Principle:Openai Openai python Image Editing
| Knowledge Sources | |
|---|---|
| Domains | Computer_Vision, Image_Editing |
| Last Updated | 2026-02-15 00:00 GMT |
Overview
A text-guided image modification technique that edits existing images based on natural language descriptions, with optional mask-based region targeting.
Description
Image editing takes a source image and a text prompt to produce a modified version. DALL-E 2 uses explicit masks (transparent regions indicating where to edit), while newer models can understand edit intent from the prompt alone. Multiple source images can be provided for composite operations. Edit fidelity can be controlled to balance accuracy with creative freedom.
Usage
Use this principle when modifying existing images: adding elements, removing objects, changing styles, or compositing multiple images. Provide a mask for precise control with DALL-E 2, or rely on prompt-based editing with newer models.
Theoretical Basis
Image editing follows an Inpainting/Outpainting approach:
# Masked editing (DALL-E 2)
result = edit(
image=source_image,
mask=transparent_mask, # Regions to edit
prompt="Add a blue bird",
)
# Prompt-based editing (newer models)
result = edit(
image=source_image,
prompt="Make it a winter scene",
input_fidelity="high", # Preserve source details
)