Image Segmentation
ultralytics
PyTorch
semantic-segmentation
aerial-imagery
drone
uavid
yolo26
computer-vision
Eval Results (legacy)
Instructions to use dronefreak/uavid-yolo26m-sem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use dronefreak/uavid-yolo26m-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/uavid-yolo26m-sem") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download confusion_matrix_normalized.png from dronefreak/uavid-yolo26m-sem: direct link, hf CLI and curl.
- Browser
- Download file 224 kB
-
https://huggingface.co/dronefreak/uavid-yolo26m-sem/resolve/main/confusion_matrix_normalized.png
- Command line
-
hf download hf://dronefreak/uavid-yolo26m-sem/confusion_matrix_normalized.png
-
curl -L -o confusion_matrix_normalized.png https://huggingface.co/dronefreak/uavid-yolo26m-sem/resolve/main/confusion_matrix_normalized.png
224 kB

- Xet hash:
- bb19ecb2e33ec7ed72699856cd95636d7f8805c5d363ecdec082772d29c32f9d
- Size of remote file:
- 224 kB
- SHA256:
- 2a9bb82f540a9a924b29138295db00528a61356f2f4a5031ae1564328be20c94
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