Preparing images

The images in your training and test dataset contain the objects, scenes, or concepts that you want your model to find.

The content of images should be in a variety of backgrounds and lighting that represent the images that you want the trained model to identify.

This section provides information about the images in your training and test dataset.

Image format

You can train Amazon Rekognition Custom Labels models with images that are in PNG and in JPEG format. Similarly, to detect custom labels using DetectCustomLabels, you need images that are in PNG and JPEG format.

Input image recommendations

Amazon Rekognition Custom Labels requires images to train and test your model. To prepare your images, consider following:

• Choose a specific domain for the model you want to create. For example, you could choose a model for scenic views and another model for objects such as machine parts. Amazon Rekognition Custom Labels works best if your images are in the chosen domain.

• Use at least 10 images to train your model.

• Images must be in PNG or JPEG format.

• Use images that show the object in a variety of lightings, backgrounds, and resolutions.

• Training and testing images should be similar to the images that you want to use the model with.

• Decide what labels to assign to the images.

• Ensure that images are sufficiently large in terms of resolution. For more information, see Guidelines and quotas in Amazon Rekognition Custom Labels.

• Ensure that occlusions don't obscure objects that you want to detect.

• Use images that have sufficient contrast with the background.

• Use images that are bright and sharp. Avoid using images that may be blurry due to subject and camera motion as much as possible.

• Use an image where the object occupies a large proportion of the image.

• Images in your test dataset shouldn't be images that are in the training dataset. They should include the objects, scenes, and concepts that the model is trained to analyze.

Image set size

Amazon Rekognition Custom Labels uses a set of images to train a model. At a minimum, you should use at least 10 images for training. Amazon Rekognition Custom Labels stores training and testing images in datasets. For more information, see Creating training and test datasets with images.