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This project utilizes supervised learning to detect and classify facial expressions in real-time using video and camera input. It leverages the FER (Facial Expression Recognition) dataset to train a model capable of recognizing various emotions such as happiness, sadness, surprise, anger, and more.
🤔 Why this feature?
Real-time facial expression detection using live camera feed 📸
Supports multiple expressions including happiness, sadness, anger, surprise, etc. 😊😢😡😲
Uses a trained supervised learning model for accurate prediction
Integration of OpenCV for video capture and face detection
Easy-to-use interface for emotion tracking during live video input
📋 Expected Behavior
It will predict and display the expression around the face.
🖼️ Example/Mockups
If applicable, add examples or mockups that illustrate how the feature should look or behave.
📝 Additional Details
Add any other details or suggestions.
The text was updated successfully, but these errors were encountered:
🌟 Feature Overview
This project utilizes supervised learning to detect and classify facial expressions in real-time using video and camera input. It leverages the FER (Facial Expression Recognition) dataset to train a model capable of recognizing various emotions such as happiness, sadness, surprise, anger, and more.
🤔 Why this feature?
Real-time facial expression detection using live camera feed 📸
Supports multiple expressions including happiness, sadness, anger, surprise, etc. 😊😢😡😲
Uses a trained supervised learning model for accurate prediction
Integration of OpenCV for video capture and face detection
Easy-to-use interface for emotion tracking during live video input
📋 Expected Behavior
It will predict and display the expression around the face.
🖼️ Example/Mockups
If applicable, add examples or mockups that illustrate how the feature should look or behave.
📝 Additional Details
Add any other details or suggestions.
The text was updated successfully, but these errors were encountered: