# Topaz Image Upscale API

> Escalador de imágenes de Topaz Labs con recuperación facial, reducción de ruido y enfoque, de hasta 4x.

Amplía una foto o un renderizado hasta cuatro veces con modelos Topaz ajustados para distintas fuentes: fotos estándar, fuentes de alta fidelidad y baja resolución, CGI, texto y rostros. Mejora facial, eliminación de ruido, enfoque y reparación de compresión opcionales; salida JPEG o PNG.

- Model id: `topaz/upscale/image/precision`
- Made by: Topaz Labs
- Category: Upscale
- Output: image
- Price per 24 megapixels of your output image: $0.08 / 24 megapixels of output image (cheapest run $0.08 (80 API credits))
- Run: `POST https://api.doitong.ru/v1/run/topaz/upscale/image/precision`
- Quote: `POST https://api.doitong.ru/v1/quote/topaz/upscale/image/precision`
- Docs page: https://doitong.com/es-ES/developers/models/topaz/upscale/image/precision

## Pricing

Price: **$0.08 / 24 megapixels of output image**. Price per 24 megapixels of your output image: 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 × 24 MP output image × $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/topaz/upscale/image/precision` 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 |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  | ≥ 1 characters | URL de la imagen de origen para la ampliación de resolución. |
| `model` |  | enum (string) | no | `Standard V2` | `Standard V2`, `High Fidelity V3`, `High Fidelity V2`, `Low Resolution V2`, `CGI`, `Text Refine`, `Faces` | Selección del modelo de ampliación de precisión: Faces usa Face Recovery 3 para reconstrucción facial, Text Refine conserva texto y formas nítidos, y CGI es adecuado para ilustraciones y gráficos renderizados. Para fotografías, Standard V2 cubre la mayoría de los usos, High Fidelity V3 y High Fidelity V2 conservan los detalles capturados profesionalmente, y Low Resolution V2 reconstruye fuentes comprimidas. |
| `upscale_factor` |  | number | no | `2` | 1 – 4 | Multiplicador de ampliación de imagen; por ejemplo, 2.0 duplica ambas dimensiones. |
| `crop_to_fill` |  | boolean | no | `false` |  |  |
| `output_format` |  | enum (string) | no | `jpeg` | `jpeg`, `png` | Formato usado para la imagen ampliada. |
| `subject_detection` |  | enum (string) | no | `All` | `All`, `Foreground`, `Background` | Ajuste de detección de sujetos usado durante la mejora de imágenes. |
| `face_enhancement` |  | boolean | no | `true` |  | Activación de mejora facial para la imagen. |
| `face_enhancement_creativity` |  | number | no | `0` | 0 – 1 | Control de creatividad de la mejora facial, activo únicamente mientras la mejora facial está habilitada: establece 1.0 para obtener la creatividad máxima o 0.0 para desactivarla. |
| `face_enhancement_strength` |  | number | no | `0.8` | 0 – 1 | Control de intensidad de la mejora facial, activo únicamente mientras la mejora facial está habilitada: establece 1.0 para obtener la mejora máxima o 0.0 para desactivarla. |
| `sharpen` |  | number \| null | no |  | 0 – 1 | Intensidad de enfoque de 0.0 a 1.0, con un valor predeterminado que depende del modelo. |
| `denoise` |  | number \| null | no |  | 0 – 1 | Intensidad de reducción de ruido de 0.0 a 1.0, con un valor predeterminado que depende del modelo. |
| `fix_compression` |  | number \| null | no |  | 0 – 1 | Intensidad de eliminación de artefactos de compresión de 0.0 a 1.0; no disponible con CGI. |
| `strength` |  | number \| null | no |  | 0.01 – 1 | Intensidad de mejora de 0.01 a 1.0, compatible únicamente con Text Refine. |

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
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "upscale_factor": 2
}
```

## 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/topaz/upscale/image/precision?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "upscale_factor": 2
  }'

# 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/topaz/upscale/image/precision?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "upscale_factor": 2
  }),
});
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 = {
    "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "upscale_factor": 2,
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/topaz/upscale/image/precision", 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": "topaz/upscale/image/precision",
      "input": {
        "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
        "upscale_factor": 2
      },
      "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": "topaz/upscale/image/precision",
  "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": {
    "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "upscale_factor": 2
  },
  "output": {
    "image": {
      "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
    }
  },
  "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 |
|---|---|---|
| `image` | object {url, content_type, file_name, file_size} | Imagen producida mediante ampliación. |

## Related models

- [Topaz Upscale Image Creative](https://doitong.com/developers/models/topaz/upscale/image/creative.md) (`topaz/upscale/image/creative`): $0.08 / 2 megapixels of output image
- [Topaz Upscale Image Generative](https://doitong.com/developers/models/topaz/upscale/image/generative.md) (`topaz/upscale/image/generative`): from $0.01 / megapixel of output image
- [Topaz Upscale Image Transparent](https://doitong.com/developers/models/topaz/upscale/image/transparent.md) (`topaz/upscale/image/transparent`): $0.08 / 24 megapixels of output image
- [Topaz Video Upscale](https://doitong.com/developers/models/topaz/upscale/video/precision.md) (`topaz/upscale/video/precision`): from $0.00667 / second of input video
- [Topaz Upscale Video Creative](https://doitong.com/developers/models/topaz/upscale/video/creative.md) (`topaz/upscale/video/creative`): from $0.30 / second of input video
- [Topaz Upscale Video Generative](https://doitong.com/developers/models/topaz/upscale/video/generative.md) (`topaz/upscale/video/generative`): from $0.06 / second of input video
- [AuraSR](https://doitong.com/developers/models/aura-sr.md) (`aura-sr`): $0.001111 / second of processing time
- [Bria Increase Resolution](https://doitong.com/developers/models/bria/increase-resolution.md) (`bria/increase-resolution`): $0.04 / image

## Links

- HTML page: https://doitong.com/developers/models/topaz/upscale/image/precision
- 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=topaz/upscale/image/precision
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/topaz/upscale/image/precision