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Use in agentBFL models

BFL modelsimage generation api

bfl/flux-lora-depth

Flux Lora Depth 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 depth input
035
The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you. Range: 0 to 35.
150
The number of inference steps to perform. Range: 1 to 50.
The format of the generated image. Allowed values: jpeg, png.
The LoRAs to use for the image generation. You can use any number of LoRAs and they will be merged together to generate the final image.
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.
Idle

Example output — click Run to generate your own

API README

Flux Lora Depth

Flux Lora Depth belongs at the adapted image creation organized by scene depth 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 a spatial plan can survive across stylistic and subject variations while the learned adapter establishes the collection’s identity. 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 Lora Depth is environment art, interior concepts, staged product scenes, and branded imagery built around a consistent arrangement of space. 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

Depth-faithful composition. Maintains foreground, middle-ground, and background ordering in the generated still image.

Volume-aware restyling. Changes materials and appearance while respecting the source scene's perceived geometry.

Viewpoint structure retention. Preserves spatial relationships and object scale across the generated still composition.

Prompt-and-depth fusion. Combines written art direction with depth conditioning for controlled still-image creation. The LoRA-enabled configuration applies specialized subject or style knowledge while retaining the underlying FLUX image prior.

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.

{
  "aspect_ratio": "21:9",
  "image": "https://example.com/start-frame.png",
  "loras": [],
  "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-lora-depth
Input fieldsseed (integer)<br>image (string)<br>loras (array)<br>prompt (string)<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

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