# PATINA · Material · Extract API

> Wydobywa kafelkowalną teksturę z mapami PBR z obrazu źródłowego na podstawie promptu określającego powierzchnię

Przyjmuje obraz wejściowy oraz prompt opisujący powierzchnię do wydobycia i zwraca kafelkowalną teksturę wraz z przewidywanymi mapami PBR. `maps` wybiera mapy basecolor, normal, roughness, metalness i height do wygenerowania. Opcje obejmują `tiling_mode`, `strength` od 0 do 1, `upscale_factor` o wartości 0, 2 lub 4 oraz od 1 do 4 wyników.

- 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/pl/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 |  |  | Opis tekstury do wyodrębnienia z obrazu. |
| `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` | Wymiary pikselowe wynikowej tekstury. |
| `num_inference_steps` |  | integer | no | `8` | 1 – 8 | Liczba kroków odszumiania użytych do generowania tekstur. |
| `seed` |  | integer \| null | no |  |  | Losowe ziarno zapewniające powtarzalność generowania. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Liczba obrazów tekstur do utworzenia. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Włącza rozszerzanie promptu oparte na LLM w celu dodania szczegółów. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Włącza sprawdzanie bezpieczeństwa generowanych obrazów. |
| `tiling_mode` |  | enum (string) | no | `both` | `both`, `horizontal`, `vertical` | Kierunek kafelkowania: 'both' dla kafelkowania wielokierunkowego, 'horizontal' lub 'vertical'. |
| `tile_size` |  | integer | no | `128` | 32 – 256 | Rozmiar kafelka w przestrzeni utajonej, gdzie 64 oznacza 512px, a 128 oznacza 1024px. Na każdej osi kafelkowania wymiar generowanego obrazu wyznacza automatyczne ograniczenie górne. |
| `tile_stride` |  | integer | no | `64` | 16 – 128 | Ustaw odstęp między kafelkami w przestrzeni utajonej; automatyczny limit zapobiega przekroczeniu połowy efektywnego rozmiaru kafelka. |
| `image_url` | `image` | string (image URL) | yes |  |  | Adres URL obrazu źródłowego do wyodrębniania tekstury. |
| `strength` |  | number | no | `0.6` | ≤ 1, > 0 | Siła transformacji stosowana wyłącznie do obrazu dostarczonego przez image_url; w przeciwnym razie nieużywana. |
| `maps` |  | array of enum (string) | no | `["basecolor","normal","roughness","metalness","height"]` |  | Mapy PBR wybrane do predykcji; domyślnie wybrane są wszystkie pięć. Brak wyboru całkowicie pomija estymację PBR. |
| `upscale_factor` |  | enum (integer) | no | `0` | `0`, `2`, `4` | Współczynnik bezszwowego powiększania SeedVR wpływający na przewidywane mapy PBR, ale pozostawiający teksturę bazową w oryginalnej rozdzielczości. Wybierz 2 dla podwójnej rozdzielczości, 4 dla poczwórnej lub 0, aby wyłączyć powiększanie. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Format pliku obrazu dla wynikowych tekstur i map PBR. |

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 | Obrazy wynikowe zawierają mapy materiałów PBR przewidywane przez PATINA oraz kafelkowalne tekstury wygenerowane przez z-image. |
| `seed` | integer | Ziarno zastosowane podczas generowania tekstur. |
| `prompt` | string | Prompt generowania tekstury, wraz z zastosowanym rozszerzeniem. |
| `timings` | object | Rozbicie czasu obejmujące cały proces, w sekundach. |

## 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