Hello, I tried to train a traineddata file myself, but an [Error] occurred during use. Could you please give me some guidance on how to resolve this error? Thank you very much. Perform OCR ··· tesseract 0791.tif stdout -l my_chi_sim --psm 6 --oem 2 ··· The error content is: ···· Error: Tesseract (legacy) engine requested, but components are not present in /usr/local/share/tessdata/my_chi_sim.traineddata!! Failed loading language 'my_chi_sim' Tesseract couldn't load any languages! Could not initialize tesseract. ····
My training steps are as follows: Punctuation Dictionary: dawg2wordlist d:\tesseract\tessdata_best\chi_sim.lstm-unicharset d:\tesseract\tessdata_best\chi_sim.lstm-punc-dawg d:\tesseract\tessdata_best\punc.txt Let’s start with the key steps 2. Generate character set lstm-unicharset file 1. Generate character set txt file text2image --text d:\tesseract\chi_sim.txt --outputbase d:\tesseract\chi_sim --fonts_dir C:\Windows\Fonts --font="simhei" --fontconfig_tmpdir d:\tesseract\tmp 3. Generate character set lstm-unicharset file 1) Generate with box file unicharset_extractor --norm_mode 3 --output_unicharset d:\tesseract\chi_sim.lstm-unicharset d:\tesseract\chi_sim.box 2) Generate with txt file unicharset_extractor --norm_mode 3 --output_unicharset d:\tesseract\chi_sim.lstm-unicharset d:\tesseract\chi_sim.txt 3. Generate starter traineddata file 1. Generate dictionary text file Refer to the 3 dictionary files in the d:\tesseract\tessdata_best folder (word text, number numbers, punc punctuation marks) 2. Generate starter traineddata file combine_lang_model --input_unicharset d:\tesseract\chi_sim.lstm-unicharset --lang chi_sim --script_dir d:\tesseract\langdata_lstm --output_dir d:\tesseract --version_str "CSDN:watt:2022.04[1,48,0,1C3,3Ft16Mp3,3TxyLfys64Lfx96RxLrx96Lfx512O1c4000]" --words d:\tesseract\word.txt --numbers d:\tesseract\number.txt --puncs d:\tesseract\punc.txt --pass_through_recoder 3. View the newly generated starter trained data information combine_tessdata -d d:\tesseract\chi_sim\chi_sim.traineddata 4. Generate training files 1. Generate the training text file train.txt 2. Generate picture+box file text2image --text d:\tesseract\train.txt --outputbase d:\tesseract\train --fonts_dir C:\Windows\Fonts --font="simhei" --ptsize 18 --fontconfig_tmpdir d:\tesseract\tmp 3. Generate training files: tesseract d:\tesseract\train.tif d:\tesseract\train -l chi_sim --psm 6 lstm.train 4. Create a new training list file Create a new d:\tesseract\train_listfile.txt file with the content d:\tesseract\train.lstmf 5. Training 2. Start training: lstmtraining --traineddata d:\tesseract\chi_sim\chi_sim.traineddata --net_spec "[1,48,0,1Ct3,3,16 Mp3,3 Lfys64 Lfx96 Lrx96 Lfx512 O1c4000]" --model_output d:\tesseract\output\output --train_listfile d:\tesseract\train_listfile.txt --max_iterations 0 --target_error_rate 0.01 --debug_interval -1 6. Evaluate the generated checkpoint file 1. Generate evaluation text eval.txt Edit some evaluation text and save it to d:\tesseract\eval.txt, so as to cover it as comprehensively as possible and with a certain degree of complexity. 2. Generate picture+box file text2image --text d:\tesseract\eval.txt --outputbase d:\tesseract\eval --fonts_dir C:\Windows\Fonts --font="simhei" --ptsize 18 --fontconfig_tmpdir d:\tesseract\tmp 3. Generate evaluation lstmf file tesseract d:\tesseract\eval.tif d:\tesseract\eval -l chi_sim --psm 6 lstm.train 4. Generate evaluation list file Create a new d:\tesseract\eval_listfile.txt file with the content d:\tesseract\eval.lstmf 5. Start evaluating Start evaluating: lstmeval --model d:\tesseract\output\output_checkpoint --traineddata d:\tesseract\chi_sim\chi_sim.traineddata --eval_listfile d:\tesseract\eval_listfile.txt 7. Generate standard trained data 1. Generate a floating point (decimal) traineddata file (similar to tessdata_best) lstmtraining --stop_training --continue_from d:\tesseract\output\output_checkpoint --traineddata d:\tesseract\chi_sim\chi_sim.traineddata --model_output d:\tesseract\output\chi_sim.traineddata 2. Generate an integer traineddata file (similar to tessdata_fast) lstmtraining --stop_training --convert_to_int --continue_from d:\tesseract\output\output_checkpoint --traineddata d:\tesseract\chi_sim\chi_sim.traineddata --model_output d:\tesseract\output\chi_sim.traineddata 3. View the generated traineddata information combine_tessdata -d d:\tesseract\output\chi_sim.traineddata -- You received this message because you are subscribed to the Google Groups "tesseract-ocr" group. To unsubscribe from this group and stop receiving emails from it, send an email to tesseract-ocr+unsubscr...@googlegroups.com. To view this discussion visit https://groups.google.com/d/msgid/tesseract-ocr/4f54b4ff-f1f4-4e44-9e49-11a70b759d68n%40googlegroups.com.
