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ENH: Refactored code to take multiple inputs using argparse. Removed …
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…hard-coded glob
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@sebastientourbier
sebastientourbier committed May 9, 2019
1 parent e770896 commit 2ee2246
Showing 1 changed file with 48 additions and 54 deletions.
102 changes: 48 additions & 54 deletions src/IntensityStandardization/mialsrtkHistogramNormalization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -184,9 +184,12 @@ def computeMeanMapImageLandmarks(list_landmarks):
return mean_landmarks


def main(image_directory,mask_directory,output_directory,suffix,iteration):
image_paths= sorted(glob.glob(image_directory+"/*_lr_"+suffix+"_iteration_"+iteration+".nii.gz"))
mask_paths=sorted(glob.glob(mask_directory+"/*_lr_brain_mask"+str(args.mask_type)+"_reo_iteration_"+iteration+".nii.gz"))
def main(images,masks,outputs):

image_paths= sorted(images)
mask_paths=sorted(masks)
output_paths = sorted(outputs)

if(len(image_paths)!=len(mask_paths)):
print 'Loading failed: Number of images and masks are different (# images = '+str(len(image_paths))+' \ # masks = '+str(len(mask_paths))+')'
return
Expand Down Expand Up @@ -242,9 +245,8 @@ def main(image_directory,mask_directory,output_directory,suffix,iteration):
displayHistogram(maskedImageMapped,image_name,1,0)
o2o=verifyOne2OneMapping(s1,s2,list_landmarks[index],mean_landmarks)
new_image = nib.Nifti1Image(np.reshape(maskedImageMapped,np.array([dimY,dimX,dimZ])),image.get_affine(),header=image.get_header())
new_image_name = str(output_directory)+"/"+str(image_name)+'_histnorm.nii.gz'
print 'Save normalized image '+str(image_name)+ ' as '+str(new_image_name) + '(one 2 one mapping :'+str(o2o)+')'
nib.save(new_image,new_image_name)
print 'Save normalized image '+str(image_name)+ ' as '+str(output_paths[index]) + '(one 2 one mapping :'+str(o2o)+')'
nib.save(new_image,output_paths[index])
index+=1
#pyplot.legend()
#pyplot.xlabel('Intensity')
Expand All @@ -253,57 +255,49 @@ def main(image_directory,mask_directory,output_directory,suffix,iteration):
## To be uncommented to display plot before/after histogram normalizatiopn
##pyplot.show()

# Read command line args
# try:
# myopts, args = getopt.getopt(sys.argv[1:],'i:h:o', ['input_directory=','mask_directory=','output_directory'])
# except getopt.GetoptError, err:
# print str(err)
# sys.exit(2)

# for opt, arg in myopts:
# if opt in ('-i','--input_directory'):
# image_directory=arg
# print image_directory
# if opt in ('-h','--mask_directory'):
# mask_directory=arg
# print mask_directory
# if opt in ('-o','--output_directory'):
# output_directory=arg
# print output_directory
# else:
# print("Usage: %s -i input_directory -m mask_directory -o output_directory" % sys.argv[0])
# sys.exit(2)

# main(image_directory,mask_directory,output_directory)

# #directory='/Users/sebastientourbier/Desktop/F019/'
# #directory='/media/Shared_Data/MyStudies/PrereconstructionPipeline/Data/'
# Parse command line args

parser = argparse.ArgumentParser(description='Intensity histogram normalization based on percentiles')
parser.add_argument('-i','--input_dir',help='Input directory')
parser.add_argument('-m','--mask_dir',help='Mask directory')
parser.add_argument('-t','--mask_type',help='Mask type: could be "", SSMMI_CompositeVersor2DBSplineNCC, SSMMI_VersorOnlyNCC or MAN')
parser.add_argument('-o','--output_dir',help='Output directory')
parser.add_argument('-S','--suffix',help='Suffix of image filename, such as filename ended by *_Final_${suffix}_iteration_${iteration}.nii.gz, where ${iteration} is given by input flag -I or --iteration. suffix="uni_bcorr_reo" (not denoised images) or suffix="nlm_uni_bcorr_reo" (denoised images)')
parser.add_argument('-I','--iteration',help='Reconstruction iteration, needed to load the corresponding input images being histogram equalized')
parser.add_argument('-i','--input', required=True, action='append', help='Input image(s)')
parser.add_argument('-m','--mask', required=True, action='append', help='Input mask(s)')
parser.add_argument('-o','--output', required=True, action='append', help='Output normalized image(s)')

args = parser.parse_args()

print args.input_dir!=None
print args.mask_dir!=None
print args.mask_type!=None
print args.output_dir!=None
print args.suffix!=None
print args.iteration!=None

if (args.input_dir!=None and args.mask_dir!=None and args.output_dir!=None and args.mask_type!=None and args.suffix!=None and args.iteration!=None):
print 'Input directory: '+str(args.input_dir)
print 'Mask directory: '+str(args.mask_dir)
print 'Mask type: '+str(args.mask_type)
print 'Output directory: '+str(args.output_dir)
print 'Image file suffix: '+str(args.suffix)
print 'Reconstruction iteration: '+str(args.iteration)
main(str(args.input_dir),str(args.mask_dir),str(args.output_dir),str(args.suffix),str(args.iteration))
else:
print("Usage: %s -i input_directory -m mask_directory -t mask_type -o output_directory -S image_file_suffix -I iteration" % sys.argv[0])
print(len(args.input)>0)
print(len(args.mask)>0)
print(len(args.output)>0)
print('Inputs: {}'.format(args.input))
print('Masks: {}'.format(args.mask))
print('Outputs: {}'.format(args.output))

if len(args.input)==0:
print("Error: No input images provided")
print("Usage: %s -i input_image1 -m input_image1_mask -o output_image1 -i input_image2 -m input_image2_mask -o output_image2 " % sys.argv[0])
sys.exit(2)

if len(args.mask)==0:
print("Error: No masks provided")
print("Usage: %s -i input_image1 -m input_image1_mask -o output_image1 -i input_image2 -m input_image2_mask -o output_image2 " % sys.argv[0])
sys.exit(2)

if len(args.output)==0:
print("Error: No output provided")
print("Usage: %s -i input_image1 -m input_image1_mask -o output_image1 -i input_image2 -m input_image2_mask -o output_image2 " % sys.argv[0])
sys.exit(2)

if (len(args.input)!=len(args.mask)):
print("Error: Number of inputs and masks are not equal")
print("Usage: %s -i input_image1 -m input_image1_mask -o output_image1 -i input_image2 -m input_image2_mask -o output_image2 " % sys.argv[0])
sys.exit(2)

if (len(args.input)!=len(args.output)):
print("Error: Number of inputs and outputs are not equal")
print("Usage: %s -i input_image1 -m input_image1_mask -o output_image1 -i input_image2 -m input_image2_mask -o output_image2 " % sys.argv[0])
sys.exit(2)


print('Inputs: {}'.format(args.input))
print('Masks: {}'.format(args.mask))
print('Outputs: {}'.format(args.output))
main(args.input,args.mask,args.output)

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