Re: objects with their Delaunay graphs overlaid.

Try to invert the points:

triangles = tri.Triangulation(points[:,1], points[:,0])

On Wed, Mar 14, 2018 at 2:16 PM Franck Kalala Mutombo <[email protected]>
wrote:

> 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 )
> +243(04)844140 411 | +27(0)7646 91608
> skype: franckm4
>
> "*No one knows the future, however, but this does not prevent us to
> project** in it and to act as if we control it*"
>
>
> On 14 March 2018 at 16:42, Thiago Franco Moraes <[email protected]>
> 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 <
>> [email protected]> 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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