COLOR_CONVERSIONS_OF-IMAGE

AIM

To write a python program using OpenCV to do the following image manipulations.

i) Read, display, and write an image.

ii) Access the rows and columns in an image.

iii) Cut and paste a small portion of the image.

iv)To perform the color conversion between RGB, BGR, HSV, and YCbCr color models.

Software Required:

Anaconda - Python 3.7

Algorithm:

Step1:

Choose an image and save it as a filename.jpg ,

Step2:

Use imread(filename, flags) to read the file.

Step3:

Use imshow(window_name, image) to display the image.

Step4:

Use imwrite(filename, image) to write the image.

Step5:

End the program and close the output image windows.

Step6:

Convert BGR and RGB to HSV and GRAY

Step7:

Convert HSV to RGB and BGR

Step8:

Convert RGB and BGR to YCrCb

Step9:

Split and Merge RGB Image

Step10:

Split and merge HSV Image

Program:

Developed By: GANESH R

Register Number: 212222240029

Output:

i) Read and display the image

import cv2
import matplotlib.pyplot as plt

img=cv2.imread("Cheetah.jpeg",1)
cv2.imshow("display window",img)
cv2.waitKey(0)
cv2.destroyAllWindows()
print(img.shape)

Output:

ii)Write the image

import cv2
img1=cv2.imread("cheetah.jpeg",1)
cv2.imwrite('greyscale.jpeg',img1)

Output:

iii)Shape of the Image

import cv2
img1=cv2.imread("cheetah.jpeg",0)
cv2.imshow("display window",img1)
cv2.waitKey(0)
cv2.destroyAllWindows()
cv2.imwrite('greyscale.jpeg',img1)
print(img1.shape)

Output:

iv)Access rows and columns

import random
import cv2
image=cv2.imread('cheetah.jpeg',1)
#image=cv2.resize(image,(400,400))
for i in range (150,200):
    for j in range(image.shape[1]):
        image[i][j]=[random.randint(0,255),
                    random.randint(0,255),
                    random.randint(0,255)] 
cv2.imshow('part image',image)
cv2.waitKey(0)
cv2.destroyAllWindows()

Output:

v)Cut and paste portion of image

import cv2

img2 = cv2.imread("cheetah.jpeg")

x = 0
y = 200
x1 = 160
y1 = 450
x2 = 0
y2 = 0

cropimg = img2[x:x1+x2, y:y1+y2]

cv2.imshow("Original Image", img2)
cv2.imshow("Cropped Image", cropimg)
cv2.waitKey(0)
cv2.destroyAllWindows()

Output:

vi) BGR and RGB to HSV and GRAY

import cv2
img = cv2.imread('cheetah.jpeg',1)
img = cv2.resize(img,(300,200))
cv2.imshow('Original Image',img)

hsv1 = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
cv2.imshow('BGR2HSV',hsv1)

hsv2 = cv2.cvtColor(img,cv2.COLOR_RGB2HSV)
cv2.imshow('RGB2HSV',hsv2)

gray1 = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
cv2.imshow('BGR2GRAY',gray1)

gray2 = cv2.cvtColor(img,cv2.COLOR_RGB2GRAY)
cv2.imshow('RGB2GRAY',gray2)

cv2.waitKey(0)
cv2.destroyAllWindows()

Output:

vii) HSV to RGB and BGR

import cv2
img = cv2.imread('cheetah.jpeg')
img = cv2.resize(img,(300,200))

img = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
cv2.imshow('Original HSV Image',img)

RGB = cv2.cvtColor(img,cv2.COLOR_HSV2RGB)
cv2.imshow('2HSV2BGR',RGB)

BGR = cv2.cvtColor(img,cv2.COLOR_HSV2BGR)
cv2.imshow('HSV2RGB',BGR)

cv2.waitKey(0)
cv2.destroyAllWindows()

Output:

viii) RGB and BGR to YCrCb

import cv2
img = cv2.imread('cheetah.jpeg')
img = cv2.resize(img,(300,200))
cv2.imshow('Original RGB Image',img)

YCrCb1 = cv2.cvtColor(img, cv2.COLOR_BGR2YCrCb)
cv2.imshow('RGB-2-YCrCb',YCrCb1)

YCrCb2 = cv2.cvtColor(img, cv2.COLOR_RGB2YCrCb)
cv2.imshow('BGR-2-YCrCb',YCrCb2)

cv2.waitKey(0)
cv2.destroyAllWindows()

Output:

ix) Split and merge RGB Image

import cv2
img = cv2.imread('cheetah.jpeg',1)
img = cv2.resize(img,(300,200))

R = img[:,:,2]
G = img[:,:,1]
B = img[:,:,0]

cv2.imshow('R-Channel',R)
cv2.imshow('G-Channel',G)
cv2.imshow('B-Channel',B)

merged = cv2.merge((B,G,R))
cv2.imshow('Merged RGB image',merged)

cv2.waitKey(0)
cv2.destroyAllWindows()

Output:

x) Split and merge HSV Image

import cv2
img = cv2.imread("cheetah.jpeg",1)
img = cv2.resize(img,(300,200))
img=cv2.cvtColor(img,cv2.COLOR_RGB2HSV)

H,S,V=cv2.split(img)

cv2.imshow('Hue',H)
cv2.imshow('Saturation',S)
cv2.imshow('Value',V)

merged = cv2.merge((H,S,V))
cv2.imshow('Merged',merged)

cv2.waitKey(0)
cv2.destroyAllWindows()

Output:

Result:

Thus the images are read, displayed, and written ,and color conversion was performed between RGB, HSV and YCbCr color models successfully using the python program.

ganesha360 / color_conversions_of-image Goto Github PK