Smart Paper Tracer - Backend

overview: This is the backend service for the Smart Paper Tracer project built using Flask. It handles OCR-based processing of uploaded answer sheets, extracts text from files, compares student answers with the answer key, and returns evaluation results through a REST API.

Features: Upload answer key and student answer sheets OCR-based text extraction using Tesseract Answer comparison and scoring system Returns structured JSON response REST API for frontend integration

Tech Stack: Python Flask Flask-CORS Tesseract OCR (pytesseract) OpenCV NumPy API Endpoint POST /analyze

Description: Compares answer key with student sheet and returns evaluation results.

Form Data: answer_key (file) student_sheet (file)

Response Example: { "student_name": "John", "roll_no": "12", "total_score": 85, "results": [ { "question": "Q1", "answer": "Water evaporates", "student": "Water changes due to heat", "score": 80 } ] }

Deployment: Backend deployed using Render.

Start Command: python app.py

Build Command: pip install -r requirements.txt

Note: This is a prototype project and OCR accuracy depends on input quality.

Author

RRJ