model_init.py
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import os
import torch
from loguru import logger
from .model_list import AtomicModel
from ...model.layout.doclayoutyolo import DocLayoutYOLOModel
from ...model.mfd.yolo_v8 import YOLOv8MFDModel
from ...model.mfr.unimernet.Unimernet import UnimernetModel
from ...model.mfr.pp_formulanet_plus_m.predict_formula import FormulaRecognizer
from ...model.ocr.paddleocr2pytorch.pytorch_paddle import PytorchPaddleOCR
from ...model.ori_cls.paddle_ori_cls import PaddleOrientationClsModel
from ...model.table.cls.paddle_table_cls import PaddleTableClsModel
# from ...model.table.rec.RapidTable import RapidTableModel
from ...model.table.rec.slanet_plus.main import RapidTableModel
from ...model.table.rec.unet_table.main import UnetTableModel
from ...utils.enum_class import ModelPath
from ...utils.models_download_utils import auto_download_and_get_model_root_path
MFR_MODEL = os.getenv('MINERU_FORMULA_CH_SUPPORT', 'False')
if MFR_MODEL.lower() in ['true', '1', 'yes']:
MFR_MODEL = "pp_formulanet_plus_m"
elif MFR_MODEL.lower() in ['false', '0', 'no']:
MFR_MODEL = "unimernet_small"
else:
logger.warning(f"Invalid MINERU_FORMULA_CH_SUPPORT value: {MFR_MODEL}, set to default 'False'")
MFR_MODEL = "unimernet_small"
def img_orientation_cls_model_init():
atom_model_manager = AtomModelSingleton()
ocr_engine = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.OCR,
det_db_box_thresh=0.5,
det_db_unclip_ratio=1.6,
lang="ch_lite",
enable_merge_det_boxes=False
)
cls_model = PaddleOrientationClsModel(ocr_engine)
return cls_model
def table_cls_model_init():
return PaddleTableClsModel()
def wired_table_model_init(lang=None):
atom_model_manager = AtomModelSingleton()
ocr_engine = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.OCR,
det_db_box_thresh=0.5,
det_db_unclip_ratio=1.6,
lang=lang,
enable_merge_det_boxes=False
)
table_model = UnetTableModel(ocr_engine)
return table_model
def wireless_table_model_init(lang=None):
atom_model_manager = AtomModelSingleton()
ocr_engine = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.OCR,
det_db_box_thresh=0.5,
det_db_unclip_ratio=1.6,
lang=lang,
enable_merge_det_boxes=False
)
table_model = RapidTableModel(ocr_engine)
return table_model
def mfd_model_init(weight, device='cpu'):
if str(device).startswith('npu'):
device = torch.device(device)
mfd_model = YOLOv8MFDModel(weight, device)
return mfd_model
def mfr_model_init(weight_dir, device='cpu'):
if MFR_MODEL == "unimernet_small":
mfr_model = UnimernetModel(weight_dir, device)
elif MFR_MODEL == "pp_formulanet_plus_m":
mfr_model = FormulaRecognizer(weight_dir, device)
else:
logger.error('MFR model name not allow')
exit(1)
return mfr_model
def doclayout_yolo_model_init(weight, device='cpu'):
if str(device).startswith('npu'):
device = torch.device(device)
model = DocLayoutYOLOModel(weight, device)
return model
def ocr_model_init(det_db_box_thresh=0.3,
lang=None,
det_db_unclip_ratio=1.8,
enable_merge_det_boxes=True
):
if lang is not None and lang != '':
model = PytorchPaddleOCR(
det_db_box_thresh=det_db_box_thresh,
lang=lang,
use_dilation=True,
det_db_unclip_ratio=det_db_unclip_ratio,
enable_merge_det_boxes=enable_merge_det_boxes,
)
else:
model = PytorchPaddleOCR(
det_db_box_thresh=det_db_box_thresh,
use_dilation=True,
det_db_unclip_ratio=det_db_unclip_ratio,
enable_merge_det_boxes=enable_merge_det_boxes,
)
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)
if atom_model_name in [AtomicModel.WiredTable, AtomicModel.WirelessTable]:
key = (
atom_model_name,
lang
)
elif atom_model_name in [AtomicModel.OCR]:
key = (
atom_model_name,
kwargs.get('det_db_box_thresh', 0.3),
lang,
kwargs.get('det_db_unclip_ratio', 1.8),
kwargs.get('enable_merge_det_boxes', True)
)
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:
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('device')
)
elif model_name == AtomicModel.OCR:
atom_model = ocr_model_init(
kwargs.get('det_db_box_thresh', 0.3),
kwargs.get('lang'),
kwargs.get('det_db_unclip_ratio', 1.8),
kwargs.get('enable_merge_det_boxes', True)
)
elif model_name == AtomicModel.WirelessTable:
atom_model = wireless_table_model_init(
kwargs.get('lang'),
)
elif model_name == AtomicModel.WiredTable:
atom_model = wired_table_model_init(
kwargs.get('lang'),
)
elif model_name == AtomicModel.TableCls:
atom_model = table_cls_model_init()
elif model_name == AtomicModel.ImgOrientationCls:
atom_model = img_orientation_cls_model_init()
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
class MineruPipelineModel:
def __init__(self, **kwargs):
self.formula_config = kwargs.get('formula_config')
self.apply_formula = self.formula_config.get('enable', True)
self.table_config = kwargs.get('table_config')
self.apply_table = self.table_config.get('enable', True)
self.lang = kwargs.get('lang', None)
self.device = kwargs.get('device', 'cpu')
logger.info(
'DocAnalysis init, this may take some times......'
)
atom_model_manager = AtomModelSingleton()
if self.apply_formula:
# 初始化公式检测模型
self.mfd_model = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.MFD,
mfd_weights=str(
os.path.join(auto_download_and_get_model_root_path(ModelPath.yolo_v8_mfd), ModelPath.yolo_v8_mfd)
),
device=self.device,
)
# 初始化公式解析模型
if MFR_MODEL == "unimernet_small":
mfr_model_path = ModelPath.unimernet_small
elif MFR_MODEL == "pp_formulanet_plus_m":
mfr_model_path = ModelPath.pp_formulanet_plus_m
else:
logger.error('MFR model name not allow')
exit(1)
self.mfr_model = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.MFR,
mfr_weight_dir=str(os.path.join(auto_download_and_get_model_root_path(mfr_model_path), mfr_model_path)),
device=self.device,
)
# 初始化layout模型
self.layout_model = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.Layout,
doclayout_yolo_weights=str(
os.path.join(auto_download_and_get_model_root_path(ModelPath.doclayout_yolo), ModelPath.doclayout_yolo)
),
device=self.device,
)
# 初始化ocr
self.ocr_model = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.OCR,
det_db_box_thresh=0.3,
lang=self.lang
)
# init table model
if self.apply_table:
self.wired_table_model = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.WiredTable,
lang=self.lang,
)
self.wireless_table_model = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.WirelessTable,
lang=self.lang,
)
self.table_cls_model = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.TableCls,
)
self.img_orientation_cls_model = atom_model_manager.get_atom_model(
atom_model_name=AtomicModel.ImgOrientationCls,
lang=self.lang,
)
logger.info('DocAnalysis init done!')