# Pixal3d API

> Menukar satu imej menjadi model 3D GLB bertekstur dengan kawalan terperinci bagi setiap peringkat penjanaan

Menerima satu imej dan mengembalikan model GLB bersama seed yang digunakan. Peringkat struktur, bentuk dan tekstur masing-masing mempunyai tetapan panduan, penskalaan semula, bilangan langkah dan jadual hingar sendiri. `resolution` output ialah 1024 atau 1536, `texture_size` ialah 1024, 2048 atau 4096, dan `decimation_target` menetapkan bilangan bucu daripada 5000 hingga 1586021. `remesh` membina semula topologi.

- Model id: `pixal3d`
- Made by: Open model
- Category: Image to 3D
- Output: 3d
- Price: from $0.30 / request (cheapest run $0.30 (300 API credits))
- Run: `POST https://api.doitong.com/v1/run/pixal3d`
- Quote: `POST https://api.doitong.com/v1/quote/pixal3d`
- Docs page: https://doitong.com/ms/developers/models/pixal3d

## Pricing

Price: **from $0.30 / request** (the lowest tier; the quote prices your exact input). Billed once per request.

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `resolution` = 1536: $0.42 (420 API credits) / request

The full example input below costs $0.30 = 300 API credits (1 request × 300 API credits).

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/pixal3d` 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 yang menunjuk kepada imej sumber untuk penukaran 3D. |
| `seed` |  | integer \| null | no |  |  | Seed yang digunakan untuk penjanaan rawak yang boleh dihasilkan semula. |
| `resolution` |  | enum (integer) | no | `1024` | `1024`, `1536` | Resolusi output; meningkatkannya menambah perincian tetapi mengambil masa lebih lama. |
| `ss_guidance_strength` |  | number | no | `7.5` | 0 – 10 | Kawalan kesetiaan struktur 3D awal: meningkatkannya mengutamakan keserupaan lebih dekat dengan imej input dengan risiko hingar tambahan. |
| `ss_guidance_rescale` |  | number | no | `0.7` | 0 – 1 | Kawalan artifak panduan peringkat 1, yang menukar kesan panduan lebih kuat pada tetapan rendah dengan output lebih stabil pada tetapan tinggi. |
| `ss_sampling_steps` |  | integer | no | `12` | 1 – 50 | Bilangan penyahhingaran struktur awal: peningkatan kualiti berpotensi daripada langkah tambahan disertai pemprosesan yang lebih perlahan. |
| `ss_rescale_t` |  | number | no | `5` | 1 – 6 | Tetapkan ketajaman peralihan melalui jadual hingar penjanaan struktur: meningkatkan nilai ini menjadikan peralihan lebih tajam. |
| `shape_slat_guidance_strength` |  | number | no | `7.5` | 0 – 10 | Kawalan kesetiaan geometri terperinci: pematuhan yang lebih tinggi kepada imej input menghasilkan perincian tambahan, dengan risiko hingar tambahan. |
| `shape_slat_guidance_rescale` |  | number | no | `0.5` | 0 – 1 | Tingkatkan tetapan ini apabila geometri kelihatan bising: ia mengurangkan artifak yang disebabkan oleh panduan kuat semasa peringkat bentuk. |
| `shape_slat_sampling_steps` |  | integer | no | `12` | 1 – 50 | Bilangan penyahhingaran penapisan bentuk: geometri yang berpotensi lebih licin mengorbankan kelajuan apabila langkah tambahan digunakan. |
| `shape_slat_rescale_t` |  | number | no | `3` | 1 – 6 | Tetapkan ketajaman perincian geometri melalui jadual hingar penapisan bentuk; meningkatkan nilai ini menghasilkan perincian yang lebih tajam. |
| `tex_slat_guidance_strength` |  | number | no | `1` | 0 – 10 | Kawalan kesetiaan warna tekstur: pematuhan yang lebih dekat kepada warna dalam imej input pada tetapan lebih tinggi meningkatkan kecerahan tetapi boleh menyebabkan terlebih tepu. |
| `tex_slat_guidance_rescale` |  | number | no | `0` | 0 – 1 | Tingkatkan tetapan ini untuk menangani tekstur bising atau jalur warna: ia mengurangkan artifak yang disebabkan oleh panduan kuat semasa peringkat tekstur. |
| `tex_slat_sampling_steps` |  | integer | no | `12` | 1 – 50 | Bilangan langkah penyahhingaran yang digunakan untuk menjana tekstur. Meningkatkan bilangan langkah mengambil masa lebih lama tetapi mungkin menghasilkan tekstur yang lebih bersih. |
| `tex_slat_rescale_t` |  | number | no | `3` | 1 – 6 | Tetapkan ketajaman perincian tekstur melalui jadual hingar penjanaan tekstur; meningkatkan nilai ini menghasilkan perincian yang lebih tajam. |
| `mesh_scale` |  | number | no | `1` | 0.1 – 4 | Skalakan mesh yang disimpulkan untuk mempengaruhi anggaran jarak kamera yang digunakan oleh model. |
| `max_num_tokens` |  | integer | no | `49152` | 4,096 – 131,072 | Had token HR untuk pensampel bentuk berlapis, mengimbangi geometri yang lebih halus pada tetapan tinggi dengan penjimatan memori dan masa pemprosesan pada tetapan rendah. |
| `decimation_target` |  | integer | no | `200000` | 5,000 – 1,586,021 | Sasaran kerumitan mesh, dinyatakan sebagai bilangan bucu untuk hasil akhir. Mengurangkan saiz fail dengan menurunkan sasaran ini turut mengorbankan perincian. |
| `texture_size` |  | enum (integer) | no | `2048` | `1024`, `2048`, `4096` | Resolusi tekstur mesh untuk baking. Perincian permukaan yang lebih halus menghasilkan fail yang lebih besar apabila resolusi ini ditingkatkan. |
| `remesh` |  | boolean | no | `true` |  | Pembinaan semula topologi mesh yang biasanya memanfaatkan penggunaan hiliran dengan mencipta segi tiga yang lebih bersih, dengan mengorbankan pemprosesan yang lebih lama. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Pemeriksaan boleh dilonggarkan dengan menetapkannya kepada false, jika pemanggil dibenarkan. |

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/pixal3d?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/pixal3d?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/pixal3d", 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": "pixal3d",
      "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": "pixal3d",
  "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": 300,
    "usd": "0.30",
    "charged": 300,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "model_glb": {
      "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
    },
    "seed": 42
  },
  "outputs": [
    {
      "type": "file",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "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 |
|---|---|---|
| `model_glb` | object {url, content_type, file_name, file_size} | Model 3D yang dijana dalam format GLB. |
| `seed` | integer | Nilai seed yang sebenarnya digunakan. |

## Related models

- [ReconViaGen 0.5](https://doitong.com/developers/models/reconviagen-0.5.md) (`reconviagen-0.5`): from $0.25 / request
- [Hi3D Image to 3D](https://doitong.com/developers/models/hitem3d/hi3d/image-to-3d.md) (`hitem3d/hi3d/image-to-3d`): $0.50 / run
- [Hi3D Image to 3D · v3.0](https://doitong.com/developers/models/hitem3d/hi3d/v3.0/image-to-3d.md) (`hitem3d/hi3d/v3.0/image-to-3d`): from $1.80 / run
- [Hi3D Multiview to 3D · Multi View to 3D](https://doitong.com/developers/models/hitem3d/hi3d/multi-view-to-3d.md) (`hitem3d/hi3d/multi-view-to-3d`): $0.50 / run
- [Hi3D Multiview to 3D · v3.0 · Multi View to 3D](https://doitong.com/developers/models/hitem3d/hi3d/v3.0/multi-view-to-3d.md) (`hitem3d/hi3d/v3.0/multi-view-to-3d`): from $1.80 / run
- [Hunyuan 3D Pro Image to 3D](https://doitong.com/developers/models/hunyuan-3d/v3.1/pro/image-to-3d.md) (`hunyuan-3d/v3.1/pro/image-to-3d`): $0.375 / run
- [Hunyuan 3D Rapid Image to 3D](https://doitong.com/developers/models/hunyuan-3d/v3.1/rapid/image-to-3d.md) (`hunyuan-3d/v3.1/rapid/image-to-3d`): from $0.225 / request
- [Hunyuan World · Image to World](https://doitong.com/developers/models/hunyuan_world/image-to-world.md) (`hunyuan_world/image-to-world`): $0.30 / request

## Links

- HTML page: https://doitong.com/developers/models/pixal3d
- 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=pixal3d
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/pixal3d