fix
Browse files
data/hand-gesture-recognition-dataset.csv
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set_id
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0
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set_id,one,four,small,fist,me
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0,files/0/one.mp4,files/0/four.mp4,files/0/small.mp4,files/0/fist.mp4,files/0/me.mp4
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1,files/1/one.mp4,files/1/four.mp4,files/1/small.mp4,files/1/fist.mp4,files/1/me.mp4
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2,files/2/one.mp4,files/2/four.mp4,files/2/small.mp4,files/2/fist.mp4,files/2/me.mp4
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3,files/3/one.mp4,files/3/four.mp4,files/3/small.mp4,files/3/fist.mp4,files/3/me.mp4
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4,files/4/one.mp4,files/4/four.mp4,files/4/small.mp4,files/4/fist.mp4,files/4/me.mp4
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5,files/5/one.mp4,files/5/four.mp4,files/5/small.mp4,files/5/fist.mp4,files/5/me.mp4
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6,files/6/one.mp4,files/6/four.mp4,files/6/small.mp4,files/6/fist.mp4,files/6/me.mp4
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7,files/7/one.mp4,files/7/four.mp4,files/7/small.mp4,files/7/fist.mp4,files/7/me.mp4
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8,files/8/one.mp4,files/8/four.mp4,files/8/small.mp4,files/8/fist.mp4,files/8/me.mp4
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9,files/9/one.mp4,files/9/four.mp4,files/9/small.mp4,files/9/fist.mp4,files/9/me.mp4
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10,files/10/one.mp4,files/10/four.mp4,files/10/small.mp4,files/10/fist.mp4,files/10/me.mp4
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11,files/11/one.mp4,files/11/four.mp4,files/11/small.mp4,files/11/fist.mp4,files/11/me.mp4
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12,files/12/one.mp4,files/12/four.mp4,files/12/small.mp4,files/12/fist.mp4,files/12/me.mp4
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13,files/13/one.mp4,files/13/four.mp4,files/13/small.mp4,files/13/fist.mp4,files/13/me.mp4
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14,files/14/one.mp4,files/14/four.mp4,files/14/small.mp4,files/14/fist.mp4,files/14/me.mp4
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15,files/15/one.mp4,files/15/four.mp4,files/15/small.mp4,files/15/fist.mp4,files/15/me.mp4
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16,files/16/one.mp4,files/16/four.mp4,files/16/small.mp4,files/16/fist.mp4,files/16/me.mp4
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17,files/17/one.mp4,files/17/four.mp4,files/17/small.mp4,files/17/fist.mp4,files/17/me.mp4
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18,files/18/one.mp4,files/18/four.mp4,files/18/small.mp4,files/18/fist.mp4,files/18/me.mp4
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19,files/19/one.mov,files/19/four.MOV,files/19/small.MOV,files/19/fist.MOV,files/19/me.MOV
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20,files/20/one.mp4,files/20/four.mp4,files/20/small.mp4,files/20/fist.mp4,files/20/me.mp4
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21,files/21/one.mp4,files/21/four.mp4,files/21/small.mp4,files/21/fist.mp4,files/21/me.mp4
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22,files/22/one.mp4,files/22/four.mp4,files/22/small.mp4,files/22/fist.mp4,files/22/me.mp4
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23,files/23/one.mp4,files/23/four.mp4,files/23/small.mp4,files/23/fist.mp4,files/23/me.mp4
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24,files/24/one.mp4,files/24/four.mp4,files/24/small.mp4,files/24/fist.mp4,files/24/me.mp4
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25,files/25/one.mp4,files/25/four.mp4,files/25/small.mp4,files/25/fist.mp4,files/25/me.mp4
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26,files/26/one.mp4,files/26/four.mp4,files/26/small.mp4,files/26/fist.mp4,files/26/me.mp4
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27,files/27/one.mp4,files/27/four.mp4,files/27/small.mp4,files/27/fist.mp4,files/27/me.mp4
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hand-gesture-recognition-dataset.py
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import datasets
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import pandas as pd
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_CITATION = """\
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@InProceedings{huggingface:dataset,
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title = {hand-gesture-recognition-dataset},
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author = {TrainingDataPro},
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year = {2023}
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}
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"""
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_DESCRIPTION = """\
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The dataset consists of videos showcasing individuals demonstrating 5 different
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hand gestures (*"one", "four", "small", "fist", and "me"*). Each video captures
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a person prominently displaying a single hand gesture, allowing for accurate
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identification and differentiation of the gestures.
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The dataset offers a diverse range of individuals performing the gestures,
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enabling the exploration of variations in hand shapes, sizes, and movements
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across different individuals.
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The videos in the dataset are recorded in reasonable lighting conditions and
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with adequate resolution, to ensure that the hand gestures can be easily
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observed and studied.
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"""
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_NAME = 'hand-gesture-recognition-dataset'
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_HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}"
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_LICENSE = "cc-by-nc-nd-4.0"
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_DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/"
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class HandGestureRecognitionDataset(datasets.GeneratorBasedBuilder):
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# import datasets
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# import pandas as pd
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# _CITATION = """\
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# @InProceedings{huggingface:dataset,
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# title = {hand-gesture-recognition-dataset},
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# author = {TrainingDataPro},
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# year = {2023}
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# }
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# """
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# _DESCRIPTION = """\
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# The dataset consists of videos showcasing individuals demonstrating 5 different
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# hand gestures (*"one", "four", "small", "fist", and "me"*). Each video captures
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# a person prominently displaying a single hand gesture, allowing for accurate
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# identification and differentiation of the gestures.
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# The dataset offers a diverse range of individuals performing the gestures,
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# enabling the exploration of variations in hand shapes, sizes, and movements
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# across different individuals.
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# The videos in the dataset are recorded in reasonable lighting conditions and
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# with adequate resolution, to ensure that the hand gestures can be easily
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# observed and studied.
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# """
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# _NAME = 'hand-gesture-recognition-dataset'
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# _HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}"
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# _LICENSE = "cc-by-nc-nd-4.0"
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# _DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/"
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# class HandGestureRecognitionDataset(datasets.GeneratorBasedBuilder):
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# def _info(self):
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# return datasets.DatasetInfo(description=_DESCRIPTION,
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# features=datasets.Features({
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# 'set_id': datasets.Value('int32'),
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# 'fist': datasets.Value('string'),
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# 'four': datasets.Value('string'),
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# 'me': datasets.Value('string'),
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# 'one': datasets.Value('string'),
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# 'small': datasets.Value('string')
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# }),
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# supervised_keys=None,
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# homepage=_HOMEPAGE,
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# citation=_CITATION,
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# license=_LICENSE)
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# def _split_generators(self, dl_manager):
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# files = dl_manager.download_and_extract(f"{_DATA}files.zip")
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# annotations = dl_manager.download(f"{_DATA}{_NAME}.csv")
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# files = dl_manager.iter_files(files)
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# return [
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# datasets.SplitGenerator(name=datasets.Split.TRAIN,
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# gen_kwargs={
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# "files": files,
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# 'annotations': annotations
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# }),
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# ]
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# def _generate_examples(self, files, annotations):
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# annotations_df = pd.read_csv(annotations, sep=';')
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# files = sorted(files)
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# files = [files[i:i + 5] for i in range(0, len(files), 5)]
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# for idx, files_set in enumerate(files):
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# set_id = int(files_set[0].split('/')[2])
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# data = {'set_id': set_id}
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# for file in files_set:
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# file_name = file.split('/')[3]
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# if 'fist' in file_name.lower():
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# data['fist'] = file
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# elif 'four' in file_name.lower():
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# data['four'] = file
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# elif 'me' in file_name.lower():
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# data['me'] = file
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# elif 'one' in file_name.lower():
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# data['one'] = file
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# elif 'small' in file_name.lower():
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# data['small'] = file
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# yield idx, data
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