Training the YOLOv5 Object Detector on a Custom Dataset

Training the YOLOv5 Object Detector on a Custom Dataset

Training the YOLOv5 Object Detector on a Custom Dataset – PyImageSearch

“In 2020, Glenn Jocher, the founder and CEO of Ultralytics, released its open-source implementation of YOLOv5 on GitHub. YOLOv5 offers a family of object detection architectures pre-trained on the MS COCO dataset.

Today, YOLOv5 is one of the official state-of-the-art models with tremendous support and is easier to use in production. The best part is that YOLOv5 is natively implemented in PyTorch, eliminating the Darknet framework’s limitations (based on C programming language).

This massive change of YOLO to the PyTorch framework made it easier for the developers to modify the architecture and export to many deployment environments straightforwardly. And not to forget, YOLOv5 is one of the official state-of-the-art models hosted in the Torch Hub showcase…”

Source: pyimagesearch.com/2022/06/20/training-the-yolov5-object-detector-on-a-custom-dataset/