Detecting people using computer vision involves using algorithms and machine learning techniques to analyze digital images or videos and identify human figures. This process usually involves several steps, including object detection, feature extraction, and classification.One of the most popular techniques for detecting people is object detection, which involves locating the regions in the image or video that contain human figures. Object detection algorithms can be trained using large datasets of labeled images, and they can learn to detect various types of objects, including people.Once the human figures are located, feature extraction techniques can be used to extract relevant information from the images or videos. These features may include color, texture, shape, and motion characteristics, among others.Finally, classification algorithms can be used to classify the extracted features as belonging to humans or other objects. This process can be done in real-time, allowing for the continuous monitoring of human activity.There are many software tools available for detecting people using computer vision, including the Object Detection software. These tools typically use deep learning algorithms and can be trained to detect various types of objects, including people, in real-time. They can be used for a wide range of applications, from security and surveillance to retail and smart city management.