ANDREI KOVALEV'S
MIDJOURNEY
GUIDE

REMIX
To illustrate how this mode works, I'll start with a story. To put the then-recent Remix mode to the test, I started with a generation of a beetle and then used Remix to obtain a beetle-theme head-piece/mask.
Remix mode is the most impactful addition to Midjourney to date (I am writing this in October 2022). It gives us the next level of control over our generations.

With Remix, it is possible to develop one generation throughout multiple iterations to be as close as possible to our initial idea. Here is another fashion experiment: using Remix, I aimed to obtain an iridescent Yeezy unibody coat inspired by the shape of a tardigrade.
[ORIGINAL]
tachikoma by Tstutomu Nihei --ar 3:2
[REMASTER]
tachikoma by Tstutomu Nihei --ar 3:2 --test --creative
A cool tachikoma bot against smoking cyberpunk city backdrop turns into a weird teletubby with a messed up background…
[ORIGINAL]
bioreactor --ar 2:3
[REMASTER]
bioreactor --ar 2:3 --test --creative
[ORIGINAL]
elaborate hadron antimatter vacuum reactor. Highly detailed scientific photograph --ar 4:5
[REMASTER]
elaborate hadron antimatter vacuum reactor. Highly detailed scientific photograph --ar 4:5 --test --creative
An interesting-looking bioreactor with a plant whirling inside the tank becomes a dull miniature tree in front of it after a Remaster. And a complex environment of a vintage scientific research lab with intricately textured walls turns into an empty space built… out of paper? That happens…
The bottom line here: there is no manual on Remaster mode. It’s a just-press-the-button-and-see-what-happens kind of feature. However, I will share a few observations that might help you better feel Remaster’s behavior.
[ORIGINAL]
chromolithography of stag beetle --ar 2:3
[REMASTER]
chromolithography of stag beetle --ar 2:3--test --creative
[ORIGINAL]
colossal brutalist skyscrapper cat by Artur Bordalo --ar 2:3
[REMASTER]
colossal brutalist skyscrapper cat by Artur Bordalo --ar 2:3 --test --creative
From my experience, Remaster works somehow similarly to Image Prompts: instead of building upon the text of your prompt, it works with the visual part, reinterpreting the image itself.

To establish it beyond my instincts, I ran a simple test. First, I asked Midjourney to render a nonsensical prompt: jdshgiusdh sh ss9hs in both --v3 and --test --creative modes.
[ORIGINAL]
jdshgiusdh sh ss9hs --ar 3:2
[ORIGINAL]
jdshgiusdh sh ss9hs --ar 3:2 --test --creative
The results were VERY different, so I knew that my abracadabra was not common knowledge shared between modes. I also saw how --test --creative interprets the words themselves.

I then upscaled variation #2 from the --v3 result and Remastered it.
[ORIGINAL]
jdshgiusdh sh ss9hs --ar 3:2
[REMASTER]
jdshgiusdh sh ss9hs --ar 3:2 --test --creative
Et voila! Remaster ignored the words but rendered the image based on the visual component of the --v3 result.

Now that we have a hypothesis about how Remaster works, let's deduce a few factors that affect Remastering:

1. SIMPLICITY

Remastering primitive images tends to render the closest result to the original. A more abstract and less obvious subject will sometimes lead to unexpected results.
[ORIGINAL]
silly cat by Allie Brosh --ar 2:3
[REMASTER]
silly cat by Allie Brosh --ar 2:3 --test --creative
[ORIGINAL]
druid spirit by John Kenn Mortensen --ar 2:3
[REMASTER]
druid spirit by John Kenn Mortensen--ar 2:3 --test --creative

2. recognizability

The same as #1 goes for easily recognizable subjects.
[ORIGINAL]
blue jay by Archibald Thorburn --ar 3:2
[REMASTER]
blue jay by Archibald Thorburn --ar 3:2 --test --creative

3. SIZE

The larger your subject is, the more space it takes in the image—the more chances it will be "seen" and make it into the Remastered variant. The smaller the details, the harder it is for Midjourney to spot and reinterpret them. Expect some weird Remasters!
[ORIGINAL]
baba yaga by Paolo Roversi --ar 2:3
[REMASTER]
baba yaga by Paolo Roversi --ar 2:3 --test--creative
[ORIGINAL]
baba yaga by Paolo Roversi --ar 2:3
[REMASTER]
baba yaga by Paolo Roversi --ar 2:3 --test --creative

4. REROLLS

Remastering the same --v3 result several times will give you different results each time. Rerolls behave the same way, but each reroll builds upon the image that you are rerolling at the moment instead of the original generation. In both methods, every iteration may change the outcome dramatically.
[ORIGINAL]
colossal antimatter combustion collider engine cat. Scientific photograph. Frontal projection. Slots, tubes, wires, shafts, cables --ar 2:3
[REMASTER]
colossal antimatter combustion collider engine cat. Scientific photograph. Frontal projection. Slots, tubes, wires, shafts, cables --ar 2:3 --test --creative
[REMASTER reroll #1]
colossal antimatter combustion collider engine cat. Scientific photograph. Frontal projection. Slots, tubes, wires, shafts, cables --ar 2:3 --test --creative
[REMASTER reroll #2]
colossal antimatter combustion collider engine cat. Scientific photograph. Frontal projection. Slots, tubes, wires, shafts, cables --ar 2:3 --test --creative

5. GLITCHES

Finally, Remasters often correct glitches in the original generations. And rerolls may fix those that might have appeared during a previous Remaster iteration.
[ORIGINAL]
portrait of a girl by Sacha Goldberger --ar 2:3
[REMASTER]
portrait of a girl by Sacha Goldberger --ar 2:3 --test --creative
[REMASTER]
wild cat XIX century admiral Nelson by Billy Childish --ar 2:3 --test --creative
[REMASTER reroll #1]
wild cat XIX century admiral Nelson by Billy Childish --ar 2:3 --test --creative
Remaster is a mystery, difficult to understand and wield. But it is also a powerful tool that requires many trials and errors to learn to feel and use. And if you do, your prompts will undoubtedly lead to some fantastic results!

ANDREI KOVALEV'S
MIDJOURNEY
GUIDE

A comprehensive short guide to Midjourney workflow based on personal observations and experimentations

ANDREI KOVALEV'S
MIDJOURNEY
STYLES LIBRARY

is a curated collection of styles and techniques that, when added to prompts, affect Midjourney AI generations.
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