Flux ControlNet Inpainting

Experience advanced image inpainting with Flux ControlNet Inpainting. Ready to experience the power of AI? Start your journey here!

Platform: Replicate

Image InpaintingControlNetBETA VersionFlux Architecture

129 runs

A100 (80GB)

License Check Required

🚀Function Overview

This model performs image inpainting using the Flux. Ready to experience the power of AI? Start your journey here!

Key Features

Text-guided image modification in masked areas
ControlNet conditioning for enhanced control
Negative prompts to avoid unwanted elements
Adjustable output quality and format settings
Seed control for reproducible results

Use Cases

•Removing objects from images
•Filling missing or damaged image areas
•Adding new elements to existing photos
•Creative image manipulation and enhancement

⚙️Input Parameters

image

string

Upload an image for inpainting. This will be the base image that will be partially modified.

mask

string

Upload a mask image for inpainting. White areas (255) indicate regions to be inpainted, while black areas (0) will be preserved from the original image.

prompt

string

Enter a text description to guide the image generation process.

negative_prompt

string

Negative text prompt. Used to reduce or avoid certain aspects in the generated image.

controlnet_conditioning_scale

number

ControlNet conditioning scale.

num_inference_steps

integer

Set the number of denoising steps. More steps generally result in higher quality but slower generation.

guidance_scale

number

Guidance scale for classifier-free guidance. Higher values encourage the model to generate images that are closer to the text prompt.

true_guidance_scale

number

True guidance scale for the transformer model.

num_outputs

integer

Number of images to generate.

seed

integer

Set a seed for reproducible generation. Leave as None for random results.

output_format

string

Choose the file format for the output images.

output_quality

integer

Quality of the output images (applicable for 'jpg' and 'webp'). Value between 1 (lowest quality) and 100 (highest quality). Ignored for 'png'.

💡Usage Examples

Example 1

Input Parameters

{
  "mask": "https://replicate.delivery/pbxt/Le6GAg8i6DrhZxvjibNmzKy4jPYEKIhH8DBZnUp2WAioguXI/bucket_mask.jpeg",
  "image": "https://replicate.delivery/pbxt/Le6GAdIHbCc7u5RAFQ09dqJoROHEayxjWQbg9Hx16aY2fa9L/bucket.png",
  "prompt": "a person wearing a white shoe, carrying a white bucket with text 'REPLICATE FLUX INPAINTING CONTROLNET' on it",
  "num_outputs": 1,
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "negative_prompt": "",
  "num_inference_steps": 28,
  "true_guidance_scale": 3.5,
  "controlnet_conditioning_scale": 0.9
}

Output Results

https://replicate.delivery/yhqm/3WhkfI7t6eoCQ0fi7qNtznimZcRfVnPajAgzCfV0kBtJchpkC/output_0.webp

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Technical Specifications

Hardware Type: A100 (80GB)
Run Count: 129
Commercial Use: Unknown/Restricted
Platform: Replicate

Related Keywords

Image InpaintingControlNet ConditioningText-Guided Image ModificationObject RemovalFilling Damaged AreasAdding New ElementsCreative Image Manipulation

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