Ubuntu 18.04+VS Code +Python + Anaconda + caffe(CPU)配置

Posted 2023-02-26 feisonzl

1.安装Anaconda

官方：https://www.anaconda.com/products/individual#Downloads

清华镜像：https://mirrors.tuna.tsinghua.edu.cn/help/anaconda/

2.安装VS code

https://code.visualstudio.com/docs/?dv=linux64_deb
sudo dpkg -i ./codexxx.deb

3.安装VS code插件

Visual Studio IntelliCode
Python

4.vscode配置

在~/.config/Code/User/settings.json文件中添加如下内容：

“python.condaPath”: “HOME.conda/envs/xxx/bin/conda”,
“python.pythonPath”: “HOME/.conda/envs/xxx/bin/python”
“python.autoComplete.extraPaths”: [
“~/.conda/envs/dl/lib/python3.7/site-packages”
],
“python.autoComplete.addBrackets”: true,
“python.jediEnabled”: false,

5.conda 安装模块

为指定环境安装模块

conda install -n py38 spyder-kernels=1.94

6.conda install opencv-python

sudo apt-get install libcanberra-gtk-module
sudo apt-get install -y build-essential cmake
# ubuntu 16.04
sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev 

sudo apt-get install -y qt5-default libvtk6-dev
sudo apt-get install -y zlib1g-dev libjpeg-dev libwebp-dev libpng-dev libtiff5-dev libjasper-dev libopenexr-dev libgdal-dev
sudo apt-get install -y libdc1394-22-dev libavcodec-dev libavformat-dev libswscale-dev libtheora-dev libvorbis-dev libxvidcore-dev libx264-dev yasm libopencore-amrnb-dev libopencore-amrwb-dev libv4l-dev libxine2-dev
sudo apt-get install -y libtbb-dev libeigen3-dev
sudo apt-get install -y python-dev python-tk python-numpy python3-dev python3-tk python3-numpy
cd opencv
mkdir build 
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=/opt/opencv/ -DBUILD_opencv_python3=yes -DBUILD_opencv_python2=no -DPYTHON3_EXECUTABLE=/home/feison/anaconda3/envs/py36/bin/python3.6m -DPYTHON3_INCLUDE_DIR=/home/feison/anaconda3/envs/py36/include/python3.6m -DPYTHON3_LIBRARY=/home/feison/anaconda3/envs/py36/lib/libpython3.6m.so -DPYTHON3_NUMPY_INCLUDE_DIRS=/home/feison/anaconda3/envs/py36/lib/python3.6/site-packages/numpy/core/include -DPYTHON3_PACKAGES_PATH=/home/feison/anaconda3/envs/py36/lib/python3.6/site-packages -DPYTHON_DEFAULT_EXECUTABLE=/home/feison/anaconda3/envs/py36/bin/python3.6m -DWITH_FFMPEG=ON -DWITH_OPENGL=ON -DWITH_LIBV4L=ON -DWITH_V4L=ON -DWITH_QT=OFF -DWITH_GTK=ON -DBUILD_TIFF=ON ..

~/.bashrc
export PATH=$PATH:/opt/opencv/bin
export PKG_CONFIG_PATH=/opt/opencv/lib/pkgconfig:$PKG_CONFIG_PATH
export LD_LIBRARY_PATH=/opt/opencv/lib/:$LD_LIBRARY_PATH

7.conda install caffe

7.1 install dependencies lib

sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler libopenblas-dev
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install libopenblas-dev
cd /usr/lib/x86_64-linux-gnu
sudo mv libboost_python.so libboost_python.so.back #backup py2.7 boost lib
sudo ln -s libboost_python-py36.so libboost_python.so
sudo ln -s libboost_python-py36.so libboost_python3.so

7.2 download caffe source code

# github download speed too slow
# git clone https://github.com/BVLC/caffe.git 
git clone https://gitee.com/cuibixuan/caffe.git

7.3 build caffe

7.3.1 modify Makefile.config

cp Makefile.config.example Makefile.config

7.3.2 Makefile.config content

there is some options need you be pay attention

CPU_ONLY := 1
OPENCV_VERSION := 3
ANACONDA_HOME := $(HOME)/anaconda3
PYTHON_INCLUDE := $(ANACONDA_HOME)/envs/py36/include/python3.6m \\
		$(ANACONDA_HOME)/lib/python3.8/site-packages/numpy/core/include

PYTHON_LIBRARIES := boost_python3-py36 python3.6m
PYTHON_LIB := $(ANACONDA_HOME)/envs/py36/lib

WITH_PYTHON_LAYER := 1

# Whatever else you find you need goes here.
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial /opt/opencv/include
#LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial
LIBRARY_DIRS := $(PYTHON_LIB) /usr/lib/x86_64-linux-gnu/hdf5/serial /opt/opencv/lib
LINKFLAGS := -Wl,-rpath,$(HOME)/anaconda3/lib

## 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

# 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)/anaconda3
PYTHON_INCLUDE := $(ANACONDA_HOME)/envs/py36/include/python3.6m \\
		$(ANACONDA_HOME)/lib/python3.8/site-packages/numpy/core/include

# Uncomment to use Python 3 (default is Python 2)
PYTHON_LIBRARIES := boost_python3-py36 python3.6m
# 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
PYTHON_LIB := $(ANACONDA_HOME)/envs/py36/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 /usr/include/hdf5/serial /opt/opencv/include
#LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial
LIBRARY_DIRS := $(PYTHON_LIB) /usr/lib/x86_64-linux-gnu/hdf5/serial /opt/opencv/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 ?= @

LINKFLAGS := -Wl,-rpath,$(HOME)/anaconda3/lib

7.3.3 build

conda activate py36
cd caffe
make pycaffe -j10
make all -j10
make test -j10

7.3.4 install caffe lib to conda env

cp  python/caffe/ ~/anaconda3/envs/py36/lib/python3.6/ -rf
cp build/lib/libcaffe.* ~/anaconda3/envs/py36/lib/