前言：测试一下Autoware 下的 CNN LiDAR Baidu Object Segmenter。我的环境是Ubuntu18.04+CUDA10.0+cudnn+ros melodic+opencv4
因为遇到了太多的坑，分享个大家，顺便也留一个记录。
安装最坑的是这个错误：undefined reference to google::FlagRegisterer::FlagRegisterer，找了很多资料也没有解决，所以我就搜索了所有的gflags和glog相关的文件，并将他们删除，然后重新安装，问题得到解决。
CUDA10.0 与 cudnn的安装参见：https://www.cnblogs.com/hgl0417/p/11844135.html
1. 安装opencv
（1）安装依赖：
$ sudo apt install build-essential cmake git pkg-config libgtk-3-dev
$ sudo apt install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev libxvidcore-dev libx264-dev
$ sudo apt install libjpeg-dev libpng-dev libtiff-dev gfortran openexr libatlas-base-dev
$ sudo apt install python3-dev python3-numpy libtbb2 libtbb-dev libdc1394-22-dev
（2）下载源码
$ mkdir ~/opencv_build && cd ~/opencv_build $ wget https://github.com/opencv/opencv/archive/3.4.0.zip -O opencv-3.4.0.zip $ wget https://github.com/opencv/opencv_contrib/archive/3.4.0.zip -O opencv_contrib-3.4.0.zip $ unzip opencv-3.4.0.zip $ unzip opencv_contrib-3.4.0.zip
用CUDA 10.0以上版本编译opencv3.0以上版本，会报错：找不到dynlink_nvcuvid.h
需要下载：https://developer.nvidia.com/designworks/video_codec_sdk/downloads/v8.2-ga2，解压Video_Codec_SDK_8.2.16.zip
unzip Video_Codec_SDK_8.2.16.zip
在~/Downloads/Video_Codec_SDK_8.2.16/Samples/NvCodec/NvDecoder/找到cuviddec.h，在~/Downloads/Video_Codec_SDK_8.2.16/Samples/NvCodec/NvDecoder/找到nvcuvid.h，讲这两个文件拷贝到/usr/local/cuda/include/。
$ sudo cp ~/Downloads/Video_Codec_SDK_8.2.16/Samples/NvCodec/NvDecoder/cuviddec.h /usr/local/cuda/include/ $ sudo cp ~/Downloads/Video_Codec_SDK_8.2.16/Samples/NvCodec/NvDecoder/nvcuvid.h /usr/local/cuda/include/
修改opencv-3.4.0下的modules下的一些头文件：
modules/cudacodec/src/precomp.hpp modules/cudacodec/src/frame_queue.hpp modules/cudacodec/src/cuvid_video_source.hpp modules/cudacodec/src/video_decoder.hpp modules/cudacodec/src/video_parser.hpp
将这些文件的
#if CUDA_VERSION >= 9000 #include <dynlink_nvcuvid.h> #else #include <nvcuvid.h> 改为： #if CUDA_VERSION >= 9000 && CUDA_VERSION < 10000 #include <dynlink_nvcuvid.h> #else #include <nvcuvid.h>
编译，安装
$ cd ~/opencv_build/opencv-3.4.0 && mkdir build && cd build $ cmake -DCMAKE_BUILD_TYPE=RELEASE -DCMAKE_INSTALL_PREFIX=/usr/local -DINSTALL_PYTHON_EXAMPLES=ON -DINSTALL_C_EXAMPLES=OFF -DOPENCV_EXTRA_MODULES_PATH=/home/leon/opencv_build/opencv_contrib-3.4.0/modules -DPYTHON_EXCUTABLE=/usr/bin/python2.7 -DWITH_CUDA=ON -DWITH_CUBLAS=ON -DDCUDA_NVCC_FLAGS="-D_FORCE_INLINES" -DCUDA_ARCH_BIN="6.1" -DCUDA_ARCH_PTX="" -DCUDA_FAST_MATH=ON -DWITH_TBB=ON -DWITH_V4L=ON -DWITH_GTK=ON -DWITH_OPENGL=ON -DCMAKE_C_COMPILER=/usr/bin/gcc-7 -DCUDA_HOST_COMPILER=/usr/bin/g++-7 -DCUDA_PROPAGATE_HOST_FLAGS=oFF -DCMAKE_CXX_FLAGS="-std=c++11" -DBUILD_TIFF=ON -DBUILD_EXAMPLES=ON .. $ make -j$nproc $ sudo make install
查看opencv版本
$ pkg-config opencv --modversion
2. 安装hdf5
如果没有安装hdf5，可以从 https://support.hdfgroup.org/ftp/HDF5/releases/hdf5-1.8/hdf5-1.8.21/src/ 下载hdf5-1.8.21.tar.gz，默认下载到Downloads文件夹。
解压hdf5-1.8.21.tar.gz
$ cd ~/Downloads $ tar -xvf hdf5-1.8.21.tar.gz $ sudo mv -f hdf5-1.8.21/ /opt $ cd /opt/hdf5-1.8.21/
编译安装hdf5
$ sudo ./configure --prefix=/usr/local/hdf5 $ sudo make $ sudo make check $ sudo make install
安装成功后，在安装目录/usr/local下出现hdf5文件夹，打开后有/bin，/include，/lib，/share四个文件夹
安装成功后，测试
$ cd /usr/local/hdf5/share/hdf5_examples/c $ sudo ./run-c-ex.sh
执行命令
$ sudo h5cc -o h5_extend h5_extend.c
如果出现sudo: h5cc: command not found，那么执行
$ sudo apt install hdf5-helpers
再次执行
$ sudo h5cc -o h5_extend h5_extend.c
如果出现hdf5.h not found，执行
sudo apt-get install libhdf5-serial-dev
这是应该没有错误提示。
在执行
$ sudo ./h5_extend
安装完毕，显示
Dataset: 1 1 1 1 1 1 1 1 1 2 3 4 2 3 4 2 3 4 2 3 4 2 3 4 2 3 4 2 3 4
2. 安装caffe相关的package
$ sudo apt install -y libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler $ sudo apt install -y --no-install-recommends libboost-all-dev $ sudo apt install -y libopenblas-dev #libatlas-base-dev $ sudo apt install -y libgflags-dev libgoogle-glog-dev liblmdb-dev
3. 下载/安装caffe
下载：
$ git clone https://github.com/BVLC/caffe.git
修改Makefile.config
$ cd /caffe $ cp Makefile.config.example Makefile.config
编辑Makefile.config，这里我参考了网上很多的资料，所以我直接贴上我自己的Makefile.config。
## Refer to http://caffe.berkeleyvision.org/installation.html # Contributions simplifying and improving our build system are welcome! # cuDNN acceleration switch (uncomment to build with cuDNN). USE_CUDNN := 1 # CPU-only switch (uncomment to build without GPU support). # CPU_ONLY := 1 # uncomment to disable IO dependencies and corresponding data layers USE_OPENCV := 1 # USE_LEVELDB := 0 # USE_LMDB := 0 # This code is taken from https://github.com/sh1r0/caffe-android-lib # USE_HDF5 := 0 # uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary) # You should not set this flag if you will be reading LMDBs with any # possibility of simultaneous read and write # ALLOW_LMDB_NOLOCK := 1 # Uncomment if you're using OpenCV 3 OPENCV_VERSION := 3.4.0 # To customize your choice of compiler, uncomment and set the following. # N.B. the default for Linux is g++ and the default for OSX is clang++ CUSTOM_CXX := g++ # CUDA directory contains bin/ and lib/ directories that we need. CUDA_DIR := /usr/local/cuda # On Ubuntu 14.04, if cuda tools are installed via # "sudo apt-get install nvidia-cuda-toolkit" then use this instead: # CUDA_DIR := /usr # CUDA architecture setting: going with all of them. # For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility. # For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility. # For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility. CUDA_ARCH := -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_61,code=compute_61 # BLAS choice: # atlas for ATLAS (default) # mkl for MKL # open for OpenBlas BLAS := atlas # Custom (MKL/ATLAS/OpenBLAS) include and lib directories. # Leave commented to accept the defaults for your choice of BLAS # (which should work)! # BLAS_INCLUDE := /path/to/your/blas # BLAS_LIB := /path/to/your/blas # Homebrew puts openblas in a directory that is not on the standard search path # BLAS_INCLUDE := $(shell brew --prefix openblas)/include # BLAS_LIB := $(shell brew --prefix openblas)/lib # This is required only if you will compile the matlab interface. # MATLAB directory should contain the mex binary in /bin. # MATLAB_DIR := /usr/local # MATLAB_DIR := /Applications/MATLAB_R2012b.app # NOTE: this is required only if you will compile the python interface. # We need to be able to find Python.h and numpy/arrayobject.h. PYTHON_INCLUDE := /usr/include/python2.7 /usr/lib/python2.7/dist-packages/numpy/core/include # Anaconda Python distribution is quite popular. Include path: # Verify anaconda location, sometimes it's in root. # ANACONDA_HOME := $(HOME)/anaconda # PYTHON_INCLUDE := $(ANACONDA_HOME)/include # $(ANACONDA_HOME)/include/python2.7 # $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include # Uncomment to use Python 3 (default is Python 2) # PYTHON_LIBRARIES := boost_python3 python3.5m # PYTHON_INCLUDE := /usr/include/python3.5m # /usr/lib/python3.5/dist-packages/numpy/core/include # We need to be able to find libpythonX.X.so or .dylib. PYTHON_LIB := /usr/lib # PYTHON_LIB := $(ANACONDA_HOME)/lib # Homebrew installs numpy in a non standard path (keg only) # PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include # PYTHON_LIB += $(shell brew --prefix numpy)/lib # Uncomment to support layers written in Python (will link against Python libs) WITH_PYTHON_LAYER := 1 # Whatever else you find you need goes here. INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/ /usr/local/hdf5/include/ LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/local/hdf5/lib/ # If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies # INCLUDE_DIRS += $(shell brew --prefix)/include # LIBRARY_DIRS += $(shell brew --prefix)/lib # NCCL acceleration switch (uncomment to build with NCCL) # https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0) # USE_NCCL := 1 # Uncomment to use `pkg-config` to specify OpenCV library paths. # (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.) # USE_PKG_CONFIG := 1 # N.B. both build and distribute dirs are cleared on `make clean` BUILD_DIR := build DISTRIBUTE_DIR := distribute # Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171 # DEBUG := 1 # The ID of the GPU that 'make runtest' will use to run unit tests. TEST_GPUID := 0 # enable pretty build (comment to see full commands) Q ?= @
Makefile文件
PROJECT := caffe CONFIG_FILE := Makefile.config # Explicitly check for the config file, otherwise make -k will proceed anyway. ifeq ($(wildcard $(CONFIG_FILE)),) $(error $(CONFIG_FILE) not found. See $(CONFIG_FILE).example.) endif include $(CONFIG_FILE) BUILD_DIR_LINK := $(BUILD_DIR) ifeq ($(RELEASE_BUILD_DIR),) RELEASE_BUILD_DIR := .$(BUILD_DIR)_release endif ifeq ($(DEBUG_BUILD_DIR),) DEBUG_BUILD_DIR := .$(BUILD_DIR)_debug endif DEBUG ?= 0 ifeq ($(DEBUG), 1) BUILD_DIR := $(DEBUG_BUILD_DIR) OTHER_BUILD_DIR := $(RELEASE_BUILD_DIR) else BUILD_DIR := $(RELEASE_BUILD_DIR) OTHER_BUILD_DIR := $(DEBUG_BUILD_DIR) endif # All of the directories containing code. SRC_DIRS := $(shell find * -type d -exec bash -c "find {} -maxdepth 1 ( -name '*.cpp' -o -name '*.proto' ) | grep -q ." ; -print) # The target shared library name LIBRARY_NAME := $(PROJECT) LIB_BUILD_DIR := $(BUILD_DIR)/lib STATIC_NAME := $(LIB_BUILD_DIR)/lib$(LIBRARY_NAME).a DYNAMIC_VERSION_MAJOR := 1 DYNAMIC_VERSION_MINOR := 0 DYNAMIC_VERSION_REVISION := 0 DYNAMIC_NAME_SHORT := lib$(LIBRARY_NAME).so #DYNAMIC_SONAME_SHORT := $(DYNAMIC_NAME_SHORT).$(DYNAMIC_VERSION_MAJOR) DYNAMIC_VERSIONED_NAME_SHORT := $(DYNAMIC_NAME_SHORT).$(DYNAMIC_VERSION_MAJOR).$(DYNAMIC_VERSION_MINOR).$(DYNAMIC_VERSION_REVISION) DYNAMIC_NAME := $(LIB_BUILD_DIR)/$(DYNAMIC_VERSIONED_NAME_SHORT) COMMON_FLAGS += -DCAFFE_VERSION=$(DYNAMIC_VERSION_MAJOR).$(DYNAMIC_VERSION_MINOR).$(DYNAMIC_VERSION_REVISION) ############################## # Get all source files ############################## # CXX_SRCS are the source files excluding the test ones. CXX_SRCS := $(shell find src/$(PROJECT) ! -name "test_*.cpp" -name "*.cpp") # CU_SRCS are the cuda source files CU_SRCS := $(shell find src/$(PROJECT) ! -name "test_*.cu" -name "*.cu") # TEST_SRCS are the test source files TEST_MAIN_SRC := src/$(PROJECT)/test/test_caffe_main.cpp TEST_SRCS := $(shell find src/$(PROJECT) -name "test_*.cpp") TEST_SRCS := $(filter-out $(TEST_MAIN_SRC), $(TEST_SRCS)) TEST_CU_SRCS := $(shell find src/$(PROJECT) -name "test_*.cu") GTEST_SRC := src/gtest/gtest-all.cpp # TOOL_SRCS are the source files for the tool binaries TOOL_SRCS := $(shell find tools -name "*.cpp") # EXAMPLE_SRCS are the source files for the example binaries EXAMPLE_SRCS := $(shell find examples -name "*.cpp") # BUILD_INCLUDE_DIR contains any generated header files we want to include. BUILD_INCLUDE_DIR := $(BUILD_DIR)/src # PROTO_SRCS are the protocol buffer definitions PROTO_SRC_DIR := src/$(PROJECT)/proto PROTO_SRCS := $(wildcard $(PROTO_SRC_DIR)/*.proto) # PROTO_BUILD_DIR will contain the .cc and obj files generated from # PROTO_SRCS; PROTO_BUILD_INCLUDE_DIR will contain the .h header files PROTO_BUILD_DIR := $(BUILD_DIR)/$(PROTO_SRC_DIR) PROTO_BUILD_INCLUDE_DIR := $(BUILD_INCLUDE_DIR)/$(PROJECT)/proto # NONGEN_CXX_SRCS includes all source/header files except those generated # automatically (e.g., by proto). NONGEN_CXX_SRCS := $(shell find src/$(PROJECT) include/$(PROJECT) python/$(PROJECT) matlab/+$(PROJECT)/private examples tools -name "*.cpp" -or -name "*.hpp" -or -name "*.cu" -or -name "*.cuh") LINT_SCRIPT := scripts/cpp_lint.py LINT_OUTPUT_DIR := $(BUILD_DIR)/.lint LINT_EXT := lint.txt LINT_OUTPUTS := $(addsuffix .$(LINT_EXT), $(addprefix $(LINT_OUTPUT_DIR)/, $(NONGEN_CXX_SRCS))) EMPTY_LINT_REPORT := $(BUILD_DIR)/.$(LINT_EXT) NONEMPTY_LINT_REPORT := $(BUILD_DIR)/$(LINT_EXT) # PY$(PROJECT)_SRC is the python wrapper for $(PROJECT) PY$(PROJECT)_SRC := python/$(PROJECT)/_$(PROJECT).cpp PY$(PROJECT)_SO := python/$(PROJECT)/_$(PROJECT).so PY$(PROJECT)_HXX := include/$(PROJECT)/layers/python_layer.hpp # MAT$(PROJECT)_SRC is the mex entrance point of matlab package for $(PROJECT) MAT$(PROJECT)_SRC := matlab/+$(PROJECT)/private/$(PROJECT)_.cpp ifneq ($(MATLAB_DIR),) MAT_SO_EXT := $(shell $(MATLAB_DIR)/bin/mexext) endif MAT$(PROJECT)_SO := matlab/+$(PROJECT)/private/$(PROJECT)_.$(MAT_SO_EXT) ############################## # Derive generated files ############################## # The generated files for protocol buffers PROTO_GEN_HEADER_SRCS := $(addprefix $(PROTO_BUILD_DIR)/, $(notdir ${PROTO_SRCS:.proto=.pb.h})) PROTO_GEN_HEADER := $(addprefix $(PROTO_BUILD_INCLUDE_DIR)/, $(notdir ${PROTO_SRCS:.proto=.pb.h})) PROTO_GEN_CC := $(addprefix $(BUILD_DIR)/, ${PROTO_SRCS:.proto=.pb.cc}) PY_PROTO_BUILD_DIR := python/$(PROJECT)/proto PY_PROTO_INIT := python/$(PROJECT)/proto/__init__.py PROTO_GEN_PY := $(foreach file,${PROTO_SRCS:.proto=_pb2.py}, $(PY_PROTO_BUILD_DIR)/$(notdir $(file))) # The objects corresponding to the source files # These objects will be linked into the final shared library, so we # exclude the tool, example, and test objects. CXX_OBJS := $(addprefix $(BUILD_DIR)/, ${CXX_SRCS:.cpp=.o}) CU_OBJS := $(addprefix $(BUILD_DIR)/cuda/, ${CU_SRCS:.cu=.o}) PROTO_OBJS := ${PROTO_GEN_CC:.cc=.o} OBJS := $(PROTO_OBJS) $(CXX_OBJS) $(CU_OBJS) # tool, example, and test objects TOOL_OBJS := $(addprefix $(BUILD_DIR)/, ${TOOL_SRCS:.cpp=.o}) TOOL_BUILD_DIR := $(BUILD_DIR)/tools TEST_CXX_BUILD_DIR := $(BUILD_DIR)/src/$(PROJECT)/test TEST_CU_BUILD_DIR := $(BUILD_DIR)/cuda/src/$(PROJECT)/test TEST_CXX_OBJS := $(addprefix $(BUILD_DIR)/, ${TEST_SRCS:.cpp=.o}) TEST_CU_OBJS := $(addprefix $(BUILD_DIR)/cuda/, ${TEST_CU_SRCS:.cu=.o}) TEST_OBJS := $(TEST_CXX_OBJS) $(TEST_CU_OBJS) GTEST_OBJ := $(addprefix $(BUILD_DIR)/, ${GTEST_SRC:.cpp=.o}) EXAMPLE_OBJS := $(addprefix $(BUILD_DIR)/, ${EXAMPLE_SRCS:.cpp=.o}) # Output files for automatic dependency generation DEPS := ${CXX_OBJS:.o=.d} ${CU_OBJS:.o=.d} ${TEST_CXX_OBJS:.o=.d} ${TEST_CU_OBJS:.o=.d} $(BUILD_DIR)/${MAT$(PROJECT)_SO:.$(MAT_SO_EXT)=.d} # tool, example, and test bins TOOL_BINS := ${TOOL_OBJS:.o=.bin} EXAMPLE_BINS := ${EXAMPLE_OBJS:.o=.bin} # symlinks to tool bins without the ".bin" extension TOOL_BIN_LINKS := ${TOOL_BINS:.bin=} # Put the test binaries in build/test for convenience. TEST_BIN_DIR := $(BUILD_DIR)/test TEST_CU_BINS := $(addsuffix .testbin,$(addprefix $(TEST_BIN_DIR)/, $(foreach obj,$(TEST_CU_OBJS),$(basename $(notdir $(obj)))))) TEST_CXX_BINS := $(addsuffix .testbin,$(addprefix $(TEST_BIN_DIR)/, $(foreach obj,$(TEST_CXX_OBJS),$(basename $(notdir $(obj)))))) TEST_BINS := $(TEST_CXX_BINS) $(TEST_CU_BINS) # TEST_ALL_BIN is the test binary that links caffe dynamically. TEST_ALL_BIN := $(TEST_BIN_DIR)/test_all.testbin ############################## # Derive compiler warning dump locations ############################## WARNS_EXT := warnings.txt CXX_WARNS := $(addprefix $(BUILD_DIR)/, ${CXX_SRCS:.cpp=.o.$(WARNS_EXT)}) CU_WARNS := $(addprefix $(BUILD_DIR)/cuda/, ${CU_SRCS:.cu=.o.$(WARNS_EXT)}) TOOL_WARNS := $(addprefix $(BUILD_DIR)/, ${TOOL_SRCS:.cpp=.o.$(WARNS_EXT)}) EXAMPLE_WARNS := $(addprefix $(BUILD_DIR)/, ${EXAMPLE_SRCS:.cpp=.o.$(WARNS_EXT)}) TEST_WARNS := $(addprefix $(BUILD_DIR)/, ${TEST_SRCS:.cpp=.o.$(WARNS_EXT)}) TEST_CU_WARNS := $(addprefix $(BUILD_DIR)/cuda/, ${TEST_CU_SRCS:.cu=.o.$(WARNS_EXT)}) ALL_CXX_WARNS := $(CXX_WARNS) $(TOOL_WARNS) $(EXAMPLE_WARNS) $(TEST_WARNS) ALL_CU_WARNS := $(CU_WARNS) $(TEST_CU_WARNS) ALL_WARNS := $(ALL_CXX_WARNS) $(ALL_CU_WARNS) EMPTY_WARN_REPORT := $(BUILD_DIR)/.$(WARNS_EXT) NONEMPTY_WARN_REPORT := $(BUILD_DIR)/$(WARNS_EXT) ############################## # Derive include and lib directories ############################## CUDA_INCLUDE_DIR := $(CUDA_DIR)/include CUDA_LIB_DIR := # add <cuda>/lib64 only if it exists ifneq ("$(wildcard $(CUDA_DIR)/lib64)","") CUDA_LIB_DIR += $(CUDA_DIR)/lib64 endif CUDA_LIB_DIR += $(CUDA_DIR)/lib INCLUDE_DIRS += $(BUILD_INCLUDE_DIR) ./src ./include ifneq ($(CPU_ONLY), 1) INCLUDE_DIRS += $(CUDA_INCLUDE_DIR) LIBRARY_DIRS += $(CUDA_LIB_DIR) LIBRARIES := cudart cublas curand endif LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial # handle IO dependencies USE_LEVELDB ?= 1 USE_LMDB ?= 1 # This code is taken from https://github.com/sh1r0/caffe-android-lib USE_HDF5 ?= 1 USE_OPENCV ?= 1 ifeq ($(USE_LEVELDB), 1) LIBRARIES += leveldb snappy endif ifeq ($(USE_LMDB), 1) LIBRARIES += lmdb endif # This code is taken from https://github.com/sh1r0/caffe-android-lib ifeq ($(USE_HDF5), 1) LIBRARIES += hdf5_hl hdf5 endif ifeq ($(USE_OPENCV), 1) LIBRARIES += opencv_core opencv_highgui opencv_imgproc ifeq ($(OPENCV_VERSION), 3) LIBRARIES += opencv_imgcodecs endif endif PYTHON_LIBRARIES ?= boost_python python2.7 WARNINGS := -Wall -Wno-sign-compare ############################## # Set build directories ############################## DISTRIBUTE_DIR ?= distribute DISTRIBUTE_SUBDIRS := $(DISTRIBUTE_DIR)/bin $(DISTRIBUTE_DIR)/lib DIST_ALIASES := dist ifneq ($(strip $(DISTRIBUTE_DIR)),distribute) DIST_ALIASES += distribute endif ALL_BUILD_DIRS := $(sort $(BUILD_DIR) $(addprefix $(BUILD_DIR)/, $(SRC_DIRS)) $(addprefix $(BUILD_DIR)/cuda/, $(SRC_DIRS)) $(LIB_BUILD_DIR) $(TEST_BIN_DIR) $(PY_PROTO_BUILD_DIR) $(LINT_OUTPUT_DIR) $(DISTRIBUTE_SUBDIRS) $(PROTO_BUILD_INCLUDE_DIR)) ############################## # Set directory for Doxygen-generated documentation ############################## DOXYGEN_CONFIG_FILE ?= ./.Doxyfile # should be the same as OUTPUT_DIRECTORY in the .Doxyfile DOXYGEN_OUTPUT_DIR ?= ./doxygen DOXYGEN_COMMAND ?= doxygen # All the files that might have Doxygen documentation. DOXYGEN_SOURCES := $(shell find src/$(PROJECT) include/$(PROJECT) python/ matlab/ examples tools -name "*.cpp" -or -name "*.hpp" -or -name "*.cu" -or -name "*.cuh" -or -name "*.py" -or -name "*.m") DOXYGEN_SOURCES += $(DOXYGEN_CONFIG_FILE) ############################## # Configure build ############################## # Determine platform UNAME := $(shell uname -s) ifeq ($(UNAME), Linux) LINUX := 1 else ifeq ($(UNAME), Darwin) OSX := 1 OSX_MAJOR_VERSION := $(shell sw_vers -productVersion | cut -f 1 -d .) OSX_MINOR_VERSION := $(shell sw_vers -productVersion | cut -f 2 -d .) endif # Linux ifeq ($(LINUX), 1) CXX ?= /usr/bin/g++ GCCVERSION := $(shell $(CXX) -dumpversion | cut -f1,2 -d.) # older versions of gcc are too dumb to build boost with -Wuninitalized ifeq ($(shell echo | awk '{exit $(GCCVERSION) < 4.6;}'), 1) WARNINGS += -Wno-uninitialized endif # boost::thread is reasonably called boost_thread (compare OS X) # We will also explicitly add stdc++ to the link target. LIBRARIES += boost_thread stdc++ VERSIONFLAGS += -Wl,-soname,$(DYNAMIC_VERSIONED_NAME_SHORT) -Wl,-rpath,$(ORIGIN)/../lib endif # OS X: # clang++ instead of g++ # libstdc++ for NVCC compatibility on OS X >= 10.9 with CUDA < 7.0 ifeq ($(OSX), 1) CXX := /usr/bin/clang++ ifneq ($(CPU_ONLY), 1) CUDA_VERSION := $(shell $(CUDA_DIR)/bin/nvcc -V | grep -o 'release [0-9.]*' | tr -d '[a-z ]') ifeq ($(shell echo | awk '{exit $(CUDA_VERSION) < 7.0;}'), 1) CXXFLAGS += -stdlib=libstdc++ LINKFLAGS += -stdlib=libstdc++ endif # clang throws this warning for cuda headers WARNINGS += -Wno-unneeded-internal-declaration # 10.11 strips DYLD_* env vars so link CUDA (rpath is available on 10.5+) OSX_10_OR_LATER := $(shell [ $(OSX_MAJOR_VERSION) -ge 10 ] && echo true) OSX_10_5_OR_LATER := $(shell [ $(OSX_MINOR_VERSION) -ge 5 ] && echo true) ifeq ($(OSX_10_OR_LATER),true) ifeq ($(OSX_10_5_OR_LATER),true) LDFLAGS += -Wl,-rpath,$(CUDA_LIB_DIR) endif endif endif # gtest needs to use its own tuple to not conflict with clang COMMON_FLAGS += -DGTEST_USE_OWN_TR1_TUPLE=1 # boost::thread is called boost_thread-mt to mark multithreading on OS X LIBRARIES += boost_thread-mt # we need to explicitly ask for the rpath to be obeyed ORIGIN := @loader_path VERSIONFLAGS += -Wl,-install_name,@rpath/$(DYNAMIC_VERSIONED_NAME_SHORT) -Wl,-rpath,$(ORIGIN)/../../build/lib else ORIGIN := $$ORIGIN endif # Custom compiler ifdef CUSTOM_CXX CXX := $(CUSTOM_CXX) endif # Static linking ifneq (,$(findstring clang++,$(CXX))) STATIC_LINK_COMMAND := -Wl,-force_load $(STATIC_NAME) else ifneq (,$(findstring g++,$(CXX))) STATIC_LINK_COMMAND := -Wl,--whole-archive $(STATIC_NAME) -Wl,--no-whole-archive else # The following line must not be indented with a tab, since we are not inside a target $(error Cannot static link with the $(CXX) compiler) endif # Debugging ifeq ($(DEBUG), 1) COMMON_FLAGS += -DDEBUG -g -O0 NVCCFLAGS += -G else COMMON_FLAGS += -DNDEBUG -O2 endif # cuDNN acceleration configuration. ifeq ($(USE_CUDNN), 1) LIBRARIES += cudnn COMMON_FLAGS += -DUSE_CUDNN endif # NCCL acceleration configuration ifeq ($(USE_NCCL), 1) LIBRARIES += nccl COMMON_FLAGS += -DUSE_NCCL endif # configure IO libraries ifeq ($(USE_OPENCV), 1) COMMON_FLAGS += -DUSE_OPENCV endif ifeq ($(USE_LEVELDB), 1) COMMON_FLAGS += -DUSE_LEVELDB endif ifeq ($(USE_LMDB), 1) COMMON_FLAGS += -DUSE_LMDB ifeq ($(ALLOW_LMDB_NOLOCK), 1) COMMON_FLAGS += -DALLOW_LMDB_NOLOCK endif endif # This code is taken from https://github.com/sh1r0/caffe-android-lib ifeq ($(USE_HDF5), 1) COMMON_FLAGS += -DUSE_HDF5 endif # CPU-only configuration ifeq ($(CPU_ONLY), 1) OBJS := $(PROTO_OBJS) $(CXX_OBJS) TEST_OBJS := $(TEST_CXX_OBJS) TEST_BINS := $(TEST_CXX_BINS) ALL_WARNS := $(ALL_CXX_WARNS) TEST_FILTER := --gtest_filter="-*GPU*" COMMON_FLAGS += -DCPU_ONLY endif # Python layer support ifeq ($(WITH_PYTHON_LAYER), 1) COMMON_FLAGS += -DWITH_PYTHON_LAYER LIBRARIES += $(PYTHON_LIBRARIES) endif # BLAS configuration (default = ATLAS) BLAS ?= atlas ifeq ($(BLAS), mkl) # MKL LIBRARIES += mkl_rt COMMON_FLAGS += -DUSE_MKL MKLROOT ?= /opt/intel/mkl BLAS_INCLUDE ?= $(MKLROOT)/include BLAS_LIB ?= $(MKLROOT)/lib $(MKLROOT)/lib/intel64 else ifeq ($(BLAS), open) # OpenBLAS LIBRARIES += openblas else # ATLAS ifeq ($(LINUX), 1) ifeq ($(BLAS), atlas) # Linux simply has cblas and atlas LIBRARIES += cblas atlas endif else ifeq ($(OSX), 1) # OS X packages atlas as the vecLib framework LIBRARIES += cblas # 10.10 has accelerate while 10.9 has veclib XCODE_CLT_VER := $(shell pkgutil --pkg-info=com.apple.pkg.CLTools_Executables | grep 'version' | sed 's/[^0-9]*([0-9]).*/1/') XCODE_CLT_GEQ_7 := $(shell [ $(XCODE_CLT_VER) -gt 6 ] && echo 1) XCODE_CLT_GEQ_6 := $(shell [ $(XCODE_CLT_VER) -gt 5 ] && echo 1) ifeq ($(XCODE_CLT_GEQ_7), 1) BLAS_INCLUDE ?= /Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/$(shell ls /Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/ | sort | tail -1)/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/Headers else ifeq ($(XCODE_CLT_GEQ_6), 1) BLAS_INCLUDE ?= /System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Headers/ LDFLAGS += -framework Accelerate else BLAS_INCLUDE ?= /System/Library/Frameworks/vecLib.framework/Versions/Current/Headers/ LDFLAGS += -framework vecLib endif endif endif INCLUDE_DIRS += $(BLAS_INCLUDE) LIBRARY_DIRS += $(BLAS_LIB) LIBRARY_DIRS += $(LIB_BUILD_DIR) # Automatic dependency generation (nvcc is handled separately) CXXFLAGS += -MMD -MP # Complete build flags. COMMON_FLAGS += $(foreach includedir,$(INCLUDE_DIRS),-I$(includedir)) CXXFLAGS += -pthread -fPIC $(COMMON_FLAGS) $(WARNINGS) NVCCFLAGS += -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS) # mex may invoke an older gcc that is too liberal with -Wuninitalized MATLAB_CXXFLAGS := $(CXXFLAGS) -Wno-uninitialized LINKFLAGS += -pthread -fPIC $(COMMON_FLAGS) $(WARNINGS) USE_PKG_CONFIG ?= 0 ifeq ($(USE_PKG_CONFIG), 1) PKG_CONFIG := $(shell pkg-config opencv --libs) else PKG_CONFIG := endif LDFLAGS += $(foreach librarydir,$(LIBRARY_DIRS),-L$(librarydir)) $(PKG_CONFIG) $(foreach library,$(LIBRARIES),-l$(library)) PYTHON_LDFLAGS := $(LDFLAGS) $(foreach library,$(PYTHON_LIBRARIES),-l$(library)) # 'superclean' target recursively* deletes all files ending with an extension # in $(SUPERCLEAN_EXTS) below. This may be useful if you've built older # versions of Caffe that do not place all generated files in a location known # to the 'clean' target. # # 'supercleanlist' will list the files to be deleted by make superclean. # # * Recursive with the exception that symbolic links are never followed, per the # default behavior of 'find'. SUPERCLEAN_EXTS := .so .a .o .bin .testbin .pb.cc .pb.h _pb2.py .cuo # Set the sub-targets of the 'everything' target. EVERYTHING_TARGETS := all py$(PROJECT) test warn lint # Only build matcaffe as part of "everything" if MATLAB_DIR is specified. ifneq ($(MATLAB_DIR),) EVERYTHING_TARGETS += mat$(PROJECT) endif ############################## # Define build targets ############################## .PHONY: all lib test clean docs linecount lint lintclean tools examples $(DIST_ALIASES) py mat py$(PROJECT) mat$(PROJECT) proto runtest superclean supercleanlist supercleanfiles warn everything all: lib tools examples lib: $(STATIC_NAME) $(DYNAMIC_NAME) everything: $(EVERYTHING_TARGETS) linecount: cloc --read-lang-def=$(PROJECT).cloc src/$(PROJECT) include/$(PROJECT) tools examples python matlab lint: $(EMPTY_LINT_REPORT) lintclean: @ $(RM) -r $(LINT_OUTPUT_DIR) $(EMPTY_LINT_REPORT) $(NONEMPTY_LINT_REPORT) docs: $(DOXYGEN_OUTPUT_DIR) @ cd ./docs ; ln -sfn ../$(DOXYGEN_OUTPUT_DIR)/html doxygen $(DOXYGEN_OUTPUT_DIR): $(DOXYGEN_CONFIG_FILE) $(DOXYGEN_SOURCES) $(DOXYGEN_COMMAND) $(DOXYGEN_CONFIG_FILE) $(EMPTY_LINT_REPORT): $(LINT_OUTPUTS) | $(BUILD_DIR) @ cat $(LINT_OUTPUTS) > $@ @ if [ -s "$@" ]; then cat $@; mv $@ $(NONEMPTY_LINT_REPORT); echo "Found one or more lint errors."; exit 1; fi; $(RM) $(NONEMPTY_LINT_REPORT); echo "No lint errors!"; $(LINT_OUTPUTS): $(LINT_OUTPUT_DIR)/%.lint.txt : % $(LINT_SCRIPT) | $(LINT_OUTPUT_DIR) @ mkdir -p $(dir $@) @ python $(LINT_SCRIPT) $< 2>&1 | grep -v "^Done processing " | grep -v "^Total errors found: 0" > $@ || true test: $(TEST_ALL_BIN) $(TEST_ALL_DYNLINK_BIN) $(TEST_BINS) tools: $(TOOL_BINS) $(TOOL_BIN_LINKS) examples: $(EXAMPLE_BINS) py$(PROJECT): py py: $(PY$(PROJECT)_SO) $(PROTO_GEN_PY) $(PY$(PROJECT)_SO): $(PY$(PROJECT)_SRC) $(PY$(PROJECT)_HXX) | $(DYNAMIC_NAME) @ echo CXX/LD -o $@ $< $(Q)$(CXX) -shared -o $@ $(PY$(PROJECT)_SRC) -o $@ $(LINKFLAGS) -l$(LIBRARY_NAME) $(PYTHON_LDFLAGS) -Wl,-rpath,$(ORIGIN)/../../build/lib mat$(PROJECT): mat mat: $(MAT$(PROJECT)_SO) $(MAT$(PROJECT)_SO): $(MAT$(PROJECT)_SRC) $(STATIC_NAME) @ if [ -z "$(MATLAB_DIR)" ]; then echo "MATLAB_DIR must be specified in $(CONFIG_FILE)" "to build mat$(PROJECT)."; exit 1; fi @ echo MEX $< $(Q)$(MATLAB_DIR)/bin/mex $(MAT$(PROJECT)_SRC) CXX="$(CXX)" CXXFLAGS="$$CXXFLAGS $(MATLAB_CXXFLAGS)" CXXLIBS="$$CXXLIBS $(STATIC_LINK_COMMAND) $(LDFLAGS)" -output $@ @ if [ -f "$(PROJECT)_.d" ]; then mv -f $(PROJECT)_.d $(BUILD_DIR)/${MAT$(PROJECT)_SO:.$(MAT_SO_EXT)=.d}; fi runtest: $(TEST_ALL_BIN) $(TOOL_BUILD_DIR)/caffe $(TEST_ALL_BIN) $(TEST_GPUID) --gtest_shuffle $(TEST_FILTER) pytest: py cd python; python -m unittest discover -s caffe/test mattest: mat cd matlab; $(MATLAB_DIR)/bin/matlab -nodisplay -r 'caffe.run_tests(), exit()' warn: $(EMPTY_WARN_REPORT) $(EMPTY_WARN_REPORT): $(ALL_WARNS) | $(BUILD_DIR) @ cat $(ALL_WARNS) > $@ @ if [ -s "$@" ]; then cat $@; mv $@ $(NONEMPTY_WARN_REPORT); echo "Compiler produced one or more warnings."; exit 1; fi; $(RM) $(NONEMPTY_WARN_REPORT); echo "No compiler warnings!"; $(ALL_WARNS): %.o.$(WARNS_EXT) : %.o $(BUILD_DIR_LINK): $(BUILD_DIR)/.linked # Create a target ".linked" in this BUILD_DIR to tell Make that the "build" link # is currently correct, then delete the one in the OTHER_BUILD_DIR in case it # exists and $(DEBUG) is toggled later. $(BUILD_DIR)/.linked: @ mkdir -p $(BUILD_DIR) @ $(RM) $(OTHER_BUILD_DIR)/.linked @ $(RM) -r $(BUILD_DIR_LINK) @ ln -s $(BUILD_DIR) $(BUILD_DIR_LINK) @ touch $@ $(ALL_BUILD_DIRS): | $(BUILD_DIR_LINK) @ mkdir -p $@ $(DYNAMIC_NAME): $(OBJS) | $(LIB_BUILD_DIR) @ echo LD -o $@ $(Q)$(CXX) -shared -o $@ $(OBJS) $(VERSIONFLAGS) $(LINKFLAGS) $(LDFLAGS) @ cd $(BUILD_DIR)/lib; rm -f $(DYNAMIC_NAME_SHORT); ln -s $(DYNAMIC_VERSIONED_NAME_SHORT) $(DYNAMIC_NAME_SHORT) $(STATIC_NAME): $(OBJS) | $(LIB_BUILD_DIR) @ echo AR -o $@ $(Q)ar rcs $@ $(OBJS) $(BUILD_DIR)/%.o: %.cpp $(PROTO_GEN_HEADER) | $(ALL_BUILD_DIRS) @ echo CXX $< $(Q)$(CXX) $< $(CXXFLAGS) -c -o $@ 2> $@.$(WARNS_EXT) || (cat $@.$(WARNS_EXT); exit 1) @ cat $@.$(WARNS_EXT) $(PROTO_BUILD_DIR)/%.pb.o: $(PROTO_BUILD_DIR)/%.pb.cc $(PROTO_GEN_HEADER) | $(PROTO_BUILD_DIR) @ echo CXX $< $(Q)$(CXX) $< $(CXXFLAGS) -c -o $@ 2> $@.$(WARNS_EXT) || (cat $@.$(WARNS_EXT); exit 1) @ cat $@.$(WARNS_EXT) $(BUILD_DIR)/cuda/%.o: %.cu | $(ALL_BUILD_DIRS) @ echo NVCC $< $(Q)$(CUDA_DIR)/bin/nvcc $(NVCCFLAGS) $(CUDA_ARCH) -M $< -o ${@:.o=.d} -odir $(@D) $(Q)$(CUDA_DIR)/bin/nvcc $(NVCCFLAGS) $(CUDA_ARCH) -c $< -o $@ 2> $@.$(WARNS_EXT) || (cat $@.$(WARNS_EXT); exit 1) @ cat $@.$(WARNS_EXT) $(TEST_ALL_BIN): $(TEST_MAIN_SRC) $(TEST_OBJS) $(GTEST_OBJ) | $(DYNAMIC_NAME) $(TEST_BIN_DIR) @ echo CXX/LD -o $@ $< $(Q)$(CXX) $(TEST_MAIN_SRC) $(TEST_OBJS) $(GTEST_OBJ) -o $@ $(LINKFLAGS) $(LDFLAGS) -l$(LIBRARY_NAME) -Wl,-rpath,$(ORIGIN)/../lib $(TEST_CU_BINS): $(TEST_BIN_DIR)/%.testbin: $(TEST_CU_BUILD_DIR)/%.o $(GTEST_OBJ) | $(DYNAMIC_NAME) $(TEST_BIN_DIR) @ echo LD $< $(Q)$(CXX) $(TEST_MAIN_SRC) $< $(GTEST_OBJ) -o $@ $(LINKFLAGS) $(LDFLAGS) -l$(LIBRARY_NAME) -Wl,-rpath,$(ORIGIN)/../lib $(TEST_CXX_BINS): $(TEST_BIN_DIR)/%.testbin: $(TEST_CXX_BUILD_DIR)/%.o $(GTEST_OBJ) | $(DYNAMIC_NAME) $(TEST_BIN_DIR) @ echo LD $< $(Q)$(CXX) $(TEST_MAIN_SRC) $< $(GTEST_OBJ) -o $@ $(LINKFLAGS) $(LDFLAGS) -l$(LIBRARY_NAME) -Wl,-rpath,$(ORIGIN)/../lib # Target for extension-less symlinks to tool binaries with extension '*.bin'. $(TOOL_BUILD_DIR)/%: $(TOOL_BUILD_DIR)/%.bin | $(TOOL_BUILD_DIR) @ $(RM) $@ @ ln -s $(notdir $<) $@ $(TOOL_BINS): %.bin : %.o | $(DYNAMIC_NAME) @ echo CXX/LD -o $@ $(Q)$(CXX) $< -o $@ $(LINKFLAGS) -l$(LIBRARY_NAME) $(LDFLAGS) -Wl,-rpath,$(ORIGIN)/../lib $(EXAMPLE_BINS): %.bin : %.o | $(DYNAMIC_NAME) @ echo CXX/LD -o $@ $(Q)$(CXX) $< -o $@ $(LINKFLAGS) -l$(LIBRARY_NAME) $(LDFLAGS) -Wl,-rpath,$(ORIGIN)/../../lib proto: $(PROTO_GEN_CC) $(PROTO_GEN_HEADER) $(PROTO_BUILD_DIR)/%.pb.cc $(PROTO_BUILD_DIR)/%.pb.h : $(PROTO_SRC_DIR)/%.proto | $(PROTO_BUILD_DIR) @ echo PROTOC $< $(Q)protoc --proto_path=$(PROTO_SRC_DIR) --cpp_out=$(PROTO_BUILD_DIR) $< $(PY_PROTO_BUILD_DIR)/%_pb2.py : $(PROTO_SRC_DIR)/%.proto $(PY_PROTO_INIT) | $(PY_PROTO_BUILD_DIR) @ echo PROTOC (python) $< $(Q)protoc --proto_path=src --python_out=python $< $(PY_PROTO_INIT): | $(PY_PROTO_BUILD_DIR) touch $(PY_PROTO_INIT) clean: @- $(RM) -rf $(ALL_BUILD_DIRS) @- $(RM) -rf $(OTHER_BUILD_DIR) @- $(RM) -rf $(BUILD_DIR_LINK) @- $(RM) -rf $(DISTRIBUTE_DIR) @- $(RM) $(PY$(PROJECT)_SO) @- $(RM) $(MAT$(PROJECT)_SO) supercleanfiles: $(eval SUPERCLEAN_FILES := $(strip $(foreach ext,$(SUPERCLEAN_EXTS), $(shell find . -name '*$(ext)' -not -path './data/*')))) supercleanlist: supercleanfiles @ if [ -z "$(SUPERCLEAN_FILES)" ]; then echo "No generated files found."; else echo $(SUPERCLEAN_FILES) | tr ' ' ' '; fi superclean: clean supercleanfiles @ if [ -z "$(SUPERCLEAN_FILES)" ]; then echo "No generated files found."; else echo "Deleting the following generated files:"; echo $(SUPERCLEAN_FILES) | tr ' ' ' '; $(RM) $(SUPERCLEAN_FILES); fi $(DIST_ALIASES): $(DISTRIBUTE_DIR) $(DISTRIBUTE_DIR): all py | $(DISTRIBUTE_SUBDIRS) # add proto cp -r src/caffe/proto $(DISTRIBUTE_DIR)/ # add include cp -r include $(DISTRIBUTE_DIR)/ mkdir -p $(DISTRIBUTE_DIR)/include/caffe/proto cp $(PROTO_GEN_HEADER_SRCS) $(DISTRIBUTE_DIR)/include/caffe/proto # add tool and example binaries cp $(TOOL_BINS) $(DISTRIBUTE_DIR)/bin cp $(EXAMPLE_BINS) $(DISTRIBUTE_DIR)/bin # add libraries cp $(STATIC_NAME) $(DISTRIBUTE_DIR)/lib install -m 644 $(DYNAMIC_NAME) $(DISTRIBUTE_DIR)/lib cd $(DISTRIBUTE_DIR)/lib; rm -f $(DYNAMIC_NAME_SHORT); ln -s $(DYNAMIC_VERSIONED_NAME_SHORT) $(DYNAMIC_NAME_SHORT) # add python - it's not the standard way, indeed... cp -r python $(DISTRIBUTE_DIR)/ -include $(DEPS)
安装caffe
$ make $ make distribute
4. 运行节点
roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/PATH/TO/FILE.prototxt pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel points_src:=/points_raw
需要从apollo的git上下载两个文件(https://github.com/ApolloAuto/apollo/tree/master/modules/perception/production/data/perception/lidar/models/cnnseg)，分别为：deploy.prototxt及deploy.caffemodel。找到文件后填写修改上面文件的路径，可以运行。注意输入默认的电云topic为：/points_raw。
运行时可能会出现一些错误(如下)，改正后即可运行。
5. 错误修改
这里会对opencv的几个错误，需要改一些文件
错误1：
CMake Error at /opt/ros/melodic/share/image_geometry/cmake/image_geometryConfig.cmake:113 (message):
CMake Error at /opt/ros/melodic/share/grid_map_cv/cmake/grid_map_cvConfig.cmake:113 (message):
这对这类错误，可以修改相应的Config.cmake的113行的相关文件
if(NOT "include;/usr/include;/usr/include/opencv " STREQUAL " ")
set(grid_map_cv_INCLUDE_DIRS "")
set(_include_dirs "include;/usr/include;/usr/include/opencv")
去/usr/include/去找opencv，发现找不到，而opencv文件夹在/usr/local/include/中，所以修改为：
if(NOT "include;/usr/include;/usr/local/include/opencv " STREQUAL " ")
set(grid_map_cv_INCLUDE_DIRS "")
set(_include_dirs "include;/usr/include;/usr/local/include;/usr/local/include/opencv")
错误2：
calibration_publisher.cpp:(.text.startup+0xb8e): undefined reference to `cv::read(cv::FileNode const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)'
需要修改calibration_publisher.cpp
static cv::Mat CameraExtrinsicMat;
static cv::Mat CameraMat;
static cv::Mat DistCoeff;
static cv::Size ImageSize;
static std::string DistModel;
static cv::String DistModel_cv; // add code
修改215行代码
fs["CameraExtrinsicMat"] >> CameraExtrinsicMat;
fs["CameraMat"] >> CameraMat;
fs["DistCoeff"] >> DistCoeff;
fs["ImageSize"] >> ImageSize;
// fs["DistModel"] >> DistModel; // block code
fs["DistModel"] >> DistModel_cv; // add code
DistModel = DistModel_cv.operator std::string(); // add code
错误3:
在运行
roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/home/leon/autoware.ai/C16_MODEL/deploy.prototxt pretrained_model_file:=/home/leon/autoware.ai/C16_MODEL/deploy.caffemodel points_src:=/points_raw
命令时如果提示：
/home/leon/autoware.ai/install/lidar_apollo_cnn_seg_detect/lib/lidar_apollo_cnn_seg_detect/lidar_apollo_cnn_seg_detect: error while loading shared libraries: libcaffe.so.1.0.0: cannot open shared object file: No such file or directory
需要在.bashrc中添加：
# caffe
export LD_LIBRARY_PATH=/home/usr_name/caffe/.build_release/lib:$LD_LIBRARY_PATH
错误4(重点错误)：
在运行roslaunch时，会出现错误：
Check failed: bottom[0]->shape(channel_axis_) == channels_ (8 vs. 6) Input size incompatible with convolution kernel.
需要修改代码：
（1）修改autoware.ai/src/autoware/core_perception/lidar_apollo_cnn_seg_detect/include/cnn_segmentation.h文件
double range_, score_threshold_; int width_; int height_; bool use_constant_feature_; // add code std_msgs::Header message_header_; std::string topic_src_;
（2）修改autoware.ai/src/autoware/core_perception/lidar_apollo_cnn_seg_detect/include/feature_generator.h：
FeatureGenerator(){} ~FeatureGenerator(){} // bool init(caffe::Blob<float>* out_blob); // block code bool init(caffe::Blob<float>* out_blob, bool use_constant_feature); // add code
（3）修改autoware.ai/src/autoware/core_perception/lidar_apollo_cnn_seg_detect/launch/lidar_apollo_cnn_seg_detect.launch
<!-- --> <launch> <arg name="network_definition_file" /> <arg name="pretrained_model_file" /> <arg name="points_src" default="/points_raw" /> <arg name="score_threshold" default="0.6" /> <arg name="use_gpu" default="true" /> <arg name="gpu_device_id" default="0" /> <arg name="width" default="512" /> <!-- add code --> <arg name="height" default="512" /> <!-- add code --> <arg name="range" default="60" /> <!-- add code --> <arg name="use_constant_feature" default="false"/> <!-- add code --> <node pkg="lidar_apollo_cnn_seg_detect" type="lidar_apollo_cnn_seg_detect" name="lidar_apollo_cnn_seg_detect_01" output="screen"> <param name="network_definition_file" value="$(arg network_definition_file)" /> <param name="pretrained_model_file" value="$(arg pretrained_model_file)" /> <param name="points_src" value="$(arg points_src)" /> <param name="score_threshold" value="$(arg score_threshold)" /> <param name="use_gpu" value="$(arg use_gpu)" /> <param name="gpu_device_id" value="$(arg gpu_device_id)" /> <param name="height" value="$(arg height)" /> <!-- add code --> <param name="width" value="$(arg width)" /> <!-- add code --> <param name="range" value="$(arg range)" /> <!-- add code --> <param name="use_constant_feature" value="$(arg use_constant_feature)" /> <!-- add code --> </node> <node pkg="detected_objects_visualizer" type="visualize_detected_objects" name="cluster_detect_visualization_01" output="screen" ns="/detection/lidar_detector" /> </launch>
（4）修改autoware.ai/src/autoware/core_perception/lidar_apollo_cnn_seg_detect/nodes/cnn_segmentation.cpp
private_node_handle.param<double>("range", range_, 60.); ROS_INFO("[%s] range: %.2f", __APP_NAME__, range_); // add code // ROS_INFO("[%s] Pretrained Model File: %.2f", __APP_NAME__, range_); //block code
private_node_handle.param<int>("height", height_, 512); ROS_INFO("[%s] height: %d", __APP_NAME__, height_); private_node_handle.param<bool>("use_constant_feature", use_constant_feature_, false); // add code ROS_INFO("[%s] whether to use constant features: %d", __APP_NAME__, use_constant_feature_); // add code
feature_generator_.reset(new FeatureGenerator()); // if (!feature_generator_->init(feature_blob_.get())) // block code if (!feature_generator_->init(feature_blob_.get(), use_constant_feature_)) // add code { ROS_ERROR("[%s] Fail to Initialize feature generator for CNNSegmentation", __APP_NAME__); return false; }
void CNNSegmentation::run() { // init(); // block code if(this->init()){ // add code ROS_INFO("The network init successfully!"); // add code }else{ // add code ROS_ERROR("The network init fail!!!"); // add code } // add code points_sub_ = nh_.subscribe(topic_src_, 1, &CNNSegmentation::pointsCallback, this); points_pub_ = nh_.advertise<sensor_msgs::PointCloud2>("/detection/lidar_detector/points_cluster", 1); objects_pub_ = nh_.advertise<autoware_msgs::DetectedObjectArray>("/detection/lidar_detector/objects", 1); ROS_INFO("[%s] Ready. Waiting for data...", __APP_NAME__); }
修改
// bool FeatureGenerator::init(caffe::Blob<float>* out_blob) // block code bool FeatureGenerator::init(caffe::Blob<float>* out_blob, bool use_constant_feature) // add code { out_blob_ = out_blob; // raw feature parameters range_ = 60; width_ = 512; height_ = 512; min_height_ = -5.0; max_height_ = 5.0; CHECK_EQ(width_, height_) << "Current implementation version requires input_width == input_height."; // set output blob and log lookup table // out_blob_->Reshape(1, 8, height_, width_); // clock code
/********* add code *********/
if(use_constant_feature){ // add code out_blob_->Reshape(1, 8, height_, width_); }else{ out_blob_->Reshape(1, 6, height_, width_); }
/********* add code *********/
log_table_.resize(256); for (size_t i = 0; i < log_table_.size(); ++i) { log_table_[i] = std::log1p(static_cast<float>(i)); } float* out_blob_data = nullptr; out_blob_data = out_blob_->mutable_cpu_data(); // the pretrained model inside apollo project don't use the constant feature like direction_data_ and distance_data_ // add explaination int channel_index = 0; max_height_data_ = out_blob_data + out_blob_->offset(0, channel_index++); mean_height_data_ = out_blob_data + out_blob_->offset(0, channel_index++); count_data_ = out_blob_data + out_blob_->offset(0, channel_index++); // direction_data_ = out_blob_data + out_blob_->offset(0, channel_index++); // block data
/*********** add code ***********/ if(use_constant_feature){ direction_data_ = out_blob_data + out_blob_->offset(0, channel_index++); } /********** add code ************/
top_intensity_data_ = out_blob_data + out_blob_->offset(0, channel_index++); mean_intensity_data_ = out_blob_data + out_blob_->offset(0, channel_index++); // distance_data_ = out_blob_data + out_blob_->offset(0, channel_index++); // block data
/********** add code ************/ if(use_constant_feature){ distance_data_ = out_blob_data + out_blob_->offset(0, channel_index++); }
/********** add code ************/ nonempty_data_ = out_blob_data + out_blob_->offset(0, channel_index++); CHECK_EQ(out_blob_->offset(0, channel_index), out_blob_->count());
/***********block code **********/ // // compute direction and distance features // int siz = height_ * width_; // std::vector<float> direction_data(siz); // std::vector<float> distance_data(siz); // for (int row = 0; row < height_; ++row) { // for (int col = 0; col < width_; ++col) { // int idx = row * width_ + col; // // * row <-> x, column <-> y // float center_x = Pixel2Pc(row, height_, range_); // float center_y = Pixel2Pc(col, width_, range_); // constexpr double K_CV_PI = 3.1415926535897932384626433832795; // direction_data[idx] = // static_cast<float>(std::atan2(center_y, center_x) / (2.0 * K_CV_PI)); // distance_data[idx] = // static_cast<float>(std::hypot(center_x, center_y) / 60.0 - 0.5); // } // } // caffe::caffe_copy(siz, direction_data.data(), direction_data_); // caffe::caffe_copy(siz, distance_data.data(), distance_data_);
/************** block code ******************/
/************** add code **************/ if(use_constant_feature){ // compute direction and distance features int siz = height_ * width_; std::vector<float> direction_data(siz); std::vector<float> distance_data(siz); for (int row = 0; row < height_; ++row) { for (int col = 0; col < width_; ++col) { int idx = row * width_ + col; // * row <-> x, column <-> y float center_x = Pixel2Pc(row, height_, range_); float center_y = Pixel2Pc(col, width_, range_); constexpr double K_CV_PI = 3.1415926535897932384626433832795; direction_data[idx] = static_cast<float>(std::atan2(center_y, center_x) / (2.0 * K_CV_PI)); distance_data[idx] = static_cast<float>(std::hypot(center_x, center_y) / 60.0 - 0.5); } } caffe::caffe_copy(siz, direction_data.data(), direction_data_); caffe::caffe_copy(siz, distance_data.data(), distance_data_); } /****************** add code ******************/
return true; }
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