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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OpenCV Motion Detection Python: A Complete MOG2 Background Subtraction Guide

OpenCV Background Subtraction for Car Detection in Python

Detecting movement in a video stream is a fundamental task in computer vision. In this tutorial, you will learn how to implement OpenCV motion detection Python using the MOG2 background subtraction algorithm. This approach is ideal for real-time applications like traffic monitoring or security surveillance where processing speed is critical. We will walk through the

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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

Introduction Mastering Jetson Nano Video Classification Python allows you to deploy powerful AI models directly on edge devices. In this tutorial, we build a high-performance classification pipeline using OpenCV and NVIDIA’s Jetson Inference library. You will learn how to process MP4 video files, convert frames for CUDA acceleration, and use the GoogLeNet (Inception v1) model

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How to classify objects using Jetson Nano inference and OpenCV ?

jetson nano image classification

Jetson Nano Image Classification with OpenCV and Python Introduction This tutorial shows how to run Jetson Nano image classification with Python and OpenCV.You will use the NVIDIA Jetson Inference library with GoogleNet to recognize objects in a single image. The goal is to build a CUDA-accelerated pipeline that loads an image, classifies it on the

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Eran Feit