Breaking the Myth: Object Detection Isn’t Hard as Thought

Hearing about AI and object detection can create an illusion among developers that doing such things is far beyond the reach of traditionally trained programmers.

But that’s not the case. Object detection is easy to set up and only requires a few minutes of your time.

It’s a computer vision technique that works to identify and locate objects within an image or video. For example, traffic surveillance systems, self-driving cars, and facial recognition systems all employ this technology to track down vehicles, faces, and other objects of interest.

This article will use YOLO (You Only Look Once) for performing the object detection tasks.

Object Detection with YOLO

Introduction to YOLOV8

YOLOv8 (You Only Look Once) is an open-source Computer Vision AI model released on January 10th, 2023. It’s called YOLO because it detects everything inside an image in a single pass. The new version can perform image detection, classification, instance segmentation, tracking, and pose estimation tasks.

The new v8 has better performance and flexibility. This is pre-trained on COCO (Common Objects in Context) and ImageNet datasets.

Using YOLO: An Example

YOLO can be used for a wide variety of applications and use cases. Here is an example of borderless table detection. A detailed section on implementation is presented at the end of the article.

For the full article and the practical part visit our blogpost https://journal.hexmos.com/yolo-object-detection/

原文链接：Breaking the Myth: Object Detection Isn’t Hard as Thought