CudaColorOps.C

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00001 /*!@file CUDA/CudaColorOps.C C++ wrapper for CUDA Color operations */
00002 
00003 // //////////////////////////////////////////////////////////////////// //
00004 // The iLab Neuromorphic Vision C++ Toolkit - Copyright (C) 2000-2005   //
00005 // by the University of Southern California (USC) and the iLab at USC.  //
00006 // See http://iLab.usc.edu for information about this project.          //
00007 // //////////////////////////////////////////////////////////////////// //
00008 // Major portions of the iLab Neuromorphic Vision Toolkit are protected //
00009 // under the U.S. patent ``Computation of Intrinsic Perceptual Saliency //
00010 // in Visual Environments, and Applications'' by Christof Koch and      //
00011 // Laurent Itti, California Institute of Technology, 2001 (patent       //
00012 // pending; application number 09/912,225 filed July 23, 2001; see      //
00013 // http://pair.uspto.gov/cgi-bin/final/home.pl for current status).     //
00014 // //////////////////////////////////////////////////////////////////// //
00015 // This file is part of the iLab Neuromorphic Vision C++ Toolkit.       //
00016 //                                                                      //
00017 // The iLab Neuromorphic Vision C++ Toolkit is free software; you can   //
00018 // redistribute it and/or modify it under the terms of the GNU General  //
00019 // Public License as published by the Free Software Foundation; either  //
00020 // version 2 of the License, or (at your option) any later version.     //
00021 //                                                                      //
00022 // The iLab Neuromorphic Vision C++ Toolkit is distributed in the hope  //
00023 // that it will be useful, but WITHOUT ANY WARRANTY; without even the   //
00024 // implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR      //
00025 // PURPOSE.  See the GNU General Public License for more details.       //
00026 //                                                                      //
00027 // You should have received a copy of the GNU General Public License    //
00028 // along with the iLab Neuromorphic Vision C++ Toolkit; if not, write   //
00029 // to the Free Software Foundation, Inc., 59 Temple Place, Suite 330,   //
00030 // Boston, MA 02111-1307 USA.                                           //
00031 // //////////////////////////////////////////////////////////////////// //
00032 //
00033 // Primary maintainer for this file:
00034 // $HeadURL: svn://isvn.usc.edu/software/invt/trunk/saliency/src/CUDA/CudaColorOps.C $
00035 // $Id: CudaColorOps.C 12962 2010-03-06 02:13:53Z irock $
00036 //
00037 
00038 #include "CUDA/CudaImage.H"
00039 #include "Util/Assert.H"
00040 #include "CUDA/cudadefs.h"
00041 #include "CudaColorOps.H"
00042 #include "CudaDevices.H"
00043 #include "wrap_c_cuda.h"
00044 
00045 
00046 void cudaGetRGBY(const CudaImage<PixRGB<float> >& src, CudaImage<float>& rg, CudaImage<float>& by,
00047                  const float thresh, const float min_range, const float max_range)
00048 {
00049   ASSERT(src.initialized());
00050   ASSERT(src.getMemoryPolicy() != HOST_MEMORY);
00051   const MemoryPolicy mp = src.getMemoryPolicy();
00052   const int dev = src.getMemoryDevice();
00053   rg = CudaImage<float>(src.getDims(), NO_INIT, mp, dev);
00054   by = CudaImage<float>(src.getDims(), NO_INIT, mp, dev);
00055   const Dims tile = CudaDevices::getDeviceTileSize(dev);
00056   cuda_c_getRGBY((float3_t *)src.getCudaArrayPtr(),rg.getCudaArrayPtr(),by.getCudaArrayPtr(),thresh,
00057                  min_range,max_range,src.getWidth(),src.getHeight(),tile.w(),tile.h());
00058 }
00059 
00060 CudaImage<PixRGB<float> >  cudaToRGB(const CudaImage<float>& src)
00061 {
00062 
00063   ASSERT(src.initialized());
00064   ASSERT(src.getMemoryPolicy() != HOST_MEMORY);
00065   const MemoryPolicy mp = src.getMemoryPolicy();
00066   const int dev = src.getMemoryDevice();
00067   CudaImage<PixRGB<float> > dst = CudaImage<PixRGB<float> >(src.getDims(), NO_INIT, mp, dev);
00068 
00069   const Dims tile = CudaDevices::getDeviceTileSize1D(dev);
00070   cuda_c_toRGB((float3_t *)dst.getCudaArrayPtr(),src.getCudaArrayPtr(),src.size(),tile.sz());
00071   return dst;
00072 }
00073 
00074 
00075 void cudaGetComponents(const CudaImage<PixRGB<float> >& src, CudaImage<float>& red, CudaImage<float>& green, CudaImage<float>& blue)
00076 {
00077   // Ensure that the data is valid
00078   ASSERT(src.initialized());
00079   // Ensure that we are on a CUDA device
00080   ASSERT(src.getMemoryPolicy() != HOST_MEMORY);
00081 
00082   const int dev = src.getMemoryDevice();
00083   // Set up output image memory
00084   red = CudaImage<float>(src.getDims(), NO_INIT, src.getMemoryPolicy(), dev);
00085   green = CudaImage<float>(src.getDims(), NO_INIT, src.getMemoryPolicy(), dev);
00086   blue = CudaImage<float>(src.getDims(), NO_INIT, src.getMemoryPolicy(), dev);
00087 
00088   const Dims tile = CudaDevices::getDeviceTileSize(dev);
00089   // Call CUDA implementation
00090   cuda_c_getComponents((float3_t *)src.getCudaArrayPtr(), red.getCudaArrayPtr(), green.getCudaArrayPtr(), blue.getCudaArrayPtr(),
00091                        src.getWidth(), src.getHeight(),tile.w(),tile.h());
00092 }
00093 
00094 // Our CUDA library only supports float implementation, no use pretending to support others with template style
00095 CudaImage<float> cudaLuminance(const CudaImage<PixRGB<float> >& src)
00096 {
00097   // Ensure that the data is valid
00098   ASSERT(src.initialized());
00099   // Ensure that we are on a CUDA device
00100   ASSERT(src.getMemoryPolicy() != HOST_MEMORY);
00101 
00102   const int dev = src.getMemoryDevice();
00103   // Output is the same size as the input for this filter
00104   CudaImage<float> result(src.getDims(), NO_INIT, src.getMemoryPolicy(), dev);
00105 
00106   const Dims tile = CudaDevices::getDeviceTileSize(dev);
00107   // Now call the CUDA implementation
00108   cuda_c_luminance((float3_t *)src.getCudaArrayPtr(),result.getCudaArrayPtr(),result.getWidth(),result.getHeight(),
00109                        tile.w(),tile.h());
00110   return result;
00111 }
00112 
00113 
00114 // Our CUDA library only supports float implementation, no use pretending to support others with template style
00115 CudaImage<float> cudaLuminanceNTSC(const CudaImage<PixRGB<float> >& src)
00116 {
00117   // Ensure that the data is valid
00118   ASSERT(src.initialized());
00119   // Ensure that we are on a CUDA device
00120   ASSERT(src.getMemoryPolicy() != HOST_MEMORY);
00121 
00122   const int dev = src.getMemoryDevice();
00123   // Output is the same size as the input for this filter
00124   CudaImage<float> result(src.getDims(), NO_INIT, src.getMemoryPolicy(), dev);
00125 
00126   const Dims tile = CudaDevices::getDeviceTileSize(dev);
00127   // Now call the CUDA implementation
00128   cuda_c_luminanceNTSC((float3_t *)src.getCudaArrayPtr(),result.getCudaArrayPtr(),result.getWidth(),result.getHeight(),
00129                        tile.w(),tile.h());
00130   return result;
00131 }
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