We'll call the directory that you cloned py-RFCN-priv into PRIV_ROOT
Build the Cython modules
cd $PRIV_ROOT/lib
make
Build Caffe and pycaffe
cd $RFCN_ROOT/caffe-priv# Now follow the Caffe installation instructions here:# http://caffe.berkeleyvision.org/installation.html# cp Makefile.config.example Makefile.config# If you're experienced with Caffe and have all of the requirements installed# and your Makefile.config in place, then simply do:make all -j && make pycaffe -j
Note: Caffe must be built with support for Python layers!
# In your Makefile.config, make sure to have this line uncommentedWITH_PYTHON_LAYER := 1# Unrelatedly, it's also recommended that you use CUDNNUSE_CUDNN := 1# NCCL (https://github.com/NVIDIA/nccl) is necessary for multi-GPU training with python layerUSE_NCCL := 1
How to install nccl
git clone https://github.com/NVIDIA/nccl.git
cd nccl
sudo make install -j
sudo ldconfig
License
py-RFCN-priv and caffe-priv are released under the MIT License (refer to the LICENSE file for details).
Citing
If you find R-FCN or soft-nms useful in your research, please consider citing:
@article{dai16rfcn,
Author = {Jifeng Dai, Yi Li, Kaiming He, Jian Sun},
Title = {{R-FCN}: Object Detection via Region-based Fully Convolutional Networks},
Journal = {arXiv preprint arXiv:1605.06409},
Year = {2016}
}
@article{1704.04503,
Author = {Navaneeth Bodla and Bharat Singh and Rama Chellappa and Larry S. Davis},
Title = {Improving Object Detection With One Line of Code},
Journal = {arXiv preprint arXiv:1704.04503},
Year = {2017}
}