def construct_lm(path, config_path='', logger=logging):
try:
lm = language_model.torchscript_import(compose_path(path, config_path))
except language_model.UnreadableModelError as e:
logger.warning(
'WARNING: Failed to load model as TorchScript file, original error:\n'
)
logger.warning(f'{e}\n')
logger.warning(
'WARNING: Attempting to load as a plain torch-pickled model...\n')
lm = torch.load(compose_path(path, config_path),
map_location=torch.device('cpu'))
lm._unused_prefix_len = 2
return lm
def __init__(self, config, config_path=''):
json_file = compose_path(config['OCR_JSON'], config_path)
if 'METHOD' in config and config['METHOD'] == 'pytorch_ocr':
from pero_ocr.ocr_engine.pytorch_ocr_engine import PytorchEngineLineOCR
self.ocr_engine = PytorchEngineLineOCR(json_file, gpu_id=0)
else:
self.ocr_engine = line_ocr_engine.EngineLineOCR(json_file,
gpu_id=0)
def __init__(self, config, config_path):
self.filter_directions = config.getboolean('FILTER_DIRECTIONS')
self.filter_incomplete_pages = config.getboolean(
'FILTER_INCOMPLETE_PAGES')
if self.filter_directions:
self.engine = LineFilterEngine(
model_path=compose_path(config['MODEL_PATH'], config_path),
gpu_fraction=config.getfloat('GPU_FRACTION'))
def page_decoder_factory(config, config_path=''):
from pero_ocr.decoding import decoding_itf
ocr_chars = decoding_itf.get_ocr_charset(
compose_path(config['OCR']['OCR_JSON'], config_path))
decoder = decoding_itf.decoder_factory(config['DECODER'],
ocr_chars,
allow_no_decoder=False,
use_gpu=True,
config_path=config_path)
confidence_threshold = config['DECODER'].getfloat('CONFIDENCE_THRESHOLD',
fallback=math.inf)
return PageDecoder(decoder, line_confidence_threshold=confidence_threshold)
def __init__(self, config, config_path):
self.filter_directions = config.getboolean('FILTER_DIRECTIONS')
self.filter_incomplete_pages = config.getboolean(
'FILTER_INCOMPLETE_PAGES')
self.filter_pages_with_short_lines = config.getboolean(
'FILTER_PAGES_WITH_SHORT_LINES')
self.length_threshold = config.getint('LENGTH_THRESHOLD')
if self.filter_directions:
self.engine = LineFilterEngine(
model_path=compose_path(config['MODEL_PATH'], config_path),
framework=config['FRAMEWORK'],
gpu_fraction=config.getfloat('GPU_FRACTION'),
use_cpu=config.getboolean('USE_CPU'))
def __init__(self, config, config_path=''):
self.detect_regions = config.getboolean('DETECT_REGIONS')
self.detect_lines = config.getboolean('DETECT_LINES')
self.merge_lines = config.getboolean('MERGE_LINES')
self.adjust_lines = config.getboolean('REFINE_LINES')
self.multi_orientation = config.getboolean('MULTI_ORIENTATION')
self.engine = LayoutEngine(
model_path=compose_path(config['MODEL_PATH'], config_path),
downsample=config.getint('DOWNSAMPLE'),
pad=config.getint('PAD'),
use_cpu=config.getboolean('USE_CPU'),
detection_threshold=config.getfloat('DETECTION_THRESHOLD'),
max_mp=config.getfloat('MAX_MEGAPIXELS'),
gpu_fraction=config.getfloat('GPU_FRACTION'))
self.pool = Pool()
def __init__(self, config, config_path=''):
self.detect_regions = config.getboolean('DETECT_REGIONS')
self.detect_lines = config.getboolean('DETECT_LINES')
self.detect_straight_lines_in_regions = config.getboolean(
'DETECT_STRAIGHT_LINES_IN_REGIONS')
self.merge_lines = config.getboolean('MERGE_LINES')
self.adjust_heights = config.getboolean('ADJUST_HEIGHTS')
self.multi_orientation = config.getboolean('MULTI_ORIENTATION')
self.adjust_baselines = config.getboolean('ADJUST_BASELINES')
self.engine = LayoutEngine(
framework=config.get('FRAMEWORK', fallback='tf'),
model_path=compose_path(config['MODEL_PATH'], config_path),
downsample=config.getint('DOWNSAMPLE'),
adaptive_downsample=config.getboolean('ADAPTIVE_DOWNSAMPLE',
fallback=True),
pad=config.getint('PAD'),
use_cpu=config.getboolean('USE_CPU'),
detection_threshold=config.getfloat('DETECTION_THRESHOLD'),
max_mp=config.getfloat('MAX_MEGAPIXELS'),
gpu_fraction=config.getfloat('GPU_FRACTION'))
self.pool = Pool()
if __name__ == '__main__':
args = parseargs()
config_path = args.config_path
lmdb_db = args.lmdb
input_file_path = args.input_file_path
output_file_path = args.output_file_path
batch_size = 32
config = configparser.ConfigParser()
config.read(config_path)
setGPU()
ocr_chars = decoding_itf.get_ocr_charset(
compose_path(config['OCR']['OCR_JSON'], config_path))
decoder = decoding_itf.decoder_factory(config['DECODER'],
ocr_chars,
allow_no_decoder=False,
use_gpu=True,
config_path=config_path)
confidence_threshold = config['DECODER'].getfloat('CONFIDENCE_THRESHOLD',
fallback=math.inf)
json_file = compose_path(config['OCR']['OCR_JSON'], config_path)
ocr_engine = PytorchEngineLineOCR(json_file, gpu_id=0)
env = lmdb.open(lmdb_db)
txn = env.begin()
f = open(input_file_path, "r")
def construct_lm(path, config_path=''):
lm = torch.load(compose_path(path, config_path),
map_location=torch.device('cpu'))
lm._unused_prefix_len = 2
return lm