The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: FileNotFoundError
Message: [Errno 2] No such file or directory: '<datasets.utils.file_utils.FilesIterable object at 0x7fd8f7e48080>'
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, 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 4195, 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 2533, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2711, in iter
for key, pa_table in ex_iterable.iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2249, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, 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/xml/xml.py", line 67, in _generate_tables
with open(file, encoding=self.config.encoding, errors=self.config.encoding_errors) as f:
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/streaming.py", line 73, in wrapper
return function(*args, download_config=download_config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 967, in xopen
return open(main_hop, mode, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
FileNotFoundError: [Errno 2] No such file or directory: '<datasets.utils.file_utils.FilesIterable object at 0x7fd8f7e48080>'Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Fire and Smoke Detection Dataset — Sample
⚠️ This is a free sample subset for evaluation purposes only.
The full dataset (~5,000+ annotated images, multiple formats) is available for commercial licensing.
Contact: sales@datacluster.ai · datacluster.ai
Dataset Summary
This dataset contains real-world images of fire and smoke scenarios, captured on mobile phones under diverse conditions. It is well-suited for training early fire and smoke detection models used in smart cameras, fire alarm systems, surveillance, and safety applications.
Scenes include typical domestic situations such as garbage burning, paper and plastic burning, field crop burning, and domestic cooking — covering both indoor and outdoor environments under varied lighting and weather.
Classes
firesmoke
Sample vs. Full Dataset
| Sample (this repo) | Full Dataset | |
|---|---|---|
| Images | ~100–200 (subset) | ~10,000+ |
| Annotation formats | Pascal VOC (XML) | COCO, YOLO, Pascal VOC, TF-Record |
| Scene diversity | Representative subset | Full range (indoor, outdoor, day, night, close, far) |
| Commercial use | ❌ Not permitted | ✅ With license |
| Redistribution | ❌ Not permitted | Per license terms |
| Updates | One-time | Ongoing |
To license the full dataset: sales@datacluster.ai
Dataset Structure
fire-and-smoke-sample/
├── images/ # JPG images
│ ├── image_0001.jpg
│ └── ...
└── annotations/
└── voc/ # Pascal VOC XML annotations (one per image)
├── image_0001.xml
└── ...
Each XML file contains bounding-box annotations in the Pascal VOC format, with filenames matching their corresponding image.
Data Collection
- Source: Real-world mobile phone captures
- Conditions: Indoor and outdoor scenes; varied lighting, weather, distances, and vantage points
- Use cases: Early fire/smoke detection, anomaly detection, fire alarm systems, smart surveillance
How to Use
Download
# Using the Hugging Face CLI
huggingface-cli download datacluster-labs/fire-and-smoke-sample --repo-type dataset --local-dir ./fire-and-smoke-sample
Or clone directly:
git lfs install
git clone https://huggingface.co/datasets/Dataclusterlabspvtltd/fire-and-smoke-sample
Convert VOC to YOLO or COCO
The sample ships in Pascal VOC format. Convert easily with pylabel:
from pylabel import importer
# VOC → YOLO
dataset = importer.ImportVOC(path="annotations/voc")
dataset.export.ExportToYoloV5(output_path="annotations/yolo")
# VOC → COCO
dataset.export.ExportToCoco(output_path="annotations/coco/annotations.json")
License
This sample dataset is released under a restricted commercial-sample license — see the LICENSE file in this repository.
Key points:
- ✅ Free to download and evaluate
- ✅ Free for academic research with attribution
- ❌ No commercial use without a license from DataCluster Labs
- ❌ No redistribution or re-upload
- ❌ No use in training commercial ML models
For commercial licensing of the full dataset, contact sales@datacluster.ai.
Citation
If you use this dataset in academic work, please cite:
@misc{datacluster_fire_smoke_sample,
title = {Fire and Smoke Detection Dataset (Sample)},
author = {DataCluster Labs},
year = {2026},
howpublished = {\url{https://huggingface.co/datasets/Dataclusterlabspvtltd/fire-and-smoke-sample}},
note = {Sample subset. Full dataset available for commercial licensing at sales@datacluster.ai}
}
About DataCluster Labs
DataCluster Labs specializes in managed crowd-sourced data collection and annotation — images, videos, audio, text, and surveys — through our Dailydata platform. We deliver custom datasets for computer vision, NLP, and ML use cases.
📧 Sales / Full Dataset Access: sales@datacluster.ai
🌐 Website: datacluster.ai
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