DeepMask

A Keras implementation of DeepMask based on NIPS 2015 paper Learning to Segment Object Candidates.

Requirements

ANACONDA、Keras、OpenCV3、mscoco

Here is the instructions to install them all:

Download ANACONDA and then install it, I suggest you to install the Python 3.6 version.
Install Keras by the following steps:

sudo pip install -U --pre pip setuptools wheel

sudo pip install -U --pre numpy scipy matplotlib scikit-learn scikit-image

sudo pip install -U --pre tensorflow

If your computer supports CUDA, you could install tensorflow-gpu by

sudo pip install -U --pre tensorflow-gpu

Make sure you have installed CUDA and cuDNN first.

sudo pip install -U --pre keras
Install OpenCV3 by the following steps:

brew tap homebrew/science

brew install opencv3 --with-python3 --without-python --without-numpy

cd ~/anaconda/lib/python3.6/site-packages/

ln -s /usr/local/Cellar/opencv3/3.2.0/lib/python3.6/site-packages/cv2.cpython-36m-darwin.so cv2.so

If your computer system aren't macOS Sierra, you should download OpenCV3.2.0 and then install it from source.

Make sure the compile setting 'with-python3' is on, you could do that by using cmake-gui.

When you have installed OpenCV3, make sure the cv2.so is in '~/anaconda/lib/python3.6/site-packages/'.
Install MS COCO API by the following steps:

Download coco and unzip it.

cd coco-master/PythonAPI/

python setup.py build_ext install

Download the mscoco datasets first, you should only download '2014 Training images' and '2014 Train/Val object instances'.

Make a dir named 'coco', go inside and make two dir named 'images' and 'annotations'.

Unzip '2014 Training images' to dir 'images', '2014 Train/Val object instances' to dir 'annotations'.

cd DeepMask\

python main.py