Difference between revisions of "Feeding Tensorflow from GPU"
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==Setup== | ==Setup== | ||
− | Kubuntu 18.04: | + | Kubuntu 18.04, CUDA 10.0 (10.0 is a requirement for Java version of TF 1.15 in Maven CDN): |
<font size=2>mkdir -p ~/git/tf_cv_cu | <font size=2>mkdir -p ~/git/tf_cv_cu | ||
cd ~/git/tf_cv_cu | cd ~/git/tf_cv_cu | ||
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sudo apt install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libdc1394-22-dev | sudo apt install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libdc1394-22-dev | ||
# sudo apt install libjasper-dev # missing in Kubuntu 18.04 | # sudo apt install libjasper-dev # missing in Kubuntu 18.04 | ||
+ | |||
+ | sudo cp ~/git/tf_cv_cu/fast_od/docker/nvcuvid/dynlink_* /usr/local/cuda/include | ||
+ | |||
cd ~/git/tf_cv_cu/opencv-3.4.9 | cd ~/git/tf_cv_cu/opencv-3.4.9 | ||
mkdir build; cd build | mkdir build; cd build | ||
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sudo make install | sudo make install | ||
sudo ldconfig | sudo ldconfig | ||
− | |||
</font> | </font> |
Revision as of 18:41, 14 January 2020
About
Reference guides:
- Supercharging Object Detection in Video: from Glacial to Lightning Speed
- Setup
- First App
- Optimizing Decoding and Graph Feeding
Target projects:
- tensorflow-object-detection-cpp - contains a sample model, labels and a test video
- fast_od - contains feeding Tensorflow from GPU
Setup
Kubuntu 18.04, CUDA 10.0 (10.0 is a requirement for Java version of TF 1.15 in Maven CDN):
mkdir -p ~/git/tf_cv_cu cd ~/git/tf_cv_cu # Download section git clone https://github.com/fierval/tensorflow-object-detection-cpp.git git clone https://github.com/fierval/fast_od.git wget https://github.com/Kitware/CMake/releases/download/v3.16.2/cmake-3.16.2.tar.gz wget https://github.com/bazelbuild/bazel/releases/download/0.25.2/bazel_0.25.2-linux-x86_64.deb wget https://github.com/tensorflow/tensorflow/archive/v1.15.0.tar.gz -O tensorflow-1.15.0.tar.gz wget https://github.com/opencv/opencv/archive/3.4.9.tar.gz -O opencv-3.4.9.tar.gz wget https://github.com/opencv/opencv_contrib/archive/3.4.9.tar.gz -O opencv_contrib-3.4.9.tar.gz # Unpack archives tar xzvf cmake-3.16.2.tar.gz tar xzvf tensorflow-1.15.0.tar.gz tar xzvf opencv-3.4.9.tar.gz tar xzvf opencv_contrib-3.4.9.tar.gz # Build & update cmake sudo apt install libssl-dev sudo apt install qt4-default cd cmake-3.16.2 ./bootstrap -qt-gui make -j8 sudo make install cmake -version cmake-gui -version # Install bazel sudo dpkg -i bazel_0.25.2-linux-x86_64.deb bazel version # Build TF cd ~/git/tf_cv_cu/tensorflow-1.15.0/ tensorflow/contrib/makefile/download_dependencies.sh ./configure # pick all defaults except select yes for CUDA support bazel build //tensorflow:libtensorflow_cc.so # Build OpenCV sudo apt install libgtkglext1 libgtkglext1-dev sudo apt install build-essential sudo apt install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev sudo apt install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libdc1394-22-dev # sudo apt install libjasper-dev # missing in Kubuntu 18.04
sudo cp ~/git/tf_cv_cu/fast_od/docker/nvcuvid/dynlink_* /usr/local/cuda/include
cd ~/git/tf_cv_cu/opencv-3.4.9 mkdir build; cd build cmake -D WITH_CUDA=ON \ -D OPENCV_EXTRA_MODULES_PATH=~/git/tf_cv_cu/opencv_contrib-3.4.9/modules \ -D BUILD_PERF_TESTS=OFF \ -D BUILD_TESTS=OFF \ -D BUILD_opencv_cudacodec=ON \ -D WITH_NVCUVID=ON \ -D WITH_GTK_2_X=ON \ .. make -j8 sudo make install sudo ldconfig