YOLO-NAS Object Detection On Custom Dataset - Airplane ✈
Thank you Deci AI & Harpreet Sahota 🥑 For this amazing architecture YOLO 😊 .
YOLO-NAS architecture is out! The new YOLO-NAS delivers state-of-the-art performance with the unparalleled accuracy-speed performance, outperforming other models such as YOLOv5, YOLOv6, YOLOv7 and YOLOv8. Check it out here: YOLO-NAS.
Easy to train SOTA Models
Easily load and fine-tune production-ready, pre-trained SOTA models that incorporate best practices and validated hyper-parameters for achieving best-in-class accuracy.
👉 RoboFlow100 datasets integration.
👉 Support Darknet/Yolo format detection dataset (used by Yolo v5, v6, v7, v8).
👉 Post Training Quantization and Quantization Aware Training.
🏋️ Trained in a multi-phase process involving pre-training on Object365, COCO Pseudo-Labeled data, Knowledge Distillation (KD), and Distribution Focal Loss (DFL).
📊 Outperforms existing YOLO models on the diverse RoboFlow100 (RF100) dataset, following a robust training protocol, providing significant advantages in various use cases. 🏆
🌐 Help spread the word about YOLO-NAS!
Star the SuperGradients GitHub repo, play around with the starter notebook and let's revolutionize the field of computer vision together. 👨🔬
GitHub Link ⭐ - https://lnkd.in/d6S-ss6R
Starter Colab NoteBook 😎 - https://lnkd.in/dU3zwQm4