benchmark_label.py

"""
===================
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 matplotlib.pyplot as plt
import matplotlib.patches as mpatches

from skimage import data
from skimage.filters import threshold_otsu
from skimage.segmentation import clear_border
from skimage.measure import label, regionprops
from skimage.morphology import closing, square
from skimage.color import label2rgb

from timeit import timeit


image = data.coins()[50:-50, 50:-50]

# apply threshold
thresh = threshold_otsu(image)
bw = closing(image > thresh, square(3))

# remove artifacts connected to image border
cleared = clear_border(bw)

## time it

## prove that it works
iterations = 10000
time = timeit("label(cleared)", setup="from __main__ import label, cleared", number=iterations)
print("Time: %.3fs for %d runs, %.3fms/run" % (time, iterations, time/iterations*1000))

## prove that it works
# label image regions
label_image = label(cleared)
image_label_overlay = label2rgb(label_image, image=image)

fig, ax = plt.subplots(figsize=(10, 6))
ax.imshow(image_label_overlay)

for region in regionprops(label_image):
    # take regions with large enough areas
    if region.area >= 100:
        # draw rectangle around segmented coins
        minr, minc, maxr, maxc = region.bbox
        rect = mpatches.Rectangle((minc, minr), maxc - minc, maxr - minr,
                                  fill=False, edgecolor='red', linewidth=2)
        ax.add_patch(rect)

ax.set_axis_off()
plt.tight_layout()
plt.show()

Benchmark results on my laptop with python 3.5.1:

on master 92a38515ac7222aab5e606f9de46caf5f503a7bd

(skimage-master) hulettbh@gemini ~> python benchmark_label.py 
Time: 6.746s for 10000 runs, 0.675ms/run

On PR#2282 branch 0525bb9b77e7e8e271534ffd4c6b07180f1ffa4f

(skimage-master) hulettbh@gemini ~> python benchmark_label.py 
Time: 6.746s for 10000 runs, 0.675ms/run

based on http://scikit-image.org/docs/dev/auto_examples/plot_label.html