Kindly click on the 'Agree' button to continue with the meeting schedule.
₹0.00
Total downloads: 28
This project uses a facial expression recognition (FER) model to detect emotions and estimate stress levels in real time. It works by tracking faces, extracting facial features, and classifying emotions using machine learning. The system then analyzes these emotions to assess potential stress levels.
The model is built in Python and works on both Windows and Linux, though it has mainly been tested on Windows. It uses OpenCV for real-time face detection and integrates deep learning models like CNN for accurate emotion classification. The system is designed to process data quickly, making it useful for applications like mental health monitoring, human-computer interaction, and security surveillance.
Note: This project is being developed and tested exclusively on Google Colab.
Experience the future of emotion and stress analysis with our Facial Expression Detection System! Powered by cutting-edge machine learning and computer vision, simply upload an image from your device or capture a live image, hit ‘Analyze,’ and receive instant insights into emotions and stress levels. Revolutionize mental health tracking and emotion recognition with just a click!
Only logged in customers who have purchased this product may leave a review.
shubh.shrivastava –
Nice
md.ridwan –
Good
md.ridwan –
Good
kapil.gupta –
ok
majid.ali –
Thank you
omar.faruq (verified owner) –
jiyesttt
omar.faruq (verified owner) –
buy