Evgeny
82 líneas
3.4 KiB
Common Lisp
82 líneas
3.4 KiB
Common Lisp
/******************************************************************************
|
|
|
|
Copyright ©2013 Advanced Micro Devices, Inc. All rights reserved.
|
|
|
|
Redistribution and use in source and binary forms, with or without modification,
|
|
are permitted provided that the following conditions are met:
|
|
|
|
Redistributions of source code must retain the above copyright notice, this list
|
|
of conditions and the following disclaimer.
|
|
|
|
Redistributions in binary form must reproduce the above copyright notice, this
|
|
list of conditions and the following disclaimer in the documentation and/or
|
|
other materials provided with the distribution.
|
|
|
|
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
|
|
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
|
|
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
|
|
IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
|
|
INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
|
|
BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
|
|
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
|
|
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
|
|
OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
|
|
OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
|
|
********************************************************************************/
|
|
|
|
/**
|
|
* SimpleConvolution is where each pixel of the output image
|
|
* is the weighted sum of the neighborhood pixels of the input image
|
|
* The neighborhood is defined by the dimensions of the mask and
|
|
* weight of each neighbor is defined by the mask itself.
|
|
* @param output Output matrix after performing convolution
|
|
* @param input Input matrix on which convolution is to be performed
|
|
* @param mask mask matrix using which convolution was to be performed
|
|
* @param inputDimensions dimensions of the input matrix
|
|
* @param maskDimensions dimensions of the mask matrix
|
|
*/
|
|
__kernel void SimpleConvolution(__global uint * output,
|
|
__global uint * input,
|
|
__global float * mask,
|
|
const uint2 inputDimensions,
|
|
const uint2 maskDimensions) {
|
|
|
|
uint tid = get_global_id(0);
|
|
|
|
uint width = inputDimensions.x;
|
|
uint height = inputDimensions.y;
|
|
|
|
uint x = tid%width;
|
|
uint y = tid/width;
|
|
|
|
uint maskWidth = maskDimensions.x;
|
|
uint maskHeight = maskDimensions.y;
|
|
|
|
uint vstep = (maskWidth -1)/2;
|
|
uint hstep = (maskHeight -1)/2;
|
|
|
|
// find the left, right, top and bottom indices such that
|
|
// the indices do not go beyond image boundaires
|
|
uint left = (x < vstep) ? 0 : (x - vstep);
|
|
uint right = ((x + vstep) >= width) ? width - 1 : (x + vstep);
|
|
uint top = (y < hstep) ? 0 : (y - hstep);
|
|
uint bottom = ((y + hstep) >= height)? height - 1: (y + hstep);
|
|
|
|
// initializing wighted sum value
|
|
float sumFX = 0;
|
|
|
|
for(uint i = left; i <= right; ++i) {
|
|
for(uint j = top; j <= bottom; ++j) {
|
|
// performing wighted sum within the mask boundaries
|
|
uint maskIndex = (j - (y - hstep)) * maskWidth + (i - (x - vstep));
|
|
uint index = j * width + i;
|
|
sumFX += ((float)input[index] * mask[maskIndex]);
|
|
}
|
|
}
|
|
|
|
// To round to the nearest integer
|
|
sumFX += 0.5f;
|
|
output[tid] = (uint)sumFX;
|
|
}
|