CudaSift/cudaSift_gold.cpp at master · nbergst/CudaSift · GitHub

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/*
 * Copyright 1993-2007 NVIDIA Corporation.  All rights reserved.
 *
 * NOTICE TO USER:
 *
 * This source code is subject to NVIDIA ownership rights under U.S. and
 * international Copyright laws.  Users and possessors of this source code
 * are hereby granted a nonexclusive, royalty-free license to use this code
 * in individual and commercial software.
 *
 * NVIDIA MAKES NO REPRESENTATION ABOUT THE SUITABILITY OF THIS SOURCE
 * CODE FOR ANY PURPOSE.  IT IS PROVIDED "AS IS" WITHOUT EXPRESS OR
 * IMPLIED WARRANTY OF ANY KIND.  NVIDIA DISCLAIMS ALL WARRANTIES WITH
 * REGARD TO THIS SOURCE CODE, INCLUDING ALL IMPLIED WARRANTIES OF
 * MERCHANTABILITY, NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
 * IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL,
 * OR CONSEQUENTIAL DAMAGES, OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
 * OF USE, DATA OR PROFITS,  WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE
 * OR OTHER TORTIOUS ACTION,  ARISING OUT OF OR IN CONNECTION WITH THE USE
 * OR PERFORMANCE OF THIS SOURCE CODE.
 *
 * U.S. Government End Users.   This source code is a "commercial item" as
 * that term is defined at  48 C.F.R. 2.101 (OCT 1995), consisting  of
 * "commercial computer  software"  and "commercial computer software
 * documentation" as such terms are  used in 48 C.F.R. 12.212 (SEPT 1995)
 * and is provided to the U.S. Government only as a commercial end item.
 * Consistent with 48 C.F.R.12.212 and 48 C.F.R. 227.7202-1 through
 * 227.7202-4 (JUNE 1995), all U.S. Government End Users acquire the
 * source code with only those rights set forth herein.
 *
 * Any use of this source code in individual and commercial software must
 * include, in the user documentation and internal comments to the code,
 * the above Disclaimer and U.S. Government End Users Notice.
 */


////////////////////////////////////////////////////////////////////////////////
// Reference row convolution filter
////////////////////////////////////////////////////////////////////////////////
extern "C" void ConvRowCPU(float *h_Result, float *h_Data, float *h_Kernel,
  int dataW, int dataH, int kernelR)
{
  int x, y, k, d;
  float sum;
  for (y=0;y<dataH;y++)
    for (x=0;x<dataW;x++) {
      sum = 0;
      for (k=-kernelR;k<=kernelR;k++) {
	d = x + k;
	d = (d<0 ? 0 : d);
	d = (d>=dataW ? dataW-1 : d);
	sum += h_Data[y*dataW + d] * h_Kernel[kernelR - k];
      }
      h_Result[y*dataW + x] = sum;
    }
}

////////////////////////////////////////////////////////////////////////////////
// Reference column convolution filter
////////////////////////////////////////////////////////////////////////////////
extern "C" void ConvColCPU(float *h_Result, float *h_Data, float *h_Kernel,
  int dataW, int dataH, int kernelR)
{
  int x, y, k, d;
  float sum;
  for (y=0;y<dataH;y++)
    for (x=0;x<dataW;x++) {
      sum = 0;
      for (k=-kernelR;k<=kernelR;k++) {
	d = y + k;
	d = (d<0 ? 0 : d);
	d = (d>=dataH ? dataH-1 : d);
	sum += h_Data[d*dataW + x] * h_Kernel[kernelR - k];
      }
      h_Result[y*dataW + x] = sum;
    }
}