# PATINA · Material · Extract API

> ציט אַרויס אַ טײַלבאַרע טעקסטור מיט PBR מאַפּעס פֿון אַ מקור־בילד, לויט אַ פּראמפּט וואָס נאָמעןט די ייבערפֿלאַך

נעמט אַן אַרײַנגאַנג־בילד פּלוס אַ פּראמפּט וואָס באַשרײַבט וועלכע ייבערפֿלאַך צו ציען אַרויס, און גיט צוריק אַ טײַלבאַרע טעקסטור צוזאַמען מיט פּרעדיקטירטע PBR מאַפּעס. `maps` אויסקלייבט וועלכע פֿון basecolor, normal, roughness, metalness און height צו שאַפֿן. אָפּציעס אַרײַננעמען `tiling_mode`, `strength` פֿון 0 ביז 1, `upscale_factor` פֿון 0, 2 אָדער 4, און 1 ביז 4 רעזולטאַטן.

- 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/yi/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 |  |  | באַשרײַבונג פֿונעם געוואונטשן טעקסטור צו אויסציען פֿונעם בילד. |
| `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` | פּיקסעל־דימענסיעס פֿונעם רעזולטירנדיקן טעקסטור. |
| `num_inference_steps` |  | integer | no | `8` | 1 – 8 | דענאָיִזינג־סטעפּ־צאָל גענוצט צו גענערירן טעקסטורן. |
| `seed` |  | integer \| null | no |  |  | צופֿעליקער סיד וואָס מאכט די גענערירונג רעפּראָדוצירבאַר. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | צאָל טעקסטור־בילדער צו שאַפֿן. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | דערמעגלעכט LLM־באזירטע פּראָמפּט־יקספּאַנשאַן צו צוגעבן דעטאַלן. |
| `enable_safety_checker` |  | boolean | no | `true` |  | דערמעגלעכט זיכערקייט־קאָנטראָל פֿון גענערירטע בילדער. |
| `tiling_mode` |  | enum (string) | no | `both` | `both`, `horizontal`, `vertical` | ריכטונג פֿון טײַלן: 'both' פֿאַר אַלריכטונגס־טײַלן, 'horizontal', אָדער 'vertical'. |
| `tile_size` |  | integer | no | `128` | 32 – 256 | טײַל־גרייס אין latent-space, וווּ 64 רעפּרעזענטירט 512px און 128 רעפּרעזענטירט 1024px. אויף יעדן געטײַלטן אַקס שטעלט די דימענסיע פֿונעם גענערירטן בילד אַן אויטאָמאַטישן אויבערשטן גרענעץ. |
| `tile_stride` |  | integer | no | `64` | 16 – 128 | שטעלט דעם סטרייד צווישן latent-space טײַלן; אַן אויטאָמאַטישער שיעור פֿאַרמיידט אַז ער זאָל איבערשטײַגן האַלב פֿון דער עפעקטיווער טײַל־גרייס. |
| `image_url` | `image` | string (image URL) | yes |  |  | מקור־בילד־URL פֿאַר טעקסטור־אויסציעונג. |
| `strength` |  | number | no | `0.6` | ≤ 1, > 0 | טראַנספֿאָרמאַציע־שטאַרקייט געווענדט בלויז צו אַ בילד צוגעשטעלט דורך image_url; אַנדערש נישט גענוצט. |
| `maps` |  | array of enum (string) | no | `["basecolor","normal","roughness","metalness","height"]` |  | PBR מאַפּס אויסגעקליבן פֿאַר פֿאָרויסזאָגונג, מיט אַלע פֿינף סטאַנדאַרט אויסגעקליבן. אויסקלײַבן קיינעם שפּרינגט איבער PBR־אָפּשאַצונג גאָר. |
| `upscale_factor` |  | enum (integer) | no | `0` | `0`, `2`, `4` | SeedVR־פֿאַקטאָר פֿאַר זאַמלאָזעס אויפסקעילן, וואָס ווירקט אויף פֿאָרויסגעזאָגטע PBR מאַפּס אָבער לאָזט דעם באַזע־טעקסטור אין זײַן אָריגינעלער רעזאָלוציע. קלײַבט 2 פֿאַר טאָפּלטע רעזאָלוציע, 4 פֿאַר פֿירפאַכע רעזאָלוציע, אָדער 0 צו דיסייבלען אויפסקעילן. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | בילד־פֿײַל־פֿאָרמאַט פֿאַר רעזולטאַט־טעקסטורן און PBR מאַפּס. |

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 | רעזולטאַט־בילדער אַנטהאַלטן PBR מאַטעריאַל־מאַפּס פֿאָרויסגעזאָגט דורך PATINA צוזאַמען מיט טײַלבאַרע טעקסטורן גענערירט דורך z-image. |
| `seed` | integer | סיד געווענדט בײַם גענערירן טעקסטורן. |
| `prompt` | string | טעקסטור־גענערירונג־פּראָמפּט, אַרײַנגערעכנט יעדע געווענדטע יקספּאַנשאַן. |
| `timings` | object | צײַט־איבערבליק פֿאַרן גאַנצן פּראָצעס, אין סעקונדעס. |

## 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