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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 291, in _generate_tables
                  df = pandas_read_json(f)
                       ^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 36, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 791, in read_json
                  json_reader = JsonReader(
                                ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 905, in __init__
                  self.data = self._preprocess_data(data)
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 917, in _preprocess_data
                  data = data.read()
                         ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 844, in read_with_retries
                  out = read(*args, **kwargs)
                        ^^^^^^^^^^^^^^^^^^^^^
                File "<frozen codecs>", line 322, in decode
              UnicodeDecodeError: 'utf-8' codec can't decode byte 0x93 in position 0: invalid start byte
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 247, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 4376, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2658, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2836, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2374, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 294, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 257, in _generate_tables
                  pa_table = paj.read_json(
                             ^^^^^^^^^^^^^^
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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Korean Sign Language Keypoint Dataset

Dataset Summary

This dataset contains the project keypoint cache used for Korean Sign Language isolated-word model training/evaluation experiments.

The keypoints were extracted with MediaPipe Holistic from a subset of the AI-Hub sign-language video dataset.

Source/reference: https://aihub.or.kr/aihubdata/data/view.do?srchOptnCnd=OPTNCND001&currMenu=115&topMenu=100&searchKeyword=%EC%88%98%EC%96%B4&aihubDataSe=data&dataSetSn=103

Contents

  • keypoint_cache.zip: compressed archive of the local keypoint_cache/ folder
  • Extracted archive structure:
    • keypoint_cache/1.Training/
    • keypoint_cache/2.Validation/
  • Keypoint files: 269518 .npy files in the local source folder
  • Local uncompressed folder size before upload: 27.4 GB
  • Uploaded archive size: 20.2 GB
  • source_metadata.txt: local source metadata copied from /home/moon/metadata.txt

The archive is used instead of uploading hundreds of thousands of individual .npy files so that the dataset can be downloaded and reproduced more reliably.

Source Subset Metadata

AI ν•™μŠ΅μš© λ‹€μš΄λ‘œλ“œ
β”œβ”€ μˆ˜μ–΄ μ˜μƒ/
   β”œβ”€ 1.Training/  (33 files)
   β”‚  β”œβ”€ [라벨]01_real_word_morpheme.zip
   β”‚  β”œβ”€ [μ›μ²œ]01~32_real_word_video.zip
   β”‚
   └─ 2.Validation/  (2 files)
      β”œβ”€ [라벨]01_real_word_morpheme.zip
      β”œβ”€ [μ›μ²œ]01_real_word_video.zip

Usage

Download and extract:

unzip keypoint_cache.zip

The extracted folder should contain keypoint_cache/1.Training and keypoint_cache/2.Validation.

Source And Licensing Notes

The raw videos originated from AI-Hub sign-language data. This repository contains derived keypoint cache files, not the original raw AI-Hub videos. Users should review and follow AI-Hub access/license terms for any downstream use.

AI Tools Used

AI tool used: Codex. Codex was used to package/upload the dataset and draft this dataset card. Codex was not used to create the source AI-Hub videos, keypoint labels, or original data split.

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