• py-faster-rcnn 的makefile.config 注意事项


    在配置py-faster-rcnn的过程中,我遇到一些问题,记录如下

    py-faster-rcnn文件夹下面有一个caffe-fast-rcnn文件夹

    这个过程中,我们需要编译caffe, 

     大神的caffe和caffe官网的版本不太一样

    我第一次直接照搬caffe的makefile.config,导致了很多错误

    rbgirshick 大神说,需要打开 WITH_PYTHON_LAYER := 1
                         和  USE_CUDNN := 1

    Note: Caffe must be built with support for Python layers!

    # In your Makefile.config, make sure to have this line uncommented
    WITH_PYTHON_LAYER := 1
    # Unrelatedly, it's also recommended that you use CUDNN
    USE_CUDNN := 1
    但是由于我安装的cudnn版本不对,就造成下面的报
    util/cudnn.hpp: In function ‘void caffe::cudnn::createPoolingDesc(cudnnPoolingStruct**, caffe::PoolingParameter_PoolMethod, cudnnPoolingMode_t*, int, int, int, int, int, int)’:  
    ./include/caffe/util/cudnn.hpp:117:13: error: ‘CUDNN_POOLING_AVERAGE_COUNT_INCLUDE_PADDING’ was not declared in this scope  
         *mode = CUDNN_POOLING_AVERAGE_COUNT_INCLUDE_PADDING;  
                 ^  
    Makefile:510: recipe for target '.build_release/src/caffe/util/im2col.o' failed  
    make: *** [.build_release/src/caffe/util/im2col.o] Error 1  

    这个时候,可以换cudnn的版本,这样的话,需要重新配置和编译一下caffe,我比较懒,就没这么做。
    还有最简单的办法是: 直接关掉 cudnn 这样就不会报这个错误了

    接着 make all
    出现了下面这个错误
    我在编译单独caffe的时候,就已经把opencv安装好了,按理来说不应该出现这个错误

    .build_release/lib/libcaffe.so: undefined reference to `cv::imread(cv::String const&, int)'
    .build_release/lib/libcaffe.so: undefined reference to `cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)'
    .build_release/lib/libcaffe.so: undefined reference to `cv::imdecode(cv::_InputArray const&, int)'
    collect2: error: ld returned 1 exit status
    make: *** [.build_release/tools/convert_imageset.bin] Error 1

    我 google到了解决办法

    意思就是在 makefile.config里面加一个LIBRARIES

    我是这样加的  直接加在opencv下面

    # Uncomment if you're using OpenCV 3
     OPENCV_VERSION := 3
    LIBRARIES += glog gflags protobuf leveldb snappy 
    lmdb boost_system hdf5_hl hdf5 m 
    opencv_core opencv_highgui opencv_imgproc opencv_imgcodecs

    再make all就通过了

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  • 原文地址:https://www.cnblogs.com/YangQiaoblog/p/6756372.html
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