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Merge pull request #31 from SDSRV-IDP/vietanh99-update-xlsx

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Vietanh99 update xlsx
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Đỗ Xuân Tân 2024-02-15 15:48:15 +07:00 committed by GitHub Enterprise
commit a5b7473ede
5 changed files with 49 additions and 45 deletions
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2
cope2n-ai-fi/modules/sdsvkvu

@ -1 +1 @@
Subproject commit b6d4fab46f7f8689dd6b050cfbff2faa6a6f3fec
Subproject commit 6907ea0183b141e3b4f3c21758c9123f1e9b2a27

8
cope2n-api/fwd_api/management/commands/migrate-csv.py
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@ -53,14 +53,14 @@ class Command(BaseCommand):
is_match = True
if field == 'imei_number':
if not reviewed_result == request_review:
if not reviewed_result in request_review["imei_number"]:
request_review["imei_number"].append(reviewed_result)
if not user_feedback == request_feedback:
if not user_feedback in request_feedback["imei_number"]:
request_feedback["imei_number"].append(user_feedback)
else:
if not reviewed_result == request_review:
if not reviewed_result == request_review[field]:
request_review[field] = reviewed_result
if not user_feedback == request_feedback:
if not user_feedback == request_feedback[field]:
request_feedback[field] = user_feedback
_predict_result = copy.deepcopy(predict_result_to_ready(request.predict_result))

84
cope2n-api/fwd_api/utils/file.py
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@ -443,20 +443,21 @@ def dict2xlsx(input: json, _type='report'):
mapping = {
'A': 'subs',
'B': 'extraction_date',
'C': 'num_imei',
'D': 'num_invoice',
'E': 'total_images',
'F': 'images_quality.successful',
'G': 'images_quality.successful_percent',
'H': 'images_quality.bad',
'I': 'images_quality.bad_percent',
'J': 'average_accuracy_rate.imei',
'K': 'average_accuracy_rate.purchase_date',
'L': 'average_accuracy_rate.retailer_name',
'M': 'average_processing_time.imei',
'N': 'average_processing_time.invoice',
'O': 'usage.imei',
'P': 'usage.invoice',
'C': 'usage.total_images',
'D': 'usage.imei',
'E': 'usage.invoice',
'F': 'total_images',
'G': 'num_imei',
'H': 'num_invoice',
'I': 'images_quality.successful',
'J': 'images_quality.successful_percent',
'K': 'images_quality.bad',
'L': 'images_quality.bad_percent',
'M': 'average_accuracy_rate.imei',
'N': 'average_accuracy_rate.purchase_date',
'O': 'average_accuracy_rate.retailer_name',
'P': 'average_processing_time.imei',
'Q': 'average_processing_time.invoice',
}
start_index = 5
@ -464,26 +465,27 @@ def dict2xlsx(input: json, _type='report'):
wb = load_workbook(filename = 'report_detail.xlsx')
ws = wb['Sheet1']
mapping = {
'A': 'request_id',
'B': 'redemption_number',
'C': 'image_type',
'D': 'imei_user_submitted',
'E': "imei_ocr_retrieved",
'F': "imei1_accuracy",
'G': "invoice_purchase_date_consumer",
'H': "invoice_purchase_date_ocr",
'I': "invoice_purchase_date_accuracy",
'J': "invoice_retailer_consumer",
'K': "invoice_retailer_ocr",
'L': "invoice_retailer_accuracy",
'M': "ocr_image_accuracy",
'N': "ocr_image_speed",
'O': "is_reviewed",
'P': "bad_image_reasons",
'Q': "countermeasures",
'R': 'imei_revised_accuracy',
'S': 'purchase_date_revised_accuracy',
'T': 'retailer_revised_accuracy',
'A': 'subs',
'B': 'request_id',
'C': 'redemption_number',
'D': 'image_type',
'E': 'imei_user_submitted',
'F': "imei_ocr_retrieved",
'G': "imei1_accuracy",
'H': "invoice_purchase_date_consumer",
'I': "invoice_purchase_date_ocr",
'J': "invoice_purchase_date_accuracy",
'K': "invoice_retailer_consumer",
'L': "invoice_retailer_ocr",
'M': "invoice_retailer_accuracy",
'N': "ocr_image_accuracy",
'O': "ocr_image_speed",
'P': "is_reviewed",
'Q': "bad_image_reasons",
'R': "countermeasures",
'S': 'imei_revised_accuracy',
'T': 'purchase_date_revised_accuracy',
'U': 'retailer_revised_accuracy',
}
start_index = 4
@ -497,7 +499,7 @@ def dict2xlsx(input: json, _type='report'):
if subtotal['subs'] == '+':
ws[key + str(start_index)].font = font_black_bold
if key_index in [6, 8, 9, 10, 11, 12, 13]:
ws[key + str(start_index)].number_format = numbers.FORMAT_NUMBER_00
ws[key + str(start_index)].number_format = '0.0'
if key_index == 0 or (key_index >= 9 and key_index <= 15):
ws[key + str(start_index)].fill = fill_gray
elif key_index == 1:
@ -506,25 +508,27 @@ def dict2xlsx(input: json, _type='report'):
ws[key + str(start_index)].fill = fill_yellow
else:
if 'average_accuracy_rate' in mapping[key] and type(value) in [int, float]:
if value < 95:
if value < 98:
ws[key + str(start_index)].style = normal_cell_red
ws[key + str(start_index)].number_format = numbers.FORMAT_NUMBER_00
ws[key + str(start_index)].number_format = '0.0'
elif 'average_processing_time' in mapping[key] and type(value) in [int, float]:
if value > 2.0:
ws[key + str(start_index)].style = normal_cell_red
ws[key + str(start_index)].number_format = numbers.FORMAT_NUMBER_00
ws[key + str(start_index)].number_format = '0.0'
elif 'bad_percent' in mapping[key] and type(value) in [int, float]:
if value > 10:
ws[key + str(start_index)].style = normal_cell_red
ws[key + str(start_index)].number_format = numbers.FORMAT_NUMBER_00
ws[key + str(start_index)].number_format = '0.0'
elif 'percent' in mapping[key] and type(value) in [int, float]:
ws[key + str(start_index)].number_format = numbers.FORMAT_NUMBER_00
ws[key + str(start_index)].number_format = '0.0'
else :
ws[key + str(start_index)].style = normal_cell
elif _type == 'report_detail':
if 'accuracy' in mapping[key] and type(value) in [int, float] and value < 75:
ws[key + str(start_index)].number_format = '0.0'
ws[key + str(start_index)].style = normal_cell_red
elif 'speed' in mapping[key] and type(value) in [int, float] and value > 2.0:
ws[key + str(start_index)].number_format = '0.0'
ws[key + str(start_index)].style = normal_cell_red
else:
ws[key + str(start_index)].style = normal_cell

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cope2n-api/report.xlsx
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cope2n-api/report_detail.xlsx
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