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object_detection's Introduction

Object_Detection

Object_Detection项目克隆自ultralytics/yolov5,将其修改使项目能够应用于电脑应用程序

安装

克隆项目

git clone [email protected]:Karenina-na/Object_Detection.git
pip install -r requirements.txt
python main.py

使用方法

  • parameter.xml 为模型推理参数列表,其中检测类别的标签值类可在/data/下进行选择。
  • device默认为0,可根据电脑状态更改为cpu或其他数值。

作者

证书

AGPL-3.0 License from Ultralytics
MIT License from Karenina-na

Yolo v5 简介

YOLOv5 🚀 是世界上最受欢迎的视觉 AI,代表 Ultralytics 对未来视觉 AI 方法的开源研究,结合在数千小时的研究和开发中积累的经验教训和最佳实践。

如果要申请企业许可证,请填写表格Ultralytics 许可.

预训练模型

预训练模型

模型 尺寸
(像素)
mAPval
50-95
mAPval
50
推理速度
CPU b1
(ms)
推理速度
V100 b1
(ms)
速度
V100 b32
(ms)
参数量
(M)
FLOPs
@640 (B)
YOLOv5n 640 28.0 45.7 45 6.3 0.6 1.9 4.5
YOLOv5s 640 37.4 56.8 98 6.4 0.9 7.2 16.5
YOLOv5m 640 45.4 64.1 224 8.2 1.7 21.2 49.0
YOLOv5l 640 49.0 67.3 430 10.1 2.7 46.5 109.1
YOLOv5x 640 50.7 68.9 766 12.1 4.8 86.7 205.7
YOLOv5n6 1280 36.0 54.4 153 8.1 2.1 3.2 4.6
YOLOv5s6 1280 44.8 63.7 385 8.2 3.6 12.6 16.8
YOLOv5m6 1280 51.3 69.3 887 11.1 6.8 35.7 50.0
YOLOv5l6 1280 53.7 71.3 1784 15.8 10.5 76.8 111.4
YOLOv5x6
+[TTA]
1280
1536
55.0
55.8
72.7
72.7
3136
-
26.2
-
19.4
-
140.7
-
209.8
-

object_detection's People

Contributors

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