README.md

---
license: cc-by-nc-nd-4.0
task_categories:
- object-detection
- image-classification
size_categories:
- 1K<n<10K
tags:
- indian-vehicles
- vehicle-detection
- object-detection
- image-classification
- computer-vision
- automotive
- self-driving
- traffic-analysis
pretty_name: Indian Vehicle Dataset (Sample)
---

# Indian Vehicle Dataset — Sample

> ⚠️ **This is a free sample subset for evaluation purposes only.**  
> The full dataset (50,000+ 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 Indian vehicles, captured on mobile phones across diverse urban and rural environments throughout India. It is well-suited for training vehicle detection and classification models used in traffic monitoring, autonomous driving, smart city surveillance, automated tolling, and India-specific automotive applications.

Scenes cover a wide variety of road scenarios, including dense city traffic, highways, rural roads, parking lots, and intersections — covering both indoor (parking) and outdoor environments under varied lighting and weather conditions. The dataset captures vehicle types unique to Indian roads, making it especially valuable for models that need to perform reliably in the Indian subcontinent.

## Classes

* `Indian Auto`
* `Indian Truck`
* `Bus`
* `Truck`
* `Tempo Traveller`
* `Tractor`
* `Car`
* `Two Wheelers`

## Sample vs. Full Dataset

|  | Sample (this repo) | Full Dataset |
| --- | --- | --- |
| Images | ~200 (subset) | 50,000+ |
| Annotation formats | Pascal VOC (XML) — other formats available on request | COCO, YOLO, Pascal VOC, TF-Record |
| Locations covered | Representative subset | 1,000+ cities across India |
| Resolution | HD (1920×1080 and above) | HD (1920×1080 and above) |
| Scene diversity | Representative subset | Full range (urban, rural, 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

```
indian-vehicle-dataset/
├── images/                  # JPG images
│   ├── image_0001.jpg
│   └── ...
└── annotations/             # 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.

> **Need a different annotation format?** This sample ships in Pascal VOC (XML) only. YOLO, COCO, and TF-Record versions are available on request — see the conversion snippet below, or contact [sales@datacluster.ai](mailto:sales@datacluster.ai).

## Data Collection

* **Source:** Real-world mobile phone captures, crowdsourced from 1,000+ contributors
* **Locations:** 1,000+ cities across urban and rural India
* **Capture period:** 2020–2022
* **Resolution:** 100% HD and above (1920×1080+)
* **Conditions:** Indoor and outdoor scenes; varied lighting (day, night), weather, distances, and vantage points
* **Quality:** Each image manually reviewed and verified by computer vision professionals at DataCluster Labs
* **Use cases:** Vehicle detection, automobile classification, construction vehicle detection, self-driving systems, traffic monitoring, smart city applications

## How to Use

### Download

```bash
# Using the Hugging Face CLI
huggingface-cli download Dataclusterlabspvtltd/Indian-Vehicle-Dataset --repo-type dataset --local-dir ./indian-vehicle-dataset
```

Or clone directly:

```bash
git lfs install
git clone https://huggingface.co/datasets/Dataclusterlabspvtltd/Indian-Vehicle-Dataset
```

### 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")
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 the **Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)** license.

Key points:

* ✅ Free to download and evaluate
* ✅ Free for academic and non-commercial research with attribution
* ❌ No commercial use without a license from DataCluster Labs
* ❌ No derivative works or modifications for redistribution
* ❌ No use in training commercial ML models

For commercial licensing of the full dataset, contact **[sales@datacluster.ai](mailto:sales@datacluster.ai)**.

## Citation

If you use this dataset in academic work, please cite:

```bibtex
@misc{datacluster_indian_vehicle_sample,
  title        = {Indian Vehicle Dataset (Sample)},
  author       = {DataCluster Labs},
  year         = {2026},
  howpublished = {\url{https://huggingface.co/datasets/Dataclusterlabspvtltd/Indian-Vehicle-Dataset}},
  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, with a strong focus on India-first data that captures the diversity of real-world conditions across the subcontinent.

📧 **Sales / Full Dataset Access:** [sales@datacluster.ai](mailto:sales@datacluster.ai)  
🌐 **Website:** [datacluster.ai](https://datacluster.ai)