ONNX
File size: 1,258 Bytes
bd45fa2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
---
datasets:
- detection-datasets/coco
license: gpl-3.0
---

# Introduction

This repository stores the model for YOLOv7, 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:       yolov7-tiny.optimized.onnx

# Lecture note reference

+ YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors, https://arxiv.org/abs/2207.02696

# Repository or links references

- https://github.com/WongKinYiu/yolov7
- config / weights: https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-tiny.pt


BibTeX entry and citation info
```
@inproceedings{wang2023yolov7,
  title={{YOLOv7}: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors},
  author={Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2023}
}
@article{wang2023designing,
  title={Designing Network Design Strategies Through Gradient Path Analysis},
  author={Wang, Chien-Yao and Liao, Hong-Yuan Mark and Yeh, I-Hau},
  journal={Journal of Information Science and Engineering},
  year={2023}
}
```