Demo Image Masking

In this tutorial, you’ll learn how to use DALL·E 2’s image masking feature to edit an existing picture by defining a masked region and supplying a text prompt. This approach is perfect for seamlessly replacing objects, changing backgrounds, or adding new elements to your images.

Prerequisites

Python 3.7+
The openai Python package (pip install openai)
An OpenAI API key

Make sure you’ve exported your API key as an environment variable:

export OPENAI_API_KEY="your_api_key_here"

1. Install and Authenticate

Begin by installing the client library and initializing your API key in Python:

import openai
import os
from IPython.display import Image

# Load API key from environment
openai.api_key = os.getenv("OPENAI_API_KEY")

2. Prepare Your Images

You need three files:

Original image (with the object you want to replace)
Base image (same image after removing the object)
Mask image (a transparent PNG that marks the area to edit)

display(Image(filename='images/dog_table.png'))        # Original image with dog
display(Image(filename='images/table.png'))            # Image with dog removed
display(Image(filename='images/table-masked.png'))     # Transparent mask placeholder

3. Perform the Edit

Use the create_edit endpoint to fill the masked area based on your prompt:

response = openai.Image.create_edit(
    image=open('images/table.png', 'rb'),
    mask=open('images/table-masked.png', 'rb'),
    prompt='A cat sitting on a dining table chair waiting for food',
    n=1,
    size='512x512'
)
edited_url = response['data'][0]['url']
display(Image(url=edited_url))

4. Generate Multiple Variations

If you’d like several options, increase n and iterate through the results:

response = openai.Image.create_edit(
    image=open('images/table.png', 'rb'),
    mask=open('images/table-masked.png', 'rb'),
    prompt='A cat sitting on a dining table chair waiting for food',
    n=3,
    size='512x512'
)
for result in response['data']:
    display(Image(url=result['url']))

Requesting a large number of edits or very high resolutions may incur higher usage costs. Monitor your API usage dashboard.

5. Parameter Reference

Parameter	Type	Description
`image`	File	The base image without the masked object (PNG or JPEG).
`mask`	File	A transparent PNG marking the area to edit (white = mask).
`prompt`	String	Textual description of what should appear in the masked area.
`n`	Integer	Number of edits to generate (1–10).
`size`	String	Output resolution: `256x256`, `512x512`, or `1024x1024`.

6. Generate Image Variations

Beyond masking, DALL·E 2 can also create variations of a single image without any prompt:

response = openai.Image.create_variation(
    image=open('images/table.png', 'rb'),
    n=4,
    size='512x512'
)
for img in response['data']:
    display(Image(url=img['url']))

For full details on both endpoints, see the OpenAI Image API Reference.

Introduction

What is Generative AI

Getting Started with OpenAI

Exploring ChatGPT

Understanding Prompt Engineering

Understanding Tokens and API Parameters

Implementing Word Completion

Implementing Code Completion

Building an Interactive Chatbot

Performing Text Processing and Analysis

Using Word Embeddings For Dynamic Context

Fine-tuning GPT-3 with a Custom Dataset

Generating Images

Audio Transcription & Translation

Moderating Prompts with Moderating API

Summary and Next Steps

Demo Image Masking

Prerequisites

1. Install and Authenticate

2. Prepare Your Images

3. Perform the Edit

4. Generate Multiple Variations

5. Parameter Reference

6. Generate Image Variations

Watch Video

Practice Lab

​Prerequisites

​1. Install and Authenticate

​2. Prepare Your Images

​3. Perform the Edit

​4. Generate Multiple Variations

​5. Parameter Reference

​6. Generate Image Variations

Watch Video

Practice Lab

Prerequisites

1. Install and Authenticate

2. Prepare Your Images

3. Perform the Edit

4. Generate Multiple Variations

5. Parameter Reference

6. Generate Image Variations