🔍 OCR App

Extract text from images and PDFs with the power of Google's Gemini 2.5 Flash AI model

📋 Table of Contents

• ✨ Features
• 🚀 Quick Start
• 🎬 Demo
• 📋 Requirements
• 🔧 Installation
• 🔑 API Key Setup
• 📝 Usage Guide
• 🛠️ Building from Source
• ❓ Troubleshooting
• 🤝 Contributing
• 📄 License
• 🙏 Acknowledgments

✨ Features

• 📷 Image Processing - Extract text from various image formats:
  • JPG/JPEG
  • PNG
  • GIF
  • BMP
  • WEBP
  • TIFF
• 📑 PDF Support - Extract text from PDF documents
• 👁️ Preview - View your images and PDFs directly in the app
• 📋 Copy to Clipboard - One-click copying of extracted text
• 💾 Save Results - Export extracted text to a file
• 🌙 Dark Mode - Easy on the eyes UI for day and night use
• 🧠 AI-Powered - Utilizes Google's advanced Gemini 2.5 Flash model for accurate text recognition

🚀 Quick Start

1. Download the latest release
2. Get a Google Gemini API key (instructions below)
3. Run the application and enter your API key
4. Drag & drop an image or PDF file
5. View and use the extracted text!

🎬 Demo

See the OCR App in action:

📋 Requirements

Before you begin, ensure you have the following:

• 💻 Windows operating system (Windows 10 or later recommended)
• 🔄 .NET 9.0 Runtime or SDK (Download here)
• 🔑 Google Gemini API key (free to obtain)
• 🌐 Internet connection (for API communication)

🔧 Installation

Method 1: Using the Installer (Recommended)

1. Download the latest installer from the releases page
2. Run the installer and follow the on-screen instructions
3. Launch the application from your Start menu or desktop shortcut

Method 2: Portable Version

1. Download the latest ZIP file (OCRApp_Release.zip or similar) from the GitHub Releases page.
2. Extract the ZIP file to a location of your choice.
3. Run OCRApp.exe found inside the extracted folder to start the application.

🔑 API Key Setup

The OCR App requires a Google Gemini API key to function. Here's how to get one:

Getting a Google Gemini API Key

1. Visit the Google AI Studio website
2. Sign in with your Google account (create one if needed)
3. Click on "Create API Key"
4. Copy your new API key for use with the OCR App

Configuring Your API Key

There are two ways to configure your API key:

Option 1: Using the apikey.txt file (Recommended)

1. Run the application once to generate the template apikey.txt file
2. Open the apikey.txt file located in the application directory
3. Replace "YOUR_GEMINI_API_KEY_HERE" with your actual Gemini API key
4. Save the file

YOUR_ACTUAL_API_KEY_GOES_HERE

Option 2: Using an environment variable

Set the GEMINI_API_KEY environment variable to your Gemini API key:

Windows Command Prompt:

set GEMINI_API_KEY=your_api_key_here

Windows PowerShell:

$env:GEMINI_API_KEY="your_api_key_here"

Permanent Environment Variable:

1. Press Win + R, type sysdm.cpl, and press Enter
2. Go to the "Advanced" tab
3. Click "Environment Variables"
4. Under "User variables", click "New"
5. Variable name: GEMINI_API_KEY
6. Variable value: your API key
7. Click OK on all dialogs

📝 Usage Guide

Basic Operation

1. Launch the application:
   • If you downloaded the release: Double-click OCRApp.exe from the folder where you extracted the release ZIP file.
   • If you built from source: Navigate to the build output directory (e.g., OCRApp\bin\Release\net9.0-windows\) and double-click OCRApp.exe, or run dotnet run from the OCRApp directory after building.
2. Load a file using one of these methods:
   • Drag and drop an image or PDF file onto the application window
   • Click the "Browse" button to select a file
   • Use the File menu and select "Open"
3. View the preview of your document in the left panel
4. Wait for processing - The application will communicate with the Gemini API to extract text
5. Review the results displayed in the right panel
6. Use the extracted text with the buttons at the bottom:
   • Copy to clipboard
   • Save to a text file

Keyboard Shortcuts

Action	Shortcut
Open File	Ctrl+O
Save Text	Ctrl+S
Copy Text	Ctrl+C
Exit	Alt+F4

🛠️ Building from Source

If you want to build the application from source:

1. Ensure you have the following prerequisites:

   • Visual Studio 2022 or later
   • .NET 9.0 SDK
   • Git (optional, for cloning the repository)

2. Clone or download the repository:

   git clone https://github.com/yourusername/OCRApp.git
   

3. Open the solution file (OCR.sln) in Visual Studio

4. Restore NuGet packages:

   • Right-click on the solution in Solution Explorer
   • Select "Restore NuGet Packages"

5. Build the solution:

   • Select "Build" > "Build Solution" from the menu
   • Or press Ctrl+Shift+B

6. Run the application:

   • Press F5 to start debugging.
   • Or Ctrl+F5 to start without debugging.
   • The executable will be located in the build output directory, typically bin\Debug\net9.0-windows\ or bin\Release\net9.0-windows\.

❓ Troubleshooting

Application won't start

• Ensure you have .NET 9.0 Runtime installed
• Check Windows Event Viewer for error details
• Try running as administrator

API Key errors

• Verify your API key is correct
• Ensure the apikey.txt file is in the correct location
• Check your internet connection
• Verify the API key has not expired or been revoked

File processing issues

• Ensure the file format is supported
• Check that the file is not corrupted
• For large files, allow more time for processing
• For PDFs, ensure they are not password-protected

Text extraction quality issues

• Ensure the image is clear and text is legible
• For better results, use higher resolution images
• Some handwritten text or complex layouts may not extract perfectly

🤝 Contributing

Contributions are welcome! If you'd like to contribute:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

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

🙏 Acknowledgments

• Google Gemini API for powerful text extraction capabilities
• .NET Community for the framework and tools
• Vibe Coded with assistance from the Cline VSCode Plugin and Google's Gemini 2.5 Pro model.

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Made with ❤️ for the OCR community