Location:Training / Machine Learning/Algorithm / AI Artificial Intelligence Deep Learning (RV1126)-Issue 1 Preparation / Compile the RockX routines that come with the SDK

This course is a new series of video tutorials on artificial intelligence and deep learning launched by Zhengdian Atom in 2023!

Lecture 1.0 Introduction to the content of this lecture

Lecture 1.1 Take a look at the directory after SDK compilation

Lecture 1.2 RV1126 file system partition Lecture

1.3 About self-starting at boot (Part 1)

Lecture 1.4 About self-starting at boot (Part 2)

Lecture 1.5 About booting Self-starting (Part 2)

Lecture 1.6 Setting the static IP address of the factory system (Part 1)

Chapter 1.7 Setting the static IP address of the factory system (Part 2)

Chapter 1.8 Introduction to the RKMedia framework and its routines

Chapter 1.9 Testing the SDK’s own RKMedia

routines Lecture 1.10 Compiling RKMedia routines that come with the SDK Lecture

1.11 The use of 720P and 1080P MIPI screens

Lecture 1.12 The use of IMX415 and IMX335 cameras

Lecture 2.0 Introduction to the content of this lecture Lecture

2.1 A brief introduction to the RV1126 AI model deployment process Lecture

2.2 On-point and atomic Introduction to AI routines for ATK-DLRV1126 development board

Lecture 2.3 Construction of a development environment for testing the Punctual Atomic AI routines Lecture

2.4 Compiling the Punctual Atomic AI routines

Lecture 2.5 Testing AI routines based on RockX

Lecture 2.6 Testing AI routines based on RKNN

Lecture 2.7 QR code recognition routine testing

Lecture 2.8 The use of RockX (Part 1)

Lecture 2.9 The use of RockX (Part 2) Lecture

2.10 Compiling the RockX routines that come with the SDK Lecture

2.11 Testing the RockX routines that come with the SDK Chapter

2.12 Talk about compiling and testing the RKNN routines that come with the SDK (Part 1)

Lecture 2.13 Compiling and testing the RKNN routines that come with the SDK (Part 2)

Lecture 2.14 Compiling and testing the RKNN routines that come with the SDK (Part 2)

How about Lecture 2.15 Update NPU driver

Chapter 2.16 What are the requirements for getting started with embedded AI?