# Xgrids Gaussian Splat Export

All Xgrids scanners (PortalCam, L2 Pro, K1/K2) can produce a Gaussian Splat reconstruction via **Lixel CyberColor**. This page walks through the export steps and how to package the output for upload to Multiset.

{% hint style="info" %}
For the e57 point-cloud workflow, see [Xgrids Scans](https://docs.multiset.ai/basics/third-party-scans/xgrids-scans) instead. The steps below are specific to the **Gaussian Splat** upload path.
{% endhint %}

#### You will need

* An Xgrids scan (PortalCam, L2 Pro, K1/K2).
* **Lixel CyberColor** (v1.12.1 or newer) — available from Xgrids support downloads.

## Step 1: Generate the Gaussian Splat model

1. Open **Lixel CyberColor** and click **Create** to start a new model.
2. Choose **Single Model** as the reconstruction type.
3. Give the project a name (e.g. `splats_for_vps`) and set the **Scan data** path to your captured `portalcam_capture_data` folder.
4. In the **Parameters** panel on the right:
   * **Reconstruction Settings**: choose **Slow** for the best quality suitable for VPS.
   * **Maximum Gaussian Splats**: leave at the recommended value (e.g. `28M`) or raise it for larger scenes.
   * **Portability**: **On**. This is important, it produces a metric-scaled, portable output that Multiset VPS can use.
   * Leave **Exposure Optimization** and **Low Memory Reconstruction** at defaults unless you have a specific reason to change them.
5. Click **Start** and let the reconstruction run.

<figure><img src="https://3163433004-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FokTDI7QVY04Zvb1pQ8Ry%2Fuploads%2Fgit-blob-c424a7fc8c5e512532708364b6ddd75b405fd8e3%2Fxgrids-gs-generate-model.png?alt=media" alt=""><figcaption><p>Lixel CyberColor — Generate Model with Portability On and Slow reconstruction.</p></figcaption></figure>

{% hint style="warning" %}
**Portability must be On.** Without it the Gaussian Splat will not be in metric scale and cannot be used for VPS.
{% endhint %}

## Step 2: Locate the exported `.ply`

Once the reconstruction finishes, Lixel CyberColor writes the point cloud (`.ply`) outputs under the project's output directory:

```
<output>\ply-result\point_cloud\iteration_100\
```

Inside `iteration_100` you will find files like:

* `point_cloud.ply` ← **this is the file you upload**
* `point_cloud_1.ply`, `point_cloud_2.ply`, `point_cloud_3.ply` (lower levels of detail)
* `environment.ply`

Use the top-level **`point_cloud.ply`** — it's the full-resolution Gaussian Splat.

<figure><img src="https://3163433004-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FokTDI7QVY04Zvb1pQ8Ry%2Fuploads%2Fgit-blob-f50678fb89cb79eef8f21e89bf12a1caa798ef67%2Fxgrids-gs-point-cloud-ply.png?alt=media" alt=""><figcaption><p>point_cloud.ply inside <code>output\ply-result\point_cloud\iteration_100</code>.</p></figcaption></figure>

## Step 3: Locate `poses.json`

The camera poses used to train the splat are written by Lixel CyberColor at:

```
<DATA>\<project-id>\output\render\assets\poses.json
```

<figure><img src="https://3163433004-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FokTDI7QVY04Zvb1pQ8Ry%2Fuploads%2Fgit-blob-3101ad077fae7c9108b10414dcf6bd9f0c455a02%2Fxgrids-gs-poses-json.png?alt=media" alt=""><figcaption><p>poses.json inside <code>output\render\assets</code>.</p></figcaption></figure>

This file contains an array of per-frame poses (`ts`, translation `T`, rotation quaternion `R`) that Multiset uses to register the splat against query images.

## Step 4: Zip `.ply` and `poses.json` together

Multiset expects a **single zip** containing both files at the root:

```
my-xgrids-splat.zip
├── point_cloud.ply
└── poses.json
```

Select both files, right-click → **Compress** (macOS) or **Send to → Compressed (zipped) folder** (Windows).

{% hint style="warning" %}
Do not place the files inside a subfolder inside the zip. Multiset reads them from the root of the archive.
{% endhint %}

## Step 5: Upload to Multiset

On the Multiset developer portal:

1. Open **Upload Existing Map**.
2. **Select Provider** → **XGRIDS**.
3. **File Format** → **Gaussian Splat (ply and poses.json compressed in same zip)**.
4. Click **Next** and answer the configuration prompts:
   * *Is the Gaussian Splat metric scaled?* → **Yes** (because Portability was On in Step 1).
   * *Indoor or outdoor?* → pick the one that matches your capture.
   * *Does the Gaussian Splat have poses.json?* → **Yes**.
5. Upload the zip from Step 4.

<figure><img src="https://3163433004-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FokTDI7QVY04Zvb1pQ8Ry%2Fuploads%2Fgit-blob-82018630a86f03ad96d1c6d023f898d9ff665ce2%2Fmultiset-upload-gs-xgrids.png?alt=media" alt="" width="375"><figcaption><p>Upload Existing Map — XGRIDS + Gaussian Splat file format.</p></figcaption></figure>

<figure><img src="https://3163433004-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FokTDI7QVY04Zvb1pQ8Ry%2Fuploads%2Fgit-blob-3cb7e1eed6262f6060e6fb1d21cceea70ac0ebc7%2Fmultiset-upload-gs-config.png?alt=media" alt="" width="375"><figcaption><p>Gaussian Splat configuration — metric-scaled / indoor-outdoor / poses.json.</p></figcaption></figure>

Once processing completes the map behaves like any other Multiset map — you can query it via the REST API, Unity SDK, or native SDKs.