Caffe: CMake源码编译（OpenCV4.2+CUDA)

2022-11-11 08:10:30

周六周日在家倒腾了两天，总算稍微了解点pycaffe的一些接口和api设置了，但是针对不同层，还是有很多注意的细节的，所以也准备写个博客专门总结pycaffe的常见层参数设置，（LZ这个蠢啊，之前居然手写prototxt，一把辛酸泪，太傻了/(ㄒoㄒ)/~~）

之前已经写过用Anaconda直接安装caffe，这样安装caffe不香嘛，为啥非得源码再来安装一次呢？

1.项目里后端是用的tensorflow的接口，前端是要用caffe的接口，caffe的有些参数设置还是源码查询比较方便
2.有一些层是比较特殊的，这种定制化的层可能需要使用c写完之后，再进行源码编译

不过源码编译还是有很多坑的，且听LZ一一道来：

首先下载源码，https://github.com/weiliu89/caffe

按照tutorial安装依赖项：http://caffe.berkeleyvision.org/installation.html

LZ的小小笔记本是Ubuntu16.04

  1. 所以需要先安装对应的依赖库
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install --no-install-recommends libboost-all-dev
  1. 然后LZ使用的是CMake编译的，It requires CMake version >= 2.8.7. The basic steps are as follows:
mkdir build
cd build
cmake ..
make all
make install
make runtest

按照教程，好像简简单单，10分钟就能搞定，但是事实却不是如此。

  1. 当然你得设置下CUDA
# ---[ Options
caffe_option(CPU_ONLY  "Build Caffe without CUDA support" OFF) # TODO: rename to USE_CUDA
caffe_option(USE_CUDNN "Build Caffe with cuDNN library support" ON IF NOT CPU_ONLY)
caffe_option(USE_NCCL "Build Caffe with NCCL library support" OFF)
caffe_option(BUILD_SHARED_LIBS "Build shared libraries" ON)
caffe_option(BUILD_python "Build Python wrapper" ON)
set(python_version "2" CACHE STRING "Specify which Python version to use")
caffe_option(BUILD_matlab "Build Matlab wrapper" OFF IF UNIX OR APPLE)
caffe_option(BUILD_docs   "Build documentation" ON IF UNIX OR APPLE)
caffe_option(BUILD_python_layer "Build the Caffe Python layer" ON)
caffe_option(USE_OPENCV "Build with OpenCV support" ON)
caffe_option(USE_LEVELDB "Build with levelDB" ON)
caffe_option(USE_LMDB "Build with lmdb" ON)
caffe_option(ALLOW_LMDB_NOLOCK "Allow MDB_NOLOCK when reading LMDB files (only if necessary)" OFF)
caffe_option(USE_OPENMP "Link with OpenMP (when your BLAS wants OpenMP and you get linker errors)" OFF)
  1. 首先正常操作：
cmake ..

Caffe: CMake源码编译（OpenCV4.2+CUDA)

注意前方高能（ERROR来袭）

  1. 首先第一个坑就到来了，LZ之前为了编译tensorflow源码，已经源码安装过protobuf了，也是用了-std=c++11这个标准
    所以在cmake报了一些类似如下的错误
error: #error This file requires compiler and library support for the ISO C++ 2011 standard. 
This support is currently experimental, and must be enabled with the -std=c++11 or
 -std=gnu++11 compiler options

error: 'nullptr' was not declared in this scope 这种一长串

所以第一步要添加-std=c++11， cmakel
Caffe: CMake源码编译（OpenCV4.2+CUDA)
makefile得这么改，不过makefile中LZ没有尝试，如果尝试过的小伙伴欢迎指导

CXXFLAGS += -pthread -fPIC $(COMMON_FLAGS) $(WARNINGS) -std=c++11
NVCCFLAGS += -D_FORCE_INLINES -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS) -std=c++11
LINKFLAGS += -pthread -fPIC $(COMMON_FLAGS) $(WARNINGS) -std=c++11
  1. 第二个可能遇到的错误：
nvcc fatal : Unsupported gpu architecture 'compute_20'

这个是CUDA版本决定的，LZ的版本是10.1， 这个文件是在makefile.config里面的，就顺带说一下

# 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_20,code=sm_20 \
                -gencode arch=compute_20,code=sm_21 \
                -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

//注释掉这两句：
 -gencode arch=compute_20,code=sm_20 \
 -gencode arch=compute_20,code=sm_21 \
  1. 第三个可能遇到的错误：
fatal error: hdf5.h: No such file or directory compilation terminated.

用locate定位你的hdf5.h的位置，在makefile中添加对应的路径

# Whatever else you find you need goes here.
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/local/include /usr/include/hdf5/serial/
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib  /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/hdf5/serial

修改library

LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial
  1. 第四个可能遇到的错误：

这个问题就是OpenCV 4版本接口改变导致的，这个改的就有点多了，需要把caffe源码涉及到这个 CV_LOAD_IMAGE_COLOR都换掉。

../caffe/src/caffe/layers/window_data_layer.cpp:293:42: error: ‘CV_LOAD_IMAGE_COLOR’ was not declared in this scope
         cv_img = cv::imread(image.first, CV_LOAD_IMAGE_COLOR);

src/caffe/layers/window_data_layer.cpp

          image_database_cache_[window[WindowDataLayer<Dtype>::IMAGE_INDEX]];
        cv_img = DecodeDatumToCVMat(image_cached.second, true);
      } else {
        //cv_img = cv::imread(image.first, CV_LOAD_IMAGE_COLOR);
        cv_img = cv::imread(image.first, cv::IMREAD_COLOR);
        if (!cv_img.data) {
          LOG(ERROR) << "Could not open or find file " << image.first;
          return;

src/caffe/test/test_io.cpp

bool ReadImageToDatumReference(const string& filename, const int label,
    const int height, const int width, const bool is_color, Datum* datum) {
  cv::Mat cv_img;
  //int cv_read_flag = (is_color ? CV_LOAD_IMAGE_COLOR :
    //CV_LOAD_IMAGE_GRAYSCALE);
  int cv_read_flag = (is_color ? cv::IMREAD_COLOR :
    cv::IMREAD_GRAYSCALE);

  cv::Mat cv_img_origin = cv::imread(filename, cv_read_flag);
  if (!cv_img_origin.data) {

src/caffe/util/io.cpp

void WriteProtoToBinaryFile(const Message& proto, const char* filename) {
cv::Mat ReadImageToCVMat(const string& filename,
   const int height, const int width, const bool is_color) {
 cv::Mat cv_img;
// int cv_read_flag = (is_color ? CV_LOAD_IMAGE_COLOR :
  // CV_LOAD_IMAGE_GRAYSCALE);
 int cv_read_flag = (is_color ? cv::IMREAD_COLOR :
   cv::IMREAD_GRAYSCALE);
 cv::Mat cv_img_origin = cv::imread(filename, cv_read_flag);
 if (!cv_img_origin.data) {
   LOG(ERROR) << "Could not open or find file " << filename;


cv::Mat DecodeDatumToCVMat(const Datum& datum, bool is_color) {
 CHECK(datum.encoded()) << "Datum not encoded";
 const string& data = datum.data();
 std::vector<char> vec_data(data.c_str(), data.c_str() + data.size());
// int cv_read_flag = (is_color ? CV_LOAD_IMAGE_COLOR :
  // CV_LOAD_IMAGE_GRAYSCALE);
 int cv_read_flag = (is_color ? cv::IMREAD_COLOR :
   cv::IMREAD_GRAYSCALE);
 cv_img = cv::imdecode(vec_data, cv_read_flag);
 if (!cv_img.data) {
   LOG(ERROR) << "Could not decode datum ";
  1. 第五个可能遇到的错误：
    Anaconda的三方库和本地库冲突了，那就把Anaconda的环境变量先注释掉，编译好了再放出来就好了

最后放张编译成功的图。。。
Caffe: CMake源码编译（OpenCV4.2+CUDA)
自己踩坑千千万，跳出一坑，又进了一坑！

据说OpenCV4.1版本之前存在安全隐患问题，所以现在LZ的公司都换成OpenCV4.2版本了。。。

参考地址：
1.https://blog.csdn.net/m_buddy/article/details/88085425
2.https://blog.csdn.net/qq_18649781/article/details/89047437
3.https://github.com/BVLC/caffe/issues/6680
4.https://github.com/BVLC/caffe/pull/6625/files/7f503bd9a19758a173064e299ab9d4cac65ed60f

PS:
LZ已经在自己家隔离20多天了，到工作的地方还得隔离14天，大门不出二门不卖，真希望能够肆无忌惮的在一个阳关明媚的午后压马路O(∩_∩)O～

现在是关键时刻，还不能放松，越到紧要关头，越要能忍住！
Caffe: CMake源码编译（OpenCV4.2+CUDA)Caffe: CMake源码编译（OpenCV4.2+CUDA)

武汉加油！湖北加油！中国加油！↖(ω)↗

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