Eran Feit

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.

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

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

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