NVIDIA之AI Course：Getting Started with AI on Jetson Nano—Class notes(五)

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The original text comes from?NVIDIA-AI Course. This article only provides Chinese translation.

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目錄

Conclusion ?

Recap ?回顧

1.?Setting Up Your Jetson Nano? ? ?設置你的Jetson Nano

2.?Image Classification? ?圖像分類

3.?Image Regression? ?圖像回歸

Next Steps

Find Your Way Around

Projects and Learning ??項目和學習

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Conclusion ?

正在更新……

Recap ?回顧

Congratulations! ??恭喜你!

You've successfully set up the NVIDIA Jetson Nano Developer Kit and built multiple AI projects:
您已經成功地設置了NVIDIA Jetson Nano開發工具包，并構建了多個AI項目:

1.?Setting Up Your Jetson Nano? ? ?設置你的Jetson Nano

You learned: ? ?您學習了:

• How to run your Jetson Nano in "headless" mode
  如何運行您的Jetson Nano在“無頭”模式
• How to access JupyterLab on the Jetson Nano through USB Device Mode
  如何通過USB設備模式訪問Jetson Nano上的JupyterLab
• How to burn an SD card with and use it on the Jetson Nano
  如何燒傷SD卡，并使用它的Jetson Nano

2.?Image Classification? ?圖像分類

You learned: ? ?您學習了:

• How to collect your own labeled images
  如何收集自己的標簽圖像
• How to vary data backgrounds and orientations to improve your classification model
  如何改變數據背景和方向來改進分類模型
• How to train a classification model
  如何訓練分類模型
• How to run inference on a live camera feed with your classification model
  如何使用分類模型在實時攝像機提要上運行推理

3.?Image Regression? ?圖像回歸

You learned: ?您學習了:

• How to localize features with regression models
  如何使用回歸模型本地化特性
• How to collect annotated data
  如何收集帶注釋的數據
• How to train a regression model
  如何訓練回歸模型
• How to run inference on a live camera feed with your regression model
  如何使用您的回歸模型在實時攝像機提要上運行推理

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Next Steps

Find Your Way Around

• Read the?Jetson Nano Developer Kit User Guide, which includes: ? ?閱讀Jetson Nano開發者工具包用戶指南，其中包括:
  • Many more details about the developer kit hardware.
    關于developer kit硬件的更多細節。
  • Explanations of all the components of NVIDIA JetPack, including developer tools with support for cross-compilation.
    說明NVIDIA JetPack的所有組件，包括支持交叉編譯的開發工具。
  • Lists of all included samples and sample documentation.
    所有包含的示例和示例文檔的列表。
• Head to the?NVIDIA Jetson Developer Zone?for access to all Jetson platform information.
  前往英偉達Jetson開發區訪問所有Jetson平臺信息。
• Ask questions or share a project on the?NVIDIA Jetson Forums.
  在英偉達Jetson論壇上提問或分享一個項目。

Projects and Learning ??項目和學習

The Jetson Nano Developer Kit is an AI computer for learning and for making.
Jetson Nano開發工具包是一個用于學習和制作的人工智能計算機。

• Check out the?Jetson Projects Page?for resources including: ? ?查看Jetson Projects頁面獲得的資源包括:
  • Hello AI World
    • Get started with deep learning inference for computer vision using pretrained models for image classification and object detection.
      使用預先訓練的模型進行圖像分類和目標檢測，開始計算機視覺的深度學習推理。
    • Realtime acceleration with TensorRT and live camera streaming.
      實時加速與TensorRT和實時攝像機流。
    • Code your own recognition program in C++.
      用c++編寫自己的識別程序。
    • For those interested in training their own networks, take the full Two Days to a Demo which includes both training and inference.
      對于那些對訓練自己的網絡感興趣的人，可以花整整兩天的時間來進行一個包括訓練和推理的演示。
  • JetBot?is an open-source AI project for makers, students and enthusiasts who are interested in learning AI and building fun applications. ? ? JetBot是一個開放源碼的人工智能項目，面向那些對學習人工智能和構建有趣的應用程序感興趣的制造者、學生和愛好者。
    • It’s easy to set up and use and is compatible with many popular accessories.
      它易于設置和使用，并與許多流行的配件兼容。
    • Several interactive tutorials show you how to harness the power of AI to teach JetBot to follow objects, avoid collisions and more.
      幾個交互式教程向您展示了如何利用人工智能的力量來教JetBot跟蹤對象、避免碰撞等等。
    • JetBot is a great launchpad for creating entirely new AI projects.
      JetBot對于創建全新的人工智能項目是一個很好的啟動平臺。
• Create your own!
  • After taking the DLI course, start building your own AI project on Jetson Nano and share it with the Community.
    在學習了DLI課程之后，開始在Jetson Nano上構建自己的AI項目，并與社區共享。
  • 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開發人員工具包提供了像Jetson GPIO Python庫這樣有用的工具，并且兼容常見的傳感器和外圍設備，包括許多來自Adafruit的設備。
  • 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.
    支持許多流行的AI框架，如TensorFlow、PyTorch、Caffe和MXNet, Jetson Nano能夠運行多個神經網絡并行處理數據和驅動操作。

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