Metadata-Version: 2.1
Name: sort-track
Version: 0.0.5
Summary: Packaged version of the Sort repository
Home-page: https://github.com/kadirnar/sort-pip
Author: kadirnar
License: MIT
Keywords: machine-learning,deep-learning,pytorch,vision,image-classification,object-detection,object-tracking,tracker,bytetrack
Classifier: Development Status :: 5 - Production/Stable
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Education
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

<div align="center">
<h2>
  Sort-Pip: Packaged version of the Sort repository  
</h2>
<h4>
    <img width="700" alt="teaser" src="doc/paper.png">
</h4>
</div>

## <div align="center">Overview</div>

This repo is a packaged version of the [Sort](https://github.com/abewley/sort) algorithm.
### Installation
```
pip install sort-track
```

### Detection Model + Sort 
```python
from sort.tracker import Sort

tracker = Sort(args)
for image in images:
   dets = detector(image)
   online_targets = tracker.update(dets)
```
### Reference:
 - [Sort](https://github.com/abewley/sort)

### Citation
```bibtex
@inproceedings{Bewley2016_sort,
  author={Bewley, Alex and Ge, Zongyuan and Ott, Lionel and Ramos, Fabio and Upcroft, Ben},
  booktitle={2016 IEEE International Conference on Image Processing (ICIP)},
  title={Simple online and realtime tracking},
  year={2016},
  pages={3464-3468},
  keywords={Benchmark testing;Complexity theory;Detectors;Kalman filters;Target tracking;Visualization;Computer Vision;Data Association;Detection;Multiple Object Tracking},
  doi={10.1109/ICIP.2016.7533003}
}
```
