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
61 lines
1.7 KiB
Python
61 lines
1.7 KiB
Python
"""
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=================
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Template Matching
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=================
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In this example, we use template matching to identify the occurrence of an
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image patch (in this case, a sub-image centered on a single coin). Here, we
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return a single match (the exact same coin), so the maximum value in the
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``match_template`` result corresponds to the coin location. The other coins
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look similar, and thus have local maxima; if you expect multiple matches, you
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should use a proper peak-finding function.
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The ``match_template`` function uses fast, normalized cross-correlation [1]_
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to find instances of the template in the image. Note that the peaks in the
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output of ``match_template`` correspond to the origin (i.e. top-left corner) of
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the template.
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.. [1] J. P. Lewis, "Fast Normalized Cross-Correlation", Industrial Light and
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Magic.
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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from skimage import data
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from skimage.feature import match_template
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image = data.coins()
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coin = image[170:220, 75:130]
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result = match_template(image, coin)
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ij = np.unravel_index(np.argmax(result), result.shape)
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x, y = ij[::-1]
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fig = plt.figure(figsize=(8, 3))
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ax1 = plt.subplot(1, 3, 1)
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ax2 = plt.subplot(1, 3, 2, adjustable='box-forced')
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ax3 = plt.subplot(1, 3, 3, sharex=ax2, sharey=ax2, adjustable='box-forced')
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ax1.imshow(coin)
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ax1.set_axis_off()
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ax1.set_title('template')
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ax2.imshow(image)
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ax2.set_axis_off()
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ax2.set_title('image')
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# highlight matched region
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hcoin, wcoin = coin.shape
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rect = plt.Rectangle((x, y), wcoin, hcoin, edgecolor='r', facecolor='none')
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ax2.add_patch(rect)
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ax3.imshow(result)
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ax3.set_axis_off()
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ax3.set_title('`match_template`\nresult')
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# highlight matched region
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ax3.autoscale(False)
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ax3.plot(x, y, 'o', markeredgecolor='r', markerfacecolor='none', markersize=10)
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plt.show()
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