maskrcnn 环境搭建
1，GCC 4.9 GCC降级
~$ sudo apt-get install gcc-4.9 g++-4.9
--> Set "priority=100" for gcc-4.9 and "priority=50" for gcc-5.~$ sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.9 100~$ sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5.0 50
--> Set "priority=100" for g++-4.9 and "priority=50" for g++-5.~$ sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-4.9 100~$ sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-5.0 50
2，安装cuda
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt-get install nvidia-390 nvidia-settings nvidia-prime
(connect net )
sudo dpkg -i cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64.deb
sudo apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub#具体版本号不同可以使用tab键补全
sudo apt-get update
sudo apt-get install cuda
安装cuDNN
再次重申需要选择正确对应版本，选择的是cuDNN v7的版本
下载完成后，cd到文件文件目录，执行安装命令
sudo dpkg -i libcudnn7_7.0.5.15-1+cuda9.0_amd64.deb#具体版本可能不同，不用复制这个命令安装anaconda
从这里下载速度比较快，下载链接https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-5.3.0-Linux-x86_64.sh
cd到文件的目录，假如默认下载目录是download
cd download
bash Anaconda3-5.3.0-Linux-x86_64.sh#可使用tab补全
安装maskrcnn_benchmark
在cuda安装完成，gcc也成功降级之后，到这一步直接按照maskrcnn_benchmark的官方教程按照就可以了，只不过要安装opencv,就稍加修改。中文部分就是添加的部分
# first, make sure that your conda is setup properly with the right environment
# for that, check that `which conda`, `which pip` and `which python` points to the
# right path. From a clean conda env, this is what you need to do
conda create --name maskrcnn_benchmark
source activate maskrcnn_benchmark
#安装opencv
conda install -c conda-forge opencv
#安装opencv
# this installs the right pip and dependencies for the fresh python
conda install ipython
# maskrnn_benchmark and coco api dependencies
pip install ninja yacs cython matplotlib
# follow PyTorch installation in https://pytorch.org/get-started/locally/
# we give the instructions for CUDA 9.0
conda install pytorch-nightly -c pytorch
# install torchvision
cd ~/github
git clone https://github.com/pytorch/vision.git
cd vision
python setup.py install
# install pycocotools
cd ~/github
git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
python setup.py build_ext install
# install PyTorch Detection
cd ~/github
git clone https://github.com/facebookresearch/maskrcnn-benchmark.git
cd maskrcnn-benchmark
# the following will install the lib with
# symbolic links, so that you can modify
# the files if you want and won't need to
# re-build it
python setup.py build develop
# or if you are on macOS
# MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py build develop
#到这里发现opencv失效，但是conda list查看包还在
pip install opencv-python
附上demo的测试使用
cd demo
# by default, it runs on the GPU
# for best results, use min-image-size 800 显示我的驱动版本低
python webcam.py --min-image-size 800
# can also run it on the CPU 插上摄像头即可
python webcam.py --min-image-size 300 MODEL.DEVICE cpu
# or change the model that you want to use
python webcam.py --config-file ../configs/caffe2/e2e_mask_rcnn_R_101_FPN_1x_caffe2.yaml --min-image-size 300 MODEL.DEVICE cpu
# in order to see the probability heatmaps, pass --show-mask-heatmaps
python webcam.py --min-image-size 300 --show-mask-heatmaps MODEL.DEVICE cpu