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This repository contains an adjusted version of fast-rcnn for our hospital-people-detector. The original repository is created by Ross Girshick at Microsoft Research, Redmond and can be found here.

Please consult the original repo's README for information on using fast r-cnn in general. Here, we describe how to get our version running for the hospital-people-detector.

Installation

1. Get Caffe

1.1 Install the necessary requirements for Caffe and pycaffe (see: Caffe installation instructions)

1.2 Get the caffe code: Alternative 1:

You can get the original caffe from the BVLC caffe repository.

git clone https://github.com/BVLC/caffe.git

You will need to apply the pull request BVLC/caffe#4163 to make caffe compatible with fast r-cnns special layers:

cd caffe
git pull origin pull/4163/head

1.2 Get the caffe code: Alternative 2:

You can also use our caffe fork which includes the above mentioned pull request and is intended to work with fast-rcnn-mobility-aids:

git clone https://github.com/marinaKollmitz/caffe.git

1.3 Compile caffe

cd caffe
cp Makefile.config.example Makefile.config

Adjust the Makefile.config to your needs. Make sure to uncomment the support for python layers:

# In your Makefile.config, make sure to have this line uncommented
WITH_PYTHON_LAYER := 1

Compile caffe and pycaffe

make -j8 && make pycaffe

Consult the caffe installation instructions for more information about compiling caffe.

2. Get Fast R-CNN

2.1 clone our Fast R-CNN repository

git clone https://github.com/marinaKollmitz/fast-rcnn-mobility-aids.git

2.2 Build the Cython modules

cd fast-scnn-mobility-aids/lib
make

3. Make sure the modules can be found

Add caffe and fast-rcnn-mobility-aids to your paths:

gedit ~/.bashrc    

Add the following lines (replace <path-to-caffe> and <path-to-fast-rcnn-mobility-aids> with your paths):

#Caffe
export PYTHONPATH=<path-to-caffe>/python:$PYTHONPATH 
export PATH=<path-to-caffe>/distribute:$PATH 
#Fast R-CNN
export PYTHONPATH=<path-to-fast-rcnn-mobility-aids>/lib:$PYTHONPATH

Confirm both modules are found:

python
>>> import caffe
>>> import fast_rcnn

Both lines should return without error.

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Fast R-CNN code adjusted for our hospital people detection code

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