NutriLenz is an innovative food scanning app that utilizes a custom AI model to scan food images and provide accurate nutritional information. Built with Flutter, the app allows users to upload or take photos of food, and the app will identify the item and display its nutritional details such as calories, protein, fats, and vitamins. This project also includes an integrated voice command feature for a hands-free user experience.

Key Features:

Custom AI Model: The app uses a machine learning model to analyze food images and identify their nutritional content. This model is trained on a large dataset of food images and nutritional information to ensure accuracy.
Image Scanning: Users can scan food items by either uploading a photo or taking one directly within the app. The AI model processes the image to identify the food and return detailed nutrition data.
Voice Interaction: The app includes a Speech-to-Text feature, enabling users to ask for nutritional information via voice commands, making it easier for users to interact without typing.
Text-to-Speech: Users receive voice-based responses that provide nutritional information, ensuring a hands-free and interactive experience.

Technologies Used:

Flutter: For building the cross-platform app (Android and iOS).
Custom AI Model: A trained model for food image recognition and nutritional analysis.
TensorFlow / PyTorch: For training and implementing the machine learning model.
Speech-to-Text: To process voice commands.
Text-to-Speech (TTS): To provide voice responses and feedback.

Challenges Overcome:

Accuracy of Food Recognition: Ensuring that the AI model accurately identifies a wide variety of food items.
Real-Time Analysis: Processing food images in real-time while maintaining high accuracy and speed.

Portfolio Title: NutriLenz Food Scanning App with Custom AI Model for Nutrition Analysis

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