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/reference/yolo/data/annotator.md

@@ -1,8 +1,9 @@
 ---
 description: Learn how to use auto_annotate in Ultralytics YOLO to generate annotations automatically for your dataset. Simplify object detection workflows.
+keywords: Ultralytics YOLO, Auto Annotator, AI, image annotation, object detection, labelling, tool
 ---
 
 # auto_annotate
 ---
 :::ultralytics.yolo.data.annotator.auto_annotate
-<br><br>
+<br><br>

docs/reference/yolo/data/augment.md

@@ -1,5 +1,6 @@
 ---
 description: Use Ultralytics YOLO Data Augmentation transforms with Base, MixUp, and Albumentations for object detection and classification.
+keywords: YOLO, data augmentation, transforms, BaseTransform, MixUp, RandomHSV, Albumentations, ToTensor, classify_transforms, classify_albumentations
 ---
 
 # BaseTransform
@@ -95,4 +96,4 @@ description: Use Ultralytics YOLO Data Augmentation transforms with Base, MixUp,
 # classify_albumentations
 ---
 :::ultralytics.yolo.data.augment.classify_albumentations
-<br><br>
+<br><br>

docs/reference/yolo/data/base.md

@@ -1,8 +1,9 @@
 ---
 description: Learn about BaseDataset in Ultralytics YOLO, a flexible dataset class for object detection. Maximize your YOLO performance with custom datasets.
+keywords: BaseDataset, Ultralytics YOLO, object detection, real-world applications, documentation
 ---
 
 # BaseDataset
 ---
 :::ultralytics.yolo.data.base.BaseDataset
-<br><br>
+<br><br>

docs/reference/yolo/data/build.md

@@ -1,5 +1,6 @@
 ---
 description: Maximize YOLO performance with Ultralytics' InfiniteDataLoader, seed_worker, build_dataloader, and load_inference_source functions.
+keywords: Ultralytics, YOLO, object detection, data loading, build dataloader, load inference source
 ---
 
 # InfiniteDataLoader
@@ -35,4 +36,4 @@ description: Maximize YOLO performance with Ultralytics' InfiniteDataLoader, see
 # load_inference_source
 ---
 :::ultralytics.yolo.data.build.load_inference_source
-<br><br>
+<br><br>

docs/reference/yolo/data/converter.md

@@ -1,5 +1,6 @@
 ---
 description: Convert COCO-91 to COCO-80 class, RLE to polygon, and merge multi-segment images with Ultralytics YOLO data converter. Improve your object detection.
+keywords: Ultralytics, YOLO, converter, COCO91, COCO80, rle2polygon, merge_multi_segment, annotations
 ---
 
 # coco91_to_coco80_class
@@ -30,4 +31,4 @@ description: Convert COCO-91 to COCO-80 class, RLE to polygon, and merge multi-s
 # delete_dsstore
 ---
 :::ultralytics.yolo.data.converter.delete_dsstore
-<br><br>
+<br><br>

docs/reference/yolo/data/dataloaders/stream_loaders.md

@@ -1,5 +1,6 @@
 ---
 description: 'Ultralytics YOLO Docs: Learn about stream loaders for image and tensor data, as well as autocasting techniques. Check out SourceTypes and more.'
+keywords: Ultralytics YOLO, data loaders, stream load images, screenshots, tensor data, autocast list, youtube URL retriever
 ---
 
 # SourceTypes
@@ -40,4 +41,4 @@ description: 'Ultralytics YOLO Docs: Learn about stream loaders for image and te
 # get_best_youtube_url
 ---
 :::ultralytics.yolo.data.dataloaders.stream_loaders.get_best_youtube_url
-<br><br>
+<br><br>

docs/reference/yolo/data/dataloaders/v5augmentations.md

@@ -1,5 +1,6 @@
 ---
 description: Enhance image data with Albumentations CenterCrop, normalize, augment_hsv, replicate, random_perspective, cutout, & box_candidates.
+keywords: YOLO, object detection, data loaders, V5 augmentations, CenterCrop, normalize, random_perspective
 ---
 
 # Albumentations
@@ -85,4 +86,4 @@ description: Enhance image data with Albumentations CenterCrop, normalize, augme
 # classify_transforms
 ---
 :::ultralytics.yolo.data.dataloaders.v5augmentations.classify_transforms
-<br><br>
+<br><br>

docs/reference/yolo/data/dataloaders/v5loader.md

@@ -1,5 +1,6 @@
 ---
 description: Efficiently load images and labels to models using Ultralytics YOLO's InfiniteDataLoader, LoadScreenshots, and LoadStreams.
+keywords: YOLO, data loader, image classification, object detection, Ultralytics
 ---
 
 # InfiniteDataLoader
@@ -90,4 +91,4 @@ description: Efficiently load images and labels to models using Ultralytics YOLO
 # create_classification_dataloader
 ---
 :::ultralytics.yolo.data.dataloaders.v5loader.create_classification_dataloader
-<br><br>
+<br><br>

docs/reference/yolo/data/dataset.md

@@ -1,5 +1,6 @@
 ---
 description: Create custom YOLOv5 datasets with Ultralytics YOLODataset and SemanticDataset. Streamline your object detection and segmentation projects.
+keywords: YOLODataset, SemanticDataset, Ultralytics YOLO Docs, Object Detection, Segmentation
 ---
 
 # YOLODataset
@@ -15,4 +16,4 @@ description: Create custom YOLOv5 datasets with Ultralytics YOLODataset and Sema
 # SemanticDataset
 ---
 :::ultralytics.yolo.data.dataset.SemanticDataset
-<br><br>
+<br><br>

docs/reference/yolo/data/dataset_wrappers.md

@@ -1,8 +1,9 @@
 ---
 description: Create a custom dataset of mixed and oriented rectangular objects with Ultralytics YOLO's MixAndRectDataset.
+keywords: Ultralytics YOLO, MixAndRectDataset, dataset wrapper, image-level annotations, object-level annotations, rectangular object detection
 ---
 
 # MixAndRectDataset
 ---
 :::ultralytics.yolo.data.dataset_wrappers.MixAndRectDataset
-<br><br>
+<br><br>

docs/reference/yolo/data/utils.md

@@ -1,5 +1,6 @@
 ---
 description: Efficiently handle data in YOLO with Ultralytics. Utilize HUBDatasetStats and customize dataset with these data utility functions.
+keywords: YOLOv4, Object Detection, Computer Vision, Deep Learning, Convolutional Neural Network, CNN, Ultralytics Docs
 ---
 
 # HUBDatasetStats
@@ -65,4 +66,4 @@ description: Efficiently handle data in YOLO with Ultralytics. Utilize HUBDatase
 # zip_directory
 ---
 :::ultralytics.yolo.data.utils.zip_directory
-<br><br>
+<br><br>