Installation

创建环境

conda create -n pvnet python=3.8
conda activate pvnet

安装pytorch

conda install pytorch==1.8.1 torchvision==0.9.1 torchaudio==0.8.1 cudatoolkit=11.3 -c pytorch -c conda-forge 或者 pip install torch==1.8.1+cu111 torchvision==0.9.1+cu111 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html

编译cuda拓展

bash ./script/build_script.sh

安装其他依赖

pip install -r requirements.txt

安装dgl[可选]

conda install -c dglteam dgl-cuda11.3

数据集设置

ROOT=/path/to/clean-pvnet
cd $ROOT/data
ln -s /path/to/linemod linemod
ln -s /path/to/linemod_orig linemod_orig
ln -s /path/to/occlusion_linemod occlusion_linemod

# the following is used for tless
ln -s /path/to/tless tless
ln -s /path/to/cache cache
ln -s /path/to/SUN2012pascalformat sun

Download datasets which are formatted for this project:

1. linemod
2. linemod_orig: The dataset includes the depth for each image.
3. occlusion linemod
4. truncation linemod: Check TRUNCATION_LINEMOD.md for the information about the Truncation LINEMOD dataset.
5. Tless: cat tlessa* | tar xvf - -C ..
6. Tless cache data: It is used for training and testing on Tless.
7. SUN2012pascalformat