Smash-IT: A Question Paper Analyzer

Previous Version

Website: SmashIT
Upcoming Deployment: QPaper (November 2025)

📌 Overview

Smash-IT is a Question Paper Analyzer that processes past question papers, identifies frequently asked questions, and clusters them into important topics to help students focus on key areas during their preparation.

🚀 Features

• OCR-Based Text Extraction (Powered by OCR.space API)
• Question Categorization (MCQs, Short Answer, Long Answer, Numerical, etc.)
• Topic Clustering using Machine Learning (Scikit-Learn, NumPy, Pandas)
• User Authentication via Auth0
• Dark/Light Mode Toggle
• Cross-Platform Compatibility
• Admin Dashboard for Analysis

🔗 Acknowledgements

• Django
• PostgreSQL
• OCR.space API
• scikit-learn
• NumPy
• Pandas
• Auth0

📡 API Reference

OCR.space API for Text Extraction

OCR API Endpoint (POST)

POST https://api.ocr.space/parse/image

OCR API via URL (GET)

GET https://api.ocr.space/parse/imageurl?apikey=YOUR_API_KEY&url=IMAGE_URL

API Parameters

Parameter	Type	Description
apikey	String	Required. Your API key.
url / file / base64Image	String	Required. URL, file upload, or Base64-encoded image.
language	String	Optional. Language for OCR (default: eng). Other options: ara, chs, spa, fre, etc.
isOverlayRequired	Boolean	Optional. If true, returns text bounding box coordinates.
detectOrientation	Boolean	Optional. Auto-rotate image if true.

Example JSON Response

{
  "ParsedResults": [
    {
      "ParsedText": "Hello World!",
      "ErrorMessage": "",
      "ErrorDetails": ""
    }
  ],
  "OCRExitCode": 1,
  "IsErroredOnProcessing": false
}

📷 Screenshots

🛠️ Installation

Prerequisites

• Python 3.x
• PostgreSQL
• Virtual Environment (recommended)

1️⃣ Clone the Repository

git clone https://github.com/coder-abhi07/smashIT
cd smashIT

2️⃣ Create a Virtual Environment (Optional)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Run Migrations

python manage.py migrate

5️⃣ Start the Server

python manage.py runserver

📦 Deployment

To deploy this project, run:

npm run deploy

🤝 Contributing

Contributions are always welcome! Please adhere to this project's code of conduct.

🏷️ License

MIT License

👨‍💻 Author

• Abhishek Kumar

📬 Feedback

For feedback or inquiries, reach out via email: ak0188644@gmail.com

📑 Appendix

• Supported File Formats: PDF, PNG, JPG, JPEG
• Authentication: API Key-based authentication
• Limitations: Free tier has request limits per day
• Troubleshooting: Ensure images are high-resolution and use detectOrientation=true if rotated

🌟 Other Info

• 👀 Competitive Programmer
• 💻 Tech Enthusiast & Inquisitive Learner
• 🚀 Always Exploring New Technologies