mirror of
https://github.com/opencv/opencv.git
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fixed
This commit is contained in:
Elena Gvozdeva
parent
47b572f99f
commit
4da1ba56b3
@ -29,15 +29,13 @@
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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#define DATA_TYPE type
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#define DATA_SIZE ((int)sizeof(type))
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#define ELEM_TYPE elem_type
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#define ELEM_SIZE ((int)sizeof(elem_type))
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#define CN cn
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#define SQSUMS_PTR(ox, oy) mad24(gidy + oy, img_sqsums_step, (gidx + img_sqsums_offset + ox) * CN)
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#define SQSUMS(ox, oy) mad24(gidy + oy, img_sqsums_step, (gidx*CN + img_sqsums_offset + ox*CN))
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#define SUMS_PTR(ox, oy) mad24(gidy + oy, img_sums_step, (gidx*CN + img_sums_offset + ox*CN))
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#define SQSUMS_PTR(ox, oy) mad24(gidy + oy, img_sqsums_step, gidx*CN + img_sqsums_offset + ox*CN)
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#define SUMS_PTR(ox, oy) mad24(gidy + oy, img_sums_step, gidx*CN + img_sums_offset + ox*CN)
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inline float normAcc(float num, float denum)
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{
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@ -76,10 +74,7 @@ __kernel void matchTemplate_Naive_CCORR (__global const uchar * img,int img_step
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int i,j;
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float sum = 0;
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res_step /= sizeof(float);
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res_offset /= sizeof(float);
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int res_idx = mad24(gidy, res_step, res_offset + gidx);
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int res_idx = mad24(gidy, res_step, res_offset + gidx * (int)sizeof(float));
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if(gidx < res_cols && gidy < res_rows)
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{
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@ -90,12 +85,13 @@ __kernel void matchTemplate_Naive_CCORR (__global const uchar * img,int img_step
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for(j = 0; j < tpl_cols; j ++)
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#pragma unroll
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for (int c = 0; c < CN; c++)
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sum += (float)(img_ptr[j*CN+c] * tpl_ptr[j*CN+c]);
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}
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__global float * result = (__global float *)(res)+res_idx;
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__global float * result = (__global float *)(res+res_idx);
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*result = sum;
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}
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}
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@ -109,10 +105,8 @@ __kernel void matchTemplate_CCORR_NORMED ( __global const uchar * img_sqsums, in
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img_sqsums_step /= sizeof(float);
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img_sqsums_offset /= sizeof(float);
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res_step /= sizeof(float);
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res_offset /= sizeof(float);
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int res_idx = mad24(gidy, res_step, res_offset + gidx);
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int res_idx = mad24(gidy, res_step, res_offset + gidx * (int)sizeof(float));
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if(gidx < res_cols && gidy < res_rows)
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{
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@ -121,7 +115,7 @@ __kernel void matchTemplate_CCORR_NORMED ( __global const uchar * img_sqsums, in
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(sqsum[SQSUMS_PTR(tpl_cols, tpl_rows)] - sqsum[SQSUMS_PTR(tpl_cols, 0)]) -
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(sqsum[SQSUMS_PTR(0, tpl_rows)] - sqsum[SQSUMS_PTR(0, 0)]));
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__global float * result = (__global float *)(res)+res_idx;
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__global float * result = (__global float *)(res+res_idx);
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*result = normAcc(*result, sqrt(image_sqsum_ * tpl_sqsum));
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}
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}
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@ -138,10 +132,7 @@ __kernel void matchTemplate_Naive_SQDIFF(__global const uchar * img,int img_step
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float delta;
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float sum = 0;
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res_step /= sizeof(float);
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res_offset /= sizeof(float);
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int res_idx = mad24(gidy, res_step, res_offset + gidx);
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int res_idx = mad24(gidy, res_step, res_offset + gidx * (int)sizeof(float));
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if(gidx < res_cols && gidy < res_rows)
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{
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@ -152,13 +143,14 @@ __kernel void matchTemplate_Naive_SQDIFF(__global const uchar * img,int img_step
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for(j = 0; j < tpl_cols; j ++)
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#pragma unroll
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for (int c = 0; c < CN; c++)
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{
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delta = (float)(img_ptr[j*CN+c] - tpl_ptr[j*CN+c]);
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sum += delta*delta;
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}
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}
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__global float * result = (__global float *)(res)+res_idx;
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__global float * result = (__global float *)(res+res_idx);
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*result = sum;
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}
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}
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@ -172,10 +164,8 @@ __kernel void matchTemplate_SQDIFF_NORMED ( __global const uchar * img_sqsums, i
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img_sqsums_step /= sizeof(float);
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img_sqsums_offset /= sizeof(float);
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res_step /= sizeof(float);
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res_offset /= sizeof(float);
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int res_idx = mad24(gidy, res_step, res_offset + gidx);
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int res_idx = mad24(gidy, res_step, res_offset + gidx * (int)sizeof(float));
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if(gidx < res_cols && gidy < res_rows)
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{
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@ -184,7 +174,7 @@ __kernel void matchTemplate_SQDIFF_NORMED ( __global const uchar * img_sqsums, i
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(sqsum[SQSUMS_PTR(tpl_cols, tpl_rows)] - sqsum[SQSUMS_PTR(tpl_cols, 0)]) -
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(sqsum[SQSUMS_PTR(0, tpl_rows)] - sqsum[SQSUMS_PTR(0, 0)]));
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__global float * result = (__global float *)(res)+res_idx;
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__global float * result = (__global float *)(res+res_idx);
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*result = normAcc_SQDIFF(image_sqsum_ - 2.f * result[0] + tpl_sqsum, sqrt(image_sqsum_ * tpl_sqsum));
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}
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@ -201,10 +191,8 @@ __kernel void matchTemplate_Prepared_CCOEFF_C1 (__global const uchar * img_sums,
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img_sums_step /= ELEM_SIZE;
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img_sums_offset /= ELEM_SIZE;
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res_step /= sizeof(float);
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res_offset /= sizeof(float);
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int res_idx = mad24(gidy, res_step, res_offset + gidx);
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int res_idx = mad24(gidy, res_step, res_offset + gidx * (int)sizeof(float));
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float image_sum_ = 0;
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if(gidx < res_cols && gidy < res_rows)
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@ -214,7 +202,7 @@ __kernel void matchTemplate_Prepared_CCOEFF_C1 (__global const uchar * img_sums,
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image_sum_ += (float)((sum[SUMS_PTR(tpl_cols, tpl_rows)] - sum[SUMS_PTR(tpl_cols, 0)])-
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(sum[SUMS_PTR(0, tpl_rows)] - sum[SUMS_PTR(0, 0)])) * tpl_sum;
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__global float * result = (__global float *)(res)+res_idx;
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__global float * result = (__global float *)(res+res_idx);
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*result -= image_sum_;
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}
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}
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@ -228,10 +216,8 @@ __kernel void matchTemplate_Prepared_CCOEFF_C2 (__global const uchar * img_sums,
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img_sums_step /= ELEM_SIZE;
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img_sums_offset /= ELEM_SIZE;
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res_step /= sizeof(float);
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res_offset /= sizeof(float);
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int res_idx = mad24(gidy, res_step, res_offset + gidx);
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int res_idx = mad24(gidy, res_step, res_offset + gidx * (int)sizeof(float));
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float image_sum_ = 0;
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if(gidx < res_cols && gidy < res_rows)
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@ -241,37 +227,40 @@ __kernel void matchTemplate_Prepared_CCOEFF_C2 (__global const uchar * img_sums,
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image_sum_ += tpl_sum_0 * (float)((sum[SUMS_PTR(tpl_cols, tpl_rows)] - sum[SUMS_PTR(tpl_cols, 0)]) -(sum[SUMS_PTR(0, tpl_rows)] - sum[SUMS_PTR(0, 0)]));
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image_sum_ += tpl_sum_1 * (float)((sum[SUMS_PTR(tpl_cols, tpl_rows)+1] - sum[SUMS_PTR(tpl_cols, 0)+1])-(sum[SUMS_PTR(0, tpl_rows)+1] - sum[SUMS_PTR(0, 0)+1]));
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__global float * result = (__global float *)(res)+res_idx;
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__global float * result = (__global float *)(res+res_idx);
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*result -= image_sum_;
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}
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}
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__kernel void matchTemplate_Prepared_CCOEFF_C4 (__global const uchar * img_sums, int img_sums_step, int img_sums_offset,
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__global uchar * res, int res_step, int res_offset, int res_rows, int res_cols,
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int tpl_rows, int tpl_cols, float tpl_sum_0,float tpl_sum_1,float tpl_sum_2,float tpl_sum_3)
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__global uchar * res, int res_step, int res_offset, int res_rows, int res_cols,
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int tpl_rows, int tpl_cols, float tpl_sum_0,float tpl_sum_1,float tpl_sum_2,float tpl_sum_3)
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{
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int gidx = get_global_id(0);
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int gidy = get_global_id(1);
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img_sums_step /= ELEM_SIZE;
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img_sums_offset /= ELEM_SIZE;
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res_step /= sizeof(float);
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res_offset /= sizeof(float);
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int res_idx = mad24(gidy, res_step, res_offset + gidx);
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int res_idx = mad24(gidy, res_step, res_offset + gidx * (int)sizeof(float));
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float image_sum_ = 0;
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if(gidx < res_cols && gidy < res_rows)
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{
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__global ELEM_TYPE* sum = (__global ELEM_TYPE*)(img_sums);
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image_sum_ += tpl_sum_0 * (float)((sum[SUMS_PTR(tpl_cols, tpl_rows)] - sum[SUMS_PTR(tpl_cols, 0)]) -(sum[SUMS_PTR(0, tpl_rows)] - sum[SUMS_PTR(0, 0)]));
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image_sum_ += tpl_sum_1 * (float)((sum[SUMS_PTR(tpl_cols, tpl_rows)+1] - sum[SUMS_PTR(tpl_cols, 0)+1])-(sum[SUMS_PTR(0, tpl_rows)+1] - sum[SUMS_PTR(0, 0)+1]));
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image_sum_ += tpl_sum_2 * (float)((sum[SUMS_PTR(tpl_cols, tpl_rows)+2] - sum[SUMS_PTR(tpl_cols, 0)+2])-(sum[SUMS_PTR(0, tpl_rows)+2] - sum[SUMS_PTR(0, 0)+2]));
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image_sum_ += tpl_sum_3 * (float)((sum[SUMS_PTR(tpl_cols, tpl_rows)+3] - sum[SUMS_PTR(tpl_cols, 0)+3])-(sum[SUMS_PTR(0, tpl_rows)+3] - sum[SUMS_PTR(0, 0)+3]));
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int c_r = SUMS_PTR(tpl_cols, tpl_rows);
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int c_o = SUMS_PTR(tpl_cols, 0);
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int o_r = SUMS_PTR(0,tpl_rows);
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int oo = SUMS_PTR(0, 0);
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__global float * result = (__global float *)(res)+res_idx;
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image_sum_ += tpl_sum_0 * (float)((sum[c_r] - sum[c_o]) -(sum[o_r] - sum[oo]));
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image_sum_ += tpl_sum_1 * (float)((sum[c_r+1] - sum[c_o+1])-(sum[o_r+1] - sum[oo+1]));
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image_sum_ += tpl_sum_2 * (float)((sum[c_r+2] - sum[c_o+2])-(sum[o_r+2] - sum[oo+2]));
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image_sum_ += tpl_sum_3 * (float)((sum[c_r+3] - sum[c_o+3])-(sum[o_r+3] - sum[oo+3]));
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__global float * result = (__global float *)(res+res_idx);
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*result -= image_sum_;
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}
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@ -279,7 +268,7 @@ __kernel void matchTemplate_Prepared_CCOEFF_C4 (__global const uchar * img_sums,
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__kernel void matchTemplate_CCOEFF_NORMED_C1 (__global const uchar * img_sums, int img_sums_step, int img_sums_offset,
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__global const uchar * img_sqsums, int img_sqsums_step, int img_sqsums_offset,
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__global float * res, int res_step, int res_offset, int res_rows, int res_cols,
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__global uchar * res, int res_step, int res_offset, int res_rows, int res_cols,
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int t_rows, int t_cols, float weight, float tpl_sum, float tpl_sqsum)
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{
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int gidx = get_global_id(0);
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@ -289,11 +278,8 @@ __kernel void matchTemplate_CCOEFF_NORMED_C1 (__global const uchar * img_sums, i
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img_sums_step /= ELEM_SIZE;
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img_sqsums_step /= sizeof(float);
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img_sqsums_offset /= sizeof(float);
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res_step /= sizeof(*res);
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res_offset /= sizeof(*res);
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int res_idx = mad24(gidy, res_step, res_offset + gidx);
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int res_idx = mad24(gidy, res_step, res_offset + gidx * (int)sizeof(float));
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if(gidx < res_cols && gidy < res_rows)
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{
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@ -306,7 +292,7 @@ __kernel void matchTemplate_CCOEFF_NORMED_C1 (__global const uchar * img_sums, i
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float image_sqsum_ = (float)((sqsum[SQSUMS_PTR(t_cols, t_rows)] - sqsum[SQSUMS_PTR(t_cols, 0)]) -
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(sqsum[SQSUMS_PTR(0, t_rows)] - sqsum[SQSUMS_PTR(0, 0)]));
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__global float * result = (__global float *)(res)+res_idx;
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__global float * result = (__global float *)(res+res_idx);
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*result = normAcc((*result) - image_sum_ * tpl_sum,
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sqrt(tpl_sqsum * (image_sqsum_ - weight * image_sum_ * image_sum_)));
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@ -315,7 +301,7 @@ __kernel void matchTemplate_CCOEFF_NORMED_C1 (__global const uchar * img_sums, i
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__kernel void matchTemplate_CCOEFF_NORMED_C2 (__global const uchar * img_sums, int img_sums_step, int img_sums_offset,
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__global const uchar * img_sqsums, int img_sqsums_step, int img_sqsums_offset,
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__global float * res, int res_step, int res_offset, int res_rows, int res_cols,
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__global uchar * res, int res_step, int res_offset, int res_rows, int res_cols,
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int t_rows, int t_cols, float weight, float tpl_sum_0, float tpl_sum_1, float tpl_sqsum)
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{
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int gidx = get_global_id(0);
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@ -325,11 +311,8 @@ __kernel void matchTemplate_CCOEFF_NORMED_C2 (__global const uchar * img_sums, i
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img_sums_step /= ELEM_SIZE;
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img_sqsums_step /= sizeof(float);
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img_sqsums_offset /= sizeof(float);
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res_step /= sizeof(*res);
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res_offset /= sizeof(*res);
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int res_idx = mad24(gidy, res_step, res_offset + gidx);
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int res_idx = mad24(gidy, res_step, res_offset + gidx * (int)sizeof(float));
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float sum_[2];
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float sqsum_[2];
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@ -342,22 +325,22 @@ __kernel void matchTemplate_CCOEFF_NORMED_C2 (__global const uchar * img_sums, i
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sum_[0] = (float)((sum[SUMS_PTR(t_cols, t_rows)] - sum[SUMS_PTR(t_cols, 0)])-(sum[SUMS_PTR(0, t_rows)] - sum[SUMS_PTR(0, 0)]));
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sum_[1] = (float)((sum[SUMS_PTR(t_cols, t_rows)+1] - sum[SUMS_PTR(t_cols, 0)+1])-(sum[SUMS_PTR(0, t_rows)+1] - sum[SUMS_PTR(0, 0)+1]));
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sqsum_[0] = (float)((sqsum[SQSUMS(t_cols, t_rows)] - sqsum[SQSUMS(t_cols, 0)])-(sqsum[SQSUMS(0, t_rows)] - sqsum[SQSUMS(0, 0)]));
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sqsum_[1] = (float)((sqsum[SQSUMS(t_cols, t_rows)+1] - sqsum[SQSUMS(t_cols, 0)+1])-(sqsum[SQSUMS(0, t_rows)+1] - sqsum[SQSUMS(0, 0)+1]));
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sqsum_[0] = (float)((sqsum[SQSUMS_PTR(t_cols, t_rows)] - sqsum[SQSUMS_PTR(t_cols, 0)])-(sqsum[SQSUMS_PTR(0, t_rows)] - sqsum[SQSUMS_PTR(0, 0)]));
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sqsum_[1] = (float)((sqsum[SQSUMS_PTR(t_cols, t_rows)+1] - sqsum[SQSUMS_PTR(t_cols, 0)+1])-(sqsum[SQSUMS_PTR(0, t_rows)+1] - sqsum[SQSUMS_PTR(0, 0)+1]));
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float num = sum_[0]*tpl_sum_0 + sum_[1]*tpl_sum_1;
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float denum = sqrt( tpl_sqsum * (sqsum_[0] - weight * sum_[0]* sum_[0] +
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sqsum_[1] - weight * sum_[1]* sum_[1]));
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__global float * result = (__global float *)(res)+res_idx;
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__global float * result = (__global float *)(res+res_idx);
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*result = normAcc((*result) - num, denum);
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}
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}
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__kernel void matchTemplate_CCOEFF_NORMED_C4 (__global const uchar * img_sums, int img_sums_step, int img_sums_offset,
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__global const uchar * img_sqsums, int img_sqsums_step, int img_sqsums_offset,
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__global float * res, int res_step, int res_offset, int res_rows, int res_cols,
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__global uchar * res, int res_step, int res_offset, int res_rows, int res_cols,
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int t_rows, int t_cols, float weight,
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float tpl_sum_0,float tpl_sum_1,float tpl_sum_2,float tpl_sum_3,
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float tpl_sqsum)
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@ -369,11 +352,8 @@ __kernel void matchTemplate_CCOEFF_NORMED_C4 (__global const uchar * img_sums, i
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img_sums_step /= ELEM_SIZE;
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img_sqsums_step /= sizeof(float);
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img_sqsums_offset /= sizeof(float);
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res_step /= sizeof(*res);
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res_offset /= sizeof(*res);
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int res_idx = mad24(gidy, res_step, res_offset + gidx);
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int res_idx = mad24(gidy, res_step, res_offset + gidx * (int)sizeof(float));
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float sum_[4];
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float sqsum_[4];
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@ -383,15 +363,25 @@ __kernel void matchTemplate_CCOEFF_NORMED_C4 (__global const uchar * img_sums, i
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__global ELEM_TYPE* sum = (__global ELEM_TYPE*)(img_sums);
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__global float * sqsum = (__global float*)(img_sqsums);
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sum_[0] = (float)((sum[SUMS_PTR(t_cols, t_rows)] - sum[SUMS_PTR(t_cols, 0)])-(sum[SUMS_PTR(0, t_rows)] - sum[SUMS_PTR(0, 0)]));
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sum_[1] = (float)((sum[SUMS_PTR(t_cols, t_rows)+1] - sum[SUMS_PTR(t_cols, 0)+1])-(sum[SUMS_PTR(0, t_rows)+1] - sum[SUMS_PTR(0, 0)+1]));
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sum_[2] = (float)((sum[SUMS_PTR(t_cols, t_rows)+2] - sum[SUMS_PTR(t_cols, 0)+2])-(sum[SUMS_PTR(0, t_rows)+2] - sum[SUMS_PTR(0, 0)+2]));
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sum_[3] = (float)((sum[SUMS_PTR(t_cols, t_rows)+3] - sum[SUMS_PTR(t_cols, 0)+3])-(sum[SUMS_PTR(0, t_rows)+3] - sum[SUMS_PTR(0, 0)+3]));
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int c_r = SUMS_PTR(t_cols, t_rows);
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int c_o = SUMS_PTR(t_cols, 0);
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int o_r = SUMS_PTR(0, t_rows);
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int o_o = SUMS_PTR(0, 0);
|
||||
|
||||
sqsum_[0] = (float)((sqsum[SQSUMS(t_cols, t_rows)] - sqsum[SQSUMS(t_cols, 0)])-(sqsum[SQSUMS(0, t_rows)] - sqsum[SQSUMS(0, 0)]));
|
||||
sqsum_[1] = (float)((sqsum[SQSUMS(t_cols, t_rows)+1] - sqsum[SQSUMS(t_cols, 0)+1])-(sqsum[SQSUMS(0, t_rows)+1] - sqsum[SQSUMS(0, 0)+1]));
|
||||
sqsum_[2] = (float)((sqsum[SQSUMS(t_cols, t_rows)+2] - sqsum[SQSUMS(t_cols, 0)+2])-(sqsum[SQSUMS(0, t_rows)+2] - sqsum[SQSUMS(0, 0)+2]));
|
||||
sqsum_[3] = (float)((sqsum[SQSUMS(t_cols, t_rows)+3] - sqsum[SQSUMS(t_cols, 0)+3])-(sqsum[SQSUMS(0, t_rows)+3] - sqsum[SQSUMS(0, 0)+3]));
|
||||
sum_[0] = (float)((sum[c_r] - sum[c_o]) -(sum[o_r] - sum[o_o ]));
|
||||
sum_[1] = (float)((sum[c_r+1] - sum[c_o+1])-(sum[o_r+1] - sum[o_o +1]));
|
||||
sum_[2] = (float)((sum[c_r+2] - sum[c_o+2])-(sum[o_r+2] - sum[o_o +2]));
|
||||
sum_[3] = (float)((sum[c_r+3] - sum[c_o+3])-(sum[o_r+3] - sum[o_o +3]));
|
||||
|
||||
c_r = SQSUMS_PTR(t_cols, t_rows);
|
||||
c_o = SQSUMS_PTR(t_cols, 0);
|
||||
o_r = SQSUMS_PTR(0, t_rows);
|
||||
o_o = SQSUMS_PTR(0, 0);
|
||||
|
||||
sqsum_[0] = (float)((sqsum[c_r] - sqsum[c_o]) -(sqsum[o_r] - sqsum[o_o]));
|
||||
sqsum_[1] = (float)((sqsum[c_r+1] - sqsum[c_o+1])-(sqsum[o_r+1] - sqsum[o_o+1]));
|
||||
sqsum_[2] = (float)((sqsum[c_r+2] - sqsum[c_o+2])-(sqsum[o_r+2] - sqsum[o_o+2]));
|
||||
sqsum_[3] = (float)((sqsum[c_r+3] - sqsum[c_o+3])-(sqsum[o_r+3] - sqsum[o_o+3]));
|
||||
|
||||
float num = sum_[0]*tpl_sum_0 + sum_[1]*tpl_sum_1 + sum_[2]*tpl_sum_2 + sum_[3]*tpl_sum_3;
|
||||
|
||||
@ -401,7 +391,7 @@ __kernel void matchTemplate_CCOEFF_NORMED_C4 (__global const uchar * img_sums, i
|
||||
sqsum_[2] - weight * sum_[2]* sum_[2] +
|
||||
sqsum_[3] - weight * sum_[3]* sum_[3] ));
|
||||
|
||||
__global float * result = (__global float *)(res)+res_idx;
|
||||
__global float * result = (__global float *)(res+res_idx);
|
||||
*result = normAcc((*result) - num, denum);
|
||||
}
|
||||
}
|
||||
@ -101,9 +101,8 @@ namespace cv
|
||||
result = _result.getUMat();
|
||||
|
||||
size_t globalsize[2] = {result.cols, result.rows};
|
||||
size_t localsize[2] = {16, 16};
|
||||
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image), ocl::KernelArg::ReadOnly(templ), ocl::KernelArg::WriteOnly(result)).run(2,globalsize,localsize,false);
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image), ocl::KernelArg::ReadOnly(templ), ocl::KernelArg::WriteOnly(result)).run(2,globalsize,NULL,false);
|
||||
}
|
||||
|
||||
static bool matchTemplate_CCORR_NORMED(InputArray _image, InputArray _templ, OutputArray _result)
|
||||
@ -124,24 +123,18 @@ namespace cv
|
||||
_result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
|
||||
result = _result.getUMat();
|
||||
|
||||
UMat temp, image_sums, image_sqsums;
|
||||
integral(image.reshape(1), image_sums, temp);
|
||||
UMat image_sums, image_sqsums;
|
||||
integral(image.reshape(1), image_sums, image_sqsums, CV_32F, CV_32F);
|
||||
|
||||
if(temp.depth() == CV_64F)
|
||||
temp.convertTo(image_sqsums, CV_32F);
|
||||
else
|
||||
image_sqsums = temp;
|
||||
|
||||
UMat templ_resh;
|
||||
UMat templ_resh, temp;
|
||||
templ.reshape(1).convertTo(templ_resh, CV_32F);
|
||||
|
||||
multiply(templ_resh, templ_resh, temp);
|
||||
unsigned long long templ_sqsum = (unsigned long long)sum(temp)[0];
|
||||
|
||||
size_t globalsize[2] = {result.cols, result.rows};
|
||||
size_t localsize[2] = {16, 16};
|
||||
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sqsums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, templ_sqsum).run(2,globalsize,localsize,false);
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sqsums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, templ_sqsum).run(2,globalsize,NULL,false);
|
||||
}
|
||||
|
||||
//////////////////////////////////////SQDIFF//////////////////////////////////////////////////////////////
|
||||
@ -173,9 +166,8 @@ namespace cv
|
||||
result = _result.getUMat();
|
||||
|
||||
size_t globalsize[2] = {result.cols, result.rows};
|
||||
size_t localsize[2] = {16, 16};
|
||||
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image), ocl::KernelArg::ReadOnly(templ), ocl::KernelArg::WriteOnly(result)).run(2,globalsize,localsize,false);
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image), ocl::KernelArg::ReadOnly(templ), ocl::KernelArg::WriteOnly(result)).run(2,globalsize,NULL,false);
|
||||
}
|
||||
|
||||
static bool matchTemplate_SQDIFF_NORMED (InputArray _image, InputArray _templ, OutputArray _result)
|
||||
@ -196,24 +188,18 @@ namespace cv
|
||||
_result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
|
||||
result = _result.getUMat();
|
||||
|
||||
UMat temp, image_sums, image_sqsums;
|
||||
integral(image.reshape(1), image_sums, temp);
|
||||
UMat image_sums, image_sqsums;
|
||||
integral(image.reshape(1), image_sums, image_sqsums, CV_32F, CV_32F);
|
||||
|
||||
if(temp.depth() == CV_64F)
|
||||
temp.convertTo(image_sqsums, CV_32F);
|
||||
else
|
||||
image_sqsums = temp;
|
||||
|
||||
UMat templ_resh;
|
||||
UMat temp, templ_resh;
|
||||
templ.reshape(1).convertTo(templ_resh, CV_32F);
|
||||
|
||||
multiply(templ_resh, templ_resh, temp);
|
||||
unsigned long long templ_sqsum = (unsigned long long)sum(temp)[0];
|
||||
|
||||
size_t globalsize[2] = {result.cols, result.rows};
|
||||
size_t localsize[2] = {16, 16};
|
||||
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sqsums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, templ_sqsum).run(2,globalsize,localsize,false);
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sqsums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, templ_sqsum).run(2,globalsize,NULL,false);
|
||||
}
|
||||
|
||||
/////////////////////////////////////CCOEFF/////////////////////////////////////////////////////////////////
|
||||
@ -242,17 +228,16 @@ namespace cv
|
||||
return false;
|
||||
|
||||
UMat templ = _templ.getUMat(), result;
|
||||
int image_rows = _image.size().height, image_cols = _image.size().width;
|
||||
_result.create(image_rows - templ.rows + 1, image_cols - templ.cols + 1, CV_32F);
|
||||
Size size = _image.size();
|
||||
_result.create(size.height - templ.rows + 1, size.width - templ.cols + 1, CV_32F);
|
||||
result = _result.getUMat();
|
||||
|
||||
size_t globalsize[2] = {result.cols, result.rows};
|
||||
size_t localsize[2] = {16, 16};
|
||||
|
||||
if (cn==1)
|
||||
{
|
||||
float templ_sum = (float)sum(_templ)[0]/ _templ.size().area();
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, templ_sum).run(2,globalsize,localsize,false);
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, templ_sum).run(2,globalsize,NULL,false);
|
||||
}
|
||||
else
|
||||
{
|
||||
@ -260,10 +245,10 @@ namespace cv
|
||||
templ_sum = sum(templ)/ templ.size().area();
|
||||
if (cn==2)
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols,
|
||||
templ_sum[0],templ_sum[1]).run(2,globalsize,localsize,false);
|
||||
templ_sum[0],templ_sum[1]).run(2,globalsize,NULL,false);
|
||||
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols,
|
||||
templ_sum[0],templ_sum[1],templ_sum[2],templ_sum[3]).run(2,globalsize,localsize,false);
|
||||
templ_sum[0],templ_sum[1],templ_sum[2],templ_sum[3]).run(2,globalsize,NULL,false);
|
||||
}
|
||||
}
|
||||
|
||||
@ -279,7 +264,7 @@ namespace cv
|
||||
const char * kernelName;
|
||||
|
||||
UMat temp, image_sums, image_sqsums;
|
||||
integral(_image,image_sums, temp);
|
||||
integral(_image,image_sums, image_sqsums, CV_32F, CV_32F);
|
||||
|
||||
int type = image_sums.type();
|
||||
int depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
|
||||
@ -302,13 +287,7 @@ namespace cv
|
||||
_result.create(image_rows - templ.rows + 1, image_cols - templ.cols + 1, CV_32F);
|
||||
result = _result.getUMat();
|
||||
|
||||
if(temp.depth() == CV_64F)
|
||||
temp.convertTo(image_sqsums, CV_32F);
|
||||
else
|
||||
image_sqsums = temp;
|
||||
|
||||
size_t globalsize[2] = {result.cols, result.rows};
|
||||
size_t localsize[2] = {16, 16};
|
||||
|
||||
float scale = 1.f / templ.size().area();
|
||||
|
||||
@ -330,7 +309,7 @@ namespace cv
|
||||
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums),ocl::KernelArg::ReadOnlyNoSize(image_sqsums),
|
||||
ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, scale, templ_sum, templ_sqsum)
|
||||
.run(2,globalsize,localsize,false);
|
||||
.run(2,globalsize,NULL,false);
|
||||
}
|
||||
else
|
||||
{
|
||||
@ -360,12 +339,12 @@ namespace cv
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadOnlyNoSize(image_sqsums),
|
||||
ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, scale,
|
||||
templ_sum[0],templ_sum[1], templ_sqsum_sum)
|
||||
.run(2,globalsize,localsize,false);
|
||||
.run(2,globalsize,NULL,false);
|
||||
|
||||
return k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadOnlyNoSize(image_sqsums),
|
||||
ocl::KernelArg::WriteOnly(result), templ.rows, templ.cols, scale,
|
||||
templ_sum[0],templ_sum[1],templ_sum[2],templ_sum[3], templ_sqsum_sum)
|
||||
.run(2,globalsize,localsize,false);
|
||||
.run(2,globalsize,NULL,false);
|
||||
}
|
||||
|
||||
}
|
||||
@ -374,10 +353,10 @@ namespace cv
|
||||
|
||||
static bool ocl_matchTemplate( InputArray _img, InputArray _templ, OutputArray _result, int method)
|
||||
{
|
||||
int type = _img.type();
|
||||
int cn = CV_MAT_CN(type);
|
||||
int cn = CV_MAT_CN(_img.type());
|
||||
|
||||
CV_Assert( cn == _templ.channels() && cn!=3 && cn<=4);
|
||||
if (cn == 3 || cn > 4)
|
||||
return false;
|
||||
|
||||
typedef bool (*Caller)(InputArray _img, InputArray _templ, OutputArray _result);
|
||||
|
||||
@ -588,13 +567,15 @@ void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result,
|
||||
|
||||
CV_Assert( (_img.depth() == CV_8U || _img.depth() == CV_32F) && _img.type() == _templ.type() );
|
||||
|
||||
CV_Assert(_img.size().height >= _templ.size().height && _img.size().width >= _templ.size().width);
|
||||
|
||||
CV_Assert(_img.dims() <= 2);
|
||||
|
||||
bool swapNotNeed = (_img.size().height >= _templ.size().height && _img.size().width >= _templ.size().width);
|
||||
if (!swapNotNeed)
|
||||
CV_Assert(_img.size().height <= _templ.size().height && _img.size().width <= _templ.size().width);
|
||||
|
||||
bool use_opencl = ocl::useOpenCL() && _result.isUMat();
|
||||
if ( use_opencl && ocl_matchTemplate(_img,_templ,_result,method))
|
||||
return;
|
||||
if ( use_opencl && (swapNotNeed ? ocl_matchTemplate(_img,_templ,_result,method) : ocl_matchTemplate(_templ,_img,_result,method)))
|
||||
return;
|
||||
|
||||
int numType = method == CV_TM_CCORR || method == CV_TM_CCORR_NORMED ? 0 :
|
||||
method == CV_TM_CCOEFF || method == CV_TM_CCOEFF_NORMED ? 1 : 2;
|
||||
@ -603,7 +584,7 @@ void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result,
|
||||
method == CV_TM_CCOEFF_NORMED;
|
||||
|
||||
Mat img = _img.getMat(), templ = _templ.getMat();
|
||||
if( img.rows < templ.rows || img.cols < templ.cols )
|
||||
if(!swapNotNeed )
|
||||
std::swap(img, templ);
|
||||
|
||||
Size corrSize(img.cols - templ.cols + 1, img.rows - templ.rows + 1);
|
||||
|
||||
Loading…
Reference in New Issue
Block a user