--- 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 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.