parameters: (self)
return_statement: return initial_bias
docstring: see RARE paper Fig. 6 (a)
docstring_summary: see RARE paper Fig. 6 (a)
docstring_tokens: see RARE paper Fig . 6 ( a )
function: def get_initial_fiducials(self):
          """ see RARE paper Fig. 6 (a) """
          F = self.F
          ctrl_pts_x = np.linspace(-1.0, 1.0, int(F / 2))
          ctrl_pts_y_top = np.linspace(0.0, -1.0, num=int(F / 2))
          ctrl_pts_y_bottom = np.linspace(1.0, 0.0, num=int(F / 2))
          ctrl_pts_top = np.stack([ctrl_pts_x, ctrl_pts_y_top], axis=1)
          ctrl_pts_bottom = np.stack([ctrl_pts_x, ctrl_pts_y_bottom], axis=1)
          initial_bias = np.concatenate([ctrl_pts_top, ctrl_pts_bottom], axis=0)
          return initial_bias
function_tokens: def get_initial_fiducials ( self ) : F = self . F ctrl_pts_x = np . linspace ( - 1.0 , 1.0 , int ( F / 2 ) ) ctrl_pts_y_top = np . linspace ( 0.0 , - 1.0 , num = int ( F / 2 ) ) ctrl_pts_y_bottom = np . linspace ( 1.0 , 0.0 , num = int ( F / 2 ) ) ctrl_pts_top = np . stack ( [ ctrl_pts_x , ctrl_pts_y_top ] , axis = 1 ) ctrl_pts_bottom = np . stack ( [ ctrl_pts_x , ctrl_pts_y_bottom ] , axis = 1 ) initial_bias = np . concatenate ( [ ctrl_pts_top , ctrl_pts_bottom ] , axis = 0 ) return initial_bias