diff --git a/skimage/morphology/grey.py b/skimage/morphology/grey.py index dc34d3d6..a7959bb6 100644 --- a/skimage/morphology/grey.py +++ b/skimage/morphology/grey.py @@ -57,7 +57,7 @@ def erosion(image, selem, out=None, shift_x=False, shift_y=False): [0, 0, 0, 0, 0], [0, 0, 1, 0, 0], [0, 0, 0, 0, 0], - [0, 0, 0, 0, 0]], dtype='uint8') + [0, 0, 0, 0, 0]], dtype=uint8) """ @@ -109,7 +109,7 @@ def dilation(image, selem, out=None, shift_x=False, shift_y=False): [0, 1, 1, 1, 0], [0, 1, 1, 1, 0], [0, 1, 1, 1, 0], - [0, 0, 0, 0, 0]], dtype='uint8') + [0, 0, 0, 0, 0]], dtype=uint8) """ @@ -158,7 +158,7 @@ def opening(image, selem, out=None): [1, 1, 0, 1, 1], [1, 1, 0, 1, 1], [1, 1, 0, 1, 1], - [0, 0, 0, 0, 0]], dtype='uint8') + [0, 0, 0, 0, 0]], dtype=uint8) """ @@ -208,7 +208,7 @@ def closing(image, selem, out=None): [0, 0, 0, 0, 0], [1, 1, 1, 1, 1], [0, 0, 0, 0, 0], - [0, 0, 0, 0, 0]], dtype='uint8') + [0, 0, 0, 0, 0]], dtype=uint8) """ @@ -257,7 +257,7 @@ def white_tophat(image, selem, out=None): [0, 0, 1, 0, 0], [0, 1, 5, 1, 0], [0, 0, 1, 0, 0], - [0, 0, 0, 0, 0]], dtype='uint8') + [0, 0, 0, 0, 0]], dtype=uint8) """ if image is out: @@ -306,7 +306,7 @@ def black_tophat(image, selem, out=None): [0, 0, 1, 0, 0], [0, 1, 5, 1, 0], [0, 0, 1, 0, 0], - [0, 0, 0, 0, 0]], dtype='uint8') + [0, 0, 0, 0, 0]], dtype=uint8) """ diff --git a/skimage/morphology/watershed.py b/skimage/morphology/watershed.py index c0b1b34b..8a08fafc 100644 --- a/skimage/morphology/watershed.py +++ b/skimage/morphology/watershed.py @@ -261,7 +261,7 @@ def is_local_maximum(image, labels=None, footprint=None): array([[ True, False, False, False], [ True, False, True, False], [ True, False, False, False], - [ True, True, False, True]], dtype='bool') + [ True, True, False, True]], dtype=bool) >>> image = np.arange(16).reshape((4, 4)) >>> labels = np.array([[1, 2], [3, 4]]) >>> labels = np.repeat(np.repeat(labels, 2, axis=0), 2, axis=1) @@ -279,7 +279,7 @@ def is_local_maximum(image, labels=None, footprint=None): array([[False, False, False, False], [False, True, False, True], [False, False, False, False], - [False, True, False, True]], dtype='bool') + [False, True, False, True]], dtype=bool) """ if labels is None: labels = np.ones(image.shape, dtype=np.uint8)