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docs/datasets/classify/caltech101.md

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-description: Learn about the Caltech-101 dataset, a collection of images for object recognition tasks in machine learning and computer vision algorithms.
-keywords: Caltech-101 Dataset, Object recognition tasks, Ultralytics YOLO Docs, training, testing, code snippets & examples, machine learning, computer vision
+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
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 # Caltech-101 Dataset

docs/datasets/classify/caltech256.md

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-description: Learn about the Caltech-256 dataset, a broad collection of images used for object classification tasks in machine learning and computer vision algorithms.
-keywords: Caltech-256, Dataset, Object Recognition, Image Classification, Convolutional Neural Networks, SVMs, YOLO, Deep Learning Models
+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
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 # Caltech-256 Dataset

docs/datasets/classify/cifar10.md

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-description: Learn about the CIFAR-10 dataset, a collection of images that are commonly used to train machine learning and computer vision algorithms.
-keywords: CIFAR-10 dataset, YOLO model training, image classification, deep learning, computer vision, object detection, machine learning, convolutional neural networks, Alex Krizhevsky
+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
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 # CIFAR-10 Dataset

docs/datasets/classify/cifar100.md

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-description: Learn about the CIFAR-100 dataset, a collection of images that are commonly used to train machine learning and computer vision algorithms.
-keywords: CIFAR-100 dataset, CIFAR-100 classes, CIFAR-100 structure, CIFAR-100 applications, CIFAR-100 usage, YOLO model training, machine learning, computer vision
+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
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 # CIFAR-100 Dataset

docs/datasets/classify/fashion-mnist.md

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-description: Learn about the Fashion-MNIST dataset, a large database of Zalando's article images used for training various image processing systems and machine learning models.
-keywords: Fashion-MNIST, dataset, machine learning, image classification, convolutional neural networks, benchmarking, Zalando's article images
+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
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 # Fashion-MNIST Dataset

docs/datasets/classify/imagenet.md

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-description: Learn about the ImageNet dataset, a large-scale database of annotated images commonly used for training deep learning models in computer vision tasks.
-keywords: ImageNet, dataset, deep learning, computer vision, YOLO models, training, object recognition, image classification, object detection, WordNet, synsets, ILSVRC
+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
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 # ImageNet Dataset

docs/datasets/classify/imagenet10.md

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-description: Learn about the ImageNet10 dataset, a compact subset of the original ImageNet dataset designed for quick testing, CI tests, and sanity checks.
-keywords: ImageNet10 dataset, ImageNet, small scale, subset, computer vision models, pipelines, testing, debugging, synsets, annotations, applications, structure, sample images, citations, acknowledgments, Ultralytics Docs
+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
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 # ImageNet10 Dataset

docs/datasets/classify/imagenette.md

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-description: Learn about the ImageNette dataset, a subset of 10 easily classified classes from the Imagenet dataset commonly used for training various image processing systems and machine learning models.
-keywords: ImageNette Dataset, ImageNette, training set, validation set, image classification, convolutional neural networks, machine learning, computer vision, ultralytics, yolov8n-cls.pt, python
+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
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 # ImageNette Dataset

docs/datasets/classify/imagewoof.md

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-description: Learn about the ImageWoof dataset, a subset of the ImageNet consisting of 10 challenging-to-classify dog breed classes.
-keywords: ImageWoof dataset, dog breed images, image classification, noisy labels, deep learning models, CNN training, fastai
+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
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 # ImageWoof Dataset

docs/datasets/classify/index.md

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-description: Learn how torchvision organizes classification image datasets. Use this code to create and train models. CLI and Python code shown.
-keywords: image classification, datasets, format, torchvision, YOLO, Ultralytics
+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
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 # Image Classification Datasets Overview

docs/datasets/classify/mnist.md

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-description: Learn about the MNIST dataset, a large database of handwritten digits commonly used for training various image processing systems and machine learning models.
-keywords: MNIST, EMNIST, dataset, handwritten digits, convolutional neural networks, support vector machines, machine learning, computer vision, image processing, benchmark data, Ultralytics
+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
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 # MNIST Dataset

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
 ---
 
 # 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
 ---
 
 # 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

docs/datasets/index.md

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-description: Ultralytics provides support for various datasets to facilitate multiple computer vision tasks. Check out our list of main datasets and their summaries.
-keywords: ultralytics, computer vision, object detection, instance segmentation, pose estimation, image classification, multi-object tracking
+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
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 # Datasets Overview

docs/datasets/pose/coco.md

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-description: Learn about the COCO-Pose dataset, designed to encourage research on pose estimation tasks with standardized evaluation metrics.
-keywords: COCO-Pose, COCO dataset, pose estimation, keypoints detection, computer vision, deep learning, YOLOv8n-pose, dataset configuration
+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
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 # COCO-Pose Dataset

docs/datasets/pose/coco8-pose.md

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-description: Test and debug object detection models with Ultralytics COCO8-Pose Dataset - a small, versatile pose detection dataset with 8 images.
-keywords: coco8-pose dataset, ultralytics, object detection, pose detection, yolo, hub
+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
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 # COCO8-Pose Dataset

docs/datasets/pose/index.md

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-description: Learn how to format your dataset for training YOLO models with Ultralytics YOLO format using our concise tutorial and example YAML files.
-keywords: pose estimation, datasets, supported formats, YAML file, object class index, keypoints, ultralytics YOLO format
+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
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 # Pose Estimation Datasets Overview
@@ -125,4 +125,4 @@ from ultralytics.data.converter import convert_coco
 convert_coco(labels_dir='../coco/annotations/', use_keypoints=True)
 ```
 
-This conversion tool can be used to convert the COCO dataset or any dataset in the COCO format to the Ultralytics YOLO format. The `use_keypoints` parameter specifies whether to include keypoints (for pose estimation) in the converted labels.
+This conversion tool can be used to convert the COCO dataset or any dataset in the COCO format to the Ultralytics YOLO format. The `use_keypoints` parameter specifies whether to include keypoints (for pose estimation) in the converted labels.

docs/datasets/segment/coco.md

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-description: Learn about the COCO-Seg dataset, designed for simple training of YOLO models on instance segmentation tasks.
-keywords: COCO-Seg, COCO, instance segmentation, segmentation annotations, computer vision, deep learning, data science, YOLO models, image size, open-source datasets
+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
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 # COCO-Seg Dataset

docs/datasets/segment/coco8-seg.md

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-description: Test and debug segmentation models on small, versatile COCO8-Seg instance segmentation dataset, now available for use with YOLOv8 and Ultralytics HUB.
-keywords: Ultralytics, COCO8-Seg, instance segmentation dataset, segmentation models, new detection approaches, COCO train 2017 set
+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
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 # COCO8-Seg Dataset

docs/datasets/segment/index.md

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-description: Learn about the Ultralytics YOLO dataset format for segmentation models. Use YAML to train Detection Models. Convert COCO to YOLO format using Python.
-keywords: instance segmentation datasets, yolov8 segmentations, yaml dataset format, auto annotation, convert label formats
+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
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 # Instance Segmentation Datasets Overview

docs/datasets/track/index.md

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-description: Discover the datasets compatible with Multi-Object Detector. Train your trackers and make your detections more efficient with Ultralytics' YOLO.
-keywords: multi-object tracking, dataset format, ultralytics yolo, object detection, segmentation, pose model, python, cli
+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
 ---
 
 # Multi-object Tracking Datasets Overview