Image Processing in Python using Pillow

Image Processing in Python
#original Image

from PIL import Image

Image.open('clcodingmr.jpg')

1. Image Resizing:

from PIL import Image

def resize_image(image_path, output_path, width, height):

    image = Image.open(image_path)

    resized_image = image.resize((width, height))

    resized_image.save(output_path)

# Example usage:

resize_image('clcodingmr.jpg', 'resized_output.jpg', 300, 200)

# Now, open and show the resized image

Image.open('clcodingmr.jpg')

Image.open('resized_output.jpg')

​

2. Image Rotation with Pillow:

from PIL import Image

​

def rotate_image(image_path, output_path, angle):

    image = Image.open(image_path)

    rotated_image = image.rotate(angle)

    rotated_image.save(output_path)

​

# Example usage:

rotate_image('clcodingmr.jpg', 'rotated_output.jpg', 45)

Image.open('rotated_output.jpg')

3. Image Translation (using crop) with Pillow:

from PIL import Image

​

def translate_image(image_path, output_path, tx, ty):

    image = Image.open(image_path)

    translated_image = image.crop((tx, ty, image.width, image.height))

    translated_image.save(output_path)

​

# Example usage:

translate_image('clcodingmr.jpg', 'translated_output.jpg', 50, 30)

Image.open('translated_output.jpg')

4. Image Shearing (using affine transform) with Pillow:

Image.open('sheared_output.jpg')

from PIL import Image, ImageOps

​

def shear_image(image_path, output_path, shear_factor):

    image = Image.open(image_path)

    shear_matrix = [1, shear_factor, 0, 0, 1, 0]

    sheared_image = image.transform(image.size, Image.AFFINE, shear_matrix)

    sheared_image.save(output_path)

​

# Example usage:

shear_image('clcodingmr.jpg', 'sheared_output.jpg', 0.2)

Image.open('sheared_output.jpg')

5. Image Normalization (simple contrast adjustment) with Pillow:

from PIL import Image

​

def normalize_image(image_path, output_path):

    image = Image.open(image_path)

    normalized_image = ImageOps.autocontrast(image)

    normalized_image.save(output_path)

​

# Example usage:

normalize_image('clcodingmr.jpg', 'normalized_output.jpg')

Image.open('normalized_output.jpg')

​

6. Image Blurring (using a filter) with Pillow:

from PIL import Image, ImageFilter

​

def blur_image(image_path, output_path, radius):

    image = Image.open(image_path)

    blurred_image = image.filter(ImageFilter.GaussianBlur(radius))

    blurred_image.save(output_path)

​

# Example usage:

blur_image('clcodingmr.jpg', 'blurred_output.jpg', 5)

Image.open('blurred_output.jpg')