image-utils✓ Pass
Use when performing classic image manipulation - resize, crop, composite, format conversion, watermarks, adjustments. Pillow-based utilities for deterministic pixel-level operations. Use alongside AI image generation (like Bria) for post-processing, or standalone for any image processing task.
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references/code-examples
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SKILL.md Content
---
name: image-utils
description: Use when performing classic image manipulation - resize, crop, composite, format conversion, watermarks, adjustments. Pillow-based utilities for deterministic pixel-level operations. Use alongside AI image generation (like Bria) for post-processing, or standalone for any image processing task.
---
# 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
## 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
```bash
pip install Pillow requests
```
## Basic Usage
```python
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
```python
# 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
```python
# 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
```python
# 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
```python
# 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
```python
# 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
```python
# 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
```python
# 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
```python
# 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
```python
# Optimize for web delivery
optimized_bytes = ImageUtils.optimize_for_web(
image,
max_dimension=1920, # Resize if larger
format="WEBP", # Best compression
quality=85
)
# Save optimized
with open("optimized.webp", "wb") as f:
f.write(optimized_bytes)
```
## Integration with AI Image Generation
Use with Bria AI or other image generation APIs:
```python
from bria_client import BriaClient
from image_utils import ImageUtils
client = BriaClient()
# Generate with AI
result = client.generate("product photo of headphones", aspect_ratio="1:1")
image_url = result['result']['image_url']
# Download and post-process
image = ImageUtils.load_from_url(image_url)
# Create multiple sizes for responsive images
sizes = {
"large": ImageUtils.resize(image, width=1200),
"medium": ImageUtils.resize(image, width=600),
"thumb": ImageUtils.thumbnail(image, (150, 150))
}
# Save all as optimized WebP
for name, img in sizes.items():
ImageUtils.save(img, f"product_{name}.webp", quality=85)
```
## Batch Processing Example
```python
from pathlib import Path
from image_utils import ImageUtils
def process_catalog(input_dir, output_dir):
"""Process all images in a directory."""
output_path = Path(output_dir)
output_path.mkdir(exist_ok=True)
for image_file in Path(input_dir).glob("*.{jpg,png,webp}"):
image = ImageUtils.load(image_file)
# Crop to square
square = ImageUtils.crop_to_aspect(image, "1:1")
# Resize to standard size
resized = ImageUtils.resize(square, width=800, height=800)
# Add watermark
final = ImageUtils.add_text_watermark(resized, "© My Brand")
# Save optimized
output_file = output_path / f"{image_file.stem}.webp"
ImageUtils.save(final, output_file, quality=85)
process_catalog("./raw_images", "./processed")
```
## API Reference
See [image_utils.py](./references/code-examples/image_utils.py) for complete implementation with docstrings.
License
Declared license: MIT
MIT License
Copyright (c) 2026 openclaw
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.View the license in the source repository — the version published there is authoritative.
// Install Skill
Install Skill
Skills are third-party code from public GitHub repositories. SkillHub scans for known malicious patterns but cannot guarantee safety. Review the source code before installing.
Install globally (user-level):
npx skillhub install openclaw/skills/image-utilsInstall in current project:
npx skillhub install openclaw/skills/image-utils --projectskill.install.customTargetHelp
npx skillhub install openclaw/skills/image-utils --target-dir /path/to/skillsSuggested path: ~/.claude/skills/image-utils/