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from typing import Tuple
import numpy as np
import PIL
import streamlit as st
import torch
import torch.nn.functional as F
from briarmbg import BriaRMBG
from PIL import Image
from torchvision.transforms.functional import normalize
def resize_image(image):
image = image.convert("RGB")
model_input_size = (1024, 1024)
image = image.resize(model_input_size, Image.BILINEAR)
return image
def process(image):
# prepare input
orig_image = Image.open(image)
w, h = orig_image.size
image = resize_image(orig_image)
im_np = np.array(image)
im_tensor = torch.tensor(im_np, dtype=torch.float32).permute(2, 0, 1)
im_tensor = torch.unsqueeze(im_tensor, 0)
im_tensor = torch.divide(im_tensor, 255.0)
im_tensor = normalize(im_tensor, [0.5, 0.5, 0.5], [1.0, 1.0, 1.0])
if torch.cuda.is_available():
im_tensor = im_tensor.cuda()
net = BriaRMBG.from_pretrained("briaai/RMBG-1.4")
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
net.to(device)
result = net(im_tensor)
# post process
result = torch.squeeze(F.interpolate(result[0][0], size=(h, w), mode="bilinear"), 0)
ma = torch.max(result)
mi = torch.min(result)
result = (result - mi) / (ma - mi)
# image to pil
im_array = (result * 255).cpu().data.numpy().astype(np.uint8)
pil_im = Image.fromarray(np.squeeze(im_array))
# paste the mask on the original image
new_im = Image.new("RGBA", pil_im.size, (0, 0, 0, 0))
new_im.paste(orig_image, mask=pil_im)
# new_orig_image = orig_image.convert('RGBA')
return new_im
def main():
st.set_page_config(page_title="bg-remove", page_icon="⛺️", layout="wide")
st.markdown(
"""<h1 align="center";>Background Remover</h1>""",
unsafe_allow_html=True,
)
# sidebar
with st.sidebar:
img_file = st.file_uploader(
label="Upload image",
type=["jpg", "png", "jpeg"],
key="image_file_uploader",
)
cols = st.columns(2)
with cols[0]:
with st.container(border=True, height=600):
if img_file:
st.image(img_file)
else:
st.info("Drag and drop the sample image into upload sidebar", icon="💡")
sub_btn = st.button("Remove bg", key="sub_btn")
with cols[1]:
with st.container(border=True, height=600):
if sub_btn and img_file:
processed_img = process(img_file)
st.image(processed_img)
else:
st.write("Waiting for image...")
with st.container(border=True, height=400):
st.write("Sample image")
st.image("input.jpg")
if __name__ == "__main__":
main()
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