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import numpy as np
import cv2

img = cv2.imread('shapes.jpg')
imgGrey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
_, thrash = cv2.threshold(imgGrey, 240, 255, cv2.THRESH_BINARY)
contours, _ = cv2.findContours(thrash, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)

cv2.imshow("img", img)
for contour in contours:

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import cv2 as cv
import numpy as np

img = cv.imread('sudoku.png',0)
_, th1 = cv.threshold(img, 127, 255, cv.THRESH_BINARY)
th2 = cv.adaptiveThreshold(img, 255, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY, 11, 2);
th3 = cv.adaptiveThreshold(img, 255, cv.ADAPTIVE_THRESH_GAUSSIAN_C, cv.THRESH_BINARY, 11, 2);

cv.imshow("Image", img)
cv.imshow("THRESH_BINARY", th1)

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def add(x, y=2):
    return x + y


def product(x, y=2):
    return x * y

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import cv2
import numpy as np
apple = cv2.imread('apple.jpg')
orange = cv2.imread('orange.jpg')
print(apple.shape)
print(orange.shape)
apple_orange = np.hstack((apple[:, :256], orange[:, 256:]))

# generate Gaussian pyramid for apple
apple_copy = apple.copy()

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import numpy as np
import cv2 as cv
cap = cv.VideoCapture('vtest.avi')
#kernel = cv.getStructuringElement(cv.MORPH_ELLIPSE, (3,3))
fgbg = cv.bgsegm.createBackgroundSubtractorMOG()
#fgbg = cv.bgsegm.BackgroundSubtractorGMG()
#fgbg = cv.createBackgroundSubtractorMOG2(detectShadows=True)
#fgbg = cv.createBackgroundSubtractorKNN(detectShadows=True)
while True:
    ret, frame = cap.read()

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import cv2
import numpy as np
from matplotlib import pyplot as plt

img = cv2.imread("lena.jpg")
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
canny = cv2.Canny(img, 100, 200)

titles = ['image', 'canny']
images = [img, canny]

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	$objShell = New-Object -ComObject Shell.Application
	$objFolder = $objShell.Namespace(0xA)
	$WinTemp = "c:\Windows\Temp\*"
	
#1#	Empty Recycle Bin #
	write-Host "Emptying Recycle Bin." -ForegroundColor Cyan 
	$objFolder.items() | %{ remove-item $_.path -Recurse -Confirm:$false}
	
#2# Remove Temp

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import numpy as np
import cv2 as cv
from matplotlib import pyplot as plt

img = cv.imread("lena.jpg")
#img = np.zeros((200,200), np.uint8)
#cv.rectangle(img, (0, 100), (200, 200), (255), -1)
#cv.rectangle(img, (0, 50), (100, 100), (127), -1)
b, g, r = cv.split(img)
cv.imshow("img", img)

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#include <SoftwareSerial.h> // Import Soft Uart library
#include <Servo.h>  // Import Servo library

// Bluetooth communication pins
#define TX 2 
#define RX 4

// L298N communication pins
#define IN1 3
#define IN2 5

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def add(x, y):
    return x + y