Omkar2118/datasets huggingface dataset:
REFUGE2

The goal of REFUGE2 challenge is to evaluate and compare automated algorithms for glaucoma detection and optic disc/cup segmentation on a standard dataset of retinal fundus images. 
We invite the medical image analysis community to participate by developing and testing existing and novel automated classification and segmentation methods.

REFUGE2 challenge consists of THREE Tasks:
    Classification of clinical Glaucoma
    Segmentation of Optic Disc and Cup
    Localization of Fovea (macular center)

Introducing paper: REFUGE2 Challenge: A Treasure Trove for Multi-Dimension Analysis and Evaluation in Glaucoma Screening
GAMMA Challenge

GAMMA releases the world's first multi-modal dataset for glaucoma grading, which was provided by the Sun Yat-sen Ophthalmic Center of Sun Yat-sen University in Guangzhou, China. The dataset consists of 2D fundus images and 3D optical coherence tomography (OCT) images of 300 patients. The dataset was annotated with glaucoma grade in every sample, and macular fovea coordinates as well as optic disc/cup segmentation mask in the fundus image. 

We invite the medical image analysis community to participate by developing and testing existing and novel automated classification and segmentation methods.

GAMMA challenge consists of THREE Tasks:

    Grading glaucoma using multi-modality data

    Segmentation of optic disc and cup in fundus images

    Localization of fovea macula in fundus image

Introducing paper: GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges
ClonedPerson

The ClonedPerson dataset is a large-scale synthetic person re-identification dataset introduced in the paper "Cloning Outfits from Real-World Images to 3D Characters for Generalizable Person Re-Identification" in CVPR 2022. It is generated by MakeHuman and Unity3D. Characters in this dataset use an automatic approach to directly clone the whole outfits from real-world person images to virtual 3D characters, such that any virtual person thus created will appear very similar to its real-world counterpart. The dataset contains 887,766 synthesized person images of 5,621 identities.

Introducing paper: Cloning Outfits from Real-World Images to 3D Characters for Generalizable Person Re-Identification