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🚀 Open-sourcing the BDD100K Object Detection Model Zoo on Hugging Face.
- 🤖 10 models: YOLOv8/v9/v10/YOLO11/YOLO26 (n/s) and RF-DETR Nano.
- 🚗 Driving-scene detection: 10 classes including traffic lights and signs, across varied weather and lighting.
- 📊 Model cards with metrics, per-class results, curves, showcases, dashcam demo videos and full configs.
Headline numbers:
- 🏆 Best mAP@50: 58.76% (YOLO26s), 33.86% mAP@50:95.
- ⚡ YOLO26n gets 52.25% mAP@50 at 6.1 GFLOPs, ~3.7x fewer than YOLO26s.
Trained and evaluated with DetectionBench: https://github.com/dronefreak/DetectionBench
Dataset credit: Fisher Yu et al. (UC Berkeley, CVPR 2020). It has a non-commercial license, so it is not mirrored; get it from https://www.bdd100k.com/. The "test" split here is BDD100K's official validation set.
🤖 Collection: dronefreak/bdd100k-object-detection-model-zoo-6aafc46f2f6c5e4d8676d894
Feedback and contributions welcome.
- 🤖 10 models: YOLOv8/v9/v10/YOLO11/YOLO26 (n/s) and RF-DETR Nano.
- 🚗 Driving-scene detection: 10 classes including traffic lights and signs, across varied weather and lighting.
- 📊 Model cards with metrics, per-class results, curves, showcases, dashcam demo videos and full configs.
Headline numbers:
- 🏆 Best mAP@50: 58.76% (YOLO26s), 33.86% mAP@50:95.
- ⚡ YOLO26n gets 52.25% mAP@50 at 6.1 GFLOPs, ~3.7x fewer than YOLO26s.
Trained and evaluated with DetectionBench: https://github.com/dronefreak/DetectionBench
Dataset credit: Fisher Yu et al. (UC Berkeley, CVPR 2020). It has a non-commercial license, so it is not mirrored; get it from https://www.bdd100k.com/. The "test" split here is BDD100K's official validation set.
🤖 Collection: dronefreak/bdd100k-object-detection-model-zoo-6aafc46f2f6c5e4d8676d894
Feedback and contributions welcome.