Background Removal with Deep Learning

This repository show the code to remove the background of the pictures using the U2Net pre-trained model.

The application has three simple functions:

1. Remove the background, producing a transparent PNG file.

2. Change the background by another picture.

3. Combine the image and multiple backgrounds to augment the dataset.

Demos

---

Endpoint available

Endpoint	Description
http://localhost:8000/	Front-end to perform background remove.
http://localhost:8000/augmentation	Front-end to perform augment images.

Install

1. Clone this repository

git clone https://github.com/renatoviolin/bg-remove-augment.git
cd bg-remove-augment

2. Install dependencies

pip install -r requirements.txt

3. Download the pre-trained model

gdown --id 1ao1ovG1Qtx4b7EoskHXmi2E9rp5CHLcZ -O ./ckpt/u2net.pth

4. Start web-application

cd webapp
uvicorn app:app --host 0.0.0.0 --port 8000

References

U2Net: https://github.com/xuebinqin/U-2-Net

BibTeX

@InProceedings{Qin_2020_PR,
    title = {U2-Net: Going Deeper with Nested U-Structure for Salient Object Detection},
    author = {Qin, Xuebin and Zhang, Zichen and Huang, Chenyang and Dehghan, Masood and Zaiane, Osmar and Jagersand, Martin},
    journal = {Pattern Recognition},
    volume = {106},
    pages = {107404},
    year = {2020}

}