[Scilab-users] Scilab Computer Vision Module

[simon.marchetto at scilab-enterprises.com]

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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