import cv2
import numpy as np

from PIL import Image
from transparent_background import Remover

# Load model
remover = Remover() # default setting
remover = Remover(mode='fast', jit=True, device='cuda:0', ckpt='~/latest.pth') # custom setting
remover = Remover(mode='base-nightly') # nightly release checkpoint
remover = Remover(resize='dynamic') # use dynamic resizing instead of static resizing

# Usage for image
img = Image.open('samples/aeroplane.jpg').convert('RGB') # read image

out = remover.process(img) # default setting - transparent background
out = remover.process(img, type='rgba') # same as above
out = remover.process(img, type='map') # object map only
out = remover.process(img, type='green') # image matting - green screen
out = remover.process(img, type='white') # change backround with white color
out = remover.process(img, type=[255, 0, 0]) # change background with color code [255, 0, 0]
out = remover.process(img, type='blur') # blur background
out = remover.process(img, type='overlay') # overlay object map onto the image
out = remover.process(img, type='samples/background.jpg') # use another image as a background

out = remover.process(img, threshold=0.5) # use threhold parameter for hard prediction.
out = remover.process(img, reverse=True) # reverse output. background -> foreground

out.save('output.png') # save result
out.save('output.jpg') # save as jpg