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Evaluation can be used in the following modules:
/wiki/spaces/KB3141/pages/533529141
/wiki/spaces/KB3141/pages/533529197
/wiki/spaces/KB3141/pages/533529217
/wiki/spaces/KB3141/pages/533529284
/wiki/spaces/KB3141/pages/533529337
/wiki/spaces/KB3141/pages/533529386Anomaly Detector
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.
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The evaluation considers the number of anomalies and compares it with a threshold value. More information on calculating the threshold can be found here. If the values are bigger than the threshold, the image is evaluated as NOK, otherwise, it is considered OK.
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The value determines the number of anomalies that are tolerated.
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Detector, Classifier, Surface Detector, Measure
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Images are evaluated based on set rules. If the image follows all of the rules it is considered OK, otherwise it is NOK.
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If you set the rules for a trained model and then train another one, the rules are automatically copied to the new model, so you don’t need to set them again if no changes in evaluation are needed. |
OCR
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 multiple regexes and then the result will only be true if all of them are found in the image.
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