YOLOv9, YOLOv10 & YOLO11: Learn Object Detection & Web Apps

Welcome to the YOLOv9, YOLOv10 & YOLO11 Course, a 3-in-1 course. YOLO11, YOLOv10 & YOLOv9 represent the latest advancements in computer vision object detection models.  This course begins by covering the fundamentals of computer vision, including Non-Maximum Suppression and Mean Average Precision. Moving forward, we delve deeply into YOLOv9, exploring its architecture and highlighting how it surpasses other object detection models. In Section 04, we demonstrate object detection on images and videos using YOLOv9, evaluating its performance across various parameters.Subsequently, in Section 05, we train the YOLOv9 model on a custom dataset for Personal Protective Equipment (PPE) detection. Additionally, Section 06 focuses on object tracking, where we integrate YOLOv9 with the DeepSORT & SORT algorithms. Here, we also develop an application for person/vehicle counting (entry and exit) using YOLOv9 and the DeepSORT algorithm.Section 07 provides a review of YOLO-World and a step by step guide to perform object detection using YOLO-World. Finally, in Section 08, we will create web applications by integrating YOLOv9 with Flask.Section 09, provides an introduction to YOLOv10, which includes what is YOLOv10, how YOLOv10 works, what architecture enhancements are made in YOLOv10, furthermore a performance comparison of YOLOv10 with other YOLO models is also presented in this section.In Section 10, we demonstrate object detection in images and videos using YOLOv10. Subsequently, in Section 11, we train the YOLOv10 model on a custom dataset for Personal Protective Equipment (PPE) detection. In Section 12, we perform License Plate Detection and Recognition using YOLOv10 and PaddleOCR. Similarly, in Section 13, we showcase Real-Time Object Tracking using YOLOv10 and the DeepSORT algorithm.Section 14