it's okay I managed to solve the issue, dont worry about this anymore
On Monday, 28 April 2025 at 15:59:37 UTC+8 zdenop wrote:
>
>
> β Training failed: Command '['make', 'unicharset', 'lists',
>> 'proto-model', 'tesseract-langdata', 'training', 'MODEL_NAME=jpn1',
>> 'START_MODEL=jpn', 'TESSDATA=C:/Users/Chan Jian
>> Sen/Documents/TesseractFineT Training failed: Command
>
>
> Why are you showing us so much python code if your shell command fails? Or
> does it work in the terminal?
>
> ) BTW:
>
>> for fname in os.listdir(tessdata_path):
>> if fname.startswith(model_prefix) and fname.endswith(
>> ".traineddata"):
>> suffix = fname[len(model_prefix):-len(".traineddata")]
>
>
> What is your python version? 2.x? Have you heard about `pathlib` (or
> `glob`)?
>
> Zdenko
>
>
> po 28. 4. 2025 o 9:43 Jiansen Chan <[email protected]> napΓsal(a):
>
>> My goal is to automate model training in tesseract OCR for Japanese
>> words. The user should just paste ground truth files and picture files into
>> a particular folder, and then use that data to train a new model. this
>> process should be able to be carried out multiple times. Every single time
>> data is added to the folder I expect an automated model training.
>>
>> However, this is the error that i run into when I try to run automated
>> tesseract training on VSCode. What I did is that I had a script that uses
>> watchdog to detect newly added .tif/.png files alongside their
>> corresponding .gt.txt files into a particular folder (from which the model
>> is supposed to treat as training data and use it to train). The watcher
>> file looks something like this:
>>
>> (watcher.py)
>>
>> import time
>> import os
>> from watchdog.observers import Observer
>> from watchdog.events import FileSystemEventHandler
>> from pathlib import Path
>> from training.tesseract_training import run_tesseract_training
>> from training.training_model_utils import get_latest_and_next_model
>> WATCHED_FOLDER = r"C:\Users\Chan Jian Sen\Documents\ocr-japanese\I
>> NPUT_TRAINING_DATA" #ground truth put here
>> tesstrain_dir = r"C:\Users\Chan Jian Sen\Documents\T
>> esseractFineTuningJpn5\tesstrain"
>>
>> class TrainingInputHandler(FileSystemEventHandler):
>>
>> def on_modified(self, event):
>> self.check_and_trigger_training()
>>
>> def on_created(self, event):
>> self.check_and_trigger_training()
>>
>> def check_and_trigger_training(self):
>> files = os.listdir(WATCHED_FOLDER)
>> pngs = {Path(f).stem for f in files if f.endswith('.png')}
>> gts = {Path(f).stem for f in files if f.endswith('.gt.txt')}
>> common = pngs & gts
>>
>> if len(common) == 0:
>> print("β³ Waiting for matching .png and .gt.txt pairs...")
>>
>>
>> tessdata_path = r"C:\Users\Chan Jian Sen\Documents\T
>> esseractFineTuningJpn5\tessdata"
>> start_model, new_model = get_latest_and_next_model(tessdata_path)
>>
>> print(f"π Using {start_model} as base, training new model: {
>> new_model}") #problem here is the the old model they saw it as jpn and
>> the new model as jpn1
>>
>> run_tesseract_training(tesstrain_dir, new_model, start_model) #the
>> first parameter MUST be your tesstrain folder
>> observer.stop()
>>
>> if __name__ == "__main__":
>> print(f"π Watching training data folder: {WATCHED_FOLDER}")
>> event_handler = TrainingInputHandler()
>> observer = Observer()
>> observer.schedule(event_handler, WATCHED_FOLDER, recursive=False)
>> observer.start()
>>
>> try:
>> while observer.is_alive():
>> time.sleep(1)
>> except KeyboardInterrupt:
>> observer.stop()
>> observer.join()
>>
>>
>>
>>
>> To generate a new model name (since I want to automate model training), i
>> also have these functions here:
>> (training_model_utils.py)
>> import os
>>
>> def get_model_names(tessdata_path, model_prefix="jpn"):
>> models = []
>> for fname in os.listdir(tessdata_path):
>> if fname.startswith(model_prefix) and fname.endswith(
>> ".traineddata"):
>> suffix = fname[len(model_prefix):-len(".traineddata")]
>> if suffix == "":
>> models.append((0, "jpn"))
>> elif suffix.isdigit():
>> models.append((int(suffix), f"{model_prefix}{suffix}"))
>> models.sort()
>> return models
>>
>> def get_latest_and_next_model(tessdata_path, model_prefix="jpn"):
>> models = get_model_names(tessdata_path, model_prefix)
>> if not models:
>> return model_prefix, f"{model_prefix}2"
>> latest = models[-1][1]
>> next_num = models[-1][0] + 1
>> next_model = f"{model_prefix}{next_num}" if next_num > 0 else f"{
>> model_prefix}2"
>> return latest, next_model
>>
>> I also coded the make training procedure into VSCode, with a python
>> script that calls for it. This code snippet below is meant to run the
>> tesseract training.
>> (tesseract_training.py)
>> import subprocess
>> import os
>>
>> def run_tesseract_training(training_dir, model_name, start_model,
>> max_iterations=4000): #previously start model is jpn
>> """
>> Run the full Tesseract tesstrain workflow including unicharset and
>> langdata.
>> """
>> tessdata_path = r"C:\Users\Chan Jian Sen\Documents\T
>> esseractFineTuningJpn5\tessdata"
>> # Important: replace backslashes with forward slashes
>> tessdata_path = tessdata_path.replace("\\", "/")
>> command = [
>> "make",
>> "unicharset", "lists", "proto-model", "tesseract-langdata",
>> "training",
>> f"MODEL_NAME={model_name}",
>> f"START_MODEL={start_model}",
>> f"TESSDATA={tessdata_path}", # Adjust path depending on where
>> your .traineddata are
>> f"GROUND_TRUTH_DIR={training_dir}",
>> f"MAX_ITERATIONS={max_iterations}",
>> "LEARNING_RATE=0.001"
>> ]
>>
>> print("π Running full Tesseract training pipeline...")
>> try:
>> subprocess.run(command, cwd=r"C:\Users\Chan Jian Sen\Documents\T
>> esseractFineTuningJpn5\tesstrain", shell=True, check=True)
>> print(f"β
Training complete: {model_name}.traineddata generated."
>> )
>> except subprocess.CalledProcessError as e:
>> print(f"β Training failed: {e}")
>>
>> However, when I run the code an issue appears, and I'm not sure how to
>> deal with it:
>>
>>
>> PS C:\Users\Chan Jian Sen\Documents\ocr-japanese> c:; cd 'c:\Users\Chan
>> Jian Sen\Documents\ocr-japanese'; & 'c:\Users\Chan J
>> Sen\.vscode\extensions\ms-python.debugpy-2025.6.0-win32-x64\bundled\libs\debugpy\launcher'
>>
>> '58725' '--' 'C:\Users\Chan Jian S
>> π Watching training data folder: C:\Users\Chan Jian
>> Sen\Documents\ocr-japanese\INPUT_TRAINING_DATA
>> β³ Waiting for matching .png and .gt.txt pairs...
>> π Using jpn as base, training new model: jpn1
>> π Running full Tesseract training pipeline...
>> You are using make version: 4.4.1
>> Makefile:438: *** mixed implicit and normal rules: deprecated syntax
>> combine_tessdata -u C:/Users/Chan Jian
>> Sen/Documents/TesseractFineTuningJpn5/tessdata/jpn.traineddata data/jpn/jpn1
>> π Watching training data folder: C:\Users\Chan Jian
>> Sen\Documents\ocr-japanπ Watching training data folder: C:\Users\Chan Jian
>> Sen\Documents\ocr-japanese\INPUT_TRAINING_DATA
>> π Watching training data folder: C:\Users\Chan Jian
>> Sen\Documents\ocr-japanπ Watching training data folder: C:\Users\Chan Jian
>> Sen\Documents\ocr-japanese\INPUT_TRAINING_DATA
>> β³ Waiting for matching .png and .gt.txt pairs...
>> π Using jpn as base, training new model: jpn1
>> π Running full Tesseract training pipeline...
>> You are using make version: 4.4.1
>> Makefile:438: *** mixed implicit and normal rules: deprecated syntax
>> combine_tessdata -u C:/Users/Chan Jian
>> Sen/Documents/TesseractFineTuningJpn5/tessdata/jpn.traineddata data/jpn/jpn1
>> Failed to read C:/Users/Chan
>> make: *** [Makefile:207: data/jpn/jpn1.lstm-unicharset] Error 1
>> β Training failed: Command '['make', 'unicharset', 'lists',
>> 'proto-model', 'tesseract-langdata', 'training', 'MODEL_NAME=jpn1',
>> 'START_MODEL=jpn', 'TESSDATA=C:/Users/Chan Jian
>> Sen/Documents/TesseractFineT Training failed: Command '['make',
>> 'unicharset', 'lists', 'proto-model', ATIONS=4000', 'LEARNING_RATE=0.001']'
>> returned no
>> uningJpn5/tessdata', 'GROUND_TRUTH_DIR=C:\\Users\\Chan Jian
>> Sen\\Documents\\TesseractFineTuningJpn5\\tesstrain', 'MAX_ITERATIONS=4000',
>> 'LEARNING_RATE=0.001']' returned non-zero exit status 2.
>>
>> (Yellow parts is the error). Would greatly appreciate for any help given!
>> Sorry if it looks complicated hahah
>>
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>
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