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Ricerca sulle capacità della scheda STM32F4 nell’eseguire task di Machine Learning

STM32CubeIDE UNIVPM GitHub


📝 Table of Contents

📋 About

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🗂 Project Topology

|-- Core
|   |-- Inc/*.h
|   |-- Src/*.c
|   |-- Startup/...
|-- Drivers
|   |-- BSP/...
|   |-- CMSIS/...
|   |-- STM32F4Xxx_HAL_Driver/...
|-- FATFS
|   |-- App/...
|   |-- Target/...
|-- LIBJPEG
|   |-- App/...
|   |-- Target/...
|-- Middlewares
|   |-- ST/...
|   |-- Third_Party/...
|-- Model
|   |-- labels.txt
|   |-- model.tflite
|-- USB_HOST
|   |-- App/...
|   |-- Target/...
|-- Utilities
|   |-- Fonts/...
|-- X-CUBE-AI
|   |-- App/
|   |   |-- app_x-cube-ai-.c/.h
|   |   |-- network_config.h
|   |   |-- network_data.c/.h
|   |   |-- network_generate_report.txt
|   |   |-- network.c/.h
|   |-- constants_ai.h
|-- stm32f4-ai-framework.ioc
|-- STM32F429ZITX_FLASH.ld
|-- STM32F429ZITX_RAM.ld

⚙️ STM32F4 Ad Hoc Framework

Framework

🤖 Image Classification: Teachable Machine

Teachable Machine

🍱 Food Recognition: FD-MobileNet

FD-MobileNet

🚶‍♂️ Human Presence Detection: MobileNet v2

MobileNet v2

📟 Constrained Object Detection: FOMO

FOMO

⛏️ Built Using

✍️ Authors

🎉 Acknowledgements