---
license: agpl-3.0
datasets:
- detection-datasets/coco
---

# Introduction

This repository stores the model for YOLOv3-tiny, compatible with Kalray's neural network API. </br>
Please see www.github.com/kalray/kann-models-zoo for details and proper usage. </br>

# Contents

- ONNX:       yolov3-tiny.onnx
- Tensorflow: yolov3-tiny.pb

# Lecture note reference

+ YOLOv3: An Incremental Improvement, https://arxiv.org/abs/1804.02767
+ You Only Look Once: Unified, Real-Time Object Detection, https://arxiv.org/abs/1506.02640

# Repository or links references

- source code : https://github.com/ultralytics/yolov3/
- config: https://github.com/ultralytics/yolov3/blob/master/models/yolov3-tiny.yaml
- weights: from [yolov3.pt](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov3-tiny.pt) then re-trained with ReLU activation


BibTeX entry and citation info
```
@article{ redmon2018yolov3,
  title={ YOLOv3: An Incremental Improvement },
  author={ Redmon, Joseph and Farhadi, Ali },
  journal={ arXiv preprint arXiv:1804.02767 },
  year={ 2018 }
}
```

from source code CITATION.cff:
```
cff-version: 1.2.0
preferred-citation:
  type: software
  message: If you use YOLOv3, please cite it as below.
  authors:
    - family-names: Jocher
      given-names: Glenn
      orcid: "https://orcid.org/0000-0001-5950-6979"
  title: "YOLOv3 by Ultralytics"
  version: 7.0
  doi: 10.5281/zenodo.3908559
  date-released: 2020-5-29
  license: AGPL-3.0
  url: "https://github.com/ultralytics/yolov3"
```