Image Manipulation for Machine Learning

Last modified: 2023-08-20

Computer Vision Machine Learning

We can update each pixel value to change an image.

Swapping Pixels


This example updates pixel values at specified positions.

import numpy as np
from PIL import Image

img ="example.png")

# Reshape image data to desired size for easy processing
pixels = np.array(img.getdata())
pixels = np.reshape(pixels, (28, 28))

# Update each pixel with desired value for changing image
for i in range(img.size[0]):
	for j in range(img.size[1]):
		# change pixel value at position (8, 19)
		if i == 8 and j == 19:
			pixels[i, j] = 255
		# change pixel value at position 25th row, 20th column onwards
		if i > 25 and j > 20:
			pixels[i, j] = np.random.randint(0, 50)

# Convert numpy array to image
img_updated = Image.fromarray(pixels.astype(np.uint8))