Adding missing datasets information to docs (#15916)

3 months ago · cbaf027db2
parent f816426335
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--- a/docs/en/datasets/detect/index.md
+++ b/docs/en/datasets/detect/index.md
@ -77,6 +77,7 @@ Here is a list of the supported datasets and a brief description for each:
 - [COCO](coco.md): Common Objects in Context (COCO) is a large-scale object detection, segmentation, and captioning dataset with 80 object categories.
 - [LVIS](lvis.md): A large-scale object detection, segmentation, and captioning dataset with 1203 object categories.
 - [COCO8](coco8.md): A smaller subset of the first 4 images from COCO train and COCO val, suitable for quick tests.
 - [COCO128](coco.md): A smaller subset of the first 128 images from COCO train and COCO val, suitable for tests.
 - [Global Wheat 2020](globalwheat2020.md): A dataset containing images of wheat heads for the Global Wheat Challenge 2020.
 - [Objects365](objects365.md): A high-quality, large-scale dataset for object detection with 365 object categories and over 600K annotated images.
 - [OpenImagesV7](open-images-v7.md): A comprehensive dataset by Google with 1.7M train images and 42k validation images.
--- a/docs/en/datasets/index.md
+++ b/docs/en/datasets/index.md
@ -38,6 +38,7 @@ Bounding box object detection is a computer vision technique that involves detec
 - [COCO](detect/coco.md): Common Objects in Context (COCO) is a large-scale object detection, segmentation, and captioning dataset with 80 object categories.
 - [LVIS](detect/lvis.md): A large-scale object detection, segmentation, and captioning dataset with 1203 object categories.
 - [COCO8](detect/coco8.md): A smaller subset of the first 4 images from COCO train and COCO val, suitable for quick tests.
 - [COCO128](detect/coco.md): A smaller subset of the first 128 images from COCO train and COCO val, suitable for tests.
 - [Global Wheat 2020](detect/globalwheat2020.md): A dataset containing images of wheat heads for the Global Wheat Challenge 2020.
 - [Objects365](detect/objects365.md): A high-quality, large-scale dataset for object detection with 365 object categories and over 600K annotated images.
 - [OpenImagesV7](detect/open-images-v7.md): A comprehensive dataset by Google with 1.7M train images and 42k validation images.
@ -56,6 +57,7 @@ Instance segmentation is a computer vision technique that involves identifying a
 - [COCO](segment/coco.md): A large-scale dataset designed for object detection, segmentation, and captioning tasks with over 200K labeled images.
 - [COCO8-seg](segment/coco8-seg.md): A smaller dataset for instance segmentation tasks, containing a subset of 8 COCO images with segmentation annotations.
 - [COCO128-seg](segment/coco.md): A smaller dataset for instance segmentation tasks, containing a subset of 128 COCO images with segmentation annotations.
 - [Crack-seg](segment/crack-seg.md): Specifically crafted dataset for detecting cracks on roads and walls, applicable for both object detection and segmentation tasks.
 - [Package-seg](segment/package-seg.md): Tailored dataset for identifying packages in warehouses or industrial settings, suitable for both object detection and segmentation applications.
 - [Carparts-seg](segment/carparts-seg.md): Purpose-built dataset for identifying vehicle parts, catering to design, manufacturing, and research needs. It serves for both object detection and segmentation tasks.
@ -88,6 +90,7 @@ Image classification is a computer vision task that involves categorizing an ima
 Oriented Bounding Boxes (OBB) is a method in computer vision for detecting angled objects in images using rotated bounding boxes, often applied to aerial and satellite imagery.
 - [DOTA-v2](obb/dota-v2.md): A popular OBB aerial imagery dataset with 1.7 million instances and 11,268 images.
 - [DOTA8](obb/dota8.md): A smaller subset of the first 8 images from the DOTAv1 split set, 4 for training and 4 for validation, suitable for quick tests.
 ## [Multi-Object Tracking](track/index.md)
--- a/docs/en/datasets/segment/index.md
+++ b/docs/en/datasets/segment/index.md
@ -93,6 +93,7 @@ The `train` and `val` fields specify the paths to the directories containing the
 - [COCO](coco.md): A comprehensive dataset for object detection, segmentation, and captioning, featuring over 200K labeled images across a wide range of categories.
 - [COCO8-seg](coco8-seg.md): A compact, 8-image subset of COCO designed for quick testing of segmentation model training, ideal for CI checks and workflow validation in the `ultralytics` repository.
 - [COCO128-seg](coco.md): A smaller dataset for instance segmentation tasks, containing a subset of 128 COCO images with segmentation annotations.
 - [Carparts-seg](carparts-seg.md): A specialized dataset focused on the segmentation of car parts, ideal for automotive applications. It includes a variety of vehicles with detailed annotations of individual car components.
 - [Crack-seg](crack-seg.md): A dataset tailored for the segmentation of cracks in various surfaces. Essential for infrastructure maintenance and quality control, it provides detailed imagery for training models to identify structural weaknesses.
 - [Package-seg](package-seg.md): A dataset dedicated to the segmentation of different types of packaging materials and shapes. It's particularly useful for logistics and warehouse automation, aiding in the development of systems for package handling and sorting.