CAPTCHA Solver Project

A comprehensive Python-based CAPTCHA solving toolkit that combines image preprocessing, OCR (Optical Character Recognition), and web automation to solve various types of text-based CAPTCHAs.

⚠️ Important Disclaimer

This tool is intended for educational purposes, security research, and legitimate testing only.

• Use only on systems you own or have explicit permission to test
• Respect website terms of service and rate limits
• Do not use for malicious activities or to bypass security measures
• The developers are not responsible for misuse of this software

🚀 Features

• Multi-source CAPTCHA extraction: From files, URLs, and web elements
• Advanced image preprocessing: Noise reduction, enhancement, and optimization
• Robust OCR engine: Multiple Tesseract configurations for better accuracy
• Web automation support: Selenium integration for form submission
• Batch processing: Handle multiple CAPTCHAs efficiently
• Comprehensive logging: Detailed processing information and debugging
• Flexible configuration: Customizable settings for different CAPTCHA types
• Performance monitoring: Statistics and confidence scoring

📋 Requirements

System Requirements

• Python 3.7 or higher
• Tesseract OCR engine
• Chrome/Firefox browser (for Selenium)

Python Dependencies

See requirements.txt for the complete list. Key dependencies include:

• requests - HTTP requests
• beautifulsoup4 - HTML parsing
• Pillow - Image processing
• pytesseract - OCR engine interface
• selenium - Web automation
• opencv-python - Advanced image processing
• numpy - Numerical operations

🛠️ Installation

1. Install Tesseract OCR

Windows:

# Download and install from: https://github.com/UB-Mannheim/tesseract/wiki
# Or using chocolatey:
choco install tesseract

Linux (Ubuntu/Debian):

sudo apt-get update
sudo apt-get install tesseract-ocr
sudo apt-get install libtesseract-dev

macOS:

brew install tesseract

2. Clone and Setup Project

git clone <repository-url>
cd Captcha_Solver
pip install -r requirements.txt

3. Verify Installation

from captcha_solver import CAPTCHASolver

solver = CAPTCHASolver()
print(solver.test_components())

📖 Quick Start

Basic Usage

from captcha_solver import CAPTCHASolver

# Initialize solver
solver = CAPTCHASolver()

# Solve from image file
result = solver.solve_from_file("captcha.png")
print(f"CAPTCHA solved: {result}")

# Solve from URL
result = solver.solve_from_url("https://example.com/captcha-page")
print(f"CAPTCHA solved: {result}")

Advanced Usage with Custom Configuration

from captcha_solver import CAPTCHASolver, Config

# Custom configuration
config = {
    "tesseract": {
        "config": "--psm 8 -c tessedit_char_whitelist=0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ",
        "timeout": 30
    },
    "preprocessing": {
        "steps": ["grayscale", "denoise", "threshold", "enhance"]
    },
    "ocr": {
        "confidence_threshold": 70
    }
}

solver = CAPTCHASolver(config=config)
result = solver.solve_from_file("difficult_captcha.png", save_processed=True)
print(f"Result: {result}, Confidence: {solver.get_confidence():.1f}%")

Selenium Integration

from selenium import webdriver
from captcha_solver import CAPTCHASolver, FormSubmitter

# Setup WebDriver
driver = webdriver.Chrome()
solver = CAPTCHASolver()
submitter = FormSubmitter(driver)

try:
    # Navigate to page with CAPTCHA
    driver.get("https://example.com/login")
    
    # Find CAPTCHA element
    captcha_element = driver.find_element("css selector", "img.captcha")
    
    # Solve CAPTCHA
    result = solver.solve_from_element(captcha_element, driver)
    
    # Submit form
    form_data = {
        "username": "your_username",
        "password": "your_password",
        "captcha": result
    }
    
    success = submitter.submit_form(form_data, "#login-form")
    print(f"Form submitted: {success}")
    
finally:
    driver.quit()

Batch Processing

from pathlib import Path
from captcha_solver import CAPTCHASolver

solver = CAPTCHASolver()

# Process all images in a directory
image_dir = Path("captcha_images")
image_paths = list(image_dir.glob("*.png"))

results = solver.solve_batch(image_paths, save_processed=True)

# Print results
for result in results:
    print(f"{result['path']}: {result['result']} ({result['confidence']:.1f}%)")

# Get statistics
stats = solver.get_statistics()
print(f"Success rate: {stats['success_rate']:.1f}%")

🏗️ Project Structure

Captcha_Solver/
├── captcha_solver/
│   ├── __init__.py          # Package initialization
│   ├── config.py            # Configuration management
│   ├── solver.py            # Main solver class
│   ├── extractor.py         # CAPTCHA image extraction
│   ├── preprocessor.py      # Image preprocessing
│   ├── ocr.py              # OCR handling
│   ├── submitter.py        # Form submission
│   └── utils.py            # Utility functions
├── examples/
│   ├── basic_usage.py      # Basic examples
│   ├── advanced_config.py  # Advanced configuration
│   ├── selenium_example.py # Selenium integration
│   └── batch_processing.py # Batch processing
├── tests/
│   ├── test_solver.py      # Main solver tests
│   ├── test_preprocessor.py # Preprocessing tests
│   └── test_ocr.py         # OCR tests
├── docs/
│   ├── configuration.md    # Configuration guide
│   ├── preprocessing.md    # Preprocessing guide
│   └── troubleshooting.md  # Common issues
├── requirements.txt        # Python dependencies
├── setup.py               # Package setup
├── README.md              # This file
└── caotcha me.py          # Original implementation

⚙️ Configuration

The solver supports extensive configuration through YAML files or Python dictionaries:

# config.yaml
tesseract:
  path: "/usr/bin/tesseract"  # Auto-detected if not specified
  config: "--psm 8 --oem 3"
  timeout: 30
  language: "eng"

preprocessing:
  steps:
    - "grayscale"
    - "denoise"
    - "threshold"
    - "enhance"
  
  grayscale:
    method: "weighted"  # "average", "weighted", "luminosity"
  
  denoise:
    method: "gaussian"  # "gaussian", "median", "bilateral"
    kernel_size: 3
  
  threshold:
    method: "adaptive"  # "binary", "adaptive", "otsu"
    block_size: 11
    c_value: 2

ocr:
  confidence_threshold: 60
  character_whitelist: "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"
  multiple_configs: true

selenium:
  implicit_wait: 10
  page_load_timeout: 30
  screenshot_on_error: true

extraction:
  default_selectors:
    - "img[src*='captcha']"
    - ".captcha img"
    - "#captcha"
  timeout: 10
  retry_attempts: 3

🔧 Preprocessing Options

The image preprocessor supports various enhancement techniques:

• Grayscale conversion: Multiple algorithms for optimal contrast
• Noise reduction: Gaussian, median, and bilateral filtering
• Thresholding: Binary, adaptive, and Otsu methods
• Morphological operations: Opening, closing, erosion, dilation
• Enhancement: Contrast adjustment, sharpening, histogram equalization
• Skew correction: Automatic rotation correction
• Character segmentation: Individual character isolation

🎯 OCR Configuration

Tesseract OCR can be fine-tuned for different CAPTCHA types:

# Numeric only CAPTCHAs
config = "--psm 8 -c tessedit_char_whitelist=0123456789"

# Alphanumeric CAPTCHAs
config = "--psm 8 -c tessedit_char_whitelist=0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"

# Single word CAPTCHAs
config = "--psm 8 --oem 3"

# Multiple words
config = "--psm 6 --oem 3"

📊 Performance Monitoring

solver = CAPTCHASolver()

# Process some CAPTCHAs...

# Get detailed statistics
stats = solver.get_statistics()
print(f"Total processed: {stats['total_processed']}")
print(f"Success rate: {stats['success_rate']:.1f}%")
print(f"Average confidence: {stats['average_confidence']:.1f}%")

# Get system information
info = solver.get_system_info()
print(f"Component tests: {info['component_tests']}")

🐛 Troubleshooting

Common Issues

1. Tesseract not found

   TesseractNotFoundError: tesseract is not installed
   

   • Install Tesseract OCR and ensure it's in PATH
   • Or specify path in configuration

2. Low accuracy

   • Try different preprocessing steps
   • Adjust OCR configuration
   • Use character whitelisting
   • Check image quality and size

3. Selenium WebDriver issues

   • Update WebDriver to match browser version
   • Use webdriver-manager for automatic management
   • Check browser compatibility

Debug Mode

solver = CAPTCHASolver(log_level="DEBUG")
result = solver.solve_from_file("captcha.png", save_processed=True)

# Check processed image
processed_img = solver.get_processed_image()
processed_img.show()  # Display processed image

# Check confidence
print(f"Confidence: {solver.get_confidence():.1f}%")

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Tesseract OCR - OCR engine
• OpenCV - Computer vision library
• Selenium - Web automation framework
• Pillow - Python imaging library

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Remember: Use this tool responsibly and ethically. Always respect website terms of service and applicable laws.