YOLO, abbreviated as You Only Look Once, was proposed as a real-time object detection technique by Joseph Redmon et al in their research work.

It frames object detection in images as a regression problem to spatially separated bounding boxes and associated class probabilities.

In this approach, a single neural network divides the image into regions and predicts bounding boxes and probabilities for each region.

Here’s great article on the subject.

In this article, we will learn how to detect objects present in the images. For the detection of objects, we will use the YOLO (You Only Look Once) algorithm and demonstrate this task on a few images. In the result, we will get the image with captioned and highlighted objects with their probability of correct detection.