saurabhpal97

#import the required libraries 
import matplotlib.pyplot as plt 
import cv2
%matplotlib inline 
#reading the image 
image = cv2.imread('index.png') 
#reading in grayscale format 
grayscale_image = cv2.imread('index.png',0) 
#plotting the image 
plt.imshow(image) 

saurabhpal97

#import the libraries
import numpy as np
import matplotlib.pyplot as plt
import cv2
%matplotlib inline

#reading the image 

image = cv2.imread('index.png')
image = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)

saurabhpal97

#import the required libraries 
import numpy as np 
import matplotlib.pyplot as plt 
import cv2 
%matplotlib inline 
image = cv2.imread('index.jpg') 
#converting image to Gray scale 
gray_image = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
#plotting the grayscale image
plt.imshow(gray_image) 

saurabhpal97

import cv2 
import numpy as np 
import matplotlib.pyplot as plt 
%matplotlib inline 
#reading the image 
image = cv2.imread('index.jpg') 
#converting image to size (100,100,3) 
smaller_image = cv2.resize(image,(100,100),inerpolation='linear') 
#plot the resized image
plt.imshow(smaller_image)

saurabhpal97

#importing the required libraries 
import numpy as np 
import cv2 
import matplotlib.pyplot as plt 
%matplotlib inline 
image = cv2.imread('index.png') 
rows,cols = image.shape[:2] 
#(col/2,rows/2) is the center of rotation for the image 
# M is the cordinates of the center 
M = cv2.getRotationMatrix2D((cols/2,rows/2),90,1) 

saurabhpal97

#importing the required libraries 
import numpy as np 
import cv2 
import matplotlib.pyplot as plt 
%matplotlib inline 
#reading the image
image = cv2.imread('index.png')
#shifting the image 100 pixels in both dimensions
M = np.float32([[1,0,-100],[0,1,-100]]) 
dst = cv2.warpAffine(image,M,(cols,rows)) 

saurabhpal97

#importing the required libraries 
import numpy as np 
import cv2 
import matplotlib.pyplot as plt 
%matplotlib inline 

#here 0 means that the image is loaded in gray scale format
gray_image = cv2.imread('index.png',0)

ret,thresh_binary = cv2.threshold(gray_image,127,255,cv2.THRESH_BINARY)

saurabhpal97

#import the libraries
import numpy as np
import matplotlib.pyplot as plt
import cv2
%matplotlib inline

#ADAPTIVE THRESHOLDING
gray_image = cv2.imread('index.png',0)

ret,thresh_global = cv2.threshold(gray_image,127,255,cv2.THRESH_BINARY)

saurabhpal97

#importing required libraries
import numpy as np
import cv2
import matplotlib.pyplot as plt

#reading the image
image = cv2.imread('coins.jpg')
#converting image to grayscale format
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
#apply thresholding

saurabhpal97

#import required libraries
import numpy as np 
import matplotlib.pyplot as plt 
import cv2 
%matplotlib inline 
#read the image
image = cv2.imread('coins.jpg')
#apply thresholdin 
ret,mask = cv2.threshold(sure_fg,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU) 
#apply AND operation on image and mask generated by thrresholding