stevenlol / capsnet-keras

A Keras implementation of CapsNet in Hinton's paper Dynamic Routing Between Capsules

CapsNet-Keras

A Keras implementation of CapsNet in Hinton's paper Dynamic Routing Between Capsules

Requirements

• Keras

Usage

Training

Step 1. Install Keras:

$ pip install keras

Step 2. Clone this repository with git.

$ git clone https://github.com/xifengguo/CapsNet-Keras.git
$ cd CapsNet-Keras

Step 3. Training:

$ python CapsNet.py

Training without reconstruction network by setting lam_recon=0.

$ python CapsNet.py --lam_recon 0.

Results

Accuracy with data augmentation (shift at most 2 pixels in each direction):
The code is ready, I'm running it to get results. Feel free to run on your own computer.

Waiting for the results

Accuracy during training with reconstruction coefficient lam_recon=0.0005:

Epoch	1	2	3	4	5	6	7	8	9	10	11
train_acc	94.8	98.9	99.3	99.4	99.6	99.7	99.8	99.8	99.9	99.9	99.95
vali_acc	98.7	99.0	99.2	99.2	99.39	99.30	99.38	99.35	99.46	99.38	99.45

Accuracy during training without reconstruction:

Epoch	1	2	3	4	5	6	7	8	9	10	11
train_acc	94.4	98.9	99.2	99.5	99.6	99.7	99.8	99.9	99.9	99.9	99.95
vali_acc	98.5	99.1	99.2	99.3	99.36	99.36	99.43	99.34	99.42	99.41	99.44

Every epoch consumes more than 300s on a single GTX 1070 GPU.
Maybe there're some problems in my implementation. Contributions are welcome.

TODO:

• Optimize the code implementation and comments. The paper says the CapsNet has 11M parameters, but my model only has 8M. There may be something wrong.

Other Implementations

• CapsNet-Tensorflow: Very good implementation. I referred to this repository in my code.

• CapsNet-PyTorch

• capsnet.pytorch