AmebaPro2
Introduction to AMB82-mini, HUB 8735 Ultra
EdgeAI AmebaPro2
教材網址:https://github.com/rkuo2000/EdgeAI-AmebaPro2
LLM服務器程式範例: AmebaPro2_server (.py)
Arduino 程式範例: Arduino/AMB82-mini (.ino)
自強基金會 WiFi
SSID: TCFSTWIFI.ALL
Pass: 035623116
1. AI 介紹
AI 簡介
AI 硬體介紹
2. 開發板介紹
RTL8735B晶片簡介
32-bit Arm v8M, up to 500MHz, 768KB ROM, 512KB RAM, 16MB Flash (MCM embedded DDR2/DDR3L up to 128MB)
802.11 a/b/g/n WiFi 2.4GHz/5GHz, BLE 5.1, NN Engine 0.4 TOPS, Crypto Engine, Audio Codec, …
HUB 8735 Ultra
https://github.com/ideashatch/HUB-8735
AMB82-mini
Ameba Arduino
3. Arduino IDE使用介紹
Arduino IDE 2.3.2 下載 & 安裝
偏好設定 (Preferences)
Hub8735 ultra
https://raw.githubusercontent.com/ideashatch/HUB-8735/main/amebapro2_arduino/Arduino_package/ideasHatch.json
AMB82-mini
https://github.com/ambiot/ambpro2_arduino/raw/main/Arduino_package/package_realtek_amebapro2_index.json
Ameba AIoT 影片
選定開發板 AMB82-MINI
Tools > Board Manager > AMB82 package > 4.0.7
Getting Started
首先將AMB82-mini板子用MicroUSB線 連接至電腦的USB port
Arduino examples 範例練習
- 01.Basics> Blink
- 02.Digitial> GPIO> Button
修改程式碼:
const int buttonPin = 1; // the number of the pushbutton pin
const int ledPin = LED_BUILTIN; // the number of the LED pin
AMB82-Mini 程式範例
- 瀏覽器打開 EdgeAI-AmebaPro2, 點[Code]並選 [Download ZIP]
- 解壓縮.zip, 並將 Arduino/AMB82-mini 複製到 Documents/Arduino底下
4. 感測器範例練習
Serial-monitor baud rate = 115200
紅外線測距模組
Datasheet: VL53L0X - Time-of-Flight ranging sensor
Sketch: IR_VL53L0X
慣性感測模組
Sketch: IMU MPU6050-DMP6v12
5.彩色顯示器 TFTLCD
AMB82-mini + ILI9341 TFT-LCD
Interface signal names:
- MOSI: Standard SPI Pin
- MISO: Standard SPI Pin
- SLK: Standard SPI Pin
- CS: Standard SPI Pin
- RESET: Used to reboot LCD.
- D/C: Data/Command. When it is at LOW, the signal transmitted are commands, otherwise the data transmitted are data.
- LED (or BL): Adapt the screen backlight. Can be controlled by PWM or connected to VCC for 100% backlight.
- VCC: Connected to 3V or 5V, depends on its spec.
- GND: Connected to GND.
AMB82 MINI and QVGA TFT LCD Wiring Diagram:
Sketch: Camera_TFTLCD
Exmples/AmebaSPI:
- LCD_Screen_ILI9341_TFT : LCD Draw Tests
- Camera_2_Lcd : Camera output , then Jpeg Decoder to TFT-LCD
- Camera_2_Lcd_JPEGDEC : Camera output, saved to SDcard, then Jpeg Decoder to read to TFT-LCD
6. 影像串流範例練習
影像串流
Sketch: RTSP_VideoOnly
動作偵測 (motion detection)
Examples: AmebaMultimedia / MotionDetection / LoopPostProcessing.ino
- 修改ssid, passwd, 後燒錄到AMB82-mini,
- 按reset後程式即開始運行, 用serial-monitor 查看顯示串流網址
- 啟動手機或電腦上之VLC player, 設定RTSP串流網址
Motion Detection Google Line Notify
Examples: AmebaMultimedia / MotionDetection / MotionDetectGoogleLineNotify
7. 音頻應用
Audio & Mic
音頻環回測試
Examples: AmebaMultimedia / Audio /LoopbackTest
MP3 播放
Skatch: MP3_Player
- store a song.mp3 onto SDcard
- cd ~/.arduino15/packages/ideasHatch/hardware/AmebaPro2/4.0.13-Release/
- copy
variants/common_libs/MP3_Player.a
to ~/.arduino15/packages/realtek/hardware/AmebaPro2/4.0.7/variants/common_libs - edit
platform.txt
(~/.arduino15/packages/realtek/hardware/AmebaPro2/4.0.7/platform.txt) to add “{com_lib.path}/MP3_Player.a” into Ameba archive list (compiler.ameba.ar.list) - copy
libraries/MP3_Player
to ~/.arduino15/packages/realtek/hardware/AmebaPro2/4.0.7/libraries
Upload & Reset to run
音頻串流範例
Examples: AmebaMultimedia / Audio / RTSPAudioStream
MP4錄音範例
Examples: AmebaMultimedia / RecordMP4 / AudioOnly
音頻分類範例
Examples: AmebaNN / AudioClassification
8. 人臉辨識與識別
人臉辨識與識別介紹
人臉檢測範例
Examples: AmebaNN / RTSPFaceDetection
人臉識別範例
Examples: AmebaNN / RTSPFaceRecognition
Serial_monitor: REG=RKUO
- Enter the command REG=Name to give the targeted face a name.
- Enter the command DEL=Name to delete a certain registered face. For example,
DEL=SAM
- Enter the command BACKUP to save a copy of registered faces to flash.
- If a backup exists, enter the command RESTORE to load registered faces from flash.
- Enter the command RESET to forget all previously registered faces.
9. 影像分類 (Image Classification)
影像分類範例
Garbage模型訓練與檔案轉換
模型訓練: kaggle.com/rkuo2000/garbage-cnn
required in kaggle for AmebaPro2 1) pip install tensorflow==2.14.1 2) model.save(‘garbage_cnn.h5’, include_optimizer=False)
模型轉換:AMB82 AI Model Conversion
- Download garbage_cnn.h5 from kaggle.com/rkuo2000/garbage-cnn
Output
- Compress garbage_cnn.h5 to garbage_cnn.zip
- Go to Amebapro2 AI convert model, fill up your E-mail
- Upload garbage_cnn.zip
- Upload one (.jpg) test picture (EX. glass100.jpg from Garbage dataset)
- Email will be sent to you for the link of
network_binary.nb
程式範例:RTSP_GarbageClassification.ino
- click the recieved Email link to download
network_binary.nb
- create NN_MDL folder in SDcard, save network_binary.nb under NN_MDL folder, and rename it to
imgclassification.nb
- plugin SDcard back to AMB82-MINI
- modify Sketch RTSP_GarbageClassification.ino 1) modify SSID and PASSWD 2) modify imgclass.modelSelect (change DEFAULT_IMGCLASS to CUSTOMIZED_IMGCLASS)
- burn code into board AMB82-MINI, and run it with VLC player streaming
10. 物件偵測 (Object Detection)
Public Dataset
物件檢測介紹
Kaggle範例:
- YOLOv7 Facemask detection
- YOLOv7 Pothole detection
- YOLOv7 Sushi detection
- YOLOv7 refrigeratoryfood
- YOLOv7 reparm
Pothole模型訓練與檔案轉換
模型訓練: kaggle.com/rkuo2000/yolov7-pothole
1) repro https://github.com/WongKinYiu/yolov7
2) create pothole.yaml
%%writefile data/pothole.yaml
train: ./Datasets/pothole/train/images
val: ./Datasets/pothole/valid/images
test: ./Datasets/pothole/test/images
# Classes
nc: 1 # number of classes
names: ['pothole'] # class names
3) YOLOv7-Tiny Fixed Resolution Training
!sed -i "s/nc: 80/nc: 1/" cfg/training/yolov7-tiny.yaml
!sed -i "s/IDetect/Detect/" cfg/training/yolov7-tiny.yaml
模型轉換:AMB82 AI Model Conversion
- Download
best.pt
from kaggle.com/rkuo2000/yolov7-pothole - Compress best.pt to
best.zip
- Go to Amebapro2 AI convert model, fill up your E-mail
- Upload best.zip
- Upload one (.jpg) test picture (EX. pothole_test.jpg from Pothole dataset)
- Email will be sent to you for the link of
network_binary.nb
程式範例:RTSP_YOLOv7_Pothole_Detection.ino
- click the recieved Email link to download
network_binary.nb
- create NN_MDL folder in SDcard, save network_binary.nb under NN_MDL folder, and rename it to
yolov7_tiny.nb
- plugin SDcard back to AMB82-MINI
- modify Sketch RTSP_YOLOv7_Pothole_Detection.ino 1) modify SSID and PASSWD 2) modify ObjDet.modelSelect(OBJECT_DETECTION, CUSTOMIZED_YOLOV7TINY, NA_MODEL, NA_MODEL);
- burn code into board AMB82-MINI, and run it with VLC player streaming
AMB82 Mini 物件偵測範例
AMB82 Mini SD卡加載模型範例
RTPS_ObjectDetection_AudioClassification.ino
Online NN Conversion Tool (客製化模型轉換工具)
11. 大型語言模型範例 (LLM)
語音辨識範例
ffmpeg.exe is needed for Windows to run Whisper!
語音交談範例
ffmpeg.exe is needed for Windows to run Whisper!
Download ffmpeg-master-latest-win64-gpl.zip, extract & put ffmpeg.exe into where you run Whisper server.
AmebaPro2 Whisper LLM_server
AmebaPro2_Whisper_Gemini_server
- 到 https://aistudio.google.com/app/apikey 取得API_Key 填入GOOGLE_API_KEY, 再執行AmebaPro2_Whisper_Gemini_server.py
RecordMP4_HTTP_Post_Audio.ino
- 修改server IP位址 in RecordMP4_HTTP_Post_Audio.ino server IP位址, then 燒錄到 AMB82-MINI
- reset AMB82-MINI 來啟動, 按鍵兩秒後即可錄音詢問 LLM/Gemini
12. 視覺語言模型 (VLM)
影像+語音交談範例
This site was last updated October 07, 2024.