ok, I will try as you said.
one more thing, what's the role of the trained_text lines will be? I have
seen Bengali text are long words of lines. so I wanna know how many words
or characters will be the better choice for the train?
and '--xsize=3600','--ysize=350', will be according to words of lines?
On Thursday, 10 August, 2023 at 1:10:14 am UTC+6 shree wrote:
> Include the default fonts also in your fine-tuning list of fonts and see
> if that helps.
>
> On Wed, Aug 9, 2023, 2:27 PM Ali hussain <mdalihu...@gmail.com> wrote:
>
>> I have trained some new fonts by fine-tune methods for the Bengali
>> language in Tesseract 5 and I have used all official trained_text and
>> tessdata_best and other things also. everything is good but the problem is
>> the default font which was trained before that does not convert text like
>> prev but my new fonts work well. I don't understand why it's happening. I
>> share code based to understand what going on.
>>
>>
>> *codes for creating tif, gt.txt, .box files:*
>> import os
>> import random
>> import pathlib
>> import subprocess
>> import argparse
>> from FontList import FontList
>>
>> def read_line_count():
>> if os.path.exists('line_count.txt'):
>> with open('line_count.txt', 'r') as file:
>> return int(file.read())
>> return 0
>>
>> def write_line_count(line_count):
>> with open('line_count.txt', 'w') as file:
>> file.write(str(line_count))
>>
>> def create_training_data(training_text_file, font_list, output_directory,
>> start_line=None, end_line=None):
>> lines = []
>> with open(training_text_file, 'r') as input_file:
>> for line in input_file.readlines():
>> lines.append(line.strip())
>>
>> if not os.path.exists(output_directory):
>> os.mkdir(output_directory)
>>
>> random.shuffle(lines)
>>
>> if start_line is None:
>> line_count = read_line_count() # Set the starting line_count
>> from the file
>> else:
>> line_count = start_line
>>
>> if end_line is None:
>> end_line_count = len(lines) - 1 # Set the ending line_count
>> else:
>> end_line_count = min(end_line, len(lines) - 1)
>>
>> for font in font_list.fonts: # Iterate through all the fonts in the
>> font_list
>> font_serial = 1
>> for line in lines:
>> training_text_file_name = pathlib.Path(training_text_file
>> ).stem
>>
>> # Generate a unique serial number for each line
>> line_serial = f"{line_count:d}"
>>
>> # GT (Ground Truth) text filename
>> line_gt_text = os.path.join(output_directory, f'{
>> training_text_file_name}_{line_serial}.gt.txt')
>> with open(line_gt_text, 'w') as output_file:
>> output_file.writelines([line])
>>
>> # Image filename
>> file_base_name = f'ben_{line_serial}' # Unique filename for
>> each font
>> subprocess.run([
>> 'text2image',
>> f'--font={font}',
>> f'--text={line_gt_text}',
>> f'--outputbase={output_directory}/{file_base_name}',
>> '--max_pages=1',
>> '--strip_unrenderable_words',
>> '--leading=36',
>> '--xsize=3600',
>> '--ysize=350',
>> '--char_spacing=1.0',
>> '--exposure=0',
>> '--unicharset_file=langdata/ben.unicharset',
>> ])
>>
>> line_count += 1
>> font_serial += 1
>>
>> # Reset font_serial for the next font iteration
>> font_serial = 1
>>
>> write_line_count(line_count) # Update the line_count in the file
>>
>> if __name__ == "__main__":
>> parser = argparse.ArgumentParser()
>> parser.add_argument('--start', type=int, help='Starting line count
>> (inclusive)')
>> parser.add_argument('--end', type=int, help='Ending line count
>> (inclusive)')
>> args = parser.parse_args()
>>
>> training_text_file = 'langdata/ben.training_text'
>> output_directory = 'tesstrain/data/ben-ground-truth'
>>
>> # Create an instance of the FontList class
>> font_list = FontList()
>>
>> create_training_data(training_text_file, font_list,
>> output_directory, args.start, args.end)
>>
>>
>> *and for training code:*
>>
>> 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)
>>
>>
>> any suggestion to identify to extract the problem.
>> thanks, everyone
>>
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>>
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