Generate Stunning Images with Highland SDXL Fine-Tune Cognitive Actions

22 Apr 2025
Generate Stunning Images with Highland SDXL Fine-Tune Cognitive Actions

In today's digital landscape, the ability to create visually appealing images programmatically has become a vital tool for developers. The hudsongraeme/highland Cognitive Actions enable you to harness the power of image generation through advanced models, specifically designed to enhance and refine images using customizable prompts and sophisticated algorithms. This blog post will guide you through the integration of the "Generate Image with Highland SDXL Fine-Tune" action, allowing you to create stunning images with precision and creativity.

Prerequisites

To get started with the Cognitive Actions, you'll need:

  • An API key for the Cognitive Actions platform, which will allow you to authenticate your requests.
  • Basic familiarity with JSON payloads and HTTP requests.

Authentication typically involves including your API key in the request headers. This ensures that only authorized users can access the image generation capabilities.

Cognitive Actions Overview

Generate Image with Highland SDXL Fine-Tune

The Generate Image with Highland SDXL Fine-Tune action allows you to create images using the Tesla Model 3 Highland SDXL model, which includes enhanced inpainting and img2img processing. This action supports a range of customizable parameters to refine the quality and style of the generated images.

Input

The required input fields for this action are structured in a JSON format as follows:

{
  "image": "https://example.com/image.jpg",
  "width": 1024,
  "height": 1024,
  "prompt": "A photo of dark red Tesla Model 3 highland parked near autumn trees, bright",
  "loraScale": 0.6,
  "scheduler": "K_EULER",
  "numOutputs": 1,
  "refineStyle": "no_refiner",
  "guidanceScale": 7.5,
  "highNoiseFrac": 0.8,
  "applyWatermark": true,
  "negativePrompt": "",
  "promptStrength": 0.9,
  "numInferenceSteps": 50
}
  • image (string, required): URI of the input image for img2img or inpaint mode.
  • width (integer, optional): Width of the output image in pixels, defaults to 1024.
  • height (integer, optional): Height of the output image in pixels, defaults to 1024.
  • prompt (string, required): Describes the desired content of the image.
  • loraScale (number, optional): Scale factor for applying LoRA, range 0 to 1.
  • scheduler (string, optional): Choice of scheduling algorithm, defaults to K_EULER.
  • numOutputs (integer, optional): Number of images to output, defaults to 1.
  • refineStyle (string, optional): Method for refining the image, defaults to no_refiner.
  • guidanceScale (number, optional): Scale for classifier-free guidance, defaults to 7.5.
  • highNoiseFrac (number, optional): Fraction of noise for expert ensemble refiner, defaults to 0.8.
  • applyWatermark (boolean, optional): Adds a watermark for identifying generated images, defaults to true.
  • negativePrompt (string, optional): Additional prompt to specify content to avoid.
  • promptStrength (number, optional): Impact of the prompt on img2img/inpaint processes, defaults to 0.8.
  • numInferenceSteps (integer, optional): Total number of iterations for noise reduction steps, defaults to 50.

Output

The action typically returns a JSON array containing the URIs of the generated images. For example:

[
  "https://assets.cognitiveactions.com/invocations/00a195c0-0347-4700-9c4a-6a9e05749bad/f5b88f68-bbfe-43b2-8294-6b131d5e7d9c.png"
]

This output provides direct links to the images created by the action, allowing seamless integration into various applications.

Conceptual Usage Example (Python)

Here’s how you might call the Cognitive Actions execution endpoint using Python:

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 = "c14c62cf-d7da-4a63-8b61-235064472038" # Action ID for Generate Image with Highland SDXL Fine-Tune

# Construct the input payload based on the action's requirements
payload = {
    "image": "https://replicate.delivery/pbxt/Jj0ek2oFHnDiI8JIcbonXLnIavOzcIknC0kyQcUe78nlLEyR/empty-autumn-road-with-trees-in-a-row-on-the-edges-photo.jpg",
    "width": 1024,
    "height": 1024,
    "prompt": "A photo of dark red Tesla Model 3 highland parked near autumn trees, bright",
    "loraScale": 0.6,
    "scheduler": "K_EULER",
    "numOutputs": 1,
    "refineStyle": "no_refiner",
    "guidanceScale": 7.5,
    "highNoiseFrac": 0.8,
    "applyWatermark": true,
    "negativePrompt": "",
    "promptStrength": 0.9,
    "numInferenceSteps": 50
}

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 example, replace "YOUR_COGNITIVE_ACTIONS_API_KEY" with your actual API key. The payload variable is structured according to the action's requirements, ensuring that you provide all necessary inputs. The response is processed to display the resulting images.

Conclusion

The hudsongraeme/highland Cognitive Action for generating images opens up a world of possibilities for developers looking to create unique visual content. By leveraging customizable prompts and advanced algorithms, you can produce high-quality images tailored to your specific needs. As you integrate this action into your applications, consider exploring additional use cases such as marketing materials, creative designs, or even personalized content for users. Happy coding!

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