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()