Object Detection
ultralytics
TensorBoard
PyTorch
v8
ultralyticsplus
yolov8
yolo
vision
visdrone
uav
Eval Results (legacy)
Instructions to use mshamrai/yolov8x-visdrone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use mshamrai/yolov8x-visdrone with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("mshamrai/yolov8x-visdrone", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download best.pt from mshamrai/yolov8x-visdrone: direct link, hf CLI and curl.
- Browser
- Download file 137 MB
-
https://huggingface.co/mshamrai/yolov8x-visdrone/resolve/main/best.pt
- Command line
-
hf download hf://mshamrai/yolov8x-visdrone/best.pt
-
curl -L -o best.pt https://huggingface.co/mshamrai/yolov8x-visdrone/resolve/main/best.pt
137 MB
- Xet hash:
- 73daa46bb97d0c62608e4349c991705ae73d2f6d542b033eac7659ebbd8d60ff
- Size of remote file:
- 137 MB
- SHA256:
- 361e1883f906f45a9780d7c6e57d9e82506a887468542093ca49cc5df59d5a4c
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