[SciPy-User] objects with their Delaunay graphs overlaid.

[Franck Kalala Mutombo]

Thank you Thiago,

It is working but the triangulation goes out of the object for some points
and is that I wanted to avoid compare the image I attached.

Best

-
Franck Kalala Mutombo, (PhD. Mathematics )
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On 14 March 2018 at 16:42, Thiago Franco Moraes <tfmoraes at cti.gov.br> wrote:

> You have to use plt.triplot. Also, you can use
> matplotlib.tri.Triangulation to triangulate using the delaunay. Something
> like this:
>
> from matplotlib import pyplot as plt
>
> from skimage.io import imread
> from skimage.feature import corner_harris, corner_subpix, corner_peaks,
> peak_local_max
> import matplotlib.tri as tri
> import matplotlib.pyplot as plt
>
> image = imread("cup.png", as_grey='True')
> points = peak_local_max(corner_harris(image), min_distance=2)
> triangles = tri.Triangulation(points[:,0], points[:,1])
> fig, ax = plt.subplots()
> ax.imshow(image, interpolation='nearest', cmap=plt.cm.gray)
> ax.triplot(triangles)
> plt.show()
>
>
>
>
> On Wed, Mar 14, 2018 at 1:24 PM Franck Kalala <franckkalala at googlemail.com>
> wrote:
>
>> Hello All
>>
>> I am not sure this a good place to ask this. I am just making a try.
>> I have and image and I would like to reproduced the Delaunay graphs
>> overlaid.
>> See the attached image for an idea.
>>
>> I try the following code:
>>
>> from matplotlib import pyplot as plt
>>
>> from skimage.io import imread
>> from skimage.feature import corner_harris, corner_subpix, corner_peaks,
>> peak_local_max
>> from scipy.spatial import Delaunay
>> import matplotlib.pyplot as plt
>>
>> image = imread("cup.png", as_grey='True')
>>
>>
>> #points = corner_peaks(corner_harris(image), min_distance=1)
>> points = peak_local_max(corner_harris(image), min_distance=2)
>> #coords_subpix = corner_subpix(image, coords, window_size=13)
>> tri = Delaunay(points)
>>
>> #imgplot = plt.imshow(image,cmap='gray')
>> #plt.triplot(points[:,0], points[:,1], tri.simplices.copy())
>> #plt.plot(points[:,0], points[:,1], 'o')
>> #plt.show()
>> #print(image)
>>
>> coords = peak_local_max(corner_harris(image), min_distance=2)
>> coords_subpix = corner_subpix(image, coords, window_size=13)
>>
>> fig, ax = plt.subplots()
>> ax.imshow(image, interpolation='nearest', cmap=plt.cm.gray)
>> ax.plot(coords[:, 1], coords[:, 0], '.b', markersize=3)
>> #ax.plot(coords_subpix[:, 1], coords_subpix[:, 0], '+r', markersize=15)
>> #ax.axis((0, 350, 350, 0))
>> plt.show()
>>
>>
>> this code does not help. I attach also the cup image for a try.
>>
>> best
>>
>> franck
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>>
>
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