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bfl/flux-krea-lora/inpainting

Flux Krea Lora Inpainting is BFL's intelligent image editing model. Transform, retouch, and reimagine existing images using text prompts - from background replacement to artistic style conversion.

Input
The prompt to generate an image from.

PNG, JPEG, WebP, or GIF · 20 MiB maximum

URL of image to use for inpainting. or img2img

PNG, JPEG, WebP, or GIF · 20 MiB maximum

The mask to area to Inpaint in.
0.011
The strength to use for inpainting/image-to-image. Only used if the image_url is provided. 1.0 is completely remakes the image while 0.0 preserves the original. Range: 0.01 to 1.
The format of the generated image. Allowed values: jpeg, png.
The aspect ratio of the generated image. Allowed values: 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16.
The same seed and the same prompt given to the same version of the model will output the same image every time.
Enter a JSON array.
035
Range: 0 to 35.
150
Range: 1 to 50.
Idle

Example output — click Run to generate your own

API README

Flux Krea Lora Inpainting

Flux Krea Lora Inpainting belongs at the Krea-oriented localized revision with customization stage of a visual workflow. Rather than treating the model as an isolated demonstration, teams can place it inside briefing, review, selection, and handoff practices where small corrections can inherit the same learned aesthetic as the approved image instead of looking like a neutral patch. This positioning clarifies why the model earns a place in a real creative pipeline and what kind of decision it helps people make.

A practical use of Flux Krea Lora Inpainting is fashion cleanup, character repair, set-detail replacement, and focused editorial revisions where the replacement must share the collection’s visual taste. Begin by agreeing on the creative objective and review criteria, prepare only the source material needed for that objective, and compare results against audience, brand, editorial, and production needs. Technical request choices remain documented below so the prose can stay focused on planning and creative value.

Highlights

Context-aware reconstruction. Rebuilds masked content with lighting, perspective, texture, and scale matched to its surroundings.

Semantic replacement. Follows written direction for new objects or materials instead of simply cloning nearby pixels.

Natural boundary blending. Integrates regenerated content across the mask edge without a pasted-on appearance.

Unmasked-area preservation. Concentrates generative change on the intended region while retaining the broader composition. Krea-LoRA joins a learned concept with the model's aesthetic tuning for cohesive, highly art-directed visual series.

Pricing

ConfigurationBilling unitPrice
Base generationPer request$0.035

When to Use

✅ Good fit❌ Consider alternatives
The project needs this exact FLUX capabilityThe intended task belongs to a different media workflow
Required source and control media are availableNecessary assets or usage rights are unavailable
Creative direction can state change and preservation goalsOutput must be deterministic at pixel or frame level
Supported dimensions and formats match final deliveryPlacement requires unsupported specifications
An asynchronous generated result fits productionA live frame-synchronous response is mandatory

Prompt Guide

Lead with the main subject and action, then specify composition, context, lighting, materials, style, typography, and atmosphere. For editing, identify each source and clearly separate the requested transformation from the subjects, regions, geometry, or identity that must remain unchanged.

{
  "image": "https://example.com/start-frame.png",
  "loras": [],
  "mask": "https://example.com/reference.png",
  "prompt": "A cinematic, precisely composed result with a clear subject, controlled camera or viewpoint, realistic lighting, exact materials, and intentional atmosphere",
  "seed": 1
}

Technical Specs

SpecValue
Model IDbfl/flux-krea-lora/inpainting
Input fieldsmask (string)<br>seed (integer)<br>image (string)<br>loras (array)<br>prompt (string)<br>strength (number; 0.01–1)<br>aspect_ratio (string; 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16)<br>output_format (string; jpeg, png)<br>guidance_scale (number; 0–35)<br>num_inference_steps (integer; 1–50)
Required inputprompt, image
Output fieldsurl, content_type
ExecutionAsynchronous job

Related Models

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