datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
celebA_spoof
Dataset Card for "celebA_spoof"
More Information needed
celeba
Dataset Card for Dataset Name
CelebFaces Attributes Dataset (CelebA) is a large-scale face attributes dataset with more than 200K celebrity images, each with 40 attribute annotations.
The images in this dataset cover large pose variations and background clutter. CelebA has large diversities, large quantities, and rich annotations, including:
10,177 number of identities,
202,599 number of face images, and
5 landmark locations, 40 binary attributes annotations per image.
The… See the full description on the dataset page: https://huggingface.co/datasets/flwrlabs/celeba.CELLDSCelebA-facescelebamask-hq
Dataset Card for celebamask-hq
This is a FiftyOne dataset with 30000 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("harpreetsahota/celebamask-hq")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/harpreetsahota/celebamask-hq.celeba-hq-256x256
CelebA-HQ-256x256
CelebA-HQ at 256x256 resolution.
Citation
@article{DBLP:journals/corr/abs-1710-10196,
title={Progressive Growing of GANs for Improved Quality, Stability, and Variation},
author={Tero Karras and Timo Aila and Samuli Laine and Jaakko Lehtinen},
year=2017,
journal={CoRR},
volume={abs/1710.10196}
}
cross-channel-toxoplasma-from-cellmask
Cross-channel toxoplasma from cellmask dataset
3030 paired fields. images/ is the input channel, masks_pv/ the instance-labelled
parasitophorous-vacuole ground truth (same stem = same field), regenerated with the promoted
PV model cpsam_v2_toxo_r5.
Train/test annotation: fields.csv gives name,split,n_objects for every field -
2567 train (31637 objects) / 463 test (6116 objects).
The split is by well (split_by_well.csv), so no well contributes to both sides.
Prepared with spaCR… See the full description on the dataset page: https://huggingface.co/datasets/einarolafsson/cross-channel-toxoplasma-from-cellmask.Assetsbollywood-celebs
bollywood-celebs
Dataset Description
This dataset has been automatically processed by AutoTrain for project bollywood-celebs.
Credits: https://www.kaggle.com/datasets/sushilyadav1998/bollywood-celeb-localized-face-dataset
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<64x64 RGB PIL image>",
"target": 15
},
{… See the full description on the dataset page: https://huggingface.co/datasets/amitpuri/bollywood-celebs.CelebA-attrs
CelebA-128x128
CelebA with attrs at 128x128 resolution.
Dataset Information
The attributes are binary attributes. The dataset is already split into train/test/validation sets.
Citation
@inproceedings{liu2015faceattributes,
title = {Deep Learning Face Attributes in the Wild},
author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
booktitle = {Proceedings of International Conference on Computer Vision (ICCV)},
month = {December},
year… See the full description on the dataset page: https://huggingface.co/datasets/tpremoli/CelebA-attrs.megalith-10mbone_marrow_cell_dataset
About This Dataset
Bone marrow biopsy is procedure applied to collect and examine bone marrow — the spongy tissue inside some of your larger bones.
This biopsy can show whether your bone marrow is healthy and making normal amounts of blood cells. Doctors use these procedures to diagnose and monitor blood and marrow diseases, cancers, as well as fevers of unknown origin.
The dataset contains a collection of over 170,000 de-identified, expert-annotated cells from the bone marrow… See the full description on the dataset page: https://huggingface.co/datasets/ekim15/bone_marrow_cell_dataset.CelebrityFacesDatasetDigiCam-CelebA-26KData is measured at 30 cm, as shown below.
After downloading and installing LenslessPiCam, the simulated PSF can be obtained and compared with the measured one with the following command:
python scripts/sim/digicam_psf.py \
huggingface_repo=bezzam/DigiCam-CelebA-26K \
sim.waveprop=False \
sim.deadspace=True \
digicam.gamma=2.2 \
digicam.ap_center="[58,76]" \
digicam.ap_shape="[19,25]" \
digicam.rotate=0 \
digicam.horizontal_shift=-60 \
digicam.vertical_shift=-80
For a… See the full description on the dataset page: https://huggingface.co/datasets/bezzam/DigiCam-CelebA-26K.celeba-hq
Dataset Card for "celeba-hq"
More Information needed
glioma-cell-radiationcelebrity-1000
Celebrity 1000
Top 1000 celebrities. 18,184 images. 256x256. Square cropped to face.
celeba-hqceleba-hq-256CelebA_bbox_and_facepointsCelebFaces Attributes Dataset (CelebA) is a large-scale face attributes dataset with more than 200K celebrity images,
each with 40 attribute annotations. The images in this dataset cover large pose variations and background clutter.
CelebA has large diversities, large quantities, and rich annotations, including 10,177 number of identities, 202,599 number of face images,
and 5 landmark locations, 40 binary attributes annotations per image.drone_warehouse_lerobotThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "uav",
"total_episodes": 200,
"total_frames": 20000,
"total_tasks": 3,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 10,
"splits": {
"train": "0:200"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/Celina717/drone_warehouse_lerobot.celeba
CelebA dataset
A copy of celeba dataset.
https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
How to use
Download data
huggingface-cli download --local-dir /path/to/datasets/celeba --repo-type dataset Yuehao/celeba
unzip /path/to/datasets/celeba/img_align_celeba.zip -d /path/to/datasets/celeba
Load data via torchvision.datasets.CelebA
torchvision.datasets.CelebA(root='/path/to/datasets')
celebA-HQ
Citation
@article{DBLP:journals/corr/abs-1710-10196,
author = {Tero Karras and
Timo Aila and
Samuli Laine and
Jaakko Lehtinen},
title = {Progressive Growing of GANs for Improved Quality, Stability, and Variation},
journal = {CoRR},
volume = {abs/1710.10196},
year = {2017},
url = {http://arxiv.org/abs/1710.10196},
eprinttype = {arXiv},
eprint = {1710.10196},
timestamp = {Mon, 13 Aug 2018… See the full description on the dataset page: https://huggingface.co/datasets/Chris1/celebA-HQ.celeba-captioned
CelebA Captioned
A captioned version of the CelebA
face dataset. Each image is paired with one or more natural-language captions generated by ChatGPT-5.5,
making it suitable for image-to-text (captioning) and text-to-image generation tasks.
Dataset Structure
Data Fields
Field
Type
Description
image
Image ({bytes, path} struct)
The face image. Renders in the dataset viewer.
celeb_id
int64
Identity label for the celebrity.
captions… See the full description on the dataset page: https://huggingface.co/datasets/lazarohurtado/celeba-captioned.celebaPorting of the famous celeba dataset to 🤗 Datasets.
Dataset Component Descriptions
Attributes (attr)
Description: The attributes feature consists of binary labels that represent the presence or absence of 40 different facial attributes. Each attribute is encoded as either 0 (absence) or 1 (presence). These attributes cover a wide range of facial characteristics and styles, such as "Smiling", "Wearing Hat", "Eyeglasses", etc.
Data Type: Sequence
Length: 40
Dtype: int8… See the full description on the dataset page: https://huggingface.co/datasets/eurecom-ds/celeba.live-cell-segmentation-dataset
Light-microscopy cell segmentation dataset
Transmitted-light fields -- phase contrast, brightfield, DIC and quantitative phase -- with
uint16 instance masks, from 14 public datasets, curated for spaCR and used to fine-tune
live-cell-segmentation-cpsam.
11,007 fields: 6,778 train, 2,030 valid,
2,199 test. Split by ACQUISITION -- a well, a dish, a time-lapse or a
z-stack is never divided between sets -- so the test set is fields the model never saw
anything of.
Layout… See the full description on the dataset page: https://huggingface.co/datasets/einarolafsson/live-cell-segmentation-dataset.hsr_nav_lerobot_newThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "hsr",
"total_episodes": 80,
"total_frames": 22766,
"total_tasks": 1,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 10,
"splits": {
"train": "0:80"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/Celina717/hsr_nav_lerobot_new.blood-cell-detection
Blood Cell Detection Dataset
Introduction
This dataset contains annotated red blood cells(RBC) and white blood cells(WBC) from peripheral blood smear taken from a light microscope.
If you use this dataset in your research, please cite it. See the Citation section below for the correct reference. Please do not cite the auto-generated Hugging Face reference, as it lists an incorrect title and year.
About Blood Cell Detection Dataset
Images are… See the full description on the dataset page: https://huggingface.co/datasets/draaslan/blood-cell-detection.cross-channel-nuclei-from-cellmask
Cross-channel nuclei-from-cellmask dataset
3029 paired fields. images/ is the
cell-mask input channel, masks/ the matching instance-labelled nuclei ground truth (same stem =
same field). split_by_well.csv gives the train/test assignment; the split is by well, so no
well contributes to both sides - field-level splitting would leak.
Prepared with spaCR
(PyPI | conda-forge).
Used to train einarolafsson/cross-channel-nuclei-from-cellmask-cpsam.
deepfake-celeba
MetaFLOS Deepfake Dataset (CelebA Face Deepfake Generated Images)
Flux2-Klein generated deepfake images from CelebA face descriptions, for deepfake detection / comparison research.
Content
19,867 generated images (full CelebA validation split)
Resolution: 256×256
Each corresponds to a CelebA real face (see real_orig field in manifest)
Generation style: snapshot/crop candid-photo look (not studio portrait) — off-center framing, subject possibly touching or cut by… See the full description on the dataset page: https://huggingface.co/datasets/tjw/deepfake-celeba.