Eve Smile – Fast & Popular

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

1. Product Overview EVE Smile is a mobile-first application that uses computer vision, voice analysis, and positive psychology to help users improve emotional well-being through guided smile exercises, mood tracking, and real-time feedback. eve smile

# Symmetry (difference between left and right smile pull) left_cheek = face_landmarks.landmark[234] # left cheek right_cheek = face_landmarks.landmark[454] # right cheek symmetry = 100 - abs(left_cheek.y - right_cheek.y) * 200 var output = List.filled(1

def calculate_smile_score(face_landmarks, image_shape): # Key landmarks: # Lip corners: 61 (left), 291 (right), 13 (upper lip), 14 (lower lip) left_mouth = face_landmarks.landmark[61] right_mouth = face_landmarks.landmark[291] upper_lip = face_landmarks.landmark[13] lower_lip = face_landmarks.landmark[14] 13 (upper lip)

Future<void> loadModel() async _interpreter = await Interpreter.fromAsset('smile_model.tflite');

-- User streaks CREATE TABLE streaks ( user_id UUID PRIMARY KEY, current_streak_days INT, longest_streak_days INT, last_smile_date DATE ); 5.1 Smile Detection Pipeline (On-Device for privacy/speed) # Pseudo-code using MediaPipe Face Mesh import mediapipe as mp import cv2 import numpy as np mp_face_mesh = mp.solutions.face_mesh face_mesh = mp_face_mesh.FaceMesh(static_image_mode=False, min_detection_confidence=0.5)

# Smile intensity (mouth opening + lip corner pull) mouth_width = distance(left_mouth, right_mouth) mouth_height = distance(upper_lip, lower_lip) intensity = min(100, (mouth_width / normalized_width) * 50 + (mouth_height / normalized_height) * 50)