Highest level background removal RMBG-1.4

Prominent objects in the image are clearly defined

The details and foreground are handled well, as shown below.

briaai/RMBG-1.4 · Hugging Face

ISNet trained on a proprietary dataset

GitHub - xuebinqin/DIS: This is the repo for our new project Highly Accurate Dichotomous Image…

There’s also a demo.

BRIA RMBG 1.4 - a Hugging Face Space by briaai

How to use

install

git clone https://huggingface.co/briaai/RMBG-1.4
cd RMBG-1.4/
pip install -r requirements.txt

Run

from skimage import io
import torch, os
from PIL import Image
from briarmbg import BriaRMBG
from utilities import preprocess_image, postprocess_image

im_path = "example_image.jpg"
net = BriaRMBG()
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
net = BriaRMBG.from_pretrained("briaai/RMBG-1.4")
net.to(device)

# prepare input
model_input_size = [1024,1024]
orig_im = io.imread(im_path)
orig_im_size = orig_im.shape[0:2]
image = preprocess_image(orig_im, model_input_size).to(device)

# inference 
result=net(image)

# post process
result_image = postprocess_image(result[0][0], orig_im_size)

# save result
pil_im = Image.fromarray(result_image)
no_bg_image = Image.new("RGBA", pil_im.size, (0,0,0,0))
orig_image = Image.open(im_path)
no_bg_image.paste(orig_image, mask=pil_im)
no_bg_image.save("example_image_no_bg.png")

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