init
dr413677671
commit
91b97c2097
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path_recorder.txt
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@ -0,0 +1,278 @@
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<a name="readme-top"></a>
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<div align="center">
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||||
[![Contributors][contributors-shield]][contributors-url]
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||||
[![Forks][forks-shield]][forks-url]
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||||
[![Stargazers][stars-shield]][stars-url]
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||||
[![Issues][issues-shield]][issues-url]
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||||
|
||||
</div>
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||||
<!-- [![MIT License][license-shield]][license-url]
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[![LinkedIn][linkedin-shield]][linkedin-url] -->
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||||
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||||
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<!-- PROJECT LOGO -->
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<br />
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<div align="center">
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<a href="https://github.com/dr413677671/PromptGallery-stable-diffusion-webui">
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<img src="images/logo.png" alt="Logo" width="206.25" height="131.25">
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</a>
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<h3 align="center">Prompt Gallery</h3>
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<p align="center">
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A prompt cookbook worked as stable-diffusion-webui extenstions.
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<br />
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<a href="https://github.com/dr413677671/PromptGallery-stable-diffusion-webui/README.md"><strong>Explore the docs »</strong></a>
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<br />
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<br />
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<a href="https://www.youtube.com/watch?v=9U6-moIJUkk">View Demo</a>
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·
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||||
<a href="https://github.com/dr413677671/PromptGallery-stable-diffusion-webui/issues">Report Bug</a>
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||||
·
|
||||
<a href="https://github.com/dr413677671/PromptGallery-stable-diffusion-webui/issues">Request Feature</a>
|
||||
</p>
|
||||
</div>
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||||
|
||||
|
||||
|
||||
<!-- TABLE OF CONTENTS -->
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<details>
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<summary>Table of Contents</summary>
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<ol>
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<li>
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<a href="#about-the-project">About The Project</a>
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<ul>
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<li><a href="#built-with">Built With</a></li>
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</ul>
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</li>
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<li>
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<a href="#getting-started">Getting Started</a>
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<ul>
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<li><a href="#prerequisites">Prerequisites</a></li>
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<li><a href="#installation">Installation</a></li>
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</ul>
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</li>
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<li><a href="#usage">Usage</a></li>
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<li><a href="#roadmap">Roadmap</a></li>
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<li><a href="#contributing">Contributing</a></li>
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<li><a href="#license">License</a></li>
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<li><a href="#contact">Contact</a></li>
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<li><a href="#acknowledgments">Acknowledgments</a></li>
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</ol>
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</details>
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||||
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|
||||
<!-- ABOUT THE PROJECT -->
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<div align=center>
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<img src='./images/front.JPG'>
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</div>
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## About The Project
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TLDR; Stable-diffusion is an AI model which can generate illustration based on text-based prompts. What does a prompt/prompt-set looks like in AI's eyes? Could we do AI illustraion like shopping?
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Prompt Gallery works as a guidebook to ease users life in AI art creation. Look at previews and select prompt-set. Life is that easy.
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## Cool Features:
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* Scalable Prompt Library
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* Stable-Diffusion-WebUI Integration
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* Avatar System (model/character presets)
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Keep your pace. Let's start from building your prompt library.
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<p align="right">(<a href="#readme-top">back to top</a>)</p>
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### Built With
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* [![Python][python-img]][python-url]
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* [![React][fastapi-img]][fastapi-url]
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* [![Vue][Vue.js]][Vue-url]
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* [![JQuery][JQuery.com]][JQuery-url]
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<p align="right">(<a href="#readme-top">back to top</a>)</p>
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|
||||
|
||||
|
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<!-- GETTING STARTED -->
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## Getting Started
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### Prerequisites
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1) Clone Prompt-Gallery extension.
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* git
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```sh
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git clone https://github.com/dr413677671/PromptGallery-stable-diffusion-webui.git
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```
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alternative-1) Download from github release
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TBD
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alternative-2) Download from docker hub
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TBD
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### Installation
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1. Paste Prompt-Gallery in the root directory of stable-diffusion-webui.
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2. Start ./webui-user.sh
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3. If you see an error of missing library. Run
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```sh
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pip install -r <stable-diffusion-webui-path>/extensions/prompt-gallery/requirements.txt
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```
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<p align="right">(<a href="#readme-top">back to top</a>)</p>
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## Usage
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View the video tutorial:
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<a href="https://www.youtube.com/watch?v=9U6-moIJUkk">View Demo</a>
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### Build up the prompt library and character library.
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| value | negative | param |
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| :-----| ----: | :----: |
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| Positive prompts | Negative prompts | Other params of image generation |
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Edit the teamplate at <stable-diffusion-webui-path>/extensions/prompt-gallery/assets/avatars.yaml, and customize your avatars.
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Teamplate:
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```yaml
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whiteHair:
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value: "1 girl, blush, White hair, Red eyes, animal ears, looking at viewer, gothic lolita, dramatic angle, very beautiful, beautiful eyes, "
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negative: ""
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pinkGirl:
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value: "petite, 1girl, solo, pink hair, very long hair, school uniform, happy,outdoors, flower field, excited"
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```
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Edit the teamplate at <stable-diffusion-webui-path>/extensions/prompt-gallery/assets/tags.yaml, and create your prompt-set categorical library.
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Teamplate:
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```yaml
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Style:
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General Effect:
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"General_ice_high_res":
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value: "flowing ice, portrait, focus on face, complex, extremely detailed , elegant, CG, (an extremely delicate and beautiful girl), incredibly absurdres, best quality,concept art"
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negative: "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, "
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param: "Steps: 30, Sampler: Euler, CFG scale: 11.5, Seed: 1058629707, Size: 512x768, Variation seed: 1692844643, Variation seed strength: 0.27, Seed resize from: 1088x512"
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Background:
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'':
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simple background:
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value: simple background
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sunburst background:
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value: sunburst background
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Nature:
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Space:
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value: "space background, space,"
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Startrails:
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value: colorful startrails
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```
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### Start stable-diffusion-webui
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```sh
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./webui-user.bat
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```
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### Start Prompt Gallery
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Slect tab "Prompt Gallery" on top navigation bar.
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Select avatar (model for demo) -> Select prompt-sets -> Click "send WebUI"
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Checkout the downloaded Images
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### Populate previews
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For instance having added two prompt-sets, and we would like to add preview pictures for them.
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Goto tab "txt2img" and Select "Prompt Gallery" in tab "scripts"
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Upload yaml library of avatar first and select avatar.
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Add default prompts and upload prompt-set yaml library.
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Wait for stable-diffusion-webui generate previews automatically.
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Pick the best image for preview.
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Check it out in Prompt Gallery.
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<p align="right">(<a href="#readme-top">back to top</a>)</p>
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|
||||
<!-- CONTRIBUTING -->
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## Contributing
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Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.
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<p align="right">(<a href="#readme-top">back to top</a>)</p>
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||||
|
||||
<!-- CONTACT -->
|
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## Talk with me
|
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|
||||
* dr413677671 - [@zhihu-Calcifer](https://www.zhihu.com/people/kumonoue) - 413677671@qq.com
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* Project Link: [https://github.com/dr413677671/PromptGallery-stable-diffusion-webui](https://github.com/dr413677671/PromptGallery-stable-diffusion-webui)
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<p align="right">(<a href="#readme-top">back to top</a>)</p>
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|
||||
<!-- ACKNOWLEDGMENTS -->
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## Acknowledgments
|
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* [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui)
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* [novelai-tag](https://github.com/blacktunes/novelai-tag)
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<p align="right">(<a href="#readme-top">back to top</a>)</p>
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<!-- MARKDOWN LINKS & IMAGES -->
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<!-- https://www.markdownguide.org/basic-syntax/#reference-style-links -->
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[contributors-shield]: https://img.shields.io/github/contributors/dr413677671/PromptGallery-stable-diffusion-webui.svg?style=for-the-badge
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[contributors-url]: https://github.com/dr413677671/PromptGallery-stable-diffusion-webui/graphs/contributors
|
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[forks-shield]: https://img.shields.io/github/forks/dr413677671/PromptGallery-stable-diffusion-webui.svg?style=for-the-badge
|
||||
[forks-url]: https://github.com/dr413677671/PromptGallery-stable-diffusion-webui/network/members
|
||||
[stars-shield]: https://img.shields.io/github/stars/dr413677671/PromptGallery-stable-diffusion-webui.svg?style=for-the-badge
|
||||
[stars-url]: https://github.com/dr413677671/PromptGallery-stable-diffusion-webui/stargazers
|
||||
[issues-shield]: https://img.shields.io/github/issues/dr413677671/PromptGallery-stable-diffusion-webui.svg?style=for-the-badge
|
||||
[issues-url]: https://github.com/dr413677671/PromptGallery-stable-diffusion-webui/issues
|
||||
|
||||
[product-screenshot]: images/screenshot.png
|
||||
[Vue.js]: https://img.shields.io/badge/Vue.js-35495E?style=for-the-badge&logo=vuedotjs&logoColor=4FC08D
|
||||
[Vue-url]: https://vuejs.org/
|
||||
[JQuery.com]: https://img.shields.io/badge/jQuery-0769AD?style=for-the-badge&logo=jquery&logoColor=white
|
||||
[JQuery-url]: https://jquery.com
|
||||
[python-img]: https://img.shields.io/badge/python-v3.9-green
|
||||
[python-url]: https://www.python.org/
|
||||
[fastapi-img]: https://img.shields.io/badge/FastAPI-v0.87.0-green
|
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[fastapi-url]: https://fastapi.tiangolo.com/
|
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|
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path_recorder.txt
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whiteHair:
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value: "1 girl, blush, White hair, Red eyes, animal ears, looking at viewer, gothic lolita, dramatic angle, very beautiful, beautiful eyes, "
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negative: ""
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pinkGirl:
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value: "petite, 1girl, solo, pink hair, very long hair, school uniform, happy,outdoors, flower field, excited"
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Presets:
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General:
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"General_ice_high_res":
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value: "flowing ice, portrait, focus on face, complex, extremely detailed , elegant, CG, (an extremely delicate and beautiful girl), incredibly absurdres, best quality,concept art"
|
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negative: "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts,signature, watermark, username, blurry, artist name,bad feet, multiple breasts, lowres, bad anatomy, bad hands, text, error, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, bad feet, single color, ((((ugly)))), (((duplicate))), ((morbid)), ((mutilated)), (((tranny))), (((trans))), (((trannsexual))), (hermaphrodite), (out of frame), extra fingers, mutated hands, ((poorly drawn hands)), ((poorly drawn face)), (((mutation))), (((deformed))), ((ugly)), blurry, ((bad anatomy)), (((bad proportions))), ((extra limbs)), (((disfigured))), out of frame, (bad anatomy), gross proportions, (malformed limbs), ((missing arms)), ((missing legs)), (((extra arms))), (((extra legs))), mutated hands,(fused fingers), (too many fingers), (((long neck))), more than one people, more than one light, more than one head, more than one face, more than one body,"
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"General_fire_high_res":
|
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value: "flowing fire, portrait, focus on face, complex, extremely detailed , elegant, CG, (an extremely delicate and beautiful girl), incredibly absurdres, best quality,concept art"
|
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negative: "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts,signature, watermark, username, blurry, artist name,bad feet, multiple breasts, lowres, bad anatomy, bad hands, text, error, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, bad feet, single color, ((((ugly)))), (((duplicate))), ((morbid)), ((mutilated)), (((tranny))), (((trans))), (((trannsexual))), (hermaphrodite), (out of frame), extra fingers, mutated hands, ((poorly drawn hands)), ((poorly drawn face)), (((mutation))), (((deformed))), ((ugly)), blurry, ((bad anatomy)), (((bad proportions))), ((extra limbs)), (((disfigured))), out of frame, (bad anatomy), gross proportions, (malformed limbs), ((missing arms)), ((missing legs)), (((extra arms))), (((extra legs))), mutated hands,(fused fingers), (too many fingers), (((long neck))), more than one people, more than one light, more than one head, more than one face, more than one body,"
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"General_celluloid_online_clean":
|
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value: "best quality, masterpiece, highres, original, extremely detailed wallpaper, intricate detailed"
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param: "Steps: 30, Sampler: Euler, CFG scale: 11.5, Seed: 1058629707, Size: 512x768, Variation seed: 1692844643, Variation seed strength: 0.27, Seed resize from: 1088x512"
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Style:
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ArtStyle:
|
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ink doodle:
|
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value: ink doodle
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cartoon:
|
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value: "(((cartoon)))"
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3D:
|
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3dCG:
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value: "3d"
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<!DOCTYPE html>
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<html lang="en">
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<head>
|
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<meta charset="UTF-8" />
|
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
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<title>Prompt Gallery</title>
|
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<script type="module" crossorigin src="/assets/index.d8193a82.js"></script>
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<link rel="stylesheet" href="/assets/index.78a31c12.css">
|
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</head>
|
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<body>
|
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<div id="app"></div>
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|
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</body>
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</html>
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pyyaml
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|
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import os
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import shutil
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import time
|
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import stat
|
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import gradio as gr
|
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import modules.extras
|
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import modules.ui
|
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from modules.shared import opts, cmd_opts
|
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from modules import shared, scripts
|
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from modules import script_callbacks
|
||||
from pathlib import Path
|
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from typing import List, Tuple
|
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import uvicorn
|
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from uvicorn import Config
|
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from fastapi import FastAPI
|
||||
from fastapi.staticfiles import StaticFiles
|
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import contextlib
|
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import threading
|
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import requests
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
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|
||||
|
||||
def on_ui_settings():
|
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app = FastAPI()
|
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app.mount('/', StaticFiles(directory='./extensions/prompt-gallery',html=True))
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config = Config(app=app, host='localhost',port=5173, log_level="info", loop="asyncio", limit_max_requests=1)
|
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app.add_middleware(
|
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CORSMiddleware,
|
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allow_origins=["*"],
|
||||
allow_credentials=True,
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"]
|
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)
|
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|
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thread = threading.Thread(target= uvicorn.run, kwargs={'app':app, 'host': 'localhost', 'port':5173})
|
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thread.start()
|
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tmp = requests.get("http://localhost:5173")
|
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while tmp.status_code != 204 and tmp.status_code != 200:
|
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time.sleep(0.01)
|
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tmp = requests.get("http://localhost:5173")
|
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pass
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# thread.join()
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|
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|
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|
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def on_ui_tabs():
|
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html = """<iframe id="tab_iframe" style="width: 100%; min-height: 864px; padding: 0;margin: 0;border: none;" src="http://localhost:5173/" frameborder="0" marginwidth="0" marginheight="0"></iframe>"""
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with gr.Blocks(analytics_enabled=False, elem_id="prompt_gallery") as prompt_gallery:
|
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prompt_gallery = gr.HTML(html)
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|
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return (prompt_gallery , "Prompt Gallery", "prompt_gallery"),
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|
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script_callbacks.on_ui_tabs(on_ui_tabs)
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script_callbacks.on_ui_settings(on_ui_settings)
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import copy
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import os
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import random
|
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import sys
|
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import traceback
|
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import shlex
|
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import yaml
|
||||
import platform
|
||||
import subprocess as sp
|
||||
import shutil
|
||||
import tempfile
|
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import gradio as gr
|
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import csv
|
||||
import typing
|
||||
import base64
|
||||
import io
|
||||
from PIL import Image
|
||||
import mimetypes
|
||||
mimetypes.init()
|
||||
mimetypes.add_type('application/javascript', '.js')
|
||||
|
||||
import modules.generation_parameters_copypaste as parameters_copypaste
|
||||
from modules.generation_parameters_copypaste import image_from_url_text
|
||||
import modules.scripts as scripts
|
||||
from modules.processing import Processed, process_images
|
||||
|
||||
from modules.shared import opts, cmd_opts, state
|
||||
import modules.shared as shared
|
||||
|
||||
if '__file__' in locals().keys():
|
||||
root_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
|
||||
root_path = os.path.join(root_path, "../")
|
||||
else:
|
||||
if platform.system() == "Windows":
|
||||
root_path = "./"
|
||||
else:
|
||||
root_path = "./"
|
||||
|
||||
# OUTPATH_SAMPLES = root_path + "/outputs/preview_outputs/preview/"
|
||||
# OUTPATH_GRIDS = root_path + "/outputs/preview_outputs/grid/"
|
||||
OUTPATH_SAMPLES = './extensions/prompt-gallery/assets/preview/'
|
||||
OUTPATH_GRIDS = './extensions/prompt-gallery/assets/grid/'
|
||||
|
||||
BATCH_SIZE = 4
|
||||
N_ITER = 2
|
||||
STEPS = 30
|
||||
CFG_SCALE = 11.5
|
||||
WIDTH = 512
|
||||
HEIGHT = 768
|
||||
SAMPLER_INDEX = 1
|
||||
RESTORE_FACE = 'true'
|
||||
TILING = 'false'
|
||||
DO_NOT_SAVE_GRID = 'false'
|
||||
SD_MODEL = '925997e9'
|
||||
|
||||
EXCLUDED_TAGS = ['']
|
||||
global SKIP_EXISTS
|
||||
SKIP_EXISTS = True
|
||||
|
||||
OUTPUTS_DICT = list()
|
||||
OUTPUTS = {}
|
||||
rawDict = {}
|
||||
qc_dict = {}
|
||||
trg_img = ''
|
||||
current_folder = ''
|
||||
|
||||
map_sampler_to_idx = {
|
||||
'Euler a': 0,
|
||||
'Euler': 1,
|
||||
'LMS': 2,
|
||||
'Heun': 3,
|
||||
'DPM2': 4,
|
||||
'DPM2 a': 5,
|
||||
'DPM fast': 6,
|
||||
'DPM adaptive': 7,
|
||||
'LMS Karras': 8,
|
||||
'DPM2 Karras': 9,
|
||||
'DPM2 a Karras': 10,
|
||||
'DDIM': 11,
|
||||
'PLMS': 12}
|
||||
|
||||
map_keys = {
|
||||
"value": "prompt",
|
||||
"negative": "negative_prompt"}
|
||||
|
||||
map_param = {
|
||||
"sd_model": "sd_model",
|
||||
"outpath_samples": "outpath_samples",
|
||||
"outpath_grids": "outpath_grids",
|
||||
"prompt_for_display": "prompt_for_display",
|
||||
"styles": "styles",
|
||||
"Seed": "seed",
|
||||
"Variation seed strength": "subseed_strength",
|
||||
"Variation seed": "subseed",
|
||||
"seed_resize_from_h": "seed_resize_from_h",
|
||||
"seed_resize_from_w": "seed_resize_from_w",
|
||||
"Sampler": "sampler_index",
|
||||
"batch_size": "batch_size",
|
||||
"n_iter": "n_iter",
|
||||
"Steps": "steps",
|
||||
"CFG scale": "cfg_scale",
|
||||
"width": "width",
|
||||
"height": "height",
|
||||
"restore_faces": "restore_faces",
|
||||
"tiling": "tiling",
|
||||
"do_not_save_samples": "do_not_save_samples",
|
||||
"do_not_save_grid": "do_not_save_grid"}
|
||||
|
||||
def process_string_tag(tag):
|
||||
return tag
|
||||
|
||||
|
||||
def process_int_tag(tag):
|
||||
return int(tag)
|
||||
|
||||
|
||||
def process_float_tag(tag):
|
||||
return float(tag)
|
||||
|
||||
|
||||
def process_boolean_tag(tag):
|
||||
return True if (tag == "true") else False
|
||||
|
||||
|
||||
prompt_tags = {
|
||||
"sd_model": None,
|
||||
"outpath_samples": process_string_tag,
|
||||
"outpath_grids": process_string_tag,
|
||||
"prompt_for_display": process_string_tag,
|
||||
"prompt": process_string_tag,
|
||||
"negative_prompt": process_string_tag,
|
||||
"styles": process_string_tag,
|
||||
"seed": process_int_tag,
|
||||
"subseed_strength": process_float_tag,
|
||||
"subseed": process_int_tag,
|
||||
"seed_resize_from_h": process_int_tag,
|
||||
"seed_resize_from_w": process_int_tag,
|
||||
"sampler_index": process_int_tag,
|
||||
"batch_size": process_int_tag,
|
||||
"n_iter": process_int_tag,
|
||||
"steps": process_int_tag,
|
||||
"cfg_scale": process_float_tag,
|
||||
"width": process_int_tag,
|
||||
"height": process_int_tag,
|
||||
"restore_faces": process_boolean_tag,
|
||||
"tiling": process_boolean_tag,
|
||||
"do_not_save_samples": process_boolean_tag,
|
||||
"do_not_save_grid": process_boolean_tag
|
||||
}
|
||||
|
||||
avatar_prompts = list()
|
||||
avatar_names = list()
|
||||
avatar_negatives = list()
|
||||
avatar_name = ""
|
||||
|
||||
def cmdargs(line):
|
||||
args = shlex.split(line)
|
||||
pos = 0
|
||||
res = {}
|
||||
|
||||
while pos < len(args):
|
||||
arg = args[pos]
|
||||
|
||||
assert arg.startswith("--"), f'must start with "--": {arg}'
|
||||
tag = arg[2:]
|
||||
|
||||
func = prompt_tags.get(tag, None)
|
||||
assert func, f'unknown commandline option: {arg}'
|
||||
|
||||
assert pos+1 < len(args), f'missing argument for command line option {arg}'
|
||||
|
||||
val = args[pos+1]
|
||||
|
||||
res[tag] = func(val)
|
||||
|
||||
pos += 2
|
||||
|
||||
return res
|
||||
|
||||
|
||||
|
||||
def add_param(key, value, cur_str):
|
||||
cur_str += '--{key} {value} '.format(key=key, value=value)
|
||||
return cur_str
|
||||
|
||||
def parse_size(i_width, i_height, str_size, cur_str):
|
||||
i_width = str_size.split('x')[0]
|
||||
i_height = str_size.split('x')[1]
|
||||
|
||||
def parse_virariant_size(str_size, cur_str):
|
||||
width = str_size.split('x')[0]
|
||||
height = str_size.split('x')[1]
|
||||
cur_str = add_param('seed_resize_from_w', width, cur_str)
|
||||
cur_str = add_param('seed_resize_from_h', height, cur_str)
|
||||
return cur_str
|
||||
|
||||
def parse_param(param_str):
|
||||
m_batch_size = BATCH_SIZE
|
||||
m_n_iter = N_ITER
|
||||
m_steps = STEPS
|
||||
m_cfg_scale = CFG_SCALE
|
||||
m_width = WIDTH
|
||||
m_height = HEIGHT
|
||||
m_sampler_index = SAMPLER_INDEX
|
||||
# m_tiling = TILING
|
||||
m_restore_faces = RESTORE_FACE
|
||||
m_do_not_save_grid = DO_NOT_SAVE_GRID
|
||||
# m_sd_model = sd_model
|
||||
cur_line = ""
|
||||
for item in param_str.split(', '):
|
||||
if item == '':
|
||||
continue
|
||||
group = item.split(': ')
|
||||
key = group[0]
|
||||
value = group[1]
|
||||
if key == 'Steps':
|
||||
m_steps = value
|
||||
elif key == "CFG scale":
|
||||
m_cfg_scale = value
|
||||
elif value == 'Sampler':
|
||||
m_sampler_index = map_sampler_to_idx[value]
|
||||
elif key == 'Size':
|
||||
parse_size(m_width, m_height, value, cur_line)
|
||||
elif key == 'Seed resize from':
|
||||
cur_line = parse_virariant_size(value, cur_line)
|
||||
elif key == 'Seed':
|
||||
cur_line = add_param("seed", value, cur_line)
|
||||
elif key == 'Variation seed strength':
|
||||
cur_line = add_param("subseed_strength", value, cur_line)
|
||||
elif key == 'Variation seed':
|
||||
cur_line = add_param("subseed", value, cur_line)
|
||||
# elif key == 'Model hash':
|
||||
# cur_line = add_param("sd_model", m_sd_model, cur_line)
|
||||
cur_line = add_param("batch_size", m_batch_size, cur_line)
|
||||
cur_line = add_param("n_iter", m_n_iter, cur_line)
|
||||
cur_line = add_param("steps", m_steps, cur_line)
|
||||
cur_line = add_param("cfg_scale", m_cfg_scale, cur_line)
|
||||
cur_line = add_param("sampler_index", m_sampler_index, cur_line)
|
||||
cur_line = add_param("width", m_width, cur_line)
|
||||
cur_line = add_param("height", m_height, cur_line)
|
||||
cur_line = add_param("restore_faces", m_restore_faces, cur_line)
|
||||
# cur_line = add_param("tiling", m_tiling, cur_line)
|
||||
cur_line = add_param("do_not_save_grid", m_do_not_save_grid, cur_line)
|
||||
return cur_line
|
||||
|
||||
def parse_yaml_dict(rawDict, tag, avatar_prompt, avatar_name, default_negative):
|
||||
# depth-first-search
|
||||
if 'value' in rawDict.keys() or 'negative' in rawDict.keys():
|
||||
if SKIP_EXISTS:
|
||||
if os.path.exists(OUTPATH_SAMPLES + tag + '/' + avatar_name+'.png') or os.path.exists(OUTPATH_SAMPLES + tag + '\\' + 'Not-available.png'):
|
||||
print("Skip "+str(tag))
|
||||
return ""
|
||||
cur = ""
|
||||
parsed_param = False
|
||||
m_positive = avatar_prompt
|
||||
m_negative = default_negative
|
||||
for item in rawDict.items():
|
||||
key = item[0]
|
||||
value = item[1]
|
||||
if key == 'param':
|
||||
params = parse_param(rawDict['param'])
|
||||
parsed_param = True
|
||||
elif key == 'value':
|
||||
m_positive = value + m_positive
|
||||
elif key == 'negative':
|
||||
m_negative = value +','+ m_negative
|
||||
|
||||
cur += "--{key} \"{value}\" ".format(key='prompt', value= m_positive)
|
||||
cur += "--{key} \"{value}\" ".format(key='negative_prompt', value= m_negative)
|
||||
|
||||
if parsed_param == False:
|
||||
params = parse_param("")
|
||||
cur += params
|
||||
cur = add_param('outpath_samples', '\"'+OUTPATH_SAMPLES + str(tag)+'\"', cur)
|
||||
cur = add_param('outpath_grids', '\"'+OUTPATH_GRIDS + str(tag)+'\"', cur)
|
||||
return cur
|
||||
else:
|
||||
for item in rawDict.items():
|
||||
key = item[0]
|
||||
ret = parse_yaml_dict(rawDict[key], tag if key=='' else key, avatar_prompt, avatar_name, default_negative)
|
||||
if len(ret) != 0:
|
||||
if tag not in EXCLUDED_TAGS:
|
||||
OUTPUTS_DICT.append({'name': key,
|
||||
'prompt': item[1]['value'] if 'value' in item[1].keys() else '',
|
||||
'negative_prompt': item[1]['negative'] if 'negative' in item[1].keys() else ''})
|
||||
if tag in OUTPUTS.keys():
|
||||
OUTPUTS[tag].append(ret)
|
||||
else:
|
||||
OUTPUTS[tag] = [ret]
|
||||
return ""
|
||||
|
||||
|
||||
def rename_preview(avatar_name):
|
||||
if avatar_name == '':
|
||||
print("Please select avatar name first.")
|
||||
return
|
||||
root = OUTPATH_SAMPLES
|
||||
for folder in os.listdir(root):
|
||||
files = os.listdir(root + folder)
|
||||
if 'Not-available.png' in files:
|
||||
print('Skip '+ folder + ' not available.')
|
||||
continue
|
||||
if avatar_name + '.png' in files:
|
||||
continue
|
||||
for each_avatar in avatar_names:
|
||||
if each_avatar + '.png' in files:
|
||||
files.remove(each_avatar + '.png')
|
||||
if len(files) == 1:
|
||||
os.rename(root + folder + '/' + files[0], root + folder + '/' + avatar_name + '.png')
|
||||
else:
|
||||
print('There are 0 or more than 1 files in ' + folder)
|
||||
|
||||
def load_prompt_file(file):
|
||||
if (file is None):
|
||||
lines = []
|
||||
else:
|
||||
lines = [x.strip() for x in file.decode('utf8', errors='ignore').split("\n")]
|
||||
|
||||
return None, "\n".join(lines), gr.update(lines=7)
|
||||
|
||||
def copy_from_prompt_app():
|
||||
return []
|
||||
|
||||
def open_folder(f):
|
||||
if not os.path.exists(f):
|
||||
print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
|
||||
return
|
||||
elif not os.path.isdir(f):
|
||||
print(f"""
|
||||
WARNING
|
||||
An open_folder request was made with an argument that is not a folder.
|
||||
This could be an error or a malicious attempt to run code on your computer.
|
||||
Requested path was: {f}
|
||||
""", file=sys.stderr)
|
||||
return
|
||||
|
||||
if not shared.cmd_opts.hide_ui_dir_config:
|
||||
path = os.path.normpath(f)
|
||||
if platform.system() == "Windows":
|
||||
os.startfile(path)
|
||||
elif platform.system() == "Darwin":
|
||||
sp.Popen(["open", path])
|
||||
else:
|
||||
sp.Popen(["xdg-open", path])
|
||||
|
||||
class PromptStyle(typing.NamedTuple):
|
||||
name: str
|
||||
prompt: str
|
||||
negative_prompt: str
|
||||
|
||||
def save_styles() -> None:
|
||||
if len(OUTPUTS.keys()) == 0:
|
||||
return
|
||||
path = root_path + '/styles.csv'
|
||||
# Write to temporary file first, so we don't nuke the file if something goes wrong
|
||||
fd, temp_path = tempfile.mkstemp(".csv")
|
||||
with os.fdopen(fd, "w", encoding="utf-8-sig", newline='') as file:
|
||||
# _fields is actually part of the public API: typing.NamedTuple is a replacement for collections.NamedTuple,
|
||||
# and collections.NamedTuple has explicit documentation for accessing _fields. Same goes for _asdict()
|
||||
writer = csv.DictWriter(file, fieldnames=PromptStyle._fields)
|
||||
writer.writeheader()
|
||||
for row in OUTPUTS_DICT:
|
||||
writer.writerow({'name': row['name'], 'prompt': row['prompt'], 'negative_prompt': row['negative_prompt']})
|
||||
# writer.writerows(style._asdict() for k, style in self.styles.items())
|
||||
|
||||
# Always keep a backup file around
|
||||
if os.path.exists(path):
|
||||
shutil.move(path, path + ".bak")
|
||||
shutil.move(temp_path, path)
|
||||
|
||||
def load_prompt(file, default_negative, dropdown, skip_exist):
|
||||
global SKIP_EXISTS
|
||||
SKIP_EXISTS = skip_exist
|
||||
if dropdown == '':
|
||||
return
|
||||
rawDict = yaml.load(file, Loader = yaml.BaseLoader)
|
||||
default_negative = default_negative + ',' + avatar_negatives[avatar_names.index(dropdown)]
|
||||
parse_yaml_dict(rawDict, "", avatar_prompts[avatar_names.index(dropdown)], dropdown, default_negative)
|
||||
prompt_txt = ""
|
||||
keys = list(filter(lambda x: x not in EXCLUDED_TAGS, OUTPUTS.keys()))
|
||||
for style in keys:
|
||||
for each_line in OUTPUTS[style]:
|
||||
prompt_txt += each_line + '\n'
|
||||
return [prompt_txt, gr.Row.update(visible=True)]
|
||||
|
||||
def load_avartar(avatar_dict, customize_tags_positive):
|
||||
avatars = yaml.load(avatar_dict, yaml.BaseLoader)
|
||||
|
||||
for name, prompt in avatars.items():
|
||||
avatar_names.append(name)
|
||||
if 'value' in prompt.keys():
|
||||
avatar_prompts.append(customize_tags_positive + ', ' + prompt['value'])
|
||||
if 'negative' in prompt.keys():
|
||||
avatar_negatives.append(prompt['negative'])
|
||||
return [gr.Dropdown.update(choices=avatar_names, value=avatar_names[0]), gr.Column.update(visible=True), gr.Group.update(visible=True)]
|
||||
|
||||
def scan_outputs(avatar_name):
|
||||
if avatar_name is None or len(avatar_name) == 0:
|
||||
print("Please select avatar name first.")
|
||||
return
|
||||
root = OUTPATH_SAMPLES
|
||||
global qc_dict
|
||||
qc_dict = {}
|
||||
for folder in os.listdir(root):
|
||||
if os.path.isdir(root + folder) == False:
|
||||
continue
|
||||
|
||||
files = os.listdir(root + folder)
|
||||
if 'Not-available.png' in files:
|
||||
print('Skip '+ folder + ' not available.')
|
||||
continue
|
||||
if avatar_name + '.png' in files:
|
||||
continue
|
||||
for each_avatar in avatar_names:
|
||||
if each_avatar + '.png' in files:
|
||||
files.remove(each_avatar + '.png')
|
||||
if len(files) == 0:
|
||||
continue
|
||||
qc_dict[folder] = [root + folder + '/' + file for file in files]
|
||||
|
||||
if len(qc_dict.keys()) == 0:
|
||||
return gr.Dropdown.update(choices=[])
|
||||
return gr.Dropdown.update(choices=list(qc_dict.keys()), value=list(qc_dict.keys())[0])
|
||||
|
||||
def update_gallery(dropdown, avatar):
|
||||
root = OUTPATH_SAMPLES
|
||||
global trg_img, current_folder
|
||||
current_folder = root + dropdown
|
||||
trg_img = root + dropdown + '/' + avatar + '.png'
|
||||
return qc_dict[dropdown]
|
||||
|
||||
def clean_select_picture(filename):
|
||||
if current_folder == '':
|
||||
print("Please select qc tag.")
|
||||
return
|
||||
for file in os.listdir(current_folder):
|
||||
is_avatar = False
|
||||
for each_avatar in avatar_names:
|
||||
if each_avatar + '.png' == file:
|
||||
is_avatar = True
|
||||
break
|
||||
if os.path.splitext(file)[0] in filename:
|
||||
os.rename(current_folder+'/'+file, trg_img)
|
||||
elif is_avatar == False:
|
||||
os.remove(current_folder+'/'+file)
|
||||
|
||||
def image_url(filedata):
|
||||
if type(filedata) == dict and filedata["is_file"]:
|
||||
filename = filedata["name"]
|
||||
tempdir = os.path.normpath(tempfile.gettempdir())
|
||||
normfn = os.path.normpath(filename)
|
||||
assert normfn.startswith(tempdir), 'trying to open image file not in temporary directory'
|
||||
|
||||
image = Image.open(filename)
|
||||
clean_select_picture(os.path.basename(filename))
|
||||
return Image.open(filename)
|
||||
|
||||
if type(filedata) == list:
|
||||
if len(filedata) == 0:
|
||||
return None
|
||||
|
||||
filedata = filedata[0]
|
||||
|
||||
if filedata.startswith("data:image/png;base64,"):
|
||||
filedata = filedata[len("data:image/png;base64,"):]
|
||||
|
||||
filedata = base64.decodebytes(filedata.encode('utf-8'))
|
||||
image = Image.open(io.BytesIO(filedata))
|
||||
return image
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
class Script(scripts.Script):
|
||||
def title(self):
|
||||
return "Prompt gallery"
|
||||
|
||||
def ui(self, is_img2img):
|
||||
with gr.Group():
|
||||
with gr.Column():
|
||||
label_avatar = gr.Label("Upload avatars config")
|
||||
avatar_dict = gr.File(label="Upload avatar prompt inputs", type='bytes')
|
||||
|
||||
# copy_from_app_button = gr.Button("Copy From Prompt Preview")
|
||||
|
||||
with gr.Group():
|
||||
with gr.Column(visible=False) as avatar_col:
|
||||
label_presets = gr.Label("Presets")
|
||||
dropdown = gr.Dropdown(label="Choose avatar", choices=[""], value="", type="value", elem_id="dropdown")
|
||||
dropdown.save_to_config = True
|
||||
with gr.Row():
|
||||
checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False)
|
||||
skip_exist = gr.Checkbox(value=True, label="skip exist")
|
||||
default_negative = gr.Textbox(label="default_negative", lines=1)
|
||||
default_positive = gr.Textbox(label="default_positive", lines=1)
|
||||
prompt_dict = gr.File(label="Upload prompt dictionary", type='bytes')
|
||||
with gr.Row(visible = False) as save_prompts:
|
||||
open_button = gr.Button("Open outputs directory")
|
||||
export_button = gr.Button("Export to WebUI style")
|
||||
prompt_display = gr.Textbox(label="List of prompt inputs", lines=1)
|
||||
|
||||
|
||||
prompt_dict.change(fn=load_prompt, inputs=[prompt_dict, default_negative, dropdown, skip_exist], outputs=[prompt_display, save_prompts])
|
||||
open_button.click(fn=lambda: open_folder(OUTPATH_SAMPLES), inputs=[], outputs=[])
|
||||
export_button.click(fn=save_styles, inputs=[], outputs=[])
|
||||
|
||||
with gr.Group(visible=False) as qc_widgets:
|
||||
label_preview = gr.Label("QC preview")
|
||||
with gr.Row():
|
||||
qc_refresh = gr.Button("QC scan")
|
||||
preview_dropdown = gr.Dropdown(label="Select prompts", choices=[""], value="", type="value", elem_id="dropdown")
|
||||
preview_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"preview_gallery").style(grid=4)
|
||||
qc_refresh.click(fn=scan_outputs, inputs=[dropdown], outputs=preview_dropdown)
|
||||
with gr.Row():
|
||||
qc_show = gr.Button(f"Show pics")
|
||||
qc_select = gr.Button(f"Select")
|
||||
rename_button = gr.Button("Auto rename")
|
||||
selected_img = gr.Image(label="Selected",show_label=False, source="upload", interactive=True, type="pil").style(height=480)
|
||||
qc_show.click(fn=update_gallery, inputs=[preview_dropdown, dropdown], outputs=preview_gallery)
|
||||
qc_select.click(
|
||||
fn=lambda x: image_url(x),
|
||||
_js="extract_image_from_gallery",
|
||||
inputs=[preview_gallery],
|
||||
outputs=[selected_img],
|
||||
)
|
||||
# qc_select.click(fn=select_picture, inputs=[dropdown, preview_dropdown, preview_gallery], outputs=[])
|
||||
rename_button.click(fn=rename_preview, inputs=[dropdown], outputs=[])
|
||||
# qc_select.click(fn=scan_outputs, inputs=[], outputs=[preview_dropdown])
|
||||
|
||||
avatar_dict.change(fn=load_avartar, inputs=[avatar_dict, default_positive], outputs=[dropdown, avatar_col, qc_widgets])
|
||||
return [checkbox_iterate, avatar_dict, prompt_dict, default_negative, default_positive, dropdown, prompt_display, rename_button, label_avatar, open_button, export_button, skip_exist, label_presets, label_preview, preview_dropdown, preview_gallery, qc_select, qc_refresh, qc_show, selected_img]
|
||||
|
||||
def run(self, p, checkbox_iterate, avatar_dict, prompt_dict, default_negative, default_positive, dropdown, prompt_display, rename_button, label_avatar, open_button, export_button, skip_exist, label_presets, label_preview, preview_dropdown, preview_gallery, qc_select, qc_refresh, qc_show, selected_img):
|
||||
lines = [x.strip() for x in prompt_display.splitlines()]
|
||||
lines = [x for x in lines if len(x) > 0]
|
||||
|
||||
p.do_not_save_grid = True
|
||||
|
||||
job_count = 0
|
||||
jobs = []
|
||||
|
||||
for line in lines:
|
||||
if "--" in line:
|
||||
try:
|
||||
args = cmdargs(line)
|
||||
except Exception:
|
||||
print(f"Error parsing line [line] as commandline:", file=sys.stderr)
|
||||
print(traceback.format_exc(), file=sys.stderr)
|
||||
args = {"prompt": line}
|
||||
else:
|
||||
args = {"prompt": line}
|
||||
|
||||
n_iter = args.get("n_iter", 1)
|
||||
if n_iter != 1:
|
||||
job_count += n_iter
|
||||
else:
|
||||
job_count += 1
|
||||
|
||||
jobs.append(args)
|
||||
|
||||
print(f"Will process {len(lines)} lines in {job_count} jobs.")
|
||||
if (checkbox_iterate and p.seed == -1):
|
||||
p.seed = int(random.randrange(4294967294))
|
||||
|
||||
state.job_count = job_count
|
||||
|
||||
images = []
|
||||
for n, args in enumerate(jobs):
|
||||
state.job = f"{state.job_no + 1} out of {state.job_count}"
|
||||
|
||||
copy_p = copy.copy(p)
|
||||
for k, v in args.items():
|
||||
setattr(copy_p, k, v)
|
||||
|
||||
proc = process_images(copy_p)
|
||||
images += proc.images
|
||||
|
||||
if (checkbox_iterate):
|
||||
p.seed = p.seed + (p.batch_size * p.n_iter)
|
||||
|
||||
OUTPUTS = {}
|
||||
rawDict = {}
|
||||
|
||||
return Processed(p, images, p.seed, "")
|
||||
Loading…
Reference in New Issue