Python OpenCV - Getting and Setting Pixels

In this article, we will discuss Getting and Setting Pixels through OpenCV in Python. 

Image is made up of pixels. A pixel will be denoted as an array. The 3 integers represent the intensity of red, green, blue in the same order. Eg. [0,0,0] in RGB mode represent black color. There are other modes as well-

• HSV
• Grayscale
• CMY

Image can be read using imread() function which returns the matrix of pixels (default is RGB mode).

Image Used:

Syntax:

For Image shape: image.shape For getting a pixel: image[row][col] For setting a pixel: image[row][col] = [r,g,b]

Example 1: Python code to display image details

# import cv2 module import cv2 # resd the image img = cv2.imread('image.png') # shape prints the tuple (height,weight,channels) print(img.shape) # img will be a numpy array of the above shape print(img) 

Output:

(225, 225, 3) [[[ 87 157 14] [ 87 157 14] [ 87 157 14] ... [ 87 157 14] [ 87 157 14] [ 87 157 14]] [[ 87 157 14] [ 87 157 14] [ 87 157 14] ... [ 87 157 14] [ 87 157 14] [ 87 157 14]] ... [[ 72 133 9] [ 72 133 9] [ 72 133 9] ... [ 87 157 14] [ 87 157 14] [ 87 157 14]] [[ 72 133 9] [ 72 133 9] [ 72 133 9] ... [ 87 157 14] [ 87 157 14] [ 87 157 14]]]

Here 225*225 pixels are there and every pixel is an array of 3 integers (Red, Green, Blue). 

Example 2: In this example, The single pixel can be extracted using indexing.

import cv2 # read the image img = cv2.imread('image.png') # this is pixel of 0th row and 0th column print(img[0][0]) 

Output:

[ 87 157 14]

Example 3: Python code to make the black cross on the image.

For that we will extract all (i,j) such that i==j or i+j == image width and for all pixels with index (i,j), the value of the pixel will set to [0,0,0].

# import the cv2 package import cv2 # read the image img = cv2.imread('image.png') for i, row in enumerate(img): # get the pixel values by iterating for j, pixel in enumerate(img): if(i == j or i+j == img.shape[0]): # update the pixel value to black img[i][j] = [0, 0, 0] # display image cv2.imshow("output", img) cv2.imwrite("output.png", img) 

Output:

Example 4: Get grayscale then the pixel will just be a number representing the intensity of white.

import cv2 img = cv2.imread('image.png', 0) # shape prints the tuple (height,weight,channels) print("image shape = ", img.shape) # img will be a numpy array of the above shape print("image array = ", img) print("pixel at index (5,5): ", img[5][5]) 

Grayscale Image:

Output:

image shape = (225, 225) image array = [[106 106 106 ... 106 106 106] [106 106 106 ... 106 106 106] [106 106 106 ... 106 106 106] ... [ 88 88 88 ... 106 106 106] [ 88 88 88 ... 106 106 106] [ 88 88 88 ... 106 106 106]] pixel at index (5,5): 106