AI Floor Plan to 3D Render: Using Nano Banana 2's Image-to-Image Mode for Space Visualization

If you're a developer or business looking to transform simple floor plan sketches into immersive 3D perspective renders quickly and affordably, this guide is for you. Using the Nano Banana 2 image-to-image AI model available via WisGate's API, you can send floor plan images combined with descriptive text prompts, and receive polished 3D renderings in as little as 20 seconds. This workflow unlocks a cost-effective path to visualize spaces without needing expensive design software or manual 3D modeling.

Before we dive in, why not try submitting your own floor plan sketch through WisGate’s API? Experience firsthand how Nano Banana 2 interprets and renders your input into a detailed 3D image. Let’s get started!

Introduction to Image-to-Image AI Models for Space Visualization

Image-to-image AI models transform one visual representation into another, preserving context while enhancing or changing the output style or perspective. For space visualization, this means converting a 2D floor plan — which is often a schematic or simple sketch — into a 3D perspective render that shows volume, depth, and spatial relationships realistically.

Nano Banana 2 is a model tailored for such image translation tasks. By providing it with an input image and a text description, it generates a refined, context-aware output. This approach allows developers and designers to bypass complex 3D modeling steps and quickly produce visualizations useful for architecture, real estate, interior design, and urban planning.

Using image-to-image AI for space visualization offers clear advantages: faster turnaround, easier iterative design, and accessibility to users without advanced 3D software skills. When combined with WisGate’s streamlined API platform, integrating this capability into your workflow becomes straightforward and cost-effective.

Preparing Your Floor Plan Input for Nano Banana 2

To get the best results with Nano Banana 2, prepare your input carefully. The API requires the floor plan image to be embedded as base64-encoded inline_data in the JSON payload. This can be a hand-drawn sketch scanned or photographed or a digital floor plan image.

Ensure your image is clear, well-lit, and cropped to focus on the plan. Convert the image file into base64 string format—this encoding allows the image to be transmitted safely within the JSON request body.

Alongside the image, craft a concise text prompt describing the desired output. For example: "3D perspective render of a modern two-bedroom apartment with furniture and lighting." The prompt guides Nano Banana 2 to generate details that complement your floor plan.

By combining inline_data input with descriptive text, you direct the model accurately toward spatial and stylistic preferences. This dual input method distinguishes WisGate’s image-to-image approach, making your results uniquely tailored.

Step-by-Step API Workflow Using WisGate’s Nano Banana 2 Model

Below is how you would construct a request to WisGate’s API endpoint for generating a 3D render from your floor plan sketch.

Prepare your API key ($WISDOM_GATE_KEY).
Convert your floor plan image to a base64 string.
Write your descriptive prompt explaining the desired 3D render.
Put these into the JSON payload, specifying inlineData for the image, text prompt, and generation configurations like resolution.
Send a POST request to WisGate’s API endpoint.
Decode the base64 image returned in the response.

Here’s an example cURL command illustrating this process:

curl -s -X POST \
  "https://wisgate.ai/v1beta/models/gemini-3-pro-image-preview:generateContent" \
  -H "x-goog-api-key: $WISDOM_GATE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [{
        "text": "3D perspective render of a modern two-bedroom apartment interior with furniture and natural light.",
        "inlineData": {
          "mimeType": "image/png",
          "data": "<base64-encoded-floorplan-image>"
        }
      }]
    }],
    "generationConfig": {
      "responseModalities": ["IMAGE"],
      "imageConfig": {
        "aspectRatio": "16:9",
        "imageSize": "2K"
      }
    }
  }' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 --decode > floorplan_render.png

Replace <base64-encoded-floorplan-image> with your actual base64 string. The response includes a base64-encoded image inside the JSON, decoded here and saved as "floorplan_render.png." This image is your 3D render output.

This example highlights how WisGate consolidates image input and text prompts into a single, easy API call. Working with known standards like base64 inline_data keeps integration smooth for developers.

Configuring Generation Parameters: Resolution, Aspect Ratio, and Output Formats

The API gives you options to specify image resolution, aspect ratio, and output format directly in the request. Available image sizes range from 0.5K up to 4K, all delivered as base64-encoded PNG files. This flexibility lets you choose file size and quality based on your project needs.

For example, setting "imageSize" to "2K" yields 2048x2048 pixel images, suitable for presentations or web display. Opting for "4K" produces higher-resolution results appropriate for print or detailed visualization. The "aspectRatio" parameter ensures your render fits common screen or print formats, such as 16:9 or 1:1.

WisGate’s infrastructure processes these images consistently within about 20 seconds regardless of resolution—a key benefit compared to slower or inconsistent speeds from alternative providers.

Handling API Responses and Decoding Base64 Outputs

The API responds with a JSON structure containing your generated content, including an embedded base64 image string. To access your rendered 3D image, extract the inlineData field from the response and decode the base64 back into a binary image file.

You can script this extraction and decoding in many languages using standard base64 libraries. The cURL example above demonstrates decoding with command-line tools. For developers integrating this into applications, keep the following in mind:

Inspect the JSON response for the .candidates[0].content.parts array.
Locate the object containing .inlineData.data, which holds the base64 image.
Decode and save the output as a PNG file.

Proper response handling ensures the 3D renders are usable in your apps or workflows with minimal manual effort.

Pricing and Performance: Comparing WisGate and Official Model Rates

Knowing your costs upfront is vital. WisGate charges 0.058 USD per image generation call using Nano Banana 2, compared to the official model rate of 0.068 USD. This 15% cost saving adds up significantly when generating multiple renders for development or business use.

Importantly, WisGate maintains output quality equal to the official provider. Alongside pricing, WisGate guarantees consistent response times of approximately 20 seconds from half-kilopixel (0.5K) resolutions up to 4K outputs.

This combination of stable latency and lower cost makes WisGate a practical choice for developers and companies building AI-enhanced space visualization tools.

Here’s a simple pricing comparison table:

Provider	Price Per Image	Typical Response Time
WisGate AI	$0.058	~20 seconds
Official Model	$0.068	Variable

Use Cases and Benefits of 3D Space Visualization via AI Models

Developers and businesses benefit from integrating AI image-to-image models like Nano Banana 2 in multiple ways:

Rapid Prototyping: Quickly visualize architectural layouts or interior designs without manual 3D modeling.
Real Estate Marketing: Enhance floor plans with realistic 3D renders to attract buyers.
Urban Planning: Model spatial relationships dynamically from plans.
Interior Design: Preview furniture placement and lighting effects based on layouts.

Because WisGate’s API workflow accepts inline_data and prompts, you can customize outputs tightly to your project or client demands. Flexibility to set resolution and aspect ratios means renders suit both digital and print deliverables.

Low, predictable costs combined with reliable ~20 second response times enable integration into production pipelines, web apps, or internal tools that require scale without ballooning expenses.

Conclusion and Next Steps

Generating 3D perspective renders from floor plan sketches is straightforward using WisGate’s API with the Nano Banana 2 image-to-image model. The hands-on example here showed how to prepare your input image and prompt, call the API with base64 inline_data, and decode the output.

Key advantages include WisGate’s competitive pricing at 0.058 USD per image, stable sub-20 second response times, and flexible resolution and formatting options. These strengths help developers build faster and spend less while producing professional 3D visualizations.

Ready to explore? Visit https://wisgate.ai/studio/image to experiment interactively with Nano Banana 2 and other models. When you’re ready to integrate, sign up and start submitting your own floor plan images via the WisGate API for detailed 3D renders at scale.

This article focused strictly on WisGate's AI API capabilities and omitted any association with hardware, IoT, or gateways, keeping the spotlight on creating value through advanced AI image generation technology.

Thank you for reading. Start visualizing your spaces today with Nano Banana 2 via WisGate.