SnapECG is an iOS app that allows users to analyze ECG images using Hugging Face's powerful vision-language model. Simply take a photo of an ECG or select one from your photo library, and the app will provide an interpretation.

SnapECG uses a specialized Hugging Face API for medical image understanding, providing accurate ECG analysis while keeping the app lightweight.

The app utilizes a specialized ECG analysis model that can identify key cardiac patterns and abnormalities. It's designed for educational purposes and to provide a quick reference, though it should not replace professional medical evaluation.

• Install the TestFligh beta. You need an iPhone running iOS 18.

Or, to build the app yourself:

• Clone the repository
• Open the Xcode project in Xcode
• Configure your API credentials:
  • Copy APIConfig.template.swift to APIConfig.swift
  • Replace the placeholder values with your actual Hugging Face API endpoint and API key
• Run the app on a physical device

You'll need to change the bundle identifier and developer team to run the app on your device.

The app uses a Hugging Face API for ECG image analysis. The default installation includes a pre-configured API key, so most users won't need to change anything.

If you need to use your own API key:

1. The API key is stored in APIConfig.swift (excluded from git)
2. This file is pre-configured with the default credentials
3. If you wish to use your own key, simply modify the huggingFaceAPIKey value

For developers:

• The actual API credentials are in APIConfig.swift (not tracked in git)
• A template version (APIConfig.template.swift) is included for reference
• The app validates API configuration at startup and provides warnings if not properly set up

SnapECG is intended for educational purposes only. The app should not be used for diagnosis, treatment, or prevention of any disease or health condition. Always consult with a qualified healthcare provider for medical advice.