- #Matlab caffe install install#
- #Matlab caffe install update#
- #Matlab caffe install driver#
- #Matlab caffe install code#
home/lixin/.local/lib/python2.7/site-packages/numpy/core/include PYTHON_INCLUDE := /usr/include/python2.7 \ # We need to be able to find Python.h and numpy/arrayobject.h. # NOTE: this is required only if you will compile the python interface. # MATLAB_DIR := /Applications/MATLAB_R2012b.app # MATLAB directory should contain the mex binary in /bin. # This is required only if you will compile the matlab interface. # BLAS_LIB := $(shell brew -prefix openblas)/lib # BLAS_INCLUDE := $(shell brew -prefix openblas)/include # Homebrew puts openblas in a directory that is not on the standard search path # Leave commented to accept the defaults for your choice of BLAS # Custom (MKL/ATLAS/OpenBLAS) include and lib directories. # For CUDA = 9.0, comment the *_20 and *_21 lines for compatibility.ĬUDA_ARCH := -gencode arch=compute_30,code=sm_30 \ # CUDA architecture setting: going with all of them.
#Matlab caffe install install#
# "sudo apt-get install nvidia-cuda-toolkit" then use this instead: # On Ubuntu 14.04, if cuda tools are installed via # CUDA directory contains bin/ and lib/ directories that we need. the default for Linux is g++ and the default for OSX is clang++ # To customize your choice of compiler, uncomment and set the following. # possibility of simultaneous read and write # You should not set this flag if you will be reading LMDBs with any # uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary) # uncomment to disable IO dependencies and corresponding data layers # CPU-only switch (uncomment to build without GPU support). # cuDNN acceleration switch (uncomment to build with cuDNN). # Contributions simplifying and improving our build system are welcome! if hdf5 version mismatch, add this at the beginning of the m file:
#Matlab caffe install code#
Step8: modify the SfSnet code to make it work. Sudo mv libstdc++.so.6 libstdc++.so.6_bak # change the path to your own.Ĭd Matlab_2015b/ # enter the home folder of the matlab Step7: solve the mismatch of cuda and matlabĬreate soft link to solve the problem caused by version mismatch of cuda and matlab. If some error about libstdc++.so.6 occur after 'sudo make mattest', you will need to do step7. If everything turns out fine, then goto step8. Sudo echo 'export PYTHONPATH=CAFFEPATH/python' > ~/.bashrc Note that you can't always use my file, some pathes need to be customly set according to your own environment.Ĭhange directory to CAFFEPATH and do: cd caffe/ I will attach my 'nfig' file for your reference. In caffe path as the way you want to install it. Sudo ldconfig /usr/local/cuda/lib64 # cuda is often created symbolicaly from cuda-x.0
#Matlab caffe install update#
Ldconfig参考解决方案 update the dynamic library sudo ldconfig /usr/local/cuda-9.0/lib64
#Matlab caffe install driver#
Otherwise, nvidia driver and corresponding version of cudnn are required.Īdd following lines to ~/.bashrc or ~/.zshrc # change the version number of your cudaĮxport LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64:$LD_LIBRARY_PATHĮxport PATH=/usr/local/cuda-9.0/bin:$PATH If you are to install a cpu version of caffe, then the nvidia driver and cudnn isn't necessary. You can also use another version of cuda if you like. enter the command below pip install -r requirements.txt Step4: get caffe source from github: git clone Ģ. Sudo apt-get install -y python-pip python-dev python-numpy python-scipy Sudo apt-get install -y libgflags-dev libgoogle-glog-dev liblmdb-dev
Sudo apt-get install -y -no-install-recommends libboost-all-dev Sudo apt-get install -y libatlas-base-dev
step3: install caffe dependencies: sudo apt-get install -y libprotobuf-dev libleveldb-dev libsnappy-dev libhdf5-serial-dev protobuf-compiler (note that Matlab2017 won't work, haven't try 2016, 2015 is recommended). Matlab+caffe-gpu on Ubuntu 18.04 step1: install and crack Matlab2015b for linux
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