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@@ -88,6 +88,11 @@ options and currently requiresloading training data into HDF5 files, instead
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of being trained off a list of image files directly (image file-based training
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will be added to `clstmctc` soon).
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The CLSTM project also provides LSTM-based language modeling that works very
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well with post-processing and correcting OCR output, as well as solving a number
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of other OCR-related tasks, such as dehyphenation or changes in orthography
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(see our publications). You can train language models using `clstmtext`.
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Generally, your best bet for CLSTM and OCRopy is to rely only on the command
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line tools; that makes it easy to replace different components. In addition, you
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should keep your OCR training data in .png/.gt.txt files so that you can easily

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