Detectron平台使用（二）Detectron平台安装与测试

2. Detectron
   安装准备：
   CUDA
   cuDNN
   CAFFE2
   目前电脑配置主要有：
   台式机 RTX2070显卡
   笔记本 1060显卡
   2.1 Detectron 平台安装
   CUDA
   cuDNN
   CAFFE2
   Detectron平台安装

目前电脑配置主要有：
台式机 RTX2070显卡
笔记本 1060显卡

2.1.1 安装caffe2

1. 安装caffe2
   参考：
   官方教程：https://caffe2.ai/docs/getting-started.html?platform=ubuntu&configuration=compile#install-with-gpu-support

sudo apt-get update
sudo apt-get install -y --no-install-recommends
build-essential
git
libgoogle-glog-dev
libgtest-dev
libiomp-dev
libleveldb-dev
liblmdb-dev
libopencv-dev
libopenmpi-dev
libsnappy-dev
libprotobuf-dev
openmpi-bin
openmpi-doc
protobuf-compiler
python-dev
python-pip
pip install --user
future
numpy
protobuf
typing
hypothesis

for Ubuntu 14.04

sudo apt-get install -y --no-install-recommends
libgflags2
cmake3

for Ubuntu 16.04

sudo apt-get install -y --no-install-recommends
libgflags-dev
cmake
安装方法1：

Clone Caffe2’s source code from our Github repository

git clone https://github.com/pytorch/pytorch.git && cd pytorch
git submodule update --init --recursive

Create a directory to put Caffe2’s build files in

mkdir build && cd build

Configure Caffe2’s build

This looks for packages on your machine and figures out which functionality

to include in the Caffe2 installation. The output of this command is very

useful in debugging.

cmake …

Compile, link, and install Caffe2

sudo make install
安装方法2：
官方安装方法，****ok
git clone https://github.com/pytorch/pytorch.git && cd pytorch
git submodule update --init --recursive
sudo python setup.py install

会在python文件夹下建立build文件夹

10. 检查caffe2是否安装成功
    Caffe2
    To install Caffe2 with CUDA support, follow the from the . If you already have Caffe2 installed, make sure to update your Caffe2 to a version that includes the .
    Please ensure that your Caffe2 installation was successful before proceeding by running the following commands and checking their output as directed in the comments.

To check if Caffe2 build was successful

在根目录下运行：
python -c ‘from caffe2.python import core’ 2>/dev/null && echo “Success” || echo “Failure”

To check if Caffe2 GPU build was successful

This must print a number > 0 in order to use Detectron

python -c ‘from caffe2.python import workspace; print(workspace.NumCudaDevices())’
If the caffe2 Python package is not found, you likely need to adjust your PYTHONPATH environment variable to include its location (/path/to/caffe2/build, where build is the Caffe2 CMake build directory).
2.1.2 增加环境变量
如果是failure，试着cd到caffe2/build的文件夹里，然后执行
python -c ‘from caffe2.python import core’ 2>/dev/null
如果successful，说明是环境变量的设置问题，如果还是失败，则会有具体的提示。
配置环境变量，编辑~/.bashrc
sudo gedit ~/.bashrc
添加以下内容：
export PYTHONPATH=/usr/local:$PYTHONPATH export PYTHONPATH=$PYTHONPATHexportPYTHONPATH=PYTHONPATH:/home/pyhthon/build (后面路径为caffe2的编译路径，在caffe2/build中，命令行输入pwd可以得到这个路径)
export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
添加完以后更新一下环境变量
source ~/.bashrc

2.1.3 错误与测试
1.附加测试：确保没有报错/usr/local/cuda-10.0/targets/x86_64-linux/lib/libcudnn.so.7 is not a symbolic link
cd /usr/local/lib
sudo ldconfig
/usr/local/cuda-9.0/targets/x86_64-linux/lib/libcudnn.so.7 is not a symbolic link解决方法 - 阿耀的博客 - ****博客

1. 运行在python2 下错误:
   错误1：
   ERROR: Command “python setup.py egg_info” failed with error code 1 in /tmp/pip-install-4HhZog/future/
   解决：

python -m pip install --upgrade --force pip
pip install setuptools

结果：
Successfully installed setuptools-41.0.1

11. 错误2：
    Traceback (most recent call last):
    File “/usr/bin/pip”, line 9, in
    from pip import main
    ImportError: cannot import name ‘main’

解决：
sudo gedit /usr/bin/pip
编辑
修改：
from pip import main # 需要修改
if name == ‘main’:
sys.exit(main._main()) # 需要修改

12. 错误3：
    RuntimeError: Missing build dependency: Unable to import yaml.
    Please install it via conda install pyyaml or pip install pyyaml
    解决：

pip install --user -i https://pypi.tuna.tsinghua.edu.cn/simple pyyaml

2.1.4 安装 COCO API

1. 安装COCO API
   Install the :

COCOAPI=/path/to/clone/cocoapi

git clone https://github.com/cocodataset/cocoapi.git $COCOAPI
cd $COCOAPI/PythonAPI

安装到全局第三方库中

sudo make install

Alternatively, if you do not have permissions or prefer

安装到用户Python库中

sudo python2 setup.py install --user
结果:

13. 错误与解决
    a) 错误1：
    Makefile:7: recipe for target ‘install’ failed
    make: *** [install] Error 1

解决：
安装make
sudo apt-get update
sudo apt-get install ubuntu-make

b) 错误2：
x86_64-linux-gnu-gcc: error: pycocotools/_mask.c: No such file or directory
x86_64-linux-gnu-gcc: fatal error: no input files
compilation terminated.
error: command ‘x86_64-linux-gnu-gcc’ failed with exit status 1
Makefile:3: recipe for target ‘all’ failed

解决方法：
pip install cython
pip install --user -i https://pypi.tuna.tsinghua.edu.cn/simple cython
2.1.5 安装 Detectron

1. 安装Detectron
   克隆Detectron存储库：

DETECTRON=/path/to/clone/detectron

git clone https://github.com/facebookresearch/detectron $DETECTRON
安装Python依赖项：
pip install --user -r $DETECTRON/requirements.txt
设置Python模块：
cd $DETECTRON && make
14) 测试Detectron
检查Detectron测试是否通过（例如）：
python $DETECTRON/detectron/tests/test_spatial_narrow_as_op.py

15. 错误与解决
    错误
    or: [Errno 13] Permission denied: ‘/home/lijie/.local/lib/python2.7/site-packages/easy-install.pth’
    Makefile:17: recipe for target ‘dev’ failed
    make: *** [dev] Error 1
    解决：
    安装make
    sudo apt-get update
    sudo apt-get install ubuntu-make