content textarea {
width: 100%;
height: 300px;
border-radius: var(--input-border-radius);
padding: 4px;
accent-color: var(--accent-color);
background: var(--input-background-color);
border: var(--input-border-size) solid var(--input-border-color);
color: var(--input-text-color);
font-size: 9pt;
resize: none;
}
.pluginDialog-dialog-buttons {
display: flex;
justify-content: flex-end;
padding: 16px;
}
.pluginDialog-dialog-buttons button {
margin-left: 8px;
padding: 8px 16px;
font-size: 16px;
border-radius: 4px;
/*background: var(--accent-color);*/
/*border: var(--primary-button-border);*/
/*color: rgb(255, 221, 255);*/
background-color: #3071a9;
border: none;
cursor: pointer;
}
.pluginDialog-dialog-buttons button:hover {
/*background: hsl(var(--accent-hue), 100%, 50%);*/
background-color: #428bca;
}
/* NOTIFICATION CENTER */
#plugin-notification-button {
float: right;
margin-top: 30px;
}
#plugin-notification-button:hover {
background: unset;
}
#plugin-notification-button:active {
transition-duration: 0.1s;
position: relative;
top: 1px;
left: 1px;
}
.plugin-notification-pill {
background-color: red;
border-radius: 50%;
color: white;
font-size: 10px;
font-weight: bold;
height: 12px;
line-height: 12px;
position: relative;
right: -8px;
text-align: center;
top: -20px;
width: 12px;
}

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@ -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);
}

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@ -1,191 +0,0 @@
:root {
--main-hue: 222;
--main-saturation: 4%;
--value-base: 13%;
--value-step: 5%;
--background-color1: hsl(var(--main-hue), var(--main-saturation), var(--value-base));
--background-color2: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (1 * var(--value-step))));
--background-color3: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (0.5 * var(--value-step))));
--background-color4: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (1.5 * var(--value-step))));
--accent-hue: 267;
--accent-lightness: 36%;
--accent-lightness-hover: 40%;
--text-color: #eee;
--link-color: rgb(0, 102, 204);
--small-label-color: rgb(153, 153, 153);
--input-text-color: #eee;
--input-background-color: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (0.7 * var(--value-step))));
--input-border-color: var(--background-color4);
--button-text-color: var(--input-text-color);
--button-color: var(--input-background-color);
--button-border: none;
--button-hover-background: hsl(var(--accent-hue), 100%, calc(var(--accent-lightness) + 6%));
--secondary-button-background: rgb(132, 8, 0);
--secondary-button-hover-background: rgb(177, 27, 0);
/* other */
--input-border-radius: 4px;
--input-border-size: 1px;
--accent-color: hsl(var(--accent-hue), 100%, var(--accent-lightness));
--accent-color-hover: hsl(var(--accent-hue), 100%, var(--accent-lightness-hover));
--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 {
--background-color1: white;
--background-color2: #ececec;
--background-color3: #e7e9eb;
--background-color4: #cccccc;
--text-color: black;
--input-text-color: black;
--input-background-color: #f8f9fa;
--input-border-color: grey;
--theme-color-fallback: #aaaaaa;
--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 {
--background-color1: #36393f;
--background-color2: #2f3136;
--background-color3: #292b2f;
--background-color4: #202225;
--accent-hue: 235;
--accent-lightness: 65%;
--input-border-size: 2px;
--input-background-color: #202225;
--input-border-color: var(--input-background-color);
--theme-color-fallback: #202225;
--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 {
--main-hue: 222;
--main-saturation: 18%;
--value-base: 18%;
--value-step: 3%;
--background-color1: hsl(var(--main-hue), var(--main-saturation), var(--value-base));
--background-color2: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (1 * var(--value-step))));
--background-color3: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (2 * var(--value-step))));
--background-color4: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (3 * var(--value-step))));
--input-background-color: var(--background-color3);
--accent-hue: 212;
--theme-color-fallback: #0056b8;
--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;
}
.theme-blurple {
--main-hue: 235;
--main-saturation: 18%;
--value-base: 16%;
--value-step: 3%;
--background-color1: hsl(var(--main-hue), var(--main-saturation), var(--value-base));
--background-color2: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (1 * var(--value-step))));
--background-color3: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (2 * var(--value-step))));
--background-color4: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (3 * var(--value-step))));
--input-background-color: var(--background-color3);
--theme-color-fallback: #5300b8;
--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 {
--main-hue: 222;
--main-saturation: 18%;
--value-base: 5%;
--value-step: 5%;
--background-color1: hsl(var(--main-hue), var(--main-saturation), var(--value-base));
--background-color2: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (1 * var(--value-step))));
--background-color3: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (2 * var(--value-step))));
--background-color4: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) + (1.4 * var(--value-step))));
--input-background-color: var(--background-color3);
--input-border-size: 0px;
--theme-color-fallback: #000000;
}
.theme-wild {
--main-hue: 128;
--main-saturation: 18%;
--value-base: 20%;
--value-step: 5%;
--background-color1: hsl(var(--main-hue), var(--main-saturation), var(--value-base));
--background-color2: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (1 * var(--value-step))));
--background-color3: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (2 * var(--value-step))));
--background-color4: hsl(var(--main-hue), var(--main-saturation), calc(var(--value-base) - (3 * var(--value-step))));
--accent-hue: 212;
--input-border-size: 1px;
--input-background-color: hsl(222, var(--main-saturation), calc(var(--value-base) - (2 * var(--value-step))));
--input-text-color: #FF0000;
--input-border-color: #005E05;
--tertiary-color: white;
--accent-text-color: #f7fbff;
}
.theme-gnomie {
--background-color1: #242424;
--background-color2: #353535;
--background-color3: #494949;
--background-color4: #000000;
--accent-hue: 213;
--accent-lightness: 55%;
--accent-color: #2168bf;
--input-border-radius: 6px;
--input-text-color: #ffffff;
--input-background-color: #2a2a2a;
--input-border-size: 0px;
--input-border-color: var(--input-background-color);
--theme-color-fallback: #2168bf;
}
.theme-gnomie .panel-box {
border: none;
box-shadow: 0px 1px 2px rgba(0, 0, 0, 0.25);
border-radius: 10px;
}

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