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dd/// 
///
/// NOTICE: We SHOULD supply 5.0 Voltage to SERVO run stably
///
///

#include <Servo.h>   //servo library
Servo servo;     
int trigPin = 5;    
int echoPin = 6;   

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import numpy as np
import cv2 as cv

img = cv.imread('pic1.png')

gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

corners = cv.goodFeaturesToTrack(gray, 100, 0.01, 10)

corners = np.int0(corners)

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import numpy as np
import cv2 as cv

img = cv.imread('chessboard_img.png')

cv.imshow('img', img)
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

gray = np.float32(gray)
dst = cv.cornerHarris(gray, 2, 3, 0.04)

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# Import the Gtts module for text  
# to speech conversion 
from gtts import gTTS 
  
# import Os module to start the audio file
import os 

fh = open("test.txt", "r")
myText = fh.read().replace("\n", " ")

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import cv2

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye_tree_eyeglasses.xml')
cap = cv2.VideoCapture('test.mp4')

while cap.isOpened():
    _, img = cap.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.1, 4)

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import cv2

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
# Read the input image
#img = cv2.imread('test.png')
cap = cv2.VideoCapture('test.mp4')

while cap.isOpened():
    _, img = cap.read()

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import numpy as np
import cv2 as cv
img = cv.imread('smarties.png')
output = img.copy()
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
gray = cv.medianBlur(gray, 5)
circles = cv.HoughCircles(gray, cv.HOUGH_GRADIENT, 1, 20,
                          param1=50, param2=30, minRadius=0, maxRadius=0)
detected_circles = np.uint16(np.around(circles))
for (x, y ,r) in detected_circles[0, :]:

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import matplotlib.pylab as plt
import cv2
import numpy as np

def region_of_interest(img, vertices):
    mask = np.zeros_like(img)
    #channel_count = img.shape[2]
    match_mask_color = 255
    cv2.fillPoly(mask, vertices, match_mask_color)
    masked_image = cv2.bitwise_and(img, mask)

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import matplotlib.pylab as plt
import cv2
import numpy as np

def region_of_interest(img, vertices):
    mask = np.zeros_like(img)
    #channel_count = img.shape[2]
    match_mask_color = 255
    cv2.fillPoly(mask, vertices, match_mask_color)
    masked_image = cv2.bitwise_and(img, mask)

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import matplotlib.pylab as plt
import cv2
import numpy as np

image = cv2.imread('road.jpg')
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

print(image.shape)
height = image.shape[0]
width = image.shape[1]