Fix gitignore to format Docs datasets (#16071)

Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

docs/en/datasets/obb/dota-v2.md

@@ -195,9 +195,7 @@ For more details on how to split and preprocess the DOTA images, refer to the [s
 ### What are the differences between DOTA-v1.0, DOTA-v1.5, and DOTA-v2.0?
 
 - **DOTA-v1.0**: Includes 15 common categories across 2,806 images with 188,282 instances. The dataset is split into training, validation, and testing sets.
-  
 - **DOTA-v1.5**: Builds upon DOTA-v1.0 by annotating very small instances (less than 10 pixels) and adding a new category, "container crane," totaling 403,318 instances.
-  
 - **DOTA-v2.0**: Expands further with annotations from Google Earth and GF-2 Satellite, featuring 11,268 images and 1,793,658 instances. It includes new categories like "airport" and "helipad."
 
 For a detailed comparison and additional specifics, check the [dataset versions section](#dataset-versions).

docs/en/datasets/obb/dota8.md

@@ -93,7 +93,7 @@ To train a YOLOv8n-obb model on the DOTA8 dataset for 100 epochs with an image s
 !!! Example "Train Example"
 
     === "Python"
-    
+
         ```python
         from ultralytics import YOLO
 
@@ -105,7 +105,7 @@ To train a YOLOv8n-obb model on the DOTA8 dataset for 100 epochs with an image s
         ```
 
     === "CLI"
-    
+
         ```bash
         # Start training from a pretrained *.pt model
         yolo obb train data=dota8.yaml model=yolov8n-obb.pt epochs=100 imgsz=640

docs/en/datasets/obb/index.md

@@ -109,7 +109,7 @@ Training a YOLOv8 model with OBBs involves ensuring your dataset is in the YOLO
 !!! Example
 
     === "Python"
-    
+
         ```python
         from ultralytics import YOLO
 
@@ -119,15 +119,14 @@ Training a YOLOv8 model with OBBs involves ensuring your dataset is in the YOLO
         # Train the model on the custom dataset
         results = model.train(data="your_dataset.yaml", epochs=100, imgsz=640)
         ```
-    
 
     === "CLI"
-    
+
         ```bash
         # Train a new YOLOv8n-OBB model on the custom dataset
         yolo obb train data=your_dataset.yaml model=yolov8n-obb.yaml epochs=100 imgsz=640
         ```
-        
+
 This ensures your model leverages the detailed OBB annotations for improved detection accuracy.
 
 ### What datasets are currently supported for OBB training in Ultralytics YOLO models?