8000 GitHub - followthwind/moodscape: aplikaski pendeteksi dan monitoring mental health berdasarkan graphology dan face recognition
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Moodscape

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Moodscape is an Android application built with Flutter that uses AI technology to analyze handwritten or printed text and facial expressions from images. It classifies both into psychological traits and provides personalized suggestions and motivation based on the results.

Tech Stack

  • Flutter – Main framework for building the app
  • TensorFlow Lite – For running machine learning models locally on Android devices
  • Teachable Machine by Google – Used to train and export image classification models
  • Camera / Gallery Input – For capturing or selecting images from the device

Core Features

Text Classification

  • The app detects text from images using Optical Character Recognition (OCR).
  • Then it classifies the detected text into one of 4 DISC personality types:
    • Dominance
    • Compliance
    • Steadiness
    • Influence

Facial Expression Classification

  • Detects faces in an image and classifies the expression into one of the 7 emotional categories:
    • Anger
    • Sadness
    • Surprise
    • Happy
    • Disgust
    • Fear
    • Neutral

Output & Motivation

  • Based on both classification results (text and facial expression):
    • Provides descriptions of two personality traits.
    • Offers personalized suggestions and motivational insights.

How to Use

  1. Take or select a photo that includes facial expression and/or text.
  2. Moodscape analyzes the image using on-device AI.
  3. Receive trait analysis and personalized motivation instantly.

Machine Learning Models

  • Models are trained using Teachable Machine.

  • Exported as TensorFlow Lite models and integrated into the Flutter app for local inference.

Permissions Required

  • The app requires access to:

  • Camera

Storage (to pick images from gallery)

📄 License MIT License

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aplikaski pendeteksi dan monitoring mental health berdasarkan graphology dan face recognition

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