Caffe

My comments on the installation process of Caffe (CPU only) on MacOS 10.15.1 with Homebrew, Python 3.7.5 and OpenCV 4.1.2

I followed this guide and made a few changes to fit my version needs: https://www.dazhuanlan.com/2019/08/15/5d5514f5efcdc/

• My changes to Makefile.config and include/caffe/ommon.hpp are already committed here

• If the pre-make step fails fails in the build folder due to a vecLib related Error, edit CMakeCache.txt and set vecLib_INCLUDE_DIR:PATH=/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk/System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Headers

• My edits to CMakeCache.txt after running cmake for premake:

//Path to a program.
PYTHON_EXECUTABLE:FILEPATH=/usr/local/bin/python3

//Path to a file.
PYTHON_INCLUDE_DIR:PATH=/usr/local/Cellar/python/3.7.5/Frameworks/Python.framework/Versions/3.7/include/python3.7m

//Path to a library.
PYTHON_LIBRARY:FILEPATH=/usr/local/Cellar/python/3.7.5/Frameworks/Python.framework/Versions/3.7/lib/libpython3.7m.dylib

//Flags used by the CXX compiler during all build types.
CMAKE_CXX_FLAGS:STRING=-std=c++11
  
//Boost python library (release)
Boost_PYTHON_LIBRARY_RELEASE:FILEPATH=/usr/local/Cellar/boost-python3/1.71.0_1/lib/libboost_python37-mt.dylib
  
//Build Caffe without CUDA support
CPU_ONLY:BOOL=ON

• For sudo make test not to fail (see this), I need to change

ifeq ($(OSX), 1)
	CXX := /usr/bin/clang++

into

ifeq ($(OSX), 1)
	CXX := /usr/bin/clang++ -std=c++11

Regular README

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.

Check out the project site for all the details like

• DIY Deep Learning for Vision with Caffe
• Tutorial Documentation
• BAIR reference models and the community model zoo
• Installation instructions

and step-by-step examples.

Custom distributions

• Intel Caffe (Optimized for CPU and support for multi-node), in particular Intel® Xeon processors.
• OpenCL Caffe e.g. for AMD or Intel devices.
• Windows Caffe

Community

Please join the caffe-users group or gitter chat to ask questions and talk about methods and models. Framework development discussions and thorough bug reports are collected on Issues.

Happy brewing!

License and Citation

Caffe is released under the BSD 2-Clause license. The BAIR/BVLC reference models are released for unrestricted use.

Please cite Caffe in your publications if it helps your research:

@article{jia2014caffe,
  Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
  Journal = {arXiv preprint arXiv:1408.5093},
  Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
  Year = {2014}
}