build failed in "make -j8 && make pycaffe" step

[Geo-fortune]

I have build Caffe successfully before building the fast-rcnn. My opencv version is 3.0.0 . the Terminal shows the error below :

Makefile:545: recipe for target '.build_release/tools/upgrade_net_proto_text.bin' failed make: *** [.build_release/tools/upgrade_net_proto_text.bin] Error 1 make: *** 正在等待未完成的任务.... Makefile:545: recipe for target '.build_release/tools/upgrade_net_proto_binary.bin' failed make: *** [.build_release/tools/upgrade_net_proto_binary.bin] Error 1 .build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用 .build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)’未定义的引用 .build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用 collect2: 错误： ld 返回 1 Makefile:545: recipe for target '.build_release/tools/extract_features.bin' failed make: *** [.build_release/tools/extract_features.bin] Error 1 .build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用 .build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)’未定义的引用 .build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用 collect2: 错误： ld 返回 1 Makefile:545: recipe for target '.build_release/tools/compute_image_mean.bin' failed make: *** [.build_release/tools/compute_image_mean.bin] Error 1

My Makefile.config is below:

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_LEVELDB := 0

USE_LMDB := 0

USE_OPENCV := 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 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_50,code=compute_50

BLAS choice:

atlas for ATLAS (default)

mkl for MKL

open for OpenBlas

BLAS := mkl

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/R2014a

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 \

We need to be able to find libpythonX.X.so or .dylib.

PYTHON_LIB := /usr/local/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/lib/x86_64-linux-gnu/hdf5/serial/include LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial

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

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

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 ?= @

[ajdroid]

Try it without the -j8 flag and see if you still get the error.

[RyanCV]

Hi, I followed the steps of Fast R-CNN, however, when I run make -j16 && make pycaffe, I also have the following problem. I load cuda/7.5, opencv2.4.10, python2.7.10. src/caffe/layers/cudnn_conv_layer.cu(142): error: too few arguments in function call detected during instantiation of "void caffe::CuDNNConvolutionLayer<Dtype>::Backward_gpu(const std::vectorcaffe::Blob<Dtype *, std::allocatorcaffe::Blob<Dtype *>> &, const std::vector<__nv_bool, std::allocator<__nv_bool>> &, const std::vectorcaffe::Blob<Dtype *, std::allocatorcaffe::Blob<Dtype *>> &) [with Dtype=double]" (159): here

20 errors detected in the compilation of "/tmp/tmpxft_0000923f_00000000-16_cudnn_conv_layer.compute_50.cpp1.ii". make: *** [.build_release/cuda/src/caffe/layers/cudnn_conv_layer.o] Error 1

[moyans]

修改上面的Makefile文件（不是Makefile.config）： LIBRARIES += glog gflags protobuf leveldb snappy \ lmdb boost_system hdf5_hl hdf5 m \ opencv_core opencv_highgui opencv_imgproc opencv_imgcodecs 也就是在libraries后面，加上opencv的相关库文件。

[riadhayachi]

you need to use opencv 3

[vokhidovhusan]

@Geo-fortune. I removed my opencv and reinstall it again and worked for me.

[caoyifeng001]

@ajdroid wrong