# Duchenne marker (eye squint) left_eye_open = eye_aspect_ratio(face_landmarks, is_left=True) right_eye_open = eye_aspect_ratio(face_landmarks, is_left=False) duchenne = 1 if (left_eye_open < 0.25 and right_eye_open < 0.25) else 0
-- Smile Frames (optional for detailed analysis) CREATE TABLE smile_frames ( id UUID PRIMARY KEY, session_id UUID REFERENCES smile_sessions(id), timestamp_offset_ms INT, score DECIMAL(3,2), symmetry DECIMAL(3,2), intensity DECIMAL(3,2), eye_squint BOOLEAN -- Duchenne marker ); eve smile
Future<double> detectSmile(CameraImage image) async // Convert CameraImage to tensor input (224x224 RGB) var input = preprocessImage(image); var output = List.filled(1, 0).reshape([1, 1]); // output: smile score 0-1 0.25 and right_eye_open <
Future<void> loadModel() async _interpreter = await Interpreter.fromAsset('smile_model.tflite'); session_id UUID REFERENCES smile_sessions(id)