datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Omni-Fake-SET
Omni-Fake-SET
Omni-Fake-SET is the in-distribution split of Omni-Fake, a unified multimodal deepfake dataset for social-media forensics. It covers image, audio, video, and audio–video talking-head (AV-TH) modalities. Each modality uses the same three-way label space: real, fully synthetic, and tampered. Pair with the held-out benchmark Omni-Fake-OOD for out-of-distribution evaluation.
Paper: arXiv:2605.01638
Project page: Omni-Fake
License: CC-BY-4.0
Video (hybrid… See the full description on the dataset page: https://huggingface.co/datasets/JamalLee/Omni-Fake-SET.dronescapes2_annotated_train_set
Dataset Card for DroneScapes2 (annotated train set)
This is a FiftyOne dataset with 218 samples. It's a subset of this split from the original repo.
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 =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/dronescapes2_annotated_train_set.open-set-synth-img-attributionThis dataset contains synthetic images generated by different architectures trained on different datasets. There are two types of labels: architecture and generator. The architecture labels are the architectures of the generators used to synthesize the images. The generator labels are a tuple of (architecture, training_dataset) used to synthesize the images. The dataset is split into train, validation, and test sets. For more information, see the [BMVC 2023 paper](https://papers.bmvc2023.org/0659.pdf).faceemo-set-features
FaceEmo-Set Features (ViT Representations)
Dataset Illustration
Overview
This dataset provides feature representations extracted from multiple facial emotion recognition datasets using a Vision Transformer (ViT-Base/16) model.
Instead of releasing raw images, which cannot be redistributed because some source materials are subject to copyright restrictions, we provide:
High-level feature embeddings
Model outputs (logits and probabilities)… See the full description on the dataset page: https://huggingface.co/datasets/jihedjabnoun/faceemo-set-features.winml-test-set
WinML Test Set
Dataset Summary
WinML Test Set is an evaluation‑only collection for validating model accuracy and stability on Windows ML / DirectML / ONNX Runtime pipelines. It aggregates several permissively‑licensed sources and harmonizes schema for reproducible, regression‑grade testing across backends and versions. Not intended for training.
Intended Use
Accuracy and regression benchmarking of Windows ML / DirectML / ONNX Runtime pipelines.… See the full description on the dataset page: https://huggingface.co/datasets/Futuremark/winml-test-set.medical_records_parsing_validation_set
Medical Records Parsing Validation Set
Dataset Composition and Clinical Relevance
The Eka Medical Records Parsing Dataset empowers evaluation of AI systems designed to extract structured information from unstructured medical documents, enabling true digitisation of healthcare data while maintaining clinical accuracy.
The dataset comprise 288 carefully selected images of laboratory reports and prescriptions representing diverse formats and templates encountered in Indian… See the full description on the dataset page: https://huggingface.co/datasets/ekacare/medical_records_parsing_validation_set.Age-Classification-Set
Image Classification Age Range Labels
This repository uses the following labels to categorize age ranges in image classification tasks:
[!Warning]
labels_list = ['0-12', '13-20', '21-44', '45-64', '65+']
the values are age range in iamge classification give the README.MD for Repository
0-12: Images depicting individuals aged 0 to 12 years old.
13-20: Images depicting individuals aged 13 to 20 years old.
21-44: Images depicting individuals aged 21 to 44 years old.
45-64: Images… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Age-Classification-Set.TTI-Set
Text-to-Image Model Attribution Dataset
This dataset is distilled from two comprehensive sources:
A 2-year snapshot of the CivitAI SFW (Safe-for-Work) image dataset, containing metadata for generated images.
A complete export of all models published on CivitAI, including metadata such as model names, types, and version identifiers.
By matching image-level resourceIDs (used to generate each image) with the corresponding model version IDs from the model dataset, we identified and… See the full description on the dataset page: https://huggingface.co/datasets/pointofnoreturn/TTI-Set.augmented_lebanese_set
augmented_lebanese_set
Split: train with 12400 rows.
Schema
image_url (string)
camera_or_phone_prob (float)
food_prob (float)
dish_name (string)
food_type (string)
ingredients (string)
portion_size (string)
cooking_method (string)
Note: image_url should point to reachable image locations (http(s) or hf:// paths).
first-set-RMBThis dataset includes images of genuine and counterfeit currency from the first set of RMB/Renminbi. Part of the genuine currency are samples of prototype banknotes.
The first set of RMB/Renminbi is incredibly rare, and gathering data has been challenging. Your contributions are welcome.
labelled-samples
WHA Spell Simulator Glyphs
Crowdsourced handwriting samples of signs and sigils from the fan-made
Witch Hat Atelier spell simulator. Contributors drew each
glyph freehand in the project's Sample Maker tool; every sample was
human-reviewed and only approved samples are included. Strokes are
simplified (polling-rate invariant) and normalised to the 0..1 range,
preserving aspect ratio.
vector config
One record per sample:
id — content hash of the raw sample… See the full description on the dataset page: https://huggingface.co/datasets/sethsama/labelled-samples.setcsset
Dataset for project: csgo-weapon-classification
Dataset Description
This dataset has for project csgo-weapon-classification was collected with the help of a bulk google image downloader.
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": "<1768x718 RGB PIL image>",
"target": 0
},
{
"image": "<716x375 RGBA PIL image>"… See the full description on the dataset page: https://huggingface.co/datasets/4lender/setcsset.