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Update YOLO11 Actions and Docs (#16596)

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docs/en/datasets/detect/sku-110k.md
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@ -51,7 +51,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
## Usage
To train a YOLOv8n model on the SKU-110K 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 SKU-110K 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"
@ -61,7 +61,7 @@ To train a YOLOv8n model on the SKU-110K 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="SKU-110K.yaml", epochs=100, imgsz=640)
@ -71,7 +71,7 @@ To train a YOLOv8n model on the SKU-110K dataset for 100 [epochs](https://www.ul
```bash
# Start training from a pretrained *.pt model
yolo detect train data=SKU-110K.yaml model=yolov8n.pt epochs=100 imgsz=640
yolo detect train data=SKU-110K.yaml model=yolo11n.pt epochs=100 imgsz=640
```
## Sample Data and Annotations
@ -109,9 +109,9 @@ We would like to acknowledge Eran Goldman et al. for creating and maintaining th
The SKU-110k dataset consists of densely packed retail shelf images designed to aid research in object detection tasks. Developed by Eran Goldman et al., it includes over 110,000 unique SKU categories. Its importance lies in its ability to challenge state-of-the-art object detectors with diverse object appearances and close proximity, making it an invaluable resource for researchers and practitioners in computer vision. Learn more about the dataset's structure and applications in our [SKU-110k Dataset](#sku-110k-dataset) section.
### How do I train a YOLOv8 model using the SKU-110k dataset?
### How do I train a YOLO11 model using the SKU-110k dataset?
Training a YOLOv8 model on the SKU-110k dataset is straightforward. Here's an example to train a YOLOv8n model for 100 epochs with an image size of 640:
Training a YOLO11 model on the SKU-110k dataset is straightforward. Here's an example to train a YOLO11n model for 100 epochs with an image size of 640:
!!! example "Train Example"
@ -121,7 +121,7 @@ Training a YOLOv8 model on the SKU-110k dataset is straightforward. Here's an ex
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="SKU-110K.yaml", epochs=100, imgsz=640)
@ -132,7 +132,7 @@ Training a YOLOv8 model on the SKU-110k dataset is straightforward. Here's an ex
```bash
# Start training from a pretrained *.pt model
yolo detect train data=SKU-110K.yaml model=yolov8n.pt epochs=100 imgsz=640
yolo detect train data=SKU-110K.yaml model=yolo11n.pt epochs=100 imgsz=640
```
For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.