JetSonNano darknet yolov3工程通过CMakeLists.txt配置编译环境

CMakeLists.txt 写的比较糙,有疑问欢迎咨询。

option(GPU ON)
option(CUDNN ON)
option(OPENCV ON)

cmake_minimum_required(VERSION 3.1)
project(darknet)
SET(CMAKE_C_FLAGS "-pipe -O2 -Wall -W -fPIC")
set(CMAKE_BUILD_TYPE "Release")

add_definitions(-DGPU)
message(STATUS "GPU")

add_definitions(-DCUDNN)
message(STATUS "CUDNN")


add_definitions(-DOPENCV)
message(STATUS "OPENCV")

list(APPEND CUDA_NVCC_FLAGS "-std=c++11")
find_package(CUDA REQUIRED)
link_directories(/usr/local/cuda/lib64/)
include_directories(/usr/local/lib /usr/local/cuda/bin/nvcc /usr/local/cuda/include/ /usr/local/cuda/lib64)

SET(OpenCV_DIR /usr/share/OpenCV)
find_package(OpenCV REQUIRED)

find_package(Boost COMPONENTS system date_time thread chrono regex random REQUIRED)
add_library(darkyl STATIC darknet.c)
set(CUDA_NVCC_FLAGS -gencode arch=compute_50,code=[sm_50,compute_50];-G;-g)
set(source_files
cuda/activation_kernels.cu
cuda/avgpool_layer_kernels.cu
cuda/blas_kernels.cu
cuda/col2im_kernels.cu
cuda/convolutional_kernels.cu
cuda/crop_layer_kernels.cu
cuda/deconvolutional_kernels.cu
cuda/dropout_layer_kernels.cu
cuda/im2col_kernels.cu
cuda/maxpool_layer_kernels.cu
cuda/activation_layer.h
cuda/activations.h
cuda/avgpool_layer.h
cuda/batchnorm_layer.h
cuda/blas.h
cuda/box.h
cuda/classifier.h
cuda/col2im.h
cuda/connected_layer.h
cuda/convolutional_layer.h
cuda/cost_layer.h
cuda/crnn_layer.h
cuda/crop_layer.h
cuda/cuda.h
cuda/data.h
cuda/deconvolutional_layer.h
cuda/demo.h
cuda/detection_layer.h
cuda/detector.h
cuda/dropout_layer.h
cuda/gemm.h
cuda/gru_layer.h
cuda/im2col.h
cuda/image.h
cuda/iseg_layer.h
cuda/l2norm_layer.h
cuda/layer.h
cuda/list.h
cuda/local_layer.h
cuda/logistic_layer.h
cuda/lstm_layer.h
cuda/matrix.h
cuda/maxpool_layer.h
cuda/network.h
cuda/normalization_layer.h
cuda/option_list.h
cuda/parser.h
cuda/region_layer.h
cuda/reorg_layer.h
cuda/rnn_layer.h
cuda/route_layer.h
cuda/shortcut_layer.h
cuda/softmax_layer.h
cuda/stb_image.h
cuda/stb_image_write.h
cuda/tree.h
cuda/upsample_layer.h
cuda/utils.h
cuda/yolo_layer.h
csrc/activation_layer.c
csrc/activations.c
csrc/art.c
csrc/attention.c
csrc/avgpool_layer.c
csrc/batchnorm_layer.c
csrc/blas.c
csrc/box.c
csrc/captcha.c
csrc/cifar.c
csrc/classifier.c
csrc/coco.c
csrc/col2im.c
csrc/connected_layer.c
csrc/convolutional_layer.c
csrc/cost_layer.c
csrc/crnn_layer.c
csrc/crop_layer.c
csrc/cuda.c
csrc/darknet.c
csrc/data.c
csrc/deconvolutional_layer.c
csrc/demo.c
csrc/detection_layer.c
csrc/detector.c
csrc/dropout_layer.c
csrc/gemm.c
csrc/go.c
csrc/gru_layer.c
csrc/im2col.c
csrc/image.c
csrc/instance-segmenter.c
csrc/iseg_layer.c
csrc/l2norm_layer.c
csrc/layer.c
csrc/list.c
csrc/local_layer.c
csrc/logistic_layer.c
csrc/lsd.c
csrc/lstm_layer.c
csrc/matrix.c
csrc/maxpool_layer.c
csrc/network.c
csrc/nightmare.c
csrc/normalization_layer.c
csrc/option_list.c
csrc/parser.c
csrc/region_layer.c
csrc/regressor.c
csrc/reorg_layer.c
csrc/rnn.c
csrc/rnn_layer.c
csrc/route_layer.c
csrc/segmenter.c
csrc/shortcut_layer.c
csrc/softmax_layer.c
csrc/super.c
csrc/tag.c
csrc/tree.c
csrc/upsample_layer.c
csrc/utils.c
csrc/yolo.c
csrc/yolo_layer.c
cppsrc/image_opencv.cpp
cppsrc/image_opencv.h
cppsrc/image.h
)
#add_executable(darknet darknet.c)
cuda_add_executable(darknet ${source_files})
target_link_libraries(darknet ${Boost_LIBRARIES} ${OpenCV_LIBS})
target_link_libraries(darknet pthread -lcuda -lcudart -lcublas -lcurand -lcudnn)
target_link_libraries(darknet m)

 

posted @ 2019-12-10 15:18  我们都是大好青年  阅读(1012)  评论(0编辑  收藏  举报