What Is YOLOv5? Plus YOLOv5 Startups [Everything to Know]

YOLOv5 is a popular emerging technology trend with online searches having increased 99X+ from 2020-2022.

YOLO, an acronym for “You Only Look Once,” is a framework for facilitating real-time object detection. The framework is popular in autonomous driving software because it can detect people, animals, traffic signals, and more in real-time.

YOLOv5 is the fifth and newest version of the YOLO framework.

At only 27 MB, YOLOv5 is approximately 88% smaller in size than YOLOv4.

This is significant as YOLOv5 can detect objects at 140 FPS, compared to YOLOv4’s max capability of 50 FPS.

YOLOv5 in context

YOLOv5 is part of the ML-Assisted Image Classification trend.

Image classification is the process of using ML algorithms to understand what images represent, which is an essential part of computer vision technology.

Last year, venture captial funding in image classification startups grew by 3x.

And estimates predict that the market for image classification technologies will grow to from almost $17 billion in 2022 to nearly $100 billion by 2030.

Sky Engine

Sky Engine is a machine learning training platform. The tool trains AI algorithms to understand images and detect objects.

SigAi

SigAi provides object detection and image classification services for enterprises.

OneView

OneView is a geospatial data platform designed to train ML algorithms to perform object detection and image classification on satellite data.

The startup has raised a total of $3.3M in funding to date.

Final word – YOLOv5

So if you’re looking to improve your skills in real-time object detection, or break into an exciting new field like autonomous driving software, YOLOv5 is definitely a framework worth exploring.

There are many reasons why YOLOv5 has become so popular in recent years.

For one thing, it is much faster and more efficient than previous versions of the YOLO framework, making it ideal for applications where real-time object detection is critical, such as self-driving cars.

Additionally, its smaller size means that it can be used on mobile devices with minimal impact on performance.

And finally, the growing popularity of image classification technologies means that there is a high demand for YOLOv5 experts.