Datasets:
Modalities:
Geospatial
Languages:
English
Size:
1M<n<10M
Tags:
street view imagery
open data
data fusion
urban analytics
GeoAI
volunteered geographic information
License:
folder to download only one folder of the dataset repository
Browse files- download_folder.py +41 -0
download_folder.py
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from huggingface_hub import HfApi, hf_hub_download
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def download_folder(repo_id, repo_type, folder_path, local_dir):
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"""
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Download an entire folder from a huggingface dataset repository.
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repo_id : string
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The ID of the repository (e.g., 'username/repo_name').
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repo_type : string
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Type of the repo, dataset or model.
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folder_path : string
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The path to the folder within the repository.
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local_dir : string
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Local folder to download the data. This mimics git behaviour
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"""
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api = HfApi()
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# list all files in the repo, keep the ones within folder_path
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all_files = api.list_repo_files(repo_id, repo_type=repo_type)
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files_list = [f for f in all_files if f.startswith(folder_path)]
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# download each of those files
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for file_path in files_list:
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hf_hub_download(repo_id=repo_id, repo_type=repo_type,
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filename=file_path, local_dir=local_dir)
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# Download entire data/ folder
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repo_id = "NUS-UAL/global-streetscapes"
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repo_type = "dataset"
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folder_path = "data/" # replace the folder you want
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local_dir = "global-streetscapes/"
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# By degfault, huggingface download them to the .cache/huggingface folder
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download_folder(repo_id, repo_type, folder_path, local_dir)
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# Download 2 additional files
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hf_hub_download(repo_id=repo_id, repo_type=repo_type,
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filename="cities688.csv", local_dir=local_dir)
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hf_hub_download(repo_id=repo_id, repo_type=repo_type,
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filename="info.csv", local_dir=local_dir)
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