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Merge pull request #13329 from elatkin:el/gapi_perf_medblur
GAPI (fluid): Median blur optimization (#13329) * GAPI (fluid): Median blur optimization: reference 3x3 * GAPI (fluid): Median blur optimization: CPU dispatcher * GAPI (fluid): Median blur optimization: manual CV_SIMD
This commit is contained in:
Evgeny Latkin
Alexander Alekhin
parent
6374b99a1a
commit
ab430b8c87
@ -1442,7 +1442,9 @@ static void run_medianblur( Buffer& dst,
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const View & src,
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int ksize)
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{
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static const int kmax = 9;
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static_assert(std::is_same<DST, SRC>::value, "unsupported combination of types");
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constexpr int kmax = 9;
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GAPI_Assert(ksize <= kmax);
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const SRC *in[ kmax ];
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@ -1460,24 +1462,33 @@ static void run_medianblur( Buffer& dst,
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int width = dst.length();
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int chan = dst.meta().chan;
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for (int w=0; w < width; w++)
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// optimized: if 3x3
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if (3 == ksize)
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{
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// TODO: make this cycle innermost
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for (int c=0; c < chan; c++)
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run_medblur3x3_impl(out, in, width, chan);
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return;
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}
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// reference: any ksize
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int length = width * chan;
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int klength = ksize * ksize;
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int klenhalf = klength / 2;
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for (int l=0; l < length; l++)
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{
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SRC neighbours[kmax * kmax];
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for (int i=0; i < ksize; i++)
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for (int j=0; j < ksize; j++)
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{
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SRC neighbours[kmax * kmax];
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for (int i=0; i < ksize; i++)
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for (int j=0; j < ksize; j++)
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{
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neighbours[i*ksize + j] = in[i][(w + j - border)*chan + c];
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}
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int length = ksize * ksize;
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std::nth_element(neighbours, neighbours + length/2, neighbours + length);
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out[w*chan + c] = saturate<DST>(neighbours[length/2], rintf);
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neighbours[i*ksize + j] = in[i][l + (j - border)*chan];
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}
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std::nth_element(neighbours, neighbours + klenhalf, neighbours + klength);
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out[l] = saturate<DST>(neighbours[klenhalf], rintf);
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}
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}
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@ -134,6 +134,26 @@ RUN_MORPHOLOGY3X3_IMPL( float)
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#undef RUN_MORPHOLOGY3X3_IMPL
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//---------------------------
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//
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// Fluid kernels: Median blur
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//
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//---------------------------
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#define RUN_MEDBLUR3X3_IMPL(T) \
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void run_medblur3x3_impl(T out[], const T *in[], int width, int chan) \
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{ \
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CV_CPU_DISPATCH(run_medblur3x3_impl, (out, in, width, chan), \
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CV_CPU_DISPATCH_MODES_ALL); \
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}
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RUN_MEDBLUR3X3_IMPL(uchar )
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RUN_MEDBLUR3X3_IMPL(ushort)
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RUN_MEDBLUR3X3_IMPL( short)
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RUN_MEDBLUR3X3_IMPL( float)
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#undef RUN_MEDBLUR3X3_IMPL
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} // namespace fliud
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} // namespace gapi
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} // namespace cv
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@ -99,6 +99,22 @@ RUN_MORPHOLOGY3X3_IMPL( float)
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#undef RUN_MORPHOLOGY3X3_IMPL
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//---------------------------
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//
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// Fluid kernels: Median blur
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//
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//---------------------------
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#define RUN_MEDBLUR3X3_IMPL(T) \
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void run_medblur3x3_impl(T out[], const T *in[], int width, int chan);
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RUN_MEDBLUR3X3_IMPL(uchar )
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RUN_MEDBLUR3X3_IMPL(ushort)
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RUN_MEDBLUR3X3_IMPL( short)
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RUN_MEDBLUR3X3_IMPL( float)
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#undef RUN_MEDBLUR3X3_IMPL
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} // namespace fluid
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} // namespace gapi
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} // namespace cv
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@ -117,6 +117,22 @@ RUN_MORPHOLOGY3X3_IMPL( float)
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#undef RUN_MORPHOLOGY3X3_IMPL
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//---------------------------
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//
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// Fluid kernels: Median blur
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//
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//---------------------------
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#define RUN_MEDBLUR3X3_IMPL(T) \
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void run_medblur3x3_impl(T out[], const T *in[], int width, int chan);
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RUN_MEDBLUR3X3_IMPL(uchar )
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RUN_MEDBLUR3X3_IMPL(ushort)
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RUN_MEDBLUR3X3_IMPL( short)
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RUN_MEDBLUR3X3_IMPL( float)
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#undef RUN_MEDBLUR3X3_IMPL
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//----------------------------------------------------------------------
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#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
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@ -1580,6 +1596,180 @@ RUN_MORPHOLOGY3X3_IMPL( float)
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#undef RUN_MORPHOLOGY3X3_IMPL
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//---------------------------
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//
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// Fluid kernels: Median blur
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//
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//---------------------------
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template<typename T>
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static void run_medblur3x3_reference(T out[], const T *in[], int width, int chan)
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{
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constexpr int ksize = 3;
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constexpr int border = (ksize - 1) / 2;
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const int length = width * chan;
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const int shift = border * chan;
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for (int l=0; l < length; l++)
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{
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T t[3][3];
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// neighbourhood 3x3
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t[0][0] = in[0][l - shift]; t[0][1] = in[0][l]; t[0][2] = in[0][l + shift];
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t[1][0] = in[1][l - shift]; t[1][1] = in[1][l]; t[1][2] = in[1][l + shift];
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t[2][0] = in[2][l - shift]; t[2][1] = in[2][l]; t[2][2] = in[2][l + shift];
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// sort 2 values
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auto sort = [](T& a, T& b)
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{
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T u=a, v=b;
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a = (std::min)(u, v);
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b = (std::max)(u, v);
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};
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// horizontal: 3-elements bubble-sort per each row
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sort(t[0][0], t[0][1]); sort(t[0][1], t[0][2]); sort(t[0][0], t[0][1]);
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sort(t[1][0], t[1][1]); sort(t[1][1], t[1][2]); sort(t[1][0], t[1][1]);
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sort(t[2][0], t[2][1]); sort(t[2][1], t[2][2]); sort(t[2][0], t[2][1]);
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// vertical: columns bubble-sort (although partial)
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sort(t[0][0], t[1][0]); sort(t[0][1], t[1][1]); /*sort(t[0][2], t[1][2]);*/
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sort(t[1][0], t[2][0]); sort(t[1][1], t[2][1]); sort(t[1][2], t[2][2]);
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/*sort(t[0][0], t[1][0]);*/ sort(t[0][1], t[1][1]); sort(t[0][2], t[1][2]);
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// diagonal: bubble-sort (in opposite order!)
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sort(t[1][1], t[0][2]); sort(t[2][0], t[1][1]); sort(t[1][1], t[0][2]);
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out[l] = t[1][1];
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}
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}
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#if CV_SIMD
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template<typename VT, typename T>
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static void run_medblur3x3_simd(T out[], const T *in[], int width, int chan)
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{
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constexpr int ksize = 3;
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constexpr int border = (ksize - 1) / 2;
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const int length = width * chan;
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const int shift = border * chan;
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for (int l=0; l < length;)
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{
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constexpr int nlanes = VT::nlanes;
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// main part of output row
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for (; l <= length - nlanes; l += nlanes)
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{
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VT t00, t01, t02, t10, t11, t12, t20, t21, t22;
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// neighbourhood 3x3
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t00 = vx_load(&in[0][l - shift]);
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t01 = vx_load(&in[0][l ]);
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t02 = vx_load(&in[0][l + shift]);
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t10 = vx_load(&in[1][l - shift]);
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t11 = vx_load(&in[1][l ]);
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t12 = vx_load(&in[1][l + shift]);
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t20 = vx_load(&in[2][l - shift]);
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t21 = vx_load(&in[2][l ]);
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t22 = vx_load(&in[2][l + shift]);
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// sort 2 values
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auto sort = [](VT& a, VT& b)
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{
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VT u=a, v=b;
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a = v_min(u, v);
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b = v_max(u, v);
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};
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// horizontal: 3-elements bubble-sort per each row
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sort(t00, t01); sort(t01, t02); sort(t00, t01);
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sort(t10, t11); sort(t11, t12); sort(t10, t11);
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sort(t20, t21); sort(t21, t22); sort(t20, t21);
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// vertical: columns bubble-sort (although partial)
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sort(t00, t10); sort(t01, t11); /*sort(t02, t12);*/
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sort(t10, t20); sort(t11, t21); sort(t12, t22);
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/*sort(t00, t10);*/ sort(t01, t11); sort(t02, t12);
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// diagonal: bubble-sort (in opposite order!)
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sort(t11, t02); sort(t20, t11); sort(t11, t02);
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v_store(&out[l], t11);
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}
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// tail (if any)
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if (l < length)
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{
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GAPI_DbgAssert(length >= nlanes);
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l = length - nlanes;
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}
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}
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}
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#endif
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template<typename T>
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static void run_medblur3x3_code(T out[], const T *in[], int width, int chan)
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{
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#if CV_SIMD
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int length = width * chan;
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// length variable may be unused if types do not match at 'if' statements below
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(void) length;
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if (std::is_same<T, float>::value && length >= v_float32::nlanes)
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{
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run_medblur3x3_simd<v_float32>(reinterpret_cast<float*>(out),
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reinterpret_cast<const float**>(in),
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width, chan);
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return;
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}
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if (std::is_same<T, short>::value && length >= v_int16::nlanes)
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{
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run_medblur3x3_simd<v_int16>(reinterpret_cast<short*>(out),
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reinterpret_cast<const short**>(in),
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width, chan);
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return;
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}
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if (std::is_same<T, ushort>::value && length >= v_uint16::nlanes)
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{
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run_medblur3x3_simd<v_uint16>(reinterpret_cast<ushort*>(out),
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reinterpret_cast<const ushort**>(in),
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width, chan);
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return;
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}
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if (std::is_same<T, uchar>::value && length >= v_uint8::nlanes)
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{
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run_medblur3x3_simd<v_uint8>(reinterpret_cast<uchar*>(out),
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reinterpret_cast<const uchar**>(in),
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width, chan);
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return;
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}
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#endif
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run_medblur3x3_reference(out, in, width, chan);
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}
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#define RUN_MEDBLUR3X3_IMPL(T) \
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void run_medblur3x3_impl(T out[], const T *in[], int width, int chan) \
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{ \
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run_medblur3x3_code(out, in, width, chan); \
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}
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RUN_MEDBLUR3X3_IMPL(uchar )
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RUN_MEDBLUR3X3_IMPL(ushort)
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RUN_MEDBLUR3X3_IMPL( short)
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RUN_MEDBLUR3X3_IMPL( float)
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#undef RUN_MEDBLUR3X3_IMPL
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//------------------------------------------------------------------------------
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#endif // CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
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