KinderAct

Description:

KinderAct is an AI-powered web application developed on the Google Cloud Platform (GCP) that specializes in real-time facial expression recognition using Vertex AI and App Engine technologies. The project focuses on enhancing user experience and interaction by accurately detecting and interpreting facial expressions.

Key Features:

• Real-time facial expression recognition from camera feed.
• Utilization of Vertex AI and App Engine for seamless deployment and scalability.
• Custom Python scraper employed for scraping and labeling 150+ facial image datasets.
• Achieved over 90% accuracy rate in labeling emotions.
• Trained a computer vision deep neural network model with over 82% validation accuracy in detecting 3 primary facial expressions: happy, sad, and angry.

Technologies Used:

• Google Cloud Platform (GCP)
  • Vertex AI
  • App Engine
• Python for scraping datasets

Dataset:

The project utilized a custom Python scraper to collect and label a diverse dataset comprising over 150 facial images. This dataset was meticulously labeled to ensure high accuracy in emotion recognition.

Model Training:

The computer vision deep neural network model was trained using the collected dataset. The model achieved an impressive validation accuracy of over 82% in accurately detecting happy, sad, and angry facial expressions.

Usage:

To utilize KinderAct, simply access the web application through the provided link. Allow access to your camera, and the application will seamlessly recognize and interpret your facial expressions in real-time.

How to Use KinderAct:

1. Open KinderAct App
2. Click "Mulai"
3. Allow your camera access on your browser
4. Enjoy!!

Notes: The image on the left shows an example of an expression that can be followed

Demo Project (https://youtu.be/irVxBsLXkRU)