→AI Text-to-Colour

Introduction

I set out with a simple goal, to programatically generate colour palettes from text in a way that’s explainable. I’m determined that the colour palette should be unconstrained across the full colour space.

Create a Clean Text Dataset

I start in Collab to create a text dataset for development and testing purposes. I come across a government website containing 146 of Aesop’s fables. They each have their own page, with incremental URL numbers, making them easy to scrape into markdown files.

Deciding on Approach

I collaborate with ChatGPT to explore several methods for converting text into colour...

• Use high-dimensional text embeddings, reduce to three dimensions for RGB values, normalise to 0-255 range, and create additional colours through strategic offsets in colour space.
• Develop a semantic colour wheel with custom embeddings → generate text embeddings → measure cosine similarity.
• Deploy a compact neural network trained to map text embeddings directly to RGB or HSL colour-space coordinates.
• Transform text embedding into a prompt → generate an image with that prompt → extract dominant colours from the resulting image.

However, these approaches seem unnecessarily complex, so I decide to start with something simpler and test its effectiveness. Here's my refined approach:

• Conduct a thematic analysis on the text to understand its style and content.
• Leverage this style and content analysis to generate an appropriate colour palette.

This streamlined approach feels possible with just a couple of ChatGPT API requests. The methodology also gives us the additional benefit of explainability, as I can provide the thematic analysis output to end users, helping them understand the rationale behind the colour selection.

Step 1: Thematic Analysis to Structured JSON

The prompt I settled on for thematic analysis:

You can see how this approach could aid explainability. For example you can see what influenced colour selection for ‘A Raven & A Swan’:

Step 2: Generate Colour Palette From Structured JSON

Now we take that thematic analysis, and get OpenAI to respond with a colour palette.

Processing Confirmation / Output

Processing file: The_Hare__the_Tortoise.md
Markdown file content read successfully.
OpenAI API call for theme analysis successful.
Theme analysis JSON parsed successfully.
OpenAI API call for color palette successful.
Color palette JSON parsed successfully.
Results for The_Hare__the_Tortoise.md stored.

Generated color palette:
{'color_palette': ['#4CAF50', '#FF5722', '#8BC34A', '#FFC107', '#FFEB3B', '#9E9E9E', '#795548', '#607D8B']}

A BBC news article about escalating tensions between the US and Russia and the deployment of nuclear submarines… and I’m pleasantly surprised. The results pass the gut check.

Generated color palette:
{'color_palette': ['#00274D', '#D9534F', '#AAB7B8', '#5D6D7E', '#F7F9F9','#A93226','#2874A6','#1C2833']}

Step 3: Computation at Scale

To check this approach scales and doesn’t take too long, I use my dataset to generate 100+ palettes in short order. Success.

I initially considered creating a static webpage for each fable with its corresponding palette. However, I decided to be more ambitious and transform this concept into a simple web product.

Step 4: To Production

The vision is simple. A text box where you can paste any text, and generate a sympathetic colour palette based on the nature of that text.

Given I’ve already got some prompts working with the OpenAI API this is largely a UI/UX challenge from here on in. It took a couple of hours to get things to an acceptable standard, most of that time is the Replit agent crunching through my requests. Here’s a concise summary of that back and forth…

And just like that, we’re up and running. Why not try HEXpert? Or watch the demo if it’s not running today.

ToDo

If you share some of my personality traits, you won't feel a sense of closure once you reach this point but instead a sense of dread about the number of loose ends you've created. I'll leave this to-do list here for my sanity:

• Iterate on the thematic analysis prompt.
• Iterate on the palette generation prompt.
• Explore training a neural net instead.