script.py

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

while vid.isOpened():
    _, frame = vid.read()

    # takes in a gray coloured filter of the frame
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # initializing the haarcascade face detector
    faces = face_cascade.detectMultiScale(frame)
    for (x,y,w,h) in faces:
        cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 2)

        # takes the region of interest of the face only in gray
        roi_gray = gray[y:y+h, x:x+h]
        resized = cv2.resize(roi_gray, (48, 48))    # resizes to 48x48 sized image

        # predict the mood
        img = img2tensor(resized)
        prediction = predict(img)

        cv2.putText(frame, f"{prediction['label']}", (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,255,0))


    cv2.imshow('video', frame)
    if cv2.waitKey(1) == 27:
        break

vid.release()
cv2.destroyAllWindows()