Product Detection Analytics on Instagram Videos

Object detection has become a cornerstone of computer vision, with applications spanning from autonomous vehicles to surveillance systems. This paper presents a novel approach using YOLOv8 for real-time object detection in video streams, coupled with a method to calculate the total duration of detected objects. We demonstrate the system's effectiveness using a custom dataset, highlighting its potential for various real-world applications where object presence duration is crucial. Our results show the count and duration of the object, indicating the viability of this approach for industrial use by various Brands to know about the appearance of their products.