AI Photo Analyzer

A simple desktop application that analyzes photos using AI and generates detailed descriptions. Built with Python and Tkinter.

Features

• Easy Photo Import: Import photos from your computer with a simple file dialog
• AI-Powered Analysis: Uses OpenAI's GPT-4 Vision API for detailed image analysis
• Fallback Analysis: Basic image analysis when API key is not available
• User-Friendly GUI: Clean and intuitive interface built with Tkinter
• Multiple Image Formats: Supports JPG, PNG, BMP, GIF, TIFF, and more

Screenshots

The application provides:

• Image preview with automatic resizing
• Detailed AI-generated descriptions
• Status updates and error handling
• Clear and analyze buttons for easy workflow

Installation

Prerequisites

• Python 3.7 or higher
• OpenAI API key (optional, for full AI analysis)

Setup

1. Clone or download the project files

   # If you have git
   git clone <your-repo-url>
   cd ai-photo-analyzer

2. Install dependencies

   pip install -r requirements.txt

3. Set up API key (Optional)

   • Copy .env.example to .env
   • Add your OpenAI API key to the .env file:

     OPENAI_API_KEY=your_openai_api_key_here
     

Usage

Running the Application

python simple_photo_analyzer.py

How to Use

1. Launch the application by running the Python script
2. Import a photo by clicking the "Import Photo" button
3. Select an image file from your computer
4. Click "Analyze Photo" to generate a detailed description
5. View the results in the analysis results area

Without API Key

If you don't have an OpenAI API key, the application will still work but provide basic image information instead of detailed AI analysis:

• Image dimensions
• Color mode
• File format
• File size

With API Key

With a valid OpenAI API key, you'll get:

• Detailed object recognition
• Scene description
• Color and mood analysis
• Context and setting information
• Comprehensive image understanding

Project Structure

ai-photo-analyzer/
├── simple_photo_analyzer.py # Main GUI application (all-in-one)
├── requirements.txt         # Python dependencies
├── .env                    # Environment variables (your API key)
└── README.md               # This file

Dependencies

• tkinter: GUI framework (included with Python)
• Pillow: Image processing and display
• requests: HTTP requests for API calls
• python-dotenv: Environment variable management

API Information

OpenAI GPT-4 Vision

The application uses OpenAI's GPT-4 Vision API for image analysis. You'll need:

• An OpenAI account
• API access to GPT-4 Vision
• Credits in your OpenAI account

Getting an API Key

1. Visit OpenAI's website
2. Create an account or sign in
3. Go to the API section
4. Generate a new API key
5. Add it to your .env file

Troubleshooting

Common Issues

1. "API key not found" error

   • Make sure you've created a .env file
   • Verify your API key is correct
   • Check that the .env file is in the same directory as the script

2. Image won't load

   • Check that the image file exists
   • Verify the image format is supported
   • Try with a different image file

3. Analysis fails

   • Check your internet connection (for API analysis)
   • Verify your OpenAI API key is valid
   • Check your OpenAI account has sufficient credits

Error Messages

• File not found: The selected image file doesn't exist
• Failed to load image: The image file is corrupted or in an unsupported format
• API Error: There's an issue with the OpenAI API (check your key and credits)

Customization

Supported Image Formats

You can modify config.py to add more image formats:

SUPPORTED_FORMATS = ['.jpg', '.jpeg', '.png', '.bmp', '.gif', '.tiff', '.webp']

Analysis Prompt

You can customize the AI analysis prompt in ai_analyzer.py:

"text": "Your custom analysis prompt here..."

Window Size

Adjust the application window size in config.py:

APP_SIZE = "1000x700"  # Width x Height

License

This project is open source and available under the MIT License.

Contributing

Feel free to contribute to this project by:

• Reporting bugs
• Suggesting new features
• Submitting pull requests
• Improving documentation

Support

If you encounter any issues or have questions, please:

1. Check the troubleshooting section
2. Review the error messages
3. Create an issue in the project repository