MLX-VLM: A package for running Vision LLMs on Mac using MLX.
A DIY project that uses a Raspberry Pi and computer vision to detect and notify about stray cat sightings, with an added feature to deter birds from approaching the cat food.
This article explores how to incorporate images into a RAG (Retrieval-Augmented Generation) knowledgebase using Large Language Models (LLMs) with vision capabilities. It provides a step-by-step guide to collecting, uploading, and transcribing images for a richer and more detailed knowledgebase.
This article guides readers through running the latest YOLO v10 object detection model on different hardware, specifically on a Raspberry Pi 5, and a computer. The article discusses the importance of computer vision in ML applications, the versatility of YOLO, and the cross-platform code presented in the article.
TrashAI is a platform that utilizes Artificial Intelligence to identify and sort waste, aiming to increase recycling rates and decrease contamination. By partnering with waste facilities and municipalities, TrashAI hopes to make a significant impact on waste management and contribute to a sustainable future.
Explore Mars Exploration Made Easy: GalaxyRVR, compatible with Arduino, navigates diverse terrains effortlessly, powered by solar charging. With real-time FPV, smart obstacle avoidance, and remote control, you're set for a genuine Martian adventure from anywhere.
Laser distance scan sensor (LDS/LIDAR) Arduino wrapper/controller for kaia.ai home robot software platform
A website for the Seeed Watcher, a physical AI agent for space management, with features like product catalog, ecosystem, support, and company information.
Grove Vision AI V2 is a highly efficient MCU-based smart vision module driven by the Himax WiseEye2 HX6538 processor, featuring a dual-core Arm Cortex-M55 and integrated Arm Ethos-U55 neural network component.
This article provides a step-by-step guide on fine-tuning the Florence-2 model for object detection tasks, including loading the pre-trained model, fine-tuning with a custom dataset, and evaluating the model's performance.
