The article explores the use of the OpenCV DNN module for object detection, particularly focusing on its application with MobileNet-SSD for real-time object detection on various platforms, including Raspberry Pi. It highlights the advantages of using OpenCV DNN, such as its ability to perform faster inference on CPUs compared to other deep learning libraries like TensorFlow, without the need for high-end GPUs. The tutorial provides a step-by-step guide on setting up the OpenCV environment, downloading pre-trained models, and using OpenCV functions to process and detect objects in images. It explains how to convert images into blobs for the network, process the detection outputs, and draw bounding boxes with labels around detected objects based on a confidence threshold. The author emphasizes the ease of use and versatility of OpenCV DNN across different devices and programming languages, encouraging experimentation with custom-trained models for diverse object detection applications.