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

# Upload Labeled Images to Object Detection Projects

export const vp = 'Visual Prompting';

export const smartLabel = 'Smart Labeling';

export const productLL = 'LandingLens';

export const mi = 'Mobile Inference';

export const llsf = 'LandingLens on Snowflake';

export const companyName = 'LandingAI';

*This article applies to these versions of LandingLens:*

<table>
  <thead>
    <tr>
      <th>LandingLens</th>
      <th>LandingLens on Snowflake</th>
    </tr>
  </thead>

  <tbody>
    <tr>
      <td><span class="check-icon">✓</span></td>
      <td><span class="check-icon">✓</span></td>
    </tr>
  </tbody>
</table>

<iframe width="560" height="315" src="https://www.youtube.com/embed/9PYGQRThZ74?&wmode=opaque&rel=0" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen />

There are several ways to upload images into LandingLens, the Visual AI platform from LandingAI. Watch this video to learn how to upload a labeled Object Detection dataset into a LandingLens project.

LandingLens supports uploading labeled Object Detection datasets in the Pascal VOC format. We provide [Helper Scripts](https://github.com/landing-ai/helper-scripts/tree/main) to convert COCO and YOLO datasets to Pascal VOC.