# Image2Pixel API

> Mengonversi gambar menjadi piksel art bersih dengan batas palet, deteksi skala, dan latar belakang transparan opsional

Mengubah gambar input menjadi piksel art dan mengembalikan gambar yang diproses beserta versi berskalanya sebagai file PNG. Anda dapat membatasi palet dengan `max_colors` (1 hingga 256), memberikan `fixed_palette` berisi warna hex, atau memaksa `scale` dari 1 hingga 64. Tersedia beberapa metode downscale, opsi pembersihan, dan mode penghapusan latar belakang. Respons juga melaporkan jumlah warna, palet, dan skala piksel yang terdeteksi.

- Model id: `image2pixel`
- Made by: Utility
- Category: Image Editing
- Output: image
- Charged by usage (up to $0.153 per run, typical $0.002; the rest of the hold is refunded): $0.00017 / second of processing time (cheapest run $0.002 (2 API credits))
- Run: `POST https://api.doitong.com/v1/run/image2pixel`
- Quote: `POST https://api.doitong.com/v1/quote/image2pixel`
- Docs page: https://doitong.com/id/developers/models/image2pixel

## Pricing

Price: **$0.00017 / second of processing time**. Charged by actual usage at $0.00017 / second of processing time: up to $0.153 per run (the quote gives the maximum for your input), the rest is refunded automatically after the run. A typical run costs $0.002.

The full example input below holds up to $0.153 = 153 API credits (up to 900 s of processing time × $0.00017) when it starts; a typical run costs $0.002 (2 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). This model is charged by usage: `POST https://api.doitong.com/v1/quote/image2pixel` with the same JSON body returns the most the run can cost for that input (`credits`, debited when the run starts); after the run you pay the usage the model reports and the rest is refunded automatically. An input whose maximum would exceed the per-run limit is refused with 422. 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 gambar sumber untuk dikonversi menjadi pixel art yang ditingkatkan. |
| `max_colors` |  | integer \| null | no | `32` | 1 – 256 | Batas jumlah warna palet output; None memungkinkan jumlah warna tak terbatas. |
| `auto_color_detect` |  | boolean | no | `false` |  | Mengaktifkan pemilihan otomatis jumlah warna optimal. |
| `fixed_palette` |  | array of string \| null | no |  |  | Palet bawaan opsional yang ditentukan dengan string heksadesimal, seperti ['#000000', '#ffffff']. |
| `detect_method` |  | enum (string) | no | `auto` | `auto`, `runs`, `edge` | Metode yang digunakan untuk mendeteksi skala. |
| `scale` |  | integer \| null | no |  | 1 – 64 | Skala piksel yang diterapkan; None mengaktifkan deteksi otomatis. |
| `downscale_method` |  | enum (string) | no | `dominant` | `dominant`, `median`, `mode`, `mean`, `content-adaptive` | Metode yang digunakan untuk memperkecil gambar menjadi pixel art. |
| `trim_borders` |  | boolean | no | `false` |  | Mengontrol pemangkasan batas gambar. |
| `transparent_background` |  | boolean | no | `false` |  | Penghapusan latar belakang melalui transparansi: setelah koreksi gambar selesai, wilayah warna terhubung yang menyentuh tepi gambar menjadi transparan. |
| `cleanup_morph` |  | boolean | no | `false` |  | Penghapusan noise menggunakan operasi morfologis. |
| `cleanup_jaggy` |  | boolean | no | `false` |  | Pembersihan tepi bergerigi dengan menghapus piksel diagonal yang terisolasi. |
| `snap_grid` |  | boolean | no | `true` |  | Menempatkan output pada kisi piksel. |
| `alpha_threshold` |  | integer | no | `128` | 0 – 255 | Ambang untuk membinerkan alfa, dari 0 hingga 255. |
| `dominant_color_threshold` |  | number | no | `0.05` | 0 – 1 | Ambang untuk warna dominan, dari 0.0 hingga 1.0. |
| `background_tolerance` |  | integer | no | `0` | 0 – 255 | Toleransi untuk latar belakang, dari 0 hingga 255. |
| `background_mode` |  | enum (string) | no | `corners` | `edges`, `corners`, `midpoints` | Lokasi awal untuk flood-fill selama penghapusan latar belakang. |

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

## 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/image2pixel?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"
  }'

# 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/image2pixel?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
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",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/image2pixel", 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": "image2pixel",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "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": "image2pixel",
  "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": 153,
    "usd": "0.153",
    "charged": 153,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "pixel_scale": 21,
    "palette": [
      "string"
    ],
    "num_colors": 10,
    "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
      }
    ]
  },
  "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 |
|---|---|---|
| `pixel_scale` | integer | Skala piksel yang terdeteksi dalam input. |
| `palette` | array of string | Palet warna dari media yang diproses. |
| `num_colors` | integer | Jumlah warna untuk media yang diproses. |
| `images` | array of object {url, content_type, file_name, file_size, width, height} | Pixel art dan gambar berskala yang diproses, keduanya dalam format PNG. |

## 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/image2pixel
- 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=image2pixel
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/image2pixel