CheckCardBoxAndDefectServer/app/core/config.py

from pathlib import Path
from typing import Dict


# 定义一个模型的配置结构
class CardModelConfig:
    pth_path: str
    class_dict: dict
    img_size: dict
    confidence: float
    input_channels: int


class Settings:
    API_prefix: str = "/api/card_inference"
    BASE_PATH = Path(__file__).parent.parent.absolute()

    # 使用一个字典来管理所有卡片检测模型
    # key (如 'outer_box') 将成为 API 路径中的 {inference_type}
    CARD_MODELS_CONFIG: Dict[str, CardModelConfig] = {
        "outer_box": {
            "pth_path": "Model/outer_box.pth",
            "class_dict": {1: 'outer_box'},
            "img_size": {'width': 1280, 'height': 1280},
            "confidence": 0.5,
            "input_channels": 3,
        },
        "inner_box": {
            "pth_path": "Model/inner_box.pth",
            "class_dict": {1: 'inner_box'},
            "img_size": {'width': 1280, 'height': 1280},
            "confidence": 0.5,
            "input_channels": 3,
        },
        "back_defect": {
            "pth_path": "Model/back_defect.pth",
            "class_dict": {
                1: 'wear', 2: 'wear_and_impact', 3: 'impact',
                4: 'damaged', 5: 'wear_and_stain',
            },
            "img_size": {'width': 512, 'height': 512},
            "confidence": 0.5,
            "input_channels": 3,
        },
        "no_reflect_front_defect": {
            "pth_path": "Model/no_reflect_front_defect.pth",
            "class_dict": {1: 'scratch',
                           2: 'pit',
                           3: 'stain'},
            "img_size": {'width': 512, 'height': 512},
            "confidence": 0.5,
            "input_channels": 3,
        }

    }


settings = Settings()
print(settings.BASE_PATH)