---
title: BrushNet
emoji: ⚡
colorFrom: yellow
colorTo: indigo
sdk: gradio
sdk_version: 3.50.2
python_version: 3.9
app_file: app.py
pinned: false
license: apache-2.0
---

# BrushNetApi

This repo implements an API that allows other applications to call it with http request.

## Instructions to Run the Application

Create a virtual environment and install dependencies.
```
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```

## Run Honcho to Start all the Services

```
honcho start
```

## Or Run the Redis, Celery and Web Server in seperate tabs

Start Redis Server
```
redis-server
```

Start the Celery Worker
```
# In a new terminal window:
./start_celery_worker.sh
```

Run the FastAPI Application
```
# In a new terminal window:
uvicorn app_api:app --host 0.0.0.0 --port 8000
```

## How to Use the API

a. Initiate Image Generation

Send a POST request to /inpaint with the required parameters.

Request Body
```
{
  "input_image": "<base64-encoded input image>",
  "input_mask": "<base64-encoded input mask>",
  "prompt": "A beautiful cake on the table",
  "negative_prompt": "ugly, low quality",
  "control_strength": 1.0,
  "guidance_scale": 12.0,
  "num_inference_steps": 50,
  "seed": 551793204,
  "randomize_seed": false,
  "blended": false,
  "invert_mask": true,
  "count": 1,
  "webhook_url": "http://your-webhook-url.com/notify"  # Optional
}
```
Response
```
{
  "job_id": "<task_id>"
}
```

b. Check Task Status

Send a GET request to /status/{job_id}.

Response
```
{
  "status": "PENDING"  # Or "STARTED", "SUCCESS", "FAILURE"
}
```

c. Retrieve Result

Once the status is “SUCCESS”, send a GET request to /result/{job_id}.

Response:
```
{
  "images": ["<base64-encoded image>", "..."]
}
```

d. Webhook Notification

If you provided a webhook_url in your request, the server will send a POST request to that URL with the images once the task is complete.

```
{
  "images": ["<base64-encoded image>", "..."]
}
```

The webhook functionality is included in the generate_image_task function. If a webhook_url is provided in the request, the server will send a POST request to that URL with the generated images.




# BrushNet(original README below )

This repository contains the gradio demo of the paper "BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion"

Keywords: Image Inpainting, Diffusion Models, Image Generation

> [Xuan Ju](https://github.com/juxuan27)<sup>12</sup>, [Xian Liu](https://alvinliu0.github.io/)<sup>12</sup>, [Xintao Wang](https://xinntao.github.io/)<sup>1*</sup>, [Yuxuan Bian](https://scholar.google.com.hk/citations?user=HzemVzoAAAAJ&hl=zh-CN&oi=ao)<sup>2</sup>, [Ying Shan](https://www.linkedin.com/in/YingShanProfile/)<sup>1</sup>, [Qiang Xu](https://cure-lab.github.io/)<sup>2*</sup><br>
> <sup>1</sup>ARC Lab, Tencent PCG <sup>2</sup>The Chinese University of Hong Kong <sup>*</sup>Corresponding Author


<p align="center">
  <a href="https://tencentarc.github.io/BrushNet/">Project Page</a> |
  <a href="https://github.com/TencentARC/BrushNet">Code</a> |
  <a href="https://arxiv.org/abs/2403.06976">Arxiv</a> |
  <a href="https://forms.gle/9TgMZ8tm49UYsZ9s5">Data</a> |
  <a href="https://drive.google.com/file/d/1IkEBWcd2Fui2WHcckap4QFPcCI0gkHBh/view">Video</a> |
</p>


## 🤝🏼 Cite Us

```
@misc{ju2024brushnet,
  title={BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion},
  author={Xuan Ju and Xian Liu and Xintao Wang and Yuxuan Bian and Ying Shan and Qiang Xu},
  year={2024},
  eprint={2403.06976},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}
```


## 💖 Acknowledgement
<span id="acknowledgement"></span>

Our code is modified based on [diffusers](https://github.com/huggingface/diffusers), thanks to all the contributors!