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Update YOLO11 Actions and Docs (#16596)

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docs/en/datasets/detect/visdrone.md
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@ -47,7 +47,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
## Usage
To train a YOLOv8n model on the VisDrone dataset for 100 [epochs](https://www.ultralytics.com/glossary/epoch) with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
To train a YOLO11n model on the VisDrone dataset for 100 [epochs](https://www.ultralytics.com/glossary/epoch) with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
!!! example "Train Example"
@ -57,7 +57,7 @@ To train a YOLOv8n model on the VisDrone dataset for 100 [epochs](https://www.ul
from ultralytics import YOLO
# Load a model
model = YOLO("yolov8n.pt") # load a pretrained model (recommended for training)
model = YOLO("yolo11n.pt") # load a pretrained model (recommended for training)
# Train the model
results = model.train(data="VisDrone.yaml", epochs=100, imgsz=640)
@ -67,7 +67,7 @@ To train a YOLOv8n model on the VisDrone dataset for 100 [epochs](https://www.ul
```bash
# Start training from a pretrained *.pt model
yolo detect train data=VisDrone.yaml model=yolov8n.pt epochs=100 imgsz=640
yolo detect train data=VisDrone.yaml model=yolo11n.pt epochs=100 imgsz=640
```
## Sample Data and Annotations
@ -113,9 +113,9 @@ The [VisDrone Dataset](https://github.com/VisDrone/VisDrone-Dataset) is a large-
- **Diversity**: Collected across 14 cities, in urban and rural settings, under different weather and lighting conditions.
- **Tasks**: Split into five main tasks—object detection in images and videos, single-object and multi-object tracking, and crowd counting.
### How can I use the VisDrone Dataset to train a YOLOv8 model with Ultralytics?
### How can I use the VisDrone Dataset to train a YOLO11 model with Ultralytics?
To train a YOLOv8 model on the VisDrone dataset for 100 epochs with an image size of 640, you can follow these steps:
To train a YOLO11 model on the VisDrone dataset for 100 epochs with an image size of 640, you can follow these steps:
!!! example "Train Example"
@ -125,7 +125,7 @@ To train a YOLOv8 model on the VisDrone dataset for 100 epochs with an image siz
from ultralytics import YOLO
# Load a pretrained model
model = YOLO("yolov8n.pt")
model = YOLO("yolo11n.pt")
# Train the model
results = model.train(data="VisDrone.yaml", epochs=100, imgsz=640)
@ -135,7 +135,7 @@ To train a YOLOv8 model on the VisDrone dataset for 100 epochs with an image siz
```bash
# Start training from a pretrained *.pt model
yolo detect train data=VisDrone.yaml model=yolov8n.pt epochs=100 imgsz=640
yolo detect train data=VisDrone.yaml model=yolo11n.pt epochs=100 imgsz=640
```
For additional configuration options, please refer to the model [Training](../../modes/train.md) page.