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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import sys
import importlib
__dir__ = os.path.dirname(__file__)
import paddle
sys.path.append(os.path.join(__dir__, ''))
import cv2
import logging
import numpy as np
from pathlib import Path
import base64
from io import BytesIO
from PIL import Image
def _import_file(module_name, file_path, make_importable=False):
spec = importlib.util.spec_from_file_location(module_name, file_path)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
if make_importable:
sys.modules[module_name] = module
return module
tools = _import_file(
'tools', os.path.join(__dir__, 'tools/__init__.py'), make_importable=True)
ppocr = importlib.import_module('ppocr', 'paddleocr')
ppstructure = importlib.import_module('ppstructure', 'paddleocr')
from ppocr.utils.logging import get_logger
logger = get_logger()
from ppocr.utils.utility import check_and_read, get_image_file_list, alpha_to_color, binarize_img
from ppocr.utils.network import maybe_download, download_with_progressbar, is_link, confirm_model_dir_url
from tools.infer.utility import draw_ocr, str2bool, check_gpu
from ppstructure.utility import init_args, draw_structure_result
from ppstructure.predict_system import StructureSystem, save_structure_res, to_excel, TextSystem
logger = get_logger()
__all__ = [
'PaddleOCR', 'PPStructure', 'draw_ocr', 'draw_structure_result',
'save_structure_res', 'download_with_progressbar', 'to_excel'
]
SUPPORT_DET_MODEL = ['DB']
VERSION = '2.7.5'
SUPPORT_REC_MODEL = ['CRNN', 'SVTR_LCNet']
BASE_DIR = os.path.expanduser("~/.paddleocr/")
DEFAULT_OCR_MODEL_VERSION = 'PP-OCRv4'
SUPPORT_OCR_MODEL_VERSION = ['PP-OCR', 'PP-OCRv2', 'PP-OCRv3', 'PP-OCRv4']
DEFAULT_STRUCTURE_MODEL_VERSION = 'PP-StructureV2'
SUPPORT_STRUCTURE_MODEL_VERSION = ['PP-Structure', 'PP-StructureV2']
MODEL_URLS = {
'OCR': {
'PP-OCRv4': {
'det': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_infer.tar',
},
'en': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar',
},
'ml': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar'
}
},
'rec': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_rec_infer.tar',
'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
},
'en': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv4/english/en_PP-OCRv4_rec_infer.tar',
'dict_path': './ppocr/utils/en_dict.txt'
},
'korean': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/korean_PP-OCRv4_rec_infer.tar',
'dict_path': './ppocr/utils/dict/korean_dict.txt'
},
'japan': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/japan_PP-OCRv4_rec_infer.tar',
'dict_path': './ppocr/utils/dict/japan_dict.txt'
},
'chinese_cht': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/chinese_cht_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt'
},
'ta': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/ta_PP-OCRv4_rec_infer.tar',
'dict_path': './ppocr/utils/dict/ta_dict.txt'
},
'te': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/te_PP-OCRv4_rec_infer.tar',
'dict_path': './ppocr/utils/dict/te_dict.txt'
},
'ka': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/ka_PP-OCRv4_rec_infer.tar',
'dict_path': './ppocr/utils/dict/ka_dict.txt'
},
'latin': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/latin_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/latin_dict.txt'
},
'arabic': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/arabic_PP-OCRv4_rec_infer.tar',
'dict_path': './ppocr/utils/dict/arabic_dict.txt'
},
'cyrillic': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/cyrillic_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/cyrillic_dict.txt'
},
'devanagari': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/devanagari_PP-OCRv4_rec_infer.tar',
'dict_path': './ppocr/utils/dict/devanagari_dict.txt'
},
},
'cls': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar',
}
},
},
'PP-OCRv3': {
'det': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar',
},
'en': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar',
},
'ml': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar'
}
},
'rec': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
},
'en': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/en_dict.txt'
},
'korean': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/korean_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/korean_dict.txt'
},
'japan': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/japan_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/japan_dict.txt'
},
'chinese_cht': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/chinese_cht_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt'
},
'ta': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/ta_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/ta_dict.txt'
},
'te': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/te_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/te_dict.txt'
},
'ka': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/ka_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/ka_dict.txt'
},
'latin': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/latin_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/latin_dict.txt'
},
'arabic': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/arabic_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/arabic_dict.txt'
},
'cyrillic': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/cyrillic_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/cyrillic_dict.txt'
},
'devanagari': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/devanagari_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/dict/devanagari_dict.txt'
},
},
'cls': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar',
}
},
},
'PP-OCRv2': {
'det': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar',
},
},
'rec': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar',
'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
}
},
'cls': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar',
}
},
},
'PP-OCR': {
'det': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar',
},
'en': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_ppocr_mobile_v2.0_det_infer.tar',
},
'structure': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar'
}
},
'rec': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
},
'en': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/en_dict.txt'
},
'french': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/french_dict.txt'
},
'german': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/german_dict.txt'
},
'korean': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/korean_dict.txt'
},
'japan': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/japan_dict.txt'
},
'chinese_cht': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt'
},
'ta': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/ta_dict.txt'
},
'te': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/te_dict.txt'
},
'ka': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/ka_dict.txt'
},
'latin': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/latin_dict.txt'
},
'arabic': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/arabic_dict.txt'
},
'cyrillic': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/cyrillic_dict.txt'
},
'devanagari': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/devanagari_dict.txt'
},
'structure': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar',
'dict_path': 'ppocr/utils/dict/table_dict.txt'
}
},
'cls': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar',
}
},
}
},
'STRUCTURE': {
'PP-Structure': {
'table': {
'en': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar',
'dict_path': 'ppocr/utils/dict/table_structure_dict.txt'
}
}
},
'PP-StructureV2': {
'table': {
'en': {
'url':
'https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar',
'dict_path': 'ppocr/utils/dict/table_structure_dict.txt'
},
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/ch_ppstructure_mobile_v2.0_SLANet_infer.tar',
'dict_path': 'ppocr/utils/dict/table_structure_dict_ch.txt'
}
},
'layout': {
'en': {
'url':
'https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_infer.tar',
'dict_path':
'ppocr/utils/dict/layout_dict/layout_publaynet_dict.txt'
},
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_cdla_infer.tar',
'dict_path':
'ppocr/utils/dict/layout_dict/layout_cdla_dict.txt'
}
}
}
}
}
def parse_args(mMain=True):
import argparse
parser = init_args()
parser.add_help = mMain
parser.add_argument("--lang", type=str, default='ch')
parser.add_argument("--det", type=str2bool, default=True)
parser.add_argument("--rec", type=str2bool, default=True)
parser.add_argument("--type", type=str, default='ocr')
parser.add_argument("--savefile", type=str2bool, default=False)
parser.add_argument(
"--ocr_version",
type=str,
choices=SUPPORT_OCR_MODEL_VERSION,
default='PP-OCRv4',
help='OCR Model version, the current model support list is as follows: '
'1. PP-OCRv4/v3 Support Chinese and English detection and recognition model, and direction classifier model'
'2. PP-OCRv2 Support Chinese detection and recognition model. '
'3. PP-OCR support Chinese detection, recognition and direction classifier and multilingual recognition model.'
)
parser.add_argument(
"--structure_version",
type=str,
choices=SUPPORT_STRUCTURE_MODEL_VERSION,
default='PP-StructureV2',
help='Model version, the current model support list is as follows:'
' 1. PP-Structure Support en table structure model.'
' 2. PP-StructureV2 Support ch and en table structure model.')
for action in parser._actions:
if action.dest in [
'rec_char_dict_path', 'table_char_dict_path', 'layout_dict_path'
]:
action.default = None
if mMain:
return parser.parse_args()
else:
inference_args_dict = {}
for action in parser._actions:
inference_args_dict[action.dest] = action.default
return argparse.Namespace(**inference_args_dict)
def parse_lang(lang):
latin_lang = [
'af', 'az', 'bs', 'cs', 'cy', 'da', 'de', 'es', 'et', 'fr', 'ga', 'hr',
'hu', 'id', 'is', 'it', 'ku', 'la', 'lt', 'lv', 'mi', 'ms', 'mt', 'nl',
'no', 'oc', 'pi', 'pl', 'pt', 'ro', 'rs_latin', 'sk', 'sl', 'sq', 'sv',
'sw', 'tl', 'tr', 'uz', 'vi', 'french', 'german'
]
arabic_lang = ['ar', 'fa', 'ug', 'ur']
cyrillic_lang = [
'ru', 'rs_cyrillic', 'be', 'bg', 'uk', 'mn', 'abq', 'ady', 'kbd', 'ava',
'dar', 'inh', 'che', 'lbe', 'lez', 'tab'
]
devanagari_lang = [
'hi', 'mr', 'ne', 'bh', 'mai', 'ang', 'bho', 'mah', 'sck', 'new', 'gom',
'sa', 'bgc'
]
if lang in latin_lang:
lang = "latin"
elif lang in arabic_lang:
lang = "arabic"
elif lang in cyrillic_lang:
lang = "cyrillic"
elif lang in devanagari_lang:
lang = "devanagari"
assert lang in MODEL_URLS['OCR'][DEFAULT_OCR_MODEL_VERSION][
'rec'], 'param lang must in {}, but got {}'.format(
MODEL_URLS['OCR'][DEFAULT_OCR_MODEL_VERSION]['rec'].keys(), lang)
if lang == "ch":
det_lang = "ch"
elif lang == 'structure':
det_lang = 'structure'
elif lang in ["en", "latin"]:
det_lang = "en"
else:
det_lang = "ml"
return lang, det_lang
def get_model_config(type, version, model_type, lang):
if type == 'OCR':
DEFAULT_MODEL_VERSION = DEFAULT_OCR_MODEL_VERSION
elif type == 'STRUCTURE':
DEFAULT_MODEL_VERSION = DEFAULT_STRUCTURE_MODEL_VERSION
else:
raise NotImplementedError
model_urls = MODEL_URLS[type]
if version not in model_urls:
version = DEFAULT_MODEL_VERSION
if model_type not in model_urls[version]:
if model_type in model_urls[DEFAULT_MODEL_VERSION]:
version = DEFAULT_MODEL_VERSION
else:
logger.error('{} models is not support, we only support {}'.format(
model_type, model_urls[DEFAULT_MODEL_VERSION].keys()))
sys.exit(-1)
if lang not in model_urls[version][model_type]:
if lang in model_urls[DEFAULT_MODEL_VERSION][model_type]:
version = DEFAULT_MODEL_VERSION
else:
logger.error(
'lang {} is not support, we only support {} for {} models'.
format(lang, model_urls[DEFAULT_MODEL_VERSION][model_type].keys(
), model_type))
sys.exit(-1)
return model_urls[version][model_type][lang]
def img_decode(content: bytes):
np_arr = np.frombuffer(content, dtype=np.uint8)
return cv2.imdecode(np_arr, cv2.IMREAD_UNCHANGED)
def check_img(img, alpha_color=(255, 255, 255)):
"""
Check the image data. If it is another type of image file, try to decode it into a numpy array.
The inference network requires three-channel images, So the following channel conversions are done
single channel image: Gray to RGB R←Y,G←Y,B←Y
four channel image: alpha_to_color
args:
img: image data
file format: jpg, png and other image formats that opencv can decode, as well as gif and pdf formats
storage type: binary image, net image file, local image file
alpha_color: Background color in images in RGBA format
return: numpy.array (h, w, 3)
"""
if isinstance(img, bytes):
img = img_decode(img)
if isinstance(img, str):
# download net image
if is_link(img):
download_with_progressbar(img, 'tmp.jpg')
img = 'tmp.jpg'
image_file = img
img, flag_gif, flag_pdf = check_and_read(image_file)
if not flag_gif and not flag_pdf:
with open(image_file, 'rb') as f:
img_str = f.read()
img = img_decode(img_str)
if img is None:
try:
buf = BytesIO()
image = BytesIO(img_str)
im = Image.open(image)
rgb = im.convert('RGB')
rgb.save(buf, 'jpeg')
buf.seek(0)
image_bytes = buf.read()
data_base64 = str(base64.b64encode(image_bytes),
encoding="utf-8")
image_decode = base64.b64decode(data_base64)
img_array = np.frombuffer(image_decode, np.uint8)
img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
except:
logger.error("error in loading image:{}".format(image_file))
return None
if img is None:
logger.error("error in loading image:{}".format(image_file))
return None
# single channel image array.shape:h,w
if isinstance(img, np.ndarray) and len(img.shape) == 2:
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
# four channel image array.shape:h,w,c
if isinstance(img, np.ndarray) and len(img.shape) == 3 and img.shape[2] == 4:
img = alpha_to_color(img, alpha_color)
return img
class PaddleOCR(TextSystem):
def __init__(self, **kwargs):
"""
paddleocr package
args:
**kwargs: other params show in paddleocr --help
"""
params = parse_args(mMain=False)
params.__dict__.update(**kwargs)
assert params.ocr_version in SUPPORT_OCR_MODEL_VERSION, "ocr_version must in {}, but get {}".format(
SUPPORT_OCR_MODEL_VERSION, params.ocr_version)
params.use_gpu = check_gpu(params.use_gpu)
if not params.show_log:
logger.setLevel(logging.INFO)
self.use_angle_cls = params.use_angle_cls
lang, det_lang = parse_lang(params.lang)
# init model dir
det_model_config = get_model_config('OCR', params.ocr_version, 'det',
det_lang)
params.det_model_dir, det_url = confirm_model_dir_url(
params.det_model_dir,
os.path.join(BASE_DIR, 'whl', 'det', det_lang),
det_model_config['url'])
rec_model_config = get_model_config('OCR', params.ocr_version, 'rec',
lang)
params.rec_model_dir, rec_url = confirm_model_dir_url(
params.rec_model_dir,
os.path.join(BASE_DIR, 'whl', 'rec', lang), rec_model_config['url'])
cls_model_config = get_model_config('OCR', params.ocr_version, 'cls',
'ch')
params.cls_model_dir, cls_url = confirm_model_dir_url(
params.cls_model_dir,
os.path.join(BASE_DIR, 'whl', 'cls'), cls_model_config['url'])
if params.ocr_version in ['PP-OCRv3', 'PP-OCRv4']:
params.rec_image_shape = "3, 48, 320"
else:
params.rec_image_shape = "3, 32, 320"
# download model if using paddle infer
if not params.use_onnx:
maybe_download(params.det_model_dir, det_url)
maybe_download(params.rec_model_dir, rec_url)
maybe_download(params.cls_model_dir, cls_url)
if params.det_algorithm not in SUPPORT_DET_MODEL:
logger.error('det_algorithm must in {}'.format(SUPPORT_DET_MODEL))
sys.exit(0)
if params.rec_algorithm not in SUPPORT_REC_MODEL:
logger.error('rec_algorithm must in {}'.format(SUPPORT_REC_MODEL))
sys.exit(0)
if params.rec_char_dict_path is None:
params.rec_char_dict_path = str(
Path(__file__).parent / rec_model_config['dict_path'])
logger.debug(params)
# init det_model and rec_model
super().__init__(params)
self.page_num = params.page_num
def ocr(self, img, det=True, rec=True, cls=True, bin=False, inv=False, alpha_color=(255, 255, 255)):
"""
OCR with PaddleOCR
args:
img: img for OCR, support ndarray, img_path and list or ndarray
det: use text detection or not. If False, only rec will be exec. Default is True
rec: use text recognition or not. If False, only det will be exec. Default is True
cls: use angle classifier or not. Default is True. If True, the text with rotation of 180 degrees can be recognized. If no text is rotated by 180 degrees, use cls=False to get better performance. Text with rotation of 90 or 270 degrees can be recognized even if cls=False.
bin: binarize image to black and white. Default is False.
inv: invert image colors. Default is False.
alpha_color: set RGB color Tuple for transparent parts replacement. Default is pure white.
"""
assert isinstance(img, (np.ndarray, list, str, bytes))
if isinstance(img, list) and det == True:
logger.error('When input a list of images, det must be false')
exit(0)
if cls == True and self.use_angle_cls == False:
logger.warning(
'Since the angle classifier is not initialized, it will not be used during the forward process'
)
img = check_img(img, alpha_color)
# for infer pdf file
if isinstance(img, list):
if self.page_num > len(img) or self.page_num == 0:
imgs = img
else:
imgs = img[:self.page_num]
else:
imgs = [img]
def preprocess_image(_image):
_image = alpha_to_color(_image, alpha_color)
if inv:
_image = cv2.bitwise_not(_image)
if bin:
_image = binarize_img(_image)
return _image
if det and rec:
ocr_res = []
for idx, img in enumerate(imgs):
img = preprocess_image(img)
dt_boxes, rec_res, _ = self.__call__(img, cls)
if not dt_boxes and not rec_res:
ocr_res.append(None)
continue
tmp_res = [[box.tolist(), res]
for box, res in zip(dt_boxes, rec_res)]
ocr_res.append(tmp_res)
return ocr_res
elif det and not rec:
ocr_res = []
for idx, img in enumerate(imgs):
img = preprocess_image(img)
dt_boxes, elapse = self.text_detector(img)
if not dt_boxes:
ocr_res.append(None)
continue
tmp_res = [box.tolist() for box in dt_boxes]
ocr_res.append(tmp_res)
return ocr_res
else:
ocr_res = []
cls_res = []
for idx, img in enumerate(imgs):
if not isinstance(img, list):
img = preprocess_image(img)
img = [img]
if self.use_angle_cls and cls:
img, cls_res_tmp, elapse = self.text_classifier(img)
if not rec:
cls_res.append(cls_res_tmp)
rec_res, elapse = self.text_recognizer(img)
ocr_res.append(rec_res)
if not rec:
return cls_res
return ocr_res
class PPStructure(StructureSystem):
def __init__(self, **kwargs):
params = parse_args(mMain=False)
params.__dict__.update(**kwargs)
assert params.structure_version in SUPPORT_STRUCTURE_MODEL_VERSION, "structure_version must in {}, but get {}".format(
SUPPORT_STRUCTURE_MODEL_VERSION, params.structure_version)
params.use_gpu = check_gpu(params.use_gpu)
params.mode = 'structure'
if not params.show_log:
logger.setLevel(logging.INFO)
lang, det_lang = parse_lang(params.lang)
if lang == 'ch':
table_lang = 'ch'
else:
table_lang = 'en'
if params.structure_version == 'PP-Structure':
params.merge_no_span_structure = False
# init model dir
det_model_config = get_model_config('OCR', params.ocr_version, 'det',
det_lang)
params.det_model_dir, det_url = confirm_model_dir_url(
params.det_model_dir,
os.path.join(BASE_DIR, 'whl', 'det', det_lang),
det_model_config['url'])
rec_model_config = get_model_config('OCR', params.ocr_version, 'rec',
lang)
params.rec_model_dir, rec_url = confirm_model_dir_url(
params.rec_model_dir,
os.path.join(BASE_DIR, 'whl', 'rec', lang), rec_model_config['url'])
table_model_config = get_model_config(
'STRUCTURE', params.structure_version, 'table', table_lang)
params.table_model_dir, table_url = confirm_model_dir_url(
params.table_model_dir,
os.path.join(BASE_DIR, 'whl', 'table'), table_model_config['url'])
layout_model_config = get_model_config(
'STRUCTURE', params.structure_version, 'layout', lang)
params.layout_model_dir, layout_url = confirm_model_dir_url(
params.layout_model_dir,
os.path.join(BASE_DIR, 'whl', 'layout'), layout_model_config['url'])
# download model
maybe_download(params.det_model_dir, det_url)
maybe_download(params.rec_model_dir, rec_url)
maybe_download(params.table_model_dir, table_url)
maybe_download(params.layout_model_dir, layout_url)
if params.rec_char_dict_path is None:
params.rec_char_dict_path = str(
Path(__file__).parent / rec_model_config['dict_path'])
if params.table_char_dict_path is None:
params.table_char_dict_path = str(
Path(__file__).parent / table_model_config['dict_path'])
if params.layout_dict_path is None:
params.layout_dict_path = str(
Path(__file__).parent / layout_model_config['dict_path'])
logger.debug(params)
super().__init__(params)
def __call__(self, img, return_ocr_result_in_table=False, img_idx=0, alpha_color=(255, 255, 255)):
img = check_img(img, alpha_color)
res, _ = super().__call__(
img, return_ocr_result_in_table, img_idx=img_idx)
return res
def main():
# for cmd
args = parse_args(mMain=True)
image_dir = args.image_dir
if is_link(image_dir):
download_with_progressbar(image_dir, 'tmp.jpg')
image_file_list = ['tmp.jpg']
else:
image_file_list = get_image_file_list(args.image_dir)
if len(image_file_list) == 0:
logger.error('no images find in {}'.format(args.image_dir))
return
if args.type == 'ocr':
engine = PaddleOCR(**(args.__dict__))
elif args.type == 'structure':
engine = PPStructure(**(args.__dict__))
else:
raise NotImplementedError
for img_path in image_file_list:
img_name = os.path.basename(img_path).split('.')[0]
logger.info('{}{}{}'.format('*' * 10, img_path, '*' * 10))
if args.type == 'ocr':
result = engine.ocr(img_path,
det=args.det,
rec=args.rec,
cls=args.use_angle_cls,
bin=args.binarize,
inv=args.invert,
alpha_color=args.alphacolor)
if result is not None:
lines = []
for idx in range(len(result)):
res = result[idx]
for line in res:
logger.info(line)
val = '['
for box in line[0]:
val += str(box[0]) + ',' + str(box[1]) + ','
val = val[:-1]
val += '],' + line[1][0] + ',' + str(line[1][1]) + '\n'
lines.append(val)
if args.savefile:
if os.path.exists(args.output) is False:
os.mkdir(args.output)
outfile = args.output + '/' + img_name + '.txt'
with open(outfile,'w',encoding='utf-8') as f:
f.writelines(lines)
elif args.type == 'structure':
img, flag_gif, flag_pdf = check_and_read(img_path)
if not flag_gif and not flag_pdf:
img = cv2.imread(img_path)
if args.recovery and args.use_pdf2docx_api and flag_pdf:
from pdf2docx.converter import Converter
docx_file = os.path.join(args.output,
'{}.docx'.format(img_name))
cv = Converter(img_path)
cv.convert(docx_file)
cv.close()
logger.info('docx save to {}'.format(docx_file))
continue
if not flag_pdf:
if img is None:
logger.error("error in loading image:{}".format(img_path))
continue
img_paths = [[img_path, img]]
else:
img_paths = []
for index, pdf_img in enumerate(img):
os.makedirs(
os.path.join(args.output, img_name), exist_ok=True)
pdf_img_path = os.path.join(
args.output, img_name,
img_name + '_' + str(index) + '.jpg')
cv2.imwrite(pdf_img_path, pdf_img)
img_paths.append([pdf_img_path, pdf_img])
all_res = []
for index, (new_img_path, img) in enumerate(img_paths):
logger.info('processing {}/{} page:'.format(index + 1,
len(img_paths)))
new_img_name = os.path.basename(new_img_path).split('.')[0]
result = engine(img, img_idx=index)
save_structure_res(result, args.output, img_name, index)
if args.recovery and result != []:
from copy import deepcopy
from ppstructure.recovery.recovery_to_doc import sorted_layout_boxes
h, w, _ = img.shape
result_cp = deepcopy(result)
result_sorted = sorted_layout_boxes(result_cp, w)
all_res += result_sorted
if args.recovery and all_res != []:
try:
from ppstructure.recovery.recovery_to_doc import convert_info_docx
convert_info_docx(img, all_res, args.output, img_name)
except Exception as ex:
logger.error(
"error in layout recovery image:{}, err msg: {}".format(
img_name, ex))
continue
for item in all_res:
item.pop('img')
item.pop('res')
logger.info(item)
logger.info('result save to {}'.format(args.output))