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Caffe

dazuo Jul 2, 2020 2020-07-02T20:19:00+08:00
Apr 29, 2022 2022-04-29T20:53:19+08:00 6 min

源码安装

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# 下载源码
git clone https://github.com/BVLC/caffe.git

# 根据当前环境基于模板修改Makefile.config
cp Makefile.config.example Makefile.config
vim Makefile.config

# 用make编译caffe bin, 找不到的头文件, lib, 通过安装对应lib，修改Makefile.config解决
make all -j8

# 安装依赖的lib
sudo apt-get install libboost-dev
sudo apt-get install libgflags-dev
sudo apt-get install libgoogle-glog-dev
sudo apt-get install libatlas-base-dev
sudo apt-get install libhdf5-dev
sudo apt-get install libleveldb-dev
sudo apt-get install liblmdb-dev

# 给依赖的lib创建软连接
sudo ln -s  /usr/lib/x86_64-linux-gnu/libboost_system.so.1.65.1 /usr/local/lib/libboost_system.so
sudo ln -s  /usr/lib/x86_64-linux-gnu/libboost_filesystem.so.1.65.1 /usr/local/lib/libboost_filesystem.so
sudo ln -s  /usr/lib/x86_64-linux-gnu/libsnappy.so.1.1.7 /usr/local/lib/libsnappy.so
sudo ln -s  /usr/lib/x86_64-linux-gnu/libboost_thread.so.1.65.1 /usr/local/lib/libboost_thread.so

# 编译Python接口
sudo apt-get install libboost-python-dev
make pycaffe

增加Upsample层

将caffe upsample中的upsample_layer.cpp和upsample_layer.h分别考到src/caffe/layers和include/caffe/layers目录下。然后把upsample_layer.cpp中的REGISTER_LAYER_CLASS(Upsample);注释掉，否则会报重复注册。

在src/caffe/layer_factory.cpp中增加注册Upsample层的代码，如下所示：

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// Get Upsample layer according to engine.
template <typename Dtype>
shared_ptr<Layer<Dtype> > GetUpsampleLayer(const LayerParameter& param) {
    int engine = 0;
#ifdef USE_CUDNN
        engine = 1;
#endif

    if (engine == 0) {
        return shared_ptr<Layer<Dtype> >(new UpsampleLayer<Dtype>(param));
#ifdef USE_CUDNN
    }
    else if (engine == 1) {
        return shared_ptr<Layer<Dtype> >(new CuDNNUpsampleLayer<Dtype>(param));
#endif
    }
    else {
        LOG(FATAL) << "Layer " << param.name() << " has unknown engine.";
        throw;  // Avoids missing return warning
    }
}

REGISTER_LAYER_CREATOR(Upsample, GetUpsampleLayer);

附录

参考文献

Makefile.config参考配置

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## 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).
# 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 := 0
# USE_LEVELDB := 0
# USE_LMDB := 0
# This code is taken from https://github.com/sh1r0/caffe-android-lib
# USE_HDF5 := 0

# 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.
# For CUDA >= 9.0, comment the *_20 and *_21 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 := /path/to/your/blas
# BLAS_LIB := /path/to/your/blas

# 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 := /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
# 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 python3.7m
PYTHON_INCLUDE := /usr/local/python3.7/include/python3.7m \
                  /usr/local/python3.7/lib/python3.7/site-packages/numpy/core/include
									

# We need to be able to find libpythonX.X.so or .dylib.
PYTHON_LIB := /usr/lib/ /usr/local/python3.7/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/include/hdf5/serial /usr/local/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/lib/x86_64-linux-gnu/hdf5/serial /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 ?= @
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