from model0 import model0 import checkTool as ct import extract_pdf as pf import extraction_data as ed import get_chinese_name as cn import search_engine as se import get_chinese_code as cc # get info from hkid card def string_similarity(s1, s2): # Levenshtein distance algorithm s1 = s1.replace(' ', '') s1 = s1.lower() s2 = s2.replace(' ', '') s2 = s2.lower() if s1 == s2: return 100.0 len1 = len(s1) len2 = len(s2) matrix = [[0] * (len2 + 1) for _ in range(len1 + 1)] for i in range(len1 + 1): matrix[i][0] = i for j in range(len2 + 1): matrix[0][j] = j for i in range(1, len1 + 1): for j in range(1, len2 + 1): if s1[i - 1] == s2[j - 1]: cost = 0 else: cost = 1 matrix[i][j] = min(matrix[i - 1][j] + 1, # deletion matrix[i][j - 1] + 1, # insertion matrix[i - 1][j - 1] + cost) # substitution similarity = (1 - matrix[len1][len2] / max(len1, len2)) * 100 return round(similarity, 1) def get_data(img1_path, img2_path): # img_fp = 'IMG_4495.jpg' # info1 = model1(img1_path) # info2 = model2(img1_path) # def print_info(name, valid_hkid, hkid, issuedate): # print(f'Name: {name}') # name is without space # print(f'HKID: {hkid} and validity: {valid_hkid}') # print(f'Date of issue: {issuedate}') # cinfo = ct.combine_info(info1, info2) cinfo = model0(img1_path) print(cinfo) # get info from bank data = ed.get_info_from_bank(img2_path) name = data["nameStatement"] ############# Similarity check ############## # img_fp = 'IMG_1234.jpg' name1 = cinfo[0] threshold = 85 similarity_score = string_similarity(name,name1) data["similarity_score"] = similarity_score data["name_on_id"] = name1 data["hkid"] = cinfo[2] data["validity"] = cinfo[1] data["issue_date"] = cinfo[3] data["dateofbirth"] = cinfo[4] # Get chinese name chi_name = cc.get_chinese_name(img1_path) # chi_name = cn.get_chiname(img1_path)["Chinese Name"] data["chi_name_id"] = chi_name return data