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detect_by_unet.py
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detect_by_unet.py
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from utils import bet_unet
from model import unet
from tqdm import tqdm
import nibabel as nib
import os
import time
import argparse
def detect_file(filename, model, unet):
data = nib.load(filename)
mask = nib.load(filename)
mask_roi = nib.load(filename)
width, height, frame_num = data.shape
matrix = data.get_data()
unet_matrix = bet_unet(matrix, unet, threshold=0.2)
start = time.time()
for i in tqdm(range(frame_num), desc='Detect in {}'.format(os.path.basename(filename))):
bet = unet_matrix[:, :, i]
mask.get_data()[:, :, i] = bet
mask_roi.get_data()[:, :, i] = bet
end = time.time()
print('Using time {}s'.format(end - start))
return mask, mask_roi
if __name__ == '__main__':
import config
data_root = config.data_root
model_path = config.model_path
result_path = config.result_path
parser = argparse.ArgumentParser()
parser.add_argument('-i', '--input', help='input path')
parser.add_argument('-o', '--output', help='output path')
args = parser.parse_args()
data_filename = args.input
data_path = os.path.join(data_root, data_filename)
result_filename = args.output if args.output else '{}_detect_by_unet.nii'.format(
data_filename.split('/')[-1].split('.')[-2])
result_path = os.path.join(result_path, result_filename)
unet_path = os.path.join(model_path, 'unet_pm25_yuzq.hdf5')
bet_net = unet(pretrained_weights=unet_path)
mask, mask_roi = detect_file(data_path, None, bet_net)
nib.save(mask, result_path)
nib.save(mask_roi, './mask/roi_by_unet.nii')