Docs updates for HUB, YOLOv4, YOLOv7, NAS (#3174)

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

docs/datasets/classify/caltech101.md

@@ -1,6 +1,7 @@
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 comments: true
 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
 ---
 
 # Caltech-101 Dataset

docs/datasets/classify/caltech256.md

@@ -1,6 +1,7 @@
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 comments: true
 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
 ---
 
 # Caltech-256 Dataset

docs/datasets/classify/cifar10.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
 ---
 
 # CIFAR-10 Dataset

docs/datasets/classify/cifar100.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
 ---
 
 # CIFAR-100 Dataset

docs/datasets/classify/fashion-mnist.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
 ---
 
 # Fashion-MNIST Dataset
@@ -75,4 +76,4 @@ The example showcases the variety and complexity of the images in the Fashion-MN
 
 ## Acknowledgments
 
-If you use the Fashion-MNIST dataset in your research or development work, please acknowledge the dataset by linking to the [GitHub repository](https://github.com/zalandoresearch/fashion-mnist). This dataset was made available by Zalando Research.
+If you use the Fashion-MNIST dataset in your research or development work, please acknowledge the dataset by linking to the [GitHub repository](https://github.com/zalandoresearch/fashion-mnist). This dataset was made available by Zalando Research.

docs/datasets/classify/imagenet.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
 ---
 
 # ImageNet Dataset

docs/datasets/classify/imagenet10.md

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 ---
 comments: true
 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
 ---
 
 # ImageNet10 Dataset

docs/datasets/classify/imagenette.md

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 ---
 comments: true
 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
 ---
 
 # ImageNette Dataset

docs/datasets/classify/imagewoof.md

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 ---
 comments: true
 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
 ---
 
 # ImageWoof Dataset

docs/datasets/classify/index.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
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 # Image Classification Datasets Overview

docs/datasets/classify/mnist.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
 ---
 
 # MNIST Dataset

docs/datasets/detect/argoverse.md

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 ---
 comments: true
 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
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 # Argoverse Dataset

docs/datasets/detect/coco.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
 ---
 
 # COCO Dataset

docs/datasets/detect/coco8.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
 ---
 
 # COCO8 Dataset

docs/datasets/detect/globalwheat2020.md

@@ -1,6 +1,7 @@
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 comments: true
 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
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 # Global Wheat Head Dataset

docs/datasets/detect/index.md

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 ---
 comments: true
 description: Learn about supported dataset formats for training YOLO detection models, including Ultralytics YOLO and COCO, in this Object Detection Datasets Overview.
+keywords: object detection, datasets, formats, Ultralytics YOLO, label format, dataset file format, dataset definition, YOLO dataset, model configuration
 ---
 
 # Object Detection Datasets Overview

docs/datasets/detect/objects365.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
 ---
 
 # Objects365 Dataset
@@ -84,4 +85,4 @@ If you use the Objects365 dataset in your research or development work, please c
 }
 ```
 
-We would like to acknowledge the team of researchers who created and maintain the Objects365 dataset as a valuable resource for the computer vision research community. For more information about the Objects365 dataset and its creators, visit the [Objects365 dataset website](https://www.objects365.org/).
+We would like to acknowledge the team of researchers who created and maintain the Objects365 dataset as a valuable resource for the computer vision research community. For more information about the Objects365 dataset and its creators, visit the [Objects365 dataset website](https://www.objects365.org/).

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

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 comments: true
 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
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 # SKU-110k Dataset

docs/datasets/detect/visdrone.md

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 ---
 comments: true
 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
 ---
 
 # VisDrone Dataset

docs/datasets/detect/voc.md

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 ---
 comments: true
 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
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 # VOC Dataset

docs/datasets/detect/xview.md

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 ---
 comments: true
 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
 ---
 
 # xView Dataset
@@ -89,4 +90,4 @@ If you use the xView dataset in your research or development work, please cite t
 }
 ```
 
-We would like to acknowledge the [Defense Innovation Unit](https://www.diu.mil/) (DIU) and the creators of the xView dataset for their valuable contribution to the computer vision research community. For more information about the xView dataset and its creators, visit the [xView dataset website](http://xviewdataset.org/).
+We would like to acknowledge the [Defense Innovation Unit](https://www.diu.mil/) (DIU) and the creators of the xView dataset for their valuable contribution to the computer vision research community. For more information about the xView dataset and its creators, visit the [xView dataset website](http://xviewdataset.org/).

docs/datasets/index.md

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 comments: true
 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
 ---
 
 # Datasets Overview

docs/datasets/pose/coco.md

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 ---
 comments: true
 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
 ---
 
 # COCO-Pose Dataset

docs/datasets/pose/coco8-pose.md

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 ---
 comments: true
 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
 ---
 
 # COCO8-Pose Dataset

docs/datasets/pose/index.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
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 # Pose Estimation Datasets Overview

docs/datasets/segment/coco.md

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 ---
 comments: true
 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
 ---
 
 # COCO-Seg Dataset

docs/datasets/segment/coco8-seg.md

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 ---
 comments: true
 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
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 # COCO8-Seg Dataset

docs/datasets/segment/index.md

@@ -1,6 +1,7 @@
 ---
 comments: true
 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
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 # Instance Segmentation Datasets Overview

docs/datasets/track/index.md

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 comments: true
 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
 ---
 
 # Multi-object Tracking Datasets Overview