fsodogandji/NNProject_DeepMask

Deep Neural Network for object segmentation.

NNProject - DeepMask

This is a Keras-based Python implementation of DeepMask- a complex deep neural network for learning object segmentation masks. The full article can be found here: Learning to Segment Object Candidates.

This was implemented as a final project for TAU Deep Learning course (2016).

Required installations

This was run on Windows 8.1 (64 bit) on a CPU with 8GB RAM. In brackets are the versions I used.

• Python
  • Anaconda for Windows x64 with Python 2.7 (Anaconda version 2.4.1)
• Theano (0.8.0.dev0)
  • conda install mingw libpython
  • git clone https://github.com/Theano/Theano.git
  • python setup.py install
• Keras (0.3.1)
  • conda install keras
• Open CV (3.1.0)
  • Download installation here
  • Copy cv2.pyd to site-packages dir inside python's lib dir in anaconda
• Coco API (1.0.1)
  • git clone https://github.com/pdollar/coco
  • python setup.py build_ext install

Required downloads

• VGG-D
  • Net was taken from here. Weights should be downloaded locally, and converted to graph format using HelperScripts/CreateVggGraphWeights.py
  • Full article: Very Deep Convolutional Networks for Large-Scale Image Recognition
• MSCOCO
  • Download annotation files here