Re: objects with their Delaunay graphs overlaid.

It does not bring a big change....

2018-03-14 17:54 GMT+00:00 Thiago Franco Moraes <[email protected]>:

> 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
>>>> _______________________________________________
>>>> SciPy-User mailing list
>>>> [email protected]
>>>> https://mail.python.org/mailman/listinfo/scipy-user
>>>>
>>>
>>> _______________________________________________
>>> SciPy-User mailing list
>>> [email protected]
>>> https://mail.python.org/mailman/listinfo/scipy-user
>>>
>>>
>> _______________________________________________
>> SciPy-User mailing list
>> [email protected]
>> https://mail.python.org/mailman/listinfo/scipy-user
>>
>
> _______________________________________________
> SciPy-User mailing list
> [email protected]
> https://mail.python.org/mailman/listinfo/scipy-user
>
>

_______________________________________________
SciPy-User mailing list
[email protected]
https://mail.python.org/mailman/listinfo/scipy-user