Lock identity, composition, lighting, and wardrobe before style words so a portrait series stays consistent instead of drifting frame to frame.
Il prompt
Create an editorial portrait of [SUBJECT] for [USE]. Preserve facial identity and natural skin texture. Composition: [FRAMING]. Lighting: [LIGHTING]. Wardrobe: [WARDROBE]. Background: [BACKGROUND]. Color grade: [PALETTE]. Avoid plastic skin, distorted hands, text, logos, and over-sharpening.
Sostituisci le variabili
[SUBJECT]The person or reference image.
[FRAMING]e.g. head-and-shoulders, 3/4.
[LIGHTING]e.g. soft key, rim light.
Quale modello usare
- Nano Banana Pro — Identity-preserving image edits are handled by the image model, not the text model.
Input di esempio
- [SUBJECT] = uploaded reference photo. [USE] = "LinkedIn headshot".
Output di esempio
Pubblichiamo output di esempio solo da esecuzioni reali del modello. Questo template non è ancora stato testato formalmente, quindi non viene mostrato alcun output. Eseguilo tu stesso con l'input qui sopra.
Perché questa struttura funziona
- Structure-before-style stops adjectives from fighting each other.
- An explicit negative list removes common artefacts.
Errori comuni e soluzioni
Face drifts between generations.
Soluzione: Reuse the same reference and keep identity terms first in the prompt.
Limiti noti
- Image models vary; results are not guaranteed and need review.
FAQ
Where are the tested portrait prompts?
The image gallery has portrait prompts with real example outputs. This page is a reusable template for building your own.