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| import streamlit as st | |
| from utils.logger import setup_logger | |
| import pandas as pd | |
| from PIL import Image | |
| import os | |
| logger = setup_logger(__name__) | |
| def prune_bank_statement_for_display(analysis_results_for_id): | |
| data_to_display = {} | |
| data_to_display["document_category"] = "bank_statement" | |
| data_to_display["document_type"] = "bank_statement" | |
| data_to_display["account_holder_name"] = analysis_results_for_id.get( | |
| "account_holder_name", None) | |
| data_to_display["account_holder_address"] = analysis_results_for_id.get( | |
| "account_holder_address", None) | |
| data_to_display["bank_name"] = analysis_results_for_id.get( | |
| "bank_name", None) | |
| data_to_display["account_number"] = analysis_results_for_id.get( | |
| "account_number", None) | |
| data_to_display["sort_code"] = analysis_results_for_id.get( | |
| "sort_code", None) | |
| data_to_display["statement_start_date"] = analysis_results_for_id.get( | |
| "statement_start_date", None) | |
| data_to_display["statement_end_date"] = analysis_results_for_id.get( | |
| "statement_end_date", None) | |
| data_to_display["salary_credits"] = analysis_results_for_id.get( | |
| "salary_credits", None) | |
| return data_to_display | |
| def display_bank_statement(extracted_files, analysis_results_pruned): | |
| col1, col2 = st.columns([2, 3]) | |
| logger.info(f"file_path while displaying: {extracted_files}") | |
| st.markdown("---") | |
| with col1: | |
| if len(extracted_files) > 1: | |
| st.image(extracted_files, caption=[os.path.basename( | |
| img) for img in extracted_files], use_container_width=True) | |
| else: | |
| image = Image.open(extracted_files[0]) | |
| st.image(image, caption=os.path.basename( | |
| extracted_files[0])) # , | |
| # use_container_width=True) | |
| logger.info( | |
| f"analysis_results_pruned : {analysis_results_pruned}") | |
| with col2: | |
| dict_str = {} | |
| for key, value in analysis_results_pruned.items(): | |
| if key != 'salary_credits': | |
| dict_str[key] = value | |
| simple_df = pd.DataFrame.from_dict( | |
| dict_str, | |
| orient='index', columns=['Value']).reset_index() | |
| simple_df.columns = ['Key', 'Value'] | |
| simple_df = simple_df.fillna(value="Missing") | |
| simple_df.index += 1 | |
| st.dataframe(simple_df, use_container_width=True) | |
| st.markdown("Salary Credits") | |
| salary_dict = analysis_results_pruned['salary_credits'] | |
| logger.info(f"salary_dict : {salary_dict}") | |
| for salary_details in salary_dict: | |
| simple_df = pd.DataFrame.from_dict( | |
| salary_details, | |
| orient='index', columns=['Value']).reset_index() | |
| simple_df.columns = ['Key', 'Value'] | |
| simple_df = simple_df.fillna(value="Missing") | |
| simple_df.index += 1 | |
| st.dataframe(simple_df, use_container_width=True) | |
| logger.info(f"simple_df: {simple_df}") | |