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
metadata
base_model:
- Ultralytics/YOLO11
tags:
- ultralyticsplus
- yolov11
- ultralytics
- yolo
- vision
- object-detection
- pytorch
- visdrone
- uav
library_name: ultralytics
library_version: 8.0.239
model-index:
- name: erbayat/yolo11n-visdrone
results:
- task:
type: object-detection
metrics:
- type: precision
value: 0.34
name: mAP@0.5(box)
license: openrail