lstmeval1
Evaluation program for lstm-based networks.
Usage
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]}
Overview
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.
Options
-
--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)
Resources
Main web site: https://github.com/tesseract-ocr Information on training tesseract LSTM: https://tesseract-ocr.github.io/tessdoc/TrainingTesseract-4.00.html
Copying
Copyright (C) 2012 Google, Inc. Licensed under the Apache License, Version 2.0
Releases
4 releases since Debian 10 (Buster); the text changed 3 times.