Dataset Viewer
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: ValueError
Message: Invalid string class label MultiFire20K@4215d51401de97229fe9a5310ea9dc9e92983b06
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2386, in __iter__
example = _apply_feature_types_on_example(
example, self.features, token_per_repo_id=self.token_per_repo_id
)
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2303, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2178, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1483, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
~~~~~~~~~~~~~~~~~~~~~^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1158, in encode_example
example_data = self.str2int(example_data)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1095, in str2int
output = [self._strval2int(value) for value in values]
~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1116, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label MultiFire20K@4215d51401de97229fe9a5310ea9dc9e92983b06Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MultiFire20K Dataset
Overview
MultiFire20K is a UAV-based dataset for fire monitoring, designed for image classification, segmentation, and multi-task learning. It contains 20,500 images extracted from 67 UAV videos captured across diverse urban and rural environments worldwide.
Statistics
| Split | Images |
|---|---|
| Train | 14,350 |
| Validation | 3,075 |
| Test | 3,075 |
| Total | 20,500 |
Classes
- Fire
- Normal
Environment Types
- Urban (Build-Up)
- Rural (Natural Landscape)
Source
Original dataset:
https://zenodo.org/records/17047113
Citation
@article{shianios2025multifire20k,
title={MultiFire20K: A semi-supervised enhanced large-scale UAV-based benchmark for advancing multi-task learning in fire monitoring},
author={Shianios, Demetris and Kolios, Panayiotis and Kyrkou, Christos},
journal={Computer Vision and Image Understanding},
volume={254},
pages={104318},
year={2025},
publisher={Elsevier}
}
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