import sys
import os
import argparse
import logging
import numpy as np
import openslide
from skimage.color import rgb2hsv
from skimage.filters import threshold_otsu
sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/../../')
parser = argparse.ArgumentParser(description='Get tissue mask of WSI and save'
' it in npy format')
parser.add_argument('wsi_path', default=None, metavar='WSI_PATH', type=str,
help='Path to the WSI file')
parser.add_argument('npy_path', default=None, metavar='NPY_PATH', type=str,
help='Path to the output npy mask file')
parser.add_argument('--level', default=6, type=int, help='at which WSI level'
' to obtain the mask, default 6')
parser.add_argument('--RGB_min', default=50, type=int, help='min value for RGB'
' channel, default 50')
def run(args):
logging.basicConfig(level=logging.INFO)
slide = openslide.OpenSlide(args.wsi_path)
# note the shape of img_RGB is the transpose of slide.level_dimensions
img_RGB = np.transpose(np.array(slide.read_region((0, 0),
args.level,
slide.level_dimensions[args.level]).convert('RGB')),
axes=[1, 0, 2])
img_HSV = rgb2hsv(img_RGB)
background_R = img_RGB[:, :, 0] > threshold_otsu(img_RGB[:, :, 0])
background_G = img_RGB[:, :, 1] > threshold_otsu(img_RGB[:, :, 1])
background_B = img_RGB[:, :, 2] > threshold_otsu(img_RGB[:, :, 2])
tissue_RGB = np.logical_not(background_R & background_G & background_B)
tissue_S = img_HSV[:, :, 1] > threshold_otsu(img_HSV[:, :, 1])
min_R = img_RGB[:, :, 0] > args.RGB_min
min_G = img_RGB[:, :, 1] > args.RGB_min
min_B = img_RGB[:, :, 2] > args.RGB_min
tissue_mask = tissue_S & tissue_RGB & min_R & min_G & min_B
np.save(args.npy_path, tissue_mask)
def main():
args = parser.parse_args()
run(args)
if __name__ == '__main__':
main()
