Awesome
About
Number recognition with MNIST on Raspberry Pi Pico + TensorFlow Lite for Microcontrollers
Device
- Raspberry Pi Pico
- LCDディスプレイ 2.8"240x320 SPI TFT LCDタッチパネルシリアルポートモジュール+ PCB ILI9341 5V / 3.3V
- LCD: Ili9341 (SPI)
- Touch Panel: TSC2046 (SPI)
Wiring
Build
git clone https://github.com/iwatake2222/pico-mnist.git
cd pico-mnist
git submodule update --init
cd pico-sdk && git submodule update --init && cd ..
mkdir build && cd build
# For Windows Visual Studio 2019 (Developer Command Prompt for VS 2019)
# cmake .. -G "NMake Makefiles" -DCMAKE_BUILD_TYPE=Debug -DPICO_DEOPTIMIZED_DEBUG=on
cmake .. -G "NMake Makefiles"
nmake
# For Windows MSYS2 (Run the following commands on MSYS2)
# cmake .. -G "MSYS Makefiles" -DCMAKE_BUILD_TYPE=Debug -DPICO_DEOPTIMIZED_DEBUG=on
cmake .. -G "MSYS Makefiles"
make
Model
- Google Colaboratory script for model creation in Keras and model conversion with quantization
- Note : It looks uint8 quantization is not supported. You need to use int8 quantization, or use FP32 model.
Acknowledgements
-
pico-sdk
- https://github.com/raspberrypi/pico-sdk
- Copyright 2020 (c) 2020 Raspberry Pi (Trading) Ltd.
-
pico-examples
- https://github.com/raspberrypi/pico-examples
- Copyright 2020 (c) 2020 Raspberry Pi (Trading) Ltd.
-
pico-tflmicro
- https://github.com/raspberrypi/pico-tflmicro
- Copyright 2019 The TensorFlow Authors. All Rights Reserved.