Object Detection
ultralytics
TensorBoard
ONNX
yolo
yolov11
drone
uav
imav
robotics
autonomous-landing
helipad-detection
Eval Results (legacy)
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 ultralytics import YOLOvv11 model = YOLOvv11.from_pretrained("blackbeedrones/imav-2025-platform") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ddbeb429e4d9cec9a4650311cb5098bfe723c7d809958023a51dcc210b65766
- Size of remote file:
- 8.77 MB
- SHA256:
- 324cbe0a70585dc86f2a5e552d634b63ccf78c980c38be492a65cd28161603c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.