Omkar2118/datasets huggingface dataset:
cryoPPP
Full name: CryoPPP: A Large Expert-Curated Cryo-EM Image Dataset for Machine Learning Protein Particle Picking

The CryoPPP dataset consists of 34 ground truth data and metadata for 335 EMPIAR IDs. The ground truth data is comprised of a variety of 9893 Micrographs (~300 cryo-EM images per EMPIAR ID) with manually curated ground truth coordinates of picked protein particles. The metadata consists of 1,698,802 high-resolution micrographs deposited in EMPIAR with their respective FPT and Globus data download paths.
BUPTCampus
Full name: BUPTCampus

BUPTCampus is a video-based visible-infrared dataset with approximately pixel-level aligned tracklet pairs and single-camera auxiliary samples.

Introducing paper: Video-based Visible-Infrared Person Re-Identification with Auxiliary Samples
BHSD
Full name: A 3D Multi-class Brain Hemorrhage Segmentation Dataset

Intracranial hemorrhage (ICH) is a pathological condition characterized by bleeding inside the skull or brain, which can be attributed to various factors. Identifying, localizing and quantifying ICH has important clinical implications, in a bleed-dependent manner. While deep learning techniques are widely used in medical image segmentation and have been applied to the ICH segmentation task, existing public ICH datasets do not support the multi-class segmentation problem. To address this, we develop the Brain Hemorrhage Segmentation Dataset (BHSD), which provides a 3D multi-class ICH dataset containing 192 volumes with pixel-level annotations and 2200 volumes with slice-level annotations across five categories of ICH. To demonstrate the utility of the dataset, we formulate a series of supervised and semi-supervised ICH segmentation tasks. We provide experimental results with state-of-the-art models as reference benchmarks for further model developments and evaluations on this dataset.

Introducing paper: BHSD: A 3D Multi-Class Brain Hemorrhage Segmentation Dataset