Face_Parsing_2016-master（Multi-Objective Convolutional Learning for Face Labeling）

源码说明：

人脸标注，11类。

1. 从github下载源码。

https://github.com/Liusifei/Face_Parsing_2016

2. 编译源码

这个源码下载后，里面只有Makefile文件，没有Makefile.config文件

将3分类FaceLabeling中配置好的Makefile.config，拷贝到Face_Parsing_2016-master/目录下（Face_Parsing_2016-master/为我的解压目录），不要使用cuDNN加速，我这里使用加速后不能编译通过。

我的配置文件如下：

## Refer to http://caffe.berkeleyvision.org/installation.html
# Contributions simplifying and improving our build system are welcome!


# cuDNN acceleration switch (uncomment to build with cuDNN).
# vUSE_CUDNN := 1


# CPU-only switch (uncomment to build without GPU support).
# CPU_ONLY := 1


# 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 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_50,code=compute_50


# 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/atlas
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_DIR := /usr/local/MATLAB/R2014a/


# 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 := /home/sfliu/anaconda/include \
#     /home/sfliu/anaconda/include/python2.7 \
#     /home/sfliu/anaconda/lib/python2.7/site-packages/numpy/core/include
PYTHON_INCLUDE := /usr/include/python2.7 \
/usr/lib/python2.7/dist-packages/numpy/core/include     
# 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 \


# We need to be able to find libpythonX.X.so or .dylib.
#PYTHON_LIB := /home/sfliu/anaconda/lib \
#        /usr/lib/python2.7
PYTHON_LIB := /usr/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 \
#                /home/sfliu/common_caffe/include \
#          /usr/include/atlas \
#                /usr/include/opencv \
#                /usr/include/opencv2 \
#                /home/sfliu/anaconda/include \
#                /usr/local/cuda-7.0/include  \
#                /usr/local/cuda/include
#LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib \
#                /home/sfliu/common_caffe/lib \
#         /usr/lib/atlas-base \
#                /usr/lib/x86_64-linux-gnu \
#                /home/sfliu/anaconda/lib \
#                /usr/local/cuda-7.0/lib64 \
#                /usr/local/cuda/lib64
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 /usr/lib/x86_64-linux-gnu/hdf5/serial


# 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


# 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


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 ?= @

3. 使用make命令编译

4. 按照 README.md 中的说明，运行matlab demo。