jeong-tae / CapsNet-pytorch

This repo aims to implement a "Dynamic Routing Between Capsules"

CapsNet-pytorch

This repo aims to implement a "Dynamic Routing Between Capsules"paper

Requirements

• python 3
• Pytorch 0.4
• torchvision
• numpy
• tensorflow

TODO

• Network building
• Training on MNIST
• Training visualization(on Tensorboard)
• Training on MultiMNIST
• Weight load and inference
• Reconstruction at test time
• Reconstructed sample visualization(Training only now)
• Results reproduce and report on README.md

Usage

For training, use following command.

See details in trainer.py to modify the hyper-params or --help will let you know

$ python trainer.py --cuda

Use CUDA_VISIBLE_DEVICES=$GPU, if you want to select GPU devices

$ CUDA_VISIBLE_DEVICES=0 python trainer.py --cuda

or try this. if you don't want to use GPU

$ python trainer.py

If you want to see visualization of training and reconstruction samples,

$ Tensorboard --log='visual/' --port=6666

and go to 'localhost:6666' on webbrowser. You can see the Loss, Acc and Images.

References

• Another pytorch implementation
• Tensorflow implementation
• Blog post: Understanding capsnet
• Video: CapsNet tutorial
  • This is best of best explanation in my mind