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ultralytics 8.0.141 create new SettingsManager (#3790)

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Glenn Jocher 2023-07-23 16:03:34 +02:00 • committed by GitHub
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10
docs/datasets/detect/visdrone.md
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@ -44,10 +44,10 @@ To train a YOLOv8n model on the VisDrone dataset for 100 epochs with an image si
```python
from ultralytics import YOLO
# Load a model
model = YOLO('yolov8n.pt') # load a pretrained model (recommended for training)
# Train the model
model.train(data='VisDrone.yaml', epochs=100, imgsz=640)
```
@ -76,8 +76,8 @@ If you use the VisDrone dataset in your research or development work, please cit
```bibtex
@ARTICLE{9573394,
author={Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={Detection and Tracking Meet Drones Challenge},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={Detection and Tracking Meet Drones Challenge},
year={2021},
volume={},
number={},
@ -85,4 +85,4 @@ If you use the VisDrone dataset in your research or development work, please cit
doi={10.1109/TPAMI.2021.3119563}}
```
We would like to acknowledge the AISKYEYE team at the Lab of Machine Learning and Data Mining, Tianjin University, China, for creating and maintaining the VisDrone dataset as a valuable resource for the drone-based computer vision research community. For more information about the VisDrone dataset and its creators, visit the [VisDrone Dataset GitHub repository](https://github.com/VisDrone/VisDrone-Dataset).
We would like to acknowledge the AISKYEYE team at the Lab of Machine Learning and Data Mining, Tianjin University, China, for creating and maintaining the VisDrone dataset as a valuable resource for the drone-based computer vision research community. For more information about the VisDrone dataset and its creators, visit the [VisDrone Dataset GitHub repository](https://github.com/VisDrone/VisDrone-Dataset).