def probabilistic_hough_line(img, threshold=10, line_length=50, line_gap=10, theta=None):
 if (img.ndim != 2):
  raise ValueError('The input image `img` must be 2D.')
 if (theta is None):
  theta = np.linspace(((- np.pi) / 2), (np.pi / 2), 180)
 return _probabilistic_hough_line(img, threshold, line_length, line_gap, theta)

def probabilistic_hough_line ( img , threshold = 10 , line_length = 50 , line_gap = 10 , theta = None ) : if ( img . ndim != 2 ) : raise ValueError ( 'The input image `img` must be 2D.' ) if ( theta is None ) : theta = np . linspace ( ( ( - np . pi ) / 2 ) , ( np . pi / 2 ) , 180 ) return _probabilistic_hough_line ( img , threshold , line_length , line_gap , theta )
return lines from a progressive probabilistic line hough transform .