README.md

---
license: apache-2.0
task_categories:
  - object-detection
  - question-answering
language:
  - en
  - hi
tags:
  - road-safety
  - india
  - emergency-services
  - traffic-law
  - geospatial
  - rag
pretty_name: SafeVixAI Dataset Hub
size_categories:
  - 1B<n<10B
---

# SafeVixAI Dataset Hub 🛡️

> The **Intelligence Layer** for the SafeVixAI platform — IIT Madras Road Safety Hackathon 2026

This repository hosts all datasets, pre-trained models, notebooks, and **reproducible data acquisition scripts** that power the SafeVixAI application. It is designed to be cloned directly into Google Colab or any research environment.

**Main Application Repo:** [SafeVixAI/SafeVixAI](https://github.com/SafeVixAI/SafeVixAI)

---

## ⚡ Quickstart (Google Colab)

```python
# Clone the entire intelligence layer
!git clone https://huggingface.co/datasets/SafeVixAI/SafeVixAI-Dataset-Hub /content/data

# Symlink into the app structure
import os
os.makedirs("/content/SafeVixAI/chatbot_service", exist_ok=True)
!ln -sfn /content/data/data/chatbot_service/data /content/SafeVixAI/chatbot_service/data
```

---

## 📦 Repository Structure

```
SafeVixAI-Dataset-Hub/
├── data/                         ← 4.2 GB of raw intelligence data (11,008 files)
│   ├── backend/
│   │   ├── data/                 ← Civic intel (OSM data, toll plazas, ward boundaries)
│   │   └── datasets/             ← Raw database assets (blackspots, violations CSVs)
│   ├── chatbot_service/data/     ← Chatbot reference directories & built vector stores
│   └── frontend/offline-data/    ← Regional translation matrices & offline PWA bundles
│
└── scripts/                      ← Complete data acquisition & processing pipelines
    ├── backend/                  ← Core backend and database migration scripts
    ├── chatbot_service/          ← Chatbot agent and QA validation scripts
    └── scripts/                  ← Legacy scrapers, downloaders, and seeders
```

---

## 🗂️ Data Contents

| Category | Files | Size | Source |
|---|---|---|---|
| Emergency Services GIS | `hospitals.csv`, `police_stations.csv`, `fire_stations.csv`, `ambulance.csv` | ~150 MB | OpenStreetMap Overpass API |
| Legal Documents | `motor_vehicles_act_1988.pdf`, `mv_amendment_act_2019.pdf` | ~30 MB | MoRTH / Indian Kanoon |
| Accident Statistics | `kaggle_india_accidents.csv`, `morth_2022/*.csv` | ~250 MB | MoRTH / Kaggle |
| Road Infrastructure | `pmgsy_roads.geojson`, `toll_plazas.csv` | ~900 MB | PMGSY GeoSadak / NHAI |
| Hospital Directory | `hospital_directory.csv`, `nin_facilities.csv` | ~1.2 GB | NHP / NIN |
| Traffic Violations | `violations_seed.csv`, `state_overrides.csv` | ~5 MB | MVA 2019 |
| PWA Translations | `translations/*.json` (11 regional Indian languages) | ~6.4 MB | Automated DeepL/Google Sync |
| Road Damage Model | `road_damage_2025/` | ~800 MB | ONNX + Training Data |
| QA Pairs | `qa_pairs/` | ~50 MB | Custom RAG Training |

---

## 🔬 Scripts — Reproducible Data Pipeline

The `scripts/` folder mirrors the main application's data acquisition pipeline.
All scripts here are **pure Python** — they run without any database or backend stack.

### Structure

```
scripts/
├── scripts/data/             ← from SafeVixAI/scripts/data/
│   ├── _overpass_utils.py    ← Core GIS utility (basic version)
│   ├── fetch_hospitals.py    ← Hospital data from OpenStreetMap
│   ├── fetch_police.py       ← Police station data
│   ├── fetch_ambulance.py    ← Ambulance service data
│   ├── fetch_blood_banks.py  ← Blood bank data
│   ├── fetch_fire.py         ← Fire station data
│   ├── download_legal_pdfs.py ← MV Act PDF downloader
│   ├── extract_morth2022_tables.py ← PDF → CSV extractor
│   ├── seed_blackspots.py    ← Accident blackspot normalizer
│   ├── bootstrap_local_data.py ← Master data orchestrator
│   ├── verify_data.py        ← Data integrity checker
│   ├── inspect_zips.py       ← Dataset zip validator
│   ├── audit_env.py          ← Environment configuration checker
│   ├── check_all_scripts.py  ← Script syntax validator
│   └── setup_kaggle.ps1      ← Kaggle API auth setup
│
├── backend/data/             ← from SafeVixAI/backend/scripts/data/
│   ├── seed_violations.py    ← Traffic fine normalizer (MVA 2019)
│   ├── prepare_road_sources.py ← CSV/GeoJSON → LineString converter
│   ├── sample_pmgsy.py       ← PMGSY 867K roads sampler
│   ├── road_sources.example.json ← Manifest template
│   └── road_sources.json     ← Active road source manifest
│
└── chatbot_service/data/     ← from SafeVixAI/chatbot_service/scripts/data/
    ├── _overpass_utils.py    ← Pro GIS utility (with retries + backoff)
    ├── fetch_hospitals.py    ← Pro hospital fetcher
    ├── fetch_police.py       ← Pro police fetcher
    ├── fetch_ambulance.py    ← Pro ambulance fetcher
    ├── fetch_blood_banks.py  ← Pro blood bank fetcher
    └── fetch_fire.py         ← Pro fire station fetcher
```

### Running the Scripts

```bash
# 1. Setup Kaggle auth (one-time)
pwsh scripts/scripts/data/setup_kaggle.ps1

# 2. Fetch all emergency service GIS data (Pro versions recommended)
python scripts/chatbot_service/data/fetch_hospitals.py
python scripts/chatbot_service/data/fetch_police.py
python scripts/chatbot_service/data/fetch_ambulance.py
python scripts/chatbot_service/data/fetch_blood_banks.py
python scripts/chatbot_service/data/fetch_fire.py

# 3. Download legal documents
python scripts/scripts/data/download_legal_pdfs.py

# 4. Extract MoRTH accident tables
python scripts/scripts/data/extract_morth2022_tables.py

# 5. Verify everything
python scripts/scripts/data/verify_data.py
```

> **Note:** `chatbot_service/data/` versions of the fetchers are the **Pro versions** — they include retry logic, exponential backoff, and more precise Indian GIS selectors.

---

## 📓 Research Notebooks — Open in Colab

> We advise running all notebooks through **Google Colab** for the easiest setup. Colab gives you a free T4 GPU with 16 GB of VRAM. All notebooks were built and tested on Colab, so it is the most stable platform. Any other cloud provider should work too.

| # | Notebook | What It Produces | Open in Colab |
|---|---|---|---|
| 1 | **YOLOv8 Pothole Detector Training** | ONNX road damage model | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1oe4Gk899lFB_vbRMUuOh4dqpsa3bbycI) |
| 2 | **ChromaDB RAG Vectorstore Build** | ChromaDB index for legal RAG | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1AzPdN9xjcjW20ko0shTYn0mvbxTUw57Q) |
| 3 | **Accident EDA & Hotspot Generator** | Blackspot seed CSV + heatmap | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1xh_lwv_B_jc0_83dvuNppWQRtVhqExTS) |
| 4 | **Roads Data Processing** | Sampled PMGSY GeoJSON | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/10_WfTlbbxW9A7ceQBZGaKF5UkydlUDin#scrollTo=z4XxGZmx0ymX) |
| 5 | **Risk Model ONNX Training** | Risk scoring ONNX model | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/16IH-rn3CedYtfIpJP4iLa_KUjvfy8hAY) |

**Recommended run order:** `1 → 2 → 3 → 4 → 5`

> Each notebook auto-clones this Hub at the start — no manual data setup needed.

---

## 📜 License

Apache 2.0 — See [LICENSE](LICENSE)

Data sourced from OpenStreetMap (ODbL), MoRTH (Government of India Open Data), Kaggle, PMGSY GeoSadak, and National Health Portal.