nph_prediction.py

###############################################################################
##  Vision Research Laboratory and                                           ##
##  Center for Multimodal Big Data Science and Healthcare                    ##
##  University of California at Santa Barbara                                ##
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import sys
import argparse
import os
from imUtils import *
from segUtils import *
from postUtils import *
from unetSeg import *


def main(base, parallel, seg_model, gpu, save_last, clear_cache):
	if clear_cache:
		from subprocess import call
		call(['rm', '-r', os.path.join(base, 'Thresholds')])
		call(['rm', '-r', os.path.join(base, 'UNet_Outputs')])
		call(['rm', '-r', os.path.join(base, 'MNI152')])
		call(['rm', '-r', os.path.join(base, 'Predictions')])
		call(['rm', '-r', os.path.join(base, 'Final_Predictions')])
		call(['rm', '-r', os.path.join(base, 'imname_list.pkl')])
		call(['rm', '-r', os.path.join(base, 'imname_list1.pkl')])

	else:
		if seg_model == 'unet':
			threshold(base, 'Scans', parallel)
			unetPredict(base, gpu)
		else:
			affine_transform(base)
			snake_seg(base, parallel, 'v')
			snake_seg(base, parallel, 'c')
			combine_segs(base)
		subarachnoid_seg(base, seg_model, parallel)
		get_volumes(base, seg_model, save_last)
		make_prediction(base, seg_model)
		clean_up(base)
	
  
if __name__== "__main__":
	parser = argparse.ArgumentParser()
	parser.add_argument('--directory', default='')
	parser.add_argument('--seg_model', default='unet', help='unet or mcv')
	parser.add_argument('--parallel', action='store_true', default=False)
	parser.add_argument('--gpu', action='store_true', default=False)
	parser.add_argument('--save_last', action='store_true', default=False, help='include this to append to previous csv analysis files')
	parser.add_argument('--clear_cache', action='store_true', default=False, help='this will delete previous calculations')
	args = parser.parse_args()
	main(args.directory, args.parallel, args.seg_model, args.gpu, args.save_last, args.clear_cache)