# Image Manipulation for Machine Learning

We can update each pixel value to change an image.

### Swapping Pixels <a href="#swapping-pixels" id="swapping-pixels"></a>

This example updates pixel values at specified positions.

```shellscript
import numpy as np
from PIL import Image

img = Image.open("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))
```

### References <a href="#references" id="references"></a>

* [Kaggle](https://www.kaggle.com/code/jonbown/ai-ctf-submissions?scriptVersionId=105606691\&cellId=102)