import numpy as np import gradio as gr from fastapi import FastAPI, File, UploadFile from app.extract_country.country_dictionary import find_country from app.extract_dates.date_engine import date_extractor from app.extract_gender.gender_extractor import gender_extract from app.extract_identity_number.doc_number_extractor import doc_number from app.ocr_engine.ocr import OCR from paddleocr import PaddleOCR from app.layoutLM_api.api import custom_ocr import cv2 def ocr(input_img): print(type(input_img)) ocr = PaddleOCR(use_angle_cls=True, lang='en') # need to run only once to download and load model into memory file_path = 'app/images/idcards/input.jpg' cv2.imwrite(file_path, input_img) # with open(file_path, "wb+") as file_object: # file_object.write(input_img.file.read()) dictionary = custom_ocr(file_path) if '' in list(dictionary.values()): print("Missing value found in Dic") extract_text = [] result = ocr.ocr(file_path, cls=True) extract_text = [line[1][0] for res in result for line in res] print("extract_text", extract_text) if len(dictionary['gender']) == 0: print("Gender Missing") gender_found, gender, ocr_list = gender_extract(extract_text) dictionary["gender"] = gender if gender_found else None if len(dictionary['dob']) == 0: print("Dob Missing") dob_found, dob, ocr_list = date_extractor(extract_text) dictionary["dob"] = dob if dob_found else None if len(dictionary['country']) == 0: print("Country Missing") country_found, country, ocr_list = find_country(extract_text) dictionary["country"] = country if country_found else None if len(dictionary['document_number']) == 0: print("document Number missing") document_number_found, document_number, ocr_list = doc_number(extract_text) dictionary["document_number"] = document_number if document_number_found else None print("Updated Dict ",dictionary) response = {"Status" : 200, "OCR" : dictionary} return response demo = gr.Interface(ocr, gr.Image(), "json") demo.launch(share=True)