Open Source Computer Vision Library https://opencv.org/
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if(WINRT)
ocv_module_disable(dnn)
endif()
if(NOT HAVE_PROTOBUF)
ocv_module_disable(opencv_dnn)
endif()
set(the_description "Deep neural network module. It allows to load models from different frameworks and to make forward pass")
ocv_add_dispatched_file_force_all("layers/layers_common" AVX AVX2 AVX512_SKX RVV)
ocv_add_dispatched_file_force_all("int8layers/layers_common" AVX2 AVX512_SKX)
ocv_add_module(dnn opencv_core opencv_imgproc WRAP python java objc js)
ocv_option(OPENCV_DNN_OPENCL "Build with OpenCL support" HAVE_OPENCL AND NOT APPLE)
if(OPENCV_DNN_OPENCL AND HAVE_OPENCL)
add_definitions(-DCV_OCL4DNN=1)
endif()
Merge pull request #20406 from MarkGHX:gsoc_2021_webnn [GSoC] OpenCV.js: Accelerate OpenCV.js DNN via WebNN * Add WebNN backend for OpenCV DNN Module Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp Add WebNN head files into OpenCV 3rd partiy files Create webnn.hpp update cmake Complete README and add OpenCVDetectWebNN.cmake file add webnn.cpp Modify webnn.cpp Can successfully compile the codes for creating a MLContext Update webnn.cpp Update README.md Update README.md Update README.md Update README.md Update cmake files and update README.md Update OpenCVDetectWebNN.cmake and README.md Update OpenCVDetectWebNN.cmake Fix OpenCVDetectWebNN.cmake and update README.md Add source webnn_cpp.cpp and libary libwebnn_proc.so Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp update dnn.cpp update op_webnn update op_webnn Update op_webnn.hpp update op_webnn.cpp & hpp Update op_webnn.hpp Update op_webnn update the skeleton Update op_webnn.cpp Update op_webnn Update op_webnn.cpp Update op_webnn.cpp Update op_webnn.hpp update op_webnn update op_webnn Solved the problems of released variables. Fixed the bugs in op_webnn.cpp Implement op_webnn Implement Relu by WebNN API Update dnn.cpp for better test Update elementwise_layers.cpp Implement ReLU6 Update elementwise_layers.cpp Implement SoftMax using WebNN API Implement Reshape by WebNN API Implement PermuteLayer by WebNN API Implement PoolingLayer using WebNN API Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Implement poolingLayer by WebNN API and add more detailed logs Update dnn.cpp Update dnn.cpp Remove redundant codes and add more logs for poolingLayer Add more logs in the pooling layer implementation Fix the indent issue and resolve the compiling issue Fix the build problems Fix the build issue FIx the build issue Update dnn.cpp Update dnn.cpp * Fix the build issue * Implement BatchNorm Layer by WebNN API * Update convolution_layer.cpp This is a temporary file for Conv2d layer implementation * Integrate some general functions into op_webnn.cpp&hpp * Update const_layer.cpp * Update convolution_layer.cpp Still have some bugs that should be fixed. * Update conv2d layer and fc layer still have some problems to be fixed. * update constLayer, conv layer, fc layer There are still some bugs to be fixed. * Fix the build issue * Update concat_layer.cpp Still have some bugs to be fixed. * Update conv2d layer, fully connected layer and const layer * Update convolution_layer.cpp * Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron) * Delete bib19450.aux * Add WebNN backend for OpenCV DNN Module Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp Add WebNN head files into OpenCV 3rd partiy files Create webnn.hpp update cmake Complete README and add OpenCVDetectWebNN.cmake file add webnn.cpp Modify webnn.cpp Can successfully compile the codes for creating a MLContext Update webnn.cpp Update README.md Update README.md Update README.md Update README.md Update cmake files and update README.md Update OpenCVDetectWebNN.cmake and README.md Update OpenCVDetectWebNN.cmake Fix OpenCVDetectWebNN.cmake and update README.md Add source webnn_cpp.cpp and libary libwebnn_proc.so Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp update dnn.cpp update op_webnn update op_webnn Update op_webnn.hpp update op_webnn.cpp & hpp Update op_webnn.hpp Update op_webnn update the skeleton Update op_webnn.cpp Update op_webnn Update op_webnn.cpp Update op_webnn.cpp Update op_webnn.hpp update op_webnn update op_webnn Solved the problems of released variables. Fixed the bugs in op_webnn.cpp Implement op_webnn Implement Relu by WebNN API Update dnn.cpp for better test Update elementwise_layers.cpp Implement ReLU6 Update elementwise_layers.cpp Implement SoftMax using WebNN API Implement Reshape by WebNN API Implement PermuteLayer by WebNN API Implement PoolingLayer using WebNN API Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Implement poolingLayer by WebNN API and add more detailed logs Update dnn.cpp Update dnn.cpp Remove redundant codes and add more logs for poolingLayer Add more logs in the pooling layer implementation Fix the indent issue and resolve the compiling issue Fix the build problems Fix the build issue FIx the build issue Update dnn.cpp Update dnn.cpp * Fix the build issue * Implement BatchNorm Layer by WebNN API * Update convolution_layer.cpp This is a temporary file for Conv2d layer implementation * Integrate some general functions into op_webnn.cpp&hpp * Update const_layer.cpp * Update convolution_layer.cpp Still have some bugs that should be fixed. * Update conv2d layer and fc layer still have some problems to be fixed. * update constLayer, conv layer, fc layer There are still some bugs to be fixed. * Update conv2d layer, fully connected layer and const layer * Update convolution_layer.cpp * Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron) * Update dnn.cpp * Fix Error in dnn.cpp * Resolve duplication in conditions in convolution_layer.cpp * Fixed the issues in the comments * Fix building issue * Update tutorial * Fixed comments * Address the comments * Update CMakeLists.txt * Offer more accurate perf test on native * Add better perf tests for both native and web * Modify per tests for better results * Use more latest version of Electron * Support latest WebNN Clamp op * Add definition of HAVE_WEBNN macro * Support group convolution * Implement Scale_layer using WebNN * Add Softmax option for native classification example * Fix comments * Fix comments
3 years ago
if(WITH_WEBNN AND HAVE_WEBNN)
add_definitions(-DHAVE_WEBNN=1)
endif()
ocv_option(OPENCV_DNN_CUDA "Build with CUDA support"
HAVE_CUDA
AND HAVE_CUBLAS
AND HAVE_CUDNN
)
if(OPENCV_DNN_CUDA)
if(HAVE_CUDA AND HAVE_CUBLAS AND HAVE_CUDNN)
add_definitions(-DCV_CUDA4DNN=1)
else()
if(NOT HAVE_CUDA)
message(SEND_ERROR "DNN: CUDA backend requires CUDA Toolkit. Please resolve dependency or disable OPENCV_DNN_CUDA=OFF")
elseif(NOT HAVE_CUBLAS)
message(SEND_ERROR "DNN: CUDA backend requires cuBLAS. Please resolve dependency or disable OPENCV_DNN_CUDA=OFF")
elseif(NOT HAVE_CUDNN)
message(SEND_ERROR "DNN: CUDA backend requires cuDNN. Please resolve dependency or disable OPENCV_DNN_CUDA=OFF")
endif()
endif()
endif()
ocv_cmake_hook_append(INIT_MODULE_SOURCES_opencv_dnn "${CMAKE_CURRENT_LIST_DIR}/cmake/hooks/INIT_MODULE_SOURCES_opencv_dnn.cmake")
if(HAVE_TENGINE)
add_definitions(-DHAVE_TENGINE=1)
endif()
if(MSVC)
add_definitions( -D_CRT_SECURE_NO_WARNINGS=1 )
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4244 /wd4267 /wd4018 /wd4355 /wd4800 /wd4251 /wd4996 /wd4146
/wd4305 /wd4127 /wd4100 /wd4512 /wd4125 /wd4389 /wd4510 /wd4610
/wd4702 /wd4456 /wd4457 /wd4065 /wd4310 /wd4661 /wd4506
)
if(MSVC_VERSION LESS 1920) # MSVS 2015/2017, .pb.cc generated files
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4309) # 'static_cast': truncation of constant value
endif()
if(MSVC_VERSION LESS 1920) # <MSVS2019, .pb.cc generated files
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4189) # local variable is initialized but not referenced
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4592) # symbol will be dynamically initialized (implementation limitation)
endif()
else()
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wno-deprecated -Wmissing-prototypes -Wmissing-declarations -Wshadow
-Wunused-parameter -Wsign-compare
)
endif()
if(HAVE_CUDA)
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef)
endif()
if(NOT HAVE_CXX11)
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wno-undef) # LANG_CXX11 from protobuf files
endif()
if(APPLE_FRAMEWORK)
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wshorten-64-to-32)
endif()
if(ANDROID)
add_definitions(-DDISABLE_POSIX_MEMALIGN -DTH_DISABLE_HEAP_TRACKING)
endif()
if(NOT BUILD_PROTOBUF)
add_definitions(-DOPENCV_DNN_EXTERNAL_PROTOBUF=1)
endif()
add_definitions(-DHAVE_PROTOBUF=1)
#suppress warnings in autogenerated caffe.pb.* files
ocv_warnings_disable(CMAKE_CXX_FLAGS
/wd4125 /wd4267 /wd4127 /wd4244 /wd4512 /wd4702
/wd4456 /wd4510 /wd4610 /wd4800
/wd4701 /wd4703 # potentially uninitialized local/pointer variable 'value' used
/wd4505 # unreferenced local function has been removed
/wd4458 # declaration of 'x' hides class member. GCC still works, MSVC bug is here: https://developercommunity.visualstudio.com/content/problem/219311/c-c4458-declaration-hides-class-member-warning-iss.html
-wd858 -wd2196
-Winvalid-offsetof # Apple Clang (attr_value.pb.cc)
)
set(include_dirs "")
set(libs "")
if(PROTOBUF_UPDATE_FILES)
file(GLOB proto_files "${CMAKE_CURRENT_LIST_DIR}/src/tensorflow/*.proto" "${CMAKE_CURRENT_LIST_DIR}/src/caffe/opencv-caffe.proto" "${CMAKE_CURRENT_LIST_DIR}/src/onnx/opencv-onnx.proto")
set(PROTOBUF_GENERATE_CPP_APPEND_PATH ON) # required for tensorflow
protobuf_generate_cpp(fw_srcs fw_hdrs ${proto_files})
else()
file(GLOB fw_srcs "${CMAKE_CURRENT_LIST_DIR}/misc/tensorflow/*.cc" "${CMAKE_CURRENT_LIST_DIR}/misc/caffe/opencv-caffe.pb.cc" "${CMAKE_CURRENT_LIST_DIR}/misc/onnx/opencv-onnx.pb.cc")
file(GLOB fw_hdrs "${CMAKE_CURRENT_LIST_DIR}/misc/tensorflow/*.h" "${CMAKE_CURRENT_LIST_DIR}/misc/caffe/opencv-caffe.pb.h" "${CMAKE_CURRENT_LIST_DIR}/misc/onnx/opencv-onnx.pb.h")
set(fw_inc "${CMAKE_CURRENT_LIST_DIR}/misc/caffe" "${CMAKE_CURRENT_LIST_DIR}/misc/tensorflow" "${CMAKE_CURRENT_LIST_DIR}/misc/onnx")
endif()
list(APPEND include_dirs ${fw_inc})
list(APPEND libs ${Protobuf_LIBRARIES})
if(NOT BUILD_PROTOBUF)
list(APPEND include_dirs ${Protobuf_INCLUDE_DIRS})
endif()
set(sources_options "")
list(APPEND libs ${LAPACK_LIBRARIES})
if(OPENCV_DNN_OPENCL AND HAVE_OPENCL)
list(APPEND include_dirs ${OPENCL_INCLUDE_DIRS})
else()
set(sources_options EXCLUDE_OPENCL)
endif()
if(OPENCV_DNN_CUDA AND HAVE_CUDA AND HAVE_CUBLAS AND HAVE_CUDNN)
list(APPEND include_dirs ${CUDA_TOOLKIT_INCLUDE} ${CUDNN_INCLUDE_DIRS})
Merge pull request #14827 from YashasSamaga:cuda4dnn-csl-low CUDA backend for the DNN module * stub cuda4dnn design * minor fixes for tests and doxygen * add csl public api directory to module headers * add low-level CSL components * add high-level CSL components * integrate csl::Tensor into backbone code * switch to CPU iff unsupported; otherwise, fail on error * add fully connected layer * add softmax layer * add activation layers * support arbitary rank TensorDescriptor * pass input wrappers to `initCUDA()` * add 1d/2d/3d-convolution * add pooling layer * reorganize and refactor code * fixes for gcc, clang and doxygen; remove cxx14/17 code * add blank_layer * add LRN layer * add rounding modes for pooling layer * split tensor.hpp into tensor.hpp and tensor_ops.hpp * add concat layer * add scale layer * add batch normalization layer * split math.cu into activations.cu and math.hpp * add eltwise layer * add flatten layer * add tensor transform api * add asymmetric padding support for convolution layer * add reshape layer * fix rebase issues * add permute layer * add padding support for concat layer * refactor and reorganize code * add normalize layer * optimize bias addition in scale layer * add prior box layer * fix and optimize normalize layer * add asymmetric padding support for pooling layer * add event API * improve pooling performance for some padding scenarios * avoid over-allocation of compute resources to kernels * improve prior box performance * enable layer fusion * add const layer * add resize layer * add slice layer * add padding layer * add deconvolution layer * fix channelwise ReLU initialization * add vector traits * add vectorized versions of relu, clipped_relu, power * add vectorized concat kernels * improve concat_with_offsets performance * vectorize scale and bias kernels * add support for multi-billion element tensors * vectorize prior box kernels * fix address alignment check * improve bias addition performance of conv/deconv/fc layers * restructure code for supporting multiple targets * add DNN_TARGET_CUDA_FP64 * add DNN_TARGET_FP16 * improve vectorization * add region layer * improve tensor API, add dynamic ranks 1. use ManagedPtr instead of a Tensor in backend wrapper 2. add new methods to tensor classes - size_range: computes the combined size of for a given axis range - tensor span/view can be constructed from a raw pointer and shape 3. the tensor classes can change their rank at runtime (previously rank was fixed at compile-time) 4. remove device code from tensor classes (as they are unused) 5. enforce strict conditions on tensor class APIs to improve debugging ability * fix parametric relu activation * add squeeze/unsqueeze tensor API * add reorg layer * optimize permute and enable 2d permute * enable 1d and 2d slice * add split layer * add shuffle channel layer * allow tensors of different ranks in reshape primitive * patch SliceOp to allow Crop Layer * allow extra shape inputs in reshape layer * use `std::move_backward` instead of `std::move` for insert in resizable_static_array * improve workspace management * add spatial LRN * add nms (cpu) to region layer * add max pooling with argmax ( and a fix to limits.hpp) * add max unpooling layer * rename DNN_TARGET_CUDA_FP32 to DNN_TARGET_CUDA * update supportBackend to be more rigorous * remove stray include from preventing non-cuda build * include op_cuda.hpp outside condition #if * refactoring, fixes and many optimizations * drop DNN_TARGET_CUDA_FP64 * fix gcc errors * increase max. tensor rank limit to six * add Interp layer * drop custom layers; use BackendNode * vectorize activation kernels * fixes for gcc * remove wrong assertion * fix broken assertion in unpooling primitive * fix build errors in non-CUDA build * completely remove workspace from public API * fix permute layer * enable accuracy and perf. tests for DNN_TARGET_CUDA * add asynchronous forward * vectorize eltwise ops * vectorize fill kernel * fixes for gcc * remove CSL headers from public API * remove csl header source group from cmake * update min. cudnn version in cmake * add numerically stable FP32 log1pexp * refactor code * add FP16 specialization to cudnn based tensor addition * vectorize scale1 and bias1 + minor refactoring * fix doxygen build * fix invalid alignment assertion * clear backend wrappers before allocateLayers * ignore memory lock failures * do not allocate internal blobs * integrate NVTX * add numerically stable half precision log1pexp * fix indentation, following coding style, improve docs * remove accidental modification of IE code * Revert "add asynchronous forward" This reverts commit 1154b9da9da07e9b52f8a81bdcea48cf31c56f70. * [cmake] throw error for unsupported CC versions * fix rebase issues * add more docs, refactor code, fix bugs * minor refactoring and fixes * resolve warnings/errors from clang * remove haveCUDA() checks from supportBackend() * remove NVTX integration * changes based on review comments * avoid exception when no CUDA device is present * add color code for CUDA in Net::dump
5 years ago
set(CC_LIST ${CUDA_ARCH_BIN})
separate_arguments(CC_LIST)
foreach(cc ${CC_LIST})
if(cc VERSION_LESS 3.0)
message(FATAL_ERROR "CUDA backend for DNN module requires CC 3.0 or higher. Please remove unsupported architectures from CUDA_ARCH_BIN option or disable OPENCV_DNN_CUDA=OFF.")
Merge pull request #14827 from YashasSamaga:cuda4dnn-csl-low CUDA backend for the DNN module * stub cuda4dnn design * minor fixes for tests and doxygen * add csl public api directory to module headers * add low-level CSL components * add high-level CSL components * integrate csl::Tensor into backbone code * switch to CPU iff unsupported; otherwise, fail on error * add fully connected layer * add softmax layer * add activation layers * support arbitary rank TensorDescriptor * pass input wrappers to `initCUDA()` * add 1d/2d/3d-convolution * add pooling layer * reorganize and refactor code * fixes for gcc, clang and doxygen; remove cxx14/17 code * add blank_layer * add LRN layer * add rounding modes for pooling layer * split tensor.hpp into tensor.hpp and tensor_ops.hpp * add concat layer * add scale layer * add batch normalization layer * split math.cu into activations.cu and math.hpp * add eltwise layer * add flatten layer * add tensor transform api * add asymmetric padding support for convolution layer * add reshape layer * fix rebase issues * add permute layer * add padding support for concat layer * refactor and reorganize code * add normalize layer * optimize bias addition in scale layer * add prior box layer * fix and optimize normalize layer * add asymmetric padding support for pooling layer * add event API * improve pooling performance for some padding scenarios * avoid over-allocation of compute resources to kernels * improve prior box performance * enable layer fusion * add const layer * add resize layer * add slice layer * add padding layer * add deconvolution layer * fix channelwise ReLU initialization * add vector traits * add vectorized versions of relu, clipped_relu, power * add vectorized concat kernels * improve concat_with_offsets performance * vectorize scale and bias kernels * add support for multi-billion element tensors * vectorize prior box kernels * fix address alignment check * improve bias addition performance of conv/deconv/fc layers * restructure code for supporting multiple targets * add DNN_TARGET_CUDA_FP64 * add DNN_TARGET_FP16 * improve vectorization * add region layer * improve tensor API, add dynamic ranks 1. use ManagedPtr instead of a Tensor in backend wrapper 2. add new methods to tensor classes - size_range: computes the combined size of for a given axis range - tensor span/view can be constructed from a raw pointer and shape 3. the tensor classes can change their rank at runtime (previously rank was fixed at compile-time) 4. remove device code from tensor classes (as they are unused) 5. enforce strict conditions on tensor class APIs to improve debugging ability * fix parametric relu activation * add squeeze/unsqueeze tensor API * add reorg layer * optimize permute and enable 2d permute * enable 1d and 2d slice * add split layer * add shuffle channel layer * allow tensors of different ranks in reshape primitive * patch SliceOp to allow Crop Layer * allow extra shape inputs in reshape layer * use `std::move_backward` instead of `std::move` for insert in resizable_static_array * improve workspace management * add spatial LRN * add nms (cpu) to region layer * add max pooling with argmax ( and a fix to limits.hpp) * add max unpooling layer * rename DNN_TARGET_CUDA_FP32 to DNN_TARGET_CUDA * update supportBackend to be more rigorous * remove stray include from preventing non-cuda build * include op_cuda.hpp outside condition #if * refactoring, fixes and many optimizations * drop DNN_TARGET_CUDA_FP64 * fix gcc errors * increase max. tensor rank limit to six * add Interp layer * drop custom layers; use BackendNode * vectorize activation kernels * fixes for gcc * remove wrong assertion * fix broken assertion in unpooling primitive * fix build errors in non-CUDA build * completely remove workspace from public API * fix permute layer * enable accuracy and perf. tests for DNN_TARGET_CUDA * add asynchronous forward * vectorize eltwise ops * vectorize fill kernel * fixes for gcc * remove CSL headers from public API * remove csl header source group from cmake * update min. cudnn version in cmake * add numerically stable FP32 log1pexp * refactor code * add FP16 specialization to cudnn based tensor addition * vectorize scale1 and bias1 + minor refactoring * fix doxygen build * fix invalid alignment assertion * clear backend wrappers before allocateLayers * ignore memory lock failures * do not allocate internal blobs * integrate NVTX * add numerically stable half precision log1pexp * fix indentation, following coding style, improve docs * remove accidental modification of IE code * Revert "add asynchronous forward" This reverts commit 1154b9da9da07e9b52f8a81bdcea48cf31c56f70. * [cmake] throw error for unsupported CC versions * fix rebase issues * add more docs, refactor code, fix bugs * minor refactoring and fixes * resolve warnings/errors from clang * remove haveCUDA() checks from supportBackend() * remove NVTX integration * changes based on review comments * avoid exception when no CUDA device is present * add color code for CUDA in Net::dump
5 years ago
endif()
endforeach()
unset(CC_LIST)
else()
set(sources_options ${sources_options} EXCLUDE_CUDA)
endif()
if(HAVE_TENGINE)
list(APPEND include_dirs ${TENGINE_INCLUDE_DIRS})
list(APPEND libs -Wl,--whole-archive ${TENGINE_LIBRARIES} -Wl,--no-whole-archive)
endif()
Merge pull request #20406 from MarkGHX:gsoc_2021_webnn [GSoC] OpenCV.js: Accelerate OpenCV.js DNN via WebNN * Add WebNN backend for OpenCV DNN Module Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp Add WebNN head files into OpenCV 3rd partiy files Create webnn.hpp update cmake Complete README and add OpenCVDetectWebNN.cmake file add webnn.cpp Modify webnn.cpp Can successfully compile the codes for creating a MLContext Update webnn.cpp Update README.md Update README.md Update README.md Update README.md Update cmake files and update README.md Update OpenCVDetectWebNN.cmake and README.md Update OpenCVDetectWebNN.cmake Fix OpenCVDetectWebNN.cmake and update README.md Add source webnn_cpp.cpp and libary libwebnn_proc.so Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp update dnn.cpp update op_webnn update op_webnn Update op_webnn.hpp update op_webnn.cpp & hpp Update op_webnn.hpp Update op_webnn update the skeleton Update op_webnn.cpp Update op_webnn Update op_webnn.cpp Update op_webnn.cpp Update op_webnn.hpp update op_webnn update op_webnn Solved the problems of released variables. Fixed the bugs in op_webnn.cpp Implement op_webnn Implement Relu by WebNN API Update dnn.cpp for better test Update elementwise_layers.cpp Implement ReLU6 Update elementwise_layers.cpp Implement SoftMax using WebNN API Implement Reshape by WebNN API Implement PermuteLayer by WebNN API Implement PoolingLayer using WebNN API Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Implement poolingLayer by WebNN API and add more detailed logs Update dnn.cpp Update dnn.cpp Remove redundant codes and add more logs for poolingLayer Add more logs in the pooling layer implementation Fix the indent issue and resolve the compiling issue Fix the build problems Fix the build issue FIx the build issue Update dnn.cpp Update dnn.cpp * Fix the build issue * Implement BatchNorm Layer by WebNN API * Update convolution_layer.cpp This is a temporary file for Conv2d layer implementation * Integrate some general functions into op_webnn.cpp&hpp * Update const_layer.cpp * Update convolution_layer.cpp Still have some bugs that should be fixed. * Update conv2d layer and fc layer still have some problems to be fixed. * update constLayer, conv layer, fc layer There are still some bugs to be fixed. * Fix the build issue * Update concat_layer.cpp Still have some bugs to be fixed. * Update conv2d layer, fully connected layer and const layer * Update convolution_layer.cpp * Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron) * Delete bib19450.aux * Add WebNN backend for OpenCV DNN Module Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp Add WebNN head files into OpenCV 3rd partiy files Create webnn.hpp update cmake Complete README and add OpenCVDetectWebNN.cmake file add webnn.cpp Modify webnn.cpp Can successfully compile the codes for creating a MLContext Update webnn.cpp Update README.md Update README.md Update README.md Update README.md Update cmake files and update README.md Update OpenCVDetectWebNN.cmake and README.md Update OpenCVDetectWebNN.cmake Fix OpenCVDetectWebNN.cmake and update README.md Add source webnn_cpp.cpp and libary libwebnn_proc.so Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp update dnn.cpp update op_webnn update op_webnn Update op_webnn.hpp update op_webnn.cpp & hpp Update op_webnn.hpp Update op_webnn update the skeleton Update op_webnn.cpp Update op_webnn Update op_webnn.cpp Update op_webnn.cpp Update op_webnn.hpp update op_webnn update op_webnn Solved the problems of released variables. Fixed the bugs in op_webnn.cpp Implement op_webnn Implement Relu by WebNN API Update dnn.cpp for better test Update elementwise_layers.cpp Implement ReLU6 Update elementwise_layers.cpp Implement SoftMax using WebNN API Implement Reshape by WebNN API Implement PermuteLayer by WebNN API Implement PoolingLayer using WebNN API Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Implement poolingLayer by WebNN API and add more detailed logs Update dnn.cpp Update dnn.cpp Remove redundant codes and add more logs for poolingLayer Add more logs in the pooling layer implementation Fix the indent issue and resolve the compiling issue Fix the build problems Fix the build issue FIx the build issue Update dnn.cpp Update dnn.cpp * Fix the build issue * Implement BatchNorm Layer by WebNN API * Update convolution_layer.cpp This is a temporary file for Conv2d layer implementation * Integrate some general functions into op_webnn.cpp&hpp * Update const_layer.cpp * Update convolution_layer.cpp Still have some bugs that should be fixed. * Update conv2d layer and fc layer still have some problems to be fixed. * update constLayer, conv layer, fc layer There are still some bugs to be fixed. * Update conv2d layer, fully connected layer and const layer * Update convolution_layer.cpp * Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron) * Update dnn.cpp * Fix Error in dnn.cpp * Resolve duplication in conditions in convolution_layer.cpp * Fixed the issues in the comments * Fix building issue * Update tutorial * Fixed comments * Address the comments * Update CMakeLists.txt * Offer more accurate perf test on native * Add better perf tests for both native and web * Modify per tests for better results * Use more latest version of Electron * Support latest WebNN Clamp op * Add definition of HAVE_WEBNN macro * Support group convolution * Implement Scale_layer using WebNN * Add Softmax option for native classification example * Fix comments * Fix comments
3 years ago
set(webnn_srcs "")
if(NOT EMSCRIPTEN)
if(HAVE_WEBNN)
list(APPEND include_dirs ${WEBNN_HEADER_DIRS})
list(APPEND include_dirs ${WEBNN_INCLUDE_DIRS})
list(APPEND libs -Wl,--whole-archive ${WEBNN_LIBRARIES} -Wl,--no-whole-archive)
list(APPEND webnn_srcs $ENV{WEBNN_NATIVE_DIR}/gen/src/webnn/webnn_cpp.cpp)
endif()
endif()
ocv_module_include_directories(${include_dirs})
if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
ocv_append_source_files_cxx_compiler_options(fw_srcs "-Wno-suggest-override") # GCC
ocv_append_source_files_cxx_compiler_options(fw_srcs "-Wno-array-bounds") # GCC 9.3.0 (Ubuntu 20.04)
elseif(CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
ocv_append_source_files_cxx_compiler_options(fw_srcs "-Wno-inconsistent-missing-override") # Clang
endif()
set(dnn_runtime_libs "")
if(INF_ENGINE_TARGET)
set(use_nn_builder OFF)
if(TARGET inference_engine_nn_builder OR # custom imported target
TARGET IE::inference_engine_nn_builder OR # default imported target via InferenceEngineConfig.cmake
INF_ENGINE_RELEASE VERSION_LESS "2020000000") # compatibility with older versions on IE
set(use_nn_builder ON)
endif()
ocv_option(OPENCV_DNN_IE_NN_BUILDER_2019 "Build with Inference Engine NN Builder API support" ${use_nn_builder}) # future: NOT HAVE_NGRAPH
if(OPENCV_DNN_IE_NN_BUILDER_2019)
message(STATUS "DNN: Enabling Inference Engine NN Builder API support")
add_definitions(-DHAVE_DNN_IE_NN_BUILDER_2019=1)
endif()
list(APPEND dnn_runtime_libs ${INF_ENGINE_TARGET})
endif()
if(HAVE_NGRAPH)
message(STATUS "DNN: Enabling Inference Engine nGraph API support")
add_definitions(-DHAVE_DNN_NGRAPH)
list(APPEND dnn_runtime_libs ngraph::ngraph)
endif()
Merge pull request #20406 from MarkGHX:gsoc_2021_webnn [GSoC] OpenCV.js: Accelerate OpenCV.js DNN via WebNN * Add WebNN backend for OpenCV DNN Module Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp Add WebNN head files into OpenCV 3rd partiy files Create webnn.hpp update cmake Complete README and add OpenCVDetectWebNN.cmake file add webnn.cpp Modify webnn.cpp Can successfully compile the codes for creating a MLContext Update webnn.cpp Update README.md Update README.md Update README.md Update README.md Update cmake files and update README.md Update OpenCVDetectWebNN.cmake and README.md Update OpenCVDetectWebNN.cmake Fix OpenCVDetectWebNN.cmake and update README.md Add source webnn_cpp.cpp and libary libwebnn_proc.so Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp update dnn.cpp update op_webnn update op_webnn Update op_webnn.hpp update op_webnn.cpp & hpp Update op_webnn.hpp Update op_webnn update the skeleton Update op_webnn.cpp Update op_webnn Update op_webnn.cpp Update op_webnn.cpp Update op_webnn.hpp update op_webnn update op_webnn Solved the problems of released variables. Fixed the bugs in op_webnn.cpp Implement op_webnn Implement Relu by WebNN API Update dnn.cpp for better test Update elementwise_layers.cpp Implement ReLU6 Update elementwise_layers.cpp Implement SoftMax using WebNN API Implement Reshape by WebNN API Implement PermuteLayer by WebNN API Implement PoolingLayer using WebNN API Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Implement poolingLayer by WebNN API and add more detailed logs Update dnn.cpp Update dnn.cpp Remove redundant codes and add more logs for poolingLayer Add more logs in the pooling layer implementation Fix the indent issue and resolve the compiling issue Fix the build problems Fix the build issue FIx the build issue Update dnn.cpp Update dnn.cpp * Fix the build issue * Implement BatchNorm Layer by WebNN API * Update convolution_layer.cpp This is a temporary file for Conv2d layer implementation * Integrate some general functions into op_webnn.cpp&hpp * Update const_layer.cpp * Update convolution_layer.cpp Still have some bugs that should be fixed. * Update conv2d layer and fc layer still have some problems to be fixed. * update constLayer, conv layer, fc layer There are still some bugs to be fixed. * Fix the build issue * Update concat_layer.cpp Still have some bugs to be fixed. * Update conv2d layer, fully connected layer and const layer * Update convolution_layer.cpp * Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron) * Delete bib19450.aux * Add WebNN backend for OpenCV DNN Module Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp Add WebNN head files into OpenCV 3rd partiy files Create webnn.hpp update cmake Complete README and add OpenCVDetectWebNN.cmake file add webnn.cpp Modify webnn.cpp Can successfully compile the codes for creating a MLContext Update webnn.cpp Update README.md Update README.md Update README.md Update README.md Update cmake files and update README.md Update OpenCVDetectWebNN.cmake and README.md Update OpenCVDetectWebNN.cmake Fix OpenCVDetectWebNN.cmake and update README.md Add source webnn_cpp.cpp and libary libwebnn_proc.so Update dnn.cpp Update dnn.cpp Update dnn.cpp Update dnn.cpp update dnn.cpp update op_webnn update op_webnn Update op_webnn.hpp update op_webnn.cpp & hpp Update op_webnn.hpp Update op_webnn update the skeleton Update op_webnn.cpp Update op_webnn Update op_webnn.cpp Update op_webnn.cpp Update op_webnn.hpp update op_webnn update op_webnn Solved the problems of released variables. Fixed the bugs in op_webnn.cpp Implement op_webnn Implement Relu by WebNN API Update dnn.cpp for better test Update elementwise_layers.cpp Implement ReLU6 Update elementwise_layers.cpp Implement SoftMax using WebNN API Implement Reshape by WebNN API Implement PermuteLayer by WebNN API Implement PoolingLayer using WebNN API Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Update pooling_layer.cpp Implement poolingLayer by WebNN API and add more detailed logs Update dnn.cpp Update dnn.cpp Remove redundant codes and add more logs for poolingLayer Add more logs in the pooling layer implementation Fix the indent issue and resolve the compiling issue Fix the build problems Fix the build issue FIx the build issue Update dnn.cpp Update dnn.cpp * Fix the build issue * Implement BatchNorm Layer by WebNN API * Update convolution_layer.cpp This is a temporary file for Conv2d layer implementation * Integrate some general functions into op_webnn.cpp&hpp * Update const_layer.cpp * Update convolution_layer.cpp Still have some bugs that should be fixed. * Update conv2d layer and fc layer still have some problems to be fixed. * update constLayer, conv layer, fc layer There are still some bugs to be fixed. * Update conv2d layer, fully connected layer and const layer * Update convolution_layer.cpp * Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron) * Update dnn.cpp * Fix Error in dnn.cpp * Resolve duplication in conditions in convolution_layer.cpp * Fixed the issues in the comments * Fix building issue * Update tutorial * Fixed comments * Address the comments * Update CMakeLists.txt * Offer more accurate perf test on native * Add better perf tests for both native and web * Modify per tests for better results * Use more latest version of Electron * Support latest WebNN Clamp op * Add definition of HAVE_WEBNN macro * Support group convolution * Implement Scale_layer using WebNN * Add Softmax option for native classification example * Fix comments * Fix comments
3 years ago
ocv_glob_module_sources(${sources_options} SOURCES ${fw_srcs} ${webnn_srcs})
ocv_create_module(${libs} ${dnn_runtime_libs})
ocv_add_samples()
ocv_add_accuracy_tests(${dnn_runtime_libs})
set(perf_path "${CMAKE_CURRENT_LIST_DIR}/perf")
file(GLOB_RECURSE perf_srcs "${perf_path}/*.cpp")
file(GLOB_RECURSE perf_hdrs "${perf_path}/*.hpp" "${perf_path}/*.h")
ocv_add_perf_tests(${INF_ENGINE_TARGET}
FILES test_common "${CMAKE_CURRENT_LIST_DIR}/test/test_common.hpp" "${CMAKE_CURRENT_LIST_DIR}/test/test_common.impl.hpp"
FILES Src ${perf_srcs}
FILES Include ${perf_hdrs}
)
ocv_option(OPENCV_DNN_PERF_CAFFE "Add performance tests of Caffe framework" OFF)
ocv_option(OPENCV_DNN_PERF_CLCAFFE "Add performance tests of clCaffe framework" OFF)
if(BUILD_PERF_TESTS)
if (OPENCV_DNN_PERF_CAFFE
OR ${the_module}_PERF_CAFFE # compatibility for deprecated option
)
find_package(Caffe QUIET)
if (Caffe_FOUND)
add_definitions(-DHAVE_CAFFE=1)
ocv_target_link_libraries(opencv_perf_dnn caffe)
endif()
elseif(OPENCV_DNN_PERF_CLCAFFE
OR ${the_module}_PERF_CAFFE # compatibility for deprecated option
)
find_package(Caffe QUIET)
if (Caffe_FOUND)
add_definitions(-DHAVE_CLCAFFE=1)
ocv_target_link_libraries(opencv_perf_dnn caffe)
endif()
endif()
endif()