diff --git a/cope2n-api/fwd_api/utils/accuracy.py b/cope2n-api/fwd_api/utils/accuracy.py index 833a4fd..55b32b3 100755 --- a/cope2n-api/fwd_api/utils/accuracy.py +++ b/cope2n-api/fwd_api/utils/accuracy.py @@ -16,8 +16,10 @@ import redis from fwd import settings from ..models import SubscriptionRequest, Report, ReportFile import json +from typing import Union, List, Dict valid_keys = ["retailername", "sold_to_party", "invoice_no", "purchase_date", "imei_number"] +optional_keys = ['invoice_no'] class ReportAccumulateByRequest: def __init__(self, sub): @@ -533,6 +535,13 @@ def first_of_list(the_list): return None return the_list[0] +def _feedback_invoice_no_exist(feedback_result): + invoice_no = feedback_result.get("invoice_no", None) + if invoice_no in ["", [], None]: + return False + else: + return True + def extract_report_detail_list(report_detail_list, lower=False, in_percent=True): data = [] for report_file in report_detail_list: @@ -549,7 +558,7 @@ def extract_report_detail_list(report_detail_list, lower=False, in_percent=True) "Invoice_Number_User": report_file.feedback_result.get("invoice_no", None) if report_file.feedback_result else None, "Invoice_Number_OCR": report_file.predict_result.get("invoice_no", None), "Invoice_Number Revised": report_file.reviewed_result.get("invoice_no", None) if report_file.reviewed_result else None, - "Invoice_Number_Accuracy": first_of_list(report_file.feedback_accuracy.get("invoice_no", [None])), + "Invoice_Number_Accuracy": first_of_list(report_file.feedback_accuracy.get("invoice_no", [None])) if _feedback_invoice_no_exist(report_file.feedback_result) else None, "Invoice_Purchase Date_Consumer": report_file.feedback_result.get("purchase_date", None) if report_file.feedback_result else None, "Invoice_Purchase Date_OCR": format_purchase_date_ocr_for_report(report_file.predict_result.get("purchase_date", [])), "Invoice_Purchase Date Revised": report_file.reviewed_result.get("purchase_date", None) if report_file.reviewed_result else None, @@ -644,57 +653,60 @@ def predict_result_to_ready(result): dict_result["invoice_no"] = result.get("content", {}).get("document", [{}])[0].get("content", [{}, {}, {}, {}, {}])[4].get("value", None) return dict_result -def align_fine_result(ready_predict, fine_result): - # print(f"[DEBUG]: fine_result: {fine_result}") - # print(f"[DEBUG]: ready_predict: {ready_predict}") - if fine_result: - if fine_result["purchase_date"] and len(ready_predict["purchase_date"]) == 0: - ready_predict["purchase_date"] = [None] - if fine_result["retailername"] and not ready_predict["retailername"]: - ready_predict["retailername"] = [None] - if ready_predict.get("invoice_no", None) and not fine_result.get("invoice_no", None): - fine_result["invoice_no"] = [None] - fine_result["purchase_date"] = [fine_result["purchase_date"] for _ in range(len(ready_predict["purchase_date"]))] - return ready_predict, fine_result - def update_temp_accuracy(accuracy, acc, keys): for key in keys: accuracy[key].add(acc[key]) return accuracy -def calculate_accuracy(key_name, inference, target): +def _accuracy_calculate_formatter(inference, target): """_summary_ + format type of inference, and target from str/None to List of str/None. + Make both list inference and target to be the same length. + """ + if not isinstance(inference, list): + inference = [] if inference is None else [inference] + if not isinstance(target, list): + target = [] if target is None else [target] + + length = max(len(target), len(inference)) + target = target + (length - len(target))*[None] + inference = inference + (length - len(inference))*[None] + return inference, target + +def _acc_will_be_ignored(key_name, _target, type): + is_optional_key = key_name in optional_keys + is_empty_target = _target in [[], None, ''] + if is_optional_key and is_empty_target and type == 'feedback': + return True + else: + return False + +def calculate_accuracy(key_name: str, inference: Dict[str, Union[str, List]], target: Dict[str, Union[str, List]], type: str): + """_summary_ + NOTE: This has been changed to return accuracy = None if Args: key_name (string): key to calculate accuracy on, ex: retailername inference (dict): result from ocr, refined to align with the target down below target (dict): result of type + is_optional_keyname: default is set to False (which mean this is not an optional keyname) + currently we have invoice_no is an optional keyname. """ acc = [] data = [] - if not target or not inference: return acc, data - if not isinstance(inference[key_name], list): - if inference[key_name] is None: - inference[key_name] = [] - else: - inference[key_name] = [inference[key_name]] - if not isinstance(target[key_name], list): - if target[key_name] is None: - target[key_name] = [] - else: - target[key_name] = [target[key_name]] - # Realign lenght for mis predicted/feedback/reivew result - if len(target[key_name]) == 0 and len(inference[key_name]) > 0: - target[key_name] = [None for _ in range(len(inference[key_name]))] - elif len(inference[key_name]) == 0 and len(target[key_name]) > 0: - target[key_name] = [None for _ in range(len(inference[key_name]))] + + _inference = inference[key_name] + _target = target[key_name] + _will_acc_be_ignored = _acc_will_be_ignored(key_name, _target, type) + _inference = _accuracy_calculate_formatter(_inference) + _target = _accuracy_calculate_formatter(_target) - for i, v in enumerate(inference[key_name]): - # TODO: target[key_name][i] is None, "" - x = post_processing_str(key_name, inference[key_name][i], is_gt=False) - y = post_processing_str(key_name, target[key_name][i], is_gt=True) + for i, v in enumerate(_inference): + # TODO: target[i] is None, "" + x = post_processing_str(key_name, _inference[i], is_gt=False) + y = post_processing_str(key_name, _target[i], is_gt=True) score = eval_ocr_metric( [x], @@ -705,7 +717,8 @@ def calculate_accuracy(key_name, inference, target): # "line_acc", # "one_minus_ned_word", ]) - acc.append(list(score.values())[0]) + if not _will_acc_be_ignored: + acc.append(list(score.values())[0]) data.append([x, y]) return acc, data @@ -821,30 +834,43 @@ def calculate_a_request(report, request): if status != 200: continue image.feedback_accuracy = att["acc"]["feedback"] # dict {key: [values]} - image.reviewed_accuracy = att["acc"]["reviewed"] # dict {key: [values]} - image.is_bad_image_quality = att["is_bad_image"] + image.is_bad_image_quality = att["is_bad_image"] # is_bad_image=avg_acc 0: - image.predict_result["purchase_date"] = [att["normalized_data"]["feedback"]["purchase_date"][i][0] for i in range(len(att["normalized_data"]["feedback"]["purchase_date"]))] + image.predict_result["purchase_date"] = [value_pair[0] for value_pair in att["normalized_data"]["feedback"]["purchase_date"]] image.feedback_result["purchase_date"] = att["normalized_data"]["feedback"]["purchase_date"][fb_max_indexes["purchase_date"]][1] if len(att["normalized_data"]["reviewed"].get("purchase_date", [])) > 0: - image.predict_result["purchase_date"] = [att["normalized_data"]["reviewed"]["purchase_date"][i][0] for i in range(len(att["normalized_data"]["reviewed"]["purchase_date"]))] + image.predict_result["purchase_date"] = [value_pair[0] for value_pair in att["normalized_data"]["reviewed"]["purchase_date"]] image.reviewed_result["purchase_date"] = att["normalized_data"]["reviewed"]["purchase_date"][rv_max_indexes["purchase_date"]][1] - # if request.is_reviewed: - # att["is_reviewed"] = 1 request_att["is_reviewed"].append(att["is_reviewed"]) + + if att["is_reviewed"] == -1: # -1 means "not required" + att["acc"]["reviewed"] = {} + reviewed_result = {} + reason = None + counter_measure = None + else: + if att["is_reviewed"] == 1: + reviewed_result = image.reviewed_result + reason = image.reason + counter_measure = image.counter_measures + new_report_file = ReportFile(report=report, subsidiary=_sub, correspond_request_id=request.request_id, @@ -853,15 +879,15 @@ def calculate_a_request(report, request): doc_type=image.doc_type, predict_result=image.predict_result, feedback_result=image.feedback_result, - reviewed_result=image.reviewed_result, + reviewed_result=reviewed_result, feedback_accuracy=att["acc"]["feedback"], reviewed_accuracy=att["acc"]["reviewed"], acc=att["avg_acc"], is_bad_image=att["is_bad_image"], is_reviewed= review_status_map(att["is_reviewed"]), time_cost=image.processing_time, - bad_image_reason=image.reason, - counter_measures=image.counter_measures, + bad_image_reason=reason, + counter_measures=counter_measure, error="|".join(att["err"]), review_status=att["is_reviewed"], ) @@ -889,18 +915,18 @@ def calculate_a_request(report, request): request_att["acc"]["feedback"]["retailername"] += _att["acc"]["feedback"]["retailername"] request_att["acc"]["feedback"]["sold_to_party"] += _att["acc"]["feedback"]["sold_to_party"] request_att["acc"]["feedback"]["invoice_no"] += _att["acc"]["feedback"]["invoice_no"] + + request_att["acc"]["reviewed"]["imei_number"] += _att["acc"]["reviewed"]["imei_number"] if _att["is_reviewed"]==1 else [] + request_att["acc"]["reviewed"]["purchase_date"] += _att["acc"]["reviewed"]["purchase_date"] if _att["is_reviewed"]==1 else [] + request_att["acc"]["reviewed"]["retailername"] += _att["acc"]["reviewed"]["retailername"] if _att["is_reviewed"]==1 else [] + request_att["acc"]["reviewed"]["sold_to_party"] += _att["acc"]["reviewed"]["sold_to_party"] if _att["is_reviewed"]==1 else [] + request_att["acc"]["reviewed"]["invoice_no"] += _att["acc"]["reviewed"]["invoice_no"] if _att["is_reviewed"]==1 else [] - request_att["acc"]["reviewed"]["imei_number"] += _att["acc"]["reviewed"]["imei_number"] - request_att["acc"]["reviewed"]["purchase_date"] += _att["acc"]["reviewed"]["purchase_date"] - request_att["acc"]["reviewed"]["retailername"] += _att["acc"]["reviewed"]["retailername"] - request_att["acc"]["reviewed"]["sold_to_party"] += _att["acc"]["reviewed"]["sold_to_party"] - request_att["acc"]["reviewed"]["invoice_no"] += _att["acc"]["reviewed"]["invoice_no"] - - request_att["acc"]["acumulated"]["imei_number"] += _att["acc"]["reviewed"]["imei_number"] if _att["acc"]["reviewed"]["imei_number"] else _att["acc"]["feedback"]["imei_number"] - request_att["acc"]["acumulated"]["purchase_date"] += _att["acc"]["reviewed"]["purchase_date"] if _att["acc"]["reviewed"]["purchase_date"] else _att["acc"]["feedback"]["purchase_date"] - request_att["acc"]["acumulated"]["retailername"] += _att["acc"]["reviewed"]["retailername"] if _att["acc"]["reviewed"]["retailername"] else _att["acc"]["feedback"]["retailername"] - request_att["acc"]["acumulated"]["sold_to_party"] += _att["acc"]["reviewed"]["sold_to_party"] if _att["acc"]["reviewed"]["sold_to_party"] else _att["acc"]["feedback"]["sold_to_party"] - request_att["acc"]["acumulated"]["invoice_no"] += _att["acc"]["reviewed"]["invoice_no"] if _att["acc"]["reviewed"]["invoice_no"] else _att["acc"]["feedback"]["invoice_no"] + request_att["acc"]["acumulated"]["imei_number"] += _att["acc"]["reviewed"]["imei_number"] if _att["acc"]["reviewed"]["imei_number"] and _att["is_reviewed"]==1 else _att["acc"]["feedback"]["imei_number"] + request_att["acc"]["acumulated"]["purchase_date"] += _att["acc"]["reviewed"]["purchase_date"] if _att["acc"]["reviewed"]["purchase_date"] and _att["is_reviewed"]==1 else _att["acc"]["feedback"]["purchase_date"] + request_att["acc"]["acumulated"]["retailername"] += _att["acc"]["reviewed"]["retailername"] if _att["acc"]["reviewed"]["retailername"] and _att["is_reviewed"]==1 else _att["acc"]["feedback"]["retailername"] + request_att["acc"]["acumulated"]["sold_to_party"] += _att["acc"]["reviewed"]["sold_to_party"] if _att["acc"]["reviewed"]["sold_to_party"] and _att["is_reviewed"]==1 else _att["acc"]["feedback"]["sold_to_party"] + request_att["acc"]["acumulated"]["invoice_no"] += _att["acc"]["reviewed"]["invoice_no"] if _att["acc"]["reviewed"]["invoice_no"] and _att["is_reviewed"]==1 else _att["acc"]["feedback"]["invoice_no"] if image.reason not in settings.ACC_EXCLUDE_RESEASONS: request_att["bad_images"] += int(_att["is_bad_image"]) @@ -926,33 +952,35 @@ def calculate_subcription_file(subcription_request_file): return 400, att inference_result = copy.deepcopy(subcription_request_file.predict_result) - inference_result, feedback_result = align_fine_result(inference_result, copy.deepcopy(subcription_request_file.feedback_result)) - inference_result, reviewed_result = align_fine_result(inference_result, copy.deepcopy(subcription_request_file.reviewed_result)) + feedback_result = copy.deepcopy(subcription_request_file.feedback_result) + reviewed_result = copy.deepcopy(subcription_request_file.reviewed_result) for key_name in valid_keys: try: - att["acc"]["feedback"][key_name], att["normalized_data"]["feedback"][key_name] = calculate_accuracy(key_name, inference_result, feedback_result) - att["acc"]["reviewed"][key_name], att["normalized_data"]["reviewed"][key_name] = calculate_accuracy(key_name, inference_result, reviewed_result) + att["acc"]["feedback"][key_name], att["normalized_data"]["feedback"][key_name] = calculate_accuracy(key_name, inference_result, feedback_result, "feedback") + att["acc"]["reviewed"][key_name], att["normalized_data"]["reviewed"][key_name] = calculate_accuracy(key_name, inference_result, reviewed_result, "reviewed") except Exception as e: att["err"].append(str(e)) - # print(f"[DEBUG]: predict_result: {subcription_request_file.predict_result}") - # print(f"[DEBUG]: e: {e} -key_name: {key_name}") subcription_request_file.feedback_accuracy = att["acc"]["feedback"] subcription_request_file.reviewed_accuracy = att["acc"]["reviewed"] - avg_reviewed = calculate_avg_accuracy(att["acc"], "reviewed", ["retailername", "sold_to_party", "invoice_no", "purchase_date", "imei_number"]) - avg_feedback = calculate_avg_accuracy(att["acc"], "feedback", ["retailername", "sold_to_party", "invoice_no", "purchase_date", "imei_number"]) + + avg_reviewed = calculate_avg_accuracy(att["acc"], "reviewed", valid_keys) + avg_feedback = calculate_avg_accuracy(att["acc"], "feedback", valid_keys) + if avg_feedback is not None or avg_reviewed is not None: avg_acc = 0 if avg_feedback is not None: avg_acc = avg_feedback if avg_feedback < settings.NEED_REVIEW: att["is_reviewed"] = 0 - if avg_reviewed is not None: + else: + att["is_reviewed"] = -1 + if avg_reviewed is not None and att["is_reviewed"]!=-1: avg_acc = avg_reviewed att["is_reviewed"] = 1 # Little trick to overcome issue caused by misleading manually review process - if subcription_request_file.reason or subcription_request_file.counter_measures: + if (subcription_request_file.reason or subcription_request_file.counter_measures) and att["is_reviewed"]!=-1: att["is_reviewed"] = 1 att["avg_acc"] = avg_acc