There was two file show how to traing with tesseract ,include comman_training and lstm training

comman_training.sh

#!/usr/bin/env bash

export PATH=$PATH:/home/tesseract/training

#for comman training
#step 1 : gen img
chmod +x ./gen_img.sh   
./gen_img.sh                            #gen_img is my script to generator the image, you can see it in my another gist

#step 2 : gen box file and gen tr file
for tifile in $(ls *.tif)
do
	tifname=`echo $tifile | awk -F "." '{print $2}'`
	tesseract --tessdata-dir /home/tessdata/ $tifile $tifname -l chi_sim batch.nochop makebox  
	tesseract -l chi_sim $tifile $tifname nobatch box.train
done
#step 3 : gen tr
#for tifile in $(ls *.tif)
#do
#	tifname=`echo $tifile | awk -F "." '{print $2}'`
#	tesseract -l chi_sim $tifile $tifname nobatch box.train
#done

#step 4 : gen unicharest
unicharset_extractor ./*.box
mv unicharset chi_sim.unicharset

#step 5 : gen font_propertis
ls *.tif | awk -F "." '{print $2, 0,0,0,0}' > font_properties

#step 6 : gen middle file 
	# gen shapetable
	shapeclustering -F font_properties -U chi_sim.unicharset *.tr
	# gen inttemp
	mftraining -F font_properties -U unicharset -O chi_sim.unicharset *.tr
	
	# gen normproto
	cntraining *.tr
	
#step 7 : rename file for combine_tessdata
	# rename
	for datafile in inttemp  normproto  pffmtable  shapetable  unicharset
	do 
		mv $datafile chi_sim.$datafile
	done	
	
	combine_tessdata chi_sim.		#please make sure your tr file and your datafile in the same folder

lstm_training.sh

#!/usr/bin/env bash
# step 1
# use fc-list check which font your want and change your languange.sh(this file in your training folder)

# step 2 : extract a lstm model from exist traineddata, if not you can training from scratch
combine_tessdata -e \
        /usr/local/share/tessdata/chi_sim.traineddata \
        ./chi_sim.lstm

# step 3 : use font file to gen train file and eval file for the lstm training
# gen train_file
tesstrain.sh --fonts_dir  /usr/share/fonts/fontfile/ \
        --lang chi_sim --linedata_only --noextract_font_properties \
        --langdata_dir /home/langdata  \
        --tessdata_dir ./tessdata \
        --output_dir /home/lstmtest/tesseract-ocr/chieval 
# gen eval_file
tesstrain.sh --fonts_dir /usr/share/fonts --lang chi_sim  --linedata_only \
      --langdata_dir ../langdata --tessdata_dir ./tessdata \
      --fontlist "STXinwei" \
      --output_dir /home/lstmtest/chitest
# step 4 : training, if you training from scratch, also you need to run a scollview.jar in another terminal
lstmtraining -U ./chitrain/chi_sim.unicharset  \
       --script_dir ../langdata \
       --debug_interval 0 \
       --continue_from ./trainlayer/chi_sim.lstm \
       --append_index 5 --net_spec '[Lfx256 O1c105]' \
       --model_output ./trainmodel \
       --train_listfile ./chitrain/chi_sim.training_files.txt --max_iterations 5000
 
 # step 5 : now you have a lot lstm file, especially when you increase the iterations, and you can combine it to have a new trained datafile
 combine_tessdata -o  ../chi_sim.traineddata \ 
        ../trainlayer/your_trained.lstm \  
        ./chi_sim.lstm-number-dawg \ 
        ./chi_sim.lstm-punc-dawg \
        ./chi_sim.lstm-word-dawg