[Scilab-users] Scilab Computer Vision Module

[Tan Chin Luh]

Hi Simon,

Thanks for your comments. Just to add, IPCV is modified from SIVP, with 
extra features. 1-2 functions were taken from IPD and SIP quite some 
time ago.

 From my opinion, the common issues of all the module above are :
1. Distributing the binary cross platform, which always give the issue 
of lib version.
2. Functions from the OPENCV are "link" to Scilab with individual 
gateway, which lead to the limited functions depending on the developer.
3. Data passing and sharing between Scilab and OpenCV

 From the look of it, the scicv seems to have solved the first 2 issues, 
and near to 1k functions in OPENCV seems to have included in the dll, 
which I believe it break the bottle neck of which others (including me) 
facing. I wonder was it hand-coded? As for number 3, I believe everyone 
might have different opinion.

Yes you're right, for the moment there should be more modules, as OpenCV 
functions are being used in different functions to perform a high level 
task in Scilab, which I believe all developers would have their own way 
to do so. Eventually I believe once the framework/basic have setup, we 
could move towards it.

Just my 2 cents, sorry if any of my statements sound wrong.

Thanks.

Regards,
Chin Luh



On 25/4/2017 4:35 PM, simon.marchetto at scilab-enterprises.com wrote:
> Hello,
>
> Thanks very much for your support.
>
> I was also very impressed about the new IPCV module, the number and 
> quality of available functions ! Particularly those related to GUI 
> manipulation, that we really missed, in comparison with Matlab.
> We really appreciate your work.
>
> For years we have been wanting to provide and support an image 
> processing toolbox, because this kind of toolboxes is among the most 
> used, at least downloaded, by the Scilab community.
>
> Yes indeed there are some image processing toolboxes now, especially 
> based on OpenCV, but no so much, if you compare with the huge number 
> available for Python.
> For me several (good) toolboxes is definitely better than one at this 
> moment. And they can have all different purposes, and follow different 
> choices in design.
>
> About hidden functions in sciCV, they will be more and more 
> documented, version after version.
>
> Regards,
>
> Simon Marchetto
>
>
> Le 2017-04-25 05:52, Tan Chin Luh a écrit :
>> Hi,
>>
>> It is great to have the new computer vision released on atoms,
>> especially a module which is created by Scilab Enterprises.
>>
>> After so long there are many image processing and computer vision
>> modules in atoms, which have their pros and cons, and this new module
>> finally allows the call of almost all functions (if not all :) ) to
>> the OpenCV 2.4.13 through its gateway function although not all are
>> documented. I believe it will be coming very soon.
>>  To make it better I think we could share some of our finding of the
>> "hidden" functions" while waiting for the module update, the following
>> code perform the image inpaint algo:
>>
>> scicv_Init();
>>
>> S = imread(getSampleImage("blobs.jpg"));
>>
>> // Creating mask to remove the object at 2nd row, 2nd col. This would
>> be easier after the support of the insertion for Mat implemented as
>> stated in help file
>> m1 = uint8(zeros(Mat_rows_get(S),Mat_cols_get(S)));
>> m1(110:200,150:250) = 255;
>> imwrite('mymask.jpg',m1);
>>
>> mask = imread('mymask.jpg',CV_LOAD_IMAGE_GRAYSCALE);
>>
>> S2 = inpaint(S,mask,3,INPAINT_NS);
>> matplot(S2)
>>
>>  Regards,
>>  Chin Luh
>>
>>
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>