VibeSign

VibeSign is a simple iPadOS application designed for capturing and storing digital signatures using an Apple Pencil. It allows users to draw signatures, view a history of their saved signatures, and export them in JSONL format. This tool is particularly useful for researchers or developers needing detailed stroke data from Apple Pencil input.

Features

• Detailed Pencil Input: Captures timestamp, precise location, force, altitude angle, and azimuth angle for each point in a signature.
• Signature History: Displays saved signatures in a list with a preview, creation date, and key statistics (point count, duration, average force).
• Interactive Drawing Canvas: A dedicated area for drawing signatures.
• Detailed View: Tap a signature in the history to view a larger preview and the raw point data.
• Signature Replay: Watch a replay of the signature being drawn in the detailed view.
• JSONL Export: Export all signature data in JSON Lines format, ideal for data analysis. Each line is a JSON object representing one signature.
• Clear Canvas: Easily clear the current drawing.
• Delete Signatures: Remove individual signatures from the history.

Getting Started

Prerequisites

• iPadOS device compatible with Apple Pencil.
• Xcode (15.0+, latest version recommended).
• Apple Pencil.

Installation

1. Clone the repository:

   git clone https://github.com/JacobLinCool/VibeSign.git

2. Open the VibeSign.xcodeproj file in Xcode.

3. Select your iPad as the build target.

4. Build and run the application on your device.

How It Works

• The application interface is divided into two main sections: a list displaying the history of saved signatures and a dedicated drawing area.
• To create a new signature, tap "Start" and begin drawing on the canvas with an Apple Pencil. The app captures detailed stroke data.
• Tap "Stop" to finish the current signature. The signature is automatically saved and added to the history.
• The signature history is displayed in reverse chronological order (newest first).
• Individual signatures can be selected from the list to view detailed information, including a replay of the signature being drawn, or be deleted.
• The "Export All" button compiles all stored signatures into a signatures.jsonl file and presents a share sheet for saving or sending the file.

Technical Details

• Framework: Built natively with SwiftUI for the user interface.
• Drawing Input: Utilizes UIViewRepresentable to wrap a custom UIView (PencilTrackView) for capturing detailed touch data from Apple Pencil. This allows access to properties like force, altitudeAngle, and azimuthAngle from UITouch.
• Data Storage: Signatures are currently stored in-memory. For persistence across app launches, further development would be needed (e.g., using Core Data, SwiftData, or saving to files).
• Data Export: Employs JSONEncoder with ISO8601 date formatting for creating the JSONL export file. Each signature record in the export includes the creation date and an array of pencil samples.
• Signature Replay: The detailed view allows for an animated replay of the signature, visualizing the drawing process based on the captured timestamps.

Export Format (JSONL)

Each line in the exported signatures.jsonl file is a JSON object representing a single signature. Here's an example structure for one line:

{"createdAt":"2025-05-14T10:30:00Z","samples":[{"timestamp":60537.123,"location":{"x":100.5,"y":150.2},"force":1.5,"altitude":0.785,"azimuth":1.570}]}
// ... more samples ...

• createdAt: ISO8601 timestamp of when the signature was saved.
• samples: An array of PencilSample objects.
  • timestamp: TimeInterval of the touch event.
  • location: CGPoint (x, y) of the touch.
  • force: Force of the touch.
  • altitude: Altitude angle of the Apple Pencil.
  • azimuth: Azimuth angle of the Apple Pencil.

Open Source & Research Utility

This application is open source under the MIT License. Its capability to capture detailed Apple Pencil input makes it a potentially valuable tool for researchers in fields such as:

• Biometric signature verification
• Handwriting analysis and generation
• Cognitive science studies on motor control
• Human-Computer Interaction (HCI) research requiring precise input data

The JSONL export feature facilitates easy data extraction and integration into various data analysis pipelines and tools.

Contributing

Contributions are welcome! If you have ideas for improvements, new features, or bug fixes, please feel free to:

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

Please ensure your code adheres to the existing style and that any new features are well-documented.

License

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