Automatically decides whether the image is OK or NOK. This information is represented by a green or red stripe in the corner of each image in the image preview.

Evaluation can be used in the following modules: Anomaly of Surface, Surface Detector, Detector, Classifier and Measure. If one of the modules in flow uses evaluation, this evaluation will affect next modules. In case the next module uses evaluation as well it will overwrite the results of previous evaluation.

When you use parallelism, a boolean operator AND is used among the branches. That means if one of the branches has a NOK result, the overall result will be NOK as well.

Anomaly of Surface

First you need to generate automatic sensitivity graph.

Evaluation considers sizes of anomalies and compares it with a threshold value. If the values are bigger than the threshold, image is evaluated as NOK, otherwise it is considered OK.


To activate this function, you need to tick the ‘Evaluation’ button above the generated sensitivity graph. When processing is active, it evaluates image as valid (green stripe) or invalid (red stripe).


Value which determines the amount of anomalies that are tolerated.

Detector, Classifier, Surface Detector, Measure, OCR

Images are evaluated based on set rules. If image follows all of the rules it is considered OK, otherwise it is NOK.

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