fast-rcnn
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rbgirshick
build failed in "make -j8 && make pycaffe" step
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
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 ?= @
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
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。
@Geo-fortune. I removed my opencv and reinstall it again and worked for me.
