This Python code demonstrates a neural network application on a CircuitPython board, utilizing a camera (OV7670) for image capture, preprocessing, and inference using a digit classifier. It includes image conversion, auto-cropping, and normalization steps.
This article details how to train an image classification model on an ESP32 using both the SenseCraft AI platform and a custom TensorFlow Lite implementation. It covers setting up binary classification, training the model, and deploying it on ESP32-S3 devices.
This article explores TinyML, a branch of machine learning run on microcontrollers like the ESP32. It details how TinyML can be used for local inference, anomaly detection, and efficient data processing with minimal power consumption, using an example of temperature and humidity monitoring.
