func.py

import smtplib
import os
from email.mime.multipart import MIMEMultipart
from email.mime.image import MIMEImage
from time import time
import cv2
import numpy as np
import ConfigParser
import time
import RPi.GPIO as GPIO
import time
import picamera


ROOT_NODE = -1

def buzzier():
    GPIO.setmode(GPIO.BOARD)
    GPIO.setup(12, GPIO.OUT)
    p = GPIO.PWM(12, 50)
    p.start(50)
   
    p.ChangeFrequency(659)
    time.sleep(1)

    p.stop()
    GPIO.cleanup()

def get_frame():
    img = open("image/1.jpg", "rb").read()
    return img

def countObj():

    if os.stat('image/0.jpg').st_size > 0:

        fidelity = False
        fidelityValue = .7
        img = cv2.imread('image/0.jpg')
        imgCopy = img.copy()
        img = cv2.medianBlur(img, 15)
        #img = cv2.adaptiveBilateralFilter(img, (5, 5), 150) # Preserve edges
        #img = cv2.blur(img, (3,3))
        img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        #imgt = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 3, 10)
        _, imgt = cv2.threshold(img, 125, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)
        #_, imgt = cv2.threshold(img, 125, 255, cv2.THRESH_BINARY_INV)
        imgt = cv2.morphologyEx(imgt, cv2.MORPH_OPEN, (5, 5))

        img2 = imgt.copy()
        c, h = cv2.findContours(img2, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
        fidelityRange = 0
        if fidelity:
            maxArea = .0;
            for i in c: # With images it is convenient to know the greater area
                area = cv2.contourArea(i)
                if area > maxArea:
                    maxArea = area
            fidelityRange = maxArea - (maxArea * fidelityValue); # If objects have same size it prevents false detection

        totalContours = 0

        br = []
        for i in xrange(len(c)):
            if h[0][i][3] == ROOT_NODE and cv2.contourArea(c[i]) >= fidelityRange:
                totalContours += 1
                approx = cv2.approxPolyDP(c[i], 3, True)
                br.append(cv2.boundingRect(approx))
        for b in br:
            cv2.rectangle(imgCopy, (b[0], b[1]), (b[0] + b[2], b[1] + b[3]), (255, 255, 0), 3)
        cv2.imwrite('image/1.jpg', imgCopy)
        print 'Total contours: ', totalContours
        return totalContours

    else:
        return -1