image-generation

Create Stunning Images with Ihor2's Inpainting Action

25 Apr 2025
Create Stunning Images with Ihor2's Inpainting Action

In the realm of digital creativity, generating high-quality images can often be a time-consuming and complex task. With Ihor2's powerful Cognitive Actions, specifically the "Generate Image with Inpainting" action, developers can effortlessly create stunning visuals using advanced image-to-image conversion techniques. This action not only simplifies the image generation process but also offers flexibility in terms of dimensions, aspect ratios, and output formats. By leveraging optimized models for speed—namely 'dev' and 'schnell'—users can achieve rapid results without compromising on quality.

Whether you're looking to create unique artwork, develop engaging marketing materials, or enhance user experiences in applications, this action provides a robust solution. Imagine generating an outdoor portrait or creating tailored images for specific themes or campaigns—this action opens up a world of possibilities for developers and designers alike.

Generate Image with Inpainting

The "Generate Image with Inpainting" action is designed to produce high-quality images through the inpainting technique, allowing for creative modifications or entirely new creations based on existing images. This action is particularly useful when you want to replace parts of an image or generate images from scratch using detailed prompts.

Input Requirements

To utilize this action, you need to provide a JSON object that includes the following required fields:

  • prompt: A textual description guiding the image generation. Optional fields include:
  • image: An existing image for inpainting.
  • mask: A mask image that specifies which parts of the input should be modified.
  • width and height: Dimensions for the generated image, applicable when using a custom aspect ratio.
  • modelType: Choose between 'dev' for detailed images or 'schnell' for faster generation.
  • numOutputs: Specify how many variations of the image you want to generate (up to 4).

Here’s an example of the input schema:

{
  "prompt": "Create an outdoor portrait of Ihor, a young man with a calm and thoughtful demeanor...",
  "loraScale": 1,
  "modelType": "dev",
  "numOutputs": 4,
  "imageFormat": "webp",
  "guidanceScale": 3.5,
  "outputQuality": 80,
  "extraLoraScale": 0.8,
  "promptStrength": 0.8,
  "imageAspectRatio": "1:1",
  "numInferenceSteps": 28
}

Expected Output

The output will be a list of generated image URLs in the specified format, such as WebP, JPG, or PNG. Here’s what you can expect:

  • A collection of image URLs, each representing a unique output based on your input prompt.

Example output:

[
  "https://assets.cognitiveactions.com/invocations/.../image1.webp",
  "https://assets.cognitiveactions.com/invocations/.../image2.webp",
  "https://assets.cognitiveactions.com/invocations/.../image3.webp",
  "https://assets.cognitiveactions.com/invocations/.../image4.webp"
]

Use Cases for this Specific Action

  • Creative Art Generation: Artists and designers can utilize this action to create unique artwork based on specific themes or concepts.
  • Marketing and Advertising: Generate customized images for campaigns or social media posts that align with brand aesthetics.
  • Game Development: Create unique character designs or backgrounds by modifying existing images or generating new ones based on detailed prompts.
  • Content Creation: Bloggers and content creators can produce eye-catching visuals to enhance their articles or presentations.
import requests
import json

# Replace with your actual Cognitive Actions API key and endpoint
# Ensure your environment securely handles the API key
COGNITIVE_ACTIONS_API_KEY = "YOUR_COGNITIVE_ACTIONS_API_KEY"
# This endpoint URL is hypothetical and should be documented for users
COGNITIVE_ACTIONS_EXECUTE_URL = "https://api.cognitiveactions.com/actions/execute"

action_id = "bbf8b5ce-d09f-4b04-b850-3a72ab1f0caa" # Action ID for: Generate Image with Inpainting

# Construct the exact input payload based on the action's requirements
# This example uses the predefined example_input for this action:
payload = {
  "prompt": "Create an outdoor portrait of Ihor, a young man with a calm and thoughtful demeanor, standing against the backdrop of a softly blurred cityscape during sunset. He is wearing a light shirt. Ihor’s expression is one of quiet contemplation, looking slightly off to the side as if he’s reflecting on something important. The warm, golden light of the setting sun softly illuminates his face, highlighting his features and giving a sense of calm confidence. The background should be slightly out of focus, with hints of modern buildings and a softly colored sky that fades from warm to cool tones, capturing the transition from day to evening.",
  "loraScale": 1,
  "modelType": "dev",
  "numOutputs": 4,
  "imageFormat": "webp",
  "guidanceScale": 3.5,
  "outputQuality": 80,
  "extraLoraScale": 0.8,
  "promptStrength": 0.8,
  "imageAspectRatio": "1:1",
  "numInferenceSteps": 28
}

headers = {
    "Authorization": f"Bearer {COGNITIVE_ACTIONS_API_KEY}",
    "Content-Type": "application/json",
    # Add any other required headers for the Cognitive Actions API
}

# Prepare the request body for the hypothetical execution endpoint
request_body = {
    "action_id": action_id,
    "inputs": payload
}

print(f"--- Calling Cognitive Action: {action.name or action_id} ---")
print(f"Endpoint: {COGNITIVE_ACTIONS_EXECUTE_URL}")
print(f"Action ID: {action_id}")
print("Payload being sent:")
print(json.dumps(request_body, indent=2))
print("------------------------------------------------")

try:
    response = requests.post(
        COGNITIVE_ACTIONS_EXECUTE_URL,
        headers=headers,
        json=request_body
    )
    response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx)

    result = response.json()
    print("Action executed successfully. Result:")
    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 (non-JSON): {e.response.text}")
    print("------------------------------------------------")

Conclusion

Ihor2's "Generate Image with Inpainting" action empowers developers to create high-quality images rapidly and efficiently. With the ability to specify detailed prompts and control various parameters, this action is invaluable for anyone looking to enhance their visual content. Whether you're in creative design, marketing, or content creation, leveraging this action can significantly streamline your workflow and elevate your projects.

As a next step, consider integrating this action into your applications to explore the endless possibilities of automated image generation.

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