Receber por email
← Voltar para o catálogo

image-utils

Classic image manipulation with Python Pillow - resize, crop, composite, format conversion, watermarks, brightness/contrast adjustments, and web optimization. Use this skill when post-processing AI-generated images, preparing images for web delivery, batch processing image directories, creating responsive image variants, or performing any deterministic pixel-level image operation. Works standalone

60estrelas
Atualizado há 4 meses

Ver no GitHub ↗

Como adicionar

/plugin marketplace add Bria-AI/bria-skill

O comando exato pode variar conforme o repositório. Confira o README no GitHub.

Para o autor da skill

Cole no README do seu repo

Mostra que sua skill está catalogada na Skillteca, gera backlink e tráfego rastreável.

[![Skillteca](https://www.skillteca.com.br/api/badge/image-utils/svg)](https://www.skillteca.com.br/skills/image-utils)

Skills relacionadas

Ver todas de Pesquisa e Web →

Alerta por categoria

Receba novas skills de Pesquisa e Web toda segunda

1 email curto, só com as skills novas de Pesquisa e Web. 4 minutos de leitura, sem spam, cancela com 1 clique.

Você confirma o email no primeiro envio. Sem spam. Cancela com 1 clique.

Ler descrição completa

Image Utilities

Pillow-based utilities for deterministic pixel-level image operations. Use for resize, crop, composite, format conversion, watermarks, and other standard image processing tasks.

When to Use This Skill

  • Post-processing AI-generated images: Resize, crop, optimize for web after generation
  • Format conversion: PNG ↔ JPEG ↔ WEBP with quality control
  • Compositing: Overlay images, paste subjects onto backgrounds
  • Batch processing: Resize to multiple sizes, add watermarks
  • Web optimization: Compress and resize for fast delivery
  • Social media preparation: Crop to platform-specific aspect ratios

When NOT to Use This Skill — Use bria-ai Instead

This skill handles deterministic pixel-level operations only. For any generative or AI-powered image work, use the bria-ai skill instead:

  • Generating images from text prompts → use bria-ai
  • AI background removal or replacement → use bria-ai
  • AI image editing (inpainting, object removal/addition) → use bria-ai
  • Style transfer or AI-driven visual effects → use bria-ai
  • Creating product lifestyle shots with AI → use bria-ai
  • Image upscaling with AI super-resolution → use bria-ai

Rule of thumb: If the task requires creating new visual content or understanding image semantics, use bria-ai. If the task requires transforming existing pixels (resize, crop, format convert, watermark), use this skill.

If bria-ai is not available, install it with:

npx skills add bria-ai/bria-skill

Quick Reference

| Operation | Method | Description | |-----------|--------|-------------| | Loading | load(source) | Load from URL, path, bytes, or base64 | | | load_from_url(url) | Download image from URL | | Saving | save(image, path) | Save with format auto-detection | | | to_bytes(image, format) | Convert to bytes | | | to_base64(image, format) | Convert to base64 string | | Resizing | resize(image, width, height) | Resize to exact dimensions | | | scale(image, factor) | Scale by factor (0.5 = half) | | | thumbnail(image, size) | Fit within size, maintain aspect | | Cropping | crop(image, left, top, right, bottom) | Crop to region | | | crop_center(image, width, height) | Crop from center | | | crop_to_aspect(image, ratio) | Crop to aspect ratio | | Compositing | paste(bg, fg, position) | Overlay at coordinates | | | composite(bg, fg, mask) | Alpha composite | | | fit_to_canvas(image, w, h) | Fit onto canvas size | | Borders | add_border(image, width, color) | Add solid border | | | add_padding(image, padding) | Add whitespace padding | | Transforms | rotate(image, angle) | Rotate by degrees | | | flip_horizontal(image) | Mirror horizontally | | | flip_vertical(image) | Flip vertically | | Watermarks | add_text_watermark(image, text) | Add text overlay | | | add_image_watermark(image, logo) | Add logo watermark | | Adjustments | adjust_brightness(image, factor) | Lighten/darken | | | adjust_contrast(image, factor) | Adjust contrast | | | adjust_saturation(image, factor) | Adjust color saturation | | | blur(image, radius) | Apply Gaussian blur | | Web | optimize_for_web(image, max_size) | Optimize for delivery | | Info | get_info(image) | Get dimensions, format, mode |

Requirements

pip install Pillow requests

Basic Usage

from image_utils import ImageUtils

# Load from URL
image = ImageUtils.load_from_url("https://example.com/image.jpg")

# Or load from various sources
image = ImageUtils.load("/path/to/image.png")         # File path
image = ImageUtils.load(image_bytes)                  # Bytes
image = ImageUtils.load("data:image/png;base64,...")  # Base64

# Resize and save
resized = ImageUtils.resize(image, width=800, height=600)
ImageUtils.save(resized, "output.webp", quality=90)

# Get image info
info = ImageUtils.get_info(image)
print(f"{info['width']}x{info['height']} {info['mode']}")

Resizing & Scaling

# Resize to exact dimensions
resized = ImageUtils.resize(image, width=800, height=600)

# Resize maintaining aspect ratio (fit within bounds)
fitted = ImageUtils.resize(image, width=800, height=600, maintain_aspect=True)

# Resize by width only (height auto-calculated)
resized = ImageUtils.resize(image, width=800)

# Scale by factor
half = ImageUtils.scale(image, 0.5)    # 50% size
double = ImageUtils.scale(image, 2.0)  # 200% size

# Create thumbnail
thumb = ImageUtils.thumbnail(image, (150, 150))

Cropping

# Crop to specific region
cropped = ImageUtils.crop(image, left=100, top=50, right=500, bottom=350)

# Crop from center
center = ImageUtils.crop_center(image, width=400, height=400)

# Crop to aspect ratio (for social media)
square = ImageUtils.crop_to_aspect(image, "1:1")      # Instagram
wide = ImageUtils.crop_to_aspect(image, "16:9")       # YouTube thumbnail
story = ImageUtils.crop_to_aspect(image, "9:16")      # Stories/Reels

# Control crop anchor
top_crop = ImageUtils.crop_to_aspect(image, "16:9", anchor="top")
bottom_crop = ImageUtils.crop_to_aspect(image, "16:9", anchor="bottom")

Compositing

# Paste foreground onto background
result = ImageUtils.paste(background, foreground, position=(100, 50))

# Alpha composite (foreground must have transparency)
result = ImageUtils.composite(background, foreground)

# Fit image onto canvas with letterboxing
canvas = ImageUtils.fit_to_canvas(
    image,
    width=1200,
    height=800,
    background_color=(255, 255, 255, 255),  # White
    position="center"  # or "top", "bottom"
)

Format Conversion

# Convert to different formats
png_bytes = ImageUtils.to_bytes(image, "PNG")
jpeg_bytes = ImageUtils.to_bytes(image, "JPEG", quality=85)
webp_bytes = ImageUtils.to_bytes(image, "WEBP", quality=90)

# Get base64 for data URLs
base64_str = ImageUtils.to_base64(image, "PNG")
data_url = ImageUtils.to_base64(image, "PNG", include_data_url=True)
# Returns: "data:image/png;base64,..."

# Save with format auto-detected from extension
ImageUtils.save(image, "output.png")
ImageUtils.save(image, "output.jpg", quality=85)
ImageUtils.save(image, "output.webp", quality=90)

Watermarks

# Text watermark
watermarked = ImageUtils.add_text_watermark(
    image,
    text="© 2024 My Company",
    position="bottom-right",  # bottom-left, top-right, top-left, center
    font_size=24,
    color=(255, 255, 255, 128),  # Semi-transparent white
    margin=20
)

# Logo/image watermark
logo = ImageUtils.load("logo.png")
watermarked = ImageUtils.add_image_watermark(
    image,
    watermark=logo,
    position="bottom-right",
    opacity=0.5,
    scale=0.15,  # 15% of image width
    margin=20
)

Adjustments

# Brightness (1.0 = original, <1 darker, >1 lighter)
bright = ImageUtils.adjust_brightness(image, 1.3)
dark = ImageUtils.adjust_brightness(image, 0.7)

# Contrast (1.0 = original)
high_contrast = ImageUtils.adjust_contrast(image, 1.5)

# Saturation (0 = grayscale, 1.0 = original, >1 more vivid)
vivid = ImageUtils.adjust_saturation(image, 1.3)
grayscale = ImageUtils.adjust_saturation(image, 0)

# Sharpness
sharp = ImageUtils.adjust_sharpness(image, 2.0)

# Blur
blurred = ImageUtils.blur(image, radius=5)

Transforms

# Rotate (counter-clockwise, degrees)
rotated = ImageUtils.rotate(image, 45)
rotated = ImageUtils.rotate(image, 90, expand=False)  # Don't expand canvas

# Flip
mirrored = ImageUtils.flip_horizontal(image)
flipped = ImageUtils.flip_vertical(image)

Borders & Padding

# Add solid border
bordered = ImageUtils.add_border(image, width=5, color=(0, 0, 0))

# Add padding (whitespace)
padded = ImageUtils.add_padding(image, padding=20)  # Uniform
padded = ImageUtils.add_padding(image, padding=(10, 20, 10, 20))  # left, top, right, bottom

Web Optimization

# Optimize for web delivery
optimized_byte
Compartilhar X LinkedIn