Edit Any Part of an Image with Fibo Edit

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Overview

Fibo Edit is an image editing AI that reads a plain-text instruction and applies it directly to a photo you provide. Rather than opening heavy editing software, selecting layers, or painting masks by hand, you type what you want changed and the model does the work. A product photographer who needs to swap a background, a designer adjusting a scene after the shoot, or a marketer retouching visuals for a campaign can act on those edits in seconds. For users who need precise, repeatable changes, Fibo Edit also supports a structured instruction format for step-by-step control over every edit. It runs on Picasso IA with no installation or coding required.

How It Works

Upload the photo you want to edit, along with an optional mask that marks the specific area to change
Write a plain-text instruction such as "make the sky blue" or "remove the bottle from the table"
Optionally add a negative prompt to prevent specific elements from appearing in the output
Set the guidance scale to decide how closely the model follows your instruction, from a subtle touch to a stronger reinterpretation
Review and download your edited image from Picasso IA once processing finishes

Frequently Asked Questions

Do I need programming skills or technical knowledge to use this? No, just open Fibo Edit on Picasso IA, adjust the settings you want, and hit generate.

Is it free to try? Yes, you can run Fibo Edit without a paid subscription to test the results. Credit usage depends on your account plan.

How long does it take to get results? Most edits finish within a few seconds. Larger images or more detailed instructions may add a moment to processing time.

What output formats are supported? Fibo Edit returns a standard image file you can download and use right away, with no watermark added.

Can I control how strongly the model applies the edit? Yes. The guidance scale lets you set the intensity of the change. A low value keeps the output close to the original; a higher value applies the instruction more aggressively.

What if the result does not look right? Rephrase the instruction, refine the mask to cover only the area that should change, or adjust the guidance scale. Adding a negative prompt can also help suppress unwanted visual elements in the output.

Can I get the same result twice? Yes. Fix the seed before generating and the model will return an identical output for the same inputs. This is useful when you want to iterate on one specific version of an edit.

Credit Cost

Each generation consumes 1 credit

1 credit

or 5 credits for 5 generations

Features

Everything this model can do for you

Text-driven edits

Describe any change in plain language and the model applies it directly to your image.

Mask control

Draw a mask over the area you want to edit and keep the rest of the image untouched.

Guidance scale

Adjust a single parameter to control how literally the model follows your instruction, from a subtle nudge to a full override.

Negative prompts

Specify what to exclude from the result to avoid unwanted elements appearing in the edited output.

Reproducible results

Set a seed value to regenerate the exact same edit whenever you need it.

Structured instructions

Pass a JSON-formatted instruction string for precise, programmatic control over the edit.

No coding required

Enter your instruction in a text field and click generate, no technical setup needed.

Use Cases

Swap a plain background in a product photo by writing a description of the background you want, without manually cutting around the subject.

Add an object to a scene by typing what you want to place and where, such as 'put a coffee cup on the table in the foreground.'

Change the color of a specific element in a photo by writing the edit instruction and drawing a mask around that area.

Remove an unwanted object from an image by masking it and instructing the model to fill the space with the surrounding context.

Test multiple visual variations of a scene by rerunning the same image with different text instructions and comparing outputs side by side.

Refine a generated image by describing the adjustment you want in one sentence and letting the model apply it without full regeneration.

Adjust the atmosphere of a photo by writing a lighting instruction, such as 'make the room look like it is lit by candlelight.'

Examples

30.1s

Instruction: change lighting to starlight nighttime