# PATINA · Material API

> Generatore da testo a texture che produce immagini piastrellabili e mappe PBR, con img2img e inpainting opzionali

Crea texture piastrellabili da un prompt e prevede mappe PBR: basecolor, normal, roughness, metalness e height. Usa `tiling_mode` per piastrellatura in entrambe le direzioni, orizzontale o verticale, e `upscale_factor` pari a 0, 2 o 4 per ingrandire le mappe. Passare `image_url` abilita image-to-image e aggiungere `mask_url` abilita l'inpainting. Fino a 4 immagini per richiesta.

- 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/it/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 |  |  | Descrizione testuale del materiale o della texture da creare. |
| `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` | Dimensioni in pixel della texture risultante. |
| `num_inference_steps` |  | integer | no | `8` | 1 – 8 | Numero di passaggi di denoising usati per generare le texture. |
| `seed` |  | integer \| null | no |  |  | Seed casuale che rende riproducibile la generazione. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Numero di immagini di texture da creare. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Abilita l'espansione del prompt basata su LLM per aggiungere dettagli. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Abilita il controllo di sicurezza delle immagini generate. |
| `tiling_mode` |  | enum (string) | no | `both` | `both`, `horizontal`, `vertical` | Direzione della tassellatura: 'both' per la tassellatura omnidirezionale, 'horizontal' o 'vertical'. |
| `tile_size` |  | integer | no | `128` | 32 – 256 | Dimensione della piastrella nello spazio latente, dove 64 rappresenta 512px e 128 rappresenta 1024px. Su ogni asse tassellato, la dimensione dell'immagine generata stabilisce un limite superiore automatico. |
| `tile_stride` |  | integer | no | `64` | 16 – 128 | Imposta lo stride tra le piastrelle nello spazio latente; un limite automatico impedisce che superi metà della dimensione effettiva della piastrella. |
| `image_url` | `image` | string (image URL) \| null | no |  |  | URL dell'immagine sorgente, usato per l'inpainting se lo accompagna mask_url e per l'elaborazione image-to-image altrimenti. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | URL della maschera di inpainting fornita insieme all'image_url obbligatorio. La maschera mantiene inalterate le aree nere e rigenera quelle bianche. |
| `strength` |  | number | no | `0.6` | ≤ 1, > 0 | Intensità della trasformazione applicata solo a un'immagine fornita tramite image_url; altrimenti non viene usata. |
| `maps` |  | array of enum (string) | no | `["basecolor","normal","roughness","metalness","height"]` |  | Mappe PBR selezionate per la predizione, con tutte e cinque selezionate per impostazione predefinita. Non selezionarne nessuna salta interamente la stima PBR. |
| `upscale_factor` |  | enum (integer) | no | `0` | `0`, `2`, `4` | Fattore di upscaling senza giunzioni di SeedVR che influisce sulle mappe PBR predette lasciando la texture di base alla risoluzione originale. Seleziona 2 per il doppio della risoluzione, 4 per il quadruplo o 0 per disabilitare l'upscaling. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Formato file dell'immagine per le texture e le mappe PBR di output. |

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 | Le immagini di output includono mappe dei materiali PBR predette da PATINA insieme a texture tassellabili generate da z-image. |
| `seed` | integer | Seed applicato durante la generazione delle texture. |
| `prompt` | string | Prompt per la generazione della texture, inclusa qualsiasi espansione applicata. |
| `timings` | object | Scomposizione dei tempi dell'intero processo, in secondi. |

## 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