AI Photo Manager

Your memories, organized.

Stop digging through endless folders and cryptic filenames. AI Photo Manager transforms your local collection of photos and videos into a smart, beautiful, and searchable library—running entirely on your own computer. No cloud uploads, no privacy concerns, just your memories.

It organizes your life into three simple views:

👥 People

Forgot where you saved those photos of your best friend? The built-in AI automatically detects faces and groups them together.

• Identify unknown faces with a click.
• Merge duplicates easily.
• Search your entire library just by clicking a person's face.

🌍 Location

Relive your journeys on an interactive world map.

• See the World: Your photos are automatically grouped into dynamic clusters, showing you exactly where you've been.
• Travel Timeline: Jump from Paris to Tokyo instantly by browsing your travel history chronologically directly on the map.

📸 Albums

Browse your folders as beautiful, high-performance visual grids.

• Seamless Playback: Videos play instantly right alongside your photos.
• Smart Metadata: Your edits and AI data are stored locally in the folder, so your library is always portable and safe.

🛠️ Prerequisites

• Python 3.8+
• Visual C++ Redistributable (Required for OpenCV/InsightFace on Windows)

📦 Installation

1. Clone or Download this repository.

2. Install Python Dependencies: Create a requirements.txt file (or just run the command below) with the following packages:

   flask
   opencv-python
   insightface
   onnxruntime
   pillow
   scikit-learn
   numpy

   Run the installation:

   pip install -r requirements.txt

   Note: If you don't have a dedicated GPU, onnxruntime (CPU) is sufficient. For faster processing with NVIDIA cards, install onnxruntime-gpu.

3. Setup Credentials: The system will automatically generate a settings.json file on the first run, but you can create it manually to set your password immediately:

   Create a file named settings.json in the root directory:

   {
      "users": {
         "admin": "your_password_here"
      }
   }

🖥️ Usage

1. Start the Server: Run the application by pointing it to your main photo directory.

   python app.py --root-photo-dir "C:/Path/To/My/Photos"

2. Access the Web Interface: Open your browser and navigate to: http://localhost:5000

3. Login: Use the username admin and the password you set in settings.json (default is pass).

4. Scan Library: Click the "🔄 Refresh" button in the sidebar to start scanning photos, detecting faces, and extracting GPS data.

📂 Data Structure

This application does not use a central database for photo metadata. Instead, it uses Sidecar Files:

• profile.json: Created inside each photo subdirectory. Contains face encodings, bounding boxes, and image hashes for that specific folder.
• people.json: Located in the application root. Maps unique UUIDs to Person Names and Avatars.

🤝 Face Management Workflow

1. Scan: Wait for the scanner to finish.
2. Identify: Go to an album or photo. Click on an "Unknown" face (dashed border).
3. Name: Enter a name to create a new person.
4. Merge: If the system finds the same person but thinks they are new, click the face, select the existing name from the dropdown, and click "Save" to merge them.

📄 License

MIT License (or whichever license you prefer)