IMAGE GENERATION , MIDJOURNEY

An advanced guide to writing prompts for Midjourney ( text-to-image)

A detailed ‘cheat sheet’ and some keywords for improving image output by using better prompts

Lars Nielsen
MLearning.ai
Published in
7 min readSep 3, 2022
How to write prompts for Text to Image generation by Midjourney , text prompt , #midjourney prompt engineering
Image generated by Midjourney , text prompt : beautiful, fantasy city unreal engine

One liner on midjourney ?

For those of you who haven’t heard about midjourney yet, here is a one line introduction : Midjourney is a text-to-image generation app similar to OpenAI’s DALLE-2 and Stable Diffusion’s DreamStudio , which uses tons of images (around 650+ million) found on the internet — to generate stunning images based on the text prompt provided. It is now in the beta phase — but is adding more features every week .. and the future is yet to be imagined ! ( Currently their AI engine is on v3 )

Raw prompt text

Anyone who has used the midjourney app knows that the more descriptive you are in your text, the more vibrant and unique the output will be. Users generally use raw and direct prompts like : a cowboy wearing a tuxedo on the moon’ , would generate something like this :

A guide to writing text prompts for Midjourney , prompt engineering
Image created on midjourney — prompt: a cowboy wearing a tuxedo on the moon

But there are more options than just the plain raw prompt text to create predictable and consistent image outputs !

Now getting directly on to advanced options list for text-prompts !

Here are some of the ways you can generate variations in images and some of the advanced settings for the same : (details on each of these settings follows the list)

  1. Providing keywords — ‘style’
  2. stylize
  3. chaos
  4. Resolution
  5. Aspect ratio
  6. passing an image as a prompt as URL
  7. applying weights to the image prompts
  8. weights to the word prompts
  9. filtering out words

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Lars Nielsen
MLearning.ai

Making ML and AI available to everyone. One commit at a time. | Quantitative programming | Python | Arduino | Comp Vision | pythoslabs@gmail.com / @PythosL