Roboflow's RF-DETR: How to Train SOTA for Object Detection on a Custom Dataset | Step-by-step guide

Master Roboflow's RF-DETR object detection with this step-by-step tutorial. RF-DETR is the current state-of-the-art object detection family of models, exceeding YOLO-based methods. From preparing datasets to training the model and deploying it in real applications, this guide covers everything. Learn to train in Google Colab or on the Roboflow Platform and build your own custom object detection model. Chapters: 00:00 RF-DETR is SOTA Object Detector 00:53 Setting Up Your RF-DETR Training Environment 03:35 Inference with Pre-trained COCO Model 06:02 Finding Free Annotated Datasets for RF-DETR 08:54 Understanding COCO Annotation Format 09:57 RF-DETR Training in Google Colab 10:55 RF-DETR Training Hyperparameters 13:48 Saving Your Fine-Tuned RF-DETR Model Weights 16:11 Evaluating Your RF-DETR Model's Performance in Google Colab 19:14 Run Inference with Fine-tuned RF-DETR Model 21:45 RF-DETR Training in Roboflow Platform 23:08 Evaluating Your RF-DETR Model's Performance in Roboflow Platform 25:30 Conclusions Resources: Roboflow: https://roboflow.com RF-DETR GitHub: https://github.com/roboflow/rf-detr Notebooks GitHub: https://github.com/roboflow/notebooks Supervision GitHub: https://github.com/roboflow/supervision RF-DETR docs: https://rfdetr.roboflow.com Supervision docs: https://supervision.roboflow.com/latest UAV dataset: https://universe.roboflow.com/roboflo... RF-DETR object detection model training notebook: https://colab.research.google.com/git... RF-DETR object detection model training blog post: https://blog.roboflow.com/train-rf-de... Mean Average Precision blog post: https://blog.roboflow.com/mean-averag... Stay updated with the projects I'm working on at https://github.com/roboflow and https://github.com/SkalskiP! ⭐