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Update to lowercase MkDocs admonitions (#15990)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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8
docs/en/datasets/pose/coco.md
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@ -43,7 +43,7 @@ The COCO-Pose dataset is specifically used for training and evaluating deep lear
A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO-Pose dataset, the `coco-pose.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco-pose.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco-pose.yaml).
!!! Example "ultralytics/cfg/datasets/coco-pose.yaml"
!!! example "ultralytics/cfg/datasets/coco-pose.yaml"
```yaml
--8<-- "ultralytics/cfg/datasets/coco-pose.yaml"
@ -53,7 +53,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
To train a YOLOv8n-pose model on the COCO-Pose dataset for 100 epochs 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"
!!! example "Train Example"
=== "Python"
@ -88,7 +88,7 @@ The example showcases the variety and complexity of the images in the COCO-Pose
If you use the COCO-Pose dataset in your research or development work, please cite the following paper:
!!! Quote ""
!!! quote ""
=== "BibTeX"
@ -115,7 +115,7 @@ The [COCO-Pose](https://cocodataset.org/#keypoints-2017) dataset is a specialize
Training a YOLOv8 model on the COCO-Pose dataset can be accomplished using either Python or CLI commands. For example, to train a YOLOv8n-pose model for 100 epochs with an image size of 640, you can follow the steps below:
!!! Example "Train Example"
!!! example "Train Example"
=== "Python"

8
docs/en/datasets/pose/coco8-pose.md
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@ -16,7 +16,7 @@ This dataset is intended for use with Ultralytics [HUB](https://hub.ultralytics.
A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO8-Pose dataset, the `coco8-pose.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco8-pose.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco8-pose.yaml).
!!! Example "ultralytics/cfg/datasets/coco8-pose.yaml"
!!! example "ultralytics/cfg/datasets/coco8-pose.yaml"
```yaml
--8<-- "ultralytics/cfg/datasets/coco8-pose.yaml"
@ -26,7 +26,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
To train a YOLOv8n-pose model on the COCO8-Pose dataset for 100 epochs 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"
!!! example "Train Example"
=== "Python"
@ -61,7 +61,7 @@ The example showcases the variety and complexity of the images in the COCO8-Pose
If you use the COCO dataset in your research or development work, please cite the following paper:
!!! Quote ""
!!! quote ""
=== "BibTeX"
@ -88,7 +88,7 @@ The COCO8-Pose dataset is a small, versatile pose detection dataset that include
To train a YOLOv8n-pose model on the COCO8-Pose dataset for 100 epochs with an image size of 640, follow these examples:
!!! Example "Train Example"
!!! example "Train Example"
=== "Python"

4
docs/en/datasets/pose/index.md
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@ -64,7 +64,7 @@ The `train` and `val` fields specify the paths to the directories containing the
## Usage
!!! Example
!!! example
=== "Python"
@ -126,7 +126,7 @@ If you have your own dataset and would like to use it for training pose estimati
Ultralytics provides a convenient conversion tool to convert labels from the popular COCO dataset format to YOLO format:
!!! Example
!!! example
=== "Python"

10
docs/en/datasets/pose/tiger-pose.md
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@ -29,7 +29,7 @@ This dataset is intended for use with [Ultralytics HUB](https://hub.ultralytics.
A YAML (Yet Another Markup Language) file serves as the means to specify the configuration details of a dataset. It encompasses crucial data such as file paths, class definitions, and other pertinent information. Specifically, for the `tiger-pose.yaml` file, you can check [Ultralytics Tiger-Pose Dataset Configuration File](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/tiger-pose.yaml).
!!! Example "ultralytics/cfg/datasets/tiger-pose.yaml"
!!! example "ultralytics/cfg/datasets/tiger-pose.yaml"
```yaml
--8<-- "ultralytics/cfg/datasets/tiger-pose.yaml"
@ -39,7 +39,7 @@ A YAML (Yet Another Markup Language) file serves as the means to specify the con
To train a YOLOv8n-pose model on the Tiger-Pose dataset for 100 epochs 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"
!!! example "Train Example"
=== "Python"
@ -72,7 +72,7 @@ The example showcases the variety and complexity of the images in the Tiger-Pose
## Inference Example
!!! Example "Inference Example"
!!! example "Inference Example"
=== "Python"
@ -107,7 +107,7 @@ The Ultralytics Tiger-Pose dataset is designed for pose estimation tasks, consis
To train a YOLOv8n-pose model on the Tiger-Pose dataset for 100 epochs with an image size of 640, use the following code snippets. For more details, visit the [Training](../../modes/train.md) page:
!!! Example "Train Example"
!!! example "Train Example"
=== "Python"
@ -137,7 +137,7 @@ The `tiger-pose.yaml` file is used to specify the configuration details of the T
To perform inference using a YOLOv8 model trained on the Tiger-Pose dataset, you can use the following code snippets. For a detailed guide, visit the [Prediction](../../modes/predict.md) page:
!!! Example "Inference Example"
!!! example "Inference Example"
=== "Python"