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

Описание: Master 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! ⭐