remove other duplicate examples

doc/examples/plot_modal_filter.py

@@ -1,67 +0,0 @@
-"""
-===================
-Label image regions
-===================
-
-This example shows how to segment an image with image labelling. The following
-steps are applied:
-
-1. Thresholding with automatic Otsu method
-2. Close small holes with binary closing
-3. Remove artifacts touching image border
-4. Measure image regions to filter small objects
-
-"""
-
-import numpy as np
-import matplotlib.pyplot as plt
-import matplotlib.patches as mpatches
-
-from skimage import data
-from skimage.filter import threshold_otsu
-
-from skimage.filter.rank import modal
-
-from skimage.morphology import label, disk
-from skimage.measure import find_contours
-
-
-image = data.coins()[50:-50, 50:-50]
-
-# apply threshold
-thresh = threshold_otsu(image)
-bw = image > thresh
-
-# label image regions
-label_image = label(bw)
-
-# filter obtained labels using model filter
-mod_label_image = modal(label_image.astype(np.uint16),disk(5))
-
-# the background is here 1
-contours = find_contours(mod_label_image==1,0, positive_orientation='low')
-
-fig, axes = plt.subplots(ncols=2, nrows=2, figsize=(6, 6))
-
-print axes
-
-ax0, ax1, ax2, ax3 = axes.ravel()
-
-ax0.imshow(bw, cmap='gray')
-ax0.set_title('Otsu threshold')
-ax1.imshow(label_image, cmap='jet')
-ax1.set_title('label image')
-ax2.imshow(mod_label_image, cmap='jet')
-ax2.set_title('filtered labels (modal)')
-ax3.imshow(image, cmap='gray')
-ax3.set_title('contour overlay')
-ax3.set_xlim((0,image.shape[1]))
-ax3.set_ylim((image.shape[0],0))
-
-
-for n, contour in enumerate(contours):
-    ax3.plot(contour[:, 1], contour[:, 0], linewidth=2)
-
-
-plt.show()
-