On Nov 13, 2017, 14:57 -0700, Stefan van der Walt , wrote:
> On Sun, Nov 12, 2017, at 23:18, Dzung Nguyen wrote:
> > How about labeling manually a dataset for training, then let machine
> > learning do the rest (of course local binary pattern could be used as
> > feature)?
I don’t know your status of knowledge, so I apologize if I state the obvious.
Your issue is that of the co-registration of images.
You have to always decide what your “prime” or “truth” is. How was your “GIS”
data precisely located? How do you know it’s not that which is off? (Even so,
if you
Errm, forgot the link:
https://gis.stackexchange.com/questions/664/whats-the-difference-between-a-projection-and-a-datum
<https://gis.stackexchange.com/questions/664/whats-the-difference-between-a-projection-and-a-datum>
> On Jun 30, 2017, at 10:03, K.-Michael Aye <kmichael..
At least it’s fine for Tritanopians! ;)
Good effort!
Michael
> On May 2, 2017, at 23:09, Stefan van der Walt wrote:
>
> Hi, everyone
>
> It's been bothering me for a while that we have a logo that is not colorblind
> friendly.
>
> E.g., try running scikit-image.org
How about applying a morphological closing operation until an ellipse fit
converges in quality?
With that fish though, maybe need a few “erosion” operations to scrape of those
fins. ;)
The disadvantage of morphological erosion alone is that the size of the object
will be reduced, while the