• 姿势估计实验-Realtime_Multi-Person_Pose_Estimation-CMU

    前言：

    论文及源代码网址：

    https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation

    地址2:

    https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/installation.md

    1.  一个失败的尝试

    首先是跑一个例子试试，使用

    https://github.com/CMU-Perceptual-Computing-Lab/openpose/

    按照作者的指导，如下：

    Training Steps

    • Run cd training; bash getData.sh to obtain the COCO images in dataset/COCO/images/, keypoints annotations in dataset/COCO/annotations/ and COCO official toolbox in dataset/COCO/coco/.
      • 　　这里建议开screen，因为要下载超级久
    • Run getANNO.m in matlab to convert the annotation format from json to mat in dataset/COCO/mat/.
    • Run genCOCOMask.m in matlab to obatin the mask images for unlabeled person. You can use 'parfor' in matlab to speed up the code.
      • 　　注意修改Matlab程序中的路径，在  im = imread(['dataset/COCO/', img_paths]);的COCO后面加上images/，原程序有点问题
      •       这里尝试开启了一下并行运算，速度特别快，将代码中第二个for循环改为parfor i = 1:L，然后使用Matlab的时候，先输入matlabpool open，然后再运行程序。关闭的方法为matlabpool close
        • 　　然后遇到了Subscripted assignment between dissimilar structures.问题，看代码也没有找到问题，参考 [1]
    • Run genJSON('COCO') to generate a json file in dataset/COCO/json/ folder. The json files contain raw informations needed for training.
    • Run python genLMDB.py to generate your LMDB. (You can also download our LMDB for the COCO dataset (189GB file) by: bash get_lmdb.sh)
    • Download our modified caffe: caffe_train. Compile pycaffe. It will be merged with caffe_rtpose (for testing) soon.
    • Run python setLayers.py --exp 1 to generate the prototxt and shell file for training.
    • Download VGG-19 model, we use it to initialize the first 10 layers for training.
    • Run bash train_pose.sh 0,1 (generated by setLayers.py) to start the training with two gpus.

    2. 安装Caffe

    这种跑一个例子失败之后，

    转而使用最根本的方法从头按照步骤编译，不走捷径：参考下面的网址

    https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/installation.md

    因为电脑里已经安装过caffe的依赖环境了，所以把caffe编译一下就可以用了，参考下面的话 [3] 

    ### Install Caffe ###
cd 3rdparty/caffe/
# Select your desired Makefile file (run only one of the next 4 commands)
cp Makefile.config.Ubuntu14_cuda7.example Makefile.config # Ubuntu 14, cuda 7
cp Makefile.config.Ubuntu14_cuda8.example Makefile.config # Ubuntu 14, cuda 8
cp Makefile.config.Ubuntu16_cuda7.example Makefile.config # Ubuntu 16, cuda 7
cp Makefile.config.Ubuntu16_cuda8.example Makefile.config # Ubuntu 16, cuda 8
# Change any custom flag from the resulting Makefile.config (e.g. OpenCV 3, Atlas/OpenBLAS/MKL, etc.)
# Compile Caffe
    make all -j${number_of_cpus} && make distribute -j${number_of_cpus}

    比如make all -j16（使用16个CPU同时运行）


    
                           3. 安装 OpenPose
cd ../../models/
bash ./getModels.sh # It just downloads the Caffe trained models
cd ..
# Same file cp command as the one used for Caffe
cp ubuntu/Makefile.config.Ubuntu14_cuda7.example Makefile.config
# Change any custom flag from the resulting Makefile.config (e.g. OpenCV 3, Atlas/OpenBLAS/MKL, etc.)
make all -j${number_of_cpus}

    一定要严格按照顺序（实验室服务器用的是zsh，所以注意替换bash为zsh）

    如果使用OpenCV 3版本的话，可以通过所有make，但是不能运行实际的例子

    按照作者在某个Issue下的回答，应该使用OpenCV2.4，然后折腾很久，见另一篇博客 [7]

    然后出现无法make，错误中关键行为这个

    ../lib/libcaffe.so: undefined reference to cv::imread(cv::String const&, int)'

    搜索之后得到解答：[4]

    open your Makefile with some text editor, locate line 164 (in my case), add opencv_imgcodecs behind.

     LIBRARIES += glog gflags protobuf leveldb snappy 
  lmdb boost_system hdf5_hl hdf5 m 
  opencv_core opencv_highgui opencv_imgproc opencv_imgcodecs

    在vim里使用

    :se nu

    然后回车，可以显示行号；使用

    /opencv

    可以快速定位到第一个出现的opencv字符串的位置

    添加后可以make了，然后不出意料的还是不能运行实际的例子：

    4. 运行一个例子

    实际例子运行方法：[3]

    1. Running on Video

    # Ubuntu
./build/examples/openpose/openpose.bin --video examples/media/video.avi
# With face and hands
./build/examples/openpose/openpose.bin --video examples/media/video.avi --face --hand

    会出现

    zsh: abort (core dumped)  ./build/examples/openpose/openpose.bin --video examples/media/video.avi

    再试试别的运行方法：

    3. Running on Images

    # Ubuntu
./build/examples/openpose/openpose.bin --image_dir examples/media/
# With face and hands
./build/examples/openpose/openpose.bin --image_dir examples/media/ --face --hand

    会出现

    Starting pose estimation demo.

    Error:

    boost::filesystem::directory_iterator::construct: No such file or directory

    Coming from:

    - src/openpose/utilities/fileSystem.cpp:getFilesOnDirectory():186

    - src/openpose/producer/imageDirectoryReader.cpp:getImagePathsOnDirectory():25

    - src/openpose/utilities/flagsToOpenPose.cpp:flagsToProducer():133

    terminate called after throwing an instance of 'std::runtime_error'

      what():  

    Error:

    boost::filesystem::directory_iterator::construct: No such file or directory

    Coming from:

    - src/openpose/utilities/fileSystem.cpp:getFilesOnDirectory():186

    - src/openpose/producer/imageDirectoryReader.cpp:getImagePathsOnDirectory():25

    - src/openpose/utilities/flagsToOpenPose.cpp:flagsToProducer():133

    zsh: abort (core dumped)  ./build/examples/openpose/openpose.bin --image_dir examples/media/

    然后搜索后，根据 [5] DuinoDu的回答，去 [6] 里找答案，“install boost from src.”

    根据user3715812的回答，输入以下命令行来安装BOOST：

    wget -O boost_1_55_0.tar.gz http://sourceforge.net/projects/boost/files/boost/1.55.0/boost_1_55_0.tar.gz/download
tar xzvf boost_1_55_0.tar.gz
cd boost_1_55_0/

./bootstrap.sh --prefix=/usr/local     // 这里改成自己想要安装到的目录
./b2
./b2 install       // 没有SUDO权限但是也可以

    然后再去运行

    ./build/examples/openpose/openpose.bin --image_dir examples/media/

    这次的报错和上次不一样了，是

    Starting pose estimation demo.
Auto-detecting GPUs... Detected 16 GPU(s), using them all.
Starting thread(s)
: cannot connect to X server 
E0819 00:20:53.031266 20765 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20766 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20771 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20773 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20767 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20775 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20776 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20777 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20778 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20765 common.cpp:121] Cannot create Curand generator. Curand won't be available.
E0819 00:20:53.031266 20769 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20768 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20774 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20770 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20779 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20772 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20779 common.cpp:121] Cannot create Curand generator. Curand won't be available.
E0819 00:20:53.031266 20771 common.cpp:121] Cannot create Curand generator. Curand won't be available.
E0819 00:20:53.031266 20773 common.cpp:121] Cannot create Curand generator. Curand won't be available.
F0819 00:20:53.031266 20779 common.cpp:152] Check failed: error == cudaSuccess (29 vs. 0)  driver shutting downF0819 00:20:53.031266 20771 common.cpp:152] Check failed: error == cudaSuccess (29 vs. 0)  driver shutting downF0819 00:20:53.035267 20773 common.cpp:152] Check failed: error == cudaSuccess (29 vs. 0)  driver shutting down
*** Check failure stack trace: ***
E0819 00:20:53.031266 20780 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0819 00:20:53.031266 20778 common.cpp:121] Cannot create Curand generator. Curand won't be available.
E0819 00:20:53.031266 20775 common.cpp:121] Cannot create Curand generator. Curand won't be available.
E0819 00:20:53.031266 20767 common.cpp:121] Cannot create Curand generator. Curand won't be available.
F0819 00:20:53.031266 20779 common.cpp:152] Check failed: error == cudaSuccess (29 vs. 0)  driver shutting downF0819 00:20:53.031266 20771 common.cpp:152] Check failed: error == cudaSuccess (29 vs. 0)  driver shutting downF0819 00:20:53.035267 20773 common.cpp:152] Check failed: error == cudaSuccess (29 vs. 0)  driver shutting downF0819 00:20:53.035267 20778 common.cpp:152] Check failed: error == cudaSuccess (29 vs. 0)  driver shutting downF0819 00:20:53.035267 20775 common.cpp:152] Check failed: error == cudaSuccess (29 vs. 0)  driver shutting downF0819 00:20:53.035267 20767 common.cpp:152] Check failed: error == cudaSuccess (29 vs. 0)  driver shutting down
*** Check failure stack trace: ***
F0819 00:20:53.031266 20765 common.cpp:152] Check failed: error == cudaSuccess (29 vs. 0)  driver shutting down
zsh: abort (core dumped)  ./build/examples/openpose/openpose.bin --image_dir examples/media/

    然后在GITHUB 的ISSUE区准备提问的时候，根据提示

    Note: add --logging_level 0 to get higher debug information.

     在运行的命令行后加上了这个，即：

    ./build/examples/openpose/openpose.bin --image_dir examples/media/  --logging_level 0

    于是得到了较为准确的信息：

    可以理解为又一个图形界面要展示但是出不来 [8]（X server相关), 

    查阅资料后根据 [9] 的xiaoyan的回答：

    Add "export DISPLAY=your ip:0.0" in ~/.bashrc, source ~/.bashrc (ip is your host IP, where you wanna display plots or things like that. If you are using Windows, cmd-ipconfig, find your IP).

     于是不再出现X server问题了，出现了下图的问题

    找了好久没找到问题，最后求助了组里的史博士，这里表示非常感谢！！！

    原因是这个Demo默认使用所有探测到的CUDA 设备，而实验室的CUDA设备还有很多人在用，这会造成问题（可能是冲突或者资源不够，或者不被允许个人使用这么多个？）

    所以在运行的命令行前面要加上一定的限制：

    CUDA_VISIBLE_DEVICES=2 ./build/examples/openpose/openpose.bin --net_resolution "160x80" --video examples/media/video.avi

    使得被探测到的设备数量只有两个。

    然后发现还是运行不了，为什么呢？

    因为OS X上的SHELL并不具备显示远程窗口的功能，

    所以在史博士的推荐下使用了MobaXterm（在WIN10下），然后就成功了，因为这个软件直接内置了X server的接口

    更新：如果想在Mac上运行，可以参考

    [10] http://blog.csdn.net/dobell/article/details/55047811

    安装XQuartz，
https://www.xquartz.org
按说明安装好

打开 mac terminal 
ssh -X   {用户名}@{远程端ip}； （注意大写的X）
这次就可以了

    实际运行截图如下： 

     

    你也可以读一下我在GITHUB上的提问：
    https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/184
    可能会有帮助

    另外：

    因为实验室的服务器出于安全考虑不允许使用

    sudo pip install

    , 所以使用

    pip install --user

    来替代。[2]

      

    参考文献：

    [1] http://www.cnblogs.com/emituofo/archive/2011/11/13/2247523.html

    [2] https://stackoverflow.com/questions/31512422/pip-install-r-oserror-errno-13-permission-denied

    [3] https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/installation.md

    [4] https://github.com/BVLC/caffe/issues/1276

    [5] https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/17

    [6] https://stackoverflow.com/questions/12578499/how-to-install-boost-on-ubuntu

    [7] http://www.cnblogs.com/QingHuan/p/7278357.html

    [8] http://www.cnblogs.com/super119/archive/2010/12/18/1910065.html

    [9] https://askubuntu.com/questions/571116/cannot-connect-to-x-server-error

    [10] http://blog.csdn.net/dobell/article/details/55047811
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  • 原文地址：https://www.cnblogs.com/QingHuan/p/7270264.html
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