diff --git a/cmake/OpenCVDetectCUDA.cmake b/cmake/OpenCVDetectCUDA.cmake index a3d987a2b8..140244ff54 100644 --- a/cmake/OpenCVDetectCUDA.cmake +++ b/cmake/OpenCVDetectCUDA.cmake @@ -101,18 +101,20 @@ if(CUDA_FOUND) message(STATUS "CUDA detected: " ${CUDA_VERSION}) OCV_OPTION(CUDA_ENABLE_DEPRECATED_GENERATION "Enable deprecated generations in the list" OFF) - set(_generations "Maxwell" "Pascal" "Volta" "Turing" "Ampere") + set(_generations "Maxwell" "Pascal" "Volta" "Turing" "Ampere" "Lovelace" "Hopper") if(CUDA_ENABLE_DEPRECATED_GENERATION) set(_generations "Fermi" "${_generations}") set(_generations "Kepler" "${_generations}") endif() - set(_arch_fermi "2.0") - set(_arch_kepler "3.0;3.5;3.7") - set(_arch_maxwell "5.0;5.2") - set(_arch_pascal "6.0;6.1") - set(_arch_volta "7.0") - set(_arch_turing "7.5") - set(_arch_ampere "8.0;8.6") + set(_arch_fermi "2.0") + set(_arch_kepler "3.0;3.5;3.7") + set(_arch_maxwell "5.0;5.2") + set(_arch_pascal "6.0;6.1") + set(_arch_volta "7.0") + set(_arch_turing "7.5") + set(_arch_ampere "8.0;8.6") + set(_arch_lovelace "8.9") + set(_arch_hopper "9.0") if(NOT CMAKE_CROSSCOMPILING) list(APPEND _generations "Auto") endif() @@ -241,6 +243,10 @@ if(CUDA_FOUND) set(__cuda_arch_bin ${_arch_turing}) elseif(CUDA_GENERATION STREQUAL "Ampere") set(__cuda_arch_bin ${_arch_ampere}) + elseif(CUDA_GENERATION STREQUAL "Lovelace") + set(__cuda_arch_bin ${_arch_lovelace}) + elseif(CUDA_GENERATION STREQUAL "Hopper") + set(__cuda_arch_bin ${_arch_hopper}) elseif(CUDA_GENERATION STREQUAL "Auto") ocv_detect_native_cuda_arch(_nvcc_res _nvcc_out) if(NOT _nvcc_res EQUAL 0) @@ -286,6 +292,8 @@ if(CUDA_FOUND) ${_arch_volta} ${_arch_turing} ${_arch_ampere} + ${_arch_lovelace} + ${_arch_hopper} ) endif() endif() diff --git a/cmake/OpenCVFindFrameworks.cmake b/cmake/OpenCVFindFrameworks.cmake index 19f6d66340..741267d269 100644 --- a/cmake/OpenCVFindFrameworks.cmake +++ b/cmake/OpenCVFindFrameworks.cmake @@ -32,6 +32,9 @@ if(WITH_OPENMP) if(OPENMP_FOUND) set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OpenMP_C_FLAGS}") set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OpenMP_CXX_FLAGS}") + if(DEFINED OpenMP_CXX_INCLUDE_DIRS AND OpenMP_CXX_INCLUDE_DIRS) + ocv_include_directories(${OpenMP_CXX_INCLUDE_DIRS}) + endif() endif() set(HAVE_OPENMP "${OPENMP_FOUND}") endif() diff --git a/cmake/checks/cpu_rvv.cpp b/cmake/checks/cpu_rvv.cpp index 684b2ecbeb..b9f19c17fd 100644 --- a/cmake/checks/cpu_rvv.cpp +++ b/cmake/checks/cpu_rvv.cpp @@ -9,6 +9,9 @@ int test() { const float src[] = { 0.0f, 0.0f, 0.0f, 0.0f }; + uint64_t ptr[2] = {0x0908060504020100, 0xFFFFFFFF0E0D0C0A}; + vuint8m1_t a = vreinterpret_v_u64m1_u8m1(vle64_v_u64m1(ptr, 2)); + //vuint8m1_t a = (vuint8m1_t)vle64_v_u64m1(ptr, 2); vfloat32m1_t val = vle32_v_f32m1((const float*)(src), 4); return (int)vfmv_f_s_f32m1_f32(val); } diff --git a/modules/core/CMakeLists.txt b/modules/core/CMakeLists.txt index eab909843b..fe747540e8 100644 --- a/modules/core/CMakeLists.txt +++ b/modules/core/CMakeLists.txt @@ -168,6 +168,10 @@ if(HAVE_HPX) ocv_target_link_libraries(${the_module} LINK_PRIVATE "${HPX_LIBRARIES}") endif() +if(HAVE_OPENMP AND DEFINED OpenMP_CXX_LIBRARIES AND OpenMP_CXX_LIBRARIES) + ocv_target_link_libraries(${the_module} LINK_PRIVATE "${OpenMP_CXX_LIBRARIES}") +endif() + ocv_add_accuracy_tests() ocv_add_perf_tests() diff --git a/modules/core/include/opencv2/core/hal/intrin_rvv.hpp b/modules/core/include/opencv2/core/hal/intrin_rvv.hpp index dca54a27d1..3e7ce51f6b 100644 --- a/modules/core/include/opencv2/core/hal/intrin_rvv.hpp +++ b/modules/core/include/opencv2/core/hal/intrin_rvv.hpp @@ -1920,20 +1920,29 @@ inline v_float64x2 v_muladd(const v_float64x2& a, const v_float64x2& b, const v_ #define OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(_Tpvec, suffix, shift, vl) \ inline bool v_check_all(const _Tpvec& a) \ { \ - v_uint64x2 v = v_uint64x2((vuint64m1_t)vsrl_vx_##suffix##m1(vnot_v_##suffix##m1(a, vl), shift, vl)); \ + v_uint64x2 v = v_uint64x2(vreinterpret_v_##suffix##m1_u64m1(vsrl_vx_##suffix##m1(vnot_v_##suffix##m1(a, vl), shift, vl))); \ return (v.val[0] | v.val[1]) == 0; \ } \ inline bool v_check_any(const _Tpvec& a) \ { \ - v_uint64x2 v = v_uint64x2((vuint64m1_t)vsrl_vx_##suffix##m1(a, shift, vl)); \ + v_uint64x2 v = v_uint64x2(vreinterpret_v_##suffix##m1_u64m1(vsrl_vx_##suffix##m1(a, shift, vl))); \ return (v.val[0] | v.val[1]) != 0; \ } OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(v_uint8x16, u8, 7, 16) OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(v_uint16x8, u16, 15, 8) OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(v_uint32x4, u32, 31, 4) -OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(v_uint64x2, u64, 63, 2) - +//OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(v_uint64x2, u64, 63, 2) +inline bool v_check_all(const v_uint64x2& a) +{ + v_uint64x2 v = v_uint64x2(vsrl_vx_u64m1(vnot_v_u64m1(a, 2), 63, 2)); + return (v.val[0] | v.val[1]) == 0; +} +inline bool v_check_any(const v_uint64x2& a) +{ + v_uint64x2 v = v_uint64x2(vsrl_vx_u64m1(a, 63, 2)); + return (v.val[0] | v.val[1]) != 0; +} inline bool v_check_all(const v_int8x16& a) { return v_check_all(v_reinterpret_as_u8(a)); } @@ -2035,15 +2044,15 @@ OPENCV_HAL_IMPL_RVV_ABSDIFF(v_int16x8, absdiffs) // use reinterpret instead of c-style casting. #ifndef __clang__ -#define OPENCV_HAL_IMPL_RVV_ABSDIFF_S(_Tpvec, _rTpvec, _nwTpvec, sub, rshr, vl) \ +#define OPENCV_HAL_IMPL_RVV_ABSDIFF_S(_Tpvec, _rTpvec, _nwTpvec, sub, rshr, width, vl) \ inline _rTpvec v_absdiff(const _Tpvec& a, const _Tpvec& b) \ { \ - return _rTpvec(rshr((_nwTpvec)sub(v_max(a, b), v_min(a, b), vl), 0, vl)); \ + return _rTpvec(rshr(vreinterpret_v_i##width##m2_u##width##m2(sub(v_max(a, b), v_min(a, b), vl)), 0, vl)); \ } -OPENCV_HAL_IMPL_RVV_ABSDIFF_S(v_int8x16, v_uint8x16, vuint16m2_t, vwsub_vv_i16m2, vnclipu_wx_u8m1, 16) -OPENCV_HAL_IMPL_RVV_ABSDIFF_S(v_int16x8, v_uint16x8, vuint32m2_t, vwsub_vv_i32m2, vnclipu_wx_u16m1, 8) -OPENCV_HAL_IMPL_RVV_ABSDIFF_S(v_int32x4, v_uint32x4, vuint64m2_t, vwsub_vv_i64m2, vnclipu_wx_u32m1, 4) +OPENCV_HAL_IMPL_RVV_ABSDIFF_S(v_int8x16, v_uint8x16, vuint16m2_t, vwsub_vv_i16m2, vnclipu_wx_u8m1, 16, 16) +OPENCV_HAL_IMPL_RVV_ABSDIFF_S(v_int16x8, v_uint16x8, vuint32m2_t, vwsub_vv_i32m2, vnclipu_wx_u16m1, 32, 8) +OPENCV_HAL_IMPL_RVV_ABSDIFF_S(v_int32x4, v_uint32x4, vuint64m2_t, vwsub_vv_i64m2, vnclipu_wx_u32m1, 64, 4) #else #define OPENCV_HAL_IMPL_RVV_ABSDIFF_S(_Tpvec, _rTpvec, _nwTpvec, sub, rshr, width, vl) \ inline _rTpvec v_absdiff(const _Tpvec& a, const _Tpvec& b) \ @@ -2806,12 +2815,15 @@ OPENCV_HAL_IMPL_RVV_SCAN_FORWOARD_OP(v_float64x2, double, f64) //////////// Pack triplets //////////// -// use reinterpret instead of c-style casting. -#ifndef __clang__ inline v_int8x16 v_pack_triplets(const v_int8x16& vec) { - uint64 ptr[2] = {0x0908060504020100, 0xFFFFFF0F0E0D0C0A}; - return v_int8x16((vint8m1_t)vrgather_vv_u8m1((vuint8m1_t)vint8m1_t(vec), (vuint8m1_t)vle64_v_u64m1(ptr, 2), 16)); + const uint64 ptr[2] = {0x0908060504020100, 0xFFFFFF0F0E0D0C0A}; + const v_uint64x2 flags(vle64_v_u64m1(ptr, 2)); + return v_reinterpret_as_s8(v_uint8x16( + vrgather_vv_u8m1( + v_reinterpret_as_u8(vec), + v_reinterpret_as_u8(flags), + 16))); } inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) { @@ -2820,8 +2832,13 @@ inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) inline v_int16x8 v_pack_triplets(const v_int16x8& vec) { - uint64 ptr[2] = {0x0908050403020100, 0xFFFF0F0E0D0C0B0A}; - return v_int16x8((vint16m1_t)vrgather_vv_u8m1((vuint8m1_t)vint16m1_t(vec), (vuint8m1_t)vle64_v_u64m1(ptr, 2), 16)); + const uint64 ptr[2] = {0x0908050403020100, 0xFFFF0F0E0D0C0B0A}; + const v_uint64x2 flags(vle64_v_u64m1(ptr, 2)); + return v_reinterpret_as_s16(v_uint8x16( + vrgather_vv_u8m1( + v_reinterpret_as_u8(vec), + v_reinterpret_as_u8(flags), + 16))); } inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec) { @@ -2832,34 +2849,6 @@ inline v_int32x4 v_pack_triplets(const v_int32x4& vec) { return vec; } inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) { return vec; } inline v_float32x4 v_pack_triplets(const v_float32x4& vec) { return vec; } -#else - -inline v_int8x16 v_pack_triplets(const v_int8x16& vec) -{ - uint64 ptr[2] = {0x0908060504020100, 0xFFFFFF0F0E0D0C0A}; - return v_int8x16(vreinterpret_i8m1(vrgather_vv_u8m1(v_reinterpret_as_u8(vec), vreinterpret_u8m1(vle64_v_u64m1(ptr, 2)), 16))); -} -inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) -{ - return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); -} - -inline v_int16x8 v_pack_triplets(const v_int16x8& vec) -{ - uint64 ptr[2] = {0x0908050403020100, 0xFFFF0F0E0D0C0B0A}; - return v_int16x8(v_reinterpret_as_s16(v_uint8x16(vrgather_vv_u8m1(v_reinterpret_as_u8(vec), vreinterpret_u8m1(vle64_v_u64m1(ptr, 2)), 16)))); -} -inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec) -{ - return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); -} - -inline v_int32x4 v_pack_triplets(const v_int32x4& vec) { return vec; } -inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) { return vec; } -inline v_float32x4 v_pack_triplets(const v_float32x4& vec) { return vec; } - -#endif - ////// FP16 support /////// #if CV_FP16 diff --git a/modules/dnn/src/layers/fast_convolution/depthwise_convolution.cpp b/modules/dnn/src/layers/fast_convolution/depthwise_convolution.cpp index 0c471e8920..4566c880c9 100644 --- a/modules/dnn/src/layers/fast_convolution/depthwise_convolution.cpp +++ b/modules/dnn/src/layers/fast_convolution/depthwise_convolution.cpp @@ -24,7 +24,7 @@ static void depthWiseBlockConv2D(const float* wptr, const float* inptr_, int height, int width, float* outptr_, - int out_d, int outH, int outW) + int out_d, int outH, int outW, bool fusedAdd) { const float w00_ = wptr[0], w01_ = wptr[1], w02_ = wptr[2], w10 = wptr[3], w11 = wptr[4], w12 = wptr[5], @@ -57,6 +57,8 @@ static void depthWiseBlockConv2D(const float* wptr, out = imgptr0[0]*w01 + imgptr0[dilation_w]*w02 + imgptr1[0]*w11 + imgptr1[dilation_w]*w12 + imgptr2[0]*w21 + imgptr2[dilation_w]*w22 + bias; + if (fusedAdd) + out += outptr[0]; if (relu) out = out > 0.f ? out : out*relu_coeff; outptr[0] = out; @@ -65,6 +67,10 @@ static void depthWiseBlockConv2D(const float* wptr, #if CV_SIMD128 const int VEC_NLANES = 4; + + if (fusedAdd) + outW1 = max(out_j, outW1 - outW1%VEC_NLANES); + v_float32x4 vw00 = v_setall_f32(w00); v_float32x4 vw01 = v_setall_f32(w01); v_float32x4 vw02 = v_setall_f32(w02); @@ -104,6 +110,8 @@ static void depthWiseBlockConv2D(const float* wptr, v_float32x4 vout = v00*vw00 + v01*vw01 + v02*vw02 + v10*vw10 + v11*vw11 + v12*vw12 + v20*vw20 + v21*vw21 + v22*vw22 + vbias; + if (fusedAdd) + vout = v_load(outptr + out_j) + vout; if (relu) vout = v_select(vout > z, vout, vout*vrc); v_store(outptr + out_j, vout); @@ -134,6 +142,8 @@ static void depthWiseBlockConv2D(const float* wptr, v10 * vw10 + v11 * vw11 + v12 * vw12 + v20 * vw20 + v21 * vw21 + v22 * vw22 + vbias; + if (fusedAdd) + vout = v_load(outptr + out_j) + vout; if (relu) vout = v_select(vout > z, vout, vout*vrc); v_store(outptr + out_j, vout); @@ -148,6 +158,8 @@ static void depthWiseBlockConv2D(const float* wptr, out = imgptr0[in_j]*w00 + imgptr0[in_j + dilation_w]*w01 + imgptr0[in_j + dilation_w*2]*w02 + imgptr1[in_j]*w10 + imgptr1[in_j + dilation_w]*w11 + imgptr1[in_j + dilation_w*2]*w12 + imgptr2[in_j]*w20 + imgptr2[in_j + dilation_w]*w21 + imgptr2[in_j + dilation_w*2]*w22 + bias; + if (fusedAdd) + out += outptr[out_j]; if (relu) out = out > 0.f ? out : out*relu_coeff; outptr[out_j] = out; @@ -175,6 +187,8 @@ static void depthWiseBlockConv2D(const float* wptr, out = imgptr0[in_j0]*w00*s0 + imgptr0[in_j1]*w01*s1 + imgptr0[in_j2]*w02*s2 + imgptr1[in_j0]*w10*s0 + imgptr1[in_j1]*w11*s1 + imgptr1[in_j2]*w12*s2 + imgptr2[in_j0]*w20*s0 + imgptr2[in_j1]*w21*s1 + imgptr2[in_j2]*w22*s2 + bias; + if (fusedAdd) + out += outptr[out_j]; if (relu) out = out > 0.f ? out : out*relu_coeff; outptr[out_j] = out; @@ -187,7 +201,7 @@ static void depthWiseBlockConv1D(const float* wptr, const float* biasptr, const float* relu, const float* inptr_, int width, float* outptr_, - int out_d, int outW) + int out_d, int outW, bool fusedAdd) { const float w00_ = wptr[0], w01_ = wptr[1], w02_ = wptr[2]; int outW1 = min(outW, (width - dilation_w * (kernel_w - 1) + pad_l)/stride_w); @@ -201,7 +215,8 @@ static void depthWiseBlockConv1D(const float* wptr, if (pad_l > 0) { out = imgptr0[0]*w01 + imgptr0[dilation_w]*w02 + bias; - + if (fusedAdd) + out += outptr[0]; if (relu) out = out > 0.f ? out : out*relu_coeff; outptr[0] = out; @@ -210,6 +225,8 @@ static void depthWiseBlockConv1D(const float* wptr, #if CV_SIMD128 const int VEC_NLANES = 4; + if (fusedAdd) + outW1 = max(out_j, outW1 - outW1%VEC_NLANES); v_float32x4 vw00 = v_setall_f32(w00); v_float32x4 vw01 = v_setall_f32(w01); v_float32x4 vw02 = v_setall_f32(w02); @@ -235,6 +252,8 @@ static void depthWiseBlockConv1D(const float* wptr, v02 = v_load(imgptr0 + in_j + dilation_w*2); v_float32x4 vout = v00*vw00 + v01*vw01 + v02*vw02 + vbias; + if (fusedAdd) + vout = v_load(outptr + out_j) + vout; if (relu) vout = v_select(vout > z, vout, vout*vrc); v_store(outptr + out_j, vout); @@ -258,6 +277,9 @@ static void depthWiseBlockConv1D(const float* wptr, v_float32x4 vout = v00 * vw00 + v01 * vw01 + v02 * vw02 + vbias; + if (fusedAdd) + vout = v_load(outptr + out_j) + vout; + if (relu) vout = v_select(vout > z, vout, vout*vrc); v_store(outptr + out_j, vout); @@ -270,6 +292,8 @@ static void depthWiseBlockConv1D(const float* wptr, { int in_j = out_j * stride_w - pad_l; out = imgptr0[in_j]*w00 + imgptr0[in_j + dilation_w]*w01 + imgptr0[in_j + dilation_w*2]*w02 + bias; + if (fusedAdd) + out += outptr[out_j]; if (relu) out = out > 0.f ? out : out*relu_coeff; outptr[out_j] = out; @@ -295,6 +319,8 @@ static void depthWiseBlockConv1D(const float* wptr, s2 = 0.f; } out = imgptr0[in_j0]*w00*s0 + imgptr0[in_j1]*w01*s1 + imgptr0[in_j2]*w02*s2 + bias; + if (fusedAdd) + out += outptr[out_j]; if (relu) out = out > 0.f ? out : out*relu_coeff; outptr[out_j] = out; @@ -302,7 +328,7 @@ static void depthWiseBlockConv1D(const float* wptr, } void runDepthwise(InputArray _input, OutputArray _output, const Ptr& conv, ActivationLayer* activ_, - const std::vector& reluslope) + const std::vector& reluslope, bool fusedAdd) { Mat input = _input.getMat(); Mat output = _output.getMat(); @@ -349,7 +375,7 @@ void runDepthwise(InputArray _input, OutputArray _output, const Ptr& c #if CV_TRY_AVX2 || CV_TRY_AVX || CV_TRY_RVV // TODO: remove the following limitation, need change code in layers_common.simd.hpp. - bool canRunOpt = Wi >= 16 + dilation_w*(Wk - 1); + bool canRunOpt = Wi >= 16 + dilation_w*(Wk - 1) && !fusedAdd; #endif std::vector ofstab_(3 * ksize, 0); int *ofstab = ofstab_.data(); @@ -399,11 +425,11 @@ void runDepthwise(InputArray _input, OutputArray _output, const Ptr& c else #endif depthWiseBlockConv2D(weights, Hk, Wk, stride_h, stride_w, dilation_h, dilation_w, - pad_top, pad_left, bias, relu, inptr0, Hi, Wi, outptr0, c, H0, W0); + pad_top, pad_left, bias, relu, inptr0, Hi, Wi, outptr0, c, H0, W0, fusedAdd); } else // conv_dim == CONV_1D, spatial branch for depth-wise Conv1D. { - depthWiseBlockConv1D(weights, Wk, stride_w, dilation_w, pad_left, bias, relu, inptr0, Wi, outptr0, c, W0); + depthWiseBlockConv1D(weights, Wk, stride_w, dilation_w, pad_left, bias, relu, inptr0, Wi, outptr0, c, W0, fusedAdd); } if (activ) diff --git a/modules/dnn/src/layers/fast_convolution/fast_convolution.avx2.cpp b/modules/dnn/src/layers/fast_convolution/fast_convolution.avx2.cpp index 0d3c144762..c98fbe72bd 100644 --- a/modules/dnn/src/layers/fast_convolution/fast_convolution.avx2.cpp +++ b/modules/dnn/src/layers/fast_convolution/fast_convolution.avx2.cpp @@ -119,7 +119,7 @@ void convBlock_AVX2(int np, const float* a, const float* b, float* c, int ldc, b void _fx_winograd_accum_f32(const float* inwptr, const float* wptr, float* outbuf, int Cg, int iblock) { - CV_Assert(_FX_WINO_IBLOCK == 6 && _FX_WINO_KBLOCK == 4);// && _FX_WINO_ATOM_F32 == 8); + CV_Assert(_FX_WINO_IBLOCK == 6 && _FX_WINO_KBLOCK == 4 && _FX_WINO_ATOM_F32 == 8); if (iblock > 3) { for (int atom_id = 0; atom_id < _FX_WINO_NATOMS_F32; atom_id++, diff --git a/modules/dnn/src/layers/fast_convolution/fast_convolution.cpp b/modules/dnn/src/layers/fast_convolution/fast_convolution.cpp index 1cde7b324f..51abf8facc 100644 --- a/modules/dnn/src/layers/fast_convolution/fast_convolution.cpp +++ b/modules/dnn/src/layers/fast_convolution/fast_convolution.cpp @@ -105,6 +105,12 @@ Ptr initFastConv( conv->conv_type = _FX_CONV_TYPE_GENERIC; #endif +#if CV_TRY_AVX2 + // Disabel Winograd when CV_TRY_AVX2 is true, but conv->useAVX2 is false. + if (conv->conv_type == _FX_CONV_TYPE_WINOGRAD3X3 && !conv->useAVX2) + conv->conv_type = _FX_CONV_TYPE_GENERIC; +#endif + Mat weightsMat = _weightsMat.getMat(); auto wShape = shape(weightsMat); const size_t wstep = weightsMat.step1(); @@ -257,7 +263,7 @@ Ptr initFastConv( // we can always read MR elements starting from any valid index { int k = 0, nbias = K + VEC_ALIGN; - conv->biasBuf.reserve(nbias); + conv->biasBuf.resize(nbias); float* biasBufPtr = conv->biasBuf.data(); for(; k < K; k++) biasBufPtr[k] = srcBias ? srcBias[k] : 0.f; @@ -369,8 +375,8 @@ void runFastConv(InputArray _input, OutputArray _output, const Ptr& co if (conv->conv_type == _FX_CONV_TYPE_DEPTHWISE) { // Depthwise-Convolution layer should not be followed by Add layer. - CV_Assert(fusedAddMat.empty() && (conv_dim == CONV_1D || conv_dim == CONV_2D)); - return runDepthwise(input, output, conv,actLayer.get(), reluslope); + CV_Assert((conv_dim == CONV_1D || conv_dim == CONV_2D)); + return runDepthwise(input, output, conv, actLayer.get(), reluslope, fusedAdd); } MatShape inputShape = shape(input); diff --git a/modules/dnn/src/layers/fast_convolution/fast_convolution.hpp b/modules/dnn/src/layers/fast_convolution/fast_convolution.hpp index 895ad562bb..7794078bb4 100644 --- a/modules/dnn/src/layers/fast_convolution/fast_convolution.hpp +++ b/modules/dnn/src/layers/fast_convolution/fast_convolution.hpp @@ -100,7 +100,7 @@ void runFastConv(InputArray _input, OutputArray _output, const Ptr& co const Ptr& actLayer, const std::vector& reluslope, bool fusedAdd); void runDepthwise(InputArray _input, OutputArray _output, const Ptr& conv, ActivationLayer* activ, - const std::vector& reluslope); + const std::vector& reluslope, bool fusedAdd); int runWinograd63(InputArray _input, InputArray _fusedAddMat, OutputArray _output, const Ptr& conv, int ntasks, float minval, float maxval, ActivationLayer* activ, bool ifMinMaxAct); diff --git a/modules/dnn/src/layers/fast_convolution/winograd_3x3s1_f63.cpp b/modules/dnn/src/layers/fast_convolution/winograd_3x3s1_f63.cpp index e3b8088410..b0ccfd0cd2 100644 --- a/modules/dnn/src/layers/fast_convolution/winograd_3x3s1_f63.cpp +++ b/modules/dnn/src/layers/fast_convolution/winograd_3x3s1_f63.cpp @@ -22,7 +22,7 @@ _fx_winograd_accum_f32(const float* inwptr, const float* wptr, float* outbuf, int Cg, int iblock) { #if CV_NEON && CV_NEON_AARCH64 - CV_Assert(_FX_WINO_IBLOCK == 6 && _FX_WINO_KBLOCK == 4); + CV_Assert(_FX_WINO_IBLOCK == 6 && _FX_WINO_KBLOCK == 4 && _FX_WINO_ATOM_F32 == 4); if (iblock > 3) { for (int atom_id = 0; atom_id < _FX_WINO_NATOMS_F32; atom_id++, @@ -144,7 +144,7 @@ _fx_winograd_accum_f32(const float* inwptr, const float* wptr, } } #elif CV_SIMD128 - CV_Assert(_FX_WINO_IBLOCK == 3 && _FX_WINO_KBLOCK == 4); + CV_Assert(_FX_WINO_IBLOCK == 3 && _FX_WINO_KBLOCK == 4 && _FX_WINO_ATOM_F32 == 4); for (int atom_id = 0; atom_id < _FX_WINO_NATOMS_F32; atom_id++, outbuf += _FX_WINO_ATOM_F32) { diff --git a/modules/dnn/test/test_onnx_importer.cpp b/modules/dnn/test/test_onnx_importer.cpp index 12dc3987b9..0ffa252c71 100644 --- a/modules/dnn/test/test_onnx_importer.cpp +++ b/modules/dnn/test/test_onnx_importer.cpp @@ -1726,6 +1726,11 @@ TEST_P(Test_ONNX_layers, ConvResizePool1d) testONNXModels("conv_resize_pool_1d"); } +TEST_P(Test_ONNX_layers, DepthWiseAdd) +{ + testONNXModels("depthwiseconv_add"); +} + TEST_P(Test_ONNX_layers, SubFromConst) { testONNXModels("sub_from_const1"); diff --git a/modules/ts/include/opencv2/ts/cuda_test.hpp b/modules/ts/include/opencv2/ts/cuda_test.hpp index f1851c5f8f..87b217fc13 100644 --- a/modules/ts/include/opencv2/ts/cuda_test.hpp +++ b/modules/ts/include/opencv2/ts/cuda_test.hpp @@ -212,6 +212,8 @@ namespace cvtest #define DIFFERENT_SIZES testing::Values(cv::Size(128, 128), cv::Size(113, 113)) + #define DIFFERENT_SIZES_EXTRA testing::Values(cv::Size(13, 1), cv::Size(1, 13), cv::Size(128, 128), cv::Size(113, 113)) + // Depth using perf::MatDepth; diff --git a/modules/video/CMakeLists.txt b/modules/video/CMakeLists.txt index 05830f0da7..4e5bd36a14 100644 --- a/modules/video/CMakeLists.txt +++ b/modules/video/CMakeLists.txt @@ -10,3 +10,7 @@ ocv_define_module(video python js ) + +if(HAVE_OPENMP AND DEFINED OpenMP_CXX_LIBRARIES AND OpenMP_CXX_LIBRARIES) + ocv_target_link_libraries(${the_module} LINK_PRIVATE "${OpenMP_CXX_LIBRARIES}") +endif() diff --git a/platforms/js/opencv_js.config.py b/platforms/js/opencv_js.config.py index 53afc87d3f..acf7a42e78 100644 --- a/platforms/js/opencv_js.config.py +++ b/platforms/js/opencv_js.config.py @@ -112,7 +112,7 @@ objdetect = {'': ['groupRectangles'], 'HOGDescriptor': ['load', 'HOGDescriptor', 'getDefaultPeopleDetector', 'getDaimlerPeopleDetector', 'setSVMDetector', 'detectMultiScale'], 'CascadeClassifier': ['load', 'detectMultiScale2', 'CascadeClassifier', 'detectMultiScale3', 'empty', 'detectMultiScale'], 'QRCodeDetector': ['QRCodeDetector', 'decode', 'decodeCurved', 'detect', 'detectAndDecode', 'detectMulti', 'setEpsX', 'setEpsY'], - 'ArucoDetector': ['getPredefinedDictionary', 'detectMarkers', 'refineDetectedMarkers', 'getDictionary', 'stetDictionary', 'getDetectorParameters', 'setDetectorParameters', 'getRefineParameters', 'setRefineParameters'], + 'ArucoDetector': ['getPredefinedDictionary', 'detectMarkers', 'refineDetectedMarkers', 'getDictionary', 'setDictionary', 'getDetectorParameters', 'setDetectorParameters', 'getRefineParameters', 'setRefineParameters'], 'GridBoard': ['create','generateImage', 'getGridSize', 'getMarkerLength', 'getMarkerSeparation'], 'CharucoBoard': ['create', 'generateImage', 'getChessboardCorners', 'getNearestMarkerCorners', 'checkCharucoCornersCollinear'] } diff --git a/samples/python/stitching_detailed.py b/samples/python/stitching_detailed.py index 2b29228302..1a6bf809e0 100644 --- a/samples/python/stitching_detailed.py +++ b/samples/python/stitching_detailed.py @@ -49,6 +49,8 @@ except AttributeError: print("AKAZE not available") SEAM_FIND_CHOICES = OrderedDict() +SEAM_FIND_CHOICES['gc_color'] = cv.detail_GraphCutSeamFinder('COST_COLOR') +SEAM_FIND_CHOICES['gc_colorgrad'] = cv.detail_GraphCutSeamFinder('COST_COLOR_GRAD') SEAM_FIND_CHOICES['dp_color'] = cv.detail_DpSeamFinder('COLOR') SEAM_FIND_CHOICES['dp_colorgrad'] = cv.detail_DpSeamFinder('COLOR_GRAD') SEAM_FIND_CHOICES['voronoi'] = cv.detail.SeamFinder_createDefault(cv.detail.SeamFinder_VORONOI_SEAM)