def corner_peaks(image, min_distance=1, threshold_abs=None, threshold_rel=0.1, exclude_border=True, indices=True, num_peaks=np.inf, footprint=None, labels=None):
 peaks = peak_local_max(image, min_distance=min_distance, threshold_abs=threshold_abs, threshold_rel=threshold_rel, exclude_border=exclude_border, indices=False, num_peaks=num_peaks, footprint=footprint, labels=labels)
 if (min_distance > 0):
  coords = np.transpose(peaks.nonzero())
  for (r, c) in coords:
   if peaks[(r, c)]:
    peaks[(r - min_distance):((r + min_distance) + 1), (c - min_distance):((c + min_distance) + 1)] = False
    peaks[(r, c)] = True
 if (indices is True):
  return np.transpose(peaks.nonzero())
 else:
  return peaks

def corner_peaks ( image , min_distance = 1 , threshold_abs = None , threshold_rel = 0.1 , exclude_border = True , indices = True , num_peaks = np . inf , footprint = None , labels = None ) : peaks = peak_local_max ( image , min_distance = min_distance , threshold_abs = threshold_abs , threshold_rel = threshold_rel , exclude_border = exclude_border , indices = False , num_peaks = num_peaks , footprint = footprint , labels = labels ) if ( min_distance > 0 ) : coords = np . transpose ( peaks . nonzero ( ) ) for ( r , c ) in coords : if peaks [ ( r , c ) ] : peaks [ ( r - min_distance ) : ( ( r + min_distance ) + 1 ) , ( c - min_distance ) : ( ( c + min_distance ) + 1 ) ] = False peaks [ ( r , c ) ] = True if ( indices is True ) : return np . transpose ( peaks . nonzero ( ) ) else : return peaks
find corners in corner measure response image .