Dataset Generation for Korean Urban Parks Analysis with Large Language Models
Pages 5375 - 5379
Abstract
Understanding how urban parks are utilized and perceived by the public is crucial for effective urban planning and management. This study introduces a novel dataset derived from Instagram, using 42,187 images tagged with #Seoul and #Park hashtags from 2017 to 2023. These images were filtered using InternLM-XComposer2, a Multimodal Large Language Model (MLLM), to confirm they depicted park scenes. GPT-4 then annotated the filtered images, resulting in 29,866 valid image annotations of physical elements, human activities, animals, and emotions. The dataset is publicly available at https://huggingface.co/datasets/RedBall/seoul-urban-park-analysis-by-llm.
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Index Terms
- Dataset Generation for Korean Urban Parks Analysis with Large Language Models
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October 2024
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Published: 21 October 2024
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- National Research Foundation of Korea grant funded by the Korean government(MSIT)
- Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT)
- Korea Planning & Evaluation Institute of Industrial Technology (KEIT) grant funded by the Korea government (MOTIE)
- Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT)
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