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INSTALL.md

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Installation

Requirements:

  • torchvision from master
  • cocoapi
  • yacs
  • matplotlib
  • GCC >= 4.9
  • OpenCV
  • CUDA >= 9.0

Option 1: Step-by-step installation

# first, make sure that your conda is setup properly with the right environment
# for that, check that `which conda`, `which pip` and `which python` points to the
# right path. From a clean conda env, this is what you need to do

conda create -n maskrcnn_benchmark python=3.7
conda activate maskrcnn_benchmark

# this installs the right pip and dependencies for the fresh python
conda install ipython pip

# maskrcnn_benchmark and coco api dependencies
python -m pip install --upgrade pip
pip install -r requirements.txt

# follow PyTorch installation in https://pytorch.org/get-started/locally/
# we give the instructions for 11.3
conda install pytorch==1.10.0 torchvision==0.11.0 cudatoolkit=11.3 -c pytorch

export INSTALL_DIR=$PWD

# install pycocotools
cd $INSTALL_DIR
git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
python setup.py build_ext install

# install cityscapesScripts
cd $INSTALL_DIR
git clone https://github.com/mcordts/cityscapesScripts.git
cd cityscapesScripts/
python setup.py build_ext install

# install apex
cd $INSTALL_DIR
git clone https://github.com/NVIDIA/apex.git
cd apex
python setup.py install


# install PyTorch Detection
cd $INSTALL_DIR
#git clone https://github.com/facebookresearch/maskrcnn-benchmark.git
cd maskrcnn-benchmark

# the following will install the lib with
# symbolic links, so that you can modify
# the files if you want and won't need to
# re-build it
python setup.py build develop

unset INSTALL_DIR

Option 2: Set the dataset

# link the corresponding VOC dataset path to the current directory
ln -s ROOT/VOC/VOCdevkit/ data/VOCdevkit