# Image Size and Dimensions

The figures in the table below, for example, the maximum number of images per stream, are experimentally tested and the values vary depending on your hardware configuration.

When working with images, observe the following considerations:

- As the number and the size of images get larger, the training Training is the process that your tool, which is a neural network, is learning about the features (pixels) based on the labels you made. For example, a tool will learn the defect/normal pixels in each image based on the defect/normal labels you drew. The goal of the tool Training is learning enough to give the correct inspection results of whether an unseen image is defective or not. The key to training is to ensure that you include all possible variations within your training set, and that your images are accurately labeled. Training times vary by the application, tool setup and the GPU in the PC being used to train the network. and processing time for all images increases as well.

- For Standard type Green Classify tools, images are automatically resized for training and processing to maximum 16 MP.

- The more memory (not GPU RAM) and hard disk capacity you have, the more and larger images you can handle.

- Using several hundred features per image with the Blue Locate tool slows down the user interface considerably.

Tool | Tool Type | Minimum Size | Maximum Size (Channel Parameter Set to 1 to 4) | Maximum Images per Stream | Maximum Trained Features per Image | Maximum Discrete Labeled Features | Maximum Number of Classes | Maximum Number of Defects per Image
Blue Locate | N/A | N/A | Images up to 32 MP (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. | 25000 | 1000 | 256 | N/A | N/A
Blue Read
Green Classify | Legacy | N/A | 25000 | N/A | N/A | 200 | N/A
Standard
Red Analyze | Legacy | N/A | 1000 | N/A | N/A | N/A | 1000
Standard | 96 x 96 (pixels)