Object detection software has revolutionized many industries, including video surveillance, self-driving cars, and robotics. One of the most common uses of object detection is to detect humans in an image or video. This article will explore how object detection software can detect humans and provide some background theory on the topic.Object detection software works by identifying objects in an image or video and classifying them into different categories. These categories can include cars, animals, and, in our case, humans. The software proposes the objects it identifies as belonging to a certain class, humans in this case, using a probability score. It then defines the boundaries of the proposed humans with x-y origins and height and length values.To detect humans, object detection software uses deep learning artificial intelligence systems that process a vast number of images to learn to recognize humans. These processing blocks, called models, are trained on millions of images that include humans in various positions, backgrounds, and lighting conditions. The models learn to detect patterns that are indicative of human features, such as head and body shapes, clothing, and facial features.The models used for human detection are typically based on convolutional neural networks (CNNs). CNNs are a type of artificial neural network that are designed to process images. They work by applying a series of filters to an image to extract features that are relevant to the task at hand. In the case of human detection, the filters are designed to recognize patterns that are indicative of human features.Once the object detection software has detected humans in an image or video, the results can be used in various ways. For example, in video surveillance, the software can be set up to trigger an alarm or send an alert when humans are detected in a certain area. In self-driving cars, the software can be used to detect pedestrians and avoid collisions. In robotics, the software can be used to recognize humans and interact with them in a more natural way.In conclusion, detecting humans in an image or video using object detection software is a complex process that involves deep learning artificial intelligence systems and convolutional neural networks. The software identifies humans based on patterns that are indicative of human features, such as head and body shapes, clothing, and facial features. The results of human detection can be used in various applications, such as video surveillance, self-driving cars, and robotics.