Enhance Image Quality with the Flux ControlNet Inpainting Action

22 Apr 2025
Enhance Image Quality with the Flux ControlNet Inpainting Action

In the realm of image processing, the ability to perform high-quality inpainting can significantly enhance creative projects. The batouresearch/flux-controlnet-inpaint API provides developers with a powerful Cognitive Action called Execute Flux Inpainting. This action utilizes the Flux model, which is compatible with Canny ControlNet, LoRAs, and HyperFlux_8step, to deliver speedy, high-quality, and accurate inpainting results. By integrating this action into applications, developers can easily add sophisticated image editing capabilities.

Prerequisites

Before diving into the use of the Cognitive Actions, ensure you have the following:

  • An API key for the Cognitive Actions platform.
  • Basic understanding of RESTful APIs and JSON.
  • Ready access to a programming environment with libraries such as requests for making HTTP calls.

To authenticate your requests, you will typically pass your API key in the headers of your requests.

Cognitive Actions Overview

Execute Flux Inpainting

The Execute Flux Inpainting action performs inpainting on images, allowing you to fill in missing or obscured parts of an image based on specified prompts and provided masks. This action is categorized under image-processing.

Input

The action requires a JSON object with the following schema:

  • prompt (required): A text description of the desired image elements and style.
  • mask (optional): URI of the mask image indicating the area to inpaint.
  • seed (optional): Random seed for reproducible results.
  • image (optional): URI of the source image to be restyled.
  • strength (optional): Strength of the image transformation (default is 0.8).
  • loraScale (optional): Scaling factor for LoRA weights (default is 0.8).
  • loraWeights (optional): Path or URL to LoRA weights.
  • controlImage (optional): URI of an image used for controlling the generation process.
  • outputFormat (optional): Desired output format (default is "jpg").
  • guidanceScale (optional): Adherence to the prompt (default is 3.5).
  • outputQuality (optional): Quality of output images (default is 100).
  • conditioningScale (optional): ControlNet strength (default is 0.5).
  • numInferenceSteps (optional): Number of inference steps (default is 8).
  • enableHyperFlux8Step (optional): Enables Hyper-FLUX (default is true).

Here’s a practical example of the JSON payload needed to invoke this action:

{
  "mask": "https://replicate.delivery/pbxt/LdzOC0eYgmiQxsZntL8aUwyQlLjtXQuhmMrXrOUbpMESw11v/output%20%282%29.png",
  "image": "https://replicate.delivery/pbxt/LdzOC2USRj4omEK2igawxoYUPG6hJ2RfRZS2TZXiqSEkybYs/output%20%283%29.png",
  "prompt": "Professional photography of a fox sitting on a bench",
  "strength": 0.8,
  "loraScale": 0.8,
  "controlImage": "https://replicate.delivery/pbxt/LdzOBqGI9FyIIPZOyOBYToYndRLXelYBSqOP1XJlE5Tq5up9/output%20%283%29.png",
  "outputFormat": "jpg",
  "guidanceScale": 3.5,
  "outputQuality": 100,
  "conditioningScale": 0.5,
  "numInferenceSteps": 8,
  "enableHyperFlux8Step": true
}

Output

Upon successful execution, the action returns a URI for the inpainted image. Here’s a sample output:

[
  "https://assets.cognitiveactions.com/invocations/e4b9cfef-8df1-425b-8c79-6c45e1a46630/73fcc2b3-7f80-4982-87ac-ab473346c7f8.jpg"
]

Conceptual Usage Example (Python)

Here’s how a developer might structure their code to call the Execute Flux Inpainting action:

import requests
import json

# Replace with your Cognitive Actions API key and endpoint
COGNITIVE_ACTIONS_API_KEY = "YOUR_COGNITIVE_ACTIONS_API_KEY"
COGNITIVE_ACTIONS_EXECUTE_URL = "https://api.cognitiveactions.com/actions/execute" # Hypothetical endpoint

action_id = "41bb59a0-d515-4bb5-a0af-e9ee1d68767e" # Action ID for Execute Flux Inpainting

# Construct the input payload based on the action's requirements
payload = {
    "mask": "https://replicate.delivery/pbxt/LdzOC0eYgmiQxsZntL8aUwyQlLjtXQuhmMrXrOUbpMESw11v/output%20%282%29.png",
    "image": "https://replicate.delivery/pbxt/LdzOC2USRj4omEK2igawxoYUPG6hJ2RfRZS2TZXiqSEkybYs/output%20%283%29.png",
    "prompt": "Professional photography of a fox sitting on a bench",
    "strength": 0.8,
    "loraScale": 0.8,
    "controlImage": "https://replicate.delivery/pbxt/LdzOBqGI9FyIIPZOyOBYToYndRLXelYBSqOP1XJlE5Tq5up9/output%20%283%29.png",
    "outputFormat": "jpg",
    "guidanceScale": 3.5,
    "outputQuality": 100,
    "conditioningScale": 0.5,
    "numInferenceSteps": 8,
    "enableHyperFlux8Step": true
}

headers = {
    "Authorization": f"Bearer {COGNITIVE_ACTIONS_API_KEY}",
    "Content-Type": "application/json"
}

try:
    response = requests.post(
        COGNITIVE_ACTIONS_EXECUTE_URL,
        headers=headers,
        json={"action_id": action_id, "inputs": payload} # Hypothetical structure
    )
    response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx)

    result = response.json()
    print("Action executed successfully:")
    print(json.dumps(result, indent=2))

except requests.exceptions.RequestException as e:
    print(f"Error executing action {action_id}: {e}")
    if e.response is not None:
        print(f"Response status: {e.response.status_code}")
        try:
            print(f"Response body: {e.response.json()}")
        except json.JSONDecodeError:
            print(f"Response body: {e.response.text}")

In this Python snippet, replace YOUR_COGNITIVE_ACTIONS_API_KEY with your actual API key. The payload is structured according to the required input schema for the action. This example demonstrates how to make a POST request to a hypothetical endpoint while handling the response gracefully.

Conclusion

By leveraging the Execute Flux Inpainting action, developers can enhance their applications with advanced image processing capabilities. This pre-built Cognitive Action simplifies the inpainting process while ensuring high quality and speed. Explore various use cases, such as creative content generation, image restoration, or professional editing, and empower your applications with the power of AI-driven image enhancements!

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