Image Feature Suggestion

[Ronnie Ghose]

so my question is should 'the wheel be reinvented' in numpy world?


On Thu, Apr 18, 2013 at 7:38 PM, Josh Warner <silvertrumpet999 at gmail.com>wrote:

> I've found that within the universe of SciPy +extensions (like the various
> SciKits, really anything that likes NumPy arrays) it's fairly easy to get
> things to play nice without much trouble.
>
> Interlacing algorithms from there with OpenCV, SimpleITK, VTK, and the
> like are more of a chore. They all exist in their own worlds as far as
> internal datatypes, syntax structure, etc. Nowhere near as friendly to hack
> together (it can be done, with order(s) of magnitude more effort). However,
> certain packages in the SciPy universe use these, usually wrapped such that
> the user never sees it.  E.g. Mayavi uses VTK heavily, and Scikit-Image now
> has a SimpleITK plugin for io - but they're wrapped to users only have to
> deal with Python/NumPy.
>
> In my opinion there is definite value in ports, though they should
> probably take somewhat lower priority than new/novel work.
>
>
> On Thursday, April 18, 2013 2:24:29 PM UTC-5, Ronnie Ghose wrote:
>
>> So first off is there a sort of to-do list? Secondly, should scikit-image
>> be used in conjunction with OpenCV? I thought in general it would be
>> standalone like a few of the other scikits or numpy/scipy (standalone in
>> the sense of only using other python libraries as dependencies).
>>
>>
>> On Thu, Apr 18, 2013 at 12:50 PM, Zachary Pincus <zachary... at yale.edu>wrote:
>>
>>> > Would this be a useful thing to add then? I thought it was interesting
>>> you made references to OpenCV rather then internal options.
>>>
>>> Yeah, but no need to reinvent the wheel. OpenCV is really focused on
>>> algorithms for cameras-moving-around-in-the-**world, which big chunks
>>> of your problem are. So if you want to port some of that code over to
>>> skimage, that would be a cool and useful contribution! But if you just
>>> wanted to solve your problem ASAP, then OpenCV might be your best
>>> resource...
>>>
>>> Zach
>>>
>>> PS. Fun story: a while ago I got a sparse optical-flow algorithm (using
>>> cross-correlation) running on a GPU. It was totally non-portable (pre-CUDA,
>>> custom-shader code), and it didn't actually work precisely right, but I
>>> think that it's something that shouldn't be too much trouble to actually
>>> make happen these days...
>>>
>>>
>>> > On Thu, Apr 18, 2013 at 8:19 AM, Stéfan van der Walt <ste... at sun.ac.za>
>>> wrote:
>>> > On Wed, Apr 17, 2013 at 11:16 PM, Zachary Pincus
>>> > <zachary... at yale.edu> wrote:
>>> > > Identifying features to track between frames is a pretty classic
>>> task in computer vision. Things that come to mind would include the simple
>>> Harris corner detector (in skimage), or more recent things like SIFT
>>> features and its variants like SURF etc. (DAISY is in skimage) might be of
>>> use. All of these tools should be in OpenCV too, IIRC. (Time to spend a
>>> while on wikipedia reading about these things and related, if it's all
>>> totally unfamiliar.)
>>> >
>>> > Having binary features (there are many) and Star Features (also known
>>> > as "Consensus") in skimage would be very valuable.
>>> >
>>> > > Alternately, you could try optical flow based techniques to densely
>>> track local pixel patches between frames.
>>> >
>>> > That's also a fun application, and a good way to learn Cython!
>>> >
>>> > Stéfan
>>> >
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