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MinerU/magic_pdf/model/sub_modules/model_init.py
myhloli 012a46e07d refactor(magic-pdf): optimize model initialization and concurrency control
- Remove concurrency limit logic from app.py
- Update model initialization process in various modules
- Remove unused VRAM check for concurrency limit
- Refactor OCR model initialization in pdf_extract_kit.py
- Update txt_spans_extract_v2 function to use lang parameter instead of ocr_model
2024-12-06 20:35:43 +08:00

160 lines
5.3 KiB
Python

from loguru import logger
from magic_pdf.config.constants import MODEL_NAME
from magic_pdf.model.model_list import AtomicModel
from magic_pdf.model.sub_modules.layout.doclayout_yolo.DocLayoutYOLO import \
DocLayoutYOLOModel
from magic_pdf.model.sub_modules.layout.layoutlmv3.model_init import \
Layoutlmv3_Predictor
from magic_pdf.model.sub_modules.mfd.yolov8.YOLOv8 import YOLOv8MFDModel
from magic_pdf.model.sub_modules.mfr.unimernet.Unimernet import UnimernetModel
from magic_pdf.model.sub_modules.ocr.paddleocr.ppocr_273_mod import \
ModifiedPaddleOCR
from magic_pdf.model.sub_modules.table.rapidtable.rapid_table import \
RapidTableModel
# from magic_pdf.model.sub_modules.ocr.paddleocr.ppocr_291_mod import ModifiedPaddleOCR
from magic_pdf.model.sub_modules.table.structeqtable.struct_eqtable import \
StructTableModel
from magic_pdf.model.sub_modules.table.tablemaster.tablemaster_paddle import \
TableMasterPaddleModel
def table_model_init(table_model_type, model_path, max_time, _device_='cpu'):
if table_model_type == MODEL_NAME.STRUCT_EQTABLE:
table_model = StructTableModel(model_path, max_new_tokens=2048, max_time=max_time)
elif table_model_type == MODEL_NAME.TABLE_MASTER:
config = {
'model_dir': model_path,
'device': _device_
}
table_model = TableMasterPaddleModel(config)
elif table_model_type == MODEL_NAME.RAPID_TABLE:
table_model = RapidTableModel()
else:
logger.error('table model type not allow')
exit(1)
return table_model
def mfd_model_init(weight, device='cpu'):
mfd_model = YOLOv8MFDModel(weight, device)
return mfd_model
def mfr_model_init(weight_dir, cfg_path, device='cpu'):
mfr_model = UnimernetModel(weight_dir, cfg_path, device)
return mfr_model
def layout_model_init(weight, config_file, device):
model = Layoutlmv3_Predictor(weight, config_file, device)
return model
def doclayout_yolo_model_init(weight, device='cpu'):
model = DocLayoutYOLOModel(weight, device)
return model
def ocr_model_init(show_log: bool = False,
det_db_box_thresh=0.3,
lang=None,
use_dilation=True,
det_db_unclip_ratio=1.8,
):
if lang is not None and lang != '':
model = ModifiedPaddleOCR(
show_log=show_log,
det_db_box_thresh=det_db_box_thresh,
lang=lang,
use_dilation=use_dilation,
det_db_unclip_ratio=det_db_unclip_ratio,
)
else:
model = ModifiedPaddleOCR(
show_log=show_log,
det_db_box_thresh=det_db_box_thresh,
use_dilation=use_dilation,
det_db_unclip_ratio=det_db_unclip_ratio,
# use_angle_cls=True,
)
return model
class AtomModelSingleton:
_instance = None
_models = {}
def __new__(cls, *args, **kwargs):
if cls._instance is None:
cls._instance = super().__new__(cls)
return cls._instance
def get_atom_model(self, atom_model_name: str, **kwargs):
lang = kwargs.get('lang', None)
layout_model_name = kwargs.get('layout_model_name', None)
table_model_name = kwargs.get('table_model_name', None)
if atom_model_name in [AtomicModel.OCR]:
key = (atom_model_name, lang)
elif atom_model_name in [AtomicModel.Layout]:
key = (atom_model_name, layout_model_name)
elif atom_model_name in [AtomicModel.Table]:
key = (atom_model_name, table_model_name)
else:
key = atom_model_name
if key not in self._models:
self._models[key] = atom_model_init(model_name=atom_model_name, **kwargs)
return self._models[key]
def atom_model_init(model_name: str, **kwargs):
atom_model = None
if model_name == AtomicModel.Layout:
if kwargs.get('layout_model_name') == MODEL_NAME.LAYOUTLMv3:
atom_model = layout_model_init(
kwargs.get('layout_weights'),
kwargs.get('layout_config_file'),
kwargs.get('device')
)
elif kwargs.get('layout_model_name') == MODEL_NAME.DocLayout_YOLO:
atom_model = doclayout_yolo_model_init(
kwargs.get('doclayout_yolo_weights'),
kwargs.get('device')
)
elif model_name == AtomicModel.MFD:
atom_model = mfd_model_init(
kwargs.get('mfd_weights'),
kwargs.get('device')
)
elif model_name == AtomicModel.MFR:
atom_model = mfr_model_init(
kwargs.get('mfr_weight_dir'),
kwargs.get('mfr_cfg_path'),
kwargs.get('device')
)
elif model_name == AtomicModel.OCR:
atom_model = ocr_model_init(
kwargs.get('ocr_show_log'),
kwargs.get('det_db_box_thresh'),
kwargs.get('lang'),
)
elif model_name == AtomicModel.Table:
atom_model = table_model_init(
kwargs.get('table_model_name'),
kwargs.get('table_model_path'),
kwargs.get('table_max_time'),
kwargs.get('device')
)
else:
logger.error('model name not allow')
exit(1)
if atom_model is None:
logger.error('model init failed')
exit(1)
else:
return atom_model