Add new example plot for match_template.

doc/examples/plot_template_alt.py

@@ -0,0 +1,56 @@
+"""
+=================
+Template Matching
+=================
+
+In this example, we use template matching to identify the occurrence of an
+image patch (in this case, a sub-image centered on a single coin). Here, we
+return a single match (the exact same coin), so the maximum value in the
+``match_template`` result corresponds to the coin location. The other coins
+look similar, and thus have local maxima; if you expect multiple matches, you
+should use a proper peak-finding function.
+
+The ``match_template`` function uses fast, normalized cross-correlation [1]_
+to find instances of the template in the image. Note that the peaks in the
+output of ``match_template`` correspond to the origin (i.e. top-left corner) of
+the template.
+
+.. [1] J. P. Lewis, "Fast Normalized Cross-Correlation", Industrial Light and
+       Magic.
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+from skimage import data
+from skimage.feature import match_template
+
+image = data.coins()
+coin = image[170:220, 75:130]
+
+result = match_template(image, coin)
+ij = np.unravel_index(np.argmax(result), result.shape)
+x, y = ij[::-1]
+
+fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=(8, 3))
+
+ax1.imshow(coin)
+ax1.set_axis_off()
+ax1.set_title('template')
+
+ax2.imshow(image)
+ax2.set_axis_off()
+ax2.set_title('image')
+# highlight matched region
+hcoin, wcoin = coin.shape
+rect = plt.Rectangle((x, y), wcoin, hcoin, edgecolor='r', facecolor='none')
+ax2.add_patch(rect)
+
+ax3.imshow(result)
+ax3.set_axis_off()
+ax3.set_title('`match_template`\nresult')
+# highlight matched region
+ax3.autoscale(False)
+ax3.plot(x, y, 'o', markeredgecolor='r', markerfacecolor='none', markersize=10)
+
+plt.show()
+