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---
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"
``` |