Eran Feit Blog posts

Text detection with Python and Opencv | OCR using EasyOCR

text detection

Text Recognition in Images with OpenCV and EasyOCR This Python script demonstrates how to perform text recognition in image files using the combined power of OpenCV, EasyOCR, and Matplotlib. The process begins by loading an image with text recognition OpenCV techniques, then detecting and extracting text using EasyOCR’s pre-trained English model. The detected text is […]

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OpenCV Image Comparison in Python: Detect Differences Like a Pro.

OpenCV image comparison

Introduction This tutorial shows how to build an OpenCV image comparison pipeline in Python that detects visual differences between two images and highlights them with bounding boxes.You will learn how to preprocess the input, isolate the two pictures inside a collage, align their sizes, compute pixel-wise differences, reduce noise, and extract clean contours of the

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Advanced Motion Detection in Video with OpenCV and Python (MOG2 Optimization Guide)

OpenCV Background Subtraction for Car Detection in Python

Implementing advanced motion detection in video with OpenCV is a fundamental milestone for computer vision engineers building traffic monitoring or automated surveillance pipelines. While basic background subtraction looks simple on paper, deploying it to production requires handling physical environmental noise, dynamic lighting shifts, and hardware limitations. In this guide, we will optimize Python scripts to

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How to Extract Text from Scanned Books with Python and OpenCV

OpenCV Word Segmentation

Introduction — Bringing Old Pages to Digital Life Optical Character Recognition (OCR) is a technology used to extract text from images which is used in applications like document digitization, license plate recognition and automated data entry. If you’ve ever wanted to digitize a physical book or scanned document, you know that the hardest part is getting

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Image Segmentation in OpenCV with Python and Contours

OpenCV Image Segmentation

Introduction In this tutorial, you will learn a practical pipeline for OpenCV image segmentation in Python.We will convert an image to grayscale, apply a smart binary threshold, detect contours, and then build a mask to extract the main object.This workflow is fast, reproducible, and ideal for object extraction, background removal, and preprocessing for computer vision

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Python Image Segmentation Made Easy with OpenCV and K-means Algorithm

OpenCV Image Segmentation with K-Means in Pytho

Introduction Image segmentation is the process of partitioning an image into meaningful regions (segments) — for example separating foreground from background, isolating objects, or splitting an image into zones of similar color or texture. One classic and relatively simple technique for segmentation is K-means clustering applied in color (or feature) space. In this post, we’ll

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Real-Time Image Classification with Jetson Nano and OpenCV — Complete Guide

Jetson Image Classification

Introduction to real-time image classification with Jetson Nano and Python In this tutorial, we will build a real-time image classification using Jetson Nano Inference and OpenCV in Python.The code connects to a webcam, captures live video, classifies each frame using a deep learning model (GoogLeNet), and overlays the recognized object name directly onto the video

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Jetson Nano Video Classification Python: Real-Time GoogLeNet Tutorial

jetson nano real time image classification

The Definitive Guide to Jetson Nano Video Classification: Python & OpenCV In the world of Edge AI, high-latency is the enemy. Standard CPU-based processing on small boards often leads to “bottlenecking,” where the hardware simply cannot keep up with a 30FPS video stream. In this masterclass, we will implement a high-performance Jetson Nano video classification

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Mastering Edge AI: Real-Time Object Classification with Jetson Nano and OpenCV

jetson nano image classification

Mastering Jetson Nano object classification is the key to building powerful, independent AI systems on the edge. While many developers struggle with slow frame rates and high latency, this guide focuses on utilizing the full potential of NVIDIA’s hardware. By integrating TensorRT inference with OpenCV, you will transform your Jetson Nano into a high-speed vision

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Eran Feit