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).
General instructions
Install all requirements, as listed below
Download mscoco annotations (see below)
Download and convert graph weights with HeplerScripts/CreateVggGraphWeights.py (see below)
Create the learning dataset using ExamplesGenerator.py
Create a train and test directories with examples to train and test on. Default locations are 'Predictions/train' and same for test (can be configured in EndToEnd.py)
Run EndToEnd.py
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
Theano (0.8.0.dev0)
Keras (0.3.1)
Open CV (3.1.0)
Coco API (1.0.1)
Required downloads