adioshun/second repository overview

# host PC에서 
$ cd /workspace
$ git clone https://github.com/traveller59/second.pytorch.git

$ docker pull adioshun/second:latest


## KITTI  데이터 위치 : /media/adioshun/data/datasets
## code 위치 : /workspace/second.pytorch
$ docker run --runtime=nvidia -it --privileged --network=host -v /tmp/.X11-unix:/tmp/.X11-unix --volume="$HOME/.Xauthority:/root/.Xauthority:rw" -e DISPLAY -v /media/adioshun/data/datasets:/datasets --volume /workspace:/workspace --name 'second'  adioshun/second:latest /bin/bash

$ docker start 
$ docker exec -it second bash

# 도커 상에서 

$ cd /workspace/second.pytorch/second

Create kitti infos:`python create_data.py create_kitti_info_file --data_path=/datasets`
Create reduced point cloud: `python create_data.py create_reduced_point_cloud --data_path=/datasets`
Create groundtruth-database infos:`python create_data.py create_groundtruth_database --data_path=/datasets`

TRAIN : `python ./pytorch/train.py train --config_path=./configs/car.fhd.config --model_dir=/path/to/model_dir`
Evaluate : `python ./pytorch/train.py evaluate --config_path=./configs/car.fhd.config --model_dir=/path/to/model_dir --measure_time=True --batch_size=1`

└── KITTI_DATASET_ROOT (eg. /datasets/
       ├── training    <-- 7481 train data
       |   ├── image_2 <-- for visualization
       |   ├── calib
       |   ├── label_2
       |   ├── velodyne
       |   └── velodyne_reduced <-- empty directory
       └── testing     <-- 7580 test data
           ├── image_2 <-- for visualization
           ├── calib
           ├── velodyne
           └── velodyne_reduced <-- empty directory

wget https://github.com/Kitware/CMake/releases/download/v3.13.3/cmake-3.13.3.tar.gz
./bootstrap
 make
 make install

cd ~
#pip3 install shapely fire pybind11 tensorboardX protobuf scikit-image numba pillow numba
conda install -c conda-forge shapely fire pybind11 tensorboardX protobuf scikit-image numba pillow numba

#pip3 install torch torchvision
conda install -c anaconda pytorch-gpu 

git clone https://github.com/traveller59/spconv.git --recursive
cd spconv
python3 setup.py bdist_wheel
cd ./dist
pip3 install spconv-1.0-cp36-cp36m-linux_x86_64.whl

# Setup cuda for numba
vi ~/.bashrc
export NUMBAPRO_CUDA_DRIVER=/usr/lib/x86_64-linux-gnu/libcuda.so
export NUMBAPRO_NVVM=/usr/local/cuda/nvvm/lib64/libnvvm.so
export NUMBAPRO_LIBDEVICE=/usr/local/cuda/nvvm/libdevice

export PATH="/usr/local/cuda/bin:$PATH"  
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64"
export CUDA_HOME=/usr/local/cuda

export PYTHONPATH=$PYTHONPATH:/workspace/second.pytorch
source ~/.bashrc

cd /workspace
git clone https://github.com/traveller59/second.pytorch.git