Prepare example images - Amazon Lookout for Vision

Prepare example images

Amazon Lookout for Vision provides example images of circuit boards that AWS customers can use to learn how to create, test, and use an image classification model.

You can copy the images from the https://github.com/aws-samples/amazon-lookout-for-vision GitHub repository. The images are in the circuitboard folder.

The circuitboard folder has the following folders.

  • train – Images you can use in a training dataset.

  • test – Images you can use in a test dataset.

  • extra_images – Images you can use to run a trial detection or to try out your trained model with the DetectAnomalies operation.

The train and test folders each have a subfolder named normal (contains images that are normal) and a subfolder named anomaly (contains images with anomalies).

Note

Later, when you create a dataset with the console, Amazon Lookout for Vision can use the folder names (normal and anomaly) to automatically label the images. For more information, see Creating a dataset using images stored in an Amazon S3 bucket.

To prepare the dataset images

  1. Clone the https://github.com/aws-samples/amazon-lookout-for-vision repository to your computer. For more information, see Cloning a repository.

  2. Create an Amazon S3 bucket. For more information, see How do I create an S3 Bucket?.

  3. At the command prompt, enter the following command to copy the dataset images from your computer to your Amazon S3 bucket.

    aws s3 cp --recursive your-repository-folder/circuitboard s3://your-bucket/circuitboard