The Hailo PCIe driver is required for interacting with a Hailo device over the PCIe interface

A minimalist Deep Learning framework for embedded Computer Vision

CMix-NN: Mixed Low-Precision CNN Library for Memory-Constrained Edge Devices

Acoustic features (MFSCs and MFCCs) for edge AI

STM32N6 Face Recognition system using AI models deployed on STM32N6570-DK with real-time face detection and recognition capabilities. Complete embedded development environment with automated model compilation, firmware signing, and flashing scripts.

Edge Virtualization Platform

Speech Recognition using STM32 and Machine Learning

Epsilon is a library with functions for machine learning and statistics written in plain C. It is intended to run on microcontrollers.

Mobilenet v1 (3,160,160, alpha=0.25, and 3,192,192, alpha=0.5) on STM32H7 using X-CUBE-AI v4.1.0

AutoEntangle (SmartTrap_V03) is an insect trap using FOMO (Edge Impulse) model, equipped with advanced features and minimal resources on the ESP-EYE, achieves an impressive 97% F1 Score in validation dataset, with an efficient mean processing time of 6 seconds per image and peak RAM usage of 2.4Mb per task!

The STM32 Image Processing Library (IPL) is a C software library of image processing and computer vision functionalities enabling to accelerate the development of vision applications on STM32 microcontrollers.

ESP32S3 Wakeword/Keyword Spotting starter project with ready to go ML model

embedded software components for event-based application development

Open source Python library for deploying deep learning model on Edge devices

A mnist classifier trained with Tinygrad running on $1 of compute (Raspberry Pi Pico | ArduCAM Pico4ML)

Arduino TinyML project that uses a ML model to recognize digits in the camera feed, the model was trained using the MNIST dataset

This project implements a wearable device that translates sign language gestures into text using flex sensors, an IMU, and edge ML inference.

Classifying workout exercises on an Arduino Nano 33 BLE Sense board.

The official Edge Impulse firmware for PSoC63 (CY8CKIT-062-BLE)

Driver Drowsiness Detection using MobileNetV2 on STM32