116 lines
4.0 KiB
Python
116 lines
4.0 KiB
Python
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import os
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from collections import defaultdict
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from config import MODEL_CONFIGS
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from detect import YOLODetector
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class UnifiedDetectionManager:
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"""统一检测管理器"""
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def __init__(self):
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self.detectors = {} # 检测器实例
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self.type_to_model = {} # 类别到模型映射
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self.loaded_models = [] # 已加载模型
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self.type_to_id = {} # 全局类别ID映射
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self._load_models()
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def _load_models(self):
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"""加载所有模型"""
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if not MODEL_CONFIGS:
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raise ValueError("模型配置为空")
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for model_name, config in MODEL_CONFIGS.items():
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try:
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model_path = config["model_path"]
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if not os.path.exists(model_path):
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print(f"跳过 {model_name}: 模型文件不存在 - {model_path}")
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continue
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# 创建检测器（自动传递新增的enable_primary配置）
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detector = YOLODetector(
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model_path=model_path,
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params=config["params"],
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type_to_id=config["type_to_id"]
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)
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# 保存状态
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self.detectors[model_name] = detector
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self.loaded_models.append(model_name)
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# 建立映射
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for det_type in config["types"]:
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det_type_lower = det_type.lower()
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if det_type_lower in self.type_to_model:
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print(f"警告: 类别 '{det_type}' 映射冲突")
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self.type_to_model[det_type_lower] = model_name
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self.type_to_id[det_type_lower] = config["type_to_id"][det_type_lower]
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print(f"加载成功: {model_name}")
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except Exception as e:
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print(f"加载失败 {model_name}: {str(e)}")
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continue
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print(f"模型加载完成: {len(self.loaded_models)}/{len(MODEL_CONFIGS)}")
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print(f"支持类别: {list(self.type_to_model.keys())}")
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def parse_types(self, types_str):
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"""解析检测类型"""
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if not types_str:
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raise ValueError("检测类型为空")
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# 清理输入
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requested_types = list(set(t.strip().lower() for t in types_str.split(',') if t.strip()))
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# 按模型分组
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model_type_map = defaultdict(list)
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for det_type in requested_types:
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if det_type in self.type_to_model:
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model_name = self.type_to_model[det_type]
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model_type_map[model_name].append(det_type)
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else:
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print(f"忽略未知类别: {det_type}")
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if not model_type_map:
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raise ValueError("无有效检测类别")
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return model_type_map
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def detect(self, img_path, detection_types):
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"""执行检测"""
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if not os.path.exists(img_path):
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raise FileNotFoundError(f"图像不存在: {img_path}")
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# 解析类型
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model_type_map = self.parse_types(detection_types)
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# 执行检测（自动适配enable_primary配置）
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all_results = []
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for model_name, target_types in model_type_map.items():
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if model_name not in self.detectors:
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continue
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print(f"检测: {model_name} -> {target_types}")
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try:
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results = self.detectors[model_name].detect(img_path, target_types)
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all_results.extend(results)
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# 获取详细统计信息
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stats = self.detectors[model_name].get_detection_stats()
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print(f" {model_name}详细统计: {stats}")
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except Exception as e:
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print(f"检测失败 {model_name}: {str(e)}")
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print(f"检测完成: 总共 {len(all_results)} 个结果")
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return all_results
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def get_available_info(self):
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"""获取可用信息"""
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return {
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"loaded_models": self.loaded_models,
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"supported_types": list(self.type_to_model.keys()),
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"type_to_model": self.type_to_model
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}
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