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pull docker
docker pull tensorflow/tensorflow:1.12.0-gpu
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start docker
docker run -it tensorflow/tensorflow:1.12.0-gpu /bin/bash
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install libs on ubuntu
apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler -y apt-get install --no-install-recommends libboost-all-dev -y apt-get install apt-get install cuda-cublas-dev-9-0 -y apt-get install libopenblas-dev -y apt-get install python-dev apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev -y apt-get install python-opencv -y pip install scikit-image
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copy ./Makefile.config to {PATH_TO_DORN}/DORN/caffe/
cp ./Makefile.config $PATH_TO_DORN/DORN/caffe/
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make soft link of lib*.so
ln -sv /usr/lib/x86_64-linux-gnu/libhdf5_serial.so /usr/lib/x86_64-linux-gnu/libhdf5.so ln -sv /usr/lib/x86_64-linux-gnu/libhdf5_serial_hl.so /usr/lib/x86_64-linux-gnu/libhdf5_hl.so
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make caffe
cd $PATH_TO_DORN/DORN/caffe/ make all make test make runtest
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export caffe/python to PYTHONPATH
export PYTHONPATH = $PATH_TO_DORN/DORN/caffe/python
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Download KITTI pretrained model from https://github.com/hufu6371/DORN, put model into
$PATH_TO_DORN/DORN/models/
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Run KITTI demo. Comment the GPU mode code. See
./demo_kitti.py
in this repo, line 11 and line 12cd $PATH_TO_DORN/DORN/ python demo_kitti.py --filename=./data/KITTI/demo_01.png --outputroot=./result/KITTI/
check result in
./result/KITTI