课程介绍

The deep neural network model can be trained and tested quickly and then deployed by the industry to effectively perform tasks in the real world. Deploying such systems on small-sized, low-power AI edge computing platforms is highly favored by the industry. This course takes a practice-driven approach to lead you to intuitively learn, practice, and master the knowledge and technology of deep neural networks.The deep neural network model can be trained and tested quickly and then deployed by the industry to effectively perform tasks in the real world. Deploying such systems on small-sized, low-power AI edge computing platforms is highly favored by the industry. This course takes a practice-driven approach to lead you to intuitively learn, practice, and master the knowledge and technology of deep neural networks.

The SOPHON AI microserver SE5 is a high-performance, low-power edge computing product equipped with the third-generation TPU chip BM1684 developed independently by SOPHGO. With an INT8 computing power of up to 17.6 TOPS, it supports 32 channels of Full HD video hardware decoding and 2 channels of encoding. This course will quickly guide you through the powerful features of the SE5 server.  Through this course, you can understand the basics of AI and master its basic applications.

Course Features

1. One-stop service 

All common problems encountered in SE5 applications can be found here.

 • Provide a full-stack solution for AI micro servers

 • Break down the development process step by step, in detail and clearly

 • Support all mainstream frameworks, easy to use products

2. Systematic teaching 

It includes everything from setting up the environment, developing applications, converting models, and deploying products, as well as having a mirrored practical environment.

• How is the environment built? 

• How is the model compiled? 

• How is the application developed? 

• How are scenarios deployed?

3. Complete materials

The course includes video tutorials, document guides, code scripts, and other comprehensive materials. 

• Rich video materials 

• Detailed application guidance 

• Clear code scripts 

Code download link: https://github.com/sophon-ai-algo/examples

4. Free cloud development resources 

Online free application for using SE5-16 microserver cloud testing space 

• SE5-16 microserver cloud testing space can be used for online development and testing, supporting user data retention and export 

• SE5-16 microserver cloud testing space has the same resource performance as the physical machine environment 

Cloud platform application link: https://account.sophgo.com/sign_in?service=https://cloud.sophgo.com&locale=zh-CN

Cloud platform usage instructions: https://cloud.sophgo.com/tpu.pdf

 

课程章节 ( 23节课)

1_ Product introduction
开始学习
1.1 SE5 hardware description
待学习
开始学习
2_ Environment set up
开始学习
2.1 SE5 Unpacking Connection guide
待学习
开始学习
2.2 SE5刷机升级指南
待学习
开始学习
2.3 SE5升级Ubuntu指南
待学习
开始学习
2.4 Linux下交叉编译环境的搭建
待学习
开始学习
2.5 快速跑通一个SoC模式example
待学习
开始学习
3_ Development Guide
开始学习
3.1 SAIL开发指南
待学习
开始学习
3.2 BMffmpeg编程开发指南
待学习
开始学习
3.3 算能量化工具介绍及使用说明
待学习
开始学习
4_ Model transformation
开始学习
4.1 Caffe模型转换
待学习
开始学习
4.2 Darknet模型转换
待学习
开始学习
4.3 Paddlepaddle模型转换
待学习
开始学习
4.4 Pytorch模型转换
待学习
开始学习
4.5 MXNet模型转换
待学习
开始学习
4.6 ONNX模型转换
待学习
开始学习
4.7 Tensorflow模型转换
待学习
开始学习
5_ AI Practice
开始学习
5.1 基于YOLOv5的目标检测算法移植与测试
待学习
开始学习
5.2 基于LPRNet的车牌识别算法移植与测试
待学习
开始学习
5.3 AI书法生成器实战
待学习
开始学习
5.4 基于YOLACT实现目标跟踪
待学习
开始学习
5.5 基于CenterNet实现图像分割
待学习
开始学习
5.6 基于PP_OCR的文字识别算法移植
待学习
开始学习
5.7 基于SE5-16微服务器云测试空间及YOLO3D的目标检测算法移植与测试
待学习
开始学习

课程概览

课程目标

Upon completing this course, students will be able to:

  • Understand the basics of deep learning
  • Master the usage of the algorithm acceleration TPU chip BM1684 architecture and platform, as well as the setup and usage of cross-compiling environments
  • Utilize various models for conversion and deployment
  • Learn to implement practical scenarios such as license plate recognition, text recognition, and object detection on the TPU platform
  • Possess fundamental abilities to apply deep learning knowledge to solve specific problems.

课程对象

This course comprehensively and systematically introduces the basic knowledge of deep learning, TPU hardware platform and TPU platform practical foundation, as well as image classification and other topics. To learn this course, it is necessary to have a certain foundation in Python programming and basic knowledge of probability and statistics.

课程推荐

course-cover

AI compiler:TPU-MLIR environment construction and use guide

course-cover

Milk-V Duo Development Board Pratical Course

This course introduces the hardware circuit design and basic environment set up, as well as provides some simple development examples and some basic AI examples.

Milk-V Duo is an ultra-compact embedded development platform based on CV1800B. It has small size and comprehensive functionality, it is equipped with dual cores and can run linux and rtos systems separately, and has various connectable peripherals.

  • Scalability: The Milk-V Duo core board has various interfaces such as GPIO, I2C, UART, SDIO1, SPI, ADC, PWM, etc.
  • Diverse connectable peripherals: The Milk-V Duo core board can be expanded with various devices such as LED, portable screens, cameras, WIFI and so on.

Course features:

  • The content materials are rich and complete, including development board hardware design, peripheral interface instructions, basic environment set up method, and sample code scripts.
  • The learning path is scientifically reasonable, starting from the introduction and basic usage of the development board, and then leading to pratical projects to fully utilize the development board and provide reference for users' own development.
  • The pratical projects are rich, and the course provides many examples of practical code usage and function demonstrations. Different functions can be implemented by simply modifying and combining the code.

course-cover

The Concept and Practice of LLM