SURF kind of works (let's see if the tests pass)

This commit is contained in:
Vadim Pisarevsky 2014-02-04 20:00:51 +04:00
parent 8d5e952263
commit c18d1ee2a9
5 changed files with 208 additions and 465 deletions

View File

@ -585,7 +585,7 @@ class CV_EXPORTS Image2D
{
public:
Image2D();
Image2D(const UMat &src);
explicit Image2D(const UMat &src);
~Image2D();
void* ptr() const;

View File

@ -52,35 +52,52 @@
#define ORI_LOCAL_SIZE (360 / ORI_SEARCH_INC)
// specialized for non-image2d_t supported platform, intel HD4000, for example
#ifdef DISABLE_IMAGE2D
#define IMAGE_INT32 __global uint *
#define IMAGE_INT8 __global uchar *
#else
#define IMAGE_INT32 image2d_t
#define IMAGE_INT8 image2d_t
#endif
#ifndef HAVE_IMAGE2D
__inline uint read_sumTex_(__global uint* sumTex, int sum_step, int img_rows, int img_cols, int2 coord)
{
int x = clamp(coord.x, 0, img_cols);
int y = clamp(coord.y, 0, img_rows);
return sumTex[sum_step * y + x];
}
uint read_sumTex(IMAGE_INT32 img, sampler_t sam, int2 coord, int rows, int cols, int elemPerRow)
__inline uchar read_imgTex_(__global uchar* imgTex, int img_step, int img_rows, int img_cols, float2 coord)
{
#ifdef DISABLE_IMAGE2D
int x = clamp(coord.x, 0, cols);
int y = clamp(coord.y, 0, rows);
return img[elemPerRow * y + x];
#else
return read_imageui(img, sam, coord).x;
#endif
int x = clamp(convert_int_rte(coord.x), 0, img_cols-1);
int y = clamp(convert_int_rte(coord.y), 0, img_rows-1);
return imgTex[img_step * y + x];
}
uchar read_imgTex(IMAGE_INT8 img, sampler_t sam, float2 coord, int rows, int cols, int elemPerRow)
#define read_sumTex(coord) read_sumTex_(sumTex, sum_step, img_rows, img_cols, coord)
#define read_imgTex(coord) read_imgTex_(imgTex, img_step, img_rows, img_cols, coord)
#define __PARAM_sumTex__ __global uint* sumTex, int sum_step, int sum_offset
#define __PARAM_imgTex__ __global uchar* imgTex, int img_step, int img_offset
#define __PASS_sumTex__ sumTex, sum_step, sum_offset
#define __PASS_imgTex__ imgTex, img_step, img_offset
#else
__inline uint read_sumTex_(image2d_t sumTex, sampler_t sam, int2 coord)
{
#ifdef DISABLE_IMAGE2D
int x = clamp(round(coord.x), 0, cols - 1);
int y = clamp(round(coord.y), 0, rows - 1);
return img[elemPerRow * y + x];
#else
return (uchar)read_imageui(img, sam, coord).x;
#endif
return read_imageui(sumTex, sam, coord).x;
}
__inline uchar read_imgTex_(image2d_t imgTex, sampler_t sam, float2 coord)
{
return (uchar)read_imageui(imgTex, sam, coord).x;
}
#define read_sumTex(coord) read_sumTex_(sumTex, sampler, coord)
#define read_imgTex(coord) read_imgTex_(imgTex, sampler, coord)
#define __PARAM_sumTex__ image2d_t sumTex
#define __PARAM_imgTex__ image2d_t imgTex
#define __PASS_sumTex__ sumTex
#define __PASS_imgTex__ imgTex
#endif
// dynamically change the precision used for floating type
#if defined (DOUBLE_SUPPORT)
@ -95,7 +112,7 @@ uchar read_imgTex(IMAGE_INT8 img, sampler_t sam, float2 coord, int rows, int col
#endif
// Image read mode
__constant sampler_t sampler = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP_TO_EDGE | CLK_FILTER_NEAREST;
__constant sampler_t sampler = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP_TO_EDGE | CLK_FILTER_NEAREST;
#ifndef FLT_EPSILON
#define FLT_EPSILON (1e-15)
@ -105,45 +122,6 @@ __constant sampler_t sampler = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAM
#define CV_PI_F 3.14159265f
#endif
// Use integral image to calculate haar wavelets.
// N = 2
// for simple haar paatern
float icvCalcHaarPatternSum_2(
IMAGE_INT32 sumTex,
__constant float2 *src,
int oldSize,
int newSize,
int y, int x,
int rows, int cols, int elemPerRow)
{
float ratio = (float)newSize / oldSize;
F d = 0;
int2 dx1 = convert_int2(round(ratio * src[0]));
int2 dy1 = convert_int2(round(ratio * src[1]));
int2 dx2 = convert_int2(round(ratio * src[2]));
int2 dy2 = convert_int2(round(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;
}
////////////////////////////////////////////////////////////////////////
// Hessian
@ -182,22 +160,20 @@ F calcAxisAlignedDerivative(
//calculate targeted layer per-pixel determinant and trace with an integral image
__kernel void SURF_calcLayerDetAndTrace(
IMAGE_INT32 sumTex, // input integral image
__global float * det, // output Determinant
__PARAM_sumTex__, // input integral image
int img_rows, int img_cols,
int c_nOctaveLayers, int c_octave, int c_layer_rows,
__global float * det, // output determinant
int det_step, int det_offset,
__global float * trace, // output trace
int det_step, // the step of det in bytes
int trace_step, // the step of trace in bytes
int c_img_rows,
int c_img_cols,
int c_nOctaveLayers,
int c_octave,
int c_layer_rows,
int sumTex_step
)
int trace_step, int trace_offset)
{
det_step /= sizeof(*det);
trace_step /= sizeof(*trace);
sumTex_step/= sizeof(uint);
#ifndef HAVE_IMAGE2D
sum_step/= sizeof(uint);
#endif
// Determine the indices
const int gridDim_y = get_num_groups(1) / (c_nOctaveLayers + 2);
const int blockIdx_y = get_group_id(1) % gridDim_y;
@ -209,13 +185,13 @@ __kernel void SURF_calcLayerDetAndTrace(
const int size = calcSize(c_octave, layer);
const int samples_i = 1 + ((c_img_rows - size) >> c_octave);
const int samples_j = 1 + ((c_img_cols - size) >> c_octave);
const int samples_i = 1 + ((img_rows - size) >> c_octave);
const int samples_j = 1 + ((img_cols - size) >> c_octave);
// Ignore pixels where some of the kernel is outside the image
const int margin = (size >> 1) >> c_octave;
if (size <= c_img_rows && size <= c_img_cols && i < samples_i && j < samples_j)
if (size <= img_rows && size <= img_cols && i < samples_i && j < samples_j)
{
int x = j << c_octave;
int y = i << c_octave;
@ -239,14 +215,14 @@ __kernel void SURF_calcLayerDetAndTrace(
{
// Some of the pixels needed to compute the derivative are
// repeated, so we only don't duplicate the fetch here.
int t02 = read_sumTex( sumTex, sampler, (int2)(x, y + r2), c_img_rows, c_img_cols, sumTex_step );
int t07 = read_sumTex( sumTex, sampler, (int2)(x, y + r7), c_img_rows, c_img_cols, sumTex_step );
int t32 = read_sumTex( sumTex, sampler, (int2)(x + r3, y + r2), c_img_rows, c_img_cols, sumTex_step );
int t37 = read_sumTex( sumTex, sampler, (int2)(x + r3, y + r7), c_img_rows, c_img_cols, sumTex_step );
int t62 = read_sumTex( sumTex, sampler, (int2)(x + r6, y + r2), c_img_rows, c_img_cols, sumTex_step );
int t67 = read_sumTex( sumTex, sampler, (int2)(x + r6, y + r7), c_img_rows, c_img_cols, sumTex_step );
int t92 = read_sumTex( sumTex, sampler, (int2)(x + r9, y + r2), c_img_rows, c_img_cols, sumTex_step );
int t97 = read_sumTex( sumTex, sampler, (int2)(x + r9, y + r7), c_img_rows, c_img_cols, sumTex_step );
int t02 = read_sumTex( (int2)(x, y + r2));
int t07 = read_sumTex( (int2)(x, y + r7));
int t32 = read_sumTex( (int2)(x + r3, y + r2));
int t37 = read_sumTex( (int2)(x + r3, y + r7));
int t62 = read_sumTex( (int2)(x + r6, y + r2));
int t67 = read_sumTex( (int2)(x + r6, y + r7));
int t92 = read_sumTex( (int2)(x + r9, y + r2));
int t97 = read_sumTex( (int2)(x + r9, y + r7));
d = calcAxisAlignedDerivative(t02, t07, t32, t37, (r3) * (r7 - r2),
t62, t67, t92, t97, (r9 - r6) * (r7 - r2),
@ -259,14 +235,14 @@ __kernel void SURF_calcLayerDetAndTrace(
{
// Some of the pixels needed to compute the derivative are
// repeated, so we only don't duplicate the fetch here.
int t20 = read_sumTex( sumTex, sampler, (int2)(x + r2, y), c_img_rows, c_img_cols, sumTex_step );
int t23 = read_sumTex( sumTex, sampler, (int2)(x + r2, y + r3), c_img_rows, c_img_cols, sumTex_step );
int t70 = read_sumTex( sumTex, sampler, (int2)(x + r7, y), c_img_rows, c_img_cols, sumTex_step );
int t73 = read_sumTex( sumTex, sampler, (int2)(x + r7, y + r3), c_img_rows, c_img_cols, sumTex_step );
int t26 = read_sumTex( sumTex, sampler, (int2)(x + r2, y + r6), c_img_rows, c_img_cols, sumTex_step );
int t76 = read_sumTex( sumTex, sampler, (int2)(x + r7, y + r6), c_img_rows, c_img_cols, sumTex_step );
int t29 = read_sumTex( sumTex, sampler, (int2)(x + r2, y + r9), c_img_rows, c_img_cols, sumTex_step );
int t79 = read_sumTex( sumTex, sampler, (int2)(x + r7, y + r9), c_img_rows, c_img_cols, sumTex_step );
int t20 = read_sumTex( (int2)(x + r2, y) );
int t23 = read_sumTex( (int2)(x + r2, y + r3) );
int t70 = read_sumTex( (int2)(x + r7, y) );
int t73 = read_sumTex( (int2)(x + r7, y + r3) );
int t26 = read_sumTex( (int2)(x + r2, y + r6) );
int t76 = read_sumTex( (int2)(x + r7, y + r6) );
int t29 = read_sumTex( (int2)(x + r2, y + r9) );
int t79 = read_sumTex( (int2)(x + r7, y + r9) );
d = calcAxisAlignedDerivative(t20, t23, t70, t73, (r7 - r2) * (r3),
t26, t29, t76, t79, (r7 - r2) * (r9 - r6),
@ -280,31 +256,31 @@ __kernel void SURF_calcLayerDetAndTrace(
// There's no saving us here, we just have to get all of the pixels in
// separate fetches
F t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + r1, y + r1), c_img_rows, c_img_cols, sumTex_step );
t -= read_sumTex( sumTex, sampler, (int2)(x + r1, y + r4), c_img_rows, c_img_cols, sumTex_step );
t -= read_sumTex( sumTex, sampler, (int2)(x + r4, y + r1), c_img_rows, c_img_cols, sumTex_step );
t += read_sumTex( sumTex, sampler, (int2)(x + r4, y + r4), c_img_rows, c_img_cols, sumTex_step );
t += read_sumTex( (int2)(x + r1, y + r1) );
t -= read_sumTex( (int2)(x + r1, y + r4) );
t -= read_sumTex( (int2)(x + r4, y + r1) );
t += read_sumTex( (int2)(x + r4, y + r4) );
d += t / ((r4 - r1) * (r4 - r1));
t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + r5, y + r1), c_img_rows, c_img_cols, sumTex_step );
t -= read_sumTex( sumTex, sampler, (int2)(x + r5, y + r4), c_img_rows, c_img_cols, sumTex_step );
t -= read_sumTex( sumTex, sampler, (int2)(x + r8, y + r1), c_img_rows, c_img_cols, sumTex_step );
t += read_sumTex( sumTex, sampler, (int2)(x + r8, y + r4), c_img_rows, c_img_cols, sumTex_step );
t += read_sumTex( (int2)(x + r5, y + r1) );
t -= read_sumTex( (int2)(x + r5, y + r4) );
t -= read_sumTex( (int2)(x + r8, y + r1) );
t += read_sumTex( (int2)(x + r8, y + r4) );
d -= t / ((r8 - r5) * (r4 - r1));
t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + r1, y + r5), c_img_rows, c_img_cols, sumTex_step );
t -= read_sumTex( sumTex, sampler, (int2)(x + r1, y + r8), c_img_rows, c_img_cols, sumTex_step );
t -= read_sumTex( sumTex, sampler, (int2)(x + r4, y + r5), c_img_rows, c_img_cols, sumTex_step );
t += read_sumTex( sumTex, sampler, (int2)(x + r4, y + r8), c_img_rows, c_img_cols, sumTex_step );
t += read_sumTex( (int2)(x + r1, y + r5) );
t -= read_sumTex( (int2)(x + r1, y + r8) );
t -= read_sumTex( (int2)(x + r4, y + r5) );
t += read_sumTex( (int2)(x + r4, y + r8) );
d -= t / ((r4 - r1) * (r8 - r5));
t = 0;
t += read_sumTex( sumTex, sampler, (int2)(x + r5, y + r5), c_img_rows, c_img_cols, sumTex_step );
t -= read_sumTex( sumTex, sampler, (int2)(x + r5, y + r8), c_img_rows, c_img_cols, sumTex_step );
t -= read_sumTex( sumTex, sampler, (int2)(x + r8, y + r5), c_img_rows, c_img_cols, sumTex_step );
t += read_sumTex( sumTex, sampler, (int2)(x + r8, y + r8), c_img_rows, c_img_cols, sumTex_step );
t += read_sumTex( (int2)(x + r5, y + r5) );
t -= read_sumTex( (int2)(x + r5, y + r8) );
t -= read_sumTex( (int2)(x + r8, y + r5) );
t += read_sumTex( (int2)(x + r8, y + r8) );
d += t / ((r8 - r5) * (r8 - r5));
}
const float dxy = (float)d;
@ -317,171 +293,17 @@ __kernel void SURF_calcLayerDetAndTrace(
////////////////////////////////////////////////////////////////////////
// NONMAX
__constant float c_DM[5] = {0, 0, 9, 9, 1};
bool within_check(IMAGE_INT32 maskSumTex, int sum_i, int sum_j, int size, int rows, int cols, int step)
{
float ratio = (float)size / 9.0f;
float d = 0;
int dx1 = round(ratio * c_DM[0]);
int dy1 = round(ratio * c_DM[1]);
int dx2 = round(ratio * c_DM[2]);
int dy2 = round(ratio * c_DM[3]);
float t = 0;
t += read_sumTex(maskSumTex, sampler, (int2)(sum_j + dx1, sum_i + dy1), rows, cols, step);
t -= read_sumTex(maskSumTex, sampler, (int2)(sum_j + dx1, sum_i + dy2), rows, cols, step);
t -= read_sumTex(maskSumTex, sampler, (int2)(sum_j + dx2, sum_i + dy1), rows, cols, step);
t += read_sumTex(maskSumTex, sampler, (int2)(sum_j + dx2, sum_i + dy2), rows, cols, step);
d += t * c_DM[4] / ((dx2 - dx1) * (dy2 - dy1));
return (d >= 0.5f);
}
// Non-maximal suppression to further filtering the candidates from previous step
__kernel
void SURF_findMaximaInLayerWithMask(
__global const float * det,
__global const float * trace,
__global int4 * maxPosBuffer,
volatile __global int* maxCounter,
int counter_offset,
int det_step, // the step of det in bytes
int trace_step, // the step of trace in bytes
int c_img_rows,
int c_img_cols,
int c_nOctaveLayers,
int c_octave,
int c_layer_rows,
int c_layer_cols,
int c_max_candidates,
float c_hessianThreshold,
IMAGE_INT32 maskSumTex,
int mask_step
)
{
volatile __local float N9[768]; // threads.x * threads.y * 3
det_step /= sizeof(*det);
trace_step /= sizeof(*trace);
maxCounter += counter_offset;
mask_step /= sizeof(uint);
// Determine the indices
const int gridDim_y = get_num_groups(1) / c_nOctaveLayers;
const int blockIdx_y = get_group_id(1) % gridDim_y;
const int blockIdx_z = get_group_id(1) / gridDim_y;
const int layer = blockIdx_z + 1;
const int size = calcSize(c_octave, layer);
// Ignore pixels without a 3x3x3 neighbourhood in the layer above
const int margin = ((calcSize(c_octave, layer + 1) >> 1) >> c_octave) + 1;
const int j = get_local_id(0) + get_group_id(0) * (get_local_size(0) - 2) + margin - 1;
const int i = get_local_id(1) + blockIdx_y * (get_local_size(1) - 2) + margin - 1;
// Is this thread within the hessian buffer?
const int zoff = get_local_size(0) * get_local_size(1);
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
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
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
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
)
{
float val0 = N9[localLin];
if (val0 > c_hessianThreshold)
{
// Coordinates for the start of the wavelet in the sum image. There
// is some integer division involved, so don't try to simplify this
// (cancel out sampleStep) without checking the result is the same
const int sum_i = (i - ((size >> 1) >> c_octave)) << c_octave;
const int sum_j = (j - ((size >> 1) >> c_octave)) << c_octave;
if (within_check(maskSumTex, sum_i, sum_j, size, c_img_rows, c_img_cols, mask_step))
{
// 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]
;
if(condmax)
{
int ind = atomic_inc(maxCounter);
if (ind < c_max_candidates)
{
const int laplacian = (int) copysign(1.0f, trace[trace_step* (layer * c_layer_rows + i) + j]);
maxPosBuffer[ind] = (int4)(j, i, layer, laplacian);
}
}
}
}
}
}
__kernel
void SURF_findMaximaInLayer(
__global float * det,
int det_step, int det_offset,
__global float * trace,
int trace_step, int trace_offset,
__global int4 * maxPosBuffer,
volatile __global int* maxCounter,
int counter_offset,
int det_step, // the step of det in bytes
int trace_step, // the step of trace in bytes
int c_img_rows,
int c_img_cols,
int img_rows,
int img_cols,
int c_nOctaveLayers,
int c_octave,
int c_layer_rows,
@ -515,8 +337,8 @@ void SURF_findMaximaInLayer(
const int zoff = get_local_size(0) * get_local_size(1);
const int localLin = get_local_id(0) + get_local_id(1) * get_local_size(0) + zoff;
int l_x = min(max(j, 0), c_img_cols - 1);
int l_y = c_layer_rows * layer + min(max(i, 0), c_img_rows - 1);
int l_x = min(max(j, 0), img_cols - 1);
int l_y = c_layer_rows * layer + min(max(i, 0), img_rows - 1);
N9[localLin - zoff] =
det[det_step * (l_y - c_layer_rows) + l_x];
@ -596,7 +418,7 @@ inline bool solve3x3_float(const float4 *A, const float *b, float *x)
if (det != 0)
{
F invdet = 1.0 / det;
F invdet = 1.0f / det;
x[0] = invdet *
(b[0] * (A[1].y * A[2].z - A[1].z * A[2].y) -
@ -632,13 +454,13 @@ inline bool solve3x3_float(const float4 *A, const float *b, float *x)
__kernel
void SURF_interpolateKeypoint(
__global const float * det,
int det_step, int det_offset,
__global const int4 * maxPosBuffer,
__global float * keypoints,
volatile __global int * featureCounter,
int det_step,
int keypoints_step,
int c_img_rows,
int c_img_cols,
int keypoints_step, int keypoints_offset,
volatile __global int* featureCounter,
int img_rows,
int img_cols,
int c_octave,
int c_layer_rows,
int c_max_features
@ -730,7 +552,7 @@ void SURF_interpolateKeypoint(
const int grad_wav_size = 2 * round(2.0f * s);
// check when grad_wav_size is too big
if ((c_img_rows + 1) >= grad_wav_size && (c_img_cols + 1) >= grad_wav_size)
if ((img_rows + 1) >= grad_wav_size && (img_cols + 1) >= grad_wav_size)
{
// Get a new feature index.
int ind = atomic_inc(featureCounter);
@ -836,22 +658,18 @@ void reduce_32_sum(volatile __local float * data, volatile float* partial_reduc
__kernel
void SURF_calcOrientation(
IMAGE_INT32 sumTex,
__global float * keypoints,
int keypoints_step,
int c_img_rows,
int c_img_cols,
int sum_step
)
__PARAM_sumTex__, int img_rows, int img_cols,
__global float * keypoints, int keypoints_step, int keypoints_offset )
{
keypoints_step /= sizeof(*keypoints);
#ifndef HAVE_IMAGE2D
sum_step /= sizeof(uint);
#endif
__global float* featureX = keypoints + X_ROW * keypoints_step;
__global float* featureY = keypoints + Y_ROW * keypoints_step;
__global float* featureSize = keypoints + SIZE_ROW * keypoints_step;
__global float* featureDir = keypoints + ANGLE_ROW * keypoints_step;
__local float s_X[ORI_SAMPLES];
__local float s_Y[ORI_SAMPLES];
__local float s_angle[ORI_SAMPLES];
@ -866,7 +684,6 @@ void SURF_calcOrientation(
and building the keypoint descriptor are defined relative to 's' */
const float s = featureSize[get_group_id(0)] * 1.2f / 9.0f;
/* To find the dominant orientation, the gradients in x and y are
sampled in a circle of radius 6s using wavelets of size 4s.
We ensure the gradient wavelet size is even to ensure the
@ -874,7 +691,7 @@ void SURF_calcOrientation(
const int grad_wav_size = 2 * round(2.0f * s);
// check when grad_wav_size is too big
if ((c_img_rows + 1) < grad_wav_size || (c_img_cols + 1) < grad_wav_size)
if ((img_rows + 1) < grad_wav_size || (img_cols + 1) < grad_wav_size)
return;
// Calc X, Y, angle and store it to shared memory
@ -886,8 +703,8 @@ void SURF_calcOrientation(
float ratio = (float)grad_wav_size / 4;
int r2 = round(ratio * 2.0);
int r4 = round(ratio * 4.0);
int r2 = round(ratio * 2.0f);
int r4 = round(ratio * 4.0f);
for (int i = tid; i < ORI_SAMPLES; i += ORI_LOCAL_SIZE )
{
float X = 0.0f, Y = 0.0f, angle = 0.0f;
@ -895,21 +712,20 @@ void SURF_calcOrientation(
const int x = round(featureX[get_group_id(0)] + c_aptX[i] * s - margin);
const int y = round(featureY[get_group_id(0)] + c_aptY[i] * s - margin);
if (y >= 0 && y < (c_img_rows + 1) - grad_wav_size &&
x >= 0 && x < (c_img_cols + 1) - grad_wav_size)
if (y >= 0 && y < (img_rows + 1) - grad_wav_size &&
x >= 0 && x < (img_cols + 1) - grad_wav_size)
{
float apt = c_aptW[i];
// Compute the haar sum without fetching duplicate pixels.
float t00 = read_sumTex( sumTex, sampler, (int2)(x, y), c_img_rows, c_img_cols, sum_step);
float t02 = read_sumTex( sumTex, sampler, (int2)(x, y + r2), c_img_rows, c_img_cols, sum_step);
float t04 = read_sumTex( sumTex, sampler, (int2)(x, y + r4), c_img_rows, c_img_cols, sum_step);
float t20 = read_sumTex( sumTex, sampler, (int2)(x + r2, y), c_img_rows, c_img_cols, sum_step);
float t24 = read_sumTex( sumTex, sampler, (int2)(x + r2, y + r4), c_img_rows, c_img_cols, sum_step);
float t40 = read_sumTex( sumTex, sampler, (int2)(x + r4, y), c_img_rows, c_img_cols, sum_step);
float t42 = read_sumTex( sumTex, sampler, (int2)(x + r4, y + r2), c_img_rows, c_img_cols, sum_step);
float t44 = read_sumTex( sumTex, sampler, (int2)(x + r4, y + r4), c_img_rows, c_img_cols, sum_step);
float t00 = read_sumTex( (int2)(x, y));
float t02 = read_sumTex( (int2)(x, y + r2));
float t04 = read_sumTex( (int2)(x, y + r4));
float t20 = read_sumTex( (int2)(x + r2, y));
float t24 = read_sumTex( (int2)(x + r2, y + r4));
float t40 = read_sumTex( (int2)(x + r4, y));
float t42 = read_sumTex( (int2)(x + r4, y + r2));
float t44 = read_sumTex( (int2)(x + r4, y + r4));
F t = t00 - t04 - t20 + t24;
X -= t / ((r2) * (r4));
@ -1001,7 +817,7 @@ void SURF_calcOrientation(
}
__kernel
void SURF_setUpright(
void SURF_setUpRight(
__global float * keypoints,
int keypoints_step, int keypoints_offset,
int rows, int cols )
@ -1050,22 +866,14 @@ __constant float c_DW[PATCH_SZ * PATCH_SZ] =
};
// utility for linear filter
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;
return read_imgTex(src, sampler, (float2)(pixel_x, pixel_y), rows, cols, elemPerRow);
}
#define readerGet(centerX, centerY, win_offset, cos_dir, sin_dir, i, j) \
read_imgTex((float2)(centerX + (win_offset + j) * cos_dir + (win_offset + i) * sin_dir, \
centerY - (win_offset + j) * sin_dir + (win_offset + i) * cos_dir))
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
)
__PARAM_imgTex__, int img_rows, int img_cols,
float centerX, float centerY, float win_offset,
float cos_dir, float sin_dir, float y, float x )
{
x -= 0.5f;
y -= 0.5f;
@ -1077,34 +885,31 @@ inline float linearFilter(
const int x2 = x1 + 1;
const int y2 = y1 + 1;
uchar src_reg = readerGet(src, centerX, centerY, win_offset, cos_dir, sin_dir, y1, x1, rows, cols, elemPerRow);
uchar src_reg = readerGet(centerX, centerY, win_offset, cos_dir, sin_dir, y1, x1);
out = out + src_reg * ((x2 - x) * (y2 - y));
src_reg = readerGet(src, centerX, centerY, win_offset, cos_dir, sin_dir, y1, x2, rows, cols, elemPerRow);
src_reg = readerGet(centerX, centerY, win_offset, cos_dir, sin_dir, y1, x2);
out = out + src_reg * ((x - x1) * (y2 - y));
src_reg = readerGet(src, centerX, centerY, win_offset, cos_dir, sin_dir, y2, x1, rows, cols, elemPerRow);
src_reg = readerGet(centerX, centerY, win_offset, cos_dir, sin_dir, y2, x1);
out = out + src_reg * ((x2 - x) * (y - y1));
src_reg = readerGet(src, centerX, centerY, win_offset, cos_dir, sin_dir, y2, x2, rows, cols, elemPerRow);
src_reg = readerGet(centerX, centerY, win_offset, cos_dir, sin_dir, y2, x2);
out = out + src_reg * ((x - x1) * (y - y1));
return out;
}
void calc_dx_dy(
IMAGE_INT8 imgTex,
__PARAM_imgTex__,
int img_rows, int img_cols,
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,
__global const float* featureDir,
int rows,
int cols,
int elemPerRow
)
__global const float* featureDir )
{
const float centerX = featureX[get_group_id(0)];
const float centerY = featureY[get_group_id(0)];
@ -1141,7 +946,9 @@ 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) * 6 + 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(__PASS_imgTex__, img_rows, img_cols, centerX, centerY,
win_offset, cos_dir, sin_dir, icoo, jcoo);
barrier(CLK_LOCAL_MEM_FENCE);
@ -1232,9 +1039,8 @@ void reduce_sum25(
__kernel
void SURF_computeDescriptors64(
IMAGE_INT8 imgTex,
int img_step, int img_offset,
int rows, int cols,
__PARAM_imgTex__,
int img_rows, int img_cols,
__global const float* keypoints,
int keypoints_step, int keypoints_offset,
__global float * descriptors,
@ -1254,7 +1060,7 @@ void SURF_computeDescriptors64(
volatile __local float sdyabs[25];
volatile __local float s_PATCH[6*6];
calc_dx_dy(imgTex, sdx, sdy, s_PATCH, featureX, featureY, featureSize, featureDir, rows, cols, img_step);
calc_dx_dy(__PASS_imgTex__, img_rows, img_cols, sdx, sdy, s_PATCH, featureX, featureY, featureSize, featureDir);
barrier(CLK_LOCAL_MEM_FENCE);
const int tid = get_local_id(1) * get_local_size(0) + get_local_id(0);
@ -1286,9 +1092,8 @@ void SURF_computeDescriptors64(
__kernel
void SURF_computeDescriptors128(
IMAGE_INT8 imgTex,
int img_step, int img_offset,
int rows, int cols,
__PARAM_imgTex__,
int img_rows, int img_cols,
__global const float* keypoints,
int keypoints_step, int keypoints_offset,
__global float* descriptors,
@ -1313,7 +1118,7 @@ void SURF_computeDescriptors128(
volatile __local float sdabs2[25];
volatile __local float s_PATCH[6*6];
calc_dx_dy(imgTex, sdx, sdy, s_PATCH, featureX, featureY, featureSize, featureDir, rows, cols, img_step);
calc_dx_dy(__PASS_imgTex__, img_rows, img_cols, sdx, sdy, s_PATCH, featureX, featureY, featureSize, featureDir);
barrier(CLK_LOCAL_MEM_FENCE);
const int tid = get_local_id(1) * get_local_size(0) + get_local_id(0);
@ -1486,7 +1291,7 @@ void reduce_sum64(volatile __local float* smem, int tid)
}
__kernel
void SURF_normalizeDescriptors128(__global float * descriptors, int descriptors_step)
void SURF_normalizeDescriptors128(__global float * descriptors, int descriptors_step, int descriptors_offset)
{
descriptors_step /= sizeof(*descriptors);
// no need for thread ID
@ -1514,7 +1319,7 @@ void SURF_normalizeDescriptors128(__global float * descriptors, int descriptors_
}
__kernel
void SURF_normalizeDescriptors64(__global float * descriptors, int descriptors_step)
void SURF_normalizeDescriptors64(__global float * descriptors, int descriptors_step, int descriptors_offset)
{
descriptors_step /= sizeof(*descriptors);
// no need for thread ID

View File

@ -902,7 +902,7 @@ void SURF::operator()(InputArray _img, InputArray _mask,
bool doDescriptors = _descriptors.needed();
CV_Assert(!_img.empty() && CV_MAT_DEPTH(imgtype) == CV_8U && (imgcn == 1 || imgcn == 3 || imgcn == 4));
CV_Assert(_descriptors.needed() && !useProvidedKeypoints);
CV_Assert(_descriptors.needed() || !useProvidedKeypoints);
if( ocl::useOpenCL() )
{

View File

@ -54,14 +54,11 @@ protected:
bool setImage(InputArray img, InputArray mask);
// kernel callers declarations
bool calcLayerDetAndTrace(UMat &det, UMat &trace, int octave, int layer_rows);
bool calcLayerDetAndTrace(int octave, int layer_rows);
bool findMaximaInLayer(const UMat &det, const UMat &trace, UMat &maxPosBuffer,
UMat &maxCounter, int counterOffset,
int octave, int layer_rows, int layer_cols);
bool findMaximaInLayer(int counterOffset, int octave, int layer_rows, int layer_cols);
bool interpolateKeypoint(const UMat &det, const UMat &maxPosBuffer, int maxCounter,
UMat &keypoints, UMat &counters, int octave, int layer_rows, int maxFeatures);
bool interpolateKeypoint(int maxCounter, UMat &keypoints, int octave, int layer_rows, int maxFeatures);
bool calcOrientation(UMat &keypoints);
@ -75,7 +72,7 @@ protected:
int refcount;
//! max keypoints = min(keypointsRatio * img.size().area(), 65535)
UMat sum, mask1, maskSum, intBuffer;
UMat sum, intBuffer;
UMat det, trace;
UMat maxPosBuffer;
@ -87,12 +84,11 @@ protected:
UMat img, counters;
// texture buffers
ocl::Image2D imgTex, sumTex, maskSumTex;
ocl::Image2D imgTex, sumTex;
bool haveImageSupport;
String kerOpts;
int status;
ocl::Kernel kerCalcDetTrace, kerFindMaxima, kerFindMaximaMask, kerInterp;
ocl::Kernel kerUpRight, kerOri, kerCalcDesc64, kerCalcDesc128, kerNormDesc64, kerNormDesc128;
};
/*

View File

@ -54,20 +54,6 @@ namespace cv
enum { ORI_SEARCH_INC=5, ORI_LOCAL_SIZE=(360 / ORI_SEARCH_INC) };
/*static void openCLExecuteKernelSURF(Context2 *clCxt, const ProgramEntry* source, String kernelName, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args, int channels, int depth)
{
std::stringstream optsStr;
optsStr << "-D ORI_LOCAL_SIZE=" << ORI_LOCAL_SIZE << " ";
optsStr << "-D ORI_SEARCH_INC=" << ORI_SEARCH_INC << " ";
cl_kernel kernel;
kernel = openCLGetKernelFromSource(clCxt, source, kernelName, optsStr.str().c_str());
size_t wave_size = queryWaveFrontSize(kernel);
CV_Assert(clReleaseKernel(kernel) == CL_SUCCESS);
optsStr << "-D WAVE_SIZE=" << wave_size;
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, channels, depth, optsStr.str().c_str());
}*/
static inline int calcSize(int octave, int layer)
{
/* Wavelet size at first layer of first octave. */
@ -100,22 +86,11 @@ bool SURF_OCL::init(const SURF* p)
if(ocl::haveOpenCL())
{
const ocl::Device& dev = ocl::Device::getDefault();
if( dev.type() == ocl::Device::TYPE_CPU )
if( dev.type() == ocl::Device::TYPE_CPU || dev.doubleFPConfig() == 0 )
return false;
haveImageSupport = dev.imageSupport();
String opts = haveImageSupport ? "-D DISABLE_IMAGE2D" : "";
if( kerCalcDetTrace.create("SURF_calcLayerDetAndTrace", ocl::nonfree::surf_oclsrc, opts) &&
kerFindMaxima.create("SURF_findMaximaInLayer", ocl::nonfree::surf_oclsrc, opts) &&
kerFindMaximaMask.create("SURF_findMaximaInLayerWithMask", ocl::nonfree::surf_oclsrc, opts) &&
kerInterp.create("SURF_interpolateKeypoint", ocl::nonfree::surf_oclsrc, opts) &&
kerUpRight.create("SURF_setUpRight", ocl::nonfree::surf_oclsrc, opts) &&
kerOri.create("SURF_calcOrientation", ocl::nonfree::surf_oclsrc, opts) &&
kerCalcDesc64.create("SURF_computeDescriptors64", ocl::nonfree::surf_oclsrc, opts) &&
kerCalcDesc128.create("SURF_computeDescriptors128", ocl::nonfree::surf_oclsrc, opts) &&
kerNormDesc64.create("SURF_normalizeDescriptors64", ocl::nonfree::surf_oclsrc, opts) &&
kerNormDesc128.create("SURF_normalizeDescriptors128", ocl::nonfree::surf_oclsrc, opts))
status = 1;
haveImageSupport = false;//dev.imageSupport();
kerOpts = haveImageSupport ? "-D HAVE_IMAGE2D -D DOUBLE_SUPPORT" : "";
status = 1;
}
}
return status > 0;
@ -126,8 +101,10 @@ bool SURF_OCL::setImage(InputArray _img, InputArray _mask)
{
if( status <= 0 )
return false;
CV_Assert(!_img.empty() && _img.type() == CV_8UC1);
CV_Assert(_mask.empty() || (_mask.size() == _img.size() && _mask.type() == CV_8UC1));
if( !_mask.empty())
return false;
int imgtype = _img.type();
CV_Assert(!_img.empty());
CV_Assert(params && params->nOctaves > 0 && params->nOctaveLayers > 0);
int min_size = calcSize(params->nOctaves - 1, 0);
@ -151,10 +128,12 @@ bool SURF_OCL::setImage(InputArray _img, InputArray _mask)
counters.setTo(Scalar::all(0));
img.release();
if(_img.isUMat())
if(_img.isUMat() && imgtype == CV_8UC1)
img = _img.getUMat();
else
else if( imgtype == CV_8UC1 )
_img.copyTo(img);
else
cvtColor(_img, img, COLOR_BGR2GRAY);
integral(img, sum);
@ -164,12 +143,6 @@ bool SURF_OCL::setImage(InputArray _img, InputArray _mask)
sumTex = ocl::Image2D(sum);
}
maskSumTex = ocl::Image2D();
if(!_mask.empty())
{
CV_Error(Error::StsBadFunc, "Masked SURF detector is not implemented yet");
}
return true;
}
@ -191,11 +164,10 @@ bool SURF_OCL::detectKeypoints(UMat &keypoints)
const int layer_rows = img_rows >> octave;
const int layer_cols = img_cols >> octave;
if(!calcLayerDetAndTrace(det, trace, octave, layer_rows))
if(!calcLayerDetAndTrace(octave, layer_rows))
return false;
if(!findMaximaInLayer(det, trace, maxPosBuffer, counters, 1 + octave, octave,
layer_rows, layer_cols))
if(!findMaximaInLayer(1 + octave, octave, layer_rows, layer_cols))
return false;
cpuCounters = counters.getMat(ACCESS_READ);
@ -205,8 +177,7 @@ bool SURF_OCL::detectKeypoints(UMat &keypoints)
if (maxCounter > 0)
{
if(!interpolateKeypoint(det, maxPosBuffer, maxCounter, keypoints,
counters, octave, layer_rows, maxFeatures))
if(!interpolateKeypoint(maxCounter, keypoints, octave, layer_rows, maxFeatures))
return false;
}
}
@ -216,7 +187,7 @@ bool SURF_OCL::detectKeypoints(UMat &keypoints)
featureCounter = std::min(featureCounter, maxFeatures);
cpuCounters.release();
keypoints = UMat(keypoints, Rect(0, 0, featureCounter, 1));
keypoints = UMat(keypoints, Rect(0, 0, featureCounter, keypoints.rows));
if (params->upright)
return setUpRight(keypoints);
@ -232,7 +203,8 @@ bool SURF_OCL::setUpRight(UMat &keypoints)
return true;
size_t globalThreads[3] = {nFeatures, 1};
return kerUpRight.args(ocl::KernelArg::ReadWrite(keypoints)).run(2, globalThreads, 0, false);
ocl::Kernel kerUpRight("SURF_setUpRight", ocl::nonfree::surf_oclsrc, kerOpts);
return kerUpRight.args(ocl::KernelArg::ReadWrite(keypoints)).run(2, globalThreads, 0, true);
}
bool SURF_OCL::computeDescriptors(const UMat &keypoints, OutputArray _descriptors)
@ -255,14 +227,14 @@ bool SURF_OCL::computeDescriptors(const UMat &keypoints, OutputArray _descriptor
if( descriptorSize == 64 )
{
kerCalcDesc = kerCalcDesc64;
kerNormDesc = kerNormDesc64;
kerCalcDesc.create("SURF_computeDescriptors64", ocl::nonfree::surf_oclsrc, kerOpts);
kerNormDesc.create("SURF_normalizeDescriptors64", ocl::nonfree::surf_oclsrc, kerOpts);
}
else
{
CV_Assert(descriptorSize == 128);
kerCalcDesc = kerCalcDesc128;
kerNormDesc = kerNormDesc128;
kerCalcDesc.create("SURF_computeDescriptors128", ocl::nonfree::surf_oclsrc, kerOpts);
kerNormDesc.create("SURF_normalizeDescriptors128", ocl::nonfree::surf_oclsrc, kerOpts);
}
size_t localThreads[] = {6, 6};
@ -271,17 +243,19 @@ bool SURF_OCL::computeDescriptors(const UMat &keypoints, OutputArray _descriptor
if(haveImageSupport)
{
kerCalcDesc.args(imgTex,
img_rows, img_cols,
ocl::KernelArg::ReadOnlyNoSize(keypoints),
ocl::KernelArg::WriteOnlyNoSize(descriptors));
}
else
{
kerCalcDesc.args(ocl::KernelArg::ReadOnly(img),
kerCalcDesc.args(ocl::KernelArg::ReadOnlyNoSize(img),
img_rows, img_cols,
ocl::KernelArg::ReadOnlyNoSize(keypoints),
ocl::KernelArg::WriteOnlyNoSize(descriptors));
}
if(!kerCalcDesc.run(2, globalThreads, localThreads, false))
if(!kerCalcDesc.run(2, globalThreads, localThreads, true))
return false;
size_t localThreads_n[] = {descriptorSize, 1};
@ -290,7 +264,7 @@ bool SURF_OCL::computeDescriptors(const UMat &keypoints, OutputArray _descriptor
globalThreads[0] = nFeatures * localThreads[0];
globalThreads[1] = localThreads[1];
bool ok = kerNormDesc.args(ocl::KernelArg::ReadWriteNoSize(descriptors)).
run(2, globalThreads_n, localThreads_n, false);
run(2, globalThreads_n, localThreads_n, true);
if(ok && !_descriptors.isUMat())
descriptors.copyTo(_descriptors);
return ok;
@ -364,19 +338,19 @@ void SURF_OCL::downloadKeypoints(const UMat &keypointsGPU, std::vector<KeyPoint>
}
}
bool SURF_OCL::detect(InputArray img, InputArray mask, UMat& keypoints)
bool SURF_OCL::detect(InputArray _img, InputArray _mask, UMat& keypoints)
{
if( !setImage(img, mask) )
if( !setImage(_img, _mask) )
return false;
return detectKeypoints(keypoints);
}
bool SURF_OCL::detectAndCompute(InputArray img, InputArray mask, UMat& keypoints,
bool SURF_OCL::detectAndCompute(InputArray _img, InputArray _mask, UMat& keypoints,
OutputArray _descriptors, bool useProvidedKeypoints )
{
if( !setImage(img, mask) )
if( !setImage(_img, _mask) )
return false;
if( !useProvidedKeypoints && !detectKeypoints(keypoints) )
@ -389,22 +363,20 @@ inline int divUp(int a, int b) { return (a + b-1)/b; }
////////////////////////////
// kernel caller definitions
bool SURF_OCL::calcLayerDetAndTrace(UMat &det, UMat &trace, int octave, int c_layer_rows)
bool SURF_OCL::calcLayerDetAndTrace(int octave, int c_layer_rows)
{
int nOctaveLayers = params->nOctaveLayers;
const int min_size = calcSize(octave, 0);
const int max_samples_i = 1 + ((img_rows - min_size) >> octave);
const int max_samples_j = 1 + ((img_cols - min_size) >> octave);
String kernelName = "SURF_calcLayerDetAndTrace";
std::vector< std::pair<size_t, const void *> > args;
size_t localThreads[3] = {16, 16};
size_t globalThreads[3] =
size_t localThreads[] = {16, 16};
size_t globalThreads[] =
{
divUp(max_samples_j, localThreads[0]) *localThreads[0],
divUp(max_samples_i, localThreads[1]) *localThreads[1] *(nOctaveLayers + 2)
};
ocl::Kernel kerCalcDetTrace("SURF_calcLayerDetAndTrace", ocl::nonfree::surf_oclsrc, kerOpts);
if(haveImageSupport)
{
kerCalcDetTrace.args(sumTex,
@ -421,56 +393,15 @@ bool SURF_OCL::calcLayerDetAndTrace(UMat &det, UMat &trace, int octave, int c_la
ocl::KernelArg::WriteOnlyNoSize(det),
ocl::KernelArg::WriteOnlyNoSize(trace));
}
return kerCalcDetTrace.run(2, globalThreads, localThreads, false);
return kerCalcDetTrace.run(2, globalThreads, localThreads, true);
}
bool SURF_OCL::findMaximaInLayer(const UMat &det, const UMat &trace,
UMat &maxPosBuffer, UMat &maxCounter,
int counterOffset, int octave,
bool SURF_OCL::findMaximaInLayer(int counterOffset, int octave,
int layer_rows, int layer_cols)
{
const int min_margin = ((calcSize(octave, 2) >> 1) >> octave) + 1;
bool haveMask = !maskSum.empty() || (maskSumTex.ptr() != 0);
int nOctaveLayers = params->nOctaveLayers;
ocl::Kernel ker;
if( haveMask )
{
if( haveImageSupport )
ker = kerFindMaximaMask.args(maskSumTex,
ocl::KernelArg::ReadOnlyNoSize(det),
ocl::KernelArg::ReadOnlyNoSize(trace),
ocl::KernelArg::PtrReadWrite(maxPosBuffer),
ocl::KernelArg::PtrReadWrite(maxCounter),
counterOffset, img_rows, img_cols,
octave, nOctaveLayers,
layer_rows, layer_cols,
maxCandidates,
(float)params->hessianThreshold);
else
ker = kerFindMaximaMask.args(ocl::KernelArg::ReadOnlyNoSize(maskSum),
ocl::KernelArg::ReadOnlyNoSize(det),
ocl::KernelArg::ReadOnlyNoSize(trace),
ocl::KernelArg::PtrReadWrite(maxPosBuffer),
ocl::KernelArg::PtrReadWrite(maxCounter),
counterOffset, img_rows, img_cols,
octave, nOctaveLayers,
layer_rows, layer_cols,
maxCandidates,
(float)params->hessianThreshold);
}
else
{
ker = kerFindMaxima.args(ocl::KernelArg::ReadOnlyNoSize(det),
ocl::KernelArg::ReadOnlyNoSize(trace),
ocl::KernelArg::PtrReadWrite(maxPosBuffer),
ocl::KernelArg::PtrReadWrite(maxCounter),
counterOffset, img_rows, img_cols,
octave, nOctaveLayers,
layer_rows, layer_cols,
maxCandidates,
(float)params->hessianThreshold);
}
size_t localThreads[3] = {16, 16};
size_t globalThreads[3] =
{
@ -478,21 +409,31 @@ bool SURF_OCL::findMaximaInLayer(const UMat &det, const UMat &trace,
divUp(layer_rows - 2 * min_margin, localThreads[1] - 2) *nOctaveLayers *localThreads[1]
};
return ker.run(2, globalThreads, localThreads, false);
ocl::Kernel kerFindMaxima("SURF_findMaximaInLayer", ocl::nonfree::surf_oclsrc, kerOpts);
return kerFindMaxima.args(ocl::KernelArg::ReadOnlyNoSize(det),
ocl::KernelArg::ReadOnlyNoSize(trace),
ocl::KernelArg::PtrReadWrite(maxPosBuffer),
ocl::KernelArg::PtrReadWrite(counters),
counterOffset, img_rows, img_cols,
octave, nOctaveLayers,
layer_rows, layer_cols,
maxCandidates,
(float)params->hessianThreshold).run(2, globalThreads, localThreads, true);
}
bool SURF_OCL::interpolateKeypoint(const UMat &det, const UMat &maxPosBuffer, int maxCounter,
UMat &keypoints, UMat &counters_, int octave, int layer_rows, int max_features)
bool SURF_OCL::interpolateKeypoint(int maxCounter, UMat &keypoints, int octave, int layer_rows, int max_features)
{
size_t localThreads[3] = {3, 3, 3};
size_t globalThreads[3] = {maxCounter*localThreads[0], localThreads[1], 3};
ocl::Kernel kerInterp("SURF_interpolateKeypoint", ocl::nonfree::surf_oclsrc, kerOpts);
return kerInterp.args(ocl::KernelArg::ReadOnlyNoSize(det),
ocl::KernelArg::PtrReadOnly(maxPosBuffer),
ocl::KernelArg::ReadWriteNoSize(keypoints),
ocl::KernelArg::PtrReadWrite(counters_),
ocl::KernelArg::PtrReadWrite(counters),
img_rows, img_cols, octave, layer_rows, max_features).
run(3, globalThreads, localThreads, false);
run(3, globalThreads, localThreads, true);
}
bool SURF_OCL::calcOrientation(UMat &keypoints)
@ -500,18 +441,19 @@ bool SURF_OCL::calcOrientation(UMat &keypoints)
int nFeatures = keypoints.cols;
if( nFeatures == 0 )
return true;
ocl::Kernel kerOri("SURF_calcOrientation", ocl::nonfree::surf_oclsrc, kerOpts);
if( haveImageSupport )
kerOri.args(sumTex,
ocl::KernelArg::ReadWriteNoSize(keypoints),
img_rows, img_cols);
kerOri.args(sumTex, img_rows, img_cols,
ocl::KernelArg::ReadWriteNoSize(keypoints));
else
kerOri.args(ocl::KernelArg::ReadOnlyNoSize(sum),
ocl::KernelArg::ReadWriteNoSize(keypoints),
img_rows, img_cols);
img_rows, img_cols,
ocl::KernelArg::ReadWriteNoSize(keypoints));
size_t localThreads[3] = {ORI_LOCAL_SIZE, 1};
size_t globalThreads[3] = {nFeatures * localThreads[0], 1};
return kerOri.run(2, globalThreads, localThreads, false);
return kerOri.run(2, globalThreads, localThreads, true);
}
}