ModelsLab Interior Design

AI-powered interior design, room decoration, floor planning, and exterior restoration.

When to Use This Skill

Redesign interior spaces
Decorate rooms with AI assistance
Generate floor plans from images
Transform room styles and aesthetics
Restore or enhance building exteriors
Create design mockups and variations
Visualize renovation ideas

Available Endpoints

Interior Design

POST https://modelslab.com/api/v6/interior/interior

Room Decorator

POST https://modelslab.com/api/v6/interior/room_decorator

Floor Planning

POST https://modelslab.com/api/v6/interior/floor_planning

Exterior Restorer

POST https://modelslab.com/api/v6/interior/exterior_restorer

Scenario Changer

POST https://modelslab.com/api/v6/interior/scenario_changer

Object Removal

POST https://modelslab.com/api/v6/interior/object_removal

Interior Mixer

POST https://modelslab.com/api/v6/interior/interior_mixer

Interior Redesign

import requests

def redesign_interior(room_image, design_prompt, api_key):
    """Redesign an interior space based on a prompt.

    Args:
        room_image: URL of the room photo
        design_prompt: Description of desired design
        api_key: Your ModelsLab API key

    Returns:
        URL of the redesigned interior
    """
    response = requests.post(
        "https://modelslab.com/api/v6/interior/interior",
        json={
            "key": api_key,
            "init_image": room_image,
            "prompt": design_prompt,
            "negative_prompt": "low quality, distorted, unrealistic",
            "num_inference_steps": 31,  # 21, 31, or 41
            "guidance_scale": 7.5,
            "strength": 0.7
        }
    )

    data = response.json()

    if data["status"] == "success":
        return data["output"][0]
    else:
        raise Exception(f"Error: {data.get('message', 'Unknown error')}")

# Usage
redesigned = redesign_interior(
    "https://example.com/living-room.jpg",
    "Modern minimalist living room with Scandinavian furniture, white walls, natural light",
    "your_api_key"
)
print(f"Redesigned room: {redesigned}")

Room Decorator

def decorate_room(room_image, decor_prompt, api_key, specific_object=None):
    """Decorate a room with AI-generated furniture and decor.

    Args:
        room_image: URL of the empty or basic room
        decor_prompt: Description of desired decoration
        specific_object: Specific furniture/decor item that must appear
    """
    payload = {
        "key": api_key,
        "init_image": room_image,
        "prompt": decor_prompt,
        "negative_prompt": "cluttered, low quality, distorted",
        "num_inference_steps": 31,
        "guidance_scale": 7.5,
        "strength": 0.8
    }

    if specific_object:
        payload["specific_object"] = specific_object

    response = requests.post(
        "https://modelslab.com/api/v6/interior/room_decorator",
        json=payload
    )

    data = response.json()

    if data["status"] == "success":
        return data["output"][0]
    else:
        raise Exception(data.get("message"))

# Decorate empty room
decorated = decorate_room(
    "https://example.com/empty-room.jpg",
    "Cozy bedroom with warm lighting, plants, wooden furniture",
    "your_api_key",
    specific_object="king size bed"
)
print(f"Decorated room: {decorated}")

Floor Planning

def generate_floor_plan(room_image, api_key):
    """Generate a floor plan from a room image.

    Args:
        room_image: URL of room photo
        api_key: Your API key

    Returns:
        URL of the generated floor plan
    """
    response = requests.post(
        "https://modelslab.com/api/v6/interior/floor_planning",
        json={
            "key": api_key,
            "init_image": room_image
        }
    )

    data = response.json()

    if data["status"] == "success":
        return data["output"][0]
    else:
        raise Exception(data.get("message"))

# Generate floor plan
floor_plan = generate_floor_plan(
    "https://example.com/room-photo.jpg",
    "your_api_key"
)
print(f"Floor plan: {floor_plan}")

Exterior Restoration

def restore_exterior(building_image, restoration_prompt, api_key):
    """Restore or enhance building exterior.

    Args:
        building_image: URL of building exterior photo
        restoration_prompt: Description of desired restoration
    """
    response = requests.post(
        "https://modelslab.com/api/v6/interior/exterior_restorer",
        json={
            "key": api_key,
            "init_image": building_image,
            "prompt": restoration_prompt,
            "negative_prompt": "damaged, old, worn",
            "num_inference_steps": 31,
            "guidance_scale": 7.5
        }
    )

    data = response.json()

    if data["status"] == "success":
        return data["output"][0]
    else:
        raise Exception(data.get("message"))

# Restore old building
restored = restore_exterior(
    "https://example.com/old-building.jpg",
    "Restored Victorian house with fresh paint, new windows, landscaped garden",
    "your_api_key"
)

Scenario Changer

def change_room_scenario(room_image, new_scenario, api_key):
    """Change the environment scenario of a room.

    Args:
        room_image: URL of room photo
        new_scenario: Description of new scenario/ambiance
    """
    response = requests.post(
        "https://modelslab.com/api/v6/interior/scenario_changer",
        json={
            "key": api_key,
            "init_image": room_image,
            "prompt": new_scenario,
            "num_inference_steps": 31,
            "guidance_scale": 7.5
        }
    )

    data = response.json()

    if data["status"] == "success":
        return data["output"][0]
    else:
        raise Exception(data.get("message"))

# Change from day to evening
evening_room = change_room_scenario(
    "https://example.com/daytime-room.jpg",
    "Evening ambiance with warm lamp lighting, cozy atmosphere",
    "your_api_key"
)

Object Removal

def remove_interior_object(room_image, object_to_remove, api_key):
    """Remove an object from an interior image.

    Args:
        room_image: URL of room photo
        object_to_remove: Description of object to remove
    """
    response = requests.post(
        "https://modelslab.com/api/v6/interior/object_removal",
        json={
            "key": api_key,
            "init_image": room_image,
            "object_name": object_to_remove
        }
    )

    data = response.json()

    if data["status"] == "success":
        return data["output"][0]
    else:
        raise Exception(data.get("message"))

# Remove furniture
cleaned = remove_interior_object(
    "https://example.com/cluttered-room.jpg",
    "old sofa",
    "your_api_key"
)

Interior Mixer

def mix_interior_objects(room_image, object_image, placement_prompt, api_key):
    """Add objects from one image into another room.

    Args:
        room_image: URL of the target room
        object_image: URL of image containing object to add
        placement_prompt: Description of how to place the object
    """
    response = requests.post(
        "https://modelslab.com/api/v6/interior/interior_mixer",
        json={
            "key": api_key,
            "init_image": room_image,
            "object_image": object_image,
            "prompt": placement_prompt,
            "width": 512,
            "height": 512,
            "num_inference_steps": 8,
            "guidance_scale": 7.5
        }
    )

    data = response.json()

    if data["status"] == "success":
        return data["output"][0]
    else:
        raise Exception(data.get("message"))

# Add furniture from another image
mixed = mix_interior_objects(
    "https://example.com/empty-room.jpg",
    "https://example.com/furniture.jpg",
    "Place the chair in the corner near the window",
    "your_api_key"
)

Key Parameters

Parameter	Description	Values
`init_image`	Room/building image	Image URL
`prompt`	Design description	Detailed text
`negative_prompt`	What to avoid	"cluttered, low quality"
`strength`	Transformation strength	0.0-1.0 (0.7 typical)
`num_inference_steps`	Quality level	21, 31, or 41
`guidance_scale`	Prompt adherence	1-20 (7.5 typical)
`specific_object`	Required item	Object name
`object_name`	Object to remove	Description

Best Practices

1. Write Detailed Design Prompts

✗ Bad: "modern room"
✓ Good: "Modern minimalist living room with Scandinavian furniture, white walls, oak floor, large windows, indoor plants"

Include: Style, furniture, colors, lighting, materials, atmosphere

2. Use Appropriate Strength Values

# Subtle changes
strength = 0.5

# Moderate redesign
strength = 0.7

# Complete transformation
strength = 0.9

3. Quality vs Speed

# Fast (21 steps)
num_inference_steps = 21

# Balanced (31 steps) - Recommended
num_inference_steps = 31

# Best quality (41 steps)
num_inference_steps = 41

4. Use High-Quality Input Images

Well-lit room photos
Clear view of the space
Minimal distortion
High resolution preferred

Common Use Cases

Virtual Staging

def stage_empty_room(room_image, style, api_key):
    """Stage an empty room for real estate listing."""
    return decorate_room(
        room_image,
        f"{style} furnished room with modern furniture, well-lit, professional",
        api_key
    )

# Stage for listing
staged = stage_empty_room(
    "https://example.com/empty-apartment.jpg",
    "Modern luxury",
    api_key
)

Design Variations

def create_design_variations(room_image, styles, api_key):
    """Generate multiple design style variations."""
    variations = []

    for style in styles:
        variant = redesign_interior(
            room_image,
            f"{style} interior design style",
            api_key
        )
        variations.append(variant)
        print(f"{style}: {variant}")

    return variations

# Generate variations
designs = create_design_variations(
    "https://example.com/room.jpg",
    ["Modern Scandinavian", "Industrial Loft", "Classic Traditional", "Bohemian"],
    api_key
)

Renovation Planning

def plan_renovation(current_room, desired_style, api_key):
    """Plan room renovation with before/after."""
    before = current_room

    after = redesign_interior(
        before,
        f"Renovated {desired_style} room with updated fixtures and furniture",
        api_key
    )

    return {"before": before, "after": after}

# Plan kitchen renovation
plan = plan_renovation(
    "https://example.com/old-kitchen.jpg",
    "modern farmhouse kitchen",
    api_key
)

Complete Room Makeover

def complete_room_makeover(room_image, api_key):
    """Full room transformation workflow."""

    # Step 1: Remove unwanted items
    cleaned = remove_interior_object(
        room_image,
        "old furniture and clutter",
        api_key
    )

    # Step 2: Redesign space
    redesigned = redesign_interior(
        cleaned,
        "Modern minimalist interior with natural materials",
        api_key
    )

    # Step 3: Add specific decor
    final = decorate_room(
        redesigned,
        "Add cozy lighting and indoor plants",
        api_key,
        specific_object="pendant lamp"
    )

    return final

Before/After Scenarios

# Day to night transformation
day_room = "https://example.com/daytime.jpg"

night = change_room_scenario(
    day_room,
    "Evening ambiance with warm lighting, twilight outside windows",
    api_key
)

# Summer to winter
winter = change_room_scenario(
    day_room,
    "Winter scene with snow outside, cozy fireplace, warm interior",
    api_key
)

Error Handling

try:
    design = redesign_interior(room_image, prompt, api_key)
    print(f"Design created: {design}")
except Exception as e:
    print(f"Design generation failed: {e}")
    # Log error, try different prompt, notify user

Performance Tips

Use Appropriate Inference Steps: 31 steps balances quality and speed
Optimize Prompts: Clear, detailed prompts work best
Batch Similar Requests: Generate multiple variations together
Cache Results: Store generated designs
Monitor Quality: Adjust strength and guidance_scale as needed

Enterprise API

For dedicated resources:

# Enterprise endpoints
url = "https://modelslab.com/api/v1/enterprise/interior/interior"
url = "https://modelslab.com/api/v1/enterprise/interior/room_decorator"

Resources

Interior API Docs: https://docs.modelslab.com/interior-api/overview
Interior Design: https://docs.modelslab.com/interior-api/interior
Room Decorator: https://docs.modelslab.com/interior-api/room-decorator
Floor Planning: https://docs.modelslab.com/interior-api/floor-planning
Get API Key: https://modelslab.com/dashboard

Related Skills

modelslab-image-generation - Generate room reference images
modelslab-image-editing - Additional editing tools
modelslab-sdk-usage - Use official SDKs

modelslab-interior-design

ModelsLab Interior Design

When to Use This Skill

Available Endpoints

Interior Design

Room Decorator

Floor Planning

Exterior Restorer

Scenario Changer

Object Removal

Interior Mixer

Interior Redesign

Room Decorator

Floor Planning

Exterior Restoration

Scenario Changer

Object Removal

Interior Mixer

Key Parameters

Best Practices

1. Write Detailed Design Prompts

2. Use Appropriate Strength Values

3. Quality vs Speed

4. Use High-Quality Input Images

Common Use Cases

Virtual Staging

Design Variations

Renovation Planning

Complete Room Makeover

Before/After Scenarios

Error Handling

Performance Tips

Enterprise API

Resources

Related Skills