# Topaz Image Upscale API

> A Topaz Labs képfelskálázója arcregenerálással, zajszűréssel és élesítéssel, legfeljebb 4x méretre.

Fényképet vagy renderelt képet legfeljebb négyszeresére nagyít a különböző forrásokhoz hangolt Topaz modellekkel: normál fényképekhez, nagy hűségű forrásokhoz, alacsony felbontású forrásokhoz, CGI-hez, szöveghez és arcokhoz. Opcionális arcfeljavítás, zajszűrés, élesítés és tömörítési hibajavítás; JPEG vagy PNG kimenet.

- 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.com/v1/run/topaz/upscale/image/precision`
- Quote: `POST https://api.doitong.com/v1/quote/topaz/upscale/image/precision`
- Docs page: https://doitong.com/hu/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.com/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 | A felskálázandó forráskép URL-je. |
| `model` |  | enum (string) | no | `Standard V2` | `Standard V2`, `High Fidelity V3`, `High Fidelity V2`, `Low Resolution V2`, `CGI`, `Text Refine`, `Faces` | Precíziós felskálázási modell kiválasztása: a Faces a Face Recovery 3-at használja az arcok rekonstrukciójához, a Text Refine megőrzi az éles szöveget és formákat, a CGI pedig grafikákhoz és renderelt képekhez illik. Fényképekhez a Standard V2 a legtöbb felhasználási esetet lefedi, a High Fidelity V3 és a High Fidelity V2 megőrzi a professzionálisan készített részleteket, a Low Resolution V2 pedig tömörített forrásokat rekonstruál. |
| `upscale_factor` |  | number | no | `2` | 1 – 4 | Kép-nagyítási szorzó; például a 2.0 mindkét méretet megduplázza. |
| `crop_to_fill` |  | boolean | no | `false` |  |  |
| `output_format` |  | enum (string) | no | `jpeg` | `jpeg`, `png` | A felskálázott képhez használt formátum. |
| `subject_detection` |  | enum (string) | no | `All` | `All`, `Foreground`, `Background` | A képjavítás során használt témadetektálási beállítás. |
| `face_enhancement` |  | boolean | no | `true` |  | A képek arcjavításának be- vagy kikapcsolása. |
| `face_enhancement_creativity` |  | number | no | `0` | 0 – 1 | Az arcjavítás kreativitásának szabályozása, csak az arcjavítás engedélyezésekor aktív: a maximális kreativitáshoz állítsa 1.0-ra, kikapcsolásához 0.0-ra. |
| `face_enhancement_strength` |  | number | no | `0.8` | 0 – 1 | Az arcjavítás erősségének szabályozása, csak az arcjavítás engedélyezésekor aktív: a maximális javításhoz állítsa 1.0-ra, kikapcsolásához 0.0-ra. |
| `sharpen` |  | number \| null | no |  | 0 – 1 | Élesítési intenzitás 0.0 és 1.0 között, modellfüggő alapértelmezett értékkel. |
| `denoise` |  | number \| null | no |  | 0 – 1 | Zajcsökkentési intenzitás 0.0 és 1.0 között, modellfüggő alapértelmezett értékkel. |
| `fix_compression` |  | number \| null | no |  | 0 – 1 | Tömörítési hibák eltávolításának intenzitása 0.0 és 1.0 között; CGI esetén nem érhető el. |
| `strength` |  | number \| null | no |  | 0.01 – 1 | Javítási intenzitás 0.01 és 1.0 között, csak a Text Refine támogatja. |

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.com/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.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/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.com/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.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": "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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `image` | object {url, content_type, file_name, file_size} | A nagyítással előállított kép. |

## 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.com/v1/models/topaz/upscale/image/precision