Skip to content
master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 

Deep Canonical Time Warping

A Tensorflow implementation of the Deep Canonical Time Warping.

Deep Canonical Time Warping
G. Trigeorgis, M. A. Nicolaou, S. Zafeiriou, B. Schuller.
Proceedings of IEEE International Conference on Computer Vision & Pattern Recognition (CVPR'16).
June 2016.

Installation Instructions

We are an avid supporter of the Menpo project (http://www.menpo.org/) which we use in various ways throughout the implementation.

In general, as explained in Menpo's installation instructions, it is highly recommended to use conda as your Python distribution.

Once downloading and installing conda, this project can be installed by:

Step 1: Create a new conda environment and activate it:

$ conda create -n dctw python=3.5
$ source activate dctw

Step 2: Install TensorFlow following the official installation instructions. For example, for 64-bit Linux, the installation of CPU-only, Python 3.5 TensorFlow involves:

(dctw)$ pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.0rc0-cp35-cp35m-linux_x86_64.whl

Step 3: Install menpo from the menpo channel as:

(dctw)$ conda install -c menpo menpo

Step 4: Compile the extra TraceNormOp op.

(dctw)$ bash compile_cpu.sh

When you are done you can go through the example in demo.ipynb.

About

No description, website, or topics provided.

Resources

License

Releases

No releases published

Packages

No packages published

Languages