mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-28 18:45:14 +08:00
Ankit Agrawal
47 lines
1.6 KiB
Python
47 lines
1.6 KiB
Python
"""
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===========================
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Censure Keypoints Detection
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===========================
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In this example, we detect and plot the Censure Keypoints at various scales
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using Difference of Boxes, Octagon and Star shaped bi-level filters.
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"""
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from skimage.feature import keypoints_censure
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from skimage.data import lena
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from skimage.color import rgb2gray
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import matplotlib.pyplot as plt
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# Initializing the parameters for Censure keypoints
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img = lena()
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gray_img = rgb2gray(img)
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min_scale = 1
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max_scale = 7
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nms_threshold = 0.15
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rpc_threshold = 10
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# Detecting Censure keypoints for the following filters
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for mode in ['dob', 'octagon', 'star']:
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kp_censure, scale = keypoints_censure(gray_img, min_scale, max_scale,
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mode, nms_threshold, rpc_threshold)
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f, axarr = plt.subplots((max_scale - min_scale + 1) // 3, 3)
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# Plotting Censure features at all the scales
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for i in range(max_scale - min_scale - 1):
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keypoints = kp_censure[scale == i + min_scale + 1]
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num = len(keypoints)
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x = keypoints[:, 1]
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y = keypoints[:, 0]
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s = 5 * 2**(i + min_scale + 1)
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axarr[i // 3, i - (i // 3) * 3].imshow(img)
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axarr[i // 3, i - (i // 3) * 3].scatter(x, y, s, facecolors='none',
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edgecolors='g')
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axarr[i // 3, i - (i // 3) * 3].set_title(' %s %s-Censure features at '
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'scale %d' % (num, mode, i +
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min_scale + 1))
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plt.suptitle('NMS threshold = %f, RPC threshold = %d'
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% (nms_threshold, rpc_threshold))
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plt.show()
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