metadata
title: Mumbai Crowd Predictor
emoji: 🚆
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
🚆 Mumbai Local Train — Crowd Density Predictor (Advanced Edition)
AI-powered crowd prediction system for Mumbai Local Trains with a full-stack FastAPI + HTML/CSS/JS deployment.
🚀 Features
- AI Prediction — RandomForest model with 17 engineered features (~97% accuracy)
- Hourly Forecast — Full day crowd pattern for any route
- Station Heatmap — Visual heatmap of crowd across stations × hours
- Risk Scoring — 0–100 risk score with reasoning and travel tips
- Beautiful UI — Dark glassmorphism design, animated charts, responsive
🗂️ Project Structure
mumbai_train_app/
├── main.py # FastAPI application (entry point)
├── requirements.txt
├── src/
│ ├── model.py # RandomForest + feature engineering
│ └── risk_engine.py # Risk scoring, explanations, tips
├── data/
│ └── raw/
│ └── mumbai_local_crowd_data.csv
├── static/
│ ├── css/style.css # Full dark-mode glassmorphism CSS
│ └── js/app.js # Frontend JavaScript
└── templates/
└── index.html # Main HTML template
⚙️ Setup & Run
1. Install dependencies
pip install -r requirements.txt
2. Run the server
python main.py
# OR with uvicorn directly:
uvicorn main:app --host 0.0.0.0 --port 8000 --reload
3. Open in browser
http://localhost:8000
🧠 ML Model Details
| Feature | Description |
|---|---|
hour |
Hour of travel (5–22) |
hour_weight |
Peak-hour weight (empirical) |
day_num |
0=Monday → 6=Sunday |
is_weekday/weekend |
Binary flags |
is_morning_peak |
7–9 AM flag |
is_evening_peak |
5–7 PM flag |
morning_southbound |
Directional rush interaction |
evening_northbound |
Directional rush interaction |
line_num |
Western/Central/Harbour encoded |
dir_num |
Northbound/Southbound encoded |
station_enc / dest_enc |
Label-encoded stations |
Algorithm: Random Forest Classifier (200 trees, balanced class weights)
Accuracy: ~97% on training data
📡 API Endpoints
| Method | Path | Description |
|---|---|---|
| GET | / |
Web UI |
| GET | /api/lines |
All train lines |
| GET | /api/stations/{line} |
Stations for a line |
| GET | /api/stats |
Dataset + model stats |
| POST | /api/predict |
Single prediction |
| POST | /api/hourly-forecast |
Full day forecast |
| GET | /api/heatmap/{line} |
Station × hour heatmap |
🛤️ Train Lines Covered
- Western Line: Churchgate → Virar (12 stations)
- Central Line: CSMT → Kalyan (9 stations)
- Harbour Line: CSMT → Panvel (8 stations)
👨💻 Tech Stack
- Backend: FastAPI + Uvicorn
- ML: scikit-learn RandomForest, Pandas, NumPy, Joblib
- Frontend: Pure HTML5 + CSS3 + Vanilla JS
- Design: Dark glassmorphism, CSS animations, responsive