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hide argparse when use whl by python

This commit is contained in:
WenmuZhou 2020-11-30 17:30:52 +08:00
parent ca34277361
commit efba14e1cc
2 changed files with 4 additions and 4 deletions
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6
paddleocr.py
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@ -117,13 +117,13 @@ def maybe_download(model_storage_directory, url):
os.remove(tmp_path) os.remove(tmp_path)
def parse_args(): def parse_args(add_help=True):
import argparse import argparse
def str2bool(v): def str2bool(v):
return v.lower() in ("true", "t", "1") return v.lower() in ("true", "t", "1")
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser(add_help=add_help)
# params for prediction engine # params for prediction engine
parser.add_argument("--use_gpu", type=str2bool, default=True) parser.add_argument("--use_gpu", type=str2bool, default=True)
parser.add_argument("--ir_optim", type=str2bool, default=True) parser.add_argument("--ir_optim", type=str2bool, default=True)
@ -181,7 +181,7 @@ class PaddleOCR(predict_system.TextSystem):
args: args:
**kwargs: other params show in paddleocr --help **kwargs: other params show in paddleocr --help
""" """
postprocess_params = parse_args() postprocess_params = parse_args(add_help=False)
postprocess_params.__dict__.update(**kwargs) postprocess_params.__dict__.update(**kwargs)
self.use_angle_cls = postprocess_params.use_angle_cls self.use_angle_cls = postprocess_params.use_angle_cls
lang = postprocess_params.lang lang = postprocess_params.lang

2
setup.py
View File

@ -32,7 +32,7 @@ setup(
package_dir={'paddleocr': ''}, package_dir={'paddleocr': ''},
include_package_data=True, include_package_data=True,
entry_points={"console_scripts": ["paddleocr= paddleocr.paddleocr:main"]}, entry_points={"console_scripts": ["paddleocr= paddleocr.paddleocr:main"]},
version='1.1.1', version='1.1.2',
install_requires=requirements, install_requires=requirements,
license='Apache License 2.0', license='Apache License 2.0',
description='Awesome OCR toolkits based on PaddlePaddle （8.6M ultra-lightweight pre-trained model, support training and deployment among server, mobile, embeded and IoT devices', description='Awesome OCR toolkits based on PaddlePaddle （8.6M ultra-lightweight pre-trained model, support training and deployment among server, mobile, embeded and IoT devices',