From jni.soma at gmail.com  Tue May  2 08:48:54 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Tue, 2 May 2017 22:48:54 +1000
Subject: [scikit-image] Using EllipseModel
In-Reply-To: <1493408394.1910667.959749680.43B38704@webmail.messagingengine.com>
References: <C088BAC2-BA60-4515-9A37-FA1E6D8C4319@udel.edu>
 <1493408394.1910667.959749680.43B38704@webmail.messagingengine.com>
Message-ID: <7627dce9-cebb-402b-a5ca-98bc2d925771@Spark>

I?ve raised the issue:
https://github.com/scikit-image/scikit-image/issues/2646

On 29 Apr 2017, 5:40 AM +1000, Stefan van der Walt <stefanv at berkeley.edu>, wrote:
> It may well be that those two functions use opposite directions for theta.? Do you mind filing an issue?
>
> Thanks
> St?fan
>
> On Fri, Apr 28, 2017, at 11:02, Surya Kasturi wrote:
> > Hi,
> >
> > I?m trying to use skimage.measure.EllipseModel to estimate an ellipse around a contour. The results seems to be not so satisfying. I am wondering if I am using ?orientation? parameter correctly.
> >
> > Could anyone please let me know whether ?theta? is in radians or degrees? / I am doing anything wrong?
> >
> > from skimage.measure import EllipseModel
> >
> > # create ellipse model
> > ellipse = EllipseModel()
> > ellipse.estimate(cnt)
> >
> > xc, yc, a, b, theta = np.array(ellipse.params, dtype=int)
> >
> > # find perimeter
> > rr, cc = draw.ellipse_perimeter(xc, yc, a, b, orientation=theta)
> >
> > # plot
> > ax.scatter(cc, rr, s=5, label="EllipseModel?)
> >
> >
> >
> >
> >
> > Thank you,
> > Surya
> >
> > _______________________________________________
> > scikit-image mailing list
> > scikit-image at python.org
> > https://mail.python.org/mailman/listinfo/scikit-image
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
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From jni.soma at gmail.com  Tue May  2 09:12:40 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Tue, 2 May 2017 23:12:40 +1000
Subject: [scikit-image] Segmentation
In-Reply-To: <F99C9807-2A4B-4934-AF20-1184E77C9493@stanford.edu>
References: <F99C9807-2A4B-4934-AF20-1184E77C9493@stanford.edu>
Message-ID: <32cc51df-b168-4362-93c2-6e118001fa70@Spark>

Yes, as you say and as suggested by Brian, I think using the background from the watershed would be the proper way. You could also find the mean intensity of each label and set to background those with a mean intensity below some threshold. The ndimage.labeled_comprehension function should be able to do this:
https://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.labeled_comprehension.html#scipy-ndimage-labeled-comprehension

as well as our own regionprops.

On 26 Apr 2017, 8:01 AM +1000, Cedric Espenel <espenel at stanford.edu>, wrote:
> Hi,
>
> Sorry, I guess I can just mask the result with the watershed segmentation. I guess I wonder if it is the proper way to do it? And also, from your point of view, if it's the way to go to segment these cells or if you think of a better way?
>
> Cedric
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
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From jni.soma at gmail.com  Tue May  2 09:55:06 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Tue, 2 May 2017 23:55:06 +1000
Subject: [scikit-image] Making glare free photo scans
Message-ID: <ccdb8891-ccf4-4402-ab4f-6a55b1c66cad@Spark>

Hi everyone,

I recently saw this blog post from Google and was struck by how easily it could map to scikit-image functions. If anyone wants to make a blog post / gallery example, it would be most welcome. ;)

https://research.googleblog.com/2017/04/photoscan-taking-glare-free-pictures-of.html

Juan.

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From suryak at udel.edu  Tue May  2 10:10:44 2017
From: suryak at udel.edu (Surya Kasturi)
Date: Tue, 2 May 2017 10:10:44 -0400
Subject: [scikit-image] Using EllipseModel
In-Reply-To: <7627dce9-cebb-402b-a5ca-98bc2d925771@Spark>
References: <C088BAC2-BA60-4515-9A37-FA1E6D8C4319@udel.edu>
 <1493408394.1910667.959749680.43B38704@webmail.messagingengine.com>
 <7627dce9-cebb-402b-a5ca-98bc2d925771@Spark>
Message-ID: <7374BB0C-38CD-47FE-8196-8A3170E53DBB@udel.edu>

Hi Juan,

Thanks for raising the ticket. I will look into it and possibly add a small script to reproduce what I?m facing.

Best,
Surya






> On May 2, 2017, at 8:48 AM, Juan Nunez-Iglesias <jni.soma at gmail.com> wrote:
> 
> I?ve raised the issue:
> https://github.com/scikit-image/scikit-image/issues/2646 <https://github.com/scikit-image/scikit-image/issues/2646>
> 
> On 29 Apr 2017, 5:40 AM +1000, Stefan van der Walt <stefanv at berkeley.edu>, wrote:
>> It may well be that those two functions use opposite directions for theta.  Do you mind filing an issue?
>> 
>> Thanks
>> St?fan
>> 
>> On Fri, Apr 28, 2017, at 11:02, Surya Kasturi wrote:
>>> Hi,
>>> 
>>> I?m trying to use skimage.measure.EllipseModel to estimate an ellipse around a contour. The results seems to be not so satisfying. I am wondering if I am using ?orientation? parameter correctly.
>>> 
>>> Could anyone please let me know whether ?theta? is in radians or degrees? / I am doing anything wrong? 
>>> 
>>> from skimage.measure import EllipseModel
>>> 
>>> # create ellipse model
>>> ellipse = EllipseModel()
>>> ellipse.estimate(cnt)
>>> 
>>> xc, yc, a, b, theta = np.array(ellipse.params, dtype=int)
>>> 
>>> # find perimeter
>>> rr, cc = draw.ellipse_perimeter(xc, yc, a, b, orientation=theta)
>>> 
>>> # plot
>>> ax.scatter(cc, rr, s=5, label="EllipseModel?)
>>> 
>>> 
>>> <plt.png>
>>> 
>>> 
>>> Thank you,
>>> Surya
>>> <plt.png>
>>> _______________________________________________
>>> scikit-image mailing list
>>> scikit-image at python.org <mailto:scikit-image at python.org>
>>> https://mail.python.org/mailman/listinfo/scikit-image <https://mail.python.org/mailman/listinfo/scikit-image>
>> _______________________________________________
>> scikit-image mailing list
>> scikit-image at python.org
>> https://mail.python.org/mailman/listinfo/scikit-image

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From suryak at udel.edu  Tue May  2 11:07:26 2017
From: suryak at udel.edu (Surya Kasturi)
Date: Tue, 2 May 2017 11:07:26 -0400
Subject: [scikit-image] Making glare free photo scans
In-Reply-To: <ccdb8891-ccf4-4402-ab4f-6a55b1c66cad@Spark>
References: <ccdb8891-ccf4-4402-ab4f-6a55b1c66cad@Spark>
Message-ID: <56D37769-5671-4D4E-A30C-F681A6F86942@udel.edu>

Looks interesting ? If possible, I?ll take a look during the weekend and update.


Surya






> On May 2, 2017, at 9:55 AM, Juan Nunez-Iglesias <jni.soma at gmail.com> wrote:
> 
> Hi everyone,
> 
> I recently saw this blog post from Google and was struck by how easily it could map to scikit-image functions. If anyone wants to make a blog post / gallery example, it would be most welcome. ;)
> 
> https://research.googleblog.com/2017/04/photoscan-taking-glare-free-pictures-of.html
> 
> Juan.
> 
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image

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From spencergardner at gmail.com  Tue May  2 13:14:18 2017
From: spencergardner at gmail.com (Spencer Gardner)
Date: Tue, 2 May 2017 12:14:18 -0500
Subject: [scikit-image] Help with MCP.goal_reached() in graph module
Message-ID: <CAHCHdbJae4MxeSQnUJpqD5TOYBizqWeAC-zsx3ziTHFVKQLWAw@mail.gmail.com>

The skimage.graph documentation states that the goal_reached method can be
overloaded to introduce additional constraints on finding the minimum cost
path. I'm having some trouble implementing this but I can't find any useful
examples to follow online. I'm hoping someone can provide some guidance.

I need to implement a minimum cost path through an array of costs. The
added twist is that I need to ensure the path does not exceed some maximum
geometric distance (represented as a total number of traversed cells). So I
need my goal_reached() method to check whether the current path has
exceeded the maximum number of cells and return 1 if true (which tells MCP
to stop checking neighbors).

Is there a good example implementation somewhere that I can refer to for
some guidance? I've sketched out a rough outline but I'm not sure I'm on
the right track:

graph = MCP(costSurfaceArray,fully_connected=False)

def goal_reached(index, cumcost):
   '''code to check total distance'''

graph.goal_reached = goal_reached

Thanks for any help!

PS I posted this also on a Google Group that appears to be defunct.
Apologies if that list is actually active and you got a double post from me.
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From zpincus at gmail.com  Tue May  2 15:11:34 2017
From: zpincus at gmail.com (Zach Pincus)
Date: Tue, 2 May 2017 14:11:34 -0500
Subject: [scikit-image] Help with MCP.goal_reached() in graph module
In-Reply-To: <CAHCHdbJae4MxeSQnUJpqD5TOYBizqWeAC-zsx3ziTHFVKQLWAw@mail.gmail.com>
References: <CAHCHdbJae4MxeSQnUJpqD5TOYBizqWeAC-zsx3ziTHFVKQLWAw@mail.gmail.com>
Message-ID: <CAD-Q3rmadVWcQn2RwsFCYioW2kk_ok8bfJy9gCm-H8+dcyOKGQ@mail.gmail.com>

> I need to implement a minimum cost path through an array of costs. The added
> twist is that I need to ensure the path does not exceed some maximum
> geometric distance (represented as a total number of traversed cells). So I
> need my goal_reached() method to check whether the current path has exceeded
> the maximum number of cells and return 1 if true (which tells MCP to stop
> checking neighbors).
>
> Is there a good example implementation somewhere that I can refer to for
> some guidance? I've sketched out a rough outline but I'm not sure I'm on the
> right track:
>
> graph = MCP(costSurfaceArray,fully_connected=False)
>
> def goal_reached(index, cumcost):
>    '''code to check total distance'''
>
> graph.goal_reached = goal_reached

First, note that MCP is implemented in cython, so you can't
monkeypatch goal-reached like you could with a pure-python class.
Instead you have to subclass:

class MyMCP(MCP):
def goal_reached(self, index, cumcost):
print(index, cumcost)
return 0

m = MyMCP(costSurfaceArray)

Second, let's figure out about casting your problem in a way that
goal_reached can address. Here's the documentation for goal_reached:

       """ int goal_reached(int index, float cumcost)
       This method is called each iteration after popping an index
       from the heap, before examining the neighbours.
       This method can be overloaded to modify the behavior of the MCP
       algorithm. An example might be to stop the algorithm when a
       certain cumulative cost is reached, or when the front is a
       certain distance away from the seed point.
       This method should return 1 if the algorithm should not check
       the current point's neighbours and 2 if the algorithm is now
       done.
       """

So basically, the function receives the "current" index (i.e. position
in the array) under consideration, along with the minimum cost to get
there. If the algorithm should not continue this portion of the search
past that index, the function needs to return 1. If the algorithm
should terminate wholesale, return 2.

If all you needed to do was stop searching after you'd gotten a
certain euclidian distance from the starting point, you could
calculate that with just the index and knowledge of the starting
points. However, you want to find out the current path length
terminating in the current index.

For this, you will need to deal with the MCP object's
traceback_offsets attribute, which stores the paths to each point. For
speed reasons, this is only available to subclasses written in cython,
rather than pure-python. So you'll have to write it as a cpdef
function in a cython subclass of MCP.

For the implementation, you'll need to consult how MCP.traceback(self,
end) is implemented, and run the same procedure in goal_reached() to
simply count the length of the path and return 1 if the path exceeds
your acceptable length:

https://github.com/scikit-image/scikit-image/blob/master/skimage/graph/_mcp.pyx#L648

This won't be totally trivial, however. You'll need to understand a
bit of cython, and a bit about how MCP works under the hood: it
doesn't store indices as n-dimensional tuples like (x,y,z) coordinates
or whatever. Instead it stores them as 1-dimensional indices into the
flattened cost array. So much of the logic in the traceback() function
is converting those indices around. Basically you'll just need to
copy-paste traceback() into goal_reached() but instead of
un-flattening the indices to append them to a traceback list, just
count the number of links required to get to a starting point.

Let me know if this helps.

Zach

On Tue, May 2, 2017 at 12:14 PM, Spencer Gardner
<spencergardner at gmail.com> wrote:
> The skimage.graph documentation states that the goal_reached method can be
> overloaded to introduce additional constraints on finding the minimum cost
> path. I'm having some trouble implementing this but I can't find any useful
> examples to follow online. I'm hoping someone can provide some guidance.
>
> I need to implement a minimum cost path through an array of costs. The added
> twist is that I need to ensure the path does not exceed some maximum
> geometric distance (represented as a total number of traversed cells). So I
> need my goal_reached() method to check whether the current path has exceeded
> the maximum number of cells and return 1 if true (which tells MCP to stop
> checking neighbors).
>
> Is there a good example implementation somewhere that I can refer to for
> some guidance? I've sketched out a rough outline but I'm not sure I'm on the
> right track:
>
> graph = MCP(costSurfaceArray,fully_connected=False)
>
> def goal_reached(index, cumcost):
>    '''code to check total distance'''
>
> graph.goal_reached = goal_reached
>
> Thanks for any help!
>
> PS I posted this also on a Google Group that appears to be defunct.
> Apologies if that list is actually active and you got a double post from me.
>
>
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
>

From spencergardner at gmail.com  Tue May  2 15:43:37 2017
From: spencergardner at gmail.com (Spencer Gardner)
Date: Tue, 2 May 2017 14:43:37 -0500
Subject: [scikit-image] Help with MCP.goal_reached() in graph module
In-Reply-To: <CAD-Q3rmadVWcQn2RwsFCYioW2kk_ok8bfJy9gCm-H8+dcyOKGQ@mail.gmail.com>
References: <CAHCHdbJae4MxeSQnUJpqD5TOYBizqWeAC-zsx3ziTHFVKQLWAw@mail.gmail.com>
 <CAD-Q3rmadVWcQn2RwsFCYioW2kk_ok8bfJy9gCm-H8+dcyOKGQ@mail.gmail.com>
Message-ID: <CAHCHdbL+gGDS8MWgQ+m=C1WqiCWJRD3Y0XgJaBL81Cs6r8JbiQ@mail.gmail.com>

Thanks. That's extremely helpful. I think I'll be able to work out the
subclassing. I've never worked in cython but there's a first time for
everything.

Is there some alternative solution to my problem that I've missed? I've
scoured the documentation from various software projects (GIS and non-GIS)
to try to find something that implements an algorithm like this but I
haven't come across anything. This seems odd to me, since it's a problem I
assume others have had to solve before.

In any case, I'm sure I'll be back with more questions as I dive in.

Spencer

On Tue, May 2, 2017 at 2:11 PM, Zach Pincus <zpincus at gmail.com> wrote:

> > I need to implement a minimum cost path through an array of costs. The
> added
> > twist is that I need to ensure the path does not exceed some maximum
> > geometric distance (represented as a total number of traversed cells).
> So I
> > need my goal_reached() method to check whether the current path has
> exceeded
> > the maximum number of cells and return 1 if true (which tells MCP to stop
> > checking neighbors).
> >
> > Is there a good example implementation somewhere that I can refer to for
> > some guidance? I've sketched out a rough outline but I'm not sure I'm on
> the
> > right track:
> >
> > graph = MCP(costSurfaceArray,fully_connected=False)
> >
> > def goal_reached(index, cumcost):
> >    '''code to check total distance'''
> >
> > graph.goal_reached = goal_reached
>
> First, note that MCP is implemented in cython, so you can't
> monkeypatch goal-reached like you could with a pure-python class.
> Instead you have to subclass:
>
> class MyMCP(MCP):
> def goal_reached(self, index, cumcost):
> print(index, cumcost)
> return 0
>
> m = MyMCP(costSurfaceArray)
>
> Second, let's figure out about casting your problem in a way that
> goal_reached can address. Here's the documentation for goal_reached:
>
>        """ int goal_reached(int index, float cumcost)
>        This method is called each iteration after popping an index
>        from the heap, before examining the neighbours.
>        This method can be overloaded to modify the behavior of the MCP
>        algorithm. An example might be to stop the algorithm when a
>        certain cumulative cost is reached, or when the front is a
>        certain distance away from the seed point.
>        This method should return 1 if the algorithm should not check
>        the current point's neighbours and 2 if the algorithm is now
>        done.
>        """
>
> So basically, the function receives the "current" index (i.e. position
> in the array) under consideration, along with the minimum cost to get
> there. If the algorithm should not continue this portion of the search
> past that index, the function needs to return 1. If the algorithm
> should terminate wholesale, return 2.
>
> If all you needed to do was stop searching after you'd gotten a
> certain euclidian distance from the starting point, you could
> calculate that with just the index and knowledge of the starting
> points. However, you want to find out the current path length
> terminating in the current index.
>
> For this, you will need to deal with the MCP object's
> traceback_offsets attribute, which stores the paths to each point. For
> speed reasons, this is only available to subclasses written in cython,
> rather than pure-python. So you'll have to write it as a cpdef
> function in a cython subclass of MCP.
>
> For the implementation, you'll need to consult how MCP.traceback(self,
> end) is implemented, and run the same procedure in goal_reached() to
> simply count the length of the path and return 1 if the path exceeds
> your acceptable length:
>
> https://github.com/scikit-image/scikit-image/blob/
> master/skimage/graph/_mcp.pyx#L648
>
> This won't be totally trivial, however. You'll need to understand a
> bit of cython, and a bit about how MCP works under the hood: it
> doesn't store indices as n-dimensional tuples like (x,y,z) coordinates
> or whatever. Instead it stores them as 1-dimensional indices into the
> flattened cost array. So much of the logic in the traceback() function
> is converting those indices around. Basically you'll just need to
> copy-paste traceback() into goal_reached() but instead of
> un-flattening the indices to append them to a traceback list, just
> count the number of links required to get to a starting point.
>
> Let me know if this helps.
>
> Zach
>
> On Tue, May 2, 2017 at 12:14 PM, Spencer Gardner
> <spencergardner at gmail.com> wrote:
> > The skimage.graph documentation states that the goal_reached method can
> be
> > overloaded to introduce additional constraints on finding the minimum
> cost
> > path. I'm having some trouble implementing this but I can't find any
> useful
> > examples to follow online. I'm hoping someone can provide some guidance.
> >
> > I need to implement a minimum cost path through an array of costs. The
> added
> > twist is that I need to ensure the path does not exceed some maximum
> > geometric distance (represented as a total number of traversed cells).
> So I
> > need my goal_reached() method to check whether the current path has
> exceeded
> > the maximum number of cells and return 1 if true (which tells MCP to stop
> > checking neighbors).
> >
> > Is there a good example implementation somewhere that I can refer to for
> > some guidance? I've sketched out a rough outline but I'm not sure I'm on
> the
> > right track:
> >
> > graph = MCP(costSurfaceArray,fully_connected=False)
> >
> > def goal_reached(index, cumcost):
> >    '''code to check total distance'''
> >
> > graph.goal_reached = goal_reached
> >
> > Thanks for any help!
> >
> > PS I posted this also on a Google Group that appears to be defunct.
> > Apologies if that list is actually active and you got a double post from
> me.
> >
> >
> > _______________________________________________
> > scikit-image mailing list
> > scikit-image at python.org
> > https://mail.python.org/mailman/listinfo/scikit-image
> >
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
>
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From zpincus at gmail.com  Tue May  2 16:01:58 2017
From: zpincus at gmail.com (Zach Pincus)
Date: Tue, 2 May 2017 15:01:58 -0500
Subject: [scikit-image] Help with MCP.goal_reached() in graph module
In-Reply-To: <CAHCHdbL+gGDS8MWgQ+m=C1WqiCWJRD3Y0XgJaBL81Cs6r8JbiQ@mail.gmail.com>
References: <CAHCHdbJae4MxeSQnUJpqD5TOYBizqWeAC-zsx3ziTHFVKQLWAw@mail.gmail.com>
 <CAD-Q3rmadVWcQn2RwsFCYioW2kk_ok8bfJy9gCm-H8+dcyOKGQ@mail.gmail.com>
 <CAHCHdbL+gGDS8MWgQ+m=C1WqiCWJRD3Y0XgJaBL81Cs6r8JbiQ@mail.gmail.com>
Message-ID: <CAD-Q3r=Zz+-i_UDUY0taPYimcmfYJVRNzqPR4ceQ-rS+b31n-A@mail.gmail.com>

I can't think of any alternatives off the top of my head. The usual
solution is to incorporate everything into your cost function, instead
of having two separate stopping criteria -- most problems lend
themselves to this pretty well.

And actually, now that I think of it: Dijkstra's algorithm (which is
all this graph traversal is running) fails with non-monotonic cost
functions. Since the algorithm only visits a given position one time
(on the minimum cost path), a shorter but more expensive path to the
same point will not be considered, even if that is part of the path
that gives a global optimum on your "minimum cost path below a certain
length" problem. It would be a good advanced algorithms problem set
question to consider if optimal solutions to that problem will
necessarily be exponential in complexity.

So that's why people usually try to blend their cost considerations
into a single cost for traversing each node...

That said, you might get OK solutions from this modified algorithm,
though there will be no guarantee of global optimality.

I can also think of one awful hack you could try to just see how well
it works. You could "store" the number of steps in the cumulative cost
by defining a custom travel_cost function.
https://github.com/scikit-image/scikit-image/blob/master/skimage/graph/_mcp.pyx#L885

Let's assume that your "actual" costs are all >> 1. Then, instead of
returning new_cost, you return new_cost + 0.001. Then goal_reached
could count the number of steps by just looking at the value of the
cumulative cost after the decimal point.

Again, this is gross, and there are lots of cases where it won't work
or will blow up badly. But for reasonably small maximum path lengths,
it should be OK. Also, for speed you'll still need to implement this
in a cython subclass. But you can use MCP_Flexible to proof out the
implementation in slow pure python.




On Tue, May 2, 2017 at 2:43 PM, Spencer Gardner
<spencergardner at gmail.com> wrote:
> Thanks. That's extremely helpful. I think I'll be able to work out the
> subclassing. I've never worked in cython but there's a first time for
> everything.
>
> Is there some alternative solution to my problem that I've missed? I've
> scoured the documentation from various software projects (GIS and non-GIS)
> to try to find something that implements an algorithm like this but I
> haven't come across anything. This seems odd to me, since it's a problem I
> assume others have had to solve before.
>
> In any case, I'm sure I'll be back with more questions as I dive in.
>
> Spencer
>
> On Tue, May 2, 2017 at 2:11 PM, Zach Pincus <zpincus at gmail.com> wrote:
>>
>> > I need to implement a minimum cost path through an array of costs. The
>> > added
>> > twist is that I need to ensure the path does not exceed some maximum
>> > geometric distance (represented as a total number of traversed cells).
>> > So I
>> > need my goal_reached() method to check whether the current path has
>> > exceeded
>> > the maximum number of cells and return 1 if true (which tells MCP to
>> > stop
>> > checking neighbors).
>> >
>> > Is there a good example implementation somewhere that I can refer to for
>> > some guidance? I've sketched out a rough outline but I'm not sure I'm on
>> > the
>> > right track:
>> >
>> > graph = MCP(costSurfaceArray,fully_connected=False)
>> >
>> > def goal_reached(index, cumcost):
>> >    '''code to check total distance'''
>> >
>> > graph.goal_reached = goal_reached
>>
>> First, note that MCP is implemented in cython, so you can't
>> monkeypatch goal-reached like you could with a pure-python class.
>> Instead you have to subclass:
>>
>> class MyMCP(MCP):
>> def goal_reached(self, index, cumcost):
>> print(index, cumcost)
>> return 0
>>
>> m = MyMCP(costSurfaceArray)
>>
>> Second, let's figure out about casting your problem in a way that
>> goal_reached can address. Here's the documentation for goal_reached:
>>
>>        """ int goal_reached(int index, float cumcost)
>>        This method is called each iteration after popping an index
>>        from the heap, before examining the neighbours.
>>        This method can be overloaded to modify the behavior of the MCP
>>        algorithm. An example might be to stop the algorithm when a
>>        certain cumulative cost is reached, or when the front is a
>>        certain distance away from the seed point.
>>        This method should return 1 if the algorithm should not check
>>        the current point's neighbours and 2 if the algorithm is now
>>        done.
>>        """
>>
>> So basically, the function receives the "current" index (i.e. position
>> in the array) under consideration, along with the minimum cost to get
>> there. If the algorithm should not continue this portion of the search
>> past that index, the function needs to return 1. If the algorithm
>> should terminate wholesale, return 2.
>>
>> If all you needed to do was stop searching after you'd gotten a
>> certain euclidian distance from the starting point, you could
>> calculate that with just the index and knowledge of the starting
>> points. However, you want to find out the current path length
>> terminating in the current index.
>>
>> For this, you will need to deal with the MCP object's
>> traceback_offsets attribute, which stores the paths to each point. For
>> speed reasons, this is only available to subclasses written in cython,
>> rather than pure-python. So you'll have to write it as a cpdef
>> function in a cython subclass of MCP.
>>
>> For the implementation, you'll need to consult how MCP.traceback(self,
>> end) is implemented, and run the same procedure in goal_reached() to
>> simply count the length of the path and return 1 if the path exceeds
>> your acceptable length:
>>
>>
>> https://github.com/scikit-image/scikit-image/blob/master/skimage/graph/_mcp.pyx#L648
>>
>> This won't be totally trivial, however. You'll need to understand a
>> bit of cython, and a bit about how MCP works under the hood: it
>> doesn't store indices as n-dimensional tuples like (x,y,z) coordinates
>> or whatever. Instead it stores them as 1-dimensional indices into the
>> flattened cost array. So much of the logic in the traceback() function
>> is converting those indices around. Basically you'll just need to
>> copy-paste traceback() into goal_reached() but instead of
>> un-flattening the indices to append them to a traceback list, just
>> count the number of links required to get to a starting point.
>>
>> Let me know if this helps.
>>
>> Zach
>>
>> On Tue, May 2, 2017 at 12:14 PM, Spencer Gardner
>> <spencergardner at gmail.com> wrote:
>> > The skimage.graph documentation states that the goal_reached method can
>> > be
>> > overloaded to introduce additional constraints on finding the minimum
>> > cost
>> > path. I'm having some trouble implementing this but I can't find any
>> > useful
>> > examples to follow online. I'm hoping someone can provide some guidance.
>> >
>> > I need to implement a minimum cost path through an array of costs. The
>> > added
>> > twist is that I need to ensure the path does not exceed some maximum
>> > geometric distance (represented as a total number of traversed cells).
>> > So I
>> > need my goal_reached() method to check whether the current path has
>> > exceeded
>> > the maximum number of cells and return 1 if true (which tells MCP to
>> > stop
>> > checking neighbors).
>> >
>> > Is there a good example implementation somewhere that I can refer to for
>> > some guidance? I've sketched out a rough outline but I'm not sure I'm on
>> > the
>> > right track:
>> >
>> > graph = MCP(costSurfaceArray,fully_connected=False)
>> >
>> > def goal_reached(index, cumcost):
>> >    '''code to check total distance'''
>> >
>> > graph.goal_reached = goal_reached
>> >
>> > Thanks for any help!
>> >
>> > PS I posted this also on a Google Group that appears to be defunct.
>> > Apologies if that list is actually active and you got a double post from
>> > me.
>> >
>> >
>> > _______________________________________________
>> > scikit-image mailing list
>> > scikit-image at python.org
>> > https://mail.python.org/mailman/listinfo/scikit-image
>> >
>> _______________________________________________
>> scikit-image mailing list
>> scikit-image at python.org
>> https://mail.python.org/mailman/listinfo/scikit-image
>
>
>
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
>

From spencergardner at gmail.com  Tue May  2 17:40:00 2017
From: spencergardner at gmail.com (Spencer Gardner)
Date: Tue, 2 May 2017 16:40:00 -0500
Subject: [scikit-image] Help with MCP.goal_reached() in graph module
In-Reply-To: <CAD-Q3r=Zz+-i_UDUY0taPYimcmfYJVRNzqPR4ceQ-rS+b31n-A@mail.gmail.com>
References: <CAHCHdbJae4MxeSQnUJpqD5TOYBizqWeAC-zsx3ziTHFVKQLWAw@mail.gmail.com>
 <CAD-Q3rmadVWcQn2RwsFCYioW2kk_ok8bfJy9gCm-H8+dcyOKGQ@mail.gmail.com>
 <CAHCHdbL+gGDS8MWgQ+m=C1WqiCWJRD3Y0XgJaBL81Cs6r8JbiQ@mail.gmail.com>
 <CAD-Q3r=Zz+-i_UDUY0taPYimcmfYJVRNzqPR4ceQ-rS+b31n-A@mail.gmail.com>
Message-ID: <CAHCHdb+gq+72UBgEtArMpRt-EAYyeob4VA0vFmw-1pB3jVh8Wg@mail.gmail.com>

Good point. Hadn't thought about the monotonic problem with Dijkstra. My
problem is I need the costs to represent considerations other than pure
distance but my ultimate outcome must be constrained by a total distance,
so there's not really a good way that I can see to fold them together.

One strategy I've been planning to investigate is developing an
unconstrained cumulative cost matrix for each origin point and each
destination point and then sum the O + D matrices to get the total route
cost for the pair at every matrix coordinate. I'm not completely sure how I
can use that to identify a route within my distance constraints but I think
it might be a promising option.

On Tue, May 2, 2017 at 3:01 PM, Zach Pincus <zpincus at gmail.com> wrote:

> I can't think of any alternatives off the top of my head. The usual
> solution is to incorporate everything into your cost function, instead
> of having two separate stopping criteria -- most problems lend
> themselves to this pretty well.
>
> And actually, now that I think of it: Dijkstra's algorithm (which is
> all this graph traversal is running) fails with non-monotonic cost
> functions. Since the algorithm only visits a given position one time
> (on the minimum cost path), a shorter but more expensive path to the
> same point will not be considered, even if that is part of the path
> that gives a global optimum on your "minimum cost path below a certain
> length" problem. It would be a good advanced algorithms problem set
> question to consider if optimal solutions to that problem will
> necessarily be exponential in complexity.
>
> So that's why people usually try to blend their cost considerations
> into a single cost for traversing each node...
>
> That said, you might get OK solutions from this modified algorithm,
> though there will be no guarantee of global optimality.
>
> I can also think of one awful hack you could try to just see how well
> it works. You could "store" the number of steps in the cumulative cost
> by defining a custom travel_cost function.
> https://github.com/scikit-image/scikit-image/blob/
> master/skimage/graph/_mcp.pyx#L885
>
> Let's assume that your "actual" costs are all >> 1. Then, instead of
> returning new_cost, you return new_cost + 0.001. Then goal_reached
> could count the number of steps by just looking at the value of the
> cumulative cost after the decimal point.
>
> Again, this is gross, and there are lots of cases where it won't work
> or will blow up badly. But for reasonably small maximum path lengths,
> it should be OK. Also, for speed you'll still need to implement this
> in a cython subclass. But you can use MCP_Flexible to proof out the
> implementation in slow pure python.
>
>
>
>
> On Tue, May 2, 2017 at 2:43 PM, Spencer Gardner
> <spencergardner at gmail.com> wrote:
> > Thanks. That's extremely helpful. I think I'll be able to work out the
> > subclassing. I've never worked in cython but there's a first time for
> > everything.
> >
> > Is there some alternative solution to my problem that I've missed? I've
> > scoured the documentation from various software projects (GIS and
> non-GIS)
> > to try to find something that implements an algorithm like this but I
> > haven't come across anything. This seems odd to me, since it's a problem
> I
> > assume others have had to solve before.
> >
> > In any case, I'm sure I'll be back with more questions as I dive in.
> >
> > Spencer
> >
> > On Tue, May 2, 2017 at 2:11 PM, Zach Pincus <zpincus at gmail.com> wrote:
> >>
> >> > I need to implement a minimum cost path through an array of costs. The
> >> > added
> >> > twist is that I need to ensure the path does not exceed some maximum
> >> > geometric distance (represented as a total number of traversed cells).
> >> > So I
> >> > need my goal_reached() method to check whether the current path has
> >> > exceeded
> >> > the maximum number of cells and return 1 if true (which tells MCP to
> >> > stop
> >> > checking neighbors).
> >> >
> >> > Is there a good example implementation somewhere that I can refer to
> for
> >> > some guidance? I've sketched out a rough outline but I'm not sure I'm
> on
> >> > the
> >> > right track:
> >> >
> >> > graph = MCP(costSurfaceArray,fully_connected=False)
> >> >
> >> > def goal_reached(index, cumcost):
> >> >    '''code to check total distance'''
> >> >
> >> > graph.goal_reached = goal_reached
> >>
> >> First, note that MCP is implemented in cython, so you can't
> >> monkeypatch goal-reached like you could with a pure-python class.
> >> Instead you have to subclass:
> >>
> >> class MyMCP(MCP):
> >> def goal_reached(self, index, cumcost):
> >> print(index, cumcost)
> >> return 0
> >>
> >> m = MyMCP(costSurfaceArray)
> >>
> >> Second, let's figure out about casting your problem in a way that
> >> goal_reached can address. Here's the documentation for goal_reached:
> >>
> >>        """ int goal_reached(int index, float cumcost)
> >>        This method is called each iteration after popping an index
> >>        from the heap, before examining the neighbours.
> >>        This method can be overloaded to modify the behavior of the MCP
> >>        algorithm. An example might be to stop the algorithm when a
> >>        certain cumulative cost is reached, or when the front is a
> >>        certain distance away from the seed point.
> >>        This method should return 1 if the algorithm should not check
> >>        the current point's neighbours and 2 if the algorithm is now
> >>        done.
> >>        """
> >>
> >> So basically, the function receives the "current" index (i.e. position
> >> in the array) under consideration, along with the minimum cost to get
> >> there. If the algorithm should not continue this portion of the search
> >> past that index, the function needs to return 1. If the algorithm
> >> should terminate wholesale, return 2.
> >>
> >> If all you needed to do was stop searching after you'd gotten a
> >> certain euclidian distance from the starting point, you could
> >> calculate that with just the index and knowledge of the starting
> >> points. However, you want to find out the current path length
> >> terminating in the current index.
> >>
> >> For this, you will need to deal with the MCP object's
> >> traceback_offsets attribute, which stores the paths to each point. For
> >> speed reasons, this is only available to subclasses written in cython,
> >> rather than pure-python. So you'll have to write it as a cpdef
> >> function in a cython subclass of MCP.
> >>
> >> For the implementation, you'll need to consult how MCP.traceback(self,
> >> end) is implemented, and run the same procedure in goal_reached() to
> >> simply count the length of the path and return 1 if the path exceeds
> >> your acceptable length:
> >>
> >>
> >> https://github.com/scikit-image/scikit-image/blob/
> master/skimage/graph/_mcp.pyx#L648
> >>
> >> This won't be totally trivial, however. You'll need to understand a
> >> bit of cython, and a bit about how MCP works under the hood: it
> >> doesn't store indices as n-dimensional tuples like (x,y,z) coordinates
> >> or whatever. Instead it stores them as 1-dimensional indices into the
> >> flattened cost array. So much of the logic in the traceback() function
> >> is converting those indices around. Basically you'll just need to
> >> copy-paste traceback() into goal_reached() but instead of
> >> un-flattening the indices to append them to a traceback list, just
> >> count the number of links required to get to a starting point.
> >>
> >> Let me know if this helps.
> >>
> >> Zach
> >>
> >> On Tue, May 2, 2017 at 12:14 PM, Spencer Gardner
> >> <spencergardner at gmail.com> wrote:
> >> > The skimage.graph documentation states that the goal_reached method
> can
> >> > be
> >> > overloaded to introduce additional constraints on finding the minimum
> >> > cost
> >> > path. I'm having some trouble implementing this but I can't find any
> >> > useful
> >> > examples to follow online. I'm hoping someone can provide some
> guidance.
> >> >
> >> > I need to implement a minimum cost path through an array of costs. The
> >> > added
> >> > twist is that I need to ensure the path does not exceed some maximum
> >> > geometric distance (represented as a total number of traversed cells).
> >> > So I
> >> > need my goal_reached() method to check whether the current path has
> >> > exceeded
> >> > the maximum number of cells and return 1 if true (which tells MCP to
> >> > stop
> >> > checking neighbors).
> >> >
> >> > Is there a good example implementation somewhere that I can refer to
> for
> >> > some guidance? I've sketched out a rough outline but I'm not sure I'm
> on
> >> > the
> >> > right track:
> >> >
> >> > graph = MCP(costSurfaceArray,fully_connected=False)
> >> >
> >> > def goal_reached(index, cumcost):
> >> >    '''code to check total distance'''
> >> >
> >> > graph.goal_reached = goal_reached
> >> >
> >> > Thanks for any help!
> >> >
> >> > PS I posted this also on a Google Group that appears to be defunct.
> >> > Apologies if that list is actually active and you got a double post
> from
> >> > me.
> >> >
> >> >
> >> > _______________________________________________
> >> > scikit-image mailing list
> >> > scikit-image at python.org
> >> > https://mail.python.org/mailman/listinfo/scikit-image
> >> >
> >> _______________________________________________
> >> scikit-image mailing list
> >> scikit-image at python.org
> >> https://mail.python.org/mailman/listinfo/scikit-image
> >
> >
> >
> > _______________________________________________
> > scikit-image mailing list
> > scikit-image at python.org
> > https://mail.python.org/mailman/listinfo/scikit-image
> >
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
>
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From stefanv at berkeley.edu  Wed May  3 01:09:56 2017
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Tue, 02 May 2017 22:09:56 -0700
Subject: [scikit-image] New logo?
Message-ID: <1493788196.2624908.963956384.603B1279@webmail.messagingengine.com>

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 through

https://www.toptal.com/designers/colorfilter

:/

*I challenge you to submit a new logo, and a hexagonal sticker [0] that
we can print for SciPy 2017.** *
I will print and ship stickers of the (community) chosen design to
anyone who contributes a design of their own.
Fire up Inkscape [1], and let's see you work your magic!
St?fan


[0] http://hexb.in/sticker.html
[1] https://github.com/terinjokes/StickerConstructorSpec/blob/master/assets/hexagonal-sticker_template.svg
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From kmichael.aye at gmail.com  Wed May  3 01:23:58 2017
From: kmichael.aye at gmail.com (K.-Michael Aye)
Date: Tue, 2 May 2017 23:23:58 -0600
Subject: [scikit-image] New logo?
In-Reply-To: <1493788196.2624908.963956384.603B1279@webmail.messagingengine.com>
References: <1493788196.2624908.963956384.603B1279@webmail.messagingengine.com>
Message-ID: <D011FA9E-F61C-4985-BA76-05E1AE05ED23@gmail.com>

At least it?s fine for Tritanopians! ;)

Good effort!

Michael

> On May 2, 2017, at 23:09, Stefan van der Walt <stefanv at berkeley.edu> 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 through
> 
> https://www.toptal.com/designers/colorfilter
> 
> :/
> 
> I challenge you to submit a new logo, and a hexagonal sticker [0] that we can print for SciPy 2017.
> 
> I will print and ship stickers of the (community) chosen design to anyone who contributes a design of their own.
> 
> Fire up Inkscape [1], and let's see you work your magic!
> St?fan
> 
> 
> [0] http://hexb.in/sticker.html
> [1] https://github.com/terinjokes/StickerConstructorSpec/blob/master/assets/hexagonal-sticker_template.svg
> 
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image


From noflaco at gmail.com  Sat May 13 22:44:50 2017
From: noflaco at gmail.com (Carlton Banks)
Date: Sun, 14 May 2017 04:44:50 +0200
Subject: [scikit-image] Storing a plot into a bumpy array such that it can
 be used for pattern recognition...
Message-ID: <8B63BF09-B9D2-4FFF-83C8-3F3A90198BF5@gmail.com>

I seem to have some problems storing a plot created using matplotlib.pcolormesh().
As far i know is pcolormesh convert an input data matrix given a colormap,
and the colormap gives a RGB values for each entries in matrix and plots it. 

Which in my head would be similar to 


    import numpy as np
    import matplotlib.pyplot as plt
    import matplotlib
    from PIL import Image
    import librosa
    import librosa.display
    from matplotlib import cm
    
    
    fig = plt.figure(figsize=(12,4))
    min = -1.828067
    max = 22.70058
    data =  np.random.uniform(low=min, high=max, size=(474,40))
    librosa.display.specshow(data.T,sr=16000,x_axis='frames',y_axis='mel',hop_length=160,cmap=cm.jet)
    plt.axis('off')
    plt.show()
    raw_input("sadas")
    
    convert = plt.get_cmap(cm.jet)
    norm = matplotlib.colors.Normalize(vmin=0,vmax=1)
    numpy_output_static = convert(norm(data.T))
    plt.imshow(numpy_output_static,cmap = cm.jet, aspect = 'auto')
    plt.show()
    raw_input("asds?)



Problem here is I need to store as a numpy array, and the data has to represent the plot as the array is being used as an input for a NN, in which input matters, and won't be able learn anything if the input doesn't resemble or show the same patterns which the NN has to learn. 

So how do make it store the actual plot, and keep the dimensions of data that used to make the plot. 

You may notice I am using librosa to make the plot above. 
Librosa basically do a pcolormesh plot, in which the argument only set the x-axis and y-axis , and scale them to the proper size. 
here is the actual source code: https://github.com/librosa/librosa/blob/master/librosa/display.py#L459 <https://github.com/librosa/librosa/blob/master/librosa/display.py#L459>

Here is the first image: 
Here is the second image: 
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From jesukirann at gmail.com  Mon May 15 05:48:14 2017
From: jesukirann at gmail.com (Jesu Kiran Spurgen)
Date: Mon, 15 May 2017 11:48:14 +0200
Subject: [scikit-image] Reg: Working to create an ROI interactively and then
 find contours.
Message-ID: <CAF-ggc4MzbYSQe009FGbcQ503hP9YHOwqo5_eC6UPrE4Nyvr1w@mail.gmail.com>

Dear Experts,

I have been able to successfully find the contours on an entire image.


However,I am more interested to define an ROI interactively and then find
the
contours for it, whilst preserving the other parts of the image without any
contour-finding.


This is what I'd like to do:

    * Create the ROI interactively for the input image

    * Find contours on that ROI (without cropping the ROI away from the
rest of image)

    * Other parts (which are not in the ROI) should remain untouched.


*Link1:* The link I used to find the interactive rectangle is:

http://stackoverflow.com/questions/21696097/how-can-i-make-a-draggable-adjustable-roi-in-opencv-python/21696862#21696862

To find contours, I use OpenCV.


Any suggestions/help/code would be great! Thanks,

P.S: Sorry for these questions, but I would be ever grateful for a gentle
and kind reply. I am new to OpenCV and SciKit, hence this question. Many
thanks!

Looking forward for your kind response. Please kindly let me know if I
could provide with more information.

Best Regards,
Kiran
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From imagepy at sina.com  Mon May 15 05:52:15 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Mon, 15 May 2017 17:52:15 +0800
Subject: [scikit-image] =?gbk?b?u9i4tDogUmVnOiBXb3JraW5nIHRvIGNyZWF0ZSBh?=
 =?gbk?q?n_ROI_interactively_and_then_find_contours=2E?=
Message-ID: <20170515095215.E04194C0ABA@webmail.sinamail.sina.com.cn>

https://github.com/yxdragon/imagepy

--------------------------------
my project. have a look. make scikitimage like photoshop!


-------- ???? --------

???:Jesu Kiran Spurgen
??????:2017?5?15? 17:48(???)
???:scikit-image at python.org
??:[scikit-image] Reg: Working to create an ROI interactively and then find contours.
Dear Experts,
I have been able to successfully find the contours on an entire image.??
However,I am more interested to define an ROI interactively and then find thecontours for it, whilst preserving the other parts of the image without anycontour-finding.
?This is what I&#39;d like to do:
? ? * Create the ROI interactively for the input image? ??? ? * Find contours on that ROI (without cropping the ROI away from the rest of image)? ??? ? * Other parts (which are not in the ROI) should remain untouched.?

Link1: The link I used to find the interactive rectangle is:
http://stackoverflow.com/questions/21696097/how-can-i-make-a-draggable-adjustable-roi-in-opencv-python/21696862#21696862

To find contours, I use OpenCV.?

Any suggestions/help/code would be great! Thanks,
P.S: Sorry for these questions, but I would be ever grateful for a gentle and kind reply. I am new to OpenCV and SciKit, hence this question. Many thanks!
Looking forward for your kind response. Please kindly let me know if I could provide with more information.
Best Regards,Kiran

_______________________________________________
scikit-image mailing list
scikit-image at python.org
https://mail.python.org/mailman/listinfo/scikit-image
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From imagepy at sina.com  Mon May 15 06:01:08 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Mon, 15 May 2017 18:01:08 +0800
Subject: [scikit-image] =?gbk?b?u9i4tKO6IFJlZzogV29ya2luZyB0byBjcmVhdGUg?=
 =?gbk?q?an_ROI_interactively_and_then_find_contours=2E?=
Message-ID: <20170515100108.B503238053E@webmail.sinamail.sina.com.cn>

It can wrap any function based on numpy, (spicy, scikit-image, opencv, itk ...). This framework can generate interactive dialog automatically acrroding your function's parameter. and support roi, mask, undo. You just need to care your function! It can run on win, Mac, linux under py2.7 or py3x now! (I just make a framework like ImageJ, but more flexable)
----- ???? -----
????Jesu Kiran Spurgen <jesukirann at gmail.com>
????scikit-image at python.org
???[scikit-image] Reg: Working to create an ROI interactively and then find contours.
???2017?05?15? 17?48?

Dear Experts,
I have been able to successfully find the contours on an entire image.  
However,I am more interested to define an ROI interactively and then find thecontours for it, whilst preserving the other parts of the image without anycontour-finding.
 This is what I'd like to do:
    * Create the ROI interactively for the input image        * Find contours on that ROI (without cropping the ROI away from the rest of image)        * Other parts (which are not in the ROI) should remain untouched. 

Link1: The link I used to find the interactive rectangle is:
http://stackoverflow.com/questions/21696097/how-can-i-make-a-draggable-adjustable-roi-in-opencv-python/21696862#21696862

To find contours, I use OpenCV. 

Any suggestions/help/code would be great! Thanks,
P.S: Sorry for these questions, but I would be ever grateful for a gentle and kind reply. I am new to OpenCV and SciKit, hence this question. Many thanks!
Looking forward for your kind response. Please kindly let me know if I could provide with more information.
Best Regards,Kiran

_______________________________________________
scikit-image mailing list
scikit-image at python.org
https://mail.python.org/mailman/listinfo/scikit-image
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From imagepy at sina.com  Wed May 17 23:07:32 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Thu, 18 May 2017 11:07:32 +0800
Subject: [scikit-image] build topograph network from skeleton
Message-ID: <20170518030732.8F705380546@webmail.sinamail.sina.com.cn>

 Hi everyone:    I saw the newest version, require the networkx module. I find some function to find shortest path from image. But I want to know if there is a method to build a network from a skeleton image(2D/3D with arcs and nodes). I wrote one, but in python. it runs very slowly...                                       yxdragon-imagepy
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From leenagour at gmail.com  Thu May 18 00:04:36 2017
From: leenagour at gmail.com (Leena Chourey)
Date: Thu, 18 May 2017 09:34:36 +0530
Subject: [scikit-image] Need help to get graph from image
Message-ID: <CAD-S5bNzjkWiNATs2Kjq=ud3mM9COD6TmSuF=zqqafetjLZERA@mail.gmail.com>

Dear All,

I need to convert shape based image(graph_search2.jpg) into graph and then
graph data structure. I have tried to filter the image and then with
threshold, contour based approach access shapes(nodes), lines(edges) and
arrows. but facing difficulty in getting relation b/w nodes and edges.
Please help to find interest point(interest_points.jpg) and relation in
node n edges.

-- 
Thanks & Regards, -???????
Leena Chourey , ???? ????
C-DAC Mumbai ??-???, ??????
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From imagepy at sina.com  Thu May 18 01:12:05 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Thu, 18 May 2017 13:12:05 +0800
Subject: [scikit-image] =?gbk?q?=BB=D8=B8=B4=3A_Need_help_to_get_graph_fr?=
 =?gbk?q?om_image?=
Message-ID: <20170518051205.E2735380546@webmail.sinamail.sina.com.cn>

1. you can do a skeleton, then use a np.ones((3,3)) to convolve. then 3 means junction, one means termin. 2 means path.2. trace from a termin. iterate all the pixel > 0. and add node if != 2!
some tips:1. if you do skeleton straightly, you will get some small branch, you can remove them by graph analysis. but I have a tip, you can do a gauss blur, then threshold again. this will smooth the binary image.2. trace the path is not very simple, you need care many detail... you can look mine.3. the scikit-image's skeleton method prefers to generate branch (sometimes we want, but here we need not), you can look here.
you can have a try my project imagery do some test. which can wrap scikit-image like photoshop!(but I do not know if scikit-image has a method to build the skeleton)
My English is solo, forgive me.														YXDragon - ImagePy--------------------------------????????android???-------- ???? --------???:Leena Chourey?    ?:2017?5?18? 12:05(???)???:scikit-image at python.org??:[scikit-image] Need help to get graph from imageDear All,I need to convert shape based image(graph_search2.jpg) into graph and then graph data structure. I have tried to filter the image and then with threshold, contour based approach access shapes(nodes), lines(edges) and arrows. but facing difficulty in getting relation b/w nodes and edges. Please help to find interest point(interest_points.jpg) and relation in node n edges.-- Thanks & Regards, -???????Leena Chourey , ???? ???? C-DAC Mumbai ??-???, ?????? _______________________________________________scikit-image mailing listscikit-image at python.orghttps://mail.python.org/mailman/listinfo/scikit-image

--------------------------------
????????android???
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From leenagour at gmail.com  Thu May 18 01:23:41 2017
From: leenagour at gmail.com (Leena Chourey)
Date: Thu, 18 May 2017 10:53:41 +0530
Subject: [scikit-image] =?utf-8?b?5Zue5aSNOiBOZWVkIGhlbHAgdG8gZ2V0IGdy?=
	=?utf-8?q?aph_from_image?=
In-Reply-To: <20170518051205.E2735380546@webmail.sinamail.sina.com.cn>
References: <20170518051205.E2735380546@webmail.sinamail.sina.com.cn>
Message-ID: <CAD-S5bPpUZE_wpN-R6HXGK_=Vp=o8fvNFGwQPeaMOd2+55K7ww@mail.gmail.com>

Thanks YXDragon for quick reply.

   1. Yes I have tried skeletonisation but hanged for further processing.
   hope the links u have sent will help to resolve.
   2. Wow.. great. that is exactly I need and done partially. Can u pls
   explain the 1.jpg--->2.jpg--->3.jpg. I want exactly the same 3.jpg
   (junction points). Can i call imagepy in my python script and get the o/p
   of it for further processing?
   3. Is it possible to convert directly image to graph data structure?


On Thu, May 18, 2017 at 10:42 AM, <imagepy at sina.com> wrote:

> 1. you can do a skeleton, then use a np.ones((3,3)) to convolve. then 3
> means junction, one means termin. 2 means path.
> 2. trace from a termin. iterate all the pixel > 0. and add node if != 2!
>
> some tips:
> 1. if you do skeleton straightly, you will get some small branch, you can
> remove them by graph analysis. but I have a tip, you can do a gauss blur,
> then threshold again. this will smooth the binary image.
> 2. trace the path is not very simple, you need care many detail... you can
> look mine.
> <https://github.com/yxdragon/imagepy/blob/master/core/graph/builder.py>
> 3. the scikit-image's skeleton method prefers to generate branch
> (sometimes we want, but here we need not), you can look here
> <https://github.com/scikit-image/scikit-image/issues/2550>.
>
>
> you can have a try my project imagery
> <https://github.com/yxdragon/imagepy> do some test. which can wrap
> scikit-image like photoshop!
> (but I do not know if scikit-image has a method to build the skeleton)
>
> My English is solo, forgive me.
> YXDragon - ImagePy
> --------------------------------
>
> ????????android???
>
> -------- ???? --------
>
> ???:Leena Chourey
>
> ?    ?:2017?5?18? 12:05(???)
>
> ???:scikit-image at python.org
>
> ??:[scikit-image] Need help to get graph from image
>
> Dear All,
>
> I need to convert shape based image(graph_search2.jpg) into graph and then
> graph data structure. I have tried to filter the image and then with
> threshold, contour based approach access shapes(nodes), lines(edges) and
> arrows. but facing difficulty in getting relation b/w nodes and edges.
> Please help to find interest point(interest_points.jpg) and relation in
> node n edges.
>
> --
>
> Thanks & Regards, -???????
>
> Leena Chourey , ???? ????
>
> C-DAC Mumbai ??-???, ??????
>
> _______________________________________________
>
> scikit-image mailing list
>
> scikit-image at python.org
>
> https://mail.python.org/mailman/listinfo/scikit-image
>
>
> --------------------------------
>
> ????????android???
>
>
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
>
>


-- 
Thanks & Regards, -???????
Leena Chourey , ???? ????
C-DAC Mumbai ??-???, ??????
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From imagepy at sina.com  Thu May 18 02:06:08 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Thu, 18 May 2017 14:06:08 +0800
Subject: [scikit-image] =?gbk?b?u9i4tDpSZTogILvYuLQ6IE5lZWQgaGVscCB0byBn?=
 =?gbk?q?et_graph_from_image?=
Message-ID: <20170518060608.D30762E0121@webmail.sinamail.sina.com.cn>

I has build the networt, look tips 2. imagepy is not a function library, but a interactive framework witch can wrap numpy, scipy, scikitimage, opencv as a friendly.software.  by another, please donot save picture as jpg. the dct transform may destroy the high frequent information.

--------------------------------
????????android???


-------- ???? --------

???:Leena Chourey
??????:2017?5?18? 13:30(???)
???:imagepy at sina.com
Mailing list for scikit-image (http://scikit-image.org)
??:Re: [scikit-image] ??: Need help to get graph from image
Thanks?YXDragon?for quick reply.?Yes I have tried skeletonisation but hanged for further processing. hope the links u have sent will help to resolve.Wow.. great. that is exactly I need and done partially.?Can u pls explain the 1.jpg--->2.jpg--->3.jpg. I want exactly the same 3.jpg (junction points). Can i call imagepy in my python script and get the o/p of it for further processing?Is it possible to convert directly image to graph data structure?
On Thu, May 18, 2017 at 10:42 AM,  <imagepy at sina.com> wrote:
1. you can do a skeleton, then use a np.ones((3,3)) to convolve. then 3 means junction, one means termin. 2 means path.2. trace from a termin. iterate all the pixel > 0. and add node if != 2!
some tips:1. if you do skeleton straightly, you will get some small branch, you can remove them by graph analysis. but I have a tip, you can do a gauss blur, then threshold again. this will smooth the binary image.2. trace the path is not very simple, you need care many detail... you can look mine.3. the scikit-image&#39;s skeleton method prefers to generate branch (sometimes we want, but here we need not), you can look here.
you can have a try my project imagery do some test. which can wrap scikit-image like photoshop!(but I do not know if scikit-image has a method to build the skeleton)
My English is solo, forgive me.														YXDragon -?ImagePy--------------------------------????????android???-------- ???? --------???:Leena Chourey??????:2017?5?18? 12:05(???)???:scikit-image at python.org??:[scikit-image] Need help to get graph from imageDear All,I need to convert shape based image(graph_search2.jpg) into graph and then graph data structure. I have tried to filter the image and then with threshold, contour based approach access shapes(nodes), lines(edges) and arrows. but facing difficulty in getting relation b/w nodes and edges. Please help to find interest point(interest_points.jpg) and relation in node n edges.-- Thanks & Regards, -???????Leena Chourey , ???? ?????C-DAC Mumbai ??-???, ???????_______________________________________________scikit-image mailing listscikit-image at python.orghttps://mail.python.org/mailman/listinfo/scikit-image

--------------------------------
????????android???

_______________________________________________

scikit-image mailing list

scikit-image at python.org

https://mail.python.org/mailman/listinfo/scikit-image




-- 
Thanks & Regards, -???????Leena Chourey , ???? ?????C-DAC Mumbai ??-???, ???????



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From jni.soma at gmail.com  Thu May 18 03:12:29 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Thu, 18 May 2017 17:12:29 +1000
Subject: [scikit-image] build topograph network from skeleton
In-Reply-To: <20170518030732.8F705380546@webmail.sinamail.sina.com.cn>
References: <20170518030732.8F705380546@webmail.sinamail.sina.com.cn>
Message-ID: <4f5e3ee9-3b8b-4752-b0fa-0780f95c8708@Spark>

Hi YXDragon!

Coincidentally, I have been working on a package to do just that, which I have imaginatively-called ?skan? (for SKeleton ANalysis). It runs lightning quick using Numba, and works with n-D skeletons. It?s available on pip (pip install skan) and conda-forge (conda install -c conda-forge skan). The source code is on github (github.com/jni/skan).

The interface is a little fiddly currently but you should be able to figure it out. The functions you want are skan.csr.skeleton_to_csgraph (produces a pixel-to-pixel graph in scipy.sparse.csr_matrix format) and skan.csr.summarise (produces a pandas DataFrame with nodes and arcs, including coordinates in the image, arc distances, and euclidean distances). You just need to provide the skeleton.

I hope this helps! Feedback on the API is much appreciated!

Juan.

PS: Oh yeah, you might want to look at my Numba post, which described part of the development of this library:?https://ilovesymposia.com/2016/12/20/numba-in-the-real-world/

On 18 May 2017, 1:08 PM +1000, imagepy at sina.com, wrote:
> ?Hi everyone:
> ? ? I saw the newest version, require the networkx module. I find some function to find shortest path from image. But I want to know if there is a method to build a network from a skeleton image(2D/3D with arcs and nodes). I wrote one, but in python. it runs very slowly...
> ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?yxdragon-imagepy
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
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From jeanpatrick.pommier at gmail.com  Fri May 19 02:46:44 2017
From: jeanpatrick.pommier at gmail.com (Jean-Patrick Pommier)
Date: Fri, 19 May 2017 08:46:44 +0200
Subject: [scikit-image] build topograph network from skeleton
In-Reply-To: <4f5e3ee9-3b8b-4752-b0fa-0780f95c8708@Spark>
References: <20170518030732.8F705380546@webmail.sinamail.sina.com.cn>
 <4f5e3ee9-3b8b-4752-b0fa-0780f95c8708@Spark>
Message-ID: <CAJHHrbv_Z7+SE6R98QtTfFa97QzciF6QdZ0ZgihvPKwzNCMkOw@mail.gmail.com>

Hi,
I wrote some time ago:

http://dip4fish.blogspot.fr/2014/05/construct-graph-from-skeleton-image-of.html

http://dip4fish.blogspot.fr/2014/06/graph-again.html

http://dip4fish.blogspot.fr/2015/11/prune-iteratively-leaves-of-toy-graph.html
https://gist.github.com/jeanpat/aac681d6b56932941281

hope this help





2017-05-18 9:12 GMT+02:00 Juan Nunez-Iglesias <jni.soma at gmail.com>:

> Hi YXDragon!
>
> Coincidentally, I have been working on a package to do just that, which I
> have imaginatively-called ?skan? (for SKeleton ANalysis). It runs lightning
> quick using Numba, and works with n-D skeletons. It?s available on pip (pip
> install skan) and conda-forge (conda install -c conda-forge skan). The
> source code is on github (github.com/jni/skan).
>
> The interface is a little fiddly currently but you should be able to
> figure it out. The functions you want are skan.csr.skeleton_to_csgraph
> (produces a pixel-to-pixel graph in scipy.sparse.csr_matrix format) and
> skan.csr.summarise (produces a pandas DataFrame with nodes and arcs,
> including coordinates in the image, arc distances, and euclidean
> distances). You just need to provide the skeleton.
>
> I hope this helps! Feedback on the API is much appreciated!
>
> Juan.
>
> PS: Oh yeah, you might want to look at my Numba post, which described part
> of the development of this library: https://ilovesymposia.com/2016/12/20/
> numba-in-the-real-world/
>
> On 18 May 2017, 1:08 PM +1000, imagepy at sina.com, wrote:
>
>  Hi everyone:
>     I saw the newest version, require the networkx module. I find some
> function to find shortest path from image. But I want to know if there is a
> method to build a network from a skeleton image(2D/3D with arcs and nodes).
> I wrote one, but in python. it runs very slowly...
>                                        yxdragon-imagepy
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
>
>
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
>
>


-- 
http://dip4fish.blogspot.fr/
Dedicated to Digital Image Processing for FISH, QFISH and other things
about the telomeres.
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From pskeshu at gmail.com  Fri May 19 12:40:05 2017
From: pskeshu at gmail.com (Kesavan Subburam)
Date: Fri, 19 May 2017 22:10:05 +0530
Subject: [scikit-image] Viewing 3D images/stacks of images
Message-ID: <CAEyWfbFMasVYo2fdrjO3sGeVwNyh9LB=WyMc0cF9oJJkC96+HQ@mail.gmail.com>

Hi all,

I'd used CollectionViewer from skimage.viewer before for viewing microscopy
Z stacks. However, I personally felt it was a bit of a pain to use. For
instance, before passing in an array of images, the image has to be
stretched, otherwise, most of the time, one would end up with a "black"
series of images.

So, I wrote a simple function using matplotlib to view image collections,
which works quite well, and I think it can be extended to display nD images
with multiple sliders.

def ddd(images):
    def _update_image(num):
        num = int(num)
        image = np.squeeze(images[num:num+1])
        img_ax.set_data(image)
        fig.canvas.draw_idle()

    if images.ndim is not 3:
        raise ValueError("Not a 3D image.")

    Z, _, _ = images.shape

    fig, ax = plt.subplots()
    img_ax = ax.imshow(np.squeeze(images[0]), cmap="gray")
    ax.axis("off")

    sliderax = plt.axes([0.19, 0.05, 0.65, 0.03],
                        facecolor="lightgoldenrodyellow")
    img_slider = Slider(sliderax, "Z", 0, Z-1,
                        valfmt='%d', valinit=0)
    img_slider.on_changed(_update_image)
    plt.show()


This might be a bit redundant, but I would like your thoughts on whether
this might be useful for scikit-image. Some of the plugins of
CollectionViewer can be rewritten for this matplotlib based approach in a
much more readable fashion -- for instance, the line profile plugin.

Best,

-- 
Kesavan Subburam
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From pskeshu at gmail.com  Fri May 19 12:45:21 2017
From: pskeshu at gmail.com (Kesavan Subburam)
Date: Fri, 19 May 2017 22:15:21 +0530
Subject: [scikit-image] Viewing 3D images/stacks of images
In-Reply-To: <CAEyWfbFMasVYo2fdrjO3sGeVwNyh9LB=WyMc0cF9oJJkC96+HQ@mail.gmail.com>
References: <CAEyWfbFMasVYo2fdrjO3sGeVwNyh9LB=WyMc0cF9oJJkC96+HQ@mail.gmail.com>
Message-ID: <CAEyWfbE1Ui2u503y=ygz+8_vcTgAK9Kf9-b3D2tV67NHLEpeuw@mail.gmail.com>

from matplotlib.widgets import Slider
import matplotlib.pyplot as plt
import numpy as np

def ddd(images):
    def _update_image(num):
        num = int(num)
        image = np.squeeze(images[num:num+1])
        img_ax.set_data(image)
        fig.canvas.draw_idle()

    if images.ndim is not 3:
        raise ValueError("Not a 3D image.")

    Z, _, _ = images.shape

    fig, ax = plt.subplots()
    img_ax = ax.imshow(np.squeeze(images[0]), cmap="gray")
    ax.axis("off")

    sliderax = plt.axes([0.19, 0.05, 0.65, 0.03],
                        facecolor="lightgoldenrodyellow")
    img_slider = Slider(sliderax, "Z", 0, Z-1,
                        valfmt='%d', valinit=0)
    img_slider.on_changed(_update_image)
    plt.show()

I'd forgotten to include the import statements. Just in case you'd like to
test the code. Input image of shape (Z, N, M).

On 19 May 2017 at 22:10, Kesavan Subburam <pskeshu at gmail.com> wrote:

> Hi all,
>
> I'd used CollectionViewer from skimage.viewer before for viewing
> microscopy Z stacks. However, I personally felt it was a bit of a pain to
> use. For instance, before passing in an array of images, the image has to
> be stretched, otherwise, most of the time, one would end up with a "black"
> series of images.
>
> So, I wrote a simple function using matplotlib to view image collections,
> which works quite well, and I think it can be extended to display nD images
> with multiple sliders.
>
> def ddd(images):
>     def _update_image(num):
>         num = int(num)
>         image = np.squeeze(images[num:num+1])
>         img_ax.set_data(image)
>         fig.canvas.draw_idle()
>
>     if images.ndim is not 3:
>         raise ValueError("Not a 3D image.")
>
>     Z, _, _ = images.shape
>
>     fig, ax = plt.subplots()
>     img_ax = ax.imshow(np.squeeze(images[0]), cmap="gray")
>     ax.axis("off")
>
>     sliderax = plt.axes([0.19, 0.05, 0.65, 0.03],
>                         facecolor="lightgoldenrodyellow")
>     img_slider = Slider(sliderax, "Z", 0, Z-1,
>                         valfmt='%d', valinit=0)
>     img_slider.on_changed(_update_image)
>     plt.show()
>
>
> This might be a bit redundant, but I would like your thoughts on whether
> this might be useful for scikit-image. Some of the plugins of
> CollectionViewer can be rewritten for this matplotlib based approach in a
> much more readable fashion -- for instance, the line profile plugin.
>
> Best,
>
> --
> Kesavan Subburam
>



-- 
Kesavan
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From fdalforno at gmail.com  Fri May 26 02:41:38 2017
From: fdalforno at gmail.com (Fabio)
Date: Fri, 26 May 2017 08:41:38 +0200
Subject: [scikit-image] Fwd: Extract a particular area in document
In-Reply-To: <CAJ_35UKh9j8EBkOkQ+c5xYhsiMC0PesXFRJ2wjPwdUsoF+x_kw@mail.gmail.com>
References: <CAJ_35UKh9j8EBkOkQ+c5xYhsiMC0PesXFRJ2wjPwdUsoF+x_kw@mail.gmail.com>
Message-ID: <CAJ_35UKQfVkz1SV1JQ3WpxSBt3f6Tk4j5b3XyC3nSU7p5qsGAg@mail.gmail.com>

Hi all, my name's Fabio Dal Forno.
I'm a basic scikit user and i have many question too.

I've a lot of scanned document like this



And i want to extract a particular area (si no, yes or no in english) see
image below


?
After that i want to train a neural networ for detect the data compiled by
people, y,x coordinate for detect the means of the area (materials damage
ecc ecc)
and a fixed dimension image for a neural network

I started to work with the following step:

1) Homography for detect document orientation after that i transform the
document for rectify that
2) Homography for detect si/no area and coordinate once

the first step work wery well but the second doesn't detect anything.

Am i wrong reasoning ?


Thanks a lot and sorry for my beginner english :)




?
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From jni.soma at gmail.com  Fri May 26 02:50:22 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Fri, 26 May 2017 16:50:22 +1000
Subject: [scikit-image] Fwd: Extract a particular area in document
In-Reply-To: <CAJ_35UKQfVkz1SV1JQ3WpxSBt3f6Tk4j5b3XyC3nSU7p5qsGAg@mail.gmail.com>
References: <CAJ_35UKh9j8EBkOkQ+c5xYhsiMC0PesXFRJ2wjPwdUsoF+x_kw@mail.gmail.com>
 <CAJ_35UKQfVkz1SV1JQ3WpxSBt3f6Tk4j5b3XyC3nSU7p5qsGAg@mail.gmail.com>
Message-ID: <bbe06db5-b879-4294-9912-3ed3ee777617@Spark>

Hi Fabio!

Ach, you just gave me flashbacks to the time someone broke my car window when I was holidaying in Lido di Ostia. =P Cool work though! =)

What do you mean by "using a homography" to detect the Si/No boxes? Could you provide maybe a sample image and working code? It's hard to tell what is going wrong without that context. I understand that there's privacy concerns but maybe you could fill in a blank form as test data? (Or your code to try to find the two si/no boxes that are not masked in the image below.)

One thing I'll say though is that neural networks require lots and lots of ground truth data to train effectively, and is probably overkill for what you want to do. In your case, you can probably align the car images very accurately, and detecting marks outside of that should not be too hard.

Good luck!

Juan.

On 26 May 2017, 4:42 PM +1000, Fabio <fdalforno at gmail.com>, wrote:
> Hi all, my name's Fabio Dal Forno.
> > I'm a basic scikit user and i have many question too.
> >
> > I've a lot of scanned document like this
> >
> >
> >
> > And i want to extract a particular area (si no, yes or no in english) see image below
> >
> >
> >
> > After that i want to train a neural networ for detect the data compiled by people, y,x coordinate for detect the means of the area (materials damage ecc ecc)
> > and a fixed dimension image for a neural network
> >
> > I started to work with the following step:
> >
> > 1) Homography for detect document orientation after that i transform the document for rectify that
> > 2) Homography for detect si/no area and coordinate once
> >
> > the first step work wery well but the second doesn't detect anything.
> >
> > Am i wrong reasoning ?
> >
> >
> > Thanks a lot and sorry for my beginner english :)
> >
> >
> >
> >
> >
>
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
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From imagepy at sina.com  Fri May 26 05:55:38 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Fri, 26 May 2017 17:55:38 +0800
Subject: [scikit-image] =?gbk?b?u9i4tKO6IEZ3ZDogRXh0cmFjdCBhIHBhcnRpY3Vs?=
 =?gbk?q?ar_area_in_document?=
Message-ID: <20170526095538.AEF5A380544@webmail.sinamail.sina.com.cn>

Hi FWD:
There are many methods to do this. as you said, you had do a transform to make sure the image in standard direction. 
if your image are in the standard scale, you can use a template match. but if has different scales, it will not work. 
but I think you can do a threshold, then binary fill, then the [no, si] will be a solid rectangle. you can do a region analysis http://scikit-image.org/docs/stable/api/skimage.measure.html#regionprops to make sure if it is your goal (by the area, perimeter and moments).  I think it will be ok!
you can also try the adboost,  sift, and other local descriptor, and so on. but I think it is too fussy and waste to solve this problem.
														YXDragon
----- ???? -----
????Fabio <fdalforno at gmail.com>
????scikit-image at python.org
???[scikit-image] Fwd: Extract a particular area in document
???2017?05?26? 14?42?

Hi all, my name's Fabio Dal Forno.
I'm a basic scikit user and i have many question too.

I've a lot of scanned document like this



And i want to extract a particular area (si no, yes or no in english) see image below


?
After that i want to train a neural networ for detect the data compiled by people, y,x coordinate for detect the means of the area (materials damage ecc ecc) 
and a fixed dimension image for a neural network

I started to work with the following step:

1) Homography for detect document orientation after that i transform the document for rectify that
2) Homography for detect si/no area and coordinate once

the first step work wery well but the second doesn't detect anything.

Am i wrong reasoning ?


Thanks a lot and sorry for my beginner english :)
 



? 




_______________________________________________
scikit-image mailing list
scikit-image at python.org
https://mail.python.org/mailman/listinfo/scikit-image
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From matthew.brett at gmail.com  Fri May 26 17:37:07 2017
From: matthew.brett at gmail.com (Matthew Brett)
Date: Fri, 26 May 2017 22:37:07 +0100
Subject: [scikit-image] Daily wheel builds
Message-ID: <CAH6Pt5oNfdD388CgGfw=wXq54xs2guiecV+gTzrY=-yVREK9SA@mail.gmail.com>

Hi,

I just set up daily wheel builds for scikit-image master.  They run
via travis-ci cron jobs, and have the dual role of testing that wheel
building works, as well as testing on 32-bit Linux, and several macOS
versions.

The wheel builds run from the "daily" branch of the scikit-image-wheels repo:

https://github.com/scikit-image/scikit-image-wheels/tree/daily

See here for logs of the daily builds:

https://travis-ci.org/scikit-image/scikit-image-wheels/branches

The build exposed a few test failures on 32-bit - see:
https://github.com/scikit-image/scikit-image/issues/2670

Cheers,

Matthew

From stefanv at berkeley.edu  Sat May 27 06:36:21 2017
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Sat, 27 May 2017 12:36:21 +0200
Subject: [scikit-image] Daily wheel builds
In-Reply-To: <CAH6Pt5oNfdD388CgGfw=wXq54xs2guiecV+gTzrY=-yVREK9SA@mail.gmail.com>
References: <CAH6Pt5oNfdD388CgGfw=wXq54xs2guiecV+gTzrY=-yVREK9SA@mail.gmail.com>
Message-ID: <15c497a70a0.273e.acf34a9c767d7bb498a799333be0433e@fastmail.com>

On May 26, 2017 23:38:20 Matthew Brett <matthew.brett at gmail.com> wrote:

> I just set up daily wheel builds for scikit-image master.

Thanks, Matthew! This is very helpful, especially the 32-bit builds.

Best regards
St?fan



From interactpy at gmail.com  Sat May 27 16:47:58 2017
From: interactpy at gmail.com (EV Petr)
Date: Sat, 27 May 2017 23:47:58 +0300
Subject: [scikit-image] Whar are values returned by measure.marching_cubes
Message-ID: <CAG2==YMb+n0=wf5Pbzr6+89Z_TynTGgRPA6cxc5SKs_p3SjkNQ@mail.gmail.com>

Hello,

I'm not familiar with scikit-image. I  only want to use the function
`measure.marching_cubes`,
but I cannot figure out what really represent the values returned by it.

`help(measure.marching_cubes)` says:

*values : (V, ) array*

*Gives a measure for the maximum value of the data in the local region
        near each vertex. This can be used by visualization tools to apply
        a colormap to the mesh.*


What is data here (this term is too general)?

I saw that values.shape[0] is the same as vertices.shape[0]. Hence
each value is associated to a vertex.

 How is it assigned to a vertex? How are these values related to the
volume or to the equation F(x,y,z)=0?

(I want to extract a triangulation of an implicit surface having this equation).


A second question is related to the coordinates of vertices.

When I plot the  trisurf defined by `vertices` and `faces` I notice

that the x, y and z-range illustrated by tick values

is different from the real values. More precisely: if my surface has
zmin=-1 and zmax=2,  on z-axis

this range is [5,11].  Is there a transformation that maps the
vertices coordinates, as they are returned by

`measure.marching_cubes` to real coordinates on my surface?


Thanks,


Eve
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