62 lines
2.3 KiB
Markdown
62 lines
2.3 KiB
Markdown
<h1 align="center">Image Sorter InPaint</h1>
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<p align="center">A free and open-source inpainting & outpainting tool powered by SOTA AI model.</p>
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## Quick Start
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### Prerequisites
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First you have to install Python3 and pip.
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In Linux run this command: `apt update && apt upgrade -y && apt install python3 python3-pip -y`
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For Windows, read this Links: [Install Python on Windows](https://www.geeksforgeeks.org/how-to-install-python-on-windows/) [Install PIP on Windows](https://www.geeksforgeeks.org/how-to-install-pip-on-windows/)
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### Start webui
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Image Sorter InPaint provides a convenient webui for using the latest AI models to edit your images.
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You can install and start Image Sorter InPaint easily by running following command:
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```bash
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pip install opencv-python-headless
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pip install "https://git.kmpr.at/kamp/IOPaint/releases/download/1.3.3/Image_Sorter_InPaint-1.3.3-py3-none-any.whl"
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imagesorter-inpaint start --model=lama --device=cpu --host 0.0.0.0 --port=8080
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```
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That's it, you can start using Imagesorter InPaint by visiting http://localhost:8080 in your web browser.
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All models will be downloaded automatically at startup. If you want to change the download directory, you can add `--model-dir`. More documentation can be found [here](https://www.iopaint.com/install/download_model)
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You can see other supported models at [here](https://www.iopaint.com/models) and how to use local sd ckpt/safetensors file at [here](https://www.iopaint.com/models#load-ckptsafetensors).
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## Development
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Install [nodejs](https://nodejs.org/en), then install the frontend dependencies.
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```bash
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git clone https://git.kmpr.at/kamp/IOPaint.git
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cd IOPaint/web_app
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npm install
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npm run build
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cp -r dist/ ../inpaint/web_app
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```
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Create a `.env.local` file in `web_app` and fill in the backend IP and port.
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```
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VITE_BACKEND=http://127.0.0.1:8080
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```
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Start front-end development environment
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```bash
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npm run dev -- --host
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```
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Install back-end requirements and start backend service
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```bash
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pip install -r requirements.txt
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pip install opencv-python-headless
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python3 main.py start --model lama --port 8080
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```
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Then you can visit `http://localhost:5173/` for development.
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The frontend code will automatically update after being modified,
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but the backend needs to restart the service after modifying the python code.
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