modelslab-interior-design

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ModelsLab Interior Design

ModelsLab 室内设计

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

基于AI的室内设计、房间装饰、平面规划与建筑外观修复。

When to Use This Skill

适用场景

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

重新设计室内空间
借助AI辅助装饰房间
通过图片生成平面图
转换房间风格与美学效果
修复或优化建筑外观
创建设计模型与变体
可视化翻新想法

Available Endpoints

可用接口

Interior Design

室内设计

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

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

Room Decorator

房间装饰

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

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

Floor Planning

平面规划

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

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

Exterior Restorer

外观修复

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

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

Scenario Changer

场景转换

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

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

Object Removal

物体移除

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

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

Interior Mixer

室内融合

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

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

Interior Redesign

室内重新设计

python

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')}")

python

import requests

def redesign_interior(room_image, design_prompt, api_key):
    """根据提示词重新设计室内空间。

    参数:
        room_image: 房间照片的URL
        design_prompt: 期望设计的描述文本
        api_key: 你的ModelsLab API密钥

    返回:
        重新设计后的室内空间图片URL
    """
    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

使用示例

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}")

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Room Decorator

房间装饰

python

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"))

python

def decorate_room(room_image, decor_prompt, api_key, specific_object=None):
    """借助AI生成的家具与装饰元素美化房间。

    参数:
        room_image: 空房间或基础房间的图片URL
        decor_prompt: 期望装饰效果的描述文本
        specific_object: 必须包含的特定家具/装饰物品
    """
    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

装饰空房间示例

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}")

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Floor Planning

平面规划

python

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"))

python

def generate_floor_plan(room_image, api_key):
    """通过房间图片生成平面图。

    参数:
        room_image: 房间照片的URL
        api_key: 你的API密钥

    返回:
        生成的平面图图片URL
    """
    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

生成平面图示例

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

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

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Exterior Restoration

外观修复

python

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"))

python

def restore_exterior(building_image, restoration_prompt, api_key):
    """修复或优化建筑外观。

    参数:
        building_image: 建筑外观照片的URL
        restoration_prompt: 期望修复效果的描述文本
    """
    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

修复老旧建筑示例

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

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

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Scenario Changer

场景转换

python

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"))

python

def change_room_scenario(room_image, new_scenario, api_key):
    """转换房间的环境场景。

    参数:
        room_image: 房间照片的URL
        new_scenario: 新场景/氛围的描述文本
    """
    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

从白天转换为夜晚场景示例

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

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

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Object Removal

物体移除

python

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"))

python

def remove_interior_object(room_image, object_to_remove, api_key):
    """从室内图片中移除指定物体。

    参数:
        room_image: 房间照片的URL
        object_to_remove: 待移除物体的描述文本
    """
    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

移除家具示例

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

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

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Interior Mixer

室内融合

python

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"))

python

def mix_interior_objects(room_image, object_image, placement_prompt, api_key):
    """将其他图片中的物体添加到目标房间中。

    参数:
        room_image: 目标房间的图片URL
        object_image: 包含待添加物体的图片URL
        placement_prompt: 物体放置方式的描述文本
    """
    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

将其他图片中的家具添加到空房间示例

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" )

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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" )

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Key Parameters

关键参数

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

参数	说明	取值
`init_image`	房间/建筑图片	图片URL
`prompt`	设计描述文本	详细描述语句
`negative_prompt`	需避免的效果	"cluttered, low quality"等
`strength`	转换强度	0.0-1.0（典型值0.7）
`num_inference_steps`	生成质量等级	21、31或41
`guidance_scale`	提示词贴合度	1-20（典型值7.5）
`specific_object`	必须包含的物品	物品名称
`object_name`	待移除的物体	物体描述

Best Practices

最佳实践

1. Write Detailed Design Prompts

1. 撰写详细的设计提示词

✗ 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

✗ 不佳示例: "modern room"
✓ 优质示例: "Modern minimalist living room with Scandinavian furniture, white walls, oak floor, large windows, indoor plants"

需包含：风格、家具、色彩、光线、材质、氛围

2. Use Appropriate Strength Values

2. 使用合适的转换强度值

python

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Subtle changes

细微调整

strength = 0.5

Moderate redesign

中度重新设计

strength = 0.7

Complete transformation

彻底转换

strength = 0.9

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strength = 0.9

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3. Quality vs Speed

3. 质量与速度的平衡

python

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python

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Fast (21 steps)

快速生成（21步）

num_inference_steps = 21

Balanced (31 steps) - Recommended

平衡方案（31步）- 推荐

num_inference_steps = 31

Best quality (41 steps)

最佳质量（41步）

num_inference_steps = 41

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num_inference_steps = 41

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4. Use High-Quality Input Images

4. 使用高质量输入图片

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

光线充足的房间照片
空间视野清晰
变形程度低
优先选择高分辨率图片

Common Use Cases

常见使用场景

Virtual Staging

虚拟样板间

python

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
    )

python

def stage_empty_room(room_image, style, api_key):
    """为房产挂牌打造空房间虚拟样板间。"""
    return decorate_room(
        room_image,
        f"{style} furnished room with modern furniture, well-lit, professional",
        api_key
    )

Stage for listing

样板间打造示例

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

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

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Design Variations

设计风格变体

python

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

python

def create_design_variations(room_image, styles, api_key):
    """生成多种设计风格变体。"""
    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

生成多种风格变体示例

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

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

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Renovation Planning

翻新规划

python

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}

python

def plan_renovation(current_room, desired_style, api_key):
    """通过前后对比规划房间翻新。"""
    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

厨房翻新规划示例

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

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

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Complete Room Makeover

完整房间改造

python

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

python

def complete_room_makeover(room_image, api_key):
    """完整的房间转换工作流。"""

    # 步骤1：移除不需要的物品
    cleaned = remove_interior_object(
        room_image,
        "old furniture and clutter",
        api_key
    )

    # 步骤2：重新设计空间
    redesigned = redesign_interior(
        cleaned,
        "Modern minimalist interior with natural materials",
        api_key
    )

    # 步骤3：添加特定装饰
    final = decorate_room(
        redesigned,
        "Add cozy lighting and indoor plants",
        api_key,
        specific_object="pendant lamp"
    )

    return final

Before/After Scenarios

前后场景对比

python

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Day to night transformation

白天转夜晚场景

day_room = "https://example.com/daytime.jpg"

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

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

夏季转冬季场景

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

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

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Error Handling

错误处理

python

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

python

try:
    design = redesign_interior(room_image, prompt, api_key)
    print(f"Design created: {design}")
except Exception as e:
    print(f"Design generation failed: {e}")
    # 记录错误、尝试更换提示词、通知用户

Performance Tips

性能优化建议

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

选择合适的推理步数：31步可平衡质量与速度
优化提示词：清晰、详细的提示词效果最佳
批量处理相似请求：一次性生成多个风格变体
缓存结果：存储已生成的设计方案
监控生成质量：根据需要调整转换强度与提示词贴合度

Enterprise API

企业版API

For dedicated resources:

python

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如需专属资源：

python

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Enterprise endpoints

企业版接口

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

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

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