CheckCardBoxAndDefectServer/app/services/score_service.py

import cv2

from app.core.config import settings
from app.core.logger import get_logger
from app.services.defect_service import DefectInferenceService
from app.services.card_rectify_and_center import CardRectifyAndCenter
from app.utils.score_inference.CardScorer import CardScorer
import numpy as np
import json

logger = get_logger(__name__)


class ScoreService:
    def __init__(self):
        self.scoring_config_path = settings.SCORE_CONFIG_PATH
        self.card_scorer = CardScorer(config_path=self.scoring_config_path)

        self.defect_service = DefectInferenceService()
        self.rectify_center_service = CardRectifyAndCenter()

    def score_inference(self, score_type: str, is_reflect_card: bool,
                        img_bgr: np.ndarray) -> dict:

        logger.info("开始进行卡片居中和转正")
        img_bgr = self.rectify_center_service.rectify_and_center(img_bgr)
        imageHeight, imageWidth = img_bgr.shape[:2]

        logger.info("开始进行卡片分数推理")
        if score_type == 'front_corner_edge' or score_type == 'front_face' or score_type == "front_face_ring_light":
            center_data = self.defect_service.defect_inference("pokemon_front_card_center", img_bgr.copy())
        else:
            center_data = self.defect_service.defect_inference("pokemon_back_card_center", img_bgr.copy())

        if is_reflect_card:
            if score_type == 'front_corner_edge':
                defect_data = self.defect_service.defect_inference('pokemon_front_corner_reflect_defect',
                                                                   img_bgr.copy())
            elif score_type == 'front_face':
                defect_data = self.defect_service.defect_inference('pokemon_front_face_reflect_defect', img_bgr.copy())
            elif score_type == 'back_corner_edge':
                defect_data = self.defect_service.defect_inference('pokemon_back_corner_defect', img_bgr.copy())
            elif score_type == 'back_face':
                defect_data = self.defect_service.defect_inference('pokemon_back_face_defect', img_bgr.copy())
            elif score_type == 'front_face_ring_light':
                defect_data = self.defect_service.defect_inference('pokemon_front_face_reflect_ring_light_defect',
                                                                   img_bgr.copy())
            elif score_type == 'back_face_ring_light':
                defect_data = self.defect_service.defect_inference('pokemon_back_face_ring_light_defect',
                                                                   img_bgr.copy())
            else:
                return {}
        else:
            if score_type == 'front_corner_edge':
                defect_data = self.defect_service.defect_inference('pokemon_front_corner_no_reflect_defect',
                                                                   img_bgr.copy())
            elif score_type == 'front_face':
                defect_data = self.defect_service.defect_inference('pokemon_front_face_no_reflect_defect',
                                                                   img_bgr.copy())
            elif score_type == 'back_corner_edge':
                defect_data = self.defect_service.defect_inference('pokemon_back_corner_defect', img_bgr.copy())
            elif score_type == 'back_face':
                defect_data = self.defect_service.defect_inference('pokemon_back_face_defect', img_bgr.copy())
            elif score_type == 'front_face_ring_light':
                defect_data = self.defect_service.defect_inference('pokemon_front_face_reflect_ring_light_defect',
                                                                   img_bgr.copy())
            elif score_type == 'back_face_ring_light':
                defect_data = self.defect_service.defect_inference('pokemon_back_face_ring_light_defect',
                                                                   img_bgr.copy())
            else:
                return {}

        logger.info("模型推理结束, 开始计算分数")
        if score_type == 'front_corner_edge' or score_type == 'front_face' or score_type=="front_face_ring_light":
            card_aspect = "front"
        else:
            card_aspect = "back"
        if score_type == 'front_corner_edge' or score_type == 'back_corner_edge':
            card_defect_type = "corner_edge"
        else:
            card_defect_type = "face"

        if card_defect_type == 'corner_edge':
            center_score_data = self.card_scorer.calculate_centering_score(card_aspect, center_data, True)

            # 先计算角的分数, 会把分数写入json, 然后传入刚写好的, 继续写边的分数
            corner_score_data = self.card_scorer.calculate_defect_score('corner', card_aspect, defect_data, True)
            defect_score_data = self.card_scorer.calculate_defect_score('edge', card_aspect, corner_score_data, True)
        elif card_defect_type == 'face':
            center_score_data = {}
            defect_score_data = self.card_scorer.calculate_defect_score('face', card_aspect, defect_data, True)
        else:
            return {}

        result_json = self.card_scorer.formate_one_card_result(center_score_data, defect_score_data,
                                                               card_defect_type=card_defect_type,
                                                               card_aspect=card_aspect,
                                                               imageHeight=imageHeight,
                                                               imageWidth=imageWidth)

        temp_score_json_path = settings.TEMP_WORK_DIR / f'{score_type}_score.json'
        with open(temp_score_json_path, 'w', encoding='utf-8') as f:
            json.dump(result_json, f, ensure_ascii=False, indent=2)
        logger.info("分数推理完成 ")
        return result_json

    def recalculate_defect_score(self, score_type: str, json_data: dict):

        center_json_data = json_data["result"]['center_result']
        defect_json_data = json_data["result"]['defect_result']
        imageHeight = json_data["result"].get('imageHeight', 0)
        imageWidth = json_data["result"].get('imageWidth', 0)

        # 边角和面 类型分类
        if score_type == 'front_corner_edge' or score_type == 'back_corner_edge':
            inference_type = "corner_edge"
        else:
            inference_type = "face"

        # 正反面类型分类
        if score_type == 'front_corner_edge' or score_type == 'front_face':
            card_aspect = "front"
        else:
            card_aspect = "back"

        logger.info("开始进行缺陷信息重计算")
        defect_data = self.defect_service.re_inference_from_json(inference_type=inference_type,
                                                                 center_json=center_json_data,
                                                                 defect_json=defect_json_data)

        logger.info("开始重新计算分数")
        if inference_type == 'corner_edge':
            logger.info("开始进行居中信息重计算")
            center_data = self.defect_service.re_inference_from_json(inference_type="center",
                                                                     center_json=center_json_data,
                                                                     defect_json=defect_json_data)

            center_score_data = self.card_scorer.calculate_centering_score(card_aspect, center_data, True)

            # 先计算角的分数, 会把分数写入json, 然后传入刚写好的, 继续写边的分数
            corner_score_data = self.card_scorer.calculate_defect_score('corner', card_aspect, defect_data, True)
            defect_score_data = self.card_scorer.calculate_defect_score('edge', card_aspect, corner_score_data, True)
        elif inference_type == 'face':
            # 面类型不计算居中
            center_score_data = {}
            defect_score_data = self.card_scorer.calculate_defect_score('face', card_aspect, defect_data, True)
        else:
            return {}

        result_json = self.card_scorer.formate_one_card_result(center_score_data, defect_score_data,
                                                               card_defect_type=inference_type,
                                                               card_aspect=card_aspect,
                                                               imageHeight=imageHeight,
                                                               imageWidth=imageWidth)

        temp_score_json_path = settings.TEMP_WORK_DIR / f're_{score_type}_score.json'
        with open(temp_score_json_path, 'w', encoding='utf-8') as f:
            json.dump(result_json, f, ensure_ascii=False, indent=2)
        logger.info("分数推理完成 ")
        return result_json