Comments (2)
For the original paper refer to: https://arxiv.org/abs/1712.05586
The basic idea is: If you train a model on only a few lines of Ground Truth some characters might not be present yet (e. g. mostly some capital letters). Thus, usually the network can only predict characters that are in the GT. However, if you start from a pretrained model that already knows all (or even more) letters you can specify which letters shall be kept (whitelist). By that the newly trained has a chance to predict unseen characters based on the original model.
The whilelist
parameter expects a list of characters to be kept, e. g. --whitelist ABCDEFG...
. Alternatively, you can use a text file and the whitelist_file
parameter.
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thank you very much
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Related Issues (20)
- Argument "val.preload" documented but not known HOT 1
- Cannot convert a symbolic Tensor - Cannot even initialize the Predictor object HOT 2
- Characters coordinates HOT 1
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- HDF5 dataset format: how to convert HOT 4
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