Image Generation, in PracticeLesson 18 of 69

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Image Generation, in Practice

Lesson 18 of 69. Sign in to keep your place.

Module 2 · From a request to a specification you can generate against

One hero or twelve pieces is a different job

7 min read

One hero and a set of twelve are different jobsThe problemWhere the time goesOne heroA searchbreadth, then one winner70% exploring30% finishingTwelve imagesConsistencythey must match50% agreeing20% generatingA set is not twelve heroes. Run it that way and you get twelve good unrelated pictures and a very longday reconciling them.
A set is not twelve heroes. Run it that way and you get twelve good unrelated pictures and a very long day reconciling them.

Figure

Two jobs that look the same on the brief

“We need an image for the campaign” and “we need the campaign images” differ by one word and by a factor of about four in effort, and not in the direction you would guess.

One hero image is a search. You are looking for a frame that is good enough to carry the whole thing, and the method is breadth: many cheap candidates, a ruthless cull, then deep work on one winner. Budget shape: 70% exploration, 30% finishing.

A set of twelve is a consistency problem. The individual images do not need to be extraordinary; they need to look like each other. One stunning frame among eleven ordinary ones actively hurts the set, because it makes the rest look like mistakes. Budget shape: 30% establishing the system, 20% generating, 50% making them agree.

The mistake is running a set like twelve heroes. You get twelve good, unrelated pictures, and then a very long day trying to reconcile them.

What “the system” means

For a set, the first job is not an image: it is a set of constants you will hold across every frame:

  • Light: direction, hardness, colour temperature. One choice for all twelve.
  • Lens: a focal length and a camera height. Mixing a 24mm wide and an 85mm portrait in one set reads as two different shoots.
  • Palette: three or four colours that recur.
  • Grain and finish: applied identically at the end, which is the cheapest consistency you can buy.
  • Crop convention: how much room around the subject.

Fix those, write them down, generate one anchor image that embodies all of them, and approve it before making the other eleven. The anchor then serves technically as well as editorially: as a style reference, as a colour-match target, and as the thing you hold up when frame nine drifts.

The arithmetic that decides the quote

A rough but honest shape for planning, in generated images rather than hours:

  • One hero: 60 to 120 exploration renders, 6 to 10 full-quality candidates, 20 to 40 inpainting passes on the winner.
  • Twelve-image set: 40 renders to find the anchor, then roughly 15 to 25 renders per frame because you are constraining harder, plus repair on each.

The second is not twelve times the first, but it is comfortably three to four times, and the shape of the work is different: it is more editing and less searching, so it benefits less from a faster GPU and more from a disciplined process.

Say which one it is, in writing

The practical outcome of this lesson is a sentence in the spec: “One hero image, plus crops” or “A set of N images sharing one visual system”. They price differently, they schedule differently, and a client who asked for one and receives the other is right to be unhappy.

Watch for the request that starts as one and becomes the other. “This is great. Can we get five more like it?” is the most common scope expansion in this work, and it is a different job. Five more like it means building the system retrospectively from an image that was composed without one, which is harder than building it from the start. The revision lesson later in the course gives you language for that conversation; the thing to do now is notice it is coming.

The honest limit

Consistency across a set has a ceiling that no current method removes. You can hold light, palette, lens and finish. You can hold a character reasonably well with the methods in the consistency block. What you cannot reliably hold is a specific object across many angles (the same chair, with the same scuffs, seen from four sides) because nothing in the model is tracking an object identity between generations.

For those, the honest answers are to photograph it, to model it in Blender, or to design the set so the object is only seen from one angle. Deciding that now, at the brief stage, is what keeps it from becoming a crisis at frame seven.

The order to make a set in

Sequence matters more than people expect, and the productive order is not first-to-last.

  1. The anchor. The single frame that best embodies the system. Finish it completely, including grade and grain, and get it approved.
  2. The hardest frame. Whichever one you privately suspect is impossible: the group shot, the specific object, the one with legible text. Do it second, while there is still time to redesign the concept around it.
  3. Everything straightforward. These go quickly once the system is fixed and the hard problem is solved.
  4. A consistency pass over all twelve together, on one screen, at the same size. Fix whatever does not belong.

Doing the hard frame second is the part people resist, because it is the least enjoyable. It is also the only order in which discovering a problem is cheap: finding at frame eleven that the concept cannot be delivered means eleven finished frames may need to change.

The final pass is not optional. Images look consistent one at a time and reveal their disagreements the moment they are side by side, which is exactly how the audience will see them.

Every lesson here is open. Your progress is recorded once you pass the Vectors, Logos and Things That Get Printed exam.

Check your understanding

Why does a twelve-image set need a different method from a single hero image?

Pick the one you would defend. Your answer stays private.

Next lesson · 7 minThe frames where a phone camera wins

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How to cite: Addaly (2026) ‘One hero or twelve pieces is a different job’, in Image Generation, in Practice. Edited by M. Mun. Addaly. Available at: https://addaly.com/learn/ai-images/one-image-or-a-set (Accessed: 13 October 2026).