mirror of
https://github.com/wassname/scikit-image.git
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emmanuelle
55f5103dd8
Modified travis_script.sh to account for the new structure of the gallery Added README.txt files in directories of gallery examples Fixed references to gallery images in user guide pages Fixed broken links
63 lines
2.0 KiB
Python
63 lines
2.0 KiB
Python
"""
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==========================================
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Find the intersection of two segmentations
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==========================================
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When segmenting an image, you may want to combine multiple alternative
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segmentations. The `skimage.segmentation.join_segmentations` function
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computes the join of two segmentations, in which a pixel is placed in
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the same segment if and only if it is in the same segment in _both_
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segmentations.
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"""
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import numpy as np
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from scipy import ndimage as ndi
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import matplotlib.pyplot as plt
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from skimage.filters import sobel
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from skimage.segmentation import slic, join_segmentations
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from skimage.morphology import watershed
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from skimage.color import label2rgb
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from skimage import data, img_as_float
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coins = img_as_float(data.coins())
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# make segmentation using edge-detection and watershed
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edges = sobel(coins)
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markers = np.zeros_like(coins)
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foreground, background = 1, 2
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markers[coins < 30.0 / 255] = background
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markers[coins > 150.0 / 255] = foreground
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ws = watershed(edges, markers)
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seg1 = ndi.label(ws == foreground)[0]
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# make segmentation using SLIC superpixels
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seg2 = slic(coins, n_segments=117, max_iter=160, sigma=1, compactness=0.75,
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multichannel=False)
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# combine the two
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segj = join_segmentations(seg1, seg2)
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# show the segmentations
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fig, axes = plt.subplots(ncols=4, figsize=(9, 2.5), sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
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axes[0].imshow(coins, cmap=plt.cm.gray, interpolation='nearest')
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axes[0].set_title('Image')
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color1 = label2rgb(seg1, image=coins, bg_label=0)
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axes[1].imshow(color1, interpolation='nearest')
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axes[1].set_title('Sobel+Watershed')
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color2 = label2rgb(seg2, image=coins, image_alpha=0.5)
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axes[2].imshow(color2, interpolation='nearest')
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axes[2].set_title('SLIC superpixels')
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color3 = label2rgb(segj, image=coins, image_alpha=0.5)
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axes[3].imshow(color3, interpolation='nearest')
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axes[3].set_title('Join')
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for ax in axes:
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ax.axis('off')
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fig.subplots_adjust(hspace=0.01, wspace=0.01, top=1, bottom=0, left=0, right=1)
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plt.show()
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