Update docs metadata (#3781)

docs/datasets/detect/argoverse.md

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-description: Learn about the Argoverse dataset, a rich dataset designed to support research in autonomous driving tasks such as 3D tracking, motion forecasting, and stereo depth estimation.
-keywords: Argoverse Dataset, Sensor Dataset, Autonomous Driving Research, Deep Learning Models, YOLOv8n Model, 3D Tracking, Motion Forecasting, Stereo Depth Estimation, Labeled 3D Object Tracks, High-Quality Sensor Data, Richly Annotated HD Maps
+description: Explore Argoverse, a comprehensive dataset for autonomous driving tasks including 3D tracking, motion forecasting and depth estimation used in YOLO.
+keywords: Argoverse dataset, autonomous driving, YOLO, 3D tracking, motion forecasting, LiDAR data, HD maps, ultralytics documentation
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 # Argoverse Dataset

docs/datasets/detect/coco.md

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-description: Learn about the COCO dataset, designed to encourage research on object detection, segmentation, and captioning with standardized evaluation metrics.
-keywords: COCO dataset, object detection, segmentation, captioning, deep learning models, computer vision, benchmarking, data annotations, COCO Consortium
+description: Learn how COCO, a leading dataset for object detection and segmentation, integrates with Ultralytics. Discover ways to use it for training YOLO models.
+keywords: Ultralytics, COCO dataset, object detection, YOLO, YOLO model training, image segmentation, computer vision, deep learning models
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 # COCO Dataset

docs/datasets/detect/coco8.md

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-description: Get started with Ultralytics COCO8. Ideal for testing and debugging object detection models or experimenting with new detection approaches.
-keywords: Ultralytics, COCO8, object detection dataset, YAML file format, dataset usage, COCO dataset, acknowledgments
+description: Discover the benefits of using the practical and diverse COCO8 dataset for object detection model testing. Learn to configure and use it via Ultralytics HUB and YOLOv8.
+keywords: Ultralytics, COCO8 dataset, object detection, model testing, dataset configuration, detection approaches, sanity check, training pipelines, YOLOv8
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 # COCO8 Dataset

docs/datasets/detect/globalwheat2020.md

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-description: Learn about the Global Wheat Head Dataset, aimed at supporting the development of accurate wheat head models for applications in wheat phenotyping and crop management.
-keywords: Global Wheat Head Dataset, wheat head detection, wheat phenotyping, crop management, object detection, deep learning models, dataset structure, annotations, sample data, citations and acknowledgments
+description: Understand how to utilize the vast Global Wheat Head Dataset for building wheat head detection models. Features, structure, applications, usage, sample data, and citation.
+keywords: Ultralytics, YOLO, Global Wheat Head Dataset, wheat head detection, plant phenotyping, crop management, deep learning, outdoor images, annotations, YAML configuration
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 # Global Wheat Head Dataset

docs/datasets/detect/index.md

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-description: Explore supported dataset formats for training YOLO detection models, including Ultralytics YOLO and COCO. This guide covers various dataset formats and their specific configurations for effective object detection training.
-keywords: object detection, datasets, formats, Ultralytics YOLO, COCO, label format, dataset file format, dataset definition, YOLO dataset, model configuration
+description: Navigate through supported dataset formats, methods to utilize them and how to add your own datasets. Get insights on porting or converting label formats.
+keywords: Ultralytics, YOLO, datasets, object detection, dataset formats, label formats, data conversion
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 # Object Detection Datasets Overview

docs/datasets/detect/objects365.md

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-description: Discover the Objects365 dataset, designed for object detection research with a focus on diverse objects, featuring 365 categories, 2 million images, and 30 million bounding boxes.
-keywords: Objects365 dataset, object detection, computer vision, deep learning, Ultralytics Docs
+description: Discover the Objects365 dataset, a wide-scale, high-quality resource for object detection research. Learn to use it with the Ultralytics YOLO model.
+keywords: Objects365, object detection, Ultralytics, dataset, YOLO, bounding boxes, annotations, computer vision, deep learning, training models
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 # Objects365 Dataset

docs/datasets/detect/sku-110k.md

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-description: Explore the SKU-110k dataset, designed for object detection in densely packed retail shelf images, featuring over 110k unique SKU categories and annotations.
-keywords: SKU-110k, object detection, retail shelves, dataset, computer vision
+description: 'Explore the SKU-110k dataset: densely packed retail shelf images for object detection research. Learn how to use it with Ultralytics.'
+keywords: SKU-110k dataset, object detection, retail shelf images, Ultralytics, YOLO, computer vision, deep learning models
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 # SKU-110k Dataset

docs/datasets/detect/visdrone.md

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-description: Discover the VisDrone dataset, a comprehensive benchmark for drone-based computer vision tasks, including object detection, tracking, and crowd counting.
-keywords: VisDrone Dataset, Ultralytics YOLO Docs, AISKYEYE, Lab of Machine Learning and Data Mining, Computer Vision tasks, drone-based image analysis, object detection, object tracking, crowd counting, YOLOv8n model
+description: Explore the VisDrone Dataset, a large-scale benchmark for drone-based image analysis, and learn how to train a YOLO model using it.
+keywords: VisDrone Dataset, Ultralytics, drone-based image analysis, YOLO model, object detection, object tracking, crowd counting
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 # VisDrone Dataset

docs/datasets/detect/voc.md

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-description: Learn about the VOC dataset, designed to encourage research on object detection, segmentation, and classification with standardized evaluation metrics.
-keywords: PASCAL VOC dataset, object detection, segmentation, classification, computer vision, deep learning, benchmarking, VOC2007, VOC2012, mean Average Precision, mAP, PASCAL VOC evaluation server, trained models, YAML, YAML file, VOC.yaml, training, YOLOv8n model, model training, image size, annotations, object bounding boxes, segmentation masks, instance segmentation, SSD, Mask R-CNN, yolov8n.pt, mosaicing, PASCAL VOC Consortium
+description: A complete guide to the PASCAL VOC dataset used for object detection, segmentation and classification tasks with relevance to YOLO model training.
+keywords: Ultralytics, PASCAL VOC dataset, object detection, segmentation, image classification, YOLO, model training, VOC.yaml, deep learning
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 # VOC Dataset

docs/datasets/detect/xview.md

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-description: Discover the xView Dataset, a large-scale overhead imagery dataset for object detection tasks, featuring 1M instances, 60 classes, and high-resolution images.
-keywords: xView dataset, overhead imagery, computer vision, deep learning models, satellite imagery analysis, object detection
+description: Explore xView, a large-scale, high resolution satellite imagery dataset for object detection. Dive into dataset structure, usage examples & its potential applications.
+keywords: Ultralytics, YOLO, computer vision, xView dataset, satellite imagery, object detection, overhead imagery, training, deep learning, dataset YAML
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 # xView Dataset