YOLOv11 Object Detection on Custom Dataset | Step-by-Step Guide

A comprehensive YOLOv11 custom object detection tutorial with a step-by-step guide for a two-class custom dataset. I cover setting up an environment for YOLOv11, how to annotate custom datasets in YOLO format, and how to train custom object detection models. Although I show a demonstration using YOLOv11 medium version, the method is generic enough to train all variations of YOLOv11 custom object detectors. This tutorial is for both Windows and Linux.

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► Time Stamps:
Introduction: (0:00)
Setting up Virtual Environment: (0:35)
Annotating custom dataset in YOLO format: (2:41)
Train YOLO v11 custom: (8:38)
Run custom object detection on images: (12:28)
Run custom object detection on videos: (16:42)
Run custom object detection on webcam: (17:14)
Export YOLOv11 to ONNX or TFLITE: (17:41)
YOLOv11 Custom Object Detection Command Line: (18:30)
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📌 Links & Resources:
https://docs.ultralytics.com/modes/ex...
https://github.com/ultralytics/ultral...
https://pytorch.org/get-started/locally/
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