import sys
from protoclass.tool.dicom_manip import OpenVolumeNumpy
from protoclass.preprocessing.flattening import Flatten3D
# Get the path to file
filename_data = sys.argv[1]
print 'Opening the following file: {}'.format(filename_data)
# Open the data
if not (filename_data.endswith('.npz')):
raise ValueError('flattening: The image in input is not a npz image.')
else:
# Read the volume using the raw image
name_var_extract = 'vol_denoised'
vol = OpenVolumeNumpy(filename_data, name_var_extract=name_var_extract)
# Apply the filtering using 8 cores
num_cores = 8
vol_flatten = Flatten3D(vol, num_cores=num_cores)
# Directory where to save the data
storing_folder = sys.argv[2]
# Create the folder if it is not existing
if not (os.path.exists(storing_folder)):
os.makedirs(storing_folder)
# Get only the filename without path directory of the input file
_, filename_patient = os.path.split(filename_data)
from protoclass.tool.dicom_manip import OpenVolumeNumpy
from protoclass.extraction.texture_analysis import LBPMapExtraction
# Get the path to file
filename_data = sys.argv[1]
print 'Opening the following file: {}'.format(filename_data)
# Open the data
if not filename_data.endswith('.npy'):
raise ValueError(
'denoising-non-local: The image in input is not a npz image.')
else:
# Read the volume using the raw image
# name_var_extract = 'vol_denoised'
# vol = OpenVolumeNumpy(filename_data, name_var_extract=name_var_extract)
vol = OpenVolumeNumpy(filename_data)
# Apply the filtering using 8 cores
num_cores = 8
radius = 4
n_points = 8 * radius
extr_3d = '2.5D'
extr_axis = 'y'
vol_lbp = LBPMapExtraction(vol,
radius=radius,
n_points=n_points,
extr_3d=extr_3d,
extr_axis=extr_axis,
num_cores=num_cores)
# Directory where to save the data