| Supported Targets | ESP32-S3 |
|---|---|
| ESP-IDF Version | v5.1.1 |
this project is to fulfill the assignments for UGM's advanced microcontroller-based systems course. This project is the implementation of digit handwritten recognition training on Tensorflow Python and tests the model/inferencing on ESP32s3 with TensorFlow Lite Micro model programmed with Espressif-IDF. The project only require ESP32s3, LCD ILI9341 + xp2046 touchscreen and a few wire.
idf.py build # build program
idf.py flash -p COM{your_number} # flash to your microcontroller specify {your_number}
The project Handwritten Digit Recognition Project contains one source file in C++ language main.cpp. The file is located in folder main.
ESP-IDF projects are built using CMake. The project build configuration is contained in CMakeLists.txt
files that provide set of directives and instructions describing the project's source files and targets
(executable, library, or both).
Below is short explanation of remaining files in the project folder.
├── CMakeLists.txt
├── main
│ ├── model_data*.h This is model generated from model_train.ipynb file (Tensorflow v2 + Python)
│ ├── NeuralNetwork.* This is NN to initiate, input data and request data output from the model that has been trained
│ ├── lcd_touch_init.* This is lcd ili9341 + xpt2046 structure init (not library)
│ ├── lvgl_component_init.* This is initialization component with LVGL
│ ├── squareline_ui This is ui exported from squareline studio 1.3.3
│ ├── CMakeLists.txt For build with idf.py build which using cmake for compiling all whole code
│ └── main.cpp This is main program
└── README.md This is the file you are currently reading