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DownloadPricingDocumentationBlogChangelog
  • Installation
  • Install LabelMe as App
  • Install LabelMe using Terminal
  • Install LabelMe using Terminal (old way)
  • Install LabelMe Toolkit
  • All released versions
  • Troubleshoot
  • Toolkit Docs
  • ai-annotate-rectangles
  • ai-text-to-annotations
  • ai-rectangle-to-mask
  • export-to-voc
  • export-to-yolo
  • extract-image
  • import-from-yolo
  • json-to-mask
  • json-to-masks
  • json-to-visualization
  • list-labels
  • print-stats
  • rename-labels
  • resize-image
  • Starter Guide
  • 1. Annotate image with LabelMe
  • 2. Open and edit annotated file
  • 3. Load annotated file with Python
  • 4. Export annotated file to PNG
  • 5. Load exported files with Python
  • Dataset Guide
  • 1. Download real dataset
  • 2. Verify dataset visually
  • 3. Verify dataset statistically
  • 4. Additional data collection
  • 5. Export dataset
  • Bonus: PyTorch dataset class

2. Verify dataset visually

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1. Visualize the JSON files#

First of all, we'd like to know how the dataset looks like.


To check the annotations visually, let's use json-to-visualization tool.

labelmetk json-to-visualization amazon-picking-challenge-2016 -b

-b option for json-to-visualization

-b = --browser to open a browser to see the images as a table.

The output should look like below:

If you're a Pro member, sign in 🔒️ to read the rest of the guide. Or check our plans if you don't have them yet.

  • 1. Visualize the JSON files#
  • 2. What we can see#
  • 3. Refine the annotation#