datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ade20k-panoptic-demo
Dataset Card for "ade20k-panoptic-demo"
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PanoCity
PanoCity Dataset
A Large-Scale Aerial Panoramic Dataset for 3D Scene Understanding
📊 Dataset Statistics
Attribute
Value
Total Size
1.4 TB
Cities
Beijing (20 blocks), Jinan (76 blocks), Ningbo (41 blocks)
Panoramic RGB Images
119,537 (2048×4096)
Panoramic Depth Maps
119,537 (2048×4096)
Total Images
239,074
Image Format
PNG
📂 Data Structure
PanoCity/
├── splits_config.json # Official train/test splits
├──… See the full description on the dataset page: https://huggingface.co/datasets/YijingGuo/PanoCity.PANORAMA
PANORAMA - Public Training & Development Dataset
Contrast-enhanced (portal-venous) abdominal CT for pancreatic ductal
adenocarcinoma (PDAC) detection, from the PANORAMA challenge organised by the
Diagnostic Image Analysis Group (DIAG), Radboud UMC. This is the largest public
PDAC CT dataset and the first public PDAC detection challenge.
Mirror of the official public training/development cohort only. The hidden
validation and test sets used for the challenge leaderboard are not… See the full description on the dataset page: https://huggingface.co/datasets/MedOtter/PANORAMA.PanScale
PanScale
Dataset Summary
PanScale is a remote-sensing pansharpening dataset with paired multispectral (ms) and panchromatic (pan) TIFF images for cross-scale evaluation.
Total pairs: 7,559
Disk size: ~6.9 GB
Format: 8-bit TIFF
Supported Tasks
Image Fusion (Cross-scale Pansharpening)
Subsets at a Glance
Subset
Splits
# Pairs
MS size
PAN size
PAN/MS scale
jilin
train200, test200/400/800
1,157
200-800
200-800
1.0
landsat
train256… See the full description on the dataset page: https://huggingface.co/datasets/kecao/PanScale.PanoInfinigen🗃️ PanoInfinigen Dataset
PanoInfinigen is a synthetic dataset of high-resolution panoramic images in ERP, featuring perfectly aligned RGB, Depth, and Surface Normals. This dataset was generated using a modified Infinigen framework to support wide-angle panoramic geometry, plus the iCity procedural city generator for the urban split.
It serves as the primary training data for PaGeR, a single-step diffusion model for zero-shot panoramic depth… See the full description on the dataset page: https://huggingface.co/datasets/prs-eth/PanoInfinigen.pandabench
PandaBench
Paper | Project Page | Code
PandaBench (and PandaSet) is an image distortion benchmark designed for evaluating perceptual comparison and distortion-aware visual reasoning. It introduces the task of learning a Distortion Graph (DG), representing dense degradation information such as distortion type, severity, and quality scores in a compact, interpretable graph structure grounded in image regions.
PandaSet (the train/val folders) is used to train the model (Panda), while… See the full description on the dataset page: https://huggingface.co/datasets/kjanjua26/pandabench.Pancreatic-CT-CBCT-SEG
Pancreatic-CT-CBCT-SEG
Breath-hold CT and cone-beam CT (CBCT) images with expert manual
organ-at-risk (OAR) segmentations from radiation treatments of locally
advanced pancreatic cancer at Memorial Sloan Kettering Cancer Center.
Dataset Details
Field
Value
Modality
CT (planning, breath-hold, contrast-enhanced) + CBCT (kV, deep-inspiration breath-hold)
Body part
Upper abdomen — gastrointestinal organs-at-risk
Task
3D multi-class segmentation (2… See the full description on the dataset page: https://huggingface.co/datasets/MedOtter/Pancreatic-CT-CBCT-SEG.dental-panoramic-xray-yolo
Dental Panoramic X-Ray Detection Dataset (YOLO Format)
Combined dataset for dental pathology detection on panoramic radiographs, in YOLO format. Built for training liodon-ai/dental-panoramic-detector.
Classes
ID
Name
Description
0
caries
Dental caries and deep caries
1
periapical_lesion
Periapical / apical periodontitis
2
impacted_tooth
Impacted and wisdom teeth
Dataset Sources
Source
Images
Boxes
License
DENTEX
724
3… See the full description on the dataset page: https://huggingface.co/datasets/liodon-ai/dental-panoramic-xray-yolo.GenEx-DB-Panorama-World
GenEx-DB-Panorama-World 🎞️🌍
This is the GenEx-DB panorama dataset for world initialization.
The dataset contains 120,000 panorama images generated by Flux-Dev-Panorama-LoRA-2, the prompts are from ``.
Each row is pairs with its generation prompt and extracted front view image from the panorama.
The dataset has been split into train, validation, test at 100,000, 10,000, 10,000.
🚀 Usage
from datasets import load_dataset
# Login using e.g. `huggingface-cli login` to… See the full description on the dataset page: https://huggingface.co/datasets/genex-world/GenEx-DB-Panorama-World.PanoEnv
CVPR 2026 Highlight - PanoEnv-QA: A Large-Scale Geometry-Grounded Panoramic VQA Benchmark for 3D Spatial Intelligence
📖 Overview
PanoEnv-QA is a large-scale Visual Question Answering benchmark designed specifically to probe 3D spatial intelligence on Equirectangular Projection (ERP) panoramas. Built from synthetic but photorealistic 3D environments (TartanAir), PanoEnv-QA offers over 14.8K questions spanning five categories that progressively… See the full description on the dataset page: https://huggingface.co/datasets/7zkk/PanoEnv.OmniSpatial
OmniSpatial Test Dataset
Spatial reasoning benchmark for vision-language models (test split).
Note: Images are stored in the image_files/ folder. The image_path column contains the relative path to each image.
Dataset Structure
Columns
id: Sample identifier
question: The spatial reasoning question
options: List of answer choices
answer: Correct answer index (0-3)
gt: Ground truth answer letter (A/B/C/D)
task_type: Main task category
sub_task_type: Specific… See the full description on the dataset page: https://huggingface.co/datasets/pangyyyyy/OmniSpatial.SeeU45_PreProcessedHFbedPanNuke
PanNuke
Description
PanNuke is a semi-automatically generated dataset for nuclei instance segmentation and classification, providing comprehensive nuclei annotations across 19 tissue types and 5 distinct cell categories. The dataset includes a total of 189,744 labeled nuclei, each accompanied by an instance segmentation mask, and contains 7,901 images, each sized 256×256 pixels. The images were captured at x40 magnification with a resolution of 0.25 µm/pixel. The dataset… See the full description on the dataset page: https://huggingface.co/datasets/RationAI/PanNuke.PAP-12K Panoramic Affordance Prediction
Zixin Zhang1*, Chenfei Liao1*, Hongfei Zhang1, Harold H. Chen1, Kanghao Chen1, Zichen Wen3, Litao Guo1, Bin Ren4, Xu Zheng1, Yinchuan Li6, Xuming Hu1, Nicu Sebe5, Ying-Cong Chen1,2†
1HKUST(GZ), 2HKUST, 3SJTU, 4MBZUAI, 5UniTrento, 6Knowin
*Equal contribution †Corresponding author
Official repository for the paper: Panoramic Affordance Prediction.
Affordance prediction serves as a critical bridge between perception and… See the full description on the dataset page: https://huggingface.co/datasets/PanoramaOrg/PAP-12K.BRIDGE
BRIDGE — Qwen Image Edit Dataset
Part of the dataset used in BRIDGE: Background Routing and Isolated Discrete Gating for Coarse-Mask Local Editing.
FLUX subject-condition extension (2026-09-19)
The same BRIDGE method is trained with LoRA on Qwen and full-transformer
fine-tuning on FLUX. The FLUX dataset adds a generated subject-reference image
condition. See the extension documentation.
Exact FLUX split: 27,834 training rows, 3,092 test rows.
30,926 selected… See the full description on the dataset page: https://huggingface.co/datasets/PANDATREE/BRIDGE.PanNuke
PanNuke
Pan-Cancer H&E Nuclei Instance Segmentation and Classification dataset
(Gamper et al., ECDP 2019; arXiv:2003.10778). Mirrored from the
Warwick TIA Centre release.
Composition
7,901 RGB patches of 256x256 at 40x magnification (~0.25 um/pixel)
19 tissue types pooled from TCGA / GTEx (Breast, Colon, Lung, Kidney,
Prostate, Stomach, Ovarian, Bladder, Esophagus, Pancreatic, Thyroid, Skin,
Cervix, Adrenal_gland, Bile-duct, Liver, HeadNeck, Testis, Uterus)
~189… See the full description on the dataset page: https://huggingface.co/datasets/MedOtter/PanNuke.cloudflare-imgbedFedJam
FedJam Dataset
The FedJam dataset is a multimodal dataset for jamming detection and classification in wireless networks, combining time–frequency spectrogram images with
cross-layer network KPI time series. Each sample includes aligned vision and time-series modalities, allowing joint analysis of physical-layer signal behavior
and network-layer performance. The data are collected from a real over-the-air experimental testbed, under a variety of operating conditions, including… See the full description on the dataset page: https://huggingface.co/datasets/panitsasi/FedJam.electrical-panels-dataset
Electrical Panels Detection Dataset
Auto-scraped, CLIP-filtered, YOLOE-26 annotated.
Classes: 107
Target images per class: 500
Annotation: Two-pass YOLOE-26m + SAM
Teacher model: YOLOE-26m-seg
Student model: YOLO26n (knowledge distilled)
solar-panel-inspectionscientry_data
Scientry Data
Contains Images & PDFs to generate Images based on Research Paper's PDF
Curated by: Nayan Kasturi
License: MIT
Dataset Sources
arXiv
DOI
Google Scholar
G4F
Franka_panda_parallel_hand_realThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "franka",
"total_episodes": 0,
"total_frames": 0,
"total_tasks": 0,
"total_videos": 0,
"total_chunks": 0,
"chunks_size": 1000,
"fps": 15,
"splits": {},
"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/GVLA/Franka_panda_parallel_hand_real.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.Pantheon-Agent-Trajectory
🏛️ Pantheon Agent Trajectory Gallery
Curated end-to-end agent runs from PantheonOS — an open multi-agent framework for scientific computing.
Each "trajectory" captures a complete chat session: the user prompt, every reasoning/tool step the agent(s) took, the code that was run, the figures that were produced, and the final report. Trajectories are fully inspectable and reproducible, designed for transparency, teaching, and benchmarking.
🔗 Browse the gallery (live):… See the full description on the dataset page: https://huggingface.co/datasets/NaNg/Pantheon-Agent-Trajectory.VisualSphinx-V1-Raw-Panelsbank-statement-structure-recognition
Synthetic Bank Statement Table Structure Dataset
A synthetically generated collection of bank statement images with pixel-perfect, automatically-produced bounding box annotations for table structure recognition (TSR).
🔑 In one sentence: fake bank statements + auto-generated YOLO labels for every table cell, built so you can train table-detection models (TATR, DETR, YOLO) without manual annotation.
At a Glance
Task
Object Detection → Table… See the full description on the dataset page: https://huggingface.co/datasets/Panhapich/bank-statement-structure-recognition.panda-pick-place-lerobot-14-18-58_01-06-2026
Franka Panda Pick-and-Place — LeRobot v3 Dataset
Visuomotor behavior-cloning dataset collected in MuJoCo with a simulated Franka Emika Panda arm.
Recorded in LeRobot v3 format (Parquet + MP4 shards).
Load
from lerobot.datasets import LeRobotDataset
ds = LeRobotDataset("av120/panda-pick-place-lerobot-14-18-58_01-06-2026")
Task
Pick up a cube and place it ~30 cm to the side using a scripted IK state-machine demonstrator.
Box position is randomized ±5… See the full description on the dataset page: https://huggingface.co/datasets/av120/panda-pick-place-lerobot-14-18-58_01-06-2026.OCR-neulab-PangeaInstruct-OCR-clean
Description
French part of the neulab/PangeaInstruct dataset (OCR data only) that we processed for a visual question answering task where answer is a caption.
Citation
@article{yue2024pangeafullyopenmultilingual,
title={Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages},
author={Xiang Yue and Yueqi Song and Akari Asai and Seungone Kim and Jean de Dieu Nyandwi and Simran Khanuja and Anjali Kantharuban and Lintang Sutawika and Sathyanarayanan Ramamoorthy… See the full description on the dataset page: https://huggingface.co/datasets/lbourdois/OCR-neulab-PangeaInstruct-OCR-clean.panda_vla_v5_advancedThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "panda",
"total_episodes": 1600,
"total_frames": 221844,
"total_tasks": 8,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 10,
"splits": {
"train": "0:1600"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/mrAms/panda_vla_v5_advanced.