update get slice mask from countour

rt_utils/image_helper.py

@@ -266,32 +266,19 @@ def get_slice_contour_data(series_slice: Dataset, contour_sequence: Sequence):
 def get_slice_mask_from_slice_contour_data(
  series_slice: Dataset, slice_contour_data, transformation_matrix: np.ndarray
 ):
- slice_mask = create_empty_slice_mask(series_slice)
+ # Go through all contours in a slice, create polygons in correct space and with a correct format 
+ # and append to polygons array (appropriate for fillPoly) 
+ polygons = []
  for contour_coords in slice_contour_data:
- fill_mask = get_contour_fill_mask(
- series_slice, contour_coords, transformation_matrix
- )
- # Invert values in the region to be filled. This will create holes where needed if contours are stacked on top of each other
- slice_mask[fill_mask == 1] = np.invert(slice_mask[fill_mask == 1])
+ reshaped_contour_data = np.reshape(contour_coords, [len(contour_coords) // 3, 3])
+ translated_contour_data = apply_transformation_to_3d_points(reshaped_contour_data, transformation_matrix)
+ polygon = [np.around([translated_contour_data[:, :2]]).astype(np.int32)]
+ polygon = np.array(polygon).squeeze()
+ polygons.append(polygon)
+ slice_mask = create_empty_slice_mask(series_slice).astype(np.uint8)
+ cv.fillPoly(img=slice_mask, pts = polygons, color = 1)
  return slice_mask
 
-
-def get_contour_fill_mask(
- series_slice: Dataset, contour_coords, transformation_matrix: np.ndarray
-):
- # Format data
- reshaped_contour_data = np.reshape(contour_coords, [len(contour_coords) // 3, 3])
- translated_contour_data = apply_transformation_to_3d_points(
- reshaped_contour_data, transformation_matrix
- )
- polygon = [np.around([translated_contour_data[:, :2]]).astype(np.int32)]
-
- # Create mask for the region. Fill with 1 for ROI
- fill_mask = create_empty_slice_mask(series_slice).astype(np.uint8)
- cv.fillPoly(img=fill_mask, pts=polygon, color=1)
- return fill_mask
-
-
 def create_empty_series_mask(series_data):
  ref_dicom_image = series_data[0]
  mask_dims = (