datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DisasterVQA
DisasterVQA: A Visual Question Answering Benchmark Dataset for Disaster Scenes
Dataset Summary
DisasterVQA is a benchmark dataset for evaluating Vision-Language Models (VLMs) on disaster-response visual question answering. It contains 1,395 real-world disaster images and 4,405 expert-curated question–answer pairs covering floods, wildfires, and earthquakes.
The dataset includes three question types:
Binary (Yes/No)
Multiple-Choice
Open-Ended
Questions span… See the full description on the dataset page: https://huggingface.co/datasets/anwan/DisasterVQA.jma-gsi-disaster-action-corpus
JMA-GSI Disaster Action Corpus
A grounded, multilingual disaster-response dataset built from official Japanese government open data (JMA alert XML + JMA multilingual glossary + JMA forecast-area GIS + GSI designated evacuation shelters). Structured hazard alerts are transformed into easy-Japanese and multilingual (ja / easy-ja / en / vi / id / ne / my) action guidance, linked to hazard-compatible evacuation shelters, with full source traceability.
License (derived dataset): CC BY… See the full description on the dataset page: https://huggingface.co/datasets/edomaru/jma-gsi-disaster-action-corpus.DisasterVQA
DisasterVQA: A Visual Question Answering Benchmark Dataset for Disaster Scenes
Dataset Summary
DisasterVQA is a benchmark dataset for evaluating Vision-Language Models (VLMs) on disaster-response visual question answering. It contains 1,395 real-world disaster images and 4,405 expert-curated question–answer pairs covering floods, wildfires, and earthquakes.
The dataset includes three question types:
Binary (Yes/No)
Multiple-Choice
Open-Ended
Questions span situational… See the full description on the dataset page: https://huggingface.co/datasets/QCRI/DisasterVQA.