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# Training Image Guidelines

Image Server creates a model of each face to recognize in a database.

You can provide multiple training images for each face model; however, in most cases HPE recommends providing only one good quality image of a face that best matches the expected appearance of the face in recognition tasks. If you expect a face to show considerable variation, for example a person who occasionally wears spectacles, it can be beneficial to use multiple training images. Keep the number of additional training images to a minimum, focusing on providing as few good quality representations of the face as needed to cover all anticipated recognition scenarios.

It is important to use good quality training images to populate the database. Each image should fulfill the following criteria:

- contain a direct, frontal view of one face only, with the face constituting the majority of the image

- be free from large compression artifacts

- have a reasonable resolution, with the face being at least 150 pixels wide

- illumination should be even across the face, so that no area of the face is washed out or shadowed

- not be blurred

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