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Update YOLO11 Actions and Docs (#16596)

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docs/en/datasets/segment/carparts-seg.md
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@ -45,7 +45,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
## Usage
To train Ultralytics YOLOv8n model on the Carparts Segmentation 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 Ultralytics YOLO11n model on the Carparts Segmentation 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"
@ -55,7 +55,7 @@ To train Ultralytics YOLOv8n model on the Carparts Segmentation dataset for 100
from ultralytics import YOLO
# Load a model
model = YOLO("yolov8n-seg.pt") # load a pretrained model (recommended for training)
model = YOLO("yolo11n-seg.pt") # load a pretrained model (recommended for training)
# Train the model
results = model.train(data="carparts-seg.yaml", epochs=100, imgsz=640)
@ -65,7 +65,7 @@ To train Ultralytics YOLOv8n model on the Carparts Segmentation dataset for 100
```bash
# Start training from a pretrained *.pt model
yolo segment train data=carparts-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640
yolo segment train data=carparts-seg.yaml model=yolo11n-seg.pt epochs=100 imgsz=640
```
## Sample Data and Annotations
@ -108,9 +108,9 @@ We extend our thanks to the Roboflow team for their dedication in developing and
The [Roboflow Carparts Segmentation Dataset](https://universe.roboflow.com/gianmarco-russo-vt9xr/car-seg-un1pm?ref=ultralytics) is a curated collection of images and videos specifically designed for car part segmentation tasks in computer vision. This dataset includes a diverse range of visuals captured from multiple perspectives, making it an invaluable resource for training and testing segmentation models for automotive applications.
### How can I use the Carparts Segmentation Dataset with Ultralytics YOLOv8?
### How can I use the Carparts Segmentation Dataset with Ultralytics YOLO11?
To train a YOLOv8 model on the Carparts Segmentation dataset, you can follow these steps:
To train a YOLO11 model on the Carparts Segmentation dataset, you can follow these steps:
!!! example "Train Example"
@ -120,7 +120,7 @@ To train a YOLOv8 model on the Carparts Segmentation dataset, you can follow the
from ultralytics import YOLO
# Load a model
model = YOLO("yolov8n-seg.pt") # load a pretrained model (recommended for training)
model = YOLO("yolo11n-seg.pt") # load a pretrained model (recommended for training)
# Train the model
results = model.train(data="carparts-seg.yaml", epochs=100, imgsz=640)
@ -130,7 +130,7 @@ To train a YOLOv8 model on the Carparts Segmentation dataset, you can follow the
```bash
# Start training from a pretrained *.pt model
yolo segment train data=carparts-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640
yolo segment train data=carparts-seg.yaml model=yolo11n-seg.pt epochs=100 imgsz=640
```
For more details, refer to the [Training](../../modes/train.md) documentation.