# PATINA · Material API

> Gerador de texto para textura que produz imagens ladrilháveis e mapas PBR, com img2img e inpainting opcionais

Cria texturas ladrilháveis a partir de um prompt e prevê mapas PBR: basecolor, normal, roughness, metalness e height. Use `tiling_mode` para ladrilhamento nos modos both, horizontal ou vertical, e `upscale_factor` de 0, 2 ou 4 para ampliar os mapas. Enviar `image_url` ativa image-to-image, e adicionar `mask_url` ativa inpainting. Até 4 imagens por solicitação.

- 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.com/v1/run/patina/material`
- Quote: `POST https://api.doitong.com/v1/quote/patina/material`
- Docs page: https://doitong.com/pt-BR/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.com/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 |  |  | Descrição em texto do material ou da textura a ser criada. |
| `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` | Dimensões em pixels da textura resultante. |
| `num_inference_steps` |  | integer | no | `8` | 1 – 8 | Quantidade de etapas de redução de ruído usada para gerar texturas. |
| `seed` |  | integer \| null | no |  |  | Seed aleatória que torna a geração reproduzível. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Quantidade de imagens de textura a criar. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Ativa a expansão do prompt baseada em LLM para adicionar detalhes. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Ativa a verificação de segurança das imagens geradas. |
| `tiling_mode` |  | enum (string) | no | `both` | `both`, `horizontal`, `vertical` | Direção da repetição: 'both' para repetição omnidirecional, 'horizontal' ou 'vertical'. |
| `tile_size` |  | integer | no | `128` | 32 – 256 | Tamanho do bloco no espaço latente, em que 64 representa 512px e 128 representa 1024px. Em cada eixo repetido, a dimensão da imagem gerada define um limite superior automático. |
| `tile_stride` |  | integer | no | `64` | 16 – 128 | Defina o stride entre os blocos do espaço latente; um limite automático impede que ele exceda metade do tamanho efetivo do bloco. |
| `image_url` | `image` | string (image URL) \| null | no |  |  | URL da imagem de origem, usada para inpainting quando mask_url a acompanha e, caso contrário, para processamento imagem-a-imagem. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | URL da máscara de inpainting fornecida junto com a image_url obrigatória. A máscara mantém as áreas pretas inalteradas e regenera as áreas brancas. |
| `strength` |  | number | no | `0.6` | ≤ 1, > 0 | Intensidade da transformação aplicada somente a uma imagem fornecida por image_url; caso contrário, não é usada. |
| `maps` |  | array of enum (string) | no | `["basecolor","normal","roughness","metalness","height"]` |  | Mapas PBR selecionados para previsão, com os cinco selecionados por padrão. Não selecionar nenhum ignora completamente a estimativa de PBR. |
| `upscale_factor` |  | enum (integer) | no | `0` | `0`, `2`, `4` | Fator de aumento de resolução contínuo do SeedVR que afeta os mapas PBR previstos, mas mantém a textura base em sua resolução original. Selecione 2 para resolução dupla, 4 para resolução quádrupla ou 0 para desativar o aumento de resolução. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Formato do arquivo de imagem para texturas e mapas PBR de saída. |

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.com/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.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?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.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",
}

# 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.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",
      "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.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 | As imagens de saída incluem mapas de material PBR previstos pelo PATINA junto com texturas repetíveis geradas pelo z-image. |
| `seed` | integer | Seed aplicado ao gerar texturas. |
| `prompt` | string | Prompt de geração de textura, incluindo qualquer expansão aplicada. |
| `timings` | object | Detalhamento do tempo de todo o processo, em 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.com/v1/models/patina/material