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DOC: changes for Marianne's coffee cup

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François Boulogne
2013-08-05 16:45:59 +02:00
parent 02acd3ce42
commit 9d7a90395b
3 changed files with 13 additions and 14 deletions
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doc/examples/plot_circular_elliptical_hough_transform.py
+10 -9
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@@ -110,27 +110,28 @@ from skimage.transform import hough_ellipse
from skimage.draw import ellipse_perimeter
# Load picture, convert to grayscale and detect edges
image_rgb = data.load('coffee.png')[100:240, 110:250]
image_rgb = data.load('coffee.png')[0:220, 100:450]
image_gray = color.rgb2gray(image_rgb)
edges = filter.canny(image_gray, sigma=2.0,
low_threshold=0.1, high_threshold=0.6)
low_threshold=0.55, high_threshold=0.8)
# Perform a Hough Transform
# The accuracy corresponds to the bin size of a major axis.
# The value is chosen in order to get a single high accumulator.
# The threshold eliminates low accumulators
accum = hough_ellipse(edges, accuracy=7, threshold=93)
accum = hough_ellipse(edges, accuracy=10, threshold=170, min_size=50)
accum.sort(key=lambda x:x[5])
# Estimated parameters for the ellipse
center_y = int(accum[0][1])
center_x = int(accum[0][2])
xradius = int(accum[0][3])
yradius = int(accum[0][4])
angle = accum[0][5]
center_y = int(accum[-1][0])
center_x = int(accum[-1][1])
xradius = int(accum[-1][2])
yradius = int(accum[-1][3])
angle = np.pi - accum[-1][4]
# Draw the ellipse on the original image
cx, cy = ellipse_perimeter(center_y, center_x,
yradius, xradius, orientation=angle)
image_rgb[cy, cx] = (0, 0, 220)
image_rgb[cy, cx] = (0, 0, 1)
# Draw the edge (white) and the resulting ellipse (red)
edges = color.gray2rgb(edges)
edges[cy, cx] = (250, 0, 0)