/photo-location-finder

This program allows the user to detect landmarks in an image using the Google Cloud Vision API. The program prompts the user for the image path, API key, and credentials to authenticate with the Google Cloud API.

Primary LanguagePythonMIT LicenseMIT

📸 Photo Location Finder

📖 Introduction

Photo Location Finder is a Python-based application that extracts and identifies the geographical location of photos using EXIF data, Google Vision API, and Google Maps API. It's designed for photographers, travelers, and researchers who need to organize or verify the locations where pictures were taken.

🌟 Features

  • EXIF Data Extraction: Extracts GPS coordinates from image metadata
  • Google Vision API Integration: Detects landmarks, labels, web entities, and more
  • Reverse Geocoding: Converts GPS coordinates into human-readable addresses
  • Street View: Provides a street view image of the location
  • Web Interface: Allows users to upload and process images via a simple web interface

📋 Requirements

  • Python 3.8 or higher
  • Google Cloud Vision API credentials
  • Required Python packages (listed in requirements.txt)

⚙️ Installation

  1. Clone the repository:

    git clone https://github.com/PierrunoYT/photo-location-finder.git
cd photo-location-finder

  2. Set up a virtual environment (optional but recommended):

    python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

  3. Install dependencies:

    pip install -r requirements.txt

  4. Configure Google API Credentials:

    • Create a project in the Google Cloud Console
    • Enable the Vision API and Maps API for your project
    • Create API credentials (API key and service account key)
    • Create a config.json file based on config.json.template

  5. Set up the upload directory:

    mkdir uploads

🔧 Configuration

Ensure your config.json is set up with the correct paths and API keys:

{
  "google_api_key": "YOUR_GOOGLE_API_KEY_HERE",
  "google_application_credentials_file_path": "PATH_TO_YOUR_GOOGLE_APPLICATION_CREDENTIALS_FILE",
  "image_directory_path": "PATH_TO_YOUR_IMAGE_DIRECTORY"
}

🚀 Usage

  1. Start the web application:

    python web_app.py

  2. Open http://localhost:5000 in your web browser

  3. Upload images and view the extracted location details

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📜 License

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

📞 Support

If you encounter any issues or have suggestions, please create an issue in the GitHub repository.

Happy exploring! 📷🌍