AI image to image takes a picture you already have and reworks it from a prompt — restyling a snapshot into an oil painting, turning a rough sketch into a finished illustration, or repainting a daytime street as a neon-lit night scene. Instead of inventing a picture from words alone, the model starts from your image and changes only as much as you tell it to. On Android, the whole process is upload, prompt, set one slider, and generate.
This guide explains how AI image to image actually works, what the denoise and strength controls really do, and the workflow inside FP AI Studio that takes you from source photo to a clean transformed result.
The core idea: image to image is a dial, not a switch. One value — denoise or strength — decides whether the AI lightly retouches your photo or rebuilds it from the ground up. Learning that single slider is most of the skill.
What AI image to image does
AI image to image transforms an existing photo according to a text prompt while keeping part of the original intact. It is the workflow people mean by img2img: you feed the model a source image and a description, and it returns a new version that follows your prompt without throwing away the composition you started with.
That one capability covers a wide range of edits people used to do by hand:
- Restyling — turn a photo into a painting, anime frame, or 3D render
- Sketch-to-image — promote a line drawing into a finished, shaded picture
- Variation — generate alternate takes that keep the same layout and pose
How does image to image work?
Image to image works by adding noise to your source photo and then having a diffusion model remove that noise while following your prompt. Because the model starts from your image rather than from pure randomness, the composition, pose, and framing survive into the output, and the prompt steers what the cleaned-up result becomes.
The pipeline behind a single generation looks like this:
- Encode — your photo is converted into the model's internal representation
- Add noise — the model partially scrambles the image, controlled by the strength value
- Read the prompt — your text description is parsed into guidance for the next step
- Denoise — the model rebuilds a clean image, steering toward the prompt
- Decode — the result is rendered back into a finished picture
The key insight is in step two: how much noise the model adds at the start decides how much of your original it has to reconstruct. Add a little, and the photo stays close to the source. Add a lot, and the model is effectively painting a new scene over your composition. That trade-off is exactly what the denoise slider exposes, which the next section covers in detail.
What do denoise and strength control?
Denoise, often labelled strength, controls how much of your source image the AI is allowed to overwrite. It runs from about 0 to 1. A low value keeps the photo almost untouched and only adjusts color or finish. A high value lets the model rebuild most of the frame from your prompt, leaving little of the original behind.
Reading the slider as a range makes it concrete:
- 0.1 to 0.3 — light touch — subtle color grading, texture, or finish; the photo is clearly the same image
- 0.4 to 0.6 — balanced restyle — recognizable subject and composition, but a new look or medium applied
- 0.7 to 0.9 — heavy transform — the model rebuilds most of the scene; only the broad layout of the source survives
- Near 1.0 — almost text-to-image — the source barely influences the result; you may as well start from a prompt alone
The practical habit is to start in the middle, around 0.5, generate, and then move the slider toward whichever outcome you want: lower to stay closer to the original, higher to let the prompt take over. Because each run samples differently, regenerating at the same setting also gives you fresh variations. Strong prompts help here, and the AI prompt engineering tips guide explains how to write descriptions the model can actually follow.
How do you transform a photo step by step?
To transform a photo in FP AI Studio, upload your source image, write a prompt describing the change, set the strength slider, and generate. The whole process takes under a minute, and you can re-run at a different strength until the balance between original and prompt looks right.
- Upload your source photo in FP AI Studio and open the image-to-image tool
- Write a clear prompt — name the subject and the change, such as "watercolor painting of this street scene"
- Set the strength slider — start near 0.5 for a balanced restyle
- Generate and wait a few seconds for the result
- Compare to the source — check whether the composition you wanted to keep survived
- Adjust the slider — lower it to stay closer to the photo, raise it to lean into the prompt
- Export at full resolution once the result matches your intent
If you want to invent a scene from scratch instead of transforming one, the AI image generation guide covers text-to-image from the prompt up. Image to image is the right path when you already have a photo whose layout you want to keep.
What can you do with image to image?
The most common uses are restyling a photo into a new medium, generating variations that keep a fixed pose, finishing a rough sketch, and refining an earlier AI render. Each follows the same upload-prompt-strength workflow but leans on a different strength setting and prompt focus to get there.
- Restyle a photo — convert a snapshot into a painting, sketch, or stylized render; mid-to-high strength
- Keep a pose, change everything else — hold the composition fixed while the prompt changes setting, outfit, or season
- Finish a sketch — turn line art into a shaded, detailed picture; high strength
- Refine a generation — feed an earlier AI image back in at low strength to clean up small flaws
- Match a target look — nudge a photo toward a specific aesthetic before a final edit
For restyling specifically, image to image and dedicated style transfer overlap. If your goal is to apply the look of one image to another, the style transfer guide walks through that workflow, while image to image is the better choice when a prompt describes the change more naturally than a reference image would.
How do you turn a sketch into an image?
To turn a sketch into a finished image, upload the drawing, write a prompt describing the completed scene, and set a high strength near 0.7 to 0.8. At that level the model treats your lines as a composition guide rather than final pixels, so the sketch fixes the layout while the prompt supplies color, lighting, and detail.
A reliable sketch-to-image pass looks like this:
- Scan or photograph the sketch on a plain background so the lines read clearly
- Upload it to the image-to-image tool as your source
- Describe the finished piece — subject, medium, lighting, and mood in the prompt
- Set strength high — 0.7 to 0.8 so the model fills in detail beyond the lines
- Generate and refine — adjust the prompt or strength if the layout drifts
The cleaner and more deliberate your sketch, the more the result respects your intended composition. If you are unsure which finished style to aim for, browsing the top AI art styles gives you concrete prompt vocabulary to drop into the description.
Text to image vs image to image: what is the difference?
Text to image and image to image start from different places and solve different problems. Text to image builds a picture from a prompt alone, beginning with random noise, so you cannot control the exact layout. Image to image starts from a photo you provide, so the composition, pose, and framing carry through. Pick the one that matches whether you are inventing a scene or transforming one.
| Aspect | Text to image | Image to image |
|---|---|---|
| Starting point | Random noise plus a prompt | Your source photo plus a prompt |
| Layout control | None — the model decides composition | High — the source fixes composition |
| Best for | Inventing a brand-new scene | Transforming an existing image |
| Key control | Prompt wording | Prompt plus denoise and strength |
The two methods chain naturally. A common sequence is to generate a base scene with text to image, then feed that result back through image to image at low strength to refine details or shift the style without losing the layout you liked.
How do you get a faithful result?
A faithful image-to-image result comes down to three habits: choose a strength that matches how much you want to change, write a prompt that names both the subject and the edit, and start from a clean, well-lit source. Most disappointing results trace back to a strength that is too high or a prompt that is too vague for the model to follow.
- Match strength to intent — light edits stay below 0.4, full restyles sit around 0.5 to 0.7
- Name the subject and the change — "this portrait as a charcoal sketch" beats "make it artistic"
- Start from a sharp source — a blurry input gives the model less structure to preserve
- Regenerate for variations — the same prompt and strength produce a fresh result each run
- Iterate in small steps — change one thing at a time so you know what moved the result
When a transform drifts too far from the original, the fix is almost always to lower the strength and run again. When it stays too close and ignores your prompt, raise the strength or sharpen the wording. Treating the slider and the prompt as a pair, rather than tuning one in isolation, is how a faithful result comes together.
FAQ
What is AI image to image?
AI image to image, also called img2img, takes an existing image plus a text prompt and generates a new image that keeps some of the original while applying the changes you describe. Instead of starting from noise like text-to-image, the model starts from your photo, so the layout, pose, and composition carry through into the result.
What does denoise or strength control in image to image?
Denoise, sometimes labelled strength, sets how much the AI is allowed to change your source image. A low value near 0.2 keeps the photo almost intact and only nudges color or style. A high value near 0.8 lets the model rebuild most of the scene from your prompt. The original composition fades as the value rises.
Can I turn a sketch into a finished image?
Yes. Sketch-to-image is a core use of img2img. You upload a rough drawing, write a prompt describing the finished scene, and set a high denoise so the model treats your lines as composition guides rather than final pixels. The sketch fixes the layout and the prompt supplies the detail, lighting, and texture.
How is image to image different from text to image?
Text-to-image builds a picture from a prompt alone, starting from random noise, so you have no control over the exact layout. Image to image starts from a source image you provide, so composition, pose, and framing are preserved. Use text-to-image to invent a scene and image to image to transform one you already have.
Why does my image to image result look too different from the original?
A result that strays too far usually means the denoise or strength value is set too high. Lower it toward 0.3 to 0.5 so the model keeps more of your source. A vague prompt also lets the AI drift, so name the subject and the change you want. Re-running at a lower strength is the fastest fix.