---
title: "Visualize point cloud data"
slug: "point-cloud-data"
updated: 2025-08-18T12:07:04Z
published: 2025-08-18T12:07:04Z
canonical: "docs.akridata.ai/point-cloud-data"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.akridata.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Visualize point cloud data

The Visual Data Copilot platform allows you to import point cloud data into your dataset and visualize it interactively.

> Point cloud images in PCD format are currently supported.

This article describes the steps to view the point cloud data images.

1. Once you create a Dataset by ingesting the images, create a CSV file with the regular image path and [the PCD file path](https://docs.akridata.ai/docs/import-raw-files).
2. Create a view that joins a primary table with the imported table with PCD file information. Refer to [Catalog Views](https://docs.akridata.ai/docs/view-actions) for the general steps to create a view.
  1. Select ‘**Add Blob Type Mapping**’ for this specific use case in the ‘**Type Mapping**’ step of the view creation flow.
  2. In the following dialog box, select **Container** as the container where the PCD files have been uploaded. Select **Type** as ‘AKD_PointCloudFilePCD’ and select the column name holding the relative file path to the PCD files. The **Mapped Column Name** field will be auto-filled to a unique name, which you can edit as required. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/create-view-type-mappings(1).jpg)
3. Click the **Visualize** button to create a visualization job from the above-created view. Refer to [job creation](https://docs.akridata.ai/data-explorer/docs/create-an-explore-job) for general steps to create the job. While creating the job, ensure the **Select Job Type** is set to **Explore**.
4. Click **View Job** to open the **Explore Jobs** screen. Once the process is completed, you will see the **Visualize** option for that job.
5. In the **Explore Jobs** screen, click **Visualize** on the job card. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/pdc-view.jpg)
6. Click any points to load the corresponding images. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/pcd-view-image.jpg)
7. Click the expand icon on any selected image to view the image in full resolution. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/pdc-view-images.jpg)
8. Click the **Load Lidar data** option on the top. Depending on the image size, the loading might take some time. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/pdc-view-full-image.jpg)
9. Once the Lidar data is loaded, click the **Open Lidar view** option. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/open-lidar-view.jpg) This action opens the Lidar image in 3D format, displaying more in-depth information about the image for better analysis. ![](https://cdn.document360.io/3e9d4528-fbc6-4948-a804-8ee7068e7ac3/Images/Documentation/lidar-data-image.jpg)
  1. **Zoom in/Zoom out**: Use the zoom in and out icons for better viewing.
  2. **Rotate image**: Use the left, right, up, and down arrow icons to rotate and view the PCD image in different directions for better analysis.
  3. **Color picker**: Click the color pen icon on the top-right corner to change the background color for better visuals as relevant to the image. Refer to the following video to learn how to [navigate and analyze lidar data](https://akridata-ai.portal.trainn.co/share/BrKYHIG0kyczKorI8vcYWg/embed) using the toolbar options.

[Embedded content](https://akridata-ai.portal.trainn.co/share/BrKYHIG0kyczKorI8vcYWg/embed)

A dataset is an entity that specifies a selector on the contents of the container. A dataset can be of Image or Video type. The selector is a glob pattern like *.png