sea@sea-X550JK:/media/sea/wsWin10/wsUbuntu16.04/DlFrames/caffe$ cat Makefile.config：

## Refer to http://caffe.berkeleyvision.org/installation.html

Contributions simplifying and improving our build system are welcome!

BUILD_PYTHON:=1
BUILD_MATLAB:=1
BUILD_docs:=1
BUILD_SHARELIB:=1

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_OPENCV := 1
USE_LEVELDB := 1
USE_LMDB := 1

uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)

You should not set this flag if you will be reading LMDBs with any

possibility of simultaneous read and write

ALLOW_LMDB_NOLOCK := 1

Uncomment if you're using OpenCV 3

OPENCV_VERSION := 3

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 through *_61 lines for compatibility.

For CUDA < 8.0, comment the *_60 and *_61 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_52,code=sm_52 \
-gencode arch=compute_60,code=sm_60 \
-gencode arch=compute_61,code=sm_61 \
-gencode arch=compute_61,code=compute_61

BLAS choice:

atlas for ATLAS (default)

mkl for MKL

open for OpenBlas

BLAS := atlas

Custom (MKL/ATLAS/OpenBLAS) include and lib directories.

Leave commented to accept the defaults for your choice of BLAS

(which should work)!

BLAS_INCLUDE := /usr/include
BLAS_LIB := /usr/lib

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/R2017b

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

#PYTHON_LIB:=/usr/lib/x86_64-linux-gnu/libpython2.7.so

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

Uncomment to use Python 3 (default is Python 2)

PYTHON_LIBRARIES := boost_python3 python3.5m

PYTHON_INCLUDE := /usr/include/python3.5m \

/usr/lib/python3.5/dist-packages/numpy/core/include

We need to be able to find libpythonX.X.so or .dylib.

PYTHON_LIB := /usr/lib /usr/local/lib /usr/lib/x86_64-linux-gnu/

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
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib

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

NCCL acceleration switch (uncomment to build with NCCL)

https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)

USE_NCCL := 1

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

N.B. both build and distribute dirs are cleared on `make clean`

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 ?= @

#INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
INCLUDE_DIRS := $(INCLUDE_DIRS) /usr/local/include /usr/include/hdf5/serial/
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial

LIBRARY_DIRS:=$(LIBRARIES_DIRS) /usr/lib/x86_64-linux-gnu/hdf5/serial

makefile.config

## Refer to http://caffe.berkeleyvision.org/installation.html

Contributions simplifying and improving our build system are welcome!

BUILD_PYTHON:=1
BUILD_MATLAB:=0
BUILD_docs:=1
BUILD_SHARELIB:=1

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_OPENCV := 1
USE_LEVELDB := 1
USE_LMDB := 1

uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)

You should not set this flag if you will be reading LMDBs with any

possibility of simultaneous read and write

ALLOW_LMDB_NOLOCK := 1

Uncomment if you're using OpenCV 3

OPENCV_VERSION := 3

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 through *_61 lines for compatibility.

For CUDA < 8.0, comment the *_60 and *_61 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_52,code=sm_52 \
-gencode arch=compute_60,code=sm_60 \
-gencode arch=compute_61,code=sm_61 \
-gencode arch=compute_61,code=compute_61

BLAS choice:

atlas for ATLAS (default)

mkl for MKL

open for OpenBlas

BLAS := atlas

Custom (MKL/ATLAS/OpenBLAS) include and lib directories.

Leave commented to accept the defaults for your choice of BLAS

(which should work)!

BLAS_INCLUDE := /usr/include
BLAS_LIB := /usr/lib

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/R2016b

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

#PYTHON_INCLUDE := /home/whale/anaconda2/include \
/home/whale/anaconda2/include/python2.7 \
/home/whale/anaconda2/lib/python2.7/site-packages/numpy/core/include

#PYTHON_LIB:=/usr/lib/x86_64-linux-gnu/libpython2.7.so

Anaconda Python distribution is quite popular. Include path:

Verify anaconda location, sometimes it's in root.

HOME:=/home/whale
ANACONDA_HOME := $(HOME)/anaconda2
PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
$(ANACONDA_HOME)/include/python2.7 \
$(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include

Uncomment to use Python 3 (default is Python 2)

PYTHON_LIBRARIES := boost_python3 python3.5m

PYTHON_INCLUDE := /usr/include/python3.5m \

/usr/lib/python3.5/dist-packages/numpy/core/include

We need to be able to find libpythonX.X.so or .dylib.

PYTHON_LIB := /usr/lib /usr/local/lib /usr/lib/x86_64-linux-gnu/

PYTHON_LIB := /home/sea/anaconda2/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
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib

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

NCCL acceleration switch (uncomment to build with NCCL)

https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)

USE_NCCL := 1

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

N.B. both build and distribute dirs are cleared on `make clean`

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 ?= @

#INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
INCLUDE_DIRS := $(PYTHON_INCLUDE) $(INCLUDE_DIRS) /usr/local/include /usr/include/hdf5/serial/
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial

LIBRARY_DIRS:=$(LIBRARIES_DIRS) /usr/lib/x86_64-linux-gnu/hdf5/serial

今天python3.6 不支持2017年的caffe源码----时间关系，不打算测试最新的代码。

下面是python3.5的配置文件：

## Refer to http://caffe.berkeleyvision.org/installation.html

Contributions simplifying and improving our build system are welcome!

BUILD_PYTHON:=1
BUILD_MATLAB:=0
BUILD_docs:=1
BUILD_SHARELIB:=1

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_OPENCV := 1
USE_LEVELDB := 1
USE_LMDB := 1

uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)

You should not set this flag if you will be reading LMDBs with any

possibility of simultaneous read and write

ALLOW_LMDB_NOLOCK := 1

Uncomment if you're using OpenCV 3

OPENCV_VERSION := 3

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 through *_61 lines for compatibility.

For CUDA < 8.0, comment the *_60 and *_61 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_52,code=sm_52 \
-gencode arch=compute_60,code=sm_60 \
-gencode arch=compute_61,code=sm_61 \
-gencode arch=compute_61,code=compute_61

BLAS choice:

atlas for ATLAS (default)

mkl for MKL

open for OpenBlas

BLAS := atlas

Custom (MKL/ATLAS/OpenBLAS) include and lib directories.

Leave commented to accept the defaults for your choice of BLAS

(which should work)!

BLAS_INCLUDE := /usr/include
BLAS_LIB := /usr/lib

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/R2016b

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

#PYTHON_INCLUDE := /home/whale/anaconda3/include \
# /home/whale/anaconda3/include/python2.7 \
# /home/whale/anaconda3/lib/python2.7/site-packages/numpy/core/include

#PYTHON_LIB:=/usr/lib/x86_64-linux-gnu/libpython2.7.so

Anaconda Python distribution is quite popular. Include path:

Verify anaconda location, sometimes it's in root.

HOME:=/home/sea
ANACONDA_HOME := /media/sea/wsWin10/Ubun/env/py35/anaconda3
PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
$(ANACONDA_HOME)/include/python3.5m \
$(ANACONDA_HOME)/lib/python3.5/site-packages/numpy/core/include

Uncomment to use Python 3 (default is Python 2)

PYTHON_LIBRARIES := boost_python3 python3.5m

PYTHON_INCLUDE := /usr/include/python3.5m \

/usr/lib/python3.5/dist-packages/numpy/core/include

We need to be able to find libpythonX.X.so or .dylib.

PYTHON_LIB := /usr/lib /usr/local/lib /usr/lib/x86_64-linux-gnu/

PYTHON_LIB := /home/sea/anaconda3/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
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib

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

NCCL acceleration switch (uncomment to build with NCCL)

https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)

USE_NCCL := 1

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

N.B. both build and distribute dirs are cleared on `make clean`

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 ?= @

#INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
INCLUDE_DIRS := $(PYTHON_INCLUDE) $(INCLUDE_DIRS) /usr/local/include /usr/include/hdf5/serial/
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial

LIBRARY_DIRS:=$(LIBRARIES_DIRS) /usr/lib/x86_64-linux-gnu/hdf5/serial