# Pixal3d API

> Pārvērš vienu attēlu teksturētā GLB 3D modelī ar detalizētu kontroli pār katru ģenerēšanas posmu

Saņem vienu attēlu un atgriež GLB modeli kopā ar izmantoto sākumvērtību. Struktūras, formas un tekstūras posmiem ir atsevišķi vadības, mērogošanas, soļu skaita un trokšņa grafika iestatījumi. Izvades `resolution` ir 1024 vai 1536, `texture_size` ir 1024, 2048 vai 4096, bet `decimation_target` nosaka virsotņu skaitu no 5000 līdz 1586021. `remesh` atjauno topoloģiju.

- 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/lv/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 |  |  | Avota attēla URL 3D pārveidei. |
| `seed` |  | integer \| null | no |  |  | Sākumvērtība atkārtojamai nejaušai ģenerēšanai. |
| `resolution` |  | enum (integer) | no | `1024` | `1024`, `1536` | Izvades izšķirtspēja; tās palielināšana pievieno detalizāciju, bet aizņem vairāk laika. |
| `ss_guidance_strength` |  | number | no | `7.5` | 0 – 10 | Sākotnējās 3D struktūras precizitātes vadība: palielināšana veicina lielāku atbilstību ievades attēlam, taču var radīt papildu troksni. |
| `ss_guidance_rescale` |  | number | no | `0.7` | 0 – 1 | 1. posma vadības artefaktu kontrole: zemas vērtības pastiprina vadības efektus, bet augstas nodrošina stabilāku izvadi. |
| `ss_sampling_steps` |  | integer | no | `12` | 1 – 50 | Sākotnējās struktūras trokšņa noņemšanas soļu skaits: papildu soļi var uzlabot kvalitāti, bet palēnina apstrādi. |
| `ss_rescale_t` |  | number | no | `5` | 1 – 6 | Iestatiet pārejas asumu, izmantojot struktūras ģenerēšanas trokšņa grafiku: palielinot šo vērtību, pārejas kļūst asākas. |
| `shape_slat_guidance_strength` |  | number | no | `7.5` | 0 – 10 | Detalizētās ģeometrijas precizitātes vadība: lielāka atbilstība ievades attēlam nodrošina papildu detalizāciju, taču var radīt troksni. |
| `shape_slat_guidance_rescale` |  | number | no | `0.5` | 0 – 1 | Palieliniet šo iestatījumu, ja ģeometrija izskatās trokšņaina: tas samazina spēcīgas vadības radītos artefaktus formas posmā. |
| `shape_slat_sampling_steps` |  | integer | no | `12` | 1 – 50 | Formas precizēšanas trokšņa noņemšanas soļu skaits: papildu soļi var nodrošināt vienmērīgāku ģeometriju, bet samazina ātrumu. |
| `shape_slat_rescale_t` |  | number | no | `3` | 1 – 6 | Iestatiet ģeometrisko detaļu asumu, izmantojot formas precizēšanas trokšņa grafiku; palielinot šo vērtību, detaļas kļūst asākas. |
| `tex_slat_guidance_strength` |  | number | no | `1` | 0 – 10 | Tekstūras krāsu precizitātes vadība: lielāka atbilstība ievades attēla krāsām pie augstākām vērtībām palielina košumu, bet var izraisīt pārsātinājumu. |
| `tex_slat_guidance_rescale` |  | number | no | `0` | 0 – 1 | Palieliniet šo iestatījumu, lai novērstu trokšņainas tekstūras vai krāsu joslojumu: tas samazina spēcīgas vadības radītos artefaktus tekstūras posmā. |
| `tex_slat_sampling_steps` |  | integer | no | `12` | 1 – 50 | Tekstūru ģenerēšanai izmantoto trokšņa noņemšanas soļu skaits. Palielinot soļu skaitu, apstrāde kļūst ilgāka, bet tekstūras var būt tīrākas. |
| `tex_slat_rescale_t` |  | number | no | `3` | 1 – 6 | Iestatiet tekstūras detaļu asumu, izmantojot tekstūras ģenerēšanas trokšņa grafiku; palielinot šo vērtību, detaļas kļūst asākas. |
| `mesh_scale` |  | number | no | `1` | 0.1 – 4 | Mērogojiet secināto režģi, lai ietekmētu modeļa izmantoto kameras attāluma aplēsi. |
| `max_num_tokens` |  | integer | no | `49152` | 4,096 – 131,072 | HR marķieru griesti kaskādes formas paraugotājam: augstākas vērtības nodrošina smalkāku ģeometriju, bet zemākas ietaupa atmiņu un apstrādes laiku. |
| `decimation_target` |  | integer | no | `200000` | 5,000 – 1,586,021 | Režģa sarežģītības mērķis, kas izteikts kā gala rezultāta virsotņu skaits. Samazinot šo mērķi, tiek samazināts faila izmērs, taču zūd detalizācija. |
| `texture_size` |  | enum (integer) | no | `2048` | `1024`, `2048`, `4096` | Režģa tekstūras izšķirtspēja cepšanai. Palielinot izšķirtspēju, virsmas detaļas kļūst smalkākas, bet faili lielāki. |
| `remesh` |  | boolean | no | `true` |  | Režģa topoloģijas pārbūve, kas parasti uzlabo turpmāko lietojumu, izveidojot tīrākus trijstūrus, taču pagarina apstrādi. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Pārbaudi var atslābināt, iestatot false, ja izsaucējam ir atļauja. |

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} | GLB formātā ģenerēts 3D modelis. |
| `seed` | integer | Faktiski izmantotā sākumvērtība. |

## 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