smile-detection

import numpy as np
import cv2
import sys

facePath = 'haarcascade_frontalface_default.xml'
smilePath = 'haarcascade_smile.xml'
face_cascade = cv2.CascadeClassifier(facePath)
smile_cascade = cv2.CascadeClassifier(smilePath)

cap = cv2.VideoCapture(0)
cap.set(3,640)
cap.set(4,480)
sF=1.05
a=0

while True:
  if a==1:
    img_name = "opencv_frame_complete.png"
    cv2.imwrite(img_name, img)
    break
  ret, img = cap.read()
  gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  faces = face_cascade.detectMultiScale(
    gray,
    scaleFactor=sF,
    minNeighbors=8,
    minSize=(55, 55),
    flags=cv2.CASCADE_SCALE_IMAGE
    )
  
  for (x, y, w, h) in faces:
    cv2.rectangle(img, (x,y), (x+w, y+h), (255, 0, 0), 2)
    roi_gray = gray[y:y+h, x:x+w]
    roi_color = img[y:y+h, x:x+w]
    
    smile=smile_cascade.detectMultiScale(
      roi_gray,
      scaleFactor=1.7,
      minNeighbors=22,
      minSize=(25, 25),
      flags=cv2.CASCADE_SCALE_IMAGE
    )
    
    for (x, y, w, h) in smile:
      print ("Found"), len(smile), ("smiles")
      cv2.rectangle(roi_color, (x, y), (x+w, y+h), (0, 0, 255), 1)
      a=1
  
  cv2.imshow('Face', img)
  k=cv2.waitKey(30) & 0xff
  if k==27:
    break

cap.release()
cv2.destroyAllWindows()