End-to-end-trainable-network-for-superpixel-and-image-segmentation

Installation

Caffe Installation

1. Go to 'lib' folder if you are not already there:

cd lib/

1. We make use of layers in 'Video Propagation Networks' caffe repository and add additional layers for SSN superpixels:

git clone https://github.com/varunjampani/video_prop_networks.git

1. Manually copy all the source files (files in lib/include and lib/src folders) to the corresponding locations in the caffe repository. In the ssn_superpixels/lib directory:

cp src/caffe/layers/* video_prop_networks/lib/caffe/src/caffe/layers/.
cp src/caffe/test/* video_prop_networks/lib/caffe/src/caffe/test/.
cp src/caffe/proto/caffe.proto video_prop_networks/lib/caffe/src/caffe/proto/caffe.proto
cp include/caffe/layers/* video_prop_networks/lib/caffe/include/caffe/layers/.

1. Install Caffe following the installation instructions. In the ssn_superpixels/lib directory:

cd video_prop_networks/lib/caffe/
mkdir build
cd build
cmake ..
make -j
cd ../../../..

Note: If you install Caffe in some other folder, update CAFFEDIR in config.py accordingly.

Install a cython file

We use a cython script taken from 'scikit-image' for enforcing connectivity in superpixels. To compile this:

cd lib/cython/
python setup.py install --user
cd ../..

Usage: BSDS segmentation

Data download

Download the BSDS dataset into data folder:

cd data
sh get_bsds.sh
cd ..

Superpixel computation

1. First download the trained segmentation models using the get_models.sh script in the models folder:

cd models
sh get_models.sh
cd ..

1. Use compute_spixel.py to compute superpixels on BSDS dataset:

python compute_spixels.py  --datatype TEST --n_spixels 100 --num_steps 10 --caffemodel ./models/intermediate_bsds_model --result_dir ./bsds_100/

You can change the number of superpixels by changing the n_spixels argument above, and you can update the datatype to TRAIN or VAL to compute superpixels on the corresponding data splits.

2. Use compute_sgement.py to compute superpixels on BSDS dataset:

python compute_sgement.py  --datatype TEST --n_spixels 100 --num_steps 10 --caffemodel ./models/intermediate_bsds_model --result_dir ./bsds_seg/