/********************************************************************
**                Image Component Library (ICL)                    **
**                                                                 **
** Copyright (C) 2006-2013 CITEC, University of Bielefeld          **
**                         Neuroinformatics Group                  **
** Website: www.iclcv.org and                                      **
**          http://opensource.cit-ec.de/projects/icl               **
**                                                                 **
** File   : ICLFilter/src/ICLFilter/UnaryOpPipe.h                  **
** Module : ICLFilter                                              **
** Authors: Christof Elbrechter                                    **
**                                                                 **
**                                                                 **
** GNU LESSER GENERAL PUBLIC LICENSE                               **
** This file may be used under the terms of the GNU Lesser General **
** Public License version 3.0 as published by the                  **
**                                                                 **
** Free Software Foundation and appearing in the file LICENSE.LGPL **
** included in the packaging of this file.  Please review the      **
** following information to ensure the license requirements will   **
** be met: http://www.gnu.org/licenses/lgpl-3.0.txt                **
**                                                                 **
** The development of this software was supported by the           **
** Excellence Cluster EXC 277 Cognitive Interaction Technology.    **
** The Excellence Cluster EXC 277 is a grant of the Deutsche       **
** Forschungsgemeinschaft (DFG) in the context of the German       **
** Excellence Initiative.                                          **
**                                                                 **
********************************************************************/

#pragma once

#include <ICLUtils/CompatMacros.h>
#include <ICLFilter/UnaryOp.h>
#include <vector>

namespace icl{
  /** \cond */
  namespace core{  class ImgBase; }
  /** \endcond */

  namespace filter{
    
    
    /// Utility class that helps applying UnaryOps one after another \ingroup UNARY
    /** Consider a default computer vision system, which has some
        preprocessing steps in the following operation order:
        -# resize the image to a given size
        -# calculate a feature map (e.g. a weighted sum of the color channels)
        -# binarize the feature map
        -# apply some morphological operation on this feature map
        
        To facilitate this, you can easily use a UnaryOpPipe, which
        internally creates a queue of UnaryOp instances and their
        individual result images (as ImgBase*). Once you have created
        this Pipe under a certain name (e.g. "MyProprocessor") you
        can easily add or remove specific preprocessing steps, without
        having to consider fall-outs elsewhere in your code.
        
        Take a look on the following example:
        \code
        #include <ICLQt/Quick.h>
        #include <ICLFilter/UnaryOpPipe.h>
        #include <ICLFilter/ScaleOp.h>
        #include <ICLFilter/WeightedSumOp.h>
        #include <ICLFilter/UnaryCompareOp.h>
        #include <ICLFilter/MorphologicalOp.h>
        
        int main(){
           // create an input image (the nice parrot here!)
           ImgQ inputImage = create("parrot");
        
           // create a weight vector (used later on by an instance of the WeightedSumOp class)
           vector<icl64f> weights(3); weights[0] = 0.2; weights[1] = 0.5; weights[0] = 0.3;
        
           // create the empty pipe
           UnaryOpPipe pipe;
    
           // add the UnaryOp's in the correct order
           pipe << new ScaleOp(0.25,0.25)
                << new WeightedSumOp(weights)
                << new UnaryCompareOp(UnaryCompareOp::gt,110)
                << new MorphologicalOp(MorphologicalOp::erode3x3);
        
           // apply this pipe on the source image (use the last image as destination)
           const ImgBase *res = pipe.apply(&inputImage);
        
           // show the result using ICLQuick
           show(cvt(res));
        }
        \endcode
    **/
    class ICLFilter_API UnaryOpPipe : public UnaryOp{
      public:
      /// create an empty pipe
      UnaryOpPipe();
      
      /// Destructor
      ~UnaryOpPipe();
      
      /// appends a new op on the end of this pipe (ownership of op and im is passed to the pipe)
      void add(UnaryOp *op, core::ImgBase*im=0);
  
      /// stream based wrapper for the add function (calls add(op,0))
      /** ownership of op is passed to the pipe*/
      UnaryOpPipe &operator<<(UnaryOp *op){
        add(op); return *this;
      }    
      /// applies all ops sequentially 
      virtual void apply(const core::ImgBase *src, core::ImgBase **dst);
  
      /// This function is reimplemented here; it uses getLastImage() as destination image
      virtual const core::ImgBase *apply(const core::ImgBase *src);
      
      /// returns the number of contained ops
      int getLength() const;
      
      /// returns the op at given index
      UnaryOp *&getOp(int i);
      
      /// returns the result buffer image at given index
      core::ImgBase *&getImage(int i);
      
      /// returns the last image (which is not used by default)
      /** This image is only used, if it is given a 2nd parameter to
          the apply function
          \code
          MyPipe.apply(mySourceImagePtr,&(MyPipe.getLastImage());
          \endcode
      **/
      core::ImgBase *&getLastImage();  
      
      private:
      /// Internal buffer of ops
      std::vector<UnaryOp*> ops;
      
      /// Internal buffer of result images
      std::vector<core::ImgBase*> ims;
    };
  } // namespace filter
}