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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ParserError
Message:      Error tokenizing data. C error: Expected 1 fields in line 4, saw 2

Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 249, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/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/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 198, in _generate_tables
                  for batch_idx, df in enumerate(csv_file_reader):
                                       ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
                  return self.get_chunk()
                         ~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
                  return self.read(nrows=size)
                         ~~~~~~~~~^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1923, in read
                  ) = self._engine.read(  # type: ignore[attr-defined]
                      ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      nrows
                      ^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
                  chunks = self._reader.read_low_memory(nrows)
                File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
                File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
                File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
                File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
                File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
              pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 4, saw 2

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Example Camera Trap Survey

License WildINTEL

Version: 1.0

A small, synthetic camera-trap dataset — 2 deployments, 5 media files (one private), 5 observations — used as a wildintel-publisher example. Not real field data; the images are generated placeholders, not photographs.

Dataset format

This dataset is distributed as a Camtrap DP data package — the community standard for structuring and sharing camera-trap data.

.
├── datapackage.json      ← Camtrap DP metadata descriptor
├── deployments.csv       ← camera deployment records
├── media.csv             ← media (image) records — public media only, filePath is remote
├── observations.csv      ← classification/observation records
├── images/               ← the public image files referenced in media.csv
├── camtrapdp-local.zip   ← same package, but media.csv's filePath is relative to images/
├── checksums-sha256.txt
├── CITATION.cff
└── LICENSE

camtrapdp-local.zip is meant for local use: extract it next to the images/ folder and media.csv's filePath will already point to images/<file> instead of a remote URL — no network access needed to resolve media files.

Privacy

Only media marked as public (filePublic=true in media.csv) is included in this export. Observations tied exclusively to non-public media have been removed.

Integrity verification

checksums-sha256.txt lists the SHA-256 hash of every file in this export, to verify nothing was corrupted or truncated after downloading.

Source

Generated from Trapper via wildintel-publisher.

Hugging Face repository

wildintelproject/examplecameratrapsurvey24

Contributing

Issues and pull requests are welcome in the source code repository: https://github.com/wildintelproject/wildintel-camtrapdp-publisher

Funding

This work is part of the WildINTEL project, funded by the Biodiversa+ Joint Research Call 2022-2023 "Improved transnational monitoring of biodiversity and ecosystem change for science and society (BiodivMon)".

License

This dataset is released under: CC0-1.0. See the LICENSE file for the full text.

Citation

To cite this dataset:

Jane Researcher & WildINTEL Example Institute (2026). Example Camera Trap Survey (Version 1.0) [Data set]. Hugging Face. https://huggingface.co/datasets/wildintelproject/examplecameratrapsurvey24

This citation was generated from the CITATION.cff file. See About CITATION files for more info.

Limitations and ethical considerations

Before using this dataset, users should review possible limitations related to camera-trap data, class imbalance, annotation quality, environmental bias, privacy, and sensitive ecological information.

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