Object Detection
ultralytics
PyTorch
detectionbench
computer-vision
maritime
uav
drone
search-and-rescue
Eval Results (legacy)
Instructions to use dronefreak/seadronessee-yolov8m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use dronefreak/seadronessee-yolov8m 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/seadronessee-yolov8m") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download BoxPR_curve.png from dronefreak/seadronessee-yolov8m: direct link, hf CLI and curl.
- Browser
- Download file 200 kB
-
https://huggingface.co/dronefreak/seadronessee-yolov8m/resolve/main/BoxPR_curve.png
- Command line
-
hf download hf://dronefreak/seadronessee-yolov8m/BoxPR_curve.png
-
curl -L -o BoxPR_curve.png https://huggingface.co/dronefreak/seadronessee-yolov8m/resolve/main/BoxPR_curve.png
200 kB

- Xet hash:
- e9d5860beeed392fcf4b4bb2d31bb3ce5bfa612eb1834309e81fb69e93b4bab3
- Size of remote file:
- 200 kB
- SHA256:
- 38e422b57776d39c59b6e7a69d69a4e8d645214f570f77b3cfecbcfcc8474961
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