datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
BarkVN-50
Dataset Card for BarkVN-50: Tree Species Identification from Bark Texture
This is a FiftyOne dataset with 5578 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("Voxel51/BarkVN-50")
# Launch the App
session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/BarkVN-50.openbrush-baroque
OpenBrush Baroque
Baroque works from OpenBrush-75K (~1600–1750) — chiaroscuro, religious painting, dramatic light.
Curated subset of jaddai/openbrush. Same CC0 license, same caption schema, same VLM (Qwen3-VL-30B-A3B). This subset exists so you don't have to download 75,313 images to get to the 4,240 you actually want.
Why this subset
The canonical Baroque visual language — Caravaggio, Rembrandt, Vermeer, Velázquez, Rubens. Useful for models learning dramatic… See the full description on the dataset page: https://huggingface.co/datasets/jaddai/openbrush-baroque.btech-01-contaminated
BTech 01 — 오염된 학습셋 (교육용)
이상 탐지 교육 과제용으로 정상 학습셋에 결함 10장을 섞어 미리 구운 데이터셋입니다.
현장에서 라벨링 실수로 흔히 생기는 학습셋 오염을 재현합니다.
구성
경로
내용
train/ok/
410장 — 정상 400 + 결함 10 이 섞여 있음
contamination_key.csv
file_name, contaminated(0/1), source_rel — 학습셋 쪽 정답
eval_contaminated.csv
평가셋 쪽 오염 소스 목록(source_rel)
파일명은 전부 새로 매겨 섞었으므로 파일명으로는 오염을 구분할 수 없습니다.
해상도 512x512. 정상·오염 동일 처리 경로.
깨끗한 기준선과 평가셋
포함하지 않습니다. 원본 BTech 01 의 train/ok 와 test/ 를 쓰십시오.
학습셋에 섞인 결함 10장은… See the full description on the dataset page: https://huggingface.co/datasets/bardroh/btech-01-contaminated.SynGallery-1024
SynGallery-1024: A Synthetic Gallery of Real Paintings for Instance-Level Artwork Recognition
The 1024×1024 high-resolution edition of
patryk-bartkowiak/SynGallery.
A synthetic dataset for instance-level artwork recognition: 4,898 real
paintings (MET Open Access) hung in a procedurally randomized 3D art-gallery
scene, each rendered from 5 camera viewpoints at 1024×1024 — 24,490
synthetic RGB images paired with their source photos and museum metadata
(title, artist, date, medium… See the full description on the dataset page: https://huggingface.co/datasets/patryk-bartkowiak/SynGallery-1024.SynGallery-abl4-tex-light-glass-frame
SynGallery-abl4-tex-light-glass-frame: + frame variety
Rung 4 of the SynGallery instance-level artwork-recognition ablation ladder. 4,898 MET paintings × 5 camera viewpoints = 24,490 synthetic RGB images at 512×512, paired with their source photos and museum metadata.
In this rung, the scene varies textures, lighting, glass and frame molding variant + color/roughness/metallic, while freezing camera pose (the only frozen factor). Same schema, source images and index↔painting… See the full description on the dataset page: https://huggingface.co/datasets/patryk-bartkowiak/SynGallery-abl4-tex-light-glass-frame.SynGallery-abl0
SynGallery-abl0: fixed-environment baseline
Rung 0 of the SynGallery instance-level artwork-recognition ablation ladder. 4,898 MET paintings × 5 camera viewpoints = 24,490 synthetic RGB images at 512×512, paired with their source photos and museum metadata.
In this rung, the scene varies nothing — the gallery is one fixed configuration for all 24,490 images, while freezing wall/floor/roof textures + floor material, lighting, glass, frame variant/color, camera pose. Same schema… See the full description on the dataset page: https://huggingface.co/datasets/patryk-bartkowiak/SynGallery-abl0.SynGallery
SynGallery: A Synthetic Gallery of Real Paintings for Instance-Level Artwork Recognition
A synthetic dataset for instance-level artwork recognition: 4,898 real
paintings (MET Open Access) hung in a procedurally randomized 3D art-gallery
scene, each rendered from 5 camera viewpoints at 512×512 — 24,490
synthetic RGB images paired with their source photos and museum metadata
(title, artist, date, medium, …). The environment is randomized per scene — wall/floor/roof textures… See the full description on the dataset page: https://huggingface.co/datasets/patryk-bartkowiak/SynGallery.SynGallery-abl1-tex
SynGallery-abl1-tex: + texture variety
Rung 1 of the SynGallery instance-level artwork-recognition ablation ladder. 4,898 MET paintings × 5 camera viewpoints = 24,490 synthetic RGB images at 512×512, paired with their source photos and museum metadata.
In this rung, the scene varies wall/floor/roof textures + floor material (on top of the baseline), while freezing lighting, glass, frame variant/color, camera pose. Same schema, source images and index↔painting mapping as every… See the full description on the dataset page: https://huggingface.co/datasets/patryk-bartkowiak/SynGallery-abl1-tex.SynGallery-abl2-tex-light
SynGallery-abl2-tex-light: + lighting variety
Rung 2 of the SynGallery instance-level artwork-recognition ablation ladder. 4,898 MET paintings × 5 camera viewpoints = 24,490 synthetic RGB images at 512×512, paired with their source photos and museum metadata.
In this rung, the scene varies textures and lighting (area-light shape/spread + instanced ceiling lights), while freezing glass, frame variant/color, camera pose. Same schema, source images and index↔painting mapping as… See the full description on the dataset page: https://huggingface.co/datasets/patryk-bartkowiak/SynGallery-abl2-tex-light.sea-turtle-behavior-data
Sea Turtle Behavior Data
Growing collection of supplementary data for the sea turtle breathing-behavior project. This repo
holds the underlying source material behind the labeled training/eval image dataset (link to be
added) and the trained classifier (link to be added), so results can be reproduced from raw
footage rather than only from already-processed crops.
Current contents: raw video
{camera}/{date}/{stem}.mp4 — 42 files, 1GB each (41.6GB total), covering… See the full description on the dataset page: https://huggingface.co/datasets/marko-barisic/sea-turtle-behavior-data.SynGallery-abl3-tex-light-glass
SynGallery-abl3-tex-light-glass: + glass
Rung 3 of the SynGallery instance-level artwork-recognition ablation ladder. 4,898 MET paintings × 5 camera viewpoints = 24,490 synthetic RGB images at 512×512, paired with their source photos and museum metadata.
In this rung, the scene varies textures, lighting and a glass sheet present with probability 0.25, while freezing frame variant/color, camera pose. Same schema, source images and index↔painting mapping as every other rung — they… See the full description on the dataset page: https://huggingface.co/datasets/patryk-bartkowiak/SynGallery-abl3-tex-light-glass.elpv-el-defectsoutfit-image-dataset
Dataset Card for Outfit Dataset
This dataset card documents the Clothing Outfit Dataset.It contains 30 original outfit images (shirt-pant combinations) with categorical and binary labels, with an augmented split expanding to 300 images.
Dataset Details
Dataset Description
Curated by: Bareethul Kader (Carnegie Mellon University)
Language(s): English (labels: formality, binary target)
License: CC BY 4.0
Repository: bareethul/clothing-outfits
Uses… See the full description on the dataset page: https://huggingface.co/datasets/bareethul/outfit-image-dataset.AIObj2