Fix censure example and fix some minor issues

doc/examples/plot_censure_keypoints.py

@@ -1,12 +1,14 @@
 """
-===========================
-Censure Keypoints Detection
-===========================
+=========================
+CenSurE Feature Detection
+=========================
 
-In this example, we detect and plot the Censure Keypoints at various scales
-using Difference of Boxes, Octagon and Star shaped bi-level filters.
+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
@@ -15,32 +17,39 @@ import matplotlib.pyplot as plt
 # Initializing the parameters for Censure keypoints
 img = lena()
 gray_img = rgb2gray(img)
-min_scale = 1
-max_scale = 7
-nms_threshold = 0.15
-rpc_threshold = 10
+min_scale = 2
+max_scale = 6
+non_max_threshold = 0.15
+line_threshold = 10
+
+
+f, 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 mode in ['dob', 'octagon', 'star']:
+for col, mode in enumerate(['dob', 'octagon', 'star']):
 
-    kp_censure, scale = keypoints_censure(gray_img, min_scale, max_scale,
-                                          mode, nms_threshold, rpc_threshold)
-    f, axarr = plt.subplots((max_scale - min_scale + 1) // 3, 3)
+    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 i in range(max_scale - min_scale - 1):
-        keypoints = kp_censure[scale == i + min_scale + 1]
-        num = len(keypoints)
-        x = keypoints[:, 1]
-        y = keypoints[:, 0]
-        s = 5 * 2**(i + min_scale + 1)
-        axarr[i // 3, i - (i // 3) * 3].imshow(img)
-        axarr[i // 3, i - (i // 3) * 3].scatter(x, y, s, facecolors='none',
-                                                edgecolors='g')
-        axarr[i // 3, i - (i // 3) * 3].set_title(' %s %s-Censure features at '
-                                                  'scale %d' % (num, mode, i +
-                                                                min_scale + 1))
+    for row, scale in enumerate(range(min_scale + 1, max_scale)):
+        keypoints_i = keypoints[scales == scale]
+        num = len(keypoints_i)
+        x = keypoints_i[:, 1]
+        y = keypoints_i[:, 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.suptitle('NMS threshold = %f, RPC threshold = %d'
-                 % (nms_threshold, rpc_threshold))
 plt.show()