Update to lowercase MkDocs admonitions (#15990)

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

docs/en/datasets/segment/carparts-seg.md

@@ -37,7 +37,7 @@ Carparts Segmentation finds applications in automotive quality control, auto rep
 
 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 Package Segmentation dataset, the `carparts-seg.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/carparts-seg.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/carparts-seg.yaml).
 
-!!! Example "ultralytics/cfg/datasets/carparts-seg.yaml"
+!!! example "ultralytics/cfg/datasets/carparts-seg.yaml"
 
     ```yaml
     --8<-- "ultralytics/cfg/datasets/carparts-seg.yaml"
@@ -47,7 +47,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
 
 To train Ultralytics YOLOv8n model on the Carparts Segmentation 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"
 
@@ -81,7 +81,7 @@ The Carparts Segmentation dataset includes a diverse array of images and videos
 
 If you integrate the Carparts Segmentation dataset into your research or development projects, please make reference to the following paper:
 
-!!! Quote ""
+!!! quote ""
 
     === "BibTeX"
 
@@ -112,7 +112,7 @@ The [Roboflow Carparts Segmentation Dataset](https://universe.roboflow.com/gianm
 
 To train a YOLOv8 model on the Carparts Segmentation dataset, you can follow these steps:
 
-!!! Example "Train Example"
+!!! example "Train Example"
 
     === "Python"
 

docs/en/datasets/segment/coco.md

@@ -41,7 +41,7 @@ COCO-Seg is widely used for training and evaluating deep learning models in inst
 
 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-Seg dataset, the `coco.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco.yaml).
 
-!!! Example "ultralytics/cfg/datasets/coco.yaml"
+!!! example "ultralytics/cfg/datasets/coco.yaml"
 
     ```yaml
     --8<-- "ultralytics/cfg/datasets/coco.yaml"
@@ -51,7 +51,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
 
 To train a YOLOv8n-seg model on the COCO-Seg 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"
 
@@ -86,7 +86,7 @@ The example showcases the variety and complexity of the images in the COCO-Seg d
 
 If you use the COCO-Seg dataset in your research or development work, please cite the original COCO paper and acknowledge the extension to COCO-Seg:
 
-!!! Quote ""
+!!! quote ""
 
     === "BibTeX"
 
@@ -113,7 +113,7 @@ The [COCO-Seg](https://cocodataset.org/#home) dataset is an extension of the ori
 
 To train a YOLOv8n-seg model on the COCO-Seg dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a detailed list of available arguments, refer to the model [Training](../../modes/train.md) page.
 
-!!! Example "Train Example"
+!!! example "Train Example"
 
     === "Python"
 

docs/en/datasets/segment/coco8-seg.md

@@ -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-Seg dataset, the `coco8-seg.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco8-seg.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco8-seg.yaml).
 
-!!! Example "ultralytics/cfg/datasets/coco8-seg.yaml"
+!!! example "ultralytics/cfg/datasets/coco8-seg.yaml"
 
     ```yaml
     --8<-- "ultralytics/cfg/datasets/coco8-seg.yaml"
@@ -26,7 +26,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
 
 To train a YOLOv8n-seg model on the COCO8-Seg 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-Seg
 
 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-Seg dataset** is a compact instance segmentation dataset by Ultralyt
 
 To train a **YOLOv8n-seg** model on the COCO8-Seg dataset for 100 epochs with an image size of 640, you can use Python or CLI commands. Here's a quick example:
 
-!!! Example "Train Example"
+!!! example "Train Example"
 
     === "Python"
 

docs/en/datasets/segment/crack-seg.md

@@ -26,7 +26,7 @@ Crack segmentation finds practical applications in infrastructure maintenance, a
 
 A YAML (Yet Another Markup Language) file is employed to outline the configuration of the dataset, encompassing details about paths, classes, and other pertinent information. Specifically, for the Crack Segmentation dataset, the `crack-seg.yaml` file is managed and accessible at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/crack-seg.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/crack-seg.yaml).
 
-!!! Example "ultralytics/cfg/datasets/crack-seg.yaml"
+!!! example "ultralytics/cfg/datasets/crack-seg.yaml"
 
     ```yaml
     --8<-- "ultralytics/cfg/datasets/crack-seg.yaml"
@@ -36,7 +36,7 @@ A YAML (Yet Another Markup Language) file is employed to outline the configurati
 
 To train Ultralytics YOLOv8n model on the Crack Segmentation 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"
 
@@ -71,7 +71,7 @@ The Crack Segmentation dataset comprises a varied collection of images and video
 
 If you incorporate the crack segmentation dataset into your research or development endeavors, kindly reference the following paper:
 
-!!! Quote ""
+!!! quote ""
 
     === "BibTeX"
 
@@ -102,7 +102,7 @@ The [Roboflow Crack Segmentation Dataset](https://universe.roboflow.com/universi
 
 To train an Ultralytics YOLOv8 model on the Crack Segmentation dataset, use the following code snippets. Detailed instructions and further parameters can be found on the model [Training](../../modes/train.md) page.
 
-!!! Example "Train Example"
+!!! example "Train Example"
 
     === "Python"
 
@@ -135,7 +135,7 @@ Ultralytics YOLO offers advanced real-time object detection, segmentation, and c
 
 If you incorporate the Crack Segmentation Dataset into your research, please use the following BibTeX reference:
 
-!!! Quote ""
+!!! quote ""
 
     === "BibTeX"
 

docs/en/datasets/segment/index.md

@@ -33,7 +33,7 @@ Here is an example of the YOLO dataset format for a single image with two object
 1 0.504 0.000 0.501 0.004 0.498 0.004 0.493 0.010 0.492 0.0104
 ```
 
-!!! Tip "Tip"
+!!! tip "Tip"
 
       - The length of each row does **not** have to be equal.
       - Each segmentation label must have a **minimum of 3 xy points**: `<class-index> <x1> <y1> <x2> <y2> <x3> <y3>`
@@ -66,7 +66,7 @@ The `train` and `val` fields specify the paths to the directories containing the
 
 ## Usage
 
-!!! Example
+!!! example
 
     === "Python"
 
@@ -108,7 +108,7 @@ If you have your own dataset and would like to use it for training segmentation
 
 You can easily convert labels from the popular COCO dataset format to the YOLO format using the following code snippet:
 
-!!! Example
+!!! example
 
     === "Python"
 
@@ -130,7 +130,7 @@ Auto-annotation is an essential feature that allows you to generate a segmentati
 
 To auto-annotate your dataset using the Ultralytics framework, you can use the `auto_annotate` function as shown below:
 
-!!! Example
+!!! example
 
     === "Python"
 

docs/en/datasets/segment/package-seg.md

@@ -26,7 +26,7 @@ Package segmentation, facilitated by the Package Segmentation Dataset, is crucia
 
 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 Package Segmentation dataset, the `package-seg.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/package-seg.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/package-seg.yaml).
 
-!!! Example "ultralytics/cfg/datasets/package-seg.yaml"
+!!! example "ultralytics/cfg/datasets/package-seg.yaml"
 
     ```yaml
     --8<-- "ultralytics/cfg/datasets/package-seg.yaml"
@@ -36,7 +36,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
 
 To train Ultralytics YOLOv8n model on the Package Segmentation 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"
 
@@ -70,7 +70,7 @@ The Package Segmentation dataset comprises a varied collection of images and vid
 
 If you integrate the crack segmentation dataset into your research or development initiatives, please cite the following paper:
 
-!!! Quote ""
+!!! quote ""
 
     === "BibTeX"
 
@@ -101,7 +101,7 @@ The [Roboflow Package Segmentation Dataset](https://universe.roboflow.com/factor
 
 You can train an Ultralytics YOLOv8n model using both Python and CLI methods. Use the snippets below:
 
-!!! Example "Train Example"
+!!! example "Train Example"
 
     === "Python"