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Fix - Inprogress: #79 Create Place holder for invoice no

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dx-tan 2024-03-12 15:52:49 +07:00
parent 826a6c6ad9
commit 3ddb7a6f4d
2 changed files with 41 additions and 60 deletions
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1
cope2n-api/fwd/settings.py
View File

@ -241,6 +241,7 @@ BAD_THRESHOLD = 0.75
NEED_REVIEW = 1.0 NEED_REVIEW = 1.0
SUB_FOR_BILLING = ["all", "seao"] SUB_FOR_BILLING = ["all", "seao"]
FIELD = ["imei_number", "purchase_date", "retailername", "sold_to_party", "invoice_no"]
CACHES = { CACHES = {
'default': { 'default': {

92
cope2n-api/fwd_api/utils/accuracy.py
View File

@ -41,7 +41,8 @@ class ReportAccumulateByRequest:
'imei': IterAvg(), 'imei': IterAvg(),
'purchase_date': IterAvg(), 'purchase_date': IterAvg(),
'retailer_name': IterAvg(), 'retailer_name': IterAvg(),
'sold_to_party': IterAvg() 'sold_to_party': IterAvg(),
'invoice_no': IterAvg(),
}, },
'average_processing_time': { 'average_processing_time': {
'imei': IterAvg(), 'imei': IterAvg(),
@ -57,13 +58,15 @@ class ReportAccumulateByRequest:
'imei_number': IterAvg(), 'imei_number': IterAvg(),
'purchase_date': IterAvg(), 'purchase_date': IterAvg(),
'retailername': IterAvg(), 'retailername': IterAvg(),
'sold_to_party': IterAvg() 'sold_to_party': IterAvg(),
'invoice_no': IterAvg()
}, },
'reviewed_accuracy': { 'reviewed_accuracy': {
'imei_number': IterAvg(), 'imei_number': IterAvg(),
'purchase_date': IterAvg(), 'purchase_date': IterAvg(),
'retailername': IterAvg(), 'retailername': IterAvg(),
'sold_to_party': IterAvg() 'sold_to_party': IterAvg(),
'invoice_no': IterAvg()
}, },
'num_request': 0, 'num_request': 0,
"review_progress": [] "review_progress": []
@ -81,10 +84,11 @@ class ReportAccumulateByRequest:
'bad_percent': 0 'bad_percent': 0
}, },
'average_accuracy_rate': { 'average_accuracy_rate': {
'imei': IterAvg(), 'imei_number': IterAvg(),
'purchase_date': IterAvg(), 'purchase_date': IterAvg(),
'retailer_name': IterAvg(), 'retailer_name': IterAvg(),
'sold_to_party': IterAvg() 'sold_to_party': IterAvg(),
'invoice_no': IterAvg()
}, },
'average_processing_time': { 'average_processing_time': {
'imei': IterAvg(), 'imei': IterAvg(),
@ -100,13 +104,15 @@ class ReportAccumulateByRequest:
'imei_number': IterAvg(), 'imei_number': IterAvg(),
'purchase_date': IterAvg(), 'purchase_date': IterAvg(),
'retailername': IterAvg(), 'retailername': IterAvg(),
'sold_to_party': IterAvg() 'sold_to_party': IterAvg(),
'invoice_no': IterAvg()
}, },
'reviewed_accuracy': { 'reviewed_accuracy': {
'imei_number': IterAvg(), 'imei_number': IterAvg(),
'purchase_date': IterAvg(), 'purchase_date': IterAvg(),
'retailername': IterAvg(), 'retailername': IterAvg(),
'sold_to_party': IterAvg() 'sold_to_party': IterAvg(),
'invoice_no': IterAvg()
}, },
"report_files": [], "report_files": [],
"num_request": 0, "num_request": 0,
@ -127,20 +133,12 @@ class ReportAccumulateByRequest:
total["num_imei"] += 1 if doc_type == "imei" else 0 total["num_imei"] += 1 if doc_type == "imei" else 0
total["num_invoice"] += 1 if doc_type == "invoice" else 0 total["num_invoice"] += 1 if doc_type == "invoice" else 0
for key in settings.FIELD:
if sum([len(report_file.reviewed_accuracy[x]) for x in report_file.reviewed_accuracy.keys() if "_count" not in x]) > 0 : if sum([len(report_file.reviewed_accuracy[x]) for x in report_file.reviewed_accuracy.keys() if "_count" not in x]) > 0 :
total["average_accuracy_rate"]["imei"].add(report_file.reviewed_accuracy.get("imei_number", [])) total["average_accuracy_rate"][key].add(report_file.reviewed_accuracy.get(key, []))
total["average_accuracy_rate"]["purchase_date"].add(report_file.reviewed_accuracy.get("purchase_date", []))
total["average_accuracy_rate"]["retailer_name"].add(report_file.reviewed_accuracy.get("retailername", []))
total["average_accuracy_rate"]["sold_to_party"].add(report_file.reviewed_accuracy.get("sold_to_party", []))
elif sum([len(report_file.feedback_accuracy[x]) for x in report_file.feedback_accuracy.keys() if "_count" not in x]) > 0: elif sum([len(report_file.feedback_accuracy[x]) for x in report_file.feedback_accuracy.keys() if "_count" not in x]) > 0:
total["average_accuracy_rate"]["imei"].add(report_file.feedback_accuracy.get("imei_number", [])) total["average_accuracy_rate"][key].add(report_file.feedback_accuracy.get(key, []))
total["average_accuracy_rate"]["purchase_date"].add(report_file.feedback_accuracy.get("purchase_date", []))
total["average_accuracy_rate"]["retailer_name"].add(report_file.feedback_accuracy.get("retailername", []))
total["average_accuracy_rate"]["sold_to_party"].add(report_file.feedback_accuracy.get("sold_to_party", []))
for key in ["imei_number", "purchase_date", "retailername", "sold_to_party"]:
total["feedback_accuracy"][key].add(report_file.feedback_accuracy.get(key, [])) total["feedback_accuracy"][key].add(report_file.feedback_accuracy.get(key, []))
for key in ["imei_number", "purchase_date", "retailername", "sold_to_party"]:
total["reviewed_accuracy"][key].add(report_file.reviewed_accuracy.get(key, [])) total["reviewed_accuracy"][key].add(report_file.reviewed_accuracy.get(key, []))
if not total["average_processing_time"].get(report_file.doc_type, None): if not total["average_processing_time"].get(report_file.doc_type, None):
@ -174,20 +172,12 @@ class ReportAccumulateByRequest:
day_data["num_invoice"] += 1 if doc_type == "invoice" else 0 day_data["num_invoice"] += 1 if doc_type == "invoice" else 0
day_data["report_files"].append(report_file) day_data["report_files"].append(report_file)
for key in settings.FIELD:
if sum([len(report_file.reviewed_accuracy[x]) for x in report_file.reviewed_accuracy.keys() if "_count" not in x]) > 0: if sum([len(report_file.reviewed_accuracy[x]) for x in report_file.reviewed_accuracy.keys() if "_count" not in x]) > 0:
day_data["average_accuracy_rate"]["imei"].add(report_file.reviewed_accuracy.get("imei_number", [])) day_data["average_accuracy_rate"][key].add(report_file.reviewed_accuracy.get(key, []))
day_data["average_accuracy_rate"]["purchase_date"].add(report_file.reviewed_accuracy.get("purchase_date", []))
day_data["average_accuracy_rate"]["retailer_name"].add(report_file.reviewed_accuracy.get("retailername", []))
day_data["average_accuracy_rate"]["sold_to_party"].add(report_file.reviewed_accuracy.get("sold_to_party", []))
elif sum([len(report_file.feedback_accuracy[x]) for x in report_file.feedback_accuracy.keys() if "_count" not in x]) > 0: elif sum([len(report_file.feedback_accuracy[x]) for x in report_file.feedback_accuracy.keys() if "_count" not in x]) > 0:
day_data["average_accuracy_rate"]["imei"].add(report_file.feedback_accuracy.get("imei_number", [])) day_data["average_accuracy_rate"][key].add(report_file.feedback_accuracy.get(key, []))
day_data["average_accuracy_rate"]["purchase_date"].add(report_file.feedback_accuracy.get("purchase_date", []))
day_data["average_accuracy_rate"]["retailer_name"].add(report_file.feedback_accuracy.get("retailername", []))
day_data["average_accuracy_rate"]["sold_to_party"].add(report_file.feedback_accuracy.get("sold_to_party", []))
for key in ["imei_number", "purchase_date", "retailername", "sold_to_party"]:
day_data["feedback_accuracy"][key].add(report_file.feedback_accuracy.get(key, [])) day_data["feedback_accuracy"][key].add(report_file.feedback_accuracy.get(key, []))
for key in ["imei_number", "purchase_date", "retailername", "sold_to_party"]:
day_data["reviewed_accuracy"][key].add(report_file.reviewed_accuracy.get(key, [])) day_data["reviewed_accuracy"][key].add(report_file.reviewed_accuracy.get(key, []))
if not day_data["average_processing_time"].get(report_file.doc_type, None): if not day_data["average_processing_time"].get(report_file.doc_type, None):
@ -264,7 +254,7 @@ class ReportAccumulateByRequest:
"reviewed_accuracy": {}} "reviewed_accuracy": {}}
for acc_type in ["feedback_accuracy", "reviewed_accuracy"]: for acc_type in ["feedback_accuracy", "reviewed_accuracy"]:
avg_acc = IterAvg() avg_acc = IterAvg()
for key in ["imei_number", "purchase_date", "retailername", "sold_to_party"]: for key in settings.FIELD:
acumulated_acc[acc_type][key] = self.data[month][1][day][acc_type][key]() acumulated_acc[acc_type][key] = self.data[month][1][day][acc_type][key]()
acumulated_acc[acc_type][key+"_count"] = self.data[month][1][day][acc_type][key].count acumulated_acc[acc_type][key+"_count"] = self.data[month][1][day][acc_type][key].count
avg_acc.add_avg(acumulated_acc[acc_type][key], acumulated_acc[acc_type][key+"_count"]) avg_acc.add_avg(acumulated_acc[acc_type][key], acumulated_acc[acc_type][key+"_count"])
@ -308,21 +298,13 @@ class ReportAccumulateByRequest:
for day in _data[month][1].keys(): for day in _data[month][1].keys():
num_transaction_imei += _data[month][1][day]["usage"].get("imei", 0) num_transaction_imei += _data[month][1][day]["usage"].get("imei", 0)
num_transaction_invoice += _data[month][1][day]["usage"].get("invoice", 0) num_transaction_invoice += _data[month][1][day]["usage"].get("invoice", 0)
_data[month][1][day]["average_accuracy_rate"]["imei"] = _data[month][1][day]["average_accuracy_rate"]["imei"]()
_data[month][1][day]["average_accuracy_rate"]["purchase_date"] = _data[month][1][day]["average_accuracy_rate"]["purchase_date"]()
_data[month][1][day]["average_accuracy_rate"]["retailer_name"] = _data[month][1][day]["average_accuracy_rate"]["retailer_name"]()
_data[month][1][day]["average_accuracy_rate"]["sold_to_party"] = _data[month][1][day]["average_accuracy_rate"]["sold_to_party"]()
for key in _data[month][1][day]["average_processing_time"].keys(): for key in _data[month][1][day]["average_processing_time"].keys():
_data[month][1][day]["average_processing_time"][key] = _data[month][1][day]["average_processing_time"][key]() _data[month][1][day]["average_processing_time"][key] = _data[month][1][day]["average_processing_time"][key]()
_data[month][1][day]["feedback_accuracy"]["imei_number"] = _data[month][1][day]["feedback_accuracy"]["imei_number"]() for key in settings.FIELD:
_data[month][1][day]["feedback_accuracy"]["purchase_date"] = _data[month][1][day]["feedback_accuracy"]["purchase_date"]() _data[month][1][day]["average_accuracy_rate"][key] = _data[month][1][day]["average_accuracy_rate"][key]()
_data[month][1][day]["feedback_accuracy"]["retailername"] = _data[month][1][day]["feedback_accuracy"]["retailername"]() for accuracy_type in ["feedback_accuracy", key]:
_data[month][1][day]["feedback_accuracy"]["sold_to_party"] = _data[month][1][day]["feedback_accuracy"]["sold_to_party"]() _data[month][1][day][accuracy_type]["imei_number"] = _data[month][1][day]["feedback_accuracy"]["imei_number"]()
_data[month][1][day]["reviewed_accuracy"]["imei_number"] = _data[month][1][day]["reviewed_accuracy"]["imei_number"]()
_data[month][1][day]["reviewed_accuracy"]["purchase_date"] = _data[month][1][day]["reviewed_accuracy"]["purchase_date"]()
_data[month][1][day]["reviewed_accuracy"]["retailername"] = _data[month][1][day]["reviewed_accuracy"]["retailername"]()
_data[month][1][day]["reviewed_accuracy"]["sold_to_party"] = _data[month][1][day]["reviewed_accuracy"]["sold_to_party"]()
_data[month][1][day]["review_progress"] = _data[month][1][day]["review_progress"].count(1)/(_data[month][1][day]["review_progress"].count(0)+ _data[month][1][day]["review_progress"].count(1)) if (_data[month][1][day]["review_progress"].count(0)+ _data[month][1][day]["review_progress"].count(1)) >0 else 0 _data[month][1][day]["review_progress"] = _data[month][1][day]["review_progress"].count(1)/(_data[month][1][day]["review_progress"].count(0)+ _data[month][1][day]["review_progress"].count(1)) if (_data[month][1][day]["review_progress"].count(0)+ _data[month][1][day]["review_progress"].count(1)) >0 else 0
_data[month][1][day].pop("report_files") _data[month][1][day].pop("report_files")
@ -332,23 +314,13 @@ class ReportAccumulateByRequest:
_data[month][0]["usage"]["imei"] = num_transaction_imei _data[month][0]["usage"]["imei"] = num_transaction_imei
_data[month][0]["usage"]["invoice"] = num_transaction_invoice _data[month][0]["usage"]["invoice"] = num_transaction_invoice
_data[month][0]["usage"]["total_images"] = num_transaction_invoice + num_transaction_imei _data[month][0]["usage"]["total_images"] = num_transaction_invoice + num_transaction_imei
_data[month][0]["average_accuracy_rate"]["imei"] = _data[month][0]["average_accuracy_rate"]["imei"]()
_data[month][0]["average_accuracy_rate"]["purchase_date"] = _data[month][0]["average_accuracy_rate"]["purchase_date"]()
_data[month][0]["average_accuracy_rate"]["retailer_name"] = _data[month][0]["average_accuracy_rate"]["retailer_name"]()
_data[month][0]["average_accuracy_rate"]["sold_to_party"] = _data[month][0]["average_accuracy_rate"]["sold_to_party"]()
for key in _data[month][0]["average_processing_time"].keys(): for key in _data[month][0]["average_processing_time"].keys():
_data[month][0]["average_processing_time"][key] = _data[month][0]["average_processing_time"][key]() _data[month][0]["average_processing_time"][key] = _data[month][0]["average_processing_time"][key]()
for key in settings.FIELD:
_data[month][0]["feedback_accuracy"]["imei_number"] = _data[month][0]["feedback_accuracy"]["imei_number"]() _data[month][0]["average_accuracy_rate"][key] = _data[month][0]["average_accuracy_rate"][key]()
_data[month][0]["feedback_accuracy"]["purchase_date"] = _data[month][0]["feedback_accuracy"]["purchase_date"]() for accuracy_type in ["feedback_accuracy", key]:
_data[month][0]["feedback_accuracy"]["retailername"] = _data[month][0]["feedback_accuracy"]["retailername"]() _data[month][0][accuracy_type][key] = _data[month][0][accuracy_type][key]()
_data[month][0]["feedback_accuracy"]["sold_to_party"] = _data[month][0]["feedback_accuracy"]["sold_to_party"]()
_data[month][0]["reviewed_accuracy"]["imei_number"] = _data[month][0]["reviewed_accuracy"]["imei_number"]()
_data[month][0]["reviewed_accuracy"]["purchase_date"] = _data[month][0]["reviewed_accuracy"]["purchase_date"]()
_data[month][0]["reviewed_accuracy"]["retailername"] = _data[month][0]["reviewed_accuracy"]["retailername"]()
_data[month][0]["reviewed_accuracy"]["sold_to_party"] = _data[month][0]["reviewed_accuracy"]["sold_to_party"]()
_data[month][0]["review_progress"] = _data[month][0]["review_progress"].count(1)/(_data[month][0]["review_progress"].count(0)+ _data[month][0]["review_progress"].count(1)) if (_data[month][0]["review_progress"].count(0)+ _data[month][0]["review_progress"].count(1)) >0 else 0 _data[month][0]["review_progress"] = _data[month][0]["review_progress"].count(1)/(_data[month][0]["review_progress"].count(0)+ _data[month][0]["review_progress"].count(1)) if (_data[month][0]["review_progress"].count(0)+ _data[month][0]["review_progress"].count(1)) >0 else 0
return _data return _data
class MonthReportAccumulate: class MonthReportAccumulate:
@ -553,6 +525,7 @@ def first_of_list(the_list):
def extract_report_detail_list(report_detail_list, lower=False, in_percent=True): def extract_report_detail_list(report_detail_list, lower=False, in_percent=True):
data = [] data = []
for report_file in report_detail_list: for report_file in report_detail_list:
# FIXME: #79 Fill None with value
data.append({ data.append({
"Subs": report_file.subsidiary, "Subs": report_file.subsidiary,
"Request ID": report_file.correspond_request_id, "Request ID": report_file.correspond_request_id,
@ -560,12 +533,19 @@ def extract_report_detail_list(report_detail_list, lower=False, in_percent=True)
"Image type": report_file.doc_type, "Image type": report_file.doc_type,
"IMEI_user submitted": first_of_list(report_file.feedback_result.get("imei_number", [None])), "IMEI_user submitted": first_of_list(report_file.feedback_result.get("imei_number", [None])),
"IMEI_OCR retrieved": first_of_list(report_file.predict_result.get("imei_number", [None])), "IMEI_OCR retrieved": first_of_list(report_file.predict_result.get("imei_number", [None])),
"IMEI Revised": None,
"IMEI1 Accuracy": first_of_list(report_file.feedback_accuracy.get("imei_number", [None])), "IMEI1 Accuracy": first_of_list(report_file.feedback_accuracy.get("imei_number", [None])),
"Invoice_Number_User": None,
"Invoice_Number_OCR": None,
"Invoice_Number Revised": None,
"Invoice_Number_Accuracy": None,
"Invoice_Purchase Date_Consumer": report_file.feedback_result.get("purchase_date", None), "Invoice_Purchase Date_Consumer": report_file.feedback_result.get("purchase_date", None),
"Invoice_Purchase Date_OCR": report_file.predict_result.get("purchase_date", []), "Invoice_Purchase Date_OCR": report_file.predict_result.get("purchase_date", []),
"Invoice_Purchase Date Revised": None,
"Invoice_Purchase Date Accuracy": first_of_list(report_file.feedback_accuracy.get("purchase_date", [None])), "Invoice_Purchase Date Accuracy": first_of_list(report_file.feedback_accuracy.get("purchase_date", [None])),
"Invoice_Retailer_Consumer": report_file.feedback_result.get("retailername", None), "Invoice_Retailer_Consumer": report_file.feedback_result.get("retailername", None),
"Invoice_Retailer_OCR": report_file.predict_result.get("retailername", None), "Invoice_Retailer_OCR": report_file.predict_result.get("retailername", None),
"Invoice_Purchase Date Revised": None,
"Invoice_Retailer Accuracy": first_of_list(report_file.feedback_accuracy.get("retailername", [None])), "Invoice_Retailer Accuracy": first_of_list(report_file.feedback_accuracy.get("retailername", [None])),
"OCR Image Accuracy": report_file.acc, "OCR Image Accuracy": report_file.acc,
"OCR Image Speed (seconds)": report_file.time_cost, "OCR Image Speed (seconds)": report_file.time_cost,