THEFASHIONGEEK

import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread("imgs/chapter5/sudoku.png", 0); 
img = cv2.blur(img, (3, 3));


#############################FOCUS################################################
ret,thresh1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
thresh2 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,11,2)

THEFASHIONGEEK

import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread("imgs/chapter5/sudoku.png", 0); 
img = cv2.blur(img, (3, 3));


# threshold -> 127
# maxval    -> 255
# Output:

THEFASHIONGEEK

import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread("imgs/chapter5/a.jpg", 0); 
img = cv2.resize(img, (256, 256));
ret,img = cv2.threshold(img,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)

kernel = np.ones((11,11),np.uint8)
eroded = cv2.erode(img,kernel,iterations = 1)

THEFASHIONGEEK

import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread("imgs/chapter5/sudoku.jpg", 0); 
img = cv2.blur(img, (3, 3));


# Otsu's thresholding
ret2,img = cv2.threshold(img,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)

THEFASHIONGEEK

import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread("imgs/chapter5/sudoku.jpg", 0); 
img = cv2.blur(img, (3, 3));


# Otsu's thresholding
ret2,img = cv2.threshold(img,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)

THEFASHIONGEEK

import numpy as np
import cv2
import scipy
from matplotlib import pyplot as plt
img = cv2.imread("imgs/chapter5/rain.jpg", 0);

edges = cv2.Canny(img,150,200)

f = plt.figure(figsize=(15,15))
f.add_subplot(1, 2, 1).set_title('Original Image');

THEFASHIONGEEK

import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread("imgs/chapter5/sudoku.png", 0);

dx = cv2.Scharr(img,cv2.CV_8UC1,1,0) # first order derivative around x
dy = cv2.Scharr(img,cv2.CV_8UC1,0,1) # first order derivative around y


f = plt.figure(figsize=(15,15))

THEFASHIONGEEK

import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread("imgs/chapter5/a.jpg", 0)

dx = cv2.Sobel(img,cv2.CV_8UC1,1,0,ksize=5) # first order derivative around x
dy = cv2.Sobel(img,cv2.CV_8UC1,0,1,ksize=5) # first order derivative around y
dx2 = cv2.Sobel(img,cv2.CV_8UC1,2,0,ksize=5) # second order derivative around x
dy2 = cv2.Sobel(img,cv2.CV_8UC1,0,2,ksize=5) # second order derivative around y
dxy = cv2.Sobel(img,cv2.CV_8UC1,1,1,ksize=5) # first order derivative around x then y

THEFASHIONGEEK

import numpy as np
from PIL import Image, ImageFilter
from matplotlib import pyplot as plt
img = Image.open("imgs/chapter5/outdoor.jpg")

#######################FOCUS##################
sharpened = img.filter(ImageFilter.SHARPEN)
##############################################

f = plt.figure(figsize=(15,15))

THEFASHIONGEEK

import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread("imgs/chapter5/sudoku.png", 0)
img = cv2.blur(img, (3, 3))

kernel = [
            [-1, -1, -1],
            [-1, 9, -1],
            [-1, -1, -1]