Thank you man. This is very useful.
On Tuesday, July 25, 2023 at 12:01:20 PM UTC+3 [email protected] wrote:
> make sure the command of the training file will be under tesstrain folder
> and run the first command for training data and if you train from any
> checkpoint then run the second post command.
> On Tuesday, 25 July, 2023 at 2:48:25 pm UTC+6 Ali hussain wrote:
>
>> import subprocess
>>
>> # List of font names
>> font_names = ['ben']
>>
>> for font in font_names:
>> command = f"lstmtraining --continue_from
>> data/ben/checkpoints/ben_19.535_298_300.checkpoint --traineddata
>> data/ben/ben.traineddata --model_output data/ben/checkpoints/ben
>> --train_listfile data/ben/list.train --eval_listfile data/ben/list.eval
>> --max_iterations 1000"
>> subprocess.run(command, shell=True)
>> i fixed the problem and this code work for me by adding the checkpoint.
>> On Thursday, 20 July, 2023 at 7:51:43 am UTC+6 Ali hussain wrote:
>>
>>> I'm new in Tesseract and trying to train my own fonts on Tesseract 5.3.2
>>> but I have to know if the electricity is cut off or if I cancel vs code or
>>> something like that of the process of training then if I run the training
>>> command again so after that it starts from begging or from electricity cut
>>> off?
>>>
>>> I have already to tested it but every time starts from begging. so I
>>> need to know any method to apply this problem to handle this. because it
>>> takes a lot of time and is not necessary to start by begging every time or
>>> it's normal?
>>>
>>>
>>> I use this command to create text-to-image.tif files for multiple fonts
>>> in Tesseract 5.3.2:
>>>
>>> import os
>>> import random
>>> import pathlib
>>> import subprocess
>>>
>>> training_text_file = 'langdata/ben.training_text'
>>> font_list = ['FL Badhon Ansari Rh. Unicode',
>>> 'F Khairuddin Barbarusa Rah. Uni',
>>> 'F Mahfuj Art Unicode Italic',
>>> 'F Mahfuj Art Unicode',
>>> 'FL Niribili Plain Unicode',
>>> 'FL Niribili Plain Unicode Itali Italic'
>>> ] # Add more fonts as needed
>>>
>>> lines = []
>>>
>>> with open(training_text_file, 'r') as input_file:
>>> for line in input_file.readlines():
>>> lines.append(line.strip())
>>>
>>> output_directory = 'tesstrain/data/ben-ground-truth'
>>>
>>> if not os.path.exists(output_directory):
>>> os.mkdir(output_directory)
>>>
>>> random.shuffle(lines)
>>>
>>> count = 100
>>>
>>> lines = lines[:count]
>>>
>>> line_count = 0
>>> for line in lines:
>>> for font in font_list:
>>> training_text_file_name = pathlib.Path(training_text_file).stem
>>> line_training_text = os.path.join(
>>> output_directory,
>>> f'{training_text_file_name}_{line_count}.gt.txt')
>>> with open(line_training_text, 'w') as output_file:
>>> output_file.writelines([line])
>>>
>>> file_base_name = f'ben_{line_count}'
>>>
>>> subprocess.run([
>>> 'text2image',
>>> f'--font={font}',
>>> f'--text={line_training_text}',
>>> f'--outputbase={output_directory}/{file_base_name}',
>>> '--max_pages=1',
>>> '--strip_unrenderable_words',
>>> '--leading=32',
>>> '--xsize=3600',
>>> '--ysize=350',
>>> '--char_spacing=1.0',
>>> '--exposure=0',
>>> '--unicharset_file=langdata/ben.unicharset'
>>> ])
>>>
>>> line_count += 1
>>>
>>>
>>>
>>> and this command is for training :
>>>
>>> import subprocess
>>>
>>> # List of font names
>>> font_names = ['ben']
>>>
>>> for font in font_names:
>>> command = f"TESSDATA_PREFIX=../tesseract/tessdata make training
>>> MODEL_NAME={font} START_MODEL=ben TESSDATA=../tesseract/tessdata
>>> MAX_ITERATIONS=10000 LANG_TYPE=Indic"
>>> subprocess.run(command, shell=True)
>>
>>
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