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

# @Author  : fantuan
# @Time    : 2019.9.4


import requests
import base64
from urllib import parse, request
import cv2
import re
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

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 test_result1 < 400:
            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 test_result1 < 400:
            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 test_result1 < 300:
            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 test_result1 < 300:
            test_result1 = min_composition_dict
        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 get_sheet_number_total(answer_sheet, res, img0):
    # img_path0 = r'C:\Users\Administrator\Desktop\score_test\image\dili\000003.jpg'
    # img0 = cv2.imread(img_path0)
    # access_token = ocr_login()
    # res = get_ocr_text_and_coordinate_in_google_format(img0, ocr_accuracy=OCR_ACCURACY, language_type='CHN_ENG') # 整张OCR
    # answer_sheet = {"img_name": "000003.jpg", "analysis_type": "geography", "regions": [{"class_name": "cloze_s", "bounding_box": {"xmin": 57, "ymin": 412, "xmax": 1554, "ymax": 514}, "score": "1.0000"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 82, "ymin": 988, "xmax": 1496, "ymax": 1073}, "score": "1.0000"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 101, "ymin": 508, "xmax": 1540, "ymax": 602}, "score": "0.9999"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 170, "ymin": 1485, "xmax": 1532, "ymax": 1556}, "score": "0.9999"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 49, "ymin": 1298, "xmax": 1516, "ymax": 1383}, "score": "0.9994"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 179, "ymin": 1067, "xmax": 1502, "ymax": 1164}, "score": "0.9994"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 118, "ymin": 1529, "xmax": 1532, "ymax": 1635}, "score": "0.9983"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 74, "ymin": 1395, "xmax": 923, "ymax": 1456}, "score": "0.9976"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 52, "ymin": 830, "xmax": 1466, "ymax": 903}, "score": "0.9960"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 79, "ymin": 1594, "xmax": 1540, "ymax": 1737}, "score": "0.9365"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 85, "ymin": 266, "xmax": 940, "ymax": 342}, "score": "0.7881"}, {"class_name": "cloze_s", "bounding_box": {"xmin": 99, "ymin": 900, "xmax": 956, "ymax": 974}, "score": "0.7662"}, {"class_name": "page", "bounding_box": {"xmin": 716, "ymin": 2220, "xmax": 995, "ymax": 2284}, "score": "0.8190"}, {"class_name": "type_score", "bounding_box": {"xmin": 63, "ymin": 757, "xmax": 242, "ymax": 821}, "score": "0.9989"}, {"class_name": "type_score", "bounding_box": {"xmin": 66, "ymin": 105, "xmax": 250, "ymax": 163}, "score": "0.9613"}, {"class_name": "type_score", "bounding_box": {"xmin": 55, "ymin": 1228, "xmax": 239, "ymax": 1287}, "score": "0.9506"}, {"class_name": "cloze", "bounding_box": {"xmin": 49, "ymin": 93, "xmax": 1518, "ymax": 754}, "score": "0.9954"}, {"class_name": "cloze", "bounding_box": {"xmin": 88, "ymin": 780, "xmax": 1524, "ymax": 1579}, "score": "0.9208"}], "series_number": "20190912000015", "is_success": 1}

    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
    model_box2 = []
    composition_boxs = []
    score2 = []
    num_redundance = 0
    num_composition = 0
    j_temp = []
    jj_temp =[]
    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)
            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

    for i in range(len(type_score_boxs)):
        test_result1 = model_type_score(type_score_boxs[i], choice_boxs, cloze_boxs, solve_boxs, composition_boxs)
        if test_result1 != -1 and test_result1 != 0:
            type_score_dict_ocr = ocr_key_words(res, test_result1)
            if type_score_dict_ocr['words'] == []:  # type_score没有ocr结果,暂定可能ocr漏识别到分数，再过一遍ocr
                type_score_dict_ocr['words'] = get_ocr_text_and_coordinate_in_google_format(img0[type_score_boxs[i][1]:type_score_boxs[i][3],type_score_boxs[i][0]:type_score_boxs[i][2]],ocr_accuracy=OCR_ACCURACY,language_type='CHN_ENG')['words']
            test = key_words(type_score_dict_ocr)
            if test == {} or test['Score_structure'] == -1:  # 如果存在type_score未识别到分数，暂定可能ocr漏识别到分数，再过一遍ocr
                image = img0[test_result1['bounding_box'][1]: test_result1['bounding_box'][3],
                        test_result1['bounding_box'][0]: test_result1['bounding_box'][2]]
                res1 = get_ocr_text_and_coordinate_in_google_format(image,ocr_accuracy=OCR_ACCURACY,language_type='CHN_ENG')
                aa = []
                for ii in range(len(res1['coordinates'])):
                    xmin11 = res1['coordinates'][ii][0] + test_result1['bounding_box'][0]
                    ymin11 = res1['coordinates'][ii][1] + test_result1['bounding_box'][1]
                    xmax11 = res1['coordinates'][ii][2] + test_result1['bounding_box'][0]
                    ymax11 = res1['coordinates'][ii][3] + test_result1['bounding_box'][1]
                    aaa = (xmin11, ymin11, xmax11, ymax11)
                    aa.append(aaa)
                res1['coordinates'] = aa
                if len(res1['words']) > 0:
                    type_score_dict_ocr['words'] = res1['words'][0]
                    new_test = key_words(type_score_dict_ocr)
                    if new_test == {} or new_test['Score_structure'] == -1:
                        if len(res1['words']) > 1:
                            type_score_dict_ocr['words'] = res1['words'][1]
                            new_test = key_words(type_score_dict_ocr)
                            if new_test == {} or new_test['Score_structure'] == -1:
                                if len(res1['words']) > 2:
                                    type_score_dict_ocr['words'] = res1['words'][2]
                                    new_test = key_words(type_score_dict_ocr)
                    if new_test != {}:
                        if new_test['volume_structure'] != -1 and 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
                        elif new_test['volume_structure'] == -1 and new_test['Score_structure'] != -1 and 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
                        all_test.append(new_test)
            else:
                if 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 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)
    for jjjj in range(len(all_test)):
        if all_test[jjjj]['Score_structure'] != -1:
            label_1 = all_test[jjjj]['Score_structure'][0]['label']
            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':
                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)):
            if choice_boxs[ij][1] - 150 > 0:
                yminss = choice_boxs[ij][1] - 150
            else:
                yminss = choice_boxs[ij][1]
            if choice_boxs[ij][0] - 100 > 0:
                xminss = choice_boxs[ij][0] - 100
            else:
                xminss = choice_boxs[ij][0]
            res1 = get_ocr_text_and_coordinate_in_google_format(
                img0[yminss:choice_boxs[ij][3], xminss:choice_boxs[ij][2]], 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] + choice_boxs[ij][0]
                ymin11 = res1['coordinates'][ii][1] + choice_boxs[ij][1]
                xmax11 = res1['coordinates'][ii][2] + choice_boxs[ij][0]
                ymax11 = res1['coordinates'][ii][3] + choice_boxs[ij][1]
                aaa = (xmin11, ymin11, xmax11, ymax11)
                aa.append(aaa)
            res1['coordinates'] = aa
            # print(res1)
            if len(res1['words']) > 0:
                type_score_dict_ocrs['words'] = res1['words'][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]
                        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]
                                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]
                                    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]
                                        new_test = key_words(type_score_dict_ocrs)
                if new_test != {} and new_test['volume_structure'] != -1 and (int(new_test['volume_structure'][0]['volume_total_score']) > 4 or int(new_test['volume_structure'][0]['volume_score']) > 4):  # 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
                    new_test['volume_structure'][0]['bounding_box'] = choice_boxs[ij]
                    new_test['volume_structure'][0]['label'] = 'choice'
                    all_test.append(new_test)
                elif new_test != {} and new_test['volume_structure'] == -1 and new_test['Score_structure'] != -1 and (int(new_test['Score_structure'][0]['item_total_score']) >4 or int(new_test['Score_structure'][0]['item_score']) > 4):  # 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]['bounding_box'] = choice_boxs[ij]
                    new_test['Score_structure'][0]['label'] = 'choice'
                    all_test.append(new_test)
    if cloze_boxs != []:
        for ij in range(len(cloze_boxs)):
            if cloze_boxs[ij][1] - 100 > 0:
                yminss = cloze_boxs[ij][1] - 100
            else:
                yminss = cloze_boxs[ij][1]
            if cloze_boxs[ij][0] - 100 > 0:
                xminss = cloze_boxs[ij][0] - 100
            else:
                xminss = cloze_boxs[ij][0]
            res1 = get_ocr_text_and_coordinate_in_google_format(
                img0[yminss:cloze_boxs[ij][3], xminss:cloze_boxs[ij][2]], 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] + cloze_boxs[ij][0]
                ymin11 = res1['coordinates'][ii][1] + cloze_boxs[ij][1]
                xmax11 = res1['coordinates'][ii][2] + cloze_boxs[ij][0]
                ymax11 = res1['coordinates'][ii][3] + cloze_boxs[ij][1]
                aaa = (xmin11, ymin11, xmax11, ymax11)
                aa.append(aaa)
            res1['coordinates'] = aa
            if len(res1['words']) > 0:
                type_score_dict_ocrs['words'] = res1['words'][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]
                        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]
                                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]
                                    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]
                                        new_test = key_words(type_score_dict_ocrs)
                if new_test != {} and new_test['volume_structure'] != -1 and (int(new_test['volume_structure'][0]['volume_total_score']) > 4 or int(new_test['volume_structure'][0]['volume_score']) > 4):  # 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
                    new_test['volume_structure'][0]['bounding_box'] = cloze_boxs[ij]
                    new_test['volume_structure'][0]['label'] = 'cloze'
                    all_test.append(new_test)
                elif new_test != {} and new_test['volume_structure'] == -1 and new_test['Score_structure'] != -1 and (int(new_test['Score_structure'][0]['item_total_score']) > 4 or int(new_test['Score_structure'][0]['item_score']) > 4):  # 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]['bounding_box'] = cloze_boxs[ij]
                    new_test['Score_structure'][0]['label'] = 'cloze'
                    all_test.append(new_test)
    if solve_boxs != []:
        for ij in range(len(solve_boxs)):
            yminss = solve_boxs[ij][1]
            xminss = solve_boxs[ij][0]
            res1 = get_ocr_text_and_coordinate_in_google_format(
                img0[yminss:solve_boxs[ij][3], xminss:solve_boxs[ij][2]], 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] + solve_boxs[ij][0]
                ymin11 = res1['coordinates'][ii][1] + solve_boxs[ij][1]
                xmax11 = res1['coordinates'][ii][2] + solve_boxs[ij][0]
                ymax11 = res1['coordinates'][ii][3] + solve_boxs[ij][1]
                aaa = (xmin11, ymin11, xmax11, ymax11)
                aa.append(aaa)
            res1['coordinates'] = aa
            if len(res1['words']) > 0:
                type_score_dict_ocrs['words'] = res1['words'][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]
                        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]
                                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]
                                    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]
                                        new_test = key_words(type_score_dict_ocrs)
                if new_test != {} and new_test['volume_structure'] != -1 and int(new_test['volume_structure'][0]['volume_total_score']) > 5:  # 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
                    new_test['volume_structure'][0]['bounding_box'] = solve_boxs[ij]
                    new_test['volume_structure'][0]['label'] = 'solve'
                    all_test.append(new_test)
                elif new_test != {} and new_test['volume_structure'] == -1 and new_test['Score_structure'] != -1 and (int(new_test['Score_structure'][0]['item_total_score']) > 5 or int(new_test['Score_structure'][0]['item_total_score']) == -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]['bounding_box'] = solve_boxs[ij]
                    new_test['Score_structure'][0]['label'] = 'solve'
                    all_test.append(new_test)
    if composition_boxs != []:
        for ij in range(len(composition_boxs)):
            if composition_boxs[ij][1] - 250 > 0:
                yminss = composition_boxs[ij][1] - 250
            else:
                yminss = composition_boxs[ij][1]
            if composition_boxs[ij][0] - 100 > 0:
                xminss = composition_boxs[ij][0] - 100
            else:
                xminss = composition_boxs[ij][0]
            res1 = get_ocr_text_and_coordinate_in_google_format(
                img0[yminss:composition_boxs[ij][3], xminss:composition_boxs[ij][2]], 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] + composition_boxs[ij][0]
                ymin11 = res1['coordinates'][ii][1] + composition_boxs[ij][1]
                xmax11 = res1['coordinates'][ii][2] + composition_boxs[ij][0]
                ymax11 = res1['coordinates'][ii][3] + composition_boxs[ij][1]
                aaa = (xmin11, ymin11, xmax11, ymax11)
                aa.append(aaa)
            res1['coordinates'] = aa
            if len(res1['words']) > 0:
                type_score_dict_ocrs['words'] = res1['words'][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]
                        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]
                                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]
                                    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]
                                        new_test = key_words(type_score_dict_ocrs)
                if new_test != {} and new_test['volume_structure'] != -1 and int(
                        new_test['volume_structure'][0]['volume_total_score']) > 4:  # 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
                    new_test['volume_structure'][0]['bounding_box'] = composition_boxs[ij]
                    new_test['volume_structure'][0]['label'] = 'composition'
                    all_test.append(new_test)
                elif new_test != {} and new_test['volume_structure'] == -1 and new_test[
                    'Score_structure'] != -1 and int(
                        new_test['Score_structure'][0]['item_total_score']) > 4:  # 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]['bounding_box'] = composition_boxs[ij]
                    new_test['Score_structure'][0]['label'] = 'composition'
                    all_test.append(new_test)

    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']}
            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']}
            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
    # Score_last = sorted(Score_last, key=lambda x: (
    # x['model_box'][0], x['model_box'][0] + x['model_box'][1], -x['score']))  # 按答题卡顺序输出

    len_Score_last = len(Score_last)
    for i in range(len_Score_last):  # 去重一个边框可能对应多个type_score的情况
        if Score_last[i]['model_box'] in model_box2:
            index2 = model_box2.index(Score_last[i]['model_box'])
            score = Score_last[i]['score']
            if score < score2[index2] and score2[index2] < 30:  # 去重，type_score多余的包含小题分数
                Score_last[i] = -1
            elif score < score2[index2] and score2[index2] > 30:  # 去重，type_score多余的包含分卷分数
                Score_last[index2] = -1
            elif score > score2[index2] and score < 30:  # 去重，type_score在不大于30分的情况下，暂定保留更大的分数
                Score_last[index2] = -1
            elif score > score2[index2] and score > 30:  # 去重，type_score去除大于30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'])
    while num_redundance < len_Score_last:  # 去重一个边框可能对应多个type_score的情况
        if Score_last[num_redundance] == -1:
            del Score_last[num_redundance]
            len_Score_last = len_Score_last - 1
        else:
            num_redundance = num_redundance + 1
    # print(Score_last)
    # print(volume_last)  # 分卷信息，暂不输出
    # print(answer_sheet['regions'])

    if Score_last != []:
        for i in range(len(Score_last)):
            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

    if Score_last != []:
        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 !=[]:
                            for index, jj in enumerate(j_temp):
                                num_score_m = round(float(Score_last[i]['score'] / count_choice_m),1)
                                answer_sheet['regions'][jj]['default_points'] = len(answer_sheet['regions'][jj]['number']) * [num_score_m]
                            break

                elif Score_last[i]['label'] == 'cloze':
                    count_cloze_s = 0
                    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']
                            else:
                                count_cloze_s = count_cloze_s + 1
                                jj_temp.append(j)
                        if j == len(answer_sheet['regions']) - 1 and jj_temp !=[] and Score_last[i]['score']!=-1:
                            for index, jj in enumerate(jj_temp):
                                num_score_m = round(float(Score_last[i]['score'] / count_cloze_s),1)
                                answer_sheet['regions'][jj]['default_points'] = num_score_m
                            break

        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 !=[]:
                            for index ,jj in enumerate(j_temp):
                                num_score_m = round(float(Score_last[i]['score'] / count_choice_m),1)
                                answer_sheet['regions'][jj]['default_points'] = len(answer_sheet['regions'][jj]['number']) * [num_score_m]
                            break
                elif Score_last[i]['label'] == 'cloze':
                    count_cloze_s = 0
                    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 Score_last[i]['number_score'] == -1 and Score_last[i]['score'] != -1 :
                                count_cloze_s = count_cloze_s + 1
                                jj_temp.append(j)
                        if j == len(answer_sheet['regions']) - 1 and jj_temp !=[]:
                            for index ,jj in enumerate(jj_temp):
                                num_score_m = round(float(Score_last[i]['score'] / count_cloze_s),1)
                                answer_sheet['regions'][jj]['default_points'] = len(answer_sheet['regions'][jj]['number']) * [num_score_m]
                            break


    if Score_last != []:
        for i in range(len(answer_sheet['regions'])):
            for j in range(len(Score_last)):
                if (Score_last[j]['model_box'][0] == answer_sheet['regions'][i]['bounding_box']['xmin']
                        and Score_last[j]['model_box'][1] == answer_sheet['regions'][i]['bounding_box']['ymin']
                        and Score_last[j]['model_box'][2] == answer_sheet['regions'][i]['bounding_box']['xmax']
                        and Score_last[j]['model_box'][3] == answer_sheet['regions'][i]['bounding_box']['ymax']):
                    if Score_last[j]['number'] != -1:
                        answer_sheet['regions'][i]['number'] = Score_last[j]['number']  # 题号
                    if Score_last[j]['score'] != -1:
                        # score = Score_last[j]['score']
                        # try:
                        #     length = len(answer_sheet['regions'][i]['number'])
                        #     answer_sheet['regions'][i]['default_points'] = length * [score]
                        # except Exception:
                        #     answer_sheet['regions'][i]['default_points'] = score
                        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'
                    # answer_sheet['regions'][i]['number_score'] = Score_last[j]['number_score']  # 小题分数
                    # answer_sheet['regions'][i]['counts'] = Score_last[j]['counts']  # 小题个数
    return answer_sheet