# Topaz Video Upscale API

> Peningkat resolusi dan pemulih video Topaz Labs, hingga 4x dengan konversi bingkai rate opsional.

Meningkatkan resolusi dan memulihkan video dengan model Proteus, Iris, Dione, Artemis, Gaia, Rhea, dan Theia milik Topaz, dari rekaman DV dan TV lama hingga animasi. Kontrol untuk pemulihan detail, noise, halo, kompresi, dan grain, serta bingkai rate target opsional dari 16 hingga 60 fps.

- Model id: `topaz/upscale/video/precision`
- Made by: Topaz Labs
- Category: Upscale
- Output: video
- Price per second of your input video: from $0.00667 / second of input video (cheapest run $0.10 (100 API credits))
- Run: `POST https://api.doitong.com/v1/run/topaz/upscale/video/precision`
- Quote: `POST https://api.doitong.com/v1/quote/topaz/upscale/video/precision`
- Docs page: https://doitong.com/id/developers/models/topaz/upscale/video/precision

## Pricing

Price: **from $0.00667 / second of input video** (the lowest tier; the quote prices your exact input). Price per second of your input video: 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.

Price by tier:

- 720p: $0.00667 / second of input video
- 1080p: $0.0133 / second of input video
- 720p, frame rate: $0.0133 / second of input video
- 1080p, frame rate: $0.0267 / second of input video
- 4K: $0.0517 / second of input video
- above 4K: $0.0919 / second of input video
- 4K, frame rate: $0.1033 / second of input video
- above 4K, frame rate: $0.1837 / second of input video

The full example input below costs $0.60 = 600 API credits (10 s input video × $0.051667 (4K), rounded up to the next $0.10).

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/video/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 |
|---|---|---|---|---|---|---|
| `video_url` | `video` | string (video URL) | yes |  |  | URL video sumber untuk peningkatan resolusi. |
| `model` |  | enum (string) | no | `Proteus` | `Proteus`, `Proteus Natural`, `Iris`, `Iris Low Quality`, `Dione DV`, `Dione TV`, `Dione Robust`, `Dione Dehalo`, `Dione Robust Dehalo`, `Artemis High Quality`, `Artemis Medium Quality`, `Artemis Low Quality`, `Artemis Strong Halo`, `Artemis Medium Halo`, `Artemis Aliasing & Moire`, `Gaia HQ`, `Gaia CG`, `Gaia 2`, `Rhea`, `Theia Fine Tune Detail`, `Theia Fine Tune Fidelity` | Model peningkatan presisi non-generatif, dengan Theia yang menawarkan kontrol manual atas kesetiaan dan detail, serta Rhea yang memaksimalkan detail halus melalui proses internal 4x. Untuk tugas restorasi, gunakan Artemis untuk mempertajam dan mengurangi noise pada rekaman yang rusak, Dione untuk deinterlace materi lama atau interlace, atau Iris untuk memulihkan wajah. Untuk sebagian besar rekaman dunia nyata, Proteus cocok digunakan dan Proteus Natural menawarkan alternatif yang lebih lembut; Gaia meningkatkan rekaman berkualitas tinggi dan CG, sedangkan Gaia 2 menyediakan peningkatan resolusi 2x untuk animasi. |
| `upscale_factor` |  | number | no | `2` | 1 – 4 | Pengali skala video; nilai 2.0 menggandakan kedua dimensi bingkai. |
| `target_fps` |  | integer \| null | no |  | 16 – 60 | Laju bingkai output target; menyamakan FPS sumber menonaktifkan interpolasi, dan hanya FPS yang berbeda yang mengaktifkannya. |
| `compression` |  | number \| null | no |  | 0 – 1 | Kekuatan penghapusan artefak kompresi, dari 0.0 hingga 1.0. Bawaannya ditentukan oleh model. |
| `noise` |  | number \| null | no |  | 0 – 1 | Kekuatan pengurangan noise, dari 0.0 hingga 1.0. Bawaannya ditentukan oleh model. |
| `halo` |  | number \| null | no |  | 0 – 1 | Kekuatan pengurangan halo, dari 0.0 hingga 1.0. Bawaannya ditentukan oleh model. |
| `grain` |  | number \| null | no |  | 0 – 0.1 | Jumlah grain film, dari 0.0 hingga 0.1. Bawaannya bergantung pada model. |
| `recover_detail` |  | number \| null | no |  | 0 – 1 | Kekuatan pemulihan detail asli, dari 0.0 hingga 1.0. Menaikkan nilai ini mempertahankan lebih banyak detail sumber. |
| `H264_output` |  | boolean | no | `false` |  | Mengontrol apakah video output menggunakan encoding H264, bukan H265 bawaan. |

File parameters (`video`) 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
{
  "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

A fuller example:

```json
{
  "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
  "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/video/precision?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "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/video/precision?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "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 = {
    "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "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/video/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/video/precision",
      "input": {
        "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
        "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/video/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": 600,
    "usd": "0.60",
    "charged": 600,
    "refunded": 0
  },
  "input": {
    "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "upscale_factor": 2
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    }
  },
  "outputs": [
    {
      "type": "video",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_size": 1843200,
      "width": 1280,
      "height": 720,
      "duration": 5,
      "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 |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | file video yang dihasilkan melalui peningkatan resolusi. |

## Related models

- [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
- [Topaz Image Upscale](https://doitong.com/developers/models/topaz/upscale/image/precision.md) (`topaz/upscale/image/precision`): $0.08 / 24 megapixels of output image
- [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
- [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/video/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/video/precision
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/topaz/upscale/video/precision