Image Segmentation
ultralytics
PyTorch
semantic-segmentation
aerial-imagery
drone
aeroscapes
yolo26
computer-vision
Eval Results (legacy)
Instructions to use dronefreak/aeroscapes-yolo26n-sem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use dronefreak/aeroscapes-yolo26n-sem with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("dronefreak/aeroscapes-yolo26n-sem") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 152511a6e8c9e54ff0f5e48d4571a7c966c6f4d4f469e1bf4ea2b2076906a6fe
- Size of remote file:
- 3.46 MB
- SHA256:
- cff57c3273fea7d983b5982628289060f18f740f264061fdada93fb441ee84b4
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