Update HUB SDK Docs (#13309)

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

docs/en/datasets/classify/caltech101.md

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-description: Learn about the Caltech-101 dataset, its structure and uses in machine learning. Includes instructions to train a YOLO model using this dataset.
-keywords: Caltech-101, dataset, YOLO training, machine learning, object recognition, ultralytics
+description: Explore the widely-used Caltech-101 dataset with 9,000 images across 101 categories. Ideal for object recognition tasks in machine learning and computer vision.
+keywords: Caltech-101, dataset, object recognition, machine learning, computer vision, YOLO, deep learning, research, AI
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 # Caltech-101 Dataset

docs/en/datasets/classify/caltech256.md

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-description: Explore the Caltech-256 dataset, a diverse collection of images used for object recognition tasks in machine learning. Learn to train a YOLO model on the dataset.
-keywords: Ultralytics, YOLO, Caltech-256, dataset, object recognition, machine learning, computer vision, deep learning
+description: Explore the Caltech-256 dataset, featuring 30,000 images across 257 categories, ideal for training and testing object recognition algorithms.
+keywords: Caltech-256 dataset, object classification, image dataset, machine learning, computer vision, deep learning, YOLO, training dataset
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 # Caltech-256 Dataset

docs/en/datasets/classify/cifar10.md

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-description: Explore the CIFAR-10 dataset, widely used for training in machine learning and computer vision, and learn how to use it with Ultralytics YOLO.
-keywords: CIFAR-10, dataset, machine learning, image classification, computer vision, YOLO, Ultralytics, training, testing, deep learning, Convolutional Neural Networks, Support Vector Machines
+description: Explore the CIFAR-10 dataset, featuring 60,000 color images in 10 classes. Learn about its structure, applications, and how to train models using YOLO.
+keywords: CIFAR-10, dataset, machine learning, computer vision, image classification, YOLO, deep learning, neural networks
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 # CIFAR-10 Dataset

docs/en/datasets/classify/cifar100.md

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-description: Discover how to leverage the CIFAR-100 dataset for machine learning and computer vision tasks with YOLO. Gain insights on its structure, use, and utilization for model training.
-keywords: Ultralytics, YOLO, CIFAR-100 dataset, image classification, machine learning, computer vision, YOLO model training
+description: Explore the CIFAR-100 dataset, consisting of 60,000 32x32 color images across 100 classes. Ideal for machine learning and computer vision tasks.
+keywords: CIFAR-100, dataset, machine learning, computer vision, image classification, deep learning, YOLO, training, testing, Alex Krizhevsky
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 # CIFAR-100 Dataset

docs/en/datasets/classify/fashion-mnist.md

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-description: Learn how to use the Fashion-MNIST dataset for image classification with the Ultralytics YOLO model. Covers dataset structure, labels, applications, and usage.
-keywords: Ultralytics, YOLO, Fashion-MNIST, dataset, image classification, machine learning, deep learning, neural networks, training, testing
+description: Explore the Fashion-MNIST dataset, a modern replacement for MNIST with 70,000 Zalando article images. Ideal for benchmarking machine learning models.
+keywords: Fashion-MNIST, image classification, Zalando dataset, machine learning, deep learning, CNN, dataset overview
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 # Fashion-MNIST Dataset

docs/en/datasets/classify/imagenet.md

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-description: Understand how to use ImageNet, an extensive annotated image dataset for object recognition research, with Ultralytics YOLO models. Learn about its structure, usage, and significance in computer vision.
-keywords: Ultralytics, YOLO, ImageNet, dataset, object recognition, deep learning, computer vision, machine learning, dataset training, model training, image classification, object detection
+description: Explore the extensive ImageNet dataset and discover its role in advancing deep learning in computer vision. Access pretrained models and training examples.
+keywords: ImageNet, deep learning, visual recognition, computer vision, pretrained models, YOLO, dataset, object detection, image classification
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 # ImageNet Dataset

docs/en/datasets/classify/imagenet10.md

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-description: Explore the compact ImageNet10 Dataset developed by Ultralytics. Ideal for fast testing of computer vision training pipelines and CV model sanity checks.
-keywords: Ultralytics, YOLO, ImageNet10 Dataset, Image detection, Deep Learning, ImageNet, AI model testing, Computer vision, Machine learning
+description: Discover ImageNet10 a compact version of ImageNet for rapid model testing and CI checks. Perfect for quick evaluations in computer vision tasks.
+keywords: ImageNet10, ImageNet, Ultralytics, CI tests, sanity checks, training pipelines, computer vision, deep learning, dataset
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 # ImageNet10 Dataset

docs/en/datasets/classify/imagenette.md

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-description: Learn about the ImageNette dataset and its usage in deep learning model training. Find code snippets for model training and explore ImageNette datatypes.
-keywords: ImageNette dataset, Ultralytics, YOLO, Image classification, Machine Learning, Deep learning, Training code snippets, CNN, ImageNette160, ImageNette320
+description: Explore the ImageNette dataset, a subset of ImageNet with 10 classes for efficient training and evaluation of image classification models. Ideal for ML and CV projects.
+keywords: ImageNette dataset, ImageNet subset, image classification, machine learning, deep learning, YOLO, Convolutional Neural Networks, ML dataset, education, training
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 # ImageNette Dataset

docs/en/datasets/classify/imagewoof.md

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-description: Explore the ImageWoof dataset, designed for challenging dog breed classification. Train AI models with Ultralytics YOLO using this dataset.
-keywords: ImageWoof, image classification, dog breeds, machine learning, deep learning, Ultralytics, YOLO, dataset
+description: Explore the ImageWoof dataset, a challenging subset of ImageNet focusing on 10 dog breeds, designed to enhance image classification models. Learn more on Ultralytics Docs.
+keywords: ImageWoof dataset, ImageNet subset, dog breeds, image classification, deep learning, machine learning, Ultralytics, training dataset, noisy labels
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 # ImageWoof Dataset

docs/en/datasets/classify/index.md

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-description: Explore image classification datasets supported by Ultralytics, learn the standard dataset format, and set up your own dataset for training models.
-keywords: Ultralytics, image classification, dataset, machine learning, CIFAR-10, ImageNet, MNIST, torchvision
+description: Learn how to structure datasets for YOLO classification tasks. Detailed folder structure and usage examples for effective training.
+keywords: YOLO, image classification, dataset structure, CIFAR-10, Ultralytics, machine learning, training data, model evaluation
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 # Image Classification Datasets Overview

docs/en/datasets/classify/mnist.md

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-description: Detailed guide on the MNIST Dataset, a benchmark in the machine learning community for image classification tasks. Learn about its structure, usage and application.
-keywords: MNIST dataset, Ultralytics, image classification, machine learning, computer vision, deep learning, AI, dataset guide
+description: Explore the MNIST dataset, a cornerstone in machine learning for handwritten digit recognition. Learn about its structure, features, and applications.
+keywords: MNIST, dataset, handwritten digits, image classification, deep learning, machine learning, training set, testing set, NIST
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 # MNIST Dataset

docs/en/datasets/detect/african-wildlife.md

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-description: African Wildlife objects detection, a leading dataset for object detection in forests, integrates with Ultralytics. Discover ways to use it for training YOLO models.
-keywords: Ultralytics, African Wildlife dataset, object detection, YOLO, YOLO model training, object tracking, computer vision, deep learning models, forest research, animals tracking
+description: Explore our African Wildlife Dataset featuring images of buffalo, elephant, rhino, and zebra for training computer vision models. Ideal for research and conservation.
+keywords: African Wildlife Dataset, South African animals, object detection, computer vision, YOLOv8, wildlife research, conservation, dataset
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 # African Wildlife Dataset

docs/en/datasets/detect/argoverse.md

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-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
+description: Explore the comprehensive Argoverse dataset by Argo AI for 3D tracking, motion forecasting, and stereo depth estimation in autonomous driving research.
+keywords: Argoverse dataset, autonomous driving, 3D tracking, motion forecasting, stereo depth estimation, Argo AI, LiDAR point clouds, high-resolution images, HD maps
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 # Argoverse Dataset

docs/en/datasets/detect/brain-tumor.md

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-description: Brain tumor detection, a leading dataset for medical imaging, integrates with Ultralytics. Discover ways to use it for training YOLO models.
-keywords: Ultralytics, Brain Tumor dataset, object detection, YOLO, YOLO model training, object tracking, computer vision, deep learning models
+description: Explore the brain tumor detection dataset with MRI/CT images. Essential for training AI models for early diagnosis and treatment planning.
+keywords: brain tumor dataset, MRI scans, CT scans, brain tumor detection, medical imaging, AI in healthcare, computer vision, early diagnosis, treatment planning
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 # Brain Tumor Dataset

docs/en/datasets/detect/coco.md

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-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
+description: Explore the COCO dataset for object detection and segmentation. Learn about its structure, usage, pretrained models, and key features.
+keywords: COCO dataset, object detection, segmentation, benchmarking, computer vision, pose estimation, YOLO models, COCO annotations
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 # COCO Dataset

docs/en/datasets/detect/coco8.md

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-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
+description: Explore the Ultralytics COCO8 dataset, a versatile and manageable set of 8 images perfect for testing object detection models and training pipelines.
+keywords: COCO8, Ultralytics, dataset, object detection, YOLOv8, training, validation, machine learning, computer vision
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 # COCO8 Dataset

docs/en/datasets/detect/globalwheat2020.md

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-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
+description: Explore the Global Wheat Head Dataset to develop accurate wheat head detection models. Includes training images, annotations, and usage for crop management.
+keywords: Global Wheat Head Dataset, wheat head detection, wheat phenotyping, crop management, deep learning, object detection, training datasets
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 # Global Wheat Head Dataset

docs/en/datasets/detect/index.md

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-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
+description: Learn about dataset formats compatible with Ultralytics YOLO for robust object detection. Explore supported datasets and learn how to convert formats.
+keywords: Ultralytics, YOLO, object detection datasets, dataset formats, COCO, dataset conversion, training datasets
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 # Object Detection Datasets Overview

docs/en/datasets/detect/lvis.md

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-description: Learn how LVIS, a leading dataset for object detection and segmentation, integrates with Ultralytics. Discover ways to use it for training YOLO models.
-keywords: Ultralytics, LVIS dataset, object detection, YOLO, YOLO model training, image segmentation, computer vision, deep learning models
+description: Discover the LVIS dataset by Facebook AI Research, a benchmark for object detection and instance segmentation with a large, diverse vocabulary. Learn how to utilize it.
+keywords: LVIS dataset, object detection, instance segmentation, Facebook AI Research, YOLO, computer vision, model training, LVIS examples
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 # LVIS Dataset

docs/en/datasets/detect/objects365.md

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-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
+description: Explore the Objects365 Dataset with 2M images and 30M bounding boxes across 365 categories. Enhance your object detection models with diverse, high-quality data.
+keywords: Objects365 dataset, object detection, machine learning, deep learning, computer vision, annotated images, bounding boxes, YOLOv8, high-resolution images, dataset configuration
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 # Objects365 Dataset

docs/en/datasets/detect/open-images-v7.md

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-description: Dive into Google's Open Images V7, a comprehensive dataset offering a broad scope for computer vision research. Understand its usage with deep learning models.
-keywords: Open Images V7, object detection, segmentation masks, visual relationships, localized narratives, computer vision, deep learning, annotations, bounding boxes
+description: Explore the comprehensive Open Images V7 dataset by Google. Learn about its annotations, applications, and use YOLOv8 pretrained models for computer vision tasks.
+keywords: Open Images V7, Google dataset, computer vision, YOLOv8 models, object detection, image segmentation, visual relationships, AI research, Ultralytics
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 # Open Images V7 Dataset

docs/en/datasets/detect/roboflow-100.md

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-description: Get to know Roboflow 100, a comprehensive object detection benchmark that brings together 100 datasets from different domains.
-keywords: Ultralytics, YOLOv8, YOLO models, Roboflow 100, object detection, benchmark, computer vision, datasets, deep learning models
+description: Explore the Roboflow 100 dataset featuring 100 diverse datasets designed to test object detection models across various domains, from healthcare to video games.
+keywords: Roboflow 100, Ultralytics, object detection, dataset, benchmarking, machine learning, computer vision, diverse datasets, model evaluation
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 # Roboflow 100 Dataset

docs/en/datasets/detect/signature.md

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-description: Signature Detection Dataset, a leading dataset for detecting signatures in documents, integrates with Ultralytics. Discover ways to use it for training YOLO models.
-keywords: Ultralytics, Signature Detection Dataset, object detection, YOLO, YOLO model training, document analysis, computer vision, deep learning models, signature tracking, document verification
+description: Discover the Signature Detection Dataset for training models to identify and verify human signatures in various documents. Perfect for document verification and fraud prevention.
+keywords: Signature Detection Dataset, document verification, fraud detection, computer vision, YOLOv8, Ultralytics, annotated signatures, training dataset
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 # Signature Detection Dataset

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

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-description: Explore the SKU-110k dataset of 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
+description: Explore the SKU-110k dataset of densely packed retail shelf images, perfect for training and evaluating deep learning models in object detection tasks.
+keywords: SKU-110k, dataset, object detection, retail shelf images, deep learning, computer vision, model training
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 # SKU-110k Dataset

docs/en/datasets/detect/visdrone.md

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-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
+description: Explore the VisDrone Dataset, a large-scale benchmark for drone-based image and video analysis with over 2.6 million annotations for objects like pedestrians and vehicles.
+keywords: VisDrone, drone dataset, computer vision, object detection, object tracking, crowd counting, machine learning, deep learning
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 # VisDrone Dataset

docs/en/datasets/detect/voc.md

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-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
+description: Discover the PASCAL VOC dataset, essential for object detection, segmentation, and classification. Learn key features, applications, and usage tips.
+keywords: PASCAL VOC, VOC dataset, object detection, segmentation, classification, YOLO, Faster R-CNN, Mask R-CNN, image annotations, computer vision
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 # VOC Dataset

docs/en/datasets/detect/xview.md

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-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
+description: Explore the xView dataset, a rich resource of 1M+ object instances in high-resolution satellite imagery. Enhance detection, learning efficiency, and more.
+keywords: xView dataset, overhead imagery, satellite images, object detection, high resolution, bounding boxes, computer vision, TensorFlow, PyTorch, dataset structure
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 # xView Dataset

docs/en/datasets/explorer/api.md

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-description: Explore and analyze CV datasets with Ultralytics Explorer API, offering SQL, vector similarity, and semantic searches for efficient dataset insights.
-keywords: Ultralytics Explorer API, Dataset Exploration, SQL Queries, Vector Similarity Search, Semantic Search, Embeddings Table, Image Similarity, Python API for Datasets, CV Dataset Analysis, LanceDB Integration
+description: Explore the Ultralytics Explorer API for dataset exploration with SQL queries, vector similarity search, and semantic search. Learn installation and usage tips.
+keywords: Ultralytics, Explorer API, dataset exploration, SQL queries, similarity search, semantic search, Python API, LanceDB, embeddings, data analysis
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 # Ultralytics Explorer API

docs/en/datasets/explorer/dashboard.md

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-description: Learn about Ultralytics Explorer GUI for semantic search, SQL queries, and AI-powered natural language search in CV datasets.
-keywords: Ultralytics, Explorer GUI, semantic search, vector similarity search, AI queries, SQL queries, computer vision, dataset exploration, image search, OpenAI integration
+description: Unlock advanced data exploration with Ultralytics Explorer GUI. Utilize semantic search, run SQL queries, and ask AI for natural language data insights.
+keywords: Ultralytics Explorer GUI, semantic search, vector similarity, SQL queries, AI, natural language search, data exploration, machine learning, OpenAI, LLMs
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 # Explorer GUI

docs/en/datasets/explorer/index.md

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-description: Discover the Ultralytics Explorer, a versatile tool and Python API for CV dataset exploration, enabling semantic search, SQL queries, and vector similarity searches.
-keywords: Ultralytics Explorer, CV Dataset Tools, Semantic Search, SQL Dataset Queries, Vector Similarity, Python API, GUI Explorer, Dataset Analysis, YOLO Explorer, Data Insights
+description: Discover Ultralytics Explorer for semantic search, SQL queries, vector similarity, and natural language dataset exploration. Enhance your CV datasets effortlessly.
+keywords: Ultralytics Explorer, CV datasets, semantic search, SQL queries, vector similarity, dataset visualization, python API, machine learning, computer vision
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 # Ultralytics Explorer

docs/en/datasets/index.md

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-description: Explore various computer vision datasets supported by Ultralytics for object detection, segmentation, pose estimation, image classification, and multi-object tracking.
-keywords: computer vision, datasets, Ultralytics, YOLO, object detection, instance segmentation, pose estimation, image classification, multi-object tracking
+description: Explore Ultralytics' diverse datasets for vision tasks like detection, segmentation, classification, and more. Enhance your projects with high-quality annotated data.
+keywords: Ultralytics, datasets, computer vision, object detection, instance segmentation, pose estimation, image classification, multi-object tracking
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 # Datasets Overview

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

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-description: Delve into DOTA, an Oriented Bounding Box (OBB) aerial imagery dataset with 1.7 million instances and 11,268 images.
-keywords: DOTA v1, DOTA v1.5, DOTA v2, object detection, aerial images, computer vision, deep learning, annotations, oriented bounding boxes, OBB
+description: Explore the DOTA dataset for object detection in aerial images, featuring 1.7M Oriented Bounding Boxes across 18 categories. Ideal for aerial image analysis.
+keywords: DOTA dataset, object detection, aerial images, oriented bounding boxes, OBB, DOTA v1.0, DOTA v1.5, DOTA v2.0, multiscale detection, Ultralytics
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 # DOTA Dataset with OBB

docs/en/datasets/obb/dota8.md

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-description: Discover the versatile DOTA8 dataset, perfect for testing and debugging oriented detection models. Learn how to get started with YOLOv8-obb model training.
-keywords: Ultralytics, YOLOv8, oriented detection, DOTA8 dataset, dataset, model training, YAML
+description: Explore the DOTA8 dataset - a small, versatile oriented object detection dataset ideal for testing and debugging object detection models using Ultralytics YOLOv8.
+keywords: DOTA8 dataset, Ultralytics, YOLOv8, object detection, debugging, training models, oriented object detection, dataset YAML
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 # DOTA8 Dataset

docs/en/datasets/obb/index.md

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-description: Dive deep into various oriented bounding box (OBB) dataset formats compatible with Ultralytics YOLO models. Grasp the nuances of using and converting datasets to this format.
-keywords: Ultralytics, YOLO, oriented bounding boxes, OBB, dataset formats, label formats, DOTA v2, data conversion
+description: Discover OBB dataset formats for Ultralytics YOLO models. Learn about their structure, application, and format conversions to enhance your object detection training.
+keywords: Oriented Bounding Box, OBB Datasets, YOLO, Ultralytics, Object Detection, Dataset Formats
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 # Oriented Bounding Box (OBB) Datasets Overview

docs/en/datasets/pose/coco.md

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-description: Detailed guide on the special COCO-Pose Dataset in Ultralytics. Learn about its key features, structure, and usage in pose estimation tasks with YOLO.
-keywords: Ultralytics YOLO, COCO-Pose Dataset, Deep Learning, Pose Estimation, Training Models, Dataset YAML, openpose, YOLO
+description: Explore the COCO-Pose dataset for advanced pose estimation. Learn about datasets, pretrained models, metrics, and applications for training with YOLO.
+keywords: COCO-Pose, pose estimation, dataset, keypoints, COCO Keypoints 2017, YOLO, deep learning, computer vision
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 # COCO-Pose Dataset

docs/en/datasets/pose/coco8-pose.md

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-description: Discover the versatile COCO8-Pose dataset, perfect for testing and debugging pose detection models. Learn how to get started with YOLOv8-pose model training.
-keywords: Ultralytics, YOLOv8, pose detection, COCO8-Pose dataset, dataset, model training, YAML
+description: Explore the compact, versatile COCO8-Pose dataset for testing and debugging object detection models. Ideal for quick experiments with YOLOv8.
+keywords: COCO8-Pose, Ultralytics, pose detection dataset, object detection, YOLOv8, machine learning, computer vision, training data
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 # COCO8-Pose Dataset

docs/en/datasets/pose/index.md

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-description: Understand the YOLO pose dataset format and learn to use Ultralytics datasets to train your pose estimation models effectively.
-keywords: Ultralytics, YOLO, pose estimation, datasets, training, YAML, keypoints, COCO-Pose, COCO8-Pose, data conversion
+description: Learn about Ultralytics YOLO format for pose estimation datasets, supported formats, COCO-Pose, COCO8-Pose, Tiger-Pose, and how to add your own dataset.
+keywords: pose estimation, Ultralytics, YOLO format, COCO-Pose, COCO8-Pose, Tiger-Pose, dataset conversion, keypoints
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 # Pose Estimation Datasets Overview

docs/en/datasets/pose/tiger-pose.md

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-description: Discover the versatile Tiger-Pose dataset, perfect for testing and debugging pose detection models. Learn how to get started with YOLOv8-pose model training.
-keywords: Ultralytics, YOLOv8, pose detection, COCO8-Pose dataset, dataset, model training, YAML
+description: Explore Ultralytics Tiger-Pose dataset with 263 diverse images. Ideal for testing, training, and refining pose estimation algorithms.
+keywords: Ultralytics, Tiger-Pose, dataset, pose estimation, YOLOv8, training data, machine learning, neural networks
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 # Tiger-Pose Dataset

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

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-description: Explore the Carparts Segmentation using Ultralytics YOLOv8 Dataset, a large-scale benchmark for Vehicle Maintenance, and learn how to train a YOLO model using it.
-keywords: CarParts Segmentation Dataset, Ultralytics, Vehicle Analytics, Spare parts Detection, YOLO model, object detection, object tracking
+description: Explore Roboflow's Carparts Segmentation Dataset for automotive AI applications. Enhance your segmentation models with rich, annotated data.
+keywords: Carparts Segmentation Dataset, Roboflow, computer vision, automotive AI, vehicle maintenance, Ultralytics
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 # Roboflow Universe Carparts Segmentation Dataset

docs/en/datasets/segment/coco.md

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-description: Explore the possibilities of the COCO-Seg dataset, designed for object instance segmentation and YOLO model training. Discover key features, dataset structure, applications, and usage.
-keywords: Ultralytics, YOLO, COCO-Seg, dataset, instance segmentation, model training, deep learning, computer vision
+description: Explore the COCO-Seg dataset, an extension of COCO, with detailed segmentation annotations. Learn how to train YOLO models with COCO-Seg.
+keywords: COCO-Seg, dataset, YOLO models, instance segmentation, object detection, COCO dataset, YOLOv8, computer vision, Ultralytics, machine learning
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 # COCO-Seg Dataset

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

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-description: 'Discover the COCO8-Seg: a compact but versatile instance segmentation dataset ideal for testing Ultralytics YOLOv8 detection approaches. Complete usage guide included.'
-keywords: COCO8-Seg dataset, Ultralytics, YOLOv8, instance segmentation, dataset configuration, YAML, YOLOv8n-seg model, mosaiced dataset images
+description: Discover the versatile and manageable COCO8-Seg dataset by Ultralytics, ideal for testing and debugging segmentation models or new detection approaches.
+keywords: COCO8-Seg, Ultralytics, segmentation dataset, YOLOv8, COCO 2017, model training, computer vision, dataset configuration
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 # COCO8-Seg Dataset

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

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-description: Explore the Crack Segmentation using Ultralytics YOLOv8 Dataset, a large-scale benchmark for road safety analysis, and learn how to train a YOLO model using it.
-keywords: Crack Segmentation Dataset, Ultralytics, road cracks monitoring, YOLO model, object detection, object tracking, road safety
+description: Explore the extensive Roboflow Crack Segmentation Dataset, perfect for transportation and public safety studies or self-driving car model development.
+keywords: Roboflow, Crack Segmentation Dataset, Ultralytics, transportation safety, public safety, self-driving cars, computer vision, road safety, infrastructure maintenance, dataset
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 # Roboflow Universe Crack Segmentation Dataset

docs/en/datasets/segment/index.md

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-description: Learn how Ultralytics YOLO supports various dataset formats for instance segmentation. This guide includes information on data conversions, auto-annotations, and dataset usage.
-keywords: Ultralytics, YOLO, Instance Segmentation, Dataset, YAML, COCO, Auto-Annotation, Image Segmentation
+description: Explore the supported dataset formats for Ultralytics YOLO and learn how to prepare and use datasets for training object segmentation models.
+keywords: Ultralytics, YOLO, instance segmentation, dataset formats, auto-annotation, COCO, segmentation models, training data
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 # Instance Segmentation Datasets Overview

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

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-description: Explore the Package Segmentation using Ultralytics YOLOv8 Dataset, a large-scale benchmark for logistics, and learn how to train a YOLO model using it.
-keywords: Packet Segmentation Dataset, Ultralytics, Manufacturing, Logistics, YOLO model, object detection, object tracking
+description: Explore Roboflow's Package Segmentation Dataset. Optimize logistics and enhance vision models with curated images for package identification and sorting.
+keywords: Roboflow, Package Segmentation Dataset, computer vision, package identification, logistics, warehouse automation, segmentation models, training data
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 # Roboflow Universe Package Segmentation Dataset

docs/en/datasets/track/index.md

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-description: Understand multi-object tracking datasets, upcoming features and how to use them with YOLO in Python and CLI. Dive in now!.
-keywords: Ultralytics, YOLO, multi-object tracking, datasets, detection, segmentation, pose models, Python, CLI
+description: Learn how to use Multi-Object Tracking with YOLO. Explore dataset formats and see upcoming features for training trackers. Start with Python or CLI examples.
+keywords: YOLO, Multi-Object Tracking, Tracking Datasets, Python Tracking Example, CLI Tracking Example, Object Detection, Ultralytics, AI, Machine Learning
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 # Multi-object Tracking Datasets Overview