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Image to prompt generator

Upload a reference, choose a model, and get an editable prompt. Free, with no account or credits.

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Add a reference

Interpretation

Describe the visible image closely.

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Resized and stripped of metadata before analysis

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Your prompt

A real reference-to-prompt case

AI-generated tutorial reference: black bottle on a stone pedestal
Reference
Recreation from the saved prompt: similar black bottle, different framing and pedestal
Text-only recreation

The scene carries over. Exact shape and framing can change.

AI-generated demo images · Opening this example makes no analysis call.See the full case and prompt formats ↗

One reference. A real result.

See what your prompt can do.

A studio bottle photo, analyzed by this tool, then recreated from its text prompt.

Read the worked examples →
AI-generated reference: matte black bottle on a thin beige stone pedestal
01 / ReferenceAI-generated tutorial image
Text-only recreation: similar black bottle with a different cap and thicker pedestal
02 / Recreated from the promptNo reference image supplied to the image generator

Case recorded September 7, 2026. Universal / Faithful output, recreated with OpenAI image generation using the exact primary prompt, without a reference image or separate negative prompt. One generation; model version and seed were not exposed.

The subject, palette and soft light carry over; the cap, proportions and framing change. One example, not a guarantee of identical results.

Try the example — no analysis needed

This saved prompt is the actual tool output. Opening or copying it does not run an analysis.

A matte black cylindrical water bottle with a matching black screw-on cap stands upright and centered on a low, round travertine stone pedestal in a minimal studio. The bottle has a smooth powder-coated matte finish with a subtle specular highlight running along its left shoulder and a gently rounded shoulder tapering into a short neck. The pedestal is a thick cylindrical slab of porous, honed beige stone with visible pitting and natural texture, resting on a smooth off-white surface. Behind them, a plain warm light-gray seamless wall provides a clean, neutral backdrop. Vertical portrait composition with the bottle on the central axis, the pedestal occupying the lower third, and generous negative space on both sides; straight-on symmetrical eye-level perspective with a normal to slightly long focal-length feel and minimal distortion. Soft diffused key light from the upper left creates low contrast, a gentle gradient shadow falling to the right of the pedestal, and a neutral daylight-like studio mood. Sharp focus across the bottle and pedestal with the background only softly out of focus. Color palette of matte black, charcoal, warm light gray, beige, off-white, and soft taupe. Minimalist commercial product photography with a clean, premium, unbranded aesthetic. No text, logos, or labels anywhere in the frame.
See the method and differences →

Image to prompt for Midjourney, Flux, Stable Diffusion and DALL·E

Each image model reads a prompt differently, so the same verified visual facts are compiled differently per target: compact descriptive clauses with justified parameters for Midjourney, complete natural-language sentences for Flux, comma-separated concepts plus a real negative prompt for Stable Diffusion, and full art direction for DALL·E.

What you get from one image

Every result contains all of the following, editable and copyable:

  • Subject, framing, camera, and composition — including shot type, angle, placement, and depth.
  • Lighting and color — direction, quality, contrast, shadows, and the specific palette.
  • Materials and style — visible textures, medium, and rendering approach.
  • Visible text — exact readable strings carried into the prompt, or an explicit instruction to add none.
  • Useful exclusions — a negative prompt where the target model benefits from one.
  • A quality report — weighted component scores, plus a revision when the review calls for it and processing time allows. The score is an AI assessment of the prompt, not a measured image similarity score.

A tested reference-to-prompt studio case and writing examples for travel, a sticker illustration, and food photography are on the examples page.

How it works in four steps

  1. Prepare in your browser. Your image is resized, converted to a clean JPEG, and stripped of file metadata on your device before anything is uploaded.
  2. Extract verified visual facts. A vision model returns structured observations only, and lists what it refuses to guess.
  3. Compile for your target model. An editor pass turns those facts into a prompt shaped for the model you picked.
  4. Review against the original. A second vision pass scores the draft against your actual image, with an optional revision when its score is below 85 and processing time allows.

The full methodology, including the scoring components, is on how image to prompt works.

Faithful or Balanced

Faithful prioritises literal recreation of the visible image and will not embellish the scene. Balanced keeps the subject and composition while allowing restrained polish in the wording. Both modes run the same review pass against your image, so neither skips the check.

Frequently asked questions

Is it free?

Yes. Image analysis, prompt editing, and copying are free. There is no daily one-use allowance, paid plan, or credit pack. Fair-use request limits and temporary service capacity limits apply.

Do I need an account?

No. There is no sign-up, no email address, and no login. The tool works straight from the browser and you can start immediately.

Are my images stored?

No. Your browser resizes the image and strips file metadata before upload, the prepared image is analysed in memory for the duration of the request, and this site does not save it.

Which image models does it write for?

Midjourney, Flux, Stable Diffusion, DALL·E, and a portable universal format. Prompt structure, parameter style, and negative prompts adapt to the target you choose.

What does a result include?

A primary prompt, an alternate wording, a negative prompt where the target model benefits from one, a structured breakdown of subject, camera, lighting, palette, and style, and a quality report with component scores.

Read about free access and fair-use limits on the free access page.

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Faithful first

Every result is checked against the original image before you see it.

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Model-aware

Prompt structure adapts to Midjourney, Flux, Stable Diffusion, and more.

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Private by design

Your prepared image is analyzed in memory and is not saved by this site.