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21f381238d
...
b130ae7c9a
@ -1,357 +0,0 @@
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cmake_minimum_required(VERSION 3.10)
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project(darknet_vendor VERSION 0.1.0)
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####################
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# Build options
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####################
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option(DARKNET_CUDA "Build darknet with CUDA support" ON)
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option(DARKNET_OPENCV "Build darknet with OpenCV support" ON)
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####################
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# Download Darknet
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####################
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if(CMAKE_VERSION VERSION_LESS "3.11")
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include("cmake/FetchContent.cmake")
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else()
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include(FetchContent)
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endif()
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# Same version as Debian Buster
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set(darknet_git_tag "61c9d02ec461e30d55762ec7669d6a1d3c356fb2")
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FetchContent_Declare(darknet-download
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GIT_REPOSITORY
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"https://github.com/pjreddie/darknet.git"
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GIT_TAG
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${darknet_git_tag}
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)
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FetchContent_GetProperties(darknet-download)
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if(NOT darknet-download_POPULATED)
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FetchContent_Populate(darknet-download)
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endif()
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set(darknet_src_dir "${darknet-download_SOURCE_DIR}")
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####################
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# Classify files
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####################
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set(darknet_public_headers
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"${CMAKE_CURRENT_BINARY_DIR}/darknet-src/include/darknet.h"
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)
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set(darknet_cuda_sources
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"${darknet_src_dir}/src/activation_kernels.cu"
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"${darknet_src_dir}/src/avgpool_layer_kernels.cu"
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"${darknet_src_dir}/src/blas_kernels.cu"
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"${darknet_src_dir}/src/col2im_kernels.cu"
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"${darknet_src_dir}/src/convolutional_kernels.cu"
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"${darknet_src_dir}/src/crop_layer_kernels.cu"
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"${darknet_src_dir}/src/deconvolutional_kernels.cu"
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"${darknet_src_dir}/src/dropout_layer_kernels.cu"
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"${darknet_src_dir}/src/im2col_kernels.cu"
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"${darknet_src_dir}/src/maxpool_layer_kernels.cu"
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)
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set(darknet_exec_c_sources
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"${darknet_src_dir}/examples/art.c"
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"${darknet_src_dir}/examples/captcha.c"
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"${darknet_src_dir}/examples/cifar.c"
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"${darknet_src_dir}/examples/classifier.c"
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"${darknet_src_dir}/examples/coco.c"
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"${darknet_src_dir}/examples/darknet.c"
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"${darknet_src_dir}/examples/detector.c"
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"${darknet_src_dir}/examples/go.c"
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"${darknet_src_dir}/examples/instance-segmenter.c"
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"${darknet_src_dir}/examples/lsd.c"
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"${darknet_src_dir}/examples/nightmare.c"
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"${darknet_src_dir}/examples/super.c"
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"${darknet_src_dir}/examples/rnn.c"
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"${darknet_src_dir}/examples/regressor.c"
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"${darknet_src_dir}/examples/segmenter.c"
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"${darknet_src_dir}/examples/tag.c"
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"${darknet_src_dir}/examples/yolo.c"
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)
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set(darknet_lib_cpp_sources
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"${darknet_src_dir}/src/image_opencv.cpp"
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)
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set(darknet_lib_c_sources
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"${darknet_src_dir}/src/activation_layer.c"
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"${darknet_src_dir}/src/activations.c"
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"${darknet_src_dir}/src/avgpool_layer.c"
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"${darknet_src_dir}/src/batchnorm_layer.c"
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"${darknet_src_dir}/src/blas.c"
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"${darknet_src_dir}/src/box.c"
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"${darknet_src_dir}/src/col2im.c"
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# "${darknet_src_dir}/src/compare.c"
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"${darknet_src_dir}/src/connected_layer.c"
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"${darknet_src_dir}/src/convolutional_layer.c"
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"${darknet_src_dir}/src/cost_layer.c"
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"${darknet_src_dir}/src/crnn_layer.c"
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"${darknet_src_dir}/src/crop_layer.c"
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"${darknet_src_dir}/src/cuda.c"
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"${darknet_src_dir}/src/data.c"
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"${darknet_src_dir}/src/deconvolutional_layer.c"
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"${darknet_src_dir}/src/demo.c"
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"${darknet_src_dir}/src/detection_layer.c"
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"${darknet_src_dir}/src/dropout_layer.c"
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"${darknet_src_dir}/src/gemm.c"
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"${darknet_src_dir}/src/gru_layer.c"
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"${darknet_src_dir}/src/im2col.c"
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"${darknet_src_dir}/src/image.c"
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"${darknet_src_dir}/src/iseg_layer.c"
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"${darknet_src_dir}/src/l2norm_layer.c"
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"${darknet_src_dir}/src/layer.c"
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"${darknet_src_dir}/src/list.c"
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"${darknet_src_dir}/src/local_layer.c"
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"${darknet_src_dir}/src/logistic_layer.c"
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"${darknet_src_dir}/src/lstm_layer.c"
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"${darknet_src_dir}/src/matrix.c"
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"${darknet_src_dir}/src/maxpool_layer.c"
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"${darknet_src_dir}/src/network.c"
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"${darknet_src_dir}/src/normalization_layer.c"
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"${darknet_src_dir}/src/option_list.c"
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"${darknet_src_dir}/src/parser.c"
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"${darknet_src_dir}/src/region_layer.c"
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"${darknet_src_dir}/src/reorg_layer.c"
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"${darknet_src_dir}/src/rnn_layer.c"
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"${darknet_src_dir}/src/route_layer.c"
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"${darknet_src_dir}/src/shortcut_layer.c"
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"${darknet_src_dir}/src/softmax_layer.c"
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"${darknet_src_dir}/src/tree.c"
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"${darknet_src_dir}/src/upsample_layer.c"
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"${darknet_src_dir}/src/utils.c"
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"${darknet_src_dir}/src/yolo_layer.c"
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)
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####################
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# Darknet Library
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####################
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# set(THREADS_PREFER_PTHREAD_FLAG True)
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find_package(Threads REQUIRED)
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if(DARKNET_CUDA)
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enable_language(CUDA)
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find_package(CUDA REQUIRED)
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# Flags taken from https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/
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if(NOT DEFINED DARKNET_VENDOR_CUDA_FLAGS)
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if(CUDA_VERSION VERSION_GREATER 10)
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set(DARKNET_VENDOR_CUDA_FLAGS
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"-arch=sm_50"
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"-gencode=arch=compute_50,code=sm_50"
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"-gencode=arch=compute_52,code=sm_52"
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"-gencode=arch=compute_60,code=sm_60"
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"-gencode=arch=compute_61,code=sm_61"
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"-gencode=arch=compute_70,code=sm_70"
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"-gencode=arch=compute_75,code=sm_75"
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"-gencode=arch=compute_75,code=compute_75"
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)
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elseif(CUDA_VERSION VERSION_GREATER 9)
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set(DARKNET_VENDOR_CUDA_FLAGS
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"-arch=sm_50"
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"-gencode=arch=compute_50,code=sm_50"
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"-gencode=arch=compute_52,code=sm_52"
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"-gencode=arch=compute_60,code=sm_60"
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"-gencode=arch=compute_61,code=sm_61"
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"-gencode=arch=compute_70,code=sm_70"
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"-gencode=arch=compute_70,code=compute_70"
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)
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endif()
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endif()
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add_library(darknet SHARED ${darknet_lib_c_sources} ${darknet_lib_cpp_sources} ${darknet_cuda_sources})
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target_compile_options(darknet PRIVATE
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$<$<COMPILE_LANGUAGE:CUDA>:${DARKNET_VENDOR_CUDA_FLAGS}>
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)
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target_compile_definitions(darknet PUBLIC GPU=1)
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target_link_libraries(darknet PUBLIC
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cuda cudart cublas curand
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)
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else() # not using CUDA
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add_library(darknet SHARED ${darknet_lib_c_sources} ${darknet_lib_cpp_sources})
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||||||
endif()
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||||||
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set_target_properties(darknet PROPERTIES LINKER_LANGUAGE C)
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target_include_directories(darknet PUBLIC
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$<BUILD_INTERFACE:${darknet_src_dir}/include>
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||||||
$<BUILD_INTERFACE:${darknet_src_dir}/src>
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||||||
$<INSTALL_INTERFACE:include>
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||||||
)
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if(DARKNET_OPENCV)
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find_package(OpenCV REQUIRED)
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target_include_directories(darknet PRIVATE ${OpenCV_INCLUDE_DIRS})
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target_link_libraries(darknet PUBLIC ${OpenCV_LIBRARIES})
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target_compile_definitions(darknet PUBLIC OPENCV=1)
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||||||
endif()
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|
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||||||
# TODO(sloretz) pthread replacement on Windows?
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|
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target_link_libraries(darknet PUBLIC Threads::Threads)
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if(UNIX)
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||||||
# Need to link C math library on some platforms
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||||||
target_link_libraries(darknet PUBLIC m)
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||||||
endif()
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|
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####################
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# Darknet_vendor target
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####################
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|
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# Add interface library for darknet_vendor headers
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||||||
add_library(darknet_vendor INTERFACE)
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||||||
target_include_directories(darknet_vendor INTERFACE
|
|
||||||
$<BUILD_INTERFACE:include>
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|
||||||
$<INSTALL_INTERFACE:include>
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|
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)
|
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||||||
target_link_libraries(darknet_vendor INTERFACE darknet)
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|
||||||
|
|
||||||
configure_file("include/darknet_vendor/version.h.in" "version.h" @ONLY)
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|
||||||
|
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||||||
####################
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|
||||||
# Darknet Executable
|
|
||||||
####################
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|
||||||
add_executable(darknet_exec ${darknet_exec_c_sources})
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||||||
target_link_libraries(darknet_exec PUBLIC darknet)
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set_target_properties(darknet_exec PROPERTIES OUTPUT_NAME "darknet")
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|
||||||
|
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####################
|
|
||||||
# ProjectConfig.cmake
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|
||||||
####################
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|
||||||
|
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||||||
set(INCLUDE_INSTALL_DIR "include")
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||||||
set(SHARE_CMAKE_INSTALL_DIR "share/darknet_vendor/cmake")
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||||||
set(EXEC_INSTALL_DIR "bin")
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||||||
include(CMakePackageConfigHelpers)
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||||||
configure_package_config_file(
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|
||||||
"cmake/darknet_vendor-config.cmake.in"
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|
||||||
"darknet_vendor-config.cmake"
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|
||||||
INSTALL_DESTINATION "${SHARE_CMAKE_INSTALL_DIR}"
|
|
||||||
PATH_VARS "INCLUDE_INSTALL_DIR" "SHARE_CMAKE_INSTALL_DIR" "EXEC_INSTALL_DIR"
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|
||||||
)
|
|
||||||
|
|
||||||
write_basic_package_version_file(
|
|
||||||
"darknet_vendor-version.cmake"
|
|
||||||
COMPATIBILITY SameMajorVersion)
|
|
||||||
|
|
||||||
####################
|
|
||||||
# Installation
|
|
||||||
####################
|
|
||||||
|
|
||||||
# Install darknet public headers
|
|
||||||
install(
|
|
||||||
DIRECTORY
|
|
||||||
"${darknet_src_dir}/include/"
|
|
||||||
DESTINATION
|
|
||||||
"include"
|
|
||||||
)
|
|
||||||
|
|
||||||
# Install darknet_vendor public headers
|
|
||||||
install(
|
|
||||||
DIRECTORY
|
|
||||||
"include/"
|
|
||||||
DESTINATION
|
|
||||||
"include"
|
|
||||||
FILES_MATCHING PATTERN
|
|
||||||
"*.h"
|
|
||||||
)
|
|
||||||
install(
|
|
||||||
FILES
|
|
||||||
"${CMAKE_CURRENT_BINARY_DIR}/version.h"
|
|
||||||
DESTINATION
|
|
||||||
"include/darknet_vendor"
|
|
||||||
)
|
|
||||||
|
|
||||||
# Install darknet library
|
|
||||||
install(
|
|
||||||
TARGETS darknet
|
|
||||||
EXPORT "darknet_vendor-targets"
|
|
||||||
ARCHIVE DESTINATION "lib"
|
|
||||||
LIBRARY DESTINATION "lib"
|
|
||||||
RUNTIME DESTINATION "bin"
|
|
||||||
)
|
|
||||||
|
|
||||||
# Install darknet_vendor interface library
|
|
||||||
install(
|
|
||||||
TARGETS darknet_vendor
|
|
||||||
EXPORT "darknet_vendor-targets"
|
|
||||||
)
|
|
||||||
|
|
||||||
# Install darknet demo executable
|
|
||||||
install(TARGETS darknet_exec DESTINATION "${EXEC_INSTALL_DIR}")
|
|
||||||
|
|
||||||
# Install config files and helper scripts
|
|
||||||
install(
|
|
||||||
DIRECTORY
|
|
||||||
"${darknet_src_dir}/cfg"
|
|
||||||
DESTINATION
|
|
||||||
"share/darknet"
|
|
||||||
)
|
|
||||||
install(
|
|
||||||
DIRECTORY
|
|
||||||
"${darknet_src_dir}/data"
|
|
||||||
DESTINATION
|
|
||||||
"share/darknet"
|
|
||||||
)
|
|
||||||
install(
|
|
||||||
DIRECTORY
|
|
||||||
"${darknet_src_dir}/scripts"
|
|
||||||
DESTINATION
|
|
||||||
"share/darknet"
|
|
||||||
)
|
|
||||||
install(
|
|
||||||
DIRECTORY
|
|
||||||
"${darknet_src_dir}/python"
|
|
||||||
DESTINATION
|
|
||||||
"share/darknet"
|
|
||||||
)
|
|
||||||
|
|
||||||
# Add an entry to the ament index
|
|
||||||
install(
|
|
||||||
FILES
|
|
||||||
resource/darknet_vendor
|
|
||||||
DESTINATION
|
|
||||||
"share/ament_index/resource_index/packages/"
|
|
||||||
)
|
|
||||||
|
|
||||||
# Install license files
|
|
||||||
install(
|
|
||||||
FILES
|
|
||||||
"${darknet_src_dir}/LICENSE"
|
|
||||||
"${darknet_src_dir}/LICENSE.fuck"
|
|
||||||
"${darknet_src_dir}/LICENSE.gen"
|
|
||||||
"${darknet_src_dir}/LICENSE.gpl"
|
|
||||||
"${darknet_src_dir}/LICENSE.meta"
|
|
||||||
"${darknet_src_dir}/LICENSE.mit"
|
|
||||||
"${darknet_src_dir}/LICENSE.v1"
|
|
||||||
DESTINATION
|
|
||||||
"share/darknet"
|
|
||||||
)
|
|
||||||
|
|
||||||
# Install project-config.cmake and project-version.cmake
|
|
||||||
install(
|
|
||||||
FILES
|
|
||||||
"${CMAKE_CURRENT_BINARY_DIR}/darknet_vendor-config.cmake"
|
|
||||||
DESTINATION
|
|
||||||
share/darknet_vendor/cmake
|
|
||||||
)
|
|
||||||
install(
|
|
||||||
FILES
|
|
||||||
"${CMAKE_CURRENT_BINARY_DIR}/darknet_vendor-version.cmake"
|
|
||||||
DESTINATION
|
|
||||||
share/darknet_vendor/cmake
|
|
||||||
)
|
|
||||||
|
|
||||||
# install exported targets
|
|
||||||
install(
|
|
||||||
EXPORT
|
|
||||||
"darknet_vendor-targets"
|
|
||||||
NAMESPACE
|
|
||||||
"darknet_vendor::"
|
|
||||||
DESTINATION
|
|
||||||
"share/darknet_vendor/cmake"
|
|
||||||
)
|
|
||||||
|
|
||||||
@ -1,18 +0,0 @@
|
|||||||
Any contribution that you make to this repository will
|
|
||||||
be under the Apache 2 License, as dictated by that
|
|
||||||
[license](http://www.apache.org/licenses/LICENSE-2.0.html):
|
|
||||||
|
|
||||||
~~~
|
|
||||||
5. Submission of Contributions. Unless You explicitly state otherwise,
|
|
||||||
any Contribution intentionally submitted for inclusion in the Work
|
|
||||||
by You to the Licensor shall be under the terms and conditions of
|
|
||||||
this License, without any additional terms or conditions.
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|
||||||
Notwithstanding the above, nothing herein shall supersede or modify
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|
||||||
the terms of any separate license agreement you may have executed
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|
||||||
with Licensor regarding such Contributions.
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|
||||||
~~~
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|
||||||
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|
||||||
Contributors must sign-off each commit by adding a `Signed-off-by: ...`
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|
||||||
line to commit messages to certify that they have the right to submit
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|
||||||
the code they are contributing to the project according to the
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|
||||||
[Developer Certificate of Origin (DCO)](https://developercertificate.org/).
|
|
||||||
@ -1,202 +0,0 @@
|
|||||||
|
|
||||||
Apache License
|
|
||||||
Version 2.0, January 2004
|
|
||||||
http://www.apache.org/licenses/
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|
||||||
|
|
||||||
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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|
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1. Definitions.
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END OF TERMS AND CONDITIONS
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APPENDIX: How to apply the Apache License to your work.
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To apply the Apache License to your work, attach the following
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Unless required by applicable law or agreed to in writing, software
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See the License for the specific language governing permissions and
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|
||||||
limitations under the License.
|
|
||||||
@ -1,68 +0,0 @@
|
|||||||
# darknet_vendor
|
|
||||||
|
|
||||||
This is a CMake wrapper around [darknet](https://pjreddie.com/darknet), an open source neural network framework.
|
|
||||||
|
|
||||||
# Building
|
|
||||||
|
|
||||||
```
|
|
||||||
cd darknet_vendor/
|
|
||||||
mkdir build/
|
|
||||||
cd build/
|
|
||||||
cmake -DCMAKE_BUILD_TYPE=Release ..
|
|
||||||
make
|
|
||||||
```
|
|
||||||
|
|
||||||
The package offers two CMake options to control how it is built.
|
|
||||||
|
|
||||||
* `DARKNET_CUDA` (default: `On`) - Whether or not to build with CUDA support
|
|
||||||
* `DARKNET_OPENCV` (default: `On`) - Whether or not to build with OpenCV support
|
|
||||||
|
|
||||||
These can be disabled prior to compiling if you don't need either of those dependencies.
|
|
||||||
|
|
||||||
```
|
|
||||||
cmake -DDARKNET_CUDA=Off -DDARKNET_OPENCV=Off ..
|
|
||||||
```
|
|
||||||
|
|
||||||
# ROS 2 and Colcon
|
|
||||||
|
|
||||||
The package includes `package.xml` and should build fine using ROS 2 Dashing.
|
|
||||||
|
|
||||||
```
|
|
||||||
colcon build --cmake-args -DCMAKE_BUILD_TYPE=Release --packages-select darknet_vendor
|
|
||||||
```
|
|
||||||
|
|
||||||
# Using darknet
|
|
||||||
|
|
||||||
If you are using `ament_cmake`, use `ament_target_dependencies()` as normal.
|
|
||||||
|
|
||||||
```CMake
|
|
||||||
|
|
||||||
find_package(darknet_vendor REQUIRED)
|
|
||||||
|
|
||||||
#...
|
|
||||||
|
|
||||||
ament_target_dependencies(my_library_or_executable_target
|
|
||||||
darknet_vendor)
|
|
||||||
```
|
|
||||||
|
|
||||||
Otherwise, use the exported target `darknet_vendor::darknet_vendor`
|
|
||||||
|
|
||||||
```CMake
|
|
||||||
find_package(darknet_vendor REQUIRED)
|
|
||||||
|
|
||||||
#...
|
|
||||||
|
|
||||||
target_link_libraries(my_library_or_executable_target PUBLIC darknet_vendor::darknet_vendor)
|
|
||||||
```
|
|
||||||
|
|
||||||
Then include the `darknet.h` header in your project to make darknet functions available.
|
|
||||||
|
|
||||||
```C
|
|
||||||
#include <darknet.h>
|
|
||||||
```
|
|
||||||
|
|
||||||
Alternatively, include `darknet_vendor/darknet_vendor.h` to get preprocessor definitions with info about the installed `darknet_vendor` version.
|
|
||||||
|
|
||||||
```C
|
|
||||||
#include <darknet_vendor/darknet_vendor.h>
|
|
||||||
```
|
|
||||||
File diff suppressed because it is too large
Load Diff
@ -1,24 +0,0 @@
|
|||||||
# Distributed under the OSI-approved BSD 3-Clause License. See accompanying
|
|
||||||
# file Copyright.txt or https://cmake.org/licensing for details.
|
|
||||||
|
|
||||||
cmake_minimum_required(VERSION ${CMAKE_VERSION})
|
|
||||||
|
|
||||||
# We name the project and the target for the ExternalProject_Add() call
|
|
||||||
# to something that will highlight to the user what we are working on if
|
|
||||||
# something goes wrong and an error message is produced.
|
|
||||||
|
|
||||||
project(${contentName}-populate NONE)
|
|
||||||
|
|
||||||
include(ExternalProject)
|
|
||||||
ExternalProject_Add(${contentName}-populate
|
|
||||||
${ARG_EXTRA}
|
|
||||||
SOURCE_DIR "${ARG_SOURCE_DIR}"
|
|
||||||
BINARY_DIR "${ARG_BINARY_DIR}"
|
|
||||||
CONFIGURE_COMMAND ""
|
|
||||||
BUILD_COMMAND ""
|
|
||||||
INSTALL_COMMAND ""
|
|
||||||
TEST_COMMAND ""
|
|
||||||
USES_TERMINAL_DOWNLOAD YES
|
|
||||||
USES_TERMINAL_UPDATE YES
|
|
||||||
)
|
|
||||||
|
|
||||||
@ -1,132 +0,0 @@
|
|||||||
CMake - Cross Platform Makefile Generator
|
|
||||||
Copyright 2000-2019 Kitware, Inc. and Contributors
|
|
||||||
All rights reserved.
|
|
||||||
|
|
||||||
Redistribution and use in source and binary forms, with or without
|
|
||||||
modification, are permitted provided that the following conditions
|
|
||||||
are met:
|
|
||||||
|
|
||||||
* Redistributions of source code must retain the above copyright
|
|
||||||
notice, this list of conditions and the following disclaimer.
|
|
||||||
|
|
||||||
* Redistributions in binary form must reproduce the above copyright
|
|
||||||
notice, this list of conditions and the following disclaimer in the
|
|
||||||
documentation and/or other materials provided with the distribution.
|
|
||||||
|
|
||||||
* Neither the name of Kitware, Inc. nor the names of Contributors
|
|
||||||
may be used to endorse or promote products derived from this
|
|
||||||
software without specific prior written permission.
|
|
||||||
|
|
||||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
|
|
||||||
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
|
|
||||||
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
|
|
||||||
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
|
|
||||||
HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
|
||||||
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
|
|
||||||
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
|
|
||||||
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
|
|
||||||
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
|
||||||
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
|
||||||
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
||||||
|
|
||||||
------------------------------------------------------------------------------
|
|
||||||
|
|
||||||
The following individuals and institutions are among the Contributors:
|
|
||||||
|
|
||||||
* Aaron C. Meadows <cmake@shadowguarddev.com>
|
|
||||||
* Adriaan de Groot <groot@kde.org>
|
|
||||||
* Aleksey Avdeev <solo@altlinux.ru>
|
|
||||||
* Alexander Neundorf <neundorf@kde.org>
|
|
||||||
* Alexander Smorkalov <alexander.smorkalov@itseez.com>
|
|
||||||
* Alexey Sokolov <sokolov@google.com>
|
|
||||||
* Alex Merry <alex.merry@kde.org>
|
|
||||||
* Alex Turbov <i.zaufi@gmail.com>
|
|
||||||
* Andreas Pakulat <apaku@gmx.de>
|
|
||||||
* Andreas Schneider <asn@cryptomilk.org>
|
|
||||||
* André Rigland Brodtkorb <Andre.Brodtkorb@ifi.uio.no>
|
|
||||||
* Axel Huebl, Helmholtz-Zentrum Dresden - Rossendorf
|
|
||||||
* Benjamin Eikel
|
|
||||||
* Bjoern Ricks <bjoern.ricks@gmail.com>
|
|
||||||
* Brad Hards <bradh@kde.org>
|
|
||||||
* Christopher Harvey
|
|
||||||
* Christoph Grüninger <foss@grueninger.de>
|
|
||||||
* Clement Creusot <creusot@cs.york.ac.uk>
|
|
||||||
* Daniel Blezek <blezek@gmail.com>
|
|
||||||
* Daniel Pfeifer <daniel@pfeifer-mail.de>
|
|
||||||
* Enrico Scholz <enrico.scholz@informatik.tu-chemnitz.de>
|
|
||||||
* Eran Ifrah <eran.ifrah@gmail.com>
|
|
||||||
* Esben Mose Hansen, Ange Optimization ApS
|
|
||||||
* Geoffrey Viola <geoffrey.viola@asirobots.com>
|
|
||||||
* Google Inc
|
|
||||||
* Gregor Jasny
|
|
||||||
* Helio Chissini de Castro <helio@kde.org>
|
|
||||||
* Ilya Lavrenov <ilya.lavrenov@itseez.com>
|
|
||||||
* Insight Software Consortium <insightsoftwareconsortium.org>
|
|
||||||
* Jan Woetzel
|
|
||||||
* Julien Schueller
|
|
||||||
* Kelly Thompson <kgt@lanl.gov>
|
|
||||||
* Laurent Montel <montel@kde.org>
|
|
||||||
* Konstantin Podsvirov <konstantin@podsvirov.pro>
|
|
||||||
* Mario Bensi <mbensi@ipsquad.net>
|
|
||||||
* Martin Gräßlin <mgraesslin@kde.org>
|
|
||||||
* Mathieu Malaterre <mathieu.malaterre@gmail.com>
|
|
||||||
* Matthaeus G. Chajdas
|
|
||||||
* Matthias Kretz <kretz@kde.org>
|
|
||||||
* Matthias Maennich <matthias@maennich.net>
|
|
||||||
* Michael Hirsch, Ph.D. <www.scivision.co>
|
|
||||||
* Michael Stürmer
|
|
||||||
* Miguel A. Figueroa-Villanueva
|
|
||||||
* Mike Jackson
|
|
||||||
* Mike McQuaid <mike@mikemcquaid.com>
|
|
||||||
* Nicolas Bock <nicolasbock@gmail.com>
|
|
||||||
* Nicolas Despres <nicolas.despres@gmail.com>
|
|
||||||
* Nikita Krupen'ko <krnekit@gmail.com>
|
|
||||||
* NVIDIA Corporation <www.nvidia.com>
|
|
||||||
* OpenGamma Ltd. <opengamma.com>
|
|
||||||
* Patrick Stotko <stotko@cs.uni-bonn.de>
|
|
||||||
* Per Øyvind Karlsen <peroyvind@mandriva.org>
|
|
||||||
* Peter Collingbourne <peter@pcc.me.uk>
|
|
||||||
* Petr Gotthard <gotthard@honeywell.com>
|
|
||||||
* Philip Lowman <philip@yhbt.com>
|
|
||||||
* Philippe Proulx <pproulx@efficios.com>
|
|
||||||
* Raffi Enficiaud, Max Planck Society
|
|
||||||
* Raumfeld <raumfeld.com>
|
|
||||||
* Roger Leigh <rleigh@codelibre.net>
|
|
||||||
* Rolf Eike Beer <eike@sf-mail.de>
|
|
||||||
* Roman Donchenko <roman.donchenko@itseez.com>
|
|
||||||
* Roman Kharitonov <roman.kharitonov@itseez.com>
|
|
||||||
* Ruslan Baratov
|
|
||||||
* Sebastian Holtermann <sebholt@xwmw.org>
|
|
||||||
* Stephen Kelly <steveire@gmail.com>
|
|
||||||
* Sylvain Joubert <joubert.sy@gmail.com>
|
|
||||||
* Thomas Sondergaard <ts@medical-insight.com>
|
|
||||||
* Tobias Hunger <tobias.hunger@qt.io>
|
|
||||||
* Todd Gamblin <tgamblin@llnl.gov>
|
|
||||||
* Tristan Carel
|
|
||||||
* University of Dundee
|
|
||||||
* Vadim Zhukov
|
|
||||||
* Will Dicharry <wdicharry@stellarscience.com>
|
|
||||||
|
|
||||||
See version control history for details of individual contributions.
|
|
||||||
|
|
||||||
The above copyright and license notice applies to distributions of
|
|
||||||
CMake in source and binary form. Third-party software packages supplied
|
|
||||||
with CMake under compatible licenses provide their own copyright notices
|
|
||||||
documented in corresponding subdirectories or source files.
|
|
||||||
|
|
||||||
------------------------------------------------------------------------------
|
|
||||||
|
|
||||||
CMake was initially developed by Kitware with the following sponsorship:
|
|
||||||
|
|
||||||
* National Library of Medicine at the National Institutes of Health
|
|
||||||
as part of the Insight Segmentation and Registration Toolkit (ITK).
|
|
||||||
|
|
||||||
* US National Labs (Los Alamos, Livermore, Sandia) ASC Parallel
|
|
||||||
Visualization Initiative.
|
|
||||||
|
|
||||||
* National Alliance for Medical Image Computing (NAMIC) is funded by the
|
|
||||||
National Institutes of Health through the NIH Roadmap for Medical Research,
|
|
||||||
Grant U54 EB005149.
|
|
||||||
|
|
||||||
* Kitware, Inc.
|
|
||||||
|
|
||||||
@ -1,20 +0,0 @@
|
|||||||
@PACKAGE_INIT@
|
|
||||||
|
|
||||||
find_package(Threads)
|
|
||||||
|
|
||||||
if(@DARKNET_OPENCV@)
|
|
||||||
find_package(OpenCV REQUIRED)
|
|
||||||
endif()
|
|
||||||
|
|
||||||
# Export targets for modern-style CMake code
|
|
||||||
if(NOT TARGET darknet_vendor::darknet_vendor)
|
|
||||||
include("@PACKAGE_SHARE_CMAKE_INSTALL_DIR@/darknet_vendor-targets.cmake")
|
|
||||||
endif()
|
|
||||||
|
|
||||||
# Set standard variables for old-style CMake code
|
|
||||||
set_and_check(darknet_vendor_INCLUDE_DIRS "@PACKAGE_INCLUDE_INSTALL_DIR@")
|
|
||||||
set(darknet_vendor_LIBRARIES "darknet_vendor::darknet_vendor")
|
|
||||||
set_and_check(darknet_vendor_EXECUTABLE "@PACKAGE_EXEC_INSTALL_DIR@/darknet")
|
|
||||||
set(darknet_vendor_VERSION_MAJOR "@PROJECT_VERSION_MAJOR@")
|
|
||||||
set(darknet_vendor_VERSION_MINOR "@PROJECT_VERSION_MINOR@")
|
|
||||||
set(darknet_vendor_VERSION_PATCH "@PROJECT_VERSION_PATCH@")
|
|
||||||
@ -1,22 +0,0 @@
|
|||||||
// Copyright 2019 Open Source Robotics Foundation, Inc.
|
|
||||||
//
|
|
||||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
||||||
// you may not use this file except in compliance with the License.
|
|
||||||
// You may obtain a copy of the License at
|
|
||||||
//
|
|
||||||
// http://www.apache.org/licenses/LICENSE-2.0
|
|
||||||
//
|
|
||||||
// Unless required by applicable law or agreed to in writing, software
|
|
||||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
||||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
||||||
// See the License for the specific language governing permissions and
|
|
||||||
// limitations under the License.
|
|
||||||
|
|
||||||
#ifndef DARKNET_VENDOR__DARKNET_VENDOR_H_
|
|
||||||
#define DARKNET_VENDOR__DARKNET_VENDOR_H_
|
|
||||||
|
|
||||||
#include <darknet.h>
|
|
||||||
#include <darknet_vendor/version.h>
|
|
||||||
|
|
||||||
#endif // DARKNET_VENDOR__DARKNET_VENDOR_H_
|
|
||||||
|
|
||||||
24
darknet_vendor/include/darknet_vendor/version.h.in
generated
24
darknet_vendor/include/darknet_vendor/version.h.in
generated
@ -1,24 +0,0 @@
|
|||||||
// Copyright 2019 Open Source Robotics Foundation, Inc.
|
|
||||||
//
|
|
||||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
||||||
// you may not use this file except in compliance with the License.
|
|
||||||
// You may obtain a copy of the License at
|
|
||||||
//
|
|
||||||
// http://www.apache.org/licenses/LICENSE-2.0
|
|
||||||
//
|
|
||||||
// Unless required by applicable law or agreed to in writing, software
|
|
||||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
||||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
||||||
// See the License for the specific language governing permissions and
|
|
||||||
// limitations under the License.
|
|
||||||
|
|
||||||
#ifndef DARKNET_VENDOR__DARKNET_VERSION_H_
|
|
||||||
#define DARKNET_VENDOR__DARKNET_VERSION_H_
|
|
||||||
|
|
||||||
#define DARKNET_VENDOR_MAJOR_VERSION @PROJECT_VERSION_MAJOR@
|
|
||||||
#define DARKNET_VENDOR_MINOR_VERSION @PROJECT_VERSION_MINOR@
|
|
||||||
#define DARKNET_VENDOR_PATCH_VERSION @PROJECT_VERSION_PATCH@
|
|
||||||
|
|
||||||
#define DARKNET_GIT_TAG "@darknet_git_tag@"
|
|
||||||
|
|
||||||
#endif // DARKNET_VENDOR__DARKNET_VERSION_H_
|
|
||||||
@ -1,26 +0,0 @@
|
|||||||
<?xml version="1.0"?>
|
|
||||||
<package format="2">
|
|
||||||
<name>darknet_vendor</name>
|
|
||||||
<version>0.1.0</version>
|
|
||||||
<description>CMake wrapper around darknet, an open source neural network framework.</description>
|
|
||||||
|
|
||||||
<author email="sloretz@openrobotics.org">Shane Loretz</author>
|
|
||||||
<maintainer email="sloretz@openrobotics.org">Shane Loretz</maintainer>
|
|
||||||
|
|
||||||
<license>Apache License 2.0</license>
|
|
||||||
|
|
||||||
<buildtool_depend>cmake</buildtool_depend>
|
|
||||||
<buildtool_depend>git</buildtool_depend>
|
|
||||||
|
|
||||||
<depend>libopencv-dev</depend>
|
|
||||||
|
|
||||||
<!-- nvidia-cuda-dev is just the libraries to link against -->
|
|
||||||
<exec_depend>nvidia-cuda-dev</exec_depend>
|
|
||||||
|
|
||||||
<!-- nvidia-cuda includes nvidia-cuda-dev plus the nvcc compiler -->
|
|
||||||
<build_depend>nvidia-cuda</build_depend>
|
|
||||||
|
|
||||||
<export>
|
|
||||||
<build_type>cmake</build_type>
|
|
||||||
</export>
|
|
||||||
</package>
|
|
||||||
@ -10,8 +10,8 @@ import threading
|
|||||||
class ImageSaver(Node):
|
class ImageSaver(Node):
|
||||||
def __init__(self):
|
def __init__(self):
|
||||||
super().__init__('image_saver')
|
super().__init__('image_saver')
|
||||||
self.depth_sub = self.create_subscription(Image, '/camera/aligned_depth_to_color/image_raw', self.depth_callback, 1)
|
self.depth_sub = self.create_subscription(Image, '/zed2i/zed_node/depth/depth_registered', self.depth_callback, 10)
|
||||||
self.image_sub = self.create_subscription(Image, '/camera/color/image_raw', self.image_callback, 1)
|
self.image_sub = self.create_subscription(Image, '/zed2i/zed_node/left_raw/image_raw_color', self.image_callback, 10)
|
||||||
self.cv_bridge = CvBridge()
|
self.cv_bridge = CvBridge()
|
||||||
self.depth_image = None
|
self.depth_image = None
|
||||||
self.color_image = None
|
self.color_image = None
|
||||||
@ -20,13 +20,12 @@ class ImageSaver(Node):
|
|||||||
|
|
||||||
def depth_callback(self, data):
|
def depth_callback(self, data):
|
||||||
print("depth cb")
|
print("depth cb")
|
||||||
self.depth_image = self.cv_bridge.imgmsg_to_cv2(data, desired_encoding="passthrough")
|
self.depth_image = self.cv_bridge.imgmsg_to_cv2(data)
|
||||||
self.save_images('d')
|
self.save_images('d')
|
||||||
|
|
||||||
|
|
||||||
def image_callback(self, data):
|
def image_callback(self, data):
|
||||||
print("image cb")
|
print("image cb")
|
||||||
|
|
||||||
self.color_image = self.cv_bridge.imgmsg_to_cv2(data)
|
self.color_image = self.cv_bridge.imgmsg_to_cv2(data)
|
||||||
self.save_images('s')
|
self.save_images('s')
|
||||||
|
|
||||||
@ -52,7 +51,7 @@ class ImageSaver(Node):
|
|||||||
if __name__ == '__main__':
|
if __name__ == '__main__':
|
||||||
rclpy.init()
|
rclpy.init()
|
||||||
image_saver = ImageSaver()
|
image_saver = ImageSaver()
|
||||||
# rate = image_saver.create_rate(1) # 10 Hz
|
rate = image_saver.create_rate(1) # 10 Hz
|
||||||
rclpy.spin(image_saver)
|
rclpy.spin(image_saver)
|
||||||
# while rclpy.ok():
|
# while rclpy.ok():
|
||||||
# image_saver.save_images()
|
# image_saver.save_images()
|
||||||
|
|||||||
@ -1,7 +1,7 @@
|
|||||||
cmake_minimum_required(VERSION 3.8)
|
cmake_minimum_required(VERSION 3.8)
|
||||||
project(find-pose)
|
project(find-pose)
|
||||||
|
|
||||||
add_compile_options(-g)
|
|
||||||
# find dependencies
|
# find dependencies
|
||||||
find_package(ament_cmake REQUIRED)
|
find_package(ament_cmake REQUIRED)
|
||||||
|
|
||||||
@ -59,7 +59,7 @@ find_package(sensor_msgs REQUIRED)
|
|||||||
find_package(pcl_msgs REQUIRED)
|
find_package(pcl_msgs REQUIRED)
|
||||||
|
|
||||||
add_executable(convert_pointcloud_to_depth src/convert_pointcloud_to_depth.cpp)
|
add_executable(convert_pointcloud_to_depth src/convert_pointcloud_to_depth.cpp)
|
||||||
ament_target_dependencies(convert_pointcloud_to_depth ${Libraries} rclcpp_components rclcpp sensor_msgs cv_bridge pcl_conversions)
|
ament_target_dependencies(convert_pointcloud_to_depth ${Libraries} rclcpp_components rclcpp sensor_msgs cv_bridge)
|
||||||
target_link_libraries(convert_pointcloud_to_depth ${PCL_LBRARIES} ${Boost_LIBRARIES})
|
target_link_libraries(convert_pointcloud_to_depth ${PCL_LBRARIES} ${Boost_LIBRARIES})
|
||||||
|
|
||||||
include_directories(
|
include_directories(
|
||||||
|
|||||||
@ -53,7 +53,7 @@ public:
|
|||||||
|
|
||||||
// public Q_SLOTS:
|
// public Q_SLOTS:
|
||||||
// void publish(const find_object::DetectionInfo & info, const find_object::Header & header, const cv::Mat & depth, float depthConstant);
|
// void publish(const find_object::DetectionInfo & info, const find_object::Header & header, const cv::Mat & depth, float depthConstant);
|
||||||
void estimate_pose(float objecWidth, float objectHeight, cv::Point2f point_1, cv::Point2f point_2, cv::Point2f point_3, cv::Point2f point_4);
|
void estimate_pose();
|
||||||
private:
|
private:
|
||||||
cv::Vec3f getDepth(const cv::Mat & depthImage,
|
cv::Vec3f getDepth(const cv::Mat & depthImage,
|
||||||
int x, int y,
|
int x, int y,
|
||||||
@ -69,10 +69,6 @@ private:
|
|||||||
std::string objFramePrefix_;
|
std::string objFramePrefix_;
|
||||||
bool usePnP_;
|
bool usePnP_;
|
||||||
std::shared_ptr<tf2_ros::TransformBroadcaster> tfBroadcaster_;
|
std::shared_ptr<tf2_ros::TransformBroadcaster> tfBroadcaster_;
|
||||||
unsigned int num_objects_;
|
|
||||||
std::vector<double> objectHeight_;
|
|
||||||
std::vector<double> objectWidth_;
|
|
||||||
|
|
||||||
|
|
||||||
};
|
};
|
||||||
|
|
||||||
|
|||||||
@ -63,28 +63,20 @@ FindObjectROS::FindObjectROS(rclcpp::Node * node) :
|
|||||||
// pubInfo_ = node->create_publisher<find_object_2d::msg::DetectionInfo>("info", rclcpp::QoS(1).reliability((rmw_qos_reliability_policy_t)1));
|
// pubInfo_ = node->create_publisher<find_object_2d::msg::DetectionInfo>("info", rclcpp::QoS(1).reliability((rmw_qos_reliability_policy_t)1));
|
||||||
|
|
||||||
// this->connect(this, SIGNAL(objectsFound(const find_object::DetectionInfo &, const find_object::Header &, const cv::Mat &, float)), this, SLOT(publish(const find_object::DetectionInfo &, const find_object::Header &, const cv::Mat &, float)));
|
// this->connect(this, SIGNAL(objectsFound(const find_object::DetectionInfo &, const find_object::Header &, const cv::Mat &, float)), this, SLOT(publish(const find_object::DetectionInfo &, const find_object::Header &, const cv::Mat &, float)));
|
||||||
num_objects_ = 2;
|
|
||||||
objectHeight_.resize(num_objects_);
|
|
||||||
}
|
}
|
||||||
|
|
||||||
void FindObjectROS::estimate_pose(float objectWidth, float objectHeight, cv::Point2f point_1, cv::Point2f point_2, cv::Point2f point_3, cv::Point2f point_4)
|
void FindObjectROS::estimate_pose()
|
||||||
{
|
{
|
||||||
// Read RGB Image
|
// Read RGB Image
|
||||||
cv::Mat rgb_image = cv::imread("/media/psf/freelancing/greenhouse/stereo/stereo_5.jpg");
|
cv::Mat rgb_image = cv::imread("/media/psf/freelancing/greenhouse/yolov3/runs/detect/exp8/stereo_image952.jpeg");
|
||||||
// read depth Image
|
// read depth Image
|
||||||
cv::Mat depth_img = cv::imread("/media/psf/freelancing/greenhouse/depth/depth_4.jpg", cv::IMREAD_ANYDEPTH);
|
cv::Mat depth = cv::imread("/media/psf/freelancing/greenhouse/depth_try1/depth_img_952.jpeg");
|
||||||
// bounding box dimensions
|
// bounding box dimensions
|
||||||
// Convert the image to a single-channel 16-bit image
|
|
||||||
cv::Mat depth;
|
|
||||||
depth_img.convertTo(depth, CV_16UC1);
|
|
||||||
|
|
||||||
std::vector<geometry_msgs::msg::TransformStamped> transforms;
|
std::vector<geometry_msgs::msg::TransformStamped> transforms;
|
||||||
// store bounding boxes. (This should come from yolo ideally)
|
// store bounding boxes. (This should come from yolo ideally)
|
||||||
// float objectWidth = 160; // width of bounding box in pixels
|
float objectWidth = 372; // width of bounding box in pixels
|
||||||
// float objectHeight = 168; // height of bounding box in pixels
|
float objectHeight = 554; // height of bounding box in pixels
|
||||||
// float objectWidth = 155; // width of bounding box in pixels
|
|
||||||
// float objectHeight = 116; // height of bounding box in pixels
|
|
||||||
|
|
||||||
|
|
||||||
geometry_msgs::msg::TransformStamped transform;
|
geometry_msgs::msg::TransformStamped transform;
|
||||||
transform.transform.rotation.x=0;
|
transform.transform.rotation.x=0;
|
||||||
@ -98,30 +90,50 @@ void FindObjectROS::estimate_pose(float objectWidth, float objectHeight, cv::Poi
|
|||||||
transform.header.frame_id = "camera_link";
|
transform.header.frame_id = "camera_link";
|
||||||
// transform.header.stamp.sec = ros::Time::now();
|
// transform.header.stamp.sec = ros::Time::now();
|
||||||
tf2::Quaternion q;
|
tf2::Quaternion q;
|
||||||
float depthConstant = 1.0f/640.8887939453125; // 0.00156033 // 1.0f/cameraInfoMsg->K[4];
|
float depthConstant = 1.0f/641.587158203125;
|
||||||
std::cout << "depthconstant: " << depthConstant << std::endl;
|
std::vector<cv::Point3f> objectPoints(6);
|
||||||
std::vector<cv::Point3f> objectPoints(4);
|
std::vector<cv::Point2f> imagePoints(6);
|
||||||
std::vector<cv::Point2f> imagePoints(4);
|
cv::Vec3f point_1 = this->getDepth(depth,
|
||||||
objectPoints[0] = cv::Point3f(-0.5, -(objectHeight/objectWidth)/2.0f,0);
|
246,665,
|
||||||
objectPoints[1] = cv::Point3f(0.5,-(objectHeight/objectWidth)/2.0f,0);
|
float(depth.cols/2)-0.5f, float(depth.rows/2)-0.5f,
|
||||||
objectPoints[2] = cv::Point3f(0.5,(objectHeight/objectWidth)/2.0f,0);
|
1.0f/depthConstant, 1.0f/depthConstant);
|
||||||
objectPoints[3] = cv::Point3f(-0.5,(objectHeight/objectWidth)/2.0f,0);
|
cv::Vec3f point_2 = this->getDepth(depth,
|
||||||
|
618, 665,
|
||||||
|
float(depth.cols/2)-0.5f, float(depth.rows/2)-0.5f,
|
||||||
|
1.0f/depthConstant, 1.0f/depthConstant);
|
||||||
|
cv::Vec3f point_3 = this->getDepth(depth,
|
||||||
|
618, 111,
|
||||||
|
float(depth.cols/2)-0.5f, float(depth.rows/2)-0.5f,
|
||||||
|
1.0f/depthConstant, 1.0f/depthConstant);
|
||||||
|
cv::Vec3f point_4 = this->getDepth(depth,
|
||||||
|
246, 111,
|
||||||
|
float(depth.cols/2)-0.5f, float(depth.rows/2)-0.5f,
|
||||||
|
1.0f/depthConstant, 1.0f/depthConstant);
|
||||||
|
cv::Vec3f point_5 = this->getDepth(depth,
|
||||||
|
432, 386,
|
||||||
|
float(depth.cols/2)-0.5f, float(depth.rows/2)-0.5f,
|
||||||
|
1.0f/depthConstant, 1.0f/depthConstant);
|
||||||
|
cv::Vec3f point_6 = this->getDepth(depth,
|
||||||
|
537,224,
|
||||||
|
float(depth.cols/2)-0.5f, float(depth.rows/2)-0.5f,
|
||||||
|
1.0f/depthConstant, 1.0f/depthConstant);
|
||||||
|
objectPoints[0] = cv::Point3f(point_1.val[0], point_1.val[1], point_1.val[2]);
|
||||||
|
objectPoints[1] = cv::Point3f(point_2.val[0], point_2.val[1], point_2.val[2]);
|
||||||
|
objectPoints[2] = cv::Point3f(point_3.val[0], point_3.val[1], point_3.val[2]);
|
||||||
|
objectPoints[3] = cv::Point3f(point_4.val[0], point_4.val[1], point_4.val[2]);
|
||||||
|
objectPoints[4] = cv::Point3f(point_5.val[0], point_5.val[1], point_5.val[2]);
|
||||||
|
objectPoints[5] = cv::Point3f(point_6.val[0], point_6.val[1], point_6.val[2]);
|
||||||
|
|
||||||
// QPointF pt = iter->map(QPointF(0, 0));
|
// QPointF pt = iter->map(QPointF(0, 0));
|
||||||
// imagePoints[0] = cv::Point2f(350,548);
|
imagePoints[0] = cv::Point2f(246,665);
|
||||||
// // pt = iter->map(QPointF(objectWidth, 0));
|
|
||||||
// imagePoints[1] = cv::Point2f(510,548);
|
|
||||||
// // pt = iter->map(QPointF(objectWidth, objectHeight));
|
|
||||||
// imagePoints[2] = cv::Point2f(510,716);
|
|
||||||
// // pt = iter->map(QPointF(0, objectHeight));
|
|
||||||
// imagePoints[3] = cv::Point2f(350,716);
|
|
||||||
// QPointF pt = iter->map(QPointF(0, 0));
|
|
||||||
imagePoints[0] = point_1;
|
|
||||||
// pt = iter->map(QPointF(objectWidth, 0));
|
// pt = iter->map(QPointF(objectWidth, 0));
|
||||||
imagePoints[1] = point_2;
|
imagePoints[1] = cv::Point2f(618, 665);
|
||||||
// pt = iter->map(QPointF(objectWidth, objectHeight));
|
// pt = iter->map(QPointF(objectWidth, objectHeight));
|
||||||
imagePoints[2] = point_3;
|
imagePoints[2] = cv::Point2f(618,111);
|
||||||
// pt = iter->map(QPointF(0, objectHeight));
|
// pt = iter->map(QPointF(0, objectHeight));
|
||||||
imagePoints[3] = point_4;
|
imagePoints[3] = cv::Point2f(246, 111);
|
||||||
|
imagePoints[4] = cv::Point2f(432, 386);
|
||||||
|
imagePoints[5] = cv::Point2f(537, 224);
|
||||||
|
|
||||||
|
|
||||||
cv::Mat cameraMatrix = cv::Mat::eye(3,3,CV_64FC1);
|
cv::Mat cameraMatrix = cv::Mat::eye(3,3,CV_64FC1);
|
||||||
@ -130,6 +142,7 @@ void FindObjectROS::estimate_pose(float objectWidth, float objectHeight, cv::Poi
|
|||||||
cameraMatrix.at<double>(0,2) = float(depth.cols/2)-0.5f;
|
cameraMatrix.at<double>(0,2) = float(depth.cols/2)-0.5f;
|
||||||
cameraMatrix.at<double>(1,2) = float(depth.rows/2)-0.5f;
|
cameraMatrix.at<double>(1,2) = float(depth.rows/2)-0.5f;
|
||||||
cv::Mat distCoeffs;
|
cv::Mat distCoeffs;
|
||||||
|
std::cout << "depth img cols: " << depth.cols << " rows: " << depth.rows << std::endl;
|
||||||
cv::Mat rvec(1,3, CV_64FC1);
|
cv::Mat rvec(1,3, CV_64FC1);
|
||||||
cv::Mat tvec(1,3, CV_64FC1);
|
cv::Mat tvec(1,3, CV_64FC1);
|
||||||
cv::solvePnP(objectPoints, imagePoints, cameraMatrix, distCoeffs, rvec, tvec);
|
cv::solvePnP(objectPoints, imagePoints, cameraMatrix, distCoeffs, rvec, tvec);
|
||||||
@ -144,14 +157,11 @@ void FindObjectROS::estimate_pose(float objectWidth, float objectHeight, cv::Poi
|
|||||||
R.at<double>(2,0), R.at<double>(2,1), R.at<double>(2,2));
|
R.at<double>(2,0), R.at<double>(2,1), R.at<double>(2,2));
|
||||||
rotationMatrix.getRotation(q);
|
rotationMatrix.getRotation(q);
|
||||||
|
|
||||||
// QPointF center = QPointF(imagePoints[0].x + objectWidth/2, imagePoints[0].y + objectHeight/2);
|
QPointF center = QPointF(objectWidth/2, objectHeight/2);
|
||||||
QPointF center = QPointF(442.252, 609.895);
|
|
||||||
cv::Vec3f center3D = this->getDepth(depth,
|
cv::Vec3f center3D = this->getDepth(depth,
|
||||||
center.x()+0.5f, center.y()+0.5f,
|
center.x()+0.5f, center.y()+0.5f,
|
||||||
float(depth.cols/2)-0.5f, float(depth.rows/2)-0.5f,
|
float(depth.cols/2)-0.5f, float(depth.rows/2)-0.5f,
|
||||||
1.0f/depthConstant, 1.0f/depthConstant);
|
1.0f/depthConstant, 1.0f/depthConstant);
|
||||||
std::cout << "center x: " << center.x() << " y: " << center.y() << std::endl;
|
|
||||||
std::cout << "center 3D x: " << center3D[0] << " y: " << center3D[1] <<" z: " << center3D[1] << std::endl;
|
|
||||||
|
|
||||||
transform.transform.translation.x = tvec.at<double>(0)*(center3D.val[2]/tvec.at<double>(2));
|
transform.transform.translation.x = tvec.at<double>(0)*(center3D.val[2]/tvec.at<double>(2));
|
||||||
transform.transform.translation.y = tvec.at<double>(1)*(center3D.val[2]/tvec.at<double>(2));
|
transform.transform.translation.y = tvec.at<double>(1)*(center3D.val[2]/tvec.at<double>(2));
|
||||||
@ -163,11 +173,10 @@ void FindObjectROS::estimate_pose(float objectWidth, float objectHeight, cv::Poi
|
|||||||
q *= q2;
|
q *= q2;
|
||||||
transform.transform.rotation = tf2::toMsg(q.normalized());
|
transform.transform.rotation = tf2::toMsg(q.normalized());
|
||||||
transforms.push_back(transform);
|
transforms.push_back(transform);
|
||||||
// if(transforms.size())
|
if(transforms.size())
|
||||||
// {
|
{
|
||||||
// tfBroadcaster_->sendTransform(transforms);
|
tfBroadcaster_->sendTransform(transforms);
|
||||||
// }
|
}
|
||||||
std::cout << "Done!!!!!!!!!!!!" << std::endl;
|
|
||||||
}
|
}
|
||||||
|
|
||||||
cv::Vec3f FindObjectROS::getDepth(const cv::Mat & depthImage,
|
cv::Vec3f FindObjectROS::getDepth(const cv::Mat & depthImage,
|
||||||
@ -190,24 +199,24 @@ cv::Vec3f FindObjectROS::getDepth(const cv::Mat & depthImage,
|
|||||||
cv::Vec3f pt;
|
cv::Vec3f pt;
|
||||||
|
|
||||||
// Use correct principal point from calibration
|
// Use correct principal point from calibration
|
||||||
float center_x = cx; //cameraInfo.K.at(2) // 656.1123046875
|
float center_x = cx; //cameraInfo.K.at(2)
|
||||||
float center_y = cy; //cameraInfo.K.at(5) // 361.80828857421875
|
float center_y = cy; //cameraInfo.K.at(5)
|
||||||
|
|
||||||
std::cout << "cx: " << center_x << " cy: " << center_y << std::endl;
|
// std::cout << "cx: " << center_x << " cy: " << center_y << std::endl;
|
||||||
std::cout << "fx: " << fx << " fy: " << fy << std::endl;
|
// std::cout << "fx: " << fx << " fy: " << fy << std::endl;
|
||||||
bool isInMM = depthImage.type() == CV_16UC1; // is in mm?
|
bool isInMM = depthImage.type() == CV_16UC1; // is in mm?
|
||||||
|
|
||||||
// Combine unit conversion (if necessary) with scaling by focal length for computing (X,Y)
|
// Combine unit conversion (if necessary) with scaling by focal length for computing (X,Y)
|
||||||
float unit_scaling = isInMM?0.001f:1.0f;
|
float unit_scaling = isInMM?0.001f:1.0f;
|
||||||
float constant_x = unit_scaling / fx; //cameraInfo.K.at(0) // 642.437744140625
|
float constant_x = unit_scaling / fx; //cameraInfo.K.at(0)
|
||||||
float constant_y = unit_scaling / fy; //cameraInfo.K.at(4) // 640.8887939453125
|
float constant_y = unit_scaling / fy; //cameraInfo.K.at(4)
|
||||||
float bad_point = std::numeric_limits<float>::quiet_NaN ();
|
float bad_point = std::numeric_limits<float>::quiet_NaN ();
|
||||||
|
|
||||||
float depth;
|
float depth;
|
||||||
bool isValid;
|
bool isValid;
|
||||||
if(isInMM)
|
if(isInMM)
|
||||||
{
|
{
|
||||||
std::cout << "depth is in mm!!" << std::endl;
|
// std::cout << "depth is in mm!!" << std::endl;
|
||||||
depth = (float)depthImage.at<uint16_t>(y,x);
|
depth = (float)depthImage.at<uint16_t>(y,x);
|
||||||
isValid = depth != 0.0f;
|
isValid = depth != 0.0f;
|
||||||
}
|
}
|
||||||
@ -216,14 +225,14 @@ cv::Vec3f FindObjectROS::getDepth(const cv::Mat & depthImage,
|
|||||||
|
|
||||||
depth = depthImage.at<float>(y,x);
|
depth = depthImage.at<float>(y,x);
|
||||||
isValid = std::isfinite(depth) && depth > 0.0f;
|
isValid = std::isfinite(depth) && depth > 0.0f;
|
||||||
std::cout << "depth is NOT in mm!! " << depth << std::endl;
|
// std::cout << "depth is NOT in mm!! " << depth << std::endl;
|
||||||
}
|
}
|
||||||
|
|
||||||
// Check for invalid measurements
|
// Check for invalid measurements
|
||||||
if (!isValid)
|
if (!isValid)
|
||||||
{
|
{
|
||||||
pt.val[0] = pt.val[1] = pt.val[2] = bad_point;
|
pt.val[0] = pt.val[1] = pt.val[2] = bad_point;
|
||||||
std::cout << "depth pt: " << pt.val[0] << " y: " << pt.val[1] << " z: " << pt.val[2] << std::endl;
|
// std::cout << "depth pt: " << pt.val[0] << " y: " << pt.val[1] << " z: " << pt.val[2] << std::endl;
|
||||||
}
|
}
|
||||||
else
|
else
|
||||||
{
|
{
|
||||||
|
|||||||
@ -11,116 +11,19 @@
|
|||||||
#include <pcl_conversions/pcl_conversions.h>
|
#include <pcl_conversions/pcl_conversions.h>
|
||||||
#include <pcl/search/impl/search.hpp>
|
#include <pcl/search/impl/search.hpp>
|
||||||
#include <pcl/filters/voxel_grid.h>
|
#include <pcl/filters/voxel_grid.h>
|
||||||
#include <pcl/filters/filter.h>
|
|
||||||
#include <pcl/filters/passthrough.h>
|
|
||||||
#include <pcl/common/transforms.h>
|
|
||||||
#include <iostream>
|
|
||||||
|
|
||||||
int count = 0;
|
int count = 0;
|
||||||
class PointCloudToDepthImageNode : public rclcpp::Node {
|
class PointCloudToDepthImageNode : public rclcpp::Node {
|
||||||
public:
|
public:
|
||||||
PointCloudToDepthImageNode() : Node("pointcloud_to_depth_image") {
|
PointCloudToDepthImageNode() : Node("pointcloud_to_depth_image") {
|
||||||
// sub_rgb_ = create_subscription<sensor_msgs::msg::Image>(
|
sub_rgb_ = create_subscription<sensor_msgs::msg::Image>(
|
||||||
// "/camera/color/image_raw", 10, std::bind(&PointCloudToDepthImageNode::rgb_callback, this, std::placeholders::_1));
|
"/camera/color/image_raw", 10, std::bind(&PointCloudToDepthImageNode::rgb_callback, this, std::placeholders::_1));
|
||||||
subscription_ = create_subscription<sensor_msgs::msg::PointCloud2>(
|
subscription_ = create_subscription<sensor_msgs::msg::PointCloud2>(
|
||||||
"/camera/depth/color/points", 10, std::bind(&PointCloudToDepthImageNode::convert_unorganized_to_organized_pc, this, std::placeholders::_1));
|
"/camera/depth/color/points", 10, std::bind(&PointCloudToDepthImageNode::pc_callback, this, std::placeholders::_1));
|
||||||
publisher_ = create_publisher<sensor_msgs::msg::Image>("/depth_image_topic", rclcpp::QoS(10));
|
publisher_ = create_publisher<sensor_msgs::msg::Image>("/depth_image_topic", rclcpp::QoS(10));
|
||||||
}
|
}
|
||||||
|
|
||||||
private:
|
private:
|
||||||
void convert_unorganized_to_organized_pc(const sensor_msgs::msg::PointCloud2::SharedPtr msg)
|
|
||||||
{
|
|
||||||
// Define lidar field of view parameters
|
|
||||||
double h_fov_max = 87.0; // Maximum horizontal angle in radians
|
|
||||||
double h_fov_min = 0; // Minimum horizontal angle in radians
|
|
||||||
double v_fov_max = 58.0; // Maximum vertical angle in radians
|
|
||||||
double v_fov_min = 0; // Minimum vertical angle in radians
|
|
||||||
|
|
||||||
double width = 1280;
|
|
||||||
double height = 720;
|
|
||||||
float hfov_deg = 87.0;
|
|
||||||
float vfov_deg = 58.0;
|
|
||||||
double pi = 3.14159265359;
|
|
||||||
float hfov_rad = hfov_deg * (pi / 180);
|
|
||||||
float vfov_rad = vfov_deg * (pi / 180);
|
|
||||||
float h_angle_per_pixel = hfov_rad / 1280; // calculate the angle per pixel
|
|
||||||
// h_fov_max = (1280 / 2) / tan(h_angle_per_pixel / 2); // calculate the maximum range
|
|
||||||
float v_angle_per_pixel = vfov_rad / 720; // calculate the angle per pixel
|
|
||||||
// v_fov_max = (720 / 2) / tan(v_angle_per_pixel / 2); // calculate the maximum range
|
|
||||||
// Calculate angular resolutions
|
|
||||||
const double h_resolution = (h_fov_max - h_fov_min) / width;
|
|
||||||
const double v_resolution = (v_fov_max - v_fov_min) / height;
|
|
||||||
std::cout << "convert_unorganized_to_organized_pc : " << h_fov_max << " v: " << v_fov_max << std::endl;
|
|
||||||
// Load the unorganized point cloud from a PCD file
|
|
||||||
pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
|
|
||||||
|
|
||||||
pcl::moveFromROSMsg(*msg, *cloud);
|
|
||||||
|
|
||||||
// Remove NaN points
|
|
||||||
// std::vector<int> indices;
|
|
||||||
// pcl::removeNaNFromPointCloud(*cloud, *cloud, indices);
|
|
||||||
|
|
||||||
// Initialize the organized point cloud
|
|
||||||
pcl::PointCloud<pcl::PointXYZRGB>::Ptr organized_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
|
|
||||||
organized_cloud->width = 1280;
|
|
||||||
organized_cloud->height = 720;
|
|
||||||
organized_cloud->is_dense = true;
|
|
||||||
organized_cloud->points.resize(organized_cloud->width * organized_cloud->height);
|
|
||||||
std::cout << "cloud width: " << cloud->width << " height: " << cloud->height << std::endl;
|
|
||||||
// pcl::PassThrough<pcl::PointXYZRGB> pass;
|
|
||||||
// pass.setInputCloud(cloud);
|
|
||||||
// pass.setFilterFieldName("x");
|
|
||||||
// pass.setFilterLimitsNegative(false);
|
|
||||||
// pass.setFilterLimits(-tan(hfov_rad / 2.0), tan(hfov_rad / 2.0));
|
|
||||||
// pass.filter(*cloud);
|
|
||||||
// pass.setInputCloud(cloud);
|
|
||||||
// pass.setFilterFieldName("y");
|
|
||||||
// pass.setFilterLimitsNegative(false);
|
|
||||||
// pass.setFilterLimits(-tan(vfov_rad / 2.0), tan(vfov_rad / 2.0));
|
|
||||||
// pass.filter(*cloud);
|
|
||||||
// Copy the points from the unorganized point cloud to the organized point cloud
|
|
||||||
// for (int i = 0; i < cloud->points.size(); ++i)
|
|
||||||
// {
|
|
||||||
// int row = i / cloud->width;
|
|
||||||
// int col = i % cloud->width;
|
|
||||||
// organized_cloud->at(col, row) = cloud->points[i];
|
|
||||||
// }
|
|
||||||
// for (int i = 0; i < cloud->points.size(); ++i)
|
|
||||||
// {
|
|
||||||
// pcl::PointXYZRGB point = cloud->points[i];
|
|
||||||
|
|
||||||
// // std::cout << point.x << std::endl;
|
|
||||||
// int x = (point.x + tan(hfov_rad / 2.0)) / (tan(hfov_rad) / organized_cloud->width);
|
|
||||||
// int y = (point.y + tan(vfov_rad / 2.0)) / (tan(vfov_rad) / organized_cloud->height);
|
|
||||||
// int index = y * organized_cloud->width + x;
|
|
||||||
// std::cout << "point x: " << x << std::endl;
|
|
||||||
// std::cout << "point y: " << y << std::endl;
|
|
||||||
// std::cout << "point index: " << index << std::endl;
|
|
||||||
// if (organized_cloud->points[index].z == 0)
|
|
||||||
// {
|
|
||||||
// organized_cloud->points[index] = point;
|
|
||||||
// }
|
|
||||||
// else if (point.z < organized_cloud->points[index].z)
|
|
||||||
// {
|
|
||||||
// organized_cloud->points[index] = point;
|
|
||||||
// }
|
|
||||||
// }
|
|
||||||
for (int i = 0; i < cloud->size(); i++) {
|
|
||||||
pcl::PointXYZRGB point = cloud->points[i];
|
|
||||||
double h_angle = atan2(point.y, point.x);
|
|
||||||
double v_angle = atan2(point.z, sqrt(point.x * point.x + point.y * point.y));
|
|
||||||
int col = static_cast<int>((h_angle - h_fov_min) / h_resolution);
|
|
||||||
int row = static_cast<int>((v_angle - v_fov_min) / v_resolution);
|
|
||||||
// std::cout << "point col: " << col << " row: " << row << std::endl;
|
|
||||||
if (col >= 0 && col < organized_cloud->width && row >= 0 && row < organized_cloud->height) {
|
|
||||||
organized_cloud->at(col, row) = point;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
// Save the organized point cloud to a PCD file
|
|
||||||
// pcl::io::savePCDFileASCII("organized_cloud.pcd", *organized_cloud);
|
|
||||||
|
|
||||||
}
|
|
||||||
// void pointCloudCallback(const sensor_msgs::msg::PointCloud2::SharedPtr msg) {
|
// void pointCloudCallback(const sensor_msgs::msg::PointCloud2::SharedPtr msg) {
|
||||||
// // Create a point cloud object from the message
|
// // Create a point cloud object from the message
|
||||||
|
|
||||||
|
|||||||
@ -35,8 +35,7 @@ class FindPoseNode : public rclcpp::Node {
|
|||||||
findObjectROS_(0)
|
findObjectROS_(0)
|
||||||
{
|
{
|
||||||
findObjectROS_ = new FindObjectROS(this);
|
findObjectROS_ = new FindObjectROS(this);
|
||||||
findObjectROS_->estimate_pose(115, 116, cv::Point2f(819,600), cv::Point2f(974,600), cv::Point2f(974,716), cv::Point2f(819,716));
|
findObjectROS_->estimate_pose();
|
||||||
findObjectROS_->estimate_pose(160, 168, cv::Point2f(350,548), cv::Point2f(510,548), cv::Point2f(510,716), cv::Point2f(350,716));
|
|
||||||
}
|
}
|
||||||
|
|
||||||
private:
|
private:
|
||||||
|
|||||||
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Reference in New Issue
Block a user