---name: image-processingdescription: Process images for web development — resize, crop, trim whitespace, convert formats (PNG/WebP/JPG), optimise file size, generate thumbnails, create OG card images. Uses Pillow (Python) — no ImageMagick needed. Trigger with 'resize image', 'convert to webp', 'trim logo', 'optimise images', 'make thumbnail', 'create OG image', 'crop whitespace', 'process image', or 'image too large'.compatibility: claude-code-only---

Image Processing

Use img-process (shipped in bin/) for common operations. For complex or custom workflows, generate a Pillow script adapted to the user's environment.

Quick Reference — img-process CLI

img-process resize hero.png --width 1920
img-process convert logo.png --format webp
img-process trim logo-raw.jpg -o logo-clean.png --padding 10
img-process thumbnail photo.jpg --size 200
img-process optimise hero.jpg --quality 85 --max-width 1920
img-process og-card -o og.png --title "My App" --subtitle "Built for speed"
img-process batch ./images --action convert --format webp -o ./optimised

Use img-process when: the operation is standard (resize, convert, trim, thumbnail, optimise, OG card, batch). This is faster and avoids generating a script each time.

Generate a custom script when: the operation needs logic img-process doesn't cover (compositing multiple images, watermarks, complex text layouts, conditional processing).

Prerequisites

Pillow is required for both img-process and custom scripts:

pip install Pillow

If Pillow is unavailable, use alternatives:

Alternative	Platform	Install	Best for
sips	macOS (built-in)	None	Resize, convert (no trim/OG)
sharp	Node.js	npm install sharp	Full feature set, high performance
ffmpeg	Cross-platform	brew install ffmpeg	Resize, convert

Output Format Guide

Use case	Format	Why
Photos, hero images	WebP	Best compression, wide browser support
Logos, icons (need transparency)	PNG	Lossless, supports alpha
Fallback for older browsers	JPG	Universal support
Thumbnails	WebP or JPG	Small file size priority
OG cards	PNG	Social platforms handle PNG best

Core Patterns

Save with Format-Specific Quality

Different formats need different save parameters. Always handle RGBA-to-JPG compositing — JPG does not support transparency, so composite onto a white background first.

from PIL import Image
import os

def save_image(img, output_path, quality=None):
    os.makedirs(os.path.dirname(output_path) or ".", exist_ok=True)
    kwargs = {}
    ext = output_path.lower().rsplit(".", 1)[-1]

    if ext == "webp":
        kwargs = {"quality": quality or 85, "method": 6}
    elif ext in ("jpg", "jpeg"):
        kwargs = {"quality": quality or 90, "optimize": True}
        # RGBA → RGB: composite onto white background
        if img.mode == "RGBA":
            bg = Image.new("RGB", img.size, (255, 255, 255))
            bg.paste(img, mask=img.split()[3])
            img = bg
    elif ext == "png":
        kwargs = {"optimize": True}

    img.save(output_path, **kwargs)

Resize with Aspect Ratio

When only width or height is given, calculate the other from aspect ratio. Use Image.LANCZOS for high-quality downscaling.

def resize_image(img, width=None, height=None):
    if width and height:
        return img.resize((width, height), Image.LANCZOS)
    elif width:
        ratio = width / img.width
        return img.resize((width, int(img.height * ratio)), Image.LANCZOS)
    elif height:
        ratio = height / img.height
        return img.resize((int(img.width * ratio), height), Image.LANCZOS)
    return img

Trim Whitespace (Auto-Crop)

Remove surrounding whitespace from logos and icons. Convert to RGBA first, then use getbbox() to find content bounds.

img = Image.open(input_path)
if img.mode != "RGBA":
    img = img.convert("RGBA")
bbox = img.getbbox()  # Bounding box of non-zero pixels
if bbox:
    img = img.crop(bbox)

Thumbnail

Fit within max dimensions while maintaining aspect ratio:

img.thumbnail((size, size), Image.LANCZOS)

Optimise for Web

Resize + compress in one step. Convert to WebP for best compression. Typical settings: width 1920, quality 85.

Cross-Platform Font Discovery

System font paths differ by OS. Try multiple paths, fall back to Pillow's default. On Linux, fc-list can discover fonts dynamically.

from PIL import ImageFont

def get_font(size):
    font_paths = [
        # macOS
        "/System/Library/Fonts/Helvetica.ttc",
        "/System/Library/Fonts/SFNSText.ttf",
        # Linux
        "/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",
        "/usr/share/fonts/truetype/liberation/LiberationSans-Regular.ttf",
        # Windows
        "C:/Windows/Fonts/arial.ttf",
    ]
    for path in font_paths:
        if os.path.exists(path):
            try:
                return ImageFont.truetype(path, size)
            except Exception:
                continue
    return ImageFont.load_default()

OG Card Generation (1200x630)

Composite text on a background image or solid colour. Apply semi-transparent overlay for text readability. Centre text horizontally.

from PIL import Image, ImageDraw, ImageFont

width, height = 1200, 630

# Background: image or solid colour
if background_path:
    img = Image.open(background_path).resize((width, height), Image.LANCZOS)
else:
    img = Image.new("RGB", (width, height), bg_color or "#1a1a2e")

# Semi-transparent overlay for text readability
overlay = Image.new("RGBA", (width, height), (0, 0, 0, 128))
img = img.convert("RGBA")
img = Image.alpha_composite(img, overlay)

draw = ImageDraw.Draw(img)
font_title = get_font(48)
font_sub = get_font(24)

# Centre title
if title:
    bbox = draw.textbbox((0, 0), title, font=font_title)
    tw = bbox[2] - bbox[0]
    draw.text(((width - tw) // 2, height // 2 - 60), title, fill="white", font=font_title)

img = img.convert("RGB")

Common Workflows

Logo Cleanup (client-supplied JPG with white background)

img-process trim logo-raw.jpg -o logo-trimmed.png --padding 10
img-process thumbnail logo-trimmed.png --size 512 -o favicon-512.png

Prepare Hero Image for Production

img-process optimise hero.jpg --max-width 1920 --quality 85
# Outputs hero.webp — resized and compressed

Batch Process

img-process batch ./raw-images --action convert --format webp --quality 85 -o ./optimised
img-process batch ./photos --action resize --width 800 -o ./thumbnails

Pipeline with Gemini Image Gen

Generate images with the gemini-image-gen skill, then process them:

# After generating with Gemini (raw PNG output):
img-process optimise generated-image.png --max-width 1920 --quality 85
# Or batch process all generated images:
img-process batch ./generated --action optimise -o ./production