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Extend Model for OCR Module
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Training data split
By adjusting the training data split you can choose how many of the images you annotated will be used for training and how many will be used for testin (the testing images will be used to calculate statistics that are displayed in the Confusion matrix).
The images are split between training and testing pseudo-randomly. A seed is used to initiate a random number generator that is used to split the images. This means that the same seed results in the same data split.
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The split with the same seed will only be the same with the same image set. If you add or remove images (to the project as a whole, not annotations) then the wplit will be different. |
Augmentation
For a detailed explanation regarding augmentation, visit the article Augmentation Glossary.
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