Published July 4, 2024 | Version v1

Landscape scenicness prompts

  • 1. ROR icon Vrije Universiteit Amsterdam
  • 2. ROR icon Institut national de recherche en sciences et technologies du numérique
  • 3. ROR icon Washington University in St. Louis
  • 4. ROR icon École Polytechnique Fédérale de Lausanne

Description

Reproduction repository for the paper titled "Prompt-guided and multimodal landscape scenicness assessments with vision-language models". This repo contains the following files:

  1. Prompts collected by our crowdsourcing effort
  2. CLIP-and SigLIP extracted embeddings of ScenicOrNot images
  3. Splits used for few-shot learning
  4. GeoJSON file containing geotagged ScenicOrNot labels for each image

The original ScenicOrNot images are hosted by Geograph, whose license terms do not allow re-sharing of the images. Instead, we make the embeddings used in our study available and provide scripts to download the original images on our Github repository, which also contains the code used for this study. Alternatively, please contact the authors for a copy of the SON images.

Files

scenicness_prompts.csv

Files (1.5 GB)

Name Size
md5:6c7e3d62e2360191cd042d5fc073da49
714.6 MB Download
md5:0e0ff4777e1f88cd4c7c31884cce34d4
714.6 MB Download
md5:44f185e8576cda6c2be066c4b4c8f57a
8.1 kB Preview Download
md5:8dd0db96ca03c6ff3eaf6f9ea1edd7bc
75.5 MB Preview Download
md5:64256dc0651d7f2e09b5cd0137520b20
7.8 kB Preview Download

Additional details

Software

Programming language
Python