pupil.py

import numpy as np
import cv2
import time
import pygame
import datetime
import requests

count = 0

pygame.mixer.init()
pygame.mixer.music.load("wakeMeUpChorus.mp3")
pygame.mixer.music.play(-1)
pygame.mixer.music.pause()

cap = cv2.VideoCapture(0)  # 640,480
w = 640
h = 480
start = 0

while(True):
    ret, frame = cap.read()
    if ret == True:

        # downsample
        # frameD = cv2.pyrDown(cv2.pyrDown(frame))
        # frameDBW = cv2.cvtColor(frameD,cv2.COLOR_RGB2GRAY)

        # detect face
        frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
        faces = cv2.CascadeClassifier('eye.xml')
        detected = faces.detectMultiScale(frame, 1.3, 5)

        # faces = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
        # detected2 = faces.detectMultiScale(frameDBW, 1.3, 5)

        pupilFrame = frame
        pupilO = frame
        windowClose = np.ones((5, 5), np.uint8)
        windowOpen = np.ones((2, 2), np.uint8)
        windowErode = np.ones((2, 2), np.uint8)

        irises = []

        for (ex, ey, ew, eh) in detected:
            iris_w = int(ex + float(ew / 2))
            iris_h = int(ey + float(eh / 2))
            irises.append([np.float32(iris_w), np.float32(iris_h)])

        if (len(irises) < 2):
            # print(start)
            start += 1
            if (start == 60):
                requests.post(
                    url="https://thawing-everglades-71893.herokuapp.com/user/count", data={"username": "duy"})
                pygame.mixer.music.unpause()

        else:
            start = 0
            pygame.mixer.music.pause()

        # draw square
        for (x, y, w, h) in detected:
            cv2.rectangle(frame, (x, y), ((x+w), (y+h)), (0, 0, 255), 1)
            cv2.line(frame, (x, y), ((x+w, y+h)), (0, 0, 255), 1)
            cv2.line(frame, (x+w, y), ((x, y+h)), (0, 0, 255), 1)
            pupilFrame = cv2.equalizeHist(
                frame[(y+(h*25//100)):(y+h), x:(x+w)])
            pupilO = pupilFrame
            ret, pupilFrame = cv2.threshold(
                pupilFrame, 55, 255, cv2.THRESH_BINARY)  # 50 ..nothin 70 is better
            pupilFrame = cv2.morphologyEx(
                pupilFrame, cv2.MORPH_CLOSE, windowClose)
            pupilFrame = cv2.morphologyEx(
                pupilFrame, cv2.MORPH_ERODE, windowErode)
            pupilFrame = cv2.morphologyEx(
                pupilFrame, cv2.MORPH_OPEN, windowOpen)

            # so above we do image processing to get the pupil..
            # now we find the biggest blob and get the centriod

            threshold = cv2.inRange(pupilFrame, 250, 255)  # get the blobs
            # (python 3.6) contours, hierarchy = cv2.findContours(threshold, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)

            contours, hierarchy = cv2.findContours(
                threshold, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)

            # if there are 3 or more blobs, delete the biggest and delete the left most for the right eye
            # if there are 2 blob, take the second largest
            # if there are 1 or less blobs, do nothing

            if len(contours) >= 2:
                # find biggest blob
                maxArea = 0
                MAindex = 0  # to get the unwanted frame
                distanceX = []  # delete the left most (for right eye)
                currentIndex = 0
                for cnt in contours:
                    area = cv2.contourArea(cnt, True)
                    center = cv2.moments(cnt)
                    if (center['m00'] != 0):
                        cx, cy = int(center['m10']/center['m00']
                                     ), int(center['m01']/center['m00'])
                        distanceX.append(cx)
                        if area > maxArea:
                            maxArea = area
                            MAindex = currentIndex
                        currentIndex = currentIndex + 1

                del contours[MAindex]  # remove the picture frame contour
                del distanceX[MAindex]

            eye = 'right'

            if len(contours) >= 2:  # delete the left most blob for right eye
                if eye == 'right':
                    edgeOfEye = distanceX.index(min(distanceX))
                else:
                    edgeOfEye = distanceX.index(max(distanceX))
                del contours[edgeOfEye]
                del distanceX[edgeOfEye]

            if len(contours) >= 1:  # get largest blob
                maxArea = 0
                for cnt in contours:
                    area = cv2.contourArea(cnt)
                    if area > maxArea:
                        maxArea = area
                        largeBlob = cnt

            if len(largeBlob) > 0:
                center = cv2.moments(largeBlob)
                cx, cy = int(center['m10']/center['m00']
                             ), int(center['m01']/center['m00'])
                cv2.circle(pupilO, (cx, cy), 5, 255, -1)

        cv2.imshow('frame', pupilO)
        # cv2.imshow('frame2', pupilFrame)
        # show picture
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

# Release everything if job is finished
cap.release()
cv2.destroyAllWindows()