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#@
/# first, make sure that your conda is setup properly with the right environment
-
for that, check that
which conda
,which pip
andwhich 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
Originally posted by @Chester171 in #84 (comment)
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