How to Train Detectron2 for Custom Instance Segmentation

RF-DETR Segmentation, a state-of-the-art instance segmentation model released in October 2025, offers significant improvements in speed and accuracy compared to YOLO11, as demonstrated on the Microsoft COCO Segmentation benchmark. The blog post provides a detailed tutorial on training custom instance segmentation models using Detectron2, focusing on the assembly, registration, and configuration of a custom dataset. It utilizes the American Sign Language dataset from Roboflow Universe and emphasizes the importance of labeling precision for accurate instance segmentation. The tutorial guides users through various stages, including dataset preparation, training pipeline setup, model training, and performance evaluation, with practical examples and code snippets. Additionally, it highlights the use of Roboflow's tools for dataset management and introduces alternative training methods such as Roboflow's AutoML solution.

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