Emotion detection system

Emotion detection system using python 

An emotion detection system using Python and a pre-trained model like fer (Facial Emotion Recognition) or DeepFace. This code will use the DeepFace library, which supports multiple models for facial emotion recognition.

Step 1: Install Required Libraries

pip install deepface opencv-python

Step 2: Write the Emotion Detection Code

import cv2
from deepface import DeepFace

# Load the pre-trained DeepFace model for emotion detection
def detect_emotion(image_path):
    # Analyze the image to detect emotions
    analysis = DeepFace.analyze(img_path=image_path, actions=['emotion'])
    
    # Get the dominant emotion
    dominant_emotion = analysis['dominant_emotion']
    
    return dominant_emotion

# Capture video from the webcam
def emotion_from_webcam():
    cap = cv2.VideoCapture(0)

    while True:
        ret, frame = cap.read()
        
        # Save the frame as a temporary image
        cv2.imwrite("temp.jpg", frame)
        
        # Detect emotion in the current frame
        emotion = detect_emotion("temp.jpg")
        
        # Display the detected emotion on the frame
        cv2.putText(frame, emotion, (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2, cv2.LINE_AA)
        
        # Show the frame
        cv2.imshow('Emotion Detection', frame)
        
        # Break the loop if 'q' is pressed
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    # Release the video capture object and close all OpenCV windows
    cap.release()
    cv2.destroyAllWindows()

# Run the emotion detection from webcam
emotion_from_webcam()

How the Code Works:

1. DeepFace: The DeepFace.analyze function is used to analyze the image and detect emotions. It supports several models, but the default model is VGG-Face.
2. Webcam Capture: The code captures video from the webcam and detects emotions in real-time.
3. Display Emotion: The detected emotion is overlaid on the video frame.

Step 3: Run the Code

When you run the code, it will open a webcam feed, detect emotions in real-time, and display the dominant emotion on the video stream. Press q to exit the webcam feed.

Notes:

• The emotion detection is based on facial expressions, so ensure your face is visible in the webcam for accurate results.
• You can replace "temp.jpg" with frame directly if you prefer to analyze the frame without saving it as an image file. However, the current approach ensures that the frame is properly analyzed in case of any format issues.