Detecting Objects in Video or Camera Images using ImageAI

Object Detection in a video is to locate the presence of objects, put them under certain classes based on our deep learning model, and place bounding boxes around them. To simply put our Input is a video or images with multiple objects and Output is the same video or image with bounding boxes (of certain height and width) around the objects class names and probabilities to which they belong. Here we will be using a pre-trained YOLO (You Only Look Once) model which was trained for a large dataset of around 80 classes of objects for a long time with high-powered resources. This article, will not go much deeper into the YOLO architecture and focus more on the ImageAI library to do object detection on our video and get the results. Building these models from scratch takes a lot of understanding of mathematics and its architecture along with thousands of lines of code.