![]() ![]() LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/hdf5/serial INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial (For ways to create an isolated Python environment, explore the topic of virtual environments here: ) PYTHON_INCLUDE := /usr/include/python2.7 /usr/lib/python2.7/dist-packages/numpy/core/include The nfig should contain the following lines, so find them and fill them in. See )Ĭhange the line accordingly by commenting it out (# CPU_ONLY := 1) if you have an NVIDIA graphics card with the proprietary driver, CUDA toolkit and CUDNN installed. (Notice that there is a special type of virtual machine inside the Ubuntu host machine that can access the physical NVIDIA graphics card directly. This is the typical setting for a computer without any NVIDIA graphics card and it is typical for the installation of Caffe inside the typical virtual machine. ![]() The following line in the configuration file tells the program to use CPU only for the computations. Enter the caffe-master directory in the terminal window.Ĭopy the to nfig like this: Unpack it to ~/bin/ or any other location. The configuration settings will differ for OpenCV 3.1 as you can see above, but here we continue with the basic settings that imply the version 2.x. (or, OpenCV 3.1 - see the instructions below)įor the instructions on how to use the OpenCV version 3.1, please see Sudo apt-get install python3-numpy python3-scipy Sudo apt-get install python-numpy python-scipy Sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev Sudo apt-get install -no-install-recommends libboost-all-dev Sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libhdf5-serial-dev protobuf-compiler Sudo apt-get install build-essential cmake git pkg-config ![]()
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