This article will mainly discuss how to build YOLOv4 to detect custom objects. Starting with the YOLOv4 introduction, how to get or build our own dataset, and how to build YOLOv4 to detect custom objects in our dataset. YOLO stands for You Only Look Once. YOLO is a state-of-the-art, real-time object detection system that was developed by Joseph Redmon. It is a real-time object recognition system that can recognize multiple objects in a single frame.

Use of deep learning in computer vision has increased in the last decade. In the past couple of years, computer vision applications such as face detection and vehicle detection have become mainstream. One of the reasons is the availability of pre-trained models. Convinced by the success of deep learning on these applications, businesses have now started to solve their own problems using deep learning. But what if the available pre-trained models are not suitable for your application?