> For the complete documentation index, see [llms.txt](https://jtheta-ai.gitbook.io/docs.jtheta.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://jtheta-ai.gitbook.io/docs.jtheta.ai/domain-specific-workflow/lidar-image-annotation/export-lidar-datasets.md).

# Export LiDAR Datasets

Once annotation and validation are complete, export the finalized LiDAR dataset from **Datasets > \[Project Name]**.

Before exporting, review the right-side configuration panel.

<figure><img src="/files/ZyfmeHP0ngY1Ef74bWFa" alt=""><figcaption></figcaption></figure>

## **Pre-Export Validation Checklist**

### **1. Release Version**

* Confirm the correct version (e.g., **v1.0**) is selected.
* Click **Release New Version** if you need to freeze the current state.

Each release version captures:

* All annotated frames
* Object instances and class mappings
* Frame-level metadata
* Media configuration

> Only released versions can be exported.

### **2. Annotation Summary**

Verify object counts (e.g., Pedestrian, Car, Cyclist).

This ensures:

* No missing annotations
* No accidental deletions
* Expected class distribution before export

### **3. Annotation Opacity (Validation Tool)**

The **Annotation Opacity** slider adjusts bounding box transparency (visual only — does not affect export).

Use it to:

* Check 3D box alignment with the LiDAR point cloud
* Verify box tightness and orientation
* Inspect overlapping objects

**Best practice:**

* Lower opacity → inspect point cloud density
* Higher opacity → validate box placement

### **4. Media Attributes**

The **Media Attributes** section displays essential metadata associated with the selected LiDAR file. This information ensures data consistency, traceability, and export readiness.

**Best practice:**\
Review and standardize all required attributes before export to ensure data quality and consistency.

## **Export Process**

#### **1. Open Export Modal**

Click **Download** (top-right).

#### **2. Select Version**

Example: **v1.0**\
Always confirm the intended release version.

#### **3. Select Format (LiDAR Supported)**

Available formats:

* **KITTI**
* **nuScenes**
* **Supervisely**
* **Custom JSON**
* **Custom CSV**

**Quick Guidance**

* **KITTI** – Standard 3D object detection format
* **nuScenes** – Multi-sensor and calibration support
* **Supervisely** – Platform-compatible structure
* **Custom JSON** – Flexible structured export
* **Custom CSV** – Tabular format for QA/analytics

## **Export Includes**

Depending on format, the package may contain:

* 3D bounding box parameters\
  \&#xNAN;*(x, y, z, length, width, height, rotation/yaw)*
* Class labels
* Object instance IDs
* Frame metadata
* Sensor metadata
* Multiview alignment data (if applicable)
* Media attributes (format-dependent)

## **Final Step**

After confirming version and format:

👉 Click **Download**

The system generates a structured LiDAR dataset package ready for training or deployment.

Exports include:

* 3D bounding box coordinates
* Class labels
* Frame metadata
* Multiview alignment data (if applicable)

<figure><img src="/files/Tj0pSFJVtkV4QhHdQrH4" alt=""><figcaption></figcaption></figure>

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