Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Learn to implement RF-DETR, the current state-of-the-art object detection model family that surpasses YOLO-based methods, through this comprehensive 26-minute tutorial. Master the complete workflow from dataset preparation to model deployment, with hands-on training in both Google Colab and the Roboflow Platform. Begin by setting up your training environment and running inference with pre-trained COCO models to understand baseline performance. Discover how to find and utilize free annotated datasets, with detailed explanations of the COCO annotation format essential for object detection tasks. Dive into practical RF-DETR training in Google Colab, exploring critical hyperparameters that affect model performance and learning techniques for saving fine-tuned model weights. Evaluate your trained model's performance using industry-standard metrics and run inference with your custom-trained RF-DETR model on new data. Compare training approaches by exploring RF-DETR training within the Roboflow Platform, including platform-specific evaluation tools and deployment options. Access comprehensive resources including GitHub repositories for RF-DETR implementation, Supervision library for computer vision tasks, detailed documentation, sample datasets like the UAV detection dataset, and ready-to-use Colab notebooks for immediate implementation.
