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mrus_data_prep.py
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mrus_data_prep.py
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import h5py
import numpy as np
import cv2
import os
def get_data(filename, dataset_ID):
data_path_main = "./datasets/us2mr/"
data_path_train = data_path_main + "train" + dataset_ID + "/"
data_path_test = data_path_main + "test" + dataset_ID + "/"
if not os.path.exists(data_path_main):
os.mkdir(data_path_main)
if not os.path.exists(data_path_train):
os.mkdir(data_path_train)
if not os.path.exists(data_path_test):
os.mkdir(data_path_test)
h5_file = h5py.File(filename, mode="r")
keys = list(h5_file.keys())
# TRAIN SPLIT
for series_num in range(int(len(keys) / 2)):
series = np.array(h5_file[keys[series_num]])
for frame_num in range(len(series)):
im = series[frame_num]
im = 255 * ((im - np.min(im)) / np.ptp(im))
im = np.rot90(im, 1)
cv2.imwrite(
data_path_train
+ str(series_num).zfill(4)
+ "-"
+ str(frame_num).zfill(4)
+ ".jpg",
im
)
# TEST SPLIT
for series_num in range(int(len(keys) / 2), int(len(keys))):
series = np.array(h5_file[keys[series_num]])
for frame_num in range(len(series)):
im = series[frame_num]
im = 255 * ((im - np.min(im)) / np.ptp(im))
im = np.rot90(im, 1)
cv2.imwrite(
data_path_test
+ str(series_num).zfill(4)
+ "-"
+ str(frame_num).zfill(4)
+ ".jpg",
im
)
get_data("../mrus/us_images_resampled800.h5", "A")
get_data("../mrus/mr_images_resampled800.h5", "B")