Title: Object Detection with Deep Learning

This course offers an in-depth exploration of object detection techniques using state-of-the-art deep learning models. It covers essential topics such as the COCO dataset, the YOLO algorithm, real-time object detection using pretrained models, and practical applications like car license plate detection and speed estimation using YOLOv8 and OpenCV.

Module 1: COCO Dataset
In this module, you will be introduced to the Common Objects in Context (COCO) dataset, one of the most widely used datasets for object detection. You'll learn about its structure, the variety of object classes it contains, and how to use it for training and evaluating object detection models. By the end of this module, you'll be able to effectively work with the COCO dataset to develop robust object detection solutions.

Module 2: YOLO (You Only Look Once) Algorithm
This module delves into the YOLO (You Only Look Once) algorithm, a breakthrough in object detection that achieves high accuracy and real-time performance. You'll learn about the architecture of YOLO, its various versions, and how it differs from other object detection methods. Practical exercises will guide you through implementing YOLO for detecting objects in images and videos.

Module 3: Real-time Object Detection using Pretrained Models like RT-DETR and Transfer Learning
Explore the cutting-edge techniques for real-time object detection in this module. You'll work with pretrained models such as RT-DETR and learn how to apply transfer learning to fine-tune these models for specific tasks. This module emphasizes the practical aspects of deploying real-time object detection systems, ensuring you can build efficient and accurate models for various applications.

Module 4: Application for Car License Plate Detection and Speed Estimation using YOLOv8 and OpenCV
In this hands-on module, you'll develop a real-world application for detecting car license plates and estimating vehicle speed using YOLOv8 and OpenCV. You'll learn how to preprocess video feeds, implement YOLOv8 for license plate detection, and use computer vision techniques to estimate the speed of moving vehicles. By the end of this module, you'll have a fully functional application that demonstrates the practical utility of object detection technologies.