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)