mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-27 20:22:51 +08:00
Tony S Yu
46 lines
1.5 KiB
Python
46 lines
1.5 KiB
Python
import numpy as np
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from ..morphology import dilation, square
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from ..util import img_as_float
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from ..color import gray2rgb
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from .._shared.utils import deprecated
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def find_boundaries(label_img):
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"""Return bool array where boundaries between labeled regions are True."""
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boundaries = np.zeros(label_img.shape, dtype=np.bool)
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boundaries[1:, :] += label_img[1:, :] != label_img[:-1, :]
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boundaries[:, 1:] += label_img[:, 1:] != label_img[:, :-1]
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return boundaries
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def mark_boundaries(image, label_img, color=(1, 1, 0), outline_color=None):
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"""Return image with boundaries between labeled regions highlighted.
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Parameters
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----------
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image : (M, N[, 3]) array
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Grayscale or RGB image.
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label_img : (M, N) array
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Label array where regions are marked by different integer values.
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color : length-3 sequence
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RGB color of boundaries in the output image.
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outline_color : length-3 sequence
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RGB color surrounding boundaries in the output image. If None, no
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outline is drawn.
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"""
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if image.ndim == 2:
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image = gray2rgb(image)
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image = img_as_float(image, force_copy=True)
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boundaries = find_boundaries(label_img)
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if outline_color is not None:
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outer_boundaries = dilation(boundaries.astype(np.uint8), square(2))
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image[outer_boundaries != 0, :] = np.array(outline_color)
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image[boundaries, :] = np.array(color)
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return image
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@deprecated('mark_boundaries')
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def visualize_boundaries(*args, **kwargs):
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return mark_boundaries(*args, **kwargs)
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