# Smart Resize API

> Recompose une image vers jusqu’à 10 dimensions cibles, utile pour les variantes publicitaires et de recadrage

Redimensionne une image source vers des tailles arbitraires en régénérant la composition plutôt qu’en la recadrant simplement. Fournissez `target_sizes` sous forme de 1 à 10 chaînes comme "1920x1080", avec 1 à 4 variantes chacune via `num_images_per_size`. Un `prompt` facultatif de 5000 caractères maximum ajoute des instructions. `resolution` vaut 1K, 2K ou 4K, et la sortie est en png, jpeg ou webp.

- Model id: `smart-resize`
- Made by: Utility
- Category: Image Editing
- Output: image
- Price per run: from $0.15 / run of output image (cheapest run $0.15 (150 API credits))
- Run: `POST https://api.doitong.com/v1/run/smart-resize`
- Quote: `POST https://api.doitong.com/v1/quote/smart-resize`
- Docs page: https://doitong.com/fr/developers/models/smart-resize

## Pricing

Price: **from $0.15 / run of output image** (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.

Price by tier:

- 1K: $0.15 / run of output image
- 2K: $0.15 / run of output image
- 4K: $0.30 / run of output image

The full example input below costs $0.50 = 500 API credits (3 runs × $0.15 (1K) + $0.05).

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/smart-resize` 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 |  |  | URL de l'image source à redimensionner. |
| `target_sizes` |  | array of string | yes |  | 1 – 10 items | Dimensions de sortie demandées sous forme de liste de chaînes `<width>x<height>`, par exemple `"1920x1080"`. Chaque cible est couverte par un préréglage nano-banana-pro choisi pour être aussi petit que possible tout en couvrant les dimensions demandées, ce qui fournit une correspondance exacte des pixels sans mise à l'échelle supérieure. Le nombre d'images pour chaque taille est égal à un multiplié par `num_images_per_size`. |
| `prompt` |  | string | no | `` | ≤ 5000 characters | Indication supplémentaire pour le redimensionnement : une valeur vide demande au modèle de rester aussi fidèle que possible au contenu source. Toute instruction fournie accompagne le prompt de redimensionnement généré automatiquement et envoyé à nano-banana-pro. |
| `num_images_per_size` |  | integer | no | `1` | 1 – 4 | Nombre de variantes par taille pour nano-banana-pro, déterminant le nombre total d'images renvoyées selon `len(target_sizes) * num_images_per_size`. |
| `resolution` |  | enum (string) | no | `1K` | `1K`, `2K`, `4K` | Indication interne du palier de résolution établissant un minimum, et non les dimensions finales spécifiées par `target_sizes`. Si ce palier ne peut pas accueillir une taille demandée, le redimensionnement intelligent peut automatiquement en choisir un plus élevé. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Format des images générées. |
| `safety_tolerance` |  | enum (string) | no | `4` | `1`, `2`, `3`, `4`, `5`, `6` | Tolérance de sécurité : augmenter ce nombre rend le filtrage moins strict pour les appels internes nano-banana-pro /edit. |
| `seed` |  | integer \| null | no |  |  | Graine facultative de reproductibilité partagée entre toutes les tailles cibles. Lorsqu'elle est fournie, elle est transmise aux appels internes nano-banana-pro /edit. |

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",
  "target_sizes": [
    "1024x1024",
    "1920x1080",
    "768x1344"
  ]
}
```

A fuller example:

```json
{
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "target_sizes": [
    "1024x1024",
    "1920x1080",
    "768x1344"
  ]
}
```

## 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/smart-resize?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "target_sizes": [
      "1024x1024",
      "1920x1080",
      "768x1344"
    ]
  }'

# 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/smart-resize?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "target_sizes": [
      "1024x1024",
      "1920x1080",
      "768x1344"
    ]
  }),
});
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_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "target_sizes": [
        "1024x1024",
        "1920x1080",
        "768x1344",
    ],
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/smart-resize", 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": "smart-resize",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
        "target_sizes": [
          "1024x1024",
          "1920x1080",
          "768x1344"
        ]
      },
      "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": "smart-resize",
  "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": 500,
    "usd": "0.50",
    "charged": 500,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "target_sizes": [
      "1024x1024",
      "1920x1080",
      "768x1344"
    ]
  },
  "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
      }
    ],
    "description": "string",
    "results": [
      {
        "images": [
          {}
        ],
        "description": "string",
        "width": 1024,
        "height": 768,
        "aspect_ratio": "string",
        "resolution": "string"
      }
    ]
  },
  "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 object {url, content_type, file_name, file_size, width, height} | Liste d'images combinée avec `num_images_per_size` entrées pour `target_sizes[0]` en premier, suivies de groupes équivalents pour les `target_sizes` suivants. Elle inclut chaque image générée dans le même ordre que `results`. |
| `description` | string | Description accompagnant les images générées. |
| `results` | array of object {images, description, width, height, aspect_ratio, resolution} | Largeur et hauteur demandées pour chaque cible, associées au préréglage nano-banana-pro utilisé lors du traitement, identifié par son aspect_ratio et sa résolution. |

## Related models

- [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
- [Age Modify](https://doitong.com/developers/models/image-apps-v2/age-modify.md) (`image-apps-v2/age-modify`): $0.04 / image
- [Cartoonify](https://doitong.com/developers/models/cartoonify.md) (`cartoonify`): $0.10 / image

## Links

- HTML page: https://doitong.com/developers/models/smart-resize
- 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=smart-resize
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/smart-resize