NVIDIA之AI Course：Getting Started with AI on Jetson Nano—Class notes(五)
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Conclusion
正在更新……
Recap 回顾
Congratulations! 恭喜你!
You've successfully set up the NVIDIA Jetson Nano Developer Kit and built multiple AI projects:
您已经成功地设置了NVIDIA Jetson Nano开发工具包，并构建了多个AI项目:
1. Setting Up Your Jetson Nano 设置你的Jetson Nano
You learned: 您学习了:
- How to run your Jetson Nano in "headless" mode
如何运行您的Jetson Nano在“无头”模式 - How to access JupyterLab on the Jetson Nano through USB Device Mode
如何通过USB设备模式访问Jetson Nano上的JupyterLab - How to burn an SD card with and use it on the Jetson Nano
如何烧伤SD卡，并使用它的Jetson Nano
2. Image Classification 图像分类
You learned: 您学习了:
- How to collect your own labeled images
如何收集自己的标签图像 - How to vary data backgrounds and orientations to improve your classification model
如何改变数据背景和方向来改进分类模型 - How to train a classification model
如何训练分类模型 - How to run inference on a live camera feed with your classification model
如何使用分类模型在实时摄像机提要上运行推理
3. Image Regression 图像回归
You learned: 您学习了:
- How to localize features with regression models
如何使用回归模型本地化特性 - How to collect annotated data
如何收集带注释的数据 - How to train a regression model
如何训练回归模型 - How to run inference on a live camera feed with your regression model
如何使用您的回归模型在实时摄像机提要上运行推理
Next Steps
Find Your Way Around
- Read the Jetson Nano Developer Kit User Guide, which includes: 阅读Jetson Nano开发者工具包用户指南，其中包括:
- Many more details about the developer kit hardware.
关于developer kit硬件的更多细节。 - Explanations of all the components of NVIDIA JetPack, including developer tools with support for cross-compilation.
说明NVIDIA JetPack的所有组件，包括支持交叉编译的开发工具。 - Lists of all included samples and sample documentation.
所有包含的示例和示例文档的列表。
- Head to the NVIDIA Jetson Developer Zone for access to all Jetson platform information.
前往英伟达Jetson开发区访问所有Jetson平台信息。 - Ask questions or share a project on the NVIDIA Jetson Forums.
在英伟达Jetson论坛上提问或分享一个项目。
Projects and Learning 项目和学习
The Jetson Nano Developer Kit is an AI computer for learning and for making.
Jetson Nano开发工具包是一个用于学习和制作的人工智能计算机。
- Check out the Jetson Projects Page for resources including: 查看Jetson Projects页面获得的资源包括:
- Hello AI World
- Get started with deep learning inference for computer vision using pretrained models for image classification and object detection.
使用预先训练的模型进行图像分类和目标检测，开始计算机视觉的深度学习推理。 - Realtime acceleration with TensorRT and live camera streaming.
实时加速与TensorRT和实时摄像机流。 - Code your own recognition program in C++.
用c++编写自己的识别程序。 - For those interested in training their own networks, take the full Two Days to a Demo which includes both training and inference.
对于那些对训练自己的网络感兴趣的人，可以花整整两天的时间来进行一个包括训练和推理的演示。
- JetBot is an open-source AI project for makers, students and enthusiasts who are interested in learning AI and building fun applications. JetBot是一个开放源码的人工智能项目，面向那些对学习人工智能和构建有趣的应用程序感兴趣的制造者、学生和爱好者。
- It’s easy to set up and use and is compatible with many popular accessories.
它易于设置和使用，并与许多流行的配件兼容。 - Several interactive tutorials show you how to harness the power of AI to teach JetBot to follow objects, avoid collisions and more.
几个交互式教程向您展示了如何利用人工智能的力量来教JetBot跟踪对象、避免碰撞等等。 - JetBot is a great launchpad for creating entirely new AI projects.
JetBot对于创建全新的人工智能项目是一个很好的启动平台。
- Create your own!
- After taking the DLI course, start building your own AI project on Jetson Nano and share it with the Community.
在学习了DLI课程之后，开始在Jetson Nano上构建自己的AI项目，并与社区共享。 - Jetson Nano Developer Kit offers useful tools like the Jetson GPIO Python library, and is compatible with common sensors and peripherals, including many from Adafruit.
Jetson Nano开发人员工具包提供了像Jetson GPIO Python库这样有用的工具，并且兼容常见的传感器和外围设备，包括许多来自Adafruit的设备。 - Many popular AI frameworks like TensorFlow, PyTorch, Caffe, and MXNet are supported, and Jetson Nano is capable of running multiple neural networks in parallel to process data and drive action.
支持许多流行的AI框架，如TensorFlow、PyTorch、Caffe和MXNet, Jetson Nano能够运行多个神经网络并行处理数据和驱动操作。
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