photo-editor

Resize, crop, filter, and convert images using Pillow, OpenCV, and sharp.

18|4|Updated Apr 3, 2026
One-click install
npx skills add https://github.com/DevHive1/DevHive-Cli --skill photo-editor-devhive1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: photo-editor
Source: https://github.com/DevHive1/DevHive-Cli/tree/main/agents/photo-editor
Command: npx skills add https://github.com/DevHive1/DevHive-Cli --skill photo-editor-devhive1

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Pillow, opencv-python, sharp, rembg, and includes assets (resource) components.

What problem does it solve?

This Skill solves the friction of performing repetitive or precise image manipulations by providing a programmatic interface to professional-grade image processing libraries.

Core Features & Use Cases

  • Image Transformation: Perform precise resizing, cropping, rotation, and orientation correction.
  • Visual Enhancement: Apply filters, adjust brightness, contrast, saturation, and sharpness.
  • Use Case: Quickly batch-process a folder of high-resolution photos into optimized WebP thumbnails for a website while automatically stripping metadata for privacy.

Quick Start

Use the photo-editor skill to resize all images in the current directory to 1080 pixels wide and convert them to optimized WebP format.

Frequently Asked Questions about photo-editor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I batch resize images and convert them to WebP for web optimization?▼

Batch resize images and convert them to WebP by running a programmatic pipeline that processes an entire directory, utilizing Pillow and sharp to optimize output while efficiently managing memory for high-throughput web optimization.

Can I use OpenCV for computer vision-based detection in an image processing pipeline?▼

Yes, you can use OpenCV for computer vision-based detection within an automated image processing pipeline, performing precise visual enhancement, filtering, and cropping tasks alongside other libraries to ensure high-quality output.

Does this image editing approach support stripping metadata for privacy during format conversion?▼

Yes, performing automated format conversion and resizing supports stripping metadata for privacy, allowing you to batch-process high-resolution photos into optimized thumbnails while automatically removing sensitive EXIF data.

What is the best way to programmatically adjust brightness, contrast, and saturation for visual enhancement?▼

The best way to adjust brightness, contrast, and saturation for visual enhancement is using a programmatic interface to professional-grade libraries like Pillow, applying precise filters and corrections across single or batch-processed images.

Can I perform background removal using rembg alongside Pillow and opencv-python?▼

Yes, background removal using rembg is supported alongside Pillow and opencv-python, enabling you to combine automated transformations, filtering, and computer vision-based detection within a single high-throughput image editing workflow.