# @Author : lightXu # @File : sheet_views.py # @Time : 2018/12/19 0019 下午 14:28 import json import os import shutil import time import traceback import cv2 from django.conf import settings from django.http import HttpResponse from django.shortcuts import render from django.views.decorators.csrf import csrf_exempt import segment.logging_config as logging from segment.form import SubmitSeriesNumberForm, UploadFileForm from segment.form import UploadImageForm, UploadImageWithPaperIdForm, DownloadImage from segment.image_operation.utils import resize_by_percent, write_single_img from segment.models import SheetBigBoxes, SheetBoxes from segment.sheet_resolve.tools.tf_sess import TfSess from segment.sheet_resolve.tools.utils import read_xml_to_json, read_single_img, NpEncoder from segment.sheet_server import handle_uploaded_xml_file, generate_serial_number from segment.sheet_server import save_raw_image_without_segment, save_raw_image_with_paper_id from segment.sheet_server import sheet_big_boxes_resolve, sheet_small_boxes_resolve, gen_xml, decide_blank_sheet from segment.sheet_server import sheet_row_col_resolve, sheet_detail_resolve, sheet_format_output, sheet_points, \ sheet_anchor from segment.sheet_resolve.analysis.sheet.sheet_infer import subfield_answer_sheet from segment.sheet_resolve.tools.brain_api import get_ocr_text_and_coordinate logger = logging.getLogger(settings.LOGGING_TYPE) subject_id_dict = {0: 'unknown_subject', 3: 'math', 6: 'math_zxhx', 8: 'english', 9: 'chinese', 12: 'physics', 13: 'chemistry', 14: 'biology', 15: 'politics', 16: 'history', 17: 'geography', 18: 'science_comprehensive', 19: 'arts_comprehensive' } tf_sess_dict = { # 'choice_m': TfSess('choice_m'), # 'cloze': TfSess('cloze'), # 'math_zxhx': TfSess('math_zxhx'), # 'math_zxhx_detail': TfSess('math_zxhx_detail'), 'math': TfSess('math'), # 'english': TfSess('english'), # 'chinese': TfSess('chinese'), # 'physics': TfSess('physics'), # 'chemistry': TfSess('chemistry'), # 'biology': TfSess('biology'), # 'politics': TfSess('politics'), # 'history': TfSess('history'), # 'geography': TfSess('geography'), # 'science_comprehensive': TfSess('science_comprehensive'), # 'arts_comprehensive': TfSess('arts_comprehensive'), # 'chinese_blank': TfSess('chinese_blank'), # 'science_comprehensive_blank': TfSess('science_comprehensive_blank'), # 'arts_comprehensive_blank': TfSess('arts_comprehensive_blank'), } # Create your views here. def index(request): return render(request, 'sheet.html') @csrf_exempt def analysis_big_box(request): if request.method == 'POST': time_str = time.strftime('%Y-%m-%d', time.localtime(time.time())) form = UploadImageForm(request.POST, request.FILES) if form.is_valid(): subject_id = int(form.cleaned_data['subject']) subject = subject_id_dict.get(subject_id) if not subject: subject = 'unknown_subject' upload_img_list = request.FILES.getlist('img_data') res_info_list = [] error_info = '' is_success = 1 try: save_path = '' image = '' series_number = '' for img in upload_img_list: start_time = time.time() raw_name = img.name try: save_path, image, _ = save_raw_image_without_segment(subject, time_str, img, subject) series_number = generate_serial_number(time_str.replace('-', ''), SheetBigBoxes) img_instance = SheetBigBoxes(series_number=series_number, raw_name=raw_name, save_path=save_path, subject_id=subject_id, subject=subject) img_instance.save() logger.info('{}试卷： {} 存储成功: {}'.format(subject, raw_name, save_path)) except Exception as e: traceback.print_exc() logger.info('{}试卷： {} 存储失败: {}'.format(subject, raw_name, e)) sheet_sess = tf_sess_dict[subject] status, bbox_info, raw_xml_path = sheet_big_boxes_resolve(series_number, image, save_path, subject, sheet_sess) bbox_info['series_number'] = series_number bbox_info["img_name"] = raw_name SheetBigBoxes.objects.filter(series_number=series_number).update(raw_big_box_path=raw_xml_path) is_success = status end_time = time.time() cost_time = '{:.2f}s'.format(float(end_time - start_time)) bbox_info.update({'cost_time': cost_time}) ocr_res = get_ocr_text_and_coordinate(image) bbox_info.update({'ocr': ocr_res}) res_info_list.append(bbox_info) except Exception as e: traceback.print_exc() logger.info('big box resolve error: ', e) is_success = 0 error_info = 'big box resolve error' res = {'is_success': is_success, 'imgs_info': res_info_list} if error_info: res['error'] = error_info res_json = json.dumps(res, ensure_ascii=False, cls=NpEncoder) logger.info('segment_info: {}\n'.format(res_json)) return HttpResponse(res_json) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form_img = UploadImageForm() form_xml = UploadFileForm() return render(request, 'sheet.html', {'form_img': form_img, 'form_xml': form_xml}) @csrf_exempt def analysis_small_box(request): if request.method == 'POST': form = UploadFileForm(request.POST, request.FILES) if form.is_valid(): upload_xml_list = request.FILES.getlist('xml_file') res_info_list = [] error_info = '' is_success = 1 try: for xml in upload_xml_list: raw_name = xml.name reviewed_xml_save_path = os.path.join(settings.XML_ROOT, raw_name.replace('.xml', '_review.xml')) handle_uploaded_xml_file(xml, reviewed_xml_save_path) sheet_dict = read_xml_to_json(reviewed_xml_save_path) start_time = time.time() series_number = sheet_dict['series_number'] raw_image_path = SheetBigBoxes.objects.get(series_number=series_number).save_path final_xml_path = raw_image_path.replace('.jpg', '.xml') shutil.move(reviewed_xml_save_path, final_xml_path) raw_img = read_single_img(raw_image_path) small_box_sheet_dict = sheet_small_boxes_resolve(raw_img, sheet_dict, tf_sess_dict['choice'], tf_sess_dict['cloze'], final_xml_path) is_success = 1 end_time = time.time() cost_time = '{:.2f}s'.format(float(end_time - start_time)) small_box_sheet_dict.update({'cost_time': cost_time}) res_info_list.append(small_box_sheet_dict) except Exception as e: logger.info('small box resolve error: {}'.format(e)) is_success = 0 error_info = 'small box resolve error' res = {'is_success': is_success, 'imgs_info': res_info_list} if error_info: res['error'] = error_info res_json = json.dumps(res, ensure_ascii=False, cls=NpEncoder) # logger.info('resolve: {}\n'.format(res_json)) return HttpResponse(res_json) else: error_json = form.errors.as_json() is_sucecss = 99 res = {'is_success': is_sucecss, 'error': error_json} return HttpResponse('{}'.format(res)) else: form_img = UploadImageForm() form_xml = UploadFileForm() return render(request, 'sheet.html', {'form_img': form_img, 'form_xml': form_xml}) @csrf_exempt def upload_exam(request): if request.method == 'POST': time_str = time.strftime('%Y-%m-%d', time.localtime(time.time())) form = UploadImageForm(request.POST, request.FILES) if form.is_valid(): subject_id = int(form.cleaned_data['subject']) subject = subject_id_dict.get(subject_id) if not subject: subject = 'unknown_subject' upload_img_list = request.FILES.getlist('img_data') res_info_list = [] error_info = '' is_success = 1 for img in upload_img_list: raw_name = img.name try: save_path, image, _ = save_raw_image_without_segment(subject, time_str, img, 'sheet') series_number = generate_serial_number(time_str.replace('-', ''), SheetBigBoxes) img_instance = SheetBigBoxes(series_number=series_number, raw_name=raw_name, save_path=save_path, subject_id=subject_id, subject=subject) img_instance.save() res_info_list.append({'raw_name': raw_name, 'series_number': series_number, raw_name: series_number}) logger.info('{}试卷： {} 存储成功: {}'.format(subject, raw_name, save_path)) except Exception as e: # traceback.print_exc() logger.info('{}试卷： {} 存储失败: {}'.format(subject, raw_name, e)) res = {'is_success': is_success, 'imgs_info': res_info_list} if error_info: res['error'] = error_info res_json = json.dumps(res, ensure_ascii=False, cls=NpEncoder) return HttpResponse(res_json) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form_img = UploadImageForm() form_xml = UploadFileForm() return render(request, 'sheet.html', {'form_img': form_img, 'form_xml': form_xml}) @csrf_exempt def analysis_box(request): if request.method == 'POST': form = SubmitSeriesNumberForm(request.POST) if form.is_valid(): series_number = form.cleaned_data['series_number'] small_box_path = SheetBigBoxes.objects.get(series_number=series_number).small_box_path if not small_box_path: res = {'series_number': series_number, 'info': '尚未处理完成', 'status': 100} return HttpResponse('{}'.format(res)) else: res = json.load(small_box_path.replace('.xml', '.json')) res['series_number'] = series_number res['status'] = 1000 return HttpResponse('{}'.format(res)) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form_img = UploadImageForm() form_xml = UploadFileForm() return render(request, 'sheet.html', {'form_img': form_img, 'form_xml': form_xml}) @csrf_exempt def analysis_box_once(request): if request.method == 'POST': time_str = time.strftime('%Y-%m-%d', time.localtime(time.time())) form = UploadImageForm(request.POST, request.FILES) if form.is_valid(): subject_id = int(form.cleaned_data['subject']) subject = subject_id_dict.get(subject_id) if not subject: subject = 'math' # default upload_img_list = request.FILES.getlist('img_data') res_info_list = [] error_info = '' is_success = 1 try: save_path = '' image = '' series_number = '' for img in upload_img_list: start_time = time.time() raw_name = img.name try: save_path, image, _ = save_raw_image_without_segment(subject, time_str, img, 'sheet') series_number = generate_serial_number(time_str.replace('-', ''), SheetBigBoxes) img_instance = SheetBigBoxes(series_number=series_number, raw_name=raw_name, save_path=save_path, subject_id=subject_id, subject=subject) img_instance.save() logger.info('{}试卷： {} 存储成功: {}'.format(subject, raw_name, save_path)) except Exception as e: # traceback.print_exc() logger.info('{}试卷： {} 存储失败: {}'.format(subject, raw_name, e)) status, bbox_info, raw_xml_path = sheet_big_boxes_resolve(series_number, image, save_path, 'sheet', tf_sess_dict['math_zxhx']) bbox_info['series_number'] = series_number bbox_info["img_name"] = raw_name SheetBigBoxes.objects.filter(series_number=series_number).update(raw_big_box_path=raw_xml_path) small_box_xml_path = raw_xml_path.replace('.xml', '_small.xml') shutil.copy(raw_xml_path, small_box_xml_path) sheet_dict = bbox_info small_box_sheet_dict = sheet_small_boxes_resolve(image, sheet_dict, tf_sess_dict['choice'], tf_sess_dict['cloze'], small_box_xml_path) SheetBigBoxes.objects.filter(series_number=series_number).update(small_box_path=small_box_xml_path) is_success = status end_time = time.time() cost_time = '{:.2f}s'.format(float(end_time - start_time)) small_box_sheet_dict.update({'cost_time': cost_time}) res_info_list.append(small_box_sheet_dict) except Exception as e: logger.info('box resolve error: {}'.format(e)) is_success = 0 error_info = 'box resolve error' res = {'is_success': is_success, 'imgs_info': res_info_list} if error_info: res['error'] = error_info res_json = json.dumps(res, ensure_ascii=False, cls=NpEncoder) # logger.info('segment_info: {}\n'.format(res_json)) return HttpResponse(res_json) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form_img = UploadImageForm() form_xml = UploadFileForm() return render(request, 'sheet.html', {'form_img': form_img, 'form_xml': form_xml}) @csrf_exempt def analysis_box_once_with_multiple_img(request): if request.method == 'POST': time_str = time.strftime('%Y-%m-%d', time.localtime(time.time())) form = UploadImageForm(request.POST, request.FILES) if form.is_valid(): subject_id = int(form.cleaned_data['subject']) subject_init = subject_id_dict.get(subject_id) if not subject_init: subject_init = 'math' upload_img_list = request.FILES.getlist('img_data') res_info_list = [] image_list = [] detail_xml = [] ocr_list = [] error_info = '' is_success = 1 save_path = '' image = '' series_number = '' for img_index, img in enumerate(upload_img_list): subject = subject_init start_time = time.time() raw_name = img.name try: save_path, image, _ = save_raw_image_without_segment(subject, time_str, img, 'sheet') series_number = generate_serial_number(time_str.replace('-', ''), SheetBigBoxes) img_instance = SheetBigBoxes(series_number=series_number, raw_name=raw_name, save_path=save_path, subject_id=subject_id, subject=subject) img_instance.save() logger.info('{}试卷： {} 存储成功: {}'.format(subject, raw_name, save_path)) except Exception as e: traceback.print_exc() logger.info('{}试卷： {} 存储失败: {}'.format(subject, raw_name, e)) try: try: ocr_res = get_ocr_text_and_coordinate(image) except Exception as e: traceback.print_exc() error_info = error_info + 'ocr error;' ocr_res = '' ocr_list.append(ocr_res) if subject not in ["chinese", "science_comprehensive", "arts_comprehensive"]: sheet_sess = tf_sess_dict[subject] answered = "fixed" elif decide_blank_sheet(image): sheet_sess = tf_sess_dict[subject + '_blank'] subject = subject + '_blank' answered = "blank" else: sheet_sess = tf_sess_dict[subject] answered = "answered" status, sheet_dict, raw_xml_path = sheet_big_boxes_resolve(series_number, image, save_path, subject, sheet_sess, ocr=ocr_res) # print(sheet_dict) sheet_dict['series_number'] = series_number sheet_dict["img_name"] = raw_name sheet_dict["answered"] = answered SheetBigBoxes.objects.filter(series_number=series_number).update(raw_big_box_path=raw_xml_path) small_box_xml_path = raw_xml_path.replace('.xml', '_small.xml') detail_xml.append(small_box_xml_path) shutil.copy(raw_xml_path, small_box_xml_path) try: # 找题号 small_box_sheet_dict = sheet_detail_resolve(image, sheet_dict, small_box_xml_path, shrink=True) except Exception as e: traceback.print_exc() status = 0 small_box_sheet_dict = sheet_dict SheetBigBoxes.objects.filter(series_number=series_number).update(small_box_path=small_box_xml_path) is_success = status end_time = time.time() cost_time = '{:.2f}s'.format(float(end_time - start_time)) small_box_sheet_dict.update({'cost_time': cost_time}) res_info_list.append(small_box_sheet_dict) image_list.append(image) except Exception as e: traceback.print_exc() logger.info('{}试卷： {} 解析失败: {}'.format(subject, raw_name, e)) is_success = 0 error_info = error_info + 'box resolve error;' try: res_info_list = sheet_points(res_info_list, image_list, ocr_list, if_ocr=False) except Exception as e: print(e) traceback.print_exc() error_info = error_info + 'number and points error;' try: logger.info('before format: {}\n'.format(res_info_list)) init_number = 500 crt_numbers = [] for i, ele in enumerate(res_info_list): image = image_list[i] res, init_number, crt_numbers = sheet_format_output(init_number, crt_numbers, ele, image, subject_init, shrink=True) res_info_list[i] = res except Exception as e: print(e) traceback.print_exc() error_info = error_info + 'format output error ;' try: for image_index, image in enumerate(image_list): anchor_list = sheet_anchor(image) res_info_list[image_index]['regions'] = res_info_list[image_index]['regions'] + anchor_list except Exception as e: print(e) traceback.print_exc() error_info = error_info + 'anchor error;' res = {'is_success': is_success, 'imgs_info': res_info_list} try: for xml_index, ele in enumerate(res_info_list): regions = ele['regions'] gen_xml(regions, detail_xml[xml_index]) except Exception as e: print(e) traceback.print_exc() if error_info: res['error'] = error_info res_json = json.dumps(res, ensure_ascii=False, cls=NpEncoder) logger.info('segment_info: {}\n'.format(res_json)) print('sheet resolve done') return HttpResponse(res_json) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form_img = UploadImageForm() form_xml = UploadFileForm() return render(request, 'sheet.html', {'form_img': form_img, 'form_xml': form_xml}) @csrf_exempt def saas_analysis_box_once_with_multiple_img(request): if request.method == 'POST': time_str = time.strftime('%Y-%m-%d', time.localtime(time.time())) form = UploadImageForm(request.POST, request.FILES) if form.is_valid(): subject_id = int(form.cleaned_data['subject']) subject = subject_id_dict.get(subject_id) if not subject: subject = 'unknown_subject' upload_img_list = request.FILES.getlist('img_data') res_info_list = [] image_list = [] detail_xml = [] ocr_list = [] error_info = '' is_success = 1 save_path = '' image = '' series_number = '' for img_index, img in enumerate(upload_img_list): start_time = time.time() raw_name = img.name try: save_path, image, _ = save_raw_image_without_segment(subject, time_str, img, 'sheet') series_number = generate_serial_number(time_str.replace('-', ''), SheetBigBoxes) img_instance = SheetBigBoxes(series_number=series_number, raw_name=raw_name, save_path=save_path, subject_id=subject_id, subject=subject) img_instance.save() logger.info('{}试卷： {} 存储成功: {}'.format(subject, raw_name, save_path)) except Exception as e: # traceback.print_exc() logger.info('{}试卷： {} 存储失败: {}'.format(subject, raw_name, e)) try: status, sheet_dict, raw_xml_path = sheet_big_boxes_resolve(series_number, image, save_path, subject, tf_sess_dict[subject]) sheet_dict['series_number'] = series_number sheet_dict["img_name"] = raw_name SheetBigBoxes.objects.filter(series_number=series_number).update(raw_big_box_path=raw_xml_path) small_box_xml_path = raw_xml_path.replace('.xml', '_small.xml') detail_xml.append(small_box_xml_path) shutil.copy(raw_xml_path, small_box_xml_path) small_box_sheet_dict = sheet_detail_resolve(image, sheet_dict, small_box_xml_path, shrink=False) SheetBigBoxes.objects.filter(series_number=series_number) \ .update(small_box_path=small_box_xml_path) is_success = status end_time = time.time() cost_time = '{:.2f}s'.format(float(end_time - start_time)) small_box_sheet_dict.update({'cost_time': cost_time}) res_info_list.append(small_box_sheet_dict) image_list.append(image) ocr_res = get_ocr_text_and_coordinate(image) ocr_list.append(ocr_res) except Exception as e: logger.info('{}试卷： {} 存储失败: {}'.format(subject, raw_name, e)) is_success = 0 error_info = error_info + 'box resolve error;' try: res_info_list = sheet_points(res_info_list, image_list, ocr_list, if_ocr=True) except Exception as e: print(e) traceback.print_exc() is_success = 0 error_info = error_info + 'number and points error;' res_info_list = [ele.update({'ocr': ocr_list[i]}) for i, ele in enumerate(res_info_list)] for i, ele in enumerate(res_info_list): image = image_list[i] res = sheet_format_output(ele, image, subject, shrink=True) res_info_list[i] = res res = {'is_success': is_success, 'imgs_info': res_info_list} for xml_index, ele in enumerate(res_info_list): regions = ele['regions'] gen_xml(regions, detail_xml[xml_index]) if error_info: res['error'] = error_info res_json = json.dumps(res, ensure_ascii=False, cls=NpEncoder) # logger.info('segment_info: {}\n'.format(res_json)) print('sheet resolve done') return HttpResponse(res_json) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form_img = UploadImageForm() form_xml = UploadFileForm() return render(request, 'sheet_detail.html', {'form_img': form_img, 'form_xml': form_xml}) @csrf_exempt def analysis_box_once_and_single_img(request): if request.method == 'POST': time_str = time.strftime('%Y-%m-%d', time.localtime(time.time())) form = UploadImageForm(request.POST, request.FILES) if form.is_valid(): subject_id = int(form.cleaned_data['subject']) subject = subject_id_dict.get(subject_id) if not subject: subject = 'unknown_subject' upload_img = request.FILES.get('img_data') error_info = '' detail_box_sheet_dict = dict() try: save_path = '' image = '' series_number = '' start_time = time.time() raw_name = upload_img.name try: save_path, image, _ = save_raw_image_without_segment(subject, time_str, upload_img, 'sheet') series_number = generate_serial_number(time_str.replace('-', ''), SheetBigBoxes) img_instance = SheetBigBoxes(series_number=series_number, raw_name=raw_name, save_path=save_path, subject_id=subject_id, subject=subject) img_instance.save() logger.info('{}试卷： {} 存储成功: {}'.format(subject, raw_name, save_path)) except Exception as e: # traceback.print_exc() logger.info('{}试卷： {} 存储失败: {}'.format(subject, raw_name, e)) status, bbox_info, raw_xml_path = sheet_big_boxes_resolve(series_number, image, save_path, subject, tf_sess_dict[subject]) bbox_info['series_number'] = series_number bbox_info["img_name"] = raw_name SheetBigBoxes.objects.filter(series_number=series_number).update(raw_big_box_path=raw_xml_path) detail_box_xml_path = raw_xml_path.replace('.xml', '_detail.xml') shutil.copy(raw_xml_path, detail_box_xml_path) sheet_dict = bbox_info # small_box_sheet_dict = sheet_row_col_resolve(image, sheet_dict, # tf_sess_dict['choice_m'], tf_sess_dict['cloze'], # small_box_xml_path) detail_box_sheet_dict = sheet_row_col_resolve(image, sheet_dict, '', tf_sess_dict['cloze'], detail_box_xml_path) SheetBigBoxes.objects.filter(series_number=series_number).update(small_box_path=detail_box_xml_path) is_success = status # end_time = time.time() # cost_time = '{:.2f}s'.format(float(end_time - start_time)) # small_box_sheet_dict.update({'cost_time': cost_time}) except Exception as e: logger.info('box resolve error: {}'.format(e)) is_success = 0 error_info = 'box resolve error' detail_box_sheet_dict.update({'is_success': is_success}) if error_info: detail_box_sheet_dict.update({'is_success': is_success, 'error': error_info}) res_json = json.dumps(detail_box_sheet_dict, ensure_ascii=False) # logger.info('segment_info: {}\n'.format(res_json)) return HttpResponse(res_json) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form_img = UploadImageForm() form_xml = UploadFileForm() return render(request, 'sheet_detail.html', {'form_img': form_img, 'form_xml': form_xml}) @csrf_exempt def analysis_box_once_and_single_img_with_paperid(request): if request.method == 'POST': form = UploadImageWithPaperIdForm(request.POST, request.FILES) if form.is_valid(): subject_id = int(form.cleaned_data['subject']) subject = subject_id_dict.get(subject_id) if not subject: subject = 'unknown_subject' upload_img = request.FILES.get('img_data') paper_id = form.cleaned_data['paper_id'] error_info = '' small_box_sheet_dict = dict() try: save_path = '' image = '' start_time = time.time() raw_name = upload_img.name try: save_path, image, image_url = save_raw_image_with_paper_id(subject, paper_id, upload_img, 'sheet') # series_number = generate_serial_number(time_str.replace('-', ''), SheetBoxes) img_instance = SheetBoxes(paper_id=paper_id, raw_name=raw_name, save_path=save_path, subject_id=subject_id, subject=subject, download_path=image_url) img_instance.save() logger.info('{}试卷： {} 存储成功: {}'.format(subject, raw_name, save_path)) except Exception as e: # traceback.print_exc() logger.info('{}试卷： {} 存储失败: {}'.format(subject, raw_name, e)) sheet_sess = tf_sess_dict[subject] status, sheet_dict, raw_xml_path = sheet_big_boxes_resolve(paper_id, image, save_path, subject, sheet_sess) sheet_dict['series_number'] = paper_id sheet_dict["img_name"] = raw_name # small_box_sheet_dict = sheet_small_boxes_resolve(image, sheet_dict, # tf_sess_dict['choice'], tf_sess_dict['cloze'], # raw_xml_path) small_box_xml_path = raw_xml_path.replace('.xml', '_small.xml') shutil.copy(raw_xml_path, small_box_xml_path) small_box_sheet_dict = sheet_row_col_resolve(image, sheet_dict, '', tf_sess_dict['cloze'], small_box_xml_path) SheetBoxes.objects.filter(paper_id=paper_id).update(xml_box_path=small_box_xml_path) is_success = status end_time = time.time() cost_time = '{:.2f}s'.format(float(end_time - start_time)) small_box_sheet_dict.update({'cost_time': cost_time}) except Exception as e: logger.info('box resolve error: {}'.format(e)) is_success = 0 error_info = 'box resolve error' small_box_sheet_dict.update({'is_success': is_success}) if error_info: small_box_sheet_dict.update({'is_success': is_success, 'error': error_info}) res_json = json.dumps(small_box_sheet_dict, ensure_ascii=False) # logger.info('segment_info: {}\n'.format(res_json)) return HttpResponse(res_json) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form = UploadImageWithPaperIdForm() return render(request, 'sheet_with_id.html', {'form': form}) @csrf_exempt def analysis_box_detail(request): if request.method == 'POST': time_str = time.strftime('%Y-%m-%d', time.localtime(time.time())) form = UploadImageForm(request.POST, request.FILES) if form.is_valid(): subject_id = int(form.cleaned_data['subject']) subject = subject_id_dict.get(subject_id) if not subject: subject = 'unknown_subject' upload_img = request.FILES.get('img_data') error_info = '' sheet_dict = dict() try: save_path = '' image = '' series_number = '' raw_name = upload_img.name try: save_path, image, _ = save_raw_image_without_segment(subject, time_str, upload_img, 'sheet') # 保存文件 series_number = generate_serial_number(time_str.replace('-', ''), SheetBigBoxes) img_instance = SheetBigBoxes(series_number=series_number, raw_name=raw_name, save_path=save_path, subject_id=subject_id, subject=subject) img_instance.save() logger.info('{}试卷： {} 存储成功: {}'.format(subject, raw_name, save_path)) except Exception as e: # traceback.print_exc() logger.info('{}试卷： {} 存储失败: {}'.format(subject, raw_name, e)) sheet_sess = tf_sess_dict[subject] status, bbox_info, raw_xml_path = sheet_big_boxes_resolve(series_number, image, save_path, subject, sheet_sess) bbox_info['series_number'] = series_number bbox_info["img_name"] = raw_name SheetBigBoxes.objects.filter(series_number=series_number).update(raw_big_box_path=raw_xml_path) # small_box_xml_path = raw_xml_path.replace('.xml', '_small.xml') # shutil.copy(raw_xml_path, small_box_xml_path) sheet_dict = bbox_info is_success = status except Exception as e: logger.info('box resolve error: {}'.format(e)) is_success = 0 error_info = 'box resolve error' sheet_dict.update({'is_success': is_success}) if error_info: sheet_dict.update({'is_success': is_success, 'error': error_info}) res_json = json.dumps(sheet_dict, ensure_ascii=False) # logger.info('segment_info: {}\n'.format(res_json)) return HttpResponse(res_json) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form_img = UploadImageForm() form_xml = UploadFileForm() return render(request, 'sheet_detail.html', {'form_img': form_img, 'form_xml': form_xml}) @csrf_exempt def analysis_box_detail_and_show(request): if request.method == 'POST': time_str = time.strftime('%Y-%m-%d', time.localtime(time.time())) form = UploadImageForm(request.POST, request.FILES) if form.is_valid(): subject_id = int(form.cleaned_data['subject']) subject = subject_id_dict.get(subject_id) if not subject: subject = 'unknown_subject' upload_img = request.FILES.get('img_data') error_info = '' img_url_path = '' sheet_dict = dict() height, width = 1200, 1600 try: save_path = '' image = '' series_number = '' raw_name = upload_img.name try: save_path, image, img_url_path = save_raw_image_without_segment(subject, time_str, upload_img, 'sheet') # small_img_path = save_path.replace('.jpg', '_small.jpg').replace('\\', '/') series_number = generate_serial_number(time_str.replace('-', ''), SheetBigBoxes) img_instance = SheetBigBoxes(series_number=series_number, raw_name=raw_name, save_path=save_path, subject_id=subject_id, subject=subject) img_instance.save() logger.info('{}试卷： {} 存储成功: {}'.format(subject, raw_name, save_path)) except Exception as e: # traceback.print_exc() logger.info('{}试卷： {} 存储失败: {}'.format(subject, raw_name, e)) sheet_sess = tf_sess_dict[subject] status, bbox_info, raw_xml_path = sheet_big_boxes_resolve(series_number, image, save_path, subject, sheet_sess) bbox_info['series_number'] = series_number bbox_info["img_name"] = raw_name SheetBigBoxes.objects.filter(series_number=series_number).update(raw_big_box_path=raw_xml_path) # small_box_xml_path = raw_xml_path.replace('.xml', '_small.xml') # shutil.copy(raw_xml_path, small_box_xml_path) sheet_dict = bbox_info is_success = status show_ratio = 0.4 img_small = resize_by_percent(image, show_ratio) font = cv2.FONT_HERSHEY_COMPLEX for ele in bbox_info['regions']: name = ele['class_name'] xmin = int(int(ele['bounding_box']['xmin']) * show_ratio) ymin = int(int(ele['bounding_box']['ymin']) * show_ratio) xmax = int(int(ele['bounding_box']['xmax']) * show_ratio) ymax = int(int(ele['bounding_box']['ymax']) * show_ratio) cv2.rectangle(img_small, (int(xmin), int(ymin)), (int(xmax), int(ymax)), (0, 255, 0), 1) cv2.putText(img_small, name, (xmin, ymax), font, 0.7, (255, 106, 106), 2, False) height, width = img_small.shape[0], img_small.shape[1] line_xmax1, line_xmax2 = subfield_answer_sheet(image, bbox_info) if line_xmax1 != 0 and line_xmax2 != 0: line_xmax1_1 = int(line_xmax1 * show_ratio) line_xmax2_1 = int(line_xmax2 * show_ratio) cv2.rectangle(img_small, (20, 20), (line_xmax1_1, height - 20), (0, 0, 255), 1) cv2.putText(img_small, 'subfield_line', (20, height - 20), font, 0.7, (0, 0, 255), 2, False) cv2.rectangle(img_small, (line_xmax1_1, 20), (line_xmax2_1, height - 20), (0, 0, 255), 1) cv2.putText(img_small, 'subfield_line', (line_xmax1_1, height - 20), font, 0.7, (0, 0, 255), 2, False) cv2.rectangle(img_small, (line_xmax2_1, 20), (width - 20, height - 20), (0, 0, 255), 1) cv2.putText(img_small, 'subfield_line', (line_xmax2_1, height - 20), font, 0.7, (0, 0, 255), 2, False) elif line_xmax1 != 0 and line_xmax2 == 0: if int(line_xmax1 * show_ratio) == width: line_xmax1_1 = int(line_xmax1 * show_ratio) cv2.rectangle(img_small, (20, 20), (line_xmax1_1 - 20, height - 20), (0, 0, 255), 1) cv2.putText(img_small, 'subfield_line', (20, height - 20), font, 0.7, (0, 0, 255), 2, False) else: line_xmax1_1 = int(line_xmax1 * show_ratio) cv2.rectangle(img_small, (20, 20), (line_xmax1_1, height - 20), (0, 0, 255), 1) cv2.putText(img_small, 'subfield_line', (20, height - 20), font, 0.7, (0, 0, 255), 2, False) cv2.rectangle(img_small, (line_xmax1_1, 20), (width - 20, height - 20), (0, 0, 255), 1) cv2.putText(img_small, 'subfield_line', (line_xmax1_1, height - 20), font, 0.7, (0, 0, 255), 2, False) write_single_img(img_small, save_path) height, width = img_small.shape[0], img_small.shape[1] except Exception as e: logger.info('box resolve error: {}'.format(e)) is_success = 0 error_info = 'box resolve error' sheet_dict.update({'is_success': is_success}) if error_info: sheet_dict.update({'is_success': is_success, 'error': error_info}) res_json = json.dumps(sheet_dict, ensure_ascii=False) # logger.info('segment_info: {}\n'.format(res_json)) res_dict = {'url': img_url_path, 'img_height': height, 'text_height': 0.9 * height, 'texts': res_json, 'raw_texts': '' } return render(request, 'showimg.html', res_dict) # return HttpResponse(res_json) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form_img = UploadImageForm() form_xml = UploadFileForm() return render(request, 'sheet_detail.html', {'form_img': form_img, 'form_xml': form_xml}) @csrf_exempt def download_image(request): if request.method == 'POST': form = DownloadImage(request.POST, request.FILES) if form.is_valid(): is_success = 1 try: paper_id = form.cleaned_data['paper_id'] # download_path = SheetBoxes.objects.get(paper_id=paper_id).download_path paper_id_obj = SheetBoxes.objects.filter(paper_id__icontains=paper_id) paper_id_list = [ele.paper_id for ele in paper_id_obj] download_path_list = [SheetBoxes.objects.get(paper_id=ele).download_path for ele in paper_id_list] res_dict = {'paper_id': paper_id_list, 'image_url': download_path_list, # 'img_height': 1000, # 'text_height': 10, # 'texts': download_path, # 'raw_texts': '', 'is_success': is_success } except Exception as e: logger.info('image address load failed: {}'.format(e)) is_success = 0 error_info = 'image address load failed' res_dict = {'is_success': is_success, 'error': error_info} res_json = json.dumps(res_dict, ensure_ascii=False) # return render(request, 'showimg.html', res_dict) return HttpResponse(res_json) else: error_json = form.errors.as_json() is_success = 99 res = {'is_success': is_success, 'error': error_json} return HttpResponse('{}'.format(res)) else: form = DownloadImage() return render(request, 'downloadimg.html', {'form': form})