def _projection_to_staves()

in moonlight/staves/projection.py [0:0]

• 33 lines of code
• 6 McCabe index (conditional complexity)

def _projection_to_staves(projection, width):
  """Pure python implementation of projection-based staff detection."""
  labels, num_labels = scipy.ndimage.measurements.label(projection)
  current_staff = []
  staff_center_lines = []
  staffline_distance = []
  staffline_thicknesses = []
  for line in range(1, num_labels + 1):
    line_start = np.where(labels == line)[0].min()
    line_end = np.where(labels == line)[0].max()
    staffline_thickness = line_end - line_start + 1
    line_center = np.int32(round((line_start + line_end) / 2.0))
    current_staff.append(line_center)
    if len(current_staff) > 5:
      del current_staff[0]
    if len(current_staff) == 5:
      dists = np.array([
          current_staff[1] - current_staff[0],
          current_staff[2] - current_staff[1],
          current_staff[3] - current_staff[2],
          current_staff[4] - current_staff[3]
      ])
      if np.max(dists) - np.min(dists) < 3:
        staff_center = round(np.mean(current_staff))
        staff_center_lines.append([[0, staff_center], [width - 1,
                                                       staff_center]])
        staffline_distance.append(round(np.mean(dists)))
        staffline_thicknesses.append(staffline_thickness)
  staffline_thickness = (
      np.median(staffline_thicknesses).astype(np.int32)
      if staffline_thicknesses else np.int32(1))
  return (np.array(staff_center_lines,
                   np.int32), np.array(staffline_distance,
                                       np.int32), staffline_thickness)