# Real-World Case Study: E-commerce Product Pipeline
import boto3
from PIL import Image
import io

def process_product_image(s3_bucket, s3_key):
    # 1. Download from S3
    s3 = boto3.client('s3')
    response = s3.get_object(Bucket=s3_bucket, Key=s3_key)
    img = Image.open(io.BytesIO(response['Body'].read()))
    
    # 2. Standardize dimensions
    img = img.convert("RGB")
    img = img.resize((1200, 1200), Image.LANCZOS)
    
    # 3. Remove background (simplified)
    # In practice: use rembg or AWS Rekognition
    img = remove_background(img)
    
    # 4. Generate variants
    variants = {
        "web": img.resize((800, 800)),
        "mobile": img.resize((400, 400)),
        "thumbnail": img.resize((100, 100))
    }
    
    # 5. Upload to CDN
    for name, variant in variants.items():
        buffer = io.BytesIO()
        variant.save(buffer, "JPEG", quality=95)
        s3.upload_fileobj(
            buffer, 
            "cdn-bucket", 
            f"products/{s3_key.split('/')[-1].split('.')[0]}_{name}.jpg",
            ExtraArgs={'ContentType': 'image/jpeg', 'CacheControl': 'max-age=31536000'}
        )
    
    # 6. Generate WebP version
    webp_buffer = io.BytesIO()
    img.save(webp_buffer, "WEBP", quality=85)
    s3.upload_fileobj(webp_buffer, "cdn-bucket", f"products/{s3_key.split('/')[-1].split('.')[0]}.webp")

process_product_image("user-uploads", "products/summer_dress.jpg")

By: @DataScienceM 👁

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💡 Applying Image Filters with Pillow

Pillow's ImageFilter module provides a set of pre-defined filters you can apply to your images with a single line of code. This example demonstrates how to apply a Gaussian blur effect, which is useful for softening images or creating depth-of-field effects.

from PIL import Image, ImageFilter

try:
    # Open an existing image
    with Image.open("your_image.jpg") as img:
        # Apply the Gaussian Blur filter
        # The radius parameter controls the blur intensity
        blurred_img = img.filter(ImageFilter.GaussianBlur(radius=5))

        # Display the blurred image
        blurred_img.show()

        # Save the new image
        blurred_img.save("blurred_image.png")

except FileNotFoundError:
    print("Error: 'your_image.jpg' not found. Please provide an image.")

Code explanation: The script opens an image file, applies a GaussianBlur filter from the ImageFilter module using the .filter() method, and then displays and saves the resulting blurred image. The blur intensity is controlled by the radius argument.

#Python #Pillow #ImageProcessing #ImageFilter #PIL

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By: @DataScienceM ✨