Automatically decides whether the an image is OK or NOK
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Evaluation can be used in the following modules:
If one of the modules in flow uses evaluation, this evaluation will affect the next modules. In case the next module uses evaluation as well it will overwrite the results of the previous evaluation.
When you use parallelism Parallelism, a boolean operator AND is used among the branches. That means if one of the branches has a NOK an
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Anomaly Detector
The evaluation considers the number of anomalies and compares it with a threshold value. More information on calculating the threshold can be found here Anomaly Detector. If the values are bigger than the threshold, the image is evaluated as NOK
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Evaluation
To activate this function, you need to tick the ‘Evaluation’ Evaluation button above the generated sensitivity graph. When processing is active, it evaluates the image as valid (green stripe) or invalid (red stripe).
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Threshold
The value determines the number of anomalies that are tolerated. Higher values filter out the defects that have lower confidence.
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Lower values keep most of the defect detections.
The threshold can be recalculated and tweaked to fit the needs of the project.
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Evaluation conditions
Images are evaluated based on a set rules. If the image follows all of the rules it is considered OK
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It is possible to set multiple groups of conditions. Each being evaluated with a logical AND or OR based on the current needs. You are able to select all detections as well as individual classes.
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If there are multiple classes, the rules can be set for a specific class or one of Any/Every/Together.
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The evaluation in the OCR module is based on the comparison of the results found in the image with the specified regex. It is possible to add specify multiple regexes and then the result will only be true if all of them are found in the image.
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rules and check if at least one is filled (use OR)
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