I've commited the changes.
-fix doxygen in headers
-test now run using otb-data input (but validation data needs to exist
somewhere... I keep one test result in "test" directory)
I removed images from my git. However I guess ideal tests must be ran on
special data (I need partly overlapping images, better if they are RGB or
multispectral. I checked in otb-data but I didn't find this kind of data)

2015-08-13 12:34 GMT+02:00 Rashad M <[email protected]>:

>
>
> On Thu, Aug 13, 2015 at 12:15 PM, Rémi Cresson <[email protected]>
> wrote:
>
>> Thank you, I've modified the headers (It seems like I can add some
>> latek?).
>> should I left the test validation data into the "test" directory?
>>
>
> you can test with some exisiting data on otb-data repo and remove images
> from your git. This is unless your data is special for your module.
>
> Also fix the errors in argument names for test
> https://github.com/remicres/otb-mosaic/blob/master/test/CMakeLists.txt#L5
>
>
>> many thanks
>>
>> 2015-08-13 10:48 GMT+02:00 Rashad M <[email protected]>:
>>
>>> you need add only to filters and not applications.
>>>
>>> see example,
>>> https://github.com/jmichel-otb/GKSVM/blob/master/include/otbChangeProfileKernelFunctor.h#L44
>>>
>>>
>>>
>>> On Thu, Aug 13, 2015 at 10:38 AM, Rémi Cresson <[email protected]>
>>> wrote:
>>>
>>>> Thank you Rashad,
>>>>
>>>> I am trying to use otb baseline in the (fixed) new test.
>>>> About doxygen, I will look into existing otb code to mimic. Do you mean
>>>> I must add the \ingroup to each filters, app, or both?
>>>>
>>>>
>>>>
>>>> 2015-08-13 9:59 GMT+02:00 Rashad M <[email protected]>:
>>>>
>>>>>
>>>>>
>>>>> On Wed, Aug 12, 2015 at 7:58 PM, Rémi Cresson <[email protected]>
>>>>> wrote:
>>>>>
>>>>>> Hello Rashad,
>>>>>>
>>>>>> Thank you for testing it.
>>>>>> I made the changes you suggest, except I put sources in include
>>>>>> folder (instead of src).
>>>>>>
>>>>>
>>>>> yes that is correct. it was my bad mentioning src if you dont have
>>>>> .cxx in library
>>>>>
>>>>>
>>>>>> I had to read the dashboard output, because it compiled fine on my
>>>>>> system without any error...
>>>>>>
>>>>>
>>>>> I have the new build without errors. But however tests are failing.
>>>>> But that can be fixed easily. Have a look at -
>>>>>
>>>>> http://dash.orfeo-toolbox.org/testDetails.php?test=32229576&build=195008
>>>>>
>>>>> For doxygen, it is required to mention the ingroup in the header as
>>>>> doxygen comments.
>>>>>
>>>>>
>>>>> Dasboard submission:
>>>>>
>>>>> http://dash.orfeo-toolbox.org/testDetails.php?test=32229575&build=195008
>>>>>
>>>>>
>>>>>
>>>>> you have test images which is now in test folder. But usually OTB
>>>>> keeps all baseline and example data in OTB-Data repository.
>>>>>  So if you could run the test on some images already existing in
>>>>> OTB-Data, I think that would be nice. Also I am not sure about adding new
>>>>> baseline for remote modules which are not official yet.
>>>>>
>>>>> OTB-Data -https://git.orfeo-toolbox.org/otb-data.git
>>>>>
>>>>>>
>>>>>> Waiting for your feedback !
>>>>>>
>>>>>> Rémi
>>>>>>
>>>>>>
>>>>>> 2015-08-12 17:15 GMT+02:00 Rashad M <[email protected]>:
>>>>>>
>>>>>>> Hi,
>>>>>>>
>>>>>>> On Mon, Aug 10, 2015 at 6:56 PM, remicres <[email protected]>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> Hi,
>>>>>>>>
>>>>>>>> I've just commited a remote module on GitHub wich deals with image
>>>>>>>> mosaics generation (https://github.com/remicres/otb-mosaic.git).
>>>>>>>> Provided are mosaicing filters and one application.
>>>>>>>> All filters support streaming. The application performs the mosaic
>>>>>>>> generation of multiple images, whith some color/radiometric 
>>>>>>>> harmonization
>>>>>>>> features, and feathering features (Details are provided above*)
>>>>>>>>
>>>>>>>> I hope that you will try and enjoy it. Keep me updated about issues
>>>>>>>> ! Feel free to ask questions, if any.
>>>>>>>>
>>>>>>>
>>>>>>> I tried to setup nightly build for your remote module but didnt work.
>>>>>>>
>>>>>>> here is the dasboard output:
>>>>>>> http://dash.orfeo-toolbox.org/buildSummary.php?buildid=194873
>>>>>>>
>>>>>>> From first look,
>>>>>>>
>>>>>>> you have all code in app folder include .h and .hxx.
>>>>>>>
>>>>>>> but otb remote module needs:
>>>>>>>
>>>>>>> all library code in src/*.h *.txx (  .txx is because all other
>>>>>>> modules use it that way. you need to confirm with someone else in the 
>>>>>>> list)
>>>>>>>
>>>>>>> all application code in app/
>>>>>>>
>>>>>>> Also please add a file like the below in your git repo.
>>>>>>>
>>>>>>> https://github.com/jmichel-otb/GKSVM/blob/master/GKSVM.remote.cmake
>>>>>>>
>>>>>>>
>>>>>>>>
>>>>>>>> Cheers,
>>>>>>>>
>>>>>>>> Rémi
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> * The application:
>>>>>>>>
>>>>>>>>    - From a given input images list, a mosaic is produced. The
>>>>>>>>    pipeline supports streaming, so there is no restriction on images 
>>>>>>>> number or
>>>>>>>>    size.
>>>>>>>>    - It implements a color harmonization method explained on our
>>>>>>>>    paper: Cresson R., Saint-Geours N., "Natural Color Satellite
>>>>>>>>    Image Mosaicking Using Quadratic Programming in Decorrelated Color
>>>>>>>>    Space"IEEE Journal of Selected Topics in Applied Earth Observations 
>>>>>>>> and
>>>>>>>>    Remote Sensing (Volume:PP ,  Issue: 99) July 2015
>>>>>>>>    
>>>>>>>> <http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7154397&filter%3DAND%28p_IS_Number%3A4609444%29>.
>>>>>>>>    In brief, it performs the global colorimetric harmonization of 
>>>>>>>> overlapping
>>>>>>>>    images in natural colors (i.e. input images must have 3 bands, 
>>>>>>>> RGB). You
>>>>>>>>    can set the application parameter "-harmo.method" to "rgb" to use 
>>>>>>>> this
>>>>>>>>    feature. However, the global radiometric harmonization can also be
>>>>>>>>    performed on each band individually by setting the application 
>>>>>>>> parameter
>>>>>>>>    "-harmo.method" to "band" (it can be useful if the color space is 
>>>>>>>> not truly
>>>>>>>>    RGB like raw Spot6/7, or if you want to perform a kind of 
>>>>>>>> radiometric
>>>>>>>>    equalized mosaic). Various statistical cost functions can be used 
>>>>>>>> (e.g.
>>>>>>>>    rmse) to find a correction model (which is linear with zero-y 
>>>>>>>> intercept:
>>>>>>>>    input images are scaled). We have developed a richer harmonization 
>>>>>>>> solver,
>>>>>>>>    wich can deal with general linear correction models (i.e. scale, 
>>>>>>>> and shift
>>>>>>>>    scale of images) but the maths tools brought by VNL were not 
>>>>>>>> sufficient,
>>>>>>>>    and we had to make use of external libraries to make it work (OOQP,
>>>>>>>>    QuadProg++). That is why we brought only simple zero-y intercept 
>>>>>>>> (i.e.
>>>>>>>>    scale) correction model in this current module. In future release, 
>>>>>>>> I think
>>>>>>>>    we should propose OOQP based (or QuadProg++ based) solver because 
>>>>>>>> it is far
>>>>>>>>    more robust than VNL routines (Sometimes VNL's routines throw 
>>>>>>>> unexpected
>>>>>>>>    errors, obviously coming from numerical instabilities). Waiting 
>>>>>>>> what will
>>>>>>>>    be the OTB framework for third parties...
>>>>>>>>    - As the harmonization method rely of local image statistics,
>>>>>>>>    those must be exempt from perturbations (e.g. clouds, ice, brutal 
>>>>>>>> landcover
>>>>>>>>    change between two images, ...). That's why it is possible to input 
>>>>>>>> some
>>>>>>>>    vector data to mask valid areas (need one vector data for one input 
>>>>>>>> image,
>>>>>>>>    in the same order as appearing in input).
>>>>>>>>    - It is possible to input some vector data for cutline (need
>>>>>>>>    one vector data for one input image, in the same order as appearing 
>>>>>>>> in
>>>>>>>>    input).
>>>>>>>>    - Another cool feature is the feathering/blending of input
>>>>>>>>    images, which allows to produce seamless mosaics. The current 
>>>>>>>> limitation is
>>>>>>>>    that we use a distance map image for each input, computed by
>>>>>>>>    itk::DanielssonDistanceMapImageFilter wich is not a streamable 
>>>>>>>> filter.
>>>>>>>>    That's why the current process first generates all distance map 
>>>>>>>> images in
>>>>>>>>    temporary .tif files, from resampled input images (the decimation 
>>>>>>>> factor
>>>>>>>>    can be set using the "-alphamasks.spacing"). Then, the filters use 
>>>>>>>> these
>>>>>>>>    previously computed distance map images to perform the 
>>>>>>>> feathering/blending
>>>>>>>>    of the input images. At the moment, 2 feathering methods are 
>>>>>>>> implemented
>>>>>>>>    (slim: blends the last image over earlier ones in areas of overlap, 
>>>>>>>> on a
>>>>>>>>    given transition distance / large: blends all images on largests 
>>>>>>>> possible
>>>>>>>>    overlapping areas)
>>>>>>>>
>>>>>>>> We tested the application successfully on big images collections:
>>>>>>>> RapidEye, France coverage from 2011 (~130 images), Spot6/7, France 
>>>>>>>> coverage
>>>>>>>> from 2014 (~190 images), both with a reasonable processing time. 
>>>>>>>> Processing
>>>>>>>> time is o(n) for both mosaic generation and statistics computation
>>>>>>>> (n=number of input images pixels). Harmonization problem is solved in 
>>>>>>>> o(m)
>>>>>>>> with m=number of input images (about some milliseconds for a hundred of
>>>>>>>> input images).
>>>>>>>>
>>>>>>>> The filters:
>>>>>>>>
>>>>>>>>    - otbStreamingMosaicFilterBase: is the base class of all
>>>>>>>>    mosaicing filters
>>>>>>>>    - otbStreamingSimpleMosaicFilter: inherits
>>>>>>>>    otbStreamingMosaicFilterBase, performs simple mosaics with a simple
>>>>>>>>    compositing technique which copies the last image over earlier ones 
>>>>>>>> in
>>>>>>>>    areas of overlap
>>>>>>>>    - otbStreamingStatisticsMosaicFilter: inherits
>>>>>>>>    otbStreamingMosaicFilterBase, computes statistics of the input 
>>>>>>>> images in
>>>>>>>>    each overlapping areas (e.g. mean of image i in overlap j, for all 
>>>>>>>> i and j)
>>>>>>>>    - otbStreamingMosaicFilterWithBlendingBase: inherits
>>>>>>>>    otbStreamingMosaicFilterBase, is the base class for all mosaicing 
>>>>>>>> filters
>>>>>>>>    which use a distance map image (feathering filters...)
>>>>>>>>    - otbStreamingFeatherMosaicFilter: inherits
>>>>>>>>    otbStreamingMosaicFilterWithBlendingBase, generates a mosaic with 
>>>>>>>> blends
>>>>>>>>    the last image over earlier ones in areas of overlap, on a given 
>>>>>>>> transition
>>>>>>>>    distance
>>>>>>>>    - otbStreamingLargeFeatherMosaicFilter: inherits
>>>>>>>>    otbStreamingMosaicFilterWithBlendingBase, blends all images on 
>>>>>>>> largests
>>>>>>>>    possible overlapping areas
>>>>>>>>    - otbStreamingMultibandFeatherMosaicFilter: inherits
>>>>>>>>    otbStreamingFeatherMosaicFilter, experimental. Multiband blending 
>>>>>>>> of input
>>>>>>>>    image using the laplacian (see Burt & Adelson "A multiresolution 
>>>>>>>> spline
>>>>>>>>    with application to image mosaics"). Could use GPU support for 
>>>>>>>> gaussian
>>>>>>>>    filtering. One need to fix some issues related to side effects 
>>>>>>>> (around no
>>>>>>>>    data pixels of images).
>>>>>>>>    - otbSummingFilter: utility filter which sums input images.
>>>>>>>>    - otbQuadraticallyConstrainedSimpleSolver: is the solver used
>>>>>>>>    for images color/radiometric harmonization. Works only with zero-y
>>>>>>>>    intercept correction models (as explained before).
>>>>>>>>
>>>>>>>> We try to make sense of this multilevel inheritance, but it might
>>>>>>>> be perfectible !
>>>>>>>> A possible optimization might be to process every threadedRegion by
>>>>>>>> subdividing it in multiple smaller regions, in order to loop only on
>>>>>>>> relevant images: an actual drawback is where the threadedRegion is 
>>>>>>>> large,
>>>>>>>> a lot of input images have to be checked even if they are out of the
>>>>>>>> region. Another one might be to pre-compute areas where interpolators 
>>>>>>>> can
>>>>>>>> work, instead of checking every processed pixel if the current point is
>>>>>>>> inside the buffer.
>>>>>>>> On excellent upgrade would be to strengthen the architecture, and
>>>>>>>> implements those optimizations in a general way (currently, we have to 
>>>>>>>> do
>>>>>>>> it for each filter... that is why I think this could be better built)
>>>>>>>>
>>>>>>>> --
>>>>>>>> --
>>>>>>>> Check the OTB FAQ at
>>>>>>>> http://www.orfeo-toolbox.org/FAQ.html
>>>>>>>>
>>>>>>>> You received this message because you are subscribed to the Google
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>>>>>>>> To unsubscribe from this group, send email to
>>>>>>>> [email protected]
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>>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> --
>>>>>>> Regards,
>>>>>>>    Rashad
>>>>>>>
>>>>>>> --
>>>>>>> --
>>>>>>> Check the OTB FAQ at
>>>>>>> http://www.orfeo-toolbox.org/FAQ.html
>>>>>>>
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>>>>>>>
>>>>>>
>>>>>> --
>>>>>> --
>>>>>> Check the OTB FAQ at
>>>>>> http://www.orfeo-toolbox.org/FAQ.html
>>>>>>
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>>>>>> To unsubscribe from this group, send email to
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>>>>>>
>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> Regards,
>>>>>    Rashad
>>>>>
>>>>> --
>>>>> --
>>>>> Check the OTB FAQ at
>>>>> http://www.orfeo-toolbox.org/FAQ.html
>>>>>
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>>>>>
>>>>
>>>> --
>>>> --
>>>> Check the OTB FAQ at
>>>> http://www.orfeo-toolbox.org/FAQ.html
>>>>
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>>>
>>>
>>>
>>> --
>>> Regards,
>>>    Rashad
>>>
>>> --
>>> --
>>> Check the OTB FAQ at
>>> http://www.orfeo-toolbox.org/FAQ.html
>>>
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>>
>> --
>> --
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>
>
>
> --
> Regards,
>    Rashad
>
> --
> --
> Check the OTB FAQ at
> http://www.orfeo-toolbox.org/FAQ.html
>
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