Emotion Detection Using Machine Learning Python - Creation Code

Emotion Recognition: 

Emotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. The use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context. To date, most work has been conducted on automating the recognition of facial expressions from video.

Modules and libraries:

1. Keras - pip install keras
2. Numpy - pip install numpy
3. OpenCV - pip install opencv-python

Note:

We will use two main files which will help us to recognize faces and expressions

You can download the files from here

Code:

from keras.models import load_model

from time import sleep

from keras.preprocessing.image import img_to_array

from keras.preprocessing import image

import cv2

import numpy as np

face_classifier = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

classifier =load_model('model.h5')

emotion_labels = ['Angry','Disgust','Fear','Happy','Neutral', 'Sad', 'Surprise']

cap = cv2.VideoCapture(0)

while True:

    _, frame = cap.read()

    labels = []

    gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)

    faces = face_classifier.detectMultiScale(gray)

    for (x,y,w,h) in faces:

        cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,255),2)

        roi_gray = gray[y:y+h,x:x+w]

        roi_gray = cv2.resize(roi_gray,(48,48),interpolation=cv2.INTER_AREA)

        if np.sum([roi_gray])!=0:

            roi = roi_gray.astype('float')/255.0

            roi = img_to_array(roi)

            roi = np.expand_dims(roi,axis=0)

            prediction = classifier.predict(roi)[0]

            label=emotion_labels[prediction.argmax()]

            label_position = (x,y)

            cv2.putText(frame,label,label_position,cv2.FONT_HERSHEY_SIMPLEX,1,(0,255,0),2)

        else:

            cv2.putText(frame,'No Faces',(30,80),cv2.FONT_HERSHEY_SIMPLEX,1,(0,255,0),2)

    cv2.imshow('Emotion Detector',frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):

        break

cap.release()

cv2.destroyAllWindows()

Follow my socials:

Youtube:https://www.youtube.com/channel/UCU1qNFntn7dCi9uqyvrGKOg

Instagram: https://www.instagram.com/python.math/

Twitter:https://twitter.com/Pritish369

For any question or coding discussion, you can join my discord or telegram:

Discord:https://discord.gg/be7MmSuV

Telegram:https://t.me/Python_Math_Community