app.py

from flask import Flask, render_template, Response
from deepface import DeepFace 
import cv2

app = Flask(__name__)

faceCascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
cap = cv2.VideoCapture(0)

def analyze_video():
    while True:
        ret, frame = cap.read()
        result = DeepFace.analyze(frame, actions=['emotion'], enforce_detection=False)
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        faces = faceCascade.detectMultiScale(gray, 1.1, 4)
        try:
            for (x, y, w, h) in faces:
                cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
                font = cv2.FONT_HERSHEY_SIMPLEX
                cv2.putText(frame, result[0]['dominant_emotion'], (50, 100), font, 3, (0, 0, 255), 5, cv2.LINE_4)
        except:
            pass
        cv2.imshow('Demo video', frame)
        ret, jpeg = cv2.imencode('.jpg', frame)
        frame = jpeg.tobytes()
        yield (b'--frame\r\n'
               b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')

@app.route('/')
def index():
    return render_template('index.html')

@app.route('/video_feed')
def video_feed():
    return Response(analyze_video(), mimetype='multipart/x-mixed-replace; boundary=frame')

if __name__ == '__main__':
    app.run(debug=True)