Hugging Face Adds D-Fine Model for Lightning-Fast Object Detection
- D-Fine brings state-of-the-art real-time object detection to Hugging Face with five model sizes and robust pretrained variants.
- Released under Apache 2.0, it’s free for research and commercial projects.
Hugging Face has added D-Fine, a real-time object detection model family, to the Transformers library. Contributed by Vladislav Bronzov, D-Fine delivers strong detection performance focusing on speed and flexibility.
The model suite comes in five sizes, allowing developers to tailor performance to their system’s latency and memory constraints. D-Fine includes checkpoints trained on COCO, Objects365, and a hybrid set fine-tuned across both, helping it generalize to various detection scenarios.
D-Fine is a significant update because it makes fast, accurate, and adaptable object detection available to anyone building spatial or visual systems, without needing proprietary tools or heavyweight infrastructure. As a model built for the Hugging Face ecosystem, it’s ready to deploy out of the box with inference and fine-tuning notebooks and demo spaces supporting both image and video input.
🌀 Tom's Take:
The ability to recognize objects unlocks powerful use cases, from labeling the world in AR glasses, to enhancing interactivity in mixed reality, to helping robots perceive and navigate their surroundings more like we do.
Source: LinkedIn – Pavel Iakubovskii
