Vision-Flan/vision-flan

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We introduce Vision-Flan, the largest human-annotated visual instruction tuning dataset that consists of 200+ diverse vision-language tasks derived from 101 open-source computer vision datasets. Each task is equipped with an expert written instruction and carefully designed templates for the inputs and outputs. The dataset encompasses a wide range of tasks such as image captioning, visual question-answering, and visual understanding. Vision-Flan is built to support various researches and applications in vision-language models, pushing the boundaries of understanding and interaction between these two modalities. Researchers and practitioners can leverage this dataset to advance the state of the art vision-language models and develop innovative algorithms in a wide range of domains.

This dataset includes:

• 1,664,261 instances sourced from academic datasets
• 187 diverse tasks

Usage

from datasets import load_dataset

# save the dataset to disk
dataset = load_dataset("Vision-Flan/vision-flan")
dataset.save_to_disk("test.hf")

Run the script to unzip all data that is zipped

unzip.sh

Dataset Details

Dataset columns

conversations	id	task_name	image
LIST(DICT)	STRING	STRING	STRING

Collection and Annotation

Examples

Acknowledgement

Vision-Flan dataset is for research purpose only. Please carefully check the licenses of the original datasets before using Vision-Flan. We provide the URLs to the original datasets and their Bibtex on this page of our work. The images and tasks may be taken down at any time when requested by the original dataset owners or owners of the referenced images. If you hope to take down any tasks or the images, please contact Zhiyang Xu and Lifu Huang at zhiyangx@vt.edu and lifuh@cs.vt.edu.