Re3 is a real-time recurrent regression tracker. It offers accuracy and robustness similar to other state-of-the-art trackers while operating at 150 FPS. For more details, contact xkcd@cs.washington.edu. This repository implements the training and testing procedure from https://arxiv.org/pdf/1705.06368.pdf. A sample of the tracker can be found here: https://youtu.be/RByCiOLlxug.
## Model:
The model weights we used in our paper were ported from Caffe to Tensorflow. Because they deal with padding differently, results are slightly different, but the model still works well.
To use it, download it [here](https://goo.gl/NWGXGM), extract the tar, and place in your log directory (mine is "logs").
## Requirements:
1. Python 2 (don't get me started on Python3 not being backwards compatible).
2.[Tensorflow](https://www.tensorflow.org/) and its requirements. I use the pip tensorflow-gpu==1.2.0
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@@ -17,6 +21,7 @@ cd re3-tensorflow
sudo apt-get install python-virtualenv
virtualenv venv --system-site-packages
source venv/bin/activate
pip install--upgrade pip
pip install-r requirements.txt
```
### Enter the virtualenv in a later session to use the installed libraries.
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@@ -28,10 +33,6 @@ source venv/bin/activate
deactivate
```
## Model:
The model weights we used in our paper were ported from Caffe to Tensorflow. Because they deal with padding differently, results are slightly different, but the model still works well.
To use it, download it [here](https://goo.gl/NWGXGM), extract the tar, and place in your log directory (mine is "logs").
## Folders and Files:
### Most important for using Re3 in a new project:
