datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ctrl-shift
Dataset Card for Control+Shift: Generating Controllable Distribution Shifts
[arXiv], [GitHub]
Curated by: Roy Friedman and Rhea Chowers
This dataset is the one that accompanies the paper Control+Shift: Generating Controllable Distribution Shifts.
Our data is based on CIFAR10 and ImageNet, using EDM to generate our data. We generated datasets for 3 types of distribution shift on CIFAR10 and ImageNet - so a total of 6 datasets. The types of distribution shifts are called overlap… See the full description on the dataset page: https://huggingface.co/datasets/friedmanroy/ctrl-shift.ICDAR2019_cTDaR_TRACKB_resized
Dataset Card for ICDAR2019-cTDaR-TRACKB
This dataset is a resized version of the original cndplab-founder/ICDAR2019_cTDaR, merged with with its supplement cndplab-founder/ICDAR2019_cTDaR_dataset_supplement.
You can easily and quickly load it:
dataset = load_dataset("dvgodoy/ICDAR2019_cTDaR_TRACKB_resized")
DatasetDict({
train: Dataset({
features: ['image', 'width', 'height', 'category', 'label', 'bboxes_table', 'bboxes_cell'],
num_rows: 1200
})
test:… See the full description on the dataset page: https://huggingface.co/datasets/dvgodoy/ICDAR2019_cTDaR_TRACKB_resized.mb-change_cls_ctx
mb-change_cls_ctx
A Mars image classification dataset for planetary science research.
Dataset Metadata
License: CC-BY-4.0 (Creative Commons Attribution 4.0 International)
Version: 1.0
Date Published: 2025-05-14
Cite As: TBD
Classes
This dataset contains the following classes:
0: no_change
1: change
Statistics
train: 72 images
test: 20 images
val: 20 images
partition_train_0.50x_partition: 18 images
partition_train_0.20x_partition: 7 images… See the full description on the dataset page: https://huggingface.co/datasets/Mirali33/mb-change_cls_ctx.radgenome-ct-reshaped-tiny
RadGenome ChestCT Reshaped Tiny Dataset
This dataset contains resized chest CT scans from the RadGenome-ChestCT dataset.
Dataset Details
Original Resolution: 900x900xN
Resized Resolution: 300x300xN
Format: NIfTI (.nii.gz)
Number of Volumes: 253
Space Reduction: ~89% (resized to 1/9th of original spatial dimensions)
Dataset Structure
Each entry contains:
volumename: Name of the CT volume file (string)
anatomy: Anatomical region information (string)
sentence:… See the full description on the dataset page: https://huggingface.co/datasets/nahidhasan/radgenome-ct-reshaped-tiny.ICDAR2019_cTDaR_TRACKA_resized
Dataset Card for ICDAR2019-cTDaR-TRACKA
This dataset is a resized version of the original cndplab-founder/ICDAR2019_cTDaR.
You can easily and quickly load it:
dataset = load_dataset("dvgodoy/ICDAR2019_cTDaR_TRACKA_resized")
DatasetDict({
train: Dataset({
features: ['image', 'width', 'height', 'category', 'label', 'bboxes'],
num_rows: 1200
})
test: Dataset({
features: ['image', 'width', 'height', 'category', 'label', 'bboxes'],
num_rows:… See the full description on the dataset page: https://huggingface.co/datasets/dvgodoy/ICDAR2019_cTDaR_TRACKA_resized.