Raspberry Pi

VLM on Edge: Worth the Hype or Just a Novelty?

Testing Vision Language Models (VLM) on edge devices. Check how small VLMs perform on our custom Raspberry Pi Cluster and Jetson Nanos.

Edge Devices, Jetson Nano, Raspberry Pi, VLMs

YOLO11 on Raspberry Pi: Optimizing Object Detection for Edge Devices

Imagine you have multiple warehouses in different places where you don’t have time to monitor everything at a time, and you can’t afford a lot of computes due to their

Computer Vision, Edge Devices, Object Detection, Object Tracking, Raspberry Pi, YOLO

TensorFlow Model Optimization Toolkit – A Deep Dive

In the previous posts of the TFLite series, we introduced TFLite and the process of creating a model. In this post, we will take a deeper dive into the TensorFlow

CNN, Deep Learning, Edge Devices, Image Classification, Model Optimization, Post Training Quantization, Raspberry Pi

TensorFlow Lite Model Maker: Create Models for On-Device Machine Learning

In this article, we will learn how to create a TensorFlow Lite model using the TF Lite Model Maker Library. We will fine-tune a pre-trained image classification model on the

CNN, Deep Learning, Edge Devices, Image Classification, Model Optimization, OpenCV Tutorials, Post Training Quantization, Raspberry Pi

TensorFlow Lite: TFLite Model Optimization for On-Device Machine Learning

The recent trend in developing larger and larger Deep Learning models for a slight increase in accuracy raises concerns about their computational efficiency and wide scaled usability. We can not

CNN, Deep Learning, Edge Devices, Image Classification, Model Optimization, OpenCV Tutorials, Post Training Quantization, Raspberry Pi

Install OpenCV 4 on Raspberry Pi

Install OpenCV 4 on Raspberry Pi. In this post, we will provide a bash script for installing OpenCV-4.0 (C++, Python 2.7 and Python 3.5) on Raspbian Operating System on Raspberry

Edge Devices, Install, OpenCV, OpenCV Beginners, Raspberry Pi