Object Detection Using Raspberry Pi and TensorFlow

Real-time object detection is considered a vast, vibrant, and complex area of computer vision. When an image has a single object to be detected, it is known as Image Localization, while multiple objects in an image is referred to as Object Detection.[1] The semantic objects of a class in digital images and videos are detected through this process. Various applications of real-time object detection include object tracking, video surveillance, pedestrian detection, people counting, self-driving cars, face detection, ball tracking in sports, and more. The SSD MobilenetV2 FPN model, which is a representative tool of deep learning to detect objects, can be used with TensorFlow or OpenCV, an open-source computer vision library of programming functions primarily focused on real-time computer vision.[2]