Smile detection using OpenCv

Here are the Installation steps for Python OpenCv on Raspberry Pi:

1) sudo apt-get update

2) sudo apt-get upgrade

3) sudo apt-get install build-essential

4) sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev

5)sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev        

    libjasper-dev libdc1394-22-dev

6) sudo apt-get install python-opencv

7) sudo apt-get install python-matplotlib

Step for Configure and Enable Camera:

Project Code for Smile Detection:

import cv2

import numpy as np

import sys

facePath = "haarcascade_frontalface_default.xml"

smilePath = "haarcascade_smile.xml"

faceCascade = cv2.CascadeClassifier(facePath)

smileCascade = cv2.CascadeClassifier(smilePath)

cap = cv2.VideoCapture(0)

cap.set(3,640)

cap.set(4,480)

sF = 1.05

print(" Welcome to smile detection project")

while True:

    ret, frame = cap.read() # Capture frame-by-frame

    img = frame

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

    faces = faceCascade.detectMultiScale(

        gray,

        scaleFactor= sF,

        minNeighbors=8,

        minSize=(55, 55),

        flags=cv2.CASCADE_SCALE_IMAGE

    )

    # ---- Draw a rectangle around the faces

    for (x, y, w, h) in faces:

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

        roi_gray = gray[y:y+h, x:x+w]

        roi_color = frame[y:y+h, x:x+w]

        smile = smileCascade.detectMultiScale(

            roi_gray,

            scaleFactor= 1.7,

            minNeighbors=22,

            minSize=(25, 25),

            flags=cv2.CASCADE_SCALE_IMAGE

            )

        # Set region of interest for smiles

        for (x, y, w, h) in smile:

            print ("Found"), len(smile), ("smiles!")

            cv2.rectangle(roi_color, (x, y), (x+w, y+h), (255, 0, 0), 1)

            

       

    cv2.imshow('Smile Detector', frame)

    c = cv2.waitKey(7) % 0x100

    if c == 27:

        break

cap.release()

cv2.destroyAllWindows()