The requirement that separates demos from jobs
One striking image is easy now. Ten images of *the same person* in different scenes, or forty shots of *the* product with *the* label, is the requirement almost every real commission has, and it is genuinely hard.
There are four approaches. They are not alternatives to each other so much as rungs, and it is worth knowing exactly how far up each one gets you.
Rung one: seeds. Almost useless for this
A seed is the starting noise. Same seed, same model, same prompt, same settings gives you the same image, bit for bit. Change one word and the face changes.
So seeds reproduce an image, not an identity. They matter enormously for controlled experiments — change one clause, keep the seed, see what that clause did — and they matter for going back to a frame you liked. They do not give you the same person in a new pose. People waste days on this.
Rung two: identity adapters. Family resemblance
Feed one photograph of a face; get back a generated face that resembles it. This is IP-Adapter FaceID, InstantID and PuLID in the open world, and "character reference" or a trained identity object like Higgsfield's Soul ID on hosted platforms.
Honest ceiling: these carry the broad geometry of a face — the proportions, the general structure — and they are family-resemblance accurate, not identity accurate. The person's sister comes out. Skin texture drifts, apparent age drifts, and unusual angles break it. Expression is often flattened toward neutral.
That is fine for a stylised character, a game avatar, an illustrated persona. It is not fine when the client is looking at a picture of themselves, because humans have dedicated neural hardware for faces and will spot the wrongness without being able to name it.
The platform versions that ask for a set of photographs rather than one are doing something closer to rung three, and get closer to the person.
Rung three: a LoRA. The real answer
Train a small adapter on images of your subject. Twenty to thirty images, an hour or so of training, and the concept becomes something you can name in a prompt and place anywhere.
What actually determines whether it works:
- Variety beats quantity. Twenty photographs across different lighting, angles, distances and clothing beat two hundred taken in one session. If every training image was shot against the same blue wall, the LoRA has learned the blue wall as part of the person, and it will follow them into every scene.
- Crop consistently and caption honestly. Caption what varies, not what stays constant.
- Stop early. Overtraining bakes in the training set. The face becomes rigid and one of the photographs starts reappearing wholesale.
- Free to do. Kohya_ss, OneTrainer and ai-toolkit are free, and Kaggle's or Colab's free GPU hours are enough for a character LoRA. Fine-tuning covers the general method.
Rung four: do it in an editor
Generate the scene. Composite the real photographed head, or the real product, onto it. Match colour, match grain, match the light direction.
This is unglamorous and it is the most reliable thing in this lesson. Half of what looks like extraordinary AI work in commercial studios is a generated background with a photographed subject on top. Image editing is the skill that makes it invisible.
Products are harder than faces
A face can be five per cent wrong and read as the person. A logo cannot be five per cent wrong — a wrong letterform is simply a counterfeit. Bottle proportions, the exact green of a brand, the position of a seam: all of these must be exact and none of these are things a model holds precisely.
The professional answer: photograph the product, generate the environment, composite. Do not ask a model to draw a product that exists. Ask it to build a room to put the photograph in.
The consent line
A LoRA of a person is a tool for producing unlimited images of that person doing things they did not do. Training one on someone who has not agreed is not a technical decision, and in several countries it is now a legal one. Get permission in writing, and say what the images will be used for. Making things with AI sets out the wider consent and likeness position.
Today: if you have a recurring character, count your reference photographs. If they were all taken in one place on one afternoon, you do not yet have a training set — you have one photograph repeated.
Before you move on