lstmeval --model lang.lstm|modelname_checkpoint|modelname_N.NN_NN_NN.checkpoint [--traineddata lang/lang.traineddata] --eval_listfile lang.eval_files.txt [--verbosity N] [--max_image_MB NNNN]
lstmeval(1) evaluates LSTM-based networks. Either a recognition model or a training checkpoint can be given as input for evaluation along with a list of lstmf files. If evaluating a training checkpoint, --traineddata should also be specified. Intermediate training checkpoints can also be used.
- --model FILE
Name of model file (training or recognition) (type:string default:)
- --traineddata FILE
If model is a training checkpoint, then traineddata must be the traineddata file that was given to the trainer (type:string default:)
- --eval_listfile FILE
File listing sample files in lstmf training format. (type:string default:)
- --max_image_MB INT
Max memory to use for images. (type:int default:2000)
- --verbosity INT
Amount of diagnosting information to output (0-2). (type:int default:1)
lstmeval(1) was first made available for tesseract4.00.00alpha.
Main web site: https://github.com/tesseract-ocr Information on training tesseract LSTM: https://tesseract-ocr.github.io/tessdoc/TrainingTesseract-4.00.html
Copyright (C) 2012 Google, Inc. Licensed under the Apache License, Version 2.0
The Tesseract OCR engine was written by Ray Smith and his research groups at Hewlett Packard (1985-1995) and Google (2006-present).