README.md

---
---
language:
- en
task_categories:
- visual-question-answering
- image-classification
task_ids:
- visual-question-answering
license: cc-by-4.0
---

# Building Defect VQA Dataset

## Dataset Description

This dataset is a **Visual Question Answering (VQA)** version of the original **BD3 (Building Defect Dataset)**.
It is designed for training and evaluating **Vision–Language Models (VLMs)** on building defect recognition tasks.

Each image is paired with a fixed question and a defect category as the answer.

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## Dataset Structure

Each sample contains:

- **image**: RGB image of a building surface  
- **question**:  
  > *"What type of building defect is visible in the image?"*
- **answer**: One of the following defect classes:
  - `algae`
  - `major_crack`
  - `minor_crack`
  - `peeling`
  - `plain`
  - `spalling`
  - `stain`

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## Intended Use

This dataset is suitable for:
- Visual Question Answering (VQA)
- Vision–Language Model fine-tuning
- Prompt-based image classification
- Zero-shot / few-shot VLM evaluation

Compatible with models such as:
- LLaVA
- SmolVLM
- Pixtral
- Qwen-VL
- BLIP-style models

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## Source Dataset & Credits

This dataset is **derived from the original BD3 (Building Defect Dataset)**.

### Original Dataset
- **Name**: BD3 – Building Defect Dataset
- **Authors**: *{Kottari, Praveen and Arjunan, Pandarasamy}*
- **Original Source**: *[https://github.com/Praveenkottari/BD3-Dataset]*

### Credit Statement
> This VQA dataset is a **reformatted version** of the original BD3 dataset.  
> All image rights and original credit belong to the original authors.  
> This version only changes the data format to support VQA-style learning.

If you use this dataset, **please cite the original BD3 dataset and paper**.

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## License

This dataset follows the **same license as the original BD3 dataset**.  
Please check the original source before using it for commercial purposes.

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## Citation

If you use this dataset, please cite:

```bibtex
@dataset{bd3_building_defect,
  title     = {BD3: Building Defect Dataset},
  author    = {Kottari, Praveen and Arjunan, Pandarasamy},
  year      = {2024},
  url       = {https://github.com/Praveenkottari/BD3-Dataset)}
}