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CMU-Perceptual-Computing-Lab / caffe_rtpose

Realtime C++ code for multi-person pose estimation
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memory issue when cudnn is found #54

Closed Gjain234 closed 6 years ago

Gjain234 commented 6 years ago

I've looked through the older issues but still can't seem to figure this out. I am trying to install openpose and am fairly sure I am using CUDNN because making on CMake gives this summary.

-- GCC detected, adding compile flags -- Building with CUDA. -- CUDA detected: 8.0 -- Found cuDNN: ver. 5.1.10 found (include: /usr/local/cuda/include, library: /usr/local/cuda/lib64/libcudnn.so) -- Added CUDA NVCC flags for: sm_50 -- Found cuDNN: ver. 5.1.10 found (include: /usr/local/cuda/include, library: /usr/local/cuda/lib64/libcudnn.so) -- Found gflags (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libgflags.so) -- Found glog (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libglog.so) -- Caffe will be downloaded from source now. NOTE: This process might take several minutes depending on your internet connection. -- Caffe has already been downloaded.

However, when I build openpose using 'make -jnproc', the caffe configuration summary shows this:

General: -- Version : 1.0.0 -- Git : 1.0-112-g9453eb0-dirty -- System : Linux -- C++ compiler : /usr/bin/c++ -- Release CXX flags : -O3 -DNDEBUG -fPIC -Wall -Wno-sign-compare -Wno-uninitialized -- Debug CXX flags : -g -fPIC -Wall -Wno-sign-compare -Wno-uninitialized -- Build type : Release -- -- BUILD_SHARED_LIBS : ON -- BUILD_python : OFF -- BUILD_matlab : OFF -- BUILD_docs : OFF -- CPU_ONLY : OFF -- USE_OPENCV : OFF -- USE_LEVELDB : OFF -- USE_LMDB : OFF -- USE_NCCL : OFF -- ALLOW_LMDB_NOLOCK : OFF -- -- Dependencies: -- BLAS : Yes (Atlas) -- Boost : Yes (ver. 1.58) -- glog : Yes -- gflags : Yes -- protobuf : Yes (ver. 2.6.1) -- CUDA : Yes (ver. 8.0) -- -- NVIDIA CUDA: -- Target GPU(s) : Auto -- GPU arch(s) : sm_50 -- cuDNN : Not found -- -- Install: -- Install path : /home/il/software/openpose/build/caffe

This summary seems to say that cuDNN was not found, and I get the same failure message (Check failed: error == cudaSuccess (2 vs. 0) out of memory) when I run any of the commands in the openpose quickstart section. Any ideas why there is the discrepancy about the cudnn being found?

gineshidalgo99 commented 6 years ago

Use OpenPose, this repo is no longer maintained