Jump to content

Connect SuperML | Leeroopedia MCP: Equip your AI agents with best practices, code verification, and debugging knowledge. Powered by Leeroo — building Organizational Superintelligence. Contact us at founders@leeroo.com.

Principle:Googleapis Python genai Image Editing

From Leeroopedia
Knowledge Sources
Domains Computer_Vision, Image_Processing
Last Updated 2026-02-15 00:00 GMT

Overview

A technique for modifying existing images based on text instructions, optionally guided by reference images and masks.

Description

Image Editing applies text-guided modifications to existing images. Unlike image generation (which creates from scratch), editing preserves the original image structure while applying targeted changes. Edits can be guided by: a raw reference image (the source image to modify), a mask reference image (specifying which regions to edit), and a text prompt (describing the desired modification). Supported edit modes include inpainting (filling masked regions), outpainting (extending image boundaries), and style transfer. This enables precise image manipulation without manual pixel editing.

Usage

Use image editing when you need to modify specific aspects of an existing image: changing backgrounds, adding/removing objects, changing styles, or filling in masked regions. Provide a clear edit instruction as the prompt, the source image as a RawReferenceImage, and optionally a mask as a MaskReferenceImage to target specific regions.

Theoretical Basis

Text-guided image editing conditions the diffusion process on both the source image and the text instruction:

xt1=fθ(xt,Isrc,M,c)

Where:

  • I_src is the source image
  • M is the optional edit mask
  • c is the text instruction encoding
  • The denoising process preserves unmasked regions while generating new content in masked areas

Related Pages

Implemented By

Page Connections

Double-click a node to navigate. Hold to expand connections.
Principle
Implementation
Heuristic
Environment