datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
random_streetview_images_pano_v0.0.2
Dataset Card for panoramic street view images (v.0.0.2)
Dataset Summary
The random streetview images dataset are labeled, panoramic images scraped from randomstreetview.com. Each image shows a location
accessible by Google Streetview that has been roughly combined to provide ~360 degree view of a single location. The dataset was designed with the intent to geolocate an image purely based on its visual content.
Supported Tasks and Leaderboards
None as of now!… See the full description on the dataset page: https://huggingface.co/datasets/stochastic/random_streetview_images_pano_v0.0.2.hateful-memes-data
Hateful Memes (CS5242 submission mirror)
Mirror of the Facebook Hateful Memes Challenge dataset (Kiela et al., 2020)
used for reproducibility of our CS5242 (NUS) submission.
Contents
img/ — 10,000 PNG images of memes
train.jsonl (8,500), dev_seen.jsonl (500), dev_unseen.jsonl (540),
test_seen.jsonl (1,000), test_unseen.jsonl (2,000)
Provenance
This mirror merges two existing mirrors of the original Meta release:
Label files and most images from… See the full description on the dataset page: https://huggingface.co/datasets/panjiyarsunil/hateful-memes-data.PANDA-PLUS-Bench
PANDA-PLUS-Bench
A benchmark dataset for evaluating WSI-specific feature collapse in pathology foundation models.
Dataset Description
PANDA-PLUS-Bench contains expert-annotated prostate biopsy patches from 9 whole slide images (9 unique patients) with pixel-level Gleason pattern annotations.
Dataset Summary
Patches: ~2,770 per augmentation condition
Resolution: 224×224 pixels at 20× magnification
Classes: Benign (0), GP3 (1), GP4 (2), GP5 (3)
Slides: 9 (one… See the full description on the dataset page: https://huggingface.co/datasets/dellacorte/PANDA-PLUS-Bench.pangaea2-vhr
Mirror Notice
This repository contains unofficial mirrors of the following datasets, provided solely for hash-based versioning and reproducibility of research results. This is NOT the official source.
PureForest: https://huggingface.co/datasets/IGNF/PureForest
mpv4ger: https://huggingface.co/datasets/recursix/geo-bench-1.0
xView2: https://xview2.org/dataset
SpaceNet 3 Roads: https://spacenet.ai/spacenet-roads-dataset/ (S3: s3://spacenet-dataset/spacenet/SN3_roads/)
Legal Notice:… See the full description on the dataset page: https://huggingface.co/datasets/kshitijrajsharma/pangaea2-vhr.Induction-Cooker-Ceramic-Panel-Crack-Identification-Dataset
Induction Cooker Ceramic Panel Crack Identification Dataset
In the current industrial field, the crack problem of induction cooker ceramic panels poses a threat to product safety, leading to potential explosion risks. Existing detection methods mostly rely on manual inspection, which is inefficient and prone to errors. This dataset aims to provide high-quality crack image data to train machine learning models, automating the detection process and improving detection efficiency and… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Induction-Cooker-Ceramic-Panel-Crack-Identification-Dataset.Pansy-Recognition-Image-Dataset
Pansy Recognition Image Dataset
Currently, garden management faces the challenge of efficiently and accurately identifying flower varieties. Traditional manual identification relies on experience and is inefficient. Existing image recognition technologies still need improvement in the accuracy of specific flower types, especially in complex backgrounds. This dataset aims to address common accuracy deficiencies in pansy recognition by providing a large number of high-quality images… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Pansy-Recognition-Image-Dataset.Pansy-Recognition-Image-Dataset
Pansy Recognition Image Dataset
Currently, garden management faces the challenge of efficiently and accurately identifying flower varieties. Traditional manual identification relies on experience and is inefficient. Existing image recognition technologies still need improvement in the accuracy of specific flower types, especially in complex backgrounds. This dataset aims to address common accuracy deficiencies in pansy recognition by providing a large number of high-quality images… See the full description on the dataset page: https://huggingface.co/datasets/shangzx/Pansy-Recognition-Image-Dataset.opencs2_panorama
OpenCS2 — Panorama Dataset
360° panoramas captured in-engine from Counter-Strike 2 at positions
sampled from real player movement in HLTV demos. For each position the
dataset ships six cube-map faces (90° HFOV, 1024×1024) and the
stitched 4096×2048 equirectangular preview, plus the camera pose in
Source 2 hammer-unit coordinates (the same convention as
blanchon/opencs2_dataset).
Stat
Value
Maps
de_ancient, de_anubis, de_dust2, de_inferno, de_mirage, de_nuke… See the full description on the dataset page: https://huggingface.co/datasets/blanchon/opencs2_panorama.heb_synth_pangoline
Dataset Card for Hebrew Synthetic Pangoline Dataset
INFO: I'm not giving access to users with 0 models/0 datasets/0 activity - sharing is both ways
Dataset Summary
The Hebrew Synthetic Pangoline Dataset is a comprehensive collection of synthetic Hebrew document images generated using a custom implementation of Pangoline, a text-to-image synthesis tool. The dataset contains high-quality synthetic Hebrew text rendered as images, along with corresponding ground truth… See the full description on the dataset page: https://huggingface.co/datasets/johnlockejrr/heb_synth_pangoline.yid_synth_pangolineINFO: I'm not giving access to users with 0 models/0 datasets/0 activity - sharing is both ways
Dataset Summary
The Yiddish Synthetic Pangoline Dataset is a comprehensive collection of synthetic Yiddish document images generated using a custom implementation of Pangoline, a text-to-image synthesis tool. The dataset contains high-quality synthetic Yiddish text rendered as images, along with corresponding ground truth text and ALTO-XML layout annotations. This dataset is designed… See the full description on the dataset page: https://huggingface.co/datasets/johnlockejrr/yid_synth_pangoline.