Ubuntu 16.04 + Caffe Environment Setup (CPU)

1. Installation dependencies

sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compilersudo apt-get install --no-install-recommends libboost-all-devsudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-devsudo apt-get install libatlas-base-dev

Note: It is important to make sure that each is installed, there is no error, or there will be problems later.

2. Installing Python-dev

sudo apt-get install python-dev

3. Download Caffe

Go directly to the website (Https://github.com/BVLC/caffe
) Download and unzip to the/home/usr_name/directory

4. Compiling Caffe

4.1 switch to the Caffe directory you just unzipped
cp Makefile.config.example Makefile.config
4.2 Modifying a configuration file Makefile.config

• Cpu_only: = 1
• Include_dirs: = $ (python_include)/usr/local/include/usr/include/hdf5/serial
  Library_dirs: = $ (python_lib)/usr/local/lib/usr/lib/usr/lib/x86_64-linux-gnu/hdf5/serial
  Note: (Here is to add a section primarily to solve the new version of the HDF5 path problem) Notice the underscore and minus sign

4.3 compiling

sudo make all sudo make testsudo make runtest

Note: The default is a single-core run, you can add a -j4 4-core in the back, indicating success

5. Compiling the Python interface

• Make sure Python-pip and Python-numpy are installed

• Performing installation dependencies
  Under the Python folder in the Caffe root directory, there is a requirements.txt manifest file, which lists the required libraries, which are installed as per the list.
  First go back to Caffe's home directory

  sudo apt-get install gfortrancd ./pythonsudo cat python/requirements.txt|xargs -L 1 sudo pip install

  Once the installation is complete, go back to the Cafffe root directory and we can execute:

  sudo pip install -r python/requirements.txt

  You will see that the successful compilation will show requirement already satisfied, and the installation will continue without a successful compilation.

• Compiling the Python interface

  sudo make pycaffe

  After compiling, run the python structure, go to Caffe/python and execute the command, otherwise you will not be prompted to find Caffe

  6. Running Lenet in Mnist
• Get Data source

sudo ./data/mnist/get_mnist.shsudo ./examples/mnist/create_mnist.sh

• Because the CPU is running, modify the Lenet.prototxt under mnist under the examples file solver_mode:cpu

• Training model

  ./examples/mnist/train_lenet.sh

  The training is completed as follows (i5-7200u 18 minutes or so):
  
  Above

Ubuntu 16.04 + Caffe Environment Setup (CPU)