The objective of this project is to develop a real-time object detection system using deep learning models. Object detection is a computer vision task that involves identifying and localizing objects within an image or video. This project will focus on developing a system that can detect multiple objects in real-time, with high accuracy and efficiency.
To achieve this goal, the project will make use of deep learning models, specifically convolutional neural networks (CNNs) and object detection frameworks such as YOLO (You Only Look Once) and its different versions. These models have been shown to achieve state-of-the-art performance on object detection tasks.
The data that has been used up in the respected files such as weights, cfg, images and videos has been uploaded here.