Instructions to use hazemelerefy/DAFEgate-YOLO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use hazemelerefy/DAFEgate-YOLO with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("hazemelerefy/DAFEgate-YOLO") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
DAFEgate-YOLO
DAFEgate-YOLO is a dual-branch defect-aware feature enhancement model for real-time steel surface defect detection.
- Space Demo: https://huggingface.co/spaces/hazemelerefy/DAFEsteel
- Architecture: YOLOv11n + DAFEGate v4 (Defect-Aware Feature Enhancement)
- Dataset: NEU-DET (6 classes)
- mAP@0.5: 81.98%
- FPS: 145 FPS
- Parameters: 2.69M
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