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Fix gitignore to format Docs datasets (#16071)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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6
docs/en/datasets/index.md
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@ -155,6 +155,7 @@ By following these steps, you can contribute a new dataset that integrates well
### What datasets does Ultralytics support for object detection?
Ultralytics supports a wide variety of datasets for object detection, including:
- [COCO](detect/coco.md): A large-scale object detection, segmentation, and captioning dataset with 80 object categories.
- [LVIS](detect/lvis.md): An extensive dataset with 1203 object categories, designed for more fine-grained object detection and segmentation.
- [Argoverse](detect/argoverse.md): A dataset containing 3D tracking and motion forecasting data from urban environments with rich annotations.
@ -166,6 +167,7 @@ These datasets facilitate training robust models for various object detection ap
### How do I contribute a new dataset to Ultralytics?
Contributing a new dataset involves several steps:
1. **Collect Images**: Gather images from public databases or personal collections.
2. **Annotate Images**: Apply bounding boxes, segments, or keypoints, depending on the task.
3. **Export Annotations**: Convert annotations into the YOLO `*.txt` format.
@ -180,6 +182,7 @@ Visit [Contribute New Datasets](#contribute-new-datasets) for a comprehensive gu
### Why should I use Ultralytics Explorer for my dataset?
Ultralytics Explorer offers powerful features for dataset analysis, including:
- **Embeddings Generation**: Create vector embeddings for images.
- **Semantic Search**: Search for similar images using embeddings or AI.
- **SQL Queries**: Run advanced SQL queries for detailed data analysis.
@ -190,6 +193,7 @@ Explore the [Ultralytics Explorer](explorer/index.md) for more information and t
### What are the unique features of Ultralytics YOLO models for computer vision?
Ultralytics YOLO models provide several unique features:
- **Real-time Performance**: High-speed inference and training.
- **Versatility**: Suitable for detection, segmentation, classification, and pose estimation tasks.
- **Pretrained Models**: Access to high-performing, pretrained models for various applications.
@ -204,7 +208,7 @@ To optimize and zip a dataset using Ultralytics tools, follow this example code:
!!! Example "Optimize and Zip a Dataset"
=== "Python"
```python
from pathlib import Path