tensorflow_face_verification 0.1.2

AI Powered Face Verification (Face Embedding & Comparison)

Flutter Face Verification (Face Embedding & Comparison)

This package delivers TensorFlow-powered face matching by leveraging Google ML Kit’s Face Detection, wrapped in a lightweight Dart helper class. It supports determining whether two faces belong to the same person and provides a similarity score for flexible comparisons.

• 🧠 128D Face Embedding Generation (FaceNet model)
• 🔍 ML Kit Face Detection with auto-cropping
• 📸 Compare faces and compute similarity score

🚨 The code assumes the use of a tflite model facenet.tflite.

⚙️ Works offline — all computation is done on-device.

✅ Fully asynchronous and customizable.

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🧪 Features

• Match faces between two images
• Detect and crop the face region from an image
• Measure similarity between faces
• Offline use – no internet required

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🧪 Note

This package is rely on tflite_flutter.

🚨 This package may not work in the iOS simulator. It's recommended that you test with a physical device.

🚨 When creating a release archive (IPA), the symbols are stripped by Xcode, so the command flutter build ipa may throw a Failed to lookup symbol ... symbol not found error. To work around this:

1. In Xcode, go to Target Runner > Build Settings > Strip Style
2. Change from All Symbols to Non-Global Symbols

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🚀 Getting Started

1. Add Your Model

Place your model in assets/models/facenet.tflite.

flutter:
  assets:
    - assets/models/facenet.tflite

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⚙️ Usage Example

Initialize

await FaceVerification.init(modelPath: 'assets/models/facenet.tflite');

Compare Two Face Images

bool isSame = await FaceVerification.instance.verifySamePerson(
  File('path/to/image1.jpg'),
  File('path/to/image2.jpg'),
  threshold: 0.6,
);
print("Same person? $isSame");

Get Similarity Score

double score = await FaceVerification.instance.getFaceSimilarityFromFile(
  File('path/to/image1.jpg'),
  File('path/to/image2.jpg'),
);
print("Similarity: $score");

Image image1 = ....;
Image image2 = ....;

double score = await FaceVerification.instance.getFaceSimilarityFromImage(
  image1,
  image2,
);
print("Similarity: $score");

Additional customizations

Image image1FaceRegion = await FaceVerification.instance.extractFaceRegion(
  File('path/to/image1.jpg')
);

Image image2FaceRegion = await FaceVerification.instance.extractFaceRegion(
  File('path/to/image1.jpg')
);

List<double> image1EmbeddingVector = await FaceVerification.instance.extractFaceEmbedding(
  image1FaceRegion
);

List<double> image2EmbeddingVector = await FaceVerification.instance.extractFaceEmbedding(
  image2FaceRegion
);

double score = await FaceVerification.instance.getSimilarityScore(
  image1EmbeddingVector, image2EmbeddingVector
);

print("Similarity: $score");
print("Same person ${score > 0.6}");

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🤝 Contributing

Feel free to fork, modify, and submit a PR.
Suggestions, bug reports, or new features are welcome.

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📄 License

MIT License