Révision 10 bin/image2geometry/orient_sepal.py

orient_sepal.py (revision 10)
20 20 
from scipy.ndimage.morphology import binary_closing, binary_opening
21 21 

  		





  22
  22
  
    
from titk_tools.io import imread, imsave, tfread, SpatialImage


  		





  23
  
  
    
from titk_tools.registration import isotropic_resampling_seg


  		





  24
  
  
    
from titk_tools.registration import apply_transfo_on_seg1


  		





  
  23
  
    
from titk_tools.registration import isotropic_resampling_seg, isotropic_resampling


  		





  
  24
  
    
from titk_tools.registration import apply_transfo_on_seg1, apply_transfo_on_image


  		





  25
  25
  
    

  		





  26
  26
  
    
from bib_sepals import *


  		





  27
  27
  
    

  		





  ......




  30
  30
  
    
filename = argv[1]


  		





  31
  31
  
    
outputdir=argv[2]+'/'


  		





  32
  32
  
    

  		





  
  33
  
    
segmented=True


  		





  
  34
  
    

  		





  
  35
  
    
if len(argv)>3:


  		





  
  36
  
    
	imagetype=argv[3]


  		





  
  37
  
    
	if imagetype=='grey':


  		





  
  38
  
    
		segmented=False


  		





  
  39
  
    

  		





  33
  40
  
    
print(argv)


  		





  
  41
  
    
print('segmented=',segmented)


  		





  34
  42
  
    

  		





  35
  43
  
    
imname = filename.split('/')[-1]


  		





  36
  44
  
    
imnameroot = imname.split('.')[0]


  		





  ......




  38
  46
  
    
outfilename = outputdir+imnameroot+'_oriented.inr.gz'


  		





  39
  47
  
    

  		





  40
  48
  
    
# read the image


  		





  41
  
  
    
sepale=imread(filename)


  		





  
  49
  
    
img=imread(filename)


  		





  42
  50
  
    
# resample isotropically


  		





  43
  51
  
    
print("----------------------")


  		





  44
  52
  
    
print("isotropic resampling of : filename=", filename)


  		





  45
  53
  
    
print("----------------------")


  		





  46
  
  
    
voxelsize = sepale.voxelsize


  		





  
  54
  
    
voxelsize = img.voxelsize


  		





  47
  55
  
    
print("voxelsize=",voxelsize)


  		





  48
  
  
    
s = sepale.shape


  		





  
  56
  
    
s = img.shape


  		





  
  57
  
    
imgtype=img.dtype


  		





  49
  58
  
    
print("shape=",s)


  		





  50
  59
  
    

  		





  51
  60
  
    
radius=int(voxelsize[2]/voxelsize[0])


  		





  ......




  53
  62
  
    
#isovs=voxelsize[0]


  		





  54
  63
  
    
print("new voxelsize=",isovs)


  		





  55
  64
  
    

  		





  56
  
  
    
sepale=SpatialImage(sepale>0, dtype='uint8', voxelsize=voxelsize, origin=[0, 0, 0])


  		





  57
  
  
    
sepale=isotropic_resampling_seg(sepale,isovs)


  		





  
  65
  
    
sepale=SpatialImage(img>0, dtype='uint8', voxelsize=voxelsize, origin=[0, 0, 0])


  		





  
  66
  
    
if segmented:


  		





  
  67
  
    
	sepale=isotropic_resampling_seg(sepale,isovs)


  		





  
  68
  
    
else:


  		





  
  69
  
    
	img=isotropic_resampling(img,isovs)


  		





  
  70
  
    
	sepale=isotropic_resampling_seg(sepale,isovs)


  		





  58
  71
  
    

  		





  59
  72
  
    
s = sepale.shape


  		





  60
  73
  
    
voxelsize = sepale.voxelsize


  		





  ......




  68
  81
  
    
s_addy=int((np.sqrt(s[0]*s[1]*2)-np.sqrt(s[0]*s[1]))/2)


  		





  69
  82
  
    
s_addz=int(s[2]*0.20)


  		





  70
  83
  
    
sepale=add_side_slices(sepale, 0, 0, s_addy, s_addy, s_addz, s_addz)


  		





  
  84
  
    
if not segmented :


  		





  
  85
  
    
	img=add_side_slices(img, 0, 0, s_addy, s_addy, s_addz, s_addz)


  		





  71
  86
  
    

  		





  72
  87
  
    
'''


  		





  73
  88
  
    
# smooth it with opening


  		





  ......




  83
  98
  
    
'''


  		





  84
  99
  
    

  		





  85
  100
  
    
# put the center of mass in the center of the image


  		





  86
  
  
    
sepale_centered=center_on_cm(sepale, volumic=False)


  		





  
  101
  
    
sepale_centered=center_on_cm(sepale, volumic=True)


  		





  
  102
  
    
if not segmented:


  		





  
  103
  
    
	img=center_on_cm(img, volumic=True)


  		





  87
  104
  
    

  		





  88
  105
  
    
# compute principal directions


  		





  89
  
  
    
pv_flo=principal_directions(sepale_centered, volumic=False)


  		





  
  106
  
    
pv_flo=principal_directions(sepale_centered, volumic=True)


  		





  90
  107
  
    
print(pv_flo)


  		





  91
  108
  
    

  		





  92
  109
  
    
# sepals originally are oriented with top in more-or less "up" direction on the images


  		





  ......




  120
  137
  
    
os.system("rm "+trsf_file)


  		





  121
  138
  
    

  		





  122
  139
  
    
# apply transformation


  		





  123
  
  
    
oriented=apply_transfo_on_seg1(trsf, sepale_centered)


  		





  
  140
  
    
if segmented :


  		





  
  141
  
    
	oriented=apply_transfo_on_seg1(trsf, sepale_centered)


  		





  
  142
  
    
else :


  		





  
  143
  
    
	oriented=apply_transfo_on_image(trsf, img)


  		





  124
  144
  
    

  		





  125
  145
  
    
# smooth the transformed image


  		





  126
  146
  
    
#sepale = binary_closing(oriented, structure=struct_el, iterations=radius)


  		





  127
  147
  
    

  		





  128
  148
  
    
# and save the oriented sepal


  		





  129
  149
  
    
sepale_filename = outputdir+imnameroot+'_oriented.inr.gz'


  		





  130
  
  
    
sepale=SpatialImage(oriented*255, dtype='uint8', voxelsize=voxelsize, origin=[0, 0, 0])


  		





  
  150
  
    
if segmented :


  		





  
  151
  
    
	sepale=SpatialImage(oriented*255, dtype='uint8', voxelsize=voxelsize, origin=[0, 0, 0])


  		





  
  152
  
    
else:


  		





  
  153
  
    
	sepale=SpatialImage(oriented, dtype=imgtype, voxelsize=voxelsize, origin=[0, 0, 0])


  		





  
  154
  
    

  		





  131
  155
  
    
imsave(sepale_filename, sepale)


  		





  132
  156
  
    

  		












Formats disponibles :
  Unified diff