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