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 […]
Find Waldo with OpenCV Template Matching in Python Read More »
How do you transition from static object detection to robust, frame-to-frame temporal tracking without devastating your pipeline’s frame rate? Building a high-performance yolo11 object tracking python opencv application requires balancing deep learning inference speeds with stable ID association. In this technical guide, you will solve the critical problem of identity fragmentation across sequential video frames.
Real-Time Object Detection in Python with Voice Commands (OpenCV + YOLOv4-tiny) Read More »
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
Text detection with Python and Opencv | OCR using EasyOCR Read More »
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
OpenCV Image Comparison in Python: Detect Differences Like a Pro. Read More »
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
Advanced Motion Detection in Video with OpenCV and Python (MOG2 Optimization Guide) Read More »
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
How to Extract Text from Scanned Books with Python and OpenCV Read More »
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
Image Segmentation in OpenCV with Python and Contours Read More »
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
Python Image Segmentation Made Easy with OpenCV and K-means Algorithm Read More »
This tutorial elaborates how to install MediaPipe on the Jetson Nano. This is the 2022 version with the last Jetpack (Q1 2022) just follow the steps and you will get the Mediapipe install on your jetson nano The link for the video : https://youtu.be/ij9bIET4rCU You can find more similar tutorials in my blog posts page
How to install Mediapipe on the Jetson Nano ? Read More »
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
Real-Time Image Classification with Jetson Nano and OpenCV — Complete Guide Read More »