# PATINA · Material · Extract API

> Udtrækker en fliselig tekstur med PBR-kort fra et kildebillede, styret af en prompt, der navngiver overfladen

Modtager et inputbillede plus en prompt, der beskriver, hvilken overflade der skal udtrækkes, og returnerer en fliselig tekstur sammen med forudsagte PBR-kort. `maps` vælger, hvilke af basecolor, normal, roughness, metalness og height der skal produceres. Indstillingerne omfatter `tiling_mode`, `strength` fra 0 til 1, `upscale_factor` på 0, 2 eller 4 samt 1 til 4 outputs.

- Model id: `patina/material/extract`
- Made by: Open model
- Category: Image Editing
- Output: image
- Price per run: from $0.17 / run (cheapest run $0.17 (170 API credits))
- Run: `POST https://api.doitong.com/v1/run/patina/material/extract`
- Quote: `POST https://api.doitong.com/v1/quote/patina/material/extract`
- Docs page: https://doitong.com/da/developers/models/patina/material/extract

## Pricing

Price: **from $0.17 / run** (the lowest tier; the quote prices your exact input). Price per run: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $0.17 = 170 API credits (1 run × $0.17).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/patina/material/extract` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | Beskrivelse af den ønskede tekstur, der skal udtrækkes fra billedet. |
| `image_size` |  | object {width, height} \| enum (string) | no | `square_hd` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Pixeldimensioner for den resulterende tekstur. |
| `num_inference_steps` |  | integer | no | `8` | 1 – 8 | Antal denoising-trin, der bruges til at generere teksturer. |
| `seed` |  | integer \| null | no |  |  | Tilfældig seed, der gør genereringen reproducerbar. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Antal teksturbilleder, der skal oprettes. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Aktiverer LLM-baseret promptudvidelse for at tilføje detaljer. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Aktiverer sikkerhedstjek af genererede billeder. |
| `tiling_mode` |  | enum (string) | no | `both` | `both`, `horizontal`, `vertical` | Fliseretning: 'both' for fliselægning i alle retninger, 'horizontal' eller 'vertical'. |
| `tile_size` |  | integer | no | `128` | 32 – 256 | Flisestørrelse i latent space, hvor 64 repræsenterer 512px, og 128 repræsenterer 1024px. På hver flisebelagt akse sætter det genererede billedes dimension en automatisk øvre grænse. |
| `tile_stride` |  | integer | no | `64` | 16 – 128 | Angiv afstanden mellem fliser i latent space; et automatisk loft forhindrer, at den overstiger halvdelen af den effektive flisestørrelse. |
| `image_url` | `image` | string (image URL) | yes |  |  | Kildebilledets URL til teksturudtræk. |
| `strength` |  | number | no | `0.6` | ≤ 1, > 0 | Transformationsstyrke, der kun anvendes på et billede leveret via image_url; ellers ubrugt. |
| `maps` |  | array of enum (string) | no | `["basecolor","normal","roughness","metalness","height"]` |  | PBR-kort valgt til prædiktion, hvor alle fem vælges som standard. Hvis ingen vælges, springes PBR-estimering helt over. |
| `upscale_factor` |  | enum (integer) | no | `0` | `0`, `2`, `4` | SeedVR-faktor for problemfri opskalering, der påvirker prædikterede PBR-kort, men lader basisteksturen beholde sin oprindelige opløsning. Vælg 2 for dobbelt opløsning, 4 for firedobbelt opløsning eller 0 for at deaktivere opskalering. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Billedfilformat for outputteksturer og PBR-kort. |

File parameters (`image`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/patina/material/extract?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/patina/material/extract?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/patina/material/extract", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.com/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "patina/material/extract",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "patina/material/extract",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 170,
    "usd": "0.17",
    "charged": 170,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "images": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200,
        "width": 1024,
        "height": 768
      }
    ],
    "seed": 42,
    "prompt": "string",
    "timings": {}
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of any | Outputbilleder inkluderer PBR-materialekort prædikteret af PATINA sammen med fliselægbare teksturer genereret af z-image. |
| `seed` | integer | Seed anvendt ved generering af teksturer. |
| `prompt` | string | Prompt til teksturgenerering, inklusive eventuel anvendt udvidelse. |
| `timings` | object | Tidsopdeling for hele processen i sekunder. |

## Related models

- [PATINA · Material](https://doitong.com/developers/models/patina/material.md) (`patina/material`): from $0.08 / run
- [PATINA](https://doitong.com/developers/models/patina.md) (`patina`): from $0.0225 / run of input image
- [FLUX.1 Kontext \[pro\]](https://doitong.com/developers/models/flux-pro/kontext.md) (`flux-pro/kontext`): $0.04 / image
- [GPT Image 2.5 Edit](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/edit.md) (`openai/gpt-image-2.5/flare/edit`): from $0.12 / image
- [Nano Banana 2 Edit](https://doitong.com/developers/models/nano-banana-2/edit.md) (`nano-banana-2/edit`): from $0.06 / image
- [Nano Banana Pro Edit](https://doitong.com/developers/models/nano-banana-pro/edit.md) (`nano-banana-pro/edit`): from $0.15 / image
- [Qwen Image 3 Edit](https://doitong.com/developers/models/alibaba/qwen-image-3/edit.md) (`alibaba/qwen-image-3/edit`): from $0.04 / image
- [Seedream 5.0 Pro Edit](https://doitong.com/developers/models/bytedance/seedream/v5/pro/edit.md) (`bytedance/seedream/v5/pro/edit`): from $0.0675 / run of output image

## Links

- HTML page: https://doitong.com/developers/models/patina/material/extract
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=patina/material/extract
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/patina/material/extract