Temporarily remove censure keypoints example

doc/examples/plot_censure_keypoints.py

@@ -1,54 +0,0 @@
-"""
-=========================
-CenSurE Feature Detection
-=========================
-
-In this example we detect and plot the CenSurE (Center Surround Extrema)
-features at various scales using Difference of Boxes, Octagon and Star shaped
-bi-level filters.
-
-"""
-
-from skimage.feature import keypoints_censure
-from skimage.data import lena
-from skimage.color import rgb2gray
-import matplotlib.pyplot as plt
-
-# Initializing the parameters for Censure keypoints
-img = lena()
-gray_img = rgb2gray(img)
-min_scale = 2
-max_scale = 6
-non_max_threshold = 0.15
-line_threshold = 10
-
-
-_, ax = plt.subplots(nrows=(max_scale - min_scale - 1), ncols=3,
-                     figsize=(6, 6))
-plt.subplots_adjust(wspace=0.02, hspace=0.02, top=0.94,
-                    bottom=0.02, left=0.06, right=0.98)
-
-# Detecting Censure keypoints for the following filters
-for col, mode in enumerate(['dob', 'octagon', 'star']):
-
-    ax[0, col].set_title(mode.upper(), fontsize=12)
-
-    keypoints, scales = keypoints_censure(gray_img, min_scale, max_scale,
-                                          mode, non_max_threshold,
-                                          line_threshold)
-
-    # Plotting Censure features at all the scales
-    for row, scale in enumerate(range(min_scale + 1, max_scale)):
-        mask = scales == scale
-        x = keypoints[mask, 1]
-        y = keypoints[mask, 0]
-        s = 0.5 * 2 ** (scale + min_scale + 1)
-        ax[row, col].imshow(img)
-        ax[row, col].scatter(x, y, s, facecolors='none', edgecolors='b')
-        ax[row, col].set_xticks([])
-        ax[row, col].set_yticks([])
-        ax[row, col].axis((0, img.shape[1], img.shape[0], 0))
-        if col == 0:
-            ax[row, col].set_ylabel('Scale %d' % scale, fontsize=12)
-
-plt.show()