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A computer vision project that detects human emotions from facial expressions in images using the pre-trained DeepFace model. This project leverages deep learning and facial analysis to classify emotions like happy, sad, angry, surprise, and more. Built with Python and OpenCV for easy integration and testing.

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Aashish-Chandr/Emotion-Detector-From-Image

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Emotion Detection from Images using DeepFace

This project uses the pre-trained DeepFace model to detect and classify human emotions from facial expressions in images. It leverages deep learning and computer vision to identify emotions such as happy, sad, angry, surprise, and more with high accuracy.

🔍 Features

  • Emotion detection from static images
  • Uses the powerful pre-trained DeepFace model
  • Lightweight and easy to run
  • No training required – ready to use
  • Built with Python and OpenCV

🧠 Emotions Detected

  • Angry 😠
  • Disgust 🤢
  • Fear 😨
  • Happy 😄
  • Sad 😢
  • Surprise 😲
  • Neutral 😐

🛠️ Tech Stack

📦 Installation

  1. Clone the repository:
git clone https://github.com/yourusername/emotion-detection-deepface.git
cd emotion-detection-deepface
pip install -r requirements.txt
pip install deepface opencv-python matplotlib
python detect_emotion.py

About

A computer vision project that detects human emotions from facial expressions in images using the pre-trained DeepFace model. This project leverages deep learning and facial analysis to classify emotions like happy, sad, angry, surprise, and more. Built with Python and OpenCV for easy integration and testing.

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