# PATINA · Material API

> Ġeneratur text-to-texture li joħroġ immaġnijiet tileable flimkien ma’ mapep PBR, b’img2img u inpainting fakultattivi

Joħloq textures tileable minn prompt u jbassar mapep PBR: basecolor, normal, roughness, metalness u height. Uża `tiling_mode` għal tiling fiż-żewġ direzzjonijiet, orizzontali jew vertikali, u `upscale_factor` ta’ 0, 2 jew 4 biex tkabbar il-mapep. L-għoti ta’ `image_url` jippermetti image-to-image, u ż-żieda ta’ `mask_url` tippermetti inpainting. Sa 4 immaġnijiet għal kull talba.

- 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/mt/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 |  |  | Deskrizzjoni testwali tal-materjal jew in-nisġa li għandha tinħoloq. |
| `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` | Dimensjonijiet bil-pixels tan-nisġa li tirriżulta. |
| `num_inference_steps` |  | integer | no | `8` | 1 – 8 | Għadd tal-passi tad-denoising użati biex jinħolqu n-nisġiet. |
| `seed` |  | integer \| null | no |  |  | Żerriegħa każwali li tagħmel il-ġenerazzjoni riproduċibbli. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Għadd ta’ immaġnijiet tan-nisġa li għandhom jinħolqu. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Jippermetti l-espansjoni tal-prompt ibbażata fuq LLM biex iżid id-dettall. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Jippermetti l-kontroll tas-sikurezza tal-immaġnijiet iġġenerati. |
| `tiling_mode` |  | enum (string) | no | `both` | `both`, `horizontal`, `vertical` | Direzzjoni tat-tessellazzjoni: 'both' għal tessellazzjoni omnidirezzjonali, 'horizontal', jew 'vertical'. |
| `tile_size` |  | integer | no | `128` | 32 – 256 | Daqs tal-madum fl-ispazju latent, fejn 64 jirrappreżenta 512px u 128 jirrappreżenta 1024px. Fuq kull assi tessellat, id-dimensjoni tal-immaġni ġġenerata tistabbilixxi limitu massimu awtomatiku. |
| `tile_stride` |  | integer | no | `64` | 16 – 128 | Issettja l-istride bejn il-madum fl-ispazju latent; limitu awtomatiku ma jħallihx jaqbeż nofs id-daqs effettiv tal-madum. |
| `image_url` | `image` | string (image URL) \| null | no |  |  | URL tal-immaġni sors, użat għall-inpainting jekk mask_url jakkumpanjaha u għall-ipproċessar image-to-image inkella. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | URL tal-maskra tal-inpainting ipprovduta flimkien mal-image_url meħtieġ. Il-maskra żżomm iż-żoni suwed mhux mibdula u tiġġenera mill-ġdid iż-żoni bojod. |
| `strength` |  | number | no | `0.6` | ≤ 1, > 0 | Saħħa tat-trasformazzjoni applikata biss għal immaġni pprovduta permezz ta’ image_url; inkella ma tintużax. |
| `maps` |  | array of enum (string) | no | `["basecolor","normal","roughness","metalness","height"]` |  | Mapep PBR magħżula għat-tbassir, bil-ħamsa kollha magħżula b’mod prestabbilit. Jekk ma tintgħażel l-ebda waħda, l-istima PBR tinqabeż kompletament. |
| `upscale_factor` |  | enum (integer) | no | `0` | `0`, `2`, `4` | Fattur ta’ tkabbir bla xkiel ta’ SeedVR li jaffettwa l-mapep PBR imbassra iżda jħalli n-nisġa bażi fir-riżoluzzjoni oriġinali tagħha. Agħżel 2 għal riżoluzzjoni doppja, 4 għal riżoluzzjoni kwadrupla, jew 0 biex tiddiżattiva t-tkabbir. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Format tal-fajl tal-immaġni għan-nisġiet output u l-mapep 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.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 | L-immaġnijiet output jinkludu mapep tal-materjal PBR imbassra minn PATINA flimkien ma’ nisġiet tessellabbli ġġenerati minn z-image. |
| `seed` | integer | Seed applikat meta jinħolqu n-nisġiet. |
| `prompt` | string | Prompt għall-ġenerazzjoni tan-nisġa, inkluża kwalunkwe espansjoni applikata. |
| `timings` | object | Tqassim tal-ħin li jkopri l-proċess kollu, f’sekondi. |

## 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