mirror of
https://github.com/easydiffusion/easydiffusion.git
synced 2025-08-14 02:05:21 +02:00
Compare commits
1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 50cce36d94 |
2
.github/FUNDING.yml
vendored
2
.github/FUNDING.yml
vendored
@ -1,3 +1,3 @@
|
||||
# These are supported funding model platforms
|
||||
|
||||
ko_fi: easydiffusion
|
||||
ko_fi: cmdr2_stablediffusion_ui
|
||||
|
||||
3
.gitignore
vendored
3
.gitignore
vendored
@ -3,6 +3,3 @@ installer
|
||||
installer.tar
|
||||
dist
|
||||
.idea/*
|
||||
node_modules/*
|
||||
.tmp1
|
||||
.tmp2
|
||||
|
||||
@ -1,9 +0,0 @@
|
||||
*.min.*
|
||||
*.py
|
||||
*.json
|
||||
*.html
|
||||
/*
|
||||
!/ui
|
||||
/ui/easydiffusion
|
||||
!/ui/plugins
|
||||
!/ui/media
|
||||
@ -1,7 +0,0 @@
|
||||
{
|
||||
"printWidth": 120,
|
||||
"tabWidth": 4,
|
||||
"semi": false,
|
||||
"arrowParens": "always",
|
||||
"trailingComma": "es5"
|
||||
}
|
||||
1122
3rd-PARTY-LICENSES
1122
3rd-PARTY-LICENSES
File diff suppressed because it is too large
Load Diff
276
CHANGES.md
276
CHANGES.md
@ -1,276 +0,0 @@
|
||||
# What's new?
|
||||
|
||||
## v3.5 (preview)
|
||||
### Major Changes
|
||||
- **Flux** - full support for the Flux model, including quantized bnb and nf4 models.
|
||||
- **LyCORIS** - including `LoCon`, `Hada`, `IA3` and `Lokr`.
|
||||
- **11 new samplers** - `DDIM CFG++`, `DPM Fast`, `DPM++ 2m SDE Heun`, `DPM++ 3M SDE`, `Restart`, `Heun PP2`, `IPNDM`, `IPNDM_V`, `LCM`, `[Forge] Flux Realistic`, `[Forge] Flux Realistic (Slow)`.
|
||||
- **15 new schedulers** - `Uniform`, `Karras`, `Exponential`, `Polyexponential`, `SGM Uniform`, `KL Optimal`, `Align Your Steps`, `Normal`, `DDIM`, `Beta`, `Turbo`, `Align Your Steps GITS`, `Align Your Steps 11`, `Align Your Steps 32`.
|
||||
- **42 new Controlnet filters, and support for lots of new ControlNet models** (including QR ControlNets).
|
||||
- **5 upscalers** - `SwinIR`, `ScuNET`, `Nearest`, `Lanczos`, `ESRGAN`.
|
||||
- **Faster than v3.0**
|
||||
- **Major rewrite of the code** - We've switched to `Forge WebUI` under the hood, which brings a lot of new features, faster image generation, and support for all the extensions in the Forge/Automatic1111 community. This allows Easy Diffusion to stay up-to-date with the latest features, and focus on making the UI and installation experience even easier.
|
||||
|
||||
v3.5 is currently an optional upgrade, and you can switch between the v3.0 (diffusers) engine and the v3.5 (webui) engine using the `Settings` tab in the UI.
|
||||
|
||||
### Detailed changelog
|
||||
* 3.5.0 - 11 Oct 2024 - **Preview release** of the new v3.5 engine, powered by Forge WebUI (a fork of Automatic1111). This enables Flux, SD3, LyCORIS and lots of new features, while using the same familiar Easy Diffusion interface.
|
||||
|
||||
## v3.0
|
||||
### Major Changes
|
||||
- **ControlNet** - Full support for ControlNet, with native integration of the common ControlNet models. Just select a control image, then choose the ControlNet filter/model and run. No additional configuration or download necessary. Supports custom ControlNets as well.
|
||||
- **SDXL** - Full support for SDXL. No configuration necessary, just put the SDXL model in the `models/stable-diffusion` folder.
|
||||
- **Multiple LoRAs** - Use multiple LoRAs, including SDXL and SD2-compatible LoRAs. Put them in the `models/lora` folder.
|
||||
- **Embeddings** - Use textual inversion embeddings easily, by putting them in the `models/embeddings` folder and using their names in the prompt (or by clicking the `+ Embeddings` button to select embeddings visually). Thanks @JeLuf.
|
||||
- **Seamless Tiling** - Generate repeating textures that can be useful for games and other art projects. Works best in 512x512 resolution. Thanks @JeLuf.
|
||||
- **Inpainting Models** - Full support for inpainting models, including custom inpainting models. No configuration (or yaml files) necessary.
|
||||
- **Faster than v2.5** - Nearly 40% faster than Easy Diffusion v2.5, and can be even faster if you enable xFormers.
|
||||
- **Even less VRAM usage** - Less than 2 GB for 512x512 images on 'low' VRAM usage setting (SD 1.5). Can generate large images with SDXL.
|
||||
- **WebP images** - Supports saving images in the lossless webp format.
|
||||
- **Undo/Redo in the UI** - Remove tasks or images from the queue easily, and undo the action if you removed anything accidentally. Thanks @JeLuf.
|
||||
- **Three new samplers, and latent upscaler** - Added `DEIS`, `DDPM` and `DPM++ 2m SDE` as additional samplers. Thanks @ogmaresca and @rbertus2000.
|
||||
- **Significantly faster 'Upscale' and 'Fix Faces' buttons on the images**
|
||||
- **Major rewrite of the code** - We've switched to using diffusers under-the-hood, which allows us to release new features faster, and focus on making the UI and installer even easier to use.
|
||||
|
||||
### Detailed changelog
|
||||
* 3.0.10 - 11 Oct 2024 - **Major Update** - An option to upgrade to v3.5, which enables Flux, Stable Diffusion 3, LyCORIS models and lots more.
|
||||
* 3.0.9 - 28 May 2024 - Slider for controlling the strength of controlnets.
|
||||
* 3.0.8 - 27 May 2024 - SDXL ControlNets for Img2Img and Inpainting.
|
||||
* 3.0.7 - 11 Dec 2023 - Setting to enable/disable VAE tiling (in the Image Settings panel). Sometimes VAE tiling reduces the quality of the image, so this setting will help control that.
|
||||
* 3.0.6 - 18 Sep 2023 - Add thumbnails to embeddings from the UI, using the new `Upload Thumbnail` button in the Embeddings popup. Thanks @JeLuf.
|
||||
* 3.0.6 - 15 Sep 2023 - Fix broken embeddings dialog when LoRA information couldn't be fetched.
|
||||
* 3.0.6 - 14 Sep 2023 - UI for adding notes to LoRA files (to help you remember which prompts to use). Also added a button to automatically fetch prompts from Civitai for a LoRA file, using the `Import from Civitai` button. Thanks @JeLuf.
|
||||
* 3.0.5 - 2 Sep 2023 - Support SDXL ControlNets.
|
||||
* 3.0.4 - 1 Sep 2023 - Fix incorrect metadata generated for embeddings, when the exact word doesn't match the case, or is part of a larger word.
|
||||
* 3.0.4 - 1 Sep 2023 - Simplify the installation for AMD users on Linux. Thanks @JeLuf.
|
||||
* 3.0.4 - 1 Sep 2023 - Allow using a different folder for models. This is useful if you want to share a models folder across different software, or on a different drive. You can change this path in the Settings tab.
|
||||
* 3.0.3 - 31 Aug 2023 - Auto-save images to disk (if enabled by the user) when upscaling/fixing using the buttons on the image.
|
||||
* 3.0.3 - 30 Aug 2023 - Allow loading NovelAI-based custom models.
|
||||
* 3.0.3 - 30 Aug 2023 - Fix broken VAE tiling. This allows you to create larger images with lesser VRAM usage.
|
||||
* 3.0.3 - 30 Aug 2023 - Allow blocking NSFW images using a server-side config. This prevents the browser from generating NSFW images or changing the config. Open `config.yaml` in a text editor (e.g. Notepad), and add `block_nsfw: true` at the end, and save the file.
|
||||
* 3.0.2 - 29 Aug 2023 - Fixed incorrect matching of embeddings from prompts.
|
||||
* 3.0.2 - 24 Aug 2023 - Fix broken seamless tiling.
|
||||
* 3.0.2 - 23 Aug 2023 - Fix styling on mobile devices.
|
||||
* 3.0.2 - 22 Aug 2023 - Full support for inpainting models, including custom models. Support SD 1.x and SD 2.x inpainting models. Does not require you to specify a yaml config file.
|
||||
* 3.0.2 - 22 Aug 2023 - Reduce VRAM consumption of controlnet in 'low' VRAM mode, and allow accelerating controlnets using xformers.
|
||||
* 3.0.2 - 22 Aug 2023 - Improve auto-detection of SD 2.0 and 2.1 models, removing the need for custom yaml files for SD 2.x models. Improve the model load time by speeding-up the black image test.
|
||||
* 3.0.1 - 18 Aug 2023 - Rotate an image if EXIF rotation is present. For e.g. this is common in images taken with a smartphone.
|
||||
* 3.0.1 - 18 Aug 2023 - Resize control images to the task dimensions, to avoid memory errors with high-res control images.
|
||||
* 3.0.1 - 18 Aug 2023 - Show controlnet filter preview in the task entry.
|
||||
* 3.0.1 - 18 Aug 2023 - Fix drag-and-drop and 'Use these Settings' for LoRA and ControlNet.
|
||||
* 3.0.1 - 18 Aug 2023 - Auto-save LoRA models and strengths.
|
||||
* 3.0.1 - 17 Aug 2023 - Automatically use the correct yaml config file for custom SDXL models, even if a yaml file isn't present in the folder.
|
||||
* 3.0.1 - 17 Aug 2023 - Fix broken embeddings with SDXL.
|
||||
* 3.0.1 - 16 Aug 2023 - Fix broken LoRA with SDXL.
|
||||
* 3.0.1 - 15 Aug 2023 - Fix broken seamless tiling.
|
||||
* 3.0.1 - 15 Aug 2023 - Fix textual inversion embeddings not working in `low` VRAM usage mode.
|
||||
* 3.0.1 - 15 Aug 2023 - Fix for custom VAEs not working in `low` VRAM usage mode.
|
||||
* 3.0.1 - 14 Aug 2023 - Slider to change the image dimensions proportionally (in Image Settings). Thanks @JeLuf.
|
||||
* 3.0.1 - 14 Aug 2023 - Show an error to the user if an embedding isn't compatible with the model, instead of failing silently without informing the user. Thanks @JeLuf.
|
||||
* 3.0.1 - 14 Aug 2023 - Disable watermarking for SDXL img2img. Thanks @AvidGameFan.
|
||||
* 3.0.0 - 3 Aug 2023 - Enabled diffusers for everyone by default. The old v2 engine can be used by disabling the "Use v3 engine" option in the Settings tab.
|
||||
|
||||
## 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
|
||||
* 2.5.48 - 1 Aug 2023 - (beta-only) Full support for ControlNets. You can select a control image to guide the AI. You can pick a filter to pre-process the image, and one of the known (or custom) controlnet models. Supports `OpenPose`, `Canny`, `Straight Lines`, `Depth`, `Line Art`, `Scribble`, `Soft Edge`, `Shuffle` and `Segment`.
|
||||
* 2.5.47 - 30 Jul 2023 - An option to use `Strict Mask Border` while inpainting, to avoid touching areas outside the mask. But this might show a slight outline of the mask, which you will have to touch up separately.
|
||||
* 2.5.47 - 29 Jul 2023 - (beta-only) Fix long prompts with SDXL.
|
||||
* 2.5.47 - 29 Jul 2023 - (beta-only) Fix red dots in some SDXL images.
|
||||
* 2.5.47 - 29 Jul 2023 - Significantly faster `Fix Faces` and `Upscale` buttons (on the image). They no longer need to generate the image from scratch, instead they just upscale/fix the generated image in-place.
|
||||
* 2.5.47 - 28 Jul 2023 - Lots of internal code reorganization, in preparation for supporting Controlnets. No user-facing changes.
|
||||
* 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.
|
||||
@ -1,23 +1,24 @@
|
||||
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:
|
||||
[](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`
|
||||
```
|
||||
@ -32,20 +33,23 @@ REM @xcopy sd-ui-files\ui ui /s /i /Y
|
||||
REM @copy sd-ui-files\scripts\on_sd_start.bat scripts\ /Y
|
||||
REM @copy "sd-ui-files\scripts\Start Stable Diffusion UI.cmd" . /Y
|
||||
```
|
||||
6) Next, comment out the line at the top of `/projects/stable-diffusion-ui-archive/scripts/on_sd_start.sh` (or `on_sd_start.bat`) that copies `on_env_start`. For e.g. `@rem @copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y`
|
||||
7) Comment out the line at the top of `/projects/stable-diffusion-ui-archive/scripts/on_sd_start.sh` that copies `on_env_start`. For e.g. `@copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y`
|
||||
8) Delete the current `ui` folder at `/projects/stable-diffusion-ui-archive/ui`
|
||||
9) Now make a symlink between the repository clone (where you will be making changes) and this archive (where you will be running stable diffusion):
|
||||
`ln -s /projects/stable-diffusion-ui-repo/ui /projects/stable-diffusion-ui-archive/ui`
|
||||
or for Windows
|
||||
`mklink /J \projects\stable-diffusion-ui-archive\ui \projects\stable-diffusion-ui-repo\ui` (link name first, source repo dir second)
|
||||
9) Run the project again (like in step 2) and ensure you can still use the UI.
|
||||
`mklink /D \projects\stable-diffusion-ui-archive\ui \projects\stable-diffusion-ui-repo\ui` (link name first, source repo dir second)
|
||||
9) Run the archive again `start.sh` and ensure you can still use the UI.
|
||||
10) Congrats, now any changes you make in your repo `ui` folder are linked to this running archive of the app and can be previewed in the browser.
|
||||
11) Please update CHANGES.md in your pull requests.
|
||||
|
||||
Check the `ui/frontend/build/README.md` for instructions on running and building the React code.
|
||||
|
||||
## Development environment for Installer changes
|
||||
Build the Windows installer using Windows, and the Linux installer using Linux. Don't mix the two, and don't use WSL. An Ubuntu VM is fine for building the Linux installer on a Windows host.
|
||||
|
||||
1. Run `build.bat` or `./build.sh` depending on whether you're in Windows or Linux.
|
||||
2. Make a new GitHub release and upload the Windows and Linux installer builds created inside the `dist` folder.
|
||||
|
||||
For NSIS (on Windows), you need to have these plugins in the `nsis/Plugins` folder: `amd64-unicode`, `x86-ansi`, `x86-unicode`
|
||||
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.
|
||||
|
||||
@ -1,24 +1,24 @@
|
||||
Congrats on downloading Easy Diffusion, version 3!
|
||||
Congrats on downloading Stable Diffusion UI, version 2!
|
||||
|
||||
If you haven't downloaded Easy Diffusion 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:
|
||||
|
||||
For Windows:
|
||||
- Please double-click the "Easy-Diffusion-Windows.exe" file and follow the instructions.
|
||||
- Please double-click the "Start Stable Diffusion UI.cmd" file inside the "stable-diffusion-ui" folder.
|
||||
|
||||
For Linux and Mac:
|
||||
- Please open a terminal, and go to the "easy-diffusion" directory. Then run ./start.sh
|
||||
For Linux:
|
||||
- Please open a terminal, and go to the "stable-diffusion-ui" directory. Then run ./start.sh
|
||||
|
||||
That file will automatically install everything. After that it will start the Easy Diffusion interface in a web browser.
|
||||
That file will automatically install everything. After that it will start the Stable Diffusion interface in a web browser.
|
||||
|
||||
To start Easy Diffusion in the future, please run the same command mentioned above.
|
||||
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
1
NSIS/.gitignore
vendored
@ -1 +0,0 @@
|
||||
*.exe
|
||||
@ -1 +0,0 @@
|
||||
Scripts to be used with the Nullsoft Scriptable Installation System
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 565 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 223 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 454 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 46 KiB |
309
NSIS/sdui.nsi
309
NSIS/sdui.nsi
@ -1,309 +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 "3.0"
|
||||
!define PRODUCT_PUBLISHER "cmdr2 and contributors"
|
||||
!define PRODUCT_WEB_SITE "https://easydiffusion.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 "${EXISTING_INSTALLATION_DIR}\installer_files\cyborg_flower_girl.ico"
|
||||
|
||||
!define MUI_WELCOMEFINISHPAGE_BITMAP "${EXISTING_INSTALLATION_DIR}\installer_files\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 "${EXISTING_INSTALLATION_DIR}\LICENSE"
|
||||
!insertmacro MUI_PAGE_LICENSE "${EXISTING_INSTALLATION_DIR}\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 "$INSTDIR"
|
||||
File "${EXISTING_INSTALLATION_DIR}\CreativeML Open RAIL-M License"
|
||||
File "${EXISTING_INSTALLATION_DIR}\How to install and run.txt"
|
||||
File "${EXISTING_INSTALLATION_DIR}\LICENSE"
|
||||
File "${EXISTING_INSTALLATION_DIR}\Start Stable Diffusion UI.cmd"
|
||||
File /r "${EXISTING_INSTALLATION_DIR}\installer_files"
|
||||
File /r "${EXISTING_INSTALLATION_DIR}\sd-ui-files"
|
||||
|
||||
SetOutPath "$INSTDIR\scripts"
|
||||
File "${EXISTING_INSTALLATION_DIR}\scripts\install_status.txt"
|
||||
File "${EXISTING_INSTALLATION_DIR}\scripts\on_env_start.bat"
|
||||
File "C:\windows\system32\curl.exe"
|
||||
File "${EXISTING_INSTALLATION_DIR}\scripts\config.yaml.sample"
|
||||
|
||||
CreateDirectory "$INSTDIR\models\stable-diffusion"
|
||||
CreateDirectory "$INSTDIR\models\gfpgan"
|
||||
CreateDirectory "$INSTDIR\models\realesrgan"
|
||||
CreateDirectory "$INSTDIR\models\vae"
|
||||
|
||||
CreateDirectory "$INSTDIR\profile\.cache\huggingface\hub"
|
||||
SetOutPath "$INSTDIR\profile\.cache\huggingface\hub"
|
||||
File /r /x pytorch_model.bin "${EXISTING_INSTALLATION_DIR}\profile\.cache\huggingface\hub\models--openai--clip-vit-large-patch14"
|
||||
|
||||
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 1.5 model...'
|
||||
NScurl::http get "https://github.com/easydiffusion/sdkit-test-data/releases/download/assets/sd-v1-5.safetensors" "$INSTDIR\models\stable-diffusion\sd-v1-5.safetensors" /CANCEL /INSIST /END
|
||||
|
||||
DetailPrint 'Downloading the GFPGAN model...'
|
||||
NScurl::http get "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth" "$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
|
||||
@ -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
|
||||
@ -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
|
||||
209
README.md
209
README.md
@ -1,149 +1,104 @@
|
||||
# Easy Diffusion 3.0
|
||||
### 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.
|
||||
|
||||
️🔥🎉 **New!** Support for SDXL, ControlNet, multiple LoRA files, embeddings (and a lot more) have been added!
|
||||
|
||||
[Installation guide](#installation) | [Troubleshooting guide](https://github.com/easydiffusion/easydiffusion/wiki/Troubleshooting) | [User guide](https://github.com/easydiffusion/easydiffusion/wiki) | <sub>[](https://discord.com/invite/u9yhsFmEkB)</sub> <sup>(for support queries, and development discussions)</sup>
|
||||
|
||||
---
|
||||
|
||||
|
||||
|
||||
# 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/cmdr2/stable-diffusion-ui/releases/latest/download/Easy-Diffusion-Linux.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-linux.png" width="200" /></a>
|
||||
<a href="https://github.com/cmdr2/stable-diffusion-ui/releases/latest/download/Easy-Diffusion-Mac.zip"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-mac.png" width="200" /></a>
|
||||
<a href="https://github.com/cmdr2/stable-diffusion-ui/releases/latest/download/Easy-Diffusion-Windows.exe"><img src="https://github.com/cmdr2/stable-diffusion-ui/raw/main/media/download-win.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 card¹ (minimum 2 GB RAM), or run on your CPU.
|
||||
- **Linux:** NVIDIA¹ or AMD² 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.
|
||||
[](https://discord.com/invite/u9yhsFmEkB) (for support, and development discussion) | [Troubleshooting guide for common problems](Troubleshooting.md)
|
||||
|
||||
¹) [CUDA Compute capability](https://en.wikipedia.org/wiki/CUDA#GPUs_supported) level of 3.7 or higher required.
|
||||
️🔥🎉 **New!** Live Preview, More Samplers, In-Painting, Face Correction (GFPGAN) and Upscaling (RealESRGAN) have been added!
|
||||
|
||||
²) ROCm 5.2 support required.
|
||||
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.
|
||||
|
||||
The installer will take care of whatever is needed. If you face any problems, you can join the friendly [Discord community](https://discord.com/invite/u9yhsFmEkB) and ask for assistance.
|
||||
|
||||
## On Windows:
|
||||
1. Run the downloaded `Easy-Diffusion-Windows.exe` file.
|
||||
2. Run `Easy Diffusion` once the installation finishes. You can also start from your Start Menu, or from your desktop (if you created a shortcut).
|
||||
|
||||
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.
|
||||
|
||||
### Powerful image generation
|
||||
- **Supports**: "*Text to Image*", "*Image to Image*" and "*InPainting*"
|
||||
- **ControlNet**: For advanced control over the image, e.g. by setting the pose or drawing the outline for the AI to fill in.
|
||||
- **16 Samplers**: `PLMS`, `DDIM`, `DEIS`, `Heun`, `Euler`, `Euler Ancestral`, `DPM2`, `DPM2 Ancestral`, `LMS`, `DPM Solver`, `DPM++ 2s Ancestral`, `DPM++ 2m`, `DPM++ 2m SDE`, `DPM++ SDE`, `DDPM`, `UniPC`.
|
||||
- **Stable Diffusion XL and 2.1**: Generate higher-quality images using the latest Stable Diffusion XL models.
|
||||
- **Textual Inversion Embeddings**: For guiding the AI strongly towards a particular concept.
|
||||
- **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 image 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. E.g. `apple++ falling from a tree`.
|
||||
- **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 XL and 2.1 support**
|
||||
- **Merge Models**
|
||||
- **Use custom VAE models**
|
||||
- **Textual Inversion Embeddings**
|
||||
- **ControlNet**
|
||||
- **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, modify packages, and edit the conda environment.
|
||||
- **Low Memory Usage**: Creates 512x512 images with less than 4GB of VRAM!
|
||||
|
||||
**(and a lot more)**
|
||||
|
||||
|
||||
----
|
||||
|
||||
## Easy for new users, powerful features for advanced users:
|
||||
|
||||
|
||||
## Task Queue
|
||||
|
||||
## Live Preview
|
||||
|
||||
|
||||
|
||||
----
|
||||
# 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.
|
||||
|
||||
# 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.
|
||||
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.
|
||||
|
||||
## 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.
|
||||
|
||||
|
||||
|
||||
# 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.
|
||||
|
||||
|
||||
|
||||
# Image Modifiers
|
||||
|
||||
|
||||
# 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).
|
||||
|
||||
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.
|
||||
|
||||
# Credits
|
||||
* Stable Diffusion: https://github.com/Stability-AI/stablediffusion
|
||||
* CodeFormer: https://github.com/sczhou/CodeFormer (license: https://github.com/sczhou/CodeFormer/blob/master/LICENSE)
|
||||
* GFPGAN: https://github.com/TencentARC/GFPGAN
|
||||
* RealESRGAN: https://github.com/xinntao/Real-ESRGAN
|
||||
* k-diffusion: https://github.com/crowsonkb/k-diffusion
|
||||
* Code contributors and artists on the cmdr2 UI: https://github.com/cmdr2/stable-diffusion-ui and Discord (https://discord.com/invite/u9yhsFmEkB)
|
||||
* Lots of contributors on the internet
|
||||
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.
|
||||
|
||||
46
Troubleshooting.md
Normal file
46
Troubleshooting.md
Normal file
@ -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))
|
||||
81
build.bat
81
build.bat
@ -1,78 +1,47 @@
|
||||
@echo off
|
||||
setlocal enabledelayedexpansion
|
||||
|
||||
@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 Easy Diffusion, you've downloaded the wrong file."
|
||||
@echo "Please download and follow the instructions at https://github.com/easydiffusion/easydiffusion#installation" & echo.
|
||||
@echo "If you only want to use the Stable Diffusion UI, you've downloaded the wrong file."
|
||||
@echo "Please download and follow the instructions at https://github.com/cmdr2/stable-diffusion-ui#installation" & echo.
|
||||
@echo "If you are actually a developer of this project, please type Y and press enter" & echo.
|
||||
|
||||
set /p answer=Are you a developer of this project (Y/N)?
|
||||
if /i "%answer:~,1%" NEQ "Y" exit /b
|
||||
|
||||
@rem verify dependencies
|
||||
call makensis /VERSION >.tmp1 2>.tmp2
|
||||
if "!ERRORLEVEL!" NEQ "0" (
|
||||
echo makensis.exe not found! Download it from https://sourceforge.net/projects/nsisbi/files/ and set it on the PATH variable.
|
||||
pause
|
||||
exit
|
||||
)
|
||||
@set PYTHONNOUSERSITE=1
|
||||
|
||||
set /p OUT_DIR=Output folder path (will create the installer files inside this, e.g. F:\EasyDiffusion):
|
||||
@mkdir dist\stable-diffusion-ui
|
||||
|
||||
mkdir "%OUT_DIR%\scripts"
|
||||
mkdir "%OUT_DIR%\installer_files"
|
||||
@echo "Downloading components for the installer.."
|
||||
|
||||
set BASE_DIR=%cd%
|
||||
@call conda env create --prefix installer -f environment.yaml
|
||||
@call conda activate .\installer
|
||||
|
||||
@rem STEP 1: copy the installer files for Windows
|
||||
@echo "Creating a distributable package.."
|
||||
|
||||
copy "%BASE_DIR%\scripts\on_env_start.bat" "%OUT_DIR%\scripts\"
|
||||
copy "%BASE_DIR%\scripts\config.yaml.sample" "%OUT_DIR%\scripts\config.yaml.sample"
|
||||
copy "%BASE_DIR%\scripts\Start Stable Diffusion UI.cmd" "%OUT_DIR%\"
|
||||
copy "%BASE_DIR%\LICENSE" "%OUT_DIR%\"
|
||||
copy "%BASE_DIR%\CreativeML Open RAIL-M License" "%OUT_DIR%\"
|
||||
copy "%BASE_DIR%\How to install and run.txt" "%OUT_DIR%\"
|
||||
copy "%BASE_DIR%\NSIS\cyborg_flower_girl.ico" "%OUT_DIR%\installer_files\"
|
||||
copy "%BASE_DIR%\NSIS\cyborg_flower_girl.bmp" "%OUT_DIR%\installer_files\"
|
||||
echo. > "%OUT_DIR%\scripts\install_status.txt"
|
||||
@call conda install -c conda-forge -y conda-pack
|
||||
@call conda pack --n-threads -1 --prefix installer --format tar
|
||||
|
||||
echo ----
|
||||
echo Basic files ready. Verify the files in %OUT_DIR%, then press Enter to initialize the environment, or close to quit.
|
||||
echo ----
|
||||
pause
|
||||
@cd dist\stable-diffusion-ui
|
||||
@mkdir installer
|
||||
|
||||
@rem STEP 2: Initialize the environment with git, python and conda
|
||||
@call tar -xf ..\..\installer.tar -C installer
|
||||
|
||||
cd /d "%OUT_DIR%\"
|
||||
call "%BASE_DIR%\scripts\bootstrap.bat"
|
||||
@mkdir scripts
|
||||
|
||||
echo ----
|
||||
echo Environment ready. Verify the environment, then press Enter to download the necessary packages, or close to quit.
|
||||
echo ----
|
||||
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
|
||||
|
||||
@rem STEP 3: Download the packages and create a working installation
|
||||
@echo "Build ready. Zip the 'dist\stable-diffusion-ui' folder."
|
||||
|
||||
cd /d "%OUT_DIR%\"
|
||||
start "Install Easy Diffusion" /D "%OUT_DIR%" "Start Stable Diffusion UI.cmd"
|
||||
@echo "Cleaning up.."
|
||||
|
||||
echo ----
|
||||
echo Installation in progress (in a new window). Once complete, verify the installation, then press Enter to create an installer from these files, or close to quit.
|
||||
echo ----
|
||||
pause
|
||||
@cd ..\..
|
||||
|
||||
@rem STEP 4: Build the installer from a working installation
|
||||
@rmdir /s /q installer
|
||||
|
||||
cd /d "%OUT_DIR%\"
|
||||
|
||||
echo ^^!define EXISTING_INSTALLATION_DIR "%OUT_DIR%" > nsisconf.nsh
|
||||
call makensis /NOCD /V4 "%BASE_DIR%\NSIS\sdui.nsi"
|
||||
|
||||
echo ----
|
||||
if "!ERRORLEVEL!" EQU "0" (
|
||||
echo Installer built successfully at %OUT_DIR%
|
||||
) else (
|
||||
echo Installer failed to build at %OUT_DIR%
|
||||
)
|
||||
echo ----
|
||||
pause
|
||||
@del installer.tar
|
||||
59
build.sh
59
build.sh
@ -1,8 +1,8 @@
|
||||
#!/bin/bash
|
||||
|
||||
printf "Hi there, what you are running is meant for the developers of this project, not for users.\n\n"
|
||||
printf "If you only want to use Easy Diffusion, you've downloaded the wrong file.\n"
|
||||
printf "Please download and follow the instructions at https://github.com/easydiffusion/easydiffusion#installation \n\n"
|
||||
printf "If you only want to use the Stable Diffusion UI, you've downloaded the wrong file.\n"
|
||||
printf "Please download and follow the instructions at https://github.com/cmdr2/stable-diffusion-ui#installation\n\n"
|
||||
printf "If you are actually a developer of this project, please type Y and press enter\n\n"
|
||||
|
||||
read -p "Are you a developer of this project (Y/N) " yn
|
||||
@ -11,30 +11,45 @@ case $yn in
|
||||
* ) exit;;
|
||||
esac
|
||||
|
||||
mkdir -p dist/linux-mac/easy-diffusion/scripts
|
||||
export PYTHONNOUSERSITE=1
|
||||
|
||||
# copy the installer files for Linux and Mac
|
||||
mkdir -p dist/stable-diffusion-ui
|
||||
|
||||
cp scripts/on_env_start.sh dist/linux-mac/easy-diffusion/scripts/
|
||||
cp scripts/bootstrap.sh dist/linux-mac/easy-diffusion/scripts/
|
||||
cp scripts/functions.sh dist/linux-mac/easy-diffusion/scripts/
|
||||
cp scripts/config.yaml.sample dist/linux-mac/easy-diffusion/scripts/config.yaml.sample
|
||||
cp scripts/start.sh dist/linux-mac/easy-diffusion/
|
||||
cp LICENSE dist/linux-mac/easy-diffusion/
|
||||
cp "CreativeML Open RAIL-M License" dist/linux-mac/easy-diffusion/
|
||||
cp "How to install and run.txt" dist/linux-mac/easy-diffusion/
|
||||
echo "" > dist/linux-mac/easy-diffusion/scripts/install_status.txt
|
||||
echo "Downloading components for the installer.."
|
||||
|
||||
# set the permissions
|
||||
chmod u+x dist/linux-mac/easy-diffusion/scripts/on_env_start.sh
|
||||
chmod u+x dist/linux-mac/easy-diffusion/scripts/bootstrap.sh
|
||||
chmod u+x dist/linux-mac/easy-diffusion/start.sh
|
||||
source ~/miniconda3/etc/profile.d/conda.sh
|
||||
|
||||
# make the zip
|
||||
conda install -c conda-forge -y conda-pack
|
||||
|
||||
conda env create --prefix installer -f environment.yaml
|
||||
conda activate ./installer
|
||||
|
||||
echo "Creating a distributable package.."
|
||||
|
||||
conda pack --n-threads -1 --prefix installer --format tar
|
||||
|
||||
cd dist/stable-diffusion-ui
|
||||
mkdir installer
|
||||
|
||||
tar -xf ../../installer.tar -C installer
|
||||
|
||||
mkdir scripts
|
||||
|
||||
cp ../../scripts/on_env_start.sh scripts/
|
||||
cp ../../scripts/start.sh .
|
||||
cp ../../LICENSE .
|
||||
cp "../../CreativeML Open RAIL-M License" .
|
||||
cp "../../How to install and run.txt" .
|
||||
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 ../Easy-Diffusion-Linux.zip easy-diffusion
|
||||
zip -r ../Easy-Diffusion-Mac.zip easy-diffusion
|
||||
cd ../..
|
||||
|
||||
echo "Build ready. Upload the zip files inside the 'dist' folder."
|
||||
rm -rf installer
|
||||
|
||||
rm installer.tar
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 56 KiB |
Binary file not shown.
Binary file not shown.
|
Before Width: | Height: | Size: 12 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 139 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 113 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 155 KiB |
@ -1,9 +0,0 @@
|
||||
{
|
||||
"scripts": {
|
||||
"prettier-fix": "npx prettier --write \"./**/*.js\"",
|
||||
"prettier-check": "npx prettier --check \"./**/*.js\""
|
||||
},
|
||||
"devDependencies": {
|
||||
"prettier": "^1.19.1"
|
||||
}
|
||||
}
|
||||
@ -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
|
||||
@ -1,46 +1,19 @@
|
||||
@echo off
|
||||
|
||||
cd /d %~dp0
|
||||
echo Install dir: %~dp0
|
||||
|
||||
set PATH=C:\Windows\System32;C:\Windows\System32\wbem;%PATH%
|
||||
set PYTHONHOME=
|
||||
|
||||
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://easydiffusion.github.io/docs/installation/
|
||||
echo.
|
||||
echo ================================================================================
|
||||
echo.
|
||||
pause
|
||||
exit /b
|
||||
@REM Delete the post-activate hook from the old installer
|
||||
if exist "installer\etc\conda\activate.d\post_activate.bat" (
|
||||
echo. > installer\etc\conda\activate.d\post_activate.bat
|
||||
)
|
||||
|
||||
@rem set legacy installer's PATH, if it exists
|
||||
if exist "installer" set PATH=%cd%\installer;%cd%\installer\Library\bin;%cd%\installer\Scripts;%cd%\installer\Library\usr\bin;%PATH%
|
||||
@call installer\Scripts\activate.bat
|
||||
|
||||
@rem set new installer's PATH, if it downloaded any packages
|
||||
if exist "installer_files\env" set PATH=%cd%\installer_files\env;%cd%\installer_files\env\Library\bin;%cd%\installer_files\env\Scripts;%cd%\installer_files\Library\usr\bin;%PATH%
|
||||
@call conda-unpack
|
||||
|
||||
set PYTHONPATH=%cd%\installer;%cd%\installer_files\env
|
||||
@call conda --version
|
||||
@call git --version
|
||||
|
||||
@rem Test the core requirements
|
||||
call where git
|
||||
call git --version
|
||||
@cd installer
|
||||
|
||||
call where conda
|
||||
call conda --version
|
||||
echo .
|
||||
echo COMSPEC=%COMSPEC%
|
||||
wmic path win32_VideoController get name,AdapterRAM,DriverDate,DriverVersion
|
||||
@call ..\scripts\on_env_start.bat
|
||||
|
||||
@rem Download the rest of the installer and UI
|
||||
call scripts\on_env_start.bat
|
||||
@pause
|
||||
|
||||
@ -1,77 +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 PYTHONHOME=
|
||||
|
||||
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=git python=3.8.5
|
||||
|
||||
if not exist "%LEGACY_INSTALL_ENV_DIR%\etc\profile.d\conda.sh" (
|
||||
if not exist "%INSTALL_ENV_DIR%\etc\profile.d\conda.sh" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% conda
|
||||
)
|
||||
|
||||
call "%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%
|
||||
@ -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 '$PACKAGES_TO_INSTALL' failed."
|
||||
fi
|
||||
fi
|
||||
File diff suppressed because it is too large
Load Diff
@ -1,24 +0,0 @@
|
||||
# Change listen_port if port 9000 is already in use on your system
|
||||
# Set listen_to_network to true to make Easy Diffusion accessibble on your local network
|
||||
net:
|
||||
listen_port: 9000
|
||||
listen_to_network: false
|
||||
|
||||
# Multi GPU setup
|
||||
render_devices: auto
|
||||
|
||||
# Set open_browser_on_start to false to disable opening a new browser tab on each restart
|
||||
ui:
|
||||
open_browser_on_start: true
|
||||
|
||||
# set update_branch to main to use the stable version, or to beta to use the experimental
|
||||
# beta version.
|
||||
update_branch: main
|
||||
|
||||
# Set force_save_path to enforce an auto save path. Clients will not be able to change or
|
||||
# disable auto save when this option is set. Please adapt the path in the examples to your
|
||||
# needs.
|
||||
# Windows:
|
||||
# force_save_path: C:\\Easy Diffusion Images\\
|
||||
# Linux:
|
||||
# force_save_path: /data/easy-diffusion-images/
|
||||
@ -1,55 +0,0 @@
|
||||
#!/bin/bash
|
||||
|
||||
cd "$(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
|
||||
@ -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
|
||||
}
|
||||
|
||||
|
||||
@ -1,54 +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_yaml = os.path.abspath(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)
|
||||
@ -1,32 +1,20 @@
|
||||
@echo off
|
||||
|
||||
@echo. & echo "Easy Diffusion - v3" & 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.
|
||||
@ -40,40 +28,33 @@ 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 add -A .
|
||||
@call git stash
|
||||
@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\webui_console.py 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
|
||||
|
||||
|
||||
@ -1,62 +1,43 @@
|
||||
#!/bin/bash
|
||||
|
||||
source ./scripts/functions.sh
|
||||
|
||||
printf "\n\nEasy Diffusion - v3\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 $update_branch.."
|
||||
|
||||
cd sd-ui-files
|
||||
|
||||
git add -A .
|
||||
git stash
|
||||
git reset --hard
|
||||
git -c advice.detachedHead=false checkout "$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/webui_console.py scripts/
|
||||
cp sd-ui-files/scripts/start.sh .
|
||||
cp sd-ui-files/scripts/developer_console.sh .
|
||||
cp sd-ui-files/scripts/functions.sh scripts/
|
||||
|
||||
exec ./scripts/on_sd_start.sh
|
||||
./scripts/on_sd_start.sh
|
||||
|
||||
read -p "Press any key to continue"
|
||||
|
||||
@ -1,77 +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
|
||||
@copy sd-ui-files\scripts\webui_console.py 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
|
||||
set PATH=C:\Windows\System32;%PATH%
|
||||
|
||||
@rem activate the installer env
|
||||
call conda activate
|
||||
@>nul grep -c "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
|
||||
@if "%ERRORLEVEL%" EQU "0" (
|
||||
echo "Packages necessary for Stable Diffusion UI were already installed"
|
||||
) else (
|
||||
@echo. & echo "Downloading packages necessary for Stable Diffusion UI.." & echo.
|
||||
|
||||
@set PYTHONNOUSERSITE=1
|
||||
|
||||
@call conda install -c conda-forge -y --prefix env uvicorn fastapi || (
|
||||
echo "Error installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
|
||||
pause
|
||||
exit /b
|
||||
)
|
||||
)
|
||||
|
||||
call WHERE uvicorn > .tmp
|
||||
@>nul grep -c "uvicorn" .tmp
|
||||
@if "%ERRORLEVEL%" NEQ "0" (
|
||||
@echo. & echo "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.
|
||||
@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
|
||||
)
|
||||
|
||||
@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"
|
||||
if exist "ui\plugins\ui\merge.plugin.js" del "ui\plugins\ui\merge.plugin.js"
|
||||
|
||||
@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
|
||||
@>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
|
||||
)
|
||||
|
||||
@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\"
|
||||
@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"
|
||||
)
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
cd ..
|
||||
@if not exist "sd-v1-4.ckpt" (
|
||||
@echo. & echo "Downloading data files (weights) for Stable Diffusion.." & echo.
|
||||
|
||||
@rem set any overrides
|
||||
set HF_HUB_DISABLE_SYMLINKS_WARNING=true
|
||||
@call curl -L -k https://me.cmdr2.org/stable-diffusion-ui/sd-v1-4.ckpt > sd-v1-4.ckpt
|
||||
|
||||
@rem install or upgrade the required modules
|
||||
set PATH=C:\Windows\System32;%PATH%
|
||||
@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
|
||||
)
|
||||
)
|
||||
|
||||
@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
|
||||
echo PYTHONPATH=%PYTHONPATH%
|
||||
|
||||
@rem Download the required packages
|
||||
call where python
|
||||
call python --version
|
||||
|
||||
call python scripts\check_modules.py --launch-uvicorn
|
||||
pause
|
||||
exit /b
|
||||
@if exist "GFPGANv1.3.pth" (
|
||||
for %%I in ("GFPGANv1.3.pth") do if "%%~zI" EQU "348632874" (
|
||||
echo "Data files (weights) necessary for GFPGAN (Face Correction) were already downloaded"
|
||||
) else (
|
||||
echo. & echo "The GFPGAN model file present at %cd%\GFPGANv1.3.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
|
||||
del "GFPGANv1.3.pth"
|
||||
)
|
||||
)
|
||||
|
||||
@if not exist "GFPGANv1.3.pth" (
|
||||
@echo. & echo "Downloading data files (weights) for GFPGAN (Face Correction).." & echo.
|
||||
|
||||
@call curl -L -k https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth > GFPGANv1.3.pth
|
||||
|
||||
@if exist "GFPGANv1.3.pth" (
|
||||
for %%I in ("GFPGANv1.3.pth") do if "%%~zI" NEQ "348632874" (
|
||||
echo. & echo "Error: The downloaded GFPGAN model file was invalid! Bytes downloaded: %%~zI" & echo.
|
||||
echo. & echo "Error downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
|
||||
pause
|
||||
exit /b
|
||||
)
|
||||
) else (
|
||||
@echo. & echo "Error downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
|
||||
pause
|
||||
exit /b
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
|
||||
@if exist "RealESRGAN_x4plus.pth" (
|
||||
for %%I in ("RealESRGAN_x4plus.pth") do if "%%~zI" EQU "67040989" (
|
||||
echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus were already downloaded"
|
||||
) else (
|
||||
echo. & echo "The GFPGAN model file present at %cd%\RealESRGAN_x4plus.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
|
||||
del "RealESRGAN_x4plus.pth"
|
||||
)
|
||||
)
|
||||
|
||||
@if not exist "RealESRGAN_x4plus.pth" (
|
||||
@echo. & echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.." & echo.
|
||||
|
||||
@call curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth > RealESRGAN_x4plus.pth
|
||||
|
||||
@if exist "RealESRGAN_x4plus.pth" (
|
||||
for %%I in ("RealESRGAN_x4plus.pth") do if "%%~zI" NEQ "67040989" (
|
||||
echo. & echo "Error: The downloaded ESRGAN x4plus model file was invalid! Bytes downloaded: %%~zI" & echo.
|
||||
echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
|
||||
pause
|
||||
exit /b
|
||||
)
|
||||
) else (
|
||||
@echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
|
||||
pause
|
||||
exit /b
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
|
||||
@if exist "RealESRGAN_x4plus_anime_6B.pth" (
|
||||
for %%I in ("RealESRGAN_x4plus_anime_6B.pth") do if "%%~zI" EQU "17938799" (
|
||||
echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus_anime were already downloaded"
|
||||
) else (
|
||||
echo. & echo "The GFPGAN model file present at %cd%\RealESRGAN_x4plus_anime_6B.pth is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
|
||||
del "RealESRGAN_x4plus_anime_6B.pth"
|
||||
)
|
||||
)
|
||||
|
||||
@if not exist "RealESRGAN_x4plus_anime_6B.pth" (
|
||||
@echo. & echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.." & echo.
|
||||
|
||||
@call curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth > RealESRGAN_x4plus_anime_6B.pth
|
||||
|
||||
@if exist "RealESRGAN_x4plus_anime_6B.pth" (
|
||||
for %%I in ("RealESRGAN_x4plus_anime_6B.pth") do if "%%~zI" NEQ "17938799" (
|
||||
echo. & echo "Error: The downloaded ESRGAN x4plus_anime model file was invalid! Bytes downloaded: %%~zI" & echo.
|
||||
echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
|
||||
pause
|
||||
exit /b
|
||||
)
|
||||
) else (
|
||||
@echo. & echo "Error downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
|
||||
pause
|
||||
exit /b
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
|
||||
@>nul grep -c "sd_install_complete" ..\scripts\install_status.txt
|
||||
@if "%ERRORLEVEL%" NEQ "0" (
|
||||
@echo sd_weights_downloaded >> ..\scripts\install_status.txt
|
||||
@echo sd_install_complete >> ..\scripts\install_status.txt
|
||||
)
|
||||
|
||||
@echo. & echo "Stable Diffusion is ready!" & echo.
|
||||
|
||||
@set SD_DIR=%cd%
|
||||
|
||||
@cd env\lib\site-packages
|
||||
@set PYTHONPATH=%SD_DIR%;%cd%
|
||||
@cd ..\..\..
|
||||
@echo PYTHONPATH=%PYTHONPATH%
|
||||
|
||||
@cd ..
|
||||
@set SD_UI_PATH=%cd%\ui
|
||||
@cd stable-diffusion
|
||||
|
||||
@call python --version
|
||||
|
||||
@uvicorn server:app --app-dir "%SD_UI_PATH%" --port 9000 --host 0.0.0.0
|
||||
|
||||
@pause
|
||||
@ -1,57 +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/
|
||||
cp sd-ui-files/scripts/webui_console.py scripts/
|
||||
|
||||
source installer/etc/profile.d/conda.sh
|
||||
|
||||
source ./scripts/functions.sh
|
||||
python -c "import os; import shutil; frm = 'sd-ui-files/ui/hotfix/9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'; dst = os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'transformers', '9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'); shutil.copyfile(frm, dst) if os.path.exists(dst) else print(''); print('Hotfixed broken JSON file from OpenAI');"
|
||||
|
||||
# activate the installer env
|
||||
export CONDA_BASEPATH=$(conda info --base)
|
||||
source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # avoids the 'shell not initialized' error
|
||||
# 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.
|
||||
|
||||
conda activate || fail "Failed to activate conda"
|
||||
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.."
|
||||
|
||||
# hack to fix conda 4.14 on older installations
|
||||
cp $CONDA_BASEPATH/condabin/conda $CONDA_BASEPATH/bin/conda
|
||||
cd stable-diffusion
|
||||
|
||||
# remove the old version of the dev console script, if it's still present
|
||||
if [ -e "open_dev_console.sh" ]; then
|
||||
rm "open_dev_console.sh"
|
||||
git reset --hard
|
||||
git pull
|
||||
git checkout f6cfebffa752ee11a7b07497b8529d5971de916c
|
||||
|
||||
git apply ../ui/sd_internal/ddim_callback.patch
|
||||
git apply ../ui/sd_internal/env_yaml.patch
|
||||
|
||||
cd ..
|
||||
else
|
||||
printf "\n\nDownloading Stable Diffusion..\n\n"
|
||||
|
||||
if git clone https://github.com/basujindal/stable-diffusion.git ; then
|
||||
echo sd_git_cloned >> scripts/install_status.txt
|
||||
else
|
||||
printf "\n\nError downloading Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
|
||||
cd stable-diffusion
|
||||
git checkout f6cfebffa752ee11a7b07497b8529d5971de916c
|
||||
|
||||
git apply ../ui/sd_internal/ddim_callback.patch
|
||||
git apply ../ui/sd_internal/env_yaml.patch
|
||||
|
||||
cd ..
|
||||
fi
|
||||
|
||||
if [ -e "ui/plugins/ui/merge.plugin.js" ]; then
|
||||
rm "ui/plugins/ui/merge.plugin.js"
|
||||
fi
|
||||
|
||||
# set the correct installer path (current vs legacy)
|
||||
if [ -e "installer_files/env" ]; then
|
||||
export INSTALL_ENV_DIR="$(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"
|
||||
|
||||
export PYTHONNOUSERSITE=1
|
||||
|
||||
if pip install -e git+https://github.com/TencentARC/GFPGAN#egg=GFPGAN ; then
|
||||
echo "Installed. Testing.."
|
||||
else
|
||||
printf "\n\nError installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
|
||||
out_test=`python -c "from gfpgan import GFPGANer; print(42)"`
|
||||
if [ "$out_test" != "42" ]; then
|
||||
printf "\n\nDependency test failed! Error installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
|
||||
echo conda_sd_gfpgan_deps_installed >> ../scripts/install_status.txt
|
||||
fi
|
||||
|
||||
if [ `grep -c conda_sd_esrgan_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
|
||||
echo "Packages necessary for ESRGAN (Resolution Upscaling) were already installed"
|
||||
else
|
||||
printf "\n\nDownloading packages necessary for ESRGAN (Resolution Upscaling)..\n"
|
||||
|
||||
export PYTHONNOUSERSITE=1
|
||||
|
||||
if pip install -e git+https://github.com/xinntao/Real-ESRGAN#egg=realesrgan ; then
|
||||
echo "Installed. Testing.."
|
||||
else
|
||||
printf "\n\nError installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
|
||||
out_test=`python -c "from basicsr.archs.rrdbnet_arch import RRDBNet; from realesrgan import RealESRGANer; print(42)"`
|
||||
if [ "$out_test" != "42" ]; then
|
||||
printf "\n\nDependency test failed! Error installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
|
||||
echo conda_sd_esrgan_deps_installed >> ../scripts/install_status.txt
|
||||
fi
|
||||
|
||||
if [ `grep -c conda_sd_ui_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
|
||||
echo "Packages necessary for Stable Diffusion UI were already installed"
|
||||
else
|
||||
printf "\n\nDownloading packages necessary for Stable Diffusion UI..\n\n"
|
||||
|
||||
export PYTHONNOUSERSITE=1
|
||||
|
||||
if conda install -c conda-forge --prefix ./env -y uvicorn fastapi ; then
|
||||
echo "Installed. Testing.."
|
||||
else
|
||||
printf "\n\nError installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
|
||||
if ! command -v uvicorn &> /dev/null; then
|
||||
printf "\n\nUI packages not found! Error installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
|
||||
echo conda_sd_ui_deps_installed >> ../scripts/install_status.txt
|
||||
fi
|
||||
|
||||
|
||||
|
||||
if [ -f "sd-v1-4.ckpt" ]; then
|
||||
model_size=`ls -l sd-v1-4.ckpt | awk '{print $5}'`
|
||||
|
||||
if [ "$model_size" -eq "4265380512" ] || [ "$model_size" -eq "7703807346" ] || [ "$model_size" -eq "7703810927" ]; then
|
||||
echo "Data files (weights) necessary for Stable Diffusion were already downloaded"
|
||||
else
|
||||
printf "\n\nThe model file present at $PWD/sd-v1-4.ckpt is invalid. It is only $model_size bytes in size. Re-downloading.."
|
||||
rm sd-v1-4.ckpt
|
||||
fi
|
||||
fi
|
||||
|
||||
if [ ! -f "sd-v1-4.ckpt" ]; then
|
||||
echo "Downloading data files (weights) for Stable Diffusion.."
|
||||
|
||||
curl -L -k https://me.cmdr2.org/stable-diffusion-ui/sd-v1-4.ckpt > sd-v1-4.ckpt
|
||||
|
||||
if [ -f "sd-v1-4.ckpt" ]; then
|
||||
model_size=`ls -l sd-v1-4.ckpt | awk '{print $5}'`
|
||||
if [ ! "$model_size" == "4265380512" ]; then
|
||||
printf "\n\nError: The downloaded model file was invalid! Bytes downloaded: $model_size\n\n"
|
||||
printf "\n\nError downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
else
|
||||
printf "\n\nError downloading the data files (weights) for Stable Diffusion. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
fi
|
||||
|
||||
|
||||
if [ -f "GFPGANv1.3.pth" ]; then
|
||||
model_size=`ls -l GFPGANv1.3.pth | awk '{print $5}'`
|
||||
|
||||
if [ "$model_size" -eq "348632874" ]; then
|
||||
echo "Data files (weights) necessary for GFPGAN (Face Correction) were already downloaded"
|
||||
else
|
||||
printf "\n\nThe model file present at $PWD/GFPGANv1.3.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
|
||||
rm GFPGANv1.3.pth
|
||||
fi
|
||||
fi
|
||||
|
||||
if [ ! -f "GFPGANv1.3.pth" ]; then
|
||||
echo "Downloading data files (weights) for GFPGAN (Face Correction).."
|
||||
|
||||
curl -L -k https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth > GFPGANv1.3.pth
|
||||
|
||||
if [ -f "GFPGANv1.3.pth" ]; then
|
||||
model_size=`ls -l GFPGANv1.3.pth | awk '{print $5}'`
|
||||
if [ ! "$model_size" -eq "348632874" ]; then
|
||||
printf "\n\nError: The downloaded GFPGAN model file was invalid! Bytes downloaded: $model_size\n\n"
|
||||
printf "\n\nError downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
else
|
||||
printf "\n\nError downloading the data files (weights) for GFPGAN (Face Correction). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
fi
|
||||
|
||||
|
||||
if [ -f "RealESRGAN_x4plus.pth" ]; then
|
||||
model_size=`ls -l RealESRGAN_x4plus.pth | awk '{print $5}'`
|
||||
|
||||
if [ "$model_size" -eq "67040989" ]; then
|
||||
echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus were already downloaded"
|
||||
else
|
||||
printf "\n\nThe model file present at $PWD/RealESRGAN_x4plus.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
|
||||
rm RealESRGAN_x4plus.pth
|
||||
fi
|
||||
fi
|
||||
|
||||
if [ ! -f "RealESRGAN_x4plus.pth" ]; then
|
||||
echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.."
|
||||
|
||||
curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth > RealESRGAN_x4plus.pth
|
||||
|
||||
if [ -f "RealESRGAN_x4plus.pth" ]; then
|
||||
model_size=`ls -l RealESRGAN_x4plus.pth | awk '{print $5}'`
|
||||
if [ ! "$model_size" -eq "67040989" ]; then
|
||||
printf "\n\nError: The downloaded ESRGAN x4plus model file was invalid! Bytes downloaded: $model_size\n\n"
|
||||
printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
else
|
||||
printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
fi
|
||||
|
||||
|
||||
if [ -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
|
||||
model_size=`ls -l RealESRGAN_x4plus_anime_6B.pth | awk '{print $5}'`
|
||||
|
||||
if [ "$model_size" -eq "17938799" ]; then
|
||||
echo "Data files (weights) necessary for ESRGAN (Resolution Upscaling) x4plus_anime were already downloaded"
|
||||
else
|
||||
printf "\n\nThe model file present at $PWD/RealESRGAN_x4plus_anime_6B.pth is invalid. It is only $model_size bytes in size. Re-downloading.."
|
||||
rm RealESRGAN_x4plus_anime_6B.pth
|
||||
fi
|
||||
fi
|
||||
|
||||
if [ ! -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
|
||||
echo "Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.."
|
||||
|
||||
curl -L -k https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth > RealESRGAN_x4plus_anime_6B.pth
|
||||
|
||||
if [ -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
|
||||
model_size=`ls -l RealESRGAN_x4plus_anime_6B.pth | awk '{print $5}'`
|
||||
if [ ! "$model_size" -eq "17938799" ]; then
|
||||
printf "\n\nError: The downloaded ESRGAN x4plus_anime model file was invalid! Bytes downloaded: $model_size\n\n"
|
||||
printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
else
|
||||
printf "\n\nError downloading the data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime. Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/blob/main/Troubleshooting.md\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
|
||||
read -p "Press any key to continue"
|
||||
exit
|
||||
fi
|
||||
fi
|
||||
|
||||
|
||||
if [ `grep -c sd_install_complete ../scripts/install_status.txt` -gt "0" ]; then
|
||||
echo sd_weights_downloaded >> ../scripts/install_status.txt
|
||||
echo sd_install_complete >> ../scripts/install_status.txt
|
||||
fi
|
||||
|
||||
printf "\n\nStable Diffusion is ready!\n\n"
|
||||
|
||||
SD_PATH=`pwd`
|
||||
export PYTHONPATH="$SD_PATH;$SD_PATH/env/lib/python3.8/site-packages"
|
||||
echo "PYTHONPATH=$PYTHONPATH"
|
||||
|
||||
cd ..
|
||||
# Download the required packages
|
||||
python scripts/check_modules.py --launch-uvicorn
|
||||
export SD_UI_PATH=`pwd`/ui
|
||||
cd stable-diffusion
|
||||
|
||||
python --version
|
||||
|
||||
uvicorn server:app --app-dir "$SD_UI_PATH" --port 9000 --host 0.0.0.0
|
||||
|
||||
read -p "Press any key to continue"
|
||||
|
||||
6
scripts/post_activate.bat
Normal file
6
scripts/post_activate.bat
Normal 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
12
scripts/post_activate.sh
Executable file
@ -0,0 +1,12 @@
|
||||
#!/bin/bash
|
||||
|
||||
conda-unpack
|
||||
|
||||
source $CONDA_PREFIX/etc/profile.d/conda.sh
|
||||
|
||||
conda --version
|
||||
git --version
|
||||
|
||||
cd $CONDA_PREFIX/../scripts
|
||||
|
||||
./on_env_start.sh
|
||||
40
scripts/start.sh
Executable file → Normal file
40
scripts/start.sh
Executable file → Normal file
@ -1,42 +1,10 @@
|
||||
#!/bin/bash
|
||||
|
||||
cd "$(dirname "${BASH_SOURCE[0]}")"
|
||||
source installer/bin/activate
|
||||
|
||||
if [ -f "on_sd_start.bat" ]; then
|
||||
echo ================================================================================
|
||||
echo
|
||||
echo !!!! WARNING !!!!
|
||||
echo
|
||||
echo It looks like you\'re trying to run the installation script from a source code
|
||||
echo download. This will not work.
|
||||
echo
|
||||
echo Recommended: Please close this window and download the installer from
|
||||
echo https://easydiffusion.github.io/docs/installation/
|
||||
echo
|
||||
echo ================================================================================
|
||||
echo
|
||||
read
|
||||
exit 1
|
||||
fi
|
||||
conda-unpack
|
||||
|
||||
unset PYTHONHOME
|
||||
conda --version
|
||||
git --version
|
||||
|
||||
# set legacy installer's PATH, if it exists
|
||||
if [ -e "installer" ]; then export PATH="$(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
|
||||
|
||||
@ -1,101 +0,0 @@
|
||||
import os
|
||||
import platform
|
||||
import subprocess
|
||||
|
||||
|
||||
def configure_env(dir):
|
||||
env_entries = {
|
||||
"PATH": [
|
||||
f"{dir}",
|
||||
f"{dir}/bin",
|
||||
f"{dir}/Library/bin",
|
||||
f"{dir}/Scripts",
|
||||
f"{dir}/usr/bin",
|
||||
],
|
||||
"PYTHONPATH": [
|
||||
f"{dir}",
|
||||
f"{dir}/lib/site-packages",
|
||||
f"{dir}/lib/python3.10/site-packages",
|
||||
],
|
||||
"PYTHONHOME": [],
|
||||
"PY_LIBS": [
|
||||
f"{dir}/Scripts/Lib",
|
||||
f"{dir}/Scripts/Lib/site-packages",
|
||||
f"{dir}/lib",
|
||||
f"{dir}/lib/python3.10/site-packages",
|
||||
],
|
||||
"PY_PIP": [f"{dir}/Scripts", f"{dir}/bin"],
|
||||
}
|
||||
|
||||
if platform.system() == "Windows":
|
||||
env_entries["PATH"].append("C:/Windows/System32")
|
||||
env_entries["PATH"].append("C:/Windows/System32/wbem")
|
||||
env_entries["PYTHONNOUSERSITE"] = ["1"]
|
||||
env_entries["PYTHON"] = [f"{dir}/python"]
|
||||
env_entries["GIT"] = [f"{dir}/Library/bin/git"]
|
||||
else:
|
||||
env_entries["PATH"].append("/bin")
|
||||
env_entries["PATH"].append("/usr/bin")
|
||||
env_entries["PATH"].append("/usr/sbin")
|
||||
env_entries["PYTHONNOUSERSITE"] = ["y"]
|
||||
env_entries["PYTHON"] = [f"{dir}/bin/python"]
|
||||
env_entries["GIT"] = [f"{dir}/bin/git"]
|
||||
|
||||
env = {}
|
||||
for key, paths in env_entries.items():
|
||||
paths = [p.replace("/", os.path.sep) for p in paths]
|
||||
paths = os.pathsep.join(paths)
|
||||
|
||||
os.environ[key] = paths
|
||||
|
||||
return env
|
||||
|
||||
|
||||
def print_env_info():
|
||||
which_cmd = "where" if platform.system() == "Windows" else "which"
|
||||
|
||||
python = "python"
|
||||
|
||||
def locate_python():
|
||||
nonlocal python
|
||||
|
||||
python = subprocess.getoutput(f"{which_cmd} python")
|
||||
python = python.split("\n")
|
||||
python = python[0].strip()
|
||||
print("python: ", python)
|
||||
|
||||
locate_python()
|
||||
|
||||
def run(cmd):
|
||||
with subprocess.Popen(cmd) as p:
|
||||
p.wait()
|
||||
|
||||
run([which_cmd, "git"])
|
||||
run(["git", "--version"])
|
||||
run([which_cmd, "python"])
|
||||
run([python, "--version"])
|
||||
|
||||
print(f"PATH={os.environ['PATH']}")
|
||||
|
||||
if platform.system() == "Windows":
|
||||
print(f"COMSPEC={os.environ['COMSPEC']}")
|
||||
print("")
|
||||
run("wmic path win32_VideoController get name,AdapterRAM,DriverDate,DriverVersion".split(" "))
|
||||
|
||||
print(f"PYTHONPATH={os.environ['PYTHONPATH']}")
|
||||
print("")
|
||||
|
||||
|
||||
def open_dev_shell():
|
||||
if platform.system() == "Windows":
|
||||
subprocess.Popen("cmd").communicate()
|
||||
else:
|
||||
subprocess.Popen("bash").communicate()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
env_dir = os.path.abspath(os.path.join("webui", "system"))
|
||||
|
||||
configure_env(env_dir)
|
||||
print_env_info()
|
||||
open_dev_shell()
|
||||
@ -1,486 +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, backend_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()
|
||||
|
||||
ROOT_DIR = os.path.abspath(os.path.join(SD_DIR, ".."))
|
||||
|
||||
SD_UI_DIR = os.getenv("SD_UI_PATH", None)
|
||||
|
||||
CONFIG_DIR = os.path.abspath(os.path.join(ROOT_DIR, "scripts"))
|
||||
BUCKET_DIR = os.path.abspath(os.path.join(ROOT_DIR, "bucket"))
|
||||
|
||||
USER_PLUGINS_DIR = os.path.abspath(os.path.join(ROOT_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,
|
||||
},
|
||||
"backend": "ed_diffusers",
|
||||
}
|
||||
|
||||
IMAGE_EXTENSIONS = [
|
||||
".png",
|
||||
".apng",
|
||||
".jpg",
|
||||
".jpeg",
|
||||
".jfif",
|
||||
".pjpeg",
|
||||
".pjp",
|
||||
".jxl",
|
||||
".gif",
|
||||
".webp",
|
||||
".avif",
|
||||
".svg",
|
||||
]
|
||||
CUSTOM_MODIFIERS_DIR = os.path.abspath(os.path.join(ROOT_DIR, "modifiers"))
|
||||
CUSTOM_MODIFIERS_PORTRAIT_EXTENSIONS = [
|
||||
".portrait",
|
||||
"_portrait",
|
||||
" portrait",
|
||||
"-portrait",
|
||||
]
|
||||
CUSTOM_MODIFIERS_LANDSCAPE_EXTENSIONS = [
|
||||
".landscape",
|
||||
"_landscape",
|
||||
" landscape",
|
||||
"-landscape",
|
||||
]
|
||||
|
||||
MODELS_DIR = os.path.abspath(os.path.join(ROOT_DIR, "models"))
|
||||
|
||||
|
||||
def init():
|
||||
global MODELS_DIR
|
||||
|
||||
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")
|
||||
|
||||
config = getConfig()
|
||||
config_models_dir = config.get("models_dir", None)
|
||||
if config_models_dir is not None and config_models_dir != "":
|
||||
MODELS_DIR = config_models_dir
|
||||
|
||||
backend_manager.start_backend()
|
||||
|
||||
|
||||
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")
|
||||
config_yaml_path = os.path.abspath(config_yaml_path)
|
||||
|
||||
# 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.__use_backend_on_startup is None:
|
||||
getConfig.__use_backend_on_startup = config.get("backend", "ed_diffusers")
|
||||
config["config_on_startup"] = {"backend": getConfig.__use_backend_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
|
||||
|
||||
if "backend" not in config:
|
||||
if "use_v3_engine" in config:
|
||||
config["backend"] = "ed_diffusers" if config["use_v3_engine"] else "ed_classic"
|
||||
else:
|
||||
config["backend"] = "ed_diffusers"
|
||||
# this default will need to be smarter when WebUI becomes the main backend, but needs to maintain backwards
|
||||
# compatibility with existing ED 3.0 installations that haven't opted into the WebUI backend, and haven't
|
||||
# set a "use_v3_engine" flag in their config
|
||||
|
||||
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.__use_backend_on_startup = None
|
||||
|
||||
|
||||
def setConfig(config):
|
||||
global MODELS_DIR
|
||||
|
||||
try: # config.yaml
|
||||
config_yaml_path = os.path.join(CONFIG_DIR, "..", "config.yaml")
|
||||
config_yaml_path = os.path.abspath(config_yaml_path)
|
||||
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())
|
||||
|
||||
if config.get("models_dir"):
|
||||
MODELS_DIR = config["models_dir"]
|
||||
|
||||
|
||||
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():
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
config = getConfig()
|
||||
ui = config.get("ui", {})
|
||||
net = config.get("net", {})
|
||||
port = net.get("listen_port", 9000)
|
||||
|
||||
if backend.is_installed():
|
||||
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",
|
||||
)
|
||||
)
|
||||
else:
|
||||
backend_name = config["backend"]
|
||||
Console().print(
|
||||
Panel(
|
||||
"\n"
|
||||
+ f"[white]Backend: {backend_name} is still installing..\n\n"
|
||||
+ "A new browser tab will open automatically after it finishes.\n"
|
||||
+ f"If it does not, please open your web browser and navigate to [bold yellow underline]http://localhost:{port}/\n",
|
||||
title=f"Backend engine is installing",
|
||||
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
|
||||
@ -1,105 +0,0 @@
|
||||
import os
|
||||
import ast
|
||||
import sys
|
||||
import importlib.util
|
||||
import traceback
|
||||
|
||||
from easydiffusion.utils import log
|
||||
|
||||
backend = None
|
||||
curr_backend_name = None
|
||||
|
||||
|
||||
def is_valid_backend(file_path):
|
||||
with open(file_path, "r", encoding="utf-8") as file:
|
||||
node = ast.parse(file.read())
|
||||
|
||||
# Check for presence of a dictionary named 'ed_info'
|
||||
for item in node.body:
|
||||
if isinstance(item, ast.Assign):
|
||||
for target in item.targets:
|
||||
if isinstance(target, ast.Name) and target.id == "ed_info":
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def find_valid_backends(root_dir) -> dict:
|
||||
backends_path = os.path.join(root_dir, "backends")
|
||||
valid_backends = {}
|
||||
|
||||
if not os.path.exists(backends_path):
|
||||
return valid_backends
|
||||
|
||||
for item in os.listdir(backends_path):
|
||||
item_path = os.path.join(backends_path, item)
|
||||
|
||||
if os.path.isdir(item_path):
|
||||
init_file = os.path.join(item_path, "__init__.py")
|
||||
if os.path.exists(init_file) and is_valid_backend(init_file):
|
||||
valid_backends[item] = item_path
|
||||
elif item.endswith(".py"):
|
||||
if is_valid_backend(item_path):
|
||||
backend_name = os.path.splitext(item)[0] # strip the .py extension
|
||||
valid_backends[backend_name] = item_path
|
||||
|
||||
return valid_backends
|
||||
|
||||
|
||||
def load_backend_module(backend_name, backend_dict):
|
||||
if backend_name not in backend_dict:
|
||||
raise ValueError(f"Backend '{backend_name}' not found.")
|
||||
|
||||
module_path = backend_dict[backend_name]
|
||||
|
||||
mod_dir = os.path.dirname(module_path)
|
||||
|
||||
sys.path.insert(0, mod_dir)
|
||||
|
||||
# If it's a package (directory), add its parent directory to sys.path
|
||||
if os.path.isdir(module_path):
|
||||
module_path = os.path.join(module_path, "__init__.py")
|
||||
|
||||
spec = importlib.util.spec_from_file_location(backend_name, module_path)
|
||||
module = importlib.util.module_from_spec(spec)
|
||||
spec.loader.exec_module(module)
|
||||
|
||||
if mod_dir in sys.path:
|
||||
sys.path.remove(mod_dir)
|
||||
|
||||
log.info(f"Loaded backend: {module}")
|
||||
|
||||
return module
|
||||
|
||||
|
||||
def start_backend():
|
||||
global backend, curr_backend_name
|
||||
|
||||
from easydiffusion.app import getConfig, ROOT_DIR
|
||||
|
||||
curr_dir = os.path.dirname(__file__)
|
||||
|
||||
backends = find_valid_backends(curr_dir)
|
||||
plugin_backends = find_valid_backends(ROOT_DIR)
|
||||
backends.update(plugin_backends)
|
||||
|
||||
config = getConfig()
|
||||
backend_name = config["backend"]
|
||||
|
||||
if backend_name not in backends:
|
||||
raise RuntimeError(
|
||||
f"Couldn't find the backend configured in config.yaml: {backend_name}. Please check the name!"
|
||||
)
|
||||
|
||||
if backend is not None and backend_name != curr_backend_name:
|
||||
try:
|
||||
backend.stop_backend()
|
||||
except:
|
||||
log.exception(traceback.format_exc())
|
||||
|
||||
log.info(f"Loading backend: {backend_name}")
|
||||
backend = load_backend_module(backend_name, backends)
|
||||
|
||||
try:
|
||||
backend.start_backend()
|
||||
except:
|
||||
log.exception(traceback.format_exc())
|
||||
@ -1,28 +0,0 @@
|
||||
from sdkit_common import (
|
||||
start_backend,
|
||||
stop_backend,
|
||||
install_backend,
|
||||
uninstall_backend,
|
||||
is_installed,
|
||||
create_sdkit_context,
|
||||
ping,
|
||||
load_model,
|
||||
unload_model,
|
||||
set_options,
|
||||
generate_images,
|
||||
filter_images,
|
||||
get_url,
|
||||
stop_rendering,
|
||||
refresh_models,
|
||||
list_controlnet_filters,
|
||||
)
|
||||
|
||||
ed_info = {
|
||||
"name": "Classic backend for Easy Diffusion v2",
|
||||
"version": (1, 0, 0),
|
||||
"type": "backend",
|
||||
}
|
||||
|
||||
|
||||
def create_context():
|
||||
return create_sdkit_context(use_diffusers=False)
|
||||
@ -1,28 +0,0 @@
|
||||
from sdkit_common import (
|
||||
start_backend,
|
||||
stop_backend,
|
||||
install_backend,
|
||||
uninstall_backend,
|
||||
is_installed,
|
||||
create_sdkit_context,
|
||||
ping,
|
||||
load_model,
|
||||
unload_model,
|
||||
set_options,
|
||||
generate_images,
|
||||
filter_images,
|
||||
get_url,
|
||||
stop_rendering,
|
||||
refresh_models,
|
||||
list_controlnet_filters,
|
||||
)
|
||||
|
||||
ed_info = {
|
||||
"name": "Diffusers Backend for Easy Diffusion v3",
|
||||
"version": (1, 0, 0),
|
||||
"type": "backend",
|
||||
}
|
||||
|
||||
|
||||
def create_context():
|
||||
return create_sdkit_context(use_diffusers=True)
|
||||
@ -1,246 +0,0 @@
|
||||
from sdkit import Context
|
||||
|
||||
from easydiffusion.types import UserInitiatedStop
|
||||
|
||||
from sdkit.utils import (
|
||||
diffusers_latent_samples_to_images,
|
||||
gc,
|
||||
img_to_base64_str,
|
||||
latent_samples_to_images,
|
||||
)
|
||||
|
||||
opts = {}
|
||||
|
||||
|
||||
def install_backend():
|
||||
pass
|
||||
|
||||
|
||||
def start_backend():
|
||||
print("Started sdkit backend")
|
||||
|
||||
|
||||
def stop_backend():
|
||||
pass
|
||||
|
||||
|
||||
def uninstall_backend():
|
||||
pass
|
||||
|
||||
|
||||
def is_installed():
|
||||
return True
|
||||
|
||||
|
||||
def create_sdkit_context(use_diffusers):
|
||||
c = Context()
|
||||
c.test_diffusers = use_diffusers
|
||||
return c
|
||||
|
||||
|
||||
def ping(timeout=1):
|
||||
return True
|
||||
|
||||
|
||||
def load_model(context, model_type, **kwargs):
|
||||
from sdkit.models import load_model
|
||||
|
||||
load_model(context, model_type, **kwargs)
|
||||
|
||||
|
||||
def unload_model(context, model_type, **kwargs):
|
||||
from sdkit.models import unload_model
|
||||
|
||||
unload_model(context, model_type, **kwargs)
|
||||
|
||||
|
||||
def set_options(context, **kwargs):
|
||||
if "vae_tiling" in kwargs and context.test_diffusers:
|
||||
pipe = context.models["stable-diffusion"]["default"]
|
||||
vae_tiling = kwargs["vae_tiling"]
|
||||
|
||||
if vae_tiling:
|
||||
if hasattr(pipe, "enable_vae_tiling"):
|
||||
pipe.enable_vae_tiling()
|
||||
else:
|
||||
if hasattr(pipe, "disable_vae_tiling"):
|
||||
pipe.disable_vae_tiling()
|
||||
|
||||
for key in (
|
||||
"output_format",
|
||||
"output_quality",
|
||||
"output_lossless",
|
||||
"stream_image_progress",
|
||||
"stream_image_progress_interval",
|
||||
):
|
||||
if key in kwargs:
|
||||
opts[key] = kwargs[key]
|
||||
|
||||
|
||||
def generate_images(
|
||||
context: Context,
|
||||
callback=None,
|
||||
controlnet_filter=None,
|
||||
distilled_guidance_scale: float = 3.5,
|
||||
scheduler_name: str = "simple",
|
||||
output_type="pil",
|
||||
**req,
|
||||
):
|
||||
from sdkit.generate import generate_images
|
||||
|
||||
if req["init_image"] is not None and not context.test_diffusers:
|
||||
req["sampler_name"] = "ddim"
|
||||
|
||||
gc(context)
|
||||
|
||||
context.stop_processing = False
|
||||
|
||||
if req["control_image"] and controlnet_filter:
|
||||
controlnet_filter = convert_ED_controlnet_filter_name(controlnet_filter)
|
||||
req["control_image"] = filter_images(context, req["control_image"], controlnet_filter)[0]
|
||||
|
||||
callback = make_step_callback(context, callback)
|
||||
|
||||
try:
|
||||
images = generate_images(context, callback=callback, **req)
|
||||
except UserInitiatedStop:
|
||||
images = []
|
||||
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
|
||||
|
||||
gc(context)
|
||||
|
||||
if output_type == "base64":
|
||||
output_format = opts.get("output_format", "jpeg")
|
||||
output_quality = opts.get("output_quality", 75)
|
||||
output_lossless = opts.get("output_lossless", False)
|
||||
images = [img_to_base64_str(img, output_format, output_quality, output_lossless) for img in images]
|
||||
|
||||
return images
|
||||
|
||||
|
||||
def filter_images(context: Context, images, filters, filter_params={}, input_type="pil"):
|
||||
gc(context)
|
||||
|
||||
if "nsfw_checker" in filters:
|
||||
filters.remove("nsfw_checker") # handled by ED directly
|
||||
|
||||
if len(filters) == 0:
|
||||
return images
|
||||
|
||||
images = _filter_images(context, images, filters, filter_params)
|
||||
|
||||
if input_type == "base64":
|
||||
output_format = opts.get("output_format", "jpg")
|
||||
output_quality = opts.get("output_quality", 75)
|
||||
output_lossless = opts.get("output_lossless", False)
|
||||
images = [img_to_base64_str(img, output_format, output_quality, output_lossless) for img in images]
|
||||
|
||||
return images
|
||||
|
||||
|
||||
def _filter_images(context, images, filters, filter_params={}):
|
||||
from sdkit.filter import apply_filters
|
||||
|
||||
filters = filters if isinstance(filters, list) else [filters]
|
||||
filters = convert_ED_controlnet_filter_name(filters)
|
||||
|
||||
for filter_name in filters:
|
||||
params = filter_params.get(filter_name, {})
|
||||
|
||||
previous_state = before_filter(context, filter_name, params)
|
||||
|
||||
try:
|
||||
images = apply_filters(context, filter_name, images, **params)
|
||||
finally:
|
||||
after_filter(context, filter_name, params, previous_state)
|
||||
|
||||
return images
|
||||
|
||||
|
||||
def before_filter(context, filter_name, filter_params):
|
||||
if filter_name == "codeformer":
|
||||
from easydiffusion.model_manager import DEFAULT_MODELS, resolve_model_to_use
|
||||
|
||||
default_realesrgan = DEFAULT_MODELS["realesrgan"][0]["file_name"]
|
||||
prev_realesrgan_path = None
|
||||
|
||||
upscale_faces = filter_params.get("upscale_faces", False)
|
||||
if upscale_faces and default_realesrgan not in context.model_paths["realesrgan"]:
|
||||
prev_realesrgan_path = context.model_paths.get("realesrgan")
|
||||
context.model_paths["realesrgan"] = resolve_model_to_use(default_realesrgan, "realesrgan")
|
||||
load_model(context, "realesrgan")
|
||||
|
||||
return prev_realesrgan_path
|
||||
|
||||
|
||||
def after_filter(context, filter_name, filter_params, previous_state):
|
||||
if filter_name == "codeformer":
|
||||
prev_realesrgan_path = previous_state
|
||||
if prev_realesrgan_path:
|
||||
context.model_paths["realesrgan"] = prev_realesrgan_path
|
||||
load_model(context, "realesrgan")
|
||||
|
||||
|
||||
def get_url():
|
||||
pass
|
||||
|
||||
|
||||
def stop_rendering(context):
|
||||
context.stop_processing = True
|
||||
|
||||
|
||||
def refresh_models():
|
||||
pass
|
||||
|
||||
|
||||
def list_controlnet_filters():
|
||||
from sdkit.models.model_loader.controlnet_filters import filters as cn_filters
|
||||
|
||||
return cn_filters
|
||||
|
||||
|
||||
def make_step_callback(context, callback):
|
||||
def on_step(x_samples, i, *args):
|
||||
stream_image_progress = opts.get("stream_image_progress", False)
|
||||
stream_image_progress_interval = opts.get("stream_image_progress_interval", 3)
|
||||
|
||||
if context.test_diffusers:
|
||||
context.partial_x_samples = (x_samples, args[0])
|
||||
else:
|
||||
context.partial_x_samples = x_samples
|
||||
|
||||
if stream_image_progress and stream_image_progress_interval > 0 and i % stream_image_progress_interval == 0:
|
||||
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)
|
||||
else:
|
||||
images = None
|
||||
|
||||
if callback:
|
||||
callback(images, i, *args)
|
||||
|
||||
if context.stop_processing:
|
||||
raise UserInitiatedStop("User requested that we stop processing")
|
||||
|
||||
return on_step
|
||||
|
||||
|
||||
def convert_ED_controlnet_filter_name(filter):
|
||||
def cn(n):
|
||||
if n.startswith("controlnet_"):
|
||||
return n[len("controlnet_") :]
|
||||
return n
|
||||
|
||||
if isinstance(filter, list):
|
||||
return [cn(f) for f in filter]
|
||||
return cn(filter)
|
||||
@ -1,450 +0,0 @@
|
||||
import os
|
||||
import platform
|
||||
import subprocess
|
||||
import threading
|
||||
from threading import local
|
||||
import psutil
|
||||
import time
|
||||
import shutil
|
||||
|
||||
from easydiffusion.app import ROOT_DIR, getConfig
|
||||
from easydiffusion.model_manager import get_model_dirs
|
||||
from easydiffusion.utils import log
|
||||
|
||||
from . import impl
|
||||
from .impl import (
|
||||
ping,
|
||||
load_model,
|
||||
unload_model,
|
||||
set_options,
|
||||
generate_images,
|
||||
filter_images,
|
||||
get_url,
|
||||
stop_rendering,
|
||||
refresh_models,
|
||||
list_controlnet_filters,
|
||||
)
|
||||
|
||||
|
||||
ed_info = {
|
||||
"name": "WebUI backend for Easy Diffusion",
|
||||
"version": (1, 0, 0),
|
||||
"type": "backend",
|
||||
}
|
||||
|
||||
WEBUI_REPO = "https://github.com/lllyasviel/stable-diffusion-webui-forge.git"
|
||||
WEBUI_COMMIT = "f4d5e8cac16a42fa939e78a0956b4c30e2b47bb5"
|
||||
|
||||
BACKEND_DIR = os.path.abspath(os.path.join(ROOT_DIR, "webui"))
|
||||
SYSTEM_DIR = os.path.join(BACKEND_DIR, "system")
|
||||
WEBUI_DIR = os.path.join(BACKEND_DIR, "webui")
|
||||
|
||||
OS_NAME = platform.system()
|
||||
|
||||
MODELS_TO_OVERRIDE = {
|
||||
"stable-diffusion": "--ckpt-dir",
|
||||
"vae": "--vae-dir",
|
||||
"hypernetwork": "--hypernetwork-dir",
|
||||
"gfpgan": "--gfpgan-models-path",
|
||||
"realesrgan": "--realesrgan-models-path",
|
||||
"lora": "--lora-dir",
|
||||
"codeformer": "--codeformer-models-path",
|
||||
"embeddings": "--embeddings-dir",
|
||||
"controlnet": "--controlnet-dir",
|
||||
}
|
||||
|
||||
backend_process = None
|
||||
conda = "conda"
|
||||
|
||||
|
||||
def locate_conda():
|
||||
global conda
|
||||
|
||||
which = "where" if OS_NAME == "Windows" else "which"
|
||||
conda = subprocess.getoutput(f"{which} conda")
|
||||
conda = conda.split("\n")
|
||||
conda = conda[0].strip()
|
||||
print("conda: ", conda)
|
||||
|
||||
|
||||
locate_conda()
|
||||
|
||||
|
||||
def install_backend():
|
||||
print("Installing the WebUI backend..")
|
||||
|
||||
# create the conda env
|
||||
run([conda, "create", "-y", "--prefix", SYSTEM_DIR], cwd=ROOT_DIR)
|
||||
|
||||
print("Installing packages..")
|
||||
|
||||
# install python 3.10 and git in the conda env
|
||||
run([conda, "install", "-y", "--prefix", SYSTEM_DIR, "-c", "conda-forge", "python=3.10", "git"], cwd=ROOT_DIR)
|
||||
|
||||
# print info
|
||||
run_in_conda(["git", "--version"], cwd=ROOT_DIR)
|
||||
run_in_conda(["python", "--version"], cwd=ROOT_DIR)
|
||||
|
||||
# clone webui
|
||||
run_in_conda(["git", "clone", WEBUI_REPO, WEBUI_DIR], cwd=ROOT_DIR)
|
||||
|
||||
# install cpu-only torch if the PC doesn't have a graphics card (for Windows and Linux).
|
||||
# this avoids WebUI installing a CUDA version and trying to activate it
|
||||
if OS_NAME in ("Windows", "Linux") and not has_discrete_graphics_card():
|
||||
run_in_conda(["python", "-m", "pip", "install", "torch", "torchvision"], cwd=WEBUI_DIR)
|
||||
|
||||
|
||||
def start_backend():
|
||||
config = getConfig()
|
||||
backend_config = config.get("backend_config", {})
|
||||
|
||||
if not os.path.exists(BACKEND_DIR):
|
||||
install_backend()
|
||||
|
||||
was_still_installing = not is_installed()
|
||||
|
||||
if backend_config.get("auto_update", True):
|
||||
run_in_conda(["git", "add", "-A", "."], cwd=WEBUI_DIR)
|
||||
run_in_conda(["git", "stash"], cwd=WEBUI_DIR)
|
||||
run_in_conda(["git", "reset", "--hard"], cwd=WEBUI_DIR)
|
||||
run_in_conda(["git", "fetch"], cwd=WEBUI_DIR)
|
||||
run_in_conda(["git", "-c", "advice.detachedHead=false", "checkout", WEBUI_COMMIT], cwd=WEBUI_DIR)
|
||||
|
||||
# hack to prevent webui-macos-env.sh from overwriting the COMMANDLINE_ARGS env variable
|
||||
mac_webui_file = os.path.join(WEBUI_DIR, "webui-macos-env.sh")
|
||||
if os.path.exists(mac_webui_file):
|
||||
os.remove(mac_webui_file)
|
||||
|
||||
impl.WEBUI_HOST = backend_config.get("host", "localhost")
|
||||
impl.WEBUI_PORT = backend_config.get("port", "7860")
|
||||
|
||||
env = dict(os.environ)
|
||||
env.update(get_env())
|
||||
|
||||
def restart_if_webui_dies_after_starting():
|
||||
has_started = False
|
||||
|
||||
while True:
|
||||
try:
|
||||
impl.ping(timeout=1)
|
||||
|
||||
is_first_start = not has_started
|
||||
has_started = True
|
||||
|
||||
if was_still_installing and is_first_start:
|
||||
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}")
|
||||
except (TimeoutError, ConnectionError):
|
||||
if has_started: # process probably died
|
||||
print("######################## WebUI probably died. Restarting...")
|
||||
stop_backend()
|
||||
backend_thread = threading.Thread(target=target)
|
||||
backend_thread.start()
|
||||
break
|
||||
except Exception:
|
||||
import traceback
|
||||
|
||||
log.exception(traceback.format_exc())
|
||||
|
||||
time.sleep(1)
|
||||
|
||||
def target():
|
||||
global backend_process
|
||||
|
||||
cmd = "webui.bat" if OS_NAME == "Windows" else "./webui.sh"
|
||||
|
||||
print("starting", cmd, WEBUI_DIR)
|
||||
backend_process = run_in_conda([cmd], cwd=WEBUI_DIR, env=env, wait=False, output_prefix="[WebUI] ")
|
||||
|
||||
restart_if_dead_thread = threading.Thread(target=restart_if_webui_dies_after_starting)
|
||||
restart_if_dead_thread.start()
|
||||
|
||||
backend_process.wait()
|
||||
|
||||
backend_thread = threading.Thread(target=target)
|
||||
backend_thread.start()
|
||||
|
||||
start_proxy()
|
||||
|
||||
|
||||
def start_proxy():
|
||||
# proxy
|
||||
from easydiffusion.server import server_api
|
||||
from fastapi import FastAPI, Request
|
||||
from fastapi.responses import Response
|
||||
import json
|
||||
|
||||
URI_PREFIX = "/webui"
|
||||
|
||||
webui_proxy = FastAPI(root_path=f"{URI_PREFIX}", docs_url="/swagger")
|
||||
|
||||
@webui_proxy.get("{uri:path}")
|
||||
def proxy_get(uri: str, req: Request):
|
||||
if uri == "/openapi-proxy.json":
|
||||
uri = "/openapi.json"
|
||||
|
||||
res = impl.webui_get(uri, headers=req.headers)
|
||||
|
||||
content = res.content
|
||||
headers = dict(res.headers)
|
||||
|
||||
if uri == "/docs":
|
||||
content = res.text.replace("url: '/openapi.json'", f"url: '{URI_PREFIX}/openapi-proxy.json'")
|
||||
elif uri == "/openapi.json":
|
||||
content = res.json()
|
||||
content["paths"] = {f"{URI_PREFIX}{k}": v for k, v in content["paths"].items()}
|
||||
content = json.dumps(content)
|
||||
|
||||
if isinstance(content, str):
|
||||
content = bytes(content, encoding="utf-8")
|
||||
headers["content-length"] = str(len(content))
|
||||
|
||||
# Return the same response back to the client
|
||||
return Response(content=content, status_code=res.status_code, headers=headers)
|
||||
|
||||
@webui_proxy.post("{uri:path}")
|
||||
async def proxy_post(uri: str, req: Request):
|
||||
body = await req.body()
|
||||
res = impl.webui_post(uri, data=body, headers=req.headers)
|
||||
|
||||
# Return the same response back to the client
|
||||
return Response(content=res.content, status_code=res.status_code, headers=dict(res.headers))
|
||||
|
||||
server_api.mount(f"{URI_PREFIX}", webui_proxy)
|
||||
|
||||
|
||||
def stop_backend():
|
||||
global backend_process
|
||||
|
||||
if backend_process:
|
||||
try:
|
||||
kill(backend_process.pid)
|
||||
except:
|
||||
pass
|
||||
|
||||
backend_process = None
|
||||
|
||||
|
||||
def uninstall_backend():
|
||||
shutil.rmtree(BACKEND_DIR)
|
||||
|
||||
|
||||
def is_installed():
|
||||
if not os.path.exists(BACKEND_DIR) or not os.path.exists(SYSTEM_DIR) or not os.path.exists(WEBUI_DIR):
|
||||
return True
|
||||
|
||||
env = dict(os.environ)
|
||||
env.update(get_env())
|
||||
|
||||
try:
|
||||
out = check_output_in_conda(["python", "-m", "pip", "show", "torch"], env=env)
|
||||
return "Version" in out.decode()
|
||||
except subprocess.CalledProcessError:
|
||||
pass
|
||||
|
||||
return False
|
||||
|
||||
|
||||
def read_output(pipe, prefix=""):
|
||||
while True:
|
||||
output = pipe.readline()
|
||||
if output:
|
||||
print(f"{prefix}{output.decode('utf-8')}", end="")
|
||||
else:
|
||||
break # Pipe is closed, subprocess has likely exited
|
||||
|
||||
|
||||
def run(cmds: list, cwd=None, env=None, stream_output=True, wait=True, output_prefix=""):
|
||||
p = subprocess.Popen(cmds, cwd=cwd, env=env, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
|
||||
if stream_output:
|
||||
output_thread = threading.Thread(target=read_output, args=(p.stdout, output_prefix))
|
||||
output_thread.start()
|
||||
|
||||
if wait:
|
||||
p.wait()
|
||||
|
||||
return p
|
||||
|
||||
|
||||
def run_in_conda(cmds: list, *args, **kwargs):
|
||||
cmds = [conda, "run", "--no-capture-output", "--prefix", SYSTEM_DIR] + cmds
|
||||
return run(cmds, *args, **kwargs)
|
||||
|
||||
|
||||
def check_output_in_conda(cmds: list, cwd=None, env=None):
|
||||
cmds = [conda, "run", "--no-capture-output", "--prefix", SYSTEM_DIR] + cmds
|
||||
return subprocess.check_output(cmds, cwd=cwd, env=env, stderr=subprocess.PIPE)
|
||||
|
||||
|
||||
def create_context():
|
||||
context = local()
|
||||
|
||||
# temp hack, throws an attribute not found error otherwise
|
||||
context.device = "cuda:0"
|
||||
context.half_precision = True
|
||||
context.vram_usage_level = None
|
||||
|
||||
context.models = {}
|
||||
context.model_paths = {}
|
||||
context.model_configs = {}
|
||||
context.device_name = None
|
||||
context.vram_optimizations = set()
|
||||
context.vram_usage_level = "balanced"
|
||||
context.test_diffusers = False
|
||||
context.enable_codeformer = False
|
||||
|
||||
return context
|
||||
|
||||
|
||||
def get_env():
|
||||
dir = os.path.abspath(SYSTEM_DIR)
|
||||
|
||||
if not os.path.exists(dir):
|
||||
raise RuntimeError("The system folder is missing!")
|
||||
|
||||
config = getConfig()
|
||||
models_dir = config.get("models_dir", os.path.join(ROOT_DIR, "models"))
|
||||
|
||||
model_path_args = get_model_path_args()
|
||||
|
||||
env_entries = {
|
||||
"PATH": [
|
||||
f"{dir}",
|
||||
f"{dir}/bin",
|
||||
f"{dir}/Library/bin",
|
||||
f"{dir}/Scripts",
|
||||
f"{dir}/usr/bin",
|
||||
],
|
||||
"PYTHONPATH": [
|
||||
f"{dir}",
|
||||
f"{dir}/lib/site-packages",
|
||||
f"{dir}/lib/python3.10/site-packages",
|
||||
],
|
||||
"PYTHONHOME": [],
|
||||
"PY_LIBS": [
|
||||
f"{dir}/Scripts/Lib",
|
||||
f"{dir}/Scripts/Lib/site-packages",
|
||||
f"{dir}/lib",
|
||||
f"{dir}/lib/python3.10/site-packages",
|
||||
],
|
||||
"PY_PIP": [f"{dir}/Scripts", f"{dir}/bin"],
|
||||
"PIP_INSTALLER_LOCATION": [], # [f"{dir}/python/get-pip.py"],
|
||||
"TRANSFORMERS_CACHE": [f"{dir}/transformers-cache"],
|
||||
"HF_HUB_DISABLE_SYMLINKS_WARNING": ["true"],
|
||||
"COMMANDLINE_ARGS": [f'--api --models-dir "{models_dir}" {model_path_args} --skip-torch-cuda-test'],
|
||||
"SKIP_VENV": ["1"],
|
||||
"SD_WEBUI_RESTARTING": ["1"],
|
||||
}
|
||||
|
||||
if OS_NAME == "Windows":
|
||||
env_entries["PATH"].append("C:/Windows/System32")
|
||||
env_entries["PATH"].append("C:/Windows/System32/wbem")
|
||||
env_entries["PYTHONNOUSERSITE"] = ["1"]
|
||||
env_entries["PYTHON"] = [f"{dir}/python"]
|
||||
env_entries["GIT"] = [f"{dir}/Library/bin/git"]
|
||||
else:
|
||||
env_entries["PATH"].append("/bin")
|
||||
env_entries["PATH"].append("/usr/bin")
|
||||
env_entries["PATH"].append("/usr/sbin")
|
||||
env_entries["PYTHONNOUSERSITE"] = ["y"]
|
||||
env_entries["PYTHON"] = [f"{dir}/bin/python"]
|
||||
env_entries["GIT"] = [f"{dir}/bin/git"]
|
||||
env_entries["venv_dir"] = ["-"]
|
||||
|
||||
if OS_NAME == "Darwin":
|
||||
# based on https://github.com/lllyasviel/stable-diffusion-webui-forge/blob/e26abf87ecd1eefd9ab0a198eee56f9c643e4001/webui-macos-env.sh
|
||||
# hack - have to define these here, otherwise webui-macos-env.sh will overwrite COMMANDLINE_ARGS
|
||||
env_entries["COMMANDLINE_ARGS"][0] += " --upcast-sampling --no-half-vae --use-cpu interrogate"
|
||||
env_entries["PYTORCH_ENABLE_MPS_FALLBACK"] = ["1"]
|
||||
|
||||
cpu_name = str(subprocess.check_output(["sysctl", "-n", "machdep.cpu.brand_string"]))
|
||||
if "Intel" in cpu_name:
|
||||
env_entries["TORCH_COMMAND"] = ["pip install torch==2.1.2 torchvision==0.16.2"]
|
||||
else:
|
||||
env_entries["TORCH_COMMAND"] = ["pip install torch==2.3.1 torchvision==0.18.1"]
|
||||
else:
|
||||
import torch
|
||||
from easydiffusion.device_manager import needs_to_force_full_precision, is_cuda_available
|
||||
|
||||
vram_usage_level = config.get("vram_usage_level", "balanced")
|
||||
if config.get("render_devices", "auto") == "cpu" or not has_discrete_graphics_card() or not is_cuda_available():
|
||||
env_entries["COMMANDLINE_ARGS"][0] += " --always-cpu"
|
||||
else:
|
||||
c = local()
|
||||
c.device_name = torch.cuda.get_device_name()
|
||||
|
||||
if needs_to_force_full_precision(c):
|
||||
env_entries["COMMANDLINE_ARGS"][0] += " --no-half --precision full"
|
||||
|
||||
if vram_usage_level == "low":
|
||||
env_entries["COMMANDLINE_ARGS"][0] += " --always-low-vram"
|
||||
elif vram_usage_level == "high":
|
||||
env_entries["COMMANDLINE_ARGS"][0] += " --always-high-vram"
|
||||
|
||||
env = {}
|
||||
for key, paths in env_entries.items():
|
||||
paths = [p.replace("/", os.path.sep) for p in paths]
|
||||
paths = os.pathsep.join(paths)
|
||||
|
||||
env[key] = paths
|
||||
|
||||
return env
|
||||
|
||||
|
||||
def has_discrete_graphics_card():
|
||||
system = OS_NAME
|
||||
|
||||
if system == "Windows":
|
||||
try:
|
||||
output = subprocess.check_output(
|
||||
["wmic", "path", "win32_videocontroller", "get", "name"], stderr=subprocess.STDOUT
|
||||
)
|
||||
# Filter for discrete graphics cards (NVIDIA, AMD, etc.)
|
||||
discrete_gpus = ["NVIDIA", "AMD", "ATI"]
|
||||
return any(gpu in output.decode() for gpu in discrete_gpus)
|
||||
except subprocess.CalledProcessError:
|
||||
return False
|
||||
|
||||
elif system == "Linux":
|
||||
try:
|
||||
output = subprocess.check_output(["lspci"], stderr=subprocess.STDOUT)
|
||||
# Check for discrete GPUs (NVIDIA, AMD)
|
||||
discrete_gpus = ["NVIDIA", "AMD", "Advanced Micro Devices"]
|
||||
return any(gpu in line for line in output.decode().splitlines() for gpu in discrete_gpus)
|
||||
except subprocess.CalledProcessError:
|
||||
return False
|
||||
|
||||
elif system == "Darwin": # macOS
|
||||
try:
|
||||
output = subprocess.check_output(["system_profiler", "SPDisplaysDataType"], stderr=subprocess.STDOUT)
|
||||
# Check for discrete GPU in the output
|
||||
return "NVIDIA" in output.decode() or "AMD" in output.decode()
|
||||
except subprocess.CalledProcessError:
|
||||
return False
|
||||
|
||||
return False
|
||||
|
||||
|
||||
# https://stackoverflow.com/a/25134985
|
||||
def kill(proc_pid):
|
||||
process = psutil.Process(proc_pid)
|
||||
for proc in process.children(recursive=True):
|
||||
proc.kill()
|
||||
process.kill()
|
||||
|
||||
|
||||
def get_model_path_args():
|
||||
args = []
|
||||
for model_type, flag in MODELS_TO_OVERRIDE.items():
|
||||
model_dir = get_model_dirs(model_type)[0]
|
||||
args.append(f'{flag} "{model_dir}"')
|
||||
|
||||
return " ".join(args)
|
||||
@ -1,654 +0,0 @@
|
||||
import os
|
||||
import requests
|
||||
from requests.exceptions import ConnectTimeout, ConnectionError
|
||||
from typing import Union, List
|
||||
from threading import local as Context
|
||||
from threading import Thread
|
||||
import uuid
|
||||
import time
|
||||
from copy import deepcopy
|
||||
|
||||
from sdkit.utils import base64_str_to_img, img_to_base64_str
|
||||
|
||||
WEBUI_HOST = "localhost"
|
||||
WEBUI_PORT = "7860"
|
||||
|
||||
DEFAULT_WEBUI_OPTIONS = {
|
||||
"show_progress_every_n_steps": 3,
|
||||
"show_progress_grid": True,
|
||||
"live_previews_enable": False,
|
||||
"forge_additional_modules": [],
|
||||
}
|
||||
|
||||
|
||||
webui_opts: dict = None
|
||||
|
||||
|
||||
curr_models = {
|
||||
"stable-diffusion": None,
|
||||
"vae": None,
|
||||
}
|
||||
|
||||
|
||||
def set_options(context, **kwargs):
|
||||
changed_opts = {}
|
||||
|
||||
opts_mapping = {
|
||||
"stream_image_progress": ("live_previews_enable", bool),
|
||||
"stream_image_progress_interval": ("show_progress_every_n_steps", int),
|
||||
"clip_skip": ("CLIP_stop_at_last_layers", int),
|
||||
"clip_skip_sdxl": ("sdxl_clip_l_skip", bool),
|
||||
"output_format": ("samples_format", str),
|
||||
}
|
||||
|
||||
for ed_key, webui_key in opts_mapping.items():
|
||||
webui_key, webui_type = webui_key
|
||||
|
||||
if ed_key in kwargs and (webui_opts is None or webui_opts.get(webui_key, False) != webui_type(kwargs[ed_key])):
|
||||
changed_opts[webui_key] = webui_type(kwargs[ed_key])
|
||||
|
||||
if changed_opts:
|
||||
changed_opts["sd_model_checkpoint"] = curr_models["stable-diffusion"]
|
||||
|
||||
print(f"Got options: {kwargs}. Sending options: {changed_opts}")
|
||||
|
||||
try:
|
||||
res = webui_post("/sdapi/v1/options", json=changed_opts)
|
||||
if res.status_code != 200:
|
||||
raise Exception(res.text)
|
||||
|
||||
webui_opts.update(changed_opts)
|
||||
except Exception as e:
|
||||
print(f"Error setting options: {e}")
|
||||
|
||||
|
||||
def ping(timeout=1):
|
||||
"timeout (in seconds)"
|
||||
|
||||
global webui_opts
|
||||
|
||||
try:
|
||||
res = webui_get("/internal/ping", timeout=timeout)
|
||||
|
||||
if res.status_code != 200:
|
||||
raise ConnectTimeout(res.text)
|
||||
|
||||
if webui_opts is None:
|
||||
try:
|
||||
res = webui_post("/sdapi/v1/options", json=DEFAULT_WEBUI_OPTIONS)
|
||||
if res.status_code != 200:
|
||||
raise Exception(res.text)
|
||||
except Exception as e:
|
||||
print(f"Error setting options: {e}")
|
||||
|
||||
try:
|
||||
res = webui_get("/sdapi/v1/options")
|
||||
if res.status_code != 200:
|
||||
raise Exception(res.text)
|
||||
|
||||
webui_opts = res.json()
|
||||
except Exception as e:
|
||||
print(f"Error getting options: {e}")
|
||||
|
||||
return True
|
||||
except (ConnectTimeout, ConnectionError) as e:
|
||||
raise TimeoutError(e)
|
||||
|
||||
|
||||
def load_model(context, model_type, **kwargs):
|
||||
model_path = context.model_paths[model_type]
|
||||
|
||||
if webui_opts is None:
|
||||
print("Server not ready, can't set the model")
|
||||
return
|
||||
|
||||
if model_type == "stable-diffusion":
|
||||
model_name = os.path.basename(model_path)
|
||||
model_name = os.path.splitext(model_name)[0]
|
||||
print(f"setting sd model: {model_name}")
|
||||
if curr_models[model_type] != model_name:
|
||||
try:
|
||||
res = webui_post("/sdapi/v1/options", json={"sd_model_checkpoint": model_name})
|
||||
if res.status_code != 200:
|
||||
raise Exception(res.text)
|
||||
except Exception as e:
|
||||
raise RuntimeError(
|
||||
f"The engine failed to set the required options. Please check the logs in the command line window for more details."
|
||||
)
|
||||
|
||||
curr_models[model_type] = model_name
|
||||
elif model_type == "vae":
|
||||
if curr_models[model_type] != model_path:
|
||||
vae_model = [model_path] if model_path else []
|
||||
|
||||
opts = {"sd_model_checkpoint": curr_models["stable-diffusion"], "forge_additional_modules": vae_model}
|
||||
print("setting opts 2", opts)
|
||||
|
||||
try:
|
||||
res = webui_post("/sdapi/v1/options", json=opts)
|
||||
if res.status_code != 200:
|
||||
raise Exception(res.text)
|
||||
except Exception as e:
|
||||
raise RuntimeError(
|
||||
f"The engine failed to set the required options. Please check the logs in the command line window for more details."
|
||||
)
|
||||
|
||||
curr_models[model_type] = model_path
|
||||
|
||||
|
||||
def unload_model(context, model_type, **kwargs):
|
||||
if model_type == "vae":
|
||||
context.model_paths[model_type] = None
|
||||
load_model(context, model_type)
|
||||
|
||||
|
||||
def generate_images(
|
||||
context: Context,
|
||||
prompt: str = "",
|
||||
negative_prompt: str = "",
|
||||
seed: int = 42,
|
||||
width: int = 512,
|
||||
height: int = 512,
|
||||
num_outputs: int = 1,
|
||||
num_inference_steps: int = 25,
|
||||
guidance_scale: float = 7.5,
|
||||
distilled_guidance_scale: float = 3.5,
|
||||
init_image=None,
|
||||
init_image_mask=None,
|
||||
control_image=None,
|
||||
control_alpha=1.0,
|
||||
controlnet_filter=None,
|
||||
prompt_strength: float = 0.8,
|
||||
preserve_init_image_color_profile=False,
|
||||
strict_mask_border=False,
|
||||
sampler_name: str = "euler_a",
|
||||
scheduler_name: str = "simple",
|
||||
hypernetwork_strength: float = 0,
|
||||
tiling=None,
|
||||
lora_alpha: Union[float, List[float]] = 0,
|
||||
sampler_params={},
|
||||
callback=None,
|
||||
output_type="pil",
|
||||
):
|
||||
|
||||
task_id = str(uuid.uuid4())
|
||||
|
||||
sampler_name = convert_ED_sampler_names(sampler_name)
|
||||
controlnet_filter = convert_ED_controlnet_filter_name(controlnet_filter)
|
||||
|
||||
cmd = {
|
||||
"force_task_id": task_id,
|
||||
"prompt": prompt,
|
||||
"negative_prompt": negative_prompt,
|
||||
"sampler_name": sampler_name,
|
||||
"scheduler": scheduler_name,
|
||||
"steps": num_inference_steps,
|
||||
"seed": seed,
|
||||
"cfg_scale": guidance_scale,
|
||||
"distilled_cfg_scale": distilled_guidance_scale,
|
||||
"batch_size": num_outputs,
|
||||
"width": width,
|
||||
"height": height,
|
||||
}
|
||||
|
||||
if init_image:
|
||||
cmd["init_images"] = [init_image]
|
||||
cmd["denoising_strength"] = prompt_strength
|
||||
if init_image_mask:
|
||||
cmd["mask"] = init_image_mask
|
||||
cmd["include_init_images"] = True
|
||||
cmd["inpainting_fill"] = 1
|
||||
cmd["initial_noise_multiplier"] = 1
|
||||
cmd["inpaint_full_res"] = 1
|
||||
|
||||
if context.model_paths.get("lora"):
|
||||
lora_model = context.model_paths["lora"]
|
||||
lora_model = lora_model if isinstance(lora_model, list) else [lora_model]
|
||||
lora_alpha = lora_alpha if isinstance(lora_alpha, list) else [lora_alpha]
|
||||
|
||||
for lora, alpha in zip(lora_model, lora_alpha):
|
||||
lora = os.path.basename(lora)
|
||||
lora = os.path.splitext(lora)[0]
|
||||
cmd["prompt"] += f" <lora:{lora}:{alpha}>"
|
||||
|
||||
if controlnet_filter and control_image and context.model_paths.get("controlnet"):
|
||||
controlnet_model = context.model_paths["controlnet"]
|
||||
|
||||
model_hash = auto1111_hash(controlnet_model)
|
||||
controlnet_model = os.path.basename(controlnet_model)
|
||||
controlnet_model = os.path.splitext(controlnet_model)[0]
|
||||
print(f"setting controlnet model: {controlnet_model}")
|
||||
controlnet_model = f"{controlnet_model} [{model_hash}]"
|
||||
|
||||
cmd["alwayson_scripts"] = {
|
||||
"controlnet": {
|
||||
"args": [
|
||||
{
|
||||
"image": control_image,
|
||||
"weight": control_alpha,
|
||||
"module": controlnet_filter,
|
||||
"model": controlnet_model,
|
||||
"resize_mode": "Crop and Resize",
|
||||
"threshold_a": 50,
|
||||
"threshold_b": 130,
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
operation_to_apply = "img2img" if init_image else "txt2img"
|
||||
|
||||
stream_image_progress = webui_opts.get("live_previews_enable", False)
|
||||
|
||||
progress_thread = Thread(
|
||||
target=image_progress_thread, args=(task_id, callback, stream_image_progress, num_outputs, num_inference_steps)
|
||||
)
|
||||
progress_thread.start()
|
||||
|
||||
print(f"task id: {task_id}")
|
||||
print_request(operation_to_apply, cmd)
|
||||
|
||||
res = webui_post(f"/sdapi/v1/{operation_to_apply}", json=cmd)
|
||||
if res.status_code == 200:
|
||||
res = res.json()
|
||||
else:
|
||||
raise Exception(
|
||||
"The engine failed while generating this image. Please check the logs in the command-line window for more details."
|
||||
)
|
||||
|
||||
import json
|
||||
|
||||
print(json.loads(res["info"])["infotexts"])
|
||||
|
||||
images = res["images"]
|
||||
if output_type == "pil":
|
||||
images = [base64_str_to_img(img) for img in images]
|
||||
elif output_type == "base64":
|
||||
images = [base64_buffer_to_base64_img(img) for img in images]
|
||||
|
||||
return images
|
||||
|
||||
|
||||
def filter_images(context: Context, images, filters, filter_params={}, input_type="pil"):
|
||||
"""
|
||||
* context: Context
|
||||
* images: str or PIL.Image or list of str/PIL.Image - image to filter. if a string is passed, it needs to be a base64-encoded image
|
||||
* filters: filter_type (string) or list of strings
|
||||
* filter_params: dict
|
||||
|
||||
returns: [PIL.Image] - list of filtered images
|
||||
"""
|
||||
images = images if isinstance(images, list) else [images]
|
||||
filters = filters if isinstance(filters, list) else [filters]
|
||||
|
||||
if "nsfw_checker" in filters:
|
||||
filters.remove("nsfw_checker") # handled by ED directly
|
||||
|
||||
args = {}
|
||||
controlnet_filters = []
|
||||
|
||||
print(filter_params)
|
||||
|
||||
for filter_name in filters:
|
||||
params = filter_params.get(filter_name, {})
|
||||
|
||||
if filter_name == "gfpgan":
|
||||
args["gfpgan_visibility"] = 1
|
||||
|
||||
if filter_name in ("realesrgan", "esrgan_4x", "lanczos", "nearest", "scunet", "swinir"):
|
||||
args["upscaler_1"] = params.get("upscaler", "RealESRGAN_x4plus")
|
||||
args["upscaling_resize"] = params.get("scale", 4)
|
||||
|
||||
if args["upscaler_1"] == "RealESRGAN_x4plus":
|
||||
args["upscaler_1"] = "R-ESRGAN 4x+"
|
||||
elif args["upscaler_1"] == "RealESRGAN_x4plus_anime_6B":
|
||||
args["upscaler_1"] = "R-ESRGAN 4x+ Anime6B"
|
||||
|
||||
if filter_name == "codeformer":
|
||||
args["codeformer_visibility"] = 1
|
||||
args["codeformer_weight"] = params.get("codeformer_fidelity", 0.5)
|
||||
|
||||
if filter_name.startswith("controlnet_"):
|
||||
filter_name = convert_ED_controlnet_filter_name(filter_name)
|
||||
controlnet_filters.append(filter_name)
|
||||
|
||||
print(f"filtering {len(images)} images with {args}. {controlnet_filters=}")
|
||||
|
||||
if len(filters) > len(controlnet_filters):
|
||||
filtered_images = extra_batch_images(images, input_type=input_type, **args)
|
||||
else:
|
||||
filtered_images = images
|
||||
|
||||
for filter_name in controlnet_filters:
|
||||
filtered_images = controlnet_filter(filtered_images, module=filter_name, input_type=input_type)
|
||||
|
||||
return filtered_images
|
||||
|
||||
|
||||
def get_url():
|
||||
return f"//{WEBUI_HOST}:{WEBUI_PORT}/?__theme=dark"
|
||||
|
||||
|
||||
def stop_rendering(context):
|
||||
try:
|
||||
res = webui_post("/sdapi/v1/interrupt")
|
||||
if res.status_code != 200:
|
||||
raise Exception(res.text)
|
||||
except Exception as e:
|
||||
print(f"Error interrupting webui: {e}")
|
||||
|
||||
|
||||
def refresh_models():
|
||||
def make_refresh_call(type):
|
||||
try:
|
||||
webui_post(f"/sdapi/v1/refresh-{type}")
|
||||
except:
|
||||
pass
|
||||
|
||||
try:
|
||||
for type in ("checkpoints", "vae"):
|
||||
t = Thread(target=make_refresh_call, args=(type,))
|
||||
t.start()
|
||||
except Exception as e:
|
||||
print(f"Error refreshing models: {e}")
|
||||
|
||||
|
||||
def list_controlnet_filters():
|
||||
return [
|
||||
"openpose",
|
||||
"openpose_face",
|
||||
"openpose_faceonly",
|
||||
"openpose_hand",
|
||||
"openpose_full",
|
||||
"animal_openpose",
|
||||
"densepose_parula (black bg & blue torso)",
|
||||
"densepose (pruple bg & purple torso)",
|
||||
"dw_openpose_full",
|
||||
"mediapipe_face",
|
||||
"instant_id_face_keypoints",
|
||||
"InsightFace+CLIP-H (IPAdapter)",
|
||||
"InsightFace (InstantID)",
|
||||
"canny",
|
||||
"mlsd",
|
||||
"scribble_hed",
|
||||
"scribble_hedsafe",
|
||||
"scribble_pidinet",
|
||||
"scribble_pidsafe",
|
||||
"scribble_xdog",
|
||||
"softedge_hed",
|
||||
"softedge_hedsafe",
|
||||
"softedge_pidinet",
|
||||
"softedge_pidsafe",
|
||||
"softedge_teed",
|
||||
"normal_bae",
|
||||
"depth_midas",
|
||||
"normal_midas",
|
||||
"depth_zoe",
|
||||
"depth_leres",
|
||||
"depth_leres++",
|
||||
"depth_anything_v2",
|
||||
"depth_anything",
|
||||
"depth_hand_refiner",
|
||||
"depth_marigold",
|
||||
"lineart_coarse",
|
||||
"lineart_realistic",
|
||||
"lineart_anime",
|
||||
"lineart_standard (from white bg & black line)",
|
||||
"lineart_anime_denoise",
|
||||
"reference_adain",
|
||||
"reference_only",
|
||||
"reference_adain+attn",
|
||||
"tile_colorfix",
|
||||
"tile_resample",
|
||||
"tile_colorfix+sharp",
|
||||
"CLIP-ViT-H (IPAdapter)",
|
||||
"CLIP-G (Revision)",
|
||||
"CLIP-G (Revision ignore prompt)",
|
||||
"CLIP-ViT-bigG (IPAdapter)",
|
||||
"InsightFace+CLIP-H (IPAdapter)",
|
||||
"inpaint_only",
|
||||
"inpaint_only+lama",
|
||||
"inpaint_global_harmonious",
|
||||
"seg_ufade20k",
|
||||
"seg_ofade20k",
|
||||
"seg_anime_face",
|
||||
"seg_ofcoco",
|
||||
"shuffle",
|
||||
"segment",
|
||||
"invert (from white bg & black line)",
|
||||
"threshold",
|
||||
"t2ia_sketch_pidi",
|
||||
"t2ia_color_grid",
|
||||
"recolor_intensity",
|
||||
"recolor_luminance",
|
||||
"blur_gaussian",
|
||||
]
|
||||
|
||||
|
||||
def controlnet_filter(images, module="none", processor_res=512, threshold_a=64, threshold_b=64, input_type="pil"):
|
||||
if input_type == "pil":
|
||||
images = [img_to_base64_str(x) for x in images]
|
||||
|
||||
payload = {
|
||||
"controlnet_module": module,
|
||||
"controlnet_input_images": images,
|
||||
"controlnet_processor_res": processor_res,
|
||||
"controlnet_threshold_a": threshold_a,
|
||||
"controlnet_threshold_b": threshold_b,
|
||||
}
|
||||
res = webui_post("/controlnet/detect", json=payload)
|
||||
res = res.json()
|
||||
filtered_images = res["images"]
|
||||
|
||||
if input_type == "pil":
|
||||
filtered_images = [base64_str_to_img(img) for img in filtered_images]
|
||||
elif input_type == "base64":
|
||||
filtered_images = [base64_buffer_to_base64_img(img) for img in filtered_images]
|
||||
|
||||
return filtered_images
|
||||
|
||||
|
||||
def image_progress_thread(task_id, callback, stream_image_progress, total_images, total_steps):
|
||||
from PIL import Image
|
||||
|
||||
last_preview_id = -1
|
||||
|
||||
EMPTY_IMAGE = Image.new("RGB", (1, 1))
|
||||
|
||||
while True:
|
||||
res = webui_post(
|
||||
f"/internal/progress",
|
||||
json={"id_task": task_id, "live_preview": stream_image_progress, "id_live_preview": last_preview_id},
|
||||
)
|
||||
if res.status_code == 200:
|
||||
res = res.json()
|
||||
else:
|
||||
raise RuntimeError(f"Unexpected progress response. Status code: {res.status_code}. Res: {res.text}")
|
||||
|
||||
last_preview_id = res["id_live_preview"]
|
||||
|
||||
if res["progress"] is not None:
|
||||
step_num = int(res["progress"] * total_steps)
|
||||
|
||||
if res["live_preview"] is not None:
|
||||
img = res["live_preview"]
|
||||
img = base64_str_to_img(img)
|
||||
images = [EMPTY_IMAGE] * total_images
|
||||
images[0] = img
|
||||
else:
|
||||
images = None
|
||||
|
||||
callback(images, step_num)
|
||||
|
||||
if res["completed"] == True:
|
||||
print("Complete!")
|
||||
break
|
||||
|
||||
time.sleep(0.5)
|
||||
|
||||
|
||||
def webui_get(uri, *args, **kwargs):
|
||||
url = f"http://{WEBUI_HOST}:{WEBUI_PORT}{uri}"
|
||||
return requests.get(url, *args, **kwargs)
|
||||
|
||||
|
||||
def webui_post(uri, *args, **kwargs):
|
||||
url = f"http://{WEBUI_HOST}:{WEBUI_PORT}{uri}"
|
||||
return requests.post(url, *args, **kwargs)
|
||||
|
||||
|
||||
def print_request(operation_to_apply, args):
|
||||
args = deepcopy(args)
|
||||
if "init_images" in args:
|
||||
args["init_images"] = ["img" for _ in args["init_images"]]
|
||||
if "mask" in args:
|
||||
args["mask"] = "mask_img"
|
||||
|
||||
controlnet_args = args.get("alwayson_scripts", {}).get("controlnet", {}).get("args", [])
|
||||
if controlnet_args:
|
||||
controlnet_args[0]["image"] = "control_image"
|
||||
|
||||
print(f"operation: {operation_to_apply}, args: {args}")
|
||||
|
||||
|
||||
def auto1111_hash(file_path):
|
||||
import hashlib
|
||||
|
||||
with open(file_path, "rb") as f:
|
||||
f.seek(0x100000)
|
||||
b = f.read(0x10000)
|
||||
return hashlib.sha256(b).hexdigest()[:8]
|
||||
|
||||
|
||||
def extra_batch_images(
|
||||
images, # list of PIL images
|
||||
name_list=None, # list of image names
|
||||
resize_mode=0,
|
||||
show_extras_results=True,
|
||||
gfpgan_visibility=0,
|
||||
codeformer_visibility=0,
|
||||
codeformer_weight=0,
|
||||
upscaling_resize=2,
|
||||
upscaling_resize_w=512,
|
||||
upscaling_resize_h=512,
|
||||
upscaling_crop=True,
|
||||
upscaler_1="None",
|
||||
upscaler_2="None",
|
||||
extras_upscaler_2_visibility=0,
|
||||
upscale_first=False,
|
||||
use_async=False,
|
||||
input_type="pil",
|
||||
):
|
||||
if name_list is not None:
|
||||
if len(name_list) != len(images):
|
||||
raise RuntimeError("len(images) != len(name_list)")
|
||||
else:
|
||||
name_list = [f"image{i + 1:05}" for i in range(len(images))]
|
||||
|
||||
if input_type == "pil":
|
||||
images = [img_to_base64_str(x) for x in images]
|
||||
|
||||
image_list = []
|
||||
for name, image in zip(name_list, images):
|
||||
image_list.append({"data": image, "name": name})
|
||||
|
||||
payload = {
|
||||
"resize_mode": resize_mode,
|
||||
"show_extras_results": show_extras_results,
|
||||
"gfpgan_visibility": gfpgan_visibility,
|
||||
"codeformer_visibility": codeformer_visibility,
|
||||
"codeformer_weight": codeformer_weight,
|
||||
"upscaling_resize": upscaling_resize,
|
||||
"upscaling_resize_w": upscaling_resize_w,
|
||||
"upscaling_resize_h": upscaling_resize_h,
|
||||
"upscaling_crop": upscaling_crop,
|
||||
"upscaler_1": upscaler_1,
|
||||
"upscaler_2": upscaler_2,
|
||||
"extras_upscaler_2_visibility": extras_upscaler_2_visibility,
|
||||
"upscale_first": upscale_first,
|
||||
"imageList": image_list,
|
||||
}
|
||||
|
||||
res = webui_post("/sdapi/v1/extra-batch-images", json=payload)
|
||||
if res.status_code == 200:
|
||||
res = res.json()
|
||||
else:
|
||||
raise Exception(
|
||||
"The engine failed while filtering this image. Please check the logs in the command-line window for more details."
|
||||
)
|
||||
|
||||
images = res["images"]
|
||||
|
||||
if input_type == "pil":
|
||||
images = [base64_str_to_img(img) for img in images]
|
||||
elif input_type == "base64":
|
||||
images = [base64_buffer_to_base64_img(img) for img in images]
|
||||
|
||||
return images
|
||||
|
||||
|
||||
def base64_buffer_to_base64_img(img):
|
||||
output_format = webui_opts.get("samples_format", "jpeg")
|
||||
mime_type = f"image/{output_format.lower()}"
|
||||
return f"data:{mime_type};base64," + img
|
||||
|
||||
|
||||
def convert_ED_sampler_names(sampler_name):
|
||||
name_mapping = {
|
||||
"dpmpp_2m": "DPM++ 2M",
|
||||
"dpmpp_sde": "DPM++ SDE",
|
||||
"dpmpp_2m_sde": "DPM++ 2M SDE",
|
||||
"dpmpp_2m_sde_heun": "DPM++ 2M SDE Heun",
|
||||
"dpmpp_2s_a": "DPM++ 2S a",
|
||||
"dpmpp_3m_sde": "DPM++ 3M SDE",
|
||||
"euler_a": "Euler a",
|
||||
"euler": "Euler",
|
||||
"lms": "LMS",
|
||||
"heun": "Heun",
|
||||
"dpm2": "DPM2",
|
||||
"dpm2_a": "DPM2 a",
|
||||
"dpm_fast": "DPM fast",
|
||||
"dpm_adaptive": "DPM adaptive",
|
||||
"restart": "Restart",
|
||||
"heun_pp2": "HeunPP2",
|
||||
"ipndm": "IPNDM",
|
||||
"ipndm_v": "IPNDM_V",
|
||||
"deis": "DEIS",
|
||||
"ddim": "DDIM",
|
||||
"ddim_cfgpp": "DDIM CFG++",
|
||||
"plms": "PLMS",
|
||||
"unipc": "UniPC",
|
||||
"lcm": "LCM",
|
||||
"ddpm": "DDPM",
|
||||
"forge_flux_realistic": "[Forge] Flux Realistic",
|
||||
"forge_flux_realistic_slow": "[Forge] Flux Realistic (Slow)",
|
||||
# deprecated samplers in 3.5
|
||||
"dpm_solver_stability": None,
|
||||
"unipc_snr": None,
|
||||
"unipc_tu": None,
|
||||
"unipc_snr_2": None,
|
||||
"unipc_tu_2": None,
|
||||
"unipc_tq": None,
|
||||
}
|
||||
return name_mapping.get(sampler_name)
|
||||
|
||||
|
||||
def convert_ED_controlnet_filter_name(filter):
|
||||
if filter is None:
|
||||
return None
|
||||
|
||||
def cn(n):
|
||||
if n.startswith("controlnet_"):
|
||||
return n[len("controlnet_") :]
|
||||
return n
|
||||
|
||||
mapping = {
|
||||
"controlnet_scribble_hedsafe": None,
|
||||
"controlnet_scribble_pidsafe": None,
|
||||
"controlnet_softedge_pidsafe": "controlnet_softedge_pidisafe",
|
||||
"controlnet_normal_bae": "controlnet_normalbae",
|
||||
"controlnet_segment": None,
|
||||
}
|
||||
if isinstance(filter, list):
|
||||
return [cn(mapping.get(f, f)) for f in filter]
|
||||
return cn(mapping.get(filter, filter))
|
||||
@ -1,107 +0,0 @@
|
||||
from typing import List
|
||||
|
||||
from fastapi import Depends, FastAPI, HTTPException, Response, File
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from easydiffusion.easydb import crud, models, schemas
|
||||
from easydiffusion.easydb.database import SessionLocal, engine
|
||||
|
||||
from requests.compat import urlparse
|
||||
|
||||
import base64, json
|
||||
|
||||
MIME_TYPES = {
|
||||
"jpg": "image/jpeg",
|
||||
"jpeg": "image/jpeg",
|
||||
"gif": "image/gif",
|
||||
"png": "image/png",
|
||||
"webp": "image/webp",
|
||||
"js": "text/javascript",
|
||||
"htm": "text/html",
|
||||
"html": "text/html",
|
||||
"css": "text/css",
|
||||
"json": "application/json",
|
||||
"mjs": "application/json",
|
||||
"yaml": "application/yaml",
|
||||
"svg": "image/svg+xml",
|
||||
"txt": "text/plain",
|
||||
}
|
||||
|
||||
def init():
|
||||
from easydiffusion.server import server_api
|
||||
|
||||
models.BucketBase.metadata.create_all(bind=engine)
|
||||
|
||||
|
||||
# Dependency
|
||||
def get_db():
|
||||
db = SessionLocal()
|
||||
try:
|
||||
yield db
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
@server_api.get("/bucket/{obj_path:path}")
|
||||
def bucket_get_object(obj_path: str, db: Session = Depends(get_db)):
|
||||
filename = get_filename_from_url(obj_path)
|
||||
path = get_path_from_url(obj_path)
|
||||
|
||||
if filename==None:
|
||||
bucket = crud.get_bucket_by_path(db, path=path)
|
||||
if bucket == None:
|
||||
raise HTTPException(status_code=404, detail="Bucket not found")
|
||||
bucketfiles = db.query(models.BucketFile).with_entities(models.BucketFile.filename).filter(models.BucketFile.bucket_id == bucket.id).all()
|
||||
bucketfiles = [ x.filename for x in bucketfiles ]
|
||||
return bucketfiles
|
||||
|
||||
else:
|
||||
bucket = crud.get_bucket_by_path(db, path)
|
||||
if bucket == None:
|
||||
raise HTTPException(status_code=404, detail="Bucket not found")
|
||||
bucket_id = bucket.id
|
||||
bucketfile = db.query(models.BucketFile).filter(models.BucketFile.bucket_id == bucket_id, models.BucketFile.filename == filename).first()
|
||||
if bucketfile == None:
|
||||
raise HTTPException(status_code=404, detail="File not found")
|
||||
|
||||
suffix = get_suffix_from_filename(filename)
|
||||
|
||||
return Response(content=bucketfile.data, media_type=MIME_TYPES.get(suffix, "application/octet-stream"))
|
||||
|
||||
@server_api.post("/bucket/{obj_path:path}")
|
||||
def bucket_post_object(obj_path: str, file: bytes = File(), db: Session = Depends(get_db)):
|
||||
filename = get_filename_from_url(obj_path)
|
||||
path = get_path_from_url(obj_path)
|
||||
bucket = crud.get_bucket_by_path(db, path)
|
||||
|
||||
if bucket == None:
|
||||
bucket = crud.create_bucket(db=db, bucket=schemas.BucketCreate(path=path))
|
||||
bucket_id = bucket.id
|
||||
|
||||
bucketfile = schemas.BucketFileCreate(filename=filename, data=file)
|
||||
result = crud.create_bucketfile(db=db, bucketfile=bucketfile, bucket_id=bucket_id)
|
||||
result.data = base64.encodestring(result.data)
|
||||
return result
|
||||
|
||||
|
||||
@server_api.post("/buckets/{bucket_id}/items/", response_model=schemas.BucketFile)
|
||||
def create_bucketfile_in_bucket(
|
||||
bucket_id: int, bucketfile: schemas.BucketFileCreate, db: Session = Depends(get_db)
|
||||
):
|
||||
bucketfile.data = base64.decodestring(bucketfile.data)
|
||||
result = crud.create_bucketfile(db=db, bucketfile=bucketfile, bucket_id=bucket_id)
|
||||
result.data = base64.encodestring(result.data)
|
||||
return result
|
||||
|
||||
|
||||
def get_filename_from_url(url):
|
||||
path = urlparse(url).path
|
||||
name = path[path.rfind('/')+1:]
|
||||
return name or None
|
||||
|
||||
def get_path_from_url(url):
|
||||
path = urlparse(url).path
|
||||
path = path[0:path.rfind('/')]
|
||||
return path or None
|
||||
|
||||
def get_suffix_from_filename(filename):
|
||||
return filename[filename.rfind('.')+1:]
|
||||
@ -1,258 +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":
|
||||
if "/usr/sbin" not in os.environ["PATH"].split(os.pathsep):
|
||||
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"
|
||||
@ -1,24 +0,0 @@
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from easydiffusion.easydb import models, schemas
|
||||
|
||||
|
||||
def get_bucket_by_path(db: Session, path: str):
|
||||
return db.query(models.Bucket).filter(models.Bucket.path == path).first()
|
||||
|
||||
|
||||
def create_bucket(db: Session, bucket: schemas.BucketCreate):
|
||||
db_bucket = models.Bucket(path=bucket.path)
|
||||
db.add(db_bucket)
|
||||
db.commit()
|
||||
db.refresh(db_bucket)
|
||||
return db_bucket
|
||||
|
||||
|
||||
def create_bucketfile(db: Session, bucketfile: schemas.BucketFileCreate, bucket_id: int):
|
||||
db_bucketfile = models.BucketFile(**bucketfile.dict(), bucket_id=bucket_id)
|
||||
db.merge(db_bucketfile)
|
||||
db.commit()
|
||||
db_bucketfile = db.query(models.BucketFile).filter(models.BucketFile.bucket_id==bucket_id, models.BucketFile.filename==bucketfile.filename).first()
|
||||
return db_bucketfile
|
||||
|
||||
@ -1,14 +0,0 @@
|
||||
import os
|
||||
from easydiffusion import app
|
||||
|
||||
from sqlalchemy import create_engine
|
||||
from sqlalchemy.ext.declarative import declarative_base
|
||||
from sqlalchemy.orm import sessionmaker
|
||||
|
||||
os.makedirs(app.BUCKET_DIR, exist_ok=True)
|
||||
SQLALCHEMY_DATABASE_URL = "sqlite:///"+os.path.join(app.BUCKET_DIR, "bucket.db")
|
||||
|
||||
engine = create_engine(SQLALCHEMY_DATABASE_URL, connect_args={"check_same_thread": False})
|
||||
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
|
||||
|
||||
BucketBase = declarative_base()
|
||||
@ -1,25 +0,0 @@
|
||||
from sqlalchemy import Boolean, Column, ForeignKey, Integer, String, BLOB
|
||||
from sqlalchemy.orm import relationship
|
||||
|
||||
from easydiffusion.easydb.database import BucketBase
|
||||
|
||||
|
||||
class Bucket(BucketBase):
|
||||
__tablename__ = "bucket"
|
||||
|
||||
id = Column(Integer, primary_key=True, index=True)
|
||||
path = Column(String, unique=True, index=True)
|
||||
|
||||
bucketfiles = relationship("BucketFile", back_populates="bucket")
|
||||
|
||||
|
||||
class BucketFile(BucketBase):
|
||||
__tablename__ = "bucketfile"
|
||||
|
||||
filename = Column(String, index=True, primary_key=True)
|
||||
bucket_id = Column(Integer, ForeignKey("bucket.id"), primary_key=True)
|
||||
|
||||
data = Column(BLOB, index=False)
|
||||
|
||||
bucket = relationship("Bucket", back_populates="bucketfiles")
|
||||
|
||||
@ -1,35 +0,0 @@
|
||||
from typing import List, Union
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
class BucketFileBase(BaseModel):
|
||||
filename: str
|
||||
data: bytes
|
||||
|
||||
|
||||
class BucketFileCreate(BucketFileBase):
|
||||
pass
|
||||
|
||||
|
||||
class BucketFile(BucketFileBase):
|
||||
bucket_id: int
|
||||
|
||||
class Config:
|
||||
orm_mode = True
|
||||
|
||||
|
||||
class BucketBase(BaseModel):
|
||||
path: str
|
||||
|
||||
|
||||
class BucketCreate(BucketBase):
|
||||
pass
|
||||
|
||||
|
||||
class Bucket(BucketBase):
|
||||
id: int
|
||||
bucketfiles: List[BucketFile] = []
|
||||
|
||||
class Config:
|
||||
orm_mode = True
|
||||
@ -1,481 +0,0 @@
|
||||
import os
|
||||
import shutil
|
||||
from glob import glob
|
||||
import traceback
|
||||
from typing import Union
|
||||
|
||||
from easydiffusion import app
|
||||
from easydiffusion.types import ModelsData
|
||||
from easydiffusion.utils import log
|
||||
from sdkit import Context
|
||||
from sdkit.models import scan_model, download_model, get_model_info_from_db
|
||||
from sdkit.models.model_loader.controlnet_filters import filters as cn_filters
|
||||
from sdkit.utils import hash_file_quick
|
||||
from sdkit.models.model_loader.embeddings import get_embedding_token
|
||||
|
||||
KNOWN_MODEL_TYPES = [
|
||||
"stable-diffusion",
|
||||
"vae",
|
||||
"hypernetwork",
|
||||
"gfpgan",
|
||||
"realesrgan",
|
||||
"lora",
|
||||
"codeformer",
|
||||
"embeddings",
|
||||
"controlnet",
|
||||
]
|
||||
MODEL_EXTENSIONS = {
|
||||
"stable-diffusion": [".ckpt", ".safetensors", ".sft", ".gguf"],
|
||||
"vae": [".vae.pt", ".ckpt", ".safetensors", ".sft"],
|
||||
"hypernetwork": [".pt", ".safetensors", ".sft"],
|
||||
"gfpgan": [".pth"],
|
||||
"realesrgan": [".pth"],
|
||||
"lora": [".ckpt", ".safetensors", ".sft", ".pt"],
|
||||
"codeformer": [".pth"],
|
||||
"embeddings": [".pt", ".bin", ".safetensors", ".sft"],
|
||||
"controlnet": [".pth", ".safetensors", ".sft"],
|
||||
}
|
||||
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"]
|
||||
ALTERNATE_FOLDER_NAMES = { # for WebUI compatibility
|
||||
"stable-diffusion": "Stable-diffusion",
|
||||
"vae": "VAE",
|
||||
"hypernetwork": "hypernetworks",
|
||||
"codeformer": "Codeformer",
|
||||
"gfpgan": "GFPGAN",
|
||||
"realesrgan": "RealESRGAN",
|
||||
"lora": "Lora",
|
||||
"controlnet": "ControlNet",
|
||||
}
|
||||
|
||||
known_models = {}
|
||||
|
||||
|
||||
def init():
|
||||
make_model_folders()
|
||||
migrate_legacy_model_location() # if necessary
|
||||
download_default_models_if_necessary()
|
||||
|
||||
|
||||
def load_default_models(context: Context):
|
||||
from easydiffusion import runtime
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
runtime.set_vram_optimizations(context)
|
||||
|
||||
# init default model paths
|
||||
for model_type in MODELS_TO_LOAD_ON_START:
|
||||
context.model_paths[model_type] = resolve_model_to_use(model_type=model_type, fail_if_not_found=False)
|
||||
try:
|
||||
backend.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):
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
for model_type in KNOWN_MODEL_TYPES:
|
||||
backend.unload_model(context, model_type)
|
||||
if hasattr(context, "model_load_errors") and 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 = []
|
||||
for m in model_names:
|
||||
if model_type == "embeddings":
|
||||
try:
|
||||
resolve_model_to_use_single(m, model_type)
|
||||
except FileNotFoundError: # try with spaces
|
||||
m = m.replace("_", " ")
|
||||
|
||||
path = resolve_model_to_use_single(m, model_type, fail_if_not_found)
|
||||
model_paths.append(path)
|
||||
|
||||
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()
|
||||
|
||||
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]
|
||||
|
||||
for model_dir in get_model_dirs(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 FileNotFoundError(
|
||||
f"Could not find the desired model {model_name}! Is it present in the {model_dir} folder?"
|
||||
)
|
||||
|
||||
|
||||
def reload_models_if_necessary(context: Context, models_data: ModelsData, models_to_force_reload: list = []):
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
models_to_reload = {
|
||||
model_type: path
|
||||
for model_type, path in models_data.model_paths.items()
|
||||
if context.model_paths.get(model_type) != path or (path is not None and context.models.get(model_type) is None)
|
||||
}
|
||||
|
||||
if models_data.model_paths.get("codeformer"):
|
||||
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
|
||||
|
||||
for model_type in models_to_force_reload:
|
||||
if model_type not in models_data.model_paths:
|
||||
continue
|
||||
models_to_reload[model_type] = models_data.model_paths[model_type]
|
||||
|
||||
for model_type, model_path_in_req in models_to_reload.items():
|
||||
context.model_paths[model_type] = model_path_in_req
|
||||
|
||||
action_fn = backend.unload_model if context.model_paths[model_type] is None else backend.load_model
|
||||
extra_params = models_data.model_params.get(model_type, {})
|
||||
try:
|
||||
action_fn(context, model_type, scan_model=False, **extra_params) # 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 == backend.load_model:
|
||||
context.model_load_errors[model_type] = str(e) # storing the entire Exception can lead to memory leaks
|
||||
|
||||
|
||||
def resolve_model_paths(models_data: ModelsData):
|
||||
model_paths = models_data.model_paths
|
||||
skip_models = cn_filters + [
|
||||
"latent_upscaler",
|
||||
"nsfw_checker",
|
||||
"esrgan_4x",
|
||||
"lanczos",
|
||||
"nearest",
|
||||
"scunet",
|
||||
"swinir",
|
||||
]
|
||||
|
||||
for model_type in model_paths:
|
||||
if model_type in skip_models: # doesn't use model paths
|
||||
continue
|
||||
if model_type == "codeformer" and model_paths[model_type]:
|
||||
download_if_necessary("codeformer", "codeformer.pth", "codeformer-0.1.0")
|
||||
elif model_type == "controlnet" and model_paths[model_type]:
|
||||
model_id = model_paths[model_type]
|
||||
model_info = get_model_info_from_db(model_type=model_type, model_id=model_id)
|
||||
if model_info:
|
||||
filename = model_info.get("url", "").split("/")[-1]
|
||||
download_if_necessary("controlnet", filename, model_id, skip_if_others_exist=False)
|
||||
|
||||
model_paths[model_type] = resolve_model_to_use(model_paths[model_type], model_type=model_type)
|
||||
|
||||
|
||||
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, skip_if_others_exist=True):
|
||||
model_dir = get_model_dirs(model_type)[0]
|
||||
model_path = os.path.join(model_dir, 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) and skip_if_others_exist
|
||||
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, download_config_if_available=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):
|
||||
model_dir = get_model_dirs(model_type)[0]
|
||||
shutil.move(legacy_path, os.path.join(model_dir, file_name))
|
||||
|
||||
|
||||
def any_model_exists(model_type: str) -> bool:
|
||||
extensions = MODEL_EXTENSIONS.get(model_type, [])
|
||||
for model_dir in get_model_dirs(model_type):
|
||||
for ext in extensions:
|
||||
if any(glob(f"{model_dir}/**/*{ext}", recursive=True)):
|
||||
return True
|
||||
|
||||
return False
|
||||
|
||||
|
||||
def make_model_folders():
|
||||
for model_type in KNOWN_MODEL_TYPES:
|
||||
model_dir_path = get_model_dirs(model_type)[0]
|
||||
|
||||
try:
|
||||
os.makedirs(model_dir_path, exist_ok=True)
|
||||
except Exception as e:
|
||||
from rich.console import Console
|
||||
from rich.panel import Panel
|
||||
|
||||
Console().print(
|
||||
Panel(
|
||||
"\n"
|
||||
+ f"Error while creating the models directory: '{model_dir_path}'\n"
|
||||
+ f"Error: {e}\n\n"
|
||||
+ f"[white]Check the 'models_dir:' line in the file '{os.path.join(app.ROOT_DIR, 'config.yaml')}'.[/white]\n",
|
||||
title="Fatal Error starting Easy Diffusion",
|
||||
style="bold yellow on red",
|
||||
)
|
||||
)
|
||||
input("Press Enter to terminate...")
|
||||
exit(1)
|
||||
|
||||
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):
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
backend.refresh_models()
|
||||
|
||||
models = {
|
||||
"options": {
|
||||
"stable-diffusion": [],
|
||||
"vae": [],
|
||||
"hypernetwork": [],
|
||||
"lora": [],
|
||||
"codeformer": [{"codeformer": "CodeFormer"}],
|
||||
"embeddings": [],
|
||||
"controlnet": [
|
||||
# {"control_v11p_sd15_canny": "Canny (*)"},
|
||||
# {"control_v11p_sd15_openpose": "OpenPose (*)"},
|
||||
# {"control_v11p_sd15_normalbae": "Normal BAE (*)"},
|
||||
# {"control_v11f1p_sd15_depth": "Depth (*)"},
|
||||
# {"control_v11p_sd15_scribble": "Scribble"},
|
||||
# {"control_v11p_sd15_softedge": "Soft Edge"},
|
||||
# {"control_v11p_sd15_inpaint": "Inpaint"},
|
||||
# {"control_v11p_sd15_lineart": "Line Art"},
|
||||
# {"control_v11p_sd15s2_lineart_anime": "Line Art Anime"},
|
||||
# {"control_v11p_sd15_mlsd": "Straight Lines"},
|
||||
# {"control_v11p_sd15_seg": "Segment"},
|
||||
# {"control_v11e_sd15_shuffle": "Shuffle"},
|
||||
# {"control_v11f1e_sd15_tile": "Tile"},
|
||||
],
|
||||
},
|
||||
}
|
||||
|
||||
models_scanned = 0
|
||||
|
||||
class MaliciousModelException(Exception):
|
||||
"Raised when picklescan reports a problem with a model"
|
||||
|
||||
def scan_directory(directory, suffixes, directoriesFirst: bool = True, default_entries=[], nameFilter=None):
|
||||
nonlocal models_scanned
|
||||
|
||||
tree = list(default_entries)
|
||||
|
||||
if not os.path.exists(directory):
|
||||
return 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
|
||||
|
||||
model_id = entry.name[: -len(matching_suffix)]
|
||||
if callable(nameFilter):
|
||||
model_id = nameFilter(model_id)
|
||||
if model_id is None:
|
||||
continue
|
||||
|
||||
model_exists = False
|
||||
for m in tree: # allows default "named" models, like CodeFormer and known ControlNet models
|
||||
if (isinstance(m, str) and model_id == m) or (isinstance(m, dict) and model_id in m):
|
||||
model_exists = True
|
||||
break
|
||||
if not model_exists:
|
||||
tree.append(model_id)
|
||||
|
||||
elif entry.is_dir():
|
||||
scan = scan_directory(entry.path, suffixes, directoriesFirst=False, nameFilter=nameFilter)
|
||||
|
||||
if len(scan) != 0:
|
||||
tree.append((entry.name, scan))
|
||||
return tree
|
||||
|
||||
def listModels(model_type, nameFilter=None):
|
||||
nonlocal models_scanned
|
||||
|
||||
model_extensions = MODEL_EXTENSIONS.get(model_type, [])
|
||||
models_dirs = get_model_dirs(model_type)
|
||||
if not os.path.exists(models_dirs[0]):
|
||||
os.makedirs(models_dirs[0])
|
||||
|
||||
for model_dir in models_dirs:
|
||||
try:
|
||||
default_tree = models["options"].get(model_type, [])
|
||||
models["options"][model_type] = scan_directory(
|
||||
model_dir, model_extensions, default_entries=default_tree, nameFilter=nameFilter
|
||||
)
|
||||
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", nameFilter=lambda x: (x if "gfpgan" in x.lower() else None))
|
||||
listModels(model_type="lora")
|
||||
listModels(model_type="embeddings", nameFilter=get_embedding_token)
|
||||
listModels(model_type="controlnet")
|
||||
|
||||
if scan_for_malicious and models_scanned > 0:
|
||||
log.info(f"[green]Scanned {models_scanned} models. Nothing infected[/]")
|
||||
|
||||
return models
|
||||
|
||||
|
||||
def get_model_dirs(model_type: str, base_dir=None):
|
||||
"Returns the possible model directory paths for the given model type. Mainly used for WebUI compatibility"
|
||||
|
||||
if base_dir is None:
|
||||
base_dir = app.MODELS_DIR
|
||||
|
||||
dirs = [os.path.join(base_dir, model_type)]
|
||||
|
||||
if model_type in ALTERNATE_FOLDER_NAMES:
|
||||
alt_dir = ALTERNATE_FOLDER_NAMES[model_type]
|
||||
alt_dir = os.path.join(base_dir, alt_dir)
|
||||
if os.path.exists(alt_dir) and os.path.isdir(alt_dir):
|
||||
dirs.append(alt_dir)
|
||||
|
||||
return dirs
|
||||
@ -1,104 +0,0 @@
|
||||
import sys
|
||||
import os
|
||||
import platform
|
||||
from importlib.metadata import version as pkg_version
|
||||
|
||||
from easydiffusion import app
|
||||
|
||||
# future home of scripts/check_modules.py
|
||||
|
||||
manifest = {
|
||||
"tensorrt": {
|
||||
"install": [
|
||||
"wheel",
|
||||
"nvidia-cudnn-cu11==8.9.4.25",
|
||||
"tensorrt==9.0.0.post11.dev1 --pre --extra-index-url=https://pypi.nvidia.com --trusted-host pypi.nvidia.com",
|
||||
],
|
||||
"uninstall": ["tensorrt"],
|
||||
# TODO also uninstall tensorrt-libs and nvidia-cudnn, but do it upon restarting (avoid 'file in use' error)
|
||||
}
|
||||
}
|
||||
installing = []
|
||||
|
||||
# remove this once TRT releases on pypi
|
||||
if platform.system() == "Windows":
|
||||
trt_dir = os.path.join(app.ROOT_DIR, "tensorrt")
|
||||
if os.path.exists(trt_dir) and os.path.isdir(trt_dir) and len(os.listdir(trt_dir)) > 0:
|
||||
files = os.listdir(trt_dir)
|
||||
|
||||
packages = manifest["tensorrt"]["install"]
|
||||
packages = tuple(p.replace("-", "_") for p in packages)
|
||||
|
||||
wheels = []
|
||||
for p in packages:
|
||||
p = p.split(" ")[0]
|
||||
f = next((f for f in files if f.startswith(p) and f.endswith((".whl", ".tar.gz"))), None)
|
||||
if f:
|
||||
wheels.append(os.path.join(trt_dir, f))
|
||||
|
||||
manifest["tensorrt"]["install"] = wheels
|
||||
|
||||
|
||||
def get_installed_packages() -> list:
|
||||
return {module_name: version(module_name) for module_name in manifest if is_installed(module_name)}
|
||||
|
||||
|
||||
def is_installed(module_name) -> bool:
|
||||
return version(module_name) is not None
|
||||
|
||||
|
||||
def install(module_name):
|
||||
from easydiffusion.utils import log
|
||||
|
||||
if is_installed(module_name):
|
||||
log.info(f"{module_name} has already been installed!")
|
||||
return
|
||||
if module_name in installing:
|
||||
log.info(f"{module_name} is already installing!")
|
||||
return
|
||||
|
||||
if module_name not in manifest:
|
||||
raise RuntimeError(f"Can't install unknown package: {module_name}!")
|
||||
|
||||
commands = manifest[module_name]["install"]
|
||||
if module_name == "tensorrt":
|
||||
commands += [
|
||||
"protobuf==3.20.3 polygraphy==0.47.1 onnx==1.14.0 --extra-index-url=https://pypi.ngc.nvidia.com --trusted-host pypi.ngc.nvidia.com"
|
||||
]
|
||||
commands = [f"python -m pip install --upgrade {cmd}" for cmd in commands]
|
||||
|
||||
installing.append(module_name)
|
||||
|
||||
try:
|
||||
for cmd in commands:
|
||||
print(">", cmd)
|
||||
if os.system(cmd) != 0:
|
||||
raise RuntimeError(f"Error while running {cmd}. Please check the logs in the command-line.")
|
||||
finally:
|
||||
installing.remove(module_name)
|
||||
|
||||
|
||||
def uninstall(module_name):
|
||||
from easydiffusion.utils import log
|
||||
|
||||
if not is_installed(module_name):
|
||||
log.info(f"{module_name} hasn't been installed!")
|
||||
return
|
||||
|
||||
if module_name not in manifest:
|
||||
raise RuntimeError(f"Can't uninstall unknown package: {module_name}!")
|
||||
|
||||
commands = manifest[module_name]["uninstall"]
|
||||
commands = [f"python -m pip uninstall -y {cmd}" for cmd in commands]
|
||||
|
||||
for cmd in commands:
|
||||
print(">", cmd)
|
||||
if os.system(cmd) != 0:
|
||||
raise RuntimeError(f"Error while running {cmd}. Please check the logs in the command-line.")
|
||||
|
||||
|
||||
def version(module_name: str) -> str:
|
||||
try:
|
||||
return pkg_version(module_name)
|
||||
except:
|
||||
return None
|
||||
@ -1,45 +0,0 @@
|
||||
"""
|
||||
(OUTDATED DOC)
|
||||
A runtime that runs on a specific device (in a thread).
|
||||
|
||||
It can run various tasks like image generation, image filtering, model merge etc by using that thread-local context.
|
||||
|
||||
This creates an `sdkit.Context` that's bound to the device specified while calling the `init()` function.
|
||||
"""
|
||||
|
||||
context = None
|
||||
|
||||
|
||||
def init(device):
|
||||
"""
|
||||
Initializes the fields that will be bound to this runtime's context, and sets the current torch device
|
||||
"""
|
||||
|
||||
global context
|
||||
|
||||
from easydiffusion import device_manager
|
||||
from easydiffusion.backend_manager import backend
|
||||
from easydiffusion.app import getConfig
|
||||
|
||||
context = backend.create_context()
|
||||
|
||||
context.stop_processing = False
|
||||
context.temp_images = {}
|
||||
context.partial_x_samples = None
|
||||
context.model_load_errors = {}
|
||||
context.enable_codeformer = True
|
||||
|
||||
device_manager.device_init(context, device)
|
||||
|
||||
|
||||
def set_vram_optimizations(context):
|
||||
from easydiffusion.app import getConfig
|
||||
|
||||
config = 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
|
||||
@ -1,514 +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, package_manager
|
||||
from easydiffusion.tasks import RenderTask, FilterTask
|
||||
from easydiffusion.types import (
|
||||
GenerateImageRequest,
|
||||
FilterImageRequest,
|
||||
MergeRequest,
|
||||
TaskData,
|
||||
RenderTaskData,
|
||||
ModelsData,
|
||||
OutputFormatData,
|
||||
SaveToDiskData,
|
||||
convert_legacy_render_req_to_new,
|
||||
convert_legacy_controlnet_filter_name,
|
||||
)
|
||||
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",
|
||||
}
|
||||
PROTECTED_CONFIG_KEYS = ("block_nsfw",) # can't change these via the HTTP API
|
||||
|
||||
|
||||
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
|
||||
use_v3_engine: bool = True
|
||||
backend: str = "ed_diffusers"
|
||||
models_dir: str = None
|
||||
vram_usage_level: str = "balanced"
|
||||
|
||||
|
||||
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("/filter")
|
||||
def render(req: dict):
|
||||
return filter_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.post("/package/{package_name:str}")
|
||||
def modify_package(package_name: str, req: dict):
|
||||
return modify_package_internal(package_name, req)
|
||||
|
||||
@server_api.get("/sha256/{obj_path:path}")
|
||||
def get_sha256(obj_path: str):
|
||||
return get_sha256_internal(obj_path)
|
||||
|
||||
@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.")
|
||||
|
||||
@server_api.on_event("startup")
|
||||
def start_event():
|
||||
from easydiffusion.app import open_browser
|
||||
|
||||
open_browser()
|
||||
|
||||
|
||||
# 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["use_v3_engine"] = req.backend == "ed_diffusers"
|
||||
config["backend"] = req.backend
|
||||
config["models_dir"] = req.models_dir
|
||||
config["vram_usage_level"] = req.vram_usage_level
|
||||
|
||||
for property, property_value in req.dict().items():
|
||||
if property_value is not None and property not in req.__fields__ and property not in PROTECTED_CONFIG_KEYS:
|
||||
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":
|
||||
config = app.getConfig()
|
||||
|
||||
if "models_dir" not in config:
|
||||
config["models_dir"] = app.MODELS_DIR
|
||||
|
||||
return JSONResponse(config, headers=NOCACHE_HEADERS)
|
||||
elif key == "system_info":
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
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),
|
||||
"enforce_output_metadata": ("force_save_metadata" in config),
|
||||
"backend_url": backend.get_url(),
|
||||
}
|
||||
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()
|
||||
response["packages_installed"] = package_manager.get_installed_packages()
|
||||
response["packages_installing"] = package_manager.installing
|
||||
|
||||
if cloudflare.address != None:
|
||||
response["cloudflare"] = cloudflare.address
|
||||
|
||||
return JSONResponse(response, headers=NOCACHE_HEADERS)
|
||||
|
||||
|
||||
def render_internal(req: dict):
|
||||
try:
|
||||
req = convert_legacy_render_req_to_new(req)
|
||||
|
||||
# separate out the request data into rendering and task-specific data
|
||||
render_req: GenerateImageRequest = GenerateImageRequest.parse_obj(req)
|
||||
task_data: RenderTaskData = RenderTaskData.parse_obj(req)
|
||||
models_data: ModelsData = ModelsData.parse_obj(req)
|
||||
output_format: OutputFormatData = OutputFormatData.parse_obj(req)
|
||||
save_data: SaveToDiskData = SaveToDiskData.parse_obj(req)
|
||||
|
||||
# Overwrite user specified save path
|
||||
config = app.getConfig()
|
||||
if "force_save_path" in config:
|
||||
save_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(
|
||||
models_data.model_paths.get("stable-diffusion"),
|
||||
models_data.model_paths.get("vae"),
|
||||
models_data.model_paths.get("hypernetwork"),
|
||||
task_data.vram_usage_level,
|
||||
)
|
||||
|
||||
# enqueue the task
|
||||
task = RenderTask(render_req, task_data, models_data, output_format, save_data)
|
||||
return enqueue_task(task)
|
||||
except HTTPException as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
log.error(traceback.format_exc())
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
def filter_internal(req: dict):
|
||||
try:
|
||||
filter_req: FilterImageRequest = FilterImageRequest.parse_obj(req)
|
||||
task_data: TaskData = TaskData.parse_obj(req)
|
||||
models_data: ModelsData = ModelsData.parse_obj(req)
|
||||
output_format: OutputFormatData = OutputFormatData.parse_obj(req)
|
||||
save_data: SaveToDiskData = SaveToDiskData.parse_obj(req)
|
||||
|
||||
filter_req.filter = convert_legacy_controlnet_filter_name(filter_req.filter)
|
||||
|
||||
for model_name in ("realesrgan", "esrgan_4x", "lanczos", "nearest", "scunet", "swinir"):
|
||||
if models_data.model_paths.get(model_name):
|
||||
if model_name not in filter_req.filter_params:
|
||||
filter_req.filter_params[model_name] = {}
|
||||
|
||||
filter_req.filter_params[model_name]["upscaler"] = models_data.model_paths[model_name]
|
||||
|
||||
# enqueue the task
|
||||
task = FilterTask(filter_req, task_data, models_data, output_format, save_data)
|
||||
return enqueue_task(task)
|
||||
except HTTPException as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
log.error(traceback.format_exc())
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
def enqueue_task(task):
|
||||
try:
|
||||
task_manager.enqueue_task(task)
|
||||
response = {
|
||||
"status": str(task_manager.current_state),
|
||||
"queue": len(task_manager.tasks_queue),
|
||||
"stream": f"/image/stream/{task.id}",
|
||||
"task": task.id,
|
||||
}
|
||||
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
|
||||
|
||||
|
||||
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)
|
||||
|
||||
sd_model_dir = model_manager.get_model_dir("stable-diffusion")[0]
|
||||
|
||||
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(sd_model_dir, 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))
|
||||
|
||||
|
||||
def modify_package_internal(package_name: str, req: dict):
|
||||
try:
|
||||
cmd = req["command"]
|
||||
if cmd not in ("install", "uninstall"):
|
||||
raise RuntimeError(f"Unknown command: {cmd}")
|
||||
|
||||
cmd = getattr(package_manager, cmd)
|
||||
cmd(package_name)
|
||||
|
||||
return JSONResponse({"status": "OK"}, headers=NOCACHE_HEADERS)
|
||||
except Exception as e:
|
||||
log.error(str(e))
|
||||
log.error(traceback.format_exc())
|
||||
return HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
def get_sha256_internal(obj_path):
|
||||
from easydiffusion.utils import sha256sum
|
||||
|
||||
path = obj_path.split("/")
|
||||
type = path.pop(0)
|
||||
|
||||
try:
|
||||
model_path = model_manager.resolve_model_to_use("/".join(path), type)
|
||||
except Exception as e:
|
||||
log.error(str(e))
|
||||
log.error(traceback.format_exc())
|
||||
|
||||
return HTTPException(status_code=404)
|
||||
try:
|
||||
digest = sha256sum(model_path)
|
||||
return {"digest": digest}
|
||||
except Exception as e:
|
||||
log.error(str(e))
|
||||
log.error(traceback.format_exc())
|
||||
return HTTPException(status_code=500, detail=str(e))
|
||||
@ -1,525 +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.tasks import Task
|
||||
from easydiffusion.utils import log
|
||||
|
||||
THREAD_NAME_PREFIX = ""
|
||||
ERR_LOCK_FAILED = " failed to acquire lock within timeout."
|
||||
LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
|
||||
# It's better to get an exception than a deadlock... ALWAYS use timeout in critical paths.
|
||||
|
||||
DEVICE_START_TIMEOUT = 60 # seconds - Maximum time to wait for a render device to init.
|
||||
MAX_OVERLOAD_ALLOWED_RATIO = 2 # i.e. 2x pending tasks compared to the number of render threads
|
||||
|
||||
|
||||
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
|
||||
|
||||
|
||||
# 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, Task):
|
||||
log.debug(f"Task {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: Task, ttl=TASK_TTL):
|
||||
task_id = task.id
|
||||
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 keep_task_alive(task: Task):
|
||||
task_cache.keep(task.id, TASK_TTL)
|
||||
session_cache.keep(task.session_id, TASK_TTL)
|
||||
|
||||
|
||||
def thread_get_next_task():
|
||||
from easydiffusion import runtime
|
||||
|
||||
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
|
||||
log.warn(f"Render thread on device: {runtime.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 runtime.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 runtime.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, runtime
|
||||
from easydiffusion.backend_manager import backend
|
||||
from requests import ConnectionError
|
||||
|
||||
try:
|
||||
runtime.init(device)
|
||||
|
||||
weak_thread_data[threading.current_thread()] = {
|
||||
"device": runtime.context.device,
|
||||
"device_name": runtime.context.device_name,
|
||||
"alive": True,
|
||||
}
|
||||
|
||||
current_state = ServerStates.LoadingModel
|
||||
|
||||
while True:
|
||||
try:
|
||||
if backend.ping(timeout=1):
|
||||
break
|
||||
|
||||
time.sleep(1)
|
||||
except (TimeoutError, ConnectionError):
|
||||
time.sleep(1)
|
||||
|
||||
model_manager.load_default_models(runtime.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 {runtime.context.device}")
|
||||
model_manager.unload_all(runtime.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.session_id} starting task {task.id} on {runtime.context.device_name}")
|
||||
if not task.lock.acquire(blocking=False):
|
||||
raise Exception("Got locked task from queue.")
|
||||
try:
|
||||
task.run()
|
||||
|
||||
# Before looping back to the generator, mark cache as still alive.
|
||||
keep_task_alive(task)
|
||||
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:
|
||||
task.lock.release()
|
||||
|
||||
keep_task_alive(task)
|
||||
|
||||
if isinstance(task.error, StopAsyncIteration):
|
||||
log.info(f"Session {task.session_id} task {task.id} cancelled!")
|
||||
elif task.error is not None:
|
||||
log.info(f"Session {task.session_id} task {task.id} failed!")
|
||||
else:
|
||||
log.info(f"Session {task.session_id} task {task.id} completed by {runtime.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()
|
||||
|
||||
# temp until TRT releases
|
||||
import os
|
||||
from easydiffusion import app
|
||||
|
||||
devices["enable_trt"] = os.path.exists(os.path.join(app.ROOT_DIR, "tensorrt"))
|
||||
|
||||
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 enqueue_task(task: Task):
|
||||
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.session_id, update_ttl=True)
|
||||
pending_tasks = list(filter(lambda t: t.is_pending, session.tasks))
|
||||
if len(pending_tasks) > current_thread_count * MAX_OVERLOAD_ALLOWED_RATIO:
|
||||
raise ConnectionRefusedError(
|
||||
f"Session {task.session_id} already has {len(pending_tasks)} pending tasks, with {current_thread_count} workers."
|
||||
)
|
||||
|
||||
if session.put(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(task)
|
||||
idle_event.set()
|
||||
return task
|
||||
finally:
|
||||
manager_lock.release()
|
||||
raise RuntimeError("Failed to add task to cache.")
|
||||
@ -1,3 +0,0 @@
|
||||
from .task import Task
|
||||
from .render_images import RenderTask
|
||||
from .filter_images import FilterTask
|
||||
@ -1,129 +0,0 @@
|
||||
import os
|
||||
import json
|
||||
import pprint
|
||||
import time
|
||||
|
||||
from numpy import base_repr
|
||||
|
||||
from sdkit.utils import img_to_base64_str, log, save_images, base64_str_to_img
|
||||
|
||||
from easydiffusion import model_manager, runtime
|
||||
from easydiffusion.types import (
|
||||
FilterImageRequest,
|
||||
FilterImageResponse,
|
||||
ModelsData,
|
||||
OutputFormatData,
|
||||
SaveToDiskData,
|
||||
TaskData,
|
||||
GenerateImageRequest,
|
||||
)
|
||||
from easydiffusion.utils import filter_nsfw
|
||||
from easydiffusion.utils.save_utils import format_folder_name
|
||||
|
||||
from .task import Task
|
||||
|
||||
|
||||
class FilterTask(Task):
|
||||
"For applying filters to input images"
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
req: FilterImageRequest,
|
||||
task_data: TaskData,
|
||||
models_data: ModelsData,
|
||||
output_format: OutputFormatData,
|
||||
save_data: SaveToDiskData,
|
||||
):
|
||||
super().__init__(task_data.session_id)
|
||||
|
||||
task_data.request_id = self.id
|
||||
|
||||
self.request = req
|
||||
self.task_data = task_data
|
||||
self.models_data = models_data
|
||||
self.output_format = output_format
|
||||
self.save_data = save_data
|
||||
|
||||
# convert to multi-filter format, if necessary
|
||||
if isinstance(req.filter, str):
|
||||
if req.filter not in req.filter_params:
|
||||
req.filter_params = {req.filter: req.filter_params}
|
||||
|
||||
req.filter = [req.filter]
|
||||
|
||||
if not isinstance(req.image, list):
|
||||
req.image = [req.image]
|
||||
|
||||
def run(self):
|
||||
"Runs the image filtering task on the assigned thread"
|
||||
|
||||
from easydiffusion import app
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
context = runtime.context
|
||||
|
||||
model_manager.resolve_model_paths(self.models_data)
|
||||
model_manager.reload_models_if_necessary(context, self.models_data)
|
||||
model_manager.fail_if_models_did_not_load(context)
|
||||
|
||||
print_task_info(self.request, self.models_data, self.output_format, self.save_data)
|
||||
|
||||
has_nsfw_filter = "nsfw_filter" in self.request.filter
|
||||
|
||||
output_format = self.output_format
|
||||
|
||||
backend.set_options(
|
||||
context,
|
||||
output_format=output_format.output_format,
|
||||
output_quality=output_format.output_quality,
|
||||
output_lossless=output_format.output_lossless,
|
||||
)
|
||||
|
||||
images = backend.filter_images(
|
||||
context, self.request.image, self.request.filter, self.request.filter_params, input_type="base64"
|
||||
)
|
||||
|
||||
if has_nsfw_filter:
|
||||
images = filter_nsfw(images)
|
||||
|
||||
if self.save_data.save_to_disk_path is not None:
|
||||
app_config = app.getConfig()
|
||||
folder_format = app_config.get("folder_format", "$id")
|
||||
|
||||
dummy_req = GenerateImageRequest()
|
||||
img_id = base_repr(int(time.time() * 10000), 36)[-7:] # Base 36 conversion, 0-9, A-Z
|
||||
|
||||
save_dir_path = os.path.join(
|
||||
self.save_data.save_to_disk_path, format_folder_name(folder_format, dummy_req, self.task_data)
|
||||
)
|
||||
images_pil = [base64_str_to_img(img) for img in images]
|
||||
save_images(
|
||||
images_pil,
|
||||
save_dir_path,
|
||||
file_name=img_id,
|
||||
output_format=output_format.output_format,
|
||||
output_quality=output_format.output_quality,
|
||||
output_lossless=output_format.output_lossless,
|
||||
)
|
||||
|
||||
res = FilterImageResponse(self.request, self.models_data, images=images)
|
||||
res = res.json()
|
||||
self.buffer_queue.put(json.dumps(res))
|
||||
|
||||
log.info("Filter task completed")
|
||||
|
||||
self.response = res
|
||||
|
||||
|
||||
def print_task_info(
|
||||
req: FilterImageRequest, models_data: ModelsData, output_format: OutputFormatData, save_data: SaveToDiskData
|
||||
):
|
||||
req_str = pprint.pformat({"filter": req.filter, "filter_params": req.filter_params}).replace("[", "\[")
|
||||
models_data = pprint.pformat(models_data.dict()).replace("[", "\[")
|
||||
output_format = pprint.pformat(output_format.dict()).replace("[", "\[")
|
||||
save_data = pprint.pformat(save_data.dict()).replace("[", "\[")
|
||||
|
||||
log.info(f"request: {req_str}")
|
||||
log.info(f"models data: {models_data}")
|
||||
log.info(f"output format: {output_format}")
|
||||
log.info(f"save data: {save_data}")
|
||||
@ -1,310 +0,0 @@
|
||||
import json
|
||||
import pprint
|
||||
import queue
|
||||
import time
|
||||
from PIL import Image
|
||||
|
||||
from easydiffusion import model_manager, runtime
|
||||
from easydiffusion.types import GenerateImageRequest, ModelsData, OutputFormatData, SaveToDiskData
|
||||
from easydiffusion.types import Image as ResponseImage
|
||||
from easydiffusion.types import GenerateImageResponse, RenderTaskData
|
||||
from easydiffusion.utils import get_printable_request, log, save_images_to_disk, filter_nsfw
|
||||
from sdkit.utils import (
|
||||
img_to_base64_str,
|
||||
base64_str_to_img,
|
||||
img_to_buffer,
|
||||
resize_img,
|
||||
get_image,
|
||||
log,
|
||||
)
|
||||
|
||||
from .task import Task
|
||||
|
||||
|
||||
class RenderTask(Task):
|
||||
"For image generation"
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
req: GenerateImageRequest,
|
||||
task_data: RenderTaskData,
|
||||
models_data: ModelsData,
|
||||
output_format: OutputFormatData,
|
||||
save_data: SaveToDiskData,
|
||||
):
|
||||
super().__init__(task_data.session_id)
|
||||
|
||||
task_data.request_id = self.id
|
||||
|
||||
self.render_request = req # Initial Request
|
||||
self.task_data = task_data
|
||||
self.models_data = models_data
|
||||
self.output_format = output_format
|
||||
self.save_data = save_data
|
||||
|
||||
self.temp_images: list = [None] * req.num_outputs * (1 if task_data.show_only_filtered_image else 2)
|
||||
|
||||
def run(self):
|
||||
"Runs the image generation task on the assigned thread"
|
||||
|
||||
from easydiffusion import task_manager, app
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
context = runtime.context
|
||||
config = app.getConfig()
|
||||
|
||||
if config.get("block_nsfw", False): # override if set on the server
|
||||
self.task_data.block_nsfw = True
|
||||
|
||||
def step_callback():
|
||||
task_manager.keep_task_alive(self)
|
||||
task_manager.current_state = task_manager.ServerStates.Rendering
|
||||
|
||||
if isinstance(task_manager.current_state_error, (SystemExit, StopAsyncIteration)) or isinstance(
|
||||
self.error, StopAsyncIteration
|
||||
):
|
||||
backend.stop_rendering(context)
|
||||
if isinstance(task_manager.current_state_error, StopAsyncIteration):
|
||||
self.error = task_manager.current_state_error
|
||||
task_manager.current_state_error = None
|
||||
log.info(f"Session {self.session_id} sent cancel signal for task {self.id}")
|
||||
|
||||
task_manager.current_state = task_manager.ServerStates.LoadingModel
|
||||
model_manager.resolve_model_paths(self.models_data)
|
||||
|
||||
models_to_force_reload = []
|
||||
if runtime.set_vram_optimizations(context) or self.has_param_changed(context, "clip_skip"):
|
||||
models_to_force_reload.append("stable-diffusion")
|
||||
|
||||
model_manager.reload_models_if_necessary(context, self.models_data, models_to_force_reload)
|
||||
model_manager.fail_if_models_did_not_load(context)
|
||||
|
||||
task_manager.current_state = task_manager.ServerStates.Rendering
|
||||
self.response = make_images(
|
||||
context,
|
||||
self.render_request,
|
||||
self.task_data,
|
||||
self.models_data,
|
||||
self.output_format,
|
||||
self.save_data,
|
||||
self.buffer_queue,
|
||||
self.temp_images,
|
||||
step_callback,
|
||||
self,
|
||||
)
|
||||
|
||||
def has_param_changed(self, context, param_name):
|
||||
if not getattr(context, "test_diffusers", False):
|
||||
return False
|
||||
if "stable-diffusion" not in context.models or "params" not in context.models["stable-diffusion"]:
|
||||
return True
|
||||
|
||||
model = context.models["stable-diffusion"]
|
||||
new_val = self.models_data.model_params.get("stable-diffusion", {}).get(param_name, False)
|
||||
return model["params"].get(param_name) != new_val
|
||||
|
||||
|
||||
def make_images(
|
||||
context,
|
||||
req: GenerateImageRequest,
|
||||
task_data: RenderTaskData,
|
||||
models_data: ModelsData,
|
||||
output_format: OutputFormatData,
|
||||
save_data: SaveToDiskData,
|
||||
data_queue: queue.Queue,
|
||||
task_temp_images: list,
|
||||
step_callback,
|
||||
task,
|
||||
):
|
||||
print_task_info(req, task_data, models_data, output_format, save_data)
|
||||
|
||||
images, seeds = make_images_internal(
|
||||
context,
|
||||
req,
|
||||
task_data,
|
||||
models_data,
|
||||
output_format,
|
||||
save_data,
|
||||
data_queue,
|
||||
task_temp_images,
|
||||
step_callback,
|
||||
task,
|
||||
)
|
||||
|
||||
res = GenerateImageResponse(
|
||||
req, task_data, models_data, output_format, save_data, images=construct_response(images, seeds, output_format)
|
||||
)
|
||||
res = res.json()
|
||||
data_queue.put(json.dumps(res))
|
||||
log.info("Task completed")
|
||||
|
||||
return res
|
||||
|
||||
|
||||
def print_task_info(
|
||||
req: GenerateImageRequest,
|
||||
task_data: RenderTaskData,
|
||||
models_data: ModelsData,
|
||||
output_format: OutputFormatData,
|
||||
save_data: SaveToDiskData,
|
||||
):
|
||||
req_str = pprint.pformat(get_printable_request(req, task_data, models_data, output_format, save_data)).replace(
|
||||
"[", "\["
|
||||
)
|
||||
task_str = pprint.pformat(task_data.dict()).replace("[", "\[")
|
||||
models_data = pprint.pformat(models_data.dict()).replace("[", "\[")
|
||||
output_format = pprint.pformat(output_format.dict()).replace("[", "\[")
|
||||
save_data = pprint.pformat(save_data.dict()).replace("[", "\[")
|
||||
|
||||
log.info(f"request: {req_str}")
|
||||
log.info(f"task data: {task_str}")
|
||||
log.info(f"models data: {models_data}")
|
||||
log.info(f"output format: {output_format}")
|
||||
log.info(f"save data: {save_data}")
|
||||
|
||||
|
||||
def make_images_internal(
|
||||
context,
|
||||
req: GenerateImageRequest,
|
||||
task_data: RenderTaskData,
|
||||
models_data: ModelsData,
|
||||
output_format: OutputFormatData,
|
||||
save_data: SaveToDiskData,
|
||||
data_queue: queue.Queue,
|
||||
task_temp_images: list,
|
||||
step_callback,
|
||||
task,
|
||||
):
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
# prep the nsfw_filter
|
||||
if task_data.block_nsfw:
|
||||
filter_nsfw([Image.new("RGB", (1, 1))]) # hack - ensures that the model is available
|
||||
|
||||
images = generate_images_internal(
|
||||
context,
|
||||
req,
|
||||
task_data,
|
||||
models_data,
|
||||
output_format,
|
||||
data_queue,
|
||||
task_temp_images,
|
||||
step_callback,
|
||||
task_data.stream_image_progress,
|
||||
task_data.stream_image_progress_interval,
|
||||
)
|
||||
user_stopped = isinstance(task.error, StopAsyncIteration)
|
||||
|
||||
filters, filter_params = task_data.filters, task_data.filter_params
|
||||
if len(filters) > 0 and not user_stopped:
|
||||
filtered_images = backend.filter_images(context, images, filters, filter_params, input_type="base64")
|
||||
else:
|
||||
filtered_images = images
|
||||
|
||||
if task_data.block_nsfw:
|
||||
filtered_images = filter_nsfw(filtered_images)
|
||||
|
||||
if save_data.save_to_disk_path is not None:
|
||||
images_pil = [base64_str_to_img(img) for img in images]
|
||||
filtered_images_pil = [base64_str_to_img(img) for img in filtered_images]
|
||||
save_images_to_disk(images_pil, filtered_images_pil, req, task_data, models_data, output_format, save_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(
|
||||
context,
|
||||
req: GenerateImageRequest,
|
||||
task_data: RenderTaskData,
|
||||
models_data: ModelsData,
|
||||
output_format: OutputFormatData,
|
||||
data_queue: queue.Queue,
|
||||
task_temp_images: list,
|
||||
step_callback,
|
||||
stream_image_progress: bool,
|
||||
stream_image_progress_interval: int,
|
||||
):
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
callback = make_step_callback(context, req, task_data, data_queue, task_temp_images, step_callback)
|
||||
|
||||
req.width, req.height = map(lambda x: x - x % 8, (req.width, req.height)) # clamp to 8
|
||||
|
||||
if req.control_image and task_data.control_filter_to_apply:
|
||||
req.controlnet_filter = task_data.control_filter_to_apply
|
||||
|
||||
if req.init_image is not None and int(req.num_inference_steps * req.prompt_strength) == 0:
|
||||
req.prompt_strength = 1 / req.num_inference_steps if req.num_inference_steps > 0 else 1
|
||||
|
||||
backend.set_options(
|
||||
context,
|
||||
output_format=output_format.output_format,
|
||||
output_quality=output_format.output_quality,
|
||||
output_lossless=output_format.output_lossless,
|
||||
vae_tiling=task_data.enable_vae_tiling,
|
||||
stream_image_progress=stream_image_progress,
|
||||
stream_image_progress_interval=stream_image_progress_interval,
|
||||
clip_skip=2 if task_data.clip_skip else 1,
|
||||
)
|
||||
|
||||
images = backend.generate_images(context, callback=callback, output_type="base64", **req.dict())
|
||||
|
||||
return images
|
||||
|
||||
|
||||
def construct_response(images: list, seeds: list, output_format: OutputFormatData):
|
||||
return [ResponseImage(data=img, seed=seed) for img, seed in zip(images, seeds)]
|
||||
|
||||
|
||||
def make_step_callback(
|
||||
context,
|
||||
req: GenerateImageRequest,
|
||||
task_data: RenderTaskData,
|
||||
data_queue: queue.Queue,
|
||||
task_temp_images: list,
|
||||
step_callback,
|
||||
):
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
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(images, task_temp_images: list):
|
||||
partial_images = []
|
||||
|
||||
if images is None:
|
||||
return []
|
||||
|
||||
if task_data.block_nsfw:
|
||||
images = filter_nsfw(images, print_log=False)
|
||||
|
||||
for i, img in enumerate(images):
|
||||
img = img.convert("RGB")
|
||||
img = resize_img(img, req.width, req.height)
|
||||
buf = img_to_buffer(img, output_format="JPEG")
|
||||
|
||||
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(images, i, *args):
|
||||
nonlocal last_callback_time
|
||||
|
||||
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 images is not None:
|
||||
progress["output"] = update_temp_img(images, task_temp_images)
|
||||
|
||||
data_queue.put(json.dumps(progress))
|
||||
|
||||
step_callback()
|
||||
|
||||
return on_image_step
|
||||
@ -1,47 +0,0 @@
|
||||
from threading import Lock
|
||||
from queue import Queue, Empty as EmptyQueueException
|
||||
from typing import Any
|
||||
|
||||
|
||||
class Task:
|
||||
"Task with output queue and completion lock"
|
||||
|
||||
def __init__(self, session_id):
|
||||
self.id = id(self)
|
||||
self.session_id = session_id
|
||||
self.render_device = None # Select the task affinity. (Not used to change active devices).
|
||||
self.error: Exception = None
|
||||
self.lock: Lock = Lock() # Locks at task start and unlocks when task is completed
|
||||
self.buffer_queue: Queue = Queue() # Queue of JSON string segments
|
||||
self.response: Any = None # Copy of the last reponse
|
||||
|
||||
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 EmptyQueueException 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)
|
||||
|
||||
def run(self):
|
||||
"Override this to implement the task's behavior"
|
||||
pass
|
||||
@ -1,298 +0,0 @@
|
||||
from typing import Any, List, Dict, 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
|
||||
distilled_guidance_scale: float = 3.5
|
||||
|
||||
init_image: Any = None
|
||||
init_image_mask: Any = None
|
||||
control_image: Any = None
|
||||
control_alpha: Union[float, List[float]] = None
|
||||
controlnet_filter: str = None
|
||||
prompt_strength: float = 0.8
|
||||
preserve_init_image_color_profile: bool = False
|
||||
strict_mask_border: bool = False
|
||||
|
||||
sampler_name: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
|
||||
scheduler_name: str = None
|
||||
hypernetwork_strength: float = 0
|
||||
lora_alpha: Union[float, List[float]] = 0
|
||||
tiling: str = None # None, "x", "y", "xy"
|
||||
|
||||
|
||||
class FilterImageRequest(BaseModel):
|
||||
image: Any = None
|
||||
filter: Union[str, List[str]] = None
|
||||
filter_params: dict = {}
|
||||
|
||||
|
||||
class ModelsData(BaseModel):
|
||||
"""
|
||||
Contains the information related to the models involved in a request.
|
||||
|
||||
- To load a model: set the relative path(s) to the model in `model_paths`. No effect if already loaded.
|
||||
- To unload a model: set the model to `None` in `model_paths`. No effect if already unloaded.
|
||||
|
||||
Models that aren't present in `model_paths` will not be changed.
|
||||
"""
|
||||
|
||||
model_paths: Dict[str, Union[str, None, List[str]]] = None
|
||||
"model_type to string path, or list of string paths"
|
||||
|
||||
model_params: Dict[str, Dict[str, Any]] = {}
|
||||
"model_type to dict of parameters"
|
||||
|
||||
|
||||
class OutputFormatData(BaseModel):
|
||||
output_format: str = "jpeg" # or "png" or "webp"
|
||||
output_quality: int = 75
|
||||
output_lossless: bool = False
|
||||
|
||||
|
||||
class SaveToDiskData(BaseModel):
|
||||
save_to_disk_path: str = None
|
||||
metadata_output_format: str = "txt" # or "json"
|
||||
|
||||
|
||||
class TaskData(BaseModel):
|
||||
request_id: str = None
|
||||
session_id: str = "session"
|
||||
|
||||
|
||||
class RenderTaskData(TaskData):
|
||||
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
|
||||
use_controlnet_model: Union[str, List[str]] = None
|
||||
use_embeddings_model: Union[str, List[str]] = None
|
||||
filters: List[str] = []
|
||||
filter_params: Dict[str, Dict[str, Any]] = {}
|
||||
control_filter_to_apply: Union[str, List[str]] = None
|
||||
enable_vae_tiling: bool = True
|
||||
|
||||
show_only_filtered_image: bool = False
|
||||
block_nsfw: bool = False
|
||||
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: bool = 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 GenerateImageResponse:
|
||||
render_request: GenerateImageRequest
|
||||
task_data: TaskData
|
||||
models_data: ModelsData
|
||||
images: list
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
render_request: GenerateImageRequest,
|
||||
task_data: TaskData,
|
||||
models_data: ModelsData,
|
||||
output_format: OutputFormatData,
|
||||
save_data: SaveToDiskData,
|
||||
images: list,
|
||||
):
|
||||
self.render_request = render_request
|
||||
self.task_data = task_data
|
||||
self.models_data = models_data
|
||||
self.output_format = output_format
|
||||
self.save_data = save_data
|
||||
self.images = images
|
||||
|
||||
def json(self):
|
||||
del self.render_request.init_image
|
||||
del self.render_request.init_image_mask
|
||||
del self.render_request.control_image
|
||||
|
||||
task_data = self.task_data.dict()
|
||||
task_data.update(self.output_format.dict())
|
||||
task_data.update(self.save_data.dict())
|
||||
|
||||
res = {
|
||||
"status": "succeeded",
|
||||
"render_request": self.render_request.dict(),
|
||||
"task_data": task_data,
|
||||
# "models_data": self.models_data.dict(), # haven't migrated the UI to the new format (yet)
|
||||
"output": [],
|
||||
}
|
||||
|
||||
for image in self.images:
|
||||
res["output"].append(image.json())
|
||||
|
||||
return res
|
||||
|
||||
|
||||
class FilterImageResponse:
|
||||
request: FilterImageRequest
|
||||
models_data: ModelsData
|
||||
images: list
|
||||
|
||||
def __init__(self, request: FilterImageRequest, models_data: ModelsData, images: list):
|
||||
self.request = request
|
||||
self.models_data = models_data
|
||||
self.images = images
|
||||
|
||||
def json(self):
|
||||
del self.request.image
|
||||
|
||||
res = {
|
||||
"status": "succeeded",
|
||||
"request": self.request.dict(),
|
||||
"models_data": self.models_data.dict(),
|
||||
"output": [],
|
||||
}
|
||||
|
||||
for image in self.images:
|
||||
res["output"].append(image)
|
||||
|
||||
return res
|
||||
|
||||
|
||||
class UserInitiatedStop(Exception):
|
||||
pass
|
||||
|
||||
|
||||
def convert_legacy_render_req_to_new(old_req: dict):
|
||||
new_req = dict(old_req)
|
||||
|
||||
# new keys
|
||||
model_paths = new_req["model_paths"] = {}
|
||||
model_params = new_req["model_params"] = {}
|
||||
filters = new_req["filters"] = []
|
||||
filter_params = new_req["filter_params"] = {}
|
||||
|
||||
# move the model info
|
||||
model_paths["stable-diffusion"] = old_req.get("use_stable_diffusion_model")
|
||||
model_paths["vae"] = old_req.get("use_vae_model")
|
||||
model_paths["hypernetwork"] = old_req.get("use_hypernetwork_model")
|
||||
model_paths["lora"] = old_req.get("use_lora_model")
|
||||
model_paths["controlnet"] = old_req.get("use_controlnet_model")
|
||||
model_paths["embeddings"] = old_req.get("use_embeddings_model")
|
||||
|
||||
## ensure that the model name is in the model path
|
||||
for model_name in ("gfpgan", "codeformer"):
|
||||
model_paths[model_name] = old_req.get("use_face_correction", "")
|
||||
model_paths[model_name] = model_paths[model_name] if model_name in model_paths[model_name].lower() else None
|
||||
|
||||
for model_name in ("realesrgan", "latent_upscaler", "esrgan_4x", "lanczos", "nearest", "scunet", "swinir"):
|
||||
model_paths[model_name] = old_req.get("use_upscale", "")
|
||||
model_paths[model_name] = model_paths[model_name] if model_name in model_paths[model_name].lower() else None
|
||||
|
||||
if "control_filter_to_apply" in old_req:
|
||||
filter_model = old_req["control_filter_to_apply"]
|
||||
model_paths[filter_model] = filter_model
|
||||
old_req["control_filter_to_apply"] = convert_legacy_controlnet_filter_name(old_req["control_filter_to_apply"])
|
||||
|
||||
if old_req.get("block_nsfw"):
|
||||
model_paths["nsfw_checker"] = "nsfw_checker"
|
||||
|
||||
# move the model params
|
||||
if model_paths["stable-diffusion"]:
|
||||
model_params["stable-diffusion"] = {
|
||||
"clip_skip": bool(old_req.get("clip_skip", False)),
|
||||
"convert_to_tensorrt": bool(old_req.get("convert_to_tensorrt", False)),
|
||||
"trt_build_config": old_req.get(
|
||||
"trt_build_config", {"batch_size_range": (1, 1), "dimensions_range": [(768, 1024)]}
|
||||
),
|
||||
}
|
||||
|
||||
# move the filter params
|
||||
for model_name in ("realesrgan", "esrgan_4x", "lanczos", "nearest", "scunet", "swinir"):
|
||||
if model_paths[model_name]:
|
||||
filter_params[model_name] = {
|
||||
"upscaler": model_paths[model_name],
|
||||
"scale": int(old_req.get("upscale_amount", 4)),
|
||||
}
|
||||
if model_paths["latent_upscaler"]:
|
||||
filter_params["latent_upscaler"] = {
|
||||
"prompt": old_req["prompt"],
|
||||
"negative_prompt": old_req.get("negative_prompt"),
|
||||
"seed": int(old_req.get("seed", 42)),
|
||||
"num_inference_steps": int(old_req.get("latent_upscaler_steps", 10)),
|
||||
"guidance_scale": 0,
|
||||
}
|
||||
if model_paths["codeformer"]:
|
||||
filter_params["codeformer"] = {
|
||||
"upscale_faces": bool(old_req.get("codeformer_upscale_faces", True)),
|
||||
"codeformer_fidelity": float(old_req.get("codeformer_fidelity", 0.5)),
|
||||
}
|
||||
|
||||
# set the filters
|
||||
if old_req.get("block_nsfw"):
|
||||
filters.append("nsfw_checker")
|
||||
|
||||
for model_name in ("gfpgan", "codeformer"):
|
||||
if model_paths[model_name]:
|
||||
filters.append(model_name)
|
||||
break
|
||||
|
||||
for model_name in ("realesrgan", "latent_upscaler", "esrgan_4x", "lanczos", "nearest", "scunet", "swinir"):
|
||||
if model_paths[model_name]:
|
||||
filters.append(model_name)
|
||||
break
|
||||
|
||||
return new_req
|
||||
|
||||
|
||||
def convert_legacy_controlnet_filter_name(filter):
|
||||
from easydiffusion.backend_manager import backend
|
||||
|
||||
if filter is None:
|
||||
return None
|
||||
|
||||
controlnet_filter_names = backend.list_controlnet_filters()
|
||||
|
||||
def apply(f):
|
||||
return f"controlnet_{f}" if f in controlnet_filter_names else f
|
||||
|
||||
if isinstance(filter, list):
|
||||
return [apply(f) for f in filter]
|
||||
|
||||
return apply(filter)
|
||||
@ -1,22 +0,0 @@
|
||||
import logging
|
||||
import hashlib
|
||||
|
||||
log = logging.getLogger("easydiffusion")
|
||||
|
||||
from .save_utils import (
|
||||
save_images_to_disk,
|
||||
get_printable_request,
|
||||
)
|
||||
from .nsfw_checker import filter_nsfw
|
||||
|
||||
|
||||
def sha256sum(filename):
|
||||
sha256 = hashlib.sha256()
|
||||
with open(filename, "rb") as f:
|
||||
while True:
|
||||
data = f.read(8192) # Read in chunks of 8192 bytes
|
||||
if not data:
|
||||
break
|
||||
sha256.update(data)
|
||||
|
||||
return sha256.hexdigest()
|
||||
@ -1,80 +0,0 @@
|
||||
# possibly move this to sdkit in the future
|
||||
import os
|
||||
|
||||
# mirror of https://huggingface.co/AdamCodd/vit-base-nsfw-detector/blob/main/onnx/model_quantized.onnx
|
||||
NSFW_MODEL_URL = (
|
||||
"https://github.com/easydiffusion/sdkit-test-data/releases/download/assets/vit-base-nsfw-detector-quantized.onnx"
|
||||
)
|
||||
MODEL_HASH_QUICK = "220123559305b1b07b7a0894c3471e34dccd090d71cdf337dd8012f9e40d6c28"
|
||||
|
||||
nsfw_check_model = None
|
||||
|
||||
|
||||
def filter_nsfw(images, blur_radius: float = 75, print_log=True):
|
||||
global nsfw_check_model
|
||||
|
||||
from easydiffusion.model_manager import get_model_dirs
|
||||
from sdkit.utils import base64_str_to_img, img_to_base64_str, download_file, log, hash_file_quick
|
||||
|
||||
import onnxruntime as ort
|
||||
from PIL import ImageFilter
|
||||
import numpy as np
|
||||
|
||||
if nsfw_check_model is None:
|
||||
model_dir = get_model_dirs("nsfw-checker")[0]
|
||||
model_path = os.path.join(model_dir, "vit-base-nsfw-detector-quantized.onnx")
|
||||
|
||||
os.makedirs(model_dir, exist_ok=True)
|
||||
|
||||
if not os.path.exists(model_path) or hash_file_quick(model_path) != MODEL_HASH_QUICK:
|
||||
download_file(NSFW_MODEL_URL, model_path)
|
||||
|
||||
nsfw_check_model = ort.InferenceSession(model_path, providers=["CPUExecutionProvider"])
|
||||
|
||||
# Preprocess the input image
|
||||
def preprocess_image(img):
|
||||
img = img.convert("RGB")
|
||||
|
||||
# config based on based on https://huggingface.co/AdamCodd/vit-base-nsfw-detector/blob/main/onnx/preprocessor_config.json
|
||||
# Resize the image
|
||||
img = img.resize((384, 384))
|
||||
|
||||
# Normalize the image
|
||||
img = np.array(img) / 255.0 # Scale pixel values to [0, 1]
|
||||
mean = np.array([0.5, 0.5, 0.5])
|
||||
std = np.array([0.5, 0.5, 0.5])
|
||||
img = (img - mean) / std
|
||||
|
||||
# Transpose to match input shape (batch_size, channels, height, width)
|
||||
img = np.transpose(img, (2, 0, 1)).astype(np.float32)
|
||||
|
||||
# Add batch dimension
|
||||
img = np.expand_dims(img, axis=0)
|
||||
|
||||
return img
|
||||
|
||||
# Run inference
|
||||
input_name = nsfw_check_model.get_inputs()[0].name
|
||||
output_name = nsfw_check_model.get_outputs()[0].name
|
||||
|
||||
if print_log:
|
||||
log.info("Running NSFW checker (onnx)")
|
||||
|
||||
results = []
|
||||
for img in images:
|
||||
is_base64 = isinstance(img, str)
|
||||
|
||||
input_img = base64_str_to_img(img) if is_base64 else img
|
||||
|
||||
result = nsfw_check_model.run([output_name], {input_name: preprocess_image(input_img)})
|
||||
is_nsfw = [np.argmax(arr) == 1 for arr in result][0]
|
||||
|
||||
if is_nsfw:
|
||||
output_img = input_img.filter(ImageFilter.GaussianBlur(blur_radius))
|
||||
output_img = img_to_base64_str(output_img) if is_base64 else output_img
|
||||
else:
|
||||
output_img = img
|
||||
|
||||
results.append(output_img)
|
||||
|
||||
return results
|
||||
@ -1,369 +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,
|
||||
RenderTaskData,
|
||||
OutputFormatData,
|
||||
SaveToDiskData,
|
||||
ModelsData,
|
||||
)
|
||||
from numpy import base_repr
|
||||
from sdkit.utils import save_dicts, save_images
|
||||
from sdkit.models.model_loader.embeddings import get_embedding_token
|
||||
|
||||
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_controlnet_model": "ControlNet model",
|
||||
"control_filter_to_apply": "ControlNet Filter",
|
||||
"control_alpha": "ControlNet Strength",
|
||||
"use_vae_model": "VAE model",
|
||||
"sampler_name": "Sampler",
|
||||
"scheduler_name": "Scheduler",
|
||||
"width": "Width",
|
||||
"height": "Height",
|
||||
"num_inference_steps": "Steps",
|
||||
"guidance_scale": "Guidance Scale",
|
||||
"distilled_guidance_scale": "Distilled Guidance",
|
||||
"prompt_strength": "Prompt Strength",
|
||||
"use_lora_model": "LoRA model",
|
||||
"lora_alpha": "LoRA Strength",
|
||||
"use_hypernetwork_model": "Hypernetwork model",
|
||||
"hypernetwork_strength": "Hypernetwork Strength",
|
||||
"use_embeddings_model": "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],
|
||||
"$s": lambda req, task_data: str(req.seed),
|
||||
}
|
||||
|
||||
|
||||
class ImageNumber:
|
||||
_factory = None
|
||||
_evaluated = False
|
||||
|
||||
def __init__(self, factory):
|
||||
self._factory = factory
|
||||
self._evaluated = None
|
||||
|
||||
def __call__(self) -> int:
|
||||
if self._evaluated is None:
|
||||
self._evaluated = self._factory()
|
||||
return self._evaluated
|
||||
|
||||
|
||||
def format_placeholders(format: str, req: GenerateImageRequest, task_data: TaskData, now=None):
|
||||
if now is None:
|
||||
now = time.time()
|
||||
|
||||
for placeholder, time_format in time_placeholders.items():
|
||||
if placeholder in format:
|
||||
format = format.replace(placeholder, datetime.fromtimestamp(now).strftime(time_format))
|
||||
for placeholder, replace_func in other_placeholders.items():
|
||||
if placeholder in format:
|
||||
format = format.replace(placeholder, replace_func(req, task_data))
|
||||
|
||||
return format
|
||||
|
||||
|
||||
def format_folder_name(format: str, req: GenerateImageRequest, task_data: TaskData):
|
||||
format = format_placeholders(format, req, task_data)
|
||||
return filename_regex.sub("_", format)
|
||||
|
||||
|
||||
def format_file_name(
|
||||
format: str,
|
||||
req: GenerateImageRequest,
|
||||
task_data: RenderTaskData,
|
||||
now: float,
|
||||
batch_file_number: int,
|
||||
folder_img_number: ImageNumber,
|
||||
):
|
||||
format = format_placeholders(format, req, task_data, now)
|
||||
|
||||
if "$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("$ts", str(int(now * 1000) + batch_file_number))
|
||||
|
||||
return filename_regex.sub("_", format)
|
||||
|
||||
|
||||
def save_images_to_disk(
|
||||
images: list,
|
||||
filtered_images: list,
|
||||
req: GenerateImageRequest,
|
||||
task_data: RenderTaskData,
|
||||
models_data: ModelsData,
|
||||
output_format: OutputFormatData,
|
||||
save_data: SaveToDiskData,
|
||||
):
|
||||
now = time.time()
|
||||
app_config = app.getConfig()
|
||||
folder_format = app_config.get("folder_format", "$id")
|
||||
save_dir_path = os.path.join(save_data.save_to_disk_path, format_folder_name(folder_format, req, task_data))
|
||||
metadata_entries = get_metadata_entries_for_request(req, task_data, models_data, output_format, save_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=output_format.output_format,
|
||||
output_quality=output_format.output_quality,
|
||||
output_lossless=output_format.output_lossless,
|
||||
)
|
||||
if save_data.metadata_output_format:
|
||||
for metadata_output_format in save_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=output_format.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=output_format.output_format,
|
||||
output_quality=output_format.output_quality,
|
||||
output_lossless=output_format.output_lossless,
|
||||
)
|
||||
save_images(
|
||||
filtered_images,
|
||||
save_dir_path,
|
||||
file_name=make_filter_filename,
|
||||
output_format=output_format.output_format,
|
||||
output_quality=output_format.output_quality,
|
||||
output_lossless=output_format.output_lossless,
|
||||
)
|
||||
if save_data.metadata_output_format:
|
||||
for metadata_output_format in save_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=metadata_output_format,
|
||||
file_format=output_format.output_format,
|
||||
)
|
||||
|
||||
|
||||
def get_metadata_entries_for_request(
|
||||
req: GenerateImageRequest,
|
||||
task_data: RenderTaskData,
|
||||
models_data: ModelsData,
|
||||
output_format: OutputFormatData,
|
||||
save_data: SaveToDiskData,
|
||||
):
|
||||
metadata = get_printable_request(req, task_data, models_data, output_format, save_data)
|
||||
|
||||
# if text, format it in the text format expected by the UI
|
||||
is_txt_format = save_data.metadata_output_format and "txt" in save_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: RenderTaskData,
|
||||
models_data: ModelsData,
|
||||
output_format: OutputFormatData,
|
||||
save_data: SaveToDiskData,
|
||||
):
|
||||
req_metadata = req.dict()
|
||||
task_data_metadata = task_data.dict()
|
||||
task_data_metadata.update(output_format.dict())
|
||||
task_data_metadata.update(save_data.dict())
|
||||
|
||||
app_config = app.getConfig()
|
||||
using_diffusers = app_config.get("backend", "ed_diffusers") in ("ed_diffusers", "webui")
|
||||
|
||||
# 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]
|
||||
|
||||
if key == "use_embeddings_model" and task_data_metadata[key] and using_diffusers:
|
||||
embeddings_used = models_data.model_paths["embeddings"]
|
||||
embeddings_used = embeddings_used if isinstance(embeddings_used, list) else [embeddings_used]
|
||||
|
||||
metadata["use_embeddings_model"] = embeddings_used if len(embeddings_used) > 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 task_data.use_controlnet_model is None and "control_filter_to_apply" in metadata:
|
||||
del metadata["control_filter_to_apply"]
|
||||
|
||||
if using_diffusers:
|
||||
for key in (x for x in ["use_hypernetwork_model", "hypernetwork_strength"] if x in metadata):
|
||||
del metadata[key]
|
||||
else:
|
||||
for key in (
|
||||
x
|
||||
for x in [
|
||||
"use_lora_model",
|
||||
"lora_alpha",
|
||||
"clip_skip",
|
||||
"tiling",
|
||||
"latent_upscaler_steps",
|
||||
"use_controlnet_model",
|
||||
"control_filter_to_apply",
|
||||
]
|
||||
if x in metadata
|
||||
):
|
||||
del metadata[key]
|
||||
|
||||
return metadata
|
||||
|
||||
|
||||
def make_filename_callback(
|
||||
filename_format: str,
|
||||
req: GenerateImageRequest,
|
||||
task_data: RenderTaskData,
|
||||
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: RenderTaskData):
|
||||
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: RenderTaskData):
|
||||
return ImageNumber(lambda: _calculate_img_number(save_dir_path, task_data))
|
||||
@ -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
|
||||
}
|
||||
}
|
||||
1047
ui/index.html
1047
ui/index.html
File diff suppressed because it is too large
Load Diff
11
ui/main.py
11
ui/main.py
@ -1,11 +0,0 @@
|
||||
from easydiffusion import model_manager, app, server, bucket_manager
|
||||
from easydiffusion.server import server_api # required for uvicorn
|
||||
|
||||
app.init()
|
||||
|
||||
server.init()
|
||||
|
||||
# Init the app
|
||||
model_manager.init()
|
||||
app.init_render_threads()
|
||||
bucket_manager.init()
|
||||
@ -1,68 +0,0 @@
|
||||
@keyframes ldio-8f673ktaleu-1 {
|
||||
0% { transform: rotate(0deg) }
|
||||
50% { transform: rotate(-45deg) }
|
||||
100% { transform: rotate(0deg) }
|
||||
}
|
||||
@keyframes ldio-8f673ktaleu-2 {
|
||||
0% { transform: rotate(180deg) }
|
||||
50% { transform: rotate(225deg) }
|
||||
100% { transform: rotate(180deg) }
|
||||
}
|
||||
.ldio-8f673ktaleu > div:nth-child(2) {
|
||||
transform: translate(-15px,0);
|
||||
}
|
||||
.ldio-8f673ktaleu > div:nth-child(2) div {
|
||||
position: absolute;
|
||||
top: 20px;
|
||||
left: 20px;
|
||||
width: 60px;
|
||||
height: 30px;
|
||||
border-radius: 60px 60px 0 0;
|
||||
background: #f3b72e;
|
||||
animation: ldio-8f673ktaleu-1 1s linear infinite;
|
||||
transform-origin: 30px 30px
|
||||
}
|
||||
.ldio-8f673ktaleu > div:nth-child(2) div:nth-child(2) {
|
||||
animation: ldio-8f673ktaleu-2 1s linear infinite
|
||||
}
|
||||
.ldio-8f673ktaleu > div:nth-child(2) div:nth-child(3) {
|
||||
transform: rotate(-90deg);
|
||||
animation: none;
|
||||
}@keyframes ldio-8f673ktaleu-3 {
|
||||
0% { transform: translate(95px,0); opacity: 0 }
|
||||
20% { opacity: 1 }
|
||||
100% { transform: translate(35px,0); opacity: 1 }
|
||||
}
|
||||
.ldio-8f673ktaleu > div:nth-child(1) {
|
||||
display: block;
|
||||
}
|
||||
.ldio-8f673ktaleu > div:nth-child(1) div {
|
||||
position: absolute;
|
||||
top: 46px;
|
||||
left: -4px;
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
border-radius: 50%;
|
||||
background: #3869c5;
|
||||
animation: ldio-8f673ktaleu-3 1s linear infinite
|
||||
}
|
||||
.ldio-8f673ktaleu > div:nth-child(1) div:nth-child(1) { animation-delay: -0.67s }
|
||||
.ldio-8f673ktaleu > div:nth-child(1) div:nth-child(2) { animation-delay: -0.33s }
|
||||
.ldio-8f673ktaleu > div:nth-child(1) div:nth-child(3) { animation-delay: 0s }
|
||||
.loadingio-spinner-bean-eater-x0y3u8qky4n {
|
||||
width: 58px;
|
||||
height: 58px;
|
||||
display: inline-block;
|
||||
overflow: hidden;
|
||||
background: none;
|
||||
}
|
||||
.ldio-8f673ktaleu {
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
position: relative;
|
||||
transform: translateZ(0) scale(0.58);
|
||||
backface-visibility: hidden;
|
||||
transform-origin: 0 0; /* see note above */
|
||||
}
|
||||
.ldio-8f673ktaleu div { box-sizing: content-box; }
|
||||
/* generated by https://loading.io/ */
|
||||
@ -1,85 +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,
|
||||
.parameters-table .fa-robot {
|
||||
color: #F7630C;
|
||||
}
|
||||
@ -1,58 +0,0 @@
|
||||
.croppr-container * {
|
||||
user-select: none;
|
||||
-moz-user-select: none;
|
||||
-webkit-user-select: none;
|
||||
-ms-user-select: none;
|
||||
box-sizing: border-box;
|
||||
-webkit-box-sizing: border-box;
|
||||
-moz-box-sizing: border-box;
|
||||
}
|
||||
|
||||
.croppr-container img {
|
||||
vertical-align: middle;
|
||||
max-width: 100%;
|
||||
}
|
||||
|
||||
.croppr {
|
||||
position: relative;
|
||||
display: inline-block;
|
||||
}
|
||||
|
||||
.croppr-overlay {
|
||||
background: rgba(0,0,0,0.5);
|
||||
position: absolute;
|
||||
top: 0;
|
||||
right: 0;
|
||||
bottom: 0;
|
||||
left: 0;
|
||||
z-index: 1;
|
||||
cursor: crosshair;
|
||||
}
|
||||
|
||||
.croppr-region {
|
||||
border: 1px dashed rgba(0, 0, 0, 0.5);
|
||||
position: absolute;
|
||||
z-index: 3;
|
||||
cursor: move;
|
||||
top: 0;
|
||||
}
|
||||
|
||||
.croppr-imageClipped {
|
||||
position: absolute;
|
||||
top: 0;
|
||||
right: 0;
|
||||
bottom: 0;
|
||||
left: 0;
|
||||
z-index: 2;
|
||||
pointer-events: none;
|
||||
}
|
||||
|
||||
.croppr-handle {
|
||||
border: 1px solid black;
|
||||
background-color: white;
|
||||
width: 10px;
|
||||
height: 10px;
|
||||
position: absolute;
|
||||
z-index: 4;
|
||||
top: 0;
|
||||
}
|
||||
6
ui/media/css/fontawesome-all.min.css
vendored
6
ui/media/css/fontawesome-all.min.css
vendored
File diff suppressed because one or more lines are too long
@ -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+ */
|
||||
}
|
||||
|
||||
@ -1,255 +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;
|
||||
}
|
||||
|
||||
.editor-canvas-overlay {
|
||||
cursor: none;
|
||||
}
|
||||
|
||||
.image-brush-preview {
|
||||
position: fixed;
|
||||
background: black;
|
||||
opacity: 0.3;
|
||||
borderRadius: 50%;
|
||||
cursor: none;
|
||||
pointer-events: none;
|
||||
transform: translate(-50%, -50%);
|
||||
}
|
||||
|
||||
.editor-options-container > * > *:not(.active):not(.button) {
|
||||
border: 1px dotted slategray;
|
||||
}
|
||||
|
||||
.image_editor_opacity .editor-options-container > * > *:not(.active):not(.button) {
|
||||
border: 1px dotted slategray;
|
||||
}
|
||||
|
||||
@ -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;
|
||||
}
|
||||
9
ui/media/css/jquery-confirm.min.css
vendored
9
ui/media/css/jquery-confirm.min.css
vendored
File diff suppressed because one or more lines are too long
File diff suppressed because it is too large
Load Diff
@ -1,288 +0,0 @@
|
||||
.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;
|
||||
}
|
||||
@ -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);
|
||||
}
|
||||
@ -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;
|
||||
}
|
||||
5
ui/media/drawingboard.min.css
vendored
Normal file
5
ui/media/drawingboard.min.css
vendored
Normal file
File diff suppressed because one or more lines are too long
4
ui/media/drawingboard.min.js
vendored
Normal file
4
ui/media/drawingboard.min.js
vendored
Normal file
File diff suppressed because one or more lines are too long
BIN
ui/media/favicon-16x16.png
Normal file
BIN
ui/media/favicon-16x16.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 466 B |
BIN
ui/media/favicon-32x32.png
Normal file
BIN
ui/media/favicon-32x32.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 973 B |
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user