#@
/# 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 --name maskrcnn_benchmark
source activate maskrcnn_benchmark

this installs the right pip and dependencies for the fresh python

conda install ipython

maskrcnn_benchmark and coco api dependencies

pip install ninja yacs cython matplotlib

follow PyTorch installation in https://pytorch.org/get-started/locally/

we give the instructions for CUDA 9.0

conda install pytorch-nightly -c pytorch

install torchvision

cd ~/github
git clone https://github.com/pytorch/vision.git
cd vision
python setup.py install

install pycocotools

cd ~/github
git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
python setup.py build_ext install

install PyTorch Detection

cd ~/github
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

or if you are on macOS

MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py build develop

from pytorch-tutorial.

from pytorch-tutorial.

from pytorch-tutorial.