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| import os | |
| from scipy.io import loadmat | |
| import numpy as np | |
| from PIL import Image | |
| from tqdm import tqdm | |
| data_directory = "/vol/data/histo_datasets/CoNIC/" | |
| images = np.load(data_directory+"images.npy") | |
| masks = np.load(data_directory+"labels.npy") | |
| for i in tqdm(range(len(images))): | |
| j = 0 | |
| while np.max(masks[i,:,:,0]) > 255: | |
| mask = np.where(masks[i,:,:,0] < 256, masks[i,:,:,0], 0).astype(np.uint8) | |
| masks[i,:,:,0] = np.where(masks[i,:,:,0] > 255, masks[i,:,:,0] - 256, 0) | |
| Image.fromarray(mask).save(data_directory + "labels_png/" + str(i).zfill(4) + "_" + str(j) + ".png") | |
| j += 1 | |
| Image.fromarray(images[i]).save(data_directory + "images_png/" + str(i).zfill(4) + ".png") | |
| Image.fromarray(masks[i,:,:,0]).save(data_directory + "labels_png/" + str(i).zfill(4) + ".png") |