def compute_all_scores():
lpba_dir = get_lpba_base_dir()
cnt = 0
for i in range(1,41):
i_idx = str(i) if i>=10 else '0'+str(i)
for j in range(1,41):
if i == j:
continue
cnt += 1
j_idx = str(j) if j>=10 else '0'+str(j)
reference_name = lpba_dir+'/S'+i_idx+'/S'+i_idx+'_strip_seg.img'
warped_name = 'warpedDiff_S'+j_idx+'_strip_seg_S'+i_idx+'_strip.nii.gz'
if os.path.exists(reference_name) and os.path.exists(warped_name):
print(str(cnt)+'/'+str(40*39), reference_name, warped_name)
compute_target_overlap(reference_name, warped_name, True)
compute_jaccard(reference_name, warped_name, True)
import nibabel as nib
import experiments.registration.dataset_info as info
if __name__ == "__main__":
lpba_base_dir = info.get_lpba_base_dir()
for i in range(1,41):
idx = '0'+str(i) if i<10 else str(i)
strip_name = lpba_base_dir + '/S'+idx+'/S'+idx+'_strip.img'
seg_name = lpba_base_dir + '/S'+idx+'/S'+idx+'_seg.img'
print('Masking annotations: ' + seg_name)
strip_ana = nib.load(strip_name)
seg_ana = nib.load(seg_name)
strip = strip_ana.get_data().squeeze()
seg = seg_ana.get_data().squeeze()
p = seg_name.find('_seg')
strip_seg_name = seg_name[:p]+'_strip_seg.img'
seg *= (strip>0)
seg_ana.to_filename(strip_seg_name)
