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import os
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Dict
class DetectionLabels(Enum):
table = 0
table_column = 1
table_row = 2
table_column_header = 3
table_projected_row_header = 4
table_spanning_cell = 5
class ExtractionContext(Enum):
document = 1
table = 2
row = 3
@dataclass
class Cell:
cellindex : int = 0
value : str = ''
prob : float = 0.5
@dataclass
class Row:
rowindex : int = 0
extracted_cells : List[Cell]= field(default_factory=lambda: [])
@dataclass
class TableRecognitionData:
scores : List = field(default_factory=lambda: [])
labels : List = field(default_factory=lambda: [])
boxes : List = field(default_factory=lambda: [])
@dataclass
class TableRecognitionOrdered:
recognized_row : List = field(default_factory=lambda: [])
recognized_column : List = field(default_factory=lambda: [])
@dataclass
class TableDetectionData:
detection_score : float = 0.0
detection_label : int = 0
detection_box : List = field(default_factory=lambda: [])
recognitiondata : TableRecognitionData = field(default_factory=lambda: [])
ordered_recognitiondata : List[TableRecognitionOrdered] = field(default_factory=lambda: [])
extracted_rows : List[Row] = field(default_factory=lambda: [])
@dataclass
class ImageData:
tables: List[TableDetectionData]
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