YOLOv5目标检测实战：Jetson Nano部署
Rating 4.08 out of 5 (6 ratings in Udemy)
What you'll learn
- 了解AI视频处理加速引擎TensorRT和Deepstream
- 掌握YOLOv5的Jetson Nano部署方法
Description
PyTorch版的YOLOv5是高性能的实时目标检测方法。Jetson Nano是英伟达含有GPU的人工智能硬件。本课程讲述如何部署YOLOv5在Jetson Nano开发板上。部署完成后可进行图像、视频文件和摄像头视频的实时目标检测。部署时使用AI视频处理加速引擎TensorRT和DeepStream。
DeepStream应用程序框架具有硬件加速构建块，可将深层神经网络和其他复杂处理任务带入流处理管道。开发者只需专注于构建核心深度学习网络，而不是从头开始设计端到端解决方案。DeepStream 实时视频流分析包含实时视频解码和神经网络进行推理。推理由一个主线程通过调用TensorRT推理引擎来处理所有批量推理任务。Tensorrtx使用TensorRT网络定义API实施流行的深度学习网络，支持YOLOv5 …
Duration 1 Hours 58 Minutes
Paid
Self paced
Intermediate Level
Simplified Chinese (China)
22
Rating 4.08 out of 5 (6 ratings in Udemy)
Go to the Course
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Paid
Self paced
Intermediate Level
Simplified Chinese (China)
22
Rating 4.08 out of 5 (6 ratings in Udemy)
Go to the Course