| --- |
| license: other |
| license_name: datacluster-commercial-sample |
| license_link: LICENSE |
| tags: |
| - fire-detection |
| - smoke-detection |
| - object-detection |
| - computer-vision |
| - surveillance |
| - safety |
| - sample-dataset |
| pretty_name: Fire and Smoke Detection Dataset (Sample) |
| size_categories: |
| - n<1K |
| task_categories: |
| - object-detection |
| - image-classification |
| --- |
| |
| # Fire and Smoke Detection Dataset — Sample |
|
|
| > ⚠️ **This is a free sample subset for evaluation purposes only.** |
| > The full dataset (~10,000+ annotated images, multiple formats) is available for commercial licensing. |
| > **Contact:** [sales@datacluster.ai](mailto:sales@datacluster.ai) · [datacluster.ai](https://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 |
|
|
| - `fire` |
| - `smoke` |
|
|
| ## 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](mailto: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 |
|
|
| ```bash |
| # 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: |
|
|
| ```bash |
| 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`: |
|
|
| ```python |
| 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: |
|
|
| ```bibtex |
| @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](https://datacluster.ai) |
