🛡️ Label-Buster AI: The Food Deception Detector

"Don't eat what you can't read."

Label-Buster AI is a Computer Vision application designed to protect consumers from deceptive food marketing. It scans ingredient labels in real-time, detects hidden sugars, unhealthy fats, and artificial additives, and provides an instant "Health Score."

---

🚀 The Problem

Modern food packaging is designed to mislead. A product can claim "100% Natural" on the front while hiding Maltodextrin (Sugar), Palm Oil (Inflammatory Fat), and E621 (MSG) in the fine print on the back. Most consumers do not have the time or knowledge to decode these chemical names.

💡 The Solution

Label-Buster acts as a personal AI Nutritionist.

1. Scan: The user uploads a photo or uses their webcam to scan a food packet.
2. Decode: The app uses OCR (Optical Character Recognition) to read the text.
3. Analyze: It cross-references ingredients against a database of 50+ harmful additives.
4. Score: It generates a visual Health Score and flags specific risks (e.g., "Insulin Spike Warning").

---

🛠️ Tech Stack

This project bridges Data Science and Consumer Health.

• Frontend: Streamlit (Python) for the interactive Web UI.
• Computer Vision: OpenCV & EasyOCR for text extraction.
• Logic: Python-based Keyword Matching & Risk Scoring Algorithm.
• Visualization: Dynamic CSS animations for the "Live Health" dashboard.

---

📸 Demo

---

⚙️ How to Run Locally

1. Clone the Repository

   git clone [https://github.com/praannav/Label-Buster-AI.git](https://github.com/praannav/Label-Buster-AI.git)
   cd Label-Buster-AI

2. Install Dependencies

   pip install -r requirements.txt

3. Run the App

   streamlit run app.py

---

🔮 Future Roadmap

• Deployment: Hosting the web app for public use.
• Barcode Integration: Scanning barcodes to fetch nutritional info via API.
• Macro-Counter: Automatically calculating protein/carbs from the label.

---

👨‍💻 Author

Praannav Computer Engineering Student | AI Researcher | Fitness Content Creator