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Commit ac8506db authored by Roman Donchenko's avatar Roman Donchenko Committed by OpenCV Buildbot
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Merge pull request #1210 from pengx17:2.4_ocl_surf_intel_fix

parents 35cb59bb fd77a49e
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modules/nonfree/src/opencl/surf.cl
View file @ ac8506db
......@@ -16,6 +16,7 @@
//
// @Authors
// Peng Xiao, pengxiao@multicorewareinc.com
// Sen Liu, swjtuls1987@126.com
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
......@@ -43,9 +44,6 @@
//
//M*/
#pragma OPENCL EXTENSION cl_khr_global_int32_base_atomics : enable
#pragma OPENCL EXTENSION cl_khr_local_int32_base_atomics : enable
// specialized for non-image2d_t supported platform, intel HD4000, for example
#ifdef DISABLE_IMAGE2D
#define IMAGE_INT32 __global uint *
......@@ -105,7 +103,7 @@ __constant sampler_t sampler = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAM
// for simple haar paatern
float icvCalcHaarPatternSum_2(
IMAGE_INT32 sumTex,
__constant float src[2][5],
__constant float2 *src,
int oldSize,
int newSize,
int y, int x,
......@@ -116,21 +114,24 @@ float icvCalcHaarPatternSum_2(
F d = 0;
#pragma unroll
for (int k = 0; k < 2; ++k)
{
int dx1 = convert_int_rte(ratio * src[k][0]);
int dy1 = convert_int_rte(ratio * src[k][1]);
int dx2 = convert_int_rte(ratio * src[k][2]);
int dy2 = convert_int_rte(ratio * src[k][3]);
F t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1, y + dy1), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1, y + dy2), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2, y + dy1), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2, y + dy2), rows, cols, elemPerRow );
d += t * src[k][4] / ((dx2 - dx1) * (dy2 - dy1));
}
int2 dx1 = convert_int2_rte(ratio * src[0]);
int2 dy1 = convert_int2_rte(ratio * src[1]);
int2 dx2 = convert_int2_rte(ratio * src[2]);
int2 dy2 = convert_int2_rte(ratio * src[3]);
F t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1.x, y + dy1.x), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1.x, y + dy2.x), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2.x, y + dy1.x), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2.x, y + dy2.x), rows, cols, elemPerRow );
d += t * src[4].x / ((dx2.x - dx1.x) * (dy2.x - dy1.x));
t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1.y, y + dy1.y), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1.y, y + dy2.y), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2.y, y + dy1.y), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2.y, y + dy2.y), rows, cols, elemPerRow );
d += t * src[4].y / ((dx2.y - dx1.y) * (dy2.y - dy1.y));
return (float)d;
}
......@@ -138,7 +139,7 @@ float icvCalcHaarPatternSum_2(
// N = 3
float icvCalcHaarPatternSum_3(
IMAGE_INT32 sumTex,
__constant float src[2][5],
__constant float4 *src,
int oldSize,
int newSize,
int y, int x,
......@@ -149,21 +150,31 @@ float icvCalcHaarPatternSum_3(
F d = 0;
#pragma unroll
for (int k = 0; k < 3; ++k)
{
int dx1 = convert_int_rte(ratio * src[k][0]);
int dy1 = convert_int_rte(ratio * src[k][1]);
int dx2 = convert_int_rte(ratio * src[k][2]);
int dy2 = convert_int_rte(ratio * src[k][3]);
F t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1, y + dy1), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1, y + dy2), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2, y + dy1), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2, y + dy2), rows, cols, elemPerRow );
d += t * src[k][4] / ((dx2 - dx1) * (dy2 - dy1));
}
int4 dx1 = convert_int4_rte(ratio * src[0]);
int4 dy1 = convert_int4_rte(ratio * src[1]);
int4 dx2 = convert_int4_rte(ratio * src[2]);
int4 dy2 = convert_int4_rte(ratio * src[3]);
F t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1.x, y + dy1.x), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1.x, y + dy2.x), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2.x, y + dy1.x), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2.x, y + dy2.x), rows, cols, elemPerRow );
d += t * src[4].x / ((dx2.x - dx1.x) * (dy2.x - dy1.x));
t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1.y, y + dy1.y), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1.y, y + dy2.y), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2.y, y + dy1.y), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2.y, y + dy2.y), rows, cols, elemPerRow );
d += t * src[4].y / ((dx2.y - dx1.y) * (dy2.y - dy1.y));
t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1.z, y + dy1.z), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1.z, y + dy2.z), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2.z, y + dy1.z), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2.z, y + dy2.z), rows, cols, elemPerRow );
d += t * src[4].z / ((dx2.z - dx1.z) * (dy2.z - dy1.z));
return (float)d;
}
......@@ -171,7 +182,7 @@ float icvCalcHaarPatternSum_3(
// N = 4
float icvCalcHaarPatternSum_4(
IMAGE_INT32 sumTex,
__constant float src[2][5],
__constant float4 *src,
int oldSize,
int newSize,
int y, int x,
......@@ -182,21 +193,38 @@ float icvCalcHaarPatternSum_4(
F d = 0;
#pragma unroll
for (int k = 0; k < 4; ++k)
{
int dx1 = convert_int_rte(ratio * src[k][0]);
int dy1 = convert_int_rte(ratio * src[k][1]);
int dx2 = convert_int_rte(ratio * src[k][2]);
int dy2 = convert_int_rte(ratio * src[k][3]);
F t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1, y + dy1), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1, y + dy2), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2, y + dy1), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2, y + dy2), rows, cols, elemPerRow );
d += t * src[k][4] / ((dx2 - dx1) * (dy2 - dy1));
}
int4 dx1 = convert_int4_rte(ratio * src[0]);
int4 dy1 = convert_int4_rte(ratio * src[1]);
int4 dx2 = convert_int4_rte(ratio * src[2]);
int4 dy2 = convert_int4_rte(ratio * src[3]);
F t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1.x, y + dy1.x), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1.x, y + dy2.x), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2.x, y + dy1.x), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2.x, y + dy2.x), rows, cols, elemPerRow );
d += t * src[4].x / ((dx2.x - dx1.x) * (dy2.x - dy1.x));
t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1.y, y + dy1.y), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1.y, y + dy2.y), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2.y, y + dy1.y), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2.y, y + dy2.y), rows, cols, elemPerRow );
d += t * src[4].y / ((dx2.y - dx1.y) * (dy2.y - dy1.y));
t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1.z, y + dy1.z), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1.z, y + dy2.z), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2.z, y + dy1.z), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2.z, y + dy2.z), rows, cols, elemPerRow );
d += t * src[4].z / ((dx2.z - dx1.z) * (dy2.z - dy1.z));
t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + dx1.w, y + dy1.w), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx1.w, y + dy2.w), rows, cols, elemPerRow );
t -= read_sumTex( sumTex, sampler, (int2)(x + dx2.w, y + dy1.w), rows, cols, elemPerRow );
t += read_sumTex( sumTex, sampler, (int2)(x + dx2.w, y + dy2.w), rows, cols, elemPerRow );
d += t * src[4].w / ((dx2.w - dx1.w) * (dy2.w - dy1.w));
return (float)d;
}
......@@ -204,9 +232,9 @@ float icvCalcHaarPatternSum_4(
////////////////////////////////////////////////////////////////////////
// Hessian
__constant float c_DX [3][5] = { {0, 2, 3, 7, 1}, {3, 2, 6, 7, -2}, {6, 2, 9, 7, 1} };
__constant float c_DY [3][5] = { {2, 0, 7, 3, 1}, {2, 3, 7, 6, -2}, {2, 6, 7, 9, 1} };
__constant float c_DXY[4][5] = { {1, 1, 4, 4, 1}, {5, 1, 8, 4, -1}, {1, 5, 4, 8, -1}, {5, 5, 8, 8, 1} };
__constant float4 c_DX[5] = { (float4)(0, 3, 6, 0), (float4)(2, 2, 2, 0), (float4)(3, 6, 9, 0), (float4)(7, 7, 7, 0), (float4)(1, -2, 1, 0) };
__constant float4 c_DY[5] = { (float4)(2, 2, 2, 0), (float4)(0, 3, 6, 0), (float4)(7, 7, 7, 0), (float4)(3, 6, 9, 0), (float4)(1, -2, 1, 0) };
__constant float4 c_DXY[5] = { (float4)(1, 5, 1, 5), (float4)(1, 1, 5, 5), (float4)(4, 8, 4, 8), (float4)(4, 4, 8, 8), (float4)(1, -1, -1, 1) };// Use integral image to calculate haar wavelets.
__inline int calcSize(int octave, int layer)
{
......@@ -236,7 +264,7 @@ __kernel void icvCalcLayerDetAndTrace(
int c_octave,
int c_layer_rows,
int sumTex_step
)
)
{
det_step /= sizeof(*det);
trace_step /= sizeof(*trace);
......@@ -300,7 +328,7 @@ bool within_check(IMAGE_INT32 maskSumTex, int sum_i, int sum_j, int size, int ro
// Non-maximal suppression to further filtering the candidates from previous step
__kernel
void icvFindMaximaInLayer_withmask(
void icvFindMaximaInLayer_withmask(
__global const float * det,
__global const float * trace,
__global int4 * maxPosBuffer,
......@@ -318,7 +346,7 @@ __kernel
float c_hessianThreshold,
IMAGE_INT32 maskSumTex,
int mask_step
)
)
{
volatile __local float N9[768]; // threads.x * threads.y * 3
......@@ -347,26 +375,26 @@ __kernel
const int localLin = get_local_id(0) + get_local_id(1) * get_local_size(0) + zoff;
N9[localLin - zoff] =
det[det_step *
(c_layer_rows * (layer - 1) + min(max(i, 0), c_img_rows - 1)) // y
+ min(max(j, 0), c_img_cols - 1)]; // x
(c_layer_rows * (layer - 1) + min(max(i, 0), c_img_rows - 1)) // y
+ min(max(j, 0), c_img_cols - 1)]; // x
N9[localLin ] =
det[det_step *
(c_layer_rows * (layer ) + min(max(i, 0), c_img_rows - 1)) // y
+ min(max(j, 0), c_img_cols - 1)]; // x
(c_layer_rows * (layer ) + min(max(i, 0), c_img_rows - 1)) // y
+ min(max(j, 0), c_img_cols - 1)]; // x
N9[localLin + zoff] =
det[det_step *
(c_layer_rows * (layer + 1) + min(max(i, 0), c_img_rows - 1)) // y
+ min(max(j, 0), c_img_cols - 1)]; // x
(c_layer_rows * (layer + 1) + min(max(i, 0), c_img_rows - 1)) // y
+ min(max(j, 0), c_img_cols - 1)]; // x
barrier(CLK_LOCAL_MEM_FENCE);
if (i < c_layer_rows - margin
&& j < c_layer_cols - margin
&& get_local_id(0) > 0
&& get_local_id(0) < get_local_size(0) - 1
&& get_local_id(1) > 0
&& get_local_id(1) < get_local_size(1) - 1 // these are unnecessary conditions ported from CUDA
)
&& j < c_layer_cols - margin
&& get_local_id(0) > 0
&& get_local_id(0) < get_local_size(0) - 1
&& get_local_id(1) > 0
&& get_local_id(1) < get_local_size(1) - 1 // these are unnecessary conditions ported from CUDA
)
{
float val0 = N9[localLin];
......@@ -382,34 +410,34 @@ __kernel
{
// Check to see if we have a max (in its 26 neighbours)
const bool condmax = val0 > N9[localLin - 1 - get_local_size(0) - zoff]
&& val0 > N9[localLin - get_local_size(0) - zoff]
&& val0 > N9[localLin + 1 - get_local_size(0) - zoff]
&& val0 > N9[localLin - 1 - zoff]
&& val0 > N9[localLin - zoff]
&& val0 > N9[localLin + 1 - zoff]
&& val0 > N9[localLin - 1 + get_local_size(0) - zoff]
&& val0 > N9[localLin + get_local_size(0) - zoff]
&& val0 > N9[localLin + 1 + get_local_size(0) - zoff]
&& val0 > N9[localLin - 1 - get_local_size(0)]
&& val0 > N9[localLin - get_local_size(0)]
&& val0 > N9[localLin + 1 - get_local_size(0)]
&& val0 > N9[localLin - 1 ]
&& val0 > N9[localLin + 1 ]
&& val0 > N9[localLin - 1 + get_local_size(0)]
&& val0 > N9[localLin + get_local_size(0)]
&& val0 > N9[localLin + 1 + get_local_size(0)]
&& val0 > N9[localLin - 1 - get_local_size(0) + zoff]
&& val0 > N9[localLin - get_local_size(0) + zoff]
&& val0 > N9[localLin + 1 - get_local_size(0) + zoff]
&& val0 > N9[localLin - 1 + zoff]
&& val0 > N9[localLin + zoff]
&& val0 > N9[localLin + 1 + zoff]
&& val0 > N9[localLin - 1 + get_local_size(0) + zoff]
&& val0 > N9[localLin + get_local_size(0) + zoff]
&& val0 > N9[localLin + 1 + get_local_size(0) + zoff]
;
&& val0 > N9[localLin - get_local_size(0) - zoff]
&& val0 > N9[localLin + 1 - get_local_size(0) - zoff]
&& val0 > N9[localLin - 1 - zoff]
&& val0 > N9[localLin - zoff]
&& val0 > N9[localLin + 1 - zoff]
&& val0 > N9[localLin - 1 + get_local_size(0) - zoff]
&& val0 > N9[localLin + get_local_size(0) - zoff]
&& val0 > N9[localLin + 1 + get_local_size(0) - zoff]
&& val0 > N9[localLin - 1 - get_local_size(0)]
&& val0 > N9[localLin - get_local_size(0)]
&& val0 > N9[localLin + 1 - get_local_size(0)]
&& val0 > N9[localLin - 1 ]
&& val0 > N9[localLin + 1 ]
&& val0 > N9[localLin - 1 + get_local_size(0)]
&& val0 > N9[localLin + get_local_size(0)]
&& val0 > N9[localLin + 1 + get_local_size(0)]
&& val0 > N9[localLin - 1 - get_local_size(0) + zoff]
&& val0 > N9[localLin - get_local_size(0) + zoff]
&& val0 > N9[localLin + 1 - get_local_size(0) + zoff]
&& val0 > N9[localLin - 1 + zoff]
&& val0 > N9[localLin + zoff]
&& val0 > N9[localLin + 1 + zoff]
&& val0 > N9[localLin - 1 + get_local_size(0) + zoff]
&& val0 > N9[localLin + get_local_size(0) + zoff]
&& val0 > N9[localLin + 1 + get_local_size(0) + zoff]
;
if(condmax)
{
......@@ -428,7 +456,7 @@ __kernel
}
__kernel
void icvFindMaximaInLayer(
void icvFindMaximaInLayer(
__global float * det,
__global float * trace,
__global int4 * maxPosBuffer,
......@@ -444,7 +472,7 @@ __kernel
int c_layer_cols,
int c_max_candidates,
float c_hessianThreshold
)
)
{
volatile __local float N9[768]; // threads.x * threads.y * 3
......@@ -483,12 +511,12 @@ __kernel
barrier(CLK_LOCAL_MEM_FENCE);
if (i < c_layer_rows - margin
&& j < c_layer_cols - margin
&& get_local_id(0) > 0
&& get_local_id(0) < get_local_size(0) - 1
&& get_local_id(1) > 0
&& get_local_id(1) < get_local_size(1) - 1 // these are unnecessary conditions ported from CUDA
)
&& j < c_layer_cols - margin
&& get_local_id(0) > 0
&& get_local_id(0) < get_local_size(0) - 1
&& get_local_id(1) > 0
&& get_local_id(1) < get_local_size(1) - 1 // these are unnecessary conditions ported from CUDA
)
{
float val0 = N9[localLin];
if (val0 > c_hessianThreshold)
......@@ -499,38 +527,38 @@ __kernel
// Check to see if we have a max (in its 26 neighbours)
const bool condmax = val0 > N9[localLin - 1 - get_local_size(0) - zoff]
&& val0 > N9[localLin - get_local_size(0) - zoff]
&& val0 > N9[localLin + 1 - get_local_size(0) - zoff]
&& val0 > N9[localLin - 1 - zoff]
&& val0 > N9[localLin - zoff]
&& val0 > N9[localLin + 1 - zoff]
&& val0 > N9[localLin - 1 + get_local_size(0) - zoff]
&& val0 > N9[localLin + get_local_size(0) - zoff]
&& val0 > N9[localLin + 1 + get_local_size(0) - zoff]
&& val0 > N9[localLin - 1 - get_local_size(0)]
&& val0 > N9[localLin - get_local_size(0)]
&& val0 > N9[localLin + 1 - get_local_size(0)]
&& val0 > N9[localLin - 1 ]
&& val0 > N9[localLin + 1 ]
&& val0 > N9[localLin - 1 + get_local_size(0)]
&& val0 > N9[localLin + get_local_size(0)]
&& val0 > N9[localLin + 1 + get_local_size(0)]
&& val0 > N9[localLin - 1 - get_local_size(0) + zoff]
&& val0 > N9[localLin - get_local_size(0) + zoff]
&& val0 > N9[localLin + 1 - get_local_size(0) + zoff]
&& val0 > N9[localLin - 1 + zoff]
&& val0 > N9[localLin + zoff]
&& val0 > N9[localLin + 1 + zoff]
&& val0 > N9[localLin - 1 + get_local_size(0) + zoff]
&& val0 > N9[localLin + get_local_size(0) + zoff]
&& val0 > N9[localLin + 1 + get_local_size(0) + zoff]
;
&& val0 > N9[localLin - get_local_size(0) - zoff]
&& val0 > N9[localLin + 1 - get_local_size(0) - zoff]
&& val0 > N9[localLin - 1 - zoff]
&& val0 > N9[localLin - zoff]
&& val0 > N9[localLin + 1 - zoff]
&& val0 > N9[localLin - 1 + get_local_size(0) - zoff]
&& val0 > N9[localLin + get_local_size(0) - zoff]
&& val0 > N9[localLin + 1 + get_local_size(0) - zoff]
&& val0 > N9[localLin - 1 - get_local_size(0)]
&& val0 > N9[localLin - get_local_size(0)]
&& val0 > N9[localLin + 1 - get_local_size(0)]
&& val0 > N9[localLin - 1 ]
&& val0 > N9[localLin + 1 ]
&& val0 > N9[localLin - 1 + get_local_size(0)]
&& val0 > N9[localLin + get_local_size(0)]
&& val0 > N9[localLin + 1 + get_local_size(0)]
&& val0 > N9[localLin - 1 - get_local_size(0) + zoff]
&& val0 > N9[localLin - get_local_size(0) + zoff]
&& val0 > N9[localLin + 1 - get_local_size(0) + zoff]
&& val0 > N9[localLin - 1 + zoff]
&& val0 > N9[localLin + zoff]
&& val0 > N9[localLin + 1 + zoff]
&& val0 > N9[localLin - 1 + get_local_size(0) + zoff]
&& val0 > N9[localLin + get_local_size(0) + zoff]
&& val0 > N9[localLin + 1 + get_local_size(0) + zoff]
;
if(condmax)
{
int ind = atomic_inc(maxCounter);
int ind = atomic_inc(maxCounter);
if (ind < c_max_candidates)
{
......@@ -544,30 +572,30 @@ __kernel
}
// solve 3x3 linear system Ax=b for floating point input
inline bool solve3x3_float(volatile __local const float A[3][3], volatile __local const float b[3], volatile __local float x[3])
inline bool solve3x3_float(volatile __local const float4 *A, volatile __local const float *b, volatile __local float *x)
{
float det = A[0][0] * (A[1][1] * A[2][2] - A[1][2] * A[2][1])
- A[0][1] * (A[1][0] * A[2][2] - A[1][2] * A[2][0])
+ A[0][2] * (A[1][0] * A[2][1] - A[1][1] * A[2][0]);
float det = A[0].x * (A[1].y * A[2].z - A[1].z * A[2].y)
- A[0].y * (A[1].x * A[2].z - A[1].z * A[2].x)
+ A[0].z * (A[1].x * A[2].y - A[1].y * A[2].x);
if (det != 0)
{
F invdet = 1.0 / det;
x[0] = invdet *
(b[0] * (A[1][1] * A[2][2] - A[1][2] * A[2][1]) -
A[0][1] * (b[1] * A[2][2] - A[1][2] * b[2] ) +
A[0][2] * (b[1] * A[2][1] - A[1][1] * b[2] ));
(b[0] * (A[1].y * A[2].z - A[1].z * A[2].y) -
A[0].y * (b[1] * A[2].z - A[1].z * b[2] ) +
A[0].z * (b[1] * A[2].y - A[1].y * b[2] ));
x[1] = invdet *
(A[0][0] * (b[1] * A[2][2] - A[1][2] * b[2] ) -
b[0] * (A[1][0] * A[2][2] - A[1][2] * A[2][0]) +
A[0][2] * (A[1][0] * b[2] - b[1] * A[2][0]));
(A[0].x * (b[1] * A[2].z - A[1].z * b[2] ) -
b[0] * (A[1].x * A[2].z - A[1].z * A[2].x) +
A[0].z * (A[1].x * b[2] - b[1] * A[2].x));
x[2] = invdet *
(A[0][0] * (A[1][1] * b[2] - b[1] * A[2][1]) -
A[0][1] * (A[1][0] * b[2] - b[1] * A[2][0]) +
b[0] * (A[1][0] * A[2][1] - A[1][1] * A[2][0]));
(A[0].x * (A[1].y * b[2] - b[1] * A[2].y) -
A[0].y * (A[1].x * b[2] - b[1] * A[2].x) +
b[0] * (A[1].x * A[2].y - A[1].y * A[2].x));
return true;
}
......@@ -586,7 +614,7 @@ inline bool solve3x3_float(volatile __local const float A[3][3], volatile __loc
////////////////////////////////////////////////////////////////////////
// INTERPOLATION
__kernel
void icvInterpolateKeypoint(
void icvInterpolateKeypoint(
__global const float * det,
__global const int4 * maxPosBuffer,
__global float * keypoints,
......@@ -598,7 +626,7 @@ __kernel
int c_octave,
int c_layer_rows,
int c_max_features
)
)
{
det_step /= sizeof(*det);
keypoints_step /= sizeof(*keypoints);
......@@ -632,26 +660,26 @@ __kernel
//ds
dD[2] = -0.5f * (N9[2][1][1] - N9[0][1][1]);
volatile __local float H[3][3];
volatile __local float4 H[3];
//dxx
H[0][0] = N9[1][1][0] - 2.0f * N9[1][1][1] + N9[1][1][2];
H[0].x = N9[1][1][0] - 2.0f * N9[1][1][1] + N9[1][1][2];
//dxy
H[0][1]= 0.25f * (N9[1][2][2] - N9[1][2][0] - N9[1][0][2] + N9[1][0][0]);
H[0].y= 0.25f * (N9[1][2][2] - N9[1][2][0] - N9[1][0][2] + N9[1][0][0]);
//dxs
H[0][2]= 0.25f * (N9[2][1][2] - N9[2][1][0] - N9[0][1][2] + N9[0][1][0]);
H[0].z= 0.25f * (N9[2][1][2] - N9[2][1][0] - N9[0][1][2] + N9[0][1][0]);
//dyx = dxy
H[1][0] = H[0][1];
H[1].x = H[0].y;
//dyy
H[1][1] = N9[1][0][1] - 2.0f * N9[1][1][1] + N9[1][2][1];
H[1].y = N9[1][0][1] - 2.0f * N9[1][1][1] + N9[1][2][1];
//dys
H[1][2]= 0.25f * (N9[2][2][1] - N9[2][0][1] - N9[0][2][1] + N9[0][0][1]);
H[1].z= 0.25f * (N9[2][2][1] - N9[2][0][1] - N9[0][2][1] + N9[0][0][1]);
//dsx = dxs
H[2][0] = H[0][2];
H[2].x = H[0].z;
//dsy = dys
H[2][1] = H[1][2];
H[2].y = H[1].z;
//dss
H[2][2] = N9[0][1][1] - 2.0f * N9[1][1][1] + N9[2][1][1];
H[2].z = N9[0][1][1] - 2.0f * N9[1][1][1] + N9[2][1][1];
volatile __local float x[3];
......@@ -689,7 +717,7 @@ __kernel
if ((c_img_rows + 1) >= grad_wav_size && (c_img_cols + 1) >= grad_wav_size)
{
// Get a new feature index.
int ind = atomic_inc(featureCounter);
int ind = atomic_inc(featureCounter);
if (ind < c_max_features)
{
......@@ -716,31 +744,32 @@ __kernel
__constant float c_aptX[ORI_SAMPLES] = {-6, -5, -5, -5, -5, -5, -5, -5, -4, -4, -4, -4, -4, -4, -4, -4, -4, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 6};
__constant float c_aptY[ORI_SAMPLES] = {0, -3, -2, -1, 0, 1, 2, 3, -4, -3, -2, -1, 0, 1, 2, 3, 4, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, -4, -3, -2, -1, 0, 1, 2, 3, 4, -3, -2, -1, 0, 1, 2, 3, 0};
__constant float c_aptW[ORI_SAMPLES] = {0.001455130288377404f, 0.001707611023448408f, 0.002547456417232752f, 0.003238451667129993f, 0.0035081731621176f,
0.003238451667129993f, 0.002547456417232752f, 0.001707611023448408f, 0.002003900473937392f, 0.0035081731621176f, 0.005233579315245152f,
0.00665318313986063f, 0.00720730796456337f, 0.00665318313986063f, 0.005233579315245152f, 0.0035081731621176f,
0.002003900473937392f, 0.001707611023448408f, 0.0035081731621176f, 0.006141661666333675f, 0.009162282571196556f,
0.01164754293859005f, 0.01261763460934162f, 0.01164754293859005f, 0.009162282571196556f, 0.006141661666333675f,
0.0035081731621176f, 0.001707611023448408f, 0.002547456417232752f, 0.005233579315245152f, 0.009162282571196556f,
0.01366852037608624f, 0.01737609319388866f, 0.0188232995569706f, 0.01737609319388866f, 0.01366852037608624f,
0.009162282571196556f, 0.005233579315245152f, 0.002547456417232752f, 0.003238451667129993f, 0.00665318313986063f,
0.01164754293859005f, 0.01737609319388866f, 0.02208934165537357f, 0.02392910048365593f, 0.02208934165537357f,
0.01737609319388866f, 0.01164754293859005f, 0.00665318313986063f, 0.003238451667129993f, 0.001455130288377404f,
0.0035081731621176f, 0.00720730796456337f, 0.01261763460934162f, 0.0188232995569706f, 0.02392910048365593f,
0.02592208795249462f, 0.02392910048365593f, 0.0188232995569706f, 0.01261763460934162f, 0.00720730796456337f,
0.0035081731621176f, 0.001455130288377404f, 0.003238451667129993f, 0.00665318313986063f, 0.01164754293859005f,
0.01737609319388866f, 0.02208934165537357f, 0.02392910048365593f, 0.02208934165537357f, 0.01737609319388866f,
0.01164754293859005f, 0.00665318313986063f, 0.003238451667129993f, 0.002547456417232752f, 0.005233579315245152f,
0.009162282571196556f, 0.01366852037608624f, 0.01737609319388866f, 0.0188232995569706f, 0.01737609319388866f,
0.01366852037608624f, 0.009162282571196556f, 0.005233579315245152f, 0.002547456417232752f, 0.001707611023448408f,
0.0035081731621176f, 0.006141661666333675f, 0.009162282571196556f, 0.01164754293859005f, 0.01261763460934162f,
0.01164754293859005f, 0.009162282571196556f, 0.006141661666333675f, 0.0035081731621176f, 0.001707611023448408f,
0.002003900473937392f, 0.0035081731621176f, 0.005233579315245152f, 0.00665318313986063f, 0.00720730796456337f,
0.00665318313986063f, 0.005233579315245152f, 0.0035081731621176f, 0.002003900473937392f, 0.001707611023448408f,
0.002547456417232752f, 0.003238451667129993f, 0.0035081731621176f, 0.003238451667129993f, 0.002547456417232752f,
0.001707611023448408f, 0.001455130288377404f};
__constant float c_NX[2][5] = {{0, 0, 2, 4, -1}, {2, 0, 4, 4, 1}};
__constant float c_NY[2][5] = {{0, 0, 4, 2, 1}, {0, 2, 4, 4, -1}};
0.003238451667129993f, 0.002547456417232752f, 0.001707611023448408f, 0.002003900473937392f, 0.0035081731621176f, 0.005233579315245152f,
0.00665318313986063f, 0.00720730796456337f, 0.00665318313986063f, 0.005233579315245152f, 0.0035081731621176f,
0.002003900473937392f, 0.001707611023448408f, 0.0035081731621176f, 0.006141661666333675f, 0.009162282571196556f,
0.01164754293859005f, 0.01261763460934162f, 0.01164754293859005f, 0.009162282571196556f, 0.006141661666333675f,
0.0035081731621176f, 0.001707611023448408f, 0.002547456417232752f, 0.005233579315245152f, 0.009162282571196556f,
0.01366852037608624f, 0.01737609319388866f, 0.0188232995569706f, 0.01737609319388866f, 0.01366852037608624f,
0.009162282571196556f, 0.005233579315245152f, 0.002547456417232752f, 0.003238451667129993f, 0.00665318313986063f,
0.01164754293859005f, 0.01737609319388866f, 0.02208934165537357f, 0.02392910048365593f, 0.02208934165537357f,
0.01737609319388866f, 0.01164754293859005f, 0.00665318313986063f, 0.003238451667129993f, 0.001455130288377404f,
0.0035081731621176f, 0.00720730796456337f, 0.01261763460934162f, 0.0188232995569706f, 0.02392910048365593f,
0.02592208795249462f, 0.02392910048365593f, 0.0188232995569706f, 0.01261763460934162f, 0.00720730796456337f,
0.0035081731621176f, 0.001455130288377404f, 0.003238451667129993f, 0.00665318313986063f, 0.01164754293859005f,
0.01737609319388866f, 0.02208934165537357f, 0.02392910048365593f, 0.02208934165537357f, 0.01737609319388866f,
0.01164754293859005f, 0.00665318313986063f, 0.003238451667129993f, 0.002547456417232752f, 0.005233579315245152f,
0.009162282571196556f, 0.01366852037608624f, 0.01737609319388866f, 0.0188232995569706f, 0.01737609319388866f,
0.01366852037608624f, 0.009162282571196556f, 0.005233579315245152f, 0.002547456417232752f, 0.001707611023448408f,
0.0035081731621176f, 0.006141661666333675f, 0.009162282571196556f, 0.01164754293859005f, 0.01261763460934162f,
0.01164754293859005f, 0.009162282571196556f, 0.006141661666333675f, 0.0035081731621176f, 0.001707611023448408f,
0.002003900473937392f, 0.0035081731621176f, 0.005233579315245152f, 0.00665318313986063f, 0.00720730796456337f,
0.00665318313986063f, 0.005233579315245152f, 0.0035081731621176f, 0.002003900473937392f, 0.001707611023448408f,
0.002547456417232752f, 0.003238451667129993f, 0.0035081731621176f, 0.003238451667129993f, 0.002547456417232752f,
0.001707611023448408f, 0.001455130288377404f
};
__constant float2 c_NX[5] = { (float2)(0, 2), (float2)(0, 0), (float2)(2, 4), (float2)(4, 4), (float2)(-1, 1) };
__constant float2 c_NY[5] = { (float2)(0, 0), (float2)(0, 2), (float2)(4, 4), (float2)(2, 4), (float2)(1, -1) };
void reduce_32_sum(volatile __local float * data, volatile float* partial_reduction, int tid)
{
......@@ -759,14 +788,14 @@ void reduce_32_sum(volatile __local float * data, volatile float* partial_reduc
if (tid < 8)
{
#endif
data[tid] = *partial_reduction = op(partial_reduction, data[tid + 8 ]);
data[tid] = *partial_reduction = op(partial_reduction, data[tid + 8]);
#if WAVE_SIZE < 8
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 4)
{
#endif
data[tid] = *partial_reduction = op(partial_reduction, data[tid + 4 ]);
data[tid] = *partial_reduction = op(partial_reduction, data[tid + 4]);
#if WAVE_SIZE < 4
}
barrier(CLK_LOCAL_MEM_FENCE);
......@@ -787,14 +816,14 @@ void reduce_32_sum(volatile __local float * data, volatile float* partial_reduc
}
__kernel
void icvCalcOrientation(
void icvCalcOrientation(
IMAGE_INT32 sumTex,
__global float * keypoints,
int keypoints_step,
int c_img_rows,
int c_img_cols,
int sum_step
)
)
{
keypoints_step /= sizeof(*keypoints);
sum_step /= sizeof(uint);
......@@ -838,7 +867,7 @@ __kernel
const int y = convert_int_rte(featureY[get_group_id(0)] + c_aptY[tid] * s - margin);
if (y >= 0 && y < (c_img_rows + 1) - grad_wav_size &&
x >= 0 && x < (c_img_cols + 1) - grad_wav_size)
x >= 0 && x < (c_img_cols + 1) - grad_wav_size)
{
X = c_aptW[tid] * icvCalcHaarPatternSum_2(sumTex, c_NX, 4, grad_wav_size, y, x, c_img_rows, c_img_cols, sum_step);
Y = c_aptW[tid] * icvCalcHaarPatternSum_2(sumTex, c_NY, 4, grad_wav_size, y, x, c_img_rows, c_img_cols, sum_step);
......@@ -934,11 +963,11 @@ __kernel
__kernel
void icvSetUpright(
void icvSetUpright(
__global float * keypoints,
int keypoints_step,
int nFeatures
)
)
{
keypoints_step /= sizeof(*keypoints);
__global float* featureDir = keypoints + ANGLE_ROW * keypoints_step;
......@@ -988,7 +1017,7 @@ inline uchar readerGet(
IMAGE_INT8 src,
const float centerX, const float centerY, const float win_offset, const float cos_dir, const float sin_dir,
int i, int j, int rows, int cols, int elemPerRow
)
)
{
float pixel_x = centerX + (win_offset + j) * cos_dir + (win_offset + i) * sin_dir;
float pixel_y = centerY - (win_offset + j) * sin_dir + (win_offset + i) * cos_dir;
......@@ -999,7 +1028,7 @@ inline float linearFilter(
IMAGE_INT8 src,
const float centerX, const float centerY, const float win_offset, const float cos_dir, const float sin_dir,
float y, float x, int rows, int cols, int elemPerRow
)
)
{
x -= 0.5f;
y -= 0.5f;
......@@ -1028,9 +1057,9 @@ inline float linearFilter(
void calc_dx_dy(
IMAGE_INT8 imgTex,
volatile __local float s_dx_bin[25],
volatile __local float s_dy_bin[25],
volatile __local float s_PATCH[6][6],
volatile __local float *s_dx_bin,
volatile __local float *s_dy_bin,
volatile __local float *s_PATCH,
__global const float* featureX,
__global const float* featureY,
__global const float* featureSize,
......@@ -1038,7 +1067,7 @@ void calc_dx_dy(
int rows,
int cols,
int elemPerRow
)
)
{
const float centerX = featureX[get_group_id(0)];
const float centerY = featureY[get_group_id(0)];
......@@ -1048,6 +1077,7 @@ void calc_dx_dy(
{
descriptor_dir = 0.0f;
}
descriptor_dir *= (float)(CV_PI_F / 180.0f);
/* The sampling intervals and wavelet sized for selecting an orientation
......@@ -1074,7 +1104,7 @@ void calc_dx_dy(
const float icoo = ((float)yIndex / (PATCH_SZ + 1)) * win_size;
const float jcoo = ((float)xIndex / (PATCH_SZ + 1)) * win_size;
s_PATCH[get_local_id(1)][get_local_id(0)] = linearFilter(imgTex, centerX, centerY, win_offset, cos_dir, sin_dir, icoo, jcoo, rows, cols, elemPerRow);
s_PATCH[get_local_id(1) * 6 + get_local_id(0)] = linearFilter(imgTex, centerX, centerY, win_offset, cos_dir, sin_dir, icoo, jcoo, rows, cols, elemPerRow);
barrier(CLK_LOCAL_MEM_FENCE);
......@@ -1085,17 +1115,17 @@ void calc_dx_dy(
const float dw = c_DW[yIndex * PATCH_SZ + xIndex];
const float vx = (
s_PATCH[get_local_id(1) ][get_local_id(0) + 1] -
s_PATCH[get_local_id(1) ][get_local_id(0) ] +
s_PATCH[get_local_id(1) + 1][get_local_id(0) + 1] -
s_PATCH[get_local_id(1) + 1][get_local_id(0) ])
* dw;
s_PATCH[ get_local_id(1) * 6 + get_local_id(0) + 1] -
s_PATCH[ get_local_id(1) * 6 + get_local_id(0) ] +
s_PATCH[(get_local_id(1) + 1) * 6 + get_local_id(0) + 1] -
s_PATCH[(get_local_id(1) + 1) * 6 + get_local_id(0) ])
* dw;
const float vy = (
s_PATCH[get_local_id(1) + 1][get_local_id(0) ] -
s_PATCH[get_local_id(1) ][get_local_id(0) ] +
s_PATCH[get_local_id(1) + 1][get_local_id(0) + 1] -
s_PATCH[get_local_id(1) ][get_local_id(0) + 1])
* dw;
s_PATCH[(get_local_id(1) + 1) * 6 + get_local_id(0) ] -
s_PATCH[ get_local_id(1) * 6 + get_local_id(0) ] +
s_PATCH[(get_local_id(1) + 1) * 6 + get_local_id(0) + 1] -
s_PATCH[ get_local_id(1) * 6 + get_local_id(0) + 1])
* dw;
s_dx_bin[tid] = vx;
s_dy_bin[tid] = vy;
}
......@@ -1106,7 +1136,7 @@ void reduce_sum25(
volatile __local float* sdata3,
volatile __local float* sdata4,
int tid
)
)
{
#ifndef WAVE_SIZE
#define WAVE_SIZE 1
......@@ -1125,11 +1155,8 @@ void reduce_sum25(
{
#endif
sdata1[tid] += sdata1[tid + 8];
sdata2[tid] += sdata2[tid + 8];
sdata3[tid] += sdata3[tid + 8];
sdata4[tid] += sdata4[tid + 8];
#if WAVE_SIZE < 8
}
......@@ -1166,7 +1193,7 @@ void reduce_sum25(
}
__kernel
void compute_descriptors64(
void compute_descriptors64(
IMAGE_INT8 imgTex,
__global float * descriptors,
__global const float * keypoints,
......@@ -1175,7 +1202,7 @@ __kernel
int rows,
int cols,
int img_step
)
)
{
descriptors_step /= sizeof(float);
keypoints_step /= sizeof(float);
......@@ -1189,7 +1216,7 @@ __kernel
volatile __local float sdy[25];
volatile __local float sdxabs[25];
volatile __local float sdyabs[25];
volatile __local float s_PATCH[6][6];
volatile __local float s_PATCH[6*6];
calc_dx_dy(imgTex, sdx, sdy, s_PATCH, featureX, featureY, featureSize, featureDir, rows, cols, img_step);
barrier(CLK_LOCAL_MEM_FENCE);
......@@ -1203,7 +1230,7 @@ __kernel
}
barrier(CLK_LOCAL_MEM_FENCE);
reduce_sum25(sdx, sdy, sdxabs, sdyabs, tid);
reduce_sum25(sdx, sdy, sdxabs, sdyabs, tid);
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 25)
......@@ -1221,7 +1248,7 @@ __kernel
}
}
__kernel
void compute_descriptors128(
void compute_descriptors128(
IMAGE_INT8 imgTex,
__global float * descriptors,
__global float * keypoints,
......@@ -1230,7 +1257,7 @@ __kernel
int rows,
int cols,
int img_step
)
)
{
descriptors_step /= sizeof(*descriptors);
keypoints_step /= sizeof(*keypoints);
......@@ -1249,7 +1276,7 @@ __kernel
volatile __local float sd2[25];
volatile __local float sdabs1[25];
volatile __local float sdabs2[25];
volatile __local float s_PATCH[6][6];
volatile __local float s_PATCH[6*6];
calc_dx_dy(imgTex, sdx, sdy, s_PATCH, featureX, featureY, featureSize, featureDir, rows, cols, img_step);
barrier(CLK_LOCAL_MEM_FENCE);
......@@ -1275,7 +1302,7 @@ __kernel
}
barrier(CLK_LOCAL_MEM_FENCE);
reduce_sum25(sd1, sd2, sdabs1, sdabs2, tid);
reduce_sum25(sd1, sd2, sdabs1, sdabs2, tid);
barrier(CLK_LOCAL_MEM_FENCE);
__global float* descriptors_block = descriptors + descriptors_step * get_group_id(0) + (get_group_id(1) << 3);
......@@ -1306,8 +1333,7 @@ __kernel
}
}
barrier(CLK_LOCAL_MEM_FENCE);
reduce_sum25(sd1, sd2, sdabs1, sdabs2, tid);
reduce_sum25(sd1, sd2, sdabs1, sdabs2, tid);
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 25)
......@@ -1322,11 +1348,13 @@ __kernel
}
}
}
void reduce_sum128(volatile __local float* smem, int tid)
{
#ifndef WAVE_SIZE
#define WAVE_SIZE 1
#endif
if (tid < 64)
{
smem[tid] += smem[tid + 64];
......@@ -1374,6 +1402,8 @@ void reduce_sum128(volatile __local float* smem, int tid)
smem[tid] += smem[tid + 1];
}
}
void reduce_sum64(volatile __local float* smem, int tid)
{
#ifndef WAVE_SIZE
......@@ -1421,7 +1451,7 @@ void reduce_sum64(volatile __local float* smem, int tid)
}
__kernel
void normalize_descriptors128(__global float * descriptors, int descriptors_step)
void normalize_descriptors128(__global float * descriptors, int descriptors_step)
{
descriptors_step /= sizeof(*descriptors);
// no need for thread ID
......@@ -1436,8 +1466,6 @@ __kernel
reduce_sum128(sqDesc, get_local_id(0));
barrier(CLK_LOCAL_MEM_FENCE);
// compute length (square root)
volatile __local float len;
if (get_local_id(0) == 0)
......@@ -1450,7 +1478,7 @@ __kernel
descriptor_base[get_local_id(0)] = lookup / len;
}
__kernel
void normalize_descriptors64(__global float * descriptors, int descriptors_step)
void normalize_descriptors64(__global float * descriptors, int descriptors_step)
{
descriptors_step /= sizeof(*descriptors);
// no need for thread ID
......@@ -1462,7 +1490,6 @@ __kernel
sqDesc[get_local_id(0)] = lookup * lookup;
barrier(CLK_LOCAL_MEM_FENCE);
reduce_sum64(sqDesc, get_local_id(0));
barrier(CLK_LOCAL_MEM_FENCE);
......
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