IOPaint/README.md

<h1 align="center">Image Sorter InPaint</h1>
<p align="center">A free and open-source inpainting & outpainting tool powered by SOTA AI model.</p>


## Quick Start

### Prerequisites

First you have to install Python3 and pip.
In Linux run this command: `apt update && apt upgrade -y && apt install python3 python3-pip -y`   
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/)

### Start webui

Image Sorter InPaint provides a convenient webui for using the latest AI models to edit your images.
You can install and start Image Sorter InPaint easily by running following command:

```bash
pip install opencv-python-headless
pip install "https://git.kmpr.at/kamp/IOPaint/releases/download/1.3.3/Image_Sorter_InPaint-1.3.3-py3-none-any.whl"
imagesorter-inpaint start --model=lama --device=cpu --host 0.0.0.0 --port=8080
```

That's it, you can start using Imagesorter InPaint by visiting http://localhost:8080 in your web browser.

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)

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).

## Development

Install [nodejs](https://nodejs.org/en), then install the frontend dependencies.

```bash
git clone https://git.kmpr.at/kamp/IOPaint.git
cd IOPaint/web_app
npm install
npm run build
cp -r dist/ ../inpaint/web_app
```

Create a `.env.local` file in `web_app` and fill in the backend IP and port.
```
VITE_BACKEND=http://127.0.0.1:8080
```

Start front-end development environment
```bash
npm run dev -- --host
```

Install back-end requirements and start backend service
```bash
pip install -r requirements.txt
pip install opencv-python-headless
python3 main.py start --model lama --port 8080
```

Then you can visit `http://localhost:5173/` for development.
The frontend code will automatically update after being modified,
but the backend needs to restart the service after modifying the python code.