import os import re import pytesseract from pytesseract import Output from datatypes.datatypes import Row, Cell from codes.image_processing import ImageProcessor from datatypes.config import Config class TextDataExtraction(): def __init__(self): pass def clean_ocr_data(self, value): transf = ''.join(e for e in value if e==' 'or e=='.' or e.isalnum()) transf.strip() return transf def pytess(self, cell_pil_img): return ' '.join(pytesseract.image_to_data(cell_pil_img, output_type=Output.DICT, config='-c tessedit_char_blacklist=œ˜â€œï¬â™Ã©œ¢!|”?«“¥ --psm 6 preserve_interword_spaces')['text']).strip() def cell_data_extraction(self, image, table_data): for table in table_data.tables: tableimg_processor = ImageProcessor() table_bbox = table.detection_box table_image = image.crop(table_bbox) table_image = tableimg_processor.image_padding(table_image, padd=Config['table_padd']) for row_idx, table_row in enumerate(table.ordered_recognitiondata[0].recognized_row): row_obj = Row([]) xmin_row, ymin_row, xmax_row, ymax_row, _, _ = table_row row_image = table_image.crop((xmin_row,ymin_row,xmax_row,ymax_row)) row_width, row_height = row_image.size row_obj.rowindex = row_idx # Cell bounding box creation xa, ya, xb, yb = 0, 0, 0, row_height for indx, table_column in enumerate(table.ordered_recognitiondata[0].recognized_column): cell_obj = Cell() xmin_col, _, xmax_col, _,_,_ = table_column xmin_col, xmax_col = xmin_col -Config['table_padd'], xmax_col - Config['table_padd'] xa = xmin_col xb = xmax_col if indx == 0: xa = 0 if indx == len(table.ordered_recognitiondata[0].recognized_column)-1: xb = row_width cell_img = row_image.crop((xa, ya, xb, yb)) xa, ya, xb, yb = xa, ya, xb, yb cell_value = self.pytess(cell_img) transformed_cell_value = self.clean_ocr_data(cell_value) cell_obj.cellindex = indx cell_obj.value = transformed_cell_value row_obj.extracted_cells.append(cell_obj) table.extracted_rows.append(row_obj) return table_data