Week #10: Make-through

from picamera.array import PiRGBArray

from picamera import PiCamera

import time

import cv2

import RPi.GPIO as GPIO

import tim

camera = PiCamera() # this part of capturing the video

camera.resolution = (640, 480)

camera.framerate = 15

rawCapture = PiRGBArray(camera, size=(640, 480))

eye_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') # using classfier to detect face

GPIO.setmode(GPIO.BOARD)

GPIO.setup(11,GPIO.OUT) # indetfy the pins

GPIO.setup(13,GPIO.OUT)

servo1 = GPIO.PWM(11,50)

servo1.start(0)# using to servo-one with start angle zero

time.sleep(0.1)

for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):

frame = frame.array

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)# convert image to gray to make easy in processing

eyes = eye_cascade.detectMultiScale(gray, 1.3, 8)#function which detect the eyes in the video search about the value between the brackets it can increase or decrease the accuracy (after convert to gray to make easy processing)

for (x, y, w, h) in eyes:

center = (int(x + w / 2), int(y + h / 2)) # X and Y is the dimension of image and w and h is the dimension of the rectange Which draw around the face. the equation give the center of face.

if center[0] > 320 and center[1] >240: # condition of changing the color of rectangle according tho the position of face on the screen (screen divide into 4 parts)

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

elif center[0] > 320 and center[1] <240:

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

elif center[0] < 320 and center[1] < 240:

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

else:

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

print (center)# print the center you will show under code

cv2.circle(frame, center, 1, (0, 255, 0), 2)

cv2.circle(frame, center, 1, (0, 255, 0), 2)

w = center[0]

h = center[1]

# control movement of servo

angle1 = (w/640)*180

angle2 = (h/480)*180

servo1.ChangeDutyCycle(2+(angle1/18))

time.sleep(0.2)

servo1.ChangeDutyCycle(0)

time.sleep(0.3)

print (angle1,angle2) #show the angle of servo see the orange arrow

cv2.imshow("Frame", frame)

key = cv2.waitKey(1) & 0xFF

rawCapture.truncate(0)