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Age, Gender & Emotion Detection using swatahVision (OpenVINO Engine)

This example demonstrates how to perform real-time Age, Gender, and Emotion prediction using OpenVINO retail models through the swatahVision framework.

The script captures frames from the webcam, detects faces, and predicts:

  • Age
  • Gender
  • Emotion

for each detected face in real time.

The results are displayed directly on the webcam feed.

📁 Folder Structure

emotion_detection_project/
├── emotions-recognition-retail-0003_openvino.py
├── README.md

Model files are loaded from the OpenVINO model directory.

📥 Model Download

Pretrained models used in this example:

Model Purpose
age-gender-recognition-retail-0013 Predicts age and gender
emotions-recognition-retail-0003 Predicts facial emotion

These models are part of the OpenVINO Model Zoo.

More models are available here:

🔗 https://visionai4bharat.github.io/swatahVision/model_zoo/

🔧 Requirements

  • Python 3.9+
  • NumPy
  • OpenCV
  • swatahVision

🧩 Installation

conda create -n swatah_env python=3.9 -y
conda activate swatah_env

Install Dependencies

pip install numpy
pip install opencv-python
pip install swatahVision

🚀 How to Run

Run the script:

python emotions-recognition-retail-0003_openvino.py

Your webcam will open and start detecting:

Age
Gender
Emotion

Press ESC to exit the program.

📊 Example Output

The webcam window will display bounding boxes with predictions:

Male 34 | happy
Female 22 | surprise
Male 45 | neutral

Each label contains:

Gender Age | Emotion

🧠 Model Information

Property Value
Framework swatahVision
Engine OpenVINO
Hardware CPU
Age/Gender Model age-gender-recognition-retail-0013
Emotion Model emotions-recognition-retail-0003
Input Face image
Output Age, Gender, Emotion

⚠️ Notes

  • The webcam must be enabled.
  • The model works best with clear frontal faces.
  • Face detection uses OpenCV Haar Cascade.
  • Bounding box smoothing is applied to reduce jitter.
  • Age prediction is an estimate, not exact.

Summary

This project demonstrates a real-time face analysis system using swatahVision and OpenVINO.

The pipeline performs:

Webcam Frame
      ↓
Face Detection
      ↓
Age & Gender Prediction
      ↓
Emotion Recognition
      ↓
Display Results on Screen

This can be used in applications such as:

  • Human-computer interaction
  • Smart retail analytics
  • Emotion-aware systems
  • Computer vision demos