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Match a Reference API

hakankaan/match-reference

Restyle your room to match a reference photo — its palette, materials, and mood, in your space.

Starts from $0.039 /run
2 model optionspublicpublished
OpenAPI

Wrapper Input

Input

External URL of the user's room photo. Its architecture, layout, camera angle, and through-window views are preserved.

External URL of the reference interior photo — the look to match. Only its style transfers (palette, materials, furniture character, lighting mood); its architecture, layout, and camera are ignored.

How literally to chase the reference: precise adapts the look gently to the room, balanced restyles decisively, creative fully transforms toward the reference.

Min: 0.5 - Max: 1

Fine-grained creativity value used only when creativity is precise.

Optional extra guidance for the restyle, e.g. "keep my sofa" or "match the reference's wall color exactly".

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Wrapper Output

Output

Fill in the input form and click submit to see the output
Logs (1 lines)

Pricing

Base ModelPricing ModeEffective Cost
nano-banana-2/editdefaultmegapixel tieredTiered pricing
nano-bananaper output0.039

Match a Reference API

Match a Reference is a image-to-image AI wrapper by hakankaan. On ModelRunner it runs through a REST API or via MCP from any AI assistant with pay-per-use pricing.

POST https://queue.modelrunner.run/hakankaan/match-reference

cURL

# Submit a request to the queue. Input fields go at the top level of the
# body. The optional reserved "metadata" object holds your own flat string
# tags — stored on the request, never sent to the model; filter later with
# GET https://queue.modelrunner.run/requests?metadata=<url-encoded JSON>.
curl -X POST https://queue.modelrunner.run/hakankaan/match-reference \
  -H "Authorization: Key $MRUN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "file_url": "https://example.com/input.jpg",
    "reference_url": "https://example.com/input.jpg",
    "creativity": "balanced",
    "metadata": {
      "project": "my-project"
    }
  }'
# → { "request_id": "...", "status_url": "...", "response_url": "..." }

# Poll status_url until "COMPLETED", then fetch the result
curl "https://queue.modelrunner.run/hakankaan/match-reference/requests/$REQUEST_ID/status" \
  -H "Authorization: Key $MRUN_API_KEY"
curl "https://queue.modelrunner.run/hakankaan/match-reference/requests/$REQUEST_ID" \
  -H "Authorization: Key $MRUN_API_KEY"

JavaScript

import { modelrunner } from "@modelrunner/client";

const result = await modelrunner.subscribe("hakankaan/match-reference", {
  input: {
    "file_url": "https://example.com/input.jpg",
    "reference_url": "https://example.com/input.jpg",
    "creativity": "balanced"
  },
});
console.log(result);

Python

import os
import requests

headers = {"Authorization": f"Key {os.environ['MRUN_API_KEY']}"}

submitted = requests.post(
    "https://queue.modelrunner.run/hakankaan/match-reference",
    headers=headers,
    json={
      "file_url": "https://example.com/input.jpg",
      "reference_url": "https://example.com/input.jpg",
      "creativity": "balanced"
    },
).json()

# Poll submitted["status_url"] until "COMPLETED", then:
result = requests.get(submitted["response_url"], headers=headers).json()

Input parameters

NameTypeRequiredDescription
file_urlstring (uri)yesExternal URL of the user's room photo. Its architecture, layout, camera angle, and through-window views are preserved.
reference_urlstring (uri)yesExternal URL of the reference interior photo — the look to match. Only its style transfers (palette, materials, furniture character, lighting mood); its architecture, layout, and camera are ignored.
creativityenumyesHow literally to chase the reference: precise adapts the look gently to the room, balanced restyles decisively, creative fully transforms toward the reference. Default: "balanced".
creativity_levelnumbernoFine-grained creativity value used only when creativity is precise. Default: 0.7.
promptstringnoOptional extra guidance for the restyle, e.g. "keep my sofa" or "match the reference's wall color exactly".

Machine-readable: OpenAPI schema · llms.txt

Use Match a Reference from Claude & Cursor (MCP)

Point Claude Code, Claude Desktop, Cursor, or any MCP client at the ModelRunner MCP server and Match a Reference becomes a tool your assistant can call directly — it authorizes via OAuth (no API key in config) and runs this wrapper with the run_model tool using the endpoint hakankaan/match-reference.

MCP client config (Claude Desktop, Cursor)

{
  "mcpServers": {
    "modelrunner": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.modelrunner.run/mcp"]
    }
  }
}

Claude Code

claude mcp add --transport http modelrunner https://mcp.modelrunner.run/mcp

Then ask your assistant, for example: “Run hakankaan/match-reference on ModelRunner to generate image”. MCP setup guide.

Wrapper Details

Model Details

**Restyle your room to match a reference photo — the reference's palette, materials, furniture character, and lighting mood, recreated inside your room's own architecture.**

Give it two photos: your room (`file_url`) and an interior whose look you love (`reference_url`) — a Pinterest find, a hotel room, a showroom shot. The result is your room, restyled: its layout, walls, windows, doors, camera angle, and through-window views stay exactly as photographed, while the reference's aesthetic takes over the furnishings and finishes. This is a style and mood transfer, not object insertion — nothing is pasted 1:1 from the reference; its pieces are reinterpreted to fit your room's scale and function.

## Inputs

- `file_url` — your room photo. Architecture, layout, and camera are locked. - `reference_url` — the look to match. Only its style transfers: color palette, wall and floor finishes, materials, furniture style and character, lighting mood, decor density. - `creativity` — how literally to chase the reference: `precise` adapts the look gently (your furniture arrangement stays recognizable), `balanced` restyles decisively, `creative` fully transforms toward the reference. - `creativity_level` — fine-grained strength from 0.5 (closest to your room) to 1.0; used only when `creativity` is `precise`. - `prompt` — optional extra guidance, e.g. `keep my sofa`.

## How to use

1. Shoot the room well lit and wide; pick a reference whose style reads clearly in a single image. 2. Start with `creativity: balanced`. Result drifting too far from your room? Switch to `precise` and lower `creativity_level` toward 0.5. Clinging too hard to your current furniture? Go `creative`. 3. Pin details with `prompt` (`keep my sofa`, `use the reference's wall color exactly`). 4. Restyling several rooms to one look? Pass the SAME `reference_url` to every run — never a previous run's output — so the set stays coherent.