Dive into the world of YOLOv11,
the latest iteration of the renowned You Only Look Once object detection algorithm. This video explores the key aspects of YOLOv11, from its core concepts to hands-on implementation.
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Table of Contents
1. Introduction to YOLOv11
2. Overview of YOLOv11 and its significance in real-time object detection
3. Understanding the inferencing process
4. Model Retraining for Custom Detection
5. Preparing datasets for retraining
6. Fine-tuning YOLOv11 for specific object detection tasks
7. Inferencing with Trained Models
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Resources
YOLOv11 (Ultralytics): https://docs.ultralytics.com/models/yolo11/#supported-tasks-and-modes
Code Repository: https://github.com/Gagan824/Computer-Vision-Projects/blob/main/Yolo_V11_object_detection/yolov11.ipynb
Model training: https://colab.research.google.com/drive/1AAUyTNrW7G-R_KLLi3omxMC0oEmO-UFm#scrollTo=o7d0zAupd6Vw
Roboflow: https://app.roboflow.com/
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