From georgesamarasdit at gmail.com  Fri Jun  3 18:11:14 2016
From: georgesamarasdit at gmail.com (Georgios Samaras)
Date: Fri, 3 Jun 2016 15:11:14 -0700 (PDT)
Subject: ImportError: No module named skimage.io
Message-ID: <bab35bd2-2d1f-495b-8d64-8901db067664@googlegroups.com>

I am trying to do this:

sudo pip install -U scikit-image

but I am getting:

Cleaning up...
Exception:
Traceback (most recent call last):
  File "/usr/lib/python2.7/dist-packages/pip/basecommand.py", line 122, in 
main
    status = self.run(options, args)
  File "/usr/lib/python2.7/dist-packages/pip/commands/install.py", line 
278, in run
    requirement_set.prepare_files(finder, force_root_egg_info=self.bundle, 
bundle=self.bundle)
  File "/usr/lib/python2.7/dist-packages/pip/req.py", line 1091, in 
prepare_files
    req_to_install.check_if_exists()
  File "/usr/lib/python2.7/dist-packages/pip/req.py", line 811, in 
check_if_exists
    self.satisfied_by = pkg_resources.get_distribution(self.req)
  File "/usr/local/lib/python2.7/dist-packages/pkg_resources/__init__.py", 
line 535, in get_distribution
    dist = get_provider(dist)
  File "/usr/local/lib/python2.7/dist-packages/pkg_resources/__init__.py", 
line 415, in get_provider
    return working_set.find(moduleOrReq) or require(str(moduleOrReq))[0]
IndexError: list index out of range

Storing debug log for failure in /home/gsamaras/.pip/pip.log
--------------------------------------------------------------------------------------------------------------------------------------------------------

How to fix this? For more, see this SO question 
<https://stackoverflow.com/questions/37623259/unable-to-import-caffe>.
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From georgesamarasdit at gmail.com  Fri Jun  3 18:36:30 2016
From: georgesamarasdit at gmail.com (Georgios Samaras)
Date: Sat, 4 Jun 2016 01:36:30 +0300
Subject: ImportError: No module named skimage.io
In-Reply-To: <bab35bd2-2d1f-495b-8d64-8901db067664@googlegroups.com>
References: <bab35bd2-2d1f-495b-8d64-8901db067664@googlegroups.com>
Message-ID: <CAL_Bz4Xde1_t6bFQkXQrirfQjWTAKPSJ4zr5Q3U3T_KmpqAt8A@mail.gmail.com>

I had to use sudo apt-get install -U scikit-image after all!

On Sat, Jun 4, 2016 at 1:11 AM, Georgios Samaras <georgesamarasdit at gmail.com
> wrote:

> I am trying to do this:
>
> sudo pip install -U scikit-image
>
> but I am getting:
>
> Cleaning up...
> Exception:
> Traceback (most recent call last):
>   File "/usr/lib/python2.7/dist-packages/pip/basecommand.py", line 122, in
> main
>     status = self.run(options, args)
>   File "/usr/lib/python2.7/dist-packages/pip/commands/install.py", line
> 278, in run
>     requirement_set.prepare_files(finder, force_root_egg_info=self.bundle,
> bundle=self.bundle)
>   File "/usr/lib/python2.7/dist-packages/pip/req.py", line 1091, in
> prepare_files
>     req_to_install.check_if_exists()
>   File "/usr/lib/python2.7/dist-packages/pip/req.py", line 811, in
> check_if_exists
>     self.satisfied_by = pkg_resources.get_distribution(self.req)
>   File "/usr/local/lib/python2.7/dist-packages/pkg_resources/__init__.py",
> line 535, in get_distribution
>     dist = get_provider(dist)
>   File "/usr/local/lib/python2.7/dist-packages/pkg_resources/__init__.py",
> line 415, in get_provider
>     return working_set.find(moduleOrReq) or require(str(moduleOrReq))[0]
> IndexError: list index out of range
>
> Storing debug log for failure in /home/gsamaras/.pip/pip.log
>
> --------------------------------------------------------------------------------------------------------------------------------------------------------
>
> How to fix this? For more, see this SO question
> <https://stackoverflow.com/questions/37623259/unable-to-import-caffe>.
>
> --
> You received this message because you are subscribed to a topic in the
> Google Groups "scikit-image" group.
> To unsubscribe from this topic, visit
> https://groups.google.com/d/topic/scikit-image/0qGiE4BI2j8/unsubscribe.
> To unsubscribe from this group and all its topics, send an email to
> scikit-image+unsubscribe at googlegroups.com.
> To post to this group, send email to scikit-image at googlegroups.com.
> To view this discussion on the web, visit
> https://groups.google.com/d/msgid/scikit-image/bab35bd2-2d1f-495b-8d64-8901db067664%40googlegroups.com
> <https://groups.google.com/d/msgid/scikit-image/bab35bd2-2d1f-495b-8d64-8901db067664%40googlegroups.com?utm_medium=email&utm_source=footer>
> .
> For more options, visit https://groups.google.com/d/optout.
>
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From simone at codeluppi.org  Tue Jun  7 07:11:13 2016
From: simone at codeluppi.org (Simone Codeluppi)
Date: Tue, 7 Jun 2016 04:11:13 -0700 (PDT)
Subject: Do all functions return float64 dtype?
Message-ID: <3ca4a0a3-4d44-4fb7-b04c-7601d9ad3bd4@googlegroups.com>

Hi
I was just wondering if the majority of the skimage functions return 
float64 as default dtype. I am processing a big dataset and saving the data 
as float64 increase the size quite a bit (compared to float32). Is there 
also an additional computational cost in processing float64 instead of 
float32?  Beside the precision level is there any advantage in using 
float64? 
Thanks a lot!

Simone
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From thomas.edgar.walter at googlemail.com  Wed Jun  8 04:28:22 2016
From: thomas.edgar.walter at googlemail.com (Thomas Walter)
Date: Wed, 8 Jun 2016 01:28:22 -0700 (PDT)
Subject: PhD position in Bioimage Informatics at Mines ParisTech / Institut
 Curie, Paris, France
Message-ID: <6bea3cc2-40bd-422a-ad9a-f57b669a9f55@googlegroups.com>

 PhD position in Bioimage Informatics at Mines ParisTech / Institut Curie, 
Paris, France 

 

Title: Machine Learning for Multi-cell-line Drug Screening

Duration: 3 years

Starting date: October 2016

 
Description: 

The objective of drug screening is to identify new molecules active against 
diseases, such as cancer. For this, a large number (typically hundreds or 
thousands) of experiments are performed on a cell line, which is supposed 
to be representative for the disease. In High Content Screening, the 
readout consists in images: for each individual drug, the effect is 
measured by fluorescence microscopy, giving thus a comprehensive 
description of the cellular phenotypes induced by the drug exposure. Such 
data sets are therefore large and complex and typically challenging to 
analyze. 

The traditional way of scoring for drug effects from images can be divided 
into five steps [1]: (1) image segmentation (identification of cells and 
cellular compartments); (2) feature extraction for each individual cell; 
(3) classification of single cells into phenotypic classes (such as cell 
death, mitosis, interphase, etc.); (4) description of the population 
phenotype (e.g. the percentage of cells in each phenotypic class); and (5) 
analysis of phenotypic similarities between different drug exposures based 
on the phenotypic profiles, e.g. by clustering approaches. This family of 
workflows has been successfully applied to large-scale screens [2], [3] in 
the past.

In this PhD thesis, we want to explore new methods for the analysis of such 
data sets, applicable in the case where multiple cell lines with potential 
different basic properties are screened against large drug panels. 

 
References 

[1] T. Walter, M. Held, B. Neumann, J.-K. H?rich?, C. Conrad, R. Pepperkok, 
and J. Ellenberg, ?Automatic identification and clustering of chromosome 
phenotypes genome wide RNAi screen by time-lapse imaging?, J. Struct. 
Biol., vol. 170, no. 1, pp. 1?9, Apr. 2010.

[2] Z. E. Perlman, M. D. Slack, Y. Feng, T. J. Mitchison, L. F. Wu, and S. 
J. Altschuler, ?Multidimensional drug profiling by automated microscopy?, 
Science, vol. 306, no. 5699, pp. 1194?8, Nov. 2004.

[3] L. Loo, L. F. Wu, and S. J. Altschuler, ?Image-based multivariate 
profiling of drug responses from single cells?, Nat. Methods, vol. 4, no. 
5, pp. 445?453, 2007.

 
Candidate profile: 

The candidate should have a strong background in image analysis, computer 
vision and/or machine learning. Basic knowledge in biology and/or 
bioinformatics is an advantage, but not a requirement. Good 
interdisciplinary communication skills and a fundamental interest in 
biological and medical applications are expected. The project also involves 
a fair amount of programming (ideally in Python or R). 

 
Application 

Applications should be addressed to Thomas.Walter(at)mines-paristech.fr, 
and should contain a CV, a motivation letter, degrees and grades and any 
further useful information. 

 
Working Environment 

The project will take place at the Centre for Computational Biology (CBIO ? 
http://cbio.ensmp.fr) under the supervision of Thomas Walter (
http://cbio.ensmp.fr/~twalter) and in collaboration with the Reyal group at 
the Institut Curie. The CBIO is a research center of Mines ParisTech, an 
important French engineering school, and is directed by Jean-Philippe Vert (
http://cbio.ensmp.fr/~jvert). The main topic is machine learning, applied 
to problems in biology. There is also an official partnership with the 
Curie Institute, a major hospital and research facility dedicated to 
cancer. Both the Curie Institute and the Centre for Computational Biology 
are situated in the heart of Paris, in an exciting and scientifically 
stimulating environment. 

 





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From nelle.varoquaux at gmail.com  Wed Jun  8 13:01:49 2016
From: nelle.varoquaux at gmail.com (Nelle Varoquaux)
Date: Wed, 8 Jun 2016 10:01:49 -0700
Subject: Fwd: [scikit-learn] EuroSciPy 2016 Call for Papers Extended
In-Reply-To: <CAGvd0=gq=3+YgJy1CYgnkfQ1h9Sc0WGy43mfyoHHnvMU1jmUMg@mail.gmail.com>
References: <CAGvd0=gq=3+YgJy1CYgnkfQ1h9Sc0WGy43mfyoHHnvMU1jmUMg@mail.gmail.com>
Message-ID: <CAE-UAvS6t_VoiRVUMk2t9LMpyuvK-Hn5NOWCSrBwh-n-vC5tdQ@mail.gmail.com>

This email may be of interest!

---------- Forwarded message ----------
From: federico vaggi <vaggi.federico at gmail.com>
Date: 8 June 2016 at 01:43
Subject: [scikit-learn] EuroSciPy 2016 Call for Papers Extended
To: Scikit-learn user and developer mailing list <scikit-learn at python.org>


Hi everyone,

The call for contributions (talks, posters, sprints) is still open until
June 24th.

EuroSciPy 2016 takes place in Erlangen, Germany, from the 23 to the 27 of
August
and consists of two days of tutorials (beginner and advanced tracks) and two
days of conference representing many fields of science, with a focus on
Python
tools for science. A day of sprints follows (sprints TBA).

The keynote speakers are Ga?l Varoquaux (you might have heard of him) and
Abby Cabunoc Mayes and we can expect
a rich tutorial and scientific program! Videos from previous years are
available
at https://www.youtube.com/playlist?list=PLYx7XA2nY5GeQCCugyvtnHMVLdhYlrRxH
and
https://www.youtube.com/playlist?list=PLYx7XA2nY5Gcpabmu61kKcToLz0FapmHu

We are particularly eager to receive proposals from newcomers.  EuroSciPy
is a very welcoming conference, and we are very curious to hear how you use
Python/machine learning in your every day research.

Visit us, register and submit an abstract on our website!
https://www.euroscipy.org/2016/

SciPythonic regards,

The EuroSciPy 2016 team

_______________________________________________
scikit-learn mailing list
scikit-learn at python.org
https://mail.python.org/mailman/listinfo/scikit-learn
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From michael.obrien at ul.ie  Sat Jun 11 09:39:16 2016
From: michael.obrien at ul.ie (michael.obrien at ul.ie)
Date: Sat, 11 Jun 2016 06:39:16 -0700 (PDT)
Subject: Segmentation Fault when running Censure demo
Message-ID: <f1830ae6-0b8d-4968-8402-8f228a1b7630@googlegroups.com>

Hi all,

I've new to computer vision and I hope you don't mind helping me out. I was 
interested in trying the demo
http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_censure.html 
so I downloaded the notebook and py script. 

Im running on Ubuntu 14.04 and python 2.7.6. 
*Some background:* To install scikit-image I needed to install Cython and 
update pip. I had previously used the apt-get install method but it 
reported scikit-image version as 0.9 and couldn't find the CENSURE module 
or the astronaut data when I tried to run the notebooks so I removed that 
and used cython -> pip install (after upgrading pip)


When I run the notebook I am notified the kernel needs to be restarted and 
when I run the py script I get the following 

michael at michael-VirtualBox:~/Downloads$ python plot_censure.py
Traceback (most recent call last):
  File "plot_censure.py", line 11, in <module>
    from skimage import data
  File "/usr/local/lib/python2.7/dist-packages/skimage/data/__init__.py", 
line 12, in <module>
    from ..io import imread, use_plugin
  File "/usr/local/lib/python2.7/dist-packages/skimage/io/__init__.py", 
line 7, in <module>
    from .manage_plugins import *
  File 
"/usr/local/lib/python2.7/dist-packages/skimage/io/manage_plugins.py", line 
28, in <module>
    from .collection import imread_collection_wrapper
  File "/usr/local/lib/python2.7/dist-packages/skimage/io/collection.py", 
line 14, in <module>
    from ..external.tifffile import TiffFile
  File 
"/usr/local/lib/python2.7/dist-packages/skimage/external/tifffile/__init__.py", 
line 1, in <module>
    from .tifffile import imsave, imread, imshow, TiffFile, TiffWriter, 
TiffSequence
  File 
"/usr/local/lib/python2.7/dist-packages/skimage/external/tifffile/tifffile.py", 
line 153, in <module>
    from . import _tifffile
RuntimeError: module compiled against API version a but this version of 
numpy is 9
Segmentation fault (core dumped)

When I run 
import numpy
inumpy.__version__
'1.8.2'


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From stefanv at berkeley.edu  Sat Jun 11 21:30:14 2016
From: stefanv at berkeley.edu (=?UTF-8?Q?St=C3=A9fan_van_der_Walt?=)
Date: Sat, 11 Jun 2016 18:30:14 -0700
Subject: Segmentation Fault when running Censure demo
In-Reply-To: <f1830ae6-0b8d-4968-8402-8f228a1b7630@googlegroups.com>
References: <f1830ae6-0b8d-4968-8402-8f228a1b7630@googlegroups.com>
Message-ID: <CABDkGQnms7gvhPt+J2+Pq+2CUs+nFFfi1=DYY624mbkHJHtGFg@mail.gmail.com>

Hi Michael

This looks like a numpy version mismatch. Would you please set up a virtual
environment and try again?

If that still fails, we should be able to isolate the problem more easily.

Best regards
St?fan
On Jun 11, 2016 06:39, <michael.obrien at ul.ie> wrote:

> Hi all,
>
> I've new to computer vision and I hope you don't mind helping me out. I
> was interested in trying the demo
>
> http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_censure.html
> so I downloaded the notebook and py script.
>
> Im running on Ubuntu 14.04 and python 2.7.6.
> *Some background:* To install scikit-image I needed to install Cython and
> update pip. I had previously used the apt-get install method but it
> reported scikit-image version as 0.9 and couldn't find the CENSURE module
> or the astronaut data when I tried to run the notebooks so I removed that
> and used cython -> pip install (after upgrading pip)
>
>
> When I run the notebook I am notified the kernel needs to be restarted and
> when I run the py script I get the following
>
> michael at michael-VirtualBox:~/Downloads$ python plot_censure.py
> Traceback (most recent call last):
>   File "plot_censure.py", line 11, in <module>
>     from skimage import data
>   File "/usr/local/lib/python2.7/dist-packages/skimage/data/__init__.py",
> line 12, in <module>
>     from ..io import imread, use_plugin
>   File "/usr/local/lib/python2.7/dist-packages/skimage/io/__init__.py",
> line 7, in <module>
>     from .manage_plugins import *
>   File
> "/usr/local/lib/python2.7/dist-packages/skimage/io/manage_plugins.py", line
> 28, in <module>
>     from .collection import imread_collection_wrapper
>   File "/usr/local/lib/python2.7/dist-packages/skimage/io/collection.py",
> line 14, in <module>
>     from ..external.tifffile import TiffFile
>   File
> "/usr/local/lib/python2.7/dist-packages/skimage/external/tifffile/__init__.py",
> line 1, in <module>
>     from .tifffile import imsave, imread, imshow, TiffFile, TiffWriter,
> TiffSequence
>   File
> "/usr/local/lib/python2.7/dist-packages/skimage/external/tifffile/tifffile.py",
> line 153, in <module>
>     from . import _tifffile
> RuntimeError: module compiled against API version a but this version of
> numpy is 9
> Segmentation fault (core dumped)
>
> When I run
> import numpy
> inumpy.__version__
> '1.8.2'
>
>
> --
> You received this message because you are subscribed to the Google Groups
> "scikit-image" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to scikit-image+unsubscribe at googlegroups.com.
> To post to this group, send email to scikit-image at googlegroups.com.
> To view this discussion on the web, visit
> https://groups.google.com/d/msgid/scikit-image/f1830ae6-0b8d-4968-8402-8f228a1b7630%40googlegroups.com
> <https://groups.google.com/d/msgid/scikit-image/f1830ae6-0b8d-4968-8402-8f228a1b7630%40googlegroups.com?utm_medium=email&utm_source=footer>
> .
> For more options, visit https://groups.google.com/d/optout.
>
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From abdealikothari at gmail.com  Sun Jun 12 10:37:18 2016
From: abdealikothari at gmail.com (Abdeali Kothari)
Date: Sun, 12 Jun 2016 07:37:18 -0700 (PDT)
Subject: Haarcascades implementation
Message-ID: <0a9ab8ba-a248-46b9-9780-2d4b99e729a9@googlegroups.com>

Hi, I recently switched from opencv to skimage as I found it much more 
pythonic and easier to install.

There is one feature which I seem to be missing - The Haarcascades and 
CascadeClassifier[1]. Is there plan to add this in skimage ? I'm quite new 
to haarcascades, but my understanding is that first there are HAAR features 
that are found from the image and then these features are classified using 
multiple weak classifiers (using adaboost) to "detect" an object.

It seems to me that to get this functionality I would need skimage (to 
create the haar features) and sklearn (for the adaboost setup). I found 
issues/1431[2] which seems to talk about creating HAAR features.

Am I on the right track ? Is there already some example code available 
which uses skimage and sklearn using one of the haarcascadde xml files 
provided by opencv ?

Regards,
Abdeali JK


[1] 
- http://docs.opencv.org/master/d7/d8b/tutorial_py_face_detection.html#gsc.tab=0
[2] - https://github.com/scikit-image/scikit-image/issues/1431
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From daniil.j.pakhomov at gmail.com  Sun Jun 12 19:12:08 2016
From: daniil.j.pakhomov at gmail.com (Daniil Pakhomov)
Date: Sun, 12 Jun 2016 16:12:08 -0700 (PDT)
Subject: Haarcascades implementation
In-Reply-To: <0a9ab8ba-a248-46b9-9780-2d4b99e729a9@googlegroups.com>
References: <0a9ab8ba-a248-46b9-9780-2d4b99e729a9@googlegroups.com>
Message-ID: <5600d5e4-92c5-41f4-8e3e-14ae6a7435cc@googlegroups.com>

Hello, Abdeali Kothari.

The detection module is about to be integrated.

The respective Pool Request can be found here:
https://github.com/scikit-image/scikit-image/pull/1570

You can clone it, compile, and test. The examples of usage can be found in 
the /examples or /tests.
Please, report if you have any problems when using it. Also, don't hesitate 
to ask for help in installing it.

It uses Multi-Block Local Binary Patterns (MB-LBP) instead of Haar Features.
This was done because of speed concerns.
You can use any .xml file from OpenCV directory /lbp to run it.
To run it, you don't need OpenCV dependency though.

Cheers,
Daniil
 
???????????, 12 ???? 2016 ?., 10:37:18 UTC-4 ???????????? Abdeali Kothari 
???????:
>
> Hi, I recently switched from opencv to skimage as I found it much more 
> pythonic and easier to install.
>
> There is one feature which I seem to be missing - The Haarcascades and 
> CascadeClassifier[1]. Is there plan to add this in skimage ? I'm quite new 
> to haarcascades, but my understanding is that first there are HAAR features 
> that are found from the image and then these features are classified using 
> multiple weak classifiers (using adaboost) to "detect" an object.
>
> It seems to me that to get this functionality I would need skimage (to 
> create the haar features) and sklearn (for the adaboost setup). I found 
> issues/1431[2] which seems to talk about creating HAAR features.
>
> Am I on the right track ? Is there already some example code available 
> which uses skimage and sklearn using one of the haarcascadde xml files 
> provided by opencv ?
>
> Regards,
> Abdeali JK
>
>
> [1] - 
> http://docs.opencv.org/master/d7/d8b/tutorial_py_face_detection.html#gsc.tab=0
> [2] - https://github.com/scikit-image/scikit-image/issues/1431
>
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From daniil.j.pakhomov at gmail.com  Sun Jun 12 19:23:36 2016
From: daniil.j.pakhomov at gmail.com (Daniil Pakhomov)
Date: Sun, 12 Jun 2016 16:23:36 -0700 (PDT)
Subject: Haarcascades implementation
In-Reply-To: <0a9ab8ba-a248-46b9-9780-2d4b99e729a9@googlegroups.com>
References: <0a9ab8ba-a248-46b9-9780-2d4b99e729a9@googlegroups.com>
Message-ID: <bb52ccad-e9fe-4a61-b980-26778bab2267@googlegroups.com>

Also, this might be useful:
http://warmspringwinds.github.io/

???????????, 12 ???? 2016 ?., 10:37:18 UTC-4 ???????????? Abdeali Kothari 
???????:
>
> Hi, I recently switched from opencv to skimage as I found it much more 
> pythonic and easier to install.
>
> There is one feature which I seem to be missing - The Haarcascades and 
> CascadeClassifier[1]. Is there plan to add this in skimage ? I'm quite new 
> to haarcascades, but my understanding is that first there are HAAR features 
> that are found from the image and then these features are classified using 
> multiple weak classifiers (using adaboost) to "detect" an object.
>
> It seems to me that to get this functionality I would need skimage (to 
> create the haar features) and sklearn (for the adaboost setup). I found 
> issues/1431[2] which seems to talk about creating HAAR features.
>
> Am I on the right track ? Is there already some example code available 
> which uses skimage and sklearn using one of the haarcascadde xml files 
> provided by opencv ?
>
> Regards,
> Abdeali JK
>
>
> [1] - 
> http://docs.opencv.org/master/d7/d8b/tutorial_py_face_detection.html#gsc.tab=0
> [2] - https://github.com/scikit-image/scikit-image/issues/1431
>
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From sira.ferradans at gmail.com  Mon Jun 13 09:02:15 2016
From: sira.ferradans at gmail.com (Sira Ferradans)
Date: Mon, 13 Jun 2016 06:02:15 -0700 (PDT)
Subject: Interesting to include a the Scattering transform in sci-kit image?
Message-ID: <ad063b83-f44d-463a-85fe-159ba77733a8@googlegroups.com>

Dear Sci-kit image developers, 


at the ENS (Paris) we are planning on implementing a Python version of the 
Scattering transform 2D and 1D. The scattering transform has proven to be 
very powerful as a descriptor for image classification and signal analysis. 
We thought that it may be useful to integrate the 2D version in the sci-kit 
image package, since it aligns well with the software package and the 
community. The idea would be to implement the functionalities following as 
much as possible the APIs you already have for similar functions. More 
specifically, we will need the following (approximately): 


                -Morlet wavelet: Closely related to the Gabor wavelet, so 
it should take into account its API
                -Scattering transform: output the scattering transform 
coefficients, either for display or (as a vector) for learning purposes. 


We are attaching a small tutorial (better visualized if you download it) 
that compares the performance of the first order scattering coefficients 
computed with Gabor filters, versus the coefficients you extract in the *'Gabor 
filter banks for texture classification' 
<http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_gabor.html#example-features-detection-plot-gabor-py>* 
tutorial. The goal of this ipython notebook is to show that the 
implementation can be easily integrated in you library while providing a 
powerful tool for image analysis. 

If you think this is a good idea, please let us know. Moreover, it would be 
great if you could give us some guidelines that you think would make the 
process easier. We will be adhering to the instructions given on the 
contributions page, but please don't hesitate to give feedback on our PR! 


Best Regards, 

Michael Eickenberg and Sira Ferradans. 
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From abdealikothari at gmail.com  Sun Jun 12 20:54:27 2016
From: abdealikothari at gmail.com (Abdeali Kothari)
Date: Mon, 13 Jun 2016 06:24:27 +0530
Subject: Haarcascades implementation
In-Reply-To: <bb52ccad-e9fe-4a61-b980-26778bab2267@googlegroups.com>
References: <0a9ab8ba-a248-46b9-9780-2d4b99e729a9@googlegroups.com> <bb52ccad-e9fe-4a61-b980-26778bab2267@googlegroups.com>
Message-ID: <CA+BKPDW+MeSoSdycZEqpHkn7kcaCQAkzJzzBMfdo9WswLoRLXw@mail.gmail.com>

Hi Daniil,

Thank you very much for that mail

The LBP features do look interesting, and I had no idea OpenCV had that !
It seems LBP is considerably faster than HAAR, but not as accurate[1].
Which makes me wonder whether that is the right choice. Also, there are
more pre-trained haarcascades than lbpcascades which makes me favor
haarcascade more.

But this implementation is something that I can read and understand how to
do it myself better ! Thanks :)

I'm wondering as to why sklearn was not used in pull/1570 [2] ? It seems to
me like a lot of the code in skimage/future/detect/cascade.pyx [3] would
already be available there (Probably in sklearn.ensemble.AdaBoostClassifier
[4])? It could be made an "optional" feature which only works if sklearn is
installed ?

Regards,
Abdeali JK

[1] -
http://stackoverflow.com/questions/8791178/haar-cascades-vs-lbp-cascades-in-face-detection
[2] - https://github.com/scikit-image/scikit-image/pull/1570
[3] -
https://github.com/warmspringwinds/scikit-image/blob/7face0ebbfadab299b0e2a15e95a761648639c98/skimage/future/detect/cascade.pyx
[4] -
http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostClassifier.html

On Mon, Jun 13, 2016 at 4:53 AM, Daniil Pakhomov <
daniil.j.pakhomov at gmail.com> wrote:

> Also, this might be useful:
> http://warmspringwinds.github.io/
>
> ???????????, 12 ???? 2016 ?., 10:37:18 UTC-4 ???????????? Abdeali Kothari
> ???????:
>>
>> Hi, I recently switched from opencv to skimage as I found it much more
>> pythonic and easier to install.
>>
>> There is one feature which I seem to be missing - The Haarcascades and
>> CascadeClassifier[1]. Is there plan to add this in skimage ? I'm quite new
>> to haarcascades, but my understanding is that first there are HAAR features
>> that are found from the image and then these features are classified using
>> multiple weak classifiers (using adaboost) to "detect" an object.
>>
>> It seems to me that to get this functionality I would need skimage (to
>> create the haar features) and sklearn (for the adaboost setup). I found
>> issues/1431[2] which seems to talk about creating HAAR features.
>>
>> Am I on the right track ? Is there already some example code available
>> which uses skimage and sklearn using one of the haarcascadde xml files
>> provided by opencv ?
>>
>> Regards,
>> Abdeali JK
>>
>>
>> [1] -
>> http://docs.opencv.org/master/d7/d8b/tutorial_py_face_detection.html#gsc.tab=0
>> [2] - https://github.com/scikit-image/scikit-image/issues/1431
>>
> --
> You received this message because you are subscribed to a topic in the
> Google Groups "scikit-image" group.
> To unsubscribe from this topic, visit
> https://groups.google.com/d/topic/scikit-image/PIpELINpmek/unsubscribe.
> To unsubscribe from this group and all its topics, send an email to
> scikit-image+unsubscribe at googlegroups.com.
> To post to this group, send email to scikit-image at googlegroups.com.
> To view this discussion on the web, visit
> https://groups.google.com/d/msgid/scikit-image/bb52ccad-e9fe-4a61-b980-26778bab2267%40googlegroups.com
> <https://groups.google.com/d/msgid/scikit-image/bb52ccad-e9fe-4a61-b980-26778bab2267%40googlegroups.com?utm_medium=email&utm_source=footer>
> .
>
> For more options, visit https://groups.google.com/d/optout.
>
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From daniil.j.pakhomov at gmail.com  Mon Jun 13 19:00:27 2016
From: daniil.j.pakhomov at gmail.com (Daniil Pakhomov)
Date: Mon, 13 Jun 2016 16:00:27 -0700 (PDT)
Subject: Haarcascades implementation
In-Reply-To: <CA+BKPDW+MeSoSdycZEqpHkn7kcaCQAkzJzzBMfdo9WswLoRLXw@mail.gmail.com>
References: <0a9ab8ba-a248-46b9-9780-2d4b99e729a9@googlegroups.com> <bb52ccad-e9fe-4a61-b980-26778bab2267@googlegroups.com>
 <CA+BKPDW+MeSoSdycZEqpHkn7kcaCQAkzJzzBMfdo9WswLoRLXw@mail.gmail.com>
Message-ID: <f9009f2d-26ae-4506-bc1e-6ae7f4985321@googlegroups.com>

You are welcome.

In the original paper, the authors got better results using MB-LBP than 
using Haar features:
http://www.cbsr.ia.ac.cn/users/scliao/papers/Zhang-ICB07-MBLBP.pdf

The scikit-learn wasn't used because:
1) They don't have gentle adaboost.
2) Their implementation is based on pure Python, which is slow.

Overall, the implementation aims to provide very fast detection with good 
precision.
The implementation also enables one to use OpenMP, which makes it almost 
real-time for some cases.

???????????, 12 ???? 2016 ?., 17:54:58 UTC-7 ???????????? Abdeali Kothari 
???????:
>
> Hi Daniil,
>
> Thank you very much for that mail
>
> The LBP features do look interesting, and I had no idea OpenCV had that ! 
> It seems LBP is considerably faster than HAAR, but not as accurate[1]. 
> Which makes me wonder whether that is the right choice. Also, there are 
> more pre-trained haarcascades than lbpcascades which makes me favor 
> haarcascade more.
>
> But this implementation is something that I can read and understand how to 
> do it myself better ! Thanks :)
>
> I'm wondering as to why sklearn was not used in pull/1570 [2] ? It seems 
> to me like a lot of the code in skimage/future/detect/cascade.pyx [3] would 
> already be available there (Probably in sklearn.ensemble.AdaBoostClassifier 
> [4])? It could be made an "optional" feature which only works if sklearn is 
> installed ?
>
> Regards,
> Abdeali JK
>
> [1] - 
> http://stackoverflow.com/questions/8791178/haar-cascades-vs-lbp-cascades-in-face-detection
> [2] - https://github.com/scikit-image/scikit-image/pull/1570
> [3] - 
> https://github.com/warmspringwinds/scikit-image/blob/7face0ebbfadab299b0e2a15e95a761648639c98/skimage/future/detect/cascade.pyx
> [4] - 
> http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostClassifier.html
>
> On Mon, Jun 13, 2016 at 4:53 AM, Daniil Pakhomov <daniil.j... at gmail.com 
> <javascript:>> wrote:
>
>> Also, this might be useful:
>> http://warmspringwinds.github.io/
>>
>> ???????????, 12 ???? 2016 ?., 10:37:18 UTC-4 ???????????? Abdeali Kothari 
>> ???????:
>>>
>>> Hi, I recently switched from opencv to skimage as I found it much more 
>>> pythonic and easier to install.
>>>
>>> There is one feature which I seem to be missing - The Haarcascades and 
>>> CascadeClassifier[1]. Is there plan to add this in skimage ? I'm quite new 
>>> to haarcascades, but my understanding is that first there are HAAR features 
>>> that are found from the image and then these features are classified using 
>>> multiple weak classifiers (using adaboost) to "detect" an object.
>>>
>>> It seems to me that to get this functionality I would need skimage (to 
>>> create the haar features) and sklearn (for the adaboost setup). I found 
>>> issues/1431[2] which seems to talk about creating HAAR features.
>>>
>>> Am I on the right track ? Is there already some example code available 
>>> which uses skimage and sklearn using one of the haarcascadde xml files 
>>> provided by opencv ?
>>>
>>> Regards,
>>> Abdeali JK
>>>
>>>
>>> [1] - 
>>> http://docs.opencv.org/master/d7/d8b/tutorial_py_face_detection.html#gsc.tab=0
>>> [2] - https://github.com/scikit-image/scikit-image/issues/1431
>>>
>> -- 
>> You received this message because you are subscribed to a topic in the 
>> Google Groups "scikit-image" group.
>> To unsubscribe from this topic, visit 
>> https://groups.google.com/d/topic/scikit-image/PIpELINpmek/unsubscribe.
>> To unsubscribe from this group and all its topics, send an email to 
>> scikit-image... at googlegroups.com <javascript:>.
>> To post to this group, send email to scikit... at googlegroups.com 
>> <javascript:>.
>> To view this discussion on the web, visit 
>> https://groups.google.com/d/msgid/scikit-image/bb52ccad-e9fe-4a61-b980-26778bab2267%40googlegroups.com 
>> <https://groups.google.com/d/msgid/scikit-image/bb52ccad-e9fe-4a61-b980-26778bab2267%40googlegroups.com?utm_medium=email&utm_source=footer>
>> .
>>
>> For more options, visit https://groups.google.com/d/optout.
>>
>
>
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From stefanv at berkeley.edu  Tue Jun 14 16:51:58 2016
From: stefanv at berkeley.edu (=?UTF-8?Q?St=C3=A9fan_van_der_Walt?=)
Date: Tue, 14 Jun 2016 13:51:58 -0700
Subject: New core team member
Message-ID: <CABDkGQ=V6KyEFc-hCqYQceFQ8tN0m9CQ4VLbeF3UnRuoT05m4w@mail.gmail.com>

Hi everyone

I am happy to announce that Fran?ois Boulogne is joining the scikit-image
core team.  Welcome, Fran?ois!  We look forward to working with and
learning from you.

Best regards
St?fan
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From multicolor.mood at gmail.com  Tue Jun 14 17:00:52 2016
From: multicolor.mood at gmail.com (Egor Panfilov)
Date: Tue, 14 Jun 2016 14:00:52 -0700 (PDT)
Subject: New core team member
In-Reply-To: <CABDkGQ=V6KyEFc-hCqYQceFQ8tN0m9CQ4VLbeF3UnRuoT05m4w@mail.gmail.com>
References: <CABDkGQ=V6KyEFc-hCqYQceFQ8tN0m9CQ4VLbeF3UnRuoT05m4w@mail.gmail.com>
Message-ID: <aee881f8-6fc0-425d-abac-fdec44d14ef2@googlegroups.com>

A warm welcome to you, Francois, from Eastern Europe!

Regards,
Egor Panfilov

???????, 14 ???? 2016 ?., 23:52:20 UTC+3 ???????????? stefanv ???????:
>
> Hi everyone
>
> I am happy to announce that Fran?ois Boulogne is joining the scikit-image 
> core team.  Welcome, Fran?ois!  We look forward to working with and 
> learning from you.
>
> Best regards
> St?fan
>
>
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From stefanv at berkeley.edu  Tue Jun 14 17:29:42 2016
From: stefanv at berkeley.edu (=?UTF-8?Q?St=C3=A9fan_van_der_Walt?=)
Date: Tue, 14 Jun 2016 14:29:42 -0700
Subject: Interesting to include a the Scattering transform in sci-kit image?
In-Reply-To: <ad063b83-f44d-463a-85fe-159ba77733a8@googlegroups.com>
References: <ad063b83-f44d-463a-85fe-159ba77733a8@googlegroups.com>
Message-ID: <CABDkGQkTD7Hh=1tEh3qkndc_B-7FJvGju4_gfknu9fyLpOJs3w@mail.gmail.com>

Hi Sira, Michael

This looks very interesting!  The papers you mention are well cited, and
the classification results promising (I did some texture classification on
rock slices during my masters, and even then it seemed like wavelets would
come to dominate this domain).

I look forward to your PR & gallery example.

Thanks!
St?fan

On 13 June 2016 at 06:02, Sira Ferradans <sira.ferradans at gmail.com> wrote:

> Dear Sci-kit image developers,
>
>
> at the ENS (Paris) we are planning on implementing a Python version of the
> Scattering transform 2D and 1D. The scattering transform has proven to be
> very powerful as a descriptor for image classification and signal analysis.
> We thought that it may be useful to integrate the 2D version in the sci-kit
> image package, since it aligns well with the software package and the
> community. The idea would be to implement the functionalities following as
> much as possible the APIs you already have for similar functions. More
> specifically, we will need the following (approximately):
>
>
>                 -Morlet wavelet: Closely related to the Gabor wavelet, so
> it should take into account its API
>                 -Scattering transform: output the scattering transform
> coefficients, either for display or (as a vector) for learning purposes.
>
>
> We are attaching a small tutorial (better visualized if you download it)
> that compares the performance of the first order scattering coefficients
> computed with Gabor filters, versus the coefficients you extract in the *'Gabor
> filter banks for texture classification'
> <http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_gabor.html#example-features-detection-plot-gabor-py>*
> tutorial. The goal of this ipython notebook is to show that the
> implementation can be easily integrated in you library while providing a
> powerful tool for image analysis.
>
> If you think this is a good idea, please let us know. Moreover, it would
> be great if you could give us some guidelines that you think would make the
> process easier. We will be adhering to the instructions given on the
> contributions page, but please don't hesitate to give feedback on our PR!
>
>
> Best Regards,
>
> Michael Eickenberg and Sira Ferradans.
>
> --
> You received this message because you are subscribed to the Google Groups
> "scikit-image" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to scikit-image+unsubscribe at googlegroups.com.
> To post to this group, send email to scikit-image at googlegroups.com.
> To view this discussion on the web, visit
> https://groups.google.com/d/msgid/scikit-image/ad063b83-f44d-463a-85fe-159ba77733a8%40googlegroups.com
> <https://groups.google.com/d/msgid/scikit-image/ad063b83-f44d-463a-85fe-159ba77733a8%40googlegroups.com?utm_medium=email&utm_source=footer>
> .
> For more options, visit https://groups.google.com/d/optout.
>
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From emmanuelle.gouillart at nsup.org  Wed Jun 15 02:59:14 2016
From: emmanuelle.gouillart at nsup.org (Emmanuelle Gouillart)
Date: Wed, 15 Jun 2016 08:59:14 +0200
Subject: New core team member
In-Reply-To: <aee881f8-6fc0-425d-abac-fdec44d14ef2@googlegroups.com>
References: <CABDkGQ=V6KyEFc-hCqYQceFQ8tN0m9CQ4VLbeF3UnRuoT05m4w@mail.gmail.com>
 <aee881f8-6fc0-425d-abac-fdec44d14ef2@googlegroups.com>
Message-ID: <20160615065914.GA880925@phare.normalesup.org>

Welcome on board, Fran?ois! Thanks for your past contributions, looking
forward to your new ones :-)!

Emma

On Tue, Jun 14, 2016 at 02:00:52PM -0700, Egor Panfilov wrote:
> A warm welcome to you, Francois, from Eastern Europe!

> Regards,
> Egor Panfilov

> ???????, 14 ???? 2016 ?., 23:52:20 UTC+3 ???????????? stefanv ???????:

>     Hi everyone

>     I am happy to announce that Fran?ois Boulogne is joining the scikit-image
>     core team.? Welcome, Fran?ois!? We look forward to working with and
>     learning from you.

>     Best regards
>     St?fan


From daniil.j.pakhomov at gmail.com  Wed Jun 15 23:39:39 2016
From: daniil.j.pakhomov at gmail.com (Daniil Pakhomov)
Date: Wed, 15 Jun 2016 20:39:39 -0700 (PDT)
Subject: Testing of object detection module.
Message-ID: <65c54f16-1312-42a2-b8f9-8bcab64c2130@googlegroups.com>

Hello everyone.

I am testing an object detection module in scikit-image.
Currently I have added a face detection file.

If someone is interested and have time to test it on their PC, it would be 
great.

Just clone this branch:
https://github.com/warmspringwinds/scikit-image/tree/object_detect_module

and run cython compilation in the root of the repository:
python setup.py build_ext --inplace

After that run the object_detection.ipynb 
<https://github.com/warmspringwinds/scikit-image/blob/object_detect_module/object_detection.ipynb> ipython 
notebook file and see if it works for you.

Please, report any problems that you 'face' :P
I will appreciate any help :)
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From sira.ferradans at gmail.com  Thu Jun 16 12:18:15 2016
From: sira.ferradans at gmail.com (Sira Ferradans)
Date: Thu, 16 Jun 2016 09:18:15 -0700 (PDT)
Subject: Interesting to include a the Scattering transform in sci-kit
 image?
In-Reply-To: <CABDkGQkTD7Hh=1tEh3qkndc_B-7FJvGju4_gfknu9fyLpOJs3w@mail.gmail.com>
References: <ad063b83-f44d-463a-85fe-159ba77733a8@googlegroups.com>
 <CABDkGQkTD7Hh=1tEh3qkndc_B-7FJvGju4_gfknu9fyLpOJs3w@mail.gmail.com>
Message-ID: <9a3ccf5c-91a5-4228-b2a7-d488fc4667c8@googlegroups.com>

Hello, 
I have one implementation question now: In order to implement the 
scattering, we need the wavelet transform, with morlet filters. I saw that 
scikit-image has support for pywt, but morlet filters are not supported 
now. This leaves the only option of implementing the wavelet transform 
directly. I thought that a good idea would be to define a list of list for 
all the filters, that would be saved in the fourier domain. In this context 
the convolution of the signal with the filter would be implemented as a 
multiplication in the Fourier domain. 
Is this implementation ok? do you have any comments, maybe references where 
to see a similar code already available in scikit-image?
Thanks a lot for the possible comments and recommendations.

On Tuesday, June 14, 2016 at 11:30:03 PM UTC+2, stefanv wrote:
>
> Hi Sira, Michael
>
> This looks very interesting!  The papers you mention are well cited, and 
> the classification results promising (I did some texture classification on 
> rock slices during my masters, and even then it seemed like wavelets would 
> come to dominate this domain).
>
> I look forward to your PR & gallery example.
>
> Thanks!
> St?fan
>
> On 13 June 2016 at 06:02, Sira Ferradans <sira.fe... at gmail.com 
> <javascript:>> wrote:
>
>> Dear Sci-kit image developers, 
>>
>>
>> at the ENS (Paris) we are planning on implementing a Python version of 
>> the Scattering transform 2D and 1D. The scattering transform has proven to 
>> be very powerful as a descriptor for image classification and signal 
>> analysis. We thought that it may be useful to integrate the 2D version in 
>> the sci-kit image package, since it aligns well with the software package 
>> and the community. The idea would be to implement the functionalities 
>> following as much as possible the APIs you already have for similar 
>> functions. More specifically, we will need the following (approximately): 
>>
>>
>>                 -Morlet wavelet: Closely related to the Gabor wavelet, 
>> so it should take into account its API
>>                 -Scattering transform: output the scattering transform 
>> coefficients, either for display or (as a vector) for learning purposes. 
>>
>>
>> We are attaching a small tutorial (better visualized if you download it) 
>> that compares the performance of the first order scattering coefficients 
>> computed with Gabor filters, versus the coefficients you extract in the *'Gabor 
>> filter banks for texture classification' 
>> <http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_gabor.html#example-features-detection-plot-gabor-py>* 
>> tutorial. The goal of this ipython notebook is to show that the 
>> implementation can be easily integrated in you library while providing a 
>> powerful tool for image analysis. 
>>
>> If you think this is a good idea, please let us know. Moreover, it would 
>> be great if you could give us some guidelines that you think would make the 
>> process easier. We will be adhering to the instructions given on the 
>> contributions page, but please don't hesitate to give feedback on our PR! 
>>
>>
>> Best Regards, 
>>
>> Michael Eickenberg and Sira Ferradans. 
>>
>> -- 
>> You received this message because you are subscribed to the Google Groups 
>> "scikit-image" group.
>> To unsubscribe from this group and stop receiving emails from it, send an 
>> email to scikit-image... at googlegroups.com <javascript:>.
>> To post to this group, send email to scikit... at googlegroups.com 
>> <javascript:>.
>> To view this discussion on the web, visit 
>> https://groups.google.com/d/msgid/scikit-image/ad063b83-f44d-463a-85fe-159ba77733a8%40googlegroups.com 
>> <https://groups.google.com/d/msgid/scikit-image/ad063b83-f44d-463a-85fe-159ba77733a8%40googlegroups.com?utm_medium=email&utm_source=footer>
>> .
>> For more options, visit https://groups.google.com/d/optout.
>>
>
>
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From msarahan at gmail.com  Thu Jun 16 08:44:10 2016
From: msarahan at gmail.com (Michael Sarahan)
Date: Thu, 16 Jun 2016 12:44:10 +0000
Subject: FW: Python version of your subpixel registration code
In-Reply-To: <CANfRhPoKKvSsdm_zYG6i6hb6phqqzvR3KxM1Eqx3v_4pvQaePw@mail.gmail.com>
References: <8E2924888511274B95014C2DD906E58A0B0D2089@MAILBOX0A.psi.ch>
 <CANfRhPoo37ifMeQp2CzsW58onq9=LLjxaJRYiUOes=CxkZiccQ@mail.gmail.com>
 <CAB9hrOpSaZg_9KcfSV0UJSd1qbB2Zn_qiS9i4V_XRmqJe6Q7JQ@mail.gmail.com>
 <CANfRhPpHrh5dmC22EcUq_aQ7YR69J_-W+U8gFYT33=tNTvDCHg@mail.gmail.com> <CANfRhPoKKvSsdm_zYG6i6hb6phqqzvR3KxM1Eqx3v_4pvQaePw@mail.gmail.com>
Message-ID: <CAB9hrOqzb0_Uo5xTvWSnaxoXRQB-WesQxf52gufZ+9jfbKRGBQ@mail.gmail.com>

Manuel,

Many thanks for the good news! I have copied the scikit image mailing list
here.   Stefan was able to get permission from Prof. Fienup so that we
could include it, but this news is still excellent. Scikit image team,
please ping me on github if this news raises any issues.

Best regards,
Michael

On Thu, Jun 16, 2016, 04:21 Manuel Guizar <mguizar at gmail.com> wrote:

> Hi Michael,
>
> I am not sure if you are still interested or if this has any impact on
> your scikit contribution. Took some time but now the code is under a BSD
> license. I had to rewrite parts of it in the end.
>
>
> http://ch.mathworks.com/matlabcentral/fileexchange/18401-efficient-subpixel-image-registration-by-cross-correlation
>
> Cheers,
>
>
> --
> Manuel Guizar-Sicairos, PhD
>
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From nabil.freij at gmail.com  Thu Jun 16 06:45:32 2016
From: nabil.freij at gmail.com (Nabil Freij)
Date: Thu, 16 Jun 2016 12:45:32 +0200
Subject: Thresholding a dark region in an image
In-Reply-To: <etPan.57427a2d.38cc4305.141c@MacBook.local>
References: <CADwJ0z1Sthz7OW8uu2G2i+m9VaKPOEfnkuu+V70u-0Tjz75PMQ@mail.gmail.com>
 <etPan.57427a2d.38cc4305.141c@MacBook.local>
Message-ID: <CADwJ0z1Nwosv5tmpzaDcK3awpqE_rd814+gGKCYQ8cEKVuin7w@mail.gmail.com>

Hi Juan and Fran?ois,

Thanks for those suggestions. So from my understanding, threshold_isodata,
threshold_li, threshold_otsu and threshold_yen return values that allow me
to threshold an image. Using these on the whole image returns a threshold
value which return a value which does a good job of getting the entire
sunspot. Which can be seen in Figure 1. Varying the bin size, where
possible, changes very little. So I decided to use them on a smaller image
that shows just the sunspot and the results are very good as you can see in
Figure 2. I will carry on trying the various routines to see what the
results are.

I used the minimum algorithm when it was merged into scikit master and I
have found it to be the most useful in my cases so far. But my current
results are very rough.

Thanks for all the help!
Nabil

On 23 May 2016 at 05:34, Juan Nunez-Iglesias <jni.soma at gmail.com> wrote:

> Hi Nabil,
>
> Have you looked at the skimage.filters.threshold_* functions? I would
> start by looking at the results from each of those on a few example
> sunspots to see whether one reliably gives you a reasonable result.
>
> Juan.
>
> On 20 May 2016 at 12:26:37 AM, Nabil Freij (nabil.freij at gmail.com) wrote:
>
> Hello,
>
> I have been investigating how to threshold a structure in my images. More
> specifically, a sunspot, that can be seen in Figure 1. The aim has been to
> isolate and measure the number of pixels that are part of the central part
> of a sunspot, which is the darkest region of the structure.
>
> The method I have been using is to define a region which contains no
> features that are similar to a sunspot. The size of this region is not
> fixed but I generally make it as large as the data allows. This region is
> at the bottom black box in Figure 1 (ignore the slider). The mean and
> standard deviation of this region is calculated, which allows me to define
> a threshold limit, which is subtracting the standard deviation multiplied
> by a user defined constant from the mean. The constant is chosen so that
> overall, the threshold is selecting the pixels we know that are part of the
> central region. But this value varies depending the structure and the data
> source.
>
> Another method I have discussed or looked into are related to Figure 2. On
> the left is a cropped field of view of the sunspot and on the right is a
> histogram of this image in red and in yellow is the histogram of the
> background box from Figure 1. By using the histogram, I can work out the
> numerical gradient and pick the points with the largest shift. I also tried
> this method on the original image by taking slices along the sunspot,
> however, due to the non-uniform nature of a sunspot the results were not
> very good.
>
> I was wondering if there were any suggestions to threshold this region
> that is not as ad hoc as my method?
>
> Thanks,
> Nabil
> --
> You received this message because you are subscribed to the Google Groups
> "scikit-image" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to scikit-image+unsubscribe at googlegroups.com.
> To post to this group, send email to scikit-image at googlegroups.com.
> To view this discussion on the web, visit
> https://groups.google.com/d/msgid/scikit-image/CADwJ0z1Sthz7OW8uu2G2i%2Bm9VaKPOEfnkuu%2BV70u-0Tjz75PMQ%40mail.gmail.com
> <https://groups.google.com/d/msgid/scikit-image/CADwJ0z1Sthz7OW8uu2G2i%2Bm9VaKPOEfnkuu%2BV70u-0Tjz75PMQ%40mail.gmail.com?utm_medium=email&utm_source=footer>
> .
> For more options, visit https://groups.google.com/d/optout.
> ------------------------------
>
> --
> You received this message because you are subscribed to the Google Groups
> "scikit-image" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to scikit-image+unsubscribe at googlegroups.com.
> To post to this group, send email to scikit-image at googlegroups.com.
> To view this discussion on the web, visit
> https://groups.google.com/d/msgid/scikit-image/etPan.57427a2d.38cc4305.141c%40MacBook.local
> <https://groups.google.com/d/msgid/scikit-image/etPan.57427a2d.38cc4305.141c%40MacBook.local?utm_medium=email&utm_source=footer>
> .
> For more options, visit https://groups.google.com/d/optout.
>
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From fboulogne at sciunto.org  Thu Jun 16 16:32:41 2016
From: fboulogne at sciunto.org (=?UTF-8?Q?Fran=c3=a7ois_Boulogne?=)
Date: Thu, 16 Jun 2016 22:32:41 +0200
Subject: Interesting to include a the Scattering transform in sci-kit
 image?
In-Reply-To: <9a3ccf5c-91a5-4228-b2a7-d488fc4667c8@googlegroups.com>
References: <ad063b83-f44d-463a-85fe-159ba77733a8@googlegroups.com>
 <CABDkGQkTD7Hh=1tEh3qkndc_B-7FJvGju4_gfknu9fyLpOJs3w@mail.gmail.com>
 <9a3ccf5c-91a5-4228-b2a7-d488fc4667c8@googlegroups.com>
Message-ID: <b6073b27-f97d-f9c9-3402-148a830fda18@sciunto.org>

Le 16/06/2016 ? 18:18, Sira Ferradans a ?crit :
> Hello,
> I have one implementation question now: In order to implement the
> scattering, we need the wavelet transform, with morlet filters. I saw
> that scikit-image has support for pywt,

Not yet afaik. We have two main PR discussing this:
https://github.com/scikit-image/scikit-image/pull/1837 and
https://github.com/scikit-image/scikit-image/pull/1833

In #1837, @JDWarner voted in favor of pywavelet for 0.13. I would also
be happy to see these features coming in 0.13; I convinced Ralf to put
pywavelet on a new floating boat a couple of years ago, and scikit-image
was a motivation for me.

IMO, this could be also a killing feature for users who still hesitate
with scikit-image :)

-- 
Fran?ois Boulogne.
http://www.sciunto.org
GPG: 32D5F22F




From stefanv at berkeley.edu  Fri Jun 17 03:47:11 2016
From: stefanv at berkeley.edu (=?UTF-8?Q?St=C3=A9fan_van_der_Walt?=)
Date: Fri, 17 Jun 2016 00:47:11 -0700
Subject: FW: Python version of your subpixel registration code
In-Reply-To: <CAB9hrOqzb0_Uo5xTvWSnaxoXRQB-WesQxf52gufZ+9jfbKRGBQ@mail.gmail.com>
References: <8E2924888511274B95014C2DD906E58A0B0D2089@MAILBOX0A.psi.ch>
 <CANfRhPoo37ifMeQp2CzsW58onq9=LLjxaJRYiUOes=CxkZiccQ@mail.gmail.com>
 <CAB9hrOpSaZg_9KcfSV0UJSd1qbB2Zn_qiS9i4V_XRmqJe6Q7JQ@mail.gmail.com>
 <CANfRhPpHrh5dmC22EcUq_aQ7YR69J_-W+U8gFYT33=tNTvDCHg@mail.gmail.com>
 <CANfRhPoKKvSsdm_zYG6i6hb6phqqzvR3KxM1Eqx3v_4pvQaePw@mail.gmail.com> <CAB9hrOqzb0_Uo5xTvWSnaxoXRQB-WesQxf52gufZ+9jfbKRGBQ@mail.gmail.com>
Message-ID: <CABDkGQnXc1L361obnSSELCXJnXYAi+DpP1Xsgd_-n8v7=US7Uw@mail.gmail.com>

Hi Michael

Thanks for letting us know--as you correctly point out, our code was vetted
& approved by the original authors, so we are not affected.

Best regards
St?fan

On 16 June 2016 at 05:44, Michael Sarahan <msarahan at gmail.com> wrote:

> Manuel,
>
> Many thanks for the good news! I have copied the scikit image mailing list
> here.   Stefan was able to get permission from Prof. Fienup so that we
> could include it, but this news is still excellent. Scikit image team,
> please ping me on github if this news raises any issues.
>
> Best regards,
> Michael
>
> On Thu, Jun 16, 2016, 04:21 Manuel Guizar <mguizar at gmail.com> wrote:
>
>> Hi Michael,
>>
>> I am not sure if you are still interested or if this has any impact on
>> your scikit contribution. Took some time but now the code is under a BSD
>> license. I had to rewrite parts of it in the end.
>>
>>
>> http://ch.mathworks.com/matlabcentral/fileexchange/18401-efficient-subpixel-image-registration-by-cross-correlation
>>
>> Cheers,
>>
>>
>> --
>> Manuel Guizar-Sicairos, PhD
>>
> --
> You received this message because you are subscribed to the Google Groups
> "scikit-image" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to scikit-image+unsubscribe at googlegroups.com.
> To post to this group, send email to scikit-image at googlegroups.com.
> To view this discussion on the web, visit
> https://groups.google.com/d/msgid/scikit-image/CAB9hrOqzb0_Uo5xTvWSnaxoXRQB-WesQxf52gufZ%2B9jfbKRGBQ%40mail.gmail.com
> <https://groups.google.com/d/msgid/scikit-image/CAB9hrOqzb0_Uo5xTvWSnaxoXRQB-WesQxf52gufZ%2B9jfbKRGBQ%40mail.gmail.com?utm_medium=email&utm_source=footer>
> .
> For more options, visit https://groups.google.com/d/optout.
>
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From fboulogne at sciunto.org  Fri Jun 17 02:50:14 2016
From: fboulogne at sciunto.org (=?UTF-8?Q?Fran=c3=a7ois_Boulogne?=)
Date: Fri, 17 Jun 2016 08:50:14 +0200
Subject: Thresholding a dark region in an image
In-Reply-To: <CADwJ0z1Nwosv5tmpzaDcK3awpqE_rd814+gGKCYQ8cEKVuin7w@mail.gmail.com>
References: <CADwJ0z1Sthz7OW8uu2G2i+m9VaKPOEfnkuu+V70u-0Tjz75PMQ@mail.gmail.com>
 <etPan.57427a2d.38cc4305.141c@MacBook.local>
 <CADwJ0z1Nwosv5tmpzaDcK3awpqE_rd814+gGKCYQ8cEKVuin7w@mail.gmail.com>
Message-ID: <d19af2f8-8241-0dd4-9fbf-098a8e319259@sciunto.org>

Le 16/06/2016 ? 12:45, Nabil Freij a ?crit :
> Hi Juan and Fran?ois,
>
> Thanks for those suggestions. So from my
> understanding, threshold_isodata, threshold_li, threshold_otsu and
> threshold_yen return values that allow me to threshold an image. Using
> these on the whole image returns a threshold value which return a
> value which does a good job of getting the entire sunspot. Which can
> be seen in Figure 1. Varying the bin size, where possible, changes
> very little. So I decided to use them on a smaller image that shows
> just the sunspot and the results are very good as you can see in
> Figure 2. I will carry on trying the various routines to see what the
> results are. 
>
> I used the minimum algorithm when it was merged into scikit master and
> I have found it to be the most useful in my cases so far. But my
> current results are very rough.  
>

You can give a try to multiotsu.
https://github.com/scikit-image/scikit-image/pull/2076
It's not merged yet, there is a missing import (from skimage.util import
img_as_float). For the rest, it should be good enough for a quick test. :)

Feel free to comment on this one.

-- 
Fran?ois Boulogne.
http://www.sciunto.org
GPG: 32D5F22F




From silvertrumpet999 at gmail.com  Fri Jun 17 20:53:27 2016
From: silvertrumpet999 at gmail.com (Josh Warner)
Date: Fri, 17 Jun 2016 17:53:27 -0700 (PDT)
Subject: FW: Python version of your subpixel registration code
In-Reply-To: <CABDkGQnXc1L361obnSSELCXJnXYAi+DpP1Xsgd_-n8v7=US7Uw@mail.gmail.com>
References: <8E2924888511274B95014C2DD906E58A0B0D2089@MAILBOX0A.psi.ch>
 <CANfRhPoo37ifMeQp2CzsW58onq9=LLjxaJRYiUOes=CxkZiccQ@mail.gmail.com>
 <CAB9hrOpSaZg_9KcfSV0UJSd1qbB2Zn_qiS9i4V_XRmqJe6Q7JQ@mail.gmail.com>
 <CANfRhPpHrh5dmC22EcUq_aQ7YR69J_-W+U8gFYT33=tNTvDCHg@mail.gmail.com>
 <CANfRhPoKKvSsdm_zYG6i6hb6phqqzvR3KxM1Eqx3v_4pvQaePw@mail.gmail.com> <CAB9hrOqzb0_Uo5xTvWSnaxoXRQB-WesQxf52gufZ+9jfbKRGBQ@mail.gmail.com>
 <CABDkGQnXc1L361obnSSELCXJnXYAi+DpP1Xsgd_-n8v7=US7Uw@mail.gmail.com>
Message-ID: <2bed7f50-70fb-4f39-9660-a3c59561e64d@googlegroups.com>

Tangentially related: 

I'd very much like to see a highly accurate rotational/angular registration 
algorithm added to scikit-image to complement this one. From my own 
experience, when combining a bracketed set into HDR images the alignment 
must be near-perfect. This does a great job for translation, but often 
there's a rotational component also. 

I've got another great advanced tutorial example brewing, but need highly 
accurate rotational registration to make it really properly robust...

Josh

On Friday, June 17, 2016 at 2:47:33 AM UTC-5, stefanv wrote:
>
> Hi Michael
>
> Thanks for letting us know--as you correctly point out, our code was 
> vetted & approved by the original authors, so we are not affected.
>
> Best regards
> St?fan
>
> On 16 June 2016 at 05:44, Michael Sarahan <msarahan at gmail.com> wrote:
>
>> Manuel, 
>>
>> Many thanks for the good news! I have copied the scikit image mailing 
>> list here.   Stefan was able to get permission from Prof. Fienup so that we 
>> could include it, but this news is still excellent. Scikit image team, 
>> please ping me on github if this news raises any issues. 
>>
>> Best regards, 
>> Michael 
>>
>> On Thu, Jun 16, 2016, 04:21 Manuel Guizar <mguizar at gmail.com> wrote:
>>
>>> Hi Michael,
>>>
>>> I am not sure if you are still interested or if this has any impact on 
>>> your scikit contribution. Took some time but now the code is under a BSD 
>>> license. I had to rewrite parts of it in the end.
>>>
>>>
>>> http://ch.mathworks.com/matlabcentral/fileexchange/18401-efficient-subpixel-image-registration-by-cross-correlation
>>>
>>> Cheers,
>>>
>>>
>>> --
>>> Manuel Guizar-Sicairos, PhD
>>>
>> -- 
>> You received this message because you are subscribed to the Google Groups 
>> "scikit-image" group.
>> To unsubscribe from this group and stop receiving emails from it, send an 
>> email to scikit-image+unsubscribe at googlegroups.com.
>> To post to this group, send email to scikit-image at googlegroups.com.
>> To view this discussion on the web, visit 
>> https://groups.google.com/d/msgid/scikit-image/CAB9hrOqzb0_Uo5xTvWSnaxoXRQB-WesQxf52gufZ%2B9jfbKRGBQ%40mail.gmail.com 
>> <https://groups.google.com/d/msgid/scikit-image/CAB9hrOqzb0_Uo5xTvWSnaxoXRQB-WesQxf52gufZ%2B9jfbKRGBQ%40mail.gmail.com?utm_medium=email&utm_source=footer>
>> .
>> For more options, visit https://groups.google.com/d/optout.
>>
>
>
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From silvertrumpet999 at gmail.com  Fri Jun 17 20:58:01 2016
From: silvertrumpet999 at gmail.com (Josh Warner)
Date: Fri, 17 Jun 2016 17:58:01 -0700 (PDT)
Subject: Interesting to include a the Scattering transform in sci-kit
 image?
In-Reply-To: <b6073b27-f97d-f9c9-3402-148a830fda18@sciunto.org>
References: <ad063b83-f44d-463a-85fe-159ba77733a8@googlegroups.com>
 <CABDkGQkTD7Hh=1tEh3qkndc_B-7FJvGju4_gfknu9fyLpOJs3w@mail.gmail.com>
 <9a3ccf5c-91a5-4228-b2a7-d488fc4667c8@googlegroups.com>
 <b6073b27-f97d-f9c9-3402-148a830fda18@sciunto.org>
Message-ID: <956a9c33-4998-435a-91fb-1d93d0d4f152@googlegroups.com>

I'll come out in favor of a required wavelet dependency again here. We need 
that domain. 

Wavelet coefficients are features (should be present in skimage.feature), 
their coefficients sparsely describe images which is useful both for 
compression and denoising (skimage.restoration), and that's just off the 
top of my head. There are immediate uses we just can't add until we can 
depend on wavelet functionality.

IMHO of course.

Josh

On Thursday, June 16, 2016 at 3:32:44 PM UTC-5, Fran?ois Boulogne wrote:
>
> Le 16/06/2016 ? 18:18, Sira Ferradans a ?crit : 
> > Hello, 
> > I have one implementation question now: In order to implement the 
> > scattering, we need the wavelet transform, with morlet filters. I saw 
> > that scikit-image has support for pywt, 
>
> Not yet afaik. We have two main PR discussing this: 
> https://github.com/scikit-image/scikit-image/pull/1837 and 
> https://github.com/scikit-image/scikit-image/pull/1833 
>
> In #1837, @JDWarner voted in favor of pywavelet for 0.13. I would also 
> be happy to see these features coming in 0.13; I convinced Ralf to put 
> pywavelet on a new floating boat a couple of years ago, and scikit-image 
> was a motivation for me. 
>
> IMO, this could be also a killing feature for users who still hesitate 
> with scikit-image :) 
>
> -- 
> Fran?ois Boulogne. 
> http://www.sciunto.org 
> GPG: 32D5F22F 
>
>
>
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From jni.soma at gmail.com  Tue Jun 21 18:02:11 2016
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Tue, 21 Jun 2016 18:02:11 -0400
Subject: Do all functions return float64 dtype?
In-Reply-To: <3ca4a0a3-4d44-4fb7-b04c-7601d9ad3bd4@googlegroups.com>
References: <3ca4a0a3-4d44-4fb7-b04c-7601d9ad3bd4@googlegroups.com>
Message-ID: <CA+JHcKTm9rS4gQkAOMyzNToFtU29h9yg-1YfAAzWzMuGV0jH6w@mail.gmail.com>

Hi Simone,

Sorry for the long gap in response time!

Most functions indeed work with float64, and this is not easy to fix,
unfortunately. For some functions, you can provide an `out=` argument where
you pre-allocate an array with whatever type you want.

Depending on your workflow, we might be able to help you avoid float64. In
many cases, we would welcome contributions to make specific functions more
flexible about their return type/inner workings.

Juan.

On Tue, Jun 7, 2016 at 7:11 AM, Simone Codeluppi <simone at codeluppi.org>
wrote:

> Hi
> I was just wondering if the majority of the skimage functions return
> float64 as default dtype. I am processing a big dataset and saving the data
> as float64 increase the size quite a bit (compared to float32). Is there
> also an additional computational cost in processing float64 instead of
> float32?  Beside the precision level is there any advantage in using
> float64?
> Thanks a lot!
>
> Simone
>
> --
> You received this message because you are subscribed to the Google Groups
> "scikit-image" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to scikit-image+unsubscribe at googlegroups.com.
> To post to this group, send email to scikit-image at googlegroups.com.
> To view this discussion on the web, visit
> https://groups.google.com/d/msgid/scikit-image/3ca4a0a3-4d44-4fb7-b04c-7601d9ad3bd4%40googlegroups.com
> <https://groups.google.com/d/msgid/scikit-image/3ca4a0a3-4d44-4fb7-b04c-7601d9ad3bd4%40googlegroups.com?utm_medium=email&utm_source=footer>
> .
> For more options, visit https://groups.google.com/d/optout.
>
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From jni.soma at gmail.com  Tue Jun 21 18:04:28 2016
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Tue, 21 Jun 2016 18:04:28 -0400
Subject: Genetic Algorithms based feature extraction algorithm (by
 minimizing a metric)
In-Reply-To: <b151d21c-cf0b-4892-8910-f89f0c772064@googlegroups.com>
References: <b151d21c-cf0b-4892-8910-f89f0c772064@googlegroups.com>
Message-ID: <CA+JHcKSEW7KiY7v40ZAmBmWmToyWkes4MP42B4T-CX=EeDXttg@mail.gmail.com>

Hi Hakim!

I haven't seen something like what you're mentioning but I'm intrigued! If
you can point to papers etc that implement something like this, we might be
interested in including it in scikit-image. However, we only accept
established algorithms, not the latest and greatest thing.

Juan.

On Sun, May 29, 2016 at 6:46 PM, Hakim Benoudjit <h.benoudjit at gmail.com>
wrote:

> Hello,
>
> Is there a pixel-based region growing algorithm implemented with
> Scikit-image that would be employed for feature extraction on an image?
> Basically, the kind of algorithms I'm looking for (or just checking if
> someone came across it, to see if I'm in the right direction) works by
> adding pixels to the detected feature based on the minimization of a
> certain metric. Potentially, a pixel can be removed if the metric is not
> optimized when this pixel is added.
>
> I'm thinking of implementing this feature extraction algorithm using
> Genetic Algorithms (GA), but I can't think of a way to make it possible to
> backtrack (i.e. remove a pixel).
> Anyone encountered something similar even if it's not using GAs?
>
> --
> You received this message because you are subscribed to the Google Groups
> "scikit-image" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to scikit-image+unsubscribe at googlegroups.com.
> To post to this group, send email to scikit-image at googlegroups.com.
> To view this discussion on the web, visit
> https://groups.google.com/d/msgid/scikit-image/b151d21c-cf0b-4892-8910-f89f0c772064%40googlegroups.com
> <https://groups.google.com/d/msgid/scikit-image/b151d21c-cf0b-4892-8910-f89f0c772064%40googlegroups.com?utm_medium=email&utm_source=footer>
> .
> For more options, visit https://groups.google.com/d/optout.
>
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From silvertrumpet999 at gmail.com  Wed Jun 22 20:49:00 2016
From: silvertrumpet999 at gmail.com (Josh Warner)
Date: Wed, 22 Jun 2016 17:49:00 -0700 (PDT)
Subject: Genetic Algorithms based feature extraction algorithm (by
 minimizing a metric)
In-Reply-To: <CA+JHcKSEW7KiY7v40ZAmBmWmToyWkes4MP42B4T-CX=EeDXttg@mail.gmail.com>
References: <b151d21c-cf0b-4892-8910-f89f0c772064@googlegroups.com>
 <CA+JHcKSEW7KiY7v40ZAmBmWmToyWkes4MP42B4T-CX=EeDXttg@mail.gmail.com>
Message-ID: <52eb28c9-cbb8-4d1c-91c0-9b5b6043c366@googlegroups.com>

Genetic algorithms are good at minimizing difficult, non-convex spaces so I 
imagine the foundations for such would be useful for image segmentation via 
expectation minimization as well.

Josh

On Tuesday, June 21, 2016 at 5:04:49 PM UTC-5, Juan Nunez-Iglesias wrote:
>
> Hi Hakim!
>
> I haven't seen something like what you're mentioning but I'm intrigued! If 
> you can point to papers etc that implement something like this, we might be 
> interested in including it in scikit-image. However, we only accept 
> established algorithms, not the latest and greatest thing.
>
> Juan.
>
> On Sun, May 29, 2016 at 6:46 PM, Hakim Benoudjit <h.benoudjit at gmail.com> 
> wrote:
>
>> Hello,
>>
>> Is there a pixel-based region growing algorithm implemented with 
>> Scikit-image that would be employed for feature extraction on an image? 
>> Basically, the kind of algorithms I'm looking for (or just checking if 
>> someone came across it, to see if I'm in the right direction) works by 
>> adding pixels to the detected feature based on the minimization of a 
>> certain metric. Potentially, a pixel can be removed if the metric is not 
>> optimized when this pixel is added.
>>
>> I'm thinking of implementing this feature extraction algorithm using 
>> Genetic Algorithms (GA), but I can't think of a way to make it possible to 
>> backtrack (i.e. remove a pixel).
>> Anyone encountered something similar even if it's not using GAs?
>>
>> -- 
>> You received this message because you are subscribed to the Google Groups 
>> "scikit-image" group.
>> To unsubscribe from this group and stop receiving emails from it, send an 
>> email to scikit-image+unsubscribe at googlegroups.com.
>> To post to this group, send email to scikit-image at googlegroups.com.
>> To view this discussion on the web, visit 
>> https://groups.google.com/d/msgid/scikit-image/b151d21c-cf0b-4892-8910-f89f0c772064%40googlegroups.com 
>> <https://groups.google.com/d/msgid/scikit-image/b151d21c-cf0b-4892-8910-f89f0c772064%40googlegroups.com?utm_medium=email&utm_source=footer>
>> .
>> For more options, visit https://groups.google.com/d/optout.
>>
>
>
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From sja353 at nyu.edu  Thu Jun 23 20:30:36 2016
From: sja353 at nyu.edu (sja353 at nyu.edu)
Date: Thu, 23 Jun 2016 17:30:36 -0700 (PDT)
Subject: Import error when importing from skimage.transform
Message-ID: <d7a8d058-2202-424e-b6b4-b4cd85c1811e@googlegroups.com>



The environment I'm using is a Jupyter notebook running python 3.5. I can import other packages, but importing anything from skimage.transform results in the following error:


ImportError                               Traceback (most recent call last)<ipython-input-19-741b6a154664> in <module>()----> 1 from skimage.transform import resize
/home/jupyter/anaconda3/envs/py35/lib/python3.5/site-packages/skimage/transform/__init__.py in <module>()----> 1 from .hough_transform import (hough_line, hough_line_peaks,      2                               probabilistic_hough_line, hough_circle,      3                               hough_ellipse)      4 from .radon_transform import radon, iradon, iradon_sart      5 from .finite_radon_transform import frt2, ifrt2
/home/jupyter/anaconda3/envs/py35/lib/python3.5/site-packages/skimage/transform/hough_transform.py in <module>()      2 from scipy import ndimage as ndi      3 from .. import measure----> 4 from ._hough_transform import (_hough_circle,      5                                hough_ellipse as _hough_ellipse,      6                                hough_line as _hough_line,
ImportError: cannot import name '_hough_circle'


We've already tried uninstalling skimage, updating cython and then re-installing. Anyone else encounter this problem?

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From jni.soma at gmail.com  Fri Jun 24 14:30:59 2016
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Fri, 24 Jun 2016 14:30:59 -0400
Subject: Import error when importing from skimage.transform
In-Reply-To: <d7a8d058-2202-424e-b6b4-b4cd85c1811e@googlegroups.com>
References: <d7a8d058-2202-424e-b6b4-b4cd85c1811e@googlegroups.com>
Message-ID: <CA+JHcKRXyKg1mJ1CygqK0V08mZARp3wpEkSXD2tmfMRaEy=g3g@mail.gmail.com>

This usually has to do with an incorrect build of scikit-image. Can you
tell us how you "reinstalled" scikit-image? My guess is that you either:

- did not actually compile the Cython files (pyx -> c -> so), or
- compiled in-place but did not install to your Python environment, or
- compiled and installed to Python environment but running from
scikit-image source directory, which often causes Python's import machinery
to get confused.

If you can give us more details about your Python install and how you're
running your notebook, we might be able to help diagnose the problem!

One nice trick to do is:

>>> import skimage
>>> skimage

The output should show you *which* skimage file you are loading when
importing.

Juan.

On Thu, Jun 23, 2016 at 8:30 PM, <sja353 at nyu.edu> wrote:

> The environment I'm using is a Jupyter notebook running python 3.5. I can import other packages, but importing anything from skimage.transform results in the following error:
>
>
> ImportError                               Traceback (most recent call last)<ipython-input-19-741b6a154664> in <module>()----> 1 from skimage.transform import resize
> /home/jupyter/anaconda3/envs/py35/lib/python3.5/site-packages/skimage/transform/__init__.py in <module>()----> 1 from .hough_transform import (hough_line, hough_line_peaks,      2                               probabilistic_hough_line, hough_circle,      3                               hough_ellipse)      4 from .radon_transform import radon, iradon, iradon_sart      5 from .finite_radon_transform import frt2, ifrt2
> /home/jupyter/anaconda3/envs/py35/lib/python3.5/site-packages/skimage/transform/hough_transform.py in <module>()      2 from scipy import ndimage as ndi      3 from .. import measure----> 4 from ._hough_transform import (_hough_circle,      5                                hough_ellipse as _hough_ellipse,      6                                hough_line as _hough_line,
> ImportError: cannot import name '_hough_circle'
>
>
> We've already tried uninstalling skimage, updating cython and then re-installing. Anyone else encounter this problem?
>
> --
> You received this message because you are subscribed to the Google Groups
> "scikit-image" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to scikit-image+unsubscribe at googlegroups.com.
> To post to this group, send email to scikit-image at googlegroups.com.
> To view this discussion on the web, visit
> https://groups.google.com/d/msgid/scikit-image/d7a8d058-2202-424e-b6b4-b4cd85c1811e%40googlegroups.com
> <https://groups.google.com/d/msgid/scikit-image/d7a8d058-2202-424e-b6b4-b4cd85c1811e%40googlegroups.com?utm_medium=email&utm_source=footer>
> .
> For more options, visit https://groups.google.com/d/optout.
>
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From jaredalewis at gmail.com  Sat Jun 25 22:21:42 2016
From: jaredalewis at gmail.com (Jared Lewis)
Date: Sat, 25 Jun 2016 19:21:42 -0700 (PDT)
Subject: Image differencing / Change detection : Implementation problem
Message-ID: <25a28f5b-473c-4fd8-a5f1-9c8ef3b14b2b@googlegroups.com>

Hi all,

I am attempting to create an image differencing script using scikit-image. 
Essentially, I would like to subtract one image from the other. Since the 
images are numpy arrays it should be possible to calculate the difference 
between images and then plot the result as an image. However, my result is 
consistently an array with a singular value,  i.e. values are all the same. 
 Below is a sample script using the built-in skimage imagery data. In this 
case the output is an array where all values are 156. Interestingly, when I 
add the image objects, it works. Any help would be much appreciated.



import skimage
from skimage import io, data
import matplotlib.pyplot as plt
import numpy as np

im = data.moon()
im2 = data.moon() + 100
im3 = im -im2


plt.imshow(im3, interpolation= 'nearest')




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From multicolor.mood at gmail.com  Sun Jun 26 01:11:19 2016
From: multicolor.mood at gmail.com (Egor Panfilov)
Date: Sat, 25 Jun 2016 22:11:19 -0700 (PDT)
Subject: Image differencing / Change detection : Implementation problem
In-Reply-To: <25a28f5b-473c-4fd8-a5f1-9c8ef3b14b2b@googlegroups.com>
References: <25a28f5b-473c-4fd8-a5f1-9c8ef3b14b2b@googlegroups.com>
Message-ID: <cd0dea28-caae-453f-878d-e9af4a3b52a9@googlegroups.com>

Hi Jared,

The output of your code is correct.
I'm not sure what kind of behaviour you are looking for.

im = data.moon()
> im2 = data.moon() + 100
> im3 = im -im2


Both `im`, 'im2` and, therefore, `im3` are arrays of uin8.
Basically, im - im2 = moon() - (moon() + 100) = -100 = (underflows because 
of uint8) = 256-100 = 156.
For im + im2 = moon() + (moon() + 100) = 2*moon() + 100 = {moon() is not 
single valued} = something varying.

If this doesn't anwsers your question, could you elaborate more on it?

Cheers,
Egor

???????????, 26 ???? 2016 ?., 5:21:42 UTC+3 ???????????? Jared Lewis 
???????:
>
> Hi all,
>
> I am attempting to create an image differencing script using scikit-image. 
> Essentially, I would like to subtract one image from the other. Since the 
> images are numpy arrays it should be possible to calculate the difference 
> between images and then plot the result as an image. However, my result is 
> consistently an array with a singular value,  i.e. values are all the same. 
>  Below is a sample script using the built-in skimage imagery data. In this 
> case the output is an array where all values are 156. Interestingly, when I 
> add the image objects, it works. Any help would be much appreciated.
>
>
>
> import skimage
> from skimage import io, data
> import matplotlib.pyplot as plt
> import numpy as np
>
> im = data.moon()
> im2 = data.moon() + 100
> im3 = im -im2
>
>
> plt.imshow(im3, interpolation= 'nearest')
>
>
>
>
>
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From robbmcleod at gmail.com  Thu Jun 30 14:09:20 2016
From: robbmcleod at gmail.com (Robert McLeod)
Date: Thu, 30 Jun 2016 11:09:20 -0700 (PDT)
Subject: Speedy IO for multi-page compressed TIFF
Message-ID: <99f3218c-cceb-4dab-921f-d811a81c2cd2@googlegroups.com>

Hi everyone,

I have some questions about IO plugins.  Namely I want to import image 
stacks, say 20 x 4096 x 4096 x int8, that have been compressed (LZW 
normally). I did some benchmarking of various skimage.io plugins:

'tifffile' was about 16 s
'pil' was about 5.5 s
'freeimage' was about 0.13 s but only imports page 0 !

If we project the 'freeimage' time it's about twice as fast as PILlow, so I 
would prefer to use it as the preferred plugin, but the single-page issue 
is a show stopper.  Can anyone comment on the 'freeimage' plugin, since I 
know in C++ it's capable of handling multipage TIFFs what the problem is 
here?

Sincerely,

Robert

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From barbara.collignon at gmail.com  Thu Jun 30 16:19:55 2016
From: barbara.collignon at gmail.com (Barbara Collignon)
Date: Thu, 30 Jun 2016 13:19:55 -0700 (PDT)
Subject: Import error when importing from skimage.transform
In-Reply-To: <d7a8d058-2202-424e-b6b4-b4cd85c1811e@googlegroups.com>
References: <d7a8d058-2202-424e-b6b4-b4cd85c1811e@googlegroups.com>
Message-ID: <98b2c001-1f06-482f-b800-6e09438e6b86@googlegroups.com>

same issue here with python2.7+

On Thursday, June 23, 2016 at 8:30:36 PM UTC-4, sja... at nyu.edu wrote:
>
> The environment I'm using is a Jupyter notebook running python 3.5. I can import other packages, but importing anything from skimage.transform results in the following error:
>
>
> ImportError                               Traceback (most recent call last)<ipython-input-19-741b6a154664> in <module>()----> 1 from skimage.transform import resize
> /home/jupyter/anaconda3/envs/py35/lib/python3.5/site-packages/skimage/transform/__init__.py in <module>()----> 1 from .hough_transform import (hough_line, hough_line_peaks,      2                               probabilistic_hough_line, hough_circle,      3                               hough_ellipse)      4 from .radon_transform import radon, iradon, iradon_sart      5 from .finite_radon_transform import frt2, ifrt2
> /home/jupyter/anaconda3/envs/py35/lib/python3.5/site-packages/skimage/transform/hough_transform.py in <module>()      2 from scipy import ndimage as ndi      3 from .. import measure----> 4 from ._hough_transform import (_hough_circle,      5                                hough_ellipse as _hough_ellipse,      6                                hough_line as _hough_line,
> ImportError: cannot import name '_hough_circle'
>
>
> We've already tried uninstalling skimage, updating cython and then re-installing. Anyone else encounter this problem?
>
>
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