extract_body_mask.py

from scipy import ndimage
from geometric_utils import find_largest_object

def extract_body_mask(im):

  im_thresholded = im > 90
  im_filled = ndimage.binary_erosion(im_thresholded, iterations=1)
  im_filled = ndimage.binary_fill_holes(im_filled)
  im_filled = ndimage.binary_erosion(im_filled, iterations=3)

  body_mask = find_largest_object(im_filled)

  return body_mask.astype(int)
  
def find_largest_object(im):

  all_labels = measure.label(im)
 
  max_size, max_region = 0, None

  for i in range(0,np.unique(all_labels).shape[0]):
    size = im[all_labels == i].shape[0]
    if size > max_size and i != im[0,0]:
      max_region = i
      max_size = size
 
  region = np.zeros(im.shape)
  region[all_labels == max_region] = 1
  
  return region