Ubuntu 18.04 ROS Melodic Yolov4 error

问题遇到的现象和发生背景
環境 Ubuntu 18.04 ROS Melodic (vmware虛擬環境)
執行Cmake 編譯 darknet_ros 功能包

问题相关代码，请勿粘贴截图
cmake_minimum_required(VERSION 2.8.12)
project(darknet_ros)

Set c++11 cmake flags

set(CMAKE_CXX_FLAGS "-std=c++11 ${CMAKE_CXX_FLAGS}")
set(CMAKE_C_FLAGS "-Wall -Wno-unused-result -Wno-unknown-pragmas -Wno-unused-variable -Wfatal-errors -fPIC ${CMAKE_C_FLAGS}")
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)

Define path of darknet folder here.

find_path(DARKNET_PATH
NAMES "README.md"
HINTS "${CMAKE_CURRENT_SOURCE_DIR}/../darknet/")
message(STATUS "Darknet path dir = ${DARKNET_PATH}")
add_definitions(-DDARKNET_FILE_PATH="${DARKNET_PATH}")

Find CUDA

find_package(CUDA QUIET)
if (CUDA_FOUND)
find_package(CUDA REQUIRED)
message(STATUS "CUDA Version: ${CUDA_VERSION_STRINGS}")
message(STATUS "CUDA Libararies: ${CUDA_LIBRARIES}")
set(
CUDA_NVCC_FLAGS
${CUDA_NVCC_FLAGS};
-O3
-gencode arch=compute_30,code=sm_30
-gencode arch=compute_35,code=sm_35
-gencode arch=compute_50,code=[sm_50,compute_50]
-gencode arch=compute_52,code=[sm_52,compute_52]
-gencode arch=compute_61,code=sm_61
-gencode arch=compute_62,code=sm_62
)
add_definitions(-DGPU)
else()
list(APPEND LIBRARIES "m")
endif()

Find X11

message ( STATUS "Searching for X11..." )
find_package ( X11 REQUIRED )
if ( X11_FOUND )
include_directories ( ${X11_INCLUDE_DIR} )
link_libraries ( ${X11_LIBRARIES} )
message ( STATUS " X11_INCLUDE_DIR: " ${X11_INCLUDE_DIR} )
message ( STATUS " X11_LIBRARIES: " ${X11_LIBRARIES} )
endif ( X11_FOUND )

Find rquired packeges

find_package(Boost REQUIRED COMPONENTS thread)
find_package(OpenCV 3.4.10 REQUIRED)

include_directories(${OpenCV_INCLUDE_DIRS})
message("wocako ${OpenCV_INCLUDE_DIRS}")
find_package(catkin REQUIRED
COMPONENTS
cv_bridge
roscpp
rospy
std_msgs
actionlib
darknet_ros_msgs
image_transport
)

Enable OPENCV in darknet

add_definitions(-DOPENCV)
add_definitions(-O4 -g)

catkin_package(
INCLUDE_DIRS
include
LIBRARIES
${PROJECT_NAME}_lib
CATKIN_DEPENDS
cv_bridge
roscpp
actionlib
rospy
std_msgs
darknet_ros_msgs
image_transport
DEPENDS
Boost
)

include_directories(
${DARKNET_PATH}/src
${DARKNET_PATH}/include
include
${Boost_INCLUDE_DIRS}
${catkin_INCLUDE_DIRS}
)

set(PROJECT_LIB_FILES
src/YoloObjectDetector.cpp src/image_interface.c
)

set(DARKNET_CORE_FILES
${DARKNET_PATH}/src/activation_layer.c ${DARKNET_PATH}/src/im2col.c
${DARKNET_PATH}/src/activations.c ${DARKNET_PATH}/src/image.c
${DARKNET_PATH}/src/avgpool_layer.c ${DARKNET_PATH}/src/layer.c
${DARKNET_PATH}/src/batchnorm_layer.c ${DARKNET_PATH}/src/list.c
${DARKNET_PATH}/src/blas.c ${DARKNET_PATH}/src/local_layer.c
${DARKNET_PATH}/src/box.c ${DARKNET_PATH}/src/lstm_layer.c
${DARKNET_PATH}/src/col2im.c ${DARKNET_PATH}/src/matrix.c
${DARKNET_PATH}/src/connected_layer.c ${DARKNET_PATH}/src/maxpool_layer.c
${DARKNET_PATH}/src/convolutional_layer.c ${DARKNET_PATH}/src/network.c
${DARKNET_PATH}/src/cost_layer.c ${DARKNET_PATH}/src/normalization_layer.c
${DARKNET_PATH}/src/crnn_layer.c ${DARKNET_PATH}/src/option_list.c
${DARKNET_PATH}/src/crop_layer.c ${DARKNET_PATH}/src/parser.c
${DARKNET_PATH}/src/dark_cuda.c ${DARKNET_PATH}/src/region_layer.c
${DARKNET_PATH}/src/data.c ${DARKNET_PATH}/src/reorg_layer.c
${DARKNET_PATH}/src/deconvolutional_layer.c ${DARKNET_PATH}/src/rnn_layer.c
${DARKNET_PATH}/src/demo.c ${DARKNET_PATH}/src/route_layer.c
${DARKNET_PATH}/src/detection_layer.c ${DARKNET_PATH}/src/shortcut_layer.c
${DARKNET_PATH}/src/dropout_layer.c ${DARKNET_PATH}/src/softmax_layer.c
${DARKNET_PATH}/src/gemm.c ${DARKNET_PATH}/src/tree.c
${DARKNET_PATH}/src/gru_layer.c ${DARKNET_PATH}/src/utils.c
${DARKNET_PATH}/src/upsample_layer.c #${DARKNET_PATH}/src/logistic_layer.c
#${DARKNET_PATH}/src/l2norm_layer.c
${DARKNET_PATH}/src/yolo_layer.c

${DARKNET_PATH}/src/art.c                #${DARKNET_PATH}/src/lsd.c
#${DARKNET_PATH}/src/attention.c
${DARKNET_PATH}/src/nightmare.c
${DARKNET_PATH}/src/captcha.c            #${DARKNET_PATH}/src/regressor.c
${DARKNET_PATH}/src/cifar.c              ${DARKNET_PATH}/src/rnn.c
${DARKNET_PATH}/src/classifier.c         #${DARKNET_PATH}/src/segmenter.c
${DARKNET_PATH}/src/coco.c               ${DARKNET_PATH}/src/super.c
${DARKNET_PATH}/src/darknet.c            ${DARKNET_PATH}/src/tag.c
${DARKNET_PATH}/src/detector.c           ${DARKNET_PATH}/src/yolo.c
${DARKNET_PATH}/src/go.c
${DARKNET_PATH}/src/image_opencv.cpp
${DARKNET_PATH}/src/conv_lstm_layer.c

${DARKNET_PATH}/src/gettimeofday.c
${DARKNET_PATH}/src/getopt.c

${DARKNET_PATH}/src/gaussian_yolo_layer.c

${DARKNET_PATH}/src/dice.c
${DARKNET_PATH}/src/rnn_vid.c


${DARKNET_PATH}/src/compare.c


${DARKNET_PATH}/src/writing.c

${DARKNET_PATH}/src/voxel.c
${DARKNET_PATH}/src/network_kernels.cu

${DARKNET_PATH}/src/swag.c


${DARKNET_PATH}/src/scale_channels_layer.c

${DARKNET_PATH}/src/sam_layer.c
${DARKNET_PATH}/src/http_stream.cpp
${DARKNET_PATH}/src/yolo_v2_class.cpp
#${DARKNET_PATH}/src/yolo_console_dll.cpp

${DARKNET_PATH}/src/reorg_old_layer.c
${DARKNET_PATH}/src/image_opencv.cpp
${DARKNET_PATH}/src/art.c
${DARKNET_PATH}/src/conv_lstm_layer.c
${DARKNET_PATH}/src/network_kernels.cu
${DARKNET_PATH}/src/network.c
${DARKNET_PATH}/src/sam_layer.c
${DARKNET_PATH}/src/yolo_layer.c
${DARKNET_PATH}/src/gaussian_yolo_layer.c
${DARKNET_PATH}/src/http_stream.cpp
${DARKNET_PATH}/src/scale_channels_layer.c
${DARKNET_PATH}/src/voxel.c
${DARKNET_PATH}/src/compare.c
${DARKNET_PATH}/src/writing.c
${DARKNET_PATH}/src/dice.c
${DARKNET_PATH}/src/rnn_vid.c
${DARKNET_PATH}/src/reorg_old_layer.c
${DARKNET_PATH}/src/swag.c
${DARKNET_PATH}/src/yolo_v2_class.cpp
${DARKNET_PATH}/src/gettimeofday.c
${DARKNET_PATH}/src/getopt.c
${DARKNET_PATH}/src/image.c

)

set(DARKNET_CUDA_FILES
${DARKNET_PATH}/src/activation_kernels.cu ${DARKNET_PATH}/src/crop_layer_kernels.cu
${DARKNET_PATH}/src/avgpool_layer_kernels.cu ${DARKNET_PATH}/src/deconvolutional_kernels.cu
${DARKNET_PATH}/src/blas_kernels.cu ${DARKNET_PATH}/src/dropout_layer_kernels.cu
${DARKNET_PATH}/src/col2im_kernels.cu ${DARKNET_PATH}/src/im2col_kernels.cu
${DARKNET_PATH}/src/convolutional_kernels.cu ${DARKNET_PATH}/src/maxpool_layer_kernels.cu
)

if (CUDA_FOUND)

link_directories(
${CUDA_TOOLKIT_ROOT_DIR}/lib64
)

cuda_add_library(${PROJECT_NAME}_lib
${PROJECT_LIB_FILES} ${DARKNET_CORE_FILES}
${DARKNET_CUDA_FILES}
)

target_link_libraries(${PROJECT_NAME}_lib
cuda
cudart
cublas
curand
)

cuda_add_executable(${PROJECT_NAME}
src/yolo_object_detector_node.cpp
)

else()

add_library(${PROJECT_NAME}_lib
${PROJECT_LIB_FILES} ${DARKNET_CORE_FILES}
)

add_executable(${PROJECT_NAME}
src/yolo_object_detector_node.cpp
)

endif()

target_link_libraries(${PROJECT_NAME}_lib
m
pthread
stdc++
${Boost_LIBRARIES}
${OpenCV_LIBRARIES}
${catkin_LIBRARIES}
${OpenCV_LIBS}
)

target_link_libraries(${PROJECT_NAME}
${PROJECT_NAME}_lib
)

add_dependencies(${PROJECT_NAME}_lib
darknet_ros_msgs_generate_messages_cpp
)

install(TARGETS ${PROJECT_NAME}_lib
ARCHIVE DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
LIBRARY DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
RUNTIME DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
)

install(TARGETS ${PROJECT_NAME}
RUNTIME DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
)

install(
DIRECTORY include/${PROJECT_NAME}/
DESTINATION ${CATKIN_PACKAGE_INCLUDE_DESTINATION}
FILES_MATCHING PATTERN "*.h"
)

install(DIRECTORY config launch yolo_network_config
DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
)

Download yolov2-tiny.weights

set(PATH "${CMAKE_CURRENT_SOURCE_DIR}/yolo_network_config/weights")
set(FILE "${PATH}/yolov2-tiny.weights")
message(STATUS "Checking and downloading yolov2-tiny.weights if needed ...")
if (NOT EXISTS "${FILE}")
message(STATUS "... file does not exist. Downloading now ...")

execute_process(COMMAND wget -q https://github.com/leggedrobotics/darknet_ros/releases/download/1.1.4/yolov2-tiny.weights -P ${PATH})

endif()

Download yolov3.weights

set(FILE "${PATH}/yolov3.weights")
message(STATUS "Checking and downloading yolov3.weights if needed ...")
if (NOT EXISTS "${FILE}")
message(STATUS "... file does not exist. Downloading now ...")

execute_process(COMMAND wget -q https://github.com/leggedrobotics/darknet_ros/releases/download/1.1.4/yolov3.weights -P ${PATH})

endif()

if(CATKIN_ENABLE_TESTING)

Download yolov2.weights

set(PATH "${CMAKE_CURRENT_SOURCE_DIR}/yolo_network_config/weights")
set(FILE "${PATH}/yolov2.weights")
message(STATUS "Checking and downloading yolov2.weights if needed ...")
if (NOT EXISTS "${FILE}")
message(STATUS "... file does not exist. Downloading now ...")

execute_process(COMMAND wget -q https://github.com/leggedrobotics/darknet_ros/releases/download/1.1.4/yolov2.weights -P ${PATH})

endif()

find_package(rostest REQUIRED)

Object detection in images.

add_rostest_gtest(${PROJECT_NAME}_object_detection-test
test/object_detection.test
test/test_main.cpp
test/ObjectDetection.cpp
)
target_link_libraries(${PROJECT_NAME}_object_detection-test
${catkin_LIBRARIES}
)
endif()

find_package(cmake_clang_tools QUIET)
if (cmake_clang_tools_FOUND)
message(STATUS "Run clang tooling")
add_clang_tooling(
TARGETS ${PROJECT_NAME}
SOURCE_DIRS ${CMAKE_CURRENT_LIST_DIR}/src ${CMAKE_CURRENT_LIST_DIR}/include ${CMAKE_CURRENT_LIST_DIR}/test
CT_HEADER_DIRS ${CMAKE_CURRENT_LIST_DIR}/include
CF_WERROR
)
endif (cmake_clang_tools_FOUND)

运行结果及报错内容
/home/fei/yolo4_ws/devel/lib/libdarknet_ros_lib.so: undefined reference to `make_implicit_layer'
collect2: error: ld returned 1 exit status
darknet_ros_yolov4/darknet_ros/CMakeFiles/darknet_ros.dir/build.make:186: recipe for target '/home/fei/yolo4_ws/devel/lib/darknet_ros/darknet_ros' failed
make[2]: * [/home/fei/yolo4_ws/devel/lib/darknet_ros/darknet_ros] Error 1
CMakeFiles/Makefile2:2060: recipe for target 'darknet_ros_yolov4/darknet_ros/CMakeFiles/darknet_ros.dir/all' failed
make[1]: * [darknet_ros_yolov4/darknet_ros/CMakeFiles/darknet_ros.dir/all] Error 2
Makefile:140: recipe for target 'all' failed
make: * [all] Error 2
Invoking "make -j2 -l2" failed

img


我想要达到的结果
成功編譯

坊间传闻虚拟机使用GPU不灵，得用实体机。