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"""CASAS download script to get CASAS smart home datasets |
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""" |
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from __future__ import absolute_import |
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import os |
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import logging |
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import zipfile |
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import argparse |
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from fuel.downloaders.base import default_downloader |
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logger = logging.getLogger(__file__) |
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master_url = 'http://eecs.wsu.edu/~twang3/datasets/' |
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dataset_dict = { |
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'B1': 'B1.zip', |
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'B2': 'B2.zip', |
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'B3': 'B3.zip', |
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'bosch_legacy': 'bosch_legacy.zip' |
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} |
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def CASAS_download(directory, datasets): |
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"""Download CASAS datasets to directory |
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Args: |
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directory (:obj:`str`): path to directory to store the downloaded |
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datasets (:obj:`tuple` of :obj:`str`): list of datasets to download |
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""" |
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for dataset in datasets: |
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filename = dataset_dict.get(dataset, None) |
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if filename is None: |
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print('Cannot find dataset %s' % dataset) |
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print('Here are the available datasets:') |
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for key in dataset_dict.keys(): |
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print(' * %s' % key) |
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else: |
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# Download zipped files |
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default_downloader(directory=directory, |
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urls=[master_url + filename], |
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filenames=[filename], |
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clear=False) |
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# Expand it in place |
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file_path = os.path.join(directory, filename) |
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if os.path.exists(file_path): |
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zip_ref = zipfile.ZipFile(file_path, 'r') |
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zip_ref.extractall(directory) |
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zip_ref.close() |
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def main(): |
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""" |
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usage: casas_download.py [-h] [-d DIR] datasets [datasets ...] |
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Download CASAS datasets to a directory. |
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positional arguments: |
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datasets Dataset Names |
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optional arguments: |
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-h, --help show this help message and exit |
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-d DIR, --dir DIR Directory to store datasets |
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""" |
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parser = argparse.ArgumentParser(description='Download CASAS datasets to a directory.') |
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parser.add_argument('-d', '--dir', help='Directory to store datasets') |
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parser.add_argument('datasets', nargs='+', type=str, help='Dataset Names') |
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args = parser.parse_args() |
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dir_abs_path = os.path.abspath(os.path.expanduser(args.dir)) |
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if not os.path.isdir(dir_abs_path): |
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user_input = input('Directory %s does not exist. Do you want to create it? [Y/n] ' % |
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dir_abs_path) |
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if str.capitalize(user_input) == 'N': |
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exit() |
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CASAS_download(args.dir, tuple(args.datasets)) |
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if __name__ == '__main__': |
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main() |
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TinghuiWang /
pyActLearn
