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INSTALL.md

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Installation of the detector-retrieval benchmark

Installation of the maskrcnn_benchmark

Needed for the detector-retrieval baseline. These instructions assume OS2D is installed and largely follow the ones of maskrcnn-benchmark

# activate the os2d env
conda activate os2d

# dependencies
conda install ninja=1.9.0 cython=0.29.15
pip install opencv-python==4.2.0.32

# the rest will be compiling from sources - set the path for that
INSTALL_DIR=$HOME/local/software/pytorch/os2d
mkdir -p $INSTALL_DIR

# install pycocotools
cd $INSTALL_DIR
git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
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 --cuda_ext --cpp_ext

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

# difference from the standard instruction: get v0.1
git checkout v0.1

# 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

Installation of cnnimageretrieval-pytorch

# activate the os2d env
conda activate os2d

# move to the folder of the baseline
cd $OS2D_ROOT/baselines/detector_retrieval/retrieval

git clone https://github.com/filipradenovic/cnnimageretrieval-pytorch.git cnnimageretrieval-pytorch
cd cnnimageretrieval-pytorch
git checkout v1.1
cd ..