CapsNet COCO

This repository contains the implementation of Capsule Networks on MSCOCO 2017 dataset using Keras with Tensorflow Backend.

Dataset Preparation

1. Go to the directory dataset.
2. Inside the directory, download and the MSCOCO 2017 Train and Val images along with Train/Val annotations from here and then extract them.
3. Create a simplified version of MSCOCO 2017 dataset
   $ python dataset/parse_coco.py
4. Preprocess the dataset for training Capsule-Network
   $ python capsnet_create_dataset.py

Train Capsule-Network

1. To run with the default settings
   $ python capsule_network.py

Issue

The current architecture of CapsNet is not suitable handling complex real-world images present in the MSCOCO dataset. As a result, the trained model does not converge.

We used this repository's implementation of CapsNet.