datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
typed_digital_signatures
Typed Digital Signatures Dataset
This comprehensive dataset contains synthetic digital signatures rendered across 30 different Google Fonts, specifically selected for their handwriting and signature-style characteristics. Each font contributes unique stylistic elements, making this dataset ideal for robust signature analysis and font recognition tasks.
Dataset Overview
Total Fonts: 30 different Google Fonts
Images per Font: 3,000 signatures
Total Dataset Size:… See the full description on the dataset page: https://huggingface.co/datasets/Benjy/typed_digital_signatures.SignLanguage_MiniProjectDataset used for training a model to classify Danish Sign Language signs, based on MediaPipe hand landmark data.
The data is not split into training, test and validation sets.
The dataset consist of four classes, 'unknown', 'hello', 'bye' and 'thanks'.
There are 30 datapoints for each class.
Each data point is 30 frames of data stored in individual Numpy files with x, y and z values for each hand landmark.
American-Sign-Language-MNIST
Dataset Card for ASL-MNIST
This is a FiftyOne dataset with 34,627 samples of American Sign Language (ASL) alphabet images, converted from the original Kaggle Sign Language MNIST dataset into a format optimized for computer vision workflows.
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… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/American-Sign-Language-MNIST.appworld-qwen35-4b-9b-s_signal_6-epoch4-iter1
appworld-qwen35-4b-9b-s_signal_6-epoch4-iter1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3953125
Action score: 0.446875
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-epoch4
total-300-lambda02-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.4046875
Action score: 0.4140625
Valid samples: 320/320
total-300-lambda00-s_signal_type6-jh-epoch4
total-300-lambda00-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3875
Action score: 0.43125
Valid samples: 320/320
total-300-lambda05-s_signal_type6-jh-epoch4
total-300-lambda05-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.35703125
Action score: 0.4375
Valid samples: 320/320
total-300-lambda08-s_signal_type6-jh-epoch4
total-300-lambda08-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.38046875
Action score: 0.4078125
Valid samples: 320/320
total-300-lambda10-s_signal_type6-jh-epoch4
total-300-lambda10-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.36640625
Action score: 0.41875
Valid samples: 320/320
total-300noapp-lambda02-s_signal_type6-jh-epoch4
total-300noapp-lambda02-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.36640625
Action score: 0.409375
Valid samples: 320/320
total-300app-lambda02-s_signal_type6-jh-epoch4
total-300app-lambda02-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3625
Action score: 0.4015625
Valid samples: 320/320
total-131-lambda02-residual-s_signal_type6-jh-epoch4
total-131-lambda02-residual-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3765625
Action score: 0.4171875
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-retry-epoch4
total-300-lambda02-s_signal_type6-jh-retry-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.36953125
Action score: 0.3984375
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-epoch4-reeval2
total-300-lambda02-s_signal_type6-jh-epoch4-reeval2
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.4125
Action score: 0.4265625
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-epoch4-reeval1
total-300-lambda02-s_signal_type6-jh-epoch4-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.38828125
Action score: 0.4234375
Valid samples: 320/320
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1-reeval1
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.41328125
Action score: 0.4359375
Valid samples: 320/320
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1
appworld-qwen35-4b-9b-s_signal_5-epoch4-iter1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.41953125
Action score: 0.4515625
Valid samples: 320/320
qwen35-4b-filter-s_signal5-200-qwen38-27b-newprompt-4k-epoch4
qwen35-4b-filter-s_signal5-200-qwen38-27b-newprompt-4k-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3890625
Action score: 0.4359375
Valid samples: 320/320
American-Sign-Language-Dataset
American Sign Language (ASL) Dataset
Description:This dataset contains 108,618 videos representing 2,208 ASL words, with each word having a minimum of 30 videos. The videos were scraped, collected from multiple sources, and preprocessed to ensure consistency, quality, and usability for machine learning and gesture recognition tasks. Each video is ≤10 MB, optimized for storage and model training.The dataset can be used for ASL gesture recognition, video-based ML tasks, and model… See the full description on the dataset page: https://huggingface.co/datasets/shpouladi/American-Sign-Language-Dataset.fi-etf-macro-signal-master-datarussian-road-signs
Датасет размеченных знаков
Датасет размеченных дорожных знаков для задач компьютерного зрения и детекции объектов.
Загрузка
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="Dognellaf/russian-road-signs",
repo_type="dataset",
local_dir="./russian-road-signs"
)
Описание
Датасет содержит размеченные вручную кадры из видеозаписей с российскими дорожными знаками. Разметка в формате YOLO.
Изображений: 43 851 (JPEG)… See the full description on the dataset page: https://huggingface.co/datasets/Dognellaf/russian-road-signs.SignVerse-2M
SignVerse-2M
SignVerse-2M: A Two-Million-Clip Pose-Native Universe of 55+ Sign Languages
Links: [Paper] | [Data Files] | [Project Page]
SignVerse-2M is a large-scale multilingual pose-native dataset for sign language research. The dataset reorganizes publicly available sign language videos into a unified DWPose-based representation and releases the result as approximately 2 million clips from 39,196 videos covering 55+ sign languages. Rather than… See the full description on the dataset page: https://huggingface.co/datasets/SignerX/SignVerse-2M.bit-signal-store
Bit Signal Store
A shared, append-only cache of raw time-series model outputs and OHLCV
prices, used by the Backtest Lab
Space.
The one rule
This store holds raw model outputs and prices. It never holds trade
decisions. No entries, no exits, no position sizes, no P&L. Trading rules,
costs, slippage and sizing are applied live, per request, by the Backtest
Lab's engine. That separation is what lets many different strategies be
compared against the same model… See the full description on the dataset page: https://huggingface.co/datasets/The-Bit-Trading-Company/bit-signal-store.world-signals
World Signals — a daily cross-country snapshot of attention
One folder per day under data/YYYY-MM-DD/, and the same files copied to latest/.
Built every morning (JST) by the EmpireOS world model. Nothing is generated by a model; every row is a measurement from a public source.
file
what
source
search_trends.csv
rising searches, 30 countries, with approximate traffic and the headline that drove them
Google Trends daily RSS
podcast_charts.csv
top-100 podcasts, 30… See the full description on the dataset page: https://huggingface.co/datasets/Lilambd/world-signals.traffic_signal_imagesThis dataset contains traffic images from traffic signal cameras of singapore. The images are captured at 1.5 minute interval from 6 pm to 7 pm everyday for the month of January 2024.sign_language_comparison_table_modifiedpopsign-images
PopSign Images Dataset
This dataset contains frame sequences extracted from PopSign ASL (American Sign Language) video clips, organized for sign language recognition tasks.
Dataset Description
The PopSign dataset consists of short video clips of isolated ASL signs. This version provides pre-extracted image frames from each video clip, suitable for training image-based or video-based models for sign language recognition.
Subsets
The dataset contains two subsets:… See the full description on the dataset page: https://huggingface.co/datasets/sign/popsign-images.sign-bibles
bible-nlp/sign-bibles
This dataset is still being generated and currently includes only test files
This dataset contains sign language videos from the Digital Bible Library (DBL), processed for machine learning applications. The dataset is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).
Dataset Structure
Each sample contains:
["mp4"] the original video
["json"] Metadata, including bible reference, copyright information… See the full description on the dataset page: https://huggingface.co/datasets/bible-nlp/sign-bibles.msp-raw-multimodal-signal-corpus
Dataset Card for MSP Raw Multimodal Signal Corpus
Dataset Summary
This repository hosts the raw, uncompressed iterations of the Multimodal Signal Corpus (Epoch 2). The objective of this dataset is to provide researchers with high-density, completely unstructured multimodal vectors—including raw acoustic captures, spatial matrices, and continuous signal representations.
Because the focus of this research phase is on handling unformatted, noisy, and uncompressed latent… See the full description on the dataset page: https://huggingface.co/datasets/multimodal-signal-group/msp-raw-multimodal-signal-corpus.American-Sign-Language-Dataset
American Sign Language (ASL) Dataset
Description:This dataset contains 108,618 videos representing 2,208 ASL words, with each word having a minimum of 30 videos. The videos were scraped, collected from multiple sources, and preprocessed to ensure consistency, quality, and usability for machine learning and gesture recognition tasks. Each video is ≤10 MB, optimized for storage and model training.The dataset can be used for ASL gesture recognition, video-based ML tasks, and model… See the full description on the dataset page: https://huggingface.co/datasets/akasheroor/American-Sign-Language-Dataset.