# Cognex Deep Learning Tool Operation Guidelines

The following guidelines will help you determine how best to configure your Deep Learning application, within these operational parameters. The figures in the table below (for example the maximum number of images per stream) are experimentally tested and the values vary more or less on which hardware settings you rely. Generally, the larger your memory (not GPU RAM) and hard disk capacity you have, the more the number and the size of the image you can handle.

Image and Deep Learning Tools | Configuration | Maximum Supported Value
--- | --- | ---
Images | Maximum image size (Channel parameter set to 1 to 4) | Images up to 32MP (up to 16k in height or width) are supported Images up to 32k pixels wide (in one dimension, dependent upon GPU resources) Images over 32k are not supported
Maximum number of images per stream | Red Analyze tool = 1000
Blue Locate, Blue Read and Green Classify tools = 25000
Blue Locate and Blue Read tools | Maximum number of trained features in an image | 1000
Maximum number of discrete labeled features | 256
Red Analyze tool, Supervised and Unsupervised Mode | Maximum number of defects per image | 1000
Green Classify tool | Maximum number of classes | 200

Tip: As the number and the size of images are getting larger, the training and processing time for all images increases as well.