Skip to content
This is the python implementation of single object tracking from GOTURN paper
Python Shell
Branch: goturn-dev
Clone or download
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
doc/images
goturn
nets PEP8 standard Apr 12, 2018
output
.gitignore
LICENSE
README.md update readme Apr 12, 2018
how_to_test.md
how_to_train.md
show_tracker_vot.sh
train_tracker.sh

README.md

PY-GOTURN

News

I'm back on working on this codebase again, can expect the following changes on the development branch goturn-dev

  • Code clean up

  • Bug fixes, if any

  • Try to add much better interface for easy debugging - Visualization of training, understanding different modules of the code.

  • Documentation or blog on the code.

NOTE: Please switch to goturn-0.1 branch to try out stable version.


This is the python implementation of GOTURN: Generic Object Tracking Using Regression Networks.

Learning to Track at 100 FPS with Deep Regression Networks,
David Held, Sebastian Thrun, Silvio Savarese,

Outputs

Car Sunshade

Why implementation in python, when C++ code is already available?

  • Easy to understand the overall pipeline of the algorithm in detail
  • Easy to experiment new ideas
  • Easy to debug and visualize the network with tools like visdom
  • Little effort in portability to other OS

Functionalites added so far

  • Training the deep network on Imagenet and ALOV dataset

  • Test code for VOT

How to train your own tracker

To train your own tracker, please follow the guide

How to test on VOT dataset

To test your own tracker on VOT2014, please follow the guide

Contact

Please write to me at nrupatunga.tunga@gmail.com, if you have any suggestions or any new functionality you like to see.

You can’t perform that action at this time.