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foxeye / opencv-libs deb
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Version:
3.4.8 ▾
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ÿÿÿHÄHA_A^A]A\[]ÃHìHÄÃ I0temp.size() == I1temp.size() /home/dburd/build/opencv_contrib/modules/optflow/src/deepflow.cpp I0temp.type() == I1temp.type() I0temp.channels() == 1 calc N2cv6detail8PtrOwnerE N2cv16DenseOpticalFlowE N2cv7optflow19OpticalFlowDeepFlowE N2cv6detail12PtrOwnerImplINS_7optflow19OpticalFlowDeepFlowENS_14DefaultDeleterIS3_EEEE ÿB ÿÿÿ ? @@ K ? @ ð?dis_patch_inverse_search_fwd_1 dis_patch_inverse_search_fwd_2 dis_patch_inverse_search_bwd_1 dis_patch_inverse_search_bwd_2 dis_densification dis_precomputeStructureTensor_hor dis_precomputeStructureTensor_ver vector::_M_default_append !I1.empty() && I1.depth() == CV_8U && I1.channels() == 1 /home/dburd/build/opencv_contrib/modules/optflow/src/dis_flow.cpp !I0.empty() && I0.depth() == CV_8U && I0.channels() == 1 I0.sameSize(I1) I0.isContinuous() I1.isContinuous() calc N2cv7optflow14DISOpticalFlowE N2cv7optflow18DISOpticalFlowImpl26PatchInverseSearch_ParBodyE N2cv7optflow18DISOpticalFlowImpl21Densification_ParBodyE N2cv7optflow18DISOpticalFlowImplE N2cv6detail12PtrOwnerImplINS_7optflow18DISOpticalFlowImplENS_14DefaultDeleterIS3_EEEE o:ùPÿÿÿ ÿÿÿÿÿÿÿ 0C @ï9úþB.æ? à? @ À? ð¿ N2cv7optflow21OpticalFlowSimpleFlowE N2cv7optflow20OpticalFlowFarnebackE N2cv7optflow24OpticalFlowSparseToDenseE N2cv6detail12PtrOwnerImplINS_7optflow21OpticalFlowSimpleFlowENS_14DefaultDeleterIS3_EEEE N2cv6detail12PtrOwnerImplINS_7optflow20OpticalFlowFarnebackENS_14DefaultDeleterIS3_EEEE N2cv6detail12PtrOwnerImplINS_7optflow24OpticalFlowSparseToDenseENS_14DefaultDeleterIS3_EEEE ffffff@ 9@ K@ffffffÖ? $@/home/dburd/build/opencv_contrib/modules/optflow/src/motempl.cpp _silhouette.type() == CV_8UC1 && _mhi.type() == CV_32FC1 _silhouette.sameSize(_mhi) updateMotionHistory aperture_size must be 3, 5 or 7 MHI must be single-channel floating-point images both delta's must be positive mask.type() == CV_8U && orient.type() == CV_32F && mhi.type() == CV_32F mask.size() == size && orient.size() == size duration > 0 mhi.type() == CV_32F segThresh >= 0 segmentMotion calcGlobalOrientation calcMotionGradient updateMotionHistory ÿ ÿ ÿ ÿ ÿ ÿ ÿ ÿ ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿïÿÿÿÿÿÿï àßßßßßï?·Ñ8 ´C ´Ã 4Ã 4C 4B
×#<PIEH PIEHA.size().height == b.size().height /home/dburd/build/opencv_contrib/modules/optflow/src/pcaflow.cpp A.type() == CV_32F b.type() == CV_32F fillDCTSampledPoints basisSize.width > 0 && basisSize.height > 0 sparseRate > 0 && sparseRate <= 0.1 retainedCornersFraction >= 0 && retainedCornersFraction <= 1.0 occlusionsThreshold > 0 rb fread( &n, sizeof( n ), 1, f ) == 1 fread( &m, sizeof( m ), 1, f ) == 1 fread( L1.ptr<float>(), n * m * sizeof( float ), 1, f ) == 1 fread( L2.ptr<float>(), n * m * sizeof( float ), 1, f ) == 1 fread( c1.ptr<float>(), n * sizeof( float ), 1, f ) == 1 fread( c2.ptr<float>(), n * sizeof( float ), 1, f ) == 1 prior->getBasisSize() == basisSize.area() size == I1.size() from.channels() == 1 to.channels() == 1 __kernel void fillDCTSampledPoints(__global const uchar* features, int fstep, int foff, __global uchar* A, int Astep, int Aoff, int fs, int bsw, int bsh, int sw, int sh) {const int i = get_global_id(0);const int n1 = get_global_id(1);const int n2 = get_global_id(2);if (i >= fs || n1 >= bsw || n2 >= bsh) return;__global const float2* f = (__global const float2*)(features + (fstep * i + foff));__global float* a = (__global float*)(A + (Astep * i + Aoff + (n1 * bsh + n2) * sizeof(float)));const float2 p = f[0];const float pi = 3.14159265358979323846;a[0] = cos((n1 * pi / sw) * (p.x + 0.5)) * cos((n2 * pi / sh) * (p.y + 0.5));} PCAPrior OpticalFlowPCAFlow solveLSQR calc getSystem getSystem N2cv7optflow18OpticalFlowPCAFlowE N2cv6detail12PtrOwnerImplINS_7optflow18OpticalFlowPCAFlowENS_14DefaultDeleterIS3_EEEE D@ -DTû! @¹?-C ëâ6?{®Gáz¤? @{®Gázt?Í;f ö? Ð? @@ Í;f ö?Í;f ö? `A¬ŧ7RI9ÍÌL>¦Ä<!src_.empty() !confidence_.empty() !joint_.empty() /home/dburd/build/opencv_contrib/modules/optflow/src/simpleflow.cpp src.size() == joint.size() && confidence.size() == src.size() joint.depth() == CV_8U && confidence.type() == CV_32F confidence.at<float>(r0, c0) >= 0 height > 0 && width > 0 (int)pyr_from_images.size() == layers && (int)pyr_to_images.size() == layers crossBilateralFilter extrapolateValueInRect calcConfidence calcOpticalFlowSF N2cv7optflow20CrossBilateralFilterINS_3VecIhLi3EEENS2_IfLi2EEEEE N2cv7optflow28CalcOpticalFlowSingleScaleSFINS_3VecIhLi3EEENS2_IfLi2EEEEE ? ? ? ? Ö&è .> à¿ ø? @ÿÿ vector::_M_range_check: __n (which is %zu) >= this->size() (which is %zu) Tree have not been trained /home/dburd/build/opencv_contrib/modules/optflow/src/sparse_matching_gpc.cpp No element name has been given /home/dburd/build/opencv/modules/core/include/opencv2/core/persistence.hpp -DPATCH_RADIUS_DOUBLED=%d -DCV_PI=%f -DSQRT2_INV=%f sz.height - 2 * patchRadius > 0 sz.width - 2 * patchRadius > 0 getPatchDescriptor vector::reserve Unknown descriptor type nodes dtype [%u] Correct %.2f (%u/%d)
Weights: %.3f Descriptor type mismatch! Check that samples are collected with the same descriptor type. imagesFrom.size() == imagesTo.size() imagesFrom.size() == gt.size() imagesFrom.total() == imagesTo.total() imagesFrom.total() == gt.total() create getTrainingSamples create operator<< operator<< write train ocl_getAllDCTDescriptorsForImage getAllDescriptorsForImage N2cv7optflow7GPCTreeE *N2cv7optflow12_GLOBAL__N_117ParallelDCTFillerE *N2cv7optflow12_GLOBAL__N_117ParallelWHTFillerE N2cv6detail12PtrOwnerImplINS_7optflow18GPCTrainingSamplesENS_14DefaultDeleterIS3_EEEE 4@Ì;f æ? ð;¤p=
ף@¤p=
ףø?É?ê-q= ð?ÑÜÿÿÿÿï? i@ ø\Âõ(\ï? àCé? ¹?¹? from.size == to.from.size == gtFfrom.channels() to.channels() ==grid_step>1 && k>3 && sigma>0.0001f && fgs_lambda>1.0f && fgs_sigma>0.01f /home/dburd/build/opencv_contrib/modules/optflow/src/sparsetodenseflow.cpp !from.empty() && from.depth() == CV_8U && (from.channels() == 3 || from.channels() == 1) !to .empty() && to .depth() == CV_8U && (to .channels() == 3 || to .channels() == 1) from.sameSize(to) calcOpticalFlowSparseToDense /home/dburd/build/opencv_contrib/modules/optflow/src/variational_refinement.cpp !I1.empty() && I1.channels() == 1 !I0.empty() && I0.channels() == 1 !flow_u.empty() && flow_u.depth() == CV_32F && flow_u.channels() == 1 (I0.depth() == CV_8U && I1.depth() == CV_8U) || (I0.depth() == CV_32F && I1.depth() == CV_32F) !flow_v.empty() && flow_v.depth() == CV_32F && flow_v.channels() == 1 I0.sameSize(flow_u) flow_u.sameSize(flow_v) !flow.empty() && flow.depth() == CV_32F && flow.channels() == 2 I0.sameSize(flow) calcUV calc N2cv7optflow21VariationalRefinementE N2cv7optflow25VariationalRefinementImpl18ParallelOp_ParBodyE N2cv7optflow25VariationalRefinementImpl23ComputeDataTerm_ParBodyE N2cv7optflow25VariationalRefinementImpl36ComputeSmoothnessTermHorPass_ParBodyE N2cv7optflow25VariationalRefinementImpl37ComputeSmoothnessTermVertPass_ParBodyE N2cv7optflow25VariationalRefinementImpl19RedBlackSOR_ParBodyE N2cv7optflow25VariationalRefinementImplE N2cv6detail12PtrOwnerImplINS_7optflow25VariationalRefinementImplENS_14DefaultDeleterIS3_EEEE ÿÿÿÿÿÿÿ @optflow updatemotionhistory sparse_matching_gpc dis_flow __kernel void updateMotionHistory(__global const uchar * silh, int silh_step, int silh_offset,
__global uchar * mhiptr, int mhi_step, int mhi_offset, int mhi_rows, int mhi_cols,
float timestamp, float delbound)
{
int x = get_global_id(0);
int y = get_global_id(1);
if (x < mhi_cols && y < mhi_rows)
{
int silh_index = mad24(y, silh_step, silh_offset + x);
int mhi_index = mad24(y, mhi_step, mhi_offset + x * (int)sizeof(float));
silh += silh_index;
__global float * mhi = (__global float *)(mhiptr + mhi_index);
float val = mhi[0];
val = silh[0] ? timestamp : val < delbound ? 0 : val;
mhi[0] = val;
}
}
b19beb01d0c6052524049341b55a2be5 __kernel void getPatchDescriptor(
__global const uchar* imgCh0, int ic0step, int ic0off,
__global const uchar* imgCh1, int ic1step, int ic1off,
__global const uchar* imgCh2, int ic2step, int ic2off,
__global uchar* out, int outstep, int outoff,
const int gh, const int gw, const int PR )
{
const int i = get_global_id(0);
const int j = get_global_id(1);
if (i >= gh || j >= gw)
return;
__global double* desc = (__global double*)(out + (outstep * (i * gw + j) + outoff));
const int patchRadius = PR * 2;
float patch[PATCH_RADIUS_DOUBLED][PATCH_RADIUS_DOUBLED];
for (int i0 = 0; i0 < patchRadius; ++i0) {
__global const float* ch0Row = (__global const float*)(imgCh0 + (ic0step * (i + i0) + ic0off + j * sizeof(float)));
for (int j0 = 0; j0 < patchRadius; ++j0)
patch[i0][j0] = ch0Row[j0];
}
#pragma unroll
for (int n0 = 0; n0 < 4; ++n0) {
#pragma unroll
for (int n1 = 0; n1 < 4; ++n1) {
double sum = 0;
for (int i0 = 0; i0 < patchRadius; ++i0)
for (int j0 = 0; j0 < patchRadius; ++j0)
sum += patch[i0][j0] * cos(CV_PI * (i0 + 0.5) * n0 / patchRadius) * cos(CV_PI * (j0 + 0.5) * n1 / patchRadius);
desc[n0 * 4 + n1] = sum / PR;
}
}
for (int k = 0; k < 4; ++k) {
desc[k] *= SQRT2_INV;
desc[k * 4] *= SQRT2_INV;
}
double sum = 0;
for (int i0 = 0; i0 < patchRadius; ++i0) {
__global const float* ch1Row = (__global const float*)(imgCh1 + (ic1step * (i + i0) + ic1off + j * sizeof(float)));
for (int j0 = 0; j0 < patchRadius; ++j0)
sum += ch1Row[j0];
}
desc[16] = sum / patchRadius;
sum = 0;
for (int i0 = 0; i0 < patchRadius; ++i0) {
__global const float* ch2Row = (__global const float*)(imgCh2 + (ic2step * (i + i0) + ic2off + j * sizeof(float)));
for (int j0 = 0; j0 < patchRadius; ++j0)
sum += ch2Row[j0];
}
desc[17] = sum / patchRadius;
}
4de6dbd7b34900887da8399ec2e431b0 #define EPS 0.001f
#define INF 1E+10F
__kernel void dis_precomputeStructureTensor_hor(__global const short *I0x,
__global const short *I0y,
int patch_size, int patch_stride,
int w, int h, int ws,
__global float *I0xx_aux_ptr,
__global float *I0yy_aux_ptr,
__global float *I0xy_aux_ptr,
__global float *I0x_aux_ptr,
__global float *I0y_aux_ptr)
{
int i = get_global_id(0);
if (i >= h) return;
const __global short *x_row = I0x + i * w;
const __global short *y_row = I0y + i * w;
float sum_xx = 0.0f, sum_yy = 0.0f, sum_xy = 0.0f, sum_x = 0.0f, sum_y = 0.0f;
float8 x_vec = convert_float8(vload8(0, x_row));
float8 y_vec = convert_float8(vload8(0, y_row));
sum_xx = dot(x_vec.lo, x_vec.lo) + dot(x_vec.hi, x_vec.hi);
sum_yy = dot(y_vec.lo, y_vec.lo) + dot(y_vec.hi, y_vec.hi);
sum_xy = dot(x_vec.lo, y_vec.lo) + dot(x_vec.hi, y_vec.hi);
sum_x = dot(x_vec.lo, 1.0f) + dot(x_vec.hi, 1.0f);
sum_y = dot(y_vec.lo, 1.0f) + dot(y_vec.hi, 1.0f);
I0xx_aux_ptr[i * ws] = sum_xx;
I0yy_aux_ptr[i * ws] = sum_yy;
I0xy_aux_ptr[i * ws] = sum_xy;
I0x_aux_ptr[i * ws] = sum_x;
I0y_aux_ptr[i * ws] = sum_y;
int js = 1;
for (int j = patch_size; j < w; j++)
{
short x_val1 = x_row[j];
short x_val2 = x_row[j - patch_size];
short y_val1 = y_row[j];
short y_val2 = y_row[j - patch_size];
sum_xx += (x_val1 * x_val1 - x_val2 * x_val2);
sum_yy += (y_val1 * y_val1 - y_val2 * y_val2);
sum_xy += (x_val1 * y_val1 - x_val2 * y_val2);
sum_x += (x_val1 - x_val2);
sum_y += (y_val1 - y_val2);
if ((j - patch_size + 1) % patch_stride == 0)
{
int index = i * ws + js;
I0xx_aux_ptr[index] = sum_xx;
I0yy_aux_ptr[index] = sum_yy;
I0xy_aux_ptr[index] = sum_xy;
I0x_aux_ptr[index] = sum_x;
I0y_aux_ptr[index] = sum_y;
js++;
}
}
}
__kernel void dis_precomputeStructureTensor_ver(__global const float *I0xx_aux_ptr,
__global const float *I0yy_aux_ptr,
__global const float *I0xy_aux_ptr,
__global const float *I0x_aux_ptr,
__global const float *I0y_aux_ptr,
int patch_size, int patch_stride,
int w, int h, int ws,
__global float *I0xx_ptr,
__global float *I0yy_ptr,
__global float *I0xy_ptr,
__global float *I0x_ptr,
__global float *I0y_ptr)
{
int j = get_global_id(0);
if (j >= ws) return;
float sum_xx, sum_yy, sum_xy, sum_x, sum_y;
sum_xx = sum_yy = sum_xy = sum_x = sum_y = 0.0f;
for (int i = 0; i < patch_size; i++)
{
sum_xx += I0xx_aux_ptr[i * ws + j];
sum_yy += I0yy_aux_ptr[i * ws + j];
sum_xy += I0xy_aux_ptr[i * ws + j];
sum_x += I0x_aux_ptr[i * ws + j];
sum_y += I0y_aux_ptr[i * ws + j];
}
I0xx_ptr[j] = sum_xx;
I0yy_ptr[j] = sum_yy;
I0xy_ptr[j] = sum_xy;
I0x_ptr[j] = sum_x;
I0y_ptr[j] = sum_y;
int is = 1;
for (int i = patch_size; i < h; i++)
{
sum_xx += (I0xx_aux_ptr[i * ws + j] - I0xx_aux_ptr[(i - patch_size) * ws + j]);
sum_yy += (I0yy_aux_ptr[i * ws + j] - I0yy_aux_ptr[(i - patch_size) * ws + j]);
sum_xy += (I0xy_aux_ptr[i * ws + j] - I0xy_aux_ptr[(i - patch_size) * ws + j]);
sum_x += (I0x_aux_ptr[i * ws + j] - I0x_aux_ptr[(i - patch_size) * ws + j]);
sum_y += (I0y_aux_ptr[i * ws + j] - I0y_aux_ptr[(i - patch_size) * ws + j]);
if ((i - patch_size + 1) % patch_stride == 0)
{
I0xx_ptr[is * ws + j] = sum_xx;
I0yy_ptr[is * ws + j] = sum_yy;
I0xy_ptr[is * ws + j] = sum_xy;
I0x_ptr[is * ws + j] = sum_x;
I0y_ptr[is * ws + j] = sum_y;
is++;
}
}
}
__kernel void dis_densification(__global const float *sx, __global const float *sy,
__global const uchar *i0, __global const uchar *i1,
int psz, int pstr,
int w, int h, int ws,
__global float *ux, __global float *uy)
{
int x = get_global_id(0);
int y = get_global_id(1);
int i, j;
if (x >= w || y >= h) return;
int start_is, end_is;
int start_js, end_js;
end_is = min(y / pstr, (h - psz) / pstr);
start_is = max(0, y - psz + pstr) / pstr;
start_is = min(start_is, end_is);
end_js = min(x / pstr, (w - psz) / pstr);
start_js = max(0, x - psz + pstr) / pstr;
start_js = min(start_js, end_js);
float coef, sum_coef = 0.0f;
float sum_Ux = 0.0f;
float sum_Uy = 0.0f;
int i_l, i_u;
int j_l, j_u;
float i_m, j_m, diff;
i = y;
j = x;
for (int is = start_is; is <= end_is; is++)
for (int js = start_js; js <= end_js; js++)
{
float sx_val = sx[is * ws + js];
float sy_val = sy[is * ws + js];
uchar2 i1_vec1, i1_vec2;
j_m = min(max(j + sx_val, 0.0f), w - 1.0f - EPS);
i_m = min(max(i + sy_val, 0.0f), h - 1.0f - EPS);
j_l = (int)j_m;
j_u = j_l + 1;
i_l = (int)i_m;
i_u = i_l + 1;
i1_vec1 = vload2(0, i1 + i_u * w + j_l);
i1_vec2 = vload2(0, i1 + i_l * w + j_l);
diff = (j_m - j_l) * (i_m - i_l) * i1_vec1.y +
(j_u - j_m) * (i_m - i_l) * i1_vec1.x +
(j_m - j_l) * (i_u - i_m) * i1_vec2.y +
(j_u - j_m) * (i_u - i_m) * i1_vec2.x - i0[i * w + j];
coef = 1 / max(1.0f, fabs(diff));
sum_Ux += coef * sx_val;
sum_Uy += coef * sy_val;
sum_coef += coef;
}
ux[i * w + j] = sum_Ux / sum_coef;
uy[i * w + j] = sum_Uy / sum_coef;
}
#define INIT_BILINEAR_WEIGHTS(Ux, Uy) \
i_I1 = min(max(i + Uy + bsz, i_lower_limit), i_upper_limit); \
j_I1 = min(max(j + Ux + bsz, j_lower_limit), j_upper_limit); \
\
w11 = (i_I1 - floor(i_I1)) * (j_I1 - floor(j_I1)); \
w10 = (i_I1 - floor(i_I1)) * (floor(j_I1) + 1 - j_I1); \
w01 = (floor(i_I1) + 1 - i_I1) * (j_I1 - floor(j_I1)); \
w00 = (floor(i_I1) + 1 - i_I1) * (floor(j_I1) + 1 - j_I1);
float computeSSDMeanNorm(const __global uchar *I0_ptr, const __global uchar *I1_ptr,
int I0_stride, int I1_stride,
float w00, float w01, float w10, float w11, int patch_sz, int i)
{
float sum_diff = 0.0f, sum_diff_sq = 0.0f;
int n = patch_sz * patch_sz;
uchar8 I1_vec1, I1_vec2, I0_vec;
uchar I1_val1, I1_val2;
I0_vec = vload8(0, I0_ptr + i * I0_stride);
I1_vec1 = vload8(0, I1_ptr + i * I1_stride);
I1_vec2 = vload8(0, I1_ptr + (i + 1) * I1_stride);
I1_val1 = I1_ptr[i * I1_stride + 8];
I1_val2 = I1_ptr[(i + 1) * I1_stride + 8];
float8 vec = w00 * convert_float8(I1_vec1) + w01 * convert_float8((uchar8)(I1_vec1.s123, I1_vec1.s4567, I1_val1)) +
w10 * convert_float8(I1_vec2) + w11 * convert_float8((uchar8)(I1_vec2.s123, I1_vec2.s4567, I1_val2)) -
convert_float8(I0_vec);
sum_diff = (dot(vec.lo, 1.0) + dot(vec.hi, 1.0));
sum_diff_sq = (dot(vec.lo, vec.lo) + dot(vec.hi, vec.hi));
sum_diff = sub_group_reduce_add(sum_diff);
sum_diff_sq = sub_group_reduce_add(sum_diff_sq);
return sum_diff_sq - sum_diff * sum_diff / n;
}
__kernel void dis_patch_inverse_search_fwd_1(__global const float *Ux_ptr, __global const float *Uy_ptr,
__global const uchar *I0_ptr, __global const uchar *I1_ptr,
int border_size, int patch_size, int patch_stride,
int w, int h, int ws, int hs, int pyr_level,
__global float *Sx_ptr, __global float *Sy_ptr)
{
int id = get_global_id(0);
int is = id / 8;
if (id >= (hs * 8)) return;
int i = is * patch_stride;
int j = 0;
int psz = patch_size;
int psz2 = psz / 2;
int w_ext = w + 2 * border_size;
int bsz = border_size;
float i_lower_limit = bsz - psz + 1.0f;
float i_upper_limit = bsz + h - 1.0f;
float j_lower_limit = bsz - psz + 1.0f;
float j_upper_limit = bsz + w - 1.0f;
float i_I1, j_I1, w00, w01, w10, w11;
float prev_Ux = Ux_ptr[(i + psz2) * w + j + psz2];
float prev_Uy = Uy_ptr[(i + psz2) * w + j + psz2];
Sx_ptr[is * ws] = prev_Ux;
Sy_ptr[is * ws] = prev_Uy;
j += patch_stride;
int sid = get_sub_group_local_id();
for (int js = 1; js < ws; js++, j += patch_stride)
{
float min_SSD, cur_SSD;
float Ux = Ux_ptr[(i + psz2) * w + j + psz2];
float Uy = Uy_ptr[(i + psz2) * w + j + psz2];
INIT_BILINEAR_WEIGHTS(Ux, Uy);
min_SSD = computeSSDMeanNorm(I0_ptr + i * w + j, I1_ptr + (int)i_I1 * w_ext + (int)j_I1,
w, w_ext, w00, w01, w10, w11, psz, sid);
INIT_BILINEAR_WEIGHTS(prev_Ux, prev_Uy);
cur_SSD = computeSSDMeanNorm(I0_ptr + i * w + j, I1_ptr + (int)i_I1 * w_ext + (int)j_I1,
w, w_ext, w00, w01, w10, w11, psz, sid);
if (cur_SSD < min_SSD)
{
Ux = prev_Ux;
Uy = prev_Uy;
}
prev_Ux = Ux;
prev_Uy = Uy;
Sx_ptr[is * ws + js] = Ux;
Sy_ptr[is * ws + js] = Uy;
}
}
float3 processPatchMeanNorm(const __global uchar *I0_ptr, const __global uchar *I1_ptr,
const __global short *I0x_ptr, const __global short *I0y_ptr,
int I0_stride, int I1_stride, float w00, float w01, float w10,
float w11, int patch_sz, float x_grad_sum, float y_grad_sum)
{
float sum_diff = 0.0, sum_diff_sq = 0.0;
float sum_I0x_mul = 0.0, sum_I0y_mul = 0.0;
int n = patch_sz * patch_sz;
uchar8 I1_vec1, I1_vec2;
uchar I1_val1, I1_val2;
for (int i = 0; i < 8; i++)
{
uchar8 I0_vec = vload8(0, I0_ptr + i * I0_stride);
I1_vec1 = (i == 0) ? vload8(0, I1_ptr + i * I1_stride) : I1_vec2;
I1_vec2 = vload8(0, I1_ptr + (i + 1) * I1_stride);
I1_val1 = (i == 0) ? I1_ptr[i * I1_stride + patch_sz] : I1_val2;
I1_val2 = I1_ptr[(i + 1) * I1_stride + patch_sz];
float8 vec = w00 * convert_float8(I1_vec1) + w01 * convert_float8((uchar8)(I1_vec1.s123, I1_vec1.s4567, I1_val1)) +
w10 * convert_float8(I1_vec2) + w11 * convert_float8((uchar8)(I1_vec2.s123, I1_vec2.s4567, I1_val2)) -
convert_float8(I0_vec);
sum_diff += (dot(vec.lo, 1.0) + dot(vec.hi, 1.0));
sum_diff_sq += (dot(vec.lo, vec.lo) + dot(vec.hi, vec.hi));
short8 I0x_vec = vload8(0, I0x_ptr + i * I0_stride);
short8 I0y_vec = vload8(0, I0y_ptr + i * I0_stride);
sum_I0x_mul += dot(vec.lo, convert_float4(I0x_vec.lo));
sum_I0x_mul += dot(vec.hi, convert_float4(I0x_vec.hi));
sum_I0y_mul += dot(vec.lo, convert_float4(I0y_vec.lo));
sum_I0y_mul += dot(vec.hi, convert_float4(I0y_vec.hi));
}
float dst_dUx = sum_I0x_mul - sum_diff * x_grad_sum / n;
float dst_dUy = sum_I0y_mul - sum_diff * y_grad_sum / n;
float SSD = sum_diff_sq - sum_diff * sum_diff / n;
return (float3)(SSD, dst_dUx, dst_dUy);
}
__kernel void dis_patch_inverse_search_fwd_2(__global const float *Ux_ptr, __global const float *Uy_ptr,
__global const uchar *I0_ptr, __global const uchar *I1_ptr,
__global const short *I0x_ptr, __global const short *I0y_ptr,
__global const float *xx_ptr, __global const float *yy_ptr,
__global const float *xy_ptr,
__global const float *x_ptr, __global const float *y_ptr,
int border_size, int patch_size, int patch_stride,
int w, int h, int ws, int hs, int num_inner_iter, int pyr_level,
__global float *Sx_ptr, __global float *Sy_ptr)
{
int js = get_global_id(0);
int is = get_global_id(1);
int i = is * patch_stride;
int j = js * patch_stride;
int psz = patch_size;
int psz2 = psz / 2;
int w_ext = w + 2 * border_size;
int bsz = border_size;
int index = is * ws + js;
if (js >= ws || is >= hs) return;
float Ux = Sx_ptr[index];
float Uy = Sy_ptr[index];
float cur_Ux = Ux;
float cur_Uy = Uy;
float cur_xx = xx_ptr[index];
float cur_yy = yy_ptr[index];
float cur_xy = xy_ptr[index];
float detH = cur_xx * cur_yy - cur_xy * cur_xy;
if (fabs(detH) < EPS) detH = EPS;
float invH11 = cur_yy / detH;
float invH12 = -cur_xy / detH;
float invH22 = cur_xx / detH;
float prev_SSD = INF, SSD;
float x_grad_sum = x_ptr[index];
float y_grad_sum = y_ptr[index];
float i_lower_limit = bsz - psz + 1.0f;
float i_upper_limit = bsz + h - 1.0f;
float j_lower_limit = bsz - psz + 1.0f;
float j_upper_limit = bsz + w - 1.0f;
float dUx, dUy, i_I1, j_I1, w00, w01, w10, w11, dx, dy;
float3 res;
for (int t = 0; t < num_inner_iter; t++)
{
INIT_BILINEAR_WEIGHTS(cur_Ux, cur_Uy);
res = processPatchMeanNorm(I0_ptr + i * w + j,
I1_ptr + (int)i_I1 * w_ext + (int)j_I1, I0x_ptr + i * w + j,
I0y_ptr + i * w + j, w, w_ext, w00, w01, w10, w11, psz,
x_grad_sum, y_grad_sum);
SSD = res.x;
dUx = res.y;
dUy = res.z;
dx = invH11 * dUx + invH12 * dUy;
dy = invH12 * dUx + invH22 * dUy;
cur_Ux -= dx;
cur_Uy -= dy;
if (SSD >= prev_SSD)
break;
prev_SSD = SSD;
}
float2 vec = (float2)(cur_Ux - Ux, cur_Uy - Uy);
if (dot(vec, vec) <= (float)(psz * psz))
{
Sx_ptr[index] = cur_Ux;
Sy_ptr[index] = cur_Uy;
}
}
__kernel void dis_patch_inverse_search_bwd_1(__global const uchar *I0_ptr, __global const uchar *I1_ptr,
int border_size, int patch_size, int patch_stride,
int w, int h, int ws, int hs, int pyr_level,
__global float *Sx_ptr, __global float *Sy_ptr)
{
int id = get_global_id(0);
int is = id / 8;
if (id >= (hs * 8)) return;
is = (hs - 1 - is);
int i = is * patch_stride;
int j = (ws - 2) * patch_stride;
int psz = patch_size;
int psz2 = psz / 2;
int w_ext = w + 2 * border_size;
int bsz = border_size;
float i_lower_limit = bsz - psz + 1.0f;
float i_upper_limit = bsz + h - 1.0f;
float j_lower_limit = bsz - psz + 1.0f;
float j_upper_limit = bsz + w - 1.0f;
float i_I1, j_I1, w00, w01, w10, w11;
int sid = get_sub_group_local_id();
for (int js = (ws - 2); js > -1; js--, j -= patch_stride)
{
float min_SSD, cur_SSD;
float2 Ux = vload2(0, Sx_ptr + is * ws + js);
float2 Uy = vload2(0, Sy_ptr + is * ws + js);
INIT_BILINEAR_WEIGHTS(Ux.x, Uy.x);
min_SSD = computeSSDMeanNorm(I0_ptr + i * w + j, I1_ptr + (int)i_I1 * w_ext + (int)j_I1,
w, w_ext, w00, w01, w10, w11, psz, sid);
INIT_BILINEAR_WEIGHTS(Ux.y, Uy.y);
cur_SSD = computeSSDMeanNorm(I0_ptr + i * w + j, I1_ptr + (int)i_I1 * w_ext + (int)j_I1,
w, w_ext, w00, w01, w10, w11, psz, sid);
if (cur_SSD < min_SSD)
{
Sx_ptr[is * ws + js] = Ux.y;
Sy_ptr[is * ws + js] = Uy.y;
}
}
}
__kernel void dis_patch_inverse_search_bwd_2(__global const uchar *I0_ptr, __global const uchar *I1_ptr,
__global const short *I0x_ptr, __global const short *I0y_ptr,
__global const float *xx_ptr, __global const float *yy_ptr,
__global const float *xy_ptr,
__global const float *x_ptr, __global const float *y_ptr,
int border_size, int patch_size, int patch_stride,
int w, int h, int ws, int hs, int num_inner_iter,
__global float *Sx_ptr, __global float *Sy_ptr)
{
int js = get_global_id(0);
int is = get_global_id(1);
if (js >= ws || is >= hs) return;
js = (ws - 1 - js);
is = (hs - 1 - is);
int j = js * patch_stride;
int i = is * patch_stride;
int psz = patch_size;
int psz2 = psz / 2;
int w_ext = w + 2 * border_size;
int bsz = border_size;
int index = is * ws + js;
float Ux = Sx_ptr[index];
float Uy = Sy_ptr[index];
float cur_Ux = Ux;
float cur_Uy = Uy;
float cur_xx = xx_ptr[index];
float cur_yy = yy_ptr[index];
float cur_xy = xy_ptr[index];
float detH = cur_xx * cur_yy - cur_xy * cur_xy;
if (fabs(detH) < EPS) detH = EPS;
float invH11 = cur_yy / detH;
float invH12 = -cur_xy / detH;
float invH22 = cur_xx / detH;
float prev_SSD = INF, SSD;
float x_grad_sum = x_ptr[index];
float y_grad_sum = y_ptr[index];
float i_lower_limit = bsz - psz + 1.0f;
float i_upper_limit = bsz + h - 1.0f;
float j_lower_limit = bsz - psz + 1.0f;
float j_upper_limit = bsz + w - 1.0f;
float dUx, dUy, i_I1, j_I1, w00, w01, w10, w11, dx, dy;
float3 res;
for (int t = 0; t < num_inner_iter; t++)
{
INIT_BILINEAR_WEIGHTS(cur_Ux, cur_Uy);
res = processPatchMeanNorm(I0_ptr + i * w + j,
I1_ptr + (int)i_I1 * w_ext + (int)j_I1, I0x_ptr + i * w + j,
I0y_ptr + i * w + j, w, w_ext, w00, w01, w10, w11, psz,
x_grad_sum, y_grad_sum);
SSD = res.x;
dUx = res.y;
dUy = res.z;
dx = invH11 * dUx + invH12 * dUy;
dy = invH12 * dUx + invH22 * dUy;
cur_Ux -= dx;
cur_Uy -= dy;
if (SSD >= prev_SSD)
break;
prev_SSD = SSD;
}
float2 vec = (float2)(cur_Ux - Ux, cur_Uy - Uy);
if ((dot(vec, vec)) <= (float)(psz * psz))
{
Sx_ptr[index] = cur_Ux;
Sy_ptr[index] = cur_Uy;
}
}
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_ZNSt6vectorIN2cv7optflow18GPCPatchDescriptorESaIS2_EE17_M_default_appendEm putchar@@GLIBC_2.2.5 _ZN2cv8ximgproc27createEdgeAwareInterpolatorEv _ZNSt6localeD1Ev@@GLIBCXX_3.4 __cxa_throw_bad_array_new_length@@CXXABI_1.3.8 _ZN2cv11createCLAHEEdNS_5Size_IiEE _ZN2cv8cvtColorERKNS_11_InputArrayERKNS_12_OutputArrayEii _ZTVN2cv16DenseOpticalFlowE __cxa_rethrow@@CXXABI_1.3 _ZNSt14basic_ofstreamIcSt11char_traitsIcEED1Ev@@GLIBCXX_3.4 _ZN2cv5writeERNS_11FileStorageERKNS_6StringEi fread@@GLIBC_2.2.5 _ZNK2cv12_OutputArray7releaseEv _ZNK2cv12_OutputArray6createEiiiibi _ZN2cv5SobelERKNS_11_InputArrayERKNS_12_OutputArrayEiiiiddi __bss_start _ZTSN2cv7optflow14DISOpticalFlowE _ZSt24__throw_out_of_range_fmtPKcz@@GLIBCXX_3.4.20 _ZTVSt13basic_filebufIcSt11char_traitsIcEE@@GLIBCXX_3.4 _ZNSt8ios_base4InitC1Ev@@GLIBCXX_3.4 _ZTVSt14basic_ofstreamIcSt11char_traitsIcEE@@GLIBCXX_3.4 _ZNSt13basic_filebufIcSt11char_traitsIcEED1Ev@@GLIBCXX_3.4 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