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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: RuntimeError
Message: File 'Images/Amelia/Anger/00000.jpg' is encrypted, password required for extraction
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 322, in compute
compute_first_rows_from_parquet_response(
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response
rows_index = indexer.get_rows_index(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 640, in get_rows_index
return RowsIndex(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 521, in __init__
self.parquet_index = self._init_parquet_index(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 538, in _init_parquet_index
response = get_previous_step_or_raise(
File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 591, in get_previous_step_or_raise
raise CachedArtifactError(
libcommon.simple_cache.CachedArtifactError: The previous step failed.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 96, in get_rows_or_raise
return get_rows(
File "/src/libs/libcommon/src/libcommon/utils.py", line 197, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 73, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1393, in __iter__
example = _apply_feature_types_on_example(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1082, in _apply_feature_types_on_example
decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1983, in decode_example
return {
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1984, in <dictcomp>
column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1349, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/image.py", line 183, in decode_example
with xopen(path, "rb", download_config=download_config) as f:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1227, in xopen
file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 135, in open
return self.__enter__()
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 103, in __enter__
f = self.fs.open(self.path, mode=mode)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 1293, in open
f = self._open(
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 129, in _open
out = self.zip.open(path, mode.strip("b"), force_zip64=self.force_zip_64)
File "/usr/local/lib/python3.9/zipfile.py", line 1563, in open
raise RuntimeError("File %r is encrypted, password "
RuntimeError: File 'Images/Amelia/Anger/00000.jpg' is encrypted, password required for extractionNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
FExGAN-Meta: Facial Expression Generation with Meta-Humans
This is a facial expression image dataset proposed in the following article:
FExGAN-Meta: Facial Expression Generation with Meta-Humans
Fill the Below Form to get the password
Citation
If you use any part of this dataset for experiments, please cite the following article.
@article{Siddiqui_FExGAN-Meta_2022,
author = {{Siddiqui}, J. Rafid},
title = {{FExGAN-Meta: Facial Expression Generation with Meta-Humans}},
journal = {ArXiv e-prints},
archivePrefix = "arXiv:2203.05975",
keywords = {Deep Learning, GAN, Facial Expressions},
year = {2022}
url = {https://arxiv.org/abs/2203.05975},
DOI: 10.31219/osf.io/ygdrt
}
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