OpenCV

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Introduction This tutorial shows how to use OpenCV template matching in Python to find a smaller image inside a larger image.We will solve a fun Where’s Waldo style problem using a single, simple algorithm.The code reads two images, converts the scene to grayscale, and runs cv2.matchTemplate to measure visual similarity.We then extract the best match

You can find the video here : https://www.youtube.com/watch?v=fd1msoIpM5Q What you’ll build A Python app that listens for your voice command (for example, “person”, “bottle”, “dog”) and highlights only those objects in the webcam stream. We’ll use: By the end, you’ll speak a class name and the app will box just those detections. You can find

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

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

Why Background Subtraction Works for Car Detection Car detection in video starts by separating moving objects from a static background. Background subtraction is a simple yet powerful technique to isolate the foreground and extract moving vehicles:contentReference[oaicite:0]{index=0}. It’s ideal for traffic scenes where the background continuously changes and no “clean” background image is available:contentReference[oaicite:1]{index=1}. By combining

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