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dronefreak
/
vdd-yolo26l-sem

Image Segmentation
ultralytics
PyTorch
semantic-segmentation
aerial-imagery
drone
vdd
yolo26
computer-vision
Eval Results (legacy)
Model card Files Files and versions
xet
Community
1

Instructions to use dronefreak/vdd-yolo26l-sem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • ultralytics

    How to use dronefreak/vdd-yolo26l-sem with ultralytics:

    from huggingface_hub import hf_hub_download
    from ultralytics import YOLO
    
    # pick the weights file from this repo's "Files and versions" tab
    weights = hf_hub_download("dronefreak/vdd-yolo26l-sem", "<weights>.pt")
    model = YOLO(weights)
    source = 'http://images.cocodataset.org/val2017/000000039769.jpg'
    model.predict(source=source, save=True)
  • Notebooks
  • Google Colab
  • Kaggle
vdd-yolo26l-sem
39.1 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
dronefreak's picture
dronefreak
Add model-index metadata for HF evaluation results widget
1ea91cf verified about 1 month ago
  • .gitattributes
    1.74 kB
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  • README.md
    8.21 kB
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  • args.yaml
    1.77 kB
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  • best.pt
    36.1 MB
    xet
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  • confusion_matrix.png
    257 kB
    xet
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  • confusion_matrix_normalized.png
    169 kB
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  • demo_grid.png
    2.2 MB
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  • iou_bar_chart.png
    80.1 kB
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  • results.csv
    26.1 kB
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  • results.png
    222 kB
    xet
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