Train YOLO-NAS - SOTA Object Detection Model - on Custom Dataset

Video Description

Discover the power of YOLO-NAS, Deci's next-generation object detection model, in this comprehensive guide. We'll walk you through the Python setup, installing YOLO-NAS, running inferences with the pre-trained COCO model, and even training YOLO-NAS on your custom dataset. Dive into the superior real-time object detection capabilities of this game-changing model and learn how to use it to optimize your own AI projects. Chapters: 00:00 Introduction and Model Overview 01:57 Python Environment Setup and Installing YOLO-NAS 04:56 Inference with pre-trained COCO model 07:21 YOLO-NAS Inference Output Format 09:06 Finding Open-source Datasets 10:19 Training YOLO-NAS on Custom Dataset 16:34 Evaluate Trained Model 17:28 Inference with Trained Model 18:39 Conclusion Resources: 🌏 Roboflow: https://roboflow.com 🌌 Roboflow Universe: https://universe.roboflow.com 📚 Roboflow Notebooks Repository: https://github.com/roboflow/notebooks 📚 How to Train YOLO-NAS on a Custom Dataset blog post: https://blog.roboflow.com/yolo-nas-how-to-train-on-custom-dataset/ 📓 How to Train YOLO-NAS on a Custom Dataset notebook: https://colab.research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/train-yolo-nas-on-custom-dataset.ipynb ❓ Why do we need to restart Google Colab? https://github.com/obss/sahi/discussions/781 🎬 YOLOv8: How to Train for Object Detection on a Custom Dataset: https://youtu.be/wuZtUMEiKWY Stay updated with the projects I'm working on at https://github.com/roboflow and https://github.com/SkalskiP! ⭐ Don't forget to like, comment, and subscribe for more content on AI, computer vision, and the latest technological breakthroughs! 🚀 #YOLO_NAS #Deci #ObjectDetection #NeuralArchitectureSearch #Python #COCO #MachineLearning #ArtificialIntelligence #CustomDataset #Inference #ModelEvaluation #OpenSource #Datasets