Object Detection
ultralytics
PyTorch
11
ultralyticsplus
yolov11
yolo
vision
visdrone
uav
Eval Results (legacy)
Instructions to use erbayat/yolov11n-visdrone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use erbayat/yolov11n-visdrone with ultralytics:
from ultralytics import YOLOvv11 model = YOLOvv11.from_pretrained("erbayat/yolov11n-visdrone") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f276190ca03b0625b8c3bf051b6184b1c136b428e3a2e7de7e4b17afb3075500
- Size of remote file:
- 5.48 MB
- SHA256:
- d7a6f6db0ca8baaecd36dec177a73a7ec1b3a36643d67244afe5454e57ed43ee
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