import numpy as np
from matplotlib import pyplot as plt, cm
from skimage import io
from scipy import ndimage as nd
from skimage.filter import threshold_otsu
from skimage.morphology import disk
from skimage.color import rgb2gray
from skimage import img_as_float
from skimage.morphology import opening
from skimage.morphology import remove_small_objects
# needs skimage 0.9dev; comment out the following line if your version is earlier
from skimage.color import label2rgb

%cd ~/Downloads/
filename = 'P1.jpg'
disk_size = 18
otsu_scale_factor = 1.45

%pylab inline
pothole = io.imread(filename)
gpot = img_as_float(rgb2gray(pothole))
plt.imshow(gpot, cmap=cm.gray)
plt.show()

t = threshold_otsu(gpot) * otsu_scale_factor
s = disk(disk_size)
tpot = gpot < t
plt.imshow(tpot, cmap=cm.gray)
plt.show()

tpot_open = opening(tpot, s)
plt.imshow(tpot_open, cmap=cm.gray)
plt.show()

objects = nd.label(tpot_open)[0] # label each connected region
b = np.bincount(objects.ravel()) # find object sizes
largest_object_size = sorted(b)[-2] # get second largest object
pothole_object = remove_small_objects(tpot_open.astype(bool), largest_object_size - 1)
plt.imshow(pothole_object)
plt.show()

pothole_object = nd.binary_fill_holes(pothole_object)
plt.imshow(pothole_object)
plt.show()

found_pothole = label2rgb(pothole_object, pothole)
plt.imshow(found_pothole)
plt.show()