Ten years ago, computer vision researchers thought that getting a computer to tell the difference between a cat and a dog would be almost impossible, even with the significant advance in the state of artificial intelligence. But now using image classification computers can not only detect the object but also can categorize thousand different types.

Object detection is not a new term. It was there from the 1980s but the problem with it was the accuracy and speed.

The reason being why speed is more important in this field is whenever we detect the object using traditional methods of open-cv and python the entire state of the environment was changed, making the use of that technology in real-world was limited.

YOLO (You Ony Look Once) changed the entire scenario when it came out in 2017. YOLO uses a totally different approach. It applies a single neural network to the full image. This network divides the image into regions and predicts bounding boxes and probabilities for each region. These bounding boxes are weighted by the predicted probabilities.