Datasets:
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Error code: DatasetGenerationCastError Exception: DatasetGenerationCastError Message: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 2 new columns ({'door_opening_1.mp4', '6'}) and 2 missing columns ({'0', 'AXrvCEVn5HM-001.mp4'}). This happened while the csv dataset builder was generating data using hf://datasets/hdong51/Human-Animal-Cartoon/HAC_train_only_cartoon.csv (at revision e74938ea09a8b296f6fd8afbb89bfc53dcbc9100) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations) Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table pa_table = table_cast(pa_table, self._schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast door_opening_1.mp4: string 6: int64 -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 496 to {'AXrvCEVn5HM-001.mp4': Value(dtype='string', id=None), '0': Value(dtype='int64', id=None)} because column names don't match During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1572, in compute_config_parquet_and_info_response parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet( File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1136, in stream_convert_to_parquet builder._prepare_split( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single raise DatasetGenerationCastError.from_cast_error( datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 2 new columns ({'door_opening_1.mp4', '6'}) and 2 missing columns ({'0', 'AXrvCEVn5HM-001.mp4'}). This happened while the csv dataset builder was generating data using hf://datasets/hdong51/Human-Animal-Cartoon/HAC_train_only_cartoon.csv (at revision e74938ea09a8b296f6fd8afbb89bfc53dcbc9100) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
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AXrvCEVn5HM-001.mp4
string | 0
int64 |
---|---|
BV13TS990ZY-001.mp4 | 0 |
DAnk0ORUcrQ-001.mp4 | 0 |
EH5YYezBNzs-001.mp4 | 0 |
El_MmyZolp8-001.mp4 | 0 |
ErH7JnItZto-001.mp4 | 0 |
KEoUIz15NGo-001.mp4 | 0 |
KhYooJbM27A-001.mp4 | 0 |
Rb8M54Bx_D4-001.mp4 | 0 |
SoR1ElwEoPg-001.mp4 | 0 |
T4U6JKT-c0c-001.mp4 | 0 |
T4U6JKT-c0c-002.mp4 | 0 |
bsks-HasXSg-001.mp4 | 0 |
czB5sY9Y0N8-001.mp4 | 0 |
ixhdyDEQukw-001.mp4 | 0 |
mGDqhBV_SpY-001.mp4 | 0 |
tYAf5jlnzeg-001.mp4 | 0 |
ziVpfQaCID8-001.mp4 | 0 |
zjvHEVWJK4I-001.mp4 | 0 |
-hAno2-MdLY-006.mp4 | 1 |
-hAno2-MdLY-007.mp4 | 1 |
-hAno2-MdLY-008.mp4 | 1 |
-hAno2-MdLY-009.mp4 | 1 |
-hAno2-MdLY-010.mp4 | 1 |
-hAno2-MdLY-011.mp4 | 1 |
-hAno2-MdLY-012.mp4 | 1 |
-hAno2-MdLY-013.mp4 | 1 |
-hAno2-MdLY-014.mp4 | 1 |
-hAno2-MdLY-015.mp4 | 1 |
-hAno2-MdLY-016.mp4 | 1 |
-hAno2-MdLY-017.mp4 | 1 |
-hAno2-MdLY-018.mp4 | 1 |
-hAno2-MdLY-019.mp4 | 1 |
-hAno2-MdLY-020.mp4 | 1 |
10KOFNxiLa0-001.mp4 | 1 |
10KOFNxiLa0-002.mp4 | 1 |
8uXovEw-6Pc-001.mp4 | 1 |
ML8bsnBTO3I-001.mp4 | 1 |
SpHNCvksFKI-001.mp4 | 1 |
Tq0gwLY4yQE-001.mp4 | 1 |
p4kM9VetmdA-001.mp4 | 1 |
p4kM9VetmdA-002.mp4 | 1 |
pX4cE70s488-001.mp4 | 1 |
pX4cE70s488-002.mp4 | 1 |
pX4cE70s488-003.mp4 | 1 |
pX4cE70s488-004.mp4 | 1 |
pX4cE70s488-005.mp4 | 1 |
pX4cE70s488-006.mp4 | 1 |
tKJdtStWMas-001.mp4 | 1 |
2Syd_BUbl5A-002.mp4 | 2 |
3h4UkvhQQMU-001.mp4 | 2 |
GI4iAcTA9KY-001.mp4 | 2 |
GI4iAcTA9KY-002.mp4 | 2 |
IaC4wnSUlGE-001.mp4 | 2 |
IbZM_l6_ugA-001.mp4 | 2 |
M7S80qzlC3k-001.mp4 | 2 |
MLwSLMPBJQU-001.mp4 | 2 |
MV5IODe0v5U-001.mp4 | 2 |
MoUH5mUeKL8-001.mp4 | 2 |
S8zhnXZdTFM-001.mp4 | 2 |
TQwUjl-HmZo-001.mp4 | 2 |
TQwUjl-HmZo-002.mp4 | 2 |
Tish3KkNnLc-001.mp4 | 2 |
dx3X-qtnQkE-001.mp4 | 2 |
dx3X-qtnQkE-002.mp4 | 2 |
hdn1R7O6cgA-001.mp4 | 2 |
hdn1R7O6cgA-002.mp4 | 2 |
hdn1R7O6cgA-003.mp4 | 2 |
hjjDh2NOup4-001.mp4 | 2 |
jZFh75kRWzY-001.mp4 | 2 |
jZFh75kRWzY-002.mp4 | 2 |
jxXNwhXIobc-001.mp4 | 2 |
jxXNwhXIobc-002.mp4 | 2 |
mOWBwFqltYA-001.mp4 | 2 |
tuBSFDR0mbw-001.mp4 | 2 |
ud13yQc5njM-001.mp4 | 2 |
ud13yQc5njM-002.mp4 | 2 |
ud13yQc5njM-003.mp4 | 2 |
ud13yQc5njM-004.mp4 | 2 |
ud13yQc5njM-005.mp4 | 2 |
ud13yQc5njM-006.mp4 | 2 |
ud13yQc5njM-007.mp4 | 2 |
ud13yQc5njM-008.mp4 | 2 |
ud13yQc5njM-009.mp4 | 2 |
wE_dvTtnUoc-001.mp4 | 2 |
wE_dvTtnUoc-002.mp4 | 2 |
wE_dvTtnUoc-003.mp4 | 2 |
xcgW3s-NBBI-001.mp4 | 2 |
zRYtQsowie0-001.mp4 | 2 |
zRYtQsowie0-002.mp4 | 2 |
DaKkNt2Yb3A-001.mp4 | 3 |
EeKFKFiHFf4-001.mp4 | 3 |
F-DpCQlLJ3U-001.mp4 | 3 |
JuZnd2jey9Y-001.mp4 | 3 |
JuZnd2jey9Y-002.mp4 | 3 |
MLwSLMPBJQU-002.mp4 | 3 |
MeVXdwz6KNY-001.mp4 | 3 |
MoUH5mUeKL8-002.mp4 | 3 |
PVlKTr2xx-0-001.mp4 | 3 |
RbBAE9ZSvKI-001.mp4 | 3 |
UASWCSuB_uc-001.mp4 | 3 |
Human-Animal-Cartoon dataset
Our Human-Animal-Cartoon (HAC) dataset consists of seven actions (‘sleeping’, ‘watching tv’, ‘eating’, ‘drinking’, ‘swimming’, ‘running’, and ‘opening door’) performed by humans, animals, and cartoon figures, forming three different domains. We collect 3381 video clips from the internet with around 1000 for each domain and provide three modalities in our dataset: video, audio, and pre-computed optical flow.
The dataset can be used for Multi-modal Domain Generalization and Adaptation. More details are in SimMMDG paper and code.
Related Projects
SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
MOOSA: Towards Multimodal Open-Set Domain Generalization and Adaptation through Self-supervision
MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities
Citation
If you find our dataset useful in your research please consider citing our paper:
@inproceedings{dong2023SimMMDG,
title={Sim{MMDG}: A Simple and Effective Framework for Multi-modal Domain Generalization},
author={Dong, Hao and Nejjar, Ismail and Sun, Han and Chatzi, Eleni and Fink, Olga},
booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
year={2023}
}
![](/datasets/hdong51/Human-Animal-Cartoon/resolve/main/hac.jpg)
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