mirror of https://github.com/vladmandic/automatic
decouple from origin
Vladimir Mandic
parent
af55cf273c
commit
a70b6d0013
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@ -2,33 +2,13 @@ __pycache__
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*.ckpt
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*.safetensors
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*.pth
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/ESRGAN/*
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/SwinIR/*
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/repositories
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/venv
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/tmp
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/model.ckpt
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/models/**/*
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/GFPGANv1.3.pth
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/gfpgan/weights/*.pth
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/ui-config.json
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/outputs
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/config.json
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/log
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/webui.settings.bat
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/embeddings
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/styles.csv
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*.pt
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*.bin
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/params.txt
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/styles.csv.bak
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/webui-user.bat
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/webui-user.sh
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/interrogate
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/user.css
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/.idea
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notification.mp3
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/SwinIR
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/textual_inversion
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.vscode
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/extensions
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/test/stdout.txt
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/test/stderr.txt
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/repositories/*
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/embeddings/*
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/extensions/*
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/outputs/*
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/models/**/*
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/tmp
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12
CODEOWNERS
12
CODEOWNERS
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@ -1,12 +0,0 @@
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* @AUTOMATIC1111
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# if you were managing a localization and were removed from this file, this is because
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# the intended way to do localizations now is via extensions. See:
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# https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Developing-extensions
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# Make a repo with your localization and since you are still listed as a collaborator
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# you can add it to the wiki page yourself. This change is because some people complained
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# the git commit log is cluttered with things unrelated to almost everyone and
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# because I believe this is the best overall for the project to handle localizations almost
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# entirely without my oversight.
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156
README.md
156
README.md
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@ -1,153 +1,3 @@
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# Stable Diffusion web UI
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A browser interface based on Gradio library for Stable Diffusion.
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Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Scripts) wiki page for extra scripts developed by users.
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## Features
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[Detailed feature showcase with images](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features):
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- Original txt2img and img2img modes
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- One click install and run script (but you still must install python and git)
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- Outpainting
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- Inpainting
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- Color Sketch
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- Prompt Matrix
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- Stable Diffusion Upscale
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- Attention, specify parts of text that the model should pay more attention to
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- a man in a ((tuxedo)) - will pay more attention to tuxedo
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- a man in a (tuxedo:1.21) - alternative syntax
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- select text and press ctrl+up or ctrl+down to automatically adjust attention to selected text (code contributed by anonymous user)
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- Loopback, run img2img processing multiple times
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- X/Y plot, a way to draw a 2 dimensional plot of images with different parameters
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- Textual Inversion
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- have as many embeddings as you want and use any names you like for them
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- use multiple embeddings with different numbers of vectors per token
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- works with half precision floating point numbers
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- train embeddings on 8GB (also reports of 6GB working)
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- Extras tab with:
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- GFPGAN, neural network that fixes faces
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- CodeFormer, face restoration tool as an alternative to GFPGAN
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- RealESRGAN, neural network upscaler
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- ESRGAN, neural network upscaler with a lot of third party models
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- SwinIR and Swin2SR([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers
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- LDSR, Latent diffusion super resolution upscaling
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- Resizing aspect ratio options
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- Sampling method selection
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- Adjust sampler eta values (noise multiplier)
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- More advanced noise setting options
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- Interrupt processing at any time
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- 4GB video card support (also reports of 2GB working)
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- Correct seeds for batches
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- Live prompt token length validation
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- Generation parameters
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- parameters you used to generate images are saved with that image
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- in PNG chunks for PNG, in EXIF for JPEG
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- can drag the image to PNG info tab to restore generation parameters and automatically copy them into UI
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- can be disabled in settings
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- drag and drop an image/text-parameters to promptbox
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- Read Generation Parameters Button, loads parameters in promptbox to UI
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- Settings page
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- Running arbitrary python code from UI (must run with --allow-code to enable)
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- Mouseover hints for most UI elements
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- Possible to change defaults/mix/max/step values for UI elements via text config
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- Random artist button
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- Tiling support, a checkbox to create images that can be tiled like textures
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- Progress bar and live image generation preview
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- Negative prompt, an extra text field that allows you to list what you don't want to see in generated image
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- Styles, a way to save part of prompt and easily apply them via dropdown later
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- Variations, a way to generate same image but with tiny differences
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- Seed resizing, a way to generate same image but at slightly different resolution
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- CLIP interrogator, a button that tries to guess prompt from an image
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- Prompt Editing, a way to change prompt mid-generation, say to start making a watermelon and switch to anime girl midway
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- Batch Processing, process a group of files using img2img
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- Img2img Alternative, reverse Euler method of cross attention control
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- Highres Fix, a convenience option to produce high resolution pictures in one click without usual distortions
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- Reloading checkpoints on the fly
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- Checkpoint Merger, a tab that allows you to merge up to 3 checkpoints into one
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- [Custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Scripts) with many extensions from community
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- [Composable-Diffusion](https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/), a way to use multiple prompts at once
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- separate prompts using uppercase `AND`
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- also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
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- No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
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- DeepDanbooru integration, creates danbooru style tags for anime prompts
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- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args)
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- via extension: [History tab](https://github.com/yfszzx/stable-diffusion-webui-images-browser): view, direct and delete images conveniently within the UI
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- Generate forever option
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- Training tab
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- hypernetworks and embeddings options
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- Preprocessing images: cropping, mirroring, autotagging using BLIP or deepdanbooru (for anime)
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- Clip skip
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- Use Hypernetworks
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- Use VAEs
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- Estimated completion time in progress bar
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- API
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- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML.
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- via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embeds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))
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- [Stable Diffusion 2.0](https://github.com/Stability-AI/stablediffusion) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20) for instructions
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## Installation and Running
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Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
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Alternatively, use online services (like Google Colab):
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- [List of Online Services](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services)
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### Automatic Installation on Windows
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1. Install [Python 3.10.6](https://www.python.org/downloads/windows/), checking "Add Python to PATH"
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2. Install [git](https://git-scm.com/download/win).
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3. Download the stable-diffusion-webui repository, for example by running `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git`.
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4. Place `model.ckpt` in the `models` directory (see [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) for where to get it).
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5. _*(Optional)*_ Place `GFPGANv1.4.pth` in the base directory, alongside `webui.py` (see [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) for where to get it).
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6. Run `webui-user.bat` from Windows Explorer as normal, non-administrator, user.
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### Automatic Installation on Linux
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1. Install the dependencies:
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```bash
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# Debian-based:
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sudo apt install wget git python3 python3-venv
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# Red Hat-based:
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sudo dnf install wget git python3
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# Arch-based:
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sudo pacman -S wget git python3
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```
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2. To install in `/home/$(whoami)/stable-diffusion-webui/`, run:
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```bash
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bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh)
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```
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### Installation on Apple Silicon
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Find the instructions [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Installation-on-Apple-Silicon).
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## Contributing
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Here's how to add code to this repo: [Contributing](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Contributing)
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## Documentation
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The documentation was moved from this README over to the project's [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki).
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## Credits
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Licenses for borrowed code can be found in `Settings -> Licenses` screen, and also in `html/licenses.html` file.
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- Stable Diffusion - https://github.com/CompVis/stable-diffusion, https://github.com/CompVis/taming-transformers
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- k-diffusion - https://github.com/crowsonkb/k-diffusion.git
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- GFPGAN - https://github.com/TencentARC/GFPGAN.git
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- CodeFormer - https://github.com/sczhou/CodeFormer
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- ESRGAN - https://github.com/xinntao/ESRGAN
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- SwinIR - https://github.com/JingyunLiang/SwinIR
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- Swin2SR - https://github.com/mv-lab/swin2sr
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- LDSR - https://github.com/Hafiidz/latent-diffusion
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- MiDaS - https://github.com/isl-org/MiDaS
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- Ideas for optimizations - https://github.com/basujindal/stable-diffusion
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- Cross Attention layer optimization - Doggettx - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
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- Cross Attention layer optimization - InvokeAI, lstein - https://github.com/invoke-ai/InvokeAI (originally http://github.com/lstein/stable-diffusion)
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- Textual Inversion - Rinon Gal - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas).
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- Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
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- Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
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- CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator
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- Idea for Composable Diffusion - https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch
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- xformers - https://github.com/facebookresearch/xformers
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- DeepDanbooru - interrogator for anime diffusers https://github.com/KichangKim/DeepDanbooru
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- Security advice - RyotaK
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- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
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- (You)
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# Stable Diffusion - Automatic
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Custom fork of <https://github.com/AUTOMATIC1111/stable-diffusion-webui>
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@ -0,0 +1,152 @@
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{
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"samples_save": true,
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"samples_format": "jpg",
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"samples_filename_pattern": "",
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"save_images_add_number": true,
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"grid_save": true,
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"grid_format": "jpg",
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"grid_extended_filename": true,
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"grid_only_if_multiple": true,
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"grid_prevent_empty_spots": false,
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"n_rows": -1,
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"enable_pnginfo": true,
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"save_txt": false,
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"save_images_before_face_restoration": false,
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"save_images_before_highres_fix": false,
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"save_images_before_color_correction": false,
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"jpeg_quality": 80,
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"export_for_4chan": false,
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"use_original_name_batch": true,
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"use_upscaler_name_as_suffix": true,
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"save_selected_only": true,
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"do_not_add_watermark": true,
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"temp_dir": "",
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"clean_temp_dir_at_start": true,
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"outdir_samples": "",
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"outdir_txt2img_samples": "outputs/text",
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"outdir_img2img_samples": "outputs/image",
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"outdir_extras_samples": "outputs/extras",
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"outdir_grids": "",
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"outdir_txt2img_grids": "outputs/grids",
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"outdir_img2img_grids": "outputs/grids",
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"outdir_save": "outputs/save",
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"save_to_dirs": false,
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"grid_save_to_dirs": false,
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"use_save_to_dirs_for_ui": false,
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"directories_filename_pattern": "",
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"directories_max_prompt_words": 16,
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"ESRGAN_tile": 192,
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"ESRGAN_tile_overlap": 8,
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"realesrgan_enabled_models": [
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"R-ESRGAN 4x+"
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],
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"upscaler_for_img2img": "SwinIR_4x",
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"use_scale_latent_for_hires_fix": false,
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"face_restoration_model": "CodeFormer",
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"code_former_weight": 0.15,
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"face_restoration_unload": false,
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"memmon_poll_rate": 1,
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"samples_log_stdout": false,
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"multiple_tqdm": true,
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"unload_models_when_training": true,
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"pin_memory": true,
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"save_optimizer_state": true,
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"dataset_filename_word_regex": "",
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"dataset_filename_join_string": " ",
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"training_image_repeats_per_epoch": 1,
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"training_write_csv_every": 100.0,
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"training_xattention_optimizations": true,
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"sd_model_checkpoint": "unstable-photoreal-v5.ckpt [358923a7]",
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"sd_checkpoint_cache": 0,
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"sd_vae": "vae-ft-mse-840000-ema-pruned",
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"sd_vae_as_default": false,
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"sd_hypernetwork": "None",
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"sd_hypernetwork_strength": 1.0,
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"inpainting_mask_weight": 1.0,
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"initial_noise_multiplier": 1.0,
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"img2img_color_correction": false,
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"img2img_fix_steps": false,
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"img2img_background_color": "#ffffff",
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"enable_quantization": true,
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"enable_emphasis": true,
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"use_old_emphasis_implementation": false,
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"enable_batch_seeds": true,
|
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"comma_padding_backtrack": 20,
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"CLIP_stop_at_last_layers": 1,
|
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"random_artist_categories": [],
|
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"interrogate_keep_models_in_memory": false,
|
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"interrogate_use_builtin_artists": false,
|
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"interrogate_return_ranks": true,
|
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"interrogate_clip_num_beams": 1,
|
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"interrogate_clip_min_length": 32,
|
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"interrogate_clip_max_length": 1024,
|
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"interrogate_clip_dict_limit": 0.0,
|
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"interrogate_deepbooru_score_threshold": 0.7,
|
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"deepbooru_sort_alpha": false,
|
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"deepbooru_use_spaces": false,
|
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"deepbooru_escape": true,
|
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"deepbooru_filter_tags": "",
|
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"show_progressbar": true,
|
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"show_progress_every_n_steps": -1,
|
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"show_progress_type": "Full",
|
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"show_progress_grid": true,
|
||||
"return_grid": true,
|
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"do_not_show_images": false,
|
||||
"add_model_hash_to_info": true,
|
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"add_model_name_to_info": true,
|
||||
"disable_weights_auto_swap": false,
|
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"send_seed": true,
|
||||
"send_size": true,
|
||||
"font": "",
|
||||
"js_modal_lightbox": true,
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"js_modal_lightbox_initially_zoomed": true,
|
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"show_progress_in_title": true,
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"quicksettings": "sd_model_checkpoint",
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"localization": "None",
|
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"hide_samplers": [
|
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"Euler",
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"LMS",
|
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"Heun",
|
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"DPM2",
|
||||
"DPM2 a",
|
||||
"DPM++ 2M",
|
||||
"DPM fast",
|
||||
"DPM adaptive",
|
||||
"DPM++ 2S a Karras",
|
||||
"DDIM",
|
||||
"PLMS",
|
||||
"DPM++ 2S a",
|
||||
"DPM++ SDE Karras",
|
||||
"DPM2 a Karras"
|
||||
],
|
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"eta_ddim": 0.0,
|
||||
"eta_ancestral": 1.0,
|
||||
"ddim_discretize": "uniform",
|
||||
"s_churn": 0.0,
|
||||
"s_tmin": 0.0,
|
||||
"s_noise": 1.0,
|
||||
"eta_noise_seed_delta": 0,
|
||||
"disabled_extensions": [],
|
||||
"ldsr_steps": 100,
|
||||
"ldsr_cached": false,
|
||||
"SWIN_tile": 192,
|
||||
"SWIN_tile_overlap": 8,
|
||||
"inspiration_max_samples": 20,
|
||||
"inspiration_rows_num": 16,
|
||||
"inspiration_cols_num": 6,
|
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"images_history_preload": false,
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"images_record_paths": true,
|
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"images_delete_message": true,
|
||||
"images_history_page_columns": 6.0,
|
||||
"images_history_page_rows": 20.0,
|
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"images_history_pages_perload": 20.0,
|
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"sd_vae_checkpoint_cache": 0,
|
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"use_old_karras_scheduler_sigmas": false,
|
||||
"samplers_in_dropdown": true,
|
||||
"aesthetic_scorer_enabled": false,
|
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"aesthetic_scorer_clip_model": "ViT-L/14",
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||||
"dimensions_and_batch_together": true,
|
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"ui_reorder": "sampler, dimensions, cfg, seed, checkboxes, hires_fix, batch, scripts",
|
||||
"always_discard_next_to_last_sigma": false,
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"clip_models_path": "models/CLIP"
|
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}
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@ -0,0 +1,67 @@
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model:
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base_learning_rate: 1.0e-4
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target: ldm.models.diffusion.ddpm.LatentDiffusion
|
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params:
|
||||
linear_start: 0.00085
|
||||
linear_end: 0.0120
|
||||
num_timesteps_cond: 1
|
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log_every_t: 200
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timesteps: 1000
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first_stage_key: "jpg"
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cond_stage_key: "txt"
|
||||
image_size: 64
|
||||
channels: 4
|
||||
cond_stage_trainable: false
|
||||
conditioning_key: crossattn
|
||||
monitor: val/loss_simple_ema
|
||||
scale_factor: 0.18215
|
||||
use_ema: False # we set this to false because this is an inference only config
|
||||
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
use_checkpoint: True
|
||||
use_fp16: True
|
||||
image_size: 32 # unused
|
||||
in_channels: 4
|
||||
out_channels: 4
|
||||
model_channels: 320
|
||||
attention_resolutions: [ 4, 2, 1 ]
|
||||
num_res_blocks: 2
|
||||
channel_mult: [ 1, 2, 4, 4 ]
|
||||
num_head_channels: 64 # need to fix for flash-attn
|
||||
use_spatial_transformer: True
|
||||
use_linear_in_transformer: True
|
||||
transformer_depth: 1
|
||||
context_dim: 1024
|
||||
legacy: False
|
||||
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: val/rec_loss
|
||||
ddconfig:
|
||||
#attn_type: "vanilla-xformers"
|
||||
double_z: true
|
||||
z_channels: 4
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 4
|
||||
- 4
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: []
|
||||
dropout: 0.0
|
||||
lossconfig:
|
||||
target: torch.nn.Identity
|
||||
|
||||
cond_stage_config:
|
||||
target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
|
||||
params:
|
||||
freeze: True
|
||||
layer: "penultimate"
|
||||
|
|
@ -0,0 +1,158 @@
|
|||
model:
|
||||
base_learning_rate: 5.0e-05
|
||||
target: ldm.models.diffusion.ddpm.LatentInpaintDiffusion
|
||||
params:
|
||||
linear_start: 0.00085
|
||||
linear_end: 0.0120
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: "jpg"
|
||||
cond_stage_key: "txt"
|
||||
image_size: 64
|
||||
channels: 4
|
||||
cond_stage_trainable: false
|
||||
conditioning_key: hybrid
|
||||
scale_factor: 0.18215
|
||||
monitor: val/loss_simple_ema
|
||||
finetune_keys: null
|
||||
use_ema: False
|
||||
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
use_checkpoint: True
|
||||
image_size: 32 # unused
|
||||
in_channels: 9
|
||||
out_channels: 4
|
||||
model_channels: 320
|
||||
attention_resolutions: [ 4, 2, 1 ]
|
||||
num_res_blocks: 2
|
||||
channel_mult: [ 1, 2, 4, 4 ]
|
||||
num_head_channels: 64 # need to fix for flash-attn
|
||||
use_spatial_transformer: True
|
||||
use_linear_in_transformer: True
|
||||
transformer_depth: 1
|
||||
context_dim: 1024
|
||||
legacy: False
|
||||
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: val/rec_loss
|
||||
ddconfig:
|
||||
#attn_type: "vanilla-xformers"
|
||||
double_z: true
|
||||
z_channels: 4
|
||||
resolution: 256
|
||||
in_channels: 3
|
||||
out_ch: 3
|
||||
ch: 128
|
||||
ch_mult:
|
||||
- 1
|
||||
- 2
|
||||
- 4
|
||||
- 4
|
||||
num_res_blocks: 2
|
||||
attn_resolutions: [ ]
|
||||
dropout: 0.0
|
||||
lossconfig:
|
||||
target: torch.nn.Identity
|
||||
|
||||
cond_stage_config:
|
||||
target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
|
||||
params:
|
||||
freeze: True
|
||||
layer: "penultimate"
|
||||
|
||||
|
||||
data:
|
||||
target: ldm.data.laion.WebDataModuleFromConfig
|
||||
params:
|
||||
tar_base: null # for concat as in LAION-A
|
||||
p_unsafe_threshold: 0.1
|
||||
filter_word_list: "data/filters.yaml"
|
||||
max_pwatermark: 0.45
|
||||
batch_size: 8
|
||||
num_workers: 6
|
||||
multinode: True
|
||||
min_size: 512
|
||||
train:
|
||||
shards:
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-0/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-1/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-2/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-3/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-4/{00000..18699}.tar -" #{00000-94333}.tar"
|
||||
shuffle: 10000
|
||||
image_key: jpg
|
||||
image_transforms:
|
||||
- target: torchvision.transforms.Resize
|
||||
params:
|
||||
size: 512
|
||||
interpolation: 3
|
||||
- target: torchvision.transforms.RandomCrop
|
||||
params:
|
||||
size: 512
|
||||
postprocess:
|
||||
target: ldm.data.laion.AddMask
|
||||
params:
|
||||
mode: "512train-large"
|
||||
p_drop: 0.25
|
||||
# NOTE use enough shards to avoid empty validation loops in workers
|
||||
validation:
|
||||
shards:
|
||||
- "pipe:aws s3 cp s3://deep-floyd-s3/datasets/laion_cleaned-part5/{93001..94333}.tar - "
|
||||
shuffle: 0
|
||||
image_key: jpg
|
||||
image_transforms:
|
||||
- target: torchvision.transforms.Resize
|
||||
params:
|
||||
size: 512
|
||||
interpolation: 3
|
||||
- target: torchvision.transforms.CenterCrop
|
||||
params:
|
||||
size: 512
|
||||
postprocess:
|
||||
target: ldm.data.laion.AddMask
|
||||
params:
|
||||
mode: "512train-large"
|
||||
p_drop: 0.25
|
||||
|
||||
lightning:
|
||||
find_unused_parameters: True
|
||||
modelcheckpoint:
|
||||
params:
|
||||
every_n_train_steps: 5000
|
||||
|
||||
callbacks:
|
||||
metrics_over_trainsteps_checkpoint:
|
||||
params:
|
||||
every_n_train_steps: 10000
|
||||
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
enable_autocast: False
|
||||
disabled: False
|
||||
batch_frequency: 1000
|
||||
max_images: 4
|
||||
increase_log_steps: False
|
||||
log_first_step: False
|
||||
log_images_kwargs:
|
||||
use_ema_scope: False
|
||||
inpaint: False
|
||||
plot_progressive_rows: False
|
||||
plot_diffusion_rows: False
|
||||
N: 4
|
||||
unconditional_guidance_scale: 5.0
|
||||
unconditional_guidance_label: [""]
|
||||
ddim_steps: 50 # todo check these out for depth2img,
|
||||
ddim_eta: 0.0 # todo check these out for depth2img,
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
||||
val_check_interval: 5000000
|
||||
num_sanity_val_steps: 0
|
||||
accumulate_grad_batches: 1
|
||||
|
|
@ -0,0 +1 @@
|
|||
/mnt/c/Users/mandi/OneDrive/Generative/Embeddings
|
||||
|
|
@ -1,11 +0,0 @@
|
|||
name: automatic
|
||||
channels:
|
||||
- pytorch
|
||||
- defaults
|
||||
dependencies:
|
||||
- python=3.10
|
||||
- pip=22.2.2
|
||||
- cudatoolkit=11.3
|
||||
- pytorch=1.12.1
|
||||
- torchvision=0.13.1
|
||||
- numpy=1.23.1
|
||||
Binary file not shown.
|
|
@ -1,16 +1,18 @@
|
|||
blendmodes
|
||||
accelerate
|
||||
basicsr
|
||||
fairscale
|
||||
fonts
|
||||
font-roboto
|
||||
fonts
|
||||
gfpgan
|
||||
gradio
|
||||
invisible-watermark
|
||||
jsonmerge
|
||||
kornia
|
||||
lark
|
||||
numpy
|
||||
omegaconf
|
||||
opencv-contrib-python
|
||||
requests
|
||||
piexif
|
||||
Pillow
|
||||
pytorch_lightning
|
||||
|
|
@ -23,11 +25,10 @@ einops
|
|||
jsonmerge
|
||||
clean-fid
|
||||
resize-right
|
||||
torchdiffeq
|
||||
kornia
|
||||
lark
|
||||
inflection
|
||||
GitPython
|
||||
torchsde
|
||||
safetensors
|
||||
psutil; sys_platform == 'darwin'
|
||||
scikit-image
|
||||
timm
|
||||
torch
|
||||
torchdiffeq
|
||||
torchsde
|
||||
transformers
|
||||
|
|
|
|||
|
|
@ -1,8 +1,11 @@
|
|||
accelerate==0.15.0
|
||||
basicsr==1.4.2
|
||||
blendmodes==2022
|
||||
transformers==4.25.1
|
||||
accelerate==0.15.0
|
||||
basicsr==1.4.2
|
||||
gfpgan==1.3.8
|
||||
GitPython==3.1.27
|
||||
gradio==3.15.0
|
||||
numpy==1.23.5
|
||||
Pillow==9.4.0
|
||||
|
|
@ -11,20 +14,7 @@ torch
|
|||
omegaconf==2.2.3
|
||||
pytorch_lightning==1.7.7
|
||||
scikit-image==0.19.2
|
||||
fonts
|
||||
font-roboto
|
||||
timm==0.6.7
|
||||
fairscale==0.4.9
|
||||
piexif==1.1.3
|
||||
einops==0.4.1
|
||||
jsonmerge==1.8.0
|
||||
clean-fid==0.1.29
|
||||
resize-right==0.0.2
|
||||
torchdiffeq==0.2.3
|
||||
kornia==0.6.7
|
||||
lark==1.1.2
|
||||
inflection==0.5.1
|
||||
GitPython==3.1.27
|
||||
torchsde==0.2.5
|
||||
safetensors==0.2.7
|
||||
httpcore<=0.15
|
||||
transformers==4.25.1
|
||||
|
|
|
|||
BIN
screenshot.png
BIN
screenshot.png
Binary file not shown.
|
Before Width: | Height: | Size: 513 KiB |
|
|
@ -0,0 +1 @@
|
|||
/home/vlado/dev/sd-extensions/scripts/save_steps_animation.py
|
||||
|
|
@ -1,29 +0,0 @@
|
|||
import unittest
|
||||
|
||||
|
||||
class TestExtrasWorking(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.url_img2img = "http://localhost:7860/sdapi/v1/extra-single-image"
|
||||
self.simple_extras = {
|
||||
"resize_mode": 0,
|
||||
"show_extras_results": True,
|
||||
"gfpgan_visibility": 0,
|
||||
"codeformer_visibility": 0,
|
||||
"codeformer_weight": 0,
|
||||
"upscaling_resize": 2,
|
||||
"upscaling_resize_w": 128,
|
||||
"upscaling_resize_h": 128,
|
||||
"upscaling_crop": True,
|
||||
"upscaler_1": "None",
|
||||
"upscaler_2": "None",
|
||||
"extras_upscaler_2_visibility": 0,
|
||||
"image": ""
|
||||
}
|
||||
|
||||
|
||||
class TestExtrasCorrectness(unittest.TestCase):
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
|
|
@ -1,47 +0,0 @@
|
|||
import unittest
|
||||
import requests
|
||||
|
||||
|
||||
class TestTxt2ImgWorking(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.url_txt2img = "http://localhost:7860/sdapi/v1/txt2img"
|
||||
self.simple_txt2img = {
|
||||
"enable_hr": False,
|
||||
"denoising_strength": 0,
|
||||
"firstphase_width": 0,
|
||||
"firstphase_height": 0,
|
||||
"prompt": "example prompt",
|
||||
"styles": [],
|
||||
"seed": -1,
|
||||
"subseed": -1,
|
||||
"subseed_strength": 0,
|
||||
"seed_resize_from_h": -1,
|
||||
"seed_resize_from_w": -1,
|
||||
"batch_size": 1,
|
||||
"n_iter": 1,
|
||||
"steps": 3,
|
||||
"cfg_scale": 7,
|
||||
"width": 64,
|
||||
"height": 64,
|
||||
"restore_faces": False,
|
||||
"tiling": False,
|
||||
"negative_prompt": "",
|
||||
"eta": 0,
|
||||
"s_churn": 0,
|
||||
"s_tmax": 0,
|
||||
"s_tmin": 0,
|
||||
"s_noise": 1,
|
||||
"sampler_index": "Euler a"
|
||||
}
|
||||
|
||||
def test_txt2img_with_restore_faces_performed(self):
|
||||
self.simple_txt2img["restore_faces"] = True
|
||||
self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200)
|
||||
|
||||
|
||||
class TestTxt2ImgCorrectness(unittest.TestCase):
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
|
|
@ -1,55 +0,0 @@
|
|||
import unittest
|
||||
import requests
|
||||
from gradio.processing_utils import encode_pil_to_base64
|
||||
from PIL import Image
|
||||
|
||||
|
||||
class TestImg2ImgWorking(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.url_img2img = "http://localhost:7860/sdapi/v1/img2img"
|
||||
self.simple_img2img = {
|
||||
"init_images": [encode_pil_to_base64(Image.open(r"test/test_files/img2img_basic.png"))],
|
||||
"resize_mode": 0,
|
||||
"denoising_strength": 0.75,
|
||||
"mask": None,
|
||||
"mask_blur": 4,
|
||||
"inpainting_fill": 0,
|
||||
"inpaint_full_res": False,
|
||||
"inpaint_full_res_padding": 0,
|
||||
"inpainting_mask_invert": 0,
|
||||
"prompt": "example prompt",
|
||||
"styles": [],
|
||||
"seed": -1,
|
||||
"subseed": -1,
|
||||
"subseed_strength": 0,
|
||||
"seed_resize_from_h": -1,
|
||||
"seed_resize_from_w": -1,
|
||||
"batch_size": 1,
|
||||
"n_iter": 1,
|
||||
"steps": 3,
|
||||
"cfg_scale": 7,
|
||||
"width": 64,
|
||||
"height": 64,
|
||||
"restore_faces": False,
|
||||
"tiling": False,
|
||||
"negative_prompt": "",
|
||||
"eta": 0,
|
||||
"s_churn": 0,
|
||||
"s_tmax": 0,
|
||||
"s_tmin": 0,
|
||||
"s_noise": 1,
|
||||
"override_settings": {},
|
||||
"sampler_index": "Euler a",
|
||||
"include_init_images": False
|
||||
}
|
||||
|
||||
def test_img2img_simple_performed(self):
|
||||
self.assertEqual(requests.post(self.url_img2img, json=self.simple_img2img).status_code, 200)
|
||||
|
||||
def test_inpainting_masked_performed(self):
|
||||
self.simple_img2img["mask"] = encode_pil_to_base64(Image.open(r"test/test_files/mask_basic.png"))
|
||||
self.assertEqual(requests.post(self.url_img2img, json=self.simple_img2img).status_code, 200)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
|
|
@ -1,68 +0,0 @@
|
|||
import unittest
|
||||
import requests
|
||||
|
||||
|
||||
class TestTxt2ImgWorking(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.url_txt2img = "http://localhost:7860/sdapi/v1/txt2img"
|
||||
self.simple_txt2img = {
|
||||
"enable_hr": False,
|
||||
"denoising_strength": 0,
|
||||
"firstphase_width": 0,
|
||||
"firstphase_height": 0,
|
||||
"prompt": "example prompt",
|
||||
"styles": [],
|
||||
"seed": -1,
|
||||
"subseed": -1,
|
||||
"subseed_strength": 0,
|
||||
"seed_resize_from_h": -1,
|
||||
"seed_resize_from_w": -1,
|
||||
"batch_size": 1,
|
||||
"n_iter": 1,
|
||||
"steps": 3,
|
||||
"cfg_scale": 7,
|
||||
"width": 64,
|
||||
"height": 64,
|
||||
"restore_faces": False,
|
||||
"tiling": False,
|
||||
"negative_prompt": "",
|
||||
"eta": 0,
|
||||
"s_churn": 0,
|
||||
"s_tmax": 0,
|
||||
"s_tmin": 0,
|
||||
"s_noise": 1,
|
||||
"sampler_index": "Euler a"
|
||||
}
|
||||
|
||||
def test_txt2img_simple_performed(self):
|
||||
self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200)
|
||||
|
||||
def test_txt2img_with_negative_prompt_performed(self):
|
||||
self.simple_txt2img["negative_prompt"] = "example negative prompt"
|
||||
self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200)
|
||||
|
||||
def test_txt2img_not_square_image_performed(self):
|
||||
self.simple_txt2img["height"] = 128
|
||||
self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200)
|
||||
|
||||
def test_txt2img_with_hrfix_performed(self):
|
||||
self.simple_txt2img["enable_hr"] = True
|
||||
self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200)
|
||||
|
||||
def test_txt2img_with_tiling_performed(self):
|
||||
self.simple_txt2img["tiling"] = True
|
||||
self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200)
|
||||
|
||||
def test_txt2img_with_vanilla_sampler_performed(self):
|
||||
self.simple_txt2img["sampler_index"] = "PLMS"
|
||||
self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200)
|
||||
self.simple_txt2img["sampler_index"] = "DDIM"
|
||||
self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200)
|
||||
|
||||
def test_txt2img_multiple_batches_performed(self):
|
||||
self.simple_txt2img["n_iter"] = 2
|
||||
self.assertEqual(requests.post(self.url_txt2img, json=self.simple_txt2img).status_code, 200)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
|
|
@ -1,53 +0,0 @@
|
|||
import unittest
|
||||
import requests
|
||||
|
||||
class UtilsTests(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.url_options = "http://localhost:7860/sdapi/v1/options"
|
||||
self.url_cmd_flags = "http://localhost:7860/sdapi/v1/cmd-flags"
|
||||
self.url_samplers = "http://localhost:7860/sdapi/v1/samplers"
|
||||
self.url_upscalers = "http://localhost:7860/sdapi/v1/upscalers"
|
||||
self.url_sd_models = "http://localhost:7860/sdapi/v1/sd-models"
|
||||
self.url_hypernetworks = "http://localhost:7860/sdapi/v1/hypernetworks"
|
||||
self.url_face_restorers = "http://localhost:7860/sdapi/v1/face-restorers"
|
||||
self.url_realesrgan_models = "http://localhost:7860/sdapi/v1/realesrgan-models"
|
||||
self.url_prompt_styles = "http://localhost:7860/sdapi/v1/prompt-styles"
|
||||
self.url_artist_categories = "http://localhost:7860/sdapi/v1/artist-categories"
|
||||
self.url_artists = "http://localhost:7860/sdapi/v1/artists"
|
||||
|
||||
def test_options_get(self):
|
||||
self.assertEqual(requests.get(self.url_options).status_code, 200)
|
||||
|
||||
def test_cmd_flags(self):
|
||||
self.assertEqual(requests.get(self.url_cmd_flags).status_code, 200)
|
||||
|
||||
def test_samplers(self):
|
||||
self.assertEqual(requests.get(self.url_samplers).status_code, 200)
|
||||
|
||||
def test_upscalers(self):
|
||||
self.assertEqual(requests.get(self.url_upscalers).status_code, 200)
|
||||
|
||||
def test_sd_models(self):
|
||||
self.assertEqual(requests.get(self.url_sd_models).status_code, 200)
|
||||
|
||||
def test_hypernetworks(self):
|
||||
self.assertEqual(requests.get(self.url_hypernetworks).status_code, 200)
|
||||
|
||||
def test_face_restorers(self):
|
||||
self.assertEqual(requests.get(self.url_face_restorers).status_code, 200)
|
||||
|
||||
def test_realesrgan_models(self):
|
||||
self.assertEqual(requests.get(self.url_realesrgan_models).status_code, 200)
|
||||
|
||||
def test_prompt_styles(self):
|
||||
self.assertEqual(requests.get(self.url_prompt_styles).status_code, 200)
|
||||
|
||||
def test_artist_categories(self):
|
||||
self.assertEqual(requests.get(self.url_artist_categories).status_code, 200)
|
||||
|
||||
def test_artists(self):
|
||||
self.assertEqual(requests.get(self.url_artists).status_code, 200)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
|
|
@ -1,24 +0,0 @@
|
|||
import unittest
|
||||
import requests
|
||||
import time
|
||||
|
||||
|
||||
def run_tests(proc, test_dir):
|
||||
timeout_threshold = 240
|
||||
start_time = time.time()
|
||||
while time.time()-start_time < timeout_threshold:
|
||||
try:
|
||||
requests.head("http://localhost:7860/")
|
||||
break
|
||||
except requests.exceptions.ConnectionError:
|
||||
if proc.poll() is not None:
|
||||
break
|
||||
if proc.poll() is None:
|
||||
if test_dir is None:
|
||||
test_dir = ""
|
||||
suite = unittest.TestLoader().discover(test_dir, pattern="*_test.py", top_level_dir="test")
|
||||
result = unittest.TextTestRunner(verbosity=2).run(suite)
|
||||
return len(result.failures) + len(result.errors)
|
||||
else:
|
||||
print("Launch unsuccessful")
|
||||
return 1
|
||||
Binary file not shown.
Binary file not shown.
|
Before Width: | Height: | Size: 9.7 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 362 B |
Binary file not shown.
|
Before Width: | Height: | Size: 329 KiB |
|
|
@ -0,0 +1,548 @@
|
|||
{
|
||||
"txt2img/Prompt/visible": true,
|
||||
"txt2img/Prompt/value": "photorealistic, high detailed, sharp focus, depth of field",
|
||||
"txt2img/Negative prompt/visible": true,
|
||||
"txt2img/Negative prompt/value": "foggy, blurry, blurred, duplicate, ugly, mutilated, mutation, mutated, out of frame, bad anatomy, disfigured, deformed, censored, low res, watermark, text, poorly drawn face, signature",
|
||||
"txt2img/Style 1/value": "None",
|
||||
"txt2img/Style 1/visible": true,
|
||||
"txt2img/Style 2/value": "None",
|
||||
"txt2img/Style 2/visible": true,
|
||||
"txt2img/Sampling method/value": "Euler a",
|
||||
"txt2img/Sampling method/visible": true,
|
||||
"txt2img/Sampling Steps/visible": true,
|
||||
"txt2img/Sampling Steps/value": 20,
|
||||
"txt2img/Sampling Steps/minimum": 1,
|
||||
"txt2img/Sampling Steps/maximum": 200,
|
||||
"txt2img/Sampling Steps/step": 1,
|
||||
"txt2img/Width/visible": true,
|
||||
"txt2img/Width/value": 512,
|
||||
"txt2img/Width/minimum": 64,
|
||||
"txt2img/Width/maximum": 2048,
|
||||
"txt2img/Width/step": 8,
|
||||
"txt2img/Height/visible": true,
|
||||
"txt2img/Height/value": 512,
|
||||
"txt2img/Height/minimum": 64,
|
||||
"txt2img/Height/maximum": 2048,
|
||||
"txt2img/Height/step": 8,
|
||||
"txt2img/Batch count/visible": true,
|
||||
"txt2img/Batch count/value": 1,
|
||||
"txt2img/Batch count/minimum": 1,
|
||||
"txt2img/Batch count/maximum": 100,
|
||||
"txt2img/Batch count/step": 1,
|
||||
"txt2img/Batch size/visible": true,
|
||||
"txt2img/Batch size/value": 1,
|
||||
"txt2img/Batch size/minimum": 1,
|
||||
"txt2img/Batch size/maximum": 16,
|
||||
"txt2img/Batch size/step": 1,
|
||||
"txt2img/CFG Scale/visible": true,
|
||||
"txt2img/CFG Scale/value": 6.0,
|
||||
"txt2img/CFG Scale/step": 0.1,
|
||||
"txt2img/CFG Scale/minimum": 1.0,
|
||||
"txt2img/CFG Scale/maximum": 30.0,
|
||||
"txt2img/Seed/visible": true,
|
||||
"txt2img/Seed/value": -1.0,
|
||||
"txt2img/Extra/visible": true,
|
||||
"txt2img/Extra/value": false,
|
||||
"txt2img/Variation seed/visible": true,
|
||||
"txt2img/Variation seed/value": -1.0,
|
||||
"txt2img/Variation strength/visible": true,
|
||||
"txt2img/Variation strength/value": 0.0,
|
||||
"txt2img/Variation strength/minimum": 0,
|
||||
"txt2img/Variation strength/maximum": 1,
|
||||
"txt2img/Variation strength/step": 0.01,
|
||||
"txt2img/Resize seed from width/visible": true,
|
||||
"txt2img/Resize seed from width/value": 0,
|
||||
"txt2img/Resize seed from width/minimum": 0,
|
||||
"txt2img/Resize seed from width/maximum": 2048,
|
||||
"txt2img/Resize seed from width/step": 8,
|
||||
"txt2img/Resize seed from height/visible": true,
|
||||
"txt2img/Resize seed from height/value": 0,
|
||||
"txt2img/Resize seed from height/minimum": 0,
|
||||
"txt2img/Resize seed from height/maximum": 2048,
|
||||
"txt2img/Resize seed from height/step": 8,
|
||||
"txt2img/Restore faces/visible": true,
|
||||
"txt2img/Restore faces/value": false,
|
||||
"txt2img/Tiling/visible": true,
|
||||
"txt2img/Tiling/value": false,
|
||||
"txt2img/Hires. fix/visible": true,
|
||||
"txt2img/Hires. fix/value": false,
|
||||
"txt2img/Upscale by/visible": true,
|
||||
"txt2img/Upscale by/value": 2.0,
|
||||
"txt2img/Upscale by/minimum": 1.0,
|
||||
"txt2img/Upscale by/maximum": 4.0,
|
||||
"txt2img/Upscale by/step": 0.05,
|
||||
"txt2img/Denoising strength/visible": true,
|
||||
"txt2img/Denoising strength/value": 0.7,
|
||||
"txt2img/Denoising strength/minimum": 0.0,
|
||||
"txt2img/Denoising strength/maximum": 1.0,
|
||||
"txt2img/Denoising strength/step": 0.01,
|
||||
"txt2img/Script/value": "None",
|
||||
"txt2img/Script/visible": true,
|
||||
"img2img/Prompt/visible": true,
|
||||
"img2img/Prompt/value": "",
|
||||
"img2img/Negative prompt/visible": true,
|
||||
"img2img/Negative prompt/value": "",
|
||||
"img2img/Style 1/value": "None",
|
||||
"img2img/Style 1/visible": true,
|
||||
"img2img/Style 2/value": "None",
|
||||
"img2img/Style 2/visible": true,
|
||||
"img2img/Mask blur/visible": true,
|
||||
"img2img/Mask blur/value": 4,
|
||||
"img2img/Mask blur/minimum": 0,
|
||||
"img2img/Mask blur/maximum": 64,
|
||||
"img2img/Mask blur/step": 1,
|
||||
"img2img/Mask transparency/value": 0,
|
||||
"img2img/Mask transparency/minimum": 0,
|
||||
"img2img/Mask transparency/maximum": 100,
|
||||
"img2img/Mask transparency/step": 1,
|
||||
"img2img/Mask source/visible": true,
|
||||
"img2img/Mask source/value": "Draw mask",
|
||||
"img2img/Mask mode/visible": true,
|
||||
"img2img/Mask mode/value": "Inpaint masked",
|
||||
"img2img/Masked content/visible": true,
|
||||
"img2img/Masked content/value": "original",
|
||||
"img2img/Inpaint area/visible": true,
|
||||
"img2img/Inpaint area/value": "Whole picture",
|
||||
"img2img/Only masked padding, pixels/visible": true,
|
||||
"img2img/Only masked padding, pixels/value": 32,
|
||||
"img2img/Only masked padding, pixels/minimum": 0,
|
||||
"img2img/Only masked padding, pixels/maximum": 256,
|
||||
"img2img/Only masked padding, pixels/step": 4,
|
||||
"img2img/Input directory/visible": true,
|
||||
"img2img/Input directory/value": "",
|
||||
"img2img/Output directory/visible": true,
|
||||
"img2img/Output directory/value": "",
|
||||
"img2img/Resize mode/visible": true,
|
||||
"img2img/Resize mode/value": "Just resize",
|
||||
"img2img/Sampling method/value": "Euler a",
|
||||
"img2img/Sampling method/visible": true,
|
||||
"img2img/Sampling Steps/visible": true,
|
||||
"img2img/Sampling Steps/value": 20,
|
||||
"img2img/Sampling Steps/minimum": 1,
|
||||
"img2img/Sampling Steps/maximum": 200,
|
||||
"img2img/Sampling Steps/step": 1,
|
||||
"img2img/Width/visible": true,
|
||||
"img2img/Width/value": 512,
|
||||
"img2img/Width/minimum": 64,
|
||||
"img2img/Width/maximum": 2048,
|
||||
"img2img/Width/step": 8,
|
||||
"img2img/Height/visible": true,
|
||||
"img2img/Height/value": 512,
|
||||
"img2img/Height/minimum": 64,
|
||||
"img2img/Height/maximum": 2048,
|
||||
"img2img/Height/step": 8,
|
||||
"img2img/Batch count/visible": true,
|
||||
"img2img/Batch count/value": 1,
|
||||
"img2img/Batch count/minimum": 1,
|
||||
"img2img/Batch count/maximum": 100,
|
||||
"img2img/Batch count/step": 1,
|
||||
"img2img/Batch size/visible": true,
|
||||
"img2img/Batch size/value": 1,
|
||||
"img2img/Batch size/minimum": 1,
|
||||
"img2img/Batch size/maximum": 16,
|
||||
"img2img/Batch size/step": 1,
|
||||
"img2img/CFG Scale/visible": true,
|
||||
"img2img/CFG Scale/value": 6.0,
|
||||
"img2img/CFG Scale/minimum": 1.0,
|
||||
"img2img/CFG Scale/maximum": 30.0,
|
||||
"img2img/CFG Scale/step": 0.5,
|
||||
"img2img/Denoising strength/visible": true,
|
||||
"img2img/Denoising strength/value": 0.75,
|
||||
"img2img/Denoising strength/minimum": 0.0,
|
||||
"img2img/Denoising strength/maximum": 1.0,
|
||||
"img2img/Denoising strength/step": 0.01,
|
||||
"img2img/Seed/visible": true,
|
||||
"img2img/Seed/value": -1.0,
|
||||
"img2img/Extra/visible": true,
|
||||
"img2img/Extra/value": false,
|
||||
"img2img/Variation seed/visible": true,
|
||||
"img2img/Variation seed/value": -1.0,
|
||||
"img2img/Variation strength/visible": true,
|
||||
"img2img/Variation strength/value": 0.0,
|
||||
"img2img/Variation strength/minimum": 0,
|
||||
"img2img/Variation strength/maximum": 1,
|
||||
"img2img/Variation strength/step": 0.01,
|
||||
"img2img/Resize seed from width/visible": true,
|
||||
"img2img/Resize seed from width/value": 0,
|
||||
"img2img/Resize seed from width/minimum": 0,
|
||||
"img2img/Resize seed from width/maximum": 2048,
|
||||
"img2img/Resize seed from width/step": 8,
|
||||
"img2img/Resize seed from height/visible": true,
|
||||
"img2img/Resize seed from height/value": 0,
|
||||
"img2img/Resize seed from height/minimum": 0,
|
||||
"img2img/Resize seed from height/maximum": 2048,
|
||||
"img2img/Resize seed from height/step": 8,
|
||||
"img2img/Restore faces/visible": true,
|
||||
"img2img/Restore faces/value": false,
|
||||
"img2img/Tiling/visible": true,
|
||||
"img2img/Tiling/value": false,
|
||||
"img2img/Script/value": "None",
|
||||
"img2img/Script/visible": true,
|
||||
"extras/Input directory/visible": true,
|
||||
"extras/Input directory/value": "",
|
||||
"extras/Output directory/visible": true,
|
||||
"extras/Output directory/value": "",
|
||||
"extras/Show result images/visible": true,
|
||||
"extras/Show result images/value": true,
|
||||
"extras/Resize/visible": true,
|
||||
"extras/Resize/value": 4,
|
||||
"extras/Resize/minimum": 1.0,
|
||||
"extras/Resize/maximum": 8.0,
|
||||
"extras/Resize/step": 0.05,
|
||||
"extras/Width/visible": true,
|
||||
"extras/Width/value": 512,
|
||||
"extras/Height/visible": true,
|
||||
"extras/Height/value": 512,
|
||||
"extras/Crop to fit/visible": true,
|
||||
"extras/Crop to fit/value": true,
|
||||
"extras/Upscaler 1/visible": true,
|
||||
"extras/Upscaler 1/value": "SwinIR_4x",
|
||||
"extras/Upscaler 2/visible": false,
|
||||
"extras/Upscaler 2/value": "None",
|
||||
"extras/Upscaler 2 visibility/visible": false,
|
||||
"extras/Upscaler 2 visibility/value": 1,
|
||||
"extras/Upscaler 2 visibility/minimum": 0.0,
|
||||
"extras/Upscaler 2 visibility/maximum": 1.0,
|
||||
"extras/Upscaler 2 visibility/step": 0.001,
|
||||
"extras/GFPGAN visibility/visible": true,
|
||||
"extras/GFPGAN visibility/value": 0,
|
||||
"extras/GFPGAN visibility/minimum": 0.0,
|
||||
"extras/GFPGAN visibility/maximum": 1.0,
|
||||
"extras/GFPGAN visibility/step": 0.001,
|
||||
"extras/CodeFormer visibility/visible": true,
|
||||
"extras/CodeFormer visibility/value": 1.0,
|
||||
"extras/CodeFormer visibility/minimum": 0.0,
|
||||
"extras/CodeFormer visibility/maximum": 1.0,
|
||||
"extras/CodeFormer visibility/step": 0.001,
|
||||
"extras/CodeFormer weight (0 = maximum effect, 1 = minimum effect)/visible": true,
|
||||
"extras/CodeFormer weight (0 = maximum effect, 1 = minimum effect)/value": 0.15,
|
||||
"extras/CodeFormer weight (0 = maximum effect, 1 = minimum effect)/minimum": 0.0,
|
||||
"extras/CodeFormer weight (0 = maximum effect, 1 = minimum effect)/maximum": 1.0,
|
||||
"extras/CodeFormer weight (0 = maximum effect, 1 = minimum effect)/step": 0.001,
|
||||
"extras/Upscale Before Restoring Faces/visible": true,
|
||||
"extras/Upscale Before Restoring Faces/value": false,
|
||||
"modelmerger/Custom Name (Optional)/visible": true,
|
||||
"modelmerger/Custom Name (Optional)/value": "",
|
||||
"modelmerger/Multiplier (M) - set to 0 to get model A/visible": true,
|
||||
"modelmerger/Multiplier (M) - set to 0 to get model A/value": 0.3,
|
||||
"modelmerger/Multiplier (M) - set to 0 to get model A/minimum": 0.0,
|
||||
"modelmerger/Multiplier (M) - set to 0 to get model A/maximum": 1.0,
|
||||
"modelmerger/Multiplier (M) - set to 0 to get model A/step": 0.05,
|
||||
"modelmerger/Interpolation Method/visible": true,
|
||||
"modelmerger/Interpolation Method/value": "Weighted sum",
|
||||
"modelmerger/Checkpoint format/visible": true,
|
||||
"modelmerger/Checkpoint format/value": "ckpt",
|
||||
"modelmerger/Save as float16/visible": true,
|
||||
"modelmerger/Save as float16/value": true,
|
||||
"train/Name/visible": true,
|
||||
"train/Name/value": "",
|
||||
"train/Initialization text/visible": true,
|
||||
"train/Initialization text/value": "person",
|
||||
"train/Number of vectors per token/visible": true,
|
||||
"train/Number of vectors per token/value": 2,
|
||||
"train/Number of vectors per token/minimum": 1,
|
||||
"train/Number of vectors per token/maximum": 75,
|
||||
"train/Number of vectors per token/step": 1,
|
||||
"train/Overwrite Old Embedding/visible": true,
|
||||
"train/Overwrite Old Embedding/value": true,
|
||||
"train/Enter hypernetwork layer structure/visible": true,
|
||||
"train/Enter hypernetwork layer structure/value": "1, 2, 1",
|
||||
"train/Add layer normalization/visible": true,
|
||||
"train/Add layer normalization/value": false,
|
||||
"train/Use dropout/visible": true,
|
||||
"train/Use dropout/value": false,
|
||||
"train/Overwrite Old Hypernetwork/visible": true,
|
||||
"train/Overwrite Old Hypernetwork/value": false,
|
||||
"train/Source directory/visible": true,
|
||||
"train/Source directory/value": "",
|
||||
"train/Destination directory/visible": true,
|
||||
"train/Destination directory/value": "",
|
||||
"train/Width/visible": true,
|
||||
"train/Width/value": 512,
|
||||
"train/Width/minimum": 64,
|
||||
"train/Width/maximum": 2048,
|
||||
"train/Width/step": 8,
|
||||
"train/Height/visible": true,
|
||||
"train/Height/value": 512,
|
||||
"train/Height/minimum": 64,
|
||||
"train/Height/maximum": 2048,
|
||||
"train/Height/step": 8,
|
||||
"train/Create flipped copies/visible": true,
|
||||
"train/Create flipped copies/value": false,
|
||||
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|
||||
"customscript/xy_grid.py/img2img/Draw legend/value": true,
|
||||
"customscript/xy_grid.py/img2img/Include Separate Images/visible": true,
|
||||
"customscript/xy_grid.py/img2img/Include Separate Images/value": false,
|
||||
"customscript/xy_grid.py/img2img/Keep -1 for seeds/visible": true,
|
||||
"customscript/xy_grid.py/img2img/Keep -1 for seeds/value": false,
|
||||
"customscript/inspiration.py/img2img/Prompt Placeholder, which can be used at the top of prompt input/visible": true,
|
||||
"customscript/inspiration.py/img2img/Prompt Placeholder, which can be used at the top of prompt input/value": "{inspiration}"
|
||||
}
|
||||
|
|
@ -0,0 +1,59 @@
|
|||
/* generic html tags */
|
||||
html { font-size: 16px; }
|
||||
body, button, input, select, textarea { font-family: "Segoe UI"; font-variant: small-caps; }
|
||||
img { background-color: black; }
|
||||
input[type=range] { height: 14px; appearance: none; margin-top: 12px }
|
||||
input[type=range]::-webkit-slider-runnable-track { width: 100%; height: 18px; cursor: pointer; box-shadow: 2px 2px 3px #111111; background: #50555C; border-radius: 2px; border: 0px solid #222222; }
|
||||
input[type=range]::-webkit-slider-thumb { box-shadow: 2px 2px 3px #111111; border: 0px solid #000000; height: 18px; width: 40px; border-radius: 2px; background: var(--highlight-color); cursor: pointer; -webkit-appearance: none; margin-top: 0px; }
|
||||
::-webkit-scrollbar { width: 12px; }
|
||||
::-webkit-scrollbar-track { background: #333333; }
|
||||
::-webkit-scrollbar-thumb { background-color: var(--highlight-color); border-radius: 2px; border-width: 0; box-shadow: 2px 2px 3px #111111; }
|
||||
|
||||
/* main gradio components by selector */
|
||||
div.gradio-container.dark > div.w-full.flex.flex-col.min-h-screen > div { background-color: black; }
|
||||
|
||||
/* gradio shadowroot */
|
||||
.gradio-container { font-family: "Segoe UI"; font-variant: small-caps; --left-column: 540px; --highlight-color: #CE6400; --inactive-color: #4E1400; }
|
||||
|
||||
/* gradio style classes */
|
||||
.tabs { background-color: black; }
|
||||
.dark { background-color: black; }
|
||||
.dark .gr-panel { border-radius: 0; background-color: black; }
|
||||
.dark .gr-input-label { color: lightyellow; border-width: 0; background: transparent; padding: 2px !important; }
|
||||
.dark .gr-input { background-color: #333333 !important; }
|
||||
.dark .gr-form { border-radius: 0; border-width: 0; }
|
||||
.dark .gr-check-radio { background-color: var(--inactive-color); border-width: 0; border-radius: 2px; box-shadow: 2px 2px 3px #111111; }
|
||||
.dark .gr-check-radio:checked { background-color: var(--highlight-color); }
|
||||
.dark .gr-button { border-radius: 0; font-weight: normal; box-shadow: 2px 2px 3px #111111; font-size: 0.9rem; min-width: 32px; }
|
||||
.dark .gr-box { border-radius: 0; background-color: #222222; box-shadow: 2px 2px 3px #111111; border-width: 0; padding-bottom: 12px; }
|
||||
.dark .dark\:bg-gray-900 { background-color: black; }
|
||||
.dark .bg-white { color: lightyellow; border-radius: 0; }
|
||||
.dark fieldset span.text-gray-500, .dark .gr-block.gr-box span.text-gray-500, .dark label.block span { background-color: #222222; padding: 0 12px 0 12px; }
|
||||
.dark .bg-gray-200, .dark .\!bg-gray-200 { background-color: transparent; }
|
||||
.gap-2 { padding-top: 8px; }
|
||||
.border-2 { border-width: 0; }
|
||||
.border-b-2 { border-bottom-width: 2px; border-color: var(--highlight-color) !important; padding-bottom: 2px; margin-bottom: 8px; }
|
||||
.px-4 { padding-lefT: 1rem; padding-right: 1rem; }
|
||||
.py-6 { padding-bottom: 0; }
|
||||
.overflow-hidden .flex .flex-col .relative col .gap-4 { min-width: var(--left-column); max-width: var(--left-column); } /* this is a problematic one */
|
||||
|
||||
/* automatic style classes */
|
||||
.progressDiv .progress { background: var(--highlight-color); border-radius: 2px; }
|
||||
.gallery-item { box-shadow: none !important; }
|
||||
|
||||
/* gradio elements overrides */
|
||||
#txt2img_settings, #img2img_settings { min-width: var(--left-column); max-width: var(--left-column); }
|
||||
#txt2img_prompt > label > textarea { font-size: 1.2rem; }
|
||||
#txt2img_neg_prompt > label > textarea { font-size: 1.2rem; }
|
||||
#img2img_prompt > label > textarea { font-size: 1.2rem; }
|
||||
#img2img_neg_prompt > label > textarea { font-size: 1.2rem; }
|
||||
#txt2img_generate, #img2img_generate, #txt2img_interrupt, #img2img_interrupt, #txt2img_skip, #img2img_skip { margin-top: 10px; min-height: 2rem; height: 63px; }
|
||||
#txt2img_interrupt, #img2img_interrupt, #txt2img_skip, #img2img_skip { background-color: var(--inactive-color); }
|
||||
#txt2img_gallery { background: black; }
|
||||
#tab_extensions table { background-color: #222222; }
|
||||
#style_pos_col, #style_neg_col, #roll_col { display: none; }
|
||||
#interrogate_col { margin-top: 10px; }
|
||||
#txt2img_progress_row > div { min-width: var(--left-column); max-width: var(--left-column); }
|
||||
#save-animation { border-radius: 0 !important; margin-bottom: 16px; background-color: #111111; }
|
||||
#open_folder_txt2img, #open_folder_img2img, #open_folder_extras { display: none }
|
||||
#footer { display: none; }
|
||||
|
|
@ -1,19 +0,0 @@
|
|||
#!/bin/bash
|
||||
####################################################################
|
||||
# macOS defaults #
|
||||
# Please modify webui-user.sh to change these instead of this file #
|
||||
####################################################################
|
||||
|
||||
if [[ -x "$(command -v python3.10)" ]]
|
||||
then
|
||||
python_cmd="python3.10"
|
||||
fi
|
||||
|
||||
export install_dir="$HOME"
|
||||
export COMMANDLINE_ARGS="--skip-torch-cuda-test --no-half --use-cpu interrogate"
|
||||
export TORCH_COMMAND="pip install torch==1.12.1 torchvision==0.13.1"
|
||||
export K_DIFFUSION_REPO="https://github.com/brkirch/k-diffusion.git"
|
||||
export K_DIFFUSION_COMMIT_HASH="51c9778f269cedb55a4d88c79c0246d35bdadb71"
|
||||
export PYTORCH_ENABLE_MPS_FALLBACK=1
|
||||
|
||||
####################################################################
|
||||
|
|
@ -1,8 +0,0 @@
|
|||
@echo off
|
||||
|
||||
set PYTHON=
|
||||
set GIT=
|
||||
set VENV_DIR=
|
||||
set COMMANDLINE_ARGS=
|
||||
|
||||
call webui.bat
|
||||
|
|
@ -1,46 +0,0 @@
|
|||
#!/bin/bash
|
||||
#########################################################
|
||||
# Uncomment and change the variables below to your need:#
|
||||
#########################################################
|
||||
|
||||
# Install directory without trailing slash
|
||||
#install_dir="/home/$(whoami)"
|
||||
|
||||
# Name of the subdirectory
|
||||
#clone_dir="stable-diffusion-webui"
|
||||
|
||||
# Commandline arguments for webui.py, for example: export COMMANDLINE_ARGS="--medvram --opt-split-attention"
|
||||
#export COMMANDLINE_ARGS=""
|
||||
|
||||
# python3 executable
|
||||
#python_cmd="python3"
|
||||
|
||||
# git executable
|
||||
#export GIT="git"
|
||||
|
||||
# python3 venv without trailing slash (defaults to ${install_dir}/${clone_dir}/venv)
|
||||
#venv_dir="venv"
|
||||
|
||||
# script to launch to start the app
|
||||
#export LAUNCH_SCRIPT="launch.py"
|
||||
|
||||
# install command for torch
|
||||
#export TORCH_COMMAND="pip install torch==1.12.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113"
|
||||
|
||||
# Requirements file to use for stable-diffusion-webui
|
||||
#export REQS_FILE="requirements_versions.txt"
|
||||
|
||||
# Fixed git repos
|
||||
#export K_DIFFUSION_PACKAGE=""
|
||||
#export GFPGAN_PACKAGE=""
|
||||
|
||||
# Fixed git commits
|
||||
#export STABLE_DIFFUSION_COMMIT_HASH=""
|
||||
#export TAMING_TRANSFORMERS_COMMIT_HASH=""
|
||||
#export CODEFORMER_COMMIT_HASH=""
|
||||
#export BLIP_COMMIT_HASH=""
|
||||
|
||||
# Uncomment to enable accelerated launch
|
||||
#export ACCELERATE="True"
|
||||
|
||||
###########################################
|
||||
74
webui.bat
74
webui.bat
|
|
@ -1,74 +0,0 @@
|
|||
@echo off
|
||||
|
||||
if not defined PYTHON (set PYTHON=python)
|
||||
if not defined VENV_DIR (set VENV_DIR=venv)
|
||||
|
||||
set ERROR_REPORTING=FALSE
|
||||
|
||||
mkdir tmp 2>NUL
|
||||
|
||||
%PYTHON% -c "" >tmp/stdout.txt 2>tmp/stderr.txt
|
||||
if %ERRORLEVEL% == 0 goto :start_venv
|
||||
echo Couldn't launch python
|
||||
goto :show_stdout_stderr
|
||||
|
||||
:start_venv
|
||||
if [%VENV_DIR%] == [-] goto :skip_venv
|
||||
|
||||
dir %VENV_DIR%\Scripts\Python.exe >tmp/stdout.txt 2>tmp/stderr.txt
|
||||
if %ERRORLEVEL% == 0 goto :activate_venv
|
||||
|
||||
for /f "delims=" %%i in ('CALL %PYTHON% -c "import sys; print(sys.executable)"') do set PYTHON_FULLNAME="%%i"
|
||||
echo Creating venv in directory %VENV_DIR% using python %PYTHON_FULLNAME%
|
||||
%PYTHON_FULLNAME% -m venv %VENV_DIR% >tmp/stdout.txt 2>tmp/stderr.txt
|
||||
if %ERRORLEVEL% == 0 goto :activate_venv
|
||||
echo Unable to create venv in directory %VENV_DIR%
|
||||
goto :show_stdout_stderr
|
||||
|
||||
:activate_venv
|
||||
set PYTHON="%~dp0%VENV_DIR%\Scripts\Python.exe"
|
||||
echo venv %PYTHON%
|
||||
if [%ACCELERATE%] == ["True"] goto :accelerate
|
||||
goto :launch
|
||||
|
||||
:skip_venv
|
||||
|
||||
:accelerate
|
||||
echo "Checking for accelerate"
|
||||
set ACCELERATE="%~dp0%VENV_DIR%\Scripts\accelerate.exe"
|
||||
if EXIST %ACCELERATE% goto :accelerate_launch
|
||||
|
||||
:launch
|
||||
%PYTHON% launch.py %*
|
||||
pause
|
||||
exit /b
|
||||
|
||||
:accelerate_launch
|
||||
echo "Accelerating"
|
||||
%ACCELERATE% launch --num_cpu_threads_per_process=6 launch.py
|
||||
pause
|
||||
exit /b
|
||||
|
||||
:show_stdout_stderr
|
||||
|
||||
echo.
|
||||
echo exit code: %errorlevel%
|
||||
|
||||
for /f %%i in ("tmp\stdout.txt") do set size=%%~zi
|
||||
if %size% equ 0 goto :show_stderr
|
||||
echo.
|
||||
echo stdout:
|
||||
type tmp\stdout.txt
|
||||
|
||||
:show_stderr
|
||||
for /f %%i in ("tmp\stderr.txt") do set size=%%~zi
|
||||
if %size% equ 0 goto :show_stderr
|
||||
echo.
|
||||
echo stderr:
|
||||
type tmp\stderr.txt
|
||||
|
||||
:endofscript
|
||||
|
||||
echo.
|
||||
echo Launch unsuccessful. Exiting.
|
||||
pause
|
||||
169
webui.sh
169
webui.sh
|
|
@ -1,169 +0,0 @@
|
|||
#!/usr/bin/env bash
|
||||
#################################################
|
||||
# Please do not make any changes to this file, #
|
||||
# change the variables in webui-user.sh instead #
|
||||
#################################################
|
||||
|
||||
# If run from macOS, load defaults from webui-macos-env.sh
|
||||
if [[ "$OSTYPE" == "darwin"* ]]; then
|
||||
if [[ -f webui-macos-env.sh ]]
|
||||
then
|
||||
source ./webui-macos-env.sh
|
||||
fi
|
||||
fi
|
||||
|
||||
# Read variables from webui-user.sh
|
||||
# shellcheck source=/dev/null
|
||||
if [[ -f webui-user.sh ]]
|
||||
then
|
||||
source ./webui-user.sh
|
||||
fi
|
||||
|
||||
# Set defaults
|
||||
# Install directory without trailing slash
|
||||
if [[ -z "${install_dir}" ]]
|
||||
then
|
||||
install_dir="/home/$(whoami)"
|
||||
fi
|
||||
|
||||
# Name of the subdirectory (defaults to stable-diffusion-webui)
|
||||
if [[ -z "${clone_dir}" ]]
|
||||
then
|
||||
clone_dir="stable-diffusion-webui"
|
||||
fi
|
||||
|
||||
# python3 executable
|
||||
if [[ -z "${python_cmd}" ]]
|
||||
then
|
||||
python_cmd="python3"
|
||||
fi
|
||||
|
||||
# git executable
|
||||
if [[ -z "${GIT}" ]]
|
||||
then
|
||||
export GIT="git"
|
||||
fi
|
||||
|
||||
# python3 venv without trailing slash (defaults to ${install_dir}/${clone_dir}/venv)
|
||||
if [[ -z "${venv_dir}" ]]
|
||||
then
|
||||
venv_dir="venv"
|
||||
fi
|
||||
|
||||
if [[ -z "${LAUNCH_SCRIPT}" ]]
|
||||
then
|
||||
LAUNCH_SCRIPT="launch.py"
|
||||
fi
|
||||
|
||||
# this script cannot be run as root by default
|
||||
can_run_as_root=0
|
||||
|
||||
# read any command line flags to the webui.sh script
|
||||
while getopts "f" flag > /dev/null 2>&1
|
||||
do
|
||||
case ${flag} in
|
||||
f) can_run_as_root=1;;
|
||||
*) break;;
|
||||
esac
|
||||
done
|
||||
|
||||
# Disable sentry logging
|
||||
export ERROR_REPORTING=FALSE
|
||||
|
||||
# Do not reinstall existing pip packages on Debian/Ubuntu
|
||||
export PIP_IGNORE_INSTALLED=0
|
||||
|
||||
# Pretty print
|
||||
delimiter="################################################################"
|
||||
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "\e[1m\e[32mInstall script for stable-diffusion + Web UI\n"
|
||||
printf "\e[1m\e[34mTested on Debian 11 (Bullseye)\e[0m"
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
|
||||
# Do not run as root
|
||||
if [[ $(id -u) -eq 0 && can_run_as_root -eq 0 ]]
|
||||
then
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "\e[1m\e[31mERROR: This script must not be launched as root, aborting...\e[0m"
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
exit 1
|
||||
else
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "Running on \e[1m\e[32m%s\e[0m user" "$(whoami)"
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
fi
|
||||
|
||||
if [[ -d .git ]]
|
||||
then
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "Repo already cloned, using it as install directory"
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
install_dir="${PWD}/../"
|
||||
clone_dir="${PWD##*/}"
|
||||
fi
|
||||
|
||||
# Check prerequisites
|
||||
for preq in "${GIT}" "${python_cmd}"
|
||||
do
|
||||
if ! hash "${preq}" &>/dev/null
|
||||
then
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "\e[1m\e[31mERROR: %s is not installed, aborting...\e[0m" "${preq}"
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
exit 1
|
||||
fi
|
||||
done
|
||||
|
||||
if ! "${python_cmd}" -c "import venv" &>/dev/null
|
||||
then
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "\e[1m\e[31mERROR: python3-venv is not installed, aborting...\e[0m"
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
cd "${install_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/, aborting...\e[0m" "${install_dir}"; exit 1; }
|
||||
if [[ -d "${clone_dir}" ]]
|
||||
then
|
||||
cd "${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
|
||||
else
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "Clone stable-diffusion-webui"
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
"${GIT}" clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git "${clone_dir}"
|
||||
cd "${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
|
||||
fi
|
||||
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "Create and activate python venv"
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
cd "${install_dir}"/"${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
|
||||
if [[ ! -d "${venv_dir}" ]]
|
||||
then
|
||||
"${python_cmd}" -m venv "${venv_dir}"
|
||||
first_launch=1
|
||||
fi
|
||||
# shellcheck source=/dev/null
|
||||
if [[ -f "${venv_dir}"/bin/activate ]]
|
||||
then
|
||||
source "${venv_dir}"/bin/activate
|
||||
else
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "\e[1m\e[31mERROR: Cannot activate python venv, aborting...\e[0m"
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [[ ! -z "${ACCELERATE}" ]] && [ ${ACCELERATE}="True" ] && [ -x "$(command -v accelerate)" ]
|
||||
then
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "Accelerating launch.py..."
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
exec accelerate launch --num_cpu_threads_per_process=6 "${LAUNCH_SCRIPT}" "$@"
|
||||
else
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
printf "Launching launch.py..."
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
exec "${python_cmd}" "${LAUNCH_SCRIPT}" "$@"
|
||||
fi
|
||||
|
|
@ -0,0 +1 @@
|
|||
Subproject commit bc9a09829dbc90760c8626c83824e05cfab5cb98
|
||||
Loading…
Reference in New Issue