Go OCR Text Extractor

A powerful and free OCR (Optical Character Recognition) solution for the Go community that bridges the gap between Go's efficiency and Python's rich AI ecosystem.

🎯 Why This Project Exists

The OCR market is flooded with expensive, proprietary solutions that often come with limitations:

• Costly licensing fees for commercial OCR APIs
• Limited language support in many solutions
• Vendor lock-in with cloud-based services
• Complex integration requiring specialized knowledge
• Poor accuracy on varied document types
• No local processing options for sensitive documents

This project addresses these pain points by providing a completely free, locally-run OCR solution that leverages the power of established Python AI libraries while maintaining Go's performance and simplicity.

🌟 The Python Advantage

Python has already solved many complex problems in the AI and machine learning space with mature, battle-tested libraries. Rather than reinventing the wheel in Go, this project creates a bridge that allows Go developers to harness these powerful Python capabilities:

• Tesseract OCR - Google's industry-leading OCR engine
• PIL (Python Imaging Library) - Robust image processing
• PyPDF2 & pdfplumber - Comprehensive PDF text extraction
• Extensive language support - Over 100 languages supported by Tesseract

🚀 Features

• PDF Text Extraction: Extract text from PDF documents using multiple extraction methods
• Image OCR: Convert images to text with high accuracy
• Multilingual Support: Supports Portuguese, English, and 100+ other languages
• Caching System: Built-in memory cache to avoid reprocessing the same files
• Fallback Mechanisms: Multiple extraction methods ensure maximum compatibility
• Thread-Safe: Concurrent processing with mutex protection
• Error Handling: Comprehensive error reporting and recovery
• Free & Open Source: No licensing fees or API limits

📋 Prerequisites

Python Dependencies

The project automatically handles Python dependency installation, but you can install them manually:

pip install PyPDF2 pdfplumber pytesseract Pillow

Docker

Mac Arm64 - Silicon

docker build --build-arg TARGETOS=darwin --build-arg TARGETARCH=arm64 -t ocr-processor:latest .

Windows

docker build --build-arg TARGETOS=windows --build-arg TARGETARCH=amd64 -t ocr-processor:latest .

Linux

docker build --build-arg TARGETOS=linux --build-arg TARGETARCH=amd64 -t ocr-processor:latest .

Linux arm64

docker build --build-arg TARGETOS=linux --build-arg TARGETARCH=arm64 -t ocr-processor:latest .

Tesseract OCR Installation

Windows

1. Download the installer from GitHub Tesseract releases
2. Run the installer and follow the setup wizard
3. Add Tesseract to your system PATH:
   • Default installation path: C:\Program Files\Tesseract-OCR
   • Add this path to your Windows PATH environment variable
4. Restart your command prompt

macOS

Using Homebrew:

brew install tesseract

Using MacPorts:

sudo port install tesseract

Linux (Ubuntu/Debian)

sudo apt-get update
sudo apt-get install tesseract-ocr
sudo apt-get install tesseract-ocr-por  # For Portuguese language support

Linux (CentOS/RHEL/Fedora)

sudo yum install tesseract tesseract-langpack-por

or for newer versions:

sudo dnf install tesseract tesseract-langpack-por

🏗️ Architecture

Core Components

PythonExecutor

The main orchestrator that manages Python script execution and handles:

• Python environment detection
• Dependency management
• Script execution
• Result parsing
• Caching management

PDF Text Extraction

• Primary Method: pdfplumber (more accurate)
• Fallback Method: PyPDF2 (broader compatibility)
• Automatic Selection: Chooses the best method based on document type

Image OCR Processing

• Language Detection: Attempts Portuguese first, falls back to English
• Image Preprocessing: Automatic RGB conversion
• Format Support: PNG, JPG, JPEG, TIFF, BMP, GIF

Prompt System

• LangChain Integration: Structured prompt templates for AI processing
• Flexible Configuration: Customizable prompt parameters
• JSON Output: Structured response format

Result Structures

type PDFTextResult struct {
    Success  bool   `json:"success"`
    Text     string `json:"text"`
    Error    string `json:"error"`
    Pages    int    `json:"pages"`
    Filename string `json:"filename"`
}

type ImageTextResult struct {
    Success  bool   `json:"success"`
    Text     string `json:"text"`
    Error    string `json:"error"`
    Pages    int    `json:"pages"`
    Filename string `json:"filename"`
}

🔧 Usage Example

package main

import (
    "fmt"
    "log"
    "your-project/model"
)

func main() {
    // Initialize the Python executor
    executor := model.NewPythonExecutor()
    
    // Check and install PDF dependencies
    if err := executor.CheckPythonDependenciesForPDF(); err != nil {
        log.Fatal(err)
    }
    
    // Extract text from PDF
    result, err := executor.ExtractPDFText("document.pdf")
    if err != nil {
        log.Fatal(err)
    }
    
    if result.Success {
        fmt.Printf("Extracted %d characters from %d pages\n", 
                   len(result.Text), result.Pages)
        fmt.Println(result.Text)
    } else {
        fmt.Printf("Error: %s\n", result.Error)
    }
    
    // Extract text from image
    imageResult, err := executor.ExtractImageText("scanned_document.png")
    if err != nil {
        log.Fatal(err)
    }
    
    if imageResult.Success {
        fmt.Printf("OCR Result: %s\n", imageResult.Text)
    }
    
    // Use with AI prompts
    promptInstance := model.NewPromptOCRInstance()
    prompt := promptInstance.GetPrompt(result.Text)
    // Process with your preferred LLM...
}

🤝 Contributing to the Go AI Community

This project represents a commitment to advancing AI capabilities within the Go ecosystem. By providing free access to powerful OCR functionality, we aim to:

• Lower barriers to entry for developers interested in document processing
• Accelerate innovation in Go-based AI applications
• Foster collaboration between Go and Python communities
• Enable experimentation without cost constraints
• Support education and research initiatives

📚 Dependencies & Credits

This project stands on the shoulders of giants. We extend our gratitude to the following projects and their maintainers:

Python Libraries

• Tesseract OCR - Google's open-source OCR engine
• pytesseract - Python wrapper for Tesseract
• PyPDF2 - Pure Python PDF library
• pdfplumber - Detailed PDF text extraction
• Pillow (PIL) - Python Imaging Library

Go Libraries

• LangChain Go - Go implementation of LangChain for LLM integration

🔍 Error Handling

The system provides comprehensive error handling:

• Dependency Check: Automatic verification and installation of Python packages
• File Validation: Format and existence verification
• Graceful Fallbacks: Multiple extraction methods for maximum compatibility
• Detailed Logging: Clear error messages and debugging information

🎯 Future Enhancements

• Support for more document formats (DOCX, RTF, etc.)
• Batch processing capabilities
• Configuration file support
• Docker containerization
• REST API wrapper
• Performance benchmarking tools

📄 License

This project is open-source and free to use. Please refer to the LICENSE file for details.

🤝 Contributing

We welcome contributions from the community! Whether it's bug reports, feature requests, or code contributions, every effort helps make this tool better for everyone.

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Built with ❤️ for the Go community. Empowering developers to build amazing AI applications without breaking the bank.