* This blog post is a summary of this video.

Generating AI Image Variations from a Single Image for Marketing

Author: Business Automated!Time: 2024-02-01 23:45:00

Table of Contents

Introduction to AI Image Variation Generation Including Core SEO Keywords

In the previous video, I showed how to create AI-generated images from prompts directly inside Airtable using OpenAI's DALL-E image generation model and Make.com. In this video, I will demonstrate how to leverage OpenAI DALL-E and Make.com to create variations of any existing image. Let's get started!

This video builds on the previous one where I showed how to generate images from text prompts. In this video, I'll expand on that and show how to create multiple variations of a single seed image using OpenAI DALL-E.

Overview of the Video Content

The video provides a step-by-step tutorial on using OpenAI DALL-E and Make.com to generate variations of an existing image. It covers setting up the workflow in Make.com, connecting to OpenAI API, configuring Airtable, and reviewing the generated outputs.

Benefits of Using AI to Create Image Variations

Generating variations of existing images with AI has many advantages. It allows for rapidly iterating on visual concepts without intensive manual work. The variations can be used to enhance marketing content and create diverse social media assets.

Step-by-Step Process to Generate Variations Including Core SEO Keywords

Preparing the Airtable Base

The first step is setting up an Airtable base with fields for the original input image, generated variation images, and number of variations to create. A view filters for records ready for image generation.

Configuring the Make.com Workflow

Next, a workflow is created in Make.com. It searches the Airtable records, downloads the input image, calls the OpenAI API to generate variations, and saves the outputs back to Airtable.

Connecting Airtable and OpenAI via API

The key step is connecting the Make.com workflow to the OpenAI API endpoint for image generation. The proper headers, request body, and Airtable record data is configured.

Reviewing the Generated Image Variations Including Core SEO Keywords

Assessing Variation Quality and Relevance

Once image variations are generated, it's important to review them. Factors like relevance, quality, and diversity should be evaluated.

Iterating to Improve Outputs

The prompts and parameters can be refined to iteratively improve the variation results. Additional generations may be needed to achieve the desired set.

Applications for AI-Generated Image Variations Including Core SEO Keywords

Enhancing Marketing Content

Generating a set of image variations allows for more diverse and engaging content. The images can be used across platforms like social media, websites, and ads.

Creating Social Media Assets

Unique but related images are highly valuable for social media marketing. Image variations can ensure a consistent look while providing fresh visuals.

Conclusion and Next Steps Including Core SEO Keywords

Key Takeaways

The video demonstrates how OpenAI and Make.com can be leveraged to efficiently generate image variations from a single input. This provides creative flexibility and content diversity.

Considerations for Implementation

To successfully implement this in a real business scenario, factors like image relevance, quality control, iteration, and application need to be considered.


Q: How many variations can be generated from one image?
A: OpenAI's DALL-E model can currently generate up to 10 variations of a single input image.

Q: What file formats work best for input images?
A: JPG, PNG and other standard image formats work well. Very small or low resolutions images may yield lower quality outputs.

Q: Can the variations be generated for free?
A: OpenAI offers some free credits but charges per image after a certain usage threshold. Make.com currently provides a free tier.