# -*- coding: utf-8 -*- # @Time : 2020/6/15 0015 10:10 # @Author : LF # @FileName: sheet_point_total.py # @Software: PyCharm import requests import base64 from urllib import parse, request import cv2 import re from threading import Thread import copy from collections import OrderedDict from PIL import Image from segment.sheet_resolve.tools.brain_api import get_ocr_text_and_coordinate_in_google_format from segment.sheet_resolve.analysis.sheet.ocr_key_words import key_words try: import tr.tr as tr except Exception: pass OCR_ACCURACY = 'accurate' # def ocr_login(): # grant_type = 'client_credentials' # client_id = OCR_CLIENT_ID # client_secret = OCR_CLIENT_SECRET # # textmod = {'grant_type': grant_type, 'client_id': client_id, 'client_secret': client_secret} # textmod = parse.urlencode(textmod) # # # 输出内容:user=admin&password=admin # header_dict = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Trident/7.0; rv:11.0) like Gecko'} # url = 'https://aip.baidubce.com/oauth/2.0/token' # req = request.Request(url='{}{}{}'.format(url, '?', textmod), headers=header_dict) # res = request.urlopen(req).read() # token = eval(res.decode(encoding='utf-8'))['access_token'] # return token # def opecv2base64(img): # image = cv2.imencode('.jpg', img)[1] # base64_data = str(base64.b64encode(image))[2:-1] # return base64_data # def get_ocr_raw_result(img, ocr_accuracy=OCR_ACCURACY, language_type='CHN_ENG'): # textmod = {'access_token': access_token} # textmod = parse.urlencode(textmod) # url = '{}{}{}{}'.format(OCR_BOX_URL, ocr_accuracy, '?', textmod) # url_general = '{}{}{}{}'.format(OCR_BOX_URL, 'general', '?', textmod) # # headers = {'Content-Type': 'application/x-www-form-urlencoded'} # # image_type = 'base64' # group_id = 'group001' # user_id = 'usr001' # # image = opecv2base64(img) # # data = { # 'image_type': image_type, # 'group_id': group_id, # 'user_id': user_id, # 'image': image, # 'detect_direction': 'true', # 'recognize_granularity': 'small', # 'language_type': language_type, # # 'vertexes_location': 'true', # # 'probability': 'true' # } # # resp = requests.post(url, data=data, headers=headers).json() # if resp.get('error_msg'): # if 'internal error' in resp.get('error_msg'): # resp = requests.post(url_general, data=data, headers=headers).json() # if resp.get('error_msg'): # raise Exception("ocr {}!".format(resp.get('error_msg'))) # else: # raise Exception("ocr {}!".format(resp.get('error_msg'))) # # return resp # def get_ocr_text_and_coordinate(img, ocr_accuracy=OCR_ACCURACY, language_type='CHN_ENG'): # textmod = {'access_token': access_token} # textmod = parse.urlencode(textmod) # url = '{}{}{}{}'.format(OCR_BOX_URL, ocr_accuracy, '?', textmod) # url_general = '{}{}{}{}'.format(OCR_BOX_URL, 'general', '?', textmod) # # headers = {'Content-Type': 'application/x-www-form-urlencoded'} # # image_type = 'base64' # group_id = 'group001' # user_id = 'usr001' # # image = opecv2base64(img) # # data = { # 'image_type': image_type, # 'group_id': group_id, # 'user_id': user_id, # 'image': image, # 'detect_direction': 'true', # 'recognize_granularity': 'small', # 'language_type': language_type, # # 'vertexes_location': 'true', # # 'probability': 'true' # } # # resp = requests.post(url, data=data, headers=headers).json() # if resp.get('error_msg'): # if 'internal error' in resp.get('error_msg'): # resp = requests.post(url_general, data=data, headers=headers).json() # if resp.get('error_msg'): # raise Exception("ocr {}!".format(resp.get('error_msg'))) # else: # raise Exception("ocr {}!".format(resp.get('error_msg'))) # # words_result = resp.get('words_result') # return words_result # def get_ocr_text_and_coordinate_in_google_format(img, ocr_accuracy=OCR_ACCURACY, language_type='CHN_ENG'): # textmod = {'access_token': access_token} # textmod = parse.urlencode(textmod) # url = '{}{}{}{}'.format(OCR_BOX_URL, ocr_accuracy, '?', textmod) # url_general = '{}{}{}{}'.format(OCR_BOX_URL, 'general', '?', textmod) # # headers = {'Content-Type': 'application/x-www-form-urlencoded'} # # image_type = 'base64' # group_id = 'group001' # user_id = 'usr001' # # image = opecv2base64(img) # # data = { # 'image_type': image_type, # 'group_id': group_id, # 'user_id': user_id, # 'image': image, # 'detect_direction': 'true', # 'recognize_granularity': 'small', # 'language_type': language_type, # # 'vertexes_location': 'true', # # 'probability': 'true' # } # # resp = requests.post(url, data=data, headers=headers).json() # if resp.get('error_msg'): # if 'internal error' in resp.get('error_msg'): # resp = requests.post(url_general, data=data, headers=headers).json() # if resp.get('error_msg'): # raise Exception("ocr {}!".format(resp.get('error_msg'))) # else: # raise Exception("ocr {}!".format(resp.get('error_msg'))) # # words_result = resp.get('words_result') # dict_list = [item2.get('location') for item in words_result for item2 in item['chars']] # char_list = [item2.get('char') for item in words_result for item2 in item['chars']] # words = [item.get('words') for item in words_result] # matrix = [] # for adict in dict_list: # xmin = adict['left'] # ymin = adict['top'] # xmax = adict['width'] + adict['left'] # ymax = adict['top'] + adict['height'] # item0 = (xmin, ymin, xmax, ymax) # matrix.append(item0) # # res_dict = {'chars': char_list, 'coordinates': matrix, 'words': words} # return res_dict def model_type_score(all_type_score_one, choice_box, cloze_box, solve_box,composition_box): # 与模型得到边框与type_score对应 ''' :param all_type_score_one: 模型得到的单个type_score的坐标位置 :param choice_box: 模型得到的选择题坐标位置 :param cloze_box: 模型得到的填空题坐标位置 :param solve_box: 模型得到的解答题坐标位置 :return: ''' N_choice = len(choice_box) N_cloze = len(cloze_box) N_solve_box = len(solve_box) N_composition = len(composition_box) min_choice_dict = {} min_cloze_dict = {} min_solve_dict = {} min_composition_dict = {} test_result1 = 0 min_choice = 100000000 min_cloze = 100000000 min_solve = 100000000 min_composition = 100000000 for j in range(N_choice): choice_distance_x = abs(list(all_type_score_one)[0] - choice_box[j][0]) choice_distance_y = abs(list(all_type_score_one)[1] - choice_box[j][1]) choice_distance = choice_distance_x + choice_distance_y if choice_distance < min_choice: min_choice = choice_distance min_choice_dict = {'min_choice': min_choice, 'bounding_box': choice_box[j], 'label': 'choice', 'type_box': all_type_score_one} for k in range(N_cloze): cloze_distance_x = abs(list(all_type_score_one)[0] - cloze_box[k][0]) cloze_distance_y = abs(list(all_type_score_one)[1] - cloze_box[k][1]) cloze_distance = cloze_distance_x + cloze_distance_y if cloze_distance < min_cloze: min_cloze = cloze_distance min_cloze_dict = {'min_cloze': min_cloze, 'bounding_box': cloze_box[k], 'label': 'cloze', 'type_box': all_type_score_one} for l in range(N_solve_box): solve_distance_x = abs(list(all_type_score_one)[0] - solve_box[l][0]) solve_distance_y = abs(list(all_type_score_one)[1] - solve_box[l][1]) solve_distance = solve_distance_x + solve_distance_y if solve_distance < min_solve: min_solve = solve_distance min_solve_dict = {'min_solve': min_solve, 'bounding_box': solve_box[l], 'label': 'solve', 'type_box': all_type_score_one} for m in range(N_composition): composition_distance_x = abs(list(all_type_score_one)[0] - composition_box[m][0]) composition_distance_y = abs(list(all_type_score_one)[1] - composition_box[m][1]) composition_distance = composition_distance_x + composition_distance_y if composition_distance < min_composition: min_composition = composition_distance min_composition_dict = {'min_cloze': min_composition, 'bounding_box': composition_box[m], 'label': 'composition', 'type_box': all_type_score_one} if min_choice < min_cloze and min_choice < min_solve and min_choice < min_composition: # 建立相互关联的关系。 即表示该type_score对应于选择题 if min_choice < 600: test_result1 = min_choice_dict else: test_result1 = -1 elif min_cloze < min_choice and min_cloze < min_solve and min_cloze < min_composition: # 建立相互关联的关系。 即表示该type_score对应于填空题 if min_cloze < 600: test_result1 = min_cloze_dict else: test_result1 = -1 elif min_solve < min_cloze and min_solve < min_choice and min_solve < min_composition: # 建立相互关联的关系。 即表示该type_score对应于解答题 if min_solve < 400: test_result1 = min_solve_dict else: test_result1 = -1 elif min_composition < min_cloze and min_composition < min_choice and min_composition < min_solve: # 建立相互关联的关系。 即表示该type_score对应于解答题 if min_composition < 400: test_result1 = min_composition_dict else: test_result1 = -1 return test_result1 def module_type_score(all_type_score_one, choice_box, cloze_box, solve_box, composition_box): # 每个模块内包含的type_score ''' :param all_type_score_one: 模型得到的单个type_score的坐标位置 :param choice_box: 模型得到的选择题坐标位置 :param cloze_box: 模型得到的填空题坐标位置 :param solve_box: 模型得到的解答题坐标位置 :return: ''' N_choice = len(choice_box) N_cloze = len(cloze_box) N_solve = len(solve_box) N_composition = len(composition_box) choice_type_score = {} cloze_type_score = {} solve_type_score = {} composition_type_score = {} test_result1 = {} temp_dis = 100000 for j in range(N_choice): if (list(all_type_score_one)[0] and list(all_type_score_one)[2]) in range(choice_box[j][0] - 100, choice_box[j][2] + 50) and (list(all_type_score_one)[1] and list(all_type_score_one)[3]) in range(choice_box[j][1] - 150, choice_box[j][3] - 50): choice_type_score = {'bounding_box': choice_box[j], 'label': 'choice', 'type_box': all_type_score_one} break for j in range(N_cloze): if (list(all_type_score_one)[0] and list(all_type_score_one)[2]) in range(cloze_box[j][0] - 100, cloze_box[j][2] + 50) and (list(all_type_score_one)[1] and list(all_type_score_one)[3]) in range(cloze_box[j][1] - 100, cloze_box[j][3] - 50): cloze_type_score = {'bounding_box': cloze_box[j], 'label': 'cloze', 'type_box': all_type_score_one} break for j in range(N_solve): if (list(all_type_score_one)[0] and list(all_type_score_one)[2]) in range(solve_box[j][0] - 50, solve_box[j][2] + 50) and (list(all_type_score_one)[1] and list(all_type_score_one)[3]) in range(solve_box[j][1]-50, solve_box[j][3]): solve_type_score = {'bounding_box': solve_box[j], 'label': 'solve', 'type_box': all_type_score_one} break for j in range(N_composition): if (list(all_type_score_one)[0] and list(all_type_score_one)[2]) in range(composition_box[j][0] - 100, composition_box[j][2] + 50) and (list(all_type_score_one)[1] and list(all_type_score_one)[3]) in range(composition_box[j][1] - 200, composition_box[j][3] - 50): composition_type_score = {'bounding_box': composition_box[j], 'label': 'composition', 'type_box': all_type_score_one} break if choice_type_score != {}: # 建立相互关联的关系。 即表示该type_score对应于选择题 test_result1 = choice_type_score elif cloze_type_score != {}: # 建立相互关联的关系。 即表示该type_score对应于填空题 test_result1 = cloze_type_score elif solve_type_score != {}: # 建立相互关联的关系。 即表示该type_score对应于解答题 test_result1 = solve_type_score elif composition_type_score != {}: test_result1 = composition_type_score else: test_result1 = -1 return test_result1 def ocr_key_words(rect, type_score_dict): # 将ocr识别得到的文字与模型得到的type_score对应 ''' :param rect: OCR识别结果数组，格式：res = {'chars': [},'coordinates': [(),()},'words': []} :param type_score_dict: 模型得到的type_score(与模型得到的边框相对应) :return: 字典中添加word ''' len_ocr = len(rect['chars']) xmin = type_score_dict['type_box'][0] ymin = type_score_dict['type_box'][1] xmax = type_score_dict['type_box'][2] ymax = type_score_dict['type_box'][3] words = [] for j in range(len_ocr): if rect['coordinates'][j][0] - xmin > -30 and rect['coordinates'][j][1] - ymin > -30 and rect['coordinates'][j][2] - xmax < 30 and rect['coordinates'][j][3] - ymax < 30: word = rect['chars'][j] words.append(word) type_score_dict['words'] = words type_score_dict_ocr = type_score_dict return type_score_dict_ocr def big_block_score(img0,xmins_b,ymins_b,xmaxs_b,ymaxs_b): res1 = get_ocr_text_and_coordinate_in_google_format(img0[ymins_b:ymaxs_b, xmins_b:xmaxs_b],ocr_accuracy=OCR_ACCURACY, language_type='CHN_ENG') aa = [] type_score_dict_ocrs = {} for ii in range(len(res1['coordinates'])): xmin11 = res1['coordinates'][ii][0] + xmins_b ymin11 = res1['coordinates'][ii][1] + ymins_b xmax11 = res1['coordinates'][ii][2] + xmins_b ymax11 = res1['coordinates'][ii][3] + ymins_b aaa = (xmin11, ymin11, xmax11, ymax11) aa.append(aaa) res1['coordinates'] = aa new_test = {} coordinates = 0 if len(res1['words']) > 0: type_score_dict_ocrs['words'] = res1['words'][0] coordinates = res1['coordinates'][0] new_test = key_words(type_score_dict_ocrs) if new_test == {} or new_test['Score_structure'] == -1: if len(res1['words']) > 1: type_score_dict_ocrs['words'] = res1['words'][1] coordinates = res1['coordinates'][1] new_test = key_words(type_score_dict_ocrs) if new_test == {} or new_test['Score_structure'] == -1: if len(res1['words']) > 2: type_score_dict_ocrs['words'] = res1['words'][2] coordinates = res1['coordinates'][2] new_test = key_words(type_score_dict_ocrs) if new_test == {} or new_test['Score_structure'] == -1: if len(res1['words']) > 3: type_score_dict_ocrs['words'] = res1['words'][3] coordinates = res1['coordinates'][3] new_test = key_words(type_score_dict_ocrs) if new_test == {} or new_test['Score_structure'] == -1: if len(res1['words']) > 4: type_score_dict_ocrs['words'] = res1['words'][4] coordinates = res1['coordinates'][4] new_test = key_words(type_score_dict_ocrs) if new_test != {} and new_test['volume_structure'] != -1 and new_test['volume_structure'] != 1: # 如果识别到分数，添加到输出信息；如果还没有识别到分数，默认没有分数 if int(new_test['volume_structure'][0]['volume_total_score']) > 200: # 暂定试卷分数都在200以内，超过200的表示识别错误 new_test['volume_structure'][0]['volume_total_score'] = int( new_test['volume_structure'][0]['volume_total_score']) % 100 return new_test elif new_test != {} and (new_test['volume_structure'] == -1 or new_test['volume_structure'] == 1) and new_test['Score_structure'] != -1: # 如果识别到分数，添加到输出信息；如果还没有识别到分数，默认没有分数 if int(new_test['Score_structure'][0]['item_total_score']) > 200: # 暂定试卷分数都在200以内，超过200的表示识别错误 new_test['Score_structure'][0]['item_total_score'] = int( new_test['Score_structure'][0]['item_total_score']) % 100 new_test['Score_structure'][0]['type_box'] = coordinates return new_test else: return -1 def get_sheet_number_total(answer_sheet, res, img0): # img0 = cv2.imread(img_path0) image_src = Image.fromarray(cv2.cvtColor(img0, cv2.COLOR_BGR2RGB)) img_w, img_h = image_src.size if (image_src.mode == 'RGB'): image_src = image_src.convert("L") choice_boxs = [] choice_m_boxs = [] cloze_boxs = [] solve_boxs = [] type_score_boxs = [] select_boxs = [] all_test = [] num_choice = 0 num_choice_m = 0 num_cloze = 0 num_slove = 0 num_select = 0 num_type_score = 0 volume_last = [] Score_last = [] score_last_one = 0 volume_last_one = 0 composition_boxs = [] num_composition = 0 j_temp = [] jj_temp =[] eles = [] yy_max = [] score_del = [] key_modules_classes = ['choice', 'cloze', 'solve', 'solve0', 'composition0', 'composition', 'correction', 'type_score'] for ele in answer_sheet["regions"]: # 从模型输出获取对应标签的边框信息 if ele["class_name"] == 'choice': choice_box = ele['bounding_box'] choice_one = ( int(choice_box['xmin']), int(choice_box['ymin']), int(choice_box['xmax']), int(choice_box['ymax'])) choice_boxs.append(choice_one) num_choice = num_choice + 1 elif ele["class_name"] == 'choice_m': choice_m_boxs.append(ele['bounding_box']) num_choice_m = num_choice_m + 1 elif ele["class_name"] == 'cloze': cloze_box = ele['bounding_box'] cloze_one = (int(cloze_box['xmin']), int(cloze_box['ymin']), int(cloze_box['xmax']), int(cloze_box['ymax'])) cloze_boxs.append(cloze_one) num_cloze = num_cloze + 1 elif ele["class_name"] == 'composition0' or ele["class_name"] == 'composition' or ele[ "class_name"] == 'correction': composition_box = ele['bounding_box'] composition_one = (int(composition_box['xmin']), int(composition_box['ymin']), int(composition_box['xmax']), int(composition_box['ymax'])) composition_boxs.append(composition_one) num_composition = num_composition + 1 elif ele["class_name"] == 'solve' or ele["class_name"] == 'solve0': solve_box = ele['bounding_box'] solve_one = (int(solve_box['xmin']), int(solve_box['ymin']), int(solve_box['xmax']), int(solve_box['ymax'])) solve_boxs.append(solve_one) num_slove = num_slove + 1 elif ele["class_name"] == 'select_s' or ele["class_name"] == 'select_b': select_box = ele['bounding_box'] select_one = ( int(select_box['xmin']), int(select_box['ymin']), int(select_box['xmax']), int(select_box['ymax'])) select_boxs.append(select_one) num_select = num_select + 1 elif ele["class_name"] == 'type_score': type_score_box = ele['bounding_box'] type_score_one = (int(type_score_box['xmin']), int(type_score_box['ymin']), int(type_score_box['xmax']), int(type_score_box['ymax'])) type_score_boxs.append(type_score_one) num_type_score = num_type_score + 1 '''解析type_score与对应分割模块的分数''' for i in range(len(type_score_boxs)): test_result1 = module_type_score(type_score_boxs[i], choice_boxs, cloze_boxs, solve_boxs, composition_boxs) if test_result1 != -1 and test_result1 != 0: xminss = (type_score_boxs[i][0] - 5) if type_score_boxs[i][0] - 5 > 0 else type_score_boxs[i][0] yminss = (type_score_boxs[i][1] - 5) if type_score_boxs[i][1] - 5 > 0 else type_score_boxs[i][1] if type_score_boxs[i][2] + 5 < img_w: xmaxss = type_score_boxs[i][2] + 5 else: xmaxss = type_score_boxs[i][2] if type_score_boxs[i][3] + 5 < img_h: ymaxss = type_score_boxs[i][3] + 5 else: ymaxss = type_score_boxs[i][3] test_result1['words'] = str() try: # tr_OCR image_src_type_score = image_src.crop((xminss, yminss, xmaxss, ymaxss)) w_small = xmaxss - xminss h_small = ymaxss - yminss if h_small < 100 and w_small > 100: image_src_type_score = Image.new(image_src.mode, (w_small, 100), (255)) image_src_type_score.paste(image_src, [0, 0, w_small, h_small]) elif w_small < 100 and h_small > 100: image_src_type_score = Image.new(image_src.mode, (100, h_small), (255)) image_src_type_score.paste(image_src, [0, 0, w_small, h_small]) elif w_small < 100 and h_small < 100: image_src_type_score = Image.new(image_src.mode, (100, 100), (255)) image_src_type_score.paste(image_src, [0, 0, w_small, h_small]) type_score_dict_ocr = tr.run(image_src_type_score) print('tr_OCR') for t in range(len(type_score_dict_ocr)): test_result1['words'] = test_result1['words'] + type_score_dict_ocr[t][1] except Exception as e: # baidu_OCR print('baidu_OCR') type_score_dict_ocr = get_ocr_text_and_coordinate_in_google_format(img0[yminss:ymaxss, xminss:xmaxss], ocr_accuracy=OCR_ACCURACY,language_type='CHN_ENG') for t in range(len(type_score_dict_ocr['words'])): test_result1['words'] = test_result1['words'] + type_score_dict_ocr['words'][t] test = key_words(test_result1) if test == {}: ### 添加返回值OCR结果 add_ocr = {} add_ocr['model_box'] = test_result1['bounding_box'] add_ocr['label'] = test_result1['label'] add_ocr['number'] = -1 add_ocr['score'] = -1 add_ocr['number_score'] = -1 add_ocr['counts'] = -1 add_ocr['type_score_box'] = type_score_boxs[i] add_ocr['ocr'] = test_result1['words'] Score_last.append(add_ocr) elif test['volume_structure'] == -1 and test['Score_structure'] == -1: ### 添加返回值OCR结果 add_ocr = {} add_ocr['model_box'] = test_result1['bounding_box'] add_ocr['label'] = test_result1['label'] add_ocr['number'] = -1 add_ocr['score'] = -1 add_ocr['number_score'] = -1 add_ocr['counts'] = -1 add_ocr['type_score_box'] = type_score_boxs[i] add_ocr['ocr'] = test_result1['words'] Score_last.append(add_ocr) elif test != {}: if test['volume_structure'] != -1 and test['volume_structure'] != 1 and int( test['volume_structure'][0]['volume_total_score']) > 200: # 暂定试卷分数都在200以内，超过200的表示识别错误 test['volume_structure'][0]['volume_total_score'] = int( test['volume_structure'][0]['volume_total_score']) % 100 elif (test['volume_structure'] == -1 or test['volume_structure'] == 1) and test['Score_structure'] != -1 and int( test['Score_structure'][0]['item_total_score']) > 200: # 暂定试卷分数都在200以内，超过200的表示识别错误 test['Score_structure'][0]['item_total_score'] = int( test['Score_structure'][0]['item_total_score']) % 100 all_test.append(test) else: ### 添加返回值OCR结果 add_ocr = {} add_ocr['model_box'] = test_result1['bounding_box'] add_ocr['label'] = test_result1['label'] add_ocr['number'] = -1 add_ocr['score'] = -1 add_ocr['number_score'] = -1 add_ocr['counts'] = -1 add_ocr['type_score_box'] = type_score_boxs[i] add_ocr['ocr'] = test_result1['words'] Score_last.append(add_ocr) ''' 解析模型分割模块没有对应的type_score时的分数''' for jjjj in range(len(all_test)): if all_test[jjjj]['Score_structure'] != -1: label_1 = all_test[jjjj]['Score_structure'][0]['label'] num_1 = all_test[jjjj]['Score_structure'][0]['item_N'] if label_1 == 'choice' : if choice_boxs.count(all_test[jjjj]['Score_structure'][0]['bounding_box']): choice_boxs.remove(all_test[jjjj]['Score_structure'][0]['bounding_box']) elif label_1 == 'cloze': if cloze_boxs.count(all_test[jjjj]['Score_structure'][0]['bounding_box']): cloze_boxs.remove(all_test[jjjj]['Score_structure'][0]['bounding_box']) elif label_1 == 'solve' and num_1 != 10000 and num_1 != -1: if solve_boxs.count(all_test[jjjj]['Score_structure'][0]['bounding_box']): solve_boxs.remove(all_test[jjjj]['Score_structure'][0]['bounding_box']) elif label_1 == 'composition': if solve_boxs.count(all_test[jjjj]['Score_structure'][0]['bounding_box']): solve_boxs.remove(all_test[jjjj]['Score_structure'][0]['bounding_box']) if choice_boxs != []: # 9月16号修改 for ij in range(len(choice_boxs)): yminss = choice_boxs[ij][1] - 150 if choice_boxs[ij][1] - 150 > 0 else choice_boxs[ij][1] xminss = choice_boxs[ij][0] - 100 if choice_boxs[ij][0] - 100 > 0 else choice_boxs[ij][0] try: new_test = big_block_score(img0, xminss, yminss, choice_boxs[ij][2], choice_boxs[ij][3]) if new_test != -1: new_test['Score_structure'][0]['bounding_box'] = choice_boxs[ij] new_test['Score_structure'][0]['label'] = 'choice' all_test.append(new_test) except Exception: print('choice_boxs_score_NULL_or_error') if cloze_boxs != []: for ij in range(len(cloze_boxs)): yminss = cloze_boxs[ij][1] - 100 if cloze_boxs[ij][1] - 100 > 0 else cloze_boxs[ij][1] xminss = cloze_boxs[ij][0] - 100 if cloze_boxs[ij][0] - 100 > 0 else cloze_boxs[ij][0] try: new_test = big_block_score(img0, xminss, yminss, cloze_boxs[ij][2], cloze_boxs[ij][3]) if new_test != -1: new_test['Score_structure'][0]['bounding_box'] = cloze_boxs[ij] new_test['Score_structure'][0]['label'] = 'cloze' all_test.append(new_test) except Exception: print('cloze_boxs_score_NULL_or_error') if solve_boxs != []: for ij in range(len(solve_boxs)): yminss = solve_boxs[ij][1] - 50 if solve_boxs[ij][1] - 50 > 0 else solve_boxs[ij][1] xminss = solve_boxs[ij][0] - 50 if solve_boxs[ij][0] - 50 > 0 else solve_boxs[ij][0] try: new_test = big_block_score(img0, xminss, yminss, solve_boxs[ij][2], solve_boxs[ij][3]) if new_test != -1: new_test['Score_structure'][0]['bounding_box'] = solve_boxs[ij] new_test['Score_structure'][0]['label'] = 'solve' all_test.append(new_test) except Exception: print('solve_boxs_score_NULL_or_error') if composition_boxs != []: for ij in range(len(composition_boxs)): yminss = composition_boxs[ij][1] - 240 if composition_boxs[ij][1] - 240 > 0 else composition_boxs[ij][1] xminss = composition_boxs[ij][0] - 100 if composition_boxs[ij][0] - 100 > 0 else composition_boxs[ij][0] try: new_test = big_block_score(img0, xminss, yminss, composition_boxs[ij][2], composition_boxs[ij][3]) if new_test != -1: new_test['Score_structure'][0]['bounding_box'] = composition_boxs[ij] new_test['Score_structure'][0]['label'] = 'composition' all_test.append(new_test) except Exception: print('composition_boxs_score_NULL_or_error') for aaa in range(len(all_test)): if all_test[aaa]['Score_structure'] != -1 and all_test[aaa]['volume_structure'] == -1: score_last_one = {'model_box': dict(all_test[aaa])['Score_structure'][0]['bounding_box'], 'label': dict(all_test[aaa])['Score_structure'][0]['label'], 'number': dict(all_test[aaa])['Score_structure'][0]['item_N'], 'score': dict(all_test[aaa])['Score_structure'][0]['item_total_score'], 'number_score': dict(all_test[aaa])['Score_structure'][0]['item_score'], 'counts': dict(all_test[aaa])['Score_structure'][0]['item_count'], 'type_score_box': dict(all_test[aaa])['Score_structure'][0]['type_box']} Score_last.append(score_last_one) continue elif all_test[aaa]['Score_structure'] != -1 and all_test[aaa]['volume_structure'] == 1: score_last_one = {'model_box': dict(all_test[aaa])['Score_structure'][0]['bounding_box'], 'label': dict(all_test[aaa])['Score_structure'][0]['label'], 'number': 10000, 'score': dict(all_test[aaa])['Score_structure'][0]['item_total_score'], 'number_score': dict(all_test[aaa])['Score_structure'][0]['item_score'], 'counts': dict(all_test[aaa])['Score_structure'][0]['item_count'], 'type_score_box': dict(all_test[aaa])['Score_structure'][0]['type_box']} Score_last.append(score_last_one) continue elif all_test[aaa]['Score_structure'] != -1 and all_test[aaa]['volume_structure'] != -1: score_last_one = {'model_box': dict(all_test[aaa])['Score_structure'][0]['bounding_box'], 'label': dict(all_test[aaa])['Score_structure'][0]['label'], 'number': -1, 'score': dict(all_test[aaa])['Score_structure'][0]['volume_total_score'], 'number_score': dict(all_test[aaa])['Score_structure'][0]['volume_score'], 'counts': dict(all_test[aaa])['Score_structure'][0]['volume_count'], 'type_score_box': dict(all_test[aaa])['Score_structure'][0]['type_box']} Score_last.append(score_last_one) volume_last_one = {'volume_N': dict(all_test[aaa])['volume_structure'][0]['volume_N'], 'volume_total_score': dict(all_test[aaa])['volume_structure'][0]['volume_total_score'], 'volume_count': dict(all_test[aaa])['volume_structure'][0]['volume_count'], 'volume_score': dict(all_test[aaa])['volume_structure'][0]['volume_score'], 'keyword_type': dict(all_test[aaa])['volume_structure'][0]['keyword_type']} volume_last.append(volume_last_one) continue elif all_test[aaa]['volume_structure'] != -1: volume_last_one = {'volume_N': dict(all_test[aaa])['volume_structure'][0]['volume_N'], 'volume_total_score': dict(all_test[aaa])['volume_structure'][0]['volume_total_score'], 'volume_count': dict(all_test[aaa])['volume_structure'][0]['volume_count'], 'volume_score': dict(all_test[aaa])['volume_structure'][0]['volume_score'], 'keyword_type': dict(all_test[aaa])['volume_structure'][0]['keyword_type']} volume_last.append(volume_last_one) continue '''去重一个边框可能对应多个type_score的情况,英语单独解析''' Score_last_Remove_Duplicates = OrderedDict() for item in Score_last: Score_last_Remove_Duplicates.setdefault(item['model_box'], {**item, }) Score_last_Remove_Duplicates = list(Score_last_Remove_Duplicates.values()) if len(Score_last_Remove_Duplicates) != len(Score_last): len_Score_last = len(Score_last) Score_last = sorted(Score_last, key=lambda x: (x['model_box'][0] + x['model_box'][1] + x['type_score_box'][0] + x['type_score_box'][1]),reverse=True) if answer_sheet['subject'] == 'english': # 暂定英语只去除重复分数，不修改主观题边框 for i in range(len_Score_last-1, -1, -1): if Score_last[i]['label'] == 'cloze': model_box2 = []; score2 = []; num2 = []; type_score2 = []; temp22 = [] if Score_last[i]['model_box'] in model_box2: index21 = model_box2.index(Score_last[i]['model_box']) index2 = temp22[index21] score = Score_last[i]['score'] if score < score2[index21] and score2[index21] < 20: # 去重，type_score多余的包含小题分数 Score_last[i] = -1 elif score < score2[index21] and score2[index21] > 20: # 去重，type_score多余的包含分卷分数 Score_last[index2] = -1 temp22[index21] = i score2[index21] = Score_last[i]['score'] num2[index21] = Score_last[i]['number'] type_score2[index21] = Score_last[i]['type_score_box'] elif score > score2[index21] and score < 20: # 去重，type_score在不大于20分的情况下，暂定保留更大的分数 Score_last[index2] = -1 temp22[index21] = i score2[index21] = Score_last[i]['score'] num2[index21] = Score_last[i]['number'] type_score2[index21] = Score_last[i]['type_score_box'] elif score > score2[index21] and score > 20: # 去重，type_score去除大于20分的重复分数 Score_last[i] = -1 else: Score_last[i] = -1 else: model_box2.append(Score_last[i]['model_box']) score2.append(Score_last[i]['score']) num2.append(Score_last[i]['number']) type_score2.append(Score_last[i]['type_score_box']) temp22.append(i) else: model_box2 = []; score2 = []; num2 = []; type_score2 = []; temp22 = [] if Score_last[i]['model_box'] in model_box2: index21 = model_box2.index(Score_last[i]['model_box']) index2 = temp22[index21] score = Score_last[i]['score'] if score < score2[index21]: # 去重，暂定保留更大的分数 Score_last[i] = -1 elif score > score2[index21]: # 去重，暂定保留更大的分数 Score_last[index2] = -1 temp22[index21] = i score2[index21] = Score_last[i]['score'] num2[index21] = Score_last[i]['number'] type_score2[index21] = Score_last[i]['type_score_box'] else: Score_last[i] = -1 else: model_box2.append(Score_last[i]['model_box']) score2.append(Score_last[i]['score']) num2.append(Score_last[i]['number']) type_score2.append(Score_last[i]['type_score_box']) temp22.append(i) else: # 除去英语外的主观题边框修正 model_box2 = []; score2 = []; num2 = []; type_score2 = []; temp22 = [] for i in range(len_Score_last - 1, -1, -1): # 根据type_score切分 if Score_last[i]['label'] == 'solve' or Score_last[i]['label'] == 'solve0': if Score_last[i]['model_box'] in model_box2 and type(Score_last[i]['number']) is not list: index21 = model_box2.index(Score_last[i]['model_box']) index2 = temp22[index21] score = Score_last[i]['score'] num = Score_last[i]['number'] type_score = Score_last[i]['type_score_box'] del_box = 0 if num == -1: # 去除同一主观题内对应的多个边框内的小项分数 if 'ocr' in Score_last[index2]: Score_last[index2] = -1 temp22[index21] = i score2[index21] = Score_last[i]['score'] num2[index21] = Score_last[i]['number'] type_score2[index21] = Score_last[i]['type_score_box'] elif 'ocr' in Score_last[i]: Score_last[i] = -1 else: Score_last[i] = -1 elif num == 10000: Score_last[i] = -1 elif num2[index21] == 10000 or num2[index21] == -1 and type_score[1] - type_score2[index21][1] > 100: # 同一主观题包含大题分数和小项分数，且大题分数位于边框中间，切分为两个主观题 yy_max.append(Score_last[i]['model_box'][3]) del_box = copy.deepcopy(Score_last[index2]['model_box']) score_del.append(del_box) Score_last[index2]['model_box'] = ( Score_last[index2]['model_box'][0], Score_last[index2]['model_box'][1], Score_last[index2]['model_box'][2], type_score[1]) Score_last[i]['model_box'] = ( Score_last[i]['model_box'][0], type_score[1], Score_last[i]['model_box'][2], Score_last[i]['model_box'][3]) score2[index21] = Score_last[i]['score'] num2[index21] = Score_last[i]['number'] type_score2[index21] = Score_last[i]['type_score_box'] temp22[index21] = i elif score < score2[index21] and score2[index21] > 30: # 默认有效的分数值小于30分 Score_last[index2] = -1 temp22[index21] = i score2[index21] = Score_last[i]['score'] num2[index21] = Score_last[i]['number'] type_score2[index21] = Score_last[i]['type_score_box'] elif score < 30 and score2[index21] < 30 and type_score[1] - type_score2[index21][1] > 100: # 同一主观题包含两个大题分数，且距离 >00 的情况下切分为两个主观题 yy_max.append(Score_last[i]['model_box'][3]) del_box = copy.deepcopy(Score_last[index2]['model_box']) score_del.append(del_box) Score_last[index2]['model_box'] = ( Score_last[index2]['model_box'][0], Score_last[index2]['model_box'][1], Score_last[index2]['model_box'][2], type_score[1]) Score_last[i]['model_box'] = ( Score_last[i]['model_box'][0], type_score[1], Score_last[i]['model_box'][2], Score_last[i]['model_box'][3]) score2[index21] = Score_last[i]['score'] num2[index21] = Score_last[i]['number'] type_score2[index21] = Score_last[i]['type_score_box'] temp22[index21] = i elif score > 30 and score2[index21] > 30: # 默认有效的分数值小于30分 temp_del = i if score > score2[index21] else index2 Score_last[temp_del] = -1 if temp_del == index2: temp22[index21] = i score2[index21] = Score_last[i]['score'] num2[index21] = Score_last[i]['number'] type_score2[index21] = Score_last[i]['type_score_box'] elif score < 30 and score2[index21] < 30: # 多个分数小于30，且距离 <100 的情况下，删除 temp_del = i if score < score2[index21] else index2 Score_last[temp_del] = -1 if temp_del == index2: temp22[index21] = i score2[index21] = Score_last[i]['score'] num2[index21] = Score_last[i]['number'] type_score2[index21] = Score_last[i]['type_score_box'] else: Score_last[i] = -1 else: model_box2.append(Score_last[i]['model_box']) score2.append(Score_last[i]['score']) num2.append(Score_last[i]['number']) type_score2.append(Score_last[i]['type_score_box']) temp22.append(i) for del_i in range(len_Score_last - 1, -1, -1): if Score_last[del_i] == -1: del Score_last[del_i] if answer_sheet['subject'] != 'english': Score_last = sorted(Score_last, key=lambda x: (x['model_box'][0], x['model_box'][0] + x['model_box'][1]),reverse=True) temp33 = 0 len3 = len(Score_last) for i in range(len3 - 1, -1, -1): # 根据type_score合并 if Score_last[i]['label'] == 'solve' or Score_last[i]['label'] == 'solve0': num = Score_last[i]['number'] type_score = Score_last[i]['type_score_box'] if type(Score_last[i]['number']) is not list: if num == 10000 or num == -1 or num < 4 and (Score_last[i]['label'] == 'solve' or Score_last[i]['label'] == 'solve0'): # 小题题号 temp3 = 100000 for indexi, model_box31 in enumerate(Score_last): if indexi != i and ((type_score[0] and type_score[2]) in range(model_box31['model_box'][0] - 30,model_box31['model_box'][2])) and ((type_score[1] and type_score[3]) in range(model_box31['model_box'][1],model_box31['model_box'][3]+30)): # 根据小题边框的xmin与主观题xmin的差值判断为一栏，以及纵坐标差值判断条件 del_box = copy.deepcopy(Score_last[i]['model_box']) score_del.append(del_box) score_del.append(Score_last[indexi]['model_box']) Score_last[indexi]['model_box'] = ( Score_last[indexi]['model_box'][0], Score_last[indexi]['model_box'][1], Score_last[indexi]['model_box'][2], Score_last[i]['model_box'][3]) del Score_last[i] break temp31 = int(type_score[1] - model_box31['model_box'][3]) # 计算小题边框的ymin与主观题边框ymax的距离 if (type_score[0] in range(model_box31['model_box'][0] - 30,model_box31['model_box'][2])) and temp31 > -20 and temp31 < temp3: # 根据小题边框的xmin与主观题xmin的差值判断为一栏，以及纵坐标差值判断条件 temp3 = temp31 temp33 = indexi yy_max.append(Score_last[i]['model_box'][3]) if indexi == len(Score_last) - 1: del_box = copy.deepcopy(Score_last[temp33]['model_box']) score_del.append(del_box) score_del.append(Score_last[i]['model_box']) Score_last[temp33]['model_box'] = ( Score_last[temp33]['model_box'][0], Score_last[temp33]['model_box'][1], Score_last[temp33]['model_box'][2], Score_last[i]['model_box'][3]) del Score_last[i] break elif indexi == len(Score_last) - 1 and temp3 != 100000: del_box = copy.deepcopy(Score_last[temp33]['model_box']) score_del.append(del_box) score_del.append(Score_last[i]['model_box']) Score_last[temp33]['model_box'] = ( Score_last[temp33]['model_box'][0], Score_last[temp33]['model_box'][1], Score_last[temp33]['model_box'][2], Score_last[i]['model_box'][3]) del Score_last[i] break if Score_last != []: for i in range(len(Score_last)): # 多选题题号和分数逐个显示 if type(Score_last[i]['number']) is list: C_q_s = len(Score_last[i]['number']) * [Score_last[i]['score']] Score_last[i]['score'] = C_q_s '''choice_m/cloze_s分数解析''' if num_choice == 1 or num_cloze == 1: # 对应choice_m分数 for i in range(len(Score_last)): if Score_last[i]['label'] == 'choice': count_choice_m = 0 for j in range(len(answer_sheet['regions'])): if answer_sheet['regions'][j]['class_name'] == 'choice_m': if Score_last[i]['number_score'] != -1 and ('number' in answer_sheet['regions'][j].keys()): answer_sheet['regions'][j]['default_points'] = len(answer_sheet['regions'][j]['number']) * [float(Score_last[i]['number_score'])] elif Score_last[i]['number_score'] == -1 and Score_last[i]['score'] != -1 and 'number' in answer_sheet['regions'][j].keys(): count_choice_m = count_choice_m + len(answer_sheet['regions'][j]['number']) j_temp.append(j) if j == len(answer_sheet['regions']) - 1 and j_temp !=[]: try: for index, jj in enumerate(j_temp): num_score_m = round(float(Score_last[i]['score'] / count_choice_m), 2) answer_sheet['regions'][jj]['default_points'] = len(answer_sheet['regions'][jj]['number']) * [num_score_m] break except Exception: print('choice_m_error') elif Score_last[i]['label'] == 'cloze': for j in range(len(answer_sheet['regions'])): if answer_sheet['regions'][j]['class_name'] == 'cloze_s': if Score_last[i]['number_score'] != -1: answer_sheet['regions'][j]['default_points'] = Score_last[i]['number_score'] elif num_choice > 1 or num_cloze > 1: for i in range(len(Score_last)): if Score_last[i]['label'] == 'choice': count_choice_m = 0 for j in range(len(answer_sheet['regions'])): if answer_sheet['regions'][j]['class_name'] == 'choice_m': xmin_dis = answer_sheet['regions'][j]['bounding_box']['xmin'] - \ Score_last[i]['model_box'][0] ymin_dis = answer_sheet['regions'][j]['bounding_box']['ymin'] - \ Score_last[i]['model_box'][1] xmax_dis = answer_sheet['regions'][j]['bounding_box']['xmax'] - \ Score_last[i]['model_box'][2] ymax_dis = answer_sheet['regions'][j]['bounding_box']['ymax'] - \ Score_last[i]['model_box'][3] if xmin_dis > -30 and ymin_dis > -30 and xmax_dis < 30 and ymax_dis < 30: if Score_last[i]['number_score'] != -1 and 'number' in answer_sheet['regions'][j].keys(): answer_sheet['regions'][j]['default_points'] = len(answer_sheet['regions'][j]['number']) * [float(Score_last[i]['number_score'])] elif Score_last[i]['number_score'] == -1 and Score_last[i]['score'] != -1 and 'number' in answer_sheet['regions'][j].keys(): count_choice_m = count_choice_m + len(answer_sheet['regions'][j]['number']) j_temp.append(j) if j == len(answer_sheet['regions']) - 1 and j_temp !=[]: try: for index, jj in enumerate(j_temp): num_score_m = round(float(Score_last[i]['score'] / count_choice_m), 2) answer_sheet['regions'][jj]['default_points'] = len(answer_sheet['regions'][jj]['number']) * [num_score_m] break except Exception: print('choice_m_error') elif Score_last[i]['label'] == 'cloze': for j in range(len(answer_sheet['regions'])): if answer_sheet['regions'][j]['class_name'] == 'cloze_s': xmin_dis = answer_sheet['regions'][j]['bounding_box']['xmin'] - \ Score_last[i]['model_box'][0] ymin_dis = answer_sheet['regions'][j]['bounding_box']['ymin'] - \ Score_last[i]['model_box'][1] xmax_dis = answer_sheet['regions'][j]['bounding_box']['xmax'] - \ Score_last[i]['model_box'][2] ymax_dis = answer_sheet['regions'][j]['bounding_box']['ymax'] - \ Score_last[i]['model_box'][3] if xmin_dis > -30 and ymin_dis > -30 and xmax_dis < 30 and ymax_dis < 30: if Score_last[i]['number_score'] != -1 : answer_sheet['regions'][j]['default_points'] = Score_last[i]['number_score'] elif choice_m_boxs !=[]: x_choice_m_min = 10000 y_choice_m_min = 10000 x_choice_m_max = 0 y_choice_m_max = 0 test = {} for index_m, choice_m_s in enumerate(choice_m_boxs): if int(choice_m_s['xmin']) < x_choice_m_min: x_choice_m_min = int(choice_m_s['xmin']) if int(choice_m_s['ymin']) < y_choice_m_min: y_choice_m_min = int(choice_m_s['ymin']) if int(choice_m_s['xmax']) > x_choice_m_max: x_choice_m_max = int(choice_m_s['xmax']) if int(choice_m_s['ymax']) > y_choice_m_max: y_choice_m_max = int(choice_m_s['ymax']) # 模型输出没有choice的情况下暂时假定只有一个choice type_score_choice_m = -1 for index_t1, type_score_s1 in enumerate(type_score_boxs): if type_score_s1[0] < x_choice_m_max and type_score_s1[3] < y_choice_m_min: type_score_choice_m = type_score_s1 break if type_score_choice_m != -1: test_result1 = {'min_choice_m': -1, 'bounding_box': choice_m_boxs, 'label': 'choice_m', 'type_box': type_score_choice_m} test_result1['words'] = str() try: # tr_OCR image_choice = image_src.crop((type_score_choice_m[0], type_score_choice_m[1], type_score_choice_m[2], type_score_choice_m[3])) res1 = tr.run(image_choice) print('tr_OCR') for t in range(len(res1)): test_result1['words'] = test_result1['words'] + res1[t][1] except Exception as e: # baidu_OCR print('baidu_OCR') res1 = get_ocr_text_and_coordinate_in_google_format( img0[type_score_choice_m[1]:type_score_choice_m[3], type_score_choice_m[0]:type_score_choice_m[2]], ocr_accuracy=OCR_ACCURACY, language_type='CHN_ENG') for t in range(len(res1['words'])): test_result1['words'] = test_result1['words'] + res1['words'][t] if test_result1['words'] != {}: test = key_words(test_result1) choice_m_score = -1 if test == {}: choice_m_type_score_ocr = test_result1['words'] elif test['volume_structure'] == -1 and test['Score_structure'] == -1: choice_m_type_score_ocr = test_result1['words'] else: if test['volume_structure'] != -1 and test['volume_structure'][0]['volume_score'] != -1: choice_m_score = test['volume_structure'][0]['volume_score'] elif test['volume_structure'] == -1 and test['Score_structure'] != -1 and test['Score_structure'][0]['item_score'] != -1: choice_m_score = test['Score_structure'][0]['item_score'] if choice_m_score != -1: for j in range(len(answer_sheet['regions'])): if answer_sheet['regions'][j]['class_name'] == 'choice_m': answer_sheet['regions'][j]['default_points'] = len( answer_sheet['regions'][j]['number']) * [float(choice_m_score)] elif test_result1['words'] != {}: for j in range(len(answer_sheet['regions'])): if answer_sheet['regions'][j]['class_name'] == 'choice_m': answer_sheet['regions'][j]['type_score_ocr'] = choice_m_type_score_ocr '''分数与模型对应''' ocr_flag = 0 for i in range(len(answer_sheet['regions'])-1, -1, -1): for j in range(len(Score_last)-1, -1, -1): if (int(Score_last[j]['model_box'][0]) == int(answer_sheet['regions'][i]['bounding_box']['xmin']) and int(Score_last[j]['model_box'][1]) == int(answer_sheet['regions'][i]['bounding_box']['ymin']) and int(Score_last[j]['model_box'][2]) == int(answer_sheet['regions'][i]['bounding_box']['xmax']) and int(Score_last[j]['model_box'][3]) != int(answer_sheet['regions'][i]['bounding_box']['ymax'])) and (answer_sheet['regions'][i]['class_name'] == 'solve' or answer_sheet['regions'][i]['class_name'] == 'solve0'): answer_sheet['regions'][i]['bounding_box']['ymax'] = int(Score_last[j]['model_box'][3]) if Score_last[j]['number'] == 10000: answer_sheet['regions'][i]['number'] = -1 # 题号 elif Score_last[j]['number'] != -1 and Score_last[j]['number'] != 10000: answer_sheet['regions'][i]['number'] = Score_last[j]['number'] # 题号 else: answer_sheet['regions'][i]['number'] = -1 # 题号 if Score_last[j]['score'] != -1: answer_sheet['regions'][i]['default_points'] = Score_last[j]['score'] if type(answer_sheet['regions'][i]['default_points']) is list and ( answer_sheet['regions'][i]['class_name'] == 'solve' or answer_sheet['regions'][i][ 'class_name'] == 'solve0'): answer_sheet['regions'][i]['class_name'] = 'optional_solve' elif 'default_points' not in answer_sheet['regions'][i].keys(): answer_sheet['regions'][i]['default_points'] = -1 del Score_last[j] elif (int(Score_last[j]['model_box'][0]) == int(answer_sheet['regions'][i]['bounding_box']['xmin']) and int(Score_last[j]['model_box'][1]) == int(answer_sheet['regions'][i]['bounding_box']['ymin']) and int(Score_last[j]['model_box'][2]) == int(answer_sheet['regions'][i]['bounding_box']['xmax']) and int(Score_last[j]['model_box'][3]) == int(answer_sheet['regions'][i]['bounding_box']['ymax'])): if Score_last[j]['number'] == 10000: answer_sheet['regions'][i]['number'] = -1 # 题号 elif Score_last[j]['number'] != -1 and Score_last[j]['number'] != 10000: answer_sheet['regions'][i]['number'] = Score_last[j]['number'] # 题号 else: answer_sheet['regions'][i]['number'] = -1 # 题号 if Score_last[j]['score'] != -1: answer_sheet['regions'][i]['default_points'] = Score_last[j]['score'] if type(answer_sheet['regions'][i]['default_points']) is list and ( answer_sheet['regions'][i]['class_name'] == 'solve' or answer_sheet['regions'][i][ 'class_name'] == 'solve0'): answer_sheet['regions'][i]['class_name'] = 'optional_solve' ocr_flag = 1 if 'type_score_ocr' in answer_sheet['regions'][i].keys(): del answer_sheet['regions'][i]['type_score_ocr'] elif 'default_points' not in answer_sheet['regions'][i].keys(): answer_sheet['regions'][i]['default_points'] = -1 if ocr_flag == 0 and 'ocr' in Score_last[j]: # 没有识别到分数的模块添加type_score_ocr结果 answer_sheet['regions'][i]['type_score_ocr'] = Score_last[j]['ocr'] del Score_last[j] if score_del != []: # del_model_boxs for j in range(len(score_del)): if score_del != [] and (score_del[j][0] == answer_sheet['regions'][i]['bounding_box']['xmin'] and score_del[j][1] == answer_sheet['regions'][i]['bounding_box']['ymin'] and score_del[j][2] == answer_sheet['regions'][i]['bounding_box']['xmax'] and score_del[j][3] == answer_sheet['regions'][i]['bounding_box']['ymax']): del answer_sheet['regions'][i] for jj in range(len(Score_last)): # add_model_boxs answer_sheet_one = {} answer_sheet_one['class_name'] = Score_last[jj]['label'] box_one = {} box_one['xmin'] = int(Score_last[jj]['model_box'][0]) box_one['ymin'] = int(Score_last[jj]['model_box'][1]) box_one['xmax'] = int(Score_last[jj]['model_box'][2]) box_one['ymax'] = int(Score_last[jj]['model_box'][3]) answer_sheet_one['bounding_box'] = box_one if Score_last[jj]['number'] == 10000: answer_sheet_one['number'] = -1 # 题号 elif Score_last[jj]['number'] != -1 and Score_last[jj]['number'] != 10000: answer_sheet_one['number'] = Score_last[jj]['number'] # 题号 else: answer_sheet_one['number'] = -1 # 题号 if Score_last[jj]['score'] != -1: answer_sheet_one['default_points'] = Score_last[jj]['score'] else: answer_sheet_one['default_points'] = -1 answer_sheet['regions'].append(answer_sheet_one) return answer_sheet