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Open Source Computer Vision Library
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429 lines
14 KiB
429 lines
14 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved. |
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// @Authors |
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// Sen Liu, swjtuls1987@126.com |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors as is and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#define tx (int)get_local_id(0) |
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#define ty get_local_id(1) |
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#define bx get_group_id(0) |
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#define bdx (int)get_local_size(0) |
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#define BORDER_SIZE 5 |
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#define MAX_KSIZE_HALF 100 |
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#ifndef polyN |
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#define polyN 5 |
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#endif |
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#if USE_DOUBLE |
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#ifdef cl_amd_fp64 |
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#pragma OPENCL EXTENSION cl_amd_fp64:enable |
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#elif defined (cl_khr_fp64) |
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#pragma OPENCL EXTENSION cl_khr_fp64:enable |
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#endif |
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#define TYPE double |
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#define VECTYPE double4 |
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#else |
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#define TYPE float |
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#define VECTYPE float4 |
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#endif |
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__kernel void polynomialExpansion(__global __const float * src, int srcStep, |
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__global float * dst, int dstStep, |
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const int rows, const int cols, |
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__global __const float * c_g, |
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__global __const float * c_xg, |
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__global __const float * c_xxg, |
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__local float * smem, |
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const VECTYPE ig) |
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{ |
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const int y = get_global_id(1); |
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const int x = bx * (bdx - 2*polyN) + tx - polyN; |
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int xWarped; |
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__local float *row = smem + tx; |
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if (y < rows && y >= 0) |
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{ |
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xWarped = min(max(x, 0), cols - 1); |
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row[0] = src[mad24(y, srcStep, xWarped)] * c_g[0]; |
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row[bdx] = 0.f; |
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row[2*bdx] = 0.f; |
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#pragma unroll |
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for (int k = 1; k <= polyN; ++k) |
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{ |
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float t0 = src[mad24(max(y - k, 0), srcStep, xWarped)]; |
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float t1 = src[mad24(min(y + k, rows - 1), srcStep, xWarped)]; |
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row[0] += c_g[k] * (t0 + t1); |
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row[bdx] += c_xg[k] * (t1 - t0); |
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row[2*bdx] += c_xxg[k] * (t0 + t1); |
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} |
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} |
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barrier(CLK_LOCAL_MEM_FENCE); |
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if (y < rows && y >= 0 && tx >= polyN && tx + polyN < bdx && x < cols) |
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{ |
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TYPE b1 = c_g[0] * row[0]; |
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TYPE b3 = c_g[0] * row[bdx]; |
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TYPE b5 = c_g[0] * row[2*bdx]; |
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TYPE b2 = 0, b4 = 0, b6 = 0; |
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#pragma unroll |
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for (int k = 1; k <= polyN; ++k) |
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{ |
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b1 += (row[k] + row[-k]) * c_g[k]; |
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b4 += (row[k] + row[-k]) * c_xxg[k]; |
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b2 += (row[k] - row[-k]) * c_xg[k]; |
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b3 += (row[k + bdx] + row[-k + bdx]) * c_g[k]; |
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b6 += (row[k + bdx] - row[-k + bdx]) * c_xg[k]; |
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b5 += (row[k + 2*bdx] + row[-k + 2*bdx]) * c_g[k]; |
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} |
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dst[mad24(y, dstStep, xWarped)] = (float)(b3*ig.s0); |
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dst[mad24(rows + y, dstStep, xWarped)] = (float)(b2*ig.s0); |
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dst[mad24(2*rows + y, dstStep, xWarped)] = (float)(b1*ig.s1 + b5*ig.s2); |
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dst[mad24(3*rows + y, dstStep, xWarped)] = (float)(b1*ig.s1 + b4*ig.s2); |
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dst[mad24(4*rows + y, dstStep, xWarped)] = (float)(b6*ig.s3); |
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} |
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} |
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inline int idx_row_low(const int y, const int last_row) |
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{ |
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return abs(y) % (last_row + 1); |
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} |
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inline int idx_row_high(const int y, const int last_row) |
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{ |
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return abs(last_row - abs(last_row - y)) % (last_row + 1); |
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} |
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inline int idx_col_low(const int x, const int last_col) |
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{ |
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return abs(x) % (last_col + 1); |
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} |
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inline int idx_col_high(const int x, const int last_col) |
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{ |
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return abs(last_col - abs(last_col - x)) % (last_col + 1); |
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} |
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inline int idx_col(const int x, const int last_col) |
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{ |
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return idx_col_low(idx_col_high(x, last_col), last_col); |
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} |
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__kernel void gaussianBlur(__global const float * src, int srcStep, |
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__global float * dst, int dstStep, const int rows, const int cols, |
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__global const float * c_gKer, const int ksizeHalf, |
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__local float * smem) |
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{ |
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const int y = get_global_id(1); |
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const int x = get_global_id(0); |
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__local float *row = smem + ty * (bdx + 2*ksizeHalf); |
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if (y < rows) |
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{ |
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// Vertical pass |
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for (int i = tx; i < bdx + 2*ksizeHalf; i += bdx) |
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{ |
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int xExt = (int)(bx * bdx) + i - ksizeHalf; |
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xExt = idx_col(xExt, cols - 1); |
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row[i] = src[mad24(y, srcStep, xExt)] * c_gKer[0]; |
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for (int j = 1; j <= ksizeHalf; ++j) |
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row[i] += (src[mad24(idx_row_low(y - j, rows - 1), srcStep, xExt)] |
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+ src[mad24(idx_row_high(y + j, rows - 1), srcStep, xExt)]) * c_gKer[j]; |
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} |
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} |
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barrier(CLK_LOCAL_MEM_FENCE); |
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if (y < rows && y >= 0 && x < cols && x >= 0) |
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{ |
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// Horizontal pass |
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row += tx + ksizeHalf; |
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float res = row[0] * c_gKer[0]; |
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for (int i = 1; i <= ksizeHalf; ++i) |
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res += (row[-i] + row[i]) * c_gKer[i]; |
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dst[mad24(y, dstStep, x)] = res; |
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} |
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} |
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__kernel void gaussianBlur5(__global const float * src, int srcStep, |
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__global float * dst, int dstStep, |
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const int rows, const int cols, |
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__global const float * c_gKer, const int ksizeHalf, |
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__local float * smem) |
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{ |
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const int y = get_global_id(1); |
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const int x = get_global_id(0); |
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const int smw = bdx + 2*ksizeHalf; // shared memory "cols" |
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__local volatile float *row = smem + 5 * ty * smw; |
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if (y < rows) |
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{ |
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// Vertical pass |
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for (int i = tx; i < bdx + 2*ksizeHalf; i += bdx) |
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{ |
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int xExt = (int)(bx * bdx) + i - ksizeHalf; |
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xExt = idx_col(xExt, cols - 1); |
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#pragma unroll |
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for (int k = 0; k < 5; ++k) |
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row[k*smw + i] = src[mad24(k*rows + y, srcStep, xExt)] * c_gKer[0]; |
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for (int j = 1; j <= ksizeHalf; ++j) |
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#pragma unroll |
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for (int k = 0; k < 5; ++k) |
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row[k*smw + i] += |
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(src[mad24(k*rows + idx_row_low(y - j, rows - 1), srcStep, xExt)] + |
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src[mad24(k*rows + idx_row_high(y + j, rows - 1), srcStep, xExt)]) * c_gKer[j]; |
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} |
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} |
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barrier(CLK_LOCAL_MEM_FENCE); |
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if (y < rows && y >= 0 && x < cols && x >= 0) |
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{ |
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// Horizontal pass |
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row += tx + ksizeHalf; |
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float res[5]; |
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#pragma unroll |
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for (int k = 0; k < 5; ++k) |
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res[k] = row[k*smw] * c_gKer[0]; |
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for (int i = 1; i <= ksizeHalf; ++i) |
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#pragma unroll |
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for (int k = 0; k < 5; ++k) |
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res[k] += (row[k*smw - i] + row[k*smw + i]) * c_gKer[i]; |
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#pragma unroll |
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for (int k = 0; k < 5; ++k) |
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dst[mad24(k*rows + y, dstStep, x)] = res[k]; |
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} |
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} |
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__constant float c_border[BORDER_SIZE + 1] = { 0.14f, 0.14f, 0.4472f, 0.4472f, 0.4472f, 1.f }; |
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__kernel void updateMatrices(__global const float * flowx, int xStep, |
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__global const float * flowy, int yStep, |
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const int rows, const int cols, |
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__global const float * R0, int R0Step, |
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__global const float * R1, int R1Step, |
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__global float * M, int mStep) |
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{ |
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const int y = get_global_id(1); |
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const int x = get_global_id(0); |
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if (y < rows && y >= 0 && x < cols && x >= 0) |
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{ |
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float dx = flowx[mad24(y, xStep, x)]; |
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float dy = flowy[mad24(y, yStep, x)]; |
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float fx = x + dx; |
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float fy = y + dy; |
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int x1 = convert_int(floor(fx)); |
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int y1 = convert_int(floor(fy)); |
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fx -= x1; |
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fy -= y1; |
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float r2, r3, r4, r5, r6; |
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if (x1 >= 0 && y1 >= 0 && x1 < cols - 1 && y1 < rows - 1) |
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{ |
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float a00 = (1.f - fx) * (1.f - fy); |
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float a01 = fx * (1.f - fy); |
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float a10 = (1.f - fx) * fy; |
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float a11 = fx * fy; |
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r2 = a00 * R1[mad24(y1, R1Step, x1)] + |
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a01 * R1[mad24(y1, R1Step, x1 + 1)] + |
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a10 * R1[mad24(y1 + 1, R1Step, x1)] + |
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a11 * R1[mad24(y1 + 1, R1Step, x1 + 1)]; |
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r3 = a00 * R1[mad24(rows + y1, R1Step, x1)] + |
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a01 * R1[mad24(rows + y1, R1Step, x1 + 1)] + |
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a10 * R1[mad24(rows + y1 + 1, R1Step, x1)] + |
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a11 * R1[mad24(rows + y1 + 1, R1Step, x1 + 1)]; |
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r4 = a00 * R1[mad24(2*rows + y1, R1Step, x1)] + |
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a01 * R1[mad24(2*rows + y1, R1Step, x1 + 1)] + |
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a10 * R1[mad24(2*rows + y1 + 1, R1Step, x1)] + |
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a11 * R1[mad24(2*rows + y1 + 1, R1Step, x1 + 1)]; |
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r5 = a00 * R1[mad24(3*rows + y1, R1Step, x1)] + |
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a01 * R1[mad24(3*rows + y1, R1Step, x1 + 1)] + |
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a10 * R1[mad24(3*rows + y1 + 1, R1Step, x1)] + |
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a11 * R1[mad24(3*rows + y1 + 1, R1Step, x1 + 1)]; |
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r6 = a00 * R1[mad24(4*rows + y1, R1Step, x1)] + |
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a01 * R1[mad24(4*rows + y1, R1Step, x1 + 1)] + |
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a10 * R1[mad24(4*rows + y1 + 1, R1Step, x1)] + |
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a11 * R1[mad24(4*rows + y1 + 1, R1Step, x1 + 1)]; |
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r4 = (R0[mad24(2*rows + y, R0Step, x)] + r4) * 0.5f; |
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r5 = (R0[mad24(3*rows + y, R0Step, x)] + r5) * 0.5f; |
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r6 = (R0[mad24(4*rows + y, R0Step, x)] + r6) * 0.25f; |
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} |
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else |
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{ |
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r2 = r3 = 0.f; |
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r4 = R0[mad24(2*rows + y, R0Step, x)]; |
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r5 = R0[mad24(3*rows + y, R0Step, x)]; |
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r6 = R0[mad24(4*rows + y, R0Step, x)] * 0.5f; |
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} |
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r2 = (R0[mad24(y, R0Step, x)] - r2) * 0.5f; |
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r3 = (R0[mad24(rows + y, R0Step, x)] - r3) * 0.5f; |
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r2 += r4*dy + r6*dx; |
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r3 += r6*dy + r5*dx; |
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float scale = |
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c_border[min(x, BORDER_SIZE)] * |
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c_border[min(y, BORDER_SIZE)] * |
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c_border[min(cols - x - 1, BORDER_SIZE)] * |
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c_border[min(rows - y - 1, BORDER_SIZE)]; |
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r2 *= scale; |
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r3 *= scale; |
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r4 *= scale; |
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r5 *= scale; |
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r6 *= scale; |
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M[mad24(y, mStep, x)] = r4*r4 + r6*r6; |
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M[mad24(rows + y, mStep, x)] = (r4 + r5)*r6; |
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M[mad24(2*rows + y, mStep, x)] = r5*r5 + r6*r6; |
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M[mad24(3*rows + y, mStep, x)] = r4*r2 + r6*r3; |
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M[mad24(4*rows + y, mStep, x)] = r6*r2 + r5*r3; |
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} |
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} |
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__kernel void boxFilter5(__global const float * src, int srcStep, |
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__global float * dst, int dstStep, |
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const int rows, const int cols, |
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const int ksizeHalf, |
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__local float * smem) |
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{ |
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const int y = get_global_id(1); |
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const int x = get_global_id(0); |
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const float boxAreaInv = 1.f / ((1 + 2*ksizeHalf) * (1 + 2*ksizeHalf)); |
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const int smw = bdx + 2*ksizeHalf; // shared memory "width" |
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__local float *row = smem + 5 * ty * smw; |
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if (y < rows) |
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{ |
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// Vertical pass |
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for (int i = tx; i < bdx + 2*ksizeHalf; i += bdx) |
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{ |
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int xExt = (int)(bx * bdx) + i - ksizeHalf; |
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xExt = min(max(xExt, 0), cols - 1); |
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#pragma unroll |
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for (int k = 0; k < 5; ++k) |
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row[k*smw + i] = src[mad24(k*rows + y, srcStep, xExt)]; |
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for (int j = 1; j <= ksizeHalf; ++j) |
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#pragma unroll |
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for (int k = 0; k < 5; ++k) |
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row[k*smw + i] += |
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src[mad24(k*rows + max(y - j, 0), srcStep, xExt)] + |
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src[mad24(k*rows + min(y + j, rows - 1), srcStep, xExt)]; |
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} |
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} |
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barrier(CLK_LOCAL_MEM_FENCE); |
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if (y < rows && y >= 0 && x < cols && x >= 0) |
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{ |
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// Horizontal pass |
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row += tx + ksizeHalf; |
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float res[5]; |
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#pragma unroll |
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for (int k = 0; k < 5; ++k) |
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res[k] = row[k*smw]; |
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for (int i = 1; i <= ksizeHalf; ++i) |
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#pragma unroll |
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for (int k = 0; k < 5; ++k) |
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res[k] += row[k*smw - i] + row[k*smw + i]; |
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#pragma unroll |
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for (int k = 0; k < 5; ++k) |
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dst[mad24(k*rows + y, dstStep, x)] = res[k] * boxAreaInv; |
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} |
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} |
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__kernel void updateFlow(__global const float * M, int mStep, |
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__global float * flowx, int xStep, |
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__global float * flowy, int yStep, |
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const int rows, const int cols) |
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{ |
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const int y = get_global_id(1); |
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const int x = get_global_id(0); |
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if (y < rows && y >= 0 && x < cols && x >= 0) |
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{ |
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float g11 = M[mad24(y, mStep, x)]; |
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float g12 = M[mad24(rows + y, mStep, x)]; |
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float g22 = M[mad24(2*rows + y, mStep, x)]; |
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float h1 = M[mad24(3*rows + y, mStep, x)]; |
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float h2 = M[mad24(4*rows + y, mStep, x)]; |
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float detInv = 1.f / (g11*g22 - g12*g12 + 1e-3f); |
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flowx[mad24(y, xStep, x)] = (g11*h2 - g12*h1) * detInv; |
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flowy[mad24(y, yStep, x)] = (g22*h1 - g12*h2) * detInv; |
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} |
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}
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