Face Expression detection through vedio and camera

[shivenyadavs]

Facial Expression Detection through Video and Camera 🎥😄

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.

Features

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

Dataset

FER Dataset: A widely-used dataset for emotion detection, containing labeled facial images with corresponding emotion categories.

Tech Stack

Python 🐍
OpenCV for real-time video processing 🎥
Supervised Learning models (e.g., Logistic Regression, SVM, etc.)
TensorFlow/Keras or Scikit-learn for model training 🤖

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