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blackbeedrones
/
imav-2025-platform

Object Detection
ultralytics
TensorBoard
ONNX
yolo
yolov11
drone
uav
imav
robotics
autonomous-landing
helipad-detection
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use blackbeedrones/imav-2025-platform with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • ultralytics

    How to use blackbeedrones/imav-2025-platform 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("blackbeedrones/imav-2025-platform", "<weights>.pt")
    model = YOLO(weights)
    source = 'http://images.cocodataset.org/val2017/000000039769.jpg'
    model.predict(source=source, save=True)
  • Notebooks
  • Google Colab
  • Kaggle
imav-2025-platform
33 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 18 commits
samuellimabraz's picture
samuellimabraz
Link dataset repo, update SDK references to Nectar
69c95fc verified 6 months ago
  • train
    Add training artifacts (results, curves, tensorboard events) 9 months ago
  • .gitattributes
    2.63 kB
    Add best.pt/onnx/engine (standard naming): best.engine 9 months ago
  • README.md
    3.39 kB
    Link dataset repo, update SDK references to Nectar 6 months ago
  • best.engine
    8.77 MB
    xet
    Add best.pt/onnx/engine (standard naming): best.engine 9 months ago
  • best.onnx
    10.6 MB
    xet
    Add best.pt/onnx/engine (standard naming): best.onnx 9 months ago
  • best.pt
    5.46 MB
    xet
    Add best.pt/onnx/engine (standard naming): best.pt 9 months ago
  • platform.png
    65 kB
    Update README with mission details and platform specs: platform.png 9 months ago