Object Detection
ultralytics
YOLOv10
PyTorch
computer-vision
kitti
autonomous-driving
from-scratch
Eval Results (legacy)
Instructions to use HugoHE/yolov10-kitti-vanilla with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use HugoHE/yolov10-kitti-vanilla with ultralytics:
from ultralytics import YOLOvv10 model = YOLOvv10.from_pretrained("HugoHE/yolov10-kitti-vanilla") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - YOLOv10
How to use HugoHE/yolov10-kitti-vanilla with YOLOv10:
from ultralytics import YOLOvv10 model = YOLOvv10.from_pretrained("HugoHE/yolov10-kitti-vanilla") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16f11c77a2f3a774c5388fc86cb8d994b751907cb1207b0a6bdca381f70c7de8
- Size of remote file:
- 16.5 MB
- SHA256:
- 6f649ac5ada24a56cfb4c327fcf34f674803d934873b30c31dfb6d9c70d4d0c4
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