def setup_test_init():
"""Function that should be called in the root __init__ of all tests
The call ensures that the Devices and the logging are initialized correctly
"""
DeviceConfig(DeviceConfigParams())
logging.logger(__name__).debug("Set up device config for testing")
import argparse
import os
import shutil
import tfaip.util.logging as logging
from tfaip.data.pipeline.definitions import PipelineMode
from tqdm import tqdm
from calamari_ocr.ocr import CrossFold
from calamari_ocr.ocr.dataset.datareader.file import FileDataParams
from calamari_ocr.utils import split_all_ext, glob_all
logger = logging.logger(__name__)
def main():
parser = argparse.ArgumentParser(
description="Write split of folds to separate directories")
parser.add_argument(
"--files",
nargs="+",
help=
"List all image files that shall be processed. Ground truth fils with the same "
"base name but with '.gt.txt' as extension are required at the same location",
)
parser.add_argument(
"--n_folds",
type=int,
required=True,
help="The number of fold, that is the number of models to train",
)
from paiargparse import PAIArgumentParser
from tfaip.util.logging import logger
from calamari_ocr.ocr.training.cross_fold_trainer import CrossFoldTrainer, CrossFoldTrainerParams
logger = logger(__name__)
def run():
return main(parse_args())
def parse_args(args=None):
parser = PAIArgumentParser()
parser.add_root_argument('root', CrossFoldTrainerParams,
CrossFoldTrainerParams())
params: CrossFoldTrainerParams = parser.parse_args(args).root
# TODO: add the training args (omit those params, that are set by the cross fold training)
# setup_train_args(parser, omit=["files", "validation", "weights",
# "early_stopping_best_model_output_dir", "early_stopping_best_model_prefix",
# "output_dir"])
return params
def main(params):
trainer = CrossFoldTrainer(params)
logger.info("Running cross fold train with params")
logger.info(params.to_json(indent=2))
trainer.run()