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During annotations it is important to find the ideal feature size. This value determines the size of the defects the model is able to reliably find. To find out more, open the following page Feature Size (TODO)
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Very small feature size on big defects is allowed but not ideal for performance and reliability. |
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Wrong feature size can make certain rectangles invalid. If such a thing occurs PEKAT is going to notify you before the training with possible solutions.
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Include
In case your dataset contains empty images or images with no defects, it is possible to add them into training with the Include button.
This way the model learns how empty images look and therefore it should improve detection accuracy.
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Auto-annotations
To speed up the annotation process, there is a possibility to train a model on a small number of annotations first and then use the predictions of this model to quickly make more annotations for further training.
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This adds the option to classify the object into one of the classes. If the classification is enabled, each marked object needs a class to be assigned to it. Class management is the same as in classifier and the annotations change color based on the assigned class for better visibility.
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For more details visit Classifier. This can also be achieved by combining Detector and Classifier as separate modules as described in the video below. However, classifying objects directly in the detector is easier and faster.
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