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 )
ocv_add_module ( dnn opencv_core opencv_imgproc WRAP python java 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 ( )
ocv_option ( OPENCV_DNN_CUDA "Build with CUDA support" HAVE_CUDA AND HAVE_CUBLAS AND HAVE_CUDNN )
if ( OPENCV_DNN_CUDA AND HAVE_CUDA AND HAVE_CUBLAS AND HAVE_CUDNN )
add_definitions ( -DCV_CUDA4DNN=1 )
endif ( )
ocv_cmake_hook_append ( INIT_MODULE_SOURCES_opencv_dnn "${CMAKE_CURRENT_LIST_DIR}/cmake/hooks/INIT_MODULE_SOURCES_opencv_dnn.cmake" )
if ( MSVC )
add_definitions ( -D_CRT_SECURE_NO_WARNINGS=1 )
ocv_warnings_disable ( CMAKE_CXX_FLAGS /wd4244 /wd4267 /wd4018 /wd4355 /wd4800 /wd4251 /wd4996 /wd4146
/ w d 4 3 0 5 / w d 4 1 2 7 / w d 4 1 0 0 / w d 4 5 1 2 / w d 4 1 2 5 / w d 4 3 8 9 / w d 4 5 1 0 / w d 4 6 1 0
/ w d 4 7 0 2 / w d 4 4 5 6 / w d 4 4 5 7 / w d 4 0 6 5 / w d 4 3 1 0 / w d 4 6 6 1 / w d 4 5 0 6
)
else ( )
ocv_warnings_disable ( CMAKE_CXX_FLAGS -Wno-deprecated -Wmissing-prototypes -Wmissing-declarations -Wshadow
- W u n u s e d - p a r a m e t e r - W s i g n - c o m p a r e
)
endif ( )
if ( HAVE_CUDA )
ocv_warnings_disable ( CMAKE_CXX_FLAGS -Wundef )
endif ( )
if ( NOT HAVE_CXX11 )
ocv_warnings_disable ( CMAKE_CXX_FLAGS -Wno-undef ) # LANG_CXX11 from protobuf files
endif ( )
if ( APPLE_FRAMEWORK )
ocv_warnings_disable ( CMAKE_CXX_FLAGS -Wshorten-64-to-32 )
endif ( )
if ( ANDROID )
add_definitions ( -DDISABLE_POSIX_MEMALIGN -DTH_DISABLE_HEAP_TRACKING )
endif ( )
if ( NOT BUILD_PROTOBUF )
add_definitions ( -DOPENCV_DNN_EXTERNAL_PROTOBUF=1 )
endif ( )
add_definitions ( -DHAVE_PROTOBUF=1 )
#suppress warnings in autogenerated caffe.pb.* files
ocv_warnings_disable ( CMAKE_CXX_FLAGS
/ w d 4 1 2 5 / w d 4 2 6 7 / w d 4 1 2 7 / w d 4 2 4 4 / w d 4 5 1 2 / w d 4 7 0 2
/ w d 4 4 5 6 / w d 4 5 1 0 / w d 4 6 1 0 / w d 4 8 0 0
/ w d 4 7 0 1 / w d 4 7 0 3 # potentially uninitialized local/pointer variable 'value' used
/ w d 4 5 0 5 # unreferenced local function has been removed
/ w d 4 4 5 8 # declaration of 'x' hides class member. GCC still works, MSVC bug is here: https://developercommunity.visualstudio.com/content/problem/219311/c-c4458-declaration-hides-class-member-warning-iss.html
- w d 8 5 8 - w d 2 1 9 6
- W i n v a l i d - o f f s e t o f # Apple Clang (attr_value.pb.cc)
)
if ( PROTOBUF_UPDATE_FILES )
file ( GLOB proto_files "${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 ( )
set ( include_dirs ${ fw_inc } )
set ( sources_options "" )
set ( libs libprotobuf ${ 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 ( )
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
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 )
ocv_option ( OPENCV_DNN_IE_NN_BUILDER_2019 "Build with Inference Engine NN Builder API support" ON )
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 ( )
ocv_glob_module_sources ( ${ sources_options } SOURCES ${ fw_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 }
F I L E S t e s t _ c o m m o n " $ { C M A K E _ C U R R E N T _ L I S T _ D I R } / t e s t / t e s t _ c o m m o n . h p p " " $ { C M A K E _ C U R R E N T _ L I S T _ D I R } / t e s t / t e s t _ c o m m o n . i m p l . h p p "
F I L E S S r c $ { p e r f _ s r c s }
F I L E S I n c l u d e $ { p e r f _ h d r s }
)
ocv_option ( ${ the_module } _PERF_CAFFE "Add performance tests of Caffe framework" OFF )
ocv_option ( ${ the_module } _PERF_CLCAFFE "Add performance tests of clCaffe framework" OFF )
if ( BUILD_PERF_TESTS )
if ( ${ the_module } _PERF_CAFFE )
find_package ( Caffe QUIET )
if ( Caffe_FOUND )
add_definitions ( -DHAVE_CAFFE=1 )
ocv_target_link_libraries ( opencv_perf_dnn caffe )
endif ( )
elseif ( ${ the_module } _PERF_CLCAFFE )
find_package ( Caffe QUIET )
if ( Caffe_FOUND )
add_definitions ( -DHAVE_CLCAFFE=1 )
ocv_target_link_libraries ( opencv_perf_dnn caffe )
endif ( )
endif ( )
endif ( )
