# Topaz Image Upscale API

> Mise à l’échelle d’images de Topaz Labs avec restauration des visages, réduction du bruit et accentuation, jusqu’à 4x.

Agrandit une photo ou un rendu jusqu’à quatre fois avec des modèles Topaz adaptés à différentes sources : photos standard, haute fidélité, sources basse résolution, CGI, texte et visages. Amélioration facultative des visages, réduction du bruit, accentuation et réparation de la compression ; sortie JPEG ou 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/fr/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 l’image source pour la mise à l’échelle. |
| `model` |  | enum (string) | no | `Standard V2` | `Standard V2`, `High Fidelity V3`, `High Fidelity V2`, `Low Resolution V2`, `CGI`, `Text Refine`, `Faces` | Sélection du modèle de mise à l’échelle de précision : Faces utilise Face Recovery 3 pour reconstruire les visages, Text Refine conserve la netteté du texte et des formes, et CGI convient aux illustrations et graphiques rendus. Pour les photographies, Standard V2 couvre la plupart des usages, High Fidelity V3 et High Fidelity V2 conservent les détails des prises professionnelles, et Low Resolution V2 reconstruit les sources compressées. |
| `upscale_factor` |  | number | no | `2` | 1 – 4 | Multiplicateur d’agrandissement de l’image ; par exemple, 2.0 double les deux dimensions. |
| `crop_to_fill` |  | boolean | no | `false` |  |  |
| `output_format` |  | enum (string) | no | `jpeg` | `jpeg`, `png` | Format utilisé pour l’image mise à l’échelle. |
| `subject_detection` |  | enum (string) | no | `All` | `All`, `Foreground`, `Background` | Réglage de détection des sujets utilisé pendant l’amélioration de l’image. |
| `face_enhancement` |  | boolean | no | `true` |  | Activation de l’amélioration des visages pour l’image. |
| `face_enhancement_creativity` |  | number | no | `0` | 0 – 1 | Contrôle de créativité de l’amélioration des visages, actif uniquement lorsque celle-ci est activée : définissez 1.0 pour une créativité maximale ou 0.0 pour aucune créativité. |
| `face_enhancement_strength` |  | number | no | `0.8` | 0 – 1 | Contrôle de l’intensité de l’amélioration des visages, actif uniquement lorsque celle-ci est activée : définissez 1.0 pour une amélioration maximale ou 0.0 pour aucune amélioration. |
| `sharpen` |  | number \| null | no |  | 0 – 1 | Intensité de netteté de 0.0 à 1.0, avec une valeur par défaut dépendant du modèle. |
| `denoise` |  | number \| null | no |  | 0 – 1 | Intensité du débruitage de 0.0 à 1.0, avec une valeur par défaut dépendant du modèle. |
| `fix_compression` |  | number \| null | no |  | 0 – 1 | Intensité de suppression des artefacts de compression de 0.0 à 1.0 ; indisponible avec CGI. |
| `strength` |  | number \| null | no |  | 0.01 – 1 | Intensité d’amélioration de 0.01 à 1.0, prise en charge uniquement par 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} | Image produite par l'agrandissement. |

## 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