image-generation

Transform Empty Rooms into Stunning Interiors with AI

25 Apr 2025
Transform Empty Rooms into Stunning Interiors with AI

In the world of interior design, visualizing a space's potential can be challenging, especially when starting with empty rooms. The Stabledesign Interiordesign service offers a groundbreaking solution through its Cognitive Actions, enabling developers to integrate advanced image generation capabilities directly into their applications. By leveraging deep learning models, this service allows users to transform images of empty rooms into beautifully furnished spaces, guided by detailed text prompts. This innovative approach not only streamlines the design process but also inspires creativity, making it a valuable tool for designers, real estate professionals, and anyone looking to reimagine their living spaces.

Imagine a scenario where a real estate agent showcases properties to clients. With the ability to create stunning, furnished visuals of empty homes in a matter of seconds, they can significantly enhance their presentations. Similarly, interior designers can quickly prototype ideas, providing clients with a clear vision of potential designs without the need for extensive mockups. This service is perfect for anyone needing to visualize design concepts efficiently and effectively.

Before diving into the integration of Stabledesign Interiordesign, ensure you have your Cognitive Actions API key and a basic understanding of making API calls.

Transform Empty Room to Interior Design

The Transform Empty Room to Interior Design action allows users to convert images of empty rooms into fully furnished spaces by applying text-based design prompts. Recognized for its innovative approach, this tool clinched 2nd place in the Generative Interior Design 2024 competition, showcasing its effectiveness and creativity in the realm of interior design.

Input Requirements

To utilize this action, you must provide the following inputs:

  • imageBaseUrl: A URL pointing to the base image of the empty room that you want to furnish.
  • prompt: A vivid and detailed description of the desired design style and elements to be included in the image.
  • seed (optional): An integer for random number generation, enabling repeatable results.
  • strength (optional): A numerical value that indicates how strongly the prompt influences the generated image, ranging from 0 to 1.
  • imageSize (optional): The dimensions for the output image in pixels.
  • guidanceScale (optional): An integer that determines how closely the generated image adheres to the prompt.
  • numberOfSteps (optional): The number of iterative steps taken to refine the image, with higher values producing more detailed images.

Example Input:

{
  "seed": 35853,
  "prompt": "A glamorous master bedroom in Hollywood Regency style, boasting a plush tufted headboard, mirrored furniture reflecting elegance, luxurious fabrics in rich textures, and opulent gold accents for a touch of luxury.",
  "strength": 0.9,
  "imageSize": 640,
  "imageBaseUrl": "https://replicate.delivery/pbxt/L71nWgMUQvH7zKHG3U9YYdfREv1ybOfO1Q5ntak3YmUJizSR/image_0.jpg",
  "guidanceScale": 10,
  "numberOfSteps": 50
}

Expected Output

The output will be a URL linking to the generated image of the furnished room, reflecting the design described in the prompt.

Example Output:

https://assets.cognitiveactions.com/invocations/bff1927e-6a12-4f4d-92f6-e4eececd5369/198a0776-836f-49f4-a69e-846ff5cf10ce.png

Use Cases for this Specific Action

This action is particularly useful in various scenarios:

  • Real Estate Marketing: Agents can showcase potential living spaces by transforming empty listings into beautifully designed homes, attracting more buyers.
  • Interior Design Prototyping: Designers can quickly visualize their ideas, presenting multiple concepts to clients without the need for physical staging.
  • Virtual Staging for E-commerce: Online furniture retailers can demonstrate how their products look in real-life settings, enhancing customer engagement and driving sales.
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 = "9193863e-98ea-4d39-a3bf-3dbcd4cdded0" # Action ID for: Transform Empty Room to Interior Design

# Construct the exact input payload based on the action's requirements
# This example uses the predefined example_input for this action:
payload = {
  "seed": 35853,
  "prompt": "A glamorous master bedroom in Hollywood Regency style, boasting a plush tufted headboard, mirrored furniture reflecting elegance, luxurious fabrics in rich textures, and opulent gold accents for a touch of luxury.",
  "strength": 0.9,
  "imageSize": 640,
  "imageBaseUrl": "https://replicate.delivery/pbxt/L71nWgMUQvH7zKHG3U9YYdfREv1ybOfO1Q5ntak3YmUJizSR/image_0.jpg",
  "guidanceScale": 10,
  "numberOfSteps": 50
}

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

The Stabledesign Interiordesign service provides a powerful tool for transforming empty rooms into stunning interiors, making it easier for developers to create applications that enhance user experience in real estate, design, and e-commerce. By utilizing the deep learning capabilities of this action, users can visualize and explore interior design possibilities like never before. Start integrating this innovative solution into your projects today and unlock the potential of AI-driven interior design!

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