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课程大纲
目标检测简介
- 对象检测基础知识
- 物体检测应用
- 对象检测模型的性能指标
YOLOv7 概述
- YOLOv7 安装和设置
- YOLOv7 架构和组件
- YOLOv7 相对于其他目标检测模型的优势
- YOLOv7 变体及其差异
YOLOv7 训练流程
- 数据准备和注释
- 使用流行的深度学习框架(TensorFlow、PyTorch 等)进行模型训练
- 微调预训练模型以进行自定义对象检测
- 评估和调整以获得最佳性能
实现 YOLOv7
- 在 Python 中实现 YOLOv7
- 与 OpenCV 和其他计算机视觉库集成
- 在边缘设备和云平台上部署 YOLOv7
高级主题
- 使用 YOLOv7 进行多目标跟踪
- YOLOv7 用于 3D 物体检测
- YOLOv7 用于视频对象检测
- 优化 YOLOv7 以获得实时性能
摘要和后续步骤
要求
- 具有 Python 编程经验
- 了解深度学习基础知识
- 计算机视觉基础知识
观众
- Computer 视觉工程师
- 机器学习研究人员
- 数据科学家
- 软件开发人员
21 小时
客户评论 (3)
The hands-on approach
Kevin De Cuyper
课程 - Computer Vision with OpenCV
Trainer was very knowlegable and very open to feedback on what pace to go through the content and the topics we covered. I gained alot from the training and feel like I now have a good grasp of image manipulation and some techniques for building a good training set for an image classification problem.
Anthea King - WesCEF
课程 - Computer Vision with Python
示例和练习
Kamil
课程 - Introduction to Data Science and AI using Python
机器翻译