Introduction to Object Detection using OpenCV 

This article is designed to guide Python application developers through the fascinating world of object detection using OpenCV. We will explore a variety of techniques, from traditional methods like background subtraction and contour detection to more sophisticated approaches such as optical flow and deep learning-based object detection.
To access these code examples and other exciting projects and resources, be sure to visit my GitHub page:
github.com/god...
For further reading and more advanced techniques, consider the following resources:
1. OpenCV Documentation
The official OpenCV documentation provides comprehensive guides, tutorials, and references for all OpenCV functionalities, including object detection and tracking.
2. Deep Learning with Python by François Chollet
This book offers a thorough introduction to deep learning using the Keras library, authored by the creator of Keras. It is an excellent resource for understanding the principles and applications of deep learning.
3. Object Detection with Deep Learning and OpenCV
A detailed tutorial by PyImageSearch that explains how to implement object detection using YOLO and OpenCV. It covers the setup, coding, and deployment of deep learning-based object detection systems.