Make AI images look like real photographs
The fastest way to push an image generator from “obviously AI” toward “convincing photograph” is to describe it the way a photographer would. Models are trained on millions of captioned photos, so naming a real camera body, lens, aperture and film stock activates the visual patterns the model learned from those captions. This picker lets you assemble those terms from curated, realistic options and copy them straight into your prompt.
How photographic terms steer the model
Each part of the snippet controls a different visual cue:
- Camera body sets overall fidelity and format — “medium format Hasselblad” implies high detail and a particular tonality.
- Lens / focal length controls perspective and compression — wide-angle exaggerates space, telephoto flattens it, macro gets in close.
- Aperture drives depth of field — wide apertures (f/1.2–f/2.8) blur the background; narrow ones (f/8–f/16) keep everything sharp.
- Film stock layers in color science and grain — warm Portra skin tones, saturated Velvia landscapes, or grainy expired-film nostalgia.
Combined, they produce a snippet like
shot on a Canon EOS 5D Mark IV, 85mm portrait lens, f/1.8, shallow depth of field, Kodak Portra 400 film.
Tips for believable results
- Don’t over-stack. One camera, one lens, one aperture and one film stock is usually enough — piling on more competing terms can confuse the model.
- Match the lens to the subject. Use long focal lengths and wide apertures for portraits, wide lenses for architecture and landscapes, macro for product and texture shots.
- Use film stocks for mood, not just color. Reach for Cinestill 800T for night scenes and expired film for a faded, vintage feel.
- Pair with lighting and composition terms from the related tools for a fully art-directed prompt.