[scikit-image] 回复： Numba on pypi

[Thomas Walter]

Hi YXDragon,

just a word on some aspect you mention:

 > the local_max has not a tolerance, so the result is too massy, then 
do a watershed end with too many fragments...,

The definition that underlies this function is: "A local maximum is a 
region of constant grey level strictly greater than the grey levels of 
all pixels in direct neighborhood of the region." - There is no 
tolerance associated to this definition, and I am perfectly fine with 
this. There are definitely many cases where you want to extract all 
local maxima. Nevertheless, there are other functions for detection of 
maxima that allow one to also impose certain criteria (such as h_maxima 
or peak_local_max).

A question to Stéfan: would this mean that you would remove all cython 
code from scikit-image or would numba just be another option?

Best,

Thomas.

On 7/13/17 8:49 AM, imagepy at sina.com wrote:
> Hi Stéfan:
>
>   I appreciate Numba. for sometimes, we must do a 'for' in our python 
> code, but just a 'for' with a 'if', It is fussy to compile a so/dll or 
> write cython. Numba is very portable, and can run anywhere, just need 
> to install numba and llvmlite. (That means our package could be a 
> light-weight library, undepended any native so/dll)
>
>   As I metioned befor, many scikit-image's algrisms are not exquisite 
> enough(just my own opinion),
>       the mid_axi function results too many branch and sometimes with 
> hols,
>       the local_max has not a tolerance, so the result is too massy, 
> then do a watershed end with too many fragments...,
>       and how to build a graph from the skeleton, then do a network 
> analysis.
>
> I want to do a contribute to scikit-image, But after some effort, I 
> give up, I prefor to write a dynamic lib rather then Cython. In the 
> end, I wrote them in Numba. So I appreciate to use Numba.
>
> Best
> YXDragon
>
> ----- 原始邮件 -----
> 发件人：Stefan van der Walt <stefanv at berkeley.edu>
> 收件人：scikit-image at python.org
> 主题：[scikit-image] Numba on pypi
> 日期：2017年07月13日 14点17分
>
> Hi everyone,
> As many of you know, speed has been a point of contention in
> scikit-image for a long time. We've made a very deliberate decision to
> focus on writing high-level, understandable code (via Python and
> Cython): both to lower the barrier to entry for newcomers, and to lessen
> the burden on maintainers. But execution time comparisons, vs OpenCV
> e.g., left much to be desired.
> I think we have hit a turning point in the road. Binary wheels for
> Numba (actually, llvmlite) were recently uploaded to PyPi, making this
> technology available to users on both pip and conda installations. The
> importance of this release on pypi should not be dismissed, and I am
> grateful to the numba team and Continuum for making that decision.
> So, how does that impact scikit-image? Well, imagine we choose to
> optimize various procedures via numba (see Juan's blog post for exactly
> how impactful this can be:
> https://ilovesymposia.com/2017/03/15/prettier-lowlevelcallables-with-numba-jit-and-decorators/).
> The only question we have to answer (from a survival point of view)
> needs to be: if, somehow, something happens to numba, will an
> alternative will be available at that time? Looking at the Python JIT
> landscape (which is very active), and the current state of numba
> development, I think this is likely. And, if we choose to use numba, of
> course we'll help to keep it healthy, as far as we can.
> I'd love to hear your thoughts. I, for one, am excited about the
> prospect of writing kernels as simply as:
> >>> @jit_filter_function
> ... def fmin(values):
> ... result = np.inf
> ... for v in values:
> ... if v < result:
> ... result = v
> ... return result
> >>> ndi.generic_filter(image, fmin, footprint=fp)
> Best regards
> Stéfan
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-- 
Thomas Walter
27 rue des Acacias
75017 Paris

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