YOLO11 & YOLOv12: Object Detection & Web Apps in Python 2026

In this lecture, we delve deeply into Non Maximum Suppression, which is a technique used to remove redundant and overlapping bounding boxes.

This lecture covers Mean Average Precision (mAP), which is a metric used to evaluate the performance of object detection models in computer vision

In this lecture, we'll explore how to perform object detection, instance segmentation, pose estimation, and image classification using YOLO11.

In this lecture, we'll explore how to perform object detection, instance segmentation, pose estimation, and image classification using YOLO11 on Windows and Linux.

In this lecture, we will delve into the process of testing and analyzing the performance of the YOLO11 model. By the end of this lecture, you'll have a comprehensive understanding of how to effectively evaluate YOLO11's performance and apply these insights to real-world scenarios.

In this lecture, we will explore how to train the YOLO11 object detection model on a custom dataset for Personal Protective Equipment (PPE) detection. We will conduct a detailed analysis of the results and test our fine-tuned model on random images and videos.

In this lecture, you will learn how to train an Ultralytics YOLO11 object detection model on the VisDrone dataset. The lecture covers model training and evaluating detection performance for aerial objects.

In this lecture, you will learn how to train and evaluate an object detection model using Ultralytics YOLO11 on the KITTI dataset. We will cover dataset model training, and performance evaluation.

In this lecture, you will learn how to train and evaluate an African wildlife detection model using Ultralytics YOLO11.

In this lecture, we will learn how to perform multi-object tracking on videos and live webcam feeds using YOLO11 with Bot-SORT and ByteTrack tracking algorithms. We will also plot the movement of detected objects across multiple video frames and explore multithreaded tracking, enabling us to run object tracking on multiple video streams simultaneously.