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INSTALL.md

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Set up the python environment

conda create -n snake python=3.7
conda activate snake

# make sure that the pytorch cuda is consistent with the system cuda
# e.g., if your system cuda is 9.0, install torch 1.1 built from cuda 9.0
pip install torch==1.1.0 -f https://download.pytorch.org/whl/cu90/stable

pip install Cython==0.28.2
pip install -r requirements.txt

# install apex
cd
git clone https://github.com/NVIDIA/apex.git
cd apex
git checkout 39e153a3159724432257a8fc118807b359f4d1c8
export CUDA_HOME="/usr/local/cuda-9.0"
python setup.py install --cuda_ext --cpp_ext

Compile cuda extensions under lib/csrc

ROOT=/path/to/snake
cd $ROOT/lib/csrc
export CUDA_HOME="/usr/local/cuda-9.0"
cd dcn_v2
python setup.py build_ext --inplace
cd ../extreme_utils
python setup.py build_ext --inplace
cd ../roi_align_layer
python setup.py build_ext --inplace

Set up datasets

Cityscapes

  1. Download the Cityscapes dataset (leftImg8bit_trainvaltest.zip) from the official website.
  2. Download the processed annotation file cityscapes_anno.tar.gz.
  3. Organize the dataset as the following structure: 
    ├── /path/to/cityscapes
│   ├── annotations
│   ├── coco_ann
│   ├── leftImg8bit
│   ├── gtFine
  4. Generate coco_img. 
    mkdir -p coco_img/train
cp leftImg8bit/train/*/* coco_img/train
cp leftImg8bit/val/*/* coco_img/val
cp leftImg8bit/test/*/* coco_img/test
  5. Create a soft link: 
    ROOT=/path/to/snake
cd $ROOT/data
ln -s /path/to/cityscapes cityscapes

Kitti

  1. Download the Kitti dataset from the official website.
  2. Download the annotation file instances_train.json and instances_val.json from Kins.
  3. Organize the dataset as the following structure: 
    ├── /path/to/kitti
│   ├── testing
│   │   ├── image_2
│   │   ├── instance_val.json
│   ├── training
│   │   ├── image_2
│   │   ├── instance_train.json
  4. Create a soft link: 
    ROOT=/path/to/snake
cd $ROOT/data
ln -s /path/to/kitti kitti

Sbd

  1. Download the Sbd dataset at here.
  2. Create a soft link: 
    ROOT=/path/to/snake
cd $ROOT/data
ln -s /path/to/sbd sbd