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import os
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import numpy as np
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import datasets
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_DESCRIPTION = """
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VOYA Vietnamese Sign Language (VSL) dataset.
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Dataset gồm các chuỗi keypoints đã trích xuất bằng MediaPipe cho nhận dạng ngôn ngữ ký hiệu.
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Mỗi sample có shape (60, 1605), lưu trong 'sequences', với nhãn tương ứng trong 'labels'.
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"""
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_HOMEPAGE = "https://huggingface.co/datasets/Kateht/VOYA_VSL"
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_LICENSE = "MIT"
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_CITATION = """
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@misc{voya_vsl_2025,
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author = {Kateht et al.},
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title = {VOYA Vietnamese Sign Language Dataset},
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year = {2025},
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publisher = {Hugging Face},
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howpublished = {\\url{https://huggingface.co/datasets/Kateht/VOYA_VSL}}
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}
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"""
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class VOYAVSLConfig(datasets.BuilderConfig):
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def __init__(self, **kwargs):
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super().__init__(**kwargs)
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class VOYAVSL(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [
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VOYAVSLConfig(
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name="default",
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version=datasets.Version("1.0.0"),
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description="VOYA Vietnamese Sign Language dataset",
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)
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"sequences": datasets.Array2D(
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shape=(60, 1605), dtype="float32"
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),
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"labels": datasets.Value("int32"),
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}
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),
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supervised_keys=("sequences", "labels"),
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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data_dir = dl_manager.download_and_extract(
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"https://huggingface.co/datasets/Kateht/VOYA_VSL/resolve/main/Merged"
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)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={"data_dir": data_dir},
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),
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]
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def _generate_examples(self, data_dir):
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idx = 0
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for fname in sorted(os.listdir(data_dir)):
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if not fname.endswith(".npz"):
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continue
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fpath = os.path.join(data_dir, fname)
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data = np.load(fpath)
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sequences, labels = data["sequences"], data["labels"]
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for seq, label in zip(sequences, labels):
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yield idx, {
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"sequences": seq.astype("float32"),
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"labels": int(label),
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}
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idx += 1
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