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Automated Multiplication Quiz Solver

Python 3.8+ License: MIT

An intelligent automation bot that solves multiplication problems in quizzes/games using OCR and precise mouse control.

Features

  • 🎯 Accurate OCR processing with Tesseract v5+
  • ⚙️ Configurable screen regions for question/answer detection
  • 🤖 Human-like mouse movements and click timing
  • 🔄 Automatic pop-up detection ("Back to Game" handling)
  • 📸 Debug image saving for OCR optimization
  • � Robust error recovery and retry mechanisms
  • 🧮 Supports integer multiplication problems (e.g., "12*5")
  • 📊 Confidence-based answer matching system
  • ⏲️ Randomized delays to mimic human behavior

Requirements

  • Python 3.8+
  • Tesseract OCR ≥5.0 (Windows installer)
  • Required Python packages: 
    pip install pyautogui pytesseract Pillow imagehash

Setup & Configuration

  1. Install Tesseract and note its installation path
  2. Clone repository: 
    git clone https://github.com/yourusername/multiplication-solver.git
cd multiplication-solver
  3. Edit script configuration: 
    # -*- coding: utf-8 -*-
# --- Configuration --- MUST BE EDITED ---
tesseract_path = r'C:\Program Files\Tesseract-OCR\tesseract.exe'  # Your Tesseract path

# Adjust these regions using Windows' Snipping Tool coordinates:
QUESTION_REGION = (880, 260, 300, 100)       # Region containing multiplication problem
OPTIONS_REGIONS = [                          # Answer option regions
    (900, 370, 200, 50),
    (900, 440, 200, 50),
    (900, 520, 200, 50),
    (900, 600, 200, 50)
]
BACK_TO_GAME_REGION = (900, 700, 200, 50)    # Pop-up button region

How It Works

  1. Screen Capture: Uses PIL.ImageGrab to capture configured regions
  2. Image Preprocessing:
    • Grayscale conversion
    • Threshold binarization (adjustable)
    • Optional inversion
  3. OCR Processing:
    • Custom Tesseract config for numbers/symbols
    • Text cleaning and validation
  4. Calculation:
    • Parses multiplication problems
    • Computes correct answer
  5. Answer Matching:
    • Numeric comparison with tolerance
    • Fallback strategies
  6. Execution:
    • Humanized mouse movements
    • Randomized delays
    • Pop-up handling

Troubleshooting

Common Issues:

  • Incorrect OCR results:
    • Adjust PREPROCESSING_THRESHOLD (180 default)
    • Enable SAVE_DEBUG_IMAGES = True
    • Check debug images in ocr_debug_images/
  • Tesseract not found:
    • Verify tesseract_path in configuration
    • Add Tesseract to system PATH

Performance Tips:

  • Keep target window visible
  • Disable animations in target application
  • Use consistent window positioning
  • Start with large debug thresholds (200+)

Limitations

  • Currently only supports integer multiplication
  • Requires static window positioning
  • Dependent on screen resolution (1920x1080 recommended)
  • May require calibration for different font styles

Disclaimer

This project is intended for educational purposes only. Always respect application terms of service and local laws when implementing automation solutions. Use at your own risk.