# PATINA · Material API

> Generador de texturas a partir de texto que produce imágenes teselables y mapas PBR, con img2img e inpainting opcionales

Crea texturas teselables a partir de un prompt y predice mapas PBR: basecolor, normal, roughness, metalness y height. Usa `tiling_mode` para teselado completo, horizontal o vertical, y `upscale_factor` de 0, 2 o 4 para ampliar los mapas. Pasar `image_url` activa image-to-image y añadir `mask_url` activa inpainting. Hasta 4 imágenes por solicitud.

- Model id: `patina/material`
- Made by: Open model
- Category: Text to Image
- Output: image
- Price per run: from $0.08 / run (cheapest run $0.08 (80 API credits))
- Run: `POST https://api.doitong.ru/v1/run/patina/material`
- Quote: `POST https://api.doitong.ru/v1/quote/patina/material`
- Docs page: https://doitong.com/es-ES/developers/models/patina/material

## Pricing

Price: **from $0.08 / 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 $0.08 = 80 API credits (1 run × $0.08).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.ru/v1/quote/patina/material` 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 |  |  | Descripción de texto del material o la textura que se creará. |
| `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` | Dimensiones en píxeles de la textura resultante. |
| `num_inference_steps` |  | integer | no | `8` | 1 – 8 | Número de pasos de eliminación de ruido utilizados para generar texturas. |
| `seed` |  | integer \| null | no |  |  | Semilla aleatoria que hace reproducible la generación. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Número de imágenes de textura que se crearán. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Activa la expansión del prompt basada en LLM para añadir detalles. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Activa la comprobación de seguridad de las imágenes generadas. |
| `tiling_mode` |  | enum (string) | no | `both` | `both`, `horizontal`, `vertical` | Dirección del teselado: 'both' para teselado omnidireccional, 'horizontal' o 'vertical'. |
| `tile_size` |  | integer | no | `128` | 32 – 256 | Tamaño de tesela en el espacio latente, donde 64 representa 512px y 128 representa 1024px. En cada eje teselado, la dimensión de la imagen generada establece un límite superior automático. |
| `tile_stride` |  | integer | no | `64` | 16 – 128 | Establece el paso entre teselas del espacio latente; un límite automático impide que supere la mitad del tamaño de tesela efectivo. |
| `image_url` | `image` | string (image URL) \| null | no |  |  | URL de la imagen de origen, utilizada para inpainting si la acompaña mask_url y, en caso contrario, para el procesamiento de imagen a imagen. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | URL de la máscara de inpainting proporcionada junto con la image_url obligatoria. La máscara conserva sin cambios las áreas negras y regenera las áreas blancas. |
| `strength` |  | number | no | `0.6` | ≤ 1, > 0 | Intensidad de transformación aplicada únicamente a una imagen proporcionada mediante image_url; en caso contrario, no se utiliza. |
| `maps` |  | array of enum (string) | no | `["basecolor","normal","roughness","metalness","height"]` |  | Mapas PBR seleccionados para la predicción; los cinco se seleccionan de forma predeterminada. Si no se selecciona ninguno, se omite por completo la estimación PBR. |
| `upscale_factor` |  | enum (integer) | no | `0` | `0`, `2`, `4` | Factor de ampliación sin juntas de SeedVR que afecta a los mapas PBR predichos, pero mantiene la textura base en su resolución original. Selecciona 2 para duplicar la resolución, 4 para cuadruplicarla o 0 para desactivar la ampliación. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Formato de archivo de imagen para las texturas de salida y los mapas PBR. |

File parameters (`image`, `mask`) 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"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## 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.ru/v1/run/patina/material?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"
  }'

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

### JavaScript

```javascript
const API = "https://api.doitong.ru/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?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"
  }),
});
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.ru/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",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/patina/material", 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.ru/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",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "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",
  "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": 80,
    "usd": "0.08",
    "charged": 80,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of any | Las imágenes de salida incluyen mapas de materiales PBR predichos por PATINA junto a texturas teselables generadas por z-image. |
| `seed` | integer | Semilla aplicada al generar texturas. |
| `prompt` | string | Prompt de generación de texturas, incluida cualquier expansión aplicada. |
| `timings` | object | Desglose de tiempos de todo el proceso, en segundos. |

## Related models

- [PATINA](https://doitong.com/developers/models/patina.md) (`patina`): from $0.0225 / run of input image
- [PATINA · Material · Extract](https://doitong.com/developers/models/patina/material/extract.md) (`patina/material/extract`): from $0.17 / run
- [FLUX.1 \[dev\]](https://doitong.com/developers/models/flux/dev.md) (`flux/dev`): $0.025 / megapixel
- [FLUX.1 \[schnell\]](https://doitong.com/developers/models/flux/schnell.md) (`flux/schnell`): $0.003 / megapixel
- [FLUX.2 \[dev\]](https://doitong.com/developers/models/flux-2.md) (`flux-2`): $0.012 / megapixel
- [FLUX.2 \[pro\]](https://doitong.com/developers/models/flux-2-pro.md) (`flux-2-pro`): $0.015 / megapixel of output image
- [GPT Image 2.5 Text to Image](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/text-to-image.md) (`openai/gpt-image-2.5/flare/text-to-image`): from $0.008 / image
- [Ideogram V4.5](https://doitong.com/developers/models/ideogram/v4.5.md) (`ideogram/v4.5`): from $0.03 / image

## Links

- HTML page: https://doitong.com/developers/models/patina/material
- 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
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/patina/material