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907462b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | import os
import shutil
import numpy as np
import slideio
from PIL import Image
from tqdm import tqdm
data_directory = '/home/ubuntu/thesis/data/MoNuSAC/'
image_source = data_directory + 'MoNuSAC_images_and_annotations/'
mask_source = data_directory + 'MoNuSAC_masks/'
image_destination = data_directory + 'images/'
mask_destination = data_directory + 'masks/'
image_list = os.listdir(image_source)
# Training data
for i in image_list:
subimage_list = os.listdir(image_source + i)
for j in subimage_list:
if j.endswith('.tif'):
target_image_file = image_destination + j
shutil.copyfile(image_source + i + '/' + j, target_image_file)
types = ["Epithelial", "Lymphocyte", "Macrophage", "Neutrophil"]
for t in types:
if os.path.exists(mask_source + i + '/' + j[:-4] + '/' + t):
mask_list = os.listdir(mask_source + i + '/' + j[:-4] + '/' + t)
for m in mask_list:
target_mask_file = mask_destination + j[:-4] + '_' + t + '.png'
slide = slideio.open_slide(mask_source + i + '/' + j[:-4] + '/' + t + '/' + m)
scene = slide.get_scene(0)
mask = scene.read_block((0,0, scene.size[0], scene.size[1]))
Image.fromarray(mask.astype(np.uint8)).save(target_mask_file)
# Testing data
source = data_directory + 'MoNuSAC_Testing_Color_Coded_Masks/'
image_list = os.listdir(source)
for i in tqdm(image_list):
subimage_list = os.listdir(source + i)
for j in subimage_list:
if j.endswith('.png'):
target_image_file = image_destination + j
shutil.copyfile(source + i + '/' + j, target_image_file)
else:
target_mask_file = mask_destination + j[:-17] + '.png'
mask_array = np.array(Image.open(source + i + '/' + j))
binary_arr = np.zeros((mask_array.shape[0], mask_array.shape[1]))
for x in range(mask_array.shape[0]):
for y in range(mask_array.shape[1]):
if mask_array[x, y, 0] == 255 or mask_array[x, y, 1] == 255 or mask_array[x, y, 2] == 255:
binary_arr[x][y] = 1
Image.fromarray(binary_arr.astype(np.uint8)).save(target_mask_file)
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