Classifying images (console) - Amazon Lookout for Vision

End of support notice: On October 31, 2025, AWS will discontinue support for Amazon Lookout for Vision. After October 31, 2025, you will no longer be able to access the Lookout for Vision console or Lookout for Vision resources. For more information, visit this blog post.

Classifying images (console)

You use the Lookout for Vision console to classify images in a dataset as normal or an anomaly. Unclasified images aren’t used to train your model.

If you're creating an image segmentation model, skip this procedure and do Segmenting images (console), which includes steps to classify images.

Note

If you've just completed Creating your dataset, the console should currently show your model dashboard and you don't need to do steps 1 - 4.

To classify your images (console)

  1. Open the Amazon Lookout for Vision console at https://console.aws.amazon.com/lookoutvision/.

  2. In the left navigation pane, choose Projects.

  3. In the Projects page, choose the project that you want to use.

  4. In the left navigation pane of your project, choose Dataset.

  5. If you have separate training and test datasets, choose the tab for the dataset that you want to use.

  6. Choose Start labeling.

  7. Choose Select all images on this page.

  8. If the images are normal, choose Classify as normal, otherwise choose Classify as anomaly. A label appears underneath each picture.

  9. If you need to change the label for an image, do the following:

    1. Choose Anomaly or Normal under the image.

    2. If you can't determine the correct label for an image, magnify the image by choosing the image in the gallery.

    Note

    You can filter image labels by choosing the desired label, or label state, in the Filters section.

  10. Repeat steps 7-9 on each page as necessary until all the images in the dataset have been labeled correctly.

  11. Choose Save changes.

  12. If you've finished labeling your images, you can train your model.