exam-segment-django/segment/sheet_resolve/analysis/sheet/sheet_points_total.py

# -*- 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