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Total [31] sections

Availability of courseware: Yes

You will gain

掌握使用YOLOv5进行中国交通标志识别

获得TT100K数据集及格式转换

population (esp. of a group of people)

对YOLOv5目标检测技术应用感兴趣的学员和从业者 课程介绍

在无人驾驶中，交通标志识别是一项重要的任务。YOLOv5是目前流行的非常强悍的目标检测技术。本项目以中国交通标志数据集TT100K为训练对象，采用YOLOv5目标检测方法实现实时交通标志识别。

本课程的YOLOv5使用PyTorch版的ultralytics/yolov5，分别在Windows和Ubuntu系统上做中国交通标志识别的项目演示。具体项目过程包括：安装软件环境、安装YOLOv5、TT100K数据集及格式转换、训练集和测试集自动划分、修改配置文件、准备Weights&Biases训练可视化工具、训练网络模型、测试训练出的网络模型和性能统计。

This course will describe the method of converting the format of the TT100K dataset to PASCAL VOC format and YOLO format using a Python program with corresponding code.

Course Catalog

Chapter 1: Introduction to the course

课程介绍 07:29

Chapter 2: Basics of target detection

任务说明 03:06

常用数据集 02:55

性能指标 23:12

Chapter 3: YOLOv5 target detection network

YOLO目标检测技术发展史 15:10

YOLOv5网络结构与组件 27:16

YOLOv5-4.0和5.0更新 13:08

YOLOv5的6.0更新 [视频未上传]

第四章：交通标志数据集

国外交通标志数据集 06:06

中国交通标志数据集TT100K

10:02 第五章：中国交通标志识别实战-Windows演示

安装软件环境 09:11

安装PyTorch 04:10

克隆和安装YOLOv5 07:28

TT100K数据集格式 22:15

TT100K数据集格式转换

20:26 准备数据集 09:52

修改配置文件 04:06

准备wandb训练可视化工具 04:21

训练数据集 13:20

测试训练出的网络模型及性能统计 18:35

YOLOv5-6.0项目更新 02:51

第六章：中国交通标志识别实战-Ubuntu演示

安装PyTorch 07:17

克隆和安装YOLOv5

06:13 TT100K数据集及格式转换 08:03

准备数据集 09:16

修改配置文件 03:10

准备wandb训练可视化工具 04:15

训练数据集 14:15

测试训练出的网络模型及性能统计 09:27

YOLOv5-6.0项目更新 02:51

Chapter 7: Summary of the course

课程总结 01:55

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